Vision and Locomotion Shape the Interactions between Neuron Types in Mouse Visual Cortex

Deciphering cell-cell communication at single-cell resolution for spatial transcriptomics with subgraph-based graph attention network

The inference of cell-cell communication (CCC) is crucial for a better understanding of complex cellular dynamics and regulatory mechanisms in biological systems. However, accurately inferring spatial CCCs at single-cell resolution remains a significant challenge. To address this issue, we present a versatile method, called DeepTalk, to infer spatial CCC at single-cell resolution by integrating single-cell RNA sequencing (scRNA-seq) data and spatial transcriptomics (ST) data. DeepTalk utilizes graph attention network (GAT) to integrate scRNA-seq and ST data, which enables accurate cell-type identification for single-cell ST data and deconvolution for spot-based ST data. Then, DeepTalk can capture the connections among cells at multiple levels using subgraph-based GAT, and further achieve spatially resolved CCC inference at single-cell resolution. DeepTalk achieves excellent performance in discovering meaningful spatial CCCs on multiple cross-platform datasets, which demonstrates its superior ability to dissect cellular behavior within intricate biological processes.

Flexible neural population dynamics govern the speed and stability of sensory encoding in mouse visual cortex

Time courses of neural responses underlie real-time sensory processing and perception. How these temporal dynamics change may be fundamental to how sensory systems adapt to different perceptual demands. By simultaneously recording from hundreds of neurons in mouse primary visual cortex, we examined neural population responses to visual stimuli at sub-second timescales, during different behavioural states. We discovered that during active behavioural states characterised by locomotion, single-neurons shift from transient to sustained response modes, facilitating rapid emergence of visual stimulus tuning. Differences in single-neuron response dynamics were associated with changes in temporal dynamics of neural correlations, including faster stabilisation of stimulus-evoked changes in the structure of correlations during locomotion. Using Factor Analysis, we examined temporal dynamics of latent population responses and discovered that trajectories of population activity make more direct transitions between baseline and stimulus-encoding neural states during locomotion. This could be partly explained by dampening of oscillatory dynamics present during stationary behavioural states. Functionally, changes in temporal response dynamics collectively enabled faster, more stable and more efficient encoding of new visual information during locomotion. These findings reveal a principle of how sensory systems adapt to perceptual demands, where flexible neural population dynamics govern the speed and stability of sensory encoding.

Lateral inhibition in V1 controls neural & perceptual contrast sensitivity

Lateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with anatomy and direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.

"Distinct inhibitory neurons differently shape neuronal codes for sound intensity in the auditory cortex"

Cortical circuits contain multiple types of inhibitory neurons which shape how information is processed within neuronal networks. Here, we asked whether somatostatin-expressing (SST) and vasoactive intestinal peptide-expressing (VIP) inhibitory neurons have distinct effects on population neuronal responses to noise bursts of varying intensities. We optogenetically stimulated SST or VIP neurons while simultaneously measuring the calcium responses of populations of hundreds of neurons in the auditory cortex of male and female awake, head-fixed mice to sounds. Upon SST neuronal activation, noise bursts representations became more discrete for different intensity levels, relying on cell identity rather than strength. By contrast, upon VIP neuronal activation, noise bursts of different intensity level activated overlapping neuronal populations, albeit at different response strengths. At the single-cell level, SST and VIP neuronal activation differentially activated the response-level curves of monotonic and nonmonotonic neurons. SST neuronal activation effects were consistent with a shift of the neuronal population responses toward a more localist code with different cells responding to sounds of different intensity. By contrast, VIP neuronal activation shifted responses towards a more distributed code, in which sounds of different intensity level are encoded in the relative response of similar populations of cells. These results delineate how distinct inhibitory neurons in the auditory cortex dynamically control cortical population codes. Different inhibitory neuronal populations may be recruited under different behavioral demands, depending on whether categorical or invariant representations are advantageous for the task.

Neurogliaform Cells Exhibit Laminar-specific Responses in the Visual Cortex and Modulate Behavioral State-dependent Cortical Activity

Neurogliaform cells are a distinct type of GABAergic cortical interneurons known for their 'volume transmission' output property. However, their activity and function within cortical circuits remain unclear. Here, we developed two genetic tools to target these neurons and examine their function in the primary visual cortex. We found that the spontaneous activity of neurogliaform cells positively correlated with locomotion. Silencing these neurons increased spontaneous activity during locomotion and impaired visual responses in L2/3 pyramidal neurons. Furthermore, the contrast-dependent visual response of neurogliaform cells varies with their laminar location and is constrained by their morphology and input connectivity. These findings demonstrate the importance of neurogliaform cells in regulating cortical behavioral state-dependent spontaneous activity and indicate that their functional engagement during visual stimuli is influenced by their laminar positioning and connectivity.

Stimulus-specific enhancement in mouse visual cortex requires GABA but not VIP-peptide release from VIP interneurons

When adult mice are repeatedly exposed to a particular visual stimulus for as little as 1 h per day for several days while their visual cortex (V1) is in the high-gain state produced by locomotion, that specific stimulus elicits much stronger responses in V1 neurons for the following several weeks, even when measured in anesthetized animals. Such stimulus-specific enhancement (SSE) is not seen if locomotion is prevented. The effect of locomotion on cortical responses is mediated by vasoactive intestinal peptide (VIP) positive interneurons, which can release both the peptide and the inhibitory neurotransmitter GABA. Previous studies have examined the role of VIP-ergic interneurons, but none have distinguished the individual roles of peptide from GABA release. Here, we used genetic ablation to determine which of those molecules secreted by VIP-ergic neurons is responsible for SSE. SSE was not impaired by VIP deletion but was prevented by compromising release of GABA from VIP cells. This finding suggests that SSE may result from Hebbian mechanisms that remain present in adult V1.NEW & NOTEWORTHY Many neurons package and release a peptide along with a conventional neurotransmitter. The conventional view is that such peptides exert late, slow effects on plasticity. We studied a form of cortical plasticity that depends on the activity of neurons that express both vasoactive intestinal peptide (VIP) and the inhibitory neurotransmitter GABA. GABA release accounted for their action on plasticity, with no effect of deleting the peptide on this phenomenon.

Neurogliaform Cells Exhibit Laminar-specific Responses in the Visual Cortex and Modulate Behavioral State-dependent Cortical Activity

Neurogliaform cells are a distinct type of GABAergic cortical interneurons known for their "volume transmission" output property. However, their activity and function within cortical circuits remain unclear. Here, we developed two genetic tools to target these neurons and examine their function in the primary visual cortex. We found that the spontaneous activity of neurogliaform cells positively correlated with locomotion. Silencing these neurons increased spontaneous activity during locomotion and impaired visual responses in L2/3 pyramidal neurons. Furthermore, the contrast-dependent visual response of neurogliaform cells varies with their laminar location and is constrained by their morphology and input connectivity. These findings demonstrate the importance of neurogliaform cells in regulating cortical behavioral state-dependent spontaneous activity and indicate that their functional engagement during visual stimuli is influenced by their laminar positioning and connectivity.

