A Thalamic Orphan Receptor Drives Variability in Short-Term Memory

Stem cell transcriptional profiles from mouse subspecies reveal cis -regulatory evolution at translation genes

A key goal of evolutionary genomics is to harness molecular data to draw inferences about selective forces that have acted on genomes. The field progresses in large part through the development of advanced molecular-evolution analysis methods. Here we explored the intersection between classical sequence-based tests for selection and an empirical expression-based approach, using stem cells from Mus musculus subspecies as a model. Using a test of directional, cis -regulatory evolution across genes in pathways, we discovered a unique program of induction of translation genes in stem cells of the Southeast Asian mouse M. m. castaneus relative to its sister taxa. We then mined population-genomic sequences to pursue underlying regulatory mechanisms for this expression divergence, finding robust evidence for alleles unique to M. m. castaneus at the upstream regions of the translation genes. We interpret our data under a model of changes in lineage-specific pressures across Mus musculus in stem cells with high translational capacity. Our findings underscore the rigor of integrating expression and sequence-based methods to generate hypotheses about evolutionary events from long ago.

The thalamic reticular nucleus orchestrates social memory

Social memory has been developed in humans and other animals to recognize familiar conspecifics and is essential for their survival and reproduction. Here, we demonstrated that parvalbumin-positive neurons in the sensory thalamic reticular nucleus (sTRNPvalb) are necessary and sufficient for mice to memorize conspecifics. sTRNPvalb neurons receiving glutamatergic projections from the posterior parietal cortex (PPC) transmit individual information by inhibiting the parafascicular thalamic nucleus (PF). Mice in which the PPCCaMKII→sTRNPvalb→PF circuit was inhibited exhibited a disrupted ability to discriminate familiar conspecifics from novel ones. More strikingly, a subset of sTRNPvalb neurons with high electrophysiological excitability and complex dendritic arborizations is involved in the above corticothalamic pathway and stores social memory. Single-cell RNA sequencing revealed the biochemical basis of these subset cells as a robust activation of protein synthesis. These findings elucidate that sTRNPvalb neurons modulate social memory by coordinating a hitherto unknown corticothalamic circuit and inhibitory memory engram.

Molecular insights into orphan G protein-coupled receptors relevant to schizophrenia

Schizophrenia remains a sizable socio-economic burden that continues to be treated with therapeutics based on 70-year old science. All currently approved therapeutics primarily target the dopamine D2 receptor to achieve their efficacy. Whilst dopaminergic dysregulation is a key feature in this disorder, the targeting of dopaminergic machinery has yielded limited efficacy and an appreciable side effect burden. Over the recent decades, numerous drugs that engage non-dopaminergic G protein-coupled receptors (GPCRs) have yielded a promise of efficacy without the deleterious side effect profile, yet none have successfully completed clinical studies and progressed to the market. More recently, there has been increased attention around non-dopaminergic GPCR-targeting drugs, which demonstrated efficacy in some schizophrenia symptom domains. This provides renewed hope that effective schizophrenia treatment may lie outside of the dopaminergic space. Despite the potential for muscarinic receptor- (and other well-characterised GPCR families) targeting drugs to treat schizophrenia, they are often plagued with complications such as lack of receptor subtype selectivity and peripheral on-target side effects. Orphan GPCR studies have opened a new avenue of exploration with many demonstrating schizophrenia-relevant mechanisms and a favourable expression profile, thus offering potential for novel drug development. This review discusses centrally expressed orphan GPCRs: GPR3, GPR6, GPR12, GPR52, GPR85, GPR88 and GPR139 and their relationship to schizophrenia. We review their expression, signalling mechanisms and cellular function, in conjunction with small molecule development and structural insights. We seek to provide a snapshot of the growing evidence and development potential of new classes of schizophrenia therapeutics. LINKED ARTICLES: This article is part of a themed issue Therapeutic Targeting of G Protein-Coupled Receptors: hot topics from the Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists 2021 Virtual Annual Scientific Meeting. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.14/issuetoc.

