Gender differences in human single neuron responses to male emotional faces

Encoding of Race Categories by Single Neurons in the Human Brain

Previous research has suggested that race-specific features are automatically processed during face perception, often with out-group faces treated categorically. Functional imaging has illuminated the hemodynamic correlates of this process, with fewer studies examining single-neuron responses. In the present experiment, epilepsy patients undergoing microwire recordings in preparation for surgical treatment were shown realistic computer-generated human faces, which they classified according to the emotional expression shown. Racial categories of the stimulus faces varied independently of the emotion shown, being irrelevant to the patients’ primary task. Nevertheless, we observed race-driven changes in neural firing rates in the amygdala, anterior cingulate cortex, and hippocampus. These responses were broadly distributed, with the firing rates of 28% of recorded neurons in the amygdala and 45% in the anterior cingulate cortex predicting one or more racial categories. Nearly equal proportions of neurons responded to White and Black faces (24% vs. 22% in the amygdala and 26% vs. 28% in the anterior cingulate cortex). A smaller fraction (12%) of race-responsive neurons in the hippocampus predicted only White faces. Our results imply a distributed representation of race in brain areas involved in affective judgments, decision making, and memory. They also support the hypothesis that race-specific cues are perceptually coded even when those cues are task-irrelevant.

Sex Differences in the Amygdala Resting-State Connectome of Children With Autism Spectrum Disorder

BACKGROUND

Multifactorial liability models predict greater dissimilarity in the neural phenotype of autism spectrum disorder (ASD) in female individuals than in male individuals, while gender incoherence and extreme male brain models predict attenuated sex differences in ASD. The amygdala is an informative target to explore these models because it is implicated in both the neurobiology of ASD and sex differences in typical development.

METHODS

This study investigated amygdala resting-state functional connectivity in a cohort of 116 children with ASD (36 female) and 58 typically developing children (27 female) 2 to 7 years of age during natural sleep. First, multivariate distance matrix regression assessed global sex and diagnostic differences across the amygdala connectome. Second, univariate general linear models identified regions with mean connectivity differences.

RESULTS

Multivariate distance matrix regression revealed greater differences between typically developing children and those with ASD in females than in males, consistent with multifactorial liability models, and attenuated sex differences in the left amygdala connectome of children with ASD in a pattern consistent with the gender incoherence model. Univariate analysis identified similar sex differences in dorsomedial and ventral prefrontal cortices, lingual gyrus, and posterior cingulate cortex, but also noted that lower amygdala connectivity with superior temporal sulcus is observed across sexes.

CONCLUSIONS

This study provides evidence that compared with sex-matched control subjects, ASD manifests differently in the brain at the time of diagnosis and prior to the influence of compensatory mechanisms in male and female children, consistent with multifactorial liability models, and that ASD is associated with reduced sex differences in a pattern consistent with gender incoherence models.

An earlier time of scan is associated with greater threat-related amygdala reactivity

Time-dependent variability in mood and anxiety suggest that related neural phenotypes, such as threat-related amygdala reactivity, may also follow a diurnal pattern. Here, using data from 1,043 young adult volunteers, we found that threat-related amygdala reactivity was negatively coupled with time of day, an effect which was stronger in the left hemisphere (β = -0.1083, p-fdr = 0.0012). This effect was moderated by subjective sleep quality (β = -0.0715, p-fdr = 0.0387); participants who reported average and poor sleep quality had relatively increased left amygdala reactivity in the morning. Bootstrapped simulations suggest that similar cross-sectional samples with at least 300 participants would be able to detect associations between amygdala reactivity and time of scan. In control analyses, we found no associations between time and V1 activation. Our results provide initial evidence that threat-related amygdala reactivity may vary diurnally, and that this effect is potentiated among individuals with average to low sleep quality. More broadly, our results suggest that considering time of scan in study design or modeling time of scan in analyses, as well as collecting additional measures of circadian variation, may be useful for understanding threat-related neural phenotypes and their associations with behavior, such as fear conditioning, mood and anxiety symptoms, and related phenotypes.