We investigate the neural and cognitive mechanisms underlying perceptual, reward-based and voluntary and change-of-mind decisions, preference formation, health choices, decision errors, and related cognitive processes, using methods from psychology, economics, and cognitive neuroscience.
Our lab is part of the Decision Science Hub at the Melbourne School of Psychological Sciences. We further participate in the Jülich - University of Melbourne Postgraduate Academy (JUMPA).
PhD project on health decisions available
The Decision Neuroscience Lab is looking for a highly motivated and skilled PhD student to work on a project on the neural basis of health decisions. The project will be supervised by Dr Bode and co-supervised by experienced researchers from the Centre for Behavioural Research in Cancer (Cancer Council Victoria). The PhD project will be an extension of our previous work (see publications: Rosenblatt et al., 2018, Neuroimage: Clinical; 2018, Appetite). A strong interest in neuroimaging techniques (EEG or fMRI), data analysis (e.g., MATLAB, R, SPM, EEGlab) and cognitive neuroscience research are essential. To apply, please send an email including a) cover letter, b) CV, and c) transcripts of recent marks, to Dr Stefan Bode: firstname.lastname@example.org.Announcement
Post-doctoral Research Fellow position available
The Cognitive Neurology Laboratory at Monash University and the Decision Neuroscience Laboratory at the University of Melbourne are seeking to appoint a Post-Doctoral Research Fellow. This is a two-year, full-time position and part of a program of ARC-funded research on the neuroscience of human value-based decision-making and preference formation. The successful applicant will work at Monash University, and the position will be jointly supervised by Dr Trevor Chong, Monash University, and Dr Stefan Bode. For more information please see: http://careers.pageuppeople.com/513/cw/en/job/580126/research-fellowAnnouncement
New paper demonstrating the effectiveness of health warnings for dietary decisions
Daniel Rosenblatt's new paper shows that health warning messages can improve our dietary decisions. In particular graphic negatively framed messages helped people make healthier choices.Announcement
DDTBOX - the paper describing our MVPA Toolbox for EEG data is now published in Neuroinformatics
We are happy to announce that the official paper describing our Decision Decoding Toolbox (DDTBOX), an MVPA toolbox for EEG data, is now published. Thanks to the great work by Daniel Feuerriegel, we also have an extensive online Wiki, guiding users through the functionality of the toolbox.Announcement
The Decision Neuroscience Lab is located at The University of Melbourne and part of:
Our research staff are located at the Melbourne School of Psychological Sciences.
Current Lab Members
Head of Lab
Melbourne School of Psychological Sciences
+61 3 9035 3849
Melbourne School of Psychological Sciences
+61 3 8344 4446
Melbourne School of Psychological Sciences
+61 3 8344 4185
Melbourne School of Psychological Sciences
+61 3 8344 4185
Melbourne School of Psychological Sciences
+61 3 8344 0221
Melbourne School of Psychological Sciences
+61 3 8344 4185
Melbourne School of Psychological Sciences
+61 3 8344 4185
Melbourne School of Psychological Sciences
+61 3 8344 4185
Melbourne School of Psychological Sciences
+61 3 8344 4185
Melbourne School of Psychological Sciences
+61 3 8344 4185
Melbourne School of Psychological Sciences
+61 3 8344 4185
Melbourne School of Psychological Sciences
+61 3 8344 4185
Melbourne School of Psychological Sciences
+61 3 8344 4185
Melbourne School of Psychological Sciences
+61 3 8344 4185
PhD Student (JUMPA)
Melbourne School of Psychological Sciences & INM-3 Forschungszentrum Julich
+61 3 8344 4185
PhD Student (JUMPA)
INM-3 Forschungszentrum Julich & Melbourne School of Psychological Sciences
Associated Lab Members
- Damien Crone (PhD student; primary supervisor: Dr Simon Laham)
- Tessel Blom (PhD student; primary supervisor: Dr Hinze Hogendoorn)
- Ariel Goh (PhD student; primary supervisor: Dr Trevor Chong)
Former Lab Members
Associated / Visiting Academics & Students
- Dr Carsten Murawski (associate investigator / former co-head of lab)
- Dr Carmen Morawetz (visiting scientist from FU Berlin, Germany)
- Prof Jutta Stahl (visiting scientist from University of Cologne, Germany)
- Anne Löffler (visiting PhD student from UCL, UK)
- Sebastian Speer (visiting Research Masters student from Amsterdam, The Netherlands)
- Vivian Jiayi Luo (visiting Research Masters student from South China Normal University, China)
- Alice Vidal (visiting Research Masters student from Sorbonne Université Paris, France)
- Letizia Vogler (visiting Research Masters student from University of Cologne, Germany)
Postdocs / PhD Students
- Dr Elaine Corbett (post-doctoral researcher; now University College Dublin, Ireland)
- Dr Daniel Bennett (PhD student; now Princeton University, USA)
- Dr Bowen John Fung (PhD student; now CalTech, USA)
- Dr Katharina Voigt (PhD student; now Monash University, Australia)
Honours / Masters Students
- Ariel Goh
- Tamir Goldberg
- Karen Sasmita
- Maia Tarrell
- Joanna Thio
- Aidan Jago
- Maja Brydevall
- Alyssa Ng
- William Turner
- Patrick Summerell
- Phillip Johnston
- Nicholas Tan
- Kiran Sutcliffe
- Robert Beaton
Research Assistants / Interns
- Alex Kline (RA)
- Daniel Bennett (RA)
- Bowen Fung (RA)
- Daniel Rosenblatt (RA)
- Hayley Warren (RA)
- Christina Van Heer (RA)
- Rebekah Street (RA)
- Patrick Summerell (RA)
- Amanda Ng (Intern)
- Ariel Goh (Intern, RA)
- Tracey Wang (Intern)
- Megan Edelman (intern)
- Jessica Paul (Intern)
- Marina Saade (Intern)
- Della Averill (Intern)
- Kashmira Daruwalla (Intern)
- Sophia Bock (Intern)
- Pola Held (Intern)
- Nicole Stefanac (Intern)
- Hayley McFadyen (Intern)
- Kathleen De Boer (Intern)
- Phillip Johnston (Intern)
- William Turner (Intern)
- Jamila Bahrami (Intern)
- Nicholas Tan (Intern)
- Kiran Sutcliffe (Intern)
- Leonie Glitz (Intern)
- Cheng Chua (Intern)
- Amy Du (Intern)
- Alex Diaz (Intern)
- Alice Cao (Intern)
- Dr Virginia Liu (RA)
We are looking for participants to take part in our experiments.
Become a test participant
Most of our experiments are conducted on the University of Melbourne campus in Parkville and generally last between 45 minutes and 1 hour (some might last longer). Our functional magnetic resonance imaging (fMRI) studies take place at the Monash Biomedical Imaging (MBI) centre in Clayton. Participants are compensated for their time.
If you would like to take part in one of our experiments, please click on the 'Register Here' button below, and our team will be in touch with you shortly.
If you want to find out more about our experiments, please contact us via email (email@example.com).
Publications by current members of the Decision Neuroscience Lab
Bode S, Bennett D, Sewell DK, Paton B, Egan GF, Smith PL, Murawski C (2018). Dissociating neural variability related to stimulus quality and response times in perceptual decision-making. Neuropsychologia, 111, 190-200.
Bode S, Bennett D, Sewell DK, Paton B, Egan GF, Smith PL, Murawski C
According to sequential sampling models, perceptual decision-making is based on accumulation of noisy evidence towards a decision threshold. The speed with which a decision is reached is determined by both the quality of incoming sensory information and random trial-by-trial variability in the encoded stimulus representations. To investigate those decision dynamics at the neural level, participants made perceptual decisions while functional magnetic resonance imaging (fMRI) was conducted. On each trial, participants judged whether an image presented under conditions of high, medium, or low visual noise showed a piano or a chair. Higher stimulus quality (lower visual noise) was associated with increased activation in bilateral medial occipito-temporal cortex and ventral striatum. Lower stimulus quality was related to stronger activation in posterior parietal cortex (PPC) and dorsolateral prefrontal cortex (DLPFC). When stimulus quality was fixed, faster response times were associated with a positive parametric modulation of activation in medial prefrontal and orbitofrontal cortex, while slower response times were again related to more activation in PPC, DLPFC and insula. Our results suggest that distinct neural networks were sensitive to the quality of stimulus information, and to trial-to-trial variability in the encoded stimulus representations, but that reaching a decision was a consequence of their joint activity. Read this publication.
Bode S, Feuerriegel D, Bennett D, Alday PM (2018). The Decision Decoding ToolBOX (DDTBOX): a multivariate pattern analysis toolbox for event-related potentials. Neuroinformatics, in press.
Bode S, Feuerriegel D, Bennett D, Alday PM
In recent years, neuroimaging research in cognitive neuroscience has increasingly used multivariate pattern analysis (MVPA) to investigate higher cognitive functions. Here we present DDTBOX, an open-source MVPA toolbox for electroencephalography (EEG) data. DDTBOX runs under MATLAB and is well integrated with the EEGLAB/ERPLAB and Fieldtrip toolboxes (Delorme and Makeig 2004; Lopez-Calderon and Luck 2014; Oostenveld et al. 2011). It trains support vector machines (SVMs) on patterns of event-related potential (ERP) amplitude data, following or preceding an event of interest, for classification or regression of experimental variables. These amplitude patterns can be extracted across space/electrodes (spatial decoding), time (temporal decoding), or both (spatiotemporal decoding). DDTBOX can also extract SVM feature weights, generate empirical chance distributions based on shuffled-labels decoding for group-level statistical testing, provide estimates of the prevalence of decodable information in the population, and perform a variety of corrections for multiple comparisons. It also includes plotting functions for single subject and group results. DDTBOX complements conventional analyses of ERP components, as subtle multivariate patterns can be detected that would be overlooked in standard analyses. It further allows for a more explorative search for information when no ERP component is known to be specifically linked to a cognitive process of interest. In summary, DDTBOX is an easy-to-use and open-source toolbox that allows for characterising the time-course of information related to various perceptual and cognitive processes. It can be applied to data from a large number of experimental paradigms and could therefore be a valuable tool for the neuroimaging community. Read this publication.
Brydevall M, Bennett D, Murawski C, Bode S (2018). The neural encoding of information prediction errors during non-instrumental information seeking. Scientific Reports, 8: 6134.
Brydevall M, Bennett D, Murawski C, Bode S
In a dynamic world, accurate beliefs about the environment are vital for survival, and individuals should therefore regularly seek out new information with which to update their beliefs. This aspect of behaviour is not well captured by standard theories of decision making, and the neural mechanisms of information seeking remain unclear. One recent theory posits that valuation of information results from representation of informative stimuli within canonical neural reward-processing circuits, even if that information lacks instrumental use. We investigated this question by recording EEG from twenty-three human participants performing a non-instrumental information-seeking task. In this task, participants could pay a monetary cost to receive advance information about the likelihood of receiving reward in a lottery at the end of each trial. Behavioural results showed that participants were willing to incur considerable monetary costs to acquire early but non-instrumental information. Analysis of the event-related potential elicited by informative cues revealed that the feedback-related negativity independently encoded both an information prediction error and a reward prediction error. These findings are consistent with the hypothesis that information seeking results from processing of information within neural reward circuits, and suggests that information may represent a distinct dimension of valuation in decision making under uncertainty. Read this publication.
Chandrakumar D, Feuerriegel D, Bode S, Grech M, Keage HAD (2018). Event-related potentials in relation to risk-taking: A systematic review. Frontiers in Behavioral Neuroscience, 12: 111.
Chandrakumar D, Feuerriegel D, Bode S, Grech M, Keage HAD
Event-related potentials (ERPs) have been used to investigate neural mechanisms underlying risk-related decisions over the last 16 years. We aimed to systematically evaluate associations between risk-taking and ERP components elicited during decisions and following feedback. A total of 78 articles identified from PsychINFO and PubMed databases met the inclusion criteria. Selected articles assessed early ERP components (feedback-related negativity/FRN, error-related negativity/ERN, and medial frontal negativity/MFN) and mid-latency P3 components, all using gambling paradigms that involved selecting between choices of varying risk (e.g., Iowa Gambling Task, Balloon Analogue Risk Task, and two-choice gambling tasks). The P3 component was consistently enhanced to the selection of risky options and when positive feedback (as compared to negative feedback) was provided. Also consistently, the early negative components were found to be larger following feedback indicating monetary losses as compared to gains. In the majority of studies reviewed here, risk was conceptualised in the context of simple economical decisions in gambling tasks. As such, this narrow concept of risk might not capture the diversity of risky decisions made in other areas of everyday experience, for example, social, health and recreational risk-related decisions. It therefore remains to be seen whether the risk-sensitivity of the ERP components reviewed here generalises to other domains of life. Read this publication.