Feedforward and disinhibitory circuits differentially control activity of cortical somatostatin interneurons during behavioral state transitions

Interneurons (INs), specifically those in disinhibitory circuits like somatostatin (SST) and vasoactive intestinal peptide (VIP)-INs, are strongly modulated by the behavioral context. Yet, the mechanisms by which these INs are recruited during active states and whether their activity is consistent across sensory cortices remain unclear. We now report that in mice, locomotor activity strongly recruits SST-INs in the primary somatosensory (S1) but not the visual (V1) cortex. This diverse engagement of SST-INs cannot be explained by differences in VIP-IN function but is absent in the presence of visual input, suggesting the involvement of feedforward sensory pathways. Accordingly, inactivating the somatosensory thalamus, but not decreasing VIP-IN activity, significantly reduces the modulation of SST-INs by locomotion. Model simulations suggest that the differences in SST-INs across behavioral states can be explained by varying ratios of VIP- and thalamus-driven activity. By integrating feedforward activity with neuromodulation, SST-INs are anticipated to be crucial for adapting sensory processing to behavioral states.

The meso-connectomes of mouse, marmoset, and macaque: network organization and the emergence of higher cognition

The recent publications of the inter-areal connectomes for mouse, marmoset, and macaque cortex have allowed deeper comparisons across rodent vs. primate cortical organization. In general, these show that the mouse has very widespread, "all-to-all" inter-areal connectivity (i.e. a "highly dense" connectome in a graph theoretical framework), while primates have a more modular organization. In this review, we highlight the relevance of these differences to function, including the example of primary visual cortex (V1) which, in the mouse, is interconnected with all other areas, therefore including other primary sensory and frontal areas. We argue that this dense inter-areal connectivity benefits multimodal associations, at the cost of reduced functional segregation. Conversely, primates have expanded cortices with a modular connectivity structure, where V1 is almost exclusively interconnected with other visual cortices, themselves organized in relatively segregated streams, and hierarchically higher cortical areas such as prefrontal cortex provide top-down regulation for specifying precise information for working memory storage and manipulation. Increased complexity in cytoarchitecture, connectivity, dendritic spine density, and receptor expression additionally reveal a sharper hierarchical organization in primate cortex. Together, we argue that these primate specializations permit separable deconstruction and selective reconstruction of representations, which is essential to higher cognition.

Top-down modulation in canonical cortical circuits with short-term plasticity

Cortical dynamics and computations are strongly influenced by diverse GABAergic interneurons, including those expressing parvalbumin (PV), somatostatin (SST), and vasoactive intestinal peptide (VIP). Together with excitatory (E) neurons, they form a canonical microcircuit and exhibit counterintuitive nonlinear phenomena. One instance of such phenomena is response reversal, whereby SST neurons show opposite responses to top-down modulation via VIP depending on the presence of bottom-up sensory input, indicating that the network may function in different regimes under different stimulation conditions. Combining analytical and computational approaches, we demonstrate that model networks with multiple interneuron subtypes and experimentally identified short-term plasticity mechanisms can implement response reversal. Surprisingly, despite not directly affecting SST and VIP activity, PV-to-E short-term depression has a decisive impact on SST response reversal. We show how response reversal relates to inhibition stabilization and the paradoxical effect in the presence of several short-term plasticity mechanisms demonstrating that response reversal coincides with a change in the indispensability of SST for network stabilization. In summary, our work suggests a role of short-term plasticity mechanisms in generating nonlinear phenomena in networks with multiple interneuron subtypes and makes several experimentally testable predictions.

Modulation of metastable ensemble dynamics explains optimal coding at moderate arousal in auditory cortex

Performance during perceptual decision-making exhibits an inverted-U relationship with arousal, but the underlying network mechanisms remain unclear. Here, we recorded from auditory cortex (A1) of behaving mice during passive tone presentation, while tracking arousal via pupillometry. We found that tone discriminability in A1 ensembles was optimal at intermediate arousal, revealing a population-level neural correlate of the inverted-U relationship. We explained this arousal-dependent coding using a spiking network model with a clustered architecture. Specifically, we show that optimal stimulus discriminability is achieved near a transition between a multi-attractor phase with metastable cluster dynamics (low arousal) and a single-attractor phase (high arousal). Additional signatures of this transition include arousal-induced reductions of overall neural variability and the extent of stimulus-induced variability quenching, which we observed in the empirical data. Altogether, this study elucidates computational principles underlying interactions between pupil-linked arousal, sensory processing, and neural variability, and suggests a role for phase transitions in explaining nonlinear modulations of cortical computations.

Walking modulates visual detection performance according to stride cycle phase

Walking is among our most frequent and natural of voluntary behaviours, yet the consequences of locomotion upon perceptual and cognitive function remain largely unknown. Recent work has highlighted that although walking feels smooth and continuous, critical phases exist within each step for the successful coordination of perceptual and motor function. Here, we test whether these phasic demands impact upon visual perception, by assessing performance in a visual detection task during natural unencumbered walking. We finely sample visual performance over the stride cycle as participants walk along a smooth linear path at a comfortable speed in a wireless virtual reality environment. At the group-level, accuracy, reaction times, and response likelihood show strong oscillations, modulating at approximately 2 cycles per stride (~2 Hz) with a marked phase of optimal performance aligned with the swing phase of each step. At the participant level, Bayesian inference of population prevalence reveals highly prevalent oscillations in visual detection performance that cluster in two idiosyncratic frequency ranges (2 or 4 cycles per stride), with a strong phase alignment across participants.

Developmental trajectory of cortical somatostatin interneuron function

GABAergic inhibition is critical to the proper development of neocortical circuits. However, GABAergic interneurons are highly diverse and the developmental roles of distinct inhibitory subpopulations remain largely unclear. Dendrite-targeting, somatostatin-expressing interneurons (SST-INs) in the mature cortex regulate synaptic integration and plasticity in excitatory pyramidal neurons (PNs) and exhibit unique feature selectivity. Relatively little is known about early postnatal SST-IN activity or impact on surrounding local circuits. We examined juvenile SST-INs and PNs in mouse primary visual cortex. PNs exhibited stable visual responses and feature selectivity from eye opening onwards. In contrast, SST-INs developed visual responses and feature selectivity during the third postnatal week in parallel with a rapid increase in excitatory synaptic innervation. SST-INs largely exerted a multiplicative effect on nearby PN visual responses at all ages, but this impact increased over time. Our results identify a developmental window for the emergence of an inhibitory circuit mechanism for normalization.

