Decoding fairness motivations from multivariate brain activity patterns

Abstract A preference for fairness may originate from prosocial or strategic motivations: we may wish to improve others’ well-being or avoid the repercussions of selfish behavior. Here, we used functional magnetic resonance imaging to identify neural patterns that dissociate these two motivations. Participants played both the ultimatum and dictator game (UG–DG) as proposers. Because responders can reject the offer in the UG, but not the DG, offers and neural patterns between the games should differ for strategic players but not prosocial players. Using multivariate pattern analysis, we found that the decoding accuracy of neural patterns associated with UG and DG decisions correlated significantly with differences in offers between games in regions associated with theory of mind (ToM), such as the temporoparietal junction, and cognitive control, such as the dorsolateral prefrontal cortex and inferior frontal cortex. We conclude that individual differences in prosocial behavior may be driven by variations in the degree to which self-control and ToM processes are engaged during decision-making such that the extent to which these processes are engaged is indicative of either selfish or prosocial motivations.

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The neural representational space of social memory

10.1101/130351 ◽

2017 ◽

Cited By ~ 1

Author(s):

Sarah L. Dziura ◽

James C. Thompson

Keyword(s):

Social Networks ◽

Human Brain ◽

Incidental Learning ◽

Functional Neuroimaging ◽

Brain Activity ◽

Temporoparietal Junction ◽

Representational Space ◽

Analysis Technique ◽

The Social ◽

Multivariate Pattern

AbstractSocial functioning involves learning about the social networks in which we live and interact; knowing not just our friends, but also who is friends with our friends. Here we utilized a novel incidental learning paradigm and representational similarity analysis (RSA), a functional MRI multivariate pattern analysis technique, to examine the relationship between learning social networks and the brain's response to the faces within the networks. We found that accuracy of learning face pair relationships through observation is correlated with neural similarity patterns to those pairs in the left temporoparietal junction (TPJ), the left fusiform gyrus, and the subcallosal ventromedial prefrontal cortex (vmPFC), all areas previously implicated in social cognition. This model was also significant in portions of the cerebellum and thalamus. These results show that the similarity of neural patterns represent how accurately we understand the closeness of any two faces within a network, regardless of their true relationship. Our findings indicate that these areas of the brain not only process knowledge and understanding of others, but also support learning relations between individuals in groups.Significance StatementKnowledge of the relationships between people is an important skill that helps us interact in a highly social world. While much is known about how the human brain represents the identity, goals, and intentions of others, less is known about how we represent knowledge about social relationships between others. In this study, we used functional neuroimaging to demonstrate that patterns in human brain activity represent memory for recently learned social connections.

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Spatiotemporally Resolved Multivariate Pattern Analysis for M/EEG

10.1101/2021.08.17.456594 ◽

2021 ◽

Author(s):

Cameron J Higgins ◽

Diego Vidaurre ◽

Nils Kolling ◽

Yunzhe Liu ◽

Tim Behrens ◽

...

Keyword(s):

Pattern Analysis ◽

Predictive Accuracy ◽

Brain Activity ◽

Activity Patterns ◽

Multivariate Pattern Analysis ◽

Model Framework ◽

Model Inversion ◽

Classification And Regression ◽

Multivariate Pattern ◽

Generative Encoding

An emerging goal in neuroscience is tracking what information is represented in brain activity over time as a participant completes some task. Whilst EEG and MEG offer millisecond temporal resolution of how activity patterns emerge and evolve, standard decoding methods present significant barriers to interpretability as they obscure the underlying spatial and temporal activity patterns. We instead propose the use of a generative encoding model framework that simultaneously infers the multivariate spatial patterns of activity and the variable timing at which these patterns emerge on individual trials. An encoding model inversion allows predictions to be made about unseen test data in the same way as in standard decoding methodology. These SpatioTemporally Resolved MVPA (STRM) models can be flexibly applied to a wide variety of experimental paradigms, including classification and regression tasks. We show that these models provide insightful maps of the activity driving predictive accuracy metrics; demonstrate behaviourally meaningful variation in the timing of pattern emergence on individual trials; and achieve predictive accuracies that are either equivalent or surpass those achieved by more widely used methods. This provides a new avenue for investigating the brain's representational dynamics and could ultimately support more flexible experimental designs in future.