Crone DL, Bode S, Murawski C, Laham SM (2018). The Socio-Moral Image Database (SMID): A novel stimulus set for the study of social, moral and affective processes. PLoS ONE, 13(1): e0190954.
Crone DL, Bode S, Murawski C, Laham SM
A major obstacle for the design of rigorous, reproducible studies in moral psychology is the lack of suitable stimulus sets. Here, we present the Socio-Moral Image Database (SMID), the largest standardized moral stimulus set assembled to date, containing 2,941 freely available photographic images, representing a wide range of morally (and affectively) positive, negative and neutral content. The SMID was validated with over 820,525 individual judgments from 2,716 participants, with normative ratings currently available for all images on affective valence and arousal, moral wrongness, and relevance to each of the five moral values posited by Moral Foundations Theory. We present a thorough analysis of the SMID regarding (1) inter-rater consensus, (2) rating precision, and (3) breadth and variability of moral content. Additionally, we provide recommendations for use aimed at efficient study design and reproducibility, and outline planned extensions to the database. We anticipate that the SMID will serve as a useful resource for psychological, neuroscientific and computational (e.g., natural language processing or computer vision) investigations of social, moral and affective processes. The SMID images, along with associated normative data and additional resources are available at https://osf.io/2rqad/. Read this publication.
Feuerriegel D, Churches O, Coussens S, Keage HAD (2018). Evidence for spatiotemporally distinct effects of image repetition and perceptual expectations as measured by event-related potentials. Neuroimage, 169, 94-105.
Feuerriegel D, Churches O, Coussens S, Keage HAD
Morys F, Bode S, Horstmann A (2018). Dorsolateral and medial prefrontal cortex mediate the influence of incidental priming on economic decision making in obesity. Scientific Reports, in press.
Morys F, Bode S, Horstmann A
Obese individuals discount future rewards to a higher degree than lean individuals, which is generally considered disadvantageous. Moreover, their decisions are altered more easily by decision-irrelevant cues. Here, we investigated neural correlates of this phenomenon using functional MRI. We tested 30 lean and 26 obese human subjects on a primed delay discounting paradigm using gustatory and visual cues of positive, neutral and negative valence to bias their intertemporal preferences. We hypothesised that activation differences in reward-related and behavioural control areas, and changes in connectivity between these areas, would reflect the effect of these cues. Here, obese subjects were more susceptible to priming with negative gustatory cues towards delayed choices as opposed to lean subjects. This was related to lower activity in left dorsolateral prefrontal cortex during priming. Modulation of functional connectivity between the dlPFC and the ventromedial PFC by the behavioural priming effect correlated negatively with BMI. This might indicate that default goals of obese individuals were different from those of lean participants, as the dlPFC has been suggested to be involved in internal goal pursuit. The present results further our understanding of the role of PFC in decision-making and might inform future weight-management approaches based on non-invasive brain stimulation. Read this publication.
Rens N, Bode S, Cunnington R (2018). Perceived freedom of choice is associated with neural encoding of option availability. Neuroimage, 177, 59-67.
Rens N, Bode S, Cunnington R
Freedom of choice has been defined as the opportunity to choose alternative plans of action. In this fMRI study, we investigated how the perceived freedom of choice and the underlying neural correlates are influenced by the availability of options. Participants made an initial free choice between left or right doors before beginning a virtual walk along a corridor. At the mid-point of the corridor, lock cues appeared to reveal whether one or both doors remained available, requiring participants either to select a particular door or allowing them to freely choose to stay or switch their choice. We found that participants rated trials as free when they were able to carry out their initial choice, but even more so when both doors remained available. Multi-voxel pattern analysis showed that upcoming choices could initially be decoded from visual cortices before the appearance of the lock cues, and additionally from the motor cortex after the lock cues had confirmed which doors were open. When participants were able to maintain the same choice that they originally selected, the availability of alternative options was represented in fine-grained patterns of activity in the dorsolateral prefrontal cortex. Further, decoding accuracy in this region correlated with the subjective level of freedom that participants reported. These results suggest that there is neural encoding of the availability of alternative options in the dorsolateral prefrontal cortex, and the degree of this encoding predicts an individual's perceived freedom of choice. Read this publication.
Rosenblatt DH, Bode S, Summerell P, Ng A, Murawski C, Dixon H, Wakefield M (2018). Health warnings promote healthier dietary decision making: effects of message framing and graphic versus text-based warnings. Appetite, 127, 280-288.
Rosenblatt DH, Bode S, Summerell P, Ng A, Murawski C, Dixon H, Wakefield M
Food product health warnings have been proposed as a potential obesity prevention strategy. This study examined the effects of text-only and text-and-graphic, negatively and positively framed health warnings on dietary choice behavior. In a 2×5 mixed experimental design, 96 participants completed a dietary self-control task. After providing health and taste ratings of snack foods, participants completed a baseline measure of dietary self-control, operationalized as participants' frequency of choosing healthy but not tasty items and rejecting unhealthy yet tasty items to consume at the end of the experiment. Participants were then randomly assigned to one of five health warning groups and presented with 10 health warnings of a given form: text-based, negative framing; graphic, negative framing; text, positive framing; graphic, positive framing; or a no warning control. Participants then completed a second dietary decision making session to determine whether health warnings influenced dietary self-control. Linear mixed effects modeling revealed a significant interaction between health warning group and decision stage (pre- and post-health warning presentation) on dietary selfcontrol. Negatively framed graphic health warnings promoted greater dietary self-control than other health warnings. Negatively framed text health warnings and positively framed graphic health warnings promoted greater dietary self-control than positively framed text health warnings and control images, which did not increase dietary self-control. Overall, HWs primed healthier dietary decision making behavior, with negatively framed graphic HWs being most effective. Health warnings have potential to become an important element of obesity prevention. Read this publication.
Rosenblatt DH, Summerell P, Ng A, Dixon H, Murawski C, Wakefield M, Bode S (2018). Food product health warnings promote dietary self-control through reductions in neural signals indexing food cue reactivity. Neuroimage: Clinical, 18, 702-712.
Rosenblatt DH, Summerell P, Ng A, Dixon H, Murawski C, Wakefield M, Bode S
Modern societies are replete with palatable food cues. A growing body of evidence suggests that food cue exposure activates conditioned appetitive physiological and psychological responses that may override current metabolic needs and existing eating goals, such as the desire to maintain a healthy diet. This conditioned response results in unhealthy dietary choices, undermines mass media obesity prevention campaigns, and is a contributing factor in the current obesity epidemic. Prime based obesity prevention measures such as health warnings at point-of-sale or on product packaging may have the potential to counteract the influence of the obesogenic environment at the crucial moment when people make food purchasing or consumption decisions. Existing research into the efficacy of these intervention strategies has predominantly employed self-report and population level measures, and little evidence exists to support the contention that these measures counteract food cue reactivity at the time of decision making. Using a dietary self-control priming paradigm, we demonstrated that brief exposure to food product health warnings enhanced dietary self-control. Further, we analysed electroencephalographic correlates of selective attention and food cue evoked craving to show that health warning exposure reduced the automatic appetitive response toward palatable food cues. These findings contribute to existing evidence that exogenous information can successfully prime latent goals, and substantiate the notion that food product health warnings may provide a new avenue through which to curb excessive energy intake and reduce rising obesity rates. Read this publication.
Sewell DK, Warren HA, Rosenblatt DH, Bennett D, Lyons M, Bode S (2018). Feedback discounting in probabilistic categorization: Converging evidence from EEG and cognitive modelling. Computational Brain & Behavior, 1(2), 165-183.
Sewell DK, Warren HA, Rosenblatt DH, Bennett D, Lyons M, Bode S
In simple probabilistic learning environments, the informational value of corrective feedback gradually declines over time. This is because prediction errors persist despite learners acquiring the contingencies between stimuli and outcomes. An adaptive solution to the problem of unavoidable prediction error is to discount feedback from the learning environment. We provide novel neural evidence of feedback discounting using a combination of behavioral modeling and electroencephalography (EEG). Participants completed a probabilistic categorization task while EEG activity was recorded. We used a model-based analysis of choice behavior to identify individuals that did and did not discount feedback. We then contrasted changes in the feedback-related negativity (FRN) for these two groups. For individuals who did not discount feedback, we observed learning-related reductions in the FRN that reflected incremental changes in choice behavior. By contrast, for individuals who discounted feedback, we found that the FRN was effectively eliminated due to the rapid onset of feedback discounting. The use of a feedback discounting strategy was linked to superior performance on the task, highlighting the adaptive nature of discounting when trial-to-trial outcomes are variable, but the long-term contingencies relating cues and outcomes are stable. Read this publication.
Voigt K, Murawski C, Speer S, Bode S (2018). Hard decisions shape the neural coding of preferences. Journal of Neuroscience, in press.
Voigt K, Murawski C, Speer S, Bode S
Hard decisions between equally valued alternatives can result in preference changes, meaning that subsequent valuations for chosen items increase and decrease for rejected items. Previous research suggests that this phenomenon is a consequence of cognitive dissonance reduction after the decision, induced by the mismatch between initial preferences and decision outcomes. In contrast, this functional magnetic resonance imaging and eye-tracking study with male and female human participants found that preferences are already updated online during the process of decision making. Preference changes were predicted from activity in left dorsolateral prefrontal cortex and precuneus while making hard decisions. Fixation durations during this phase predicted both choice outcomes and subsequent preference changes. These preference adjustments became behaviourally relevant only for choices that were remembered and were in turn associated with hippocampus activity. Our suggest that preferences evolve dynamically as decisions arise, potentially as a mechanism to prevent stalemate situations in underdetermined decision scenarios. Read this publication.
Barke A, Bode S, Dechent P, Schmidt-Samoa C, Van Heer C, Stahl J (2017). To err is (perfectly) human: behavioural and neural correlates of error processing and perfectionism. Social Cognitive and Affective Neuroscience, 12, 1647-1657.
Barke A, Bode S, Dechent P, Schmidt-Samoa C, Van Heer C, Stahl J
The attitude towards one's own imperfection strongly varies between individuals. Here, we investigated variations in error-related activity depending on two sub-traits of perfectionism, Personal Standard Perfectionism (PSP) and Evaluative Concern Perfectionism (ECP) in a large scale functional magnetic resonance imaging study (N = 75) using a digit-flanker task. Participants with higher PSP scores showed both more post-error slowing and more neural activity in the medial-frontal gyrus including anterior cingulate cortex after errors. Interestingly, high-EC perfectionists with low PSP showed no post-error slowing and the highest activity in the middle frontal gyrus, whereas high-EC perfectionists with high PSP showed the lowest activity in this brain area and more post-error slowing. Our findings are in line with the hypothesis that perfectionists with high concerns but low standards avoid performance monitoring to avoid the worry-inducing nature of detecting personal failure and the anticipation of poor evaluation by others. However, the stronger goal-oriented performance motivation of perfectionists with high concerns and high standards may have led to less avoidance of error processing and a more intense involvement with the imperfect behaviour, which is essential for improving future performance. Read this publication.
Bode S (2017). Uncovering contextual biases in human decision-making - A multivariate analysis approach for patterns of functional magnetic resonance imaging data and event-related potentials. Professorial Thesis: University of Cologne.
Decision-making is a fundamental aspect of human cognition and behaviour. Every day, we make a multitude of decisions, ranging from rather simple perceptual choices to complex financial decisions. The underlying cognitive and neural mechanisms appear to directly deploy external information, gathered by our senses, as well as internal information, such as preferences and beliefs. Ideally, this results in well-informed decisions and successful goal-directed behaviour. In reality, however, we are often faced with decision situations in which we do not have clear preferences, or access to all information. In these situations, contextual factors appear to have a strong influence on decision-makers. This work highlights recent research supporting the hypothesis that contextual information can exert significant biases on a variety of decision processes outside decision-makers’ awareness. These studies further exemplify a content-based cognitive neuroscience approach to human decision-making research, building on multivariate analysis techniques for brain imaging data to directly predict the content of decision outcomes and other decision-related variables from brain activity. Read this publication.
