Cell Type-specific Connections Research Articles

In vivo voltage-sensitive dye imaging of mouse cortical activity with mesoscopic optical tomography.

.Significance: Cellular layering is a hallmark of the mammalian neocortex with layer and cell type-specific connections within the cortical mantle and subcortical connections. A key challenge in studying circuit function within the neocortex is to understand the spatial and temporal patterns of information flow between different columns and layers.Aim: We aimed to investigate the three-dimensional (3D) layer- and area-specific interactions in mouse cortex in vivo.Approach: We applied a new promising neuroimaging method—fluorescence laminar optical tomography in combination with voltage-sensitive dye imaging (VSDi). VSDi is a powerful technique for interrogating membrane potential dynamics in assemblies of cortical neurons, but it is traditionally used for two-dimensional (2D) imaging. Our mesoscopic technique allows visualization of neuronal activity in a 3D manner with high temporal resolution.Results: We first demonstrated the depth-resolved capability of 3D mesoscopic imaging technology in Thy1-ChR2-YFP transgenic mice. Next, we recorded the long-range functional projections between sensory cortex (S1) and motor cortex (M1) in mice, in vivo, following single whisker deflection.Conclusions: The results show that mesoscopic imaging technique has the potential to investigate the layer-specific neural connectivity in the mouse cortex in vivo. Combination of mesoscopic imaging technique with optogenetic control strategy is a promising platform for determining depth-resolved interactions between cortical circuit elements.

Light Up the Brain: The Application of Optogenetics in Cell-Type Specific Dissection of Mouse Brain Circuits.

The exquisite intricacies of neural circuits are fundamental to an animal’s diverse and complex repertoire of sensory and motor functions. The ability to precisely map neural circuits and to selectively manipulate neural activity is critical to understanding brain function and has, therefore been a long-standing goal for neuroscientists. The recent development of optogenetic tools, combined with transgenic mouse lines, has endowed us with unprecedented spatiotemporal precision in circuit analysis. These advances greatly expand the scope of tractable experimental investigations. Here, in the first half of the review, we will present applications of optogenetics in identifying connectivity between different local neuronal cell types and of long-range projections with both in vitro and in vivo methods. We will then discuss how these tools can be used to reveal the functional roles of these cell-type specific connections in governing sensory information processing, and learning and memory in the visual cortex, somatosensory cortex, and motor cortex. Finally, we will discuss the prospect of new optogenetic tools and how their application can further advance modern neuroscience. In summary, this review serves as a primer to exemplify how optogenetics can be used in sophisticated modern circuit analyses at the levels of synapses, cells, network connectivity and behaviors.

Contextual Integration in Cortical and Convolutional Neural Networks

It has been suggested that neurons can represent sensory input using probability distributions and neural circuits can perform probabilistic inference. Lateral connections between neurons have been shown to have non-random connectivity and modulate responses to stimuli within the classical receptive field. Large-scale efforts mapping local cortical connectivity describe cell type specific connections from inhibitory neurons and like-to-like connectivity between excitatory neurons. To relate the observed connectivity to computations, we propose a neuronal network model that approximates Bayesian inference of the probability of different features being present at different image locations. We show that the lateral connections between excitatory neurons in a circuit implementing contextual integration in this should depend on correlations between unit activities, minus a global inhibitory drive. The model naturally suggests the need for two types of inhibitory gates (normalization, surround inhibition). First, using natural scene statistics and classical receptive fields corresponding to simple cells parameterized with data from mouse primary visual cortex, we show that the predicted connectivity qualitatively matches with that measured in mouse cortex: neurons with similar orientation tuning have stronger connectivity, and both excitatory and inhibitory connectivity have a modest spatial extent, comparable to that observed in mouse visual cortex. We incorporate lateral connections learned using this model into convolutional neural networks. Features are defined by supervised learning on the task, and the lateral connections provide an unsupervised learning of feature context in multiple layers. Since the lateral connections provide contextual information when the feedforward input is locally corrupted, we show that incorporating such lateral connections into convolutional neural networks makes them more robust to noise and leads to better performance on noisy versions of the MNIST dataset. Decomposing the predicted lateral connectivity matrices into low-rank and sparse components introduces additional cell types into these networks. We explore effects of cell-type specific perturbations on network computation. Our framework can potentially be applied to networks trained on other tasks, with the learned lateral connections aiding computations implemented by feedforward connections when the input is unreliable and demonstrate the potential usefulness of combining supervised and unsupervised learning techniques in real-world vision tasks.

