M2 receptors are required for spatiotemporal sequence learning in mouse primary visual cortex.

Acetylcholine is a neurotransmitter that plays a variety of roles in the central nervous system. It was previously shown that blocking muscarinic receptors with a nonselective antagonist prevents a form of experience-dependent plasticity termed "spatiotemporal sequence learning" in the mouse primary visual cortex (V1). Muscarinic signaling is a complex process involving the combined activities of five different G protein-coupled receptors, M1-M5, all of which are expressed in the murine brain but differ from each other functionally and in anatomical localization. Here we present electrophysiological evidence that M2, but not M1, receptors are required for spatiotemporal sequence learning in mouse V1. We show in male mice that M2 is highly expressed in the neuropil in V1, especially in thalamorecipient layer 4, and colocalizes with the soma in a subset of somatostatin-expressing neurons in deep layers. We also show that expression of M2 receptors is higher in the monocular region of V1 than it is in the binocular region but that the amount of experience-dependent sequence potentiation is similar in both regions and that blocking muscarinic signaling after visual stimulation does not prevent plasticity. This work establishes a new functional role for M2-type receptors in processing temporal information and demonstrates that monocular circuits are modified by experience in a manner similar to binocular circuits.NEW & NOTEWORTHY Muscarinic acetylcholine receptors are required for multiple forms of plasticity in the brain and support perceptual functions, but the precise role of the five subtypes (M1-M5) are unclear. Here we show that the M2 receptor is specifically required to encode experience-dependent representations of spatiotemporal relationships in both monocular and binocular regions of mouse V1. This work identifies a novel functional role for M2 receptors in coding temporal information into cortical circuits.

Learned response dynamics reflect stimulus timing and encode temporal expectation violations in superficial layers of mouse V1.

The ability to recognize ordered event sequences is a fundamental component of sensory cognition and underlies the capacity to generate temporally specific expectations of future events based on previous experience. Various lines of evidence suggest that the primary visual cortex participates in some form of predictive processing, but many details remain ambiguous. Here we use two-photon calcium imaging in layer 2/3 (L2/3) of the mouse primary visual cortex (V1) to study changes to neural activity under a multi-day sequence learning paradigm with respect to prediction error responses, stimulus encoding, and time. We find increased neural activity at the time an expected, but omitted, stimulus would have occurred but no significant prediction error responses following an unexpected stimulus substitution. Sequence representations became sparser and less correlated with training, although these changes had no effect on decoding accuracy of stimulus identity or timing. Additionally, we find that experience modifies the temporal structure of stimulus responses to produce a bias towards predictive stimulus-locked activity. Finally, we find significant temporal structure during intersequence rest periods that was largely unchanged by training.

Visual stimulation drives retinotopic acetylcholine release in the mouse visual cortex.

Cholinergic signaling is involved with a variety of brain functions including learning and memory, attention, and behavioral state modulation. The spatiotemporal characteristics of neocortical acetylcholine (ACh) release in response to sensory inputs are poorly understood, but a lack of intra-region topographic organization of cholinergic projections from the basal forebrain has suggested diffuse release patterns and volume transmission. Here, we use mesoscopic imaging of fluorescent ACh sensors to show that visual stimulation results in ACh release patterns that conform to a retinotopic map of visual space in the mouse primary visual cortex, suggesting new modes of functional cholinergic signaling in cortical circuits.x.

Optogenetic manipulation of inhibitory interneurons can be used to validate a model of spatiotemporal sequence learning.

