Biology subjects

Wang, X.-J.

Publications and source records attributed to Wang, X.-J..

At least 55 records · Page 3Linked to original sources

bioRxiv2020

A dopamine gradient controls access to distributed working memory in monkey cortex

Dopamine is critical for working memory. However, its effects throughout the large-scale primate cortex are poorly understood. Here we report that dopamine receptor density per neuron, measured by receptor autoradiography in the macaque monkey cortex, displays a macroscopic gradient along the cortical hierarchy. We developed a connectome- and biophysically-based model for distributed working memory that incorporates multiple neuron types and a dopamine gradient. The model captures an inverted U-shaped dependence of working memory on dopamine. The spatial distribution of mnemonic persistent activity matches that observed in over 90 experimental studies. We show that dopamine filters out irrelevant stimuli by enhancing inhibition of pyramidal cell dendrites. The level of cortical dopamine can also determine whether memory encoding is through persistent activity or an internal synaptic state. Taken together, our work represents a cross-level understanding that links molecules, cell types, recurrent circuit dynamics and a core cognitive function distributed across the cortex.

neuroscience↗

bioRxiv2020

A neural circuit mechanism of categorical perception: top-down signaling in the primate cortex

In contrast to feedforward architecture commonly used in deep networks at the core of todays AI revolution, the biological cortex is endowed with an abundance of feedback projections. Feedback signaling is often difficult to differentially identify, and its computational roles remain poorly understood. Here, we investigated a cognitive phenomenon, called categorical perception (CP), that reveals the influences of high-level category learning on low-level feature-based perception, as a putative signature of top-down signaling. By examining behavioral data from a visual motion delayed matching experiment in non-human primates, we found that, after categorization training, motion directions closer to (respectively, away from) a category center became more (less) difficult to discriminate. This distance-dependent discrimination performance change along the dimension relevant to the learned categories provides direct evidence for the CP phenomenon. To explain this experimental finding, we developed a neural circuit model that incorporated key neurophysiological findings in visual categorization, working memory and decision making. Our model accounts for the behavioral data indicative of CP, pinpoints its circuit basis, suggests novel experimentally testable predictions and provides a functional explanation for its existence. Our work shows that delayed matching paradigms in non-human primates combined with biologically-based modeling can serve as a promising model system for elucidating the neural mechanisms of CP, as a manifestation of top-down signaling in the cortex. Significant StatementCategorical perception is a cognitive phenomenon revealing the influences of high-level category learning on low-level feature-based perception. However, its underlying neural mechanisms are largely unknown. Here, we found behavioral evidence for this phenomenon from a visual motion delayed matching experiment in non-human primates. We developed a neural circuit model that can account for this behavioral data, pinpoints its circuit basis, suggests novel experimentally testable predictions and provides a functional explanation for its existence. Our work shows that delayed matching paradigms in non-human primates combined with biologically-based modeling can serve as a promising model system for elucidating the neural mechanisms of categorical perception, as a manifestation of top-down signaling in the cortex.

neuroscience↗

bioRxiv2020

Cortical Hierarchy and The Dual Counterstream Architecture.

Hierarchy is a major organizational principle of the cortex and underscores modern computational theories of cortical function. The local microcircuit amplifies long-distance inter-areal input, which show distance-dependent changes in their laminar profiles. Statistical modeling of these changes in laminar profiles demonstrates that inputs from multiple hierarchical levels to their target areas show remarkable consistency, allowing the construction of a cortical hierarchy based on a principle of hierarchical distance. The statistical modeling that is applied to structure can also be applied to laminar differences in the oscillatory coherence between areas thereby determining a functional hierarchy of the cortex. Close examination of the anatomy of inter-areal connectivity reveals a dual counterstream architecture with well-defined distance-dependent feedback and feedforward pathways in both the supra- and infragranular layers, suggesting a multiplicity of feedback pathways with well-defined functional properties. These findings are consistent with feedback connections providing a generative network involved in a wide range of cognitive functions. A dynamical model constrained by connectivity data shed insights into the experimentally observed signatures of frequency-dependent Granger causality for feedforward versus feedback signaling. Concerted experiments capitalizing on recent technical advances and combining tract-tracing, high-resolution fMRI, optogenetics and mathematical modeling hold the promise of a much improved understanding of lamina-constrained mechanisms of neural computation and cognition. However, because inter-areal interactions involve cortical layers that have been the target of important evolutionary changes in the primate lineage, these investigations will need to include human and non-human primates comparisons. PlanO_LIIntroduction C_LIO_LIHierarchy - signatures of inputs to the local circuits. C_LIO_LIModels of hierarchy C_LIO_LIHierarchy - input consistency C_LIO_LIDual stream architecture. C_LIO_LIFunctional characteristics of FF and FB pathways. C_LIO_LIThe predictive brain and the importance of top-down generative networks. C_LIO_LIConclusion. C_LI