Chan YM, Pianta MJ, Bode S, McKendrick AM (2017). Neural correlates of audiovisual synchrony judgements in older adults. Neurobiology of Aging, 55, 38-48.
Chan YM, Pianta MJ, Bode S, McKendrick AM
Older adults have altered perception of the relative timing between auditory and visual stimuli, even when stimuli are scaled to equate detectability. To help understand why, this study investigated the neural correlates of audiovisual synchrony judgments in older adults using electroencephalography (EEG). Fourteen younger (18-32 year old) and 16 older (61-74 year old) adults performed an audiovisual synchrony judgment task on flash-pip stimuli while EEG was recorded. All participants were assessed to have healthy vision and hearing for their age. Observers responded to whether audiovisual pairs were perceived as synchronous or asynchronous via a button press. The results showed that the onset of predictive sensory information for synchrony judgments was not different between groups. Channels over auditory areas contributed more to this predictive sensory information than visual areas. The spatial-temporal profile of the EEG activity also indicates that older adults used different resources to maintain a similar level of performance in audiovisual synchrony judgments compared with younger adults. Read this publication.
Fung BJ, Bode S, Murawski C (2017). Consumption of caloric rewards decreases temporal persistence. Proceedings of the Royal Society B: Biological Sciences, 284:20162759.
Fung BJ, Bode S, Murawski C
Temporal persistence refers to an individual's capacity to wait for future rewards, while forgoing possible alternatives. This requires a trade-off between the potential value of delayed rewards and opportunity costs, and is relevant to many real-world decisions, such as dieting. Theoretical models have previously suggested that high monetary reward rates, or positive energy balance, may result in decreased temporal persistence. In our study, 50 fasted participants engaged in a temporal persistence task, incentivised with monetary rewards. In alternating blocks of this task, rewards were delivered at delays drawn randomly from distributions with either a lower or higher maximum reward rate. During some blocks participants received either a caloric drink or water. We used survival analysis to estimate participants' probability of quitting conditional on the delay distribution and the consumed liquid. Participants had a higher probability of quitting in blocks with the higher reward rate. Furthermore, participants who consumed the caloric drink had a higher probability of quitting than those who consumed water. Our results support the predictions from the theoretical models, and importantly, suggest that both higher monetary reward rates and physiologically relevant rewards can decrease temporal persistence, which is a crucial determinant for survival in many species. Read this publication.
Fung BJ, Crone D, Bode S, Murawski C (2017). Cardiac signals are independently associated with temporal discounting and time perception. Frontiers in Behavioral Neuroscience, 11:1.
Fung BJ, Crone D, Bode S, Murawski C
Cardiac signals reflect the function of the autonomic nervous system (ANS) and have previously been associated with a range of self-regulatory behaviors such as emotion regulation and memory recall. It is unknown whether cardiac signals may also be associated with self-regulation in the temporal domain, in particular impulsivity. We assessed both decision impulsivity (temporal discounting, TD) and time perception impulsivity (duration reproduction, DR) in 120 participants while they underwent electrocardiography in order to test whether cardiac signals were related to these two aspects of impulsivity. We found that over the entire period of task performance, individuals with higher heart rates had a tendency toward lower discount rates, supporting previous research that has associated sympathetic responses with decreased impulsivity. We also found that low-frequency components of heart rate variability (HRV) were associated with a less accurate perception of time, suggesting that time perception may be modulated by ANS function. Overall, these findings constitute preliminary evidence that autonomic function plays an important role in both decision impulsivity and time perception. Read this publication.
Fung BJ, Murawski C, Bode S (2017). Caloric primary rewards systematically alter time perception. Journal of Experimental Psychology: Human Perception & Performance, 43(11), 1925-1936.
Fung BJ, Murawski C, Bode S
Human time perception can be influenced by contextual factors, such as the presence of reward. Yet, the exact nature of the relationship between time perception and reward has not been conclusively characterized. We implemented a novel experimental paradigm to measure estimations of time across a range of suprasecond intervals, during the anticipation and after the consumption of fruit juice, a physiologically relevant primary reward. We show that average time estimations were systematically affected by the consumption of reward, but not by the anticipation of reward. Compared with baseline estimations of time, reward consumption was associated with subsequent overproductions of time, and this effect increased for larger magnitudes of reward. Additional experiments demonstrated that the effect of consumption did not extend to a secondary reward (money), a tasteless, noncaloric primary reward (water), or a sweet, noncaloric reward (aspartame). However, a tasteless caloric reward (maltodexrin) did induce overproductions of time, although this effect did not scale with reward magnitude. These results suggest that the consumption of caloric primary rewards can alter time perception, which may be a psychophysiological mechanism by which organisms regulate homeostatic balance. Read this publication.
Morawetz C, Bode S, Baudewig J, Heekeren HR (2017). Effective amygdala-prefrontal connectivity predicts individual differences in successful emotion regulation. Social Cognitive and Affective Neuroscience, 12(4), 569-585.
Morawetz C, Bode S, Baudewig J, Heekeren HR
The ability to voluntarily regulate our emotional response to threatening and highly arousing stimuli by using cognitive reappraisal strategies is essential for our mental and physical well-being. This might be achieved by prefrontal brain regions (e.g. inferior frontal gyrus, IFG) down-regulating activity in the amygdala. It is unknown, to which degree effective connectivity within the emotion-regulation network is linked to individual differences in reappraisal skills. Using psychophysiological interaction analyses of functional magnetic resonance imaging data, we examined changes in inter-regional connectivity between the amygdala and IFG with other brain regions during reappraisal of emotional responses and used emotion regulation success as an explicit regressor. During down-regulation of emotion, reappraisal success correlated with effective connectivity between IFG with dorsolateral, dorsomedial and ventromedial prefrontal cortex (PFC). During up-regulation of emotion, effective coupling between IFG with anterior cingulate cortex, dorsomedial and ventromedial PFC as well as the amygdala correlated with reappraisal success. Activity in the amygdala covaried with activity in lateral and medial prefrontal regions during the up-regulation of emotion and correlated with reappraisal success. These results suggest that successful reappraisal is linked to changes in effective connectivity between two systems, prefrontal cognitive control regions and regions crucially involved in emotional evaluation. Read this publication.
Morawetz C, Bode S, Derntl B, Heekeren HR (2017). The effect of strategies, goals and stimulus material on the neural mechanisms of emotion regulation: A meta-analysis of fMRI studies. Neuroscience & Biobehavioral Reviews, 72, 11-128.
Morawetz C, Bode S, Derntl B, Heekeren HR (2017)
Emotion regulation comprises all extrinsic and intrinsic control processes whereby people monitor, evaluate and modify the occurrence, intensity and duration of emotional reactions. Here we sought to quantitatively summarize the existing neuroimaging literature to investigate a) whether different emotion regulation strategies are based on different or the same neural networks; b) which brain regions in particular support the up- and down-regulation of emotions, respectively; and c) to which degree the neural networks realising emotion regulation depend on the stimulus material used to elicit emotions. The left ventrolateral prefrontal cortex (VLPFC), the anterior insula and the supplementary motor area were consistently activated independent of the regulation strategy. VLPFC and posterior cingulate cortex were the main regions consistently found to be recruited during the up-regulation as well as the down-regulation of emotion. The down-regulation compared to the up-regulation of emotions was associated with more right-lateralized activity while up-regulating emotions more strongly modulated activity in the ventral striatum. Finally, the process of emotion regulation appeared to be unaffected by stimulus material. Read this publication.
Rens N, Bode S, Burianová H, Cunnington R (2017). Proactive recruitment of frontoparietal and salience networks for voluntary decisions. Frontiers in Human Neuroscience, 11: 610.
Rens N, Bode S, Burianová H, Cunnington R
Turner WF, Johnston P, de Boer K, Morawetz C, Bode S (2017). Multivariate pattern analysis of event-related potentials predicts the subjective relevance of everyday objects. Consciousness and Cognition, 55, 46-58.
Turner WF, Johnston P, de Boer K, Morawetz C, Bode S
Potentially decision-relevant stimuli have been proposed to undergo immediate semantic processing. The current study investigated whether information regarding the general desirability ('Wanting') of visually presented 'everyday' objects was rapidly and automatically processed. Participants completed a foreground task while their electroencephalogram (EEG) was recorded, and task-irrelevant images were presented in the background. Following this, participants rated the images with regards to Wanting and the potentially related attributes of Relevance, Familiarity, Aesthetic Pleasantness and Time Reference. Multivariate pattern classification was used to predict the ratings from patterns of EEG data. Prediction of Wanting and Relevance was possible between 100 and 150ms following stimulus presentation. The other dimensions could not be predicted. Wanting and Relevance ratings were highly correlated and displayed similar feature weight maps. The current results suggest that the general desirability and subjective relevance of everyday objects is rapidly and automatically processed for a wide range of visual stimuli. Read this publication.
Voigt K, Murawski C, Bode S (2017). Endogenous formation of preferences: choices systematically change willingness-to-pay for goods. Journal of Experimental Psychology: Learning, Memory and Cognition, 43(12), 1872-1882.
Voigt K, Murawski C, Bode S
Standard decision theory assumes that choices result from stable preferences. This position has been challenged by claims that the act of choosing between goods may alter preferences. To test this claim, we investigated in three experiments whether choices between equally valued snack food items can systematically shape preferences. We directly assessed changes in participants' willingness-to-pay for these items, some of which could be bought at an auction after the experiment, while others could not. We found that chosen items were valued higher, and nonchosen items were valued lower; yet this postdecisional refinement of preferences was only observed for choices and valuations that were relevant, that is, incentive-compatible for items that were available for consumption. Supplementary analyses revealed that incentive-incompatible elicitations of preferences were unreliable and may have masked potential effects of choices on preferences. In conclusion, we propose that preferences can change endogenously, that is, in the absence of external feedback or information, but rather as a function of previous relevant choices. Read this publication.
Bennett D, Bode S, Brydevall M, Warren HA, & Murawski C (2016). Intrinsic Valuation of Information in Decision Making under Uncertainty. PLoS Comput Biol, 12(7), e1005020.
In a dynamic world, an accurate model of the environment is vital for survival, and agents ought regularly to seek out new information with which to update their world models. This aspect of behaviour is not captured well by classical theories of decision making, and the cognitive mechanisms of information seeking are poorly understood. In particular, it is not known whether information is valued only for its instrumental use, or whether humans also assign it a non-instrumental intrinsic value. To address this question, the present study assessed preference for non-instrumental information among 80 healthy participants in two experiments. Participants performed a novel information preference task in which they could choose to pay a monetary cost to receive advance information about the outcome of a monetary lottery. Importantly, acquiring information did not alter lottery outcome probabilities. We found that participants were willing to incur considerable monetary costs to acquire payoff-irrelevant information about the lottery outcome. This behaviour was well explained by a computational cognitive model in which information preference resulted from aversion to temporally prolonged uncertainty. These results strongly suggest that humans assign an intrinsic value to information in a manner inconsistent with normative accounts of decision making under uncertainty. This intrinsic value may be associated with adaptive behaviour in real-world environments by producing a bias towards exploratory and information-seeking behaviour. Read this publication.
Bennett D, Dluzniak A, Cropper SJ, Partos T, Sundram S, Carter O (2016). Selective impairment of global motion integration, but not global form detection, in schizophrenia and bipolar affective disorder. Schizophrenia Research: Cognition, 3, 11-14.
Recent evidence suggests that schizophrenia is associated with impaired processing of global visual motion, but intact processing of global visual form. This project assessed whether preserved visual form detection in schizophrenia extended beyond low-level pattern discrimination to a naturalistic form-detection task. We assessed both naturalistic form detection and global motion detection in individuals with schizophrenia spectrum disorder, bipolar affective disorder, and healthy controls. Individuals with schizophrenia spectrum disorder and bipolar affective disorder were impaired relative to healthy controls on the global motion task, but not the naturalistic form-detection task. Results indicate that preservation of visual form detection in these disorders extends beyond configural forms to naturalistic object processing. Read this publication.
Morawetz C, Bode S, Baudewig J, Jacobs AM, Heekeren HR (2016). Neural representation of emotion regulation goals. Human Brain Mapping, 37(2), 600-620.
