ARTICLE Updating temporal expectancy of an aversive event engages striatal plasticity under amygdala control (original) (raw)
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Updating temporal expectancy of an aversive event engages striatal plasticity under amygdala control
Nature communications, 2017
Pavlovian aversive conditioning requires learning of the association between a conditioned stimulus (CS) and an unconditioned, aversive stimulus (US) but also involves encoding the time interval between the two stimuli. The neurobiological bases of this time interval learning are unknown. Here, we show that in rats, the dorsal striatum and basal amygdala belong to a common functional network underlying temporal expectancy and learning of a CS-US interval. Importantly, changes in coherence between striatum and amygdala local field potentials (LFPs) were found to couple these structures during interval estimation within the lower range of the theta rhythm (3-6 Hz). Strikingly, we also show that a change to the CS-US time interval results in long-term changes in cortico-striatal synaptic efficacy under the control of the amygdala. Collectively, this study reveals physiological correlates of plasticity mechanisms of interval timing that take place in the striatum and are regulated by th...
The amygdala: A potential player in timing CS–US intervals
Behavioural Processes, 2014
Pavlovian conditioning is the reference paradigm for the study of associative learning based on the programmed relation of two stimuli, the conditioned stimulus (CS) and the unconditioned stimulus (US). Some authors believe that learning the CS-US interval is a co-requisite of or a pre-requisite to learning the CS-US association. There is a substantial literature showing that the amygdala is a critical player in Pavlovian conditioning, with both aversive and appetitive USs. We review a sparse but growing body of literature suggesting that the amygdala may also participate in processing the timing of the CS-US interval. We discuss whether the amygdala, in particular its central, basal and lateral nuclei, in concert with the network it belongs to, may play a role in learning the CS-US interval. We also suggest new and dedicated strategies that would result in better knowledge of the neural mechanisms underlying the learning of the CS-US time interval in isolation from the CS-US association.
Processing of Temporal Unpredictability in Human and Animal Amygdala
Journal of Neuroscience, 2007
The amygdala has been studied extensively for its critical role in associative fear conditioning in animals and humans. Noxious stimuli, such as those used for fear conditioning, are most effective in eliciting behavioral responses and amygdala activation when experienced in an unpredictable manner. Here, we show, using a translational approach in mice and humans, that unpredictability per se without interaction with motivational information is sufficient to induce sustained neural activity in the amygdala and to elicit anxiety-like behavior. Exposing mice to mere temporal unpredictability within a time series of neutral sound pulses in an otherwise neutral sensory environment increased expression of the immediate-early gene c-fos and prevented rapid habituation of single neuron activity in the basolateral amygdala. At the behavioral level, unpredictable, but not predictable, auditory stimulation induced avoidance and anxietylike behavior. In humans, functional magnetic resonance imaging revealed that temporal unpredictably causes sustained neural activity in amygdala and anxiety-like behavior as quantified by enhanced attention toward emotional faces. Our findings show that unpredictability per se is an important feature of the sensory environment influencing habituation of neuronal activity in amygdala and emotional behavior and indicate that regulation of amygdala habituation represents an evolutionary-conserved mechanism for adapting behavior in anticipation of temporally unpredictable events.
Dissociable Reward and Timing Signals in Human Midbrain and Ventral Striatum
Neuron, 2011
Reward prediction error (RPE) signals are central to current models of reward-learning. Temporal difference (TD) learning models posit that these signals should be modulated by predictions, not only of magnitude but also timing of reward. Here we show that BOLD activity in the VTA conforms to such TD predictions: responses to unexpected rewards are modulated by a temporal hazard function and activity between a predictive stimulus and reward is depressed in proportion to predicted reward. By contrast, BOLD activity in ventral striatum (VS) does not reflect a TD RPE, but instead encodes a signal on the variable relevant for behavior, here timing but not magnitude of reward. The results have important implications for dopaminergic models of corticostriatal learning and suggest a modification of the conventional view that VS BOLD necessarily reflects inputs from dopaminergic VTA neurons signaling an RPE.
Temporal learning among prefrontal and striatal ensembles
2020
Behavioral flexibility requires the prefrontal cortex and striatum. Here, we investigate neuronal ensembles in the medial frontal cortex (MFC) and the dorsomedial striatum (DMS) during one form of behavioral flexibility: learning a new temporal interval. We studied corticostriatal neuronal activity as rodents trained to respond after a 12-second fixed interval (FI12) learned to respond at a shorter 3-second fixed interval (FI3). On FI12 trials, we discovered time-related ramping was reduced in the MFC but not in the DMS in two-interval vs. one-interval sessions. We also found that more DMS neurons than MFC neurons exhibited differential interval-related activity on the first day of two-interval performance. Finally, MFC and DMS ramping was similar with successive days of two-interval performance but DMS temporal decoding increased on FI3 trials. These data suggest that the MFC and DMS play distinct roles during temