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The phenotypic diversity of cortical GABAergic neurons is probably necessary for their functional versatility in shaping the spatiotemporal dynamics of neural circuit operations underlying cognition. Deciphering the logic of this diversity requires comprehensive analysis of multi-modal cell features and a framework of neuronal identity that reflects biological mechanisms and principles. Recent high-throughput single-cell analyses have generated unprecedented data sets characterizing the transcriptomes, morphology and electrophysiology of interneurons. We posit that cardinal interneuron types can be defined by their synaptic communication properties, which are encoded in key transcriptional signatures. This conceptual framework integrates multi-modal cell features, captures neuronal input–output properties fundamental to circuit operation and may advance understanding of the appropriate granularity of neuron types, towards a biologically grounded and operationally useful interneuron taxonomy.

The basolateral amygdala (BLA) plays essential roles in behaviors motivated by stimuli with either positive or negative valence, but how it processes motivationally opposing information and participates in establishing valence-specific behaviors remains unclear. Here, by targeting Fezf2 -expressing neurons in the BLA, we identify and characterize two functionally distinct classes in behaving mice, the negative-valence neurons and positive-valence neurons, which innately represent aversive and rewarding stimuli, respectively, and through learning acquire predictive responses that are essential for punishment avoidance or reward seeking. Notably, these two classes of neurons receive inputs from separate sets of sensory and limbic areas, and convey punishment and reward information through projections to the nucleus accumbens and olfactory tubercle, respectively, to drive negative and positive reinforcement. Thus, valence-specific BLA neurons are wired with distinctive input–output structures, forming a circuit framework that supports the roles of the BLA in encoding, learning and executing valence-specific motivated behaviors. Zhang et al. report that the BLA contains ‘hardwired’ positive-valence and negative-valence neurons, which each express Fezf2 but have distinct connectivity. These neurons separately drive learning and expression of avoidance or approach behavior.

Single-cell RNA-sequencing (scRNA-seq) technology provides a new avenue to discover and characterize cell types; however, the experiment-specific technical biases and analytic variability inherent to current pipelines may undermine its replicability. Meta-analysis is further hampered by the use of ad hoc naming conventions. Here we demonstrate our replication framework, MetaNeighbor, that quantifies the degree to which cell types replicate across datasets, and enables rapid identification of clusters with high similarity. We first measure the replicability of neuronal identity, comparing results across eight technically and biologically diverse datasets to define best practices for more complex assessments. We then apply this to novel interneuron subtypes, finding that 24/45 subtypes have evidence of replication, which enables the identification of robust candidate marker genes. Across tasks we find that large sets of variably expressed genes can identify replicable cell types with high accuracy, suggesting a general route forward for large-scale evaluation of scRNA-seq data. Single cell RNA-sequencing analysis poses challenges in replication due to technical biases and analytic variability among bioinformatics pipelines. Here, Crow et al develop MetaNeighbor for measuring cell-type replication across datasets, and use it to identify marker genes for neuron subtypes with evidence of replication.

The response of cortical neurons to a sensory stimulus is modulated by the context. In the visual cortex, for example, stimulation of a pyramidal cell's receptive-field surround can attenuate the cell’s response to a stimulus in the centre of its receptive field, a phenomenon called surround suppression. Whether cortical circuits contribute to surround suppression or whether the phenomenon is entirely relayed from earlier stages of visual processing is debated. Here we show that, in contrast to pyramidal cells, the response of somatostatin-expressing inhibitory neurons (SOMs) in the superficial layers of the mouse visual cortex increases with stimulation of the receptive-field surround. This difference results from the preferential excitation of SOMs by horizontal cortical axons. By perturbing the activity of SOMs, we show that these neurons contribute to pyramidal cells' surround suppression. These results establish a cortical circuit for surround suppression and attribute a particular function to a genetically defined type of inhibitory neuron. The activity of somatostatin-expressing inhibitory neurons (SOMs) in the superficial layers of the mouse visual cortex increases with stimulation of the receptive-field surround, thereby contributing to the surround suppression of pyramidal cells. Role of specific inhibitory neurons in visual perception The neurons of the primary visual cortex respond preferentially to stimuli of particular spatial size and are suppressed when stimuli are larger than their receptive fields. This form of modulation of neural response by contextual information is thought to underlie many perceptual phenomena, but the source of the suppression is not well understood. These authors report the identification of a circuit in the mouse visual cortex that contributes to surround suppression through a mechanism involving somatostatin-expressing interneurons.