The brain uses temporal information to link discrete events into memory structures supporting recognition, prediction, and a wide variety of complex behaviors. It is still an open question how experience-dependent synaptic plasticity creates memories including temporal and ordinal information. Various models have been proposed to explain how this could work, but these are often difficult to validate in a living brain. A recent model developed to explain sequence learning in the visual cortex encodes intervals in recurrent excitatory synapses and uses a learned offset between excitation and inhibition to generate precisely timed "messenger" cells that signal the end of an instance of time. This mechanism suggests that the recall of stored temporal intervals should be particularly sensitive to the activity of inhibitory interneurons that can be easily targeted in vivo with standard optogenetic tools. In this work we examined how simulated optogenetic manipulations of inhibitory cells modifies temporal learning and recall based on these mechanisms. We show that disinhibition and excess inhibition during learning or testing cause characteristic errors in recalled timing that could be used to validate the model in vivo using either physiological or behavioral measurements.

Expectation violations produce error signals in mouse V1.

Repeated exposure to visual sequences changes the form of evoked activity in the primary visual cortex (V1). Predictive coding theory provides a potential explanation for this, namely that plasticity shapes cortical circuits to encode spatiotemporal predictions and that subsequent responses are modulated by the degree to which actual inputs match these expectations. Here we use a recently developed statistical modeling technique called Model-Based Targeted Dimensionality Reduction (MbTDR) to study visually evoked dynamics in mouse V1 in the context of an experimental paradigm called "sequence learning." We report that evoked spiking activity changed significantly with training, in a manner generally consistent with the predictive coding framework. Neural responses to expected stimuli were suppressed in a late window (100-150 ms) after stimulus onset following training, whereas responses to novel stimuli were not. Substituting a novel stimulus for a familiar one led to increases in firing that persisted for at least 300 ms. Omitting predictable stimuli in trained animals also led to increased firing at the expected time of stimulus onset. Finally, we show that spiking data can be used to accurately decode time within the sequence. Our findings are consistent with the idea that plasticity in early visual circuits is involved in coding spatiotemporal information.

Sex and estrous cycle affect experience-dependent plasticity in mouse primary visual cortex.

Sex hormones can affect cellular physiology and modulate synaptic plasticity, but it is not always clear whether or how sex-dependent differences identified in vitro express themselves as functional dimorphisms in the brain. Historically, most experimental neuroscience has been conducted using only male animals and the literature is largely mute about whether including female mice in will introduce variability due to inherent sex differences or endogenous estrous cycles. Though this is beginning to change following an NIH directive that sex should be included as a factor in vertebrate research, the lack of information raises practical issues around how to design experimental controls and apply existing knowledge to more heterogeneous populations. Various lines of research suggest that visual processing can be affected by sex and estrous cycle stage. For these reasons, we performed a series of in vivo electrophysiological experiments to characterize baseline visual function and experience-dependent plasticity in the primary visual cortex (V1) of male and female mice. We find that sex and estrous stage have no statistically significant effect on baseline acuity measurements, but that both sex and estrous stage have can modulate two mechanistically distinct forms of experience dependent cortical plasticity. We also demonstrate that resulting variability can be largely controlled with appropriate normalizations. These findings suggest that V1 plasticity can be used for mechanistic studies focusing on how sex hormones effect experience dependent plasticity in the mammalian cortex.

Efficient Temporal Coding in the Early Visual System: Existing Evidence and Future Directions.

While it is universally accepted that the brain makes predictions, there is little agreement about how this is accomplished and under which conditions. Accurate prediction requires neural circuits to learn and store spatiotemporal patterns observed in the natural environment, but it is not obvious how such information should be stored, or encoded. Information theory provides a mathematical formalism that can be used to measure the efficiency and utility of different coding schemes for data transfer and storage. This theory shows that codes become efficient when they remove predictable, redundant spatial and temporal information. Efficient coding has been used to understand retinal computations and may also be relevant to understanding more complicated temporal processing in visual cortex. However, the literature on efficient coding in cortex is varied and can be confusing since the same terms are used to mean different things in different experimental and theoretical contexts. In this work, we attempt to provide a clear summary of the theoretical relationship between efficient coding and temporal prediction, and review evidence that efficient coding principles explain computations in the retina. We then apply the same framework to computations occurring in early visuocortical areas, arguing that data from rodents is largely consistent with the predictions of this model. Finally, we review and respond to criticisms of efficient coding and suggest ways that this theory might be used to design future experiments, with particular focus on understanding the extent to which neural circuits make predictions from efficient representations of environmental statistics.

