scholarly journals A solution to temporal credit assignment using cell-type-specific modulatory signals

2020 ◽  
Author(s):  
Yuhan Helena Liu ◽  
Stephen Smith ◽  
Stefan Mihalas ◽  
Eric Shea-Brown ◽  
Uygar Sümbül
Keyword(s):  
Neuronal Cell ◽  
Learning Rule ◽  
Cell Types ◽  
Normative Theory ◽  
Cell Type ◽  
Computationally Efficient ◽  
Credit Assignment ◽  
Mathematical Basis ◽  
Cell Type Specific ◽  
Improved Learning

AbstractAnimals learn and form memories by jointly adjusting the efficacy of their synapses. How they efficiently solve the underlying temporal credit assignment problem remains elusive. Here, we re-analyze the mathematical basis of gradient descent learning in recurrent spiking neural networks (RSNNs) in light of the recent single-cell transcriptomic evidence for cell-type-specific local neuropeptide signaling in the cortex. Our normative theory posits an important role for the notion of neuronal cell types and local diffusive communication by enabling biologically plausible and efficient weight update. While obeying fundamental biological constraints, including separating excitatory vs inhibitory cell types and observing connection sparsity, we trained RSNNs for temporal credit assignment tasks spanning seconds and observed that the inclusion of local modulatory signaling improved learning efficiency. Our learning rule puts forth a novel form of interaction between modulatory signals and synaptic transmission. Moreover, it suggests a computationally efficient on-chip learning method for bio-inspired artificial intelligence.

scholarly journals Cell-type–specific neuromodulation guides synaptic credit assignment in a spiking neural network

2021 ◽  
Vol 118 (51) ◽  
pp. e2111821118
Author(s):  
Yuhan Helena Liu ◽  
Stephen Smith ◽  
Stefan Mihalas ◽  
Eric Shea-Brown ◽  
Uygar Sümbül
Keyword(s):  
Neural Network ◽  
Normative Theory ◽  
Synaptic Connections ◽  
Neuron Type ◽  
Cell Type ◽  
Credit Assignment ◽  
Neural Network Learning ◽  
Network Learning ◽  
Cell Type Specific ◽  
Synaptic Learning

Brains learn tasks via experience-driven differential adjustment of their myriad individual synaptic connections, but the mechanisms that target appropriate adjustment to particular connections remain deeply enigmatic. While Hebbian synaptic plasticity, synaptic eligibility traces, and top-down feedback signals surely contribute to solving this synaptic credit-assignment problem, alone, they appear to be insufficient. Inspired by new genetic perspectives on neuronal signaling architectures, here, we present a normative theory for synaptic learning, where we predict that neurons communicate their contribution to the learning outcome to nearby neurons via cell-type–specific local neuromodulation. Computational tests suggest that neuron-type diversity and neuron-type–specific local neuromodulation may be critical pieces of the biological credit-assignment puzzle. They also suggest algorithms for improved artificial neural network learning efficiency.

scholarly journals Complexity and graded regulation of neuronal cell-type–specific alternative splicing revealed by single-cell RNA sequencing

2021 ◽  
Vol 118 (10) ◽  
pp. e2013056118
Author(s):  
Huijuan Feng ◽  
Daniel F. Moakley ◽  
Shuonan Chen ◽  
Melissa G. McKenzie ◽  
Vilas Menon ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Single Cell ◽  
Neuronal Cell ◽  
Cell Types ◽  
Gabaergic Neurons ◽  
Cell Type ◽  
Differential Splicing ◽  
Single Cell Rna Sequencing ◽  
Hierarchical Levels ◽  
Cell Type Specific

The enormous cellular diversity in the mammalian brain, which is highly prototypical and organized in a hierarchical manner, is dictated by cell-type–specific gene-regulatory programs at the molecular level. Although prevalent in the brain, the contribution of alternative splicing (AS) to the molecular diversity across neuronal cell types is just starting to emerge. Here, we systematically investigated AS regulation across over 100 transcriptomically defined neuronal types of the adult mouse cortex using deep single-cell RNA-sequencing data. We found distinct splicing programs between glutamatergic and GABAergic neurons and between subclasses within each neuronal class. These programs consist of overlapping sets of alternative exons showing differential splicing at multiple hierarchical levels. Using an integrative approach, our analysis suggests that RNA-binding proteins (RBPs) Celf1/2, Mbnl2, and Khdrbs3 are preferentially expressed and more active in glutamatergic neurons, while Elavl2 and Qk are preferentially expressed and more active in GABAergic neurons. Importantly, these and additional RBPs also contribute to differential splicing between neuronal subclasses at multiple hierarchical levels, and some RBPs contribute to splicing dynamics that do not conform to the hierarchical structure defined by the transcriptional profiles. Thus, our results suggest graded regulation of AS across neuronal cell types, which may provide a molecular mechanism to specify neuronal identity and function that are orthogonal to established classifications based on transcriptional regulation.