A PLURIPOTENT STEM CELL PLATFORM FOR IN VITRO SYSTEMS GENETICS STUDIES OF MOUSE DEVELOPMENT

The directed differentiation of pluripotent stem cells (PSCs) from panels of genetically diverse individuals is emerging as a powerful experimental system for characterizing the impact of natural genetic variation on developing cell types and tissues. Here, we establish new PSC lines and experimental approaches for modeling embryonic development in a genetically diverse, outbred mouse stock (Diversity Outbred mice). We show that a range of inbred and outbred PSC lines can be stably maintained in the primed pluripotent state (epiblast stem cells -- EpiSCs) and establish the contribution of genetic variation to phenotypic differences in gene regulation and directed differentiation. Using pooled in vitro fertilization, we generate and characterize a genetic reference panel of Diversity Outbred PSCs (n = 230). Finally, we demonstrate the feasibility of pooled culture of Diversity Outbred EpiSCs as "cell villages", which can facilitate the differentiation of large numbers of EpiSC lines for forward genetic screens. These data can complement and inform similar efforts within the stem cell biology and human genetics communities to model the impact of natural genetic variation on phenotypic variation and disease-risk.

ERNEST COST action overview on the (patho)physiology of GPCRs and orphan GPCRs in the nervous system

G protein-coupled receptors (GPCRs) are a large family of cell surface receptors that play a critical role in nervous system function by transmitting signals between cells and their environment. They are involved in many, if not all, nervous system processes, and their dysfunction has been linked to various neurological disorders representing important drug targets. This overview emphasises the GPCRs of the nervous system, which are the research focus of the members of ERNEST COST action (CA18133) working group 'Biological roles of signal transduction'. First, the (patho)physiological role of the nervous system GPCRs in the modulation of synapse function is discussed. We then debate the (patho)physiology and pharmacology of opioid, acetylcholine, chemokine, melatonin and adhesion GPCRs in the nervous system. Finally, we address the orphan GPCRs, their implication in the nervous system function and disease, and the challenges that need to be addressed to deorphanize them.

Beyond hippocampus: Thalamic and prefrontal contributions to an evolving memory

The hippocampus has long been at the center of memory research, and rightfully so. However, with emerging technological capabilities, we can increasingly appreciate memory as a more dynamic and brain-wide process. In this perspective, our goal is to begin developing models to understand the gradual evolution, reorganization, and stabilization of memories across the brain after their initial formation in the hippocampus. By synthesizing studies across the rodent and human literature, we suggest that as memory representations initially form in hippocampus, parallel traces emerge in frontal cortex that cue memory recall, and as they mature, with sustained support initially from limbic then diencephalic then cortical circuits, they become progressively independent of hippocampus and dependent on a mature cortical representation. A key feature of this model is that, as time progresses, memory representations are passed on to distinct circuits with progressively longer time constants, providing the opportunity to filter, forget, update, or reorganize memories in the process of committing to long-term storage.

Genetic mapping identifies Homer1 as a developmental modifier of attention

Attention is required for most higher-order cognitive functions. Prior studies have revealed functional roles for the prefrontal cortex and its extended circuits to enabling attention, but the underlying molecular processes and their impacts on cellular and circuit function remain poorly understood. To develop insights, we here took an unbiased forward genetics approach to identify single genes of large effect on attention. We studied 200 genetically diverse mice on measures of pre-attentive processing and through genetic mapping identified a small locus on chromosome 13 (95%CI: 92.22-94.09 Mb) driving substantial variation (19%) in this trait. Further characterization of the locus revealed a causative gene, Homer1, encoding a synaptic protein, where down-regulation of its short isoforms in prefrontal cortex (PFC) during early postnatal development led to improvements in multiple measures of attention in the adult. Subsequent mechanistic studies revealed that prefrontal Homer1 down-regulation is associated with GABAergic receptor up-regulation in those same cells. This enhanced inhibitory influence, together with dynamic neuromodulatory coupling, led to strikingly low PFC activity at baseline periods of the task but targeted elevations at cue onset, predicting short-latency correct choices. Notably high-Homer1, low-attentional performers, exhibited uniformly elevated PFC activity throughout the task. We thus identify a single gene of large effect on attention - Homer1 - and find that it improves prefrontal inhibitory tone and signal-to-noise (SNR) to enhance attentional performance. A therapeutic strategy focused on reducing prefrontal activity and increasing SNR, rather than uniformly elevating PFC activity, may complement the use of stimulants to improve attention.

