Sensory experience inversely regulates feedforward and feedback excitation-inhibition ratio in rodent visual cortex

Visual Deprivation during Mouse Critical Period Reorganizes Network-Level Functional Connectivity

A classic example of experience-dependent plasticity is ocular dominance (OD) shift, in which the responsiveness of neurons in the visual cortex is profoundly altered following monocular deprivation (MD). It has been postulated that OD shifts also modify global neural networks, but such effects have never been demonstrated. Here, we use wide-field fluorescence optical imaging (WFOI) to characterize calcium-based resting-state functional connectivity during acute (3 d) MD in female and male mice with genetically encoded calcium indicators (Thy1-GCaMP6f). We first establish the fundamental performance of WFOI by computing signal to noise properties throughout our data processing pipeline. Following MD, we found that Δ band (0.4-4 Hz) GCaMP6 activity in the deprived visual cortex decreased, suggesting that excitatory activity in this region was reduced by MD. In addition, interhemispheric visual homotopic functional connectivity decreased following MD, which was accompanied by a reduction in parietal and motor homotopic connectivity. Finally, we observed enhanced internetwork connectivity between the visual and parietal cortex that peaked 2 d after MD. Together, these findings support the hypothesis that early MD induces dynamic reorganization of disparate functional networks including the association cortices.

Inhibitory stabilized network behaviour in a balanced neural mass model of a cortical column

Strong inhibitory recurrent connections can reduce the tendency for a neural network to become unstable. This is known as inhibitory stabilization; networks that are unstable in the absence of strong inhibitory feedback because of their unstable excitatory recurrent connections are known as Inhibition Stabilized Networks (ISNs). One of the characteristics of ISNs is their "paradoxical response", where perturbing the inhibitory neurons with additional excitatory input results in a decrease in their activity after a temporal delay instead of increasing their activity. Here, we develop a model of populations of neurons across different layers of cortex. Within each layer, there is one population of inhibitory neurons and one population of excitatory neurons. The connectivity weights across different populations in the model are derived from a synaptic physiology database provided by the Allen Institute. The model shows a gradient of excitation-inhibition balance across different layers in the cortex, where superficial layers are more inhibitory dominated compared to deeper layers. To investigate the presence of ISNs across different layers, we measured the membrane potentials of neural populations in the model after perturbing inhibitory populations. The results show that layer 2/3 in the model does not operate in the ISN regime but layers 4 and 5 do operate in the ISN regime. These results accord with neurophysiological findings that explored the presence of ISNs across different layers in the cortex. The results show that there may be a systematic macroscopic gradient of inhibitory stabilization across different layers in the cortex that depends on the level of excitation-inhibition balance, and that the strength of the paradoxical response increases as the model moves closer to bifurcation points.

Extensive topographic remapping and functional sharpening in the adult rat visual pathway upon first visual experience

Understanding the dynamics of stability/plasticity balances during adulthood is pivotal for learning, disease, and recovery from injury. However, the brain-wide topography of sensory remapping remains unknown. Here, using a first-of-its-kind setup for delivering patterned visual stimuli in a rodent magnetic resonance imaging (MRI) scanner, coupled with biologically inspired computational models, we noninvasively mapped brain-wide properties-receptive fields (RFs) and spatial frequency (SF) tuning curves-that were insofar only available from invasive electrophysiology or optical imaging. We then tracked the RF dynamics in the chronic visual deprivation model (VDM) of plasticity and found that light exposure progressively promoted a large-scale topographic remapping in adult rats. Upon light exposure, the initially unspecialized visual pathway progressively evidenced sharpened RFs (smaller and more spatially selective) and enhanced SF tuning curves. Our findings reveal that visual experience following VDM reshapes both structure and function of the visual system and shifts the stability/plasticity balance in adults.

Forebrain E-I balance controlled in cognition through coordinated inhibition and inhibitory transcriptome mechanism

Introduction

Forebrain neural networks are vital for cognitive functioning, and their excitatory-inhibitory (E-I) balance is governed by neural homeostasis. However, the homeostatic control strategies and transcriptomic mechanisms that maintain forebrain E-I balance and optimal cognition remain unclear.

Methods

We used patch-clamp and RNA sequencing to investigate the patterns of neural network homeostasis with suppressing forebrain excitatory neural activity and spatial training.

Results

We found that inhibitory transmission and receptor transcription were reduced in tamoxifen-inducible Kir2.1 conditional knock-in mice. In contrast, spatial training increased inhibitory synaptic connections and the transcription of inhibitory receptors.