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Beta Neurofeedback Training Improves Attentional Control in the Elderly

Psychological Reports ◽

10.1177/0033294119900348 ◽

2020 ◽

pp. 003329411990034 ◽

Cited By ~ 1

Author(s):

Jacek Bielas ◽

Łukasz Michalczyk

Keyword(s):

Executive Functioning ◽

Attentional Control ◽

Brain Activity ◽

Activity Patterns ◽

Reaction Times ◽

The Elderly ◽

Self Control ◽

Control Group ◽

Neurofeedback Training ◽

Age Related

One of the well-documented behavioral changes that occur with advancing age is a decline in executive functioning, for example, attentional control. Age-related executive deficits are said to be associated with a deterioration of the frontal lobes. Neurofeedback is a training method which aims at acquiring self-control over certain brain activity patterns. It is considered as an effective approach to help improve attentional and self-management capabilities. However, studies evaluating the efficacy of neurofeedback training to boost executive functioning in an elderly population are still relatively rare and controversial. The aim of our study was to contribute to the assessment of the efficacy of neurofeedback as a method for enhancing executive functioning in the elderly. We provided a group of seniors with beta up-training (12–22 Hz), consisting of 20 sessions (30 minutes each), on the Cz site and tested its possible beneficiary influence on attentional control assessed by means of the Stroop and Simon tasks. The analysis of the subjects’ mean reaction times during consecutive tasks in the test and the retest, after implementation of neurofeedback training, showed a significant improvement. In contrast, the difference in reaction times between the test and the retest in the control group who had not been submitted to neurofeedback training was not significant.

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Low competitive status elicits aggression: behavioral and neural evidence

10.1101/2020.06.20.162586 ◽

2020 ◽

Author(s):

Macià Buades-Rotger ◽

Martin Göttlich ◽

Ronja Weiblen ◽

Pauline Petereit ◽

Thomas Scheidt ◽

...

Keyword(s):

Brain Activity ◽

Activity Patterns ◽

Ice Hockey ◽

Anterior Cingulate ◽

Neural Basis ◽

Dorsal Anterior Cingulate Cortex ◽

Overwhelming Evidence ◽

Dorsolateral Prefrontal ◽

Status Differentiation ◽

Status Position

AbstractWinners are commonly assumed to compete more aggressively than losers. Here, we find overwhelming evidence for the opposite. We first demonstrate that low-ranking teams commit more fouls than they receive in top-tier soccer, ice hockey, and basketball leagues. We replicate this effect in the laboratory, showing that participants deliver louder sound blasts to a rival when placed in a low-status position. Using neuroimaging, we characterize brain activity patterns that encode competitive status as well as those that facilitate status-dependent aggression. These analyses reveal three key findings. First, anterior hippocampus and striatum contain multivariate representations of competitive status. Second, interindividual differences in status-dependent aggression are linked with a sharper status differentiation in the striatum and with greater reactivity to status-enhancing victories in the dorsal anterior cingulate cortex. Third, activity in ventromedial, ventrolateral, and dorsolateral prefrontal cortex is associated with trial-wise increases in status-dependent aggressive behavior. Taken together, our results run counter to narratives glorifying aggression in competitive situations. Rather, we show that those in the lower ranks of skill-based hierarchies are more likely to behave aggressively and identify the potential neural basis of this phenomenon.

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Recruitment of cognitive control regions during effortful self-control is associated with altered brain activity in control and reward systems in dieters during subsequent exposure to food commercials

PeerJ ◽

10.7717/peerj.6550 ◽

2019 ◽

Vol 7 ◽

pp. e6550 ◽

Cited By ~ 3

Author(s):

Richard B. Lopez ◽

Andrea L. Courtney ◽

Dylan D. Wagner

Keyword(s):

