scholarly journals Social evaluations under conflict: negative judgments of conflicting information are easier than positive judgments

2019 ◽  
Vol 14 (7) ◽  
pp. 709-718 ◽  
Author(s):  
Hannah U Nohlen ◽  
Frenk van Harreveld ◽  
William A Cunningham
Keyword(s):  
Selection Process ◽  
Contextual Information ◽  
Decision Time ◽  
Self Report ◽  
Social Judgments ◽  
Conflicting Information ◽  
Active Selection ◽  
Dorsolateral Prefrontal ◽  
Brain Data ◽  
The Brain

Abstract In the current study, we used functional magnetic resonance imaging to investigate how the brain facilitates social judgments despite evaluatively conflicting information. Participants learned consistent (positive or negative) and ambivalent (positive and negative) person information and were then asked to provide binary judgments of these targets in situations that either resolved conflict by prioritizing a subset of information or not. Self-report, decision time and brain data confirm that integrating contextual information into our evaluations of objects or people allows for nuanced (social) evaluations. The same mixed trait information elicited or failed to elicit evaluative conflict dependent on the situation. Crucially, we provide data suggesting that negative judgments are easier and may be considered the ‘default’ action when experiencing evaluative conflict: weaker activation in dorsolateral prefrontal cortex during trials of evaluative conflict was related to a greater likelihood of unfavorable judgments, and greater activation was related to more favorable judgments. Since negative outcome consequences are arguably more detrimental and salient, this finding supports the idea that additional regulation and a more active selection process are necessary to override an initial negative response to evaluatively conflicting information.

scholarly journals Changes in Self-reported Energy and Brain Volumes

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 783-783
Author(s):  
Qu Tian ◽  
Andrea Rosso ◽  
Nancy Glynn ◽  
Xiaonan Zhu ◽  
Caterina Rosano
Keyword(s):  
Prefrontal Cortex ◽  
Mixed Models ◽  
Rate Of Change ◽  
Self Report ◽  
Precentral Gyrus ◽  
Brain Health ◽  
Brain Volumes ◽  
The Past ◽  
Dorsolateral Prefrontal ◽  
The Brain

Abstract The brain demands and consumes more energy than any other organ. Lower perceived energy may indicate compromised brain health. Little empirical data exists on the association between perceived energy and brain structure. Neuroimaging was obtained in 300 participants (mean age=83±3 y/o, 40% blacks, 57%women) with repeated self-reported energy measures(scale0-10) in the past decade. Energy decline was computed as rate of change by linear mixed models(-0.06/year). Associations of energy decline with volumes of cognitive (dorsolateral prefrontal cortex, hippocampus) and motor (precentral gyrus, putamen, caudate) areas were examined using linear regression, adjusted for demographics and total gray matter atrophy. A steeper decline in energy was associated with smaller volumes of right putamen (p=0.013) and caudate (p=0.043), a trend in right precentral gyrus (p=0.085), but not in prefrontal cortex or hippocampus. Declining energy by self-report may indicate atrophy localized in subcortical motor areas. Studies to identify the mechanisms underlying these associations are warranted.

The self-schema and addictive behaviors: Studies of alcoholic patients

2001 ◽  
Vol 60 (2) ◽  
pp. 73-81 ◽  
Author(s):  
Cyril Tarquinio ◽  
Gustave Nicolas Fischer ◽  
Aurélie Gauchet ◽  
Jacques Perarnaud
Keyword(s):  
Decision Time ◽  
The Self ◽  
Addictive Behaviors ◽  
Social Judgments ◽  
Self Perceptions ◽  
Control Subjects ◽  
Self Schema ◽  
Description Task ◽  
Positive Traits ◽  
First Interview