Quantum data are susceptible to decoherence induced by the environment and to errors in the hardware processing it. A future fault-tolerant quantum computer will use quantum error correction to actively protect against both. In the smallest error correction codes, the information in one logical qubit is encoded in a two-dimensional subspace of a larger Hilbert space of multiple physical qubits. For each code, a set of non-demolition multi-qubit measurements, termed stabilizers, can discretize and signal physical qubit errors without collapsing the encoded information. Here using a five-qubit superconducting processor, we realize the two parity measurements comprising the stabilizers of the three-qubit repetition code protecting one logical qubit from physical bit-flip errors. While increased physical qubit coherence times and shorter quantum error correction blocks are required to actively safeguard the quantum information, this demonstration is a critical step towards larger codes based on multiple parity measurements. Future quantum computers will employ error correction to protect quantum data from decoherence and faulty hardware. Here, using a quantum processor with five superconducting qubits, the authors demonstrate how to protect one logical qubit from bitflip errors using multi-qubit, stabilizer measurements.

Two major classes of inhibitory neurons in mouse anterior cingulate cortex, somatostatin and parvalbumin interneurons, form functionally homogeneous populations that are recruited at distinct moments in time and encode unique behavioral variables in a foraging task. Neuronal diversity in the cerebral cortex The cerebral cortex contains many different classes of inhibitory interneurons, each with different anatomical and physiological properties. Recent technological developments make it possible to determine the functional impact of individual classes. This optogenetic tagging study of mice performing a reward foraging task shows that parvalbumin- and somatostatin-expressing cells, two of largest interneuron populations, respond differently during different phases of the task. These findings suggest a link between circuit-level activity of the different interneuron types in regulating the flow of information flow and the behavioural functions served by the cortical circuits. Neurons in the prefrontal cortex exhibit diverse behavioural correlates 1 , 2 , 3 , 4 , an observation that has been attributed to cell-type diversity. To link identified neuron types with network and behavioural functions, we recorded from the two largest genetically defined inhibitory interneuron classes, the perisomatically targeting parvalbumin (PV) and the dendritically targeting somatostatin (SOM) neurons 5 , 6 , 7 , 8 in anterior cingulate cortex of mice performing a reward foraging task. Here we show that PV and a subtype of SOM neurons form functionally homogeneous populations showing a double dissociation between both their inhibitory effects and behavioural correlates. Out of several events pertaining to behaviour, a subtype of SOM neurons selectively responded at reward approach, whereas PV neurons responded at reward leaving and encoded preceding stay duration. These behavioural correlates of PV and SOM neurons defined a behavioural epoch and a decision variable important for foraging (whether to stay or to leave), a crucial function attributed to the anterior cingulate cortex 9 , 10 , 11 . Furthermore, PV neurons could fire in millisecond synchrony, exerting fast and powerful inhibition on principal cell firing, whereas the inhibitory effect of SOM neurons on firing output was weak and more variable, consistent with the idea that they respectively control the outputs of, and inputs to, principal neurons 12 , 13 , 14 , 15 , 16 . These results suggest a connection between the circuit-level function of different interneuron types in regulating the flow of information and the behavioural functions served by the cortical circuits. Moreover, these observations bolster the hope that functional response diversity during behaviour can in part be explained by cell-type diversity.

The authors find that long-range axons from primary motor cortex (vM1) preferentially recruit vasointestinal peptide (VIP)-expressing interneurons in somatosensory cortex (S1). VIP neurons in turn inhibit somatostatin-expressing interneurons that target the distal dendrites of pyramidal cells in S1. This dis-inhibitory circuit is active during voluntary movement, suggesting that it participates in the modulation of primary cortical sensory processing by motor cortex. The influence of motor activity on sensory processing is crucial for perception and motor execution. However, the underlying circuits are not known. To unravel the circuit by which activity in the primary vibrissal motor cortex (vM1) modulates sensory processing in the primary somatosensory barrel cortex (S1), we used optogenetics to examine the long-range inputs from vM1 to the various neuronal elements in S1. We found that S1-projecting vM1 pyramidal neurons strongly recruited vasointestinal peptide (VIP)-expressing GABAergic interneurons, a subset of serotonin receptor–expressing interneurons. These VIP interneurons preferentially inhibited somatostatin-expressing interneurons, neurons that target the distal dendrites of pyramidal cells. Consistent with this vM1-mediated disinhibitory circuit, the activity of VIP interneurons in vivo increased and that of somatostatin interneurons decreased during whisking. These changes in firing rates during whisking depended on vM1 activity. Our results suggest previously unknown circuitry by which inputs from motor cortex influence sensory processing in sensory cortex.

