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Functions of the neocortex depend on its bidirectional communication with the thalamus, via cortico-thalamo-cortical (CTC) loops. Recent work dissecting the synaptic connectivity in these loops is generating a clearer picture of their cellular organization. Here, we review findings across sensory, motor and cognitive areas, focusing on patterns of cell type-specific synaptic connections between the major types of cortical and thalamic neurons. We outline simple and complex CTC loops, and note features of these loops that appear to be general versus specialized. CTC loops are tightly interlinked with local cortical and corticocortical (CC) circuits, forming extended chains of loops that are probably critical for communication across hierarchically organized cerebral networks. Such CTC–CC loop chains appear to constitute a modular unit of organization, serving as scaffolding for area-specific structural and functional modifications. Inhibitory neurons and circuits are embedded throughout CTC loops, shaping the flow of excitation. We consider recent findings in the context of established CTC and CC circuit models, and highlight current efforts to pinpoint cell type-specific mechanisms in CTC loops involved in consciousness and perception. As pieces of the connectivity puzzle fall increasingly into place, this knowledge can guide further efforts to understand structure–function relationships in CTC loops.The neocortex and the thalamus are connected by looping circuits, enabling cortical function. In this Review, Gordon Shepherd and Naoki Yamawaki examine the patterns of connectivity between the major types of cortical and thalamic neurons and how these cortico-thalamo-cortical loops relate to corticocortical circuits.

Harris and Shepherd review our knowledge of input and output patterns for different classes of cortical cells. They propose that cortex, like other parts of the body, has a serially homologous organization, featuring area- and species-specific variations on a basic theme, that allows different types of function to emerge. Similarities in neocortical circuit organization across areas and species suggest a common strategy to process diverse types of information, including sensation from diverse modalities, motor control and higher cognitive processes. Cortical neurons belong to a small number of main classes. The properties of these classes, including their local and long-range connectivity, developmental history, gene expression, intrinsic physiology and in vivo activity patterns, are remarkably similar across areas. Each class contains subclasses; for a rapidly growing number of these, conserved patterns of input and output connections are also becoming evident. The ensemble of circuit connections constitutes a basic circuit pattern that appears to be repeated across neocortical areas, with area- and species-specific modifications. Such 'serially homologous' organization may adapt individual neocortical regions to the type of information each must process.

Key Points Corticostriatal (CStr) projections are formed by two distinct classes of cortical pyramidal neurons: intratelencephalic (IT) and pyramidal tract (PT) neurons. IT and PT neurons are highly differentiated at multiple levels, including long-range axonal projections, local cortical circuits, intrinsic electrical properties, neuromodulatory mechanisms and molecular profiles. Many neurological and neuropsychiatric diseases involve dysfunction in the CStr system. In several of these, evidence is accumulating for specific changes in the functional properties of IT and PT neurons and their circuits. Autism appears to involve changes especially in IT neurons and networks. Amyotrophic lateral sclerosis involves degeneration of corticospinal neurons, a major subtype of PT neurons. In Parkinson's disease, a hypokinetic movement disorder, PT neurons are particularly implicated in the disease process. The therapeutic efficacy of deep brain stimulation in the subthalamic nucleus has been ascribed to antidromic activation of PT neurons in the cortex. In Huntington's disease, a hyperkinetic movement disorder, CStr changes suggest both IT and PT involvement. CStr changes are prominent in neuropsychiatric disorders such as schizophrenia and obsessive-compulsive disorder. In major depression, animal studies point to IT specificity. Collectively the evidence suggests that 'IT/PT imbalance' may be a useful concept for guiding further research into diseases involving CStr dysfunction. The distinct properties of IT and PT neurons present abundant opportunities for developing cell type-specific interventions in these disorders. Corticostriatal pathways consist of two distinct classes of cortical pyramidal cells: intratelencephalic and pyramidal tract neurons. In this Review, Shepherd explains how changes in the functional properties of these neurons result in an imbalance in activity that contributes to a wide variety of neurological disorders. Corticostriatal projections are essential components of forebrain circuits and are widely involved in motivated behaviour. These axonal projections are formed by two distinct classes of cortical neurons, intratelencephalic (IT) and pyramidal tract (PT) neurons. Convergent evidence points to IT versus PT differentiation of the corticostriatal system at all levels of functional organization, from cellular signalling mechanisms to circuit topology. There is also growing evidence for IT/PT imbalance as an aetiological factor in neurodevelopmental, neuropsychiatric and movement disorders — autism, amyotrophic lateral sclerosis, obsessive-compulsive disorder, schizophrenia, Huntington's and Parkinson's diseases and major depression are highlighted here.