This study deals with the sociocognitive organization of the self-schema in alcoholic patients. It was aimed at understanding how the self-schema takes shape within the framework of social judgments known to be determinants of personality. Alcoholic subjects were interviewed twice, once during their first consultation for treatment and then again four months later after completion of treatment. Our approach was derived directly from the methodology used by Markus (1977) and Clemmey & Nicassio (1997) in their studies on the self-schema. The subjects had to perform three tasks that required manipulating personality traits with positive and negative connotations (a self-description task in which decision time was measured, an autobiographical task, and a recall task). The results of the first interview showed that 1. in their self-descriptions, alcoholics took more time than control subjects both to accept positive traits and to reject negative ones; 2. unlike control subjects, alcoholics considered more negative traits to be self-descriptive than positive traits, and 3. unlike controls, alcoholics recalled more negative traits than positive ones. By the second interview, the results for the alcoholic subjects on the autobiographical and recall tasks had changed: 1. they now described themselves more positively and less negatively than on the first meeting; 2. they recalled a marginally greater number of positive traits and a significantly smaller number of negative traits, and 3. the differences between the alcoholics and controls indicated an improvement in the alcoholics' self-perceptions.

scholarly journals Decision-related feedback in visual cortex lacks spatial selectivity

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Katrina R. Quinn ◽  
Lenka Seillier ◽  
Daniel A. Butts ◽  
Hendrikje Nienborg
Keyword(s):  
Contextual Information ◽  
Relevant Information ◽  
Common Mechanism ◽  
Spatial Selectivity ◽  
Population Responses ◽  
Stimulus Choice ◽  
Visual Areas ◽  
Computational Work ◽  
Feature Based ◽  
The Brain

AbstractFeedback in the brain is thought to convey contextual information that underlies our flexibility to perform different tasks. Empirical and computational work on the visual system suggests this is achieved by targeting task-relevant neuronal subpopulations. We combine two tasks, each resulting in selective modulation by feedback, to test whether the feedback reflected the combination of both selectivities. We used visual feature-discrimination specified at one of two possible locations and uncoupled the decision formation from motor plans to report it, while recording in macaque mid-level visual areas. Here we show that although the behavior is spatially selective, using only task-relevant information, modulation by decision-related feedback is spatially unselective. Population responses reveal similar stimulus-choice alignments irrespective of stimulus relevance. The results suggest a common mechanism across tasks, independent of the spatial selectivity these tasks demand. This may reflect biological constraints and facilitate generalization across tasks. Our findings also support a previously hypothesized link between feature-based attention and decision-related activity.

scholarly journals HIV Infection Is Associated with Attenuated Frontostriatal Intrinsic Connectivity: A Preliminary Study

2015 ◽  
Vol 21 (3) ◽  
pp. 203-213 ◽  
Author(s):  
Jonathan C. Ipser ◽  
Gregory G. Brown ◽  
Amanda Bischoff-Grethe ◽  
Colm G. Connolly ◽  
Ronald J. Ellis ◽  
...  
Keyword(s):  
Hiv Infection ◽  
Brain Regions ◽  
Group Differences ◽  
Hiv Rna ◽  
Functional Connections ◽  
Intrinsic Connectivity ◽  
Dorsolateral Prefrontal ◽  
Independent Replication ◽  
Subcortical Regions ◽  
The Brain

AbstractHIV-associated cognitive impairments are prevalent, and are consistent with injury to both frontal cortical and subcortical regions of the brain. The current study aimed to assess the association of HIV infection with functional connections within the frontostriatal network, circuitry hypothesized to be highly vulnerable to HIV infection. Fifteen HIV-positive and 15 demographically matched control participants underwent 6 min of resting-state functional magnetic resonance imaging (RS-fMRI). Multivariate group comparisons of age-adjusted estimates of connectivity within the frontostriatal network were derived from BOLD data for dorsolateral prefrontal cortex (DLPFC), dorsal caudate and mediodorsal thalamic regions of interest. Whole-brain comparisons of group differences in frontostriatal connectivity were conducted, as were pairwise tests of connectivity associations with measures of global cognitive functioning and clinical and immunological characteristics (nadir and current CD4 count, duration of HIV infection, plasma HIV RNA). HIV – associated reductions in connectivity were observed between the DLPFC and the dorsal caudate, particularly in younger participants (<50 years, N=9). Seropositive participants also demonstrated reductions in dorsal caudate connectivity to frontal and parietal brain regions previously demonstrated to be functionally connected to the DLPFC. Cognitive impairment, but none of the assessed clinical/immunological variables, was also associated with reduced frontostriatal connectivity. In conclusion, our data indicate that HIV is associated with attenuated intrinsic frontostriatal connectivity. Intrinsic connectivity of this network may therefore serve as a marker of the deleterious effects of HIV infection on the brain, possibly via HIV-associated dopaminergic abnormalities. These findings warrant independent replication in larger studies. (JINS, 2015, 21, 1–11)

scholarly journals Recurrent Multi-Fiber Network for 3D MRI Brain Tumor Segmentation