A disinhibitory circuit mechanism explains a general principle of peak performance during mid-level arousal

Perceptual decision-making is highly dependent on the momentary arousal state of the brain, which fluctuates over time on a scale of hours, minutes, and even seconds. The textbook relationship between momentary arousal and task performance is captured by an inverted U-shape, as put forward in the Yerkes-Dodson law. This law suggests optimal performance at moderate levels of arousal and impaired performance at low or high arousal levels. However, despite its popularity, the evidence for this relationship in humans is mixed at best. Here, we use pupil-indexed arousal and performance data from various perceptual decision-making tasks to provide converging evidence for the inverted U-shaped relationship between spontaneous arousal fluctuations and performance across different decision types (discrimination, detection) and sensory modalities (visual, auditory). To further understand this relationship, we built a neurobiologically plausible mechanistic model and show that it is possible to reproduce our findings by incorporating two types of interneurons that are both modulated by an arousal signal. The model architecture produces two dynamical regimes under the influence of arousal: one regime in which performance increases with arousal and another regime in which performance decreases with arousal, together forming an inverted U-shaped arousal-performance relationship. We conclude that the inverted U-shaped arousal-performance relationship is a general and robust property of sensory processing. It might be brought about by the influence of arousal on two types of interneurons that together act as a disinhibitory pathway for the neural populations that encode the available sensory evidence used for the decision.

Reward Modulates Visual Responses in the Superficial Superior Colliculus of Mice

The processing of sensory input is constantly adapting to behavioral demands and internal states. The drive to obtain reward, e.g., searching for water when thirsty, is a strong behavioral demand and associating the reward with its source, a certain environment or action, is paramount for survival. Here, we show that water reward increases subsequent visual activity in the superficial layers of the superior colliculus (SC), which receive direct input from the retina and belong to the earliest stages of visual processing. We trained mice of either sex to perform a visual decision task and recorded the activity of neurons in the SC using two-photon calcium imaging and high-density electrophysiological recordings. Responses to visual stimuli in around 20% of visually responsive neurons in the superficial SC were affected by reward delivered in the previous trial. Reward mostly increased visual responses independent from modulations due to pupil size changes. The modulation of visual responses by reward could not be explained by movements like licking. It was specific to responses to the following visual stimulus, independent of slow fluctuations in neural activity and independent of how often the stimulus was previously rewarded. Electrophysiological recordings confirmed these results and revealed that reward affected the early phase of the visual response around 80 ms after stimulus onset. Modulation of visual responses by reward, but not pupil size, significantly improved the performance of a population decoder to detect visual stimuli, indicating the relevance of reward modulation for the visual performance of the animal.SIGNIFICANCE STATEMENT To learn which actions lead to food, water, or safety, it is necessary to integrate the receiving of reward with sensory stimuli related to the reward. Cortical stages of sensory processing have been shown to represent stimulus-reward associations. Here, we show, however, that reward influences neurons at a much earlier stage of sensory processing, the superior colliculus (SC), receiving direct input from the retina. Visual responses were increased shortly after the animal received the water reward, which led to an improved stimulus signal in the population of these visual neurons. Reward modulation of early visual responses may thus improve perception of visual environments predictive of reward.

Brain state transitions primarily impact the spontaneous rate of slow-firing neurons

The spontaneous firing of neurons is modulated by brain state. Here, we examine how such modulation impacts the overall distribution of firing rates in neuronal populations of neocortical, hippocampal, and thalamic areas across natural and pharmacologically driven brain state transitions. We report that across all the examined combinations of brain area and state transition category, the structure of rate modulation is similar, with almost all fast-firing neurons experiencing proportionally weak modulation, while slow-firing neurons exhibit high inter-neuron variability in the modulation magnitude, leading to a stronger modulation on average. We further demonstrate that this modulation structure is linked to the left-skewed distribution of firing rates on the logarithmic scale and is recapitulated by bivariate log-gamma, but not Gaussian, distributions. Our findings indicate that a preconfigured log-rate distribution with rigid fast-firing neurons and a long left tail of malleable slow-firing neurons is a generic property of forebrain neuronal circuits.

Computational assessment of visual coding across mouse brain areas and behavioural states

Introduction

Our brain is bombarded by a diverse range of visual stimuli, which are converted into corresponding neuronal responses and processed throughout the visual system. The neural activity patterns that result from these external stimuli vary depending on the object or scene being observed, but they also change as a result of internal or behavioural states. This raises the question of to what extent it is possible to predict the presented visual stimuli from neural activity across behavioural states, and how this varies in different brain regions.

Methods

To address this question, we assessed the computational capacity of decoders to extract visual information in awake behaving mice, by analysing publicly available standardised datasets from the Allen Brain Institute. We evaluated how natural movie frames can be distinguished based on the activity of units recorded in distinct brain regions and under different behavioural states. This analysis revealed the spectrum of visual information present in different brain regions in response to binary and multiclass classification tasks.

Results

Visual cortical areas showed highest classification accuracies, followed by thalamic and midbrain regions, with hippocampal regions showing close to chance accuracy. In addition, we found that behavioural variability led to a decrease in decoding accuracy, whereby large behavioural changes between train and test sessions reduced the classification performance of the decoders. A generalised linear model analysis suggested that this deterioration in classification might be due to an independent modulation of neural activity by stimulus and behaviour. Finally, we reconstructed the natural movie frames from optimal linear classifiers, and observed a strong similarity between reconstructed and actual movie frames. However, the similarity was significantly higher when the decoders were trained and tested on sessions with similar behavioural states.

Conclusion

Our analysis provides a systematic assessment of visual coding in the mouse brain, and sheds light on the spectrum of visual information present across brain areas and behavioural states.

VIP interneurons regulate cortical size tuning and visual perception

Cortical circuit function is regulated by extensively interconnected, diverse populations of GABAergic interneurons that may play key roles in shaping circuit operation according to behavioral context. A specialized population of interneurons that co-express vasoactive intestinal peptides (VIP-INs) are activated during arousal and innervate other INs and pyramidal neurons (PNs). Although state-dependent modulation of VIP-INs has been extensively studied, their role in regulating sensory processing is less well understood. We examined the impact of VIP-INs in the primary visual cortex of awake behaving mice. Loss of VIP-IN activity alters the behavioral state-dependent modulation of somatostatin-expressing INs (SST-INs) but not PNs. In contrast, reduced VIP-IN activity globally disrupts visual feature selectivity for stimulus size. Moreover, the impact of VIP-INs on perceptual behavior varies with context and is more acute for small than large visual cues. VIP-INs thus contribute to both state-dependent modulation of cortical activity and sensory context-dependent perceptual performance.

Saccade-Responsive Visual Cortical Neurons Do Not Exhibit Distinct Visual Response Properties

Rapid saccadic eye movements are used by animals to sample different parts of the visual scene. Previous work has investigated neural correlates of these saccades in visual cortical areas such as V1; however, how saccade-responsive neurons are distributed across visual areas, cell types, and cortical layers has remained unknown. Through analyzing 818 1 h experimental sessions from the Allen Brain Observatory, we present a large-scale analysis of saccadic behaviors in head-fixed mice and their neural correlates. We find that saccade-responsive neurons are present across visual cortex, but their distribution varies considerably by transgenically defined cell type, cortical area, and cortical layer. We also find that saccade-responsive neurons do not exhibit distinct visual response properties from the broader neural population, suggesting that the saccadic responses of these neurons are likely not predominantly visually driven. These results provide insight into the roles played by different cell types within a broader, distributed network of sensory and motor interactions.

