A cholinergic mechanism for reward timing within primary visual cortex

Learning to express reward prediction error-like dopaminergic activity requires plastic representations of time

The dominant theoretical framework to account for reinforcement learning in the brain is temporal difference learning (TD) learning, whereby certain units signal reward prediction errors (RPE). The TD algorithm has been traditionally mapped onto the dopaminergic system, as firing properties of dopamine neurons can resemble RPEs. However, certain predictions of TD learning are inconsistent with experimental results, and previous implementations of the algorithm have made unscalable assumptions regarding stimulus-specific fixed temporal bases. We propose an alternate framework to describe dopamine signaling in the brain, FLEX (Flexibly Learned Errors in Expected Reward). In FLEX, dopamine release is similar, but not identical to RPE, leading to predictions that contrast to those of TD. While FLEX itself is a general theoretical framework, we describe a specific, biophysically plausible implementation, the results of which are consistent with a preponderance of both existing and reanalyzed experimental data.

Rule-based modulation of a sensorimotor transformation across cortical areas

Flexible responses to sensory stimuli based on changing rules are critical for adapting to a dynamic environment. However, it remains unclear how the brain encodes and uses rule information to guide behavior. Here, we made single-unit recordings while head-fixed mice performed a cross-modal sensory selection task where they switched between two rules: licking in response to tactile stimuli while rejecting visual stimuli, or vice versa. Along a cortical sensorimotor processing stream including the primary (S1) and secondary (S2) somatosensory areas, and the medial (MM) and anterolateral (ALM) motor areas, single-neuron activity distinguished between the two rules both prior to and in response to the tactile stimulus. We hypothesized that neural populations in these areas would show rule-dependent preparatory states, which would shape the subsequent sensory processing and behavior. This hypothesis was supported for the motor cortical areas (MM and ALM) by findings that (1) the current task rule could be decoded from pre-stimulus population activity; (2) neural subspaces containing the population activity differed between the two rules; and (3) optogenetic disruption of pre-stimulus states impaired task performance. Our findings indicate that flexible action selection in response to sensory input can occur via configuration of preparatory states in the motor cortex.

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.

Ex Vivo Cortical Circuits Learn to Predict and Spontaneously Replay Temporal Patterns

It has been proposed that prediction and timing are computational primitives of neocortical microcircuits, specifically, that neural mechanisms are in place to allow neocortical circuits to autonomously learn the temporal structure of external stimuli and generate internal predictions. To test this hypothesis, we trained cortical organotypic slices on two specific temporal patterns using dual-optical stimulation. After 24-hours of training, whole-cell recordings revealed network dynamics consistent with training-specific timed prediction. Unexpectedly, there was replay of the learned temporal structure during spontaneous activity. Furthermore, some neurons exhibited timed prediction errors. Mechanistically our results indicate that learning relied in part on asymmetric connectivity between distinct neuronal ensembles with temporally-ordered activation. These findings further suggest that local cortical microcircuits are intrinsically capable of learning temporal information and generating predictions, and that the learning rules underlying temporal learning and spontaneous replay can be intrinsic to local cortical microcircuits and not necessarily dependent on top-down interactions.

Rule-based modulation of a sensorimotor transformation across cortical areas

Flexible responses to sensory stimuli based on changing rules are critical for adapting to a dynamic environment. However, it remains unclear how the brain encodes rule information and uses this information to guide behavioral responses to sensory stimuli. Here, we made single-unit recordings while head-fixed mice performed a cross-modal sensory selection task in which they switched between two rules in different blocks of trials: licking in response to tactile stimuli applied to a whisker while rejecting visual stimuli, or licking to visual stimuli while rejecting the tactile stimuli. Along a cortical sensorimotor processing stream including the primary (S1) and secondary (S2) somatosensory areas, and the medial (MM) and anterolateral (ALM) motor areas, the single-trial activity of individual neurons distinguished between the two rules both prior to and in response to the tactile stimulus. Variable rule-dependent responses to identical stimuli could in principle occur via appropriate configuration of pre-stimulus preparatory states of a neural population, which would shape the subsequent response. We hypothesized that neural populations in S1, S2, MM and ALM would show preparatory activity states that were set in a rule-dependent manner to cause processing of sensory information according to the current rule. This hypothesis was supported for the motor cortical areas by findings that (1) the current task rule could be decoded from pre-stimulus population activity in ALM and MM; (2) neural subspaces containing the population activity differed between the two rules; and (3) optogenetic disruption of pre-stimulus states within ALM and MM impaired task performance. Our findings indicate that flexible selection of an appropriate action in response to a sensory input can occur via configuration of preparatory states in the motor cortex.

Reward contingency gates selective cholinergic suppression of amygdala neurons

Basal forebrain cholinergic neurons modulate how organisms process and respond to environmental stimuli through impacts on arousal, attention, and memory. It is unknown, however, whether basal forebrain cholinergic neurons are directly involved in conditioned behavior, independent of secondary roles in the processing of external stimuli. Using fluorescent imaging, we found that cholinergic neurons are active during behavioral responding for a reward - even prior to reward delivery and in the absence of discrete stimuli. Photostimulation of basal forebrain cholinergic neurons, or their terminals in the basolateral amygdala (BLA), selectively promoted conditioned responding (licking), but not unconditioned behavior nor innate motor outputs. In vivo electrophysiological recordings during cholinergic photostimulation revealed reward-contingency-dependent suppression of BLA neural activity, but not prefrontal cortex. Finally, ex vivo experiments demonstrated that photostimulation of cholinergic terminals suppressed BLA projection neuron activity via monosynaptic muscarinic receptor signaling, while also facilitating firing in BLA GABAergic interneurons. Taken together, we show that the neural and behavioral effects of basal forebrain cholinergic activation are modulated by reward contingency in a target-specific manner.

A unified model for cross-modal plasticity and skill acquisition

Historically, cross-modal plasticity following early blindness has been largely studied in the context of visual deprivation. However, more recently, there has been a shift in focus towards understanding cross-modal plasticity from the perspective of skill acquisition: the striking plasticity observed in early blind individuals reflects the extraordinary perceptual and cognitive challenges they solve. Here, inspired by two seminal papers on skill learning (the "cortical recycling" theory) and cross-modal plasticity (the "metamodal" hypothesis) respectively, we present a unified hypothesis of cortical specialization that describes how shared functional, algorithmic, and structural constraints might mediate both types of plasticity.

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.

The neural basis of somatosensory temporal discrimination threshold as a paradigm for time processing in the sub-second range: An updated review

BACKGROUND AND OBJECTIVE

The temporal aspect of somesthesia is a feature of any somatosensory process and a pre-requisite for the elaboration of proper behavior. Time processing in the milliseconds range is crucial for most of behaviors in everyday life. The somatosensory temporal discrimination threshold (STDT) is the ability to perceive two successive stimuli as separate in time, and deals with time processing in this temporal range. Herein, we focus on the physiology of STDT, on a background of the anatomophysiology of somesthesia and the neurobiological substrates of timing.

METHODS

A review of the literature through PubMed & Cochrane databases until March 2023 was performed with inclusion and exclusion criteria following PRISMA recommendations.