neuroscience↗

bioRxiv2020

An Xist-dependent protein assembly mediates Xist localization and gene silencing

Nuclear compartments play diverse roles in regulating gene expression, yet the molecular forces and components driving compartment formation are not well understood. Studying how the lncRNA Xist establishes the inactive-X-chromosome (Xi)-compartment, we found that the Xist RNA-binding-proteins PTBP1, MATR3, TDP43, and CELF1 form a condensate to create an Xi-domain that can be sustained in the absence of Xist. The E-repeat-sequence of Xist serves a multivalent binding-platform for these proteins. Without the E-repeat, Xist initially coats the X-chromosome during XCI onset but subsequently disperses across the nucleus with loss of gene silencing. Recruitment of PTBP1, MATR3, TDP-43 or CELF1 to {Delta}E-Xist rescues these phenotypes, and requires both self-association of MATR3 and TDP-43 and a heterotypic PTBP1-MATR3-interaction. Together, our data reveal that Xist sequesters itself within the Xi-territory and perpetuates gene silencing by seeding a protein-condensate. Our findings uncover an unanticipated mechanism for epigenetic memory and elucidate the interplay between RNA and RNA-binding-proteins in creating compartments for gene regulation.

molecular biology↗

bioRxiv2020

Structural attributes and principles of the neocortical connectome in the marmoset monkey

The marmoset monkey has become an important primate model in Neuroscience. Here we characterize salient statistical properties of inter-areal connections of the marmoset cerebral cortex, using data from retrograde tracer injections. We found that the connectivity weights are highly heterogeneous, spanning five orders of magnitude, and are log-normally distributed. The cortico-cortical network is dense, heterogeneous and has high specificity. The reciprocal connections are the most prominent and the probability of connection between two areas decays with their functional dissimilarity. The laminar dependence of connections defines a hierarchical network correlated with microstructural properties of each area. The marmoset connectome reveals parallel streams associated with different sensory systems. Finally, the connectome is spatially embedded with a characteristic length that obeys a power law as a function of brain volume across species. These findings provide a connectomic basis for investigations of multiple interacting areas in a complex large-scale cortical system underlying cognitive processes.

neuroscience↗

bioRxiv2020

Plastid EF-Tu Regulates Root Development through Both the ATM Pathway and GUN1

Impaired plastid translation affects various aspects of plant development, but the molecular mechanism remains elusive. Here, we described that the reduced function of plastid translation elongation factor EF-Tu encoded by RAB GTPASE HOMOLOG 8D (Rab8d) elicits defects in root development, including the reduced meristem size, programmed cell death (PCD) in the stem cell niche (SCN), and quiescent center (QC) division. We found that the ATAXIA-TELANGIECTASIA-MUTATED (ATM)-SUPPRESSOR OF GAMMA RESPONSE 1 module mediated overexpression of SIAMSE-RELATED 5 in the root meristem region is responsible for the reduced meristem size in the rab8d mutant through arresting the cell cycle. The QC activation in rab8d is dependent on ETHYLENE RESPONSE FACTOR 115, which expression is tightly associated with the PCD in SCN. We further found that Rab8d physically interacts with GENOME UNCOUPLED 1 (GUN1), and GUN1 is required for inducing PCD in the rab8d SCN. However, the loss of GUN1 function in rab8d severely impairs the root architecture, suggesting that the GUN1-mediated renewal of stem cells is essential for maintaining root growth. Our observations extend our knowledge on the roles of ATM and GUN1 in regulating root development through mediating plastid translation dependent signals. One-sentence summaryThe rab8d-dependent plastid signal mediated by ATM and GUN1 regulates the root meristem size and renewal of root stem cells, respectively.

