Regional synapse gain and loss accompany memory formation in larval zebrafish

Defining the structural and functional changes in the nervous system underlying learning and memory represents a major challenge for modern neuroscience. Although changes in neuronal activity following memory formation have been studied [B. F. Grewe et al., Nature 543, 670–675 (2017); M. T. Rogan, U. V. Stäubli, J. E. LeDoux, Nature 390, 604–607 (1997)], the underlying structural changes at the synapse level remain poorly understood. Here, we capture synaptic changes in the midlarval zebrafish brain that occur during associative memory formation by imaging excitatory synapses labeled with recombinant probes using selective plane illumination microscopy. Imaging the same subjects before and after classical conditioning at single-synapse resolution provides an unbiased mapping of synaptic changes accompanying memory formation. In control animals and animals that failed to learn the task, there were no significant changes in the spatial patterns of synapses in the pallium, which contains the equivalent of the mammalian amygdala and is essential for associative learning in teleost fish [M. Portavella, J. P. Vargas, B. Torres, C. Salas, Brain Res. Bull. 57, 397–399 (2002)]. In zebrafish that formed memories, we saw a dramatic increase in the number of synapses in the ventrolateral pallium, which contains neurons active during memory formation and retrieval. Concurrently, synapse loss predominated in the dorsomedial pallium. Surprisingly, we did not observe significant changes in the intensity of synaptic labeling, a proxy for synaptic strength, with memory formation in any region of the pallium. Our results suggest that memory formation due to classical conditioning is associated with reciprocal changes in synapse numbers in the pallium.

It is widely believed that memories are formed as a result of alterations in synaptic connections between axons and dendrites, an idea first proposed by Ramon y Cajal (1–4). Although synapse changes have been extensively studied in brain slices in the context of long-term potentiation (5, 6), less is known about how synapses in a living vertebrate are modified when a memory is formed.Memory formation has been widely studied using classical conditioning (CC), a robust and straightforward form of learning in which an animal is exposed to a neutral stimulus (conditioned stimulus, CS) paired with an appetitive or aversive stimulus (unconditioned stimulus, US) that evokes a specific behavioral response (UR, unconditioned response) (7, 8). As a result of the pairing, animals learn to associate the CS with the US, causing them to respond to the CS with a conditioned response (CR) identical to the UR, signifying memory retrieval (9, 10). Memory retrieval is also evoked by activating a cellular engram, a group of neurons active during memory formation and retrieval (11–18). The central locus of CC in mammals, the amygdala (19), is located in a relatively inaccessible area beneath the cortex (20). Thus, although numerous longitudinal imaging studies have documented experience-dependent changes in the structure of spines of cortical and hippocampal neurons (21, 22), few imaging studies have directly examined synaptic changes that occur in the amygdala during associative memory formation.Instead, synaptic changes that occur in the amygdala during CC (23) have been studied primarily using indirect measures of synaptic strength, such as the ratio of α-amino-3-hydroxy-5-methyl-4-isoxazoleproprionic acid receptor/N-methyl D-aspartate (AMPA/NMDA) currents in excitatory postsynaptic currents (EPSCs). Increases in AMPA/NMDA ratio in amygdalar neurons following auditory fear conditioning (FC), a type of CC (24–27), indicate that associative memory formation coincides with increases in synaptic strength. In addition, imaging experiments in brain regions beyond the amygdala have shown diverse effects following CC. For example, following contextual fear conditioning, engram neurons in the CA1 region of the hippocampus that receive inputs from CA3 engram neurons displayed spines that were larger and more densely packed than nonengram cells (28). Furthermore, experiments in which neuronal morphology was directly observed before and after FC found that neurons in the frontal association (29) and primary motor cortex (30) showed a decrease in the number of spines, whereas neurons in the auditory cortex showed an increase in spine number with memory formation (31).To obtain previously unavailable insight into memory formation within the central locus of associative memory storage, we developed a paradigm combining in vivo labeling and imaging with informatics and analysis tools. We used this paradigm to map synaptic changes that occur over time in the intact brain of a living vertebrate during memory formation. We imaged the pallium of teleost fish, which contains the putative homolog of the mammalian amygdala based on anatomy (32), gene expression (33), and function (34). The pallium is on the surface of the brain (35), and zebrafish larvae are highly transparent, allowing for intact, whole-brain imaging using selective plane illumination microscopy (SPIM) without the need for invasive intervention (36). In addition, while most studies of learning in zebrafish have used adults (37–40), at least one study showed that larval zebrafish can learn to associate a place with a positive valence US (41). These attributes suggest that larval zebrafish may be an ideal model organism for studying synaptic changes during memory formation due to CC. We have engaged this challenge by combining purpose-built experimental tools with data management software that enables transparent analyses of large and heterogeneous datasets. All data were characterized and stored at the time of creation in a customized data management system designed to conform to findability, accessibility, interoperability, and reusability (i.e., FAIR principles) (see Materials and Methods) (42).     

Integration of signals from different cortical areas in higher order thalamic neurons

Higher order thalamic neurons receive driving inputs from cortical layer 5 and project back to the cortex, reflecting a transthalamic route for corticocortical communication. To determine whether or not individual neurons integrate signals from different cortical populations, we combined electron microscopy “connectomics” in mice with genetic labeling to disambiguate layer 5 synapses from somatosensory and motor cortices to the higher order thalamic posterior medial nucleus. A significant convergence of these inputs was found on 19 of 33 reconstructed thalamic cells, and as a population, the layer 5 synapses were larger and located more proximally on dendrites than were unlabeled synapses. Thus, many or most of these thalamic neurons do not simply relay afferent information but instead integrate signals as disparate in this case as those emanating from sensory and motor cortices. These findings add further depth and complexity to the role of the higher order thalamus in overall cortical functioning.

Until relatively recently, the view of thalamic neurons is that they simply relay information to the cortex with little or no integrative processing. This view drew heavily on lessons learned from the dominant model of the thalamus: the lateral geniculate nucleus (LGN), where receptive fields of geniculate relay cells closely match those of their retinal inputs. However, recent evidence has dramatically changed this view. There are three main reasons for this.First, there is considerable evidence that modulatory input to the thalamus can strongly affect the response properties of thalamic relay cells (reviewed in ref. 1). Examples include the different tonic and burst firing modes, gain of response to driving inputs, etc.Second, new evidence demonstrates that driver inputs that convey different types of peripheral sensory information converge onto single thalamic relay cells, therefore suggesting the possibility of significant integration of information prior to relaying to the cortex. These studies include evidence of retinal inputs with very different receptive fields converging onto single geniculate relay cells (2, 3), of driving inputs from retina and superior colliculus converging onto single geniculate relay cells (4), and of cortical layer 5 and brainstem driver inputs converging onto single cells of the posterior medial nucleus [POm (5)]. However, these examples are few, and each is limited in scale. There is also recent evidence that some thalamic relays may function without traditional driver input (6).Third, the recent division of thalamic nuclei into two functional types, first order and higher order (reviewed in ref. 1), offers potentially new views on the extent to which thalamic neurons transform received information prior to transmission. Unlike first order thalamic relays, which receive driving input from a subcortical source (e.g., the retina for the LGN) and transmit that to the cortex, higher order relays receive inputs primarily from layer 5 of the cortex and thus serve as a transthalamic route for corticocortical communication. Therefore, the distinct functional organization of higher order thalamic relays offers an interesting substrate for thalamic integration of disparate information (7–9). Specifically, since higher order thalamic nuclei commonly receive overlapping projections from layer 5 neurons of multiple, distinct cortical areas (10), we can ask whether these multiple driving inputs containing different types of information converge to synapse onto single relay cells. Because most of thalamus by volume seems to be higher order (1) and because most or all cortical areas send layer 5 projections to the thalamus as the afferent limb in transthalamic pathways (10), such convergence would have major significance for thalamocortical functioning.To provide morphological evidence for such convergence, we employed modern viral tracing techniques to disambiguate multiple long-distance pathways in large volume serial electron microscope (EM) reconstructions (i.e., “connectomics”) in the mouse; by this approach, we could identify possible convergence of layer 5 inputs from somatosensory and motor cortices onto single relay cells of the POm, which is a higher order somatosensory thalamic nucleus. The viral tracing makes use of orthograde labeling of long pathways with an ascorbate peroxidase (APX) from the pea plant (11) that has allowed us to identify separately synaptic terminals from sensory and motor cortices onto neurons of the POm. Our results indicate significant convergence of presumptive driver inputs onto single thalamic neurons from layer 5 cells of disparate sensory and motor cortices.     

