Striatopallidal dysfunction underlies repetitive behavior in Shank3-deficient model of autism

The postsynaptic scaffolding protein SH3 and multiple ankyrin repeat domains 3 (SHANK3) is critical for the development and function of glutamatergic synapses. Disruption of the SHANK3-encoding gene has been strongly implicated as a monogenic cause of autism, and Shank3 mutant mice show repetitive grooming and social interaction deficits. Although basal ganglia dysfunction has been proposed to underlie repetitive behaviors, few studies have provided direct evidence to support this notion and the exact cellular mechanisms remain largely unknown. Here, we utilized the Shank3B mutant mouse model of autism to investigate how Shank3 mutation may differentially affect striatonigral (direct pathway) and striatopallidal (indirect pathway) medium spiny neurons (MSNs) and its relevance to repetitive grooming behavior in Shank3B mutant mice. We found that Shank3 deletion preferentially affects synapses onto striatopallidal MSNs. Striatopallidal MSNs showed profound defects, including alterations in synaptic transmission, synaptic plasticity, and spine density. Importantly, the repetitive grooming behavior was rescued by selectively enhancing the striatopallidal MSN activity via a Gq-coupled human M3 muscarinic receptor (hM3Dq), a type of designer receptors exclusively activated by designer drugs (DREADD). Our findings directly demonstrate the existence of distinct changes between 2 striatal pathways in a mouse model of autism and indicate that the indirect striatal pathway disruption might play a causative role in repetitive behavior of Shank3B mutant mice.National Institute of Mental Health (U.S.) (Grant 5R01MH097104

Cortico-thalamic interactions for head direction coding

The ability to orient oneself within an environment is critical for spatial navigation and thus for survival and reproductive success. Orienting depends on interactions between multiple brain areas carrying information about head and body movements as well as external sensory cues for reference. To adapt to changing environments and correct for error, head direction (HD) representations must be flexible. However, the circuit mechanisms and dynamics underlying how HD is modulated are largely unknown. Retrosplenial cortex (RSC) is a key region for spatial cognition and exhibits dense interconnection with visual and motor areas, the hippocampal formation, and diverse thalamic nuclei. Of these, the anterodorsal thalamus (ADn) is the major avenue by which HD is routed to cortex. In other cortical areas, cortico-thalamic loops have been shown to perform transformations on incoming sensory inputs for learning and behavior output. In this thesis I test the hypothesis that interactions between RSC and ADN provide a circuit substrate for flexible HD computations. In the first part, I describe experiments using simultaneous tetrode recordings in behaving mice. Through neural decoding, I show that RSC HD representation is synchronous with that of ADn, not only during the visually-guided HD reference update, but also in darkness. This coordination is supported by strong feedforward functional connectivity in the thalamo-cortical direction, suggesting that visually-guided adaptations likely emerge upstream of ADn, where angular velocity is integrated. In the second part, I confirm that ADn is devoid of recurrent excitatory connectivity, contrary to previously proposed attractor network architectures. My results suggest that inhibition, originating in thalamic reticular nucleus, likely plays a fundamental role in the control of ADn HD. Finally, I provide evidence, at the single cell level, of how long-range synaptic inputs are functionally targeted to specific dendritic domains in RSC. I speculate that this connectivity logic, together with different dendritic integration rules, may underlie high-dimensional tuning and combine visual and thalamic HD to represent global HD references. Altogether, this work suggests that ADn-RSC interactions alone cannot account for flexible HD coding, but are embedded in a network that constructs this spatial cognitive representation through transformation of multiple sensory signals.Ph.D

Coordinated head direction representations in mouse anterodorsal thalamic nucleus and retrosplenial cortex

The sense of direction is critical for survival in changing environments and relies on flexibly integrating self-motion signals with external sensory cues. While the anatomical substrates involved in head direction (HD) coding are well known, the mechanisms by which visual information updates HD representations remain poorly understood. Retrosplenial cortex (RSC) plays a key role in forming coherent representations of space in mammals and it encodes a variety of navigational variables, including HD. Here, we use simultaneous two-area tetrode recording to show that RSC HD representation is nearly synchronous with that of the anterodorsal nucleus of thalamus (ADn), the obligatory thalamic relay of HD to cortex, during rotation of a prominent visual cue. Moreover, coordination of HD representations in the two regions is maintained during darkness. We further show that anatomical and functional connectivity are consistent with a strong feedforward drive of HD information from ADn to RSC, with anatomically restricted corticothalamic feedback. Together, our results indicate a concerted global HD reference update across cortex and thalamus

Enhanced Dendritic Compartmentalization in Human Cortical Neurons

The biophysical features of neurons shape information processing in the brain. Cortical neurons are larger in humans than in other species, but it is unclear how their size affects synaptic integration. Here, we perform direct electrical recordings from human dendrites and report enhanced electrical compartmentalization in layer 5 pyramidal neurons. Compared to rat dendrites, distal human dendrites provide limited excitation to the soma, even in the presence of dendritic spikes. Human somas also exhibit less bursting due to reduced recruitment of dendritic electrogenesis. Finally, we find that decreased ion channel densities result in higher input resistance and underlie the lower coupling of human dendrites. We conclude that the increased length of human neurons alters their input-output properties, which will impact cortical computation. Video Abstract: Human cortical neurons exhibit a higher degree of voltage compartmentalization compared to rodent counterparts due to lower ion channel densities across larger dendritic surfaces.National Institutes of Health (Grant RO1NS106031

A comparison of ten polygenic score methods for psychiatric disorders applied across multiple cohorts

Background: Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies (GWASs). PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors. Methods: The Psychiatric Genomics Consortium working groups for schizophrenia (SCZ) and major depressive disorder (MDD) bring together many independently collected case control cohorts. We used these resources (31K SCZ cases, 41K controls; 248K MDD cases, 563K controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and nine methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) are compared. Results: Compared to PC+T, the other nine methods give higher prediction statistics, MegaPRS, LDPred2 and SBayesR significantly so, up to 9.2% variance in liability for SCZ across 30 target cohorts, an increase of 44%. For MDD across 26 target cohorts these statistics were 3.5% and 59%, respectively. Conclusions: Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparison and are recommended in applications to psychiatric disorders