scholarly journals Neural Representations of the Committed Romantic Partner in the Nucleus Accumbens

2021 ◽  
pp. 095679762110218
Author(s):  
Ryuhei Ueda ◽  
Nobuhito Abe
Keyword(s):  
Nucleus Accumbens ◽  
Neural Activity ◽  
Romantic Relationship ◽  
Pattern Analysis ◽  
Activity Patterns ◽  
Neural Mechanism ◽  
Romantic Partners ◽  
Multivoxel Pattern Analysis ◽  
Neural Representations ◽  
The Social

Having an intimate romantic relationship is an important aspect of life. Dopamine-rich reward regions, including the nucleus accumbens (NAcc), have been identified as neural correlates for both emotional bonding with the partner and interest in unfamiliar attractive nonpartners. Here, we aimed to disentangle the overlapping functions of the NAcc using multivoxel pattern analysis, which can decode the cognitive processes encoded in particular neural activity. During functional MRI scanning, 46 romantically involved men performed the social-incentive-delay task, in which a successful response resulted in the presentation of a dynamic and positive facial expression from their partner and unfamiliar women. Multivoxel pattern analysis revealed that the spatial patterns of NAcc activity could successfully discriminate between romantic partners and unfamiliar women during the period in which participants anticipated the target presentation. We speculate that neural activity patterns within the NAcc represent the relationship partner, which might be a key neural mechanism for committed romantic relationships.

scholarly journals Neural Representations Behind ‘Social Norm’ Inferences In Humans

2017 ◽  
Author(s):  
Felipe Pegado ◽  
Michelle H.A. Hendriks ◽  
Steffie Amelynck ◽  
Nicky Daniels ◽  
Jessica Bulthé ◽  
...  
Keyword(s):  
Social Norm ◽  
Pattern Analysis ◽  
Interindividual Variability ◽  
Brain Regions ◽  
Social Reasoning ◽  
Response Patterns ◽  
Conflict Monitoring ◽  
Multivoxel Pattern Analysis ◽  
Neural Representations ◽  
The Social

AbstractHumans are highly skilled in social reasoning, e.g., inferring thoughts of others. This mentalizing ability systematically recruits brain regions such as Temporo-Parietal Junction (TPJ), Precuneus (PC) and medial Prefrontal Cortex (mPFC). Further, posterior mPFC is associated with allocentric mentalizing and conflict monitoring while anterior mPFC is associated with self-related mentalizing. Here we extend this work to how we reason not just about what one person thinks but about the abstract shared social norm. We apply functional magnetic resonance imaging to investigate neural representations while participants judge the social congruency between emotional auditory in relation to visual scenes according to how ‘most people’ would perceive it. Behaviorally, judging according to a social norm increased the similarity of response patterns among participants. Multivoxel pattern analysis revealed that social congruency information was not represented in visual and auditory areas, but was clear in most parts of the mentalizing network: TPJ, PC and posterior (but not anterior) mPFC. Furthermore, interindividual variability in anterior mPFC representations was inversely related to the behavioral ability to adjust to the social norm. Our results suggest that social norm inferencing is associated with a distributed and partially individually specific representation of social congruency in the mentalizing network.

scholarly journals Exploring the role of expectations and stimulus relevance on stimulus-specific neural representations and conscious report

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Erik L Meijs ◽  
Pim Mostert ◽  
Heleen A Slagter ◽  
Floris P de Lange ◽  
Simon van Gaal
Keyword(s):  
Attentional Blink ◽  
Neural Activity ◽  
Subjective Experience ◽  
Activity Patterns ◽  
Neural Mechanisms ◽  
Top Down ◽  
Neural Representations ◽  
Dependent Signal ◽  
Task Irrelevant

Abstract Subjective experience can be influenced by top-down factors, such as expectations and stimulus relevance. Recently, it has been shown that expectations can enhance the likelihood that a stimulus is consciously reported, but the neural mechanisms supporting this enhancement are still unclear. We manipulated stimulus expectations within the attentional blink (AB) paradigm using letters and combined visual psychophysics with magnetoencephalographic (MEG) recordings to investigate whether prior expectations may enhance conscious access by sharpening stimulus-specific neural representations. We further explored how stimulus-specific neural activity patterns are affected by the factors expectation, stimulus relevance and conscious report. First, we show that valid expectations about the identity of an upcoming stimulus increase the likelihood that it is consciously reported. Second, using a series of multivariate decoding analyses, we show that the identity of letters presented in and out of the AB can be reliably decoded from MEG data. Third, we show that early sensory stimulus-specific neural representations are similar for reported and missed target letters in the AB task (active report required) and an oddball task in which the letter was clearly presented but its identity was task-irrelevant. However, later sustained and stable stimulus-specific representations were uniquely observed when target letters were consciously reported (decision-dependent signal). Fourth, we show that global pre-stimulus neural activity biased perceptual decisions for a ‘seen’ response. Fifth and last, no evidence was obtained for the sharpening of sensory representations by top-down expectations. We discuss these findings in light of emerging models of perception and conscious report highlighting the role of expectations and stimulus relevance.