Discussion

Our study provides significant evidence that inhibitory systems play a critical role in the homeostatic control of the E-I balance in the forebrain during cognitive training and E-I rebalance, and we have provided insights into multiple gene candidates for cognition-related homeostasis in the forebrain.

Spinal cord retinoic acid receptor signaling gates mechanical hypersensitivity in neuropathic pain

Central sensitization caused by spinal disinhibition is a key mechanism of mechanical allodynia in neuropathic pain. However, the molecular mechanisms underlying spinal disinhibition after nerve injury remain unclear. Here, we show in mice that spared nerve injury (SNI), which induces mechanical hypersensitivity and neuropathic pain, triggers homeostatic reduction of inhibitory outputs from dorsal horn parvalbumin-positive (PV+) interneurons onto both primary afferent terminals and excitatory interneurons. The reduction in inhibitory outputs drives hyperactivation of the spinal cord nociceptive pathway, causing mechanical hypersensitivity. We identified the retinoic acid receptor RARα, a central regulator of homeostatic plasticity, as the key molecular mediator for this synaptic disinhibition. Deletion of RARα in spinal PV+ neurons or application of an RARα antagonist in the spinal cord prevented the development of SNI-induced mechanical hypersensitivity. Our results identify RARα as a crucial molecular effector for neuropathic pain and a potential target for its treatment.

Stability and learning in excitatory synapses by nonlinear inhibitory plasticity

Synaptic changes are hypothesized to underlie learning and memory formation in the brain. But Hebbian synaptic plasticity of excitatory synapses on its own is unstable, leading to either unlimited growth of synaptic strengths or silencing of neuronal activity without additional homeostatic mechanisms. To control excitatory synaptic strengths, we propose a novel form of synaptic plasticity at inhibitory synapses. Using computational modeling, we suggest two key features of inhibitory plasticity, dominance of inhibition over excitation and a nonlinear dependence on the firing rate of postsynaptic excitatory neurons whereby inhibitory synaptic strengths change with the same sign (potentiate or depress) as excitatory synaptic strengths. We demonstrate that the stable synaptic strengths realized by this novel inhibitory plasticity model affects excitatory/inhibitory weight ratios in agreement with experimental results. Applying a disinhibitory signal can gate plasticity and lead to the generation of receptive fields and strong bidirectional connectivity in a recurrent network. Hence, a novel form of nonlinear inhibitory plasticity can simultaneously stabilize excitatory synaptic strengths and enable learning upon disinhibition.

Regulation of circuit organization and function through inhibitory synaptic plasticity

Diverse inhibitory neurons in the mammalian brain shape circuit connectivity and dynamics through mechanisms of synaptic plasticity. Inhibitory plasticity can establish excitation/inhibition (E/I) balance, control neuronal firing, and affect local calcium concentration, hence regulating neuronal activity at the network, single neuron, and dendritic level. Computational models can synthesize multiple experimental results and provide insight into how inhibitory plasticity controls circuit dynamics and sculpts connectivity by identifying phenomenological learning rules amenable to mathematical analysis. We highlight recent studies on the role of inhibitory plasticity in modulating excitatory plasticity, forming structured networks underlying memory formation and recall, and implementing adaptive phenomena and novelty detection. We conclude with experimental and modeling progress on the role of interneuron-specific plasticity in circuit computation and context-dependent learning.

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.

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.

Strong Aversive Conditioning Triggers a Long-Lasting Generalized Aversion

Generalization is an adaptive mnemonic process in which an animal can leverage past learning experiences to navigate future scenarios, but overgeneralization is a hallmark feature of anxiety disorders. Therefore, understanding the synaptic plasticity mechanisms that govern memory generalization and its persistence is an important goal. Here, we demonstrate that strong CTA conditioning results in a long-lasting generalized aversion that persists for at least 2 weeks. Using brain slice electrophysiology and activity-dependent labeling of the conditioning-active neuronal ensemble within the gustatory cortex, we find that strong CTA conditioning induces a long-lasting increase in synaptic strengths that occurs uniformly across superficial and deep layers of GC. Repeated exposure to salt, the generalized tastant, causes a rapid attenuation of the generalized aversion that correlates with a reversal of the CTA-induced increases in synaptic strength. Unlike the uniform strengthening that happens across layers, reversal of the generalized aversion results in a more pronounced depression of synaptic strengths in superficial layers. Finally, the generalized aversion and its reversal do not impact the acquisition and maintenance of the aversion to the conditioned tastant (saccharin). The strong correlation between the generalized aversion and synaptic strengthening, and the reversal of both in superficial layers by repeated salt exposure, strongly suggests that the synaptic changes in superficial layers contribute to the formation and reversal of the generalized aversion. In contrast, the persistence of synaptic strengthening in deep layers correlates with the persistence of CTA. Taken together, our data suggest that layer-specific synaptic plasticity mechanisms separately govern the persistence and generalization of CTA memory.