RESULTS

1151 abstracts were identified. 4 duplicate records were discarded before screening. 957 abstracts were excluded because of redundancy, less relevant content or not English-written. 4 were added after revision. Eventually, 194 articles were included.

CONCLUSIONS

STDT encoding relies on intracortical inhibitory S1 function and is modulated by the basal ganglia-thalamic-cortical interplay through circuits involving the nigrostriatal dopaminergic pathway and probably the superior colliculus.

Visual experience induces 4-8 Hz synchrony between V1 and higher-order visual areas

Visual perceptual experience induces persistent 4-8 Hz oscillations in the mouse primary visual cortex (V1), encoding visual familiarity. Recent studies suggest that higher-order visual areas (HVAs) are functionally specialized and segregated into information streams processing distinct visual features. However, whether visual memories are processed and stored within the distinct streams is not understood. We report here that V1 and lateromedial (LM), but not V1 and anterolateral, become more phase synchronized in 4-8 Hz after the entrainment of visual stimulus that maximally induces responses in LM. Directed information analysis reveals changes in the top-down functional connectivity between V1 and HVAs. Optogenetic inactivation of LM reduces post-stimulus oscillation peaks in V1 and impairs visual discrimination behavior. Our results demonstrate that 4-8 Hz familiarity-evoked oscillations are specific for the distinct visual features and are present in the corresponding HVAs, where they may be used for the inter-areal communication with V1 during memory-related behaviors.

A Cortico-Striatal Circuit for Sound-Triggered Prediction of Reward Timing

A crucial aspect of auditory perception is the ability to use sound cues to predict future events and to time actions accordingly. For example, distinct smartphone notification sounds reflect a call that needs to be answered within a few seconds, or a text that can be read later; the sound of an approaching vehicle signals when it is safe to cross the street. Other animals similarly use sounds to plan, time and execute behaviors such as hunting, evading predation and tending to offspring. However, the neural mechanisms that underlie sound-guided prediction of upcoming salient event timing are not well understood. To address this gap, we employed an appetitive sound-triggered reward time prediction behavior in head-fixed mice. We find that mice trained on this task reliably estimate the time from a sound cue to upcoming reward on the scale of a few seconds, as demonstrated by learning-dependent well-timed increases in reward-predictive licking. Moreover, mice showed a dramatic impairment in their ability to use sound to predict delayed reward when the auditory cortex was inactivated, demonstrating its causal involvement. To identify the neurophysiological signatures of auditory cortical reward-timing prediction, we recorded local field potentials during learning and performance of this behavior and found that the magnitude of auditory cortical responses to the sound prospectively encoded the duration of the anticipated sound-reward time interval. Next, we explored how and where these sound-triggered time interval prediction signals propagate from the auditory cortex to time and initiate consequent action. We targeted the monosynaptic projections from the auditory cortex to the posterior striatum and found that chemogenetic inactivation of these projections impairs animal's ability to predict sound-triggered delayed reward. Simultaneous neural recordings in the auditory cortex and posterior striatum during task performance revealed coordination of neural activity across these regions during the sound cue predicting the time interval to reward. Collectively, our findings identify an auditory cortical-striatal circuit supporting sound-triggered timing-prediction behaviors.

Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement

Grouping sets of sounds into relevant categories is an important cognitive ability that enables the association of stimuli with appropriate goal-directed behavioral responses. In perceptual tasks, the primary auditory cortex (A1) assumes a prominent role by concurrently encoding both sound sensory features and task-related variables. Here, we sought to explore the role of A1 in the initiation of sound categorization, shedding light on its involvement in this cognitive process. We trained ferrets to discriminate click trains of different rates in a Go/No-Go delayed categorization task and recorded neural activity during both active behavior and passive exposure to the same sounds. Purely categorical response components were extracted and analyzed separately from sensory responses to reveal their contributions to the overall population response throughout the trials. We found that categorical activity emerged during sound presentation in the population average and was present in both active behavioral and passive states. However, upon task engagement, categorical responses to the No-Go category became suppressed in the population code, leading to an asymmetrical representation of the Go stimuli relative to the No-Go sounds and pre-stimulus baseline. The population code underwent an abrupt change at stimulus offset, with sustained responses after the Go sounds during the delay period. Notably, the categorical responses observed during the stimulus period exhibited a significant correlation with those extracted from the delay epoch, suggesting an early involvement of A1 in stimulus categorization.

Distinct Patterns of Connectivity between Brain Regions Underlie the Intra-Modal and Cross-Modal Value-Driven Modulations of the Visual Cortex

Past reward associations may be signaled from different sensory modalities; however, it remains unclear how different types of reward-associated stimuli modulate sensory perception. In this human fMRI study (female and male participants), a visual target was simultaneously presented with either an intra- (visual) or a cross-modal (auditory) cue that was previously associated with rewards. We hypothesized that, depending on the sensory modality of the cues, distinct neural mechanisms underlie the value-driven modulation of visual processing. Using a multivariate approach, we confirmed that reward-associated cues enhanced the target representation in early visual areas and identified the brain valuation regions. Then, using an effective connectivity analysis, we tested three possible patterns of connectivity that could underlie the modulation of the visual cortex: a direct pathway from the frontal valuation areas to the visual areas, a mediated pathway through the attention-related areas, and a mediated pathway that additionally involved sensory association areas. We found evidence for the third model demonstrating that the reward-related information in both sensory modalities is communicated across the valuation and attention-related brain regions. Additionally, the superior temporal areas were recruited when reward was cued cross-modally. The strongest dissociation between the intra- and cross-modal reward-driven effects was observed at the level of the feedforward and feedback connections of the visual cortex estimated from the winning model. These results suggest that, in the presence of previously rewarded stimuli from different sensory modalities, a combination of domain-general and domain-specific mechanisms are recruited across the brain to adjust the visual perception.SIGNIFICANCE STATEMENT Reward has a profound effect on perception, but it is not known whether shared or disparate mechanisms underlie the reward-driven effects across sensory modalities. In this human fMRI study, we examined the reward-driven modulation of the visual cortex by visual (intra-modal) and auditory (cross-modal) reward-associated cues. Using a model-based approach to identify the most plausible pattern of inter-regional effective connectivity, we found that higher-order areas involved in the valuation and attentional processing were recruited by both types of rewards. However, the pattern of connectivity between these areas and the early visual cortex was distinct between the intra- and cross-modal rewards. This evidence suggests that, to effectively adapt to the environment, reward signals may recruit both domain-general and domain-specific mechanisms.

