Biology subjects

Chavez, R. S.

Publications and source records attributed to Chavez, R. S..

3 recordsLinked to original sources

bioRxiv2026

Person identity drives neural similarity more than action and valence during dynamic emotion perception

Facial perception is a central feature of everyday social encounters and a rich source of emotional information. Classic functional magnetic resonance imaging (fMRI) studies of emotional facial processing used static photos emotional expression to identify regions of the brain showing univariate differences in response magnitudes between different emotional categories. However, there has been much less work identifying how the brain represents dynamic emotional facial expression and the factors that drive the similarity among these representations. In the current study, incorporated dynamic facial expression stimuli and representational similarity analysis to compare three competing hypothesized models of similarity of each of the stimuli presented: action being made, valence of the expression, and the identity of the person being perceived. Participants were shown short videos of fourteen volunteer actors making positive or negative facial expressions directed either toward or away from the camera. Activation patterns were compared against competing models on a trial-by-trial basis using a full multilevel modeling approach. Results showed that the identity of the person in the video was a greater predictor of brain responses similarity than the action or valence across widely distributed brain systems, particularly in the default mode network and lower-level visual processing regions. This suggests that the specific identity of the stimulus being perceived is a central driver of neural response similarity during perceptual encoding in dynamic facial processing.

neuroscience↗

bioRxiv2023

Independent allocentric and egocentric reference frame encoding of person knowledge within the brains of social groups

Humans spontaneously infer information about others to perceive the similarity in behaviors and traits among people in our social environments. However, evaluating the similarity among people can be achieved through multiple frames of reference: other-to-other differences (allocentric similarity) or self-to-other differences (egocentric similarity), which are difficult to dissociate with behavioral measures alone. Here, we use functional magnetic resonance imaging to test whether the similarity of brain response patterns when thinking of others and the self is predicted by models of allocentric and egocentric similarity in the trait-judgments of well-acquainted peers from 20 independent groups of people (total N = 108; within-subject design). Results show that both allocentric and egocentric similarity during person representation are reflected in brain response similarity patterns when thinking of others but do so differentially and in non-overlapping brain systems. Specifically, allocentric similarity was positively related to brain similarity patterns in distributed regions involved in social cognition as well as in regions involved in general non-social spatial reference frame encoding. Egocentric similarity was inversely related to brain response similarity but only within dorsal regions of the medial prefrontal cortex and anterior cingulate, suggesting that activation within this region is important for dissociating selfrepresentation from that of similar others. These results suggest that the brain processes both kinds of reference frames independently to encode trait information about conspecifics that we use to represent person knowledge about other people within realworld social networks.

neuroscience↗

bioRxiv2017

Mass univariate testing biases the detection of interaction effects in whole-brain analysis of variance.

Whole-brain analysis of variance (ANOVA) is a common analytic approach in cognitive neuroscience. Researchers are often interested in exploring whether brain activity reflects to the interaction of two factors. Disordinal interactions -- where there is a reversal of the effect of one independent variable at a level of a second independent variable -- are common in the literature. It is well established in power-analyses of factorial ANOVAs that certain patterns of interactions, such as disordinal (e.g., cross-over interactions) require less power than others to detect. This fact, combined with the perils of mass univariate testing suggests that testing for interactions in whole-brain ANOVAs, may be biased towards the detection of disordinal interactions. Here, we report on a series of simulated analysis --including whole-brain fMRI data using realistic multi-source noise parameters-- that demonstrate a bias towards the detection of disordinal interactions in mass-univariate contexts. Moreover, results of these simulations indicated that spurious disordinal interactions are found at common thresholds and cluster sizes at the group level. Moreover, simulations based on implanting true ordinal interaction effects can nevertheless appear like crossover effects at realistic levels of signal-to-noise ratio (SNR) when performing mass univariate testing at the whole-brain level, potentially leading to erroneous conclusions when interpreted as is. Simulations of varying sample sizes and SNR levels show that this bias is driven primarily by SNR and larger sample sizes do little to ameliorate this issue. Together, the results of these simulations argue for caution when searching for ordinal interactions in whole-brain ANOVA.

neuroscience↗