Active dendrites enable strong but sparse inputs to determine orientation selectivity

The dendrites of neocortical pyramidal neurons are excitable. However, it is unknown how synaptic inputs engage nonlinear dendritic mechanisms during sensory processing in vivo, and how they in turn influence action potential output. Here, we provide a quantitative account of the relationship between synaptic inputs, nonlinear dendritic events, and action potential output. We developed a detailed pyramidal neuron model constrained by in vivo dendritic recordings. We drive this model with realistic input patterns constrained by sensory responses measured in vivo and connectivity measured in vitro. We show mechanistically that under realistic conditions, dendritic Na⁺ and NMDA spikes are the major determinants of neuronal output in vivo. We demonstrate that these dendritic spikes can be triggered by a surprisingly small number of strong synaptic inputs, in some cases even by single synapses. We predict that dendritic excitability allows the 1% strongest synaptic inputs of a neuron to control the tuning of its output. Active dendrites therefore allow smaller subcircuits consisting of only a few strongly connected neurons to achieve selectivity for specific sensory features.

There is longstanding evidence from in vitro experiments that dendrites of mammalian neurons are electrically excitable (1, 2), and theoretical work has demonstrated that these active properties can be exploited for computations so that single neurons can perform functions that could otherwise only be performed by a network (3–7). Recently, technical breakthroughs have enabled dendritic integration to be studied in vivo using both imaging and electrophysiological techniques (8, 9). These experiments have revealed that the integration of synaptic events in vivo can be highly nonlinear and that this process influences the response properties of single neurons and neuronal populations in vivo (10–16). For example, patch-clamp recordings from dendrites in mouse primary visual cortex (V1) have demonstrated that dendritic spikes are triggered by visual input and that they may contribute to the orientation selectivity of somatic membrane potential (17). However, important mechanistic questions are still unanswered. How many synaptic inputs must be locally coactive on a dendrite to recruit dendritic spikes? What is the contribution of individual dendritic spikes to somatic action potential (AP) output and its orientation selectivity? Moreover, we do not understand how the answers to these questions depend on the type of dendritic spike. Finally, how do active dendrites, by supporting dendritic spikes, influence which synaptic inputs control AP output and its tuning?These issues are extremely challenging to address experimentally. We have therefore taken a modeling approach, constrained by in vitro and in vivo experimental data, in order to provide a quantitative understanding of the relationship between synaptic input, dendritic spikes, and AP output during sensory processing in V1. We constructed a detailed active model of a layer (L) 2/3 pyramidal neuron in mouse V1 and combined this with a model of the presynaptic inputs it receives during visual stimulation with drifting gratings in vivo (17–21).Our model reproduces key features of the experimental data on dendritic and somatic responses to visual stimulation as observed in vivo and allows us to identify the synaptic inputs that trigger dendritic Na⁺ spikes and NMDA spikes. We also provide a quantitative explanation for how these dendritic spikes determine neuronal output in vivo. Our results show that dendritic spikes can be triggered by a surprisingly small number of synaptic inputs—in some cases even by single synapses. We also find that during sensory processing, already few dendritic spikes are effective at driving somatic output. Overall, this strategy allows a remarkably small number of strong synaptic inputs to dominate neural output, which may reduce the number of neurons required to represent a given sensory feature.     

Social experiences switch states of memory engrams through regulating hippocampal Rac1 activity

In pathological or artificial conditions, memory can be formed as silenced engrams that are unavailable for retrieval by presenting conditioned stimuli but can be artificially switched into the latent state so that natural recall is allowed. However, it remains unclear whether such different states of engrams bear any physiological significance and can be switched through physiological mechanisms. Here, we show that an acute social reward experience switches the silent memory engram into the latent state. Conversely, an acute social stress causes transient forgetting via turning a latent memory engram into a silent state. Such emotion-driven bidirectional switching between latent and silent states of engrams is mediated through regulation of Rac1 activity–dependent reversible forgetting in the hippocampus, as stress-activated Rac1 suppresses retrieval, while reward recovers silenced memory under amnesia by inhibiting Rac1. Thus, data presented reveal hippocampal Rac1 activity as the basis for emotion-mediated switching between latent and silent engrams to achieve emotion-driven behavioral flexibility.

Animals are required to flexibly retrieve memories according to their emotional states for achieving optimal behaviors in an ever-changing environment. To understand the underlying mechanisms of such regulation, extensive effort has been devoted to studying the impact of emotion on memory processes (1–5). For instance, stress can block memory retrieval through hormones, neuroinflammation, or depression of synapses in both human and animal models (6–12), while reward and novelty can facilitate both the formation and maintenance of memories (13, 14). However, how emotion might directly impact the memory engram remains elusive. The proposed theory and experimental demonstrations have revealed the presence of multiple states of memory engrams, such as silent, latent, and active states (15–17). In the silent state, only artificial activation of engram cells is capable of inducing memory expression, whereas latent engram cells can be activated by a natural conditioned stimulus to drive the engram into the active state for memory retrieval. It is intriguing to note that training either mouse models of Alzheimer’s disease or protein synthesis-inhibited mice are reported to yield only silent engrams, and such silent engrams could be turned into a latent state (18–22) through artificial manipulations of either optical stimulation–induced long-term potentiation (LTP) or virus-driven overexpression of activated PAK1. However, the physiological significance of the different states of engrams, particularly the silent engram, remains unclear. In the course of studying the functions of reversible forgetting (23, 24), we became interested in testing the idea that the emotional impact on memory retrieval could be mediated through switching the engram between latent and silent states, while reversible forgetting may play a role in making such switching.To investigate this idea, we tested the effects of acute social reward (SR) and social stress (SS) on memory retrieval. Since mating and fighting are widely perceived and used as behavioral stimuli for evoking feelings of reward and stress, respectively (25–27), we adopted a modified short procedure for evoking acute emotion through social interactions. For SR treatment, a single experimental male mouse is exposed to two females brought from different home cages for 10 min. Such a subtle positive experience is sufficient to enhance retrieval of contextual fear memory (28). For SS treatment, a single experimental male mouse is exposed to a group of five male littermates for 10 min. This is a hostile social environment in which the experimental mouse fights with other littermates during this time window. Such a subtle stressful experience is sufficient to significantly reduce 24-h contextual fear memory (28). Based on these two paradigms of acute social experiences, we investigated how emotion affects memory retrieval through alterations in engram states.     

Connexin hemichannels contribute to spontaneous electrical activity in the human fetal cortex