VIP interneurons in sensory cortex encode sensory and action signals but not direct reward signals

Vasoactive intestinal peptide (VIP) interneurons in sensory cortex modulate sensory responses based on global exploratory behavior and arousal state, but their function during non-exploratory, goal-directed behavior is not well understood. In particular, whether VIP cells are activated by sensory cues, reward-seeking actions, or directly by reinforcement is unclear. We trained mice on a Go/NoGo whisker touch detection task that included a delay period and other features designed to separate sensory-evoked, action-related, and reward-related neural activity. Mice had to lick in response to a whisker stimulus to receive a variable-sized reward. Using two-photon calcium imaging, we measured ΔF/F responses of L2/3 VIP neurons in whisker somatosensory cortex (S1) during behavior. In both expert and novice mice, VIP cells were strongly activated by whisker stimuli and goal-directed actions (licking), but not by reinforcement. VIP cells showed somatotopic whisker tuning that was spatially organized relative to anatomical columns in S1, unlike lick-related signals which were spatially widespread. In expert mice, lick-related VIP responses were suppressed, not enhanced, when a reward was delivered, and the amount of suppression increased with reward size. This reward-related suppression was not seen in novice mice, where reward delivery was not yoked to licking. These results indicate that besides arousal and global state variables, VIP cells are activated by local sensory features and goal-directed actions, but not directly by reinforcement. Instead, our results are consistent with a role for VIP cells in encoding the expectation of reward associated with motor actions.

Multitasking via baseline control in recurrent neural networks

Changes in behavioral state, such as arousal and movements, strongly affect neural activity in sensory areas, and can be modeled as long-range projections regulating the mean and variance of baseline input currents. What are the computational benefits of these baseline modulations? We investigate this question within a brain-inspired framework for reservoir computing, where we vary the quenched baseline inputs to a recurrent neural network with random couplings. We found that baseline modulations control the dynamical phase of the reservoir network, unlocking a vast repertoire of network phases. We uncovered a number of bistable phases exhibiting the simultaneous coexistence of fixed points and chaos, of two fixed points, and of weak and strong chaos. We identified several phenomena, including noise-driven enhancement of chaos and ergodicity breaking; neural hysteresis, whereby transitions across a phase boundary retain the memory of the preceding phase. In each bistable phase, the reservoir performs a different binary decision-making task. Fast switching between different tasks can be controlled by adjusting the baseline input mean and variance. Moreover, we found that the reservoir network achieves optimal memory performance at any first-order phase boundary. In summary, baseline control enables multitasking without any optimization of the network couplings, opening directions for brain-inspired artificial intelligence and providing an interpretation for the ubiquitously observed behavioral modulations of cortical activity.

How to incorporate biological insights into network models and why it matters

Due to the staggering complexity of the brain and its neural circuitry, neuroscientists rely on the analysis of mathematical models to elucidate its function. From Hodgkin and Huxley's detailed description of the action potential in 1952 to today, new theories and increasing computational power have opened up novel avenues to study how neural circuits implement the computations that underlie behaviour. Computational neuroscientists have developed many models of neural circuits that differ in complexity, biological realism or emergent network properties. With recent advances in experimental techniques for detailed anatomical reconstructions or large-scale activity recordings, rich biological data have become more available. The challenge when building network models is to reflect experimental results, either through a high level of detail or by finding an appropriate level of abstraction. Meanwhile, machine learning has facilitated the development of artificial neural networks, which are trained to perform specific tasks. While they have proven successful at achieving task-oriented behaviour, they are often abstract constructs that differ in many features from the physiology of brain circuits. Thus, it is unclear whether the mechanisms underlying computation in biological circuits can be investigated by analysing artificial networks that accomplish the same function but differ in their mechanisms. Here, we argue that building biologically realistic network models is crucial to establishing causal relationships between neurons, synapses, circuits and behaviour. More specifically, we advocate for network models that consider the connectivity structure and the recorded activity dynamics while evaluating task performance.

Developmental loss of ErbB4 in PV interneurons disrupts state-dependent cortical circuit dynamics

GABAergic inhibition plays an important role in the establishment and maintenance of cortical circuits during development. Neuregulin 1 (Nrg1) and its interneuron-specific receptor ErbB4 are key elements of a signaling pathway critical for the maturation and proper synaptic connectivity of interneurons. Using conditional deletions of the ERBB4 gene in mice, we tested the role of this signaling pathway at two developmental timepoints in parvalbumin-expressing (PV) interneurons, the largest subpopulation of cortical GABAergic cells. Loss of ErbB4 in PV interneurons during embryonic, but not late postnatal development leads to alterations in the activity of excitatory and inhibitory cortical neurons, along with severe disruption of cortical temporal organization. These impairments emerge by the end of the second postnatal week, prior to the complete maturation of the PV interneurons themselves. Early loss of ErbB4 in PV interneurons also results in profound dysregulation of excitatory pyramidal neuron dendritic architecture and a redistribution of spine density at the apical dendritic tuft. In association with these deficits, excitatory cortical neurons exhibit normal tuning for sensory inputs, but a loss of state-dependent modulation of the gain of sensory responses. Together these data support a key role for early developmental Nrg1/ErbB4 signaling in PV interneurons as a powerful mechanism underlying the maturation of both the inhibitory and excitatory components of cortical circuits.

Why is everyone talking about brain state?

The rapid and coordinated propagation of neural activity across the brain provides the foundation for complex behavior and cognition. Technical advances across neuroscience subfields have advanced understanding of these dynamics, but points of convergence are often obscured by semantic differences, creating silos of subfield-specific findings. In this review we describe how a parsimonious conceptualization of brain state as the fundamental building block of whole-brain activity offers a common framework to relate findings across scales and species. We present examples of the diverse techniques commonly used to study brain states associated with physiology and higher-order cognitive processes, and discuss how integration across them will enable a more comprehensive and mechanistic characterization of the neural dynamics that are crucial to survival but are disrupted in disease.

VIP interneuron impairment promotes in vivo circuit dysfunction and autism-related behaviors in Dravet syndrome

Dravet syndrome (DS) is a severe neurodevelopmental disorder caused by loss-of-function variants in SCN1A, which encodes the voltage-gated sodium channel subunit Nav1.1. We recently showed that neocortical vasoactive intestinal peptide interneurons (VIP-INs) express Nav1.1 and are hypoexcitable in DS (Scn1a+/-) mice. Here, we investigate VIP-IN function at the circuit and behavioral level by performing in vivo 2-photon calcium imaging in awake wild-type (WT) and Scn1a+/- mice. VIP-IN and pyramidal neuron activation during behavioral transition from quiet wakefulness to active running is diminished in Scn1a+/- mice, and optogenetic activation of VIP-INs restores pyramidal neuron activity to WT levels during locomotion. VIP-IN selective Scn1a deletion reproduces core autism-spectrum-disorder-related behaviors in addition to cellular- and circuit-level deficits in VIP-IN function, but without epilepsy, sudden death, or avoidance behaviors seen in the global model. Hence, VIP-INs are impaired in vivo, which may underlie non-seizure cognitive and behavioral comorbidities in DS.