Cholinergic Reinforcement Signaling Is Impaired by Amyloidosis Prior to Its Synaptic Loss

Alzheimer's disease (AD) is associated with amyloidosis and dysfunction of the cholinergic system, which is crucial for learning and memory. However, the nature of acetylcholine signaling within regions of cholinergic-dependent plasticity and how it changes with experience is poorly understood, much less the impact of amyloidosis on this signaling. Therefore, we optically measure the release profile of acetylcholine to unexpected, predicted, and predictive events in visual cortex (VC)-a site of known cholinergic-dependent plasticity-in a preclinical mouse model of AD that develops amyloidosis. We find that acetylcholine exhibits reinforcement signaling qualities, reporting behaviorally relevant outcomes and displaying release profiles to predictive and predicted events that change as a consequence of experience. We identify three stages of amyloidosis occurring before the degeneration of cholinergic synapses within VC and observe that cholinergic responses in amyloid-bearing mice become impaired over these stages, diverging progressively from age- and sex-matched littermate controls. In particular, amyloidosis degrades the signaling of unexpected rewards and punishments, and attenuates the experience-dependent (1) increase of cholinergic responses to outcome predictive visual cues, and (2) decrease of cholinergic responses to predicted outcomes. Hyperactive spontaneous acetylcholine release occurring transiently at the onset of impaired cholinergic signaling is also observed, further implicating disrupted cholinergic activity as an early functional biomarker in AD. Our findings suggest that acetylcholine acts as a reinforcement signal that is impaired by amyloidosis before pathologic degeneration of the cholinergic system, providing a deeper understanding of the effects of amyloidosis on acetylcholine signaling and informing future interventions for AD.SIGNIFICANCE STATEMENT The cholinergic system is especially vulnerable to the neurotoxic effects of amyloidosis, a hallmark of Alzheimer's disease (AD). Though amyloid-induced cholinergic synaptic loss is thought in part to account for learning and memory impairments in AD, little is known regarding how amyloid impacts signaling of the cholinergic system before its anatomic degeneration. Optical measurement of acetylcholine (ACh) release in a mouse model of AD that develops amyloidosis reveals that ACh signals reinforcement and outcome prediction that is disrupted by amyloidosis before cholinergic degeneration. These observations have important scientific and clinical implications: they implicate ACh signaling as an early functional biomarker, provide a deeper understanding of the action of acetylcholine, and inform on when and how intervention may best ameliorate cognitive decline in AD.

Striatal Dopamine Signals and Reward Learning

We are constantly bombarded by sensory information and constantly making decisions on how to act. In order to optimally adapt behavior, we must judge which sequences of sensory inputs and actions lead to successful outcomes in specific circumstances. Neuronal circuits of the basal ganglia have been strongly implicated in action selection, as well as the learning and execution of goal-directed behaviors, with accumulating evidence supporting the hypothesis that midbrain dopamine neurons might encode a reward signal useful for learning. Here, we review evidence suggesting that midbrain dopaminergic neurons signal reward prediction error, driving synaptic plasticity in the striatum underlying learning. We focus on phasic increases in action potential firing of midbrain dopamine neurons in response to unexpected rewards. These dopamine neurons prominently innervate the dorsal and ventral striatum. In the striatum, the released dopamine binds to dopamine receptors, where it regulates the plasticity of glutamatergic synapses. The increase of striatal dopamine accompanying an unexpected reward activates dopamine type 1 receptors (D1Rs) initiating a signaling cascade that promotes long-term potentiation of recently active glutamatergic input onto striatonigral neurons. Sensorimotor-evoked glutamatergic input, which is active immediately before reward delivery will thus be strengthened onto neurons in the striatum expressing D1Rs. In turn, these neurons cause disinhibition of brainstem motor centers and disinhibition of the motor thalamus, thus promoting motor output to reinforce rewarded stimulus-action outcomes. Although many details of the hypothesis need further investigation, altogether, it seems likely that dopamine signals in the striatum might underlie important aspects of goal-directed reward-based learning.

Learning to Express Reward Prediction Error-like Dopaminergic Activity Requires Plastic Representations of Time

The dominant theoretical framework to account for reinforcement learning in the brain is temporal difference (TD) reinforcement learning. The TD framework predicts that some neuronal elements should represent the reward prediction error (RPE), which means they signal the difference between the expected future rewards and the actual rewards. The prominence of the TD theory arises from the observation that firing properties of dopaminergic neurons in the ventral tegmental area appear similar to those of RPE model-neurons in TD learning. Previous implementations of TD learning assume a fixed temporal basis for each stimulus that might eventually predict a reward. Here we show that such a fixed temporal basis is implausible and that certain predictions of TD learning are inconsistent with experiments. We propose instead an alternative theoretical framework, coined FLEX (Flexibly Learned Errors in Expected Reward). In FLEX, feature specific representations of time are learned, allowing for neural representations of stimuli to adjust their timing and relation to rewards in an online manner. In FLEX dopamine acts as an instructive signal which helps build temporal models of the environment. FLEX is a general theoretical framework that has many possible biophysical implementations. In order to show that FLEX is a feasible approach, we present a specific biophysically plausible model which implements the principles of FLEX. We show that this implementation can account for various reinforcement learning paradigms, and that its results and predictions are consistent with a preponderance of both existing and reanalyzed experimental data.

The behavioral signature of stepwise learning strategy in male rats and its neural correlate in the basal forebrain

Studies of associative learning have commonly focused on how rewarding outcomes are predicted by either sensory stimuli or animals' actions. However, in many learning scenarios, reward delivery requires the occurrence of both sensory stimuli and animals' actions in a specific order, in the form of behavioral sequences. How such behavioral sequences are learned is much less understood. Here we provide behavioral and neurophysiological evidence to show that behavioral sequences are learned using a stepwise strategy. In male rats learning a new association, learning started from the behavioral event closest to the reward and sequentially incorporated earlier events. This led to the sequential refinement of reward-seeking behaviors, which was characterized by the stepwise elimination of ineffective and non-rewarded behavioral sequences. At the neuronal level, this stepwise learning process was mirrored by the sequential emergence of basal forebrain neuronal responses toward each event, which quantitatively conveyed a reward prediction error signal and promoted reward-seeking behaviors. Together, these behavioral and neural signatures revealed how behavioral sequences were learned in discrete steps and when each learning step took place.

Multimodal Temporal Pattern Discrimination Is Encoded in Visual Cortical Dynamics

Discriminating between temporal features in sensory stimuli is critical to complex behavior and decision-making. However, how sensory cortical circuit mechanisms contribute to discrimination between subsecond temporal components in sensory events is unclear. To elucidate the mechanistic underpinnings of timing in primary visual cortex (V1), we recorded from V1 using two-photon calcium imaging in awake-behaving mice performing a go/no-go discrimination timing task, which was composed of patterns of subsecond audiovisual stimuli. In both conditions, activity during the early stimulus period was temporally coordinated with the preferred stimulus. However, while network activity increased in the preferred condition, network activity was increasingly suppressed in the nonpreferred condition over the stimulus period. Multiple levels of analyses suggest that discrimination between subsecond intervals that are contained in rhythmic patterns can be accomplished by local neural dynamics in V1.

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.