The use of top–down cognitive control mechanisms to regulate emotional responses as circumstances change is critical for mental and physical health. Several theoretical models of emotion regulation have been postulated; it remains unclear, however, in which brain regions emotion regulation goals (e.g., the downregulation of fear) are represented. Here, we examined the neural mechanisms of regulating emotion using fMRI and identified brain regions representing reappraisal goals. Using a multimethodological analysis approach, combining standard activation-based and pattern-information analyses, we identified a distributed network of lateral frontal, temporal, and parietal regions implicated in reappraisal and within it, a core system that represents reappraisal goals in an abstract, stimulus-independent fashion. Within this core system, the neural pattern-separability in a subset of regions including the left inferior frontal gyrus, middle temporal gyrus, and inferior parietal lobe was related to the success in emotion regulation. Those brain regions might link the prefrontal control regions with the subcortical affective regions. Given the strong association of this subsystem with inner speech functions and semantic memory, we conclude that those cognitive mechanisms may be used for orchestrating emotion regulation. Read this publication.
Morawetz C, Bode S, Baudewig J, Kirilina E, Heekeren HR (2016). Changes in effective connectivity between dorsal and ventral prefrontal regions moderate emotion regulation. Cerebral Cortex, 26(5), 1923-1937.
Reappraisal, the cognitive reevaluation of a potentially emotionally arousing event, has been proposed to be based upon top-down appraisal systems within the prefrontal cortex (PFC). It still remains unclear, however, how different prefrontal regions interact to control and regulate emotional responses. We used fMRI and dynamic causal modeling (DCM) to characterize the functional interrelationships among dorsal and ventral PFC regions involved in reappraisal. Specifically, we examined the effective connectivity between the inferior frontal gyrus (IFG), dorsolateral PFC (DLPFC), and other reappraisal-related regions (supplementary motor area, supramarginal gyrus) during the up- and downregulation of emotions in response to highly arousing extreme sports film clips. Read this publication.
Bennett D (2015). The neural mechanisms of Bayesian belief updating. The Journal of Neuroscience, 35(50), 16300-16302.
Bennett D, Murawski C, Bode S (2015). Single-trial event-related potential correlates of belief updating. eNeuro: 2(5).
Bennett D, Murawski C, Bode S
Belief updating—the process by which an agent alters an internal model of its environment—is a core function of the central nervous system. Recent theory has proposed broad principles by which belief updating might operate, but more precise details of its implementation in the human brain remain unclear. In order to address this question, we studied how two components of the human event-related potential encoded different aspects of belief updating. Participants completed a novel perceptual learning task while electroencephalography was recorded. Participants learned the mapping between the contrast of a dynamic visual stimulus and a monetary reward, and updated their beliefs about a target contrast on each trial. A Bayesian computational model was formulated to estimate belief states at each trial and used to quantify two variables: belief update size and belief uncertainty. Robust single-trial regression was used to assess how these model-derived variables were related to the amplitudes of the P3 and the stimulus-preceding negativity (SPN), respectively. Results showed a positive relationship between belief update size and P3 amplitude at one fronto-central electrode, and a negative relationship between SPN amplitude and belief uncertainty at a left central and a right parietal electrode. These results provide evidence that belief update size and belief uncertainty have distinct neural signatures that can be tracked in single trials in specific ERP components. This, in turn, provides evidence that the cognitive mechanisms underlying belief updating in humans can be described well within a Bayesian framework. Read this publication.
Bossaerts P, Murawski C (2015). From behavioural economics to neuroeconomics to decision neuroscience: the ascent of biology in research on human decision making. Current Opinion in Behavioral Sciences, 4:37-42.
Here, we briefly review the evolution of research on human decision-making over the past few decades. We discern a trend whereby biology moves from subserving economics (neuroeconomics), to providing the data that advance our knowledge of the nature of human decision-making (decision neuroscience). Examples illustrate that the integration of behavioural and biological models is fruitful especially for understanding heterogeneity of choice in humans. Read this publication.
Simmank J, Bode S, Murawski C, Horstmann A (2015). Incidental rewarding cues influence economic decision-making in obesity. Frontiers in Behavioral Neuroscience, 9:278.
Recent research suggests that obesity is linked to prominent alterations in learning and decision-making. This general difference may also underlie the preference for immediately consumable, highly palatable but unhealthy and high-calorie foods. Such poor food-related inter-temporal decision-making can explain weight gain; however, it is not yet clear whether this deficit can be generalized to other domains of inter-temporal decision-making, for example financial decisions. Further, little is known about the stability of decision-making behavior in obesity, especially in the presence of rewarding cues. To answer these questions, obese and lean participants (n = 52) completed two sessions of a novel priming paradigm including a computerized monetary delay discounting task. Read this publication.
Bode S, Bennett DB, Stahl J, Murawski, C (2014). Distributed patterns of event-related potentials predict subsequent ratings of abstract stimulus attributes. PLoS ONE 9(10): e109070.
Exposure to pleasant and rewarding visual stimuli can bias people's choices towards either immediate or delayed gratification. We hypothesised that this phenomenon might be based on carry-over effects from a fast, unconscious assessment of the abstract ‘time reference’ of a stimuli, i.e. how the stimulus relates to one's personal understanding and connotation of time. Here we investigated whether participants' post-experiment ratings of task-irrelevant, positive background visual stimuli for the dimensions ‘arousal’ (used as a control condition) and ‘time reference’ were related to differences in single-channel event-related potentials (ERPs) and whether they could be predicted from spatio-temporal patterns of ERPs. Participants performed a demanding foreground choice-reaction task while on each trial one task-irrelevant image (depicting objects, people and scenes) was presented in the background. Conventional ERP analyses as well as multivariate support vector regression (SVR) analyses were conducted to predict participants' subsequent ratings. We found that only SVR allowed both ‘arousal’ and ‘time reference’ ratings to be predicted during the first 200 ms post-stimulus. This demonstrates an early, automatic semantic stimulus analysis, which might be related to the high relevance of ‘time reference’ to everyday decision-making and preference formation. Read this publication.
Bode S, Murawski C, Soon CS, Bode P, Stahl J, Smith P (2014).Demystifying "free will": The role of contextual information in explaining predictive brain activity for internal decisions. Neuroscience & Biobehavioral Reviews, 47:636-645.
Novel multivariate pattern classification analyses have enabled the prediction of decision outcomes from brain activity prior to decision-makers’ reported awareness. These findings are often discussed in relation to the philosophical concept of “free will”. We argue that these studies demonstrate the role of unconscious processes in simple free choices, but they do not inform the philosophical debate. Moreover, these findings are difficult to relate to cognitive decision-making models, due to misleading assumptions about random choices. We review evidence suggesting that sequential-sampling models, which assume accumulation of evidence towards a decision threshold, can also be applied to free decisions. If external evidence is eliminated by the task instructions, decision-makers might use alternative, subtle contextual information as evidence, such as their choice history, that is not consciously monitored and usually concealed by the experimental design. We conclude that the investigation of neural activity patterns associated with free decisions should aim to investigate how decisions are jointly a function of internal and external contexts, rather than to resolve the philosophical “free will” debate. Read this publication.
Bode S, Stahl J (2014). Predicting errors from patterns of event-related potentials preceding an overt response. Biological Psychology, 103, 357-369.
Everyday actions often require fast and efficient error detection and error correction. For this, the brain has to accumulate evidence for errors as soon as it becomes available. This study used multivariate pattern classification techniques for event-related potentials to track the accumulation of error-related brain activity before an overt response was made. Upcoming errors in a digit-flanker task could be predicted after the initiation of an erroneous motor response, ∼90 ms before response execution. Channels over motor and parieto-occipital cortices were most important for error prediction, suggesting ongoing perceptual analyses and comparisons of initiated and appropriate motor programmes. Lower response force on error trials as compared to correct trials was observed, which indicates that this early error information was used for attempts to correct for errors before the overt response was made. In summary, our results suggest an early, automatic accumulation of error-related information, providing input for fast correction processes. Read this publication.
Woolgar A, Golland P, Bode S (2014). Coping with confounds in multi-voxel analysis: what should we do about reaction time differences? A comment on Todd, Nystrom & Cohen 2013. Neuroimage, 98, 73-80.
Multivoxel pattern analysis (MVPA) is a sensitive and increasingly popular method for examining differences between neural activation patterns that cannot be detected using classical mass-univariate analysis. Recently, Todd et al. ("Confounds in multivariate pattern analysis: Theory and rule representation case study", 2013, NeuroImage 77: 157-165) highlighted a potential problem for these methods: high sensitivity to confounds at the level of individual participants due to the use of directionless summary statistics. Unlike traditional mass-univariate analyses where confounding activation differences in opposite directions tend to approximately average out at group level, group level MVPA results may be driven by any activation differences that can be discriminated in individual participants. In Todd et al.'s empirical data, factoring out differences in reaction time (RT) reduced a classifier's ability to distinguish patterns of activation pertaining to two task rules. This raises two significant questions for the field: to what extent have previous multivoxel discriminations in the literature been driven by RT differences, and by what methods should future studies take RT and other confounds into account? We build on the work of Todd et al. and compare two different approaches to remove the effect of RT in MVPA. We show that in our empirical data, in contrast to that of Todd et al., the effect of RT on rule decoding is negligible, and results were not affected by the specific details of RT modelling. We discuss the meaning of and sensitivity for confounds in traditional and multivoxel approaches to fMRI analysis. We observe that the increased sensitivity of MVPA comes at a price of reduced specificity, meaning that these methods in particular call for careful consideration of what differs between our conditions of interest. We conclude that the additional complexity of the experimental design, analysis and interpretation needed for MVPA is still not a reason to favour a less sensitive approach. Read this publication.
Bode S, Bogler C, Haynes JD (2013). Similar neural mechanisms for guesses and free decisions. Neuroimage, 65(2), 456-465.
When facing perceptual choices under challenging conditions we might believe to be purely guessing. But which brain regions determine the outcome of our guesses? One possibility is that higher-level, domain-general brain regions might help break the symmetry between equal-appearing choices. Here we directly investigated whether perceptual guesses share brain networks with other types of free decisions. We trained an fMRI-based pattern classifier to distinguish between two perceptual guesses and tested whether it was able to predict the outcome of similar non-perceptual choices, as in conventional free choice tasks. Activation patterns in the medial posterior parietal cortex cross-predicted free decisions from perceptual guesses and vice versa. This inter-changeability strongly speaks for a similar neural code for both types of decisions. The posterior parietal cortex might be part of a domain-general system that helps resolve decision conflicts when no choice option is more or less likely or valuable, thus preventing behavioural stalemate. Read this publication.
Bogler C, Bode S, Haynes JD (2013). Orientation pop-out processing in human visual cortex. Neuroimage. 81, 73-80.
Visual stimuli can "pop out" if they are different to their background. There has been considerable debate as to the role of primary visual cortex (V1) versus higher visual areas (esp. V4) in pop-out processing. Here we parametrically modulated the relative orientation of stimuli and their backgrounds to investigate the neural correlates of pop-out in visual cortex while subjects were performing a demanding fixation task in a scanner. Whole brain and region of interest analyses confirmed a representation of orientation contrast in extrastriate visual cortex (V4), but not in striate visual cortex (V1). Thus, although previous studies have shown that human V1 can be involved in orientation pop-out, our findings demonstrate that there are cases where V1 is "blind" and pop-out detection is restricted to higher visual areas. Pop-out processing is presumably a distributed process across multiple visual regions. Read this publication.
Burnett J, Davis K, Murawski C, Wilkins R, Wilkinson N (2013). Measuring retirement savings adequacy in Australia. JASSA, 4:28-35.
We present two new metrics to assess the adequacy of retirement savings and estimate these metrics for a representative sample of the Australian population aged 40 to 64. Our estimates support the widely held belief that most individuals are not 'on track' to achieve a comfortable standard of living in retirement, although couples appear better prepared than singles. We also estimate the relative expected contributions of the various 'pillars' of retirement income. The metrics presented here may provide a better way to communicate adequacy to individuals, and encourage increased saving. Read this publication.
Gibson R, Murawski C (2013). Margining in derivatives markets and the stability of the banking sector. Journal of Banking & Finance, 37(4),1119-1132.
We investigate the effects of margining, a widely-used mechanism for attaching collateral to derivatives contracts, on derivatives trading volume, default risk, and on the welfare in the banking sector. First, we develop a stylized banking sector equilibrium model to develop some basic intuition of the effects of margining. We find that a margin requirement can be privately and socially sub-optimal. Subsequently, we extend this model into a dynamic simulation model that captures some of the essential characteristics of over-the-counter derivatives markets. Contrarily to the common belief that margining always reduces default risk, we find that there exist situations in which margining increases default risk, reduces aggregate derivatives’ trading volume, and has an ambiguous effect on welfare in the banking sector. The negative effects of margining are exacerbated during periods of market stress when margin rates are high and collateral is scarce. We also find that central counterparties only lift some of the inefficiencies caused by margining. Read this publication.