Before the human cortex is able to process sensory information, young postmitotic neurons must maintain occasional bursts of action-potential firing to attract and keep synaptic contacts, to drive gene expression, and to transition to mature membrane properties. Before birth, human subplate (SP) neurons are spontaneously active, displaying bursts of electrical activity (plateau depolarizations with action potentials). Using whole-cell recordings in acute cortical slices, we investigated the source of this early activity. The spontaneous depolarizations in human SP neurons at midgestation (17–23 gestational weeks) were not completely eliminated by tetrodotoxin—a drug that blocks action potential firing and network activity—or by antagonists of glutamatergic, GABAergic, or glycinergic synaptic transmission. We then turned our focus away from standard chemical synapses to connexin-based gap junctions and hemichannels. PCR and immunohistochemical analysis identified the presence of connexins (Cx26/Cx32/Cx36) in the human fetal cortex. However, the connexin-positive cells were not found in clusters but, rather, were dispersed in the SP zone. Also, gap junction-permeable dyes did not diffuse to neighboring cells, suggesting that SP neurons were not strongly coupled to other cells at this age. Application of the gap junction and hemichannel inhibitors octanol, flufenamic acid, and carbenoxolone significantly blocked spontaneous activity. The putative hemichannel antagonist lanthanum alone was a potent inhibitor of the spontaneous activity. Together, these data suggest that connexin hemichannels contribute to spontaneous depolarizations in the human fetal cortex during the second trimester of gestation.In the adult brain, neuronal network activity is essentially driven by chemical synapses (1–3), whereas in the developing brain, neuronal activity is largely independent of sensory inputs (4–6). Membrane depolarizations during the earliest stages of brain development play an important role in the transition between the immature and mature signaling properties of neurons, as well as in shaping the mature functional neuronal network (7–12). Recent studies performed in the rodent model of cortical development have implicated subplate (SP) neurons as key regulators of early electrical activity and network oscillations (13, 14). Their essential role in the establishment of thalamocortical connections and cortical columns (15–18), extensive connectivity within the early synaptic network (19–21), and dense gap junction coupling (22, 23), as well as the abundant innervation by neuromodulatory transmitter systems (24, 25), put SP neurons in an ideal position to synchronize cortical activity during early development. Disruptions to the SP zone during development have been implicated in several major neurological disorders including schizophrenia, cerebral palsy, and autism (26, 27).Most of the physiological studies on SP neurons have been performed in the first postnatal week of rodent development [postnatal day 0 (P0) to P4], a time that corresponds more closely to the last (third) trimester of human gestation (28). Little is known about human SP neuron physiology in the first two trimesters, when massive proliferation, neuron migration and the initial stage of network formation are occurring in the human cerebral cortex (29, 30). General principles arising from the rodent model of cortical development should be tested in human neurons whenever possible, because it is well established in neurobiology that similar activity patterns can be produced by different sets of underlying conductances (31).Because of ethical and technical limitations associated with experimentation on human materials, there is a profound lack of information about physical, chemical, and biological agents that affect spontaneous electrical activity in human fetal cortex. Using acute brain slices obtained from postmortem human fetal tissue [17–23 gestational weeks (gw)], we analyzed the physiological effects of channel and receptor antagonists on SP neuron activity. We found that spontaneous bioelectric activity of human SP neurons is moderately influenced by drugs that block neuronal network activity and synaptic transmission and more strongly by drugs that interfere with the activity of connexin (Cx) pores. Several lines of our experimental data point to Cx hemichannels as significant contributors to spontaneous membrane depolarizations in human fetal cortex during the second trimester of gestation.     

Pop-out search instigates beta-gated feature selectivity enhancement across V4 layers

Visual search is a workhorse for investigating how attention interacts with processing of sensory information. Attentional selection has been linked to altered cortical sensory responses and feature preferences (i.e., tuning). However, attentional modulation of feature selectivity during search is largely unexplored. Here we map the spatiotemporal profile of feature selectivity during singleton search. Monkeys performed a search where a pop-out feature determined the target of attention. We recorded laminar neural responses from visual area V4. We first identified “feature columns” which showed preference for individual colors. In the unattended condition, feature columns were significantly more selective in superficial relative to middle and deep layers. Attending a stimulus increased selectivity in all layers but not equally. Feature selectivity increased most in the deep layers, leading to higher selectivity in extragranular layers as compared to the middle layer. This attention-induced enhancement was rhythmically gated in phase with the beta-band local field potential. Beta power dominated both extragranular laminar compartments, but current source density analysis pointed to an origin in superficial layers, specifically. While beta-band power was present regardless of attentional state, feature selectivity was only gated by beta in the attended condition. Neither the beta oscillation nor its gating of feature selectivity varied with microsaccade production. Importantly, beta modulation of neural activity predicted response times, suggesting a direct link between attentional gating and behavioral output. Together, these findings suggest beta-range synaptic activation in V4’s superficial layers rhythmically gates attentional enhancement of feature tuning in a way that affects the speed of attentional selection.

Throughout cortex, sensory information is organized into maps. This phenomenon is readily observable in visual cortex where maps organize information in both the radial (e.g., within cortical columns) and tangential (e.g., across a cortical area) dimensions (1–4). Importantly, sensory information attributed to these maps is malleable. For example, selective attention is linked to profound changes in neural activity organizing sensory information in both space and time (5–34).In visual cortex, cortical columnar microcircuits comprise many neurons that respond to the same location of visual space and similar stimulus features. For example, primary visual cortex (V1) features “orientation columns” consisting of neurons sharing response preference for the same stimulus orientation (35, 36) and “ocular dominance columns” consisting of neurons that preferentially respond to the same eye (37). Similar columnar organization for feature selectivity has been described across many other visual cortical areas, including area V2 (36, 38, 39), area V3 (40), middle temporal area (area MT) (41–43), and inferotemporal cortex (44–46). Midlevel visual cortical area V4, a well-studied area contributing to attentional modulation, follows suit with columnar organization of visual responses and feature preferences (44, 47–53). Yet, we do not know the extent to which attention impacts feature preferences along columns. While canonical microcircuit models of cortex predict laminar differences for attentional modulation [e.g., feedback-recipient extragranular layers modulating before granular layers (54–56)], how this modulation interacts with columnar feature selectivity is largely unknown.We sought to determine the spatiotemporal profile of feature preferences within the V4 laminar microcircuit during attentional selection. To address this question, we performed neurophysiological recordings along V4 layers in monkeys performing an attention-demanding pop-out search task. We identified feature columns demonstrating homogeneous feature preference along cortical depth. When the search array item presented in the column’s receptive field (RF) was unattended, the upper cortical layers were most selective. However, when attended, feature selectivity in the deep layers enhanced the most, resulting in overall strongest feature selectivity in both extragranular compartments. We further found that the enhancement of feature selectivity associated with attention was rhythmically gated in the beta range. While beta activity was measurable across both unattended and attended conditions, rhythmic gating of feature selectivity was only present with attention. Moreover, beta power modulating the neural response was predictive of response time (RT), suggesting a link between attentional gating and behavior. Synaptic currents revealed the beta rhythm originates in superficial cortical layers, which is compatible with top-down influence.     

Rapid homeostasis by disinhibition during whisker map plasticity

How homeostatic processes contribute to map plasticity and stability in sensory cortex is not well-understood. Classically, sensory deprivation first drives rapid Hebbian weakening of spiking responses to deprived inputs, which is followed days later by a slow homeostatic increase in spiking responses mediated by excitatory synaptic scaling. Recently, more rapid homeostasis by inhibitory circuit plasticity has been discovered in visual cortex, but whether this process occurs in other brain areas is not known. We tested for rapid homeostasis in layer 2/3 (L2/3) of rodent somatosensory cortex, where D-row whisker deprivation drives Hebbian weakening of whisker-evoked spiking responses after an unexplained initial delay, but no homeostasis of deprived whisker responses is known. We hypothesized that the delay reflects rapid homeostasis through disinhibition, which masks the onset of Hebbian weakening of L2/3 excitatory input. We found that deprivation (3 d) transiently increased whisker-evoked spiking responses in L2/3 single units before classical Hebbian weakening (≥5 d), whereas whisker-evoked synaptic input was reduced during both periods. This finding suggests a transient homeostatic increase in L2/3 excitability. In whole-cell recordings from L2/3 neurons in vivo, brief deprivation decreased whisker-evoked inhibition more than excitation and increased the excitation–inhibition ratio. In contrast, synaptic scaling and increased intrinsic excitability were absent. Thus, disinhibition is a rapid homeostatic plasticity mechanism in rodent somatosensory cortex that transiently maintains whisker-evoked spiking in L2/3, despite the onset of Hebbian weakening of excitatory input.During deprivation-induced sensory map plasticity in cerebral cortex, changes in sensory input trigger both homeostatic plasticity mechanisms that maintain stable cortical firing rates and Hebbian mechanisms, in which inactive inputs lose (and active inputs gain) representation in sensory maps (1). Diverse mechanisms for homeostasis exist, including synaptic scaling (2–4), plasticity of intrinsic excitability (5, 6), and changes in sensory-evoked inhibition and excitation–inhibition (E-I) ratio (7–11). How homeostatic and Hebbian mechanisms interact to control map stability and plasticity remains unclear.One key unknown is the relative dynamics of homeostatic and Hebbian plasticity. Homeostasis mediated by synaptic scaling is slow, occurring over hours in vitro and days in vivo. This process is evident in visual cortex, where eyelid closure during the critical period classically drives Hebbian weakening of closed eye spiking responses (after 2 d of deprivation) followed several days later by a slower homeostatic increase in visual responses (12, 13) mediated by excitatory synaptic scaling (3, 14, 15). We investigated whether more rapid forms of homeostasis also exist that shape the earliest stages of cortical plasticity. Recent results in visual cortex show that eyelid closure rapidly weakens inhibitory circuits (within 1 d), and this process increases network excitability and, therefore, is an initial homeostatic response to deprivation (10, 16). This disinhibition correlates with rapid structural plasticity in inhibitory axons and dendrites (17) and is mediated by a reduction in excitatory drive to parvalbumin-positive interneurons (10). Whether rapid homeostasis by disinhibition or other mechanisms is a general feature of cortical plasticity outside the visual cortex is unknown. Theoretical work shows that rapid homeostasis by inhibitory and/or intrinsic plasticity can guide development of realistic sensory tuning and sparse sensory coding in cortical networks, suggesting broad relevance (18).We tested for rapid homeostasis during the onset of whisker map plasticity in the rodent primary somatosensory (S1) cortex, a major model of cortical plasticity. Each cortical column in the S1 whisker map corresponds to one facial whisker, termed its principal whisker (PW). Trimming or plucking a subset of whiskers in young adults weakens spiking responses to deprived PWs in layer 2/3 (L2/3) of deprived columns (19, 20). This process is mediated by Hebbian synaptic weakening at L4–L2/3 and L2/3–L2/3 excitatory synapses (21–23). No homeostatic restoration or strengthening of deprived whisker responses is known. However, PW response weakening is often preceded by an unexplained initial delay of ∼7 d, in which deprived whisker-evoked spiking responses remain stable (24, 25). We hypothesized that this initial delay reflects not a lack of plasticity but rapid homeostasis that (i) masks initial Hebbian weakening of L2/3 excitatory input and (ii) is mediated by loss of inhibition and/or increased intrinsic excitability in L2/3 neurons. Such rapid homeostasis would be a unique component of whisker map plasticity.     