Visual cortex encodes timing information in humans and mice

Despite the importance of timing in our daily lives, our understanding of how the human brain mediates second-scale time perception is limited. Here, we combined intracranial stereoelectroencephalography (SEEG) recordings in epileptic patients and circuit dissection in mice to show that visual cortex (VC) encodes timing information. We first asked human participants to perform an interval-timing task and found VC to be a key timing brain area. We then conducted optogenetic experiments in mice and showed that VC plays an important role in the interval-timing behavior. We further found that VC neurons fired in a time-keeping sequential manner and exhibited increased excitability in a timed manner. Finally, we used a computational model to illustrate a self-correcting learning process that generates interval-timed activities with scalar-timing property. Our work reveals how localized oscillations in VC occurring in the seconds to deca-seconds range relate timing information from the external world to guide behavior.

Cholinergic activity reflects reward expectations and predicts behavioral responses

Basal forebrain cholinergic neurons (BFCNs) play an important role in associative learning, suggesting that BFCNs may participate in processing stimuli that predict future outcomes. However, the impact of outcome probabilities on BFCN activity remained elusive. Therefore, we performed bulk calcium imaging and recorded spiking of identified cholinergic neurons from the basal forebrain of mice performing a probabilistic Pavlovian cued outcome task. BFCNs responded more to sensory cues that were often paired with reward. Reward delivery also activated BFCNs, with surprising rewards eliciting a stronger response, whereas punishments evoked uniform positive-going responses. We propose that BFCNs differentially weigh predictions of positive and negative reinforcement, reflecting divergent relative salience of forecasting appetitive and aversive outcomes, partially explained by a simple reinforcement learning model of a valence-weighed unsigned prediction error. Finally, the extent of cue-driven cholinergic activation predicted subsequent decision speed, suggesting that the expectation-gated cholinergic firing is instructive to reward-seeking behaviors.

Spatiotemporally heterogeneous coordination of cholinergic and neocortical activity

Variation in an animal's behavioral state is linked to fluctuations in brain activity and cognitive ability. In the neocortex, state-dependent circuit dynamics may reflect neuromodulatory influences such as that of acetylcholine (ACh). Although early literature suggested that ACh exerts broad, homogeneous control over cortical function, recent evidence indicates potential anatomical and functional segregation of cholinergic signaling. In addition, it is unclear whether states as defined by different behavioral markers reflect heterogeneous cholinergic and cortical network activity. Here, we perform simultaneous, dual-color mesoscopic imaging of both ACh and calcium across the neocortex of awake mice to investigate their relationships with behavioral variables. We find that higher arousal, categorized by different motor behaviors, is associated with spatiotemporally dynamic patterns of cholinergic modulation and enhanced large-scale network correlations. Overall, our findings demonstrate that ACh provides a highly dynamic and spatially heterogeneous signal that links fluctuations in behavior to functional reorganization of cortical networks.

A Recurrent Neural Network Model Accounts for Both Timing and Working Memory Components of an Interval Discrimination Task

Interval discrimination is of fundamental importance to many forms of sensory processing, including speech and music. Standard interval discrimination tasks require comparing two intervals separated in time, and thus include both working memory (WM) and timing components. Models of interval discrimination invoke separate circuits for the timing and WM components. Here we examine if, in principle, the same recurrent neural network can implement both. Using human psychophysics, we first explored the role of the WM component by varying the interstimulus delay. Consistent with previous studies, discrimination was significantly worse for a 250 ms delay, compared to 750 and 1500 ms delays, suggesting that the first interval is stably stored in WM for longer delays. We next successfully trained a recurrent neural network (RNN) on the task, demonstrating that the same network can implement both the timing and WM components. Many units in the RNN were tuned to specific intervals during the sensory epoch, and others encoded the first interval during the delay period. Overall, the encoding strategy was consistent with the notion of mixed selectivity. Units generally encoded more interval information during the sensory epoch than in the delay period, reflecting categorical encoding of short versus long in WM, rather than encoding of the specific interval. Our results demonstrate that, in contrast to standard models of interval discrimination that invoke a separate memory module, the same network can, in principle, solve the timing, WM, and comparison components of an interval discrimination task.

Learning enhances encoding of time and temporal surprise in mouse primary sensory cortex

Primary sensory cortex has long been believed to play a straightforward role in the initial processing of sensory information. Yet, the superficial layers of cortex overall are sparsely active, even during sensory stimulation; additionally, cortical activity is influenced by other modalities, task context, reward, and behavioral state. Our study demonstrates that reinforcement learning dramatically alters representations among longitudinally imaged neurons in superficial layers of mouse primary somatosensory cortex. Learning an object detection task recruits previously unresponsive neurons, enlarging the neuronal population sensitive to touch and behavioral choice. Cortical responses decrease upon repeated stimulus presentation outside of the behavioral task. Moreover, training improves population encoding of the passage of time, and unexpected deviations in trial timing elicit even stronger responses than touches do. In conclusion, the superficial layers of sensory cortex exhibit a high degree of learning-dependent plasticity and are strongly modulated by non-sensory but behaviorally-relevant features, such as timing and surprise.

Activity in the superficial layers of the sensory cortex is believed to be largely driven by incoming sensory stimuli. Here the authors demonstrate how learning changes neural responses to sensations according to both behavioral relevance and timing, suggesting a high degree of non-sensory modulation.

The neural bases for timing of durations

Durations are defined by a beginning and an end, and a major distinction is drawn between durations that start in the present and end in the future ('prospective timing') and durations that start in the past and end either in the past or the present ('retrospective timing'). Different psychological processes are thought to be engaged in each of these cases. The former is thought to engage a clock-like mechanism that accurately tracks the continuing passage of time, whereas the latter is thought to engage a reconstructive process that utilizes both temporal and non-temporal information from the memory of past events. We propose that, from a biological perspective, these two forms of duration 'estimation' are supported by computational processes that are both reliant on population state dynamics but are nevertheless distinct. Prospective timing is effectively carried out in a single step where the ongoing dynamics of population activity directly serve as the computation of duration, whereas retrospective timing is carried out in two steps: the initial generation of population state dynamics through the process of event segmentation and the subsequent computation of duration utilizing the memory of those dynamics.

Selective enhancement of neural coding in V1 underlies fine-discrimination learning in tree shrew

Visual discrimination improves with training, a phenomenon that is thought to reflect plastic changes in the responses of neurons in primary visual cortex (V1). However, the identity of the neurons that undergo change, the nature of the changes, and the consequences of these changes for other visual behaviors remain unclear. We used chronic in vivo 2-photon calcium imaging to monitor the responses of neurons in the V1 of tree shrews learning a Go/No-Go fine orientation discrimination task. We observed increases in neural population measures of discriminability for task-relevant stimuli that correlate with performance and depend on a select subset of neurons with preferred orientations that include the rewarded stimulus and nearby orientations biased away from the non-rewarded stimulus. Learning is accompanied by selective enhancement in the response of these neurons to the rewarded stimulus that further increases their ability to discriminate the task stimuli. These changes persist outside of the trained task and predict observed enhancement and impairment in performance of other discriminations, providing evidence for selective and persistent learning-induced plasticity in the V1, with significant consequences for perception.