Behavioral and neuro-functional consequences of eliminating the KCNQ3 GABA binding site in mice

Voltage-gated potassium (Kv) channels formed by α subunits KCNQ2-5 are important in regulating neuronal excitability. We previously found that GABA directly binds to and activates channels containing KCNQ3, challenging the traditional understanding of inhibitory neurotransmission. To investigate the functional significance and behavioral role of this direct interaction, mice with a mutated KCNQ3 GABA binding site (Kcnq3-W266L) were generated and subjected to behavioral studies. Kcnq3-W266L mice exhibited distinctive behavioral phenotypes, of which reduced nociceptive and stress responses were profound and sex-specific. In female Kcnq3-W266L mice, the phenotype was shifted towards more nociceptive effects, while in male Kcnq3-W266L mice, it was shifted towards the stress response. In addition, female Kcnq3-W266L mice exhibited lower motor activity and reduced working spatial memory. The neuronal activity in the lateral habenula and visual cortex was altered in the female Kcnq3-W266L mice, suggesting that GABAergic activation of KCNQ3 in these regions may play a role in the regulation of the responses. Given the known overlap between the nociceptive and stress brain circuits, our data provide new insights into a sex-dependent role of KCNQ3 in regulating neural circuits involved in nociception and stress, via its GABA binding site. These findings identify new targets for effective treatments for neurological and psychiatric conditions such as pain and anxiety.

Arousal and Locomotion Differently Modulate Activity of Somatostatin Neurons across Cortex

Arousal powerfully influences cortical activity, in part by modulating local inhibitory circuits. Somatostatin (SOM)-expressing inhibitory interneurons are particularly well situated to shape local population activity in response to shifts in arousal, yet the relationship between arousal state and SOM activity has not been characterized outside of sensory cortex. To determine whether SOM activity is similarly modulated by behavioral state across different levels of the cortical processing hierarchy, we compared the behavioral modulation of SOM-expressing neurons in auditory cortex (AC), a primary sensory region, and posterior parietal cortex (PPC), an association-level region of cortex, in mice. Behavioral state modulated activity differently in AC and PPC. In PPC, transitions to high arousal were accompanied by large increases in activity across the full PPC neural population, especially in SOM neurons. In AC, arousal transitions led to more subtle changes in overall activity, as individual SOM and Non-SOM neurons could be either positively or negatively modulated during transitions to high arousal states. The coding of sensory information in population activity was enhanced during periods of high arousal in AC, but not in PPC. Our findings suggest unique relationships between activity in local circuits and arousal across cortex, which may be tailored to the roles of specific cortical regions in sensory processing or the control of behavior.

Hippocampal conjunctive and complementary CA1 populations relate sensory events to movement

Hippocampal CA1 neurons respond to sensory stimuli during enforced immobility, movement, and their transitions in a new conveyor belt task. Head-fixed mice were exposed to light flashes or air streams while at rest, spontaneously moving, or running a fixed distance. Two-photon calcium imaging of CA1 neurons revealed that 62% of 3341 imaged cells were active during one or more of 20 sensorimotor events. Of these active cells, 17% were active for any given sensorimotor event, with a higher proportion during locomotion. The study found two types of cells: Conjunctive cells that were active across multiple events, and complementary cells that were active only during individual events, encoding novel sensorimotor events or their delayed repetitions. The configuration of these cells across changing sensorimotor events may signify the role of hippocampus in functional networks integrating sensory information with ongoing movement making it suitable for movement guidance.

Brainstem serotonin neurons selectively gate retinal information flow to thalamus

Retinal ganglion cell (RGC) types relay parallel streams of visual feature information. We hypothesized that neuromodulators might efficiently control which visual information streams reach the cortex by selectively gating transmission from specific RGC axons in the thalamus. Using fiber photometry recordings, we found that optogenetic stimulation of serotonergic axons in primary visual thalamus of awake mice suppressed ongoing and visually evoked calcium activity and glutamate release from RGC boutons. Two-photon calcium imaging revealed that serotonin axon stimulation suppressed RGC boutons that responded strongly to global changes in luminance more than those responding only to local visual stimuli, while the converse was true for suppression induced by increases in arousal. Converging evidence suggests that differential expression of the 5-HT1B receptor on RGC presynaptic terminals, but not differential density of nearby serotonin axons, may contribute to the selective serotonergic gating of specific visual information streams before they can activate thalamocortical neurons.

Ongoing movement controls sensory integration in the dorsolateral striatum

The dorsolateral striatum (DLS) receives excitatory inputs from both sensory and motor cortical regions. In the neocortex, sensory responses are affected by motor activity, however, it is not known whether such sensorimotor interactions occur in the striatum and how they are shaped by dopamine. To determine the impact of motor activity on striatal sensory processing, we performed in vivo whole-cell recordings in the DLS of awake mice during the presentation of tactile stimuli. Striatal medium spiny neurons (MSNs) were activated by both whisker stimulation and spontaneous whisking, however, their responses to whisker deflection during ongoing whisking were attenuated. Dopamine depletion reduced the representation of whisking in direct-pathway MSNs, but not in those of the indirect-pathway. Furthermore, dopamine depletion impaired the discrimination between ipsilateral and contralateral sensory stimulation in both direct and indirect pathway MSNs. Our results show that whisking affects sensory responses in DLS and that striatal representation of both processes is dopamine- and cell type-dependent.

Circadian time- and sleep-dependent modulation of cortical parvalbumin-positive inhibitory neurons

Parvalbumin-positive neurons (PVs) are the main class of inhibitory neurons in the mammalian central nervous system. By examining diurnal changes in synaptic and neuronal activity of PVs in the supragranular layer of the mouse primary visual cortex (V1), we found that both PV input and output are modulated in a time- and sleep-dependent manner throughout the 24-h day. We first show that PV-evoked inhibition is stronger by the end of the light cycle (ZT12) relative to the end of the dark cycle (ZT0), which is in line with the lower inhibitory input of PV neurons at ZT12 than at ZT0. Interestingly, PV inhibitory and excitatory synaptic transmission slowly oscillate in opposite directions during the light/dark cycle. Although excitatory synapses are predominantly regulated by experience, inhibitory synapses are regulated by sleep, via acetylcholine activating M1 receptors. Consistent with synaptic regulation of PVs, we further show in vivo that spontaneous PV activity displays daily rhythm mainly determined by visual experience, which negatively correlates with the activity cycle of surrounding pyramidal neurons and the dorsal lateral geniculate nucleus-evoked responses in V1. These findings underscore the physiological significance of PV's daily modulation.

