scholarly journals A neural link between affective understanding and interpersonal attraction

2016 ◽  
Vol 113 (16) ◽  
pp. E2248-E2257 ◽  
Author(s):  
Silke Anders ◽  
Roos de Jong ◽  
Christian Beck ◽  
John-Dylan Haynes ◽  
Thomas Ethofer
Keyword(s):  
Neural Activity ◽  
Interpersonal Attraction ◽  
Affective State ◽  
Neural Mechanism ◽  
Reward System ◽  
Mental States ◽  
Neural Representation ◽  
Affective Behavior ◽  
Intrinsic Reward ◽  
Social Encounters

Being able to comprehend another person’s intentions and emotions is essential for successful social interaction. However, it is currently unknown whether the human brain possesses a neural mechanism that attracts people to others whose mental states they can easily understand. Here we show that the degree to which a person feels attracted to another person can change while they observe the other’s affective behavior, and that these changes depend on the observer’s confidence in having correctly understood the other’s affective state. At the neural level, changes in interpersonal attraction were predicted by activity in the reward system of the observer’s brain. Importantly, these effects were specific to individual observer–target pairs and could not be explained by a target’s general attractiveness or expressivity. Furthermore, using multivoxel pattern analysis (MVPA), we found that neural activity in the reward system of the observer’s brain varied as a function of how well the target’s affective behavior matched the observer’s neural representation of the underlying affective state: The greater the match, the larger the brain’s intrinsic reward signal. Taken together, these findings provide evidence that reward-related neural activity during social encounters signals how well an individual’s “neural vocabulary” is suited to infer another person’s affective state, and that this intrinsic reward might be a source of changes in interpersonal attraction.

scholarly journals A neurocomputational model for intrinsic reward

2019 ◽  
Author(s):  
Benjamin Chew ◽  
Bastien Blain ◽  
Raymond J Dolan ◽  
Robb B Rutledge
Keyword(s):  
Neural Activity ◽  
Affective State ◽  
Computational Modelling ◽  
Well Being ◽  
Learning Performance ◽  
Extrinsic Rewards ◽  
Intrinsic Rewards ◽  
Intrinsic Reward ◽  
Reward Value ◽  
Affective Dynamics

SUMMARYStandard economic indicators provide an incomplete picture of what we value both as individuals and as a society. Furthermore, canonical macroeconomic measures, such as GDP, do not account for non-market activities (e.g., cooking, childcare) that nevertheless impact well-being. Here, we introduce a computational tool that measures the subjective reward value of experiences (e.g., playing a musical instrument without errors). We go on to validate this tool with neural data, using fMRI to measure neural activity in subjects performing a reinforcement learning task that incorporated periodic ratings of subjective affective state. Learning performance determined level of payment (i.e., extrinsic reward). Crucially, the task also incorporated a skilled performance component (i.e., intrinsic reward) which did not influence payment. Both extrinsic and intrinsic rewards influenced affective dynamics, and their relative influence could be captured in our computational model. Individuals for whom intrinsic rewards had a greater influence on affective state than extrinsic rewards had greater ventromedial prefrontal cortex (vmPFC) activity for intrinsic than extrinsic rewards. Thus, we show that computational modelling of affective dynamics can index the subjective value of intrinsic relative to extrinsic rewards, a ‘computational hedonometer’ that reflects both behavior and neural activity that quantifies the subjective reward value of experience.

scholarly journals Reciprocal control of obesity and anxiety–depressive disorder via a GABA and serotonin neural circuit

2021 ◽  
Author(s):  
Guobin Xia ◽  
Yong Han ◽  
Fantao Meng ◽  
Yanlin He ◽  
Dollada Srisai ◽  
...  
Keyword(s):  
Neural Circuit ◽  
Combined Treatment ◽  
Neural Mechanism ◽  
Mental States ◽  
Genetic Enhancement ◽  
Anxiety And Depression ◽  
Calorie Intake ◽  
Bed Nucleus ◽  
Low Fat Diet ◽  
Melanocortin 4 Receptor