Hippocampus, granular retrosplenial cortex (RSCg), and anterior thalamic nuclei (ATN) interact to mediate diverse cognitive functions. To identify cellular mechanisms underlying hippocampo–thalamo–retrosplenial interactions, we investigated the potential circuit suggested by projections to RSCg layer 1 (L1) from GABAergic CA1 neurons and ATN. We find that CA1→RSCg projections stem from GABAergic neurons with a distinct morphology, electrophysiology, and molecular profile. Their long-range axons inhibit L5 pyramidal neurons in RSCg via potent synapses onto apical tuft dendrites in L1. These inhibitory inputs intercept L1-targeting thalamocortical excitatory inputs from ATN to coregulate RSCg activity. Subicular axons, in contrast, excite proximal dendrites in deeper layers. Short-term plasticity differs at each connection. Chemogenetically abrogating CA1→RSCg or ATN→RSCg connections oppositely affects the encoding of contextual fear memory. Our findings establish retrosplenial-projecting CA1 neurons as a distinct class of long-range dendrite-targeting GABAergic neuron and delineate an unusual cortical circuit specialized for integrating long-range inhibition and thalamocortical excitation.Apical tuft dendrites of pyramidal neurons in retrosplenial cortex receive inhibition from a class of CA1 GABAergic neurons with long-range layer 1-targeting axons; this inhibition opposes matrix-type thalamocortical excitation from anterior thalamus.

Rodents move their whiskers to locate and identify objects. Cortical areas involved in vibrissal somatosensation and sensorimotor integration include the vibrissal area of the primary motor cortex (vM1), primary somatosensory cortex (vS1; barrel cortex), and secondary somatosensory cortex (S2). We mapped local excitatory pathways in each area across all cortical layers using glutamate uncaging and laser scanning photostimulation. We analyzed these maps to derive laminar connectivity matrices describing the average strengths of pathways between individual neurons in different layers and between entire cortical layers. In vM1, the strongest projection was L2/3→L5. In vS1, strong projections were L2/3→L5 and L4→L3. L6 input and output were weak in both areas. In S2, L2/3→L5 exceeded the strength of the ascending L4→L3 projection, and local input to L6 was prominent. The most conserved pathways were L2/3→L5, and the most variable were L4→L2/3 and pathways involving L6. Local excitatory circuits in different cortical areas are organized around a prominent descending pathway from L2/3→L5, suggesting that sensory cortices are elaborations on a basic motor cortex-like plan.

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis – connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena. The approximately 100 billion neurons in our brain are responsible for everything we do and experience. Experiments aimed at discovering how these cells encode and process information generate vast amounts of data. These data span multiple scales, from interactions between individual molecules to coordinated waves of electrical activity that spread across the entire brain surface. To understand how the brain works, we must combine and make sense of these diverse types of information. Computational modeling provides one way of doing this. Using equations, we can calculate the chemical and electrical changes that take place in neurons. We can then build models of neurons and neural circuits that reproduce the patterns of activity seen in experiments. Exploring these models can provide insights into how the brain itself works. Several software tools are available to simulate neural circuits, but none provide an easy way of incorporating data that span different scales, from molecules to cells to networks. Moreover, most of the models require familiarity with computer programming. Dura-Bernal et al. have now developed a new software tool called NetPyNE, which allows users without programming expertise to build sophisticated models of brain circuits. It features a user-friendly interface for defining the properties of the model at molecular, cellular and circuit scales. It also provides an easy and automated method to identify the properties of the model that enable it to reproduce experimental data. Finally, NetPyNE makes it possible to run the model on supercomputers and offers a variety of ways to visualize and analyze the resulting output. Users can save the model and output in standardized formats, making them accessible to as many people as possible. Researchers in labs across the world have used NetPyNE to study different brain regions, phenomena and diseases. The software also features in courses that introduce students to neurobiology and computational modeling. NetPyNE can help to interpret isolated experimental findings, and also makes it easier to explore interactions between brain activity at different scales. This will enable researchers to decipher how the brain encodes and processes information, and ultimately could make it easier to understand and treat brain disorders.

Optically controlled nongenetic neuromodulation represents a promising approach for the fundamental study of neural circuits and the clinical treatment of neurological disorders. Among the existing material candidates that can transduce light energy into biologically relevant cues, silicon (Si) is particularly advantageous due to its highly tunable electrical and optical properties, ease of fabrication into multiple forms, ability to absorb a broad spectrum of light, and biocompatibility. This protocol describes a rational design principle for Si-based structures, general procedures for material synthesis and device fabrication, a universal method for evaluating material photoresponses, detailed illustrations of all instrumentation used, and demonstrations of optically controlled nongenetic modulation of cellular calcium dynamics, neuronal excitability, neurotransmitter release from mouse brain slices, and brain activity in the mouse brain in vivo using the aforementioned Si materials. The entire procedure takes ~4–8 d in the hands of an experienced graduate student, depending on the specific biological targets. We anticipate that our approach can also be adapted in the future to study other systems, such as cardiovascular tissues and microbial communities.This protocol describes how to fabricate and apply silicon-based structures for optically controlled neuromodulation. The structures can be used for nongenetic neuronal excitation in cultured neurons, brain slices, and in vivo applications.