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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.

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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.

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Time is a fundamental dimension of our perception of the world and is therefore of critical importance to the organization of human behavior. A corpus of work - including recent optogenetic evidence - implicates striatal dopamine as a crucial factor influencing the perception of time. Another stream of literature implicates dopamine in reward and motivation processes. However, these two domains of research have remained largely separated, despite neurobiological overlap and the apothegmatic notion that "time flies when you're having fun". This article constitutes a review of the literature linking time perception and reward, including neurobiological and behavioral studies. Together, these provide compelling support for the idea that time perception and reward processing interact via a common dopaminergic mechanism.

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The primary sensory cortex has historically been studied as a low-level feature detector, but has more recently been implicated in many higher-level cognitive functions. For instance, after an animal learns that a light predicts water at a fixed delay, neurons in the primary visual cortex (V1) can produce "reward timing activity" (i.e., spike modulation of various forms that relate the interval between the visual stimulus and expected reward). Local manipulations to V1 implicate it as a site of learning reward timing activity (as opposed to simply reporting timing information from another region via feedback input). However, the manner by which V1 then produces these representations is unknown. Here, we combine behavior, in vivo electrophysiology, and optogenetics to investigate the characteristics of and circuit mechanisms underlying V1 reward timing in the head-fixed mouse. We find that reward timing activity is present in mouse V1, that inhibitory interneurons participate in reward timing, and that these representations are consistent with a theorized network architecture. Together, these results deepen our understanding of V1 reward timing and the manner by which it is produced.

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It is not well understood how associations between two temporally removed stimuli form. In this issue of Neuron, Guo et al. (2019) implicate basal forebrain cholinergic neurons as providing a link between auditory cues and the aversive outcomes they predict.

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An emerging body of work challenges the view that primary visual cortex (V1) represents the visual world faithfully. Theta oscillations in the local field potential (LFP) of V1 have been found to convey temporal expectations and, specifically, to express the delay between a visual stimulus and the reward that it portends. We extend this work by showing how these oscillatory states in male, wild-type rats can even relate to the timing of a visually cued reward-seeking behavior. In particular, we show that, with training, high precision and accuracy in behavioral timing tracks the power of these oscillations and the time of action execution covaries with their duration. These LFP oscillations are also intimately related to spiking responses at the single-unit level, which themselves carry predictive timing information. Together, these observations extend our understanding of the role of cortical oscillations in timing generally and the role of V1 in the timing of visually cued behaviors specifically.SIGNIFICANCE STATEMENT Traditionally, primary visual cortex (V1) has been regarded as playing a purely perceptual role in stimulus-driven behaviors. Recent work has challenged that view by showing that theta oscillations in rodent V1 may come to convey timed expectations. Here, we show that these theta oscillations carry predictive information about timed reward-seeking actions, thus elucidating a behavioral role for theta oscillations in V1 and extending our understanding of the role of V1 in decision making.

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Making decisions that factor the cost of time is fundamental to survival. Yet, while it is readily appreciated that our perception of time is intimately involved in this process, theories regarding intertemporal decision-making and theories regarding time perception are treated, largely, independently. Even within these respective domains, models providing good fits to data fail to provide insight as to why, from a normative sense, those fits should take their apparent form. Conversely, normative models that proffer a rationalization for why an agent should weigh options in a particular way, or to perceive time in a particular way, fail to account for the full body of well-established experimental evidence. Here we review select, yet key advances in our understanding, identifying conceptual breakthroughs in the fields of intertemporal decision-making and in time perception, as well as their limits and failings in the face of hard-won experimental observation. On this background of accrued knowledge, a new conception unifying the domains of decision-making and time perception is put forward (Training-Integrated Maximization of Reinforcement Rate, TIMERR) to provide a better fit to observations and a more parsimonious reckoning of why we make choices, and thereby perceive time, the way we do.

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Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that "Lévy random walks"-which can produce power law path length distributions-are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent's goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.

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While many high-level cortical areas have been implicated in timing, timing activity has also been observed even in the earliest cortical stages of the visual system over the past decade. This activity has been formally modeled as one arising from a reinforcement signal, leading to testable hypotheses with recent experimental support, demonstrating the necessity and sufficiency of that reinforcement signal. As observed in other cortical areas implicated in timing, interval timing activity within the visual cortex abides by the temporal scalar property. Finally, perturbations of the visual cortex during interval timing results in lawful shifts in timing. These and related observations advance the notion that visual cortex is a substrate for learning and expressing visually-associated temporal expectations governing behaviorally-relevant actions.