Anterolateral Motor Cortex Connects with a Medial Subdivision of Ventromedial Thalamus through Cell Type-Specific Circuits, Forming an Excitatory Thalamo-Cortico-Thalamic Loop via Layer 1 Apical Tuft Dendrites of Layer 5B Pyramidal Tract Type Neurons.

The anterolateral motor cortex (ALM) and ventral medial (VM) thalamus are functionally linked to support persistent activity during motor planning. We analyzed the underlying synaptic interconnections using optogenetics and electrophysiology in mice (female/male). In cortex, thalamocortical (TC) axons from VM thalamus excited VM-projecting pyramidal tract (PT) neurons in layer 5B of ALM. These axons also strongly excited layer 2/3 neurons (which strongly excite PT neurons, as previously shown) but not VM-projecting corticothalamic (CT) neurons in layer 6. The strongest connections in the VM → PT circuit were localized to apical tuft dendrites of PT neurons, in layer 1. These tuft inputs were selectively augmented after blocking hyperpolarization-activated cyclic nucleotide-gated (HCN) channels. In thalamus, axons from ALM PT neurons excited ALM-projecting VM neurons, located medially in VM. These axons provided weak input to neurons in mediodorsal nucleus, and little or no input either to neurons in the GABAergic reticular thalamic nucleus or to neurons in VM projecting to primary motor cortex (M1). Conversely, M1 PT axons excited M1- but not ALM-projecting VM neurons. Our findings indicate, first, a set of cell type-specific connections forming an excitatory thalamo-cortico-thalamic loop for ALM ↔ VM communication and a circuit-level substrate for supporting reverberant activity in this system. Second, a key feature of this loop is the prominent involvement of layer 1 synapses onto apical dendrites, a subcellular compartment with distinct signaling properties, including HCN-mediated gain control. Third, the segregation of the ALM ↔ VM loop from M1-related circuits of VM adds cellular-level support for the concept of parallel pathway organization in the motor system.SIGNIFICANCE STATEMENT Anterolateral motor cortex (ALM), a higher-order motor area in the mouse, and ventromedial (VM) thalamus are anatomically and functionally linked, but their synaptic interconnections at the cellular level are unknown. Our results show that ALM pyramidal tract neurons monosynaptically excite ALM-projecting thalamocortical neurons in a medial subdivision of VM thalamus, and vice versa. The thalamo-cortico-thalamic loop formed by these recurrent connections constitutes a circuit-level substrate for supporting reverberant activity in this system.

A Large-Scale Gene Expression Intensity-Based Similarity Metric for Drug Repositioning

SummaryBiological systems often respond to a specific environmental or genetic perturbation without pervasive gene expression changes. Such robustness to perturbations, however, is not reflected on the current computational strategies that utilize gene expression similarity metrics for drug discovery and repositioning. Here we propose a new expression-intensity-based similarity metric that consistently achieved better performance than other state-of-the-art similarity metrics with respect to the gold-standard clustering of drugs with known mechanisms of action. The new metric directly emphasizes the genes exhibiting the greatest changes in expression in response to a perturbation. Using the new framework to systematically compare 3,332 chemical and 3,934 genetic perturbations across 10 cell types representing diverse cellular signatures, we identified thousands of recurrent and cell type-specific connections. We also experimentally validated two drugs identified by the analysis as potential topoisomerase inhibitors. The new framework is a valuable resource for hypothesis generation, functional testing, and drug repositioning.