AbstractThe high comorbidity between obesity and mental disorders, such as depression and anxiety, often exacerbates metabolic and neurological symptoms significantly. However, neural mechanisms that underlie reciprocal control of feeding and mental states are largely elusive. Here we report that melanocortin 4 receptor (MC4R) neurons located in the dorsal bed nucleus of the stria terminus (dBNST) engage in the regulation of mentally associated weight gain by receiving GABAergic projections from hypothalamic AgRP neurons onto α5-containing GABAA receptors and serotonergic afferents onto 5-HT3 receptors. Chronic treatment with a high-fat diet (HFD) significantly blunts the hyperexcitability of AgRP neurons in response to not only hunger but also anxiety and depression-like stimuli. Such HFD-mediated desensitization reduces GABAergic outputs from AgRP neurons to downstream MC4RdBNST neurons, resulting in severe mental dysregulation. Genetic enhancement of the GABAAR-α5 or suppression of the 5-HT3R within the MC4RdBNST neurons not only abolishes HFD-induced anxiety and depression but also robustly reduces body weight by suppression of food intake. To gain further translational insights, we revealed that combined treatment of zonisamide (enhancing the GABAAR-α5 signaling) and granisetron (a selective 5-HT3R antagonist) alleviates mental dysfunction and yields a robust reversal of diet-induced obesity by reducing total calorie intake and altering food preference towards a healthy low-fat diet. Our results unveil a neural mechanism for reciprocal control of appetite and mental states, which culminates in a novel zonisamide-granisetron cocktail therapy for potential tackling the psychosis-obesity comorbidity.

scholarly journals Mirror neurons are modulated by grip force and reward expectation in the sensorimotor cortices (S1, M1, PMd, PMv)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Md Moin Uddin Atique ◽  
Joseph Thachil Francis
Keyword(s):  
Neural Activity ◽  
Visual Information ◽  
Mirror Neurons ◽  
Grip Force ◽  
Neural Representation ◽  
Virtual Object ◽  
Time Lags ◽  
Subjective Value ◽  
Machine Interface ◽  
Definition Of

AbstractMirror Neurons (MNs) respond similarly when primates make or observe grasping movements. Recent work indicates that reward expectation influences rostral M1 (rM1) during manual, observational, and Brain Machine Interface (BMI) reaching movements. Previous work showed MNs are modulated by subjective value. Here we expand on the above work utilizing two non-human primates (NHPs), one male Macaca Radiata (NHP S) and one female Macaca Mulatta (NHP P), that were trained to perform a cued reward level isometric grip-force task, where the NHPs had to apply visually cued grip-force to move and transport a virtual object. We found a population of (S1 area 1–2, rM1, PMd, PMv) units that significantly represented grip-force during manual and observational trials. We found the neural representation of visually cued force was similar during observational trials and manual trials for the same units; however, the representation was weaker during observational trials. Comparing changes in neural time lags between manual and observational tasks indicated that a subpopulation fit the standard MN definition of observational neural activity lagging the visual information. Neural activity in (S1 areas 1–2, rM1, PMd, PMv) significantly represented force and reward expectation. In summary, we present results indicating that sensorimotor cortices have MNs for visually cued force and value.

scholarly journals Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics

2017 ◽  
Vol 24 (3) ◽  
pp. 277-293 ◽  
Author(s):  
Selen Atasoy ◽  
Gustavo Deco ◽  
Morten L. Kringelbach ◽  
Joel Pearson
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Activity Patterns ◽  
Structural Connectivity ◽  
Building Blocks ◽  
Mental States ◽  
Brain Dynamics ◽  
Space And Time ◽  
Wide Range ◽  
The Brain

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at “rest.” Here, we introduce the concept of harmonic brain modes—fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

scholarly journals METHODOLOGICAL APPROACHES TO THE STUDY OF THE IMPLICIT MIND THEORY AT PEOPLE DEPENDENT ON PSYCHOACTIVE SUBSTANCES

2021 ◽  
Vol 7 (2) ◽  
pp. 70-78
Author(s):  
Oleksandr Telcharov ◽  
Keyword(s):  
Research Methods ◽  
Affective State ◽  
Mental States ◽  
Structured Interview ◽  
Psychoactive Substances ◽  
Scientific Psychology ◽  
Main Research ◽  
Advantages And Disadvantages ◽  
Age Related ◽  
Mind Theory