The Response Dynamics and Function of Cholinergic and GABAergic Neurons in the Basal Forebrain During Olfactory Learning

Modulation of neural circuits is essential for flexible sensory perception and decision-making in a changing environment. Cholinergic and GABAergic projections to the olfactory system from the horizontal limb of the diagonal band of Broca (HDB) in the basal forebrain are crucial for odor detection and olfactory learning. Although studies have demonstrated that HDB neurons respond during olfactory learning, how cholinergic and GABAergic neurons differ in their response dynamics and roles in olfactory learning remains unclear. In this study, we examined the response profiles of these two subpopulations of neurons during passive odor exposure and associative olfactory learning. We show that the excitatory responses in both cholinergic and GABAergic neurons tended to habituate during repeated passive odor exposure. However, while these habituated responses were also observed in GABAergic neurons during a go-go task, there was no such habituation in cholinergic neurons. Moreover, the responses to S+ and S− trials diverged in cholinergic neurons once mice learned a go/no-go task. Furthermore, the chemogenetic inactivation of cholinergic neurons in the HDB impaired odor discrimination. Together, these findings suggest that cholinergic neurons in the HDB reflect attention to positive reinforcement and may regulate odor discrimination via top–down inputs to the olfactory system.

Movement-dependent electrical stimulation for volitional strengthening of cortical connections in behaving monkeys

Correlated activity of neurons can lead to long-term strengthening or weakening of the connections between them. In addition, the behavioral context, imparted by execution of physical movements or the presence of a reward, can modulate the plasticity induced by Hebbian mechanisms. In the present study, we have combined behavior and induced neuronal correlations to strengthen connections in the motor cortex of adult behaving monkeys. Correlated activity was induced using an electrical-conditioning protocol in which stimuli gated by voluntary movements were used to produce coactivation of neurons at motor-cortical sites involved in those movements. Delivery of movement-dependent stimulation resulted in small increases in the strength of associated cortical connections immediately after conditioning. Remarkably, when paired with further repetition of the movements that gated the conditioning stimuli, there were substantially larger gains in the strength of cortical connections, which occurred in a use-dependent manner, without delivery of additional conditioning stimulation. In the absence of such movements, little change was observed in the strength of motor-cortical connections. Performance of the motor behavior in the absence of conditioning also did not produce any changes in connectivity. Our results show that combining movement-gated stimulation with further natural use of the "conditioned" pathways after stimulation ends can produce use-dependent strengthening of connections in adult primates, highlighting an important role for behavior in cortical plasticity. Our data also provide strong support for combining movement-gated stimulation with use-dependent physical rehabilitation for strengthening connections weakened by a stroke or spinal cord injury.

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.

Outcome-Locked Cholinergic Signaling Suppresses Prefrontal Encoding of Stimulus Associations

Acetylcholine (ACh) is thought to control arousal, attention, and learning by slowly modulating cortical excitability and plasticity. Recent studies, however, discovered that cholinergic neurons emit precisely timed signals about the aversive outcome at millisecond precision. To investigate the functional relevance of such phasic cholinergic signaling, we manipulated and monitored cholinergic terminals in the mPFC while male mice associated a neutral conditioned stimulus (CS) with mildly aversive eyelid shock (US) over a short temporal gap. Optogenetic inhibition of cholinergic terminals during the US promoted the formation of the CS-US association. On the contrary, optogenetic excitation of cholinergic terminals during the US blocked the association formation. The bidirectional behavioral effects paralleled the corresponding change in the expression of an activity-regulated gene, c-Fos in the mPFC. In contrast, optogenetic inhibition of cholinergic terminals during the CS impaired associative learning, whereas their excitation had marginal effects. In parallel, photometric recording from cholinergic terminals in the mPFC revealed strong innate phasic responses to the US. With subsequent CS-US pairings, cholinergic terminals weakened the responses to the US while developing strong responses to the CS. The across-session changes in the CS- and US-evoked terminal responses were correlated with associative memory strength. These findings suggest that phasic cholinergic signaling in the mPFC exerts opposite effects on aversive associative learning depending on whether it is emitted by the outcome or the cue.SIGNIFICANCE STATEMENT Drugs compensating for the decline of acetylcholine (ACh) are used for cognitive impairment, such as Alzheimer's disease. However, their beneficial effects are limited, demanding new strategies based on better understandings of how ACh modulates cognition. Here, we report that by manipulating ACh signals in the mPFC, we can control the strength of aversive associative learning in mice. Specifically, the suppression of ACh signals during an aversive outcome facilitated its association with a preceding cue. In contrast, the suppression of ACh signals during the cue impaired learning. Considering that this paradigm depends on the brain regions affected in Alzheimer's disease, our findings indicate that precisely timed control of ACh signals is essential to refine ACh-based strategies for cognitive enhancement.

Encoding time in neural dynamic regimes with distinct computational tradeoffs

Converging evidence suggests the brain encodes time in dynamic patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Most temporal tasks, however, require more than just encoding time, and can have distinct computational requirements including the need to exhibit temporal scaling, generalize to novel contexts, or robustness to noise. It is not known how neural circuits can encode time and satisfy distinct computational requirements, nor is it known whether similar patterns of neural activity at the population level can exhibit dramatically different computational or generalization properties. To begin to answer these questions, we trained RNNs on two timing tasks based on behavioral studies. The tasks had different input structures but required producing identically timed output patterns. Using a novel framework we quantified whether RNNs encoded two intervals using either of three different timing strategies: scaling, absolute, or stimulus-specific dynamics. We found that similar neural dynamic patterns at the level of single intervals, could exhibit fundamentally different properties, including, generalization, the connectivity structure of the trained networks, and the contribution of excitatory and inhibitory neurons. Critically, depending on the task structure RNNs were better suited for generalization or robustness to noise. Further analysis revealed different connection patterns underlying the different regimes. Our results predict that apparently similar neural dynamic patterns at the population level (e.g., neural sequences) can exhibit fundamentally different computational properties in regards to their ability to generalize to novel stimuli and their robustness to noise—and that these differences are associated with differences in network connectivity and distinct contributions of excitatory and inhibitory neurons. We also predict that the task structure used in different experimental studies accounts for some of the experimentally observed variability in how networks encode time.

The ability to tell time and anticipate when external events will occur are among the most fundamental computations the brain performs. Converging evidence suggests the brain encodes time through changing patterns of neural activity. Different temporal tasks, however, have distinct computational requirements, such as the need to flexibly scale temporal patterns or generalize to novel inputs. To understand how networks can encode time and satisfy different computational requirements we trained recurrent neural networks (RNNs) on two timing tasks that have previously been used in behavioral studies. Both tasks required producing identically timed output patterns. Using a novel framework to quantify how networks encode different intervals, we found that similar patterns of neural activity—neural sequences—were associated with fundamentally different underlying mechanisms, including the connectivity patterns of the RNNs. Critically, depending on the task the RNNs were trained on, they were better suited for generalization or robustness to noise. Our results predict that similar patterns of neural activity can be produced by distinct RNN configurations, which in turn have fundamentally different computational tradeoffs. Our results also predict that differences in task structure account for some of the experimentally observed variability in how networks encode time.