Prefrontal Cortex Drives Distinct Projection Neurons in the Basolateral Amygdala

The prefrontal cortex (PFC) regulates emotional behavior via top-down control of the basolateral amygdala (BLA). However, the influence of PFC inputs on the different projection pathways within the BLA remains largely unexplored. Here, we combine whole-cell recordings and optogenetics to study these cell-type specific connections in mouse BLA.We characterize PFC inputs onto three distinct populations of BLA neurons that project to the PFC, ventral hippocampus, or nucleus accumbens. We find that PFC-evoked synaptic responses are strongest at amygdala-cortical and amygdala-hippocampal neurons and much weaker at amygdala-striatal neurons. We assess the mechanisms for this targeting and conclude that it reflects fewer connections onto amygdala-striatal neurons. Given the similar intrinsic properties of these cells, this connectivity allows the PFC to preferentially activate amygdala-cortical and amygdala-hippocampal neurons. Together, our findings reveal how PFC inputs to the BLA selectively drive feedback projections to the PFC and feedforward projections to the hippocampus.

Cell-type specific connectivity accounts for diverse in vivo functional roles of inhibitory neurons in V1

Inhibitory neurons have a large diversity [1], however functional roles of diverse subtypes have not been elucidated. We aim to help systematically addressing this question using large scale modeling and coarse graining between scales. Mesoscopic models of in vivo activity starting from structure have only recently become feasible making use of development of cortical column models [2], knowledge of connectivity [3,4], scalable simulation tools [NEST] and robust population statistic techniques [5]. Vasoactive intestinal peptide-positive (VIP+) interneurons are one of the major inhibitory cell types in the cortex [1], and their excitability has been found to be associated with various endogenous factors such as brain states and top-down signals. Zhang et al. [6] recently found that top-down signals originated in the cingulate (Cg) strongly innervate VIP + interneurons of V1, indicating the critical role of VIP+ cells in attentional gain modulation. We studied their effect on top-down signals using both analytical and computational models. Using a coarse-grained firing rate model for the cell types in the superficial layers we found that the reported cell-type specific connectivity allows top-down inputs to VIP+ interneurons to effectively disinhibit pyramidal cell activity. Due to the limitations of the firing rate model, we utilized large scale computational models to investigate mechanisms underlying attentional gain modulation in an entire network. Specifically, we adopted the multiple column model proposed by Wagatsuma et al. [4] and modified them by incorporating three inhibitory cell types into the superficial layers of the model. In our model we considered parvalbumin-positive (PV+), SST+ and VIP+ inhibitory cells. We also constructed the data-driven cell-type specific intercolumnar connections between columns. Our model was capable of reproducing multiplicative gain modulation (see Figure ​Figure1),1), and our simulation results suggest that non-specific activation of VIP cells is sufficient for generating multiplicative gain modulation. Figure 1 Simulated tuning curve for pyramidal neurons as a function of top-down inputs to VIP cells. These inputs allow a multiplicative gain modulation of the bottom-up input. We also note that PV+ cell-mediating inhibition across columns is critical for regulating the responses over small spatial scales: e.g. induced by non-preferred stimulus (orientation). SST+ cell mediate inhibition across columns and allow contextual visual processing in V1.

Synaptic Laminae in the Visual System: Molecular Mechanisms Forming Layers of Perception

Synaptic connections between neurons form the basis for perception and behavior. Synapses are often clustered in space, forming stereotyped layers. In the retina and optic tectum, multiple such synaptic laminae are stacked on top of each other, giving rise to stratified neuropil regions in which each layer combines synapses responsive to a particular sensory feature. Recently, several cellular and molecular mechanisms that underlie the development of multilaminar arrays of synapses have been discovered. These mechanisms include neurite guidance and cell-cell recognition. Molecules of the Slit, Semaphorin, Netrin, and Hedgehog families, binding to their matching receptors, bring axons and dendrites into spatial register. These guidance cues may diffuse over short distances or bind to sheets of extracellular matrix, thus conditioning the local extracellular milieu, or are presented on the surface of cells bordering the future neuropil. In addition, mutual recognition of axons and dendrites through adhesion molecules with immunoglobulin domains ensures cell type-specific connections within a given layer. Thus, an elaborate genetic program assembles the parallel processing channels that underlie visual perception.