Development of Functional Properties in the Early Visual System: New Appreciations of the Roles of Lateral Geniculate Nucleus

In the years following Hubel and Wiesel's first reports on ocular dominance plasticity and amblyopia, much attention has been focused on understanding the role of cortical circuits in developmental and experience-dependent plasticity. Initial studies found few differences between retinal ganglion cells and neurons in the lateral geniculate nucleus and uncovered little evidence for an impact of altered visual experience on the functional properties of lateral geniculate nucleus neurons. In the last two decades, however, studies have revealed that the connectivity between the retina and lateral geniculate nucleus is much richer than was previously appreciated, even revealing visual plasticity - including ocular dominance plasticity - in lateral geniculate nucleus neurons. Here we review the development of the early visual system and the impact of experience with a distinct focus on recent discoveries about lateral geniculate nucleus, its connectivity, and evidence for its plasticity and rigidity during development.

Nonlinear transient amplification in recurrent neural networks with short-term plasticity

To rapidly process information, neural circuits have to amplify specific activity patterns transiently. How the brain performs this nonlinear operation remains elusive. Hebbian assemblies are one possibility whereby strong recurrent excitatory connections boost neuronal activity. However, such Hebbian amplification is often associated with dynamical slowing of network dynamics, non-transient attractor states, and pathological run-away activity. Feedback inhibition can alleviate these effects but typically linearizes responses and reduces amplification gain. Here, we study nonlinear transient amplification (NTA), a plausible alternative mechanism that reconciles strong recurrent excitation with rapid amplification while avoiding the above issues. NTA has two distinct temporal phases. Initially, positive feedback excitation selectively amplifies inputs that exceed a critical threshold. Subsequently, short-term plasticity quenches the run-away dynamics into an inhibition-stabilized network state. By characterizing NTA in supralinear network models, we establish that the resulting onset transients are stimulus selective and well-suited for speedy information processing. Further, we find that excitatory-inhibitory co-tuning widens the parameter regime in which NTA is possible in the absence of persistent activity. In summary, NTA provides a parsimonious explanation for how excitatory-inhibitory co-tuning and short-term plasticity collaborate in recurrent networks to achieve transient amplification.

Distinct recruitment of feedforward and recurrent pathways across higher-order areas of mouse visual cortex

Cortical visual processing transforms features of the external world into increasingly complex and specialized neuronal representations. These transformations arise in part through target-specific routing of information; however, within-area computations may also contribute to area-specific function. Here, we sought to determine whether higher order visual cortical areas lateromedial (LM), anterolateral (AL), posteromedial (PM), and anteromedial (AM) have specialized anatomical and physiological properties by using a combination of whole-cell recordings and optogenetic stimulation of primary visual cortex (V1) axons in vitro. We discovered area-specific differences in the strength of recruitment of interneurons through feedforward and recurrent pathways, as well as differences in cell-intrinsic properties and interneuron densities. These differences were most striking when comparing across medial and lateral areas, suggesting that these areas have distinct profiles for net excitability and integration of V1 inputs. Thus, cortical areas are not defined simply by the information they receive but also by area-specific circuit properties that enable specialized filtering of these inputs.

The organization and development of cortical interneuron presynaptic circuits are area specific

Parvalbumin and somatostatin inhibitory interneurons gate information flow in discrete cortical areas that compute sensory and cognitive functions. Despite the considerable differences between areas, individual interneuron subtypes are genetically invariant and are thought to form canonical circuits regardless of which area they are embedded in. Here, we investigate whether this is achieved through selective and systematic variations in their afferent connectivity during development. To this end, we examined the development of their inputs within distinct cortical areas. We find that interneuron afferents show little evidence of being globally stereotyped. Rather, each subtype displays characteristic regional connectivity and distinct developmental dynamics by which this connectivity is achieved. Moreover, afferents dynamically regulated during development are disrupted by early sensory deprivation and in a model of fragile X syndrome. These data provide a comprehensive map of interneuron afferents across cortical areas and reveal the logic by which these circuits are established during development.