The Associative Thalamus: A Switchboard for Cortical Operations and a Promising Target for Schizophrenia

Schizophrenia is a brain disorder that profoundly perturbs cognitive processing. Despite the success in treating many of its symptoms, the field lacks effective methods to measure and address its impact on reasoning, inference, and decision making. Prefrontal cortical abnormalities have been well documented in schizophrenia, but additional dysfunction in the interactions between the prefrontal cortex and thalamus have recently been described. This dysfunction may be interpreted in light of parallel advances in neural circuit research based on nonhuman animals, which show critical thalamic roles in maintaining and switching prefrontal activity patterns in various cognitive tasks. Here, we review this basic literature and connect it to emerging innovations in clinical research. We highlight the value of focusing on associative thalamic structures not only to better understand the very nature of cognitive processing but also to leverage these circuits for diagnostic and therapeutic development in schizophrenia. We suggest that the time is right for building close bridges between basic thalamic research and its clinical translation, particularly in the domain of cognition and schizophrenia.

Hidden variables in stress neurobiology research

Among the central goals of stress neurobiology research is to understand the mechanisms by which stressors change neural circuit function to precipitate or exacerbate psychiatric symptoms. Yet despite decades of effort, psychiatric medications that target the biological substrates of the stress response are largely lacking. We propose that the clinical advancement of stress response-based therapeutics for psychiatric disorders may be hindered by 'hidden variables' in stress research, including considerations of behavioral study design (stressors and outcome measures), individual variability, sex differences, and the interaction of the body's stress hormone system with endogenous circadian and ultradian rhythms. We highlight key issues and suggest ways forward in stress neurobiology research that may improve the ability to assess stress mechanisms and translate preclinical findings.

How deep is the brain? The shallow brain hypothesis

Deep learning and predictive coding architectures commonly assume that inference in neural networks is hierarchical. However, largely neglected in deep learning and predictive coding architectures is the neurobiological evidence that all hierarchical cortical areas, higher or lower, project to and receive signals directly from subcortical areas. Given these neuroanatomical facts, today's dominance of cortico-centric, hierarchical architectures in deep learning and predictive coding networks is highly questionable; such architectures are likely to be missing essential computational principles the brain uses. In this Perspective, we present the shallow brain hypothesis: hierarchical cortical processing is integrated with a massively parallel process to which subcortical areas substantially contribute. This shallow architecture exploits the computational capacity of cortical microcircuits and thalamo-cortical loops that are not included in typical hierarchical deep learning and predictive coding networks. We argue that the shallow brain architecture provides several critical benefits over deep hierarchical structures and a more complete depiction of how mammalian brains achieve fast and flexible computational capabilities.

Opportunities and challenges in drug discovery targeting the orphan receptor GPR12

G-protein-coupled receptor 12 (GPR12) is a brain-specific expression orphan G-protein-coupled receptor (oGPCR) that regulates various physiological processes. It is an emerging therapeutic target for central nervous system (CNS) disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), attention deficit hyperactivity disorder (ADHD), and schizophrenia, as well as other human diseases, such as cancer, obesity, and metabolic disorders. GPR12 remains a less extensively investigated oGPCR, particularly in terms of its biological functions, signaling pathways, and ligand discovery. The discovery of drug-like small-molecule modulators to probe the brain functions of GPR12 or to act as a potential drug candidates, as well as the identification of reliable biomarkers, are vital to elucidate the roles of this receptor in various human diseases and develop novel target-based therapeutics.