Krüger D, Klapötke S, Bode S, Mattler U (2013). Neural correlates of control operations in inverse priming with relevant and irrelevant masks.Neuroimage, 64(1),197-208.
The inverse priming paradigm can be considered one example which demonstrates the operation of control processes in the absence of conscious experience of the inducing stimuli. Inverse priming is generated by a prime that is followed by a mask and a subsequent imperative target stimulus. With "relevant" masks that are composed of the superposition of both prime alternatives, the inverse priming effect is typically larger than with "irrelevant" masks that are free of task-relevant features. We used functional magnetic resonance imaging (fMRI) to examine the neural substrates that are involved in the generation of inverse priming effects with relevant and irrelevant masks. We found a network of brain areas that is accessible to unconscious primes, including supplementary motor area (SMA), anterior insula, middle cingulate cortex, and supramarginal gyrus. Activation of these brain areas were involved in inverse priming when relevant masks were used. With irrelevant masks, however, only SMA activation was involved in inverse priming effects. Activation in SMA correlated with inverse priming effects of individual participants on reaction time, indicating that this brain area reflects the size of inverse priming effects on the behavioral level. Findings are most consistent with the view that a basic inhibitory mechanism contributes to inverse priming with either type of mask and additional processes contribute to the effect with relevant masks. This study provides new evidence showing that cognitive control operations in the human cortex take account of task relevant stimulus information even if this information is not consciously perceived. Read this publication.
Soon, CS, He AH, Bode S, Haynes JD (2013). Predicting free choices for abstract intentions. Proceedings of the National Academy of Sciences of the USA, 110, 6217-6222.
Unconscious neural activity has been repeatedly shown to precede and potentially even influence subsequent free decisions. However, to date, such findings have been mostly restricted to simple motor choices, and despite considerable debate, there is no evidence that the outcome of more complex free decisions can be predicted from prior brain signals. Here, we show that the outcome of a free decision to either add or subtract numbers can already be decoded from neural activity in medial prefrontal and parietal cortex 4 s before the participant reports they are consciously making their choice. These choice-predictive signals co-occurred with the so-called default mode brain activity pattern that was still dominant at the time when the choice-predictive signals occurred. Our results suggest that unconscious preparation of free choices is not restricted to motor preparation. Instead, decisions at multiple scales of abstraction evolve from the dynamics of preceding brain activity. Read this publication.
Bode S, Bogler C, Soon CS, Haynes JD (2012). The neural encoding of guesses in the human brain. Neuroimage, 59(2), 1924-1931.
Human perception depends heavily on the quality of sensory information. When objects are hard to see we often believe ourselves to be purely guessing. Here we investigated whether such guesses use brain networks involved in perceptual decision making or independent networks. We used a combination of fMRI and pattern classification to test how visibility affects the signals, which determine choices. We found that decisions regarding clearly visible objects are predicted by signals in sensory brain regions, whereas different regions in parietal cortex became predictive when subjects were shown invisible objects and believed themselves to be purely guessing. This parietal network was highly overlapping with regions, which have previously been shown to encode free decisions. Thus, the brain might use a dedicated network for determining choices when insufficient sensory information is available. Read this publication.
Bode S, Sewell D, Lilburn S, Forte J, Smith PL, Stahl J (2012). Predicting perceptual decision biases from early brain activity. The Journal of Neuroscience, 32(36): 12488-12498.
Perceptual decision making is believed to be driven by the accumulation of sensory evidence following stimulus encoding. More controversially, some studies report that neural activity preceding the stimulus also affects the decision process. We used a multivariate pattern classification approach for the analysis of the human electroencephalogram (EEG) to decode choice outcomes in a perceptual decision task from spatially and temporally distributed patterns of brain signals. When stimuli provided discriminative information, choice outcomes were predicted by neural activity following stimulus encoding; when stimuli provided no discriminative information, choice outcomes were predicted by neural activity preceding the stimulus. Moreover, in the absence of discriminative information, the recent choice history primed the choices on subsequent trials. A diffusion model fitted to the choice probabilities and response time distributions showed that the starting point of the evidence accumulation process was shifted toward the previous choice, consistent with the hypothesis that choice priming biases the accumulation process toward a decision boundary. This bias is reflected in prestimulus brain activity, which, in turn, becomes predictive of future decisions. Our results provide a model of how non-stimulus-driven decision making in humans could be accomplished on a neural level. Read this publication.
Heinzle J, Anders S, Bode S, Bogler C, Chen Y, Cichy RM, Hackmack K, Kahnt T, Kalberlah C, Reverberi C, Soon SC, Tusche A, Weygandt M, Haynes JD (2012). Multivariate decoding of fMRI data – Towards a content-based cognitive neuroscience. e-Neuroforum, 3(1), 1-16.
Within the last two decades, functional magnetic resonance imaging has become one of the most widely used tools in human cognitive neuroscience. FMRI measures the neural activity in a 3-dimensional grid of roughly 1–3 mm resolution. Most cognitive neuroscience studies measure blood oxygen level dependent (BOLD) signals, which indirectly reflect processes in the underlying neural tissue. One of the major features—but also challenges—of neuroimaging is that it yields very complex, high-dimensional data sets including up to several hundred thousand voxels. Read this publication.
Murawski C, Harris PG, Bode S, Domínguez D. JF, Egan GF (2012). Led into temptation? Rewarding brand logos bias the neural encoding of economic decisions. PLoS ONE, 7(3): e34155.
Human decision-making is driven by subjective values assigned to alternative choice options. These valuations are based on reward cues. It is unknown, however, whether complex reward cues, such as brand logos, may bias the neural encoding of subjective value in unrelated decisions. In this functional magnetic resonance imaging (fMRI) study, we subliminally presented brand logos preceding intertemporal choices. We demonstrated that priming biased participants' preferences towards more immediate rewards in the subsequent temporal discounting task. This was associated with modulations of the neural encoding of subjective values of choice options in a network of brain regions, including but not restricted to medial prefrontal cortex. Our findings demonstrate the general susceptibility of the human decision making system to apparently incidental contextual information. We conclude that the brain incorporates seemingly unrelated value information that modifies decision making outside the decision-maker's awareness. Read this publication.
Bode S, He AH, Soon CS, Trampel R, Turner R, Haynes JD (2011). Tracking the unconscious generation of free decisions using ultra-high field fMRI. PLoS ONE, 6(6):e21612.
Recently, we demonstrated using functional magnetic resonance imaging (fMRI) that the outcome of free decisions can be decoded from brain activity several seconds before reaching conscious awareness. Activity patterns in anterior frontopolar cortex (BA 10) were temporally the first to carry intention-related information and thus a candidate region for the unconscious generation of free decisions. In the present study, the original paradigm was replicated and multivariate pattern classification was applied to functional images of frontopolar cortex, acquired using ultra-high field fMRI at 7 Tesla. Here, we show that predictive activity patterns recorded before a decision was made became increasingly stable with increasing temporal proximity to the time point of the conscious decision. Furthermore, detailed questionnaires exploring subjects' thoughts before and during the decision confirmed that decisions were made spontaneously and subjects were unaware of the evolution of their decision outcomes. These results give further evidence that FPC stands at the top of the prefrontal executive hierarchy in the unconscious generation of free decisions. Read this publication.
Bogler C, Bode S, Haynes JD (2011). Decoding successive computational stages of saliency processing. Current Biology, 21(19), 1667-1671.
An important requirement for vision is to identify interesting and relevant regions of the environment for further processing. Some models assume that salient locations from a visual scene are encoded in a dedicated spatial saliency map [1, 2]. Then, a winner-take-all (WTA) mechanism [1, 2] is often believed to threshold the graded saliency representation and identify the most salient position in the visual field. Here we aimed to assess whether neural representations of graded saliency and the subsequent WTA mechanism can be dissociated. We presented images of natural scenes while subjects were in a scanner performing a demanding fixation task, and thus their attention was directed away. Signals in early visual cortex and posterior intraparietal sulcus (IPS) correlated with graded saliency as defined by a computational saliency model. Multivariate pattern classification [3, 4] revealed that the most salient position in the visual field was encoded in anterior IPS and frontal eye fields (FEF), thus reflecting a potential WTA stage. Our results thus confirm that graded saliency and WTA-thresholded saliency are encoded in distinct neural structures. This could provide the neural representation required for rapid and automatic orientation toward salient events in natural environments. Read this publication.
Müller AD, Bode S, Myer L, Stahl J, von Steinbüchel N (2011). Predictors of adherence to antiretroviral treatment and therapeutic success among children in South Africa. AIDS Care, 23(2), 129-138.
The recent years have shown an up-scaling of treatment programs for HIV-infected children in resource-limited settings, with an increased focus on adherence. Little is known, however, about the influence of socioeconomic as well as caregivers' health beliefs on both adherence and virologic outcome of pediatric antiretroviral treatment in these settings. We conducted a cross-sectional study with 57 caregiver-child dyads at a public hospital in Cape Town, South Africa. Adherence was electronically monitored over three months, viral loads were available pre- and post-study. Caregivers answered questionnaires on their socioeconomic situation, attitudes toward and knowledge about treatment, and quality of life. Young children with a mean age of 51 months (SD 25.6) were investigated, and all were cared for by female caregivers. Mean adherence was 81%, and 67% of children achieved virologic suppression (VS). Household income, educational status, and child characteristics were not significantly correlated with adherence. Disclosure of both the child's and the caregiver's HIV status was linked to achieving VS and was a significant predictor for VS. A model including child's health status, caregiver's language skills, caregiver's disclosure, and perceived stigmatization could explain 95% of the variance in VS. Adherence and VS were not associated with socioeconomic factors in this population. Social factors such as stigmatization, fear of disclosure, and caregivers' attitudes toward the health-care system influenced VS but not adherence. Read this publication.
- Bode S (2010). From stimuli to motor responses: Decoding rules and decision mechanisms in the human brain. Leipzig: Max Planck Institute for Human Cognitive and Brain Sciences, 123 (MPI Series in Human Cognitive and Brain Sciences).
Tusche A, Bode S, Haynes JD (2010). Neural responses to unattended products predict later consumer choices. The Journal of Neuroscience, 30(23), 8024-8031.
Imagine you are standing at a street with heavy traffic watching someone on the other side of the road. Do you think your brain is implicitly registering your willingness to buy any of the cars passing by outside your focus of attention? To address this question, we measured brain responses to consumer products (cars) in two experimental groups using functional magnetic resonance imaging. Participants in the first group (high attention) were instructed to closely attend to the products and to rate their attractiveness. Participants in the second group (low attention) were distracted from products and their attention was directed elsewhere. After scanning, participants were asked to state their willingness to buy each product. During the acquisition of neural data, participants were not aware that consumer choices regarding these cars would subsequently be required. Multivariate decoding was then applied to assess the choice-related predictive information encoded in the brain during product exposure in both conditions. Distributed activation patterns in the insula and the medial prefrontal cortex were found to reliably encode subsequent choices in both the high and the low attention group. Importantly, consumer choices could be predicted equally well in the low attention as in the high attention group. This suggests that neural evaluation of products and associated choice-related processing does not necessarily depend on attentional processing of available items. Overall, the present findings emphasize the potential of implicit, automatic processes in guiding even important and complex decisions. Read this publication.
Bode S, Haynes JD (2009). Decoding sequential stages of task preparation in the human brain. Neuroimage, 45(2), 606-613.
The flow of information from sensory stimuli to motor responses in the human brain can be flexibly re-routed depending on task demands. However, it has remained unclear which sequence of processes is involved in preparing the brain for an upcoming task. Here, we used a combination of fMRI and multivariate pattern classification to decompose the information flow in a task-switching experiment. Specifically, we present a time-resolved decoding approach that allowed us to track the temporal buildup of task-related information. This approach also allowed us to distinguish encoding of the task from encoding of target stimuli and motor responses, thus separating between different components of information processing. We were able to decode from parietal and lateral prefrontal cortex which specific task-set a subject was currently holding. Importantly, this revealed that the intraparietal sulcus encoded task-set information before prefrontal cortex, and it was the only region to encode the specific task-set before the relevant target stimulus was presented. This suggests that task-related information in parietal cortex does not rely on input from prefrontal cortex as previously suggested. In contrast, our findings suggest that parietal cortex might play a role in establishing task-sets in prefrontal cortex. Read this publication.
