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

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.

scholarly journals High-level cognition during story listening is reflected in high-order dynamic correlations in neural activity patterns

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lucy L. W. Owen ◽  
Thomas H. Chang ◽  
Jeremy R. Manning
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Activity Patterns ◽  
Dynamic Network ◽  
Brain Structures ◽  
High Order ◽  
Dynamic Correlations ◽  
Neuroimaging Data ◽  
Human Participants ◽  
High Level

AbstractOur thoughts arise from coordinated patterns of interactions between brain structures that change with our ongoing experiences. High-order dynamic correlations in neural activity patterns reflect different subgraphs of the brain’s functional connectome that display homologous lower-level dynamic correlations. Here we test the hypothesis that high-level cognition is reflected in high-order dynamic correlations in brain activity patterns. We develop an approach to estimating high-order dynamic correlations in timeseries data, and we apply the approach to neuroimaging data collected as human participants either listen to a ten-minute story or listen to a temporally scrambled version of the story. We train across-participant pattern classifiers to decode (in held-out data) when in the session each neural activity snapshot was collected. We find that classifiers trained to decode from high-order dynamic correlations yield the best performance on data collected as participants listened to the (unscrambled) story. By contrast, classifiers trained to decode data from scrambled versions of the story yielded the best performance when they were trained using first-order dynamic correlations or non-correlational activity patterns. We suggest that as our thoughts become more complex, they are reflected in higher-order patterns of dynamic network interactions throughout the brain.

scholarly journals Spatiotemporally Resolved Multivariate Pattern Analysis for M/EEG

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.

scholarly journals Estudio de los correlatos neurales de la percepción emocional por análisis de patrones en multitud de voxeles

2021 ◽  
Author(s):  
Isaac David
Keyword(s):  
Brain Activity ◽  
Univariate Analysis ◽  
Parahippocampal Gyrus ◽  
Neural Basis ◽  
Basic Emotions ◽  
Negative Valence ◽  
Brain Functions ◽  
Data Points ◽  
Emotional System ◽  
Multivariate Pattern

Emotion and its perception are fundamental psychological faculties for the survival of animals and social interaction. This is recognized by the emergence of whole areas of neuroscience devoted to understanding its neural basis. Although the basic components of such emotional system have been identified, the segregation of the milieu of affective experiences into different patterns of brain signals remains poorly understood. Recent functional imaging studies have implicated simultaneous distributed activity as a better correlate of emotional state than its univariate counterpart; however, those attempts have still restricted themselves to regions of interest and severely-filtered data. In this work we tested whether the visual perception of three basic emotions can be decoded from full brain activity using multivariate pattern classification, while keeping localizationist and encoding assumptions at a minimum. Beyond stimuli prediction, we also provide proof of-concept anatomical mapping and discovery of relevant structures.To this end, we ran a face perception experiment on a sample of 16 neurotypical participants while recording their brain activity using fMRI. Per-subject SVM classifiers were trained on the fMRI data, so that they could recognize the emotion class brains were presented with. Results were cross-validated and compared against performance by chance using resampling techniques; and the whole of our reproducible pipeline was further validated using more trivial contrasts embedded within the main emotional task. Thorough assessment of behavioral data points towards the validity of our task.Results show a robust and distributed representation of (perceived) happiness in humans, but not of negative-valence anger and sadness; contrary to the more optimistic (though less diligent) existing studies. Overall, our approach proved more sensitive and anatomically specific than the classical mass-univariate analysis, amidst high-dimensionality concerns. Group inference of SVM parameters suggests the defining information-bearing pattern emanates from known structures in the ventral visual pathway and emotion-related areas. Namely: the primary visual cortex (V1) and surroundings, the middle collateral sulcus and parahippocampal gyrus (mCS, mPHG), the amygdala, the medial prefrontal cortex (mPFC) and the anterior cerebellum around the vermis; all of them in bilateral fashion. Our work paves the way for further multivariate studies to provide a complementary picture of emotions (and other brain functions), according to its macroscale dynamics.