The critical period: neurochemical and synaptic mechanisms shared by the visual cortex and the brain stem respiratory system

The landmark studies of Wiesel and Hubel in the 1960's initiated a surge of investigations into the critical period of visual cortical development, when abnormal visual experience can alter cortical structures and functions. Most studies focused on the visual cortex, with relatively little attention to subcortical structures. The goal of the present review is to elucidate neurochemical and synaptic mechanisms common to the critical periods of the visual cortex and the brain stem respiratory system in the normal rat. In both regions, the critical period is a time of (i) heightened inhibition; (ii) reduced expression of brain-derived neurotrophic factor (BDNF); and (iii) synaptic imbalance, with heightened inhibition and suppressed excitation. The last two mechanisms are contrary to the conventional premise. Synaptic imbalance renders developing neurons more vulnerable to external stressors. However, the critical period is necessary to enable each system to strengthen its circuitry, adapt to its environment, and transition from immaturity to maturity, when a state of relative synaptic balance is attained. Failure to achieve such a balance leads to neurological disorders.

Neural dynamics between anterior insular cortex and right supramarginal gyrus dissociate genuine affect sharing from perceptual saliency of pretended pain

Empathy for pain engages both shared affective responses and self-other distinction. In this study, we addressed the highly debated question of whether neural responses previously linked to affect sharing could result from the perception of salient affective displays. Moreover, we investigated how the brain network involved in affect sharing and self-other distinction underpinned our response to a pain that is either perceived as genuine or pretended (while in fact both were acted for reasons of experimental control). We found stronger activations in regions associated with affect sharing (anterior insula [aIns] and anterior mid-cingulate cortex) as well as with affective self-other distinction (right supramarginal gyrus [rSMG]), in participants watching video clips of genuine vs. pretended facial expressions of pain. Using dynamic causal modeling, we then assessed the neural dynamics between the right aIns and rSMG in these two conditions. This revealed a reduced inhibitory effect on the aIns to rSMG connection for genuine pain compared to pretended pain. For genuine pain only, brain-to-behavior regression analyses highlighted a linkage between this inhibitory effect on the one hand, and pain ratings as well as empathic traits on the other. These findings imply that if the pain of others is genuine and thus calls for an appropriate empathic response, neural responses in the aIns indeed seem related to affect sharing and self-other distinction is engaged to avoid empathic over-arousal. In contrast, if others merely pretend to be in pain, the perceptual salience of their painful expression results in neural responses that are down-regulated to avoid inappropriate affect sharing and social support.

The Genetic Control of Stoichiometry Underlying Autism

Autism is a common and complex neurologic disorder whose scientific underpinnings have begun to be established in the past decade. The essence of this breakthrough has been a focus on families, where genetic analyses are strongest, versus large-scale, case-control studies. Autism genetics has progressed in parallel with technology, from analyses of copy number variation to whole-exome sequencing (WES) and whole-genome sequencing (WGS). Gene mutations causing complete loss of function account for perhaps one-third of cases, largely detected through WES. This limitation has increased interest in understanding the regulatory variants of genes that contribute in more subtle ways to the disorder. Strategies combining biochemical analysis of gene regulation, WGS analysis of the noncoding genome, and machine learning have begun to succeed. The emerging picture is that careful control of the amounts of transcription, mRNA, and proteins made by key brain genes-stoichiometry-plays a critical role in defining the clinical features of autism.

Stability of neocortical synapses across sleep and wake states during the critical period in rats

Sleep is important for brain plasticity, but its exact function remains mysterious. An influential but controversial idea is that a crucial function of sleep is to drive widespread downscaling of excitatory synaptic strengths. Here, we used real-time sleep classification, ex vivo measurements of postsynaptic strength, and in vivo optogenetic monitoring of thalamocortical synaptic efficacy to ask whether sleep and wake states can constitutively drive changes in synaptic strength within the neocortex of juvenile rats. We found that miniature excitatory postsynaptic current amplitudes onto L4 and L2/3 pyramidal neurons were stable across sleep- and wake-dense epochs in both primary visual (V1) and prefrontal cortex (PFC). Further, chronic monitoring of thalamocortical synaptic efficacy in V1 of freely behaving animals revealed stable responses across even prolonged periods of natural sleep and wake. Together, these data demonstrate that sleep does not drive widespread downscaling of synaptic strengths during the highly plastic critical period in juvenile animals. Whether this remarkable stability across sleep and wake generalizes to the fully mature nervous system remains to be seen.

