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With advances in connectomics, transcriptome and neurophysiological technologies, the neuroscience of brain-wide neural circuits is poised to take off. A major challenge is to understand how a vast diversity of functions is subserved by parcellated areas of mammalian neocortex composed of repetitions of a canonical local circuit. Areas of the cerebral cortex differ from each other not only in their input–output patterns but also in their biological properties. Recent experimental and theoretical work has revealed that such variations are not random heterogeneities; rather, synaptic excitation and inhibition display systematic macroscopic gradients across the entire cortex, and they are abnormal in mental illness. Quantitative differences along these gradients can lead to qualitatively novel behaviours in non-linear neural dynamical systems, by virtue of a phenomenon mathematically described as bifurcation. The combination of macroscopic gradients and bifurcations, in tandem with biological evolution, development and plasticity, provides a generative mechanism for functional diversity among cortical areas, as a general principle of large-scale cortical organization.Certain biological properties vary across different areas of the cerebral cortex. In this Perspective, Xiao-Jing Wang proposes that macroscopic gradients in some properties align with functional hierarchy and can lead to qualitative differences in function.

In 2003 Rubenstein and Merzenich hypothesized that some forms of Autism (ASD) might be caused by a reduction in signal-to-noise in key neural circuits, which could be the result of changes in excitatory-inhibitory (E-I) balance. Here, we have clarified the concept of E-I balance, and updated the original hypothesis in light of the field’s increasingly sophisticated understanding of neuronal circuits. We discuss how specific developmental mechanisms, which reduce inhibition, affect cortical and hippocampal functions. After describing how mutations of some ASD genes disrupt inhibition in mice, we close by suggesting that E-I balance represents an organizing framework for understanding findings related to pathophysiology and for identifying appropriate treatments.

Two-photon calcium imaging and electron microscopy were used to explore the relationship between structure and function in mouse primary visual cortex, showing that layer 2/3 neurons are connected in subnetworks, that pyramidal neurons with similar orientation selectivity preferentially form synapses with each other, and that neurons with similar orientation tuning form larger synapses; this study exemplifies functional connectomics as a powerful method for studying the organizational logic of cortical networks. The connectomics of excitatory cortical networks To explore the relationship between structure and function in cortical networks, Wei-Chung Allen Lee and colleagues combined two-photon calcium imaging and electron microscopy in mouse primary visual cortex. They found that layer 2/3 neurons are organized into subnetworks, that pyramidal neurons with similar orientation selectivity preferentially form synapses with each other, and that neurons with similar orientation tuning form larger synapses. This study exemplifies functional connectomics as a powerful method for studying the organizational logic of cortical networks. Circuits in the cerebral cortex consist of thousands of neurons connected by millions of synapses. A precise understanding of these local networks requires relating circuit activity with the underlying network structure. For pyramidal cells in superficial mouse visual cortex (V1), a consensus is emerging that neurons with similar visual response properties excite each other 1 , 2 , 3 , 4 , 5 , but the anatomical basis of this recurrent synaptic network is unknown. Here we combined physiological imaging and large-scale electron microscopy to study an excitatory network in V1. We found that layer 2/3 neurons organized into subnetworks defined by anatomical connectivity, with more connections within than between groups. More specifically, we found that pyramidal neurons with similar orientation selectivity preferentially formed synapses with each other, despite the fact that axons and dendrites of all orientation selectivities pass near (<5 μm) each other with roughly equal probability. Therefore, we predict that mechanisms of functionally specific connectivity take place at the length scale of spines. Neurons with similar orientation tuning formed larger synapses, potentially enhancing the net effect of synaptic specificity. With the ability to study thousands of connections in a single circuit, functional connectomics is proving a powerful method to uncover the organizational logic of cortical networks.

Despite representing a minority of cortical cells, inhibitory neurons deeply shape cortical responses. Inhibitory currents closely track excitatory currents, opening only brief windows of opportunity for a neuron to fire. This explains the variability of cortical spike trains, but may also, paradoxically, render a spiking network maximally efficient and precise. Recent years have seen a growing interest in inhibitory interneurons and their circuits. A striking property of cortical inhibition is how tightly it balances excitation. Inhibitory currents not only match excitatory currents on average, but track them on a millisecond time scale, whether they are caused by external stimuli or spontaneous fluctuations. We review, together with experimental evidence, recent theoretical approaches that investigate the advantages of such tight balance for coding and computation. These studies suggest a possible revision of the dominant view that neurons represent information with firing rates corrupted by Poisson noise. Instead, tight excitatory/inhibitory balance may be a signature of a highly cooperative code, orders of magnitude more precise than a Poisson rate code. Moreover, tight balance may provide a template that allows cortical neurons to construct high-dimensional population codes and learn complex functions of their inputs.

Hattori et al . review the recent advances in our understanding of the roles of inhibitory neuron subtypes in shaping the activity and plasticity states of neocortical circuits, how neuromodulators control inhibitory neuron subtypes, and the role of inhibitory neuron dysfunction in neurological disorders. Neocortical inhibitory neurons exhibit remarkably diverse morphology, physiological properties and connectivity. Genetic access to molecularly defined subtypes of inhibitory neurons has aided their functional characterization in recent years. These studies have established that, instead of simply balancing excitatory neuron activity, inhibitory neurons actively shape excitatory circuits in a subtype-specific manner. We review the emerging view that inhibitory neuron subtypes perform context-dependent modulation of excitatory activity, as well as regulate experience-dependent plasticity of excitatory circuits. We then review the roles of neuromodulators in regulating the subtype-specific functions of inhibitory neurons. Finally, we discuss the idea that dysfunctions of inhibitory neuron subtypes may be responsible for various aspects of neurological disorders.