scholarly journals Cell type-specific biotin labeling in vivo resolves regional neuronal proteomic differences in mouse brain

2021 ◽  
Author(s):  
Sruti Rayaprolu ◽  
Sara Bitarafan ◽  
Ranjita Betarbet ◽  
Sydney N Sunna ◽  
Lihong Cheng ◽  
...  
Keyword(s):  
Mouse Brain ◽  
Neurological Diseases ◽  
Neuronal Cell ◽  
Cell Types ◽  
Proteomic Profiling ◽  
Cell Type ◽  
Specific Expression ◽  
Cell Type Specific ◽  
The Brain

Isolation and proteomic profiling of brain cell types, particularly neurons, pose several technical challenges which limit our ability to resolve distinct cellular phenotypes in neurological diseases. Therefore, we generated a novel mouse line that enables cell type-specific expression of a biotin ligase, TurboID, via Cre-lox strategy for in vivo proximity-dependent biotinylation of proteins. Using adenoviral-based and transgenic approaches, we show striking protein biotinylation in neuronal cell bodies and axons throughout the mouse brain. We quantified more than 2,000 neuron-derived proteins following enrichment that mapped to numerous subcellular compartments. Synaptic, transmembrane transporters, ion channel subunits, and disease-relevant druggable targets were among the most significantly enriched proteins. Remarkably, we resolved brain region-specific proteomic profiles of Camk2a neurons with distinct functional molecular signatures and disease associations that may underlie regional neuronal vulnerability. Leveraging the neuronal specificity of this in vivo biotinylation strategy, we used an antibody-based approach to uncover regionally unique patterns of neuron-derived signaling phospho-proteins and cytokines, particularly in the cortex and cerebellum. Our work provides a proteomic framework to investigate cell type-specific mechanisms driving physiological and pathological states of the brain as well as complex tissues beyond the brain.

scholarly journals Single nucleus analysis of the chromatin landscape in mouse forebrain development

2017 ◽  
Author(s):  
Sebastian Preissl ◽  
Rongxin Fang ◽  
Yuan Zhao ◽  
Ramya Raviram ◽  
Yanxiao Zhang ◽  
...  
Keyword(s):  
Neuronal Cell ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Regulatory Sequences ◽  
Specific Cell ◽  
Cell Type ◽  
Tissue Samples ◽  
Forebrain Development ◽  
Cell Type Specific ◽  
Accessible Chromatin

ABSTRACTGenome-wide analysis of chromatin accessibility in primary tissues has uncovered millions of candidate regulatory sequences in the human and mouse genomes1–4. However, the heterogeneity of biological samples used in previous studies has prevented a precise understanding of the dynamic chromatin landscape in specific cell types. Here, we show that analysis of the transposase-accessible-chromatin in single nuclei isolated from frozen tissue samples can resolve cellular heterogeneity and delineate transcriptional regulatory sequences in the constituent cell types. Our strategy is based on a combinatorial barcoding assisted single cell assay for transposase-accessible chromatin5 and is optimized for nuclei from flash-frozen primary tissue samples (snATAC-seq). We used this method to examine the mouse forebrain at seven development stages and in adults. From snATAC-seq profiles of more than 15,000 high quality nuclei, we identify 20 distinct cell populations corresponding to major neuronal and non-neuronal cell-types in foetal and adult forebrains. We further define cell-type specific cis regulatory sequences and infer potential master transcriptional regulators of each cell population. Our results demonstrate the feasibility of a general approach for identifying cell-type-specific cis regulatory sequences in heterogeneous tissue samples, and provide a rich resource for understanding forebrain development in mammals.

scholarly journals Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains

2019 ◽  
Author(s):  
Ekaterina Khrameeva ◽  
Ilia Kurochkin ◽  
Dingding Han ◽  
Patricia Guijarro ◽  
Sabina Kanton ◽  
...  
Keyword(s):  
Gene Expression ◽  
Neuronal Cell ◽  
Cell Types ◽  
Brain Regions ◽  
Human Cognition ◽  
Human Lineage ◽  
Cell Type ◽  
Cell Nuclei ◽  
Tissue Samples ◽  
Cell Type Specific