Homeostatic synaptic scaling establishes the specificity of an associative memory

Correlation-based (Hebbian) forms of synaptic plasticity are crucial for the initial encoding of associative memories but likely insufficient to enable the stable storage of multiple specific memories within neural circuits. Theoretical studies have suggested that homeostatic synaptic normalization rules provide an essential countervailing force that can stabilize and expand memory storage capacity. Although such homeostatic mechanisms have been identified and studied for decades, experimental evidence that they play an important role in associative memory is lacking. Here, we show that synaptic scaling, a widely studied form of homeostatic synaptic plasticity that globally renormalizes synaptic strengths, is dispensable for initial associative memory formation but crucial for the establishment of memory specificity. We used conditioned taste aversion (CTA) learning, a form of associative learning that relies on Hebbian mechanisms within gustatory cortex (GC), to show that animals conditioned to avoid saccharin initially generalized this aversion to other novel tastants. Specificity of the aversion to saccharin emerged slowly over a time course of many hours and was associated with synaptic scaling down of excitatory synapses onto conditioning-active neuronal ensembles within gustatory cortex. Blocking synaptic scaling down in the gustatory cortex enhanced the persistence of synaptic strength increases induced by conditioning and prolonged the duration of memory generalization. Taken together, these findings demonstrate that synaptic scaling is crucial for sculpting the specificity of an associative memory and suggest that the relative strengths of Hebbian and homeostatic plasticity can modulate the balance between stable memory formation and memory generalization.

State-Dependent Regulation of Cortical Processing Speed via Gain Modulation

To thrive in dynamic environments, animals must be capable of rapidly and flexibly adapting behavioral responses to a changing context and internal state. Examples of behavioral flexibility include faster stimulus responses when attentive and slower responses when distracted. Contextual or state-dependent modulations may occur early in the cortical hierarchy and may be implemented via top-down projections from corticocortical or neuromodulatory pathways. However, the computational mechanisms mediating the effects of such projections are not known. Here, we introduce a theoretical framework to classify the effects of cell type-specific top-down perturbations on the information processing speed of cortical circuits. Our theory demonstrates that perturbation effects on stimulus processing can be predicted by intrinsic gain modulation, which controls the timescale of the circuit dynamics. Our theory leads to counterintuitive effects, such as improved performance with increased input variance. We tested the model predictions using large-scale electrophysiological recordings from the visual hierarchy in freely running mice, where we found that a decrease in single-cell intrinsic gain during locomotion led to an acceleration of visual processing. Our results establish a novel theory of cell type-specific perturbations, applicable to top-down modulation as well as optogenetic and pharmacological manipulations. Our theory links connectivity, dynamics, and information processing via gain modulation.SIGNIFICANCE STATEMENT To thrive in dynamic environments, animals adapt their behavior to changing circumstances and different internal states. Examples of behavioral flexibility include faster responses to sensory stimuli when attentive and slower responses when distracted. Previous work suggested that contextual modulations may be implemented via top-down inputs to sensory cortex coming from higher brain areas or neuromodulatory pathways. Here, we introduce a theory explaining how the speed at which sensory cortex processes incoming information is adjusted by changes in these top-down projections, which control the timescale of neural activity. We tested our model predictions in freely running mice, revealing that locomotion accelerates visual processing. Our theory is applicable to internal modulation as well as optogenetic and pharmacological manipulations and links circuit connectivity, dynamics, and information processing.

Activity labeling in vivo using CaMPARI2 reveals intrinsic and synaptic differences between neurons with high and low firing rate set points

Neocortical pyramidal neurons regulate firing around a stable mean firing rate (FR) that can differ by orders of magnitude between neurons, but the factors that determine where individual neurons sit within this broad FR distribution are not understood. To access low- and high-FR neurons for ex vivo analysis, we used Ca2+- and UV-dependent photoconversion of CaMPARI2 in vivo to permanently label neurons according to mean FR. CaMPARI2 photoconversion was correlated with immediate early gene expression and higher FRs ex vivo and tracked the drop and rebound in ensemble mean FR induced by prolonged monocular deprivation. High-activity L4 pyramidal neurons had greater intrinsic excitability and recurrent excitatory synaptic strength, while E/I ratio, local output strength, and local connection probability were not different. Thus, in L4 pyramidal neurons (considered a single transcriptional cell type), a broad mean FR distribution is achieved through graded differences in both intrinsic and synaptic properties.