The article presents the psychological analysis of the implicit mind theory and its research methods. The main problems of empirical research in psychology are briefly described. The main problems of research of the mind theory are highlighted; and the status of this phenomenon’s in scientific psychology is defined. The implicit mind theory is defined as a psychological quality expressed in the ability to explain and attribute mental states – beliefs, desires, emotions, knowledge, etc. – to themselves and others; as well as understanding that others have different beliefs, desires, intentions, and attitudes. Current difficulties in the research on the implicit mind theory are described. Age-related features of formation of the implicit mind theory are depicted. The latest scientific studies on the implicit mind theory are highlighted. Biological correlates of the theory are shown. It is also described that in the case of an alcohol addiction, certain brain areas that are known to be neurological correlates of the implicit mind theory are damaged. The main research methods, which are separated into three groups, are highlighted. The first group includes methods that study the implicit mind theory using behavioural experiment with special tasks. The second group includes methods that use semi-structured interview. The third group includes methods where respondents are asked to identify an emotion or an affective state of another person based on the visual stimuli (photo, picture etc.).The main methods of research of this psychological phenomenon, features, procedure, advantages, and disadvantages are described in detail. The most appropriate methods to examine addicts’ implicit mind theory are proposed. The procedure of investigation and psychological assessment of the implicit mind theory for people dependent on psychoactive substances is offered.

scholarly journals Robust and distributed neural representation of action values

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Eun Ju Shin ◽  
Yunsil Jang ◽  
Soyoun Kim ◽  
Hoseok Kim ◽  
Xinying Cai ◽  
...  
Keyword(s):  
Neural Activity ◽  
Statistical Tests ◽  
Brain Structures ◽  
Surrogate Data ◽  
Neural Representation ◽  
Decision Variables ◽  
Multiple Regions ◽  
Serial Correlations ◽  
Action Value ◽  
The Brain

Studies in rats, monkeys, and humans have found action-value signals in multiple regions of the brain. These findings suggest that action-value signals encoded in these brain structures bias choices toward higher expected rewards. However, previous estimates of action-value signals might have been inflated by serial correlations in neural activity and also by activity related to other decision variables. Here, we applied several statistical tests based on permutation and surrogate data to analyze neural activity recorded from the striatum, frontal cortex, and hippocampus. The results show that previously identified action-value signals in these brain areas cannot be entirely accounted for by concurrent serial correlations in neural activity and action value. We also found that neural activity related to action value is intermixed with signals related to other decision variables. Our findings provide strong evidence for broadly distributed neural signals related to action value throughout the brain.

100 Years of Benham's Top in Colour Science

Perception ◽  
1995 ◽  
Vol 24 (6) ◽  
pp. 695-717 ◽  
Author(s):  
Christoph von Campenhausen ◽  
Jürgen Schramme
Keyword(s):  
Visual Cortex ◽  
Neural Activity ◽  
Medical Diagnosis ◽  
Side Effect ◽  
Neural Mechanism ◽  
Lateral Interactions ◽  
Colour Constancy ◽  
Binocular Fusion ◽  
Normal Colour ◽  
Phase Sensitive

For 100 years Benham's top has been a popular device demonstrating pattern-induced flicker colours (PIFCs). Results of early and recent investigations on PIFCs are reported and show that the phenomenon originates in phase-sensitive lateral interactions of modulated neural activity in the retina followed by additional spatial interactions in the visual cortex behind the locus of binocular fusion. Colour matches with normal colour stimuli indicate that S/(M + L) opponent neurons are involved. Dichromats do not find matching stimuli for all PIFCs. PIFCs may become useful in medical diagnosis. The phenomenon is interpreted as a side effect of a neural mechanism providing colour constancy under normal stimulus conditions.