Müller AD, Bode S, Myer L, Roux P, von Steinbüchel N (2008). Electronic measurement of adherence to paediatric antiretroviral therapy in South Africa. The Paediatric Infectious Disease Journal, 27(3), 257-262.
Little is known about adherence to pediatric antiretroviral regimens in countries of the developing world. Both assessment methods and predictors of adherence need to be examined to deliver appropriate health care to the growing patient population in resource-limited settings. METHODS: We conducted a prospective study of adherence in a pediatric HIV outpatient clinic in Cape Town, South Africa. Adherence was assessed by the Medication Event Monitoring System (MEMS) and caregiver self-report by Visual Analogue Scale (VAS). Virologic response was recorded at study baseline and closest follow-up visit, child and caregiver data were collected by questionnaires. RESULTS: For 73 children followed, median adherence by MEMS was 87.5%; median caregiver reported adherence was 100%. MEMS and caregiver report differed in reporting excellent (>95%) adherence, with MEMS classifying 36% of subjects in this category, whereas caregiver report classified 91%. Overall, 65% of children achieved virologic suppression after the study period. MEMS adherence was significantly associated with virologic suppression. The highest specificity was obtained when adjusting the data for doses taken at the prescribed time (91.3%). No predictors for the differences between MEMS and caregiver reported adherence could be identified. CONCLUSIONS: Adherence to pediatric antiretroviral regimens in South Africa is not lower than in the developed world, yet not high enough to guarantee long-term treatment success. Caregiver report seems unreliable in this setting. MEMS is a feasible and accurate measure of adherence for children on liquid drug formulations. Read this publication.
Bode S, Koeneke S, Jäncke L (2007). Different strategies do not moderate primary motor cortex involvement in mental rotation: a TMS study. Behavioral and Brain Functions, 3:38.
BACKGROUND: Regions of the dorsal visual stream are known to play an essential role during the process of mental rotation. The functional role of the primary motor cortex (M1) in mental rotation is however less clear. It has been suggested that the strategy used to mentally rotate objects determines M1 involvement. Based on the strategy hypothesis that distinguishes between an internal and an external strategy, our study was designed to specifically test the relation between strategy and M1 activity. METHODS: Twenty-two subjects were asked to participate in a standard mental rotation task. We used specific picture stimuli that were supposed to trigger either the internal (e.g. pictures of hands or tools) or the external strategy (e.g. pictures of houses or abstract figures). The strategy hypothesis predicts an involvement of M1 only in case of stimuli triggering the internal strategy (imagine grasping and rotating the object by oneself). Single-pulse Transcranial Magnetic Stimulation (TMS) was employed to quantify M1 activity during task performance by measuring Motor Evoked Potentials (MEPs) at the right hand muscle. RESULTS: Contrary to the strategy hypothesis, we found no interaction between stimulus category and corticospinal excitability. Instead, corticospinal excitability was generally increased compared with a resting baseline although subjects indicated more frequent use of the external strategy for all object categories. CONCLUSION: This finding suggests that M1 involvement is not exclusively linked with the use of the internal strategy but rather directly with the process of mental rotation. Alternatively, our results might support the hypothesis that M1 is active due to a 'spill-over' effect from adjacent brain regions. Read this publication.
Bennett D, Sasmita K, Murawski C, Bode S. Electrophysiological indices reflect switches between Bayesian and heuristic strategies in perceptual learning. BioRxiv. (available here).
Prochilo GA, Louis WR, Bode S, Zacher H, Molenberghs P. An extended commentary on post-publication peer review in organizational neuroscience. PsyArXiv. (available here).
Voigt K, Murawski C, Speer S, Bode S. Hard decisions shape the neural coding of preferences. BioRxiv. (available here).
Conferences, Symposia & Research talks
Bode S (2018). The role of voluntary decisions in shaping future preferences. Association for the Scientific Study of Consciousness (ASSC). Krakow, Poland.
Andrejevic M, Feuerriegel D, Turner WF, Laham S, Bode S (2018). Integration of morally relevant context in a novel moral judgement updating task. Australasian Society for Social and Affective Neuroscience (AS4SAN), Brisbane, Australia.
Bode S, Voigt K, Speer S, Murawski C (2018). Making hard decisions shapes the neural coding of preferences. Organisation for Human Brain Mapping (OHBM), Singapore.
Morawetz C, Heekeren HR, Bode S (2018). Regulating negative emotions affects dietary choice via modulation of value signals in vmPFC. Organisation for Human Brain Mapping (OHBM), Singapore.
Feuerriegel D, Bennett D, Alday PM, Bode S (2018). The Decision Decoding Toolbox (DDTBOX) - A multivariate pattern analysis toolbox for event-related potentials. Australian Mathematical Psychology Conference (AMPC). Perth, Australia.
Bode S (2017). The neural coding of decision-relevant information. Decision Making Seminar and Workshop, School of Health Sciences, The University of Melbourne, 21st November 2017, Melbourne, Australia.
Feuerriegel D, Bennett D, Alday PM, Bode S (2017). The Decision Decoding Toolbox (DDTBOX) - A multivariate pattern analysis toolbox for event-related potentials. Australasian Cognitive Neuroscience Conference (ACNS). Adelaide, Australia.
Goh A, Bode S, Bennett D, Chong T. (2017). Behavioural and computational studies on the value of information. Australasian Cognitive Neuroscience Conference (ACNS). Adelaide, Australia.
Voigt K, Murawski C, Speer S, Bode S (2017). The neural correlates of preference formation. Australasian Cognitive Neuroscience Conference (ACNS). Adelaide, Australia
Fung BJ, Bode S, Murawski C (2017). Caloric rewards alter time perception and time-dependent decision making. 1st Conference of the Timing Research Forum, Strasbourg, France.
Feuerriegel D, Bode S (2017). Performing MVPA on EEG data using the Decision Decoding Toolbox (DDTBOX). Multivariate Pattern Analysis (MVPA) for Cognitive Neuroscience. Workshop at the Australasian Cognitive Neuroscience Conference. Adelaide, Australia.
Bode S (2017). The value of information: would we pay for non-instrumental information? (Der Wert der Information: Würden wir auch für nutzloses Wissen zahlen?). 19 July 2017, Habilitation talk at University of Cologne, Germany.
Bennett D, Feuerriegel D, Alday PM, Bode S (2017). The Decision Decoding ToolBOX (DDTBOX): a multivariate pattern analysis toolbox for event-related potentials. Cognitive Computational Neuroscience, New York, USA.
Crone DL, Bode S, Murawski C, Laham SM (2017). The Socio-Moral Image Database (SMID): A novel stimulus set for the study of social, moral and affective processes. European Association for Social Psychology, Granada, Spain.
Crone DL, Bode S, Murawski C, Laham SM (2017). Exploring the structure of morality with a new moral image database. European Association for Social Psychology, Granada, Spain.
Chandrakumar D, Feuerriegel D, Bode S, Grech M, Keage AHD (2017). Event-related potentials in relation to risk-taking: a systematic review. 15th International Cognitive Neuroscience Conference (ICON), Amsterdam, The Netherlands.
Bode S, Bennett D, Feuerriegel D, Alday PM (2017). The Decision Decoding ToolBOX (DDTBOX) – a novel multivariate pattern analysis toolbox for ERPs. Organisation for Human Brain Mapping, Vancouver, Canada.
Morawetz C, Mohr P, Heekeren HR, Bode S (2017). Reappraisal of incidental emotions promotes risk aversion and modulates activity in VLPFC and DLPFC during risky decision-making. Organisation for Human Brain Mapping, Vancouver, Canada.
Crone DL, Bode S, Murawski C, Laham SM (2017). The Socio-Moral Image Database (SMID): A novel stimulus set for the study of social, moral and affective processes. Australasian Society for Social and Affective Neuroscience (AS4SAN), Melbourne, Australia.
Rosenblatt DH, Bode S, Dixon H, Murawski C, Wakefield M (2017). Health warnings promote healthier dietary decision making. Behavioural Research in Cancer Conference, Melbourne, Australia.
Voigt K, Murawski K, Bode S (2017). The neural basis of preference formation: The memory of past choices shapes preferences. Australasian Society for Social and Affective Neuroscience, Melbourne, Australia.
Stahl J, Bode S (2016). Main processing steps to prepare data for ERP analyses and MVPA. 2nd International Workshop on Multivariate Pattern Analysis and Event Related Potentials. 30 June / 1 August 2016, University of Cologne, Germany.
Bode S (2016). Multivariate pattern classification analysis (MVPA) for EEG: Introduction to classifiers and MVPA. 2nd International Workshop on Multivariate Pattern Analysis and Event Related Potentials. 30 June / 1 August 2016, University of Cologne, Germany.
Bode S (2016). Multivariate pattern classification analysis (MVPA) for EEG: Research questions and examples. 2nd International Workshop on Multivariate Pattern Analysis and Event Related Potentials. 30 June / 1 August 2016, University of Cologne, Germany.
Bode S (2016). Multivariate pattern classification analysis (MVPA) for EEG: The DDTBOX. 2nd International Workshop on Multivariate Pattern Analysis and Event Related Potentials. 30 June / 1 August 2016, University of Cologne, Germany.
Bode S (2016). Introduction to Multivariate pattern classification analysis (MVPA) for EEG:
General approach and examples. 1st University of South Australia & University of Melbourne Multivariate Analysis of Event-related Potentials Workshop. 4March, University of South Australia, Australia.
Bode S (2016). Introduction to Multivariate pattern classification analysis (MVPA) for EEG:
The DDTBOX. 1st University of South Australia & University of Melbourne Multivariate Analysis of Event-related Potentials Workshop. 4March, University of South Australia, Australia.
Bode S, Keage H, Feuerriegel D, Nicholls MER, Churches O (2016). Early decision-related information predicts response times: a jackknifing approach for MVPA for ERPs. Australasian Cognitive Neuroscience Society, Newcastle, Australia.
Turner W, Johnston P, de Boer K, Morawetz C, Bode S (2016). Multivariate pattern analysis of event-related potentials predicts the general desirability of objects. Australasian Cognitive Neuroscience Society, Newcastle, Australia.
Rens N, Bode S, Cunnington R (2016). Decoding voluntary decisions: perception of freedom is dependent on keeping your options open. Australasian Cognitive Neuroscience Society, Newcastle, Australia.
Rosenblatt DH, Wakefield M, Bode S, Dixon H, Murawski C (2016). Investigating the efficacy of food product health warnings. Cancer Council Victoria Research Seminar, Melbourne, Australia.
Goh A, Bode S, Bennett D, Little DR (2016). Factorial manipulation of target detectability reveals sequential accumulation processes in both ERPs and RTs. Psychonomics Society’s 57th Annual Meeting, Boston, MA, USA.
Bennett D, Brydevall M, Murawski C, Bode S (2016). The feedback-related negativity encodes an information prediction error in decisions to seek information. Society for Neuroscience, San Diego, USA.
Fung BJ, Bode S, Murawski C (2016). Consumption of caloric reward increases subjective opportunity costs. Society for Neuroscience, San Diego, USA.
Rens N, Burianová H, Bode S, Cunnington R (2016). Frontoparietal and salience networks precede voluntary decisions in a virtual environment. Society for Neuroscience, San Diego, USA.
Little DR, Bode S, Goh A, Bennett D, (2016). Factorial manipulations of target detectability reveal sequential decision processes in EEG and RT. Cognitive Lunch, The University of Melbourne, VIC.
Rosenblatt DH, Bode S, Wakefield M, Dixon H, Murawski C (2016). Anti-obesity health warnings promote healthier dietary decision making. Australian and New Zealand Obesity Society Conference, Brisbane, QL.
Goh A, Little DR, Bode S, Bennett D. (2016). Serial processing in visual search: a synthesis of event-related potential analyses and response time modelling. Students of Brain Research Conference, Melbourne, VIC.
Fung BJ, Bode S, Murawski C (2016). High monetary reward rates and caloric rewards decrease temporal persistence. Melbourne Neuroscience Institute: Decision Neuroscience Symposium, Melbourne, VIC.
Voigt K, Bennett D, Murawski C, Bode S (2016). Endogenous preference formation: Choice history systematically shapes preferences. Melbourne Neuroscience Institute: Decision Neuroscience Symposium, Melbourne, VIC.