Basal Forebrain Cholinergic Neurons Selectively Drive Coordinated Motor Learning in Mice

Motor control requires precise temporal and spatial encoding across distinct motor centers that is refined through the repetition of learning. The recruitment of motor regions requires modulatory input to shape circuit activity. Here, we identify a role for the baso-cortical cholinergic pathway in the acquisition of a coordinated motor skill in mice. Targeted depletion of basal forebrain cholinergic neurons results in significant impairments in training on the rotarod task of coordinated movement. Cholinergic neuromodulation is required during training sessions as chemogenetic inactivation of cholinergic neurons also impairs task acquisition. Rotarod learning is known to drive refinement of corticostriatal neurons arising in both medial prefrontal cortex (mPFC) and motor cortex, and we have found that cholinergic input to both motor regions is required for task acquisition. Critically, the effects of cholinergic neuromodulation are restricted to the acquisition stage, as depletion of basal forebrain cholinergic neurons after learning does not affect task execution. Our results indicate a critical role for cholinergic neuromodulation of distant cortical motor centers during coordinated motor learning.SIGNIFICANCE STATEMENT Acetylcholine release from basal forebrain cholinergic neuron terminals rapidly modulates neuronal excitability, circuit dynamics, and cortical coding; all processes required for processing complex sensory information, cognition, and attention. We found that depletion or transient silencing of cholinergic inputs to anatomically isolated motor areas, medial prefrontal cortex (mPFC) and motor cortex, selectively led to significant impairments on coordinated motor learning; disrupting this baso-cortical network after acquisition elicited no effect on task execution. Our results indicate a pivotal role for cholinergic neuromodulation of distant cortical motor centers during coordinated motor learning. These findings support the concept that cognitive components (such as attention) are indispensable in the adjustment of motor output and training-induced improvements in motor performance.

Distribution of cholinergic neurons in the brains of a lar gibbon and a chimpanzee

Using choline acetyltransferase immunohistochemistry, we describe the nuclear parcellation of the cholinergic system in the brains of two apes, a lar gibbon (Hylobates lar) and a chimpanzee (Pan troglodytes). The cholinergic nuclei observed in both apes studied are virtually identical to that observed in humans and show very strong similarity to the cholinergic nuclei observed in other primates and mammals more generally. One specific difference between humans and the two apes studied is that, with the specific choline acetyltransferase antibody used, the cholinergic pyramidal neurons observed in human cerebral cortex were not labeled. When comparing the two apes studied and humans to other primates, the presence of a greatly expanded cholinergic medullary tegmental field, and the presence of cholinergic neurons in the intermediate and dorsal horns of the cervical spinal cord are notable variations of the distribution of cholinergic neurons in apes compared to other primates. These neurons may play an important role in the modulation of ascending and descending neural transmissions through the spinal cord and caudal medulla, potentially related to the differing modes of locomotion in apes compared to other primates. Our observations also indicate that the average soma volume of the neurons forming the laterodorsal tegmental nucleus (LDT) is larger than those of the pedunculopontine nucleus (PPT) in both the lar gibbon and chimpanzee. This variability in soma volume appears to be related to the size of the adult derivatives of the alar and basal plate across mammalian species.

A functional topography within the cholinergic basal forebrain for encoding sensory cues and behavioral reinforcement outcomes

Basal forebrain cholinergic neurons (BFCNs) project throughout the cortex to regulate arousal, stimulus salience, plasticity, and learning. Although often treated as a monolithic structure, the basal forebrain features distinct connectivity along its rostrocaudal axis that could impart regional differences in BFCN processing. Here, we performed simultaneous bulk calcium imaging from rostral and caudal BFCNs over a 1-month period of variable reinforcement learning in mice. BFCNs in both regions showed equivalently weak responses to unconditioned visual stimuli and anticipated rewards. Rostral BFCNs in the horizontal limb of the diagonal band were more responsive to reward omission, more accurately classified behavioral outcomes, and more closely tracked fluctuations in pupil-indexed global brain state. Caudal tail BFCNs in globus pallidus and substantia innominata were more responsive to unconditioned auditory stimuli, orofacial movements, aversive reinforcement, and showed robust associative plasticity for punishment-predicting cues. These results identify a functional topography that diversifies cholinergic modulatory signals broadcast to downstream brain regions.

The spatiotemporal organization of experience dictates hippocampal involvement in primary visual cortical plasticity

The hippocampus and neocortex are theorized to be crucial partners in the formation of long-term memories. Here, we assess hippocampal involvement in two related forms of experience-dependent plasticity in the primary visual cortex (V1) of mice. Like control animals, those with hippocampal lesions exhibit potentiation of visually evoked potentials after passive daily exposure to a phase-reversing oriented grating stimulus, which is accompanied by long-term habituation of a reflexive behavioral response. Thus, low-level recognition memory is formed independently of the hippocampus. However, response potentiation resulting from daily exposure to a fixed sequence of four oriented gratings is severely impaired in mice with hippocampal damage. A feature of sequence plasticity in V1 of controls, which is absent in lesioned mice, is the generation of predictive responses to an anticipated stimulus element when it is withheld or delayed. Thus, the hippocampus is involved in encoding temporally structured experience, even within the primary sensory cortex.

Cortical Visual Impairment in Childhood: 'Blindsight' and the Sprague Effect Revisited

The paper discusses and provides support for diverse processes of brain plasticity in visual function after damage in infancy and childhood in comparison with injury that occurs in the adult brain. We provide support and description of neuroplastic mechanisms in childhood that do not seemingly exist in the same way in the adult brain. Examples include the ability to foster the development of thalamocortical connectivities that can circumvent the lesion and reach their cortical destination in the occipital cortex as the developing brain is more efficient in building new connections. Supporting this claim is the fact that in those with central visual field defects we can note that the extrastriatal visual connectivities are greater when a lesion occurs earlier in life as opposed to in the neurologically mature adult. The result is a significantly more optimized system of visual and spatial exploration within the ‘blind’ field of view. The discussion is provided within the context of “blindsight” and the “Sprague Effect”.

Evaluating Visual Cues Modulates Their Representation in Mouse Visual and Cingulate Cortex

Choosing an action in response to visual cues relies on cognitive processes, such as perception, evaluation, and prediction, which can modulate visual representations even at early processing stages. In the mouse, it is challenging to isolate cognitive modulations of sensory signals because concurrent overt behavior patterns, such as locomotion, can also have brainwide influences. To address this challenge, we designed a task, in which head-fixed mice had to evaluate one of two visual cues. While their global shape signaled the opportunity to earn reward, the cues provided equivalent local stimulation to receptive fields of neurons in primary visual (V1) and anterior cingulate cortex (ACC). We found that mice evaluated these cues within few hundred milliseconds. During this period, ∼30% of V1 neurons became cue-selective, with preferences for either cue being balanced across the recorded population. This selectivity emerged in response to the behavioral demands because the same neurons could not discriminate the cues in sensory control measurements. In ACC, cue evaluation affected a similar fraction of neurons; emerging selectivity, however, was stronger than in V1, and preferences in the recorded population were biased toward the cue promising reward. Such a biased selectivity regime might allow the mouse to infer the promise of reward simply by the overall level of activity. Together, these experiments isolate the impact of task demands on neural responses in mouse cerebral cortex, and document distinct neural signatures of cue evaluation in V1 and ACC.SIGNIFICANCE STATEMENT Performing a cognitive task, such as evaluating visual cues, not only recruits frontal and parietal brain regions, but also modulates sensory processing stages. We trained mice to evaluate two visual cues, and show that, during this task, ∼30% of neurons recorded in V1 became selective for either cue, although they provided equivalent visual stimulation. We also show that, during cue evaluation, mice frequently move their eyes, even under head fixation, and that ignoring systematic differences in eye position can substantially obscure the modulations seen in V1 neurons. Finally, we document that modulations are stronger in ACC, and biased toward the reward-predicting cue, suggesting a transition in the neural representation of task-relevant information across processing stages in mouse cerebral cortex.