Visual Sequences Drive Experience-Dependent Plasticity in Mouse Anterior Cingulate Cortex.

Mechanisms of experience-dependent plasticity have been well characterized in mouse primary visual cortex (V1), including a form of potentiation driven by repeated presentations of a familiar visual sequence ("sequence plasticity"). The prefrontal anterior cingulate cortex (ACC) responds to visual stimuli, yet little is known about if and how visual experience modifies ACC circuits. We find that mouse ACC exhibits sequence plasticity, but in contrast to V1, the plasticity expresses as a change in response timing, rather than a change in response magnitude. Sequence plasticity is absent in ACC, but not V1, in a mouse model of a neurodevelopmental disorder associated with intellectual disability and autism-like features. Our results demonstrate that simple sensory stimuli can be used to reveal how experience functionally (or dysfunctionally) modifies higher-order prefrontal circuits and suggest a divergence in how ACC and V1 encode familiarity.

Subanesthetic Ketamine Reactivates Adult Cortical Plasticity to Restore Vision from Amblyopia.

Subanesthetic ketamine evokes rapid and long-lasting antidepressant effects in human patients. The mechanism for ketamine's effects remains elusive, but ketamine may broadly modulate brain plasticity processes. We show that single-dose ketamine reactivates adult mouse visual cortical plasticity and promotes functional recovery of visual acuity defects from amblyopia. Ketamine specifically induces downregulation of neuregulin-1 (NRG1) expression in parvalbumin-expressing (PV) inhibitory neurons in mouse visual cortex. NRG1 downregulation in PV neurons co-tracks both the fast onset and sustained decreases in synaptic inhibition to excitatory neurons, along with reduced synaptic excitation to PV neurons in vitro and in vivo following a single ketamine treatment. These effects are blocked by exogenous NRG1 as well as PV targeted receptor knockout. Thus, ketamine reactivation of adult visual cortical plasticity is mediated through rapid and sustained cortical disinhibition via downregulation of PV-specific NRG1 signaling. Our findings reveal the neural plasticity-based mechanism for ketamine-mediated functional recovery from adult amblyopia.

Contrasting roles for parvalbumin-expressing inhibitory neurons in two forms of adult visual cortical plasticity.

The roles played by cortical inhibitory neurons in experience-dependent plasticity are not well understood. Here we evaluate the participation of parvalbumin-expressing (PV+) GABAergic neurons in two forms of experience-dependent modification of primary visual cortex (V1) in adult mice: ocular dominance (OD) plasticity resulting from monocular deprivation and stimulus-selective response potentiation (SRP) resulting from enriched visual experience. These two forms of plasticity are triggered by different events but lead to a similar increase in visual cortical response. Both also require the NMDA class of glutamate receptor (NMDAR). However, we find that PV+ inhibitory neurons in V1 play a critical role in the expression of SRP and its behavioral correlate of familiarity recognition, but not in the expression of OD plasticity. Furthermore, NMDARs expressed within PV+ cells, reversibly inhibited by the psychotomimetic drug ketamine, play a critical role in SRP, but not in the induction or expression of adult OD plasticity.

Visual recognition memory, manifested as long-term habituation, requires synaptic plasticity in V1.

Familiarity with stimuli that bring neither reward nor punishment, manifested through behavioral habituation, enables organisms to detect novelty and devote cognition to important elements of the environment. Here we describe in mice a form of long-term behavioral habituation to visual grating stimuli that is selective for stimulus orientation. Orientation-selective habituation (OSH) can be observed both in exploratory behavior in an open arena and in a stereotyped motor response to visual stimuli in head-restrained mice. We found that the latter behavioral response, termed a 'vidget', requires V1. Parallel electrophysiological recordings in V1 revealed that plasticity, in the form of stimulus-selective response potentiation (SRP), occurred in layer 4 of V1 as OSH developed. Local manipulations of V1 that prevented and reversed electrophysiological modifications likewise prevented and reversed memory demonstrated behaviorally. These findings suggest that a form of long-term visual recognition memory is stored via synaptic plasticity in primary sensory cortex.