scholarly journals Multivoxel Pattern Analysis for fMRI Data: A Review

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Abdelhak Mahmoudi ◽  
Sylvain Takerkart ◽  
Fakhita Regragui ◽  
Driss Boussaoud ◽  
Andrea Brovelli
Keyword(s):  
Neural Activity ◽  
Time Course ◽  
Pattern Analysis ◽  
Reference Model ◽  
Performance Estimation ◽  
Support Vector ◽  
Brain Areas ◽  
Experimental Conditions ◽  
Multivoxel Pattern Analysis ◽  
Brain Functions

Functional magnetic resonance imaging (fMRI) exploits blood-oxygen-level-dependent (BOLD) contrasts to map neural activity associated with a variety of brain functions including sensory processing, motor control, and cognitive and emotional functions. The general linear model (GLM) approach is used to reveal task-related brain areas by searching for linear correlations between the fMRI time course and a reference model. One of the limitations of the GLM approach is the assumption that the covariance across neighbouring voxels is not informative about the cognitive function under examination. Multivoxel pattern analysis (MVPA) represents a promising technique that is currently exploited to investigate the information contained in distributed patterns of neural activity to infer the functional role of brain areas and networks. MVPA is considered as a supervised classification problem where a classifier attempts to capture the relationships between spatial pattern of fMRI activity and experimental conditions. In this paper , we review MVPA and describe the mathematical basis of the classification algorithms used for decoding fMRI signals, such as support vector machines (SVMs). In addition, we describe the workflow of processing steps required for MVPA such as feature selection, dimensionality reduction, cross-validation, and classifier performance estimation based on receiver operating characteristic (ROC) curves.

scholarly journals Temporo-parietal cortex involved in modeling one’s own and others’ attention

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Arvid Guterstam ◽  
Branden J Bio ◽  
Andrew I Wilterson ◽  
Michael Graziano
Keyword(s):  
Theory Of Mind ◽  
Pattern Analysis ◽  
Brain Activity ◽  
Activity Patterns ◽  
Exogenous Attention ◽  
Attentional State ◽  
Brain Areas ◽  
Multivoxel Pattern Analysis ◽  
Directing Attention ◽  
The Brain

In a traditional view, in social cognition, attention is equated with gaze and people track other people’s attention by tracking their gaze. Here, we used fMRI to test whether the brain represents attention in a richer manner. People read stories describing an agent (either oneself or someone else) directing attention to an object in one of two ways: either internally directed (endogenous) or externally induced (exogenous). We used multivoxel pattern analysis to examine how brain areas within the theory-of-mind network encoded attention type and agent type. Brain activity patterns in the left temporo-parietal junction (TPJ) showed significant decoding of information about endogenous versus exogenous attention. The left TPJ, left superior temporal sulcus (STS), precuneus, and medial prefrontal cortex (MPFC) significantly decoded agent type (self versus other). These findings show that the brain constructs a rich model of one’s own and others’ attentional state, possibly aiding theory of mind.

scholarly journals Decoding the Brain: Neural Representation and the Limits of Multivariate Pattern Analysis in Cognitive Neuroscience

2017 ◽  
Author(s):  
J. Brendan Ritchie ◽  
David Michael Kaplan ◽  
Colin Klein
Keyword(s):  
Cognitive Neuroscience ◽  
Strong Evidence ◽  
Neural Activity ◽  
Pattern Analysis ◽  
Neural Representation ◽  
Neural Decoding ◽  
Multivariate Pattern Analysis ◽  
Neural Representations ◽  
Multivariate Pattern ◽  
The Brain

AbstractSince its introduction, multivariate pattern analysis (MVPA), or “neural decoding”, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the Decoder’s Dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the Dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the Dictum, arguing that it is false: decodability is a poor guide for revealing the content of neural representations. However, we also suggest how the Dictum can be improved on, in order to better justify inferences about neural representation using MVPA.

scholarly journals Temporo-Parietal Cortex Involved in Modeling One’s Own and Others’ Attention

2020 ◽  
Author(s):  
Arvid Guterstam ◽  
Branden J Bio ◽  
Andrew I Wilterson ◽  
Michael SA Graziano
Keyword(s):  
Theory Of Mind ◽  
Pattern Analysis ◽  
Brain Activity ◽  
Activity Patterns ◽  
Exogenous Attention ◽  
Attentional State ◽  
Brain Areas ◽  
Multivoxel Pattern Analysis ◽  
Directing Attention ◽  
The Brain

AbstractIn a traditional view, in social cognition, attention is equated with gaze and people track attention by tracking other people’s gaze. Here we used fMRI to test whether the brain represents attention in a richer manner. People read stories describing an agent (either oneself or someone else) directing attention to an object in one of two ways: either internally directed (endogenous) or externally induced (exogenous). We used multivoxel pattern analysis to examine how brain areas within the theory-of-mind network encoded attention type and agent type. Brain activity patterns in the left temporo-parietal junction (TPJ) showed significant decoding of information about endogenous versus exogenous attention. The left TPJ, left superior temporal sulcus (STS), precuneus, and medial prefrontal cortex (MPFC) significantly decoded agent type (self versus other). These findings show that the brain constructs a rich model of one’s own and others’ attentional state, possibly aiding theory of mind.Impact statementThis study used fMRI to show that the human brain encodes other people’s attention in enough richness to distinguish whether that attention was directed exogenously (stimulus-driven) or endogenously (internally driven).