Olfactory learning promotes input-specific synaptic plasticity in adult-born neurons

The production of new neurons in the olfactory bulb (OB) through adulthood is a major mechanism of structural and functional plasticity underlying learning-induced circuit remodeling. The recruitment of adult-born OB neurons depends not only on sensory input but also on the context in which the olfactory stimulus is received. Among the multiple steps of adult neurogenesis, the integration and survival of adult-born neurons are both strongly influenced by olfactory learning. Conversely, optogenetic stimulation of adult-born neurons has been shown to specifically improve olfactory learning and long-term memory. However, the nature of the circuit and the synaptic mechanisms underlying this reciprocal influence are not yet known. Here, we showed that olfactory learning increases the spine density in a region-restricted manner along the dendritic tree of adult-born granule cells (GCs). Anatomical and electrophysiological analysis of adult-born GCs showed that olfactory learning promotes a remodeling of both excitatory and inhibitory inputs selectively in the deep dendritic domain. Circuit mapping revealed that the malleable dendritic portion of adult-born neurons receives excitatory inputs mostly from the regions of the olfactory cortex that project back to the OB. Finally, selective optogenetic stimulation of olfactory cortical projections to the OB showed that learning strengthens these inputs onto adult-born GCs. We conclude that learning promotes input-specific synaptic plasticity in adult-born neurons, which reinforces the top-down influence from the olfactory cortex to early stages of olfactory information processing.Within the framework of Hebbian theory, information processing, learning, and memory all depend on dramatic changes in the synaptic weights throughout life. Recent progress in microscopy has extended this notion to structural synaptic plasticity, as synaptic networks were reported to be highly dynamic because of ongoing mechanisms that encompass synapse formation, stabilization, and elimination (1). Therefore, when studying synaptic plasticity today, one has to take into account both the functional and structural changes that lead to continuous remodeling of a given synaptic network.Developing cortical networks are molded by experience or activity patterns during a “sensitive period” in development (2). Similarly, newly formed neurons in the adult olfactory bulb (OB) may be subject to plastic changes during a restricted time window after generation (3). Identifying the neural mechanisms and the nature of signals that trigger changes in developing and adult brain circuits during critical periods is a matter of intense debate (4). To address this fundamental question of circuit plasticity, we used the adult OB circuit, which receives about 30,000 new neurons per day in rodents, as a model system. As in embryonic cell development, adult-born neuron integration is under a strong selection process in which half of the young neuronal population is eliminated (5). Sensory experience might promote cell survival during a specific critical window, when new neurons receive synaptic inputs from preexisting circuits (6–9) and exhibit long-term potentiation (LTP) (10). During this window, an odor-reward association task (but not a mere odor exposure) promotes cell survival (11, 12) and specific activation of adult-born neurons monitored through immediate early gene labeling (13, 14). As a result, olfactory memory is impaired when adult neurogenesis is compromised (13, 15). Conversely, the selective stimulation of adult-born neurons improves olfactory learning and memory (16), suggesting that these neurons are part of the olfactory memory engram (17). Although recent transsynaptic strategies have revealed the presynaptic connectivity of adult-born neurons (18, 19), little is known about how learning affects their structural and synaptic plasticity or which circuits and presynaptic cells are functionally recruited with them during associative learning. By demonstrating that olfactory learning triggers both selective structural rearrangements and changes in synaptic transmission onto adult-born neurons, this study represents a first attempt to link associative learning to functional plasticity of circuits endowed with adult neurogenesis.     

Novel stimuli evoke excess activity in the mouse primary visual cortex

To explore how neural circuits represent novel versus familiar inputs, we presented mice with repeated sets of images with novel images sparsely substituted. Using two-photon calcium imaging to record from layer 2/3 neurons in the mouse primary visual cortex, we found that novel images evoked excess activity in the majority of neurons. This novelty response rapidly emerged, arising with a time constant of 2.6 ± 0.9 s. When a new image set was repeatedly presented, a majority of neurons had similarly elevated activity for the first few presentations, which decayed to steady state with a time constant of 1.4 ± 0.4 s. When we increased the number of images in the set, the novelty response’s amplitude decreased, defining a capacity to store ∼15 familiar images under our conditions. These results could be explained quantitatively using an adaptive subunit model in which presynaptic neurons have individual tuning and gain control. This result shows that local neural circuits can create different representations for novel versus familiar inputs using generic, widely available mechanisms.

Because the behavioral consequences of a sensory stimulus can depend on whether that stimulus is novel or familiar, sensory systems can benefit from employing different representations of novel versus familiar stimuli. At the level of human psychophysics, stimulus novelty can enhance salience and capture attention (1–3), while familiarity can speed visual search (4). Novelty also affects aversive conditioning (5–7) and fear conditioning (8, 9). In human brain imaging, novel stimuli have been shown to generate the mismatch negativity (MMN) (10, 11) while repeated stimuli lead to repetition suppression (12). Explicit representation of novelty has been shown at higher stages of the sensory hierarchy, such as in the hippocampus (13) and inferotemporal cortex (14–16), and has been interpreted as a possible substrate of recognition memory (17). Lower in sensory hierarchies, the representation of novelty can be enhanced by stimulus-specific adaptation (SSA) (18–21) as well as by gain control (22, 23). Novelty signals are also prominently present in midbrain dopamine neurons (24).Explicit representation of stimulus novelty is also related to theories of predictive coding, in which neural circuits carry out computations that emphasize novel or surprising information. Theories of predictive coding have had a long history, starting with ideas about how the receptive field structure of retinal ganglion cells more efficiently encodes natural visual scenes by removing redundant data (25–28) and including the idea that active adaptation may aid in this process (18). Theories of predictive coding in the neocortex have typically focused on the idea that feedback from higher cortical areas encodes a prediction about lower-level sensory data (29) that is subtracted from the lower-level representation, so that the signals traveling up the cortical hierarchy represent surprise or novelty (30, 31). However, a recent study failed to find these signatures of predictive coding (32).Here, we investigate novelty processing in the mouse primary visual cortex. We repeatedly presented a set of images, each composed of a random superposition of Gabor functions, and then occasionally presented novel images drawn from the same ensemble. Using two-photon imaging of the Ca²⁺ sensor GCaMP6f to measure neural activity in layer 2/3 of awake, head-fixed mice (33), we found that the majority of neurons exhibited excess activity in response to a novel image. This distinction between novel versus familiar images was quickly reached, emerging with a time constant of 2.6 ± 0.9 s. Similarly, when we began presenting a new set of images, a majority of the neurons exhibited elevated firing that relaxed to a steady state with a time constant of 1.4 ± 0.4 s. When we presented novel images within larger image sets, the amplitude of novelty response decreased, defining a capacity of the system to encode ∼15 familiar images. All of these findings could be explained qualitatively using an adaptive subunit model in which neurons presynaptic to a recorded neuron have both individual tuning to visual stimuli and adaptive gain control.     