ABSTRACTIdentification of gene expression traits unique to the human brain sheds light on the mechanisms of human cognition. Here we searched for gene expression traits separating humans from other primates by analyzing 88,047 cell nuclei and 422 tissue samples representing 33 brain regions of humans, chimpanzees, bonobos, and macaques. We show that gene expression evolves rapidly within cell types, with more than two-thirds of cell type-specific differences not detected using conventional RNA sequencing of tissue samples. Neurons tend to evolve faster in all hominids, but non-neuronal cell types, such as astrocytes and oligodendrocyte progenitors, show more differences on the human lineage, including alterations of spatial distribution across neocortical layers.

scholarly journals A Mammalian enhancer trap resource for discovering and manipulating neuronal cell types

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Yasuyuki Shima ◽  
Ken Sugino ◽  
Chris Martin Hempel ◽  
Masami Shima ◽  
Praveen Taneja ◽  
...  
Keyword(s):  
Expression Patterns ◽  
Neuronal Cell ◽  
Cell Types ◽  
Enhancer Trap ◽  
Marker Genes ◽  
Cell Type ◽  
Reporter Expression ◽  
Other Information ◽  
Bac Transgenesis ◽  
Cell Type Specific

There is a continuing need for driver strains to enable cell-type-specific manipulation in the nervous system. Each cell type expresses a unique set of genes, and recapitulating expression of marker genes by BAC transgenesis or knock-in has generated useful transgenic mouse lines. However, since genes are often expressed in many cell types, many of these lines have relatively broad expression patterns. We report an alternative transgenic approach capturing distal enhancers for more focused expression. We identified an enhancer trap probe often producing restricted reporter expression and developed efficient enhancer trap screening with the PiggyBac transposon. We established more than 200 lines and found many lines that label small subsets of neurons in brain substructures, including known and novel cell types. Images and other information about each line are available online (enhancertrap.bio.brandeis.edu).

scholarly journals De novo missense variants disrupting protein–protein interactions affect risk for autism through gene co-expression and protein networks in neuronal cell types

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Siwei Chen ◽  
Jiebiao Wang ◽  
Ercument Cicek ◽  
Kathryn Roeder ◽  
Haiyuan Yu ◽  
...  
Keyword(s):  
Protein Interactions ◽  
De Novo ◽  
Neuronal Cell ◽  
Cell Types ◽  
Neural Progenitor ◽  
Cell Type ◽  
Protein Protein Interactions ◽  
Missense Variants ◽  
Genes Encoding ◽  
Cell Type Specific

Abstract Background Whole-exome sequencing studies have been useful for identifying genes that, when mutated, affect risk for autism spectrum disorder (ASD). Nonetheless, the association signal primarily arises from de novo protein-truncating variants, as opposed to the more common missense variants. Despite their commonness in humans, determining which missense variants affect phenotypes and how remains a challenge. We investigate the functional relevance of de novo missense variants, specifically whether they are likely to disrupt protein interactions, and nominate novel genes in risk for ASD through integrated genomic, transcriptomic, and proteomic analyses. Methods Utilizing our previous interactome perturbation predictor, we identify a set of missense variants that are likely disruptive to protein–protein interactions. For genes encoding the disrupted interactions, we evaluate their expression patterns across developing brains and within specific cell types, using both bulk and inferred cell-type-specific brain transcriptomes. Connecting all disrupted pairs of proteins, we construct an “ASD disrupted network.” Finally, we integrate protein interactions and cell-type-specific co-expression networks together with published association data to implicate novel genes in ASD risk in a cell-type-specific manner. Results Extending earlier work, we show that de novo missense variants that disrupt protein interactions are enriched in individuals with ASD, often affecting hub proteins and disrupting hub interactions. Genes encoding disrupted complementary interactors tend to be risk genes, and an interaction network built from these proteins is enriched for ASD proteins. Consistent with other studies, genes identified by disrupted protein interactions are expressed early in development and in excitatory and inhibitory neuronal lineages. Using inferred gene co-expression for three neuronal cell types—excitatory, inhibitory, and neural progenitor—we implicate several hundred genes in risk (FDR $$\le \hspace{0.17em}$$ ≤ 0.05), ~ 60% novel, with characteristics of genuine ASD genes. Across cell types, these genes affect neuronal morphogenesis and neuronal communication, while neural progenitor cells show strong enrichment for development of the limbic system. Limitations Some analyses use the imperfect guilt-by-association principle; results are statistical, not functional. Conclusions Disrupted protein interactions identify gene sets involved in risk for ASD. Their gene expression during brain development and within cell types highlights how they relate to ASD.

scholarly journals Cell-Type Specific Responses to Associative Learning in the Primary Motor Cortex

2021 ◽  
Author(s):  
Candice Lee ◽  
Emerson Harkin ◽  
Richard Naud ◽  
Simon Chen
Keyword(s):  
Motor Cortex ◽  
Associative Learning ◽  
Primary Motor Cortex ◽  
Neuronal Cell ◽  
Cell Types ◽  
Skill Learning ◽  
Cell Type ◽  
Movement Initiation ◽  
Response Properties ◽  
Cell Type Specific