Neural Representation of the Luminance and Brightness of a Uniform Surface in the Macaque Primary Visual Cortex

2001 ◽  
Vol 86 (5) ◽  
pp. 2559-2570 ◽  
Author(s):  
Masaharu Kinoshita ◽  
Hidehiko Komatsu
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Neural Activity ◽  
Dynamic Range ◽  
Neural Representation ◽  
Homogeneous Surface ◽  
V1 Neurons ◽  
Classical Receptive Field ◽  
Multiple Unit

The perceived brightness of a surface is determined not only by the luminance of the surface (local information), but also by the luminance of its surround (global information). To better understand the neural representation of surface brightness, we investigated the effects of local and global luminance on the activity of neurons in the primary visual cortex (V1) of awake macaque monkeys. Single- and multiple-unit recordings were made from V1 while the monkeys were performing a visual fixation task. The classical receptive field of each neuron was identified as a region responding to a spot stimulus. Neural responses were assessed using homogeneous surfaces at least three times as large as the receptive field as stimuli. We first examined the sensitivity of neurons to variation in local surface luminance, while the luminance of the surround was held constant. The activity of a large majority of surface-responsive neurons (106/115) varied monotonically with changes in surface luminance; in some the dynamic range was over 3 log units. This monotonic relation between surface luminance and neural activity was more evident later in the stimulus period than early on. The effect of the global luminance on neural activity was then assessed in 81 of the surface-responsive neurons by varying the luminance of the surround while holding the luminance of the surface constant. The activity of one group of neurons (25/81) was unaffected by the luminance of the surround; these neurons appear to encode the physical luminance of a surface covering the receptive field. The responses of the other neurons were affected by the luminance of the surround. The effects of the luminances of the surface and the surround on the activities of 26 of these neurons were in the same direction (either increased or decreased), while the effects on the remaining 25 neurons were in opposite directions. The activities of the latter group of neurons seemed to parallel the perceived brightness of the surface, whereas the former seemed to encode the level of illumination. There were differences across different types of neurons with regard to the layer distribution. These findings indicate that global luminance information significantly modulates the activity of surface-responsive V1 neurons and that not only physical luminance, but also perceived brightness, of a homogeneous surface is represented in V1.

Sensory discrimination: decision process

1980 ◽  
Vol 43 (6) ◽  
pp. 1771-1792 ◽  
Author(s):  
K. O. Johnson
Keyword(s):  
Experimental Design ◽  
Neural Activity ◽  
Decision Process ◽  
Experimental Studies ◽  
Experimental Designs ◽  
Neural Representation ◽  
Mathematical Representation ◽  
Sensory Discrimination ◽  
Sample Data ◽  
Sensory Processes

1. This paper and a following paper deal with problems, such as the following, that arise in experimental studies of the neural mechanisms underlying sensory discrimination: What measures of neural activity are relevant in such a study? How can sample data from the responses of single neurons be combined to represent the information relayed by a population of neurons? How can neural data be compared with results from psychophysical studies? What assumptions are implicit in any such comparison? What are the implications of assumptions that neurons respond independently or that they have homogeneous response properties? How can neural codes be assessed in a systematic way? Can psychophysical and neurophysiological observations be combined to infer mechanisms or relationships in the processes underlying discrimination? All of these questions require some theoretical framework before they can be answered. These papers set out such a framework, they deal with most of those questions, and they provide practicable formulas for relating sample data from neurophysiological experiments to behavioral measures derived from psychophysical experiments. 2. The processes that intervene between a relatively peripheral array of neural activity and a subject's decision in a discrimination task are split into two sections: a) the ascending sensory processes that provide the final patterns of neural activity on which discrimination is based, and b) a process that yields decisions of the type required by the experimental design used in the psychophysical study. The approach is to develop a theory of the decision process in this paper, and then to expand it to incorporate the ascending processes in the following paper. 3. The decision theory deals with a class of experimental designs in which a subject is required to make a decision about two stimuli S1 and S2 (e.g., S1 is larger than S2, S2 is the same as S1, S2 was the modified stimulus, and so on). A mathematical representation for experimental designs of this type is developed. 4. The decision process is analyzed in two forms: a) a multivariate form in which the discrimination decision results directly from multidimensional neural representation of the two stimuli, and b) a vivariate form in which the final representation of each stimulus is a unidimensional variable. Conditions required for equivalence of these formulations are examined. 5. The theory includes as explicit variables a) the experimental design, b) the subject's discrimination strategy, c) bias, d) memory variance, e) bias variance, f) variance in the final neural representations of the stimuli, and g) their functional dependence on the stimuli that they represent. 6. Formulas are developed for the expected values of commonly used psychophysical measures such as the classical psychometric function, receiver operating characteristic (ROC) functions, discriminatory separation index (d'), and the difference limen. 7. Optimum discrimination behavior is analyzed.

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