PirB regulates a structural substrate for cortical plasticity

Experience-driven circuit changes underlie learning and memory. Monocular deprivation (MD) engages synaptic mechanisms of ocular dominance (OD) plasticity and generates robust increases in dendritic spine density on L5 pyramidal neurons. Here we show that the paired immunoglobulin-like receptor B (PirB) negatively regulates spine density, as well as the threshold for adult OD plasticity. In PirB^−/− mice, spine density and stability are significantly greater than WT, associated with higher-frequency miniature synaptic currents, larger long-term potentiation, and deficient long-term depression. Although MD generates the expected increase in spine density in WT, in PirB^−/− this increase is occluded. In adult PirB^−/−, OD plasticity is larger and more rapid than in WT, consistent with the maintenance of elevated spine density. Thus, PirB normally regulates spine and excitatory synapse density and consequently the threshold for new learning throughout life.Experience generates both functional and structural changes in neural circuits. The learning process is robust at younger ages during developmental critical periods and continues, albeit at a lower level, into adulthood and old age (1–3). For example, young barn owls exposed to horizontally shifting prismatic spectacles can adapt readily to altered visual input, but adult owls cannot. The experience in the young owls results in a rearranged audiovisual map in tectum that is accompanied by ectopic axonal projections (1). Experience-dependent structural changes have also been observed in the mammalian cerebral cortex. Enriched sensory experience or motor learning are both associated with an increase in dendritic spine density, and a morphological shift from immature thin spines to mushroom spines which harbor larger postsynaptic densities (PSDs) and stronger synapses (4–7). On the flip side, bilateral sensory deprivation induces spine loss (8, 9). Abnormal sensory experience also results in structural modification of inhibitory synapses and circuitry that is temporally and spatially coordinated with changes in excitatory synapses on dendritic spines (10–13).These experience-driven spine changes are thought to involve synaptic mechanisms of long-term potentiation (LTP) and long-term depression (LTD). In hippocampal slices, induction of LTP causes new spines to emerge, as well as spine head enlargement on existing spines (14–16); induction of LTD results in rapid spine regression (14, 17). Importantly, the emergence or regression of spines starts soon after the induction of LTP or LTD, suggesting that these structural changes underlie the persistent expression of long-term plasticity (14, 17).Little is known about molecular mechanisms that restrict experience-dependent plasticity at circuit and synaptic levels and connect it to spine stability. Paired Ig-like receptor B (PirB), a receptor expressed in cortical pyramidal neurons, is known to limit ocular dominance (OD) plasticity both during the critical period and in adulthood (18). PirB binds major histocompatibility class I (MHCI) ligands, whose expression is regulated by visual experience and neural activity (19–21) and thus could act as a key link connecting functional to structural plasticity. If so, mice lacking PirB might be expected to have altered synaptic plasticity rules on the one hand and changes in the density and stability of dendritic spines on the other.     

Visual exposure enhances stimulus encoding and persistence in primary cortex

The brain adapts to the sensory environment. For example, simple sensory exposure can modify the response properties of early sensory neurons. How these changes affect the overall encoding and maintenance of stimulus information across neuronal populations remains unclear. We perform parallel recordings in the primary visual cortex of anesthetized cats and find that brief, repetitive exposure to structured visual stimuli enhances stimulus encoding by decreasing the selectivity and increasing the range of the neuronal responses that persist after stimulus presentation. Low-dimensional projection methods and simple classifiers demonstrate that visual exposure increases the segregation of persistent neuronal population responses into stimulus-specific clusters. These observed refinements preserve the representational details required for stimulus reconstruction and are detectable in postexposure spontaneous activity. Assuming response facilitation and recurrent network interactions as the core mechanisms underlying stimulus persistence, we show that the exposure-driven segregation of stimulus responses can arise through strictly local plasticity mechanisms, also in the absence of firing rate changes. Our findings provide evidence for the existence of an automatic, unguided optimization process that enhances the encoding power of neuronal populations in early visual cortex, thus potentially benefiting simple readouts at higher stages of visual processing.

A key property of cortical circuits is their capacity to reorganize structurally and functionally with experience (1–3). In primary visual cortex, adaptive reorganization is well documented during development (4–7) and growing evidence indicates that sensory responses continue to adapt in adulthood (8–13). The continual refinement of sensory neurons based on the statistics of the sensory environment is at odds with the traditional view of the primary visual cortex as a collection of static filters or feature detectors, passively converting sensory input into a sparse code for further feedforward processing across the visual hierarchy (14). In fact, considerable evidence suggests that primary visual cortex does not statically encode the environment but has rich spatial and temporal dynamics. For example, sensory-evoked activity propagates through the local network in wavelike patterns (15–17), displays a high degree of temporal structure (18), and can persist long after the cessation of stimulation (19–22). These rich dynamic properties exhibited by early visual neurons suggest an active involvement of primary visual cortex populations in the coordinated representation of visual stimuli. Most strikingly, repetitive visual exposure can alter the strength and selectivity of neuronal responses in the primary visual cortex, leaving a lasting mark on postexposure activity in both awake and anesthetized animals (23, 24). Yet, it remains unclear how such changes affect the joint encoding of stimuli across neuronal populations and ultimately the information transmitted to downstream areas.Given that primary neurons adapt their responses as a function of repeated exposure, one compelling hypothesis is that exposure-driven changes are coordinated across neuronal populations to collectively improve the representation and maintenance of recently experienced stimuli. Here, we test this hypothesis by investigating the impact of visual exposure on the persistent population response of neurons in cat area 17 to brief, structured stimulation. We employ a large set of abstract stimuli (letters of the Latin alphabet and Arabic numerals) that provide a rich variety of spatial conjunctions across low-level features and are well suited to capture aspects of distributed coding. We find five main signatures of functional reorganization. First, visual exposure optimizes stimulus maintenance in primary visual cortex by increasing the magnitude and decreasing the variability of neuronal responses that persist after stimulus offset. Second, these changes are associated with neural recruitment, a broadening of the dynamic range neurons employ to respond to stimuli, and an enhancement of stimulus-specific tiling of neuronal responses. Third, refinement of individual responses results in increased stimulus encoding at the population level; i.e., a simple hypothetical downstream decoder increases its accuracy in identifying recent stimuli from brief snippets of population activity. Fourth, the exposure-driven enhancements in stimulus persistence maintain the representational structure of stimuli, resulting in improved stimulus reconstruction. Fifth, exposure strengthens patterns in postexposure spontaneous activity. Finally, modeling demonstrates that exposure-driven enhancements in stimulus persistence can arise from recurrent network interactions via local, unsupervised plasticity mechanisms.     

NMDA receptor–BK channel coupling regulates synaptic plasticity in the barrel cortex

Postsynaptic N-methyl-D-aspartate receptors (NMDARs) are crucial mediators of synaptic plasticity due to their ability to act as coincidence detectors of presynaptic and postsynaptic neuronal activity. However, NMDARs exist within the molecular context of a variety of postsynaptic signaling proteins, which can fine-tune their function. Here, we describe a form of NMDAR suppression by large-conductance Ca²⁺- and voltage-gated K⁺ (BK) channels in the basal dendrites of a subset of barrel cortex layer 5 pyramidal neurons. We show that NMDAR activation increases intracellular Ca²⁺ in the vicinity of BK channels, thus activating K⁺ efflux and strong negative feedback inhibition. We further show that neurons exhibiting such NMDAR–BK coupling serve as high-pass filters for incoming synaptic inputs, precluding the induction of spike timing–dependent plasticity. Together, these data suggest that NMDAR-localized BK channels regulate synaptic integration and provide input-specific synaptic diversity to a thalamocortical circuit.