plant biology↗

bioRxiv2020

Hierarchical Network Model Excitatory-Inhibitory Tone Shapes Alternative Strategies for Different Degrees of Uncertainty in Multi-Attribute Decisions

We investigated two-attribute, two-alternative decision-making in a hierarchical neural network with three layers: an input layer encoding choice alternative attribute values; an intermediate layer of modules processing separate attributes; and a choice layer producing the decision. Depending on intermediate layer excitatory-inhibitory (E/I) tone, the network displays three distinct regimes characterized by linear (I), convex (II) or concave (III) choice indifference curves. In regimes I and II, each options attribute information is additively integrated. To maximize reward at low environmental uncertainty, the system should operate in regime I. At high environmental uncertainty, reward maximization is achieved in regime III, with each attribute module selecting a favored alternative, and the ultimate decision based upon comparison between outputs of attribute processing modules. We then use these principles to examine multi-attribute decisions with autism-related deficits in E/I balance, leading to predictions of different choice patterns and overall performance between autism and neurotypicals.

neuroscience↗

bioRxiv2020

Potential inhibitors for 2019-nCoV coronavirus M protease from clinically approved medicines

Starting from December 2019, a novel coronavirus, named 2019-nCoV, was found to cause Severe Acute Respiratory (SARI) symptoms and rapid pandemic in China. With the hope to identify candidate drugs for 2019-nCoV, we adopted a computational approach to screen for available commercial medicines which may function as inhibitors for the Mpro of 2019-nCoV. Up to 10 commercial medicines that may form hydrogen bounds to key residues within the binding pocket of 2019-nCoV Mpro were identified, which may have higher mutation tolerance than lopinavir/ritonavir and may also function as inhibitors for other coronaviruses with similar Mpro binding sites and pocket structures.

bioinformatics↗

bioRxiv2019

Mechanisms of distributed working memory in a large-scale model of the macaque neocortex

To elucidate the circuit mechanism of persistent neural activity underlying working memory that is distributed across multiple brain regions, we developed an anatomically constrained computational model of large-scale macaque cortex. We found that persistent activity may emerge from inter-areal reverberation, even in a regime where none of the isolated areas is capable of generating persistent activity. The persistent activity pattern along the cortical hierarchy indicates a robust bifurcation in space, characterized by a few association areas near dynamical criticality. A host of spatially distinct attractor states is found, potentially subserving various internal processes. The model yields testable predictions including the idea of counterstream inhibitory bias, and suggests experiments to differentiate local versus distributed mechanisms. Simulated lesion or optogenetic inactivation revealed that distributed activity patterns are resilient while dependent on a structural core. This work provides a theoretical framework for identifying large-scale brain mechanisms and computational principles of distributed cognitive processes.

neuroscience↗

bioRxiv2019

EuRBPDB: a comprehensive resource for annotation, functional and oncological investigation of eukaryotic RNA binding proteins (RBPs)

RNA binding proteins (RBPs) are a large protein family that plays important roles at almost all levels of gene regulation through interacting with RNAs, and contributes to numerous biological processes. However, the complete list of eukaryotic RBPs including human is still unavailable. In this study, we systematically identified RBPs in 162 eukaryotic species based on both computational analysis of RNA binding domains (RBDs) and large-scale RNA binding proteomic (RBPome) data, and established a comprehensive eukaryotic RBP database, EuRBPDB (http://EuRBPDB.syshospital.org:8081). We identified a total of 311,571 RBPs with RBDs and 3,639 non-canonical RBPs without known RBDs. EuRBPDB provides detailed annotations for each RBP, including basic information and functional annotation. Moreover, we systematically investigated RBPs in the context of cancer biology based on published literatures and large-scale omics data. To facilitate the exploration of the clinical relevance of RBPs, we additionally designed a cancer web interface to systematically and interactively display the biological features of RBPs in various types of cancers. EuRBPDB has a user-friendly web interface with browse and search functions, as well as data downloading function. We expect that EuRBPDB will be a widely-used resource and platform for the RNA biology community.