Interacting rhythms enhance sensitivity of target detection in a fronto-parietal computational model of visual attention

Even during sustained attention, enhanced processing of attended stimuli waxes and wanes rhythmically, with periods of enhanced and relatively diminished visual processing (and subsequent target detection) alternating at 4 or 8 Hz in a sustained visual attention task. These alternating attentional states occur alongside alternating dynamical states, in which lateral intraparietal cortex (LIP), the frontal eye field (FEF), and the mediodorsal pulvinar (mdPul) exhibit different activity and functional connectivity at α, β, and γ frequencies-rhythms associated with visual processing, working memory, and motor suppression. To assess whether and how these multiple interacting rhythms contribute to periodicity in attention, we propose a detailed computational model of FEF and LIP. When driven by θ-rhythmic inputs simulating experimentally-observed mdPul activity, this model reproduced the rhythmic dynamics and behavioral consequences of observed attentional states, revealing that the frequencies and mechanisms of the observed rhythms allow for peak sensitivity in visual target detection while maintaining functional flexibility.

Walking humans and running mice: perception and neural encoding of optic flow during self-motion

Locomotion produces full-field optic flow that often dominates the visual motion inputs to an observer. The perception of optic flow is in turn important for animals to guide their heading and interact with moving objects. Understanding how locomotion influences optic flow processing and perception is therefore essential to understand how animals successfully interact with their environment. Here, we review research investigating how perception and neural encoding of optic flow are altered during self-motion, focusing on locomotion. Self-motion has been found to influence estimation and sensitivity for optic flow speed and direction. Nonvisual self-motion signals also increase compensation for self-driven optic flow when parsing the visual motion of moving objects. The integration of visual and nonvisual self-motion signals largely follows principles of Bayesian inference and can improve the precision and accuracy of self-motion perception. The calibration of visual and nonvisual self-motion signals is dynamic, reflecting the changing visuomotor contingencies across different environmental contexts. Throughout this review, we consider experimental research using humans, non-human primates and mice. We highlight experimental challenges and opportunities afforded by each of these species and draw parallels between experimental findings. These findings reveal a profound influence of locomotion on optic flow processing and perception across species. This article is part of a discussion meeting issue 'New approaches to 3D vision'.

Independent response modulation of visual cortical neurons by attentional and behavioral states

Sensory processing is influenced by cognitive and behavioral states, but how these states interact to modulate responses of individual neurons is unknown. We trained mice in a visual discrimination task wherein they attended to different locations within a hemifield while running or sitting still, enabling us to examine how visual responses are modulated by spatial attention and running behavior. We found that spatial attention improved discrimination performance and strengthened visual responses of excitatory neurons in the primary visual cortex whose receptive fields overlapped with the attended location. Although individual neurons were modulated by both spatial attention and running, the magnitudes of these influences were not correlated. While running-dependent modulation was stable across days, attentional modulation was dynamic, influencing individual neurons to different degrees after repeated changes in attentional states. Thus, despite similar effects on neural responses, spatial attention and running act independently with different dynamics, implying separable mechanisms for their implementation.

Human visual processing during walking: Dissociable pre- and post-stimulus influences

Walking influences visual processing but the underlying mechanism remains poorly understood. In this study, we investigated the influence of walking on pre-stimulus and stimulus-induced visual neural activity and behavioural performance in a discrimination task while participants were standing or freely walking. The results showed dissociable pre- and post-stimulus influences by the movement state. Walking was associated with a reduced pre-stimulus alpha power, which predicted enhanced N1 and decreased P3 components during walking. This pre-stimulus alpha activity was additionally modulated by time on the task, which was paralleled by a similar behavioural modulation. In contrast, the post-stimulus alpha power was reduced in its modulation due to stimulus onset during walking but showed no evidence of modulation by time on the task. Additionally, stimulus parameters (eccentricity, laterality, distractor presence significantly influenced post-stimulus alpha power, whereas the visually evoked components showed no evidence of such an influence. There was further no evidence of a correlation between pre-stimulus and post stimulus alpha power. We conclude that walking has two dissociable influences on visual processing: while the walking induced reduction in alpha power suggests an attentional state change that relates to visual awareness, the post-stimulus influence on alpha power modulation indicates changed spatial visual processing during walking.

Cortex-wide response mode of VIP-expressing inhibitory neurons by reward and punishment

Neocortex is classically divided into distinct areas, each specializing in different function, but all could benefit from reinforcement feedback to inform and update local processing. Yet it remains elusive how global signals like reward and punishment are represented in local cortical computations. Previously, we identified a cortical neuron type, vasoactive intestinal polypeptide (VIP)-expressing interneurons, in auditory cortex that is recruited by behavioral reinforcers and mediates disinhibitory control by inhibiting other inhibitory neurons. As the same disinhibitory cortical circuit is present virtually throughout cortex, we wondered whether VIP neurons are likewise recruited by reinforcers throughout cortex. We monitored VIP neural activity in dozens of cortical regions using three-dimensional random access two-photon microscopy and fiber photometry while mice learned an auditory discrimination task. We found that reward and punishment during initial learning produce rapid, cortex-wide activation of most VIP interneurons. This global recruitment mode showed variations in temporal dynamics in individual neurons and across areas. Neither the weak sensory tuning of VIP interneurons in visual cortex nor their arousal state modulation was fully predictive of reinforcer responses. We suggest that the global response mode of cortical VIP interneurons supports a cell-type-specific circuit mechanism by which organism-level information about reinforcers regulates local circuit processing and plasticity.

Disinhibitory circuit mediated by connections from vasoactive intestinal polypeptide to somatostatin interneurons underlies the paradoxical decrease in spike synchrony with increased border ownership selective neuron firing rate

The activity of border ownership selective (BOS) neurons in intermediate-level visual areas indicates which side of a contour owns a border relative to its classical receptive field and provides a fundamental component of figure-ground segregation. A physiological study reported that selective attention facilitates the activity of BOS neurons with a consistent border ownership preference, defined as two neurons tuned to respond to the same visual object. However, spike synchrony between this pair is significantly suppressed by selective attention. These neurophysiological findings are derived from a biologically-plausible microcircuit model consisting of spiking neurons including two subtypes of inhibitory interneurons, somatostatin (SOM) and vasoactive intestinal polypeptide (VIP) interneurons, and excitatory BOS model neurons. In our proposed model, BOS neurons and SOM interneurons cooperate and interact with each other. VIP interneurons not only suppress SOM interneuron responses but also are activated by feedback signals mediating selective attention, which leads to disinhibition of BOS neurons when they are directing selective attention toward an object. Our results suggest that disinhibition arising from the synaptic connections from VIP to SOM interneurons plays a critical role in attentional modulation of neurons in intermediate-level visual areas.

Wide-Field Calcium Imaging of Neuronal Network Dynamics In Vivo

A central tenet of neuroscience is that sensory, motor, and cognitive behaviors are generated by the communications and interactions among neurons, distributed within and across anatomically and functionally distinct brain regions. Therefore, to decipher how the brain plans, learns, and executes behaviors requires characterizing neuronal activity at multiple spatial and temporal scales. This includes simultaneously recording neuronal dynamics at the mesoscale level to understand the interactions among brain regions during different behavioral and brain states. Wide-field Ca²⁺ imaging, which uses single photon excitation and improved genetically encoded Ca²⁺ indicators, allows for simultaneous recordings of large brain areas and is proving to be a powerful tool to study neuronal activity at the mesoscopic scale in behaving animals. This review details the techniques used for wide-field Ca²⁺ imaging and the various approaches employed for the analyses of the rich neuronal-behavioral data sets obtained. Also discussed is how wide-field Ca²⁺ imaging is providing novel insights into both normal and altered neural processing in disease. Finally, we examine the limitations of the approach and new developments in wide-field Ca²⁺ imaging that are bringing new capabilities to this important technique for investigating large-scale neuronal dynamics.