Glutamate is the primary excitatory chemical transmitter in the mammalian central nervous system (CNS), where it is essential for neuronal viability, network function, and behavioral responses (1). Glutamate activates a variety of pre- and postsynaptic receptors, including ionotropic receptors (iGluRs) that form ligand-gated cation-permeable ion channels. The iGluR superfamily includes α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs), kainate receptors, and N-methyl-D-aspartate receptors (NMDARs), all of which form tetrameric assemblies that are expressed throughout the CNS (2).NMDARs exhibit high sensitivity to glutamate (apparent half maximal effective concentration in the micromolar range) and a voltage-dependent block by Mg²⁺ (3, 4), slow gating kinetics (5), and high permeability to Ca²⁺ (6, 7) (for a review, see ref. 8). Together, these characteristics confer postsynaptic NMDARs with the ability to detect and decode coincidental activity of pre- and postsynaptic neurons: presynaptic glutamate release brings about the occupation of the agonist-binding site and AMPAR-driven postsynaptic depolarization, removing the voltage-dependent Mg²⁺ block. The coincidence of these two events leads to NMDAR activation and a Ca²⁺ influx through the channel (8, 9), which initiates several forms of synaptic plasticity (10, 11).Large-conductance Ca²⁺- and voltage-gated K⁺ (BK) channels are opened by a combination of membrane depolarization and relatively high levels of intracellular Ca²⁺ (12, 13). In CNS neurons, such micromolar Ca²⁺ increases are usually restricted to the immediate vicinity of Ca²⁺ sources, including voltage-gated Ca²⁺ channels (VGCCs) (14–16) and ryanodine receptors (RyRs) (17, 18). In addition, Ca²⁺ influx through nonselective cation-permeable channels, including NMDARs, has also been shown to activate BK channels in granule cells from the olfactory bulb and dentate gyrus (19–21). In these neurons, Ca²⁺ entry through NMDARs opens BK channels in somatic and perisomatic regions, causing the repolarization of the surrounding plasma membrane and subsequent closure of NMDARs. Because BK channel activation blunts NMDAR-mediated excitatory responses, it provides a negative feedback mechanism that modulates the excitability of these neurons (19, 20). Thus, the same characteristics that make NMDARs key components in excitatory synaptic transmission and plasticity can paradoxically give rise to an inhibitory response when NMDARs are located in the proximity of BK channels. However, it is unclear whether functional NMDAR–BK coupling is relevant at dendrites and dendritic spines.The barrel field area in the primary somatosensory cortex, also known as the barrel cortex (BC), processes information from peripheral sensory receptors for onward transmission to cortical and subcortical brain regions (22, 23). Sensory information is received in the BC from different nuclei of the thalamus. Among these nuclei, the ventral posterior medial nucleus, ventrobasal nucleus, and posterior medial nucleus are known to directly innervate layer 5 pyramidal neurons (BC-L5PNs) (24–27). In basal dendrites of BC-L5PN, the coactivation of neighboring dendritic inputs can initiate NMDAR-mediated dendritically restricted spikes characterized by large Ca²⁺ transients and long-lasting depolarizations (28–30), providing the appropriate environment for BK activation.To determine whether functional NMDAR–BK coupling plays a role in synaptic transmission, and potentially synaptic plasticity, we investigated the thalamocortical synapses at basal dendrites of BC-L5PNs. We found that the suppression of NMDAR activity by BK channels occurs in the basal dendrites of about 40% of BC-L5PNs, where NMDAR activation triggers strong negative feedback inhibition by delivering Ca²⁺ to nearby BK channels. This inhibition regulates the amplitude of postsynaptic responses and increases the threshold for the induction of synaptic plasticity. Our findings thus unveil a calibration mechanism that can decode the amount and frequency of afferent synaptic inputs by selectively attenuating synaptic plasticity and providing input-specific synaptic diversity to a thalamocortical circuit.     

Collapse of complexity of brain and body activity due to excessive inhibition and MeCP2 disruption

Complex body movements require complex dynamics and coordination among neurons in motor cortex. Conversely, a long-standing theoretical notion supposes that if many neurons in motor cortex become excessively synchronized, they may lack the necessary complexity for healthy motor coding. However, direct experimental support for this idea is rare and underlying mechanisms are unclear. Here we recorded three-dimensional body movements and spiking activity of many single neurons in motor cortex of rats with enhanced synaptic inhibition and a transgenic rat model of Rett syndrome (RTT). For both cases, we found a collapse of complexity in the motor system. Reduced complexity was apparent in lower-dimensional, stereotyped brain–body interactions, neural synchrony, and simpler behavior. Our results demonstrate how imbalanced inhibition can cause excessive synchrony among movement-related neurons and, consequently, a stereotyped motor code. Excessive inhibition and synchrony may underlie abnormal motor function in RTT.

A diverse and complex repertoire of body movements requires diverse and complex neural activity among cortical neurons. Moreover, interactions between movement-related neurons and the body must be sufficiently high dimensional to carry these movement signals with high fidelity. The complexity of movement-related neural activity and neuron–body interactions can be compromised if synchrony among neurons is excessive. Indeed, it is well understood theoretically that excessive correlations can limit the information capacity of any neural code (1–3)—if all neurons are perfectly synchronized, then different neurons cannot encode different motor signals. Synchrony is also known to play a role in pathophysiology of movement-related disorders, like Parkinson’s disease (4–6). However, synchrony and correlations also contribute to healthy function in the motor system (7–14). For instance, particular groups of synchronized neurons seem to send control signals to particular muscle groups (7, 8) and propagation of correlated firing contributes to motor planning (10). Synchrony can also play a role in motor learning (12–14). These findings suggest that correlated activity among specific subsets of neurons encodes specific motor functions. Thus, it stands to reason that if this synchrony became less selective and more stereotyped across neurons, then the motor code would become less complex and lose specificity, resulting in compromised motor function.Here we explored this possibility in rats, in the caudal part of motor cortex where neurons associated with hindlimb, forelimb, and trunk body movement are located (15–17). We focused on two conditions. First, we studied a transgenic rat model of Rett syndrome (RTT), which has disrupted expression of the MeCP2 gene. Second, we studied normal rats with acutely altered inhibitory neural interactions. Both of these cases are associated with abnormal motor behavior and, possibly, abnormal synchrony. Abnormal synchrony is a possibility, because both of these cases are linked to an imbalance between excitatory (E) and inhibitory (I) neural interactions, which in turn is likely to result in abnormal synchrony. For instance, many computational models suggest that synchrony is strongly dependent on E/I interactions (18–21). Likewise, in experiments, pharmacological manipulation of E/I causes changes in synchrony (19, 22, 23) and the excessive synchrony that occurs during epileptic seizures is often attributed to an E/I imbalance (24, 25). Similarly, the majority of people with RTT suffer from seizures (26) and many previous studies establish E/I imbalance as a common problem in RTT (27). MeCP2 dysfunction, which is known to cause RTT, seems to be particularly important in inhibitory neurons (28). For instance, two studies have shown that disrupting MeCP2 only in specific inhibitory neuron types can recapitulate the effects of brain-wide disruption of MeCP2 (29, 30). However, whether the E/I imbalance favors E or I at the population level seems to vary across different brain regions in RTT. Studies of visual cortex (29) and hippocampus (31) suggest that the balance tips toward too much excitation (perhaps explaining the prevalence of seizures), while studies of somatosensory cortex (32, 33) and a brain-wide study of Fos expression (34) suggest that frontal areas, including motor cortex, are tipped toward excessive inhibition. These facts motivated our choice to study pharmacological disruption of inhibition here. While it is clear that E/I imbalance is important in RTT, it is much less clear how it manifests at the level of dynamics and complexity of neural activity that is responsible for coordinating body movements. Thus, in addition to pursuing the general questions about synchrony and complexity in the motor system discussed above, a second goal of our work was to improve understanding of motor dysfunction due to MeCP2 disruption.Taken together, these facts led us to the following questions: How does MeCP2 disruption impact the complexity of body movements, movement-related neural activity, and motor coding? Are abnormalities in the MeCP2-disrupted motor system consistent with excessive inhibition in motor cortex? We hypothesized that both MeCP2 disruption and excessive inhibition lead to reduced complexity of interactions between cortical neurons and body movements, excessive cortical synchrony, and reduced complexity of body movements. Our findings confirmed this hypothesis and suggest that RTT-related motor dysfunction may be due, in part, to excessive synchrony and inhibition in motor cortex.     