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 320
Author(s):  
Yue Zhao ◽  
Xiaoqiang Ren ◽  
Kun Hou ◽  
Wentao Li
Keyword(s):  
Brain Tumor ◽  
Network Architecture ◽  
Contextual Information ◽  
Computational Cost ◽  
Disease Diagnosis ◽  
Tumor Segmentation ◽  
Brain Tumor Segmentation ◽  
Fiber Network ◽  
3D Network ◽  
The Brain

Automated brain tumor segmentation based on 3D magnetic resonance imaging (MRI) is critical to disease diagnosis. Moreover, robust and accurate achieving automatic extraction of brain tumor is a big challenge because of the inherent heterogeneity of the tumor structure. In this paper, we present an efficient semantic segmentation 3D recurrent multi-fiber network (RMFNet), which is based on encoder–decoder architecture to segment the brain tumor accurately. 3D RMFNet is applied in our paper to solve the problem of brain tumor segmentation, including a 3D recurrent unit and 3D multi-fiber unit. First of all, we propose that recurrent units segment brain tumors by connecting recurrent units and convolutional layers. This quality enhances the model’s ability to integrate contextual information and is of great significance to enhance the contextual information. Then, a 3D multi-fiber unit is added to the overall network to solve the high computational cost caused by the use of a 3D network architecture to capture local features. 3D RMFNet combines both advantages from a 3D recurrent unit and 3D multi-fiber unit. Extensive experiments on the Brain Tumor Segmentation (BraTS) 2018 challenge dataset show that our RMFNet remarkably outperforms state-of-the-art methods, and achieves average Dice scores of 89.62%, 83.65% and 78.72% for the whole tumor, tumor core and enhancing tumor, respectively. The experimental results prove our architecture to be an efficient tool for brain tumor segmentation accurately.

scholarly journals Social Judgments as a Measure of Right Mindfulness

SAGE Open ◽  
2017 ◽  
Vol 7 (1) ◽  
pp. 215824401668681
Author(s):  
Robert Lindsay Hakan ◽  
Julia M. Neal ◽  
John Lothes
Keyword(s):  
Empirical Evidence ◽  
Significant Relationship ◽  
Social Judgment ◽  
Self Report ◽  
Social Judgments ◽  
Demand Characteristics ◽  
Mindful Attention ◽  
Potential Demand ◽  
Mindful Attention Awareness Scale

Mindfulness should be associated with decreased automatic responding and with increased empathy and compassion. Therefore, given an opportunity to express judgments about other people, a highly mindful person should be less inclined to express negative and unnecessary judgments. The present study provided participants the opportunity to express judgments about photographs of other people in a procedure that attempted to control for potential demand characteristics associated with self-report measures of mindfulness. Expressed judgments were panel rated, and the derived judgment scores were regressed with participant scores on the Mindful Attention Awareness Scale (MAAS) and the Five Facets of Mindfulness Questionnaire (FFMQ). Results demonstrated no overall significant relationship between judgments and MAAS or FFMQ total scores. However, a significant relationship between judgment scores and the “act with awareness” and the “non-judgment” facets of the FFMQ was observed. Judgment scores were also related to self-reported involvement in mindfulness activities such as meditation and yoga. These results suggest that self-reported mindfulness may not completely align with behaviors that logically reflect right mindfulness. Moreover, social judgment may be a useful overt measure related to mindfulness. The results also provide empirical evidence of the very strong social tendency to negatively and often derogatorily judge other people.

scholarly journals Primate prefrontal neurons signal economic risk derived from the statistics of recent reward experience

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Fabian Grabenhorst ◽  
Ken-Ichiro Tsutsui ◽  
Shunsuke Kobayashi ◽  
Wolfram Schultz
Keyword(s):  
Dorsolateral Prefrontal Cortex ◽  
Choice Task ◽  
Support Vector ◽  
Probabilistic Choice ◽  
Economic Decisions ◽  
Decision Variables ◽  
Dorsolateral Prefrontal ◽  
Process Risk ◽  
The Brain ◽  
Statistical Variance