Goh A, Little DR, Bode S, Bennett D, (2016). Serial processing in visual search: a synthesis of event-related potential analyses and response time modelling. Melbourne Neuroscience Institute: Decision Neuroscience Symposium, Melbourne, VIC.
Bennett D, Brydevall M, Murawski C, Bode S (2016). The feedback-related negativity encodes an information prediction error in decisions to seek information. Melbourne Neuroscience Institute: Decision Neuroscience Symposium, Melbourne, VIC.
Bode S, Bennett D, Corbett E, Sewell DK, Paton B, Stahl J, Egan GF, Smith PL, Murawski C (2016). The neural origins of evidence accumulation for perceptual decisions: Evidence from two identical ERP and fMRI studies. XXXI International Congress of Psychology, Yokohama, Japan.
Morawetz C, Bode S, Heekeren H (2016). Neural mechanisms of controlling emotions: a meta-analysis of fMRI studies on emotion regulation in humans. European Society for Cognitive and Affective Neuroscience, Porto, Portugal.
Chan YM, Pianta MJ, Bode S, McKendrick AM (2016). Neural correlates of audiovisual synchrony judgements in older adults. Experimental Psychology Conference, Melbourne, Australia.
Brydevall M, Bennett D, Murawski C, Bode S (2016). Electrophysiological indices reflect intrinsic valuation of information in decision making under uncertainty. Experimental Psychology Conference, Melbourne, Australia.
Bennett D, Sasmita K, Murawski C, Bode S (2016). Bayes if it pays: Switches between Bayesian and heuristic learning strategies are encoded in the event-related potential. Experimental Psychology Conference, Melbourne, Australia.
Voigt K, Murawski C, Bode S (2016). Choice history systematically shapes preferences. Australasian Experimental Psychology Conference, Melbourne, Australia.
Fung BF, Bode S, Murawski C (2016). The relation between delay discounting, time perception and cardiac signals. Experimental Psychology Conference, Melbourne, Australia.
Crone DL, Bode S, Murawski C, Laham SM (2016). Probing moral perception with a novel moral image set. Society for Personality and Social Psychology, San Diego, CA, USA.
Bennett D, Brydevall M, Murawski C, Bode S (2015). The feedback-related negativity reflects intrinsic preference for information in decision making under uncertainty. Monash Brain Function Workshop, Melbourne, Australia.
Chan YM, Pianta MJ, Bode S, McKendrick AM (2015). Neural correlates of audiovisual synchrony judgements in older adults. Monash Brain Function Workshop, Melbourne, Australia.
Fung BJ, Bode S, Murawski C (2015). The relationship between time perception, temporal discounting, and cardiac measures. Monash Brain Function Workshop, Melbourne, Australia.
Bode S, Bennett D, Corbett E, Sewell DK, Paton B, Stahl J, Egan GF, Smith PL, Murawski C (2015). Tracking the neural origins of evidence accumulation for perceptual decisions using event-related potentials and functional magnetic resonance imaging. Australasian Cognitive Neuroscience Society, Auckland, New Zealand.
Rens N, Burianova H, Bode S, Cunnington R (2015). Decoding free decisions in a virtual environment. Australasian Cognitive Neuroscience Society, Auckland, New Zealand.
Fung BJ, Bode S, Murawski C (2015). The relation between delay discounting, time perception and cardiac signals. Australasian Cognitive Neuroscience Society, Auckland, New Zealand.
Bennett D, Brydevall M, Murawski C, Bode S (2015). The feedback-related negativity reflects an intrinsic preference for information in decision making under uncertainty. Australasian Cognitive Neuroscience Society, Auckland, New Zealand.
Voigt K, Bode S, Murawski C (2015). Choices of goods systematically change preferences. Australasian Cognitive Neuroscience Society, Auckland, New Zealand.
Bennett D, Brydevall M, Murawski C, Bode S (2015). The feedback-related negativity reflects an intrinsic preference for information in decision making under uncertainty. Students of Brain Research Conference, Melbourne, Australia.
Fung BJ, Bode S, Murawski C (2015). The relation between delay discounting, time perception and cardiac signals. Students of Brain Research Conference, Melbourne, Australia.
Bode S (2015). Decoding cognition from neuroimaging data. IBM and UoM Workshop: Applying advanced technology to advanced precision neuroscience, The University of Melbourne, Australia.
Bode S (2015). Predicting decision-related information from patterns of event-related potentials. NBD Invited Speaker Seminar Series. 10 September, Duke-NUS Graduate Medical School, Singapore.
Bode S (2015). Predicting decision-related information from patterns of event-related potentials. Psychology, Neuroscience & Methods Seminar, 7 September, University of Cologne, Germany.
Bode S (2015). Multivariate pattern classification analysis (MVPA) for EEG data. Workshop: An Introduction to Multivariate Pattern Analysis, 7 September, University of Cologne, Germany.
Bode S (2015). Multivariate pattern classification analysis (MVPA) for fMRI data. Workshop: An Introduction to Multivariate Pattern Analysis, 7 September, University of Cologne, Germany.
Bode S (2015). The application of MVPA to event-related potentials. Part I: Theory and examples. 1 September, Pattern Recognition in Neuroimaging Workshop, Freie University Berlin, Germany.
Bode S (2015). The application of MVPA to event-related potentials. Part II: The Decision Decoding Toolbox. 1 September, Pattern Recognition in Neuroimaging Workshop, Freie University Berlin, Germany.
Bode S (2015). The prediction of decision-related information from brain activity using multivariate analyses of event-related potentials. CCNB Seminar, 31 August, Freie University Berlin, Germany.
Bode S (2015). Free Will and neuroscience – A demystification. 17 August 2015. Forum for Culture and Science, Hannover, Germany.
Bode S (2015). Using multivariate event-related potential analyses to predict decision-related information from brain activity. 30 July, Adelaide University, Adelaide, Australia.
Bode S (2015). Prediction of decision-related information from patterns of event-related potentials. 30 March, Colloquium at the University of South Australia, Adelaide, Australia.
Bode S (2015). Can we use fMRI to read out the content of cognition? 1 April 2015. University of South Australia, Adelaide, Australia.
Morawetz C, Bode S, Baudewig J, Jacobs AM, Heekeren H (2015). Neural representation of emotion regulation goals. Pattern Recognition in Neuroimaging Workshop, Freie University Berlin, Germany.
Bode S, Murawski C (2015). Differences in intertemporal choice are predicted by the neural encoding of numerical magnitude. Organisation for Human Brain Mapping, Honululu, Hawaii, USA.
Bennett D, Bode S, Warren Hi, Murawski C (2015) Decision-makers pay for irrelevant information under uncertainty. Australasian Experimental Psychology Conference, Sydney, Australia.
Voigt K, Murawski C, Bode S (2015). How much you are willing to spend on consumable goods systematically is shaped by past decisions. Australasian Experimental Psychology Conference, Sydney, Australia.
Fung BJ, Murawski C, Bode S (2015). Time estimations are affected by the consumption of primary reward. Australasian Experimental Psychology Conference, Sydney, Australia.
Crone DL, Bode S, Murawski C, Laham, SM (2015). Development and validation of a moral foundations picture set. Society for Australasian Social Psychologists, Newcastle, Australia.
Bennett D, Bode S, Warren H, Murawski C (2015) Computational modelling of information seeking under uncertainty. Australian Mathematical Psychology Conference, Newcastle, Australia.
Morawetz C, Bode S, Baudewig J, Kirilina E, Heekeren H. (2014). Neural representations of emotion regulation strategies. 11th Meeting of the Austrian Society for Psychology (ÖGP), Vienna, Austria.
Murawski C (2014). From Decision Neuroscience to Public Policy. Problem Gambling: An Inter-disciplinary Dialogue between Neuroscientists, Clinicians and Policy Makers. Melbourne, Australia.
Burnett J, Davis K, Murawski C, Wilkins R, Wilkinson N (2014). Measuring adequacy of retirement savings in Australia. 22nd Colloquium of Superannuation Researchers, University of New South Wales, Sydney, Australia.
Murawski, C (2014). Financing our futures. 10th Economic and Social Outlook Conference, Melbourne, Australia.
Bode S, Stahl J (2013). Investigating error processing by decoding patterns of event-related potentials. The 4th Australasian Cognitive Neuroscience Society, Melbourne, Australia.
Bode S, Bennett D, Stahl J, Murawski C (2013). Predicting implicit abstract stimulus attributes from patterns of event-related potentials. The 4th Australasian Cognitive Neuroscience Conference, Melbourne, Australia.
Bennett D, Murawski C, Bode S (2013). Single-Trial P300 amplitudes index feedback information in reinforcement learning. The 4th Australasian Cognitive Neuroscience Conference, Melbourne, Australia.
Thio J, Murawski C, Bode S (2013). The effects of context priming on intertemporal decision-making. The 4th Australasian Cognitive Neuroscience Conference, Melbourne, Australia.
Stahl J, Bierbrauer A, Gommann J, Lenk K, Bode S (2013). Error detection in a force-production task: Testing the force-unit monitoring model. The 4th Australasian Cognitive Neuroscience Conference, Melbourne, Australia.
Bennett D, Murawski C, Bode S (2013). Decoding distinct dimensions of feedback in reinforcement learning: an electroencephalography study. Students of Brain Research Conference, Melbourne, Australia.
Bode S (2013). Informing decision-making models by decoding patterns of brain activity. 2 October, Queensland Brain Institute Seminar, University of Queensland, Brisbane, Australia.
Bode S (2013). Predicting decisions and decision-errors from EEG and fMRI signals using multivariate pattern analysis. 12 September, Seminar Program of the Department of Optometry and Vision Sciences, The University of Melbourne, Australia.
Bode S (2013). Informing models of human decision-making by decoding patterns of brain activity. 14th August, Colloquium, Melbourne School of Psychological Sciences, The University of Melbourne, Australia.
Bode S (2013). Extracting information from patterns of event-related potentials: Using MVPA for EEG data. Innovative Methods in Neuroimaging, Perception in Action Research Workshop. 8-9 August, Macquarie University Sydney, Australia.
Bode S (2013). Decoding decisions and post-decision errors from multivariate patterns of fMRI and EEG activity. 25 February, Colloquium, University of Newcastle, Australia.
Bode S (2013). Predicting decisions and post-decision errors from multivariate patterns of fMRI and EEG activity. 22nd February, Colloquium at Macquarie University Sydney, Australia.
Woolgar A, Bode S, Golland P (2013). Confounds in Multivoxel Pattern Analysis: what should we do about reaction time differences? Innovative Methods in Neuroimaging, Perception in Action Research Workshop. Macquarie University Sydney, Australia.
Bennett D, Murawski C, Bode S (2013). Decoding feedback value and information from EEG signals. Innovative Methods in Neuroimaging, Perception in Action Research Workshop. Macquarie University Sydney, Australia.
Stahl J, Bode S (2013). Perspectives on error processing. A methodological update. Symposium of the University of Cologne and the University of Aachen, Germany.
Bode S (2013). “Mind reading” – A dialog between neuroscience and philosophy about the (im)possibility of one of the oldest dreams of mankind. 29 April 2013, Forum for Culture and Science, Hannover, Germany.
Bode S, Stahl J (2013). ERP-based multivariate pattern classification predicts errors before an overt response is executed. Organisation for Human Brain Mapping, Seattle, WA, USA.
Stahl J, Schmidt-Samoa C, Bode S, Dechent P, Barke A (2013). Neural correlates of perfectionism-specific error processing. An event-related fMRI study. Psychologie & Gehirn, Würzburg, Germany.
Brown S, Murawski C (2013). The riskiness of household portfolios over the life-cycle. Research Seminar, Department of Finance, The University of Melbourne, Australia.
Burnett C, Davis K, Murawski C, Wilkins R, Wilkinson N (2013). Measuring retirement savings adequacy in Australia. Melbourne Money and Finance Conference, Brighton, Australia.
Murawski C (2013). The economics of the long-term. Symposium 'Renaissance of the Humanities', Ormond College, The University of Melbourne, Australia.
Murawski C (2013). Measuring retirement savings adequacy. Research seminar, Department of Finance, The University of Melbourne, Australia.
Bode S, Stahl J (2012). ERP-based multivariate pattern classification predicts errors before an overt response is executed. 3rd Australasian Cognitive Neuroscience Society, Brisbane, Australia.