Visual Familiarity Induced 5-Hz Oscillations and Improved Orientation and Direction Selectivities in V1

Neural oscillations play critical roles in information processing, communication between brain areas, learning, and memory. We have recently discovered that familiar visual stimuli can robustly induce 5-Hz oscillations in the primary visual cortex (V1) of awake mice after the visual experience. To gain more mechanistic insight into this phenomenon, we used in vivo patch-clamp recordings to monitor the subthreshold activity of individual neurons during these oscillations.

Neural oscillations play critical roles in information processing, communication between brain areas, learning, and memory. We have recently discovered that familiar visual stimuli can robustly induce 5-Hz oscillations in the primary visual cortex (V1) of awake mice after the visual experience. To gain more mechanistic insight into this phenomenon, we used in vivo patch-clamp recordings to monitor the subthreshold activity of individual neurons during these oscillations. We analyzed the visual tuning properties of V1 neurons in naive and experienced mice to assess the effect of visual experience on the orientation and direction selectivity. Using optogenetic stimulation through the patch pipette in vivo, we measured the synaptic strength of specific intracortical and thalamocortical projections in vivo in the visual cortex before and after the visual experience. We found 5-Hz oscillations in membrane potential (V_m) and firing rates evoked in single neurons in response to the familiar stimulus, consistent with previous studies. Following the visual experience, the average firing rates of visual responses were reduced while the orientation and direction selectivities were increased. Light-evoked EPSCs were significantly increased for layer 5 (L5) projections to other layers of V1 after the visual experience, while the thalamocortical synaptic strength was decreased. In addition, we developed a computational model that could reproduce 5-Hz oscillations with enhanced neuronal selectivity following synaptic plasticity within the recurrent network and decreased feedforward input.

SIGNIFICANCE STATEMENT Neural oscillations at around 5 Hz are involved in visual working memory and temporal expectations in primary visual cortex (V1). However, how the oscillations modulate the visual response properties of neurons in V1 and their underlying mechanism is poorly understood. Here, we show that these oscillations may alter the orientation and direction selectivity of the layer 2/3 (L2/3) neurons and correlate with the synaptic plasticity within V1. Our computational recurrent network model reproduces all these observations and provides a mechanistic framework for studying the role of 5-Hz oscillations in visual familiarity.

Learning precise spatiotemporal sequences via biophysically realistic learning rules in a modular, spiking network

Multiple brain regions are able to learn and express temporal sequences, and this functionality is an essential component of learning and memory. We propose a substrate for such representations via a network model that learns and recalls discrete sequences of variable order and duration. The model consists of a network of spiking neurons placed in a modular microcolumn based architecture. Learning is performed via a biophysically realistic learning rule that depends on synaptic 'eligibility traces'. Before training, the network contains no memory of any particular sequence. After training, presentation of only the first element in that sequence is sufficient for the network to recall an entire learned representation of the sequence. An extended version of the model also demonstrates the ability to successfully learn and recall non-Markovian sequences. This model provides a possible framework for biologically plausible sequence learning and memory, in agreement with recent experimental results.

Visual Cues Predictive of Behaviorally Neutral Outcomes Evoke Persistent but Not Interval Timing Activity in V1, Whereas Aversive Conditioning Suppresses This Activity

Cue-evoked persistent activity is neural activity that persists beyond stimulation of a sensory cue and has been described in many regions of the brain, including primary sensory areas. Nonetheless, the functional role that persistent activity plays in primary sensory areas is enigmatic. However, one form of persistent activity in a primary sensory area is the representation of time between a visual stimulus and a water reward. This “reward timing activity”—observed within the primary visual cortex—has been implicated in informing the timing of visually cued, reward-seeking actions. Although rewarding outcomes are sufficient to engender interval timing activity within V1, it is unclear to what extent cue-evoked persistent activity exists outside of reward conditioning, and whether temporal relationships to other outcomes (such as behaviorally neutral or aversive outcomes) are able to engender timing activity. Here we describe the existence of cue-evoked persistent activity in mouse V1 following three conditioning strategies: pseudo-conditioning (where unpaired, monocular visual stimuli are repeatedly presented to an animal), neutral conditioning (where monocular visual stimuli are paired with a binocular visual stimulus, at a delay), and aversive conditioning (where monocular visual stimuli are paired with a tail shock, at a delay). We find that these conditioning strategies exhibit persistent activity that takes one of three forms, a sustained increase of activity; a sustained decrease of activity; or a delayed, transient peak of activity, as previously observed following conditioning with delayed reward. However, these conditioning strategies do not result in visually cued interval timing activity, as observed following appetitive conditioning. Moreover, we find that neutral conditioning increases the magnitude of cue-evoked responses whereas aversive conditioning strongly diminished both the response magnitude and the prevalence of cue-evoked persistent activity. These results demonstrate that cue-evoked persistent activity within V1 can exist outside of conditioning visual stimuli with delayed outcomes and that this persistent activity can be uniquely modulated across different conditioning strategies using unconditioned stimuli of varying behavioral relevance. Together, these data extend our understanding of cue-evoked persistent activity within a primary sensory cortical network and its ability to be modulated by salient outcomes.

Cell-type-specific nicotinic input disinhibits mouse barrel cortex during active sensing

Fast synaptic transmission relies upon the activation of ionotropic receptors by neurotransmitter release to evoke postsynaptic potentials. Glutamate and GABA play dominant roles in driving highly dynamic activity in synaptically connected neuronal circuits, but ionotropic receptors for other neurotransmitters are also expressed in the neocortex, including nicotinic receptors, which are non-selective cation channels gated by acetylcholine. To study the function of non-glutamatergic excitation in neocortex, we used two-photon microscopy to target whole-cell membrane potential recordings to different types of genetically defined neurons in layer 2/3 of primary somatosensory barrel cortex in awake head-restrained mice combined with pharmacological and optogenetic manipulations. Here, we report a prominent nicotinic input, which selectively depolarizes a subtype of GABAergic neuron expressing vasoactive intestinal peptide leading to disinhibition during active sensorimotor processing. Nicotinic disinhibition of somatosensory cortex during active sensing might contribute importantly to integration of top-down and motor-related signals necessary for tactile perception and learning.