In vivo extracellular recordings of thalamic and cortical visual responses reveal V1 connectivity rules

The brain's connectome provides the scaffold for canonical neural computations. However, a comparison of connectivity studies in the mouse primary visual cortex (V1) reveals that the average number and strength of connections between specific neuron types can vary. Can variability in V1 connectivity measurements coexist with canonical neural computations? We developed a theory-driven approach to deduce V1 network connectivity from visual responses in mouse V1 and visual thalamus (dLGN). Our method revealed that the same recorded visual responses were captured by multiple connectivity configurations. Remarkably, the magnitude and selectivity of connectivity weights followed a specific order across most of the inferred connectivity configurations. We argue that this order stems from the specific shapes of the recorded contrast response functions and contrast invariance of orientation tuning. Remarkably, despite variability across connectivity studies, connectivity weights computed from individual published connectivity reports followed the order we identified with our method, suggesting that the relations between the weights, rather than their magnitudes, represent a connectivity motif supporting canonical V1 computations.

Look-up and look-down neurons in the mouse visual thalamus during freely moving exploration

Visual information reaches cortex via the thalamic dorsal lateral geniculate nucleus (dLGN). dLGN activity is modulated by global sleep/wake states and arousal, indicating that it is not simply a passive relay station. However, its potential for more specific visuomotor integration is largely unexplored. We addressed this question by developing robust 3D video reconstruction of mouse head and body during spontaneous exploration paired with simultaneous neuronal recordings from dLGN. Unbiased evaluation of a wide range of postures and movements revealed a widespread coupling between neuronal activity and few behavioral parameters. In particular, postures associated with the animal looking up/down correlated with activity in >50% neurons, and the extent of this effect was comparable with that induced by full-body movements (typically locomotion). By contrast, thalamic activity was minimally correlated with other postures or movements (e.g., left/right head and body torsions). Importantly, up/down postures and full-body movements were largely independent and jointly coupled to neuronal activity. Thus, although most units were excited during full-body movements, some expressed highest firing when the animal was looking up ("look-up" neurons), whereas others expressed highest firing when the animal was looking down ("look-down" neurons). These results were observed in the dark, thus representing a genuine behavioral modulation, and were amplified in a lit arena. Our results demonstrate that the primary visual thalamus, beyond global modulations by sleep/awake states, is potentially involved in specific visuomotor integration and reveal two distinct couplings between up/down postures and neuronal activity.

Task specificity in mouse parietal cortex

Parietal cortex is implicated in a variety of behavioral processes, but it is unknown whether and how its individual neurons participate in multiple tasks. We trained head-fixed mice to perform two visual decision tasks involving a steering wheel or a virtual T-maze and recorded from the same parietal neurons during these two tasks. Neurons that were active during the T-maze task were typically inactive during the steering-wheel task and vice versa. Recording from the same neurons in the same apparatus without task stimuli yielded the same specificity as in the task, suggesting that task specificity depends on physical context. To confirm this, we trained some mice in a third task combining the steering wheel context with the visual environment of the T-maze. This hybrid task engaged the same neurons as those engaged in the steering-wheel task. Thus, participation by neurons in mouse parietal cortex is task specific, and this specificity is determined by physical context.

Contribution of behavioural variability to representational drift

Neuronal responses to similar stimuli change dynamically over time, raising the question of how internal representations can provide a stable substrate for neural coding. Recent work has suggested a large degree of drift in neural representations even in sensory cortices, which are believed to store stable representations of the external world. While the drift of these representations is mostly characterized in relation to external stimuli, the behavioural state of the animal (for instance, the level of arousal) is also known to strongly modulate the neural activity. We therefore asked how the variability of such modulatory mechanisms can contribute to representational changes. We analysed large-scale recording of neural activity from the Allen Brain Observatory, which was used before to document representational drift in the mouse visual cortex. We found that, within these datasets, behavioural variability significantly contributes to representational changes. This effect was broadcasted across various cortical areas in the mouse, including the primary visual cortex, higher order visual areas, and even regions not primarily linked to vision like hippocampus. Our computational modelling suggests that these results are consistent with independent modulation of neural activity by behaviour over slower timescales. Importantly, our analysis suggests that reliable but variable modulation of neural representations by behaviour can be misinterpreted as representational drift if neuronal representations are only characterized in the stimulus space and marginalized over behavioural parameters.

Visual-area-specific tonic modulation of GABA release by endocannabinoids sets the activity and coordination of neocortical principal neurons

Perisomatic inhibition of pyramidal neurons (PNs) coordinates cortical network activity during sensory processing, and this role is mainly attributed to parvalbumin-expressing basket cells (BCs). However, cannabinoid receptor type 1 (CB1)-expressing interneurons are also BCs, but the connectivity and function of these elusive but prominent neocortical inhibitory neurons are unclear. We find that their connectivity pattern is visual area specific. Persistently active CB1 signaling suppresses GABA release from CB1 BCs in the medial secondary visual cortex (V2M), but not in the primary visual cortex (V1). Accordingly, in vivo, tonic CB1 signaling is responsible for higher but less coordinated PN activity in the V2M than in the V1. These differential firing dynamics in the V1 and V2M can be captured by a computational network model that incorporates visual-area-specific properties. Our results indicate a differential CB1-mediated mechanism controlling PN activity, suggesting an alternative connectivity scheme of a specific GABAergic circuit in different cortical areas.

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CB1⁺ basket cells exhibit visual-area-specific morphology and connectivity patterns

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Tonic CB1 signaling underlies high pyramidal neurons (PN) activity in V2M but not V1

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Tonic CB1 signaling differentially modulates PN-correlated activity in V1 and V2M

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Numerical simulations capture specific CB1-dependent firing dynamics of V1 and V2M

Rate and oscillatory switching dynamics of a multilayer visual microcircuit model

The neocortex is organized around layered microcircuits consisting of a variety of excitatory and inhibitory neuronal types which perform rate- and oscillation-based computations. Using modeling, we show that both superficial and deep layers of the primary mouse visual cortex implement two ultrasensitive and bistable switches built on mutual inhibitory connectivity motives between somatostatin, parvalbumin, and vasoactive intestinal polypeptide cells. The switches toggle pyramidal neurons between high and low firing rate states that are synchronized across layers through translaminar connectivity. Moreover, inhibited and disinhibited states are characterized by low- and high-frequency oscillations, respectively, with layer-specific differences in frequency and power which show asymmetric changes during state transitions. These findings are consistent with a number of experimental observations and embed firing rate together with oscillatory changes within a switch interpretation of the microcircuit.