scholarly journals Contextual expectations shape cortical reinstatement of sensory representations

2021 ◽  
Author(s):  
Alex Clarke ◽  
Jordan E Crivelli-Decker ◽  
Charan Ranganath
Keyword(s):  
Visual Cortex ◽  
Activity Patterns ◽  
Medial Cortex ◽  
Pattern Similarity ◽  
Early Visual Cortex ◽  
Animal Images ◽  
Human Participants ◽  
Visual Cortical ◽  
Multivariate Pattern ◽  
Perceptual Systems

When making a turn at a familiar intersection, we know what items and landmarks will come into view. These perceptual expectations, or predictions, come from our knowledge of the context, however it is unclear how memory and perceptual systems interact to support the prediction and reactivation of sensory details in cortex. To address this, human participants learned the spatial layout of animals positioned in a cross maze. During fMRI, participants navigated between animals to reach a target, and in the process saw a predictable sequence of five animal images. Critically, to isolate activity patterns related to item predictions, rather than bottom-up inputs, one quarter of trials ended early, with a blank screen presented instead. Using multivariate pattern similarity analysis, we reveal that activity patterns in early visual cortex, posterior medial regions, and the posterior hippocampus showed greater similarity when seeing the same item compared to different items. Further, item effects in posterior hippocampus were specific to the sequence context. Critically, activity patterns associated with seeing an item in visual cortex and posterior medial cortex, were also related to activity patterns when an item was expected, but omitted, suggesting sequence predictions were reinstated in these regions. Finally, multivariate connectivity showed that patterns in the posterior hippocampus at one position in the sequence were related to patterns in early visual cortex and posterior medial cortex at a later position. Together, our results support the idea that hippocampal representations facilitate sensory processing by modulating visual cortical activity in anticipation of expected items.

scholarly journals Eye-movement reinstatement and neural reactivation during mental imagery

2017 ◽  
Author(s):  
Michael B. Bone ◽  
Marie St-Laurent ◽  
Christa Dang ◽  
Douglas A. McQuiggan ◽  
Jennifer D. Ryan ◽  
...  
Keyword(s):  
Eye Movement ◽  
Mental Imagery ◽  
Brain Activity ◽  
Healthy Human ◽  
Supportive Role ◽  
Constructive Process ◽  
Human Participants ◽  
Multivariate Pattern ◽  
With Memory

AbstractHalf a century ago, Donald Hebb posited that mental imagery is a constructive process that emulates perception. Specifically, Hebb claimed that visual imagery results from the reactivation of neural activity associated with viewing images. He also argued that neural reactivation and imagery benefit from the re-enactment of eye movement patterns that first occurred at viewing (fixation reinstatement). To investigate these claims, we applied multivariate pattern analyses to functional MRI (fMRI) and eye-tracking data collected while healthy human participants repeatedly viewed and visualized complex images. We observed that the specificity of neural reactivation correlated positively with vivid imagery and with memory for stimulus image details. Moreover, neural reactivation correlated positively with fixation reinstatement, meaning that image-specific eye movements accompanied image-specific patterns of brain activity during visualization. These findings support the conception of mental imagery as a simulation of perception, and provide evidence of the supportive role of eye-movement in neural reactivation.

scholarly journals Skill learning strengthens cortical representations of motor sequences

eLife ◽  
2013 ◽  
Vol 2 ◽  
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.

scholarly journals Accurate sex classification from neural responses to sexual stimuli

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.

scholarly journals Trust me if you can – neurophysiological insights on the influence of consumer impulsiveness on trustworthiness evaluations in online settings

2018 ◽  
Vol 52 (1/2) ◽  
pp. 118-146 ◽  
Author(s):  
Marco Hubert ◽  
Mirja Hubert ◽  
Marc Linzmajer ◽  
René Riedl ◽  
Peter Kenning
Keyword(s):  
Decision Making ◽  
Brain Activity ◽  
Activity Patterns ◽  
Dorsal Striatum ◽  
Region Of Interest ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Neural Activation ◽  
Content Type ◽  
Brain Functions