Bode S, Sewell D, Lilburn S, Forte JD, Smith PL, Stahl J (2012). Early choice-predictive EEG signals reflect starting point bias in evidence accumulation. XXIXI International Congress of Psychology, Cape Town, South Africa.
Bode S (2012). Decoding decisions from brain signals. 18 August. Max Planck Institute for Human Cognitive and Brain Sciences, Dept. Neurology Seminar Series, Germany.
Bode S (2012). Decoding mechanisms for internal decision making from fMRI and EEG signals. 3 May, Monash Biomedical Imaging Science Seminar, Monash University, Australia.
Bode S (2012). Decoding decisions from multivariate fMRI and EEG signals. 1 May, Colloquium Melbourne Neuropsychiatry Centre, The University of Melbourne, Australia.
Morawetz C, Bode S, Baudewig J, Heekeren HR (2012). Skydivers and emotion regulation: training the amygdale. Organisation for Human Brain Mapping, Beijing, China.
Cichy RM, Bode S, Sterzer P, Haynes JD (2012). Object recognition under little and no visibility. Vision Sciences Society, Naples, Italy.
Bode S, Sewell D, Lilburn S, Forte JD, Stahl J, Smith PL (2012). Early choice-predictive EEG signals reflect starting point bias in evidence accumulation. Australian Mathematical Psychology Conference, Adelaide, Australia.
Bode S (2011). Predicting choices from brain activation. Australasian Cognitive Neurosciences Conference, Sydney, Australia.
Bode S, Murawski C, Harris PG, Domínguez D. JF, Egan GF (2011). Led into temptation? Subliminally presented reward cues bias incidental economic decisions. Organisation for Human Brain Mapping, Quebec City, Canada.
Bode S, Murawski C, Harris PG, Domínguez D. JF, Egan GF (2011). Subliminally presented reward cues bias incidental economic decisions and the encoding of subjective values in the brain. Association for the Scientific Studies of Consciousness Kyoto, Japan.
Bode S (2011). Decoding decisions from EEG signals. 24 February, EEG-Group Series, The University of Melbourne, Australia.
Murawski C, Harris PG, Bode S, Domínguez D. JF, Egan GF (2011). Subliminally presented reward cues bias the neural encoding of economic decisions. Cognitive Neuroscience Symposium, The University of Melbourne, Australia.
Harris PG, Murawski C, Bode S, Domínguez D. JF, Egan GF (2010). Brand reactions bias incidental decision-making. Neuroeconomics: Decision Making and the Brain – Society for Neuroeconomics, Evanston, IL, USA.
Murawski C, Harris PG, Bode S, Domínguez D. JF, Egan GF (2010). Brand reactions bias incidental decision-making. Computations, Decisions, and Movement, Schloss Rauischholzhausen, Germany.
Bode S (2010). Decoding decision mechanisms in the human brain. 15 September, Cognitive Neuroscience Symposium, The University of Melbourne, Australia.
Bode S (2010). Decoding rules and decision mechanisms in task preparation. 16 September, Florey Neuroscience Institute Cognitive Neuroscience Symposium, The University of Melbourne, Australia.
Bode S (2010). Decoding decision mechanisms for task preparation from distributed patterns of brain activation. 1 September, Colloquium Psychological Sciences, The University of Melbourne, Australia.
Bode S (2010). From stimuli to motor responses: Decoding rules and decision mechanisms in the human brain. 8 July, Faculty for Biological Sciences, Pharmacy & Psychology, University of Leipzig, Germany.
Bode S, Bogler C, Haynes JD (2009). Two modes of perceptual decision making with and without awareness. Berlin Brain Days, Berlin, Germany.
Bode S, Haynes JD (2009). Decoding the transition from perceptual decision making to free decisions. 24 March, Colloquium Experimental Psychology, University of Göttingen, Germany.
Schafmeister F, Bode S, Gibbons H, Kirchberg W, Menrad N, Blomeyer L, Hartmann M, von Steinbüchel N (2009). Development of a standardized stimulus-set for the investigation of semantic memory. Gehirn & Gesundheit, Deutsche Gesellschaft für Medizinische Psychologie, Göttingen, Germany.
Bode S, Bogler C, Walter Si, Haynes JD (2009). Comparing mechanisms for decision making using multivariate decoding. Organisation for Human Brain Mapping, San Francisco, CA, USA.
Bogler C, Bode S, Haynes JD (2009). Multivariate decoding reveals successive computational stages of saliency processing. Organisation for Human Brain Mapping, San Francisco, CA, USA.
Bode S, Bogler C, Soon SC, Haynes JD (2009). Differential encoding of mechanisms for human decision making. Association for the Scientific Studies of Consciousness, Berlin, Germany.
Bode S, Haynes JD (2008). Neural encoding of object categories with and without awareness: A challenge for signal detection models of human decision making. XXIX International Congress of Psychology, Berlin, Germany.
Müller AD, Bode S, von Steinbüchel N, Myer L (2008). Predictors of antiretroviral treatment adherence and therapeutic success among children in Cape Town, South Africa. XVII International AIDS Conference, Mexico City, Mexico.
Bode S, He AH (2008). Free will in the brain? 10 July, Philosophical Seminar, Leibniz University of Hanover, Germany.
Bode P, Bode S (2008). Is there a God? Proofs of God's existence in history of philosophy and natural sciences. 2 September 2008, Forum for Culture and Science, Hannover, Germany.
Bode S, He AH, Bode P (2008). A neuroscientific perspective on free will. 10 July 2008, Forum for Culture and Science, Hanover, Germany.
Bode S, Haynes JD (2008). Decoding the transformation of sensory information to motor responses. 12 June, Duke-NUS – Graduate Medical School, Singapore.
Bode S, Haynes JD (2008). Neural encoding of perceptual decision making without awareness: Challenges for signal detection models of perception. Organisation for Human Brain Mapping, Melbourne, Australia.
Bode S, Haynes JD (2007). Decoding task-sets from intraparietal sulcus and prefrontal cortex using multivariate pattern classification. 3rd Bernstein Center for Computational Neuroscience Symposium, Göttingen, Germany.
Bode S, Haynes JD (2007). Encoding of sensory stimuli and task sets in prefrontal cortex. Organisation for Human Brain Mapping, Chicago, IL, USA.
Müller AD, Myer L, Jaspan HB, Bode S, Roux P, von Steinbüchel N (2007). Paediatric adherence in South Africa measured by Medication Event Monitoring System and its effect on treatment efficacy. 2nd International Conference on HIV Treatment Adherence, New Jersey City, NY, USA.
Müller AD, Myer L, Jaspan HB, Bode S, Roux P, von Steinbüchel N (2006). Innovative use of electronic measurements for adherence to liquid antiretrovirals in an urban South African paediatric HIV clinic. Priorities in AIDS Treatment and Care, Cape Town, South Africa.
Müller AD, Bode S, Myer L, von Steinbüchel N (2006). Monitoring adherence to liquid antiretroviral medication in South African children – results and challenges. 10th European Symposium on Patient Compliance and Persistence, Bonn, Germany.
Bode S, Jäncke L (2006). Strategy-specific involvement of the primary motor cortex in mental rotation? A TMS-Study. Psychologie & Gehirn, Dresden, Germany.
Tilch HL, Richter S, Bode S, Stiens G, von Steinbüchel N, Hüther G (2006). Therapeutic effects of individual favorite music in elderly people. 48th Tagung experimentell arbeitender Psychologen, Mainz, Germany.
Bode S, Rammsayer T (2004). Correlations between self-estimated stability of behavior and fundamental dimensions of personality. 44th Kongress der Deutschen Gesellschaft für Psychologie, Göttingen, Germany.
Bischof V, Bode S, Grünkorn G, Hübbe L, Jänen I, Schulte K, Ulbricht T, Rammsayer T (2003). Age dependency of Big-Five personality traits and their stability. 7th Arbeitstagung der Fachgruppe für Differentielle Psychologie, Persönlichkeitspsychologie und Psychologische Diagnostik der DGPS, Halle, Germany.
The Decision Decoding ToolBOX (DDTBOX) is our lab's freely available open-source software toolbox for multivariate pattern analysis of EEG data in Matlab and can be accessed through this link: https://github.com/DDTBOX/DDTBOX
Our official peer-reviewed version is published in Neuroinformatics and is freely available here. When using our toolbox, please cite this paper as:
Bode S, Feuerriegel D, Bennett D, Alday PM (2018). The Decision Decoding ToolBOX (DDTBOX): a multivariate pattern analysis toolbox for event-related potentials. Neuroinformatics, in press. DOI: 10.1007/s12021-018-9375-z.
EEG Lab Usage
The Decision Neuroscience Lab assists with coordinating the Electroencephalography (EEG) lab of the Melbourne School of Psychological Sciences (MSPS). This video, produced by our fantastic lab manager Maja Brydevall (and supported by one of our students, Daniel Rosenblatt, and former research intern, Sophia Bock) shows new users how to handle the equipment correctly.
Follow us on Twitter! Stay updated on the latest publications, DDTBOX upgrades and news from the Decision Neuroscience Lab.
DLab in the Media
Would health warnings on unhealthy foods make you think again?
Our collaborative work on the impact of health warning messages on dietary decision-making, led by DLab students Daniel Rosenblatt, Patrick Summerell and Alyssa Ng, has been featured in this article in Pursuit. It has since been covered on TV, radio and for online news by ABC Online, SBS News, Nine Honey, Yahoo7, The Daily Mail (UK), The New Daily, Adelaide Advertiser, Channel 7 News, The Project on Channel 7, ABC The World Today, 3AW, Hit/2day FM, KIIS FM, 6PR, Tripple M, The Australian, Channel 10, ABC Central Victoria, ABC Perth, Namibia Press Agency (Namibia), Xinhua Net (China), DocCheck (Germany), and many more!
New article in IMPACT featuring the Decision Science Hub
This article in IMPACT features the work we are doing together with Prof Rob Hester, A/Prof Olivia Carter, Dr Nicholas Van Dam and Dr Hinze Hogendoorn as part of the University of Melbourne's Decision Science Hub.
DLab at the Science Gallery Melbourne exhibition "Blood - attract and repel"
The Decision Neuroscience Lab has participated in the exhibition by contributing more science to the gallery experience. Read the short report from the MSPS news section here. Our collaboration with the artists Ollie & Sarah (Ollie Cotsaftis and Sarah McArthur) has led to an innovative research experiment, which has been featured in an article in Pursuit.
Beyond - the new strategic plan by the Faculty of Medicine, Dentistry and Health Sciences
Katharina Voigt, Stefan Bode (and Will Turner as the participant) are featured in the research section of the booklet for the faculty's new strategic plan Beyond 2018.
Scanning your brain can predict what will happen in the future
In this article in the New Scientist Stefan Bode is commenting on Genevski, Yoon and Knutson's fascinating paper published in The Journal of Neuroscience (2017) on predicting the success of crowd-sourcing initiatives at population level from individual's brain activity patterns.
Using finance and psychology to fight fat
This article in Pursuit that accompanied the Made Possible By Melbourne campaign explores our joint efforts with the Cancer Council Victoria and the Max Planck Institute for Human Cognitive and Brain Sciences Leipzig to understand and prevent obesity.
Finance + Psychology: Finding a way to fight obesity
This article in Pursuit by Stefan Bode and Carsten Murawski discusses the recent findings from collaborative work with Dr Annette Horstmann (Simmank, Murawski, Bode, & Horstmann, 2015, Front Behav Neurosci), conducted at the Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, showing that obese people have an increased risk of being biased by environmental cues in their financial decisions.
This article in the inaugural edition of Exchange Magazine features our interdisciplinary research approach as the lab was initially conceived as a collaborative project between the School of Psychology and the Department of Finance.
How to help take control of your brain and make better decisions
In this article in The Conversation, reprinted in The Washington Post and reprinted again on SBS News, former DLab PhD student Daniel Bennett discusses our recent study (Bode, Bennett, Stahl, & Murawski, 2014, PLoS ONE) and explores the possibility of automatic, unconscious influences of stimuli in our environment on decision-making.
Bubbly personality: How our biology hits budgets
This article in Pursuit discusses how Finance and Neuroscience can be optimally combined to better understand human financial decision making, and how the Decision Neuroscience Lab contributes to this agenda.
Brain imaging: The smart way to predict intelligence?
In this article in The Conversation, Stefan Bode and Michael Farrell discuss a paper by Cole et al. (2012) on whether global connectivity of the prefrontal cortex predicts intelligence.