Which mouse multiparental population is right for your study? The Collaborative Cross inbred strains, their F1 hybrids, or the Diversity Outbred population

Multiparental populations (MPPs) encompass greater genetic diversity than traditional experimental crosses of two inbred strains, enabling broader surveys of genetic variation underlying complex traits. Two such mouse MPPs are the Collaborative Cross (CC) inbred panel and the Diversity Outbred (DO) population, which are descended from the same eight inbred strains. Additionally, the F1 intercrosses of CC strains (CC-RIX) have been used and enable study designs with replicate outbred mice. Genetic analyses commonly used by researchers to investigate complex traits in these populations include characterizing how heritable a trait is, i.e. its heritability, and mapping its underlying genetic loci, i.e. its quantitative trait loci (QTLs). Here we evaluate the relative merits of these populations for these tasks through simulation, as well as provide recommendations for performing the quantitative genetic analyses. We find that sample populations that include replicate animals, as possible with the CC and CC-RIX, provide more efficient and precise estimates of heritability. We report QTL mapping power curves for the CC, CC-RIX, and DO across a range of QTL effect sizes and polygenic backgrounds for samples of 174 and 500 mice. The utility of replicate animals in the CC and CC-RIX for mapping QTLs rapidly decreased as traits became more polygenic. Only large sample populations of 500 DO mice were well-powered to detect smaller effect loci (7.5-10%) for highly complex traits (80% polygenic background). All results were generated with our R package musppr, which we developed to simulate data from these MPPs and evaluate genetic analyses from user-provided genotypes.

Prefrontal Cortex Hemodynamics and Functional Connectivity Changes during Performance Working Memory Tasks in Older Adults with Sleep Disorders

Objective: Older adults with sleep disorders (SDs) show impaired working memory abilities, and working memory processes are closely related to the prefrontal cortex (PFC). However, the neural mechanism of working memory impairment in older adults with SD remains unclear. This study aimed to investigate changes in PFC function among older adults with SD when carrying out the N-back task by functional near-infrared spectroscopy (fNIRS). Method: A total of 37 older adults with SDs were enrolled in this study and matched with 37 healthy older adults by gender, age, and years of education. Changes in PFC function were observed by fNIRS when carrying out the N-back task. Results: The accuracy on the 0-back and 2-back tasks in the SD group was significantly lower than that in the healthy controls (HC) group. The oxygenated hemoglobin (oxy-Hb) concentration of channel 8 which located in the dorsolateral prefrontal cortex (DLPFC) was significantly reduced in the SD group during the 2-back task, and the channel-to-channel connectivity between the PFC subregions was significantly decreased. Conclusions: These results suggest that patients with sleep disorders have a weak performance of working memory; indeed, the activation and functional connectivity in the prefrontal subregions were reduced in this study. This may provide new evidence for working memory impairment and brain function changes in elderly SDs.

A domain-general frontoparietal network interacts with domain-preferential intermediate pathways to support working memory task

Working memory (WM) is essential for cognition, but the underlying neural mechanisms remain elusive. From a hierarchical processing perspective, this paper proposed and tested a hypothesis that a domain-general network at the top of the WM hierarchy can interact with distinct domain-preferential intermediate circuits to support WM. Employing a novel N-back task, we first identified the posterior superior temporal gyrus (pSTG), middle temporal area (MT), and postcentral gyrus (PoCG) as intermediate regions for biological motion and shape motion processing, respectively. Using further psychophysiological interaction analyses, we delineated a frontal-parietal network (FPN) as the domain-general network. These results were further verified and extended by a delayed match to sample (DMS) task. Although the WM load-dependent and stimulus-free activations during the DMS delay phase confirm the role of FPN as a domain-general network to maintain information, the stimulus-dependent activations within this network during the DMS encoding phase suggest its involvement in the final stage of the hierarchical processing chains. In contrast, the load-dependent activations of intermediate regions in the N-back task highlight their further roles beyond perception in WM tasks. These results provide empirical evidence for a hierarchical processing model of WM and may have significant implications for WM training.