Cognitive Control ◽

Brain Activity ◽

Self Control ◽

Food Cues ◽

Dorsolateral Prefrontal ◽

Subsequent Exposure ◽

Disinhibited Eating ◽

Regulatory Capacity ◽

Frontoparietal Control Network ◽

Control Regions

Engaging in effortful self-control can sometimes impair people’s ability to resist subsequent temptations. Existing research has shown that when chronic dieters’ self-regulatory capacity is challenged by prior exertion of effort, they demonstrate disinhibited eating and altered patterns of brain activity when exposed to food cues. However, the relationship between brain activity during self-control exertion and subsequent food cue exposure remains unclear. In the present study, we investigated whether individual differences in recruitment of cognitive control regions during a difficult response inhibition task are associated with a failure to regulate neural responses to rewarding food cues in a subsequent task in a cohort of 27 female dieters. During self-control exertion, participants recruited regions commonly associated with inhibitory control, including dorsolateral prefrontal cortex (DLPFC). Those dieters with higher DLPFC activity during the initial self-control task showed an altered balance of food cue elicited activity in regions associated with reward and self-control, namely: greater reward-related activity and less recruitment of the frontoparietal control network. These findings suggest that some dieters may be more susceptible to the effects of self-control exertion than others and, whether due to limited capacity or changes in motivation, these dieters subsequently fail to engage control regions that may otherwise modulate activity associated with craving and reward.

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Skill learning strengthens cortical representations of motor sequences

eLife ◽

10.7554/elife.00801 ◽

2013 ◽

Vol 2 ◽

Cited By ~ 92

Author(s):

Tobias Wiestler ◽

Jörn Diedrichsen

Keyword(s):

Skill Acquisition ◽

Motor Skill ◽

Brain Activity ◽

Activity Patterns ◽

Skill Learning ◽

Multivariate Pattern Analysis ◽

Motor Skill Acquisition ◽

Average Activity ◽

Multivariate Pattern ◽

Cortical Representations

Motor-skill learning can be accompanied by both increases and decreases in brain activity. Increases may indicate neural recruitment, while decreases may imply that a region became unimportant or developed a more efficient representation of the skill. These overlapping mechanisms make interpreting learning-related changes of spatially averaged activity difficult. Here we show that motor-skill acquisition is associated with the emergence of highly distinguishable activity patterns for trained movement sequences, in the absence of average activity increases. During functional magnetic resonance imaging, participants produced either four trained or four untrained finger sequences. Using multivariate pattern analysis, both untrained and trained sequences could be discriminated in primary and secondary motor areas. However, trained sequences were classified more reliably, especially in the supplementary motor area. Our results indicate skill learning leads to the development of specialized neuronal circuits, which allow the execution of fast and accurate sequential movements without average increases in brain activity.

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Localizing Brain Function Based on Full Multivariate Activity Patterns: The Case of Visual Perception and Emotion Decoding

10.1101/2021.04.04.438425 ◽

2021 ◽

Author(s):

Isaac David ◽

Fernando A Barrios

Keyword(s):

Brain Activity ◽

Activity Patterns ◽

Linear Method ◽

Functional Brain Imaging ◽

Psychological State ◽

Affective States ◽

Psychological States ◽

Brain Functions ◽

Human Participants ◽

Multivariate Pattern

It's now common to approach questions about information representation in the brain using multivariate statistics and machine learning methods. What is less recognized is that, in the process, the capacity for data-driven discovery and functional localization has diminished. This is because multivariate pattern analysis (MVPA) studies tend to restrict themselves to regions of interest and severely-filtered data, and sound parameter mapping inference is lacking. Here, reproducible evidence is presented that a high-dimensional, brain-wide multivariate linear method can better detect and characterize the occurrence of visual and socio-affective states in a task-oriented functional magnetic resonance imaging (fMRI) experiment; in comparison to the classical localizationist correlation analysis. Classification models for a group of human participants and existing rigorous cluster inference methods are used to construct group anatomical-statistical parametric maps, which correspond to the most likely neural correlates of each psychological state. This led to the discovery of a multidimensional pattern of brain activity which reliably encodes for the perception of happiness in the visual cortex, cerebellum and some limbic areas. We failed to find similar evidence for sadness and anger. Anatomical consistency of discriminating features across subjects and contrasts despite of the high number of dimensions, as well as agreement with the wider literature, suggest MVPA is a viable tool for full-brain functional neuroanatomical mapping and not just prediction of psychological states. The present work paves the way for future functional brain imaging studies to provide a complementary picture of brain functions (such as emotion), according to their macroscale dynamics.

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Accurate sex classification from neural responses to sexual stimuli

10.1101/2022.01.10.473972 ◽

2022 ◽

Author(s):

Vesa Juhani Putkinen ◽

Sanaz Nazari-Farsani ◽

Tomi Karjalainen ◽

Severi Santavirta ◽

Matthew Hudson ◽

...