The primary motor cortex (M1) is known to be a critical site for movement initiation and motor learning. Surprisingly, it has also been shown to possess reward-related activity, presumably to facilitate reward-based learning of new movements. However, whether reward-related signals are represented among different cell types in M1, and whether their response properties change after cue-reward conditioning remains unclear. Here, we performed longitudinal in vivo two-photon Ca2+ imaging to monitor the activity of different neuronal cell types in M1 while mice engaged in a classical conditioning task. Our results demonstrate that most of the major neuronal cell types in M1 showed robust but differential responses to both cue and reward stimuli, and their response properties undergo cell-type specific modifications after associative learning. PV-INs' responses became more reliable to the cue stimulus, while VIP-INs' responses became more reliable to the reward stimulus. PNs only showed robust response to the novel reward stimulus, and they habituated to it after associative learning. Lastly, SOM-IN responses emerged and became more reliable to both conditioned cue and reward stimuli after conditioning. These observations suggest that cue- and reward-related signals are represented among different neuronal cell types in M1, and the distinct modifications they undergo during associative learning could be essential in triggering different aspects of local circuit reorganization in M1 during reward-based motor skill learning.

scholarly journals Connectivity characterization of the mouse basolateral amygdalar complex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Houri Hintiryan ◽  
Ian Bowman ◽  
David L. Johnson ◽  
Laura Korobkova ◽  
Muye Zhu ◽  
...  
Keyword(s):  
Granular Cell ◽  
Cell Types ◽  
Projection Neurons ◽  
Cell Type ◽  
Connectivity Map ◽  
Analysis Techniques ◽  
Domain Specific ◽  
Cell Type Specific ◽  
Unique Domain

AbstractThe basolateral amygdalar complex (BLA) is implicated in behaviors ranging from fear acquisition to addiction. Optogenetic methods have enabled the association of circuit-specific functions to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. Here, we apply machine-learning based computational and informatics analysis techniques to the results of circuit-tracing experiments to create a foundational, comprehensive BLA connectivity map. The analyses identify three distinct domains within the anterior BLA (BLAa) that house target-specific projection neurons with distinguishable morphological features. We identify brain-wide targets of projection neurons in the three BLAa domains, as well as in the posterior BLA, ventral BLA, posterior basomedial, and lateral amygdalar nuclei. Inputs to each nucleus also are identified via retrograde tracing. The data suggests that connectionally unique, domain-specific BLAa neurons are associated with distinct behavior networks.

scholarly journals Shisa6 mediates cell-type specific regulation of depression in the nucleus accumbens

2021 ◽  
Author(s):  
Hee-Dae Kim ◽  
Jing Wei ◽  
Tanessa Call ◽  
Nicole Teru Quintus ◽  
Alexander J. Summers ◽  
...  
Keyword(s):  
Nucleus Accumbens ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Current Treatment ◽  
Specific Cell ◽  
Excitatory Synapses ◽  
Cell Type ◽  
Cell Type Specific ◽  
Specific Regulation ◽  
Circuit Function

AbstractDepression is the leading cause of disability and produces enormous health and economic burdens. Current treatment approaches for depression are largely ineffective and leave more than 50% of patients symptomatic, mainly because of non-selective and broad action of antidepressants. Thus, there is an urgent need to design and develop novel therapeutics to treat depression. Given the heterogeneity and complexity of the brain, identification of molecular mechanisms within specific cell-types responsible for producing depression-like behaviors will advance development of therapies. In the reward circuitry, the nucleus accumbens (NAc) is a key brain region of depression pathophysiology, possibly based on differential activity of D1- or D2- medium spiny neurons (MSNs). Here we report a circuit- and cell-type specific molecular target for depression, Shisa6, recently defined as an AMPAR component, which is increased only in D1-MSNs in the NAc of susceptible mice. Using the Ribotag approach, we dissected the transcriptional profile of D1- and D2-MSNs by RNA sequencing following a mouse model of depression, chronic social defeat stress (CSDS). Bioinformatic analyses identified cell-type specific genes that may contribute to the pathogenesis of depression, including Shisa6. We found selective optogenetic activation of the ventral tegmental area (VTA) to NAc circuit increases Shisa6 expression in D1-MSNs. Shisa6 is specifically located in excitatory synapses of D1-MSNs and increases excitability of neurons, which promotes anxiety- and depression-like behaviors in mice. Cell-type and circuit-specific action of Shisa6, which directly modulates excitatory synapses that convey aversive information, identifies the protein as a potential rapid-antidepressant target for aberrant circuit function in depression.

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