bioinformatics↗

bioRxiv2018

Multimodal gradients across mouse cortex

The primate cerebral cortex displays a hierarchical organization that extends from primary sensorimotor to association areas, supporting increasingly integrated function that is underpinned by a gradient of heterogeneity in the brain s microcircuits. The extent to which these properties of brain organization are unique to primate or may be conserved across mammals remains unknown. Here we report the topographic similarity of large-scale gradients in cytoarchitecture, brain-related gene expression, interneuron cell densities, and long-range axonal connectivity, which vary from primary sensory through to prefrontal areas of mouse cortex, highlighting an underappreciated spatial dimension of mouse cortical specialization. Using the T1w:T2w magnetic resonance imaging (MRI) map as a common spatial reference for comparison across species, we report interspecies agreement in a range of cortical gradients, including a significant correspondence between gene transcriptional maps in mouse cortex with their human orthologs in human cortex. The interspecies correspondence of large-scale cortical gradients suggests that a conserved anatomical organization may underlie hierarchical specialization in mammalian brains.

neuroscience↗

bioRxiv2018

Engagement of pulvino-cortical feedforward and feedback pathways in cognitive computations

Computational modeling of brain mechanisms of cognition has been largely focused on the cortex, but recent experiments have shown that higher-order nuclei of the thalamus, in particular the pulvinar, participate in major cognitive functions and are implicated in psychiatric disorders. Here we show that a pulvino-cortical circuit model, composed of two cortical areas and the pulvinar, captures a range of physiological and behavioral observations related to the macaque pulvinar. Effective connections between the two cortical areas are gated by the pulvinar, allowing the pulvinar to shift the operation regime of these areas during attentional processing and working memory, as well as to resolve decision-making conflict. Furthermore, cortico-pulvinar projections that engage the thalamic reticular nucleus enable the pulvinar to estimate decision-making confidence. Finally, feedforward and feedback pulvino-cortical pathways participate in frequency-dependent inter-areal interactions that modify the relative hierarchical positions of cortical areas. Overall, our model suggests that the pulvinar provides crucial contextual modulation to cortical computations associated with cognition.

neuroscience↗

bioRxiv2018

Circuit mechanisms for the maintenance and manipulation of information in working memory

Recently it has been proposed that information in short-term memory may not always be stored in persistent neuronal activity, but can be maintained in \"activity-silent\" hidden states such as synaptic efficacies endowed with short-term plasticity (STP). However, working memory involves manipulation as well as maintenance of information in the absence of external stimuli. In this work, we investigated working memory representation using recurrent neural network (RNN) models trained to perform several working memory dependent tasks. We found that STP can support the short-term maintenance of information provided that the memory delay period is sufficiently short. However, in tasks that require actively manipulating information, persistent neuronal activity naturally emerges from learning, and the amount of persistent neuronal activity scales with the degree of manipulation required. These results shed insight into the current debate on working memory encoding, and suggest that persistent neural activity can vary markedly between tasks used in different experiments.

neuroscience↗

bioRxiv2018

Polypyrimidine Tract Binding Protein blocks microRNA-124 biogenesis to enforce its neuronal specific expression.

MicroRNA-124 is expressed in neurons, where it represses genes inhibitory for neuronal differentiation, including the RNA binding protein PTBP1. PTBP1 maintains non-neuronal splicing patterns of mRNAs that switch to neuronal isoforms upon neuronal differentiation. We find that pri-miR-124-1 is expressed in mouse embryonic stem cells (mESCs) where mature miR-124 is absent. PTBP1 binds to this precursor RNA upstream of the miRNA stem-loop to inhibit mature miR-124 expression in vivo, and DROSHA cleavage of pri-miR-124-1 in vitro. This new function for PTBP1 in repressing miR-124 biogenesis adds an additional regulatory loop to the already intricate interplay between these two molecules. Applying mathematical modeling to examine the dynamics of this regulation, we find that the pool of pri-miR-124 whose maturation is blocked by PTBP1 creates a robust and self-reinforcing transition in gene expression as PTBP1 is depleted during early neuronal differentiation. While interlocking regulatory loops are often modeled between miRNAs and transcriptional regulators, our results indicate that miRNA targeting of posttranscriptional regulators also reinforces developmental decisions. Notably, induction of neuronal differentiation observed upon PTBP1 knockdown likely results from direct de-repression of miR-124, in addition to indirect effects previously described.