Higher brain functions served by the lowly rodent primary visual cortex.

It has been more than 50 years since the first description of ocular dominance plasticity--the profound modification of primary visual cortex (V1) following temporary monocular deprivation. This discovery immediately attracted the intense interest of neurobiologists focused on the general question of how experience and deprivation modify the brain as a potential substrate for learning and memory. The pace of discovery has quickened considerably in recent years as mice have become the preferred species to study visual cortical plasticity, and new studies have overturned the dogma that primary sensory cortex is immutable after a developmental critical period. Recent work has shown that, in addition to ocular dominance plasticity, adult visual cortex exhibits several forms of response modification previously considered the exclusive province of higher cortical areas. These "higher brain functions" include neural reports of stimulus familiarity, reward-timing prediction, and spatiotemporal sequence learning. Primary visual cortex can no longer be viewed as a simple visual feature detector with static properties determined during early development. Rodent V1 is a rich and dynamic cortical area in which functions normally associated only with "higher" brain regions can be studied at the mechanistic level.

What does scalar timing tell us about neural dynamics?

The "Scalar Timing Law," which is a temporal domain generalization of the well known Weber Law, states that the errors estimating temporal intervals scale linearly with the durations of the intervals. Linear scaling has been studied extensively in human and animal models and holds over several orders of magnitude, though to date there is no agreed upon explanation for its physiological basis. Starting from the assumption that behavioral variability stems from neural variability, this work shows how to derive firing rate functions that are consistent with scalar timing. We show that firing rate functions with a log-power form, and a set of parameters that depend on spike count statistics, can account for scalar timing. Our derivation depends on a linear approximation, but we use simulations to validate the theory and show that log-power firing rate functions result in scalar timing over a large range of times and parameters. Simulation results match the predictions of our model, though our initial formulation results in a slight bias toward overestimation that can be corrected using a simple iterative approach to learn a decision threshold.

Learned spatiotemporal sequence recognition and prediction in primary visual cortex.

Learning to recognize and predict temporal sequences is fundamental to sensory perception and is impaired in several neuropsychiatric disorders, but little is known about where and how this occurs in the brain. We discovered that repeated presentations of a visual sequence over a course of days resulted in evoked response potentiation in mouse V1 that was highly specific for stimulus order and timing. Notably, after V1 was trained to recognize a sequence, cortical activity regenerated the full sequence even when individual stimulus elements were omitted. Our results advance the understanding of how the brain makes 'intelligent guesses' on the basis of limited information to form visual percepts and suggest that it is possible to study the mechanistic basis of this high-level cognitive ability by studying low-level sensory systems.

Spontaneous and evoked release are independently regulated at individual active zones.

Neurotransmitter release from synaptic vesicle fusion is the fundamental mechanism for neuronal communication at synapses. Evoked release following an action potential has been well characterized for its function in activating the postsynaptic cell, but the significance of spontaneous release is less clear. Using transgenic tools to image single synaptic vesicle fusion events at individual release sites (active zones) in Drosophila, we characterized the spatial and temporal dynamics of exocytotic events that occur spontaneously or in response to an action potential. We also analyzed the relationship between these two modes of fusion at single release sites. A majority of active zones participate in both modes of fusion, although release probability is not correlated between the two modes of release and is highly variable across the population. A subset of active zones is specifically dedicated to spontaneous release, indicating a population of postsynaptic receptors is uniquely activated by this mode of vesicle fusion. Imaging synaptic transmission at individual release sites also revealed general rules for spontaneous and evoked release, and indicate that active zones with similar release probability can cluster spatially within individual synaptic boutons. These findings suggest neuronal connections contain two information channels that can be spatially segregated and independently regulated to transmit evoked or spontaneous fusion signals.