Sleep Promotes Downward Firing Rate Homeostasis

Homeostatic plasticity is hypothesized to bidirectionally regulate neuronal activity around a stable set point to compensate for learning-related plasticity, but to date only upward firing rate homeostasis (FRH) has been demonstrated in vivo. We combined chronic electrophysiology in freely behaving animals with an eye-reopening paradigm to enhance firing in primary visual cortex (V1) and found that neurons bidirectionally regulate firing rates around an individual set point. Downward FRH did not require N-methyl-D-aspartate receptor (NMDAR) signaling and was associated with homeostatic scaling down of synaptic strengths. Like upward FRH, downward FRH was gated by arousal state but in the opposite direction: it occurred during sleep, not during wake. In contrast, firing rate depression associated with Hebbian plasticity happened independently of sleep and wake. Thus, sleep and wake states temporally segregate upward and downward FRH, which might prevent interference or provide unopposed homeostatic compensation when it is needed most.

Homeostatic mechanisms regulate distinct aspects of cortical circuit dynamics

Homeostasis is indispensable to counteract the destabilizing effects of Hebbian plasticity. Although it is commonly assumed that homeostasis modulates synaptic strength, membrane excitability, and firing rates, its role at the neural circuit and network level is unknown. Here, we identify changes in higher-order network properties of freely behaving rodents during prolonged visual deprivation. Strikingly, our data reveal that functional pairwise correlations and their structure are subject to homeostatic regulation. Using a computational model, we demonstrate that the interplay of different plasticity and homeostatic mechanisms can capture the initial drop and delayed recovery of firing rates and correlations observed experimentally. Moreover, our model indicates that synaptic scaling is crucial for the recovery of correlations and network structure, while intrinsic plasticity is essential for the rebound of firing rates, suggesting that synaptic scaling and intrinsic plasticity can serve distinct functions in homeostatically regulating network dynamics.

Network control through coordinated inhibition

Coordinated excitatory and inhibitory activity is required for proper brain functioning. Recent computational and experimental studies have demonstrated that activity patterns in recurrent cortical networks are dominated by inhibition. Whereas previous studies have suggested that inhibitory plasticity is important for homeostatic control, this new framework puts inhibition in the driver's seat. Complex neuronal networks in the brain comprise many configurations in parallel, controlled by external and internal 'switches'. Context-dependent modulation and plasticity of inhibitory connections play a key role in memory and learning. It is therefore important to realize that synaptic plasticity is often multisynaptic and that a proper balance between excitation and inhibition is not fixed, but depends on context and activity level.

Layer 4 Gates Plasticity in Visual Cortex Independent of a Canonical Microcircuit

Disrupting binocular vision during a developmental critical period can yield enduring changes to ocular dominance (OD) in primary visual cortex (V1). Here we investigated how this experience-dependent plasticity is coordinated within the laminar circuitry of V1 by deleting separately in each cortical layer (L) a gene required to close the critical period, nogo-66 receptor (ngr1). Deleting ngr1 in excitatory neurons in L4, but not in L2/3, L5, or L6, prevented closure of the critical period, and adult mice remained sensitive to brief monocular deprivation. Intracortical disinhibition, but not thalamocortical disinhibition, accompanied this OD plasticity. Both juvenile wild-type mice and adult mice lacking ngr1 in L4 displayed OD plasticity that advanced more rapidly L4 than L2/3 or L5. Interestingly, blocking OD plasticity in L2/3 with the drug AM-251 did not impair OD plasticity in L5. We propose that L4 restricts disinhibition and gates OD plasticity independent of a canonical cortical microcircuit.

Circuitry Underlying Experience-Dependent Plasticity in the Mouse Visual System

Since the discovery of ocular dominance plasticity, neuroscientists have understood that changes in visual experience during a discrete developmental time, the critical period, trigger robust changes in the visual cortex. State-of-the-art tools used to probe connectivity with cell-type-specific resolution have expanded the understanding of circuit changes underlying experience-dependent plasticity. Here, we review the visual circuitry of the mouse, describing projections from retina to thalamus, between thalamus and cortex, and within cortex. We discuss how visual circuit development leads to precise connectivity and identify synaptic loci, which can be altered by activity or experience. Plasticity extends to visual features beyond ocular dominance, involving subcortical and cortical regions, and connections between cortical inhibitory interneurons. Experience-dependent plasticity contributes to the alignment of networks spanning retina to thalamus to cortex. Disruption of this plasticity may underlie aberrant sensory processing in some neurodevelopmental disorders.