In vivo imaging of immediate early gene expression reveals layer-specific memory traces in the mammalian brain

The dynamic processes of formatting long-term memory traces in the cortex are poorly understood. The investigation of these processes requires measurements of task-evoked neuronal activities from large numbers of neurons over many days. Here, we present a two-photon imaging-based system to track event–related neuronal activity in thousands of neurons through the quantitative measurement of EGFP proteins expressed under the control of the EGR1 gene promoter. A recognition algorithm was developed to detect GFP-positive neurons in multiple cortical volumes and thereby to allow the reproducible tracking of 4,000 neurons in each volume for 2 mo. The analysis revealed a context-specific response in sparse layer II neurons. The context-evoked response gradually increased during several days of training and was maintained 1 mo later. The formed traces were specifically activated by the training context and were linearly correlated with the behavioral response. Neuronal assemblies that responded to specific contexts were largely separated, indicating the sparse coding of memory-related traces in the layer II cortical circuit.In the mammalian brain, memory traces in cortical areas are poorly understood. In contrast to the medial temporal lobe, particularly the hippocampus, which is involved in the temporary storage of declarative memories (1, 2), the neocortex is believed to store remote memories (3–6). However, remarkably little knowledge regarding the sites and dynamics of remote memory storage has been revealed at the cellular level owing to the complexity of the connections and the large number of neurons within the cortical circuit.In vivo electrophysiological recording of neuronal firing revolutionized neurobiology by linking neuronal activity with animal behavior. The small number of neurons recorded by the electrodes, however, was a limitation, as information coding and decoding may use an army of neurons forming neuronal assemblies (7, 8). Efforts to record the activity of larger populations of neurons in cortical volumes have been actively pursued by either increasing the number of electrode probes (7, 9–11) or using calcium indicator–based imaging (12–15) and immediate early gene (IEG)-based reporters (16–18). The expression of IEGs is correlated with the averaged neuronal activation on external stimuli (19, 20), implying that the marked neurons are involved in behavior (1, 21–25). Studies using in vivo imaging of IEGs have revealed cortical coding in the visual cortex and in other cortical areas, reflecting electrical activation in individual neurons (16, 17). Among IEGs, the expression of early growth response protein 1 (EGR1, also known as zif268) is associated with high-frequency stimulation and the induction of long-term plasticity during learning (26, 27). To measure neuronal activation in cortical circuits during a behavioral task, we used an EGR1 expression reporter mouse line in which the expression of the EGFP protein is under the control of the Egr1 gene promoter. We designed offline recording strategies to monitor task-associated neuronal activity by quantifying changes in cellular EGFP signals in the mouse cortex. Patterns of activated neuronal assemblies during different tasks were visualized in the entire cortical volume. Furthermore, through computer recognition-based reconstruction, we were able to track the activity-related cellular EGFP signals from multiple cortical areas for 2 mo to reveal memory-related changes in the cortical circuit.     

Cellular organization of cortical barrel columns is whisker-specific

The cellular organization of the cortex is of fundamental importance for elucidating the structural principles that underlie its functions. It has been suggested that reconstructing the structure and synaptic wiring of the elementary functional building block of mammalian cortices, the cortical column, might suffice to reverse engineer and simulate the functions of entire cortices. In the vibrissal area of rodent somatosensory cortex, whisker-related “barrel” columns have been referred to as potential cytoarchitectonic equivalents of functional cortical columns. Here, we investigated the structural stereotypy of cortical barrel columns by measuring the 3D neuronal composition of the entire vibrissal area in rat somatosensory cortex and thalamus. We found that the number of neurons per cortical barrel column and thalamic “barreloid” varied substantially within individual animals, increasing by ∼2.5-fold from dorsal to ventral whiskers. As a result, the ratio between whisker-specific thalamic and cortical neurons was remarkably constant. Thus, we hypothesize that the cellular architecture of sensory cortices reflects the degree of similarity in sensory input and not columnar and/or cortical uniformity principles.Two major concepts of cortical neuronal organization have been proposed. Structurally, correlations between stereology-based measurements (1) of neuron density and cortical thickness resulted in the hypothesis of structural uniformity, arguing that the number of neurons beneath a square millimeter of cortical surface is constant and independent of cortical area and species (2, 3). Functionally, cortex is organized in a columnar fashion, reflecting similar neuronal activity along the vertical cortex axis in response to peripheral stimuli (4–8). Similar spatial extents of functional cortical columns in the horizontal plane, combined with the idea of cortical uniformity, resulted in the notion that a stereotypic columnar network may also represent the elementary structural building block of sensory cortices (9). In combination, the two concepts thus suggested a common organization of all sensory cortices, which led to reverse engineering and simulation efforts that build up large-scale network models of repeatedly occurring identical cortical circuits (10, 11).The ideal model system for investigating columnar structure and function is the vibrissal area of rodent somatosensory cortex. There, “barrels” of neurons in layer 4 (L4) have been identified as somatotopically organized structural correlates of peripheral receptor organs (i.e., facial whiskers). Whisker/barrel columns have thus been regarded as both structural and functional elementary cortical units (12–14). To investigate the structural stereotypy of cortical barrel columns, independent of the drawbacks associated with stereology (i.e., extrapolations from small sampling regions), we decided to locate each excitatory and inhibitory neuron soma within the entire volume of interest. Using high-resolution, large-scale confocal microscopy (15) and automated image-processing routines (16), we found that the number of neurons per barrel column increased by ∼2.5-fold from columns that correspond to the dorsal facial whiskers (A-row) to columns corresponding to the ventral whiskers (E-row). Moreover, cortical thickness increased by ∼500 μm from A- to E-rows, resulting in whisker-specific laminar neuron profiles, layer locations, and thicknesses. Further, the distributions of excitatory and inhibitory neurons outside the L4 barrels were indistinguishable between barrel columns, the septa (the cortex separating the barrel columns) (14) and the dysgranular zones (DZ) surrounding the vibrissal cortex (17).We performed the same analyses for the ventral posterior medial division (VPM) of rat thalamus, which provides whisker-specific input to the vibrissal cortex (18–20). Again, we found that the number of neurons per whisker (i.e., within so-called “barreloids”) (21) was constant within a whisker row, but increased by ∼2.5-fold from the A- to the E-row. Consequently, the ratio between neurons per barrel (column) and respective barreloid was remarkably constant. This whisker-specific cellular organization is in contrast to the ideas of columnar and cortical uniformity, questioning the stereology-based concept that mammalian cortices are composed of stereotypical elementary building blocks.     