A combination of a sensitive blue light–gated channelrhodopsin actuator and red-shifted Arch-based voltage sensors allows all-optical electrophysiology without cross-talk in cultured neurons or brain slices. All-optical electrophysiology—spatially resolved simultaneous optical perturbation and measurement of membrane voltage—would open new vistas in neuroscience research. We evolved two archaerhodopsin-based voltage indicators, QuasAr1 and QuasAr2, which show improved brightness and voltage sensitivity, have microsecond response times and produce no photocurrent. We engineered a channelrhodopsin actuator, CheRiff, which shows high light sensitivity and rapid kinetics and is spectrally orthogonal to the QuasArs. A coexpression vector, Optopatch, enabled cross-talk–free genetically targeted all-optical electrophysiology. In cultured rat neurons, we combined Optopatch with patterned optical excitation to probe back-propagating action potentials (APs) in dendritic spines, synaptic transmission, subcellular microsecond-timescale details of AP propagation, and simultaneous firing of many neurons in a network. Optopatch measurements revealed homeostatic tuning of intrinsic excitability in human stem cell–derived neurons. In rat brain slices, Optopatch induced and reported APs and subthreshold events with high signal-to-noise ratios. The Optopatch platform enables high-throughput, spatially resolved electrophysiology without the use of conventional electrodes.

In this technical report, the authors describe a new, red-shifted variant of channelrhodopsin (called red-activatable channelrhodopsin or ReaChR) that shows faster kinetics and greater photocurrents than currently available red-shifted probes. In addition, they show that ReaChR can be activated in awake mice through the intact skull. Channelrhodopsins (ChRs) are used to optogenetically depolarize neurons. We engineered a variant of ChR, denoted red-activatable ChR (ReaChR), that is optimally excited with orange to red light ( λ ∼590–630 nm) and offers improved membrane trafficking, higher photocurrents and faster kinetics compared to existing red-shifted ChRs. Red light is less scattered by tissue and is absorbed less by blood than the blue to green wavelengths that are required by other ChR variants. We used ReaChR expressed in the vibrissa motor cortex to drive spiking and vibrissa motion in awake mice when excited with red light through intact skull. Precise vibrissa movements were evoked by expressing ReaChR in the facial motor nucleus in the brainstem and illumination with red light through the external auditory canal. Thus, ReaChR enables transcranial optical activation of neurons in deep brain structures without the need to surgically thin the skull, form a transcranial window or implant optical fibers.

Neuronal dendrites are not passive cables, but whether their excitability contributes to computation at the cell’s soma has been uncertain; by observing and interfering with dendritic ‘spikes’ during sensory stimulation, it is now shown that active dendritic processing enhances somatic orientation selectivity, a fundamental brain computation. Behavioural role for dendritic spikes Neuronal dendrites are not passive cables, but whether their excitability contributes to computation at the cell's soma has been uncertain. Now Michael Häusser and colleagues have used patch-clamp recordings from dendrites of pyramidal cells in the visual cortex of awake mice to observe and interfere with dendritic 'spikes' during sensory stimulation. Their results demonstrate that active dendritic processing enhances somatic orientation selectivity, a fundamental brain computation. Neuronal dendrites are electrically excitable: they can generate regenerative events such as dendritic spikes in response to sufficiently strong synaptic input 1 , 2 , 3 . Although such events have been observed in many neuronal types 4 , 5 , 6 , 7 , 8 , 9 , it is not well understood how active dendrites contribute to the tuning of neuronal output in vivo . Here we show that dendritic spikes increase the selectivity of neuronal responses to the orientation of a visual stimulus (orientation tuning). We performed direct patch-clamp recordings from the dendrites of pyramidal neurons in the primary visual cortex of lightly anaesthetized and awake mice, during sensory processing. Visual stimulation triggered regenerative local dendritic spikes that were distinct from back-propagating action potentials. These events were orientation tuned and were suppressed by either hyperpolarization of membrane potential or intracellular blockade of NMDA ( N -methyl- d -aspartate) receptors. Both of these manipulations also decreased the selectivity of subthreshold orientation tuning measured at the soma, thus linking dendritic regenerative events to somatic orientation tuning. Together, our results suggest that dendritic spikes that are triggered by visual input contribute to a fundamental cortical computation: enhancing orientation selectivity in the visual cortex. Thus, dendritic excitability is an essential component of behaviourally relevant computations in neurons.

The mechanisms that extend lifespan in humans are poorly understood. Here we show that extended longevity in humans is associated with a distinct transcriptome signature in the cerebral cortex that is characterized by downregulation of genes related to neural excitation and synaptic function. In Caenorhabditis elegans , neural excitation increases with age and inhibition of excitation globally, or in glutamatergic or cholinergic neurons, increases longevity. Furthermore, longevity is dynamically regulated by the excitatory–inhibitory balance of neural circuits. The transcription factor REST is upregulated in humans with extended longevity and represses excitation-related genes. Notably, REST-deficient mice exhibit increased cortical activity and neuronal excitability during ageing. Similarly, loss-of-function mutations in the C. elegans REST orthologue genes spr-3 and spr-4 elevate neural excitation and reduce the lifespan of long-lived daf-2 mutants. In wild-type worms, overexpression of spr-4 suppresses excitation and extends lifespan. REST, SPR-3, SPR-4 and reduced excitation activate the longevity-associated transcription factors FOXO1 and DAF-16 in mammals and worms, respectively. These findings reveal a conserved mechanism of ageing that is mediated by neural circuit activity and regulated by REST. Studies of humans, mice and nematodes reveal a conserved role of neural activity and the transcription factor REST in extended longevity.