Stability in the Face of Change: Lifelong Experience-Dependent Plasticity in the Sensory Cortex

Plasticity is a fundamental property of the nervous system that enables its adaptations to the ever-changing environment. Heightened plasticity typical for developing circuits facilitates their robust experience-dependent functional maturation. This plasticity wanes during adolescence to permit the stabilization of mature brain function, but abundant evidence supports that adult circuits exhibit both transient and long-term experience-induced plasticity. Cortical plasticity has been extensively studied throughout the life span in sensory systems and the main distinction between development and adulthood arising from these studies is the concept that passive exposure to relevant information is sufficient to drive robust plasticity early in life, while higher-order attentional mechanisms are necessary to drive plastic changes in adults. Recent work in the primary visual and auditory cortices began to define the circuit mechanisms that govern these processes and enable continuous adaptation to the environment, with transient circuit disinhibition emerging as a common prerequisite for both developmental and adult plasticity. Drawing from studies in visual and auditory systems, this review article summarizes recent reports on the circuit and cellular mechanisms of experience-driven plasticity in the developing and adult brains and emphasizes the similarities and differences between them. The benefits of distinct plasticity mechanisms used at different ages are discussed in the context of sensory learning, as well as their relationship to maladaptive plasticity and neurodevelopmental brain disorders. Knowledge gaps and avenues for future work are highlighted, and these will hopefully motivate future research in these areas, particularly those about the learning of complex skills during development.

Long-term Monocular Deprivation during Juvenile Critical Period Disrupts Binocular Integration in Mouse Visual Thalamus

Study of the neural deficits caused by mismatched binocular vision in early childhood has predominantly focused on circuits in the primary visual cortex (V1). Recent evidence has revealed that neurons in mouse dorsolateral geniculate nucleus (dLGN) can undergo rapid ocular dominance plasticity following monocular deprivation (MD). It remains unclear, however, whether the long-lasting deficits attributed to MD during the critical period originate in the thalamus. Using in vivo two-photon Ca2+ imaging of dLGN afferents in superficial layers of V1 in female and male mice, we demonstrate that 14 d MD during the critical period leads to a chronic loss of binocular dLGN inputs while sparing response strength and spatial acuity. Importantly, MD leads to profoundly mismatched visual tuning properties in remaining binocular dLGN afferents. Furthermore, MD impairs binocular modulation, reducing facilitation of responses of both binocular and monocular dLGN inputs during binocular viewing. As predicted by our findings in thalamic inputs, Ca2+ imaging from V1 neurons revealed spared spatial acuity but impaired binocularity in L4 neurons. V1 L2/3 neurons in contrast displayed deficits in both binocularity and spatial acuity. Our data demonstrate that critical-period MD produces long-lasting disruptions in binocular integration beginning in early binocular circuits in dLGN, whereas spatial acuity deficits first arise from circuits further downstream in V1. Our findings indicate that the development of normal binocular vision and spatial acuity depend upon experience-dependent refinement of distinct stages in the mammalian visual system.SIGNIFICANCE STATEMENT Abnormal binocular vision and reduced acuity are hallmarks of amblyopia, a disorder that affects 2%-5% of the population. It is widely thought that the neural deficits underlying amblyopia begin in the circuits of primary visual cortex. Using in vivo two-photon calcium imaging of thalamocortical axons in mice, we show that depriving one eye of input during a critical period in development chronically impairs binocular integration in thalamic inputs to primary visual cortex. In contrast, visual acuity is spared in thalamic inputs. These findings shed new light on the role for developmental mechanisms in the thalamus in establishing binocular vision and may have critical implications for amblyopia.

Progressive Circuit Changes during Learning and Disease

A critical step toward understanding cognition, learning, and brain dysfunction will be identification of the underlying cellular computations that occur in and across discrete brain areas, as well as how they are progressively altered by experience or disease. These computations will be revealed by targeted analyses of the neurons that perform these calculations, defined not only by their firing properties but also by their molecular identity and how they are wired within the local and broad-scale network of the brain. New studies that take advantage of sophisticated genetic tools for cell-type-specific identification and control are revealing how learning and neurological disorders initiate and successively change the properties of defined neural circuits. Understanding the temporal sequence of adaptive or pathological synaptic changes across multiple synapses within a network will shed light into how small-scale neural circuits contribute to higher cognitive functions during learning and disease.