Structural insight into the constitutive activity of human orphan receptor GPR12

G protein-coupled receptor 12 (GPR12) is an orphan G protein-coupled receptor that is highly expressed in the thalamus of the brain and plays a vital role in driving thalamocortical functions in short-term memory. GPR12 performs high constitutive activity and couples with Gs, increasing the intracellular cyclic adenosine monophosphate (cAMP) level when it is expressed. However, exploitation for drug development is limited since it is unclear how GPR12 initiates self-activation and signal transduction, and whether it can be modulated by endogenous or synthetic ligands. Here, we report the cryo-electron microscopy structure of the GPR12-Gs complex in the absence of agonists. Our structure reveals the key determinants for the intrinsically high basal activity of GPR12, including extracellular loop 2 partially occupying the orthosteric binding pocket, a tight-packed TM1 and TM7, and unique activation-related residues in TM6 and TM7. Together with mutagenesis data, this study will improve our understanding of the function and self-activation of the orphan receptor GPR12, enable the identification of endogenous ligands, and guide drug discovery efforts that target GPR12.

A simultaneous EEG-fMRI study of thalamic load-dependent working memory delay period activity

Introduction

Working memory (WM) is an essential component of executive functions which depend on maintaining task-related information online for brief periods in both the presence and absence of interfering stimuli. Active maintenance occurs during the WM delay period, the time between stimulus encoding and subsequent retrieval. Previous studies have extensively documented prefrontal and posterior parietal cortex activity during the WM delay period, but the role of subcortical structures including the thalamus remains to be fully elucidated, especially in humans.

Methods

Using a simultaneous electroencephalogram (EEG)-functional magnetic resonance imaging (fMRI) approach, we investigated the role of the thalamus during the WM delay period in a modified Sternberg paradigm following low and high memory load encoding of naturalistic scenes. During the delay, participants passively viewed scrambled scenes containing similar color and spatial frequency to serve as a perceptual baseline. Individual source estimation was weighted by the location of the thalamic fMRI signal relative to the WM delay period onset.

Results

The effects memory load on maintenance were observed bilaterally in thalamus with higher EEG source amplitudes in the low compared to high load condition occurring 160-390 ms after the onset of the delay period.

Conclusion

The main finding that thalamic activation was elevated during the low compared to high condition despite similar duration of perceptual input and upcoming motor requirements suggests a capacity-limited role for sensory filtering of the thalamus during consolidation of stimuli into WM, where the highest activity occurs when fewer stimuli need to be maintained in the presence of interfering perceptual stimuli during the delay. The results are discussed in the context of theories regarding the role of the thalamus in sensory gating during working memory.

Thalamocortical Development: A Neurodevelopmental Framework for Schizophrenia

Adolescence is a period of increased vulnerability for the development of psychiatric disorders, including schizophrenia. The prefrontal cortex (PFC) undergoes substantial maturation during this period, and PFC dysfunction is central to cognitive impairments in schizophrenia. As a result, impaired adolescent maturation of the PFC has been proposed as a mechanism in the etiology of the disorder and its cognitive symptoms. In adulthood, PFC function is tightly linked to its reciprocal connections with the thalamus, and acutely inhibiting thalamic inputs to the PFC produces impairments in PFC function and cognitive deficits. Here, we propose that thalamic activity is equally important during adolescence because it is required for proper PFC circuit development. Because thalamic abnormalities have been observed early in the progression of schizophrenia, we further postulate that adolescent thalamic dysfunction can have long-lasting consequences for PFC function and cognition in patients with schizophrenia.

