Tactile processing in mouse cortex depends on action context.

The brain receives constant tactile input, but only a subset guides ongoing behavior. Actions associated with tactile stimuli thus endow them with behavioral relevance. It remains unclear how the relevance of tactile stimuli affects processing in the somatosensory (S1) cortex. We developed a cross-modal selection task in which head-fixed mice switched between responding to tactile stimuli in the presence of visual distractors or to visual stimuli in the presence of tactile distractors using licking movements to the left or right side in different blocks of trials. S1 spiking encoded tactile stimuli, licking actions, and direction of licking in response to tactile but not visual stimuli. Bidirectional optogenetic manipulations showed that sensory-motor activity in S1 guided behavior when touch but not vision was relevant. Our results show that S1 activity and its impact on behavior depend on the actions associated with a tactile stimulus.

NeuroTri2-VISDOT: An open-access tool to harness the power of second trimester human single cell data to inform models of Mendelian neurodevelopmental disorders.

Whole exome and genome sequencing, coupled with refined bioinformatic pipelines, have enabled improved diagnostic yields for individuals with Mendelian conditions and have led to the rapid identification of novel syndromes. For many Mendelian neurodevelopmental disorders (NDDs), there is a lack of pre-existing model systems for mechanistic work. Thus, it is critical for translational researchers to have an accessible phenotype- and genotype-informed approach for model system selection. Single-cell RNA sequencing data can be informative in such an approach, as it can indicate which cell types express a gene of interest at the highest levels across time. For Mendelian NDDs, such data for the developing human brain is especially useful. A valuable single-cell RNA sequencing dataset of the second trimester developing human brain was produced by Bhaduri et al in 2021, but access to these data can be limited by computing power and the learning curve of single-cell data analysis. To reduce these barriers for translational research on Mendelian NDDs, we have built the web-based tool, Neurodevelopment in Trimester 2 - VIsualization of Single cell Data Online Tool (NeuroTri2-VISDOT), for exploring this single-cell dataset, and we have employed it in several different settings to demonstrate its utility for the translational research community.

Expanded phenotypic spectrum of neurodevelopmental and neurodegenerative disorder Bryant-Li-Bhoj syndrome with 38 additional individuals.

Bryant-Li-Bhoj syndrome (BLBS), which became OMIM-classified in 2022 (OMIM: 619720, 619721), is caused by germline variants in the two genes that encode histone H3.3 (H3-3A/H3F3A and H3-3B/H3F3B) [1-4]. This syndrome is characterized by developmental delay/intellectual disability, craniofacial anomalies, hyper/hypotonia, and abnormal neuroimaging [1, 5]. BLBS was initially categorized as a progressive neurodegenerative syndrome caused by de novo heterozygous variants in either H3-3A or H3-3B [1-4]. Here, we analyze the data of the 58 previously published individuals along 38 unpublished, unrelated individuals. In this larger cohort of 96 people, we identify causative missense, synonymous, and stop-loss variants. We also expand upon the phenotypic characterization by elaborating on the neurodevelopmental component of BLBS. Notably, phenotypic heterogeneity was present even amongst individuals harboring the same variant. To explore the complex phenotypic variation in this expanded cohort, the relationships between syndromic phenotypes with three variables of interest were interrogated: sex, gene containing the causative variant, and variant location in the H3.3 protein. While specific genotype-phenotype correlations have not been conclusively delineated, the results presented here suggest that the location of the variants within the H3.3 protein and the affected gene (H3-3A or H3-3B) contribute more to the severity of distinct phenotypes than sex. Since these variables do not account for all BLBS phenotypic variability, these findings suggest that additional factors may play a role in modifying the phenotypes of affected individuals. Histones are poised at the interface of genetics and epigenetics, highlighting the potential role for gene-environment interactions and the importance of future research.

Stable Representations of Decision Variables for Flexible Behavior.

Decisions occur in dynamic environments. In the framework of reinforcement learning, the probability of performing an action is influenced by decision variables. Discrepancies between predicted and obtained rewards (reward prediction errors) update these variables, but they are otherwise stable between decisions. Although reward prediction errors have been mapped to midbrain dopamine neurons, it is unclear how the brain represents decision variables themselves. We trained mice on a dynamic foraging task in which they chose between alternatives that delivered reward with changing probabilities. Neurons in the medial prefrontal cortex, including projections to the dorsomedial striatum, maintained persistent firing rate changes over long timescales. These changes stably represented relative action values (to bias choices) and total action values (to bias response times) with slow decay. In contrast, decision variables were weakly represented in the anterolateral motor cortex, a region necessary for generating choices. Thus, we define a stable neural mechanism to drive flexible behavior.