A circuit mechanism for independent modulation of excitatory and inhibitory firing rates after sensory deprivation

The cortex is particularly vulnerable to perturbations during sensitive periods, such as the critical period when manipulating sensory experience can induce long-lasting changes in brain structure. Depriving rodents of vision in one eye (known as monocular deprivation [MD]) reduces network activity over two days, whereby inhibitory neurons decrease their firing rates one day after MD, while excitatory neurons are delayed by an additional day. We use spiking networks to mechanistically dissect the requirements for this independent firing-rate regulation after sensory deprivation. We find that in networks stabilized by recurrent inhibition, at least two interneuron subtypes (parvalbumin-expressing and somatostatin-expressing interneurons) are necessary to dynamically alter the circuit response after deprivation and generalize the result across sensory cortices.

Diverse interneuron subtypes shape sensory processing in mature cortical circuits. During development, sensory deprivation evokes powerful synaptic plasticity that alters circuitry, but how different inhibitory subtypes modulate circuit dynamics in response to this plasticity remains unclear. We investigate how deprivation-induced synaptic changes affect excitatory and inhibitory firing rates in a microcircuit model of the sensory cortex with multiple interneuron subtypes. We find that with a single interneuron subtype (parvalbumin-expressing [PV]), excitatory and inhibitory firing rates can only be comodulated—increased or decreased together. To explain the experimentally observed independent modulation, whereby one firing rate increases and the other decreases, requires strong feedback from a second interneuron subtype (somatostatin-expressing [SST]). Our model applies to the visual and somatosensory cortex, suggesting a general mechanism across sensory cortices. Therefore, we provide a mechanistic explanation for the differential role of interneuron subtypes in regulating firing rates, contributing to the already diverse roles they serve in the cortex.

The role of gamma oscillations in central nervous system diseases: Mechanism and treatment

Gamma oscillation is the synchronization with a frequency of 30–90 Hz of neural oscillations, which are rhythmic electric processes of neuron groups in the brain. The inhibitory interneuron network is necessary for the production of gamma oscillations, but certain disruptions such as brain inflammation, oxidative stress, and metabolic imbalances can cause this network to malfunction. Gamma oscillations specifically control the connectivity between different brain regions, which is crucial for perception, movement, memory, and emotion. Studies have linked abnormal gamma oscillations to conditions of the central nervous system, including Alzheimer’s disease, Parkinson’s disease, and schizophrenia. Evidence suggests that gamma entrainment using sensory stimuli (GENUS) provides significant neuroprotection. This review discusses the function of gamma oscillations in advanced brain activities from both a physiological and pathological standpoint, and it emphasizes gamma entrainment as a potential therapeutic approach for a range of neuropsychiatric diseases.

A transcriptomic axis predicts state modulation of cortical interneurons

Transcriptomics has revealed that cortical inhibitory neurons exhibit a great diversity of fine molecular subtypes^1-6, but it is not known whether these subtypes have correspondingly diverse patterns of activity in the living brain. Here we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, which are organized by a single factor: position along the main axis of transcriptomic variation. We combined in vivo two-photon calcium imaging of mouse V1 with a transcriptomic method to identify mRNA for 72 selected genes in ex vivo slices. We classified inhibitory neurons imaged in layers 1-3 into a three-level hierarchy of 5 subclasses, 11 types and 35 subtypes using previously defined transcriptomic clusters³. Responses to visual stimuli differed significantly only between subclasses, with cells in the Sncg subclass uniformly suppressed, and cells in the other subclasses predominantly excited. Modulation by brain state differed at all hierarchical levels but could be largely predicted from the first transcriptomic principal component, which also predicted correlations with simultaneously recorded cells. Inhibitory subtypes that fired more in resting, oscillatory brain states had a smaller fraction of their axonal projections in layer 1, narrower spikes, lower input resistance and weaker adaptation as determined in vitro⁷, and expressed more inhibitory cholinergic receptors. Subtypes that fired more during arousal had the opposite properties. Thus, a simple principle may largely explain how diverse inhibitory V1 subtypes shape state-dependent cortical processing.

Existing function in primary visual cortex is not perturbed by new skill acquisition of a non-matched sensory task

Acquisition of new skills has the potential to disturb existing network function. To directly assess whether previously acquired cortical function is altered during learning, mice were trained in an abstract task in which selected activity patterns were rewarded using an optical brain-computer interface device coupled to primary visual cortex (V1) neurons. Excitatory neurons were longitudinally recorded using 2-photon calcium imaging. Despite significant changes in local neural activity during task performance, tuning properties and stimulus encoding assessed outside of the trained context were not perturbed. Similarly, stimulus tuning was stable in neurons that remained responsive following a different, visual discrimination training task. However, visual discrimination training increased the rate of representational drift. Our results indicate that while some forms of perceptual learning may modify the contribution of individual neurons to stimulus encoding, new skill learning is not inherently disruptive to the quality of stimulus representation in adult V1.

GluN3A excitatory glycine receptors control adult cortical and amygdalar circuits

GluN3A is an atypical glycine-binding subunit of NMDA receptors (NMDARs) whose actions in the brain are mostly unknown. Here, we show that the expression of GluN3A subunits controls the excitability of mouse adult cortical and amygdalar circuits via an unusual signaling mechanism involving the formation of excitatory glycine GluN1/GluN3A receptors (eGlyRs) and their tonic activation by extracellular glycine. eGlyRs are mostly extrasynaptic and reside in specific neuronal populations, including the principal cells of the basolateral amygdala (BLA) and SST-positive interneurons (SST-INs) of the neocortex. In the BLA, tonic eGlyR currents are sensitive to fear-conditioning protocols, are subject to neuromodulation by the dopaminergic system, and control the stability of fear memories. In the neocortex, eGlyRs control the in vivo spiking of SST-INs and the behavior-dependent modulation of cortical activity. GluN3A-containing eGlyRs thus represent a novel and widespread signaling modality in the adult brain, with attributes that strikingly depart from those of conventional NMDARs.

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In mice, GluN3A is expressed by SST-INs in the cortex and pyramidal neurons in the BLA

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GluN3A assembles as excitatory glycine GluN1/GluN3A receptors (eGlyRs)

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eGlyRs detect extracellular glycine levels and generate tonic excitatory currents

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eGlyRs tune the function of SST-INs in cortex and alter the formation of fear memories in BLA

Invariant neural subspaces maintained by feedback modulation

Sensory systems reliably process incoming stimuli in spite of changes in context. Most recent models accredit this context invariance to an extraction of increasingly complex sensory features in hierarchical feedforward networks. Here, we study how context-invariant representations can be established by feedback rather than feedforward processing. We show that feedforward neural networks modulated by feedback can dynamically generate invariant sensory representations. The required feedback can be implemented as a slow and spatially diffuse gain modulation. The invariance is not present on the level of individual neurons, but emerges only on the population level. Mechanistically, the feedback modulation dynamically reorients the manifold of neural activity and thereby maintains an invariant neural subspace in spite of contextual variations. Our results highlight the importance of population-level analyses for understanding the role of feedback in flexible sensory processing.