Purpose The purpose of this study is to examine how consumer personality trait impulsiveness influences trustworthiness evaluations of online-offers with different trust-assuring and trust-reducing elements by measuring the brain activity of consumers. Shoppers with high degrees of impulsiveness are referred to as hedonic shoppers, and those with low degrees are referred to as prudent consumers. Design/methodology/approach To investigate the differences between neural processes in the brains of hedonic and prudent shoppers during the trustworthiness evaluation of online-offers, the present study used functional magnetic resonance imaging (fMRI) and region-of-interest analysis to correlate neural activity patterns with behavioral measures of the study participants. Findings Drawing upon literature reviews on the neural correlates of both trust in online settings and consumer impulsiveness and using an experimental design that links behavioral and fMRI data, the study shows that consumer impulsiveness can exert a significant influence on the evaluation of online-offers. With regard to brain activation, both groups (hedonic and prudent shoppers) exhibit similar neural activation tendencies, but differences exist in the magnitude of activation patterns in brain regions that are closely related to trust and impulsiveness such as the dorsal striatum, anterior cingulate, the dorsolateral prefrontal cortex and the insula cortex. Research limitations/implications The data provide evidence that consumers within the hedonic group evaluate online-offers differently with regard to their trustworthiness compared to the prudent group, and that these differences in evaluation are rooted in neural activation differences in the shoppers’ brains. Practical implications Marketers need to be made aware of the fact that neurological insights can be used for market segmentation, because consumers’ decision-making processes help explain behavioral outcomes (here, trustworthiness evaluations of online-offers). In addition, consumers can learn from an advanced understanding of their brain functions during decision-making and their relation to personal traits such as impulsiveness. Originality/value Considering the importance of trust in online shopping, as well as the fact that personality traits such as impulsiveness influence the purchase process to a high degree, this study is the first to systematically investigate the interplay of online trustworthiness perceptions and differences in consumer impulsiveness with neuroscientific methods.

scholarly journals Decoding fairness motivations from multivariate brain activity patterns

2019 ◽  
Vol 14 (11) ◽  
pp. 1197-1207 ◽  
Author(s):  
Sebastian P H Speer ◽  
Maarten A S Boksem
Keyword(s):  
Brain Activity ◽  
Activity Patterns ◽  
Dictator Game ◽  
Well Being ◽  
Self Control ◽  
Selfish Behavior ◽  
Temporoparietal Junction ◽  
Dorsolateral Prefrontal ◽  
Multivariate Pattern ◽  
Decoding Accuracy

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.

scholarly journals Focal neural perturbations reshape low-dimensional trajectories of brain activity supporting cognitive performance

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Kartik K. Iyer ◽  
Kai Hwang ◽  
Luke J. Hearne ◽  
Eli Muller ◽  
Mark D’Esposito ◽  
...  
Keyword(s):  
Working Memory ◽  
Neural Activity ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Memory Performance ◽  
Functional Link ◽  
Low Dimensional Topology ◽  
Brain Functions ◽  
Human Participants ◽  
Low Dimensional

AbstractThe emergence of distributed patterns of neural activity supporting brain functions and behavior can be understood by study of the brain’s low-dimensional topology. Functional neuroimaging demonstrates that brain activity linked to adaptive behavior is constrained to low-dimensional manifolds. In human participants, we tested whether these low-dimensional constraints preserve working memory performance following local neuronal perturbations. We combined multi-session functional magnetic resonance imaging, non-invasive transcranial magnetic stimulation (TMS), and methods translated from the fields of complex systems and computational biology to assess the functional link between changes in local neural activity and the reshaping of task-related low dimensional trajectories of brain activity. We show that specific reconfigurations of low-dimensional trajectories of brain activity sustain effective working memory performance following TMS manipulation of local activity on, but not off, the space traversed by these trajectories. We highlight an association between the multi-scale changes in brain activity underpinning cognitive function.

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