Keyword(s):

Sex Differences ◽

Brain Activity ◽

Activity Patterns ◽

Men And Women ◽

Sexual Stimuli ◽

Dorsal Attention Network ◽

Film Clips ◽

Attentional Engagement ◽

Visual Sexual Stimuli ◽

Multivariate Pattern

Sex differences in brain activity evoked by sexual stimuli remain elusive despite robust evidence for stronger enjoyment of and interest towards sexual stimuli in men than in women. To test whether visual sexual stimuli evoke different brain activity patterns in men and women, we measured haemodynamic brain activity induced by visual sexual stimuli in two experiments in 91 subjects (46 males). In one experiment, the subjects viewed sexual and non-sexual film clips and dynamic annotations for nudity in the clips was used to predict their hemodynamic activity. In the second experiment, the subjects viewed sexual and non-sexual pictures in an event-related design. Males showed stronger activation than females in the visual and prefrontal cortices and dorsal attention network in both experiments. Furthermore, using multivariate pattern classification we could accurately predict the sex of the subject on the basis of the brain activity elicited by the sexual stimuli. The classification generalized across the experiments indicating that the sex differences were consistent across the experiments. Eye tracking data obtained from an independent sample of subjects (N = 110) showed that men looked longer than women at the chest area of the nude female actors in the film clips. These results indicate that visual sexual stimuli evoke discernible brain activity patterns in men and women which may reflect stronger attentional engagement with sexual stimuli in men than women.

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Comparing two neurocognitive models of self-control during dietary decisions

Social Cognitive and Affective Neuroscience ◽

10.1093/scan/nsz068 ◽

2019 ◽

Vol 14 (9) ◽

pp. 957-966 ◽

Cited By ~ 3

Author(s):

Danielle Cosme ◽

Rita M Ludwig ◽

Elliot T Berkman

Keyword(s):

Decision Making ◽

Prefrontal Cortex ◽

Process Model ◽

Model Comparison ◽

Choice Model ◽

Well Being ◽

Brain Regions ◽

Self Control ◽

Dual Process ◽

Dorsolateral Prefrontal

Abstract Self-control is the process of favoring abstract, distal goals over concrete, proximal goals during decision-making and is an important factor in health and well-being. We directly compare two prominent neurocognitive models of human self-control with the goal of identifying which, if either, best describes behavioral and neural data of dietary decisions in a large sample of overweight and obese adults motivated to eat more healthfully. We extracted trial-by-trial estimates of neural activity during incentive-compatible choice from three brain regions implicated in self-control, dorsolateral prefrontal cortex, ventral striatum and ventromedial prefrontal cortex and assessed evidence for the dual-process and value-based choice models of self-control using multilevel modeling. Model comparison tests revealed that the value-based choice model outperformed the dual-process model and best fit the observed data. These results advance scientific knowledge of the neurobiological mechanisms underlying self-control-relevant decision-making and are consistent with a value-based choice model of self-control.

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Comparing two neurocognitive models of self-control during dietary decisions

10.31234/osf.io/bd7u3 ◽

2019 ◽

Author(s):

Danielle Cosme ◽

Rita M. Ludwig ◽

Elliot Berkman

Keyword(s):

Decision Making ◽

Prefrontal Cortex ◽

Process Model ◽

Model Comparison ◽

Choice Model ◽

Well Being ◽

Brain Regions ◽

Self Control ◽

Dual Process ◽

Dorsolateral Prefrontal

Self-control is the process of favoring abstract, distal goals over concrete, proximal goals during decision making, and is an important factor in health and well-being. We directly compare two prominent neurocognitive models of human self-control with the goal of identifying which, if either, best describes behavioral and neural data of dietary decisions in a large sample of overweight and obese adults motivated to eat more healthfully. We extracted trial-by-trial estimates of neural activity during incentive-compatible choice from three brain regions implicated in self-control, dorsolateral prefrontal cortex, ventral striatum, and ventromedial prefrontal cortex, and assessed evidence for the dual-process and value-based choice models of self-control using multilevel modeling. Model comparison tests revealed that the value-based choice model outperformed the dual-process model, and best fit the observed data. These results advance scientific knowledge of the neurobiological mechanisms underlying self-control relevant decision making and are consistent with a value-based choice model of self-control.

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