Scaling of perceptual errors can predict the shape of neural tuning curves.

Weber's law, first characterized in the 19th century, states that errors estimating the magnitude of perceptual stimuli scale linearly with stimulus intensity. This linear relationship is found in most sensory modalities, generalizes to temporal interval estimation, and even applies to some abstract variables. Despite its generality and long experimental history, the neural basis of Weber's law remains unknown. This work presents a simple theory explaining the conditions under which Weber's law can result from neural variability and predicts that the tuning curves of neural populations which adhere to Weber's law will have a log-power form with parameters that depend on spike-count statistics. The prevalence of Weber's law suggests that it might be optimal in some sense. We examine this possibility, using variational calculus, and show that Weber's law is optimal only when observed real-world variables exhibit power-law statistics with a specific exponent. Our theory explains how physiology gives rise to the behaviorally characterized Weber's law and may represent a general governing principle relating perception to neural activity.

A single spiking neuron that can represent interval timing: analysis, plasticity and multi-stability.

The ability to represent interval timing is crucial for many common behaviors, such as knowing whether to stop when the light turns from green to yellow. Neural representations of interval timing have been reported in the rat primary visual cortex and we have previously presented a computational framework describing how they can be learned by a network of neurons. Recent experimental and theoretical results in entorhinal cortex have shown that single neurons can exhibit persistent activity, previously thought to be generated by a network of neurons. Motivated by these single neuron results, we propose a single spiking neuron model that can learn to compute and represent interval timing. We show that a simple model, reduced analytically to a single dynamical equation, captures the average behavior of the complete high dimensional spiking model very well. Variants of this model can be used to produce bi-stable or multi-stable persistent activity. We also propose a plasticity rule by which this model can learn to represent different intervals and different levels of persistent activity.

A network of spiking neurons that can represent interval timing: mean field analysis.

Despite the vital importance of our ability to accurately process and encode temporal information, the underlying neural mechanisms are largely unknown. We have previously described a theoretical framework that explains how temporal representations, similar to those reported in the visual cortex, can form in locally recurrent cortical networks as a function of reward modulated synaptic plasticity. This framework allows networks of both linear and spiking neurons to learn the temporal interval between a stimulus and paired reward signal presented during training. Here we use a mean field approach to analyze the dynamics of non-linear stochastic spiking neurons in a network trained to encode specific time intervals. This analysis explains how recurrent excitatory feedback allows a network structure to encode temporal representations.

Rapid structural remodeling of thalamocortical synapses parallels experience-dependent functional plasticity in mouse primary visual cortex.

Monocular lid closure (MC) causes a profound shift in the ocular dominance (OD) of neurons in primary visual cortex (V1). Anatomical studies in both cat and mouse V1 suggest that large-scale structural rearrangements of eye-specific thalamocortical (TC) axons in response to MC occur much more slowly than the shift in OD. Consequently, there has been considerable debate as to whether the plasticity of TC synapses, which transmit competing visual information from each eye to V1, contributes to the early functional consequences of MC or is simply a feature of long-term deprivation. Here, we used quantitative immuno-electron microscopy to examine the possibility that alterations of TC synapses occur rapidly enough to impact OD after brief MC. The effect of short-term deprivation on TC synaptic structure was examined in male C57BL/6 mice that underwent 3 and 7 d of MC or monocular retinal inactivation (MI) with tetrodotoxin. The data show that 3 d of MC is sufficient to induce substantial remodeling of TC synapses. In contrast, 3 d of MI, which alters TC activity but does not shift OD, does not significantly affect the structure of TC synapses. Our results support the hypothesis that the rapid plasticity of TC synapses is a key step in the sequence of events that shift OD in visual cortex.