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It has been previously shown (Namboodiri, Mihalas, Marton, & Hussain Shuler, 2014) that an evolutionary theory of decision making and time perception is capable of explaining numerous behavioral observations regarding how humans and animals decide between differently delayed rewards of differing magnitudes and how they perceive time. An implementation of this theory using a stochastic drift-diffusion accumulator model (Namboodiri, Mihalas, & Hussain Shuler, 2014a) showed that errors in time perception and decision making approximately obey Weber's law for a range of parameters. However, prior calculations did not have a clear mechanistic underpinning. Further, these calculations were only approximate, with the range of parameters being limited. In this letter, we provide a full analytical treatment of such an accumulator model, along with a mechanistic implementation, to calculate the expression of these errors for the entirety of the parameter space. In our mechanistic model, Weber's law results from synaptic facilitation and depression within the feedback synapses of the accumulator. Our theory also makes the prediction that the steepness of temporal discounting can be affected by requiring the precise timing of temporal intervals. Thus, by presenting exact quantitative calculations, this work provides falsifiable predictions for future experimental testing.

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The basal forebrain (BF) houses major ascending projections to the entire neocortex that have long been implicated in arousal, learning, and attention. The disruption of the BF has been linked with major neurological disorders, such as coma and Alzheimer's disease, as well as in normal cognitive aging. Although it is best known for its cholinergic neurons, the BF is in fact an anatomically and neurochemically complex structure. Recent studies using transgenic mouse lines to target specific BF cell types have led to a renaissance in the study of the BF and are beginning to yield new insights about cell-type-specific circuit mechanisms during behavior. These approaches enable us to determine the behavioral conditions under which cholinergic and noncholinergic BF neurons are activated and how they control cortical processing to influence behavior. Here we discuss recent advances that have expanded our knowledge about this poorly understood brain region and laid the foundation for future cell-type-specific manipulations to modulate arousal, attention, and cortical plasticity in neurological disorders. SIGNIFICANCE STATEMENT: Although the basal forebrain is best known for, and often equated with, acetylcholine-containing neurons that provide most of the cholinergic innervation of the neocortex, it is in fact an anatomically and neurochemically complex structure. Recent studies using transgenic mouse lines to target specific cell types in the basal forebrain have led to a renaissance in this field and are beginning to dissect circuit mechanisms in the basal forebrain during behavior. This review discusses recent advances in the roles of basal forebrain cholinergic and noncholinergic neurons in cognition via their dynamic modulation of cortical activity.

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Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in the primary visual cortex (V1) of rodents, wherein neural responses to visual cues come to predict the time of future reward as behaviorally experienced in the past. These reward-timing responses exhibit significant heterogeneity in at least three qualitatively distinct classes: sustained increase or sustained decrease in firing rate until the time of expected reward, and a class of cells that reach a peak in firing at the expected delay. We elaborate upon our existing model by including inhibitory and excitatory units while imposing simple connectivity rules to demonstrate what role these inhibitory elements and the simple architectures play in sculpting the response dynamics of the network. We find that simply adding inhibition is not sufficient for obtaining the different distinct response classes, and that a broad distribution of inhibitory projections is necessary for obtaining peak-type responses. Furthermore, although changes in connection strength that modulate the effects of inhibition onto excitatory units have a strong impact on the firing rate profile of these peaked responses, the network exhibits robustness in its overall ability to predict the expected time of reward. Finally, we demonstrate how the magnitude of expected reward can be encoded at the expected delay in the network and how peaked responses express this reward expectancy. SIGNIFICANCE STATEMENT: Heterogeneity in single-neuron responses is a common feature of neuronal systems, although sometimes, in theoretical approaches, it is treated as a nuisance and seldom considered as conveying a different aspect of a signal. In this study, we focus on the heterogeneous responses in the primary visual cortex of rodents trained with a predictable delayed reward time. We describe under what conditions this heterogeneity can arise by self-organization, and what information it can convey. This study, while focusing on a specific system, provides insight onto how heterogeneity can arise in general while also shedding light onto mechanisms of reinforcement learning using realistic biological assumptions.

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Drug addiction and reward learning both involve mechanisms in which reinforcing neuromodulators participate in changing synaptic strength. For example, dopamine receptor activation modulates corticostriatal plasticity through a mechanism involving the induction of the immediate early gene Homer 1a, the phosphorylation of metabotropic glutamate receptor 5 (mGluR5)'s Homer ligand, and the enhancement of an NMDA receptor-dependent current. Inspired by hypotheses that Homer 1a functions selectively in recently-active synapses, we propose that Homer 1a is recruited by a synaptic tag to functionally discriminate between synapses that predict reward and those that do not. The involvement of Homer 1a in this mechanism further suggests that decaminutes-old firing patterns can define which synapses encode new information.