Cortical control of adaptation and sensory relay mode in the thalamus

A major synaptic input to the thalamus originates from neurons in cortical layer 6 (L6); however, the function of this cortico–thalamic pathway during sensory processing is not well understood. In the mouse whisker system, we found that optogenetic stimulation of L6 in vivo results in a mixture of hyperpolarization and depolarization in the thalamic target neurons. The hyperpolarization was transient, and for longer L6 activation (>200 ms), thalamic neurons reached a depolarized resting membrane potential which affected key features of thalamic sensory processing. Most importantly, L6 stimulation reduced the adaptation of thalamic responses to repetitive whisker stimulation, thereby allowing thalamic neurons to relay higher frequencies of sensory input. Furthermore, L6 controlled the thalamic response mode by shifting thalamo–cortical transmission from bursting to single spiking. Analysis of intracellular sensory responses suggests that L6 impacts these thalamic properties by controlling the resting membrane potential and the availability of the transient calcium current I_T, a hallmark of thalamic excitability. In summary, L6 input to the thalamus can shape both the overall gain and the temporal dynamics of sensory responses that reach the cortex.Sensory signals en route to the cortex undergo profound signal transformations in the thalamus. One important thalamic transformation is sensory adaptation. Adaptation is a common characteristic of sensory systems in which neural output adjusts to the statistics and dynamics of past stimuli, thereby better encoding small stimulus changes across a wide range of scales despite the limited range of possible neural outputs (1–3). Thalamic sensory adaptation is characterized by a steep decrease in action potential (AP) activity during sustained sensory stimulation (4–7), decreasing the efficacy at which subsequent sensory stimuli are transmitted to the cortex.The widely reported duality of thalamic response mode is another key property of thalamic information processing which further affects how sensory input reaches the cortex. In burst mode, sensory inputs are relayed as short, rapid clusters of APs; in contrast, in tonic mode the same inputs are translated into single APs. Both tonic and burst modes have been described during anesthesia/sleep and wakefulness/behavior, with a pronounced shift toward the tonic mode during alertness (8–12).Although the exact information content of thalamic bursts is not yet clear, it has been suggested that bursting may signal novel stimuli to the cortex, whereas the tonic mode enables linear encoding of fine stimulus details, e.g., when an object is examined (13, 14). One issue hampering the interpretation of burst/tonic responses is that currently it is unknown if the cortex itself is involved in the rapid changes in firing modes seen in the awake and anesthetized animal (15, 16) and which mechanisms initiate these shifts in vivo.On the biophysical level, the response mode depends on the resting membrane potential (RMP), which controls the availability of the transient low-threshold calcium current (I_T) (17). Depolarization decreases the size of the I_T-mediated low-threshold calcium spike (LTS), and fewer burst spikes are fired (18). Similarly, RMP influences adaptation in that depolarization reduces the voltage distance to the AP threshold, thereby increasing the probability that smaller, depressed inputs will trigger APs (6). Thus, the dynamics of the RMP may govern several key properties of signal transformation in the thalamus, thereby providing a common mechanism for controlling thalamic adaptation and response mode.Although subcortical inputs have been shown to influence thalamic firing modes (7, 9), we investigated the impact of cortical activity on thalamic sensory processing. Cortico–thalamic projections from cortical layer 6 (L6) are a likely candidate for regulating thalamic sensory processing with high spatial and temporal precision, because these projections provide a major input to the thalamus and, as shown by McCormick et al. (19), depolarize and modulate firing of thalamic cells in vitro.However, because of the inability to study sensory signals in brain slices, the role of L6 on thalamic input/output properties during sensory processing is not clear. Here, in the ventro posteromedial nucleus (VPM) of the mouse whisker thalamus, we investigate how L6 impacts the transmission of whisker inputs to the cortex. Recent advances in cell-type–specific approaches to dissect specific circuits in vivo (20–22) allowed us to activate the L6–thalamic pathway specifically and determine its impact on thalamic sensory processing.We found that cortical L6 can change key properties of thalamic sensory processing by controlling the interaction of intrinsic membrane properties and sensory inputs. This mechanism enables the cortex to control the frequency-dependent adaptation and the gain of its own input.     

Syngap1 regulates experience-dependent cortical ensemble plasticity by promoting in vivo excitatory synapse strengthening

A significant proportion of autism risk genes regulate synapse function, including plasticity, which is believed to contribute to behavioral abnormalities. However, it remains unclear how impaired synapse plasticity contributes to network-level processes linked to adaptive behaviors, such as experience-dependent ensemble plasticity. We found that Syngap1, a major autism risk gene, promoted measures of experience-dependent excitatory synapse strengthening in the mouse cortex, including spike-timing–dependent glutamatergic synaptic potentiation and presynaptic bouton formation. Synaptic depression and bouton elimination were normal in Syngap1 mice. Within cortical networks, Syngap1 promoted experience-dependent increases in somatic neural activity in weakly active neurons. In contrast, plastic changes to highly active neurons from the same ensemble that paradoxically weaken with experience were unaffected. Thus, experience-dependent excitatory synapse strengthening mediated by Syngap1 shapes neuron-specific plasticity within cortical ensembles. We propose that other genes regulate neuron-specific weakening within ensembles, and together, these processes function to redistribute activity within cortical networks during experience.

Autism risk genes converge on several neurobiological functions, including the regulation of synapse biology (1–3). Synapse processes directly controlled by autism spectrum disorder (ASD) risk genes include de novo synapse formation, synapse maturation, and activity-driven changes in synapse function (i.e., synapse plasticity). Synapse plasticity, especially in cortical excitatory neurons, is a process enabling neural circuits to store new information, which is essential for experience-dependent modifications of behavior to promote survival (4, 5). Thus, risk genes are thought to contribute to ASD etiology by disrupting how neural circuits change in response to novel experiences, which in turn contributes to maladaptive behaviors. However, the study of risk gene biology and their relationship to neural plasticity is largely restricted to reduced biological preparations that focus on isolated changes to a small subset of synapses. Therefore, it is unclear how risk gene–driven regulation of synapse plasticity contributes to changes in neural dynamics within intact functional networks known to drive adaptive behaviors.Neuronal ensembles, or groups of coactivated neurons, are thought to be the direct neural substrate of cognitive processes and behavior (6). In cortex, ensemble plasticity is a multidimensional process that reflects the distribution of distinct cellular plasticity mechanisms across individual neuronal components within the assembly. For example, neurons within the same sensory-evoked cortical ensemble can undergo either increases or decreases in activity in response to the same sensory experience (7–9). While this general phenomenon has been observed in multiple contexts, it is unclear how neurons within the same functional network can have opposing changes to enduring neuronal activity in response to the same sensory experience. One way that this may occur is through the simultaneous activation of distinct forms of experience-dependent plasticity that are differentially distributed throughout neurons that comprise a functional network. Indeed, sensory experience drives the induction of Hebbian-type synaptic plasticity that can strengthen or weaken excitatory synaptic input onto sensory-responsive neurons (10). Experience-dependent circuit plasticity is not limited to changes in excitatory synaptic strength. Robust changes to the function and connectivity of GABAergic interneurons within cortical microcircuits also occurs in response to novel experience, which in turn regulates the output of pyramidal neurons (11–13). Moreover, intrinsic changes to neuronal excitability have also been observed, and in combination with changes to GABAergic function, these collective processes are thought to maintain a set firing rate within networks even as activity is redistributed among individual neurons (8, 14, 15).We propose that experience induces heterogenous changes in activity within neurons of a cortical assembly through cellular processes controlled, at least in part, by genetic mechanisms linked to ASD risk. This hypothesis originates from the clear overrepresentation of ASD risk genes that regulate the neurobiology of synapses and synapse plasticity (1–3). However, because of the multidimensional nature of cortical network plasticity, one cannot infer how a gene influences experience-dependent changes in distributed network dynamics when the function of the gene has only been studied in isolated subcellular structures, such as synapses. It is therefore important to study major ASD risk genes in the context of intact functional networks. Doing so will help to elucidate how their influence over molecular and cellular functions contribute to intermediate network-level processes more directly linked to behaviors, such as cortical ensemble plasticity.In this study, we investigated how a major ASD risk gene, SYNGAP1/Syngap1 (HUMAN/mouse–mouse only from now on), regulates specific aspects of cellular plasticity in vivo and how this process shapes experience-dependent ensemble plasticity with sensory-responsive cortical networks. The Syngap1 gene, which is a major autism risk factor (16), is a robust regulator of various forms of long-term potentiation (LTP) (17), a cellular model of Hebbian plasticity. It regulates LTP through control of excitatory synapse structure and function by gating NMDA receptor-dependent regulation of AMPA receptor trafficking and dendritic spine size (18–20). The role of Syngap1 in regulating synapse plasticity has been observed by various researchers across distinct neuronal subtypes in a variety of in vitro and ex vivo preparations (21–24). Based on this past work in reduced preparations, we hypothesized that Syngap1 regulates experience-dependent ensemble plasticity by promoting the strengthening of excitatory synapses within functional cortical networks. We found that Syngap1 was required for spike-timing-dependent (STD) synaptic potentiation and experience-mediated synapse bouton formation in layer (L) 2/3 of somatosensory cortex (SSC) but not synaptic depression or synapse bouton elimination. Syngap1 heterozygosity in mice disrupted experience-dependent potentiation of neuronal activity within a subpopulation of L2/3 SSC neurons. Syngap1 loss of function had no effect on plasticity of neurons within the same ensemble that weakens with experience. These findings indicate that disruptions to synapse-level strengthening mechanisms in Syngap1 mice contribute to imbalanced cortical ensemble plasticity driven by novel sensory experience. We propose that a key function of Syngap1 is to promote complex network-level plasticity through the strengthening of excitatory connections within cortical circuits.