Diverse γ-aminobutyric acid—releasing interneurons regulate the functional organization of cortical circuits and derive from multiple embryonic sources. It remains unclear to what extent embryonic origin influences interneuron specification and cortical integration because of difficulties in tracking defined cell types. Here, we followed the developmental trajectory of chandelier cells (ChCs), the most distinct interneurons that innervate the axon initial segment of pyramidal neurons and control action potential initiation. ChCs mainly derive from the ventral germinal zone of the lateral ventricle during late gestation and require the homeodomain protein Nkx2.1 for their specification. They migrate with stereotyped routes and schedule and achieve specific laminar distribution in the cortex. The developmental specification of this bona fide interneuron type likely contributes to the assembly of a cortical circuit motif.

Optogenetic activation of parvalbumin-expressing versus other classes of interneurons is found to have distinct effects on the response properties of individual and populations of excitatory cells, as well as on visual behaviour in awake mice, providing evidence that this specific interneuron subtype has a unique role in visual coding and perception. Class distinction in cortical interneurons Cortical networks consist of a range of neuronal cells, including multiple classes of inhibitory interneurons. Intracortical inhibition is essential for normal brain function, but little is known about the specific roles of the neuronal subtypes. Two independent papers from the groups of Mriganka Sur and Yang Dan explore the functional consequences of activating different classes of interneurons in the mouse visual cortex. Using a variety of techniques, both papers demonstrate that activating parvalbumin-expressing versus other classes of interneurons has distinct effects on the response properties of individual excitatory cells, as well as on populations of these cells. The paper from Dan's group also finds effects on visual behaviour in awake mice. Inhibitory interneurons are essential components of the neural circuits underlying various brain functions. In the neocortex, a large diversity of GABA (γ-aminobutyric acid) interneurons has been identified on the basis of their morphology, molecular markers, biophysical properties and innervation pattern 1 , 2 , 3 . However, how the activity of each subtype of interneurons contributes to sensory processing remains unclear. Here we show that optogenetic activation of parvalbumin-positive (PV + ) interneurons in the mouse primary visual cortex (V1) sharpens neuronal feature selectivity and improves perceptual discrimination. Using multichannel recording with silicon probes 4 , 5 and channelrhodopsin-2 (ChR2)-mediated optical activation 6 , we found that increased spiking of PV + interneurons markedly sharpened orientation tuning and enhanced direction selectivity of nearby neurons. These effects were caused by the activation of inhibitory neurons rather than a decreased spiking of excitatory neurons, as archaerhodopsin-3 (Arch)-mediated optical silencing 7 of calcium/calmodulin-dependent protein kinase IIα (CAMKIIα)-positive excitatory neurons caused no significant change in V1 stimulus selectivity. Moreover, the improved selectivity specifically required PV + neuron activation, as activating somatostatin or vasointestinal peptide interneurons had no significant effect. Notably, PV + neuron activation in awake mice caused a significant improvement in their orientation discrimination, mirroring the sharpened V1 orientation tuning. Together, these results provide the first demonstration that visual coding and perception can be improved by increased spiking of a specific subtype of cortical inhibitory interneurons.

Using a combination of optogenetics, single-cell molecular profiling and paired electrophysiological recordings in the mouse visual cortex, Pfeffer and colleagues derived the connectivity matrix of three major classes of interneurons with their post-synaptic GABAergic targets. This study provides a comprehensive overview of the wiring rules of the inhibition of inhibition in the cortex. Cortical inhibitory neurons contact each other to form a network of inhibitory synaptic connections. Our knowledge of the connectivity pattern underlying this inhibitory network is, however, still incomplete. Here we describe a simple and complementary interaction scheme between three large, molecularly distinct interneuron populations in mouse visual cortex: parvalbumin-expressing interneurons strongly inhibit one another but provide little inhibition to other populations. In contrast, somatostatin-expressing interneurons avoid inhibiting one another yet strongly inhibit all other populations. Finally, vasoactive intestinal peptide–expressing interneurons preferentially inhibit somatostatin-expressing interneurons. This scheme occurs in supragranular and infragranular layers, suggesting that inhibitory networks operate similarly at the input and output of the visual cortex. Thus, as the specificity of connections between excitatory neurons forms the basis for the cortical canonical circuit, the scheme described here outlines a standard connectivity pattern among cortical inhibitory neurons.