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Acetylcholine is released in the mouse barrel cortex during active whisker sensing

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Acetylcholine depolarizes inhibitory cells expressing vasoactive intestinal peptide

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Excitation of vasoactive intestinal peptide-expressing neurons causes disinhibition

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Cholinergic-driven disinhibition could gate sensorimotor integration and plasticity

Endogenous Acetylcholine and Its Modulation of Cortical Microcircuits to Enhance Cognition

Acetylcholine regulates the cerebral cortex to sharpen sensory perception and enhance attentional focus. The cellular and circuit mechanisms of this cholinergic modulation are under active investigation in sensory and prefrontal cortex, but the universality of these mechanisms across the cerebral cortex is not clear. Anatomical maps suggest that the sensory and prefrontal cortices receive distinct cholinergic projections and have subtle differences in the expression of cholinergic receptors and the metabolic enzyme acetylcholinesterase. First, we briefly review this anatomical literature and the recent progress in the field. Next, we discuss in detail the electrophysiological effects of cholinergic receptor subtypes and the cell and circuit consequences of their stimulation by endogenous acetylcholine as established by recent optogenetic work. Finally, we explore the behavioral ramifications of in vivo manipulations of endogenous acetylcholine. We find broader similarities than we expected between the cholinergic regulation of sensory and prefrontal cortex, but there are some differences and some gaps in knowledge. In visual, auditory, and somatosensory cortex, the cell and circuit mechanisms of cholinergic sharpening of sensory perception have been probed in vivo with calcium imaging and optogenetic experiments to simultaneously test mechanism and measure the consequences of manipulation. By contrast, ascertaining the links between attentional performance and cholinergic modulation of specific prefrontal microcircuits is more complicated due to the nature of the required tasks. However, ex vivo optogenetic manipulations point to differences in the cholinergic modulation of sensory and prefrontal cortex. Understanding how and where acetylcholine acts within the cerebral cortex to shape cognition is essential to pinpoint novel treatment targets for the perceptual and attention deficits found in multiple psychiatric and neurological disorders.

Cortical Tuning is Impaired After Perceptual Experience in Primary Visual Cortex of Serotonin Transporter-Deficient Mice

Serotonin (5-hydroxytryptamine) is crucial for the proper development of neuronal circuits early in life and their refinement throughout adulthood. Its signaling is tightly regulated by the serotonin transporter (SERT), alterations of which were implicated in various neurological and psychiatric disorders. Animal models lacking a functional SERT variant display diverse phenotypes, including increased anxiety, social communication deficits, and altered cortical development. However, it remains unclear how SERT disruption affects sensory processing and experience-dependent learning in adulthood. It has been previously shown that perceptual experience leads to the development of visual familiarity-evoked theta oscillations in mouse V1. Here, we discovered that familiarity-evoked theta oscillations were longer and less stimulus specific in SERT knockout (KO) compared with wild-type (WT) mice. Interestingly, while the overall visual response properties were similar in naive mice, orientation and spatial frequency processing were significantly impaired in SERT KO compared with WT or SERT heterozygous mice following perceptual experience. Our findings shed more light on the mechanism of familiarity-evoked oscillations and highlight the importance of serotonin signaling in perceptual learning.

Cortical circuits for transforming whisker sensation into goal-directed licking

Animals can learn to use sensory stimuli to generate motor actions in order to obtain rewards. However, the precise neuronal circuits driving learning and execution of a specific goal-directed sensory-to-motor transformation remain to be elucidated. Here, we review progress in understanding the contribution of cortical neuronal circuits to a task in which head-restrained water-restricted mice learn to lick a reward spout in response to whisker deflection. We first examine 'innate' pathways for whisker sensory processing and licking motor control, and then discuss how these might become linked through reward-based learning, perhaps enabled by cholinergic-gated and dopaminergic-gated plasticity. The aim is to uncover the synaptically connected neuronal pathways that mediate reward-based learning and execution of a well-defined sensory-to-motor transformation.

Acetylcholine is released in the basolateral amygdala in response to predictors of reward and enhances the learning of cue-reward contingency

The basolateral amygdala (BLA) is critical for associating initially neutral cues with appetitive and aversive stimuli and receives dense neuromodulatory acetylcholine (ACh) projections. We measured BLA ACh signaling and activity of neurons expressing CaMKIIα (a marker for glutamatergic principal cells) in mice during cue-reward learning using a fluorescent ACh sensor and calcium indicators. We found that ACh levels and nucleus basalis of Meynert (NBM) cholinergic terminal activity in the BLA (NBM-BLA) increased sharply in response to reward-related events and shifted as mice learned the cue-reward contingency. BLA CaMKIIα neuron activity followed reward retrieval and moved to the reward-predictive cue after task acquisition. Optical stimulation of cholinergic NBM-BLA terminal fibers led to a quicker acquisition of the cue-reward contingency. These results indicate BLA ACh signaling carries important information about salient events in cue-reward learning and provides a framework for understanding how ACh signaling contributes to shaping BLA responses to emotional stimuli.

Decreased reproducibility and abnormal experience-dependent plasticity of network dynamics in Fragile X circuits

Fragile X syndrome is a neurodevelopmental disorder associated with a broad range of neural phenotypes. Interpreting these findings has proven challenging because some phenotypes may reflect compensatory mechanisms or normal forms of plasticity differentially engaged by experiential differences. To help minimize compensatory and experiential influences, we used an ex vivo approach to study network dynamics and plasticity of cortical microcircuits. In Fmr1^−/y circuits, the spatiotemporal structure of Up-states was less reproducible, suggesting alterations in the plasticity mechanisms governing network activity. Chronic optical stimulation revealed normal homeostatic plasticity of Up-states, however, Fmr1^−/y circuits exhibited abnormal experience-dependent plasticity as they did not adapt to chronically presented temporal patterns in an interval-specific manner. These results, suggest that while homeostatic plasticity is normal, Fmr1^−/y circuits exhibit deficits in the ability to orchestrate multiple forms of synaptic plasticity and to adapt to sensory patterns in an experience-dependent manner—which is likely to contribute to learning deficits.

Distinct synchronization, cortical coupling and behavioral function of two basal forebrain cholinergic neuron types

Basal forebrain cholinergic neurons (BFCNs) modulate synaptic plasticity, cortical processing, brain states and oscillations. However, whether distinct types of BFCNs support different functions remains unclear. Therefore, we recorded BFCNs in vivo, to examine their behavioral functions, and in vitro, to study their intrinsic properties. We identified two distinct types of BFCNs that differ in their firing modes, synchronization properties and behavioral correlates. Bursting cholinergic neurons (Burst-BFCNs) fired synchronously, phase-locked to cortical theta activity and fired precisely timed bursts after reward and punishment. Regular-firing cholinergic neurons (Reg-BFCNs) were found predominantly in the posterior basal forebrain, displayed strong theta rhythmicity and responded with precise single spikes after behavioral outcomes. In an auditory detection task, synchronization of Burst-BFCNs to the auditory cortex predicted the timing of behavioral responses, whereas tone-evoked cortical coupling of Reg-BFCNs predicted correct detections. We propose that differential recruitment of two basal forebrain cholinergic neuron types generates behavior-specific cortical activation.