Cortical Circuit Dynamics Are Homeostatically Tuned to Criticality In Vivo

Homeostatic mechanisms stabilize neuronal activity in vivo, but whether this process gives rise to balanced network dynamics is unknown. Here, we continuously monitored the statistics of network spiking in visual cortical circuits in freely behaving rats for 9 days. Under control conditions in light and dark, networks were robustly organized around criticality, a regime that maximizes information capacity and transmission. When input was perturbed by visual deprivation, network criticality was severely disrupted and subsequently restored to criticality over 48 h. Unexpectedly, the recovery of excitatory dynamics preceded homeostatic plasticity of firing rates by >30 h. We utilized model investigations to manipulate firing rate homeostasis in a cell-type-specific manner at the onset of visual deprivation. Our results suggest that criticality in excitatory networks is established by inhibitory plasticity and architecture. These data establish that criticality is consistent with a homeostatic set point for visual cortical dynamics and suggest a key role for homeostatic regulation of inhibition.

Input-Specific Metaplasticity in the Visual Cortex Requires Homer1a-Mediated mGluR5 Signaling

Effective sensory processing depends on sensory experience-dependent metaplasticity, which allows homeostatic maintenance of neural network activity and preserves feature selectivity. Following a strong increase in sensory drive, plasticity mechanisms that decrease the strength of excitatory synapses are preferentially engaged to maintain stability in neural networks. Such adaptation has been demonstrated in various model systems, including mouse primary visual cortex (V1), where excitatory synapses on layer 2/3 (L2/3) neurons undergo rapid reduction in strength when visually deprived mice are reexposed to light. Here, we report that this form of plasticity is specific to intracortical inputs to V1 L2/3 neurons and depends on the activity of NMDA receptors (NMDARs) and group I metabotropic glutamate receptor 5 (mGluR5). Furthermore, we found that expression of the immediate early gene (IEG) Homer1a (H1a) and its subsequent interaction with mGluR5s are necessary for this input-specific metaplasticity.

Distinct Heterosynaptic Plasticity in Fast Spiking and Non-Fast-Spiking Inhibitory Neurons in Rat Visual Cortex

Inhibition in neuronal networks of the neocortex serves a multitude of functions, such as balancing excitation and structuring neuronal activity in space and time. Plasticity of inhibition is mediated by changes at both inhibitory synapses, as well as excitatory synapses on inhibitory neurons. Using slices from visual cortex of young male rats, we describe a novel form of plasticity of excitatory synapses on inhibitory neurons, weight-dependent heterosynaptic plasticity. Recordings from connected pyramid-to-interneuron pairs confirm that postsynaptic activity alone can induce long-term changes at synapses that were not presynaptically active during the induction, i.e., heterosynaptic plasticity. Moreover, heterosynaptic changes can accompany homosynaptic plasticity induced in inhibitory neurons by conventional spike-timing-dependent plasticity protocols. In both fast-spiking (FS) and non-FS neurons, heterosynaptic changes were weight-dependent, because they correlated with initial paired-pulse ratio (PPR), indicative of initial strength of a synapse. Synapses with initially high PPR, indicative of low release probability ("weak" synapses), had the tendency to be potentiated, while synapses with low initial PPR ("strong" synapses) tended to depress or did not change. Interestingly, the net outcome of heterosynaptic changes was different in FS and non-FS neurons. FS neurons expressed balanced changes, with gross average (n = 142) not different from control. Non-FS neurons (n = 66) exhibited net potentiation. This difference could be because of higher initial PPR in the non-FS neurons. We propose that weight-dependent heterosynaptic plasticity may counteract runaway dynamics of excitatory inputs imposed by Hebbian-type learning rules and contribute to fine-tuning of distinct aspects of inhibitory function mediated by FS and non-FS neurons in neocortical networks.SIGNIFICANCE STATEMENT Dynamic balance of excitation and inhibition is fundamental for operation of neuronal networks. Fine-tuning of such balance requires synaptic plasticity. Knowledge about diverse forms of plasticity operating in excitatory and inhibitory neurons is necessary for understanding normal function and causes of dysfunction of the nervous system. Here we show that excitatory inputs to major archetypal classes of neocortical inhibitory neurons, fast-spiking (FS) and non-fast-spiking (non-FS), express a novel type of plasticity, weight-dependent heterosynaptic plasticity, which accompanies the induction of Hebbian-type changes. This novel form of plasticity may counteract runaway dynamics at excitatory synapses to inhibitory neurons imposed by Hebbian-type learning rules and contribute to fine-tuning of diverse aspects of inhibitory function mediated by FS and non-FS neurons in neocortical networks.