QTLViewer: an interactive webtool for genetic analysis in the Collaborative Cross and Diversity Outbred mouse populations

The Collaborative Cross and the Diversity Outbred mouse populations are related multiparental populations, derived from the same 8 isogenic founder strains. They carry >50 M known genetic variants, which makes them ideal tools for mapping genetic loci that regulate phenotypes, including physiological and molecular traits. Mapping quantitative trait loci requires statistical and computational training, which can present a barrier to access for some researchers. The QTLViewer software allows users to graphically explore Collaborative Cross and Diversity Outbred quantitative trait locus mapping and related analyses performed through the R/qtl2 package. Additionally, the QTLViewer website serves as a repository for published Collaborative Cross and Diversity Outbred studies, increasing the accessibility of these genetic resources to the broader scientific community.

Working memory and pattern separation in founder strains of the BXD recombinant inbred mouse panel

Working memory and pattern separation are fundamental cognitive abilities which, when impaired, significantly diminish quality of life. Discovering genetic mechanisms underlying innate and disease-induced variation in these cognitive abilities is a critical step towards treatments for common and devastating neurodegenerative conditions such as Alzheimer's disease. In this regard, the trial-unique nonmatching-to-location assay (TUNL) is a touchscreen operant conditioning procedure allowing simultaneous quantification of working memory and pattern separation in mice and rats. In the present study, we used the TUNL assay to quantify these cognitive abilities in C57BL/6J and DBA/2J mice. These strains are the founders of the BXD recombinant inbred mouse panel which enables discovery of genetic mechanisms underlying phenotypic variation. TUNL testing revealed that pattern separation was significantly influenced by mouse strain, whereas working memory was not. Moreover, horizontal distance and vertical distance between choice-phase stimuli had dissociable effects on TUNL performance. These findings provide novel data on mouse strain differences in pattern separation and support previous findings of equivalent working memory performance in C57BL/6J and DBA/2J mice. Although working memory of the BXD founder strains was equivalent in this study, working memory of BXD strains may be divergent because of transgressive segregation. Collectively, data presented here indicate that pattern separation is heritable in the mouse and that the BXD panel can be used to identify mechanisms underlying variation in pattern separation.

A Study of Two-Way Short- and Long-Term Memory Network Intelligent Computing IoT Model-Assisted Home Education Attention Mechanism

This paper analyzes and collates the research on traditional homeschooling attention mechanism and homeschooling attention mechanism based on two-way short- and long-term memory network intelligent computing IoT model and finds the superiority of two-way short- and long-term memory network intelligent computing IoT model. The two-way short- and long-term memory network intelligent computing IoT model is improved and an improved deep neural network intelligent computing IoT is proposed, and the improved method is verified based on discrete signal homeschooling classification experiments, followed by focusing on the application research of the two-way short- and long-term memory network intelligent computing IoT model-assisted homeschooling attention mechanism. Learning based on neural network, human behavior recognition method combining spatiotemporal networks, a homeschooling method integrating bidirectional short- and long-term memory networks and attention mechanisms is designed. The visual attention mechanism is used to add weight information to the deep visual features extracted by the convolutional neural network, and a new feature sequence incorporating salient attention weights is output. This feature sequence is then decoded using an IndRNN independent recurrent neural network to finally classify and decide on the homeschooling category. Experiments on the UCF101 dataset demonstrate that the incorporation of the attention mechanism can improve the ability of the network to classify. The attention mechanism can help the intelligent computing IoT model discover key features, and the self-attention mechanism can effectively capture the internal features of homeschooling and optimize the feature vector. We propose the strategy of combining the self-attention mechanism with a bidirectional short- and long-term memory network to solve the family education classification problem and experimentally verify that the intelligent computing IoT model combined with the self-attention mechanism can more easily capture the interdependent features in family education, which can effectively solve the family education problem and further improve the family education classification accuracy.