scholarly journals Action Observation Network activity related to object-directed and socially-directed actions in Adolescents

2020 ◽  
Author(s):  
Mathieu Lesourd ◽  
Alia Afyouni ◽  
Franziska Geringswald ◽  
Fabien Cignetti ◽  
Lisa Raoul ◽  
...  
Keyword(s):  
Human Brain ◽  
Pattern Analysis ◽  
Action Observation ◽  
Activity Patterns ◽  
Two Dimensions ◽  
Social Dimension ◽  
Network Activity ◽  
Action Observation Network ◽  
Observation Network ◽  
The Social

AbstractThe Action Observation Network (AON) encompasses brain areas consistently engaged when we observe other’s actions. Although the core nodes of the AON are present from childhood, it is not known to what extent they are sensitive to different action features during development. As social cognitive abilities continue to mature during adolescence, the AON response to socially-oriented actions, but not to object-related actions, may differ in adolescents and adults. To test this hypothesis, we scanned with functional magnetic resonance imaging (fMRI) 28 typically-developing teenagers and 25 adults while they passively watched videos of hand actions varying along two dimensions: sociality (i.e. directed towards another person or not) and transitivity (i.e. involving an object or not). We found that observing actions recruited the same fronto-parietal and occipito-temporal regions in adults and adolescents. The modulation of voxelwise activity by the social or transitive nature of the action was similar in both groups of participants. Multivariate pattern analysis, however, revealed that the accuracy in decoding the social dimension from the brain activity patterns, increased with age in lateral occipital and parietal regions, known to be involved in semantic representations of actions, as well as in posterior superior temporal sulcus, a region commonly associated with perception of high level features necessary for social perception. Change in decoding the transitive dimension was observed only in the latter region. These findings indicate that the representation of others’ actions, and in particular their social dimensions, in the adolescent AON is still not as robust as in adults.Significance statementThe activity of the action observation network in the human brain is modulated according to the purpose of the observed action, in particular the extent to which it involves interaction with an object or another person. How this conceptual representation of actions is implemented during development is largely unknown. Here, using multivoxel pattern analysis of fMRI data, we discovered that, while the action observation network is in place in adolescence, the fine-grain organization of its posterior regions is less robust than in adults to decode the social or transitive dimensions of an action. This finding highlights the late maturation of social processing in the human brain.

scholarly journals Differential neural activity patterns mediate learning across contexts in a social cichlid fish

2021 ◽  
Author(s):  
Mariana Rodriguez-Santiago ◽  
Alex L Jordan ◽  
Hans A Hofmann
Keyword(s):  
Social Context ◽  
Neural Activity ◽  
Discrimination Task ◽  
Basolateral Amygdala ◽  
Activity Patterns ◽  
Cichlid Fish ◽  
Brain Regions ◽  
Social Contexts ◽  
Early Gene ◽  
The Social

Learning and decision-making are greatly influenced by the social context surrounding individuals. When navigating a complex social world, individuals must quickly ascertain where to gain important resources and which group members are useful sources of such information. Such dynamic behavioral processes require neural mechanisms that are flexible across contexts. Here we examined how the social context influences the learning response during a visual cue discrimination task and the neural activity patterns that underlie acquisition of this novel information. Using the cichlid fish, Astatotilapia burtoni, we show that learning of the task is faster in social groups than in a non-social context. We quantified the expression of Fos, an immediate-early gene, across candidate brain regions known to play a role in social behavior and learning, such as the putative teleost homologues of the mammalian hippocampus, basolateral amygdala, and medial amygdala/BNST complex. We found that neural activity patterns differ between social and non-social contexts. Our results suggest that while the same brain regions may be involved in the learning of a discrimination task independent of social context, activity in each region encodes specific aspects of the task based on context.

scholarly journals Metacognition facilitates the exploitation of unconscious brain states

2019 ◽  
Author(s):  
Aurelio Cortese ◽  
Hakwan Lau ◽  
Mitsuo Kawato
Keyword(s):  
Reinforcement Learning ◽  
Neural Activity ◽  
Pattern Analysis ◽  
Brain Activity ◽  
High Dimensional ◽  
Multivoxel Pattern Analysis ◽  
Brain States ◽  
Optimal Action ◽  
The Brain ◽  
Do So

AbstractCan humans be trained to make strategic use of unconscious representations in their own brains? We investigated how one can derive reward-maximizing choices from latent high-dimensional information represented stochastically in neural activity. In a novel decision-making task, reinforcement learning contingencies were defined in real-time by fMRI multivoxel pattern analysis; optimal action policies thereby depended on multidimensional brain activity that took place below the threshold of consciousness. We found that subjects could solve the task, when their reinforcement learning processes were boosted by implicit metacognition to estimate the relevant brain states. With these results we identified a frontal-striatal mechanism by which the brain can untangle tasks of great dimensionality, and can do so much more flexibly than current artificial intelligence.

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