Risk derives from the variation of rewards and governs economic decisions, yet how the brain calculates risk from the frequency of experienced events, rather than from explicit risk-descriptive cues, remains unclear. Here, we investigated whether neurons in dorsolateral prefrontal cortex process risk derived from reward experience. Monkeys performed in a probabilistic choice task in which the statistical variance of experienced rewards evolved continually. During these choices, prefrontal neurons signaled the reward-variance associated with specific objects (‘object risk’) or actions (‘action risk’). Crucially, risk was not derived from explicit, risk-descriptive cues but calculated internally from the variance of recently experienced rewards. Support-vector-machine decoding demonstrated accurate neuronal risk discrimination. Within trials, neuronal signals transitioned from experienced reward to risk (risk updating) and from risk to upcoming choice (choice computation). Thus, prefrontal neurons encode the statistical variance of recently experienced rewards, complying with formal decision variables of object risk and action risk.

scholarly journals Compositional Restricted Boltzmann Machines Unveil the Brain-Wide Organization of Neural Assemblies

2021 ◽  
Author(s):  
Thijs L van der Plas ◽  
Jérôme Tubiana ◽  
Guillaume Le Goc ◽  
Geoffrey Migault ◽  
Michael Kunst ◽  
...  
Keyword(s):  
Structural Connectivity ◽  
Connectivity Matrix ◽  
Restricted Boltzmann Machines ◽  
Pairwise Correlation ◽  
Neural Assemblies ◽  
Data Statistics ◽  
Endogenous Activity ◽  
Brain Data ◽  
Correlation Statistics ◽  
The Brain

Patterns of endogenous activity in the brain reflect a stochastic exploration of the neuronal state space that is constrained by the underlying assembly organization of neurons. Yet it remains to be shown that this interplay between neurons and their assembly dynamics indeed suffices to generate whole-brain data statistics. Here we recorded the activity from ~40,000 neurons simultaneously in zebrafish larvae, and show that a data-driven network model of neuron-assembly interactions can accurately reproduce the mean activity and pairwise correlation statistics of their spontaneous activity. This model, the compositional Restricted Boltzmann Machine, unveils ~200 neural assemblies, which compose neurophysiological circuits and whose various combinations form successive brain states. From this, we mathematically derived an interregional functional connectivity matrix, which is conserved across individual animals and correlates well with structural connectivity. This novel, assembly-based generative model of brain-wide neural dynamics enables physiology-bound perturbation experiments in silico.

scholarly journals MicroRNA-203 represses selection and expansion of oncogenic Hras transformed tumor initiating cells

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Kent Riemondy ◽  
Xiao-jing Wang ◽  
Enrique C Torchia ◽  
Dennis R Roop ◽  
Rui Yi
Keyword(s):  
Cell Division ◽  
Skin Cancer ◽  
Mouse Model ◽  
Mouse Models ◽  
Knockout Mouse ◽  
Selection Process ◽  
Tumor Initiating Cells ◽  
Knockout Mouse Model ◽  
Active Selection ◽  
The Impact

In many mouse models of skin cancer, only a few tumors typically form even though many cells competent for tumorigenesis receive the same oncogenic stimuli. These observations suggest an active selection process for tumor-initiating cells. Here, we use quantitative mRNA- and miR-Seq to determine the impact of HrasG12V on the transcriptome of keratinocytes. We discover that microRNA-203 is downregulated by HrasG12V. Using a knockout mouse model, we demonstrate that loss of microRNA-203 promotes selection and expansion of tumor-initiating cells. Conversely, restoration of microRNA-203 using an inducible model potently inhibits proliferation of these cells. We comprehensively identify microRNA-203 targets required for Hras-initiated tumorigenesis. These targets include critical regulators of the Ras pathway and essential genes required for cell division. This study establishes a role for the loss of microRNA-203 in promoting selection and expansion of Hras mutated cells and identifies a mechanism through which microRNA-203 antagonizes Hras-mediated tumorigenesis.

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