molecular biology↗

bioRxiv2017

Propagation of spike timing and firing rate in feedforward networks reconstituted in vitro

The manner in which information is transferred and transformed across brain regions is yet unclear. Theoretical analyses of idealized feedforward networks suggest that several conditions have to be satisfied in order for activity to propagate faithfully across layers. Verifying these concepts experimentally in networks has not been possible owing to the vast number of variables that must be controlled. Here, we culture cortical neurons in a chamber with sequentially connected compartments, optogenetically stimulate individual neurons in the first layer with high spatiotemporal resolution, and monitor the subthreshold and suprathreshold potentials in subsequent layers. In the first layer, a brief stimulus with different temporal precisions resulted in the modulation of the firing rate. This temporal to rate transformation was propagated to other layers as a sustained response, thereby preserving rate information. This novel mode of propagation occurred in the balanced excitatory-inhibitory regime and is mediated by NMDA-mediated synapses activated by recurrent activity.

neuroscience↗

bioRxiv2017

Inter-areal balanced amplification enhances signal propagation in a large-scale circuit model of the primate cortex

Reliable signal transmission represents a fundamental challenge for cortical systems, which display a wide range of weights of feedforward and feedback connections among heterogeneous areas. We re-examine the question of signal transmission across the cortex in network models based on recently available mesoscopic, directed- and weighted-inter-areal connectivity data of the macaque cortex. Our findings reveal that, in contrast to feed-forward propagation models, the presence of long-range excitatory feedback projections could compromise stable signal propagation. Using population rate models as well as a spiking network model, we find that effective signal propagation can be accomplished by balanced amplification across cortical areas while ensuring dynamical stability. Moreover, the activation of prefrontal cortex in our model requires the input strength to exceed a threshold, in support of the ignition model of conscious processing, demonstrating our model as an anatomically-realistic platform for investigations of the global primate cortex dynamics.

neuroscience↗

bioRxiv2017

Clustering and compositionality of task representations in a neural network trained to perform many cognitive tasks

A neural system has the ability to flexibly perform many tasks, but the underlying mechanism cannot be elucidated in traditional experimental and modeling studies designed for one task at a time. Here, we trained a single network model to perform 20 cognitive tasks that may involve working memory, decision-making, categorization and inhibitory control. We found that after training, recurrent units developed into clusters that are functionally specialized for various cognitive processes. We introduce a measure to quantify relationships between single-unit neural representations of tasks, and report five distinct types of such relationships that can be tested experimentally. Surprisingly, our network developed compositionality of task representations, a critical feature for cognitive flexibility, whereby one task can be performed by recombining instructions for other tasks. Finally, we demonstrate how the network could learn multiple tasks sequentially. This work provides a computational platform to investigate neural representations of many cognitive tasks.

neuroscience↗

bioRxiv2017

Response Reversal During Top-Down Modulation In Cortical Circuits With Multiple Interneuron Types

Pyramidal cells and interneurons expressing parvalbumin, somatostatin, or vasoactive intestinal peptide show cell type-specific connectivity patterns leading to a canonical microcircuit across cortex. Dissecting the dynamics of this microcircuit is essential to our understanding of the mammalian cortex. However, experiments recording from this circuit often report counterintuitive and seemingly contradictory findings. For example, the response of a V1 neural population to top-down behavioral modulation can reverse from positive to negative when the bottom-up thalamic input changes. We developed a theoretical framework to explain such response reversal, and we showed how this complex dynamics can emerge in circuits that possess two key features: the presence of multiple interneuron populations and a non-linear dependence between the input and output of the populations. Furthermore, we built a cortical circuit model and the comparison of our simulations with real data shows that our model reproduces the complex dynamics observed experimentally in mouse V1. Our explicit calculations allowed us to pinpoint the connections critical to response reversal, and to predict the existence of more types of complex dynamics that could be experimentally tested and the conditions to observe them.

neuroscience↗