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The ability to time intervals confers organisms, including humans, with many remarkable capabilities. A common method for studying interval timing is classification, in which a subject must indicate whether a given probe duration is nearer a previously learned short or long reference interval. This task is designed to reveal the probe duration that is equally likely to be labeled as short or long, known as the temporal bisection point. Studies have found that this bisection point is influenced by a variety of factors including the ratio of the target intervals, the spacing of the probe durations, the modalities of the stimuli, the attentional load, and the inter-trial duration. While several of these factors are thought to be mediated by memory effects, the prototypical classification task affords no opportunity to measure these memory effects directly. Here, we present a novel bisection task, termed the "Bisection by Classification and Production" (BiCaP) task, in which classification trials are interleaved with trials in which subjects must produce either the short or long referents or their midpoint. Using this method, we found a significant correlation between the means of the remembered referents and the bisection points for both classification and production trials. We then cross-validated the bisection points for production and classification trials by showing that they were not statistically differentiable. In addition to these population-level effects, we found within-subject evidence for co-variation across a session between the production bisection points and the means of the remembered referents. Finally, by using two sets of referent durations, we showed that only memory bias-corrected measures were consistent with a previously reported effect in which the ratio of the referents affects the location of the bisection point. These results suggest that memory effects should be considered in temporal tasks.

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The primary visual cortex (V1) is widely regarded as faithfully conveying the physical properties of visual stimuli. Thus, experience-induced changes in V1 are often interpreted as improving visual perception (i.e., perceptual learning). Here we describe how, with experience, cue-evoked oscillations emerge in V1 to convey expected reward time as well as to relate experienced reward rate. We show, in chronic multisite local field potential recordings from rat V1, that repeated presentation of visual cues induces the emergence of visually evoked oscillatory activity. Early in training, the visually evoked oscillations relate to the physical parameters of the stimuli. However, with training, the oscillations evolve to relate the time in which those stimuli foretell expected reward. Moreover, the oscillation prevalence reflects the reward rate recently experienced by the animal. Thus, training induces experience-dependent changes in V1 activity that relate to what those stimuli have come to signify behaviorally: when to expect future reward and at what rate.

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As a consequence of conditioning visual cues with delayed reward, cue-evoked neural activity that predicts the time of expected future reward emerges in the primary visual cortex (V1). We hypothesized that this reward-timing activity is engendered by a reinforcement signal conveying reward acquisition to V1. In lieu of behavioral conditioning, we assessed in vivo whether selective activation of either basal forebrain (BF) or cholinergic innervation is sufficient to condition cued interval-timing activity. Substituting for actual reward, optogenetic activation of BF or cholinergic input within V1 at fixed delays following visual stimulation entrains neural responses that mimic behaviorally conditioned reward-timing activity. Optogenetically conditioned neural responses express cue-evoked temporal intervals that correspond to the conditioning intervals, are bidirectionally modifiable, display experience-dependent refinement, and exhibit a scale invariance to the encoded delay. Our results demonstrate that the activation of BF or cholinergic input within V1 is sufficient to encode cued interval-timing activity and indicate that V1 itself is a substrate for associative learning that may inform the timing of visually cued behaviors.

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Most behaviors are generated in three steps: sensing the external world, processing that information to instruct decision-making, and producing a motor action. Sensory areas, especially primary sensory cortices, have long been held to be involved only in the first step of this sequence. Here, we develop a visually cued interval timing task that requires rats to decide when to perform an action following a brief visual stimulus. Using single-unit recordings and optogenetics in this task, we show that activity generated by the primary visual cortex (V1) embodies the target interval and may instruct the decision to time the action on a trial-by-trial basis. A spiking neuronal model of local recurrent connections in V1 produces neural responses that predict and drive the timing of future actions, rationalizing our observations. Our data demonstrate that the primary visual cortex may contribute to the instruction of visually cued timed actions.

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Weber's law-the observation that the ability to perceive changes in magnitudes of stimuli is proportional to the magnitude-is a widely observed psychophysical phenomenon. It is also believed to underlie the perception of reward magnitudes and the passage of time. Since many ecological theories state that animals attempt to maximize reward rates, errors in the perception of reward magnitudes and delays must affect decision-making. Using an ecological theory of decision-making (TIMERR), we analyze the effect of multiple sources of noise (sensory noise, time estimation noise, and integration noise) on reward magnitude and subjective value perception. We show that the precision of reward magnitude perception is correlated with the precision of time perception and that Weber's law in time estimation can lead to Weber's law in value perception. The strength of this correlation is predicted to depend on the reward history of the animal. Subsequently, we show that sensory integration noise (either alone or in combination with time estimation noise) also leads to Weber's law in reward magnitude perception in an accumulator model, if it has balanced Poisson feedback. We then demonstrate that the noise in subjective value of a delayed reward, due to the combined effect of noise in both the perception of reward magnitude and delay, also abides by Weber's law. Thus, in our theory we prove analytically that the perception of reward magnitude, time, and subjective value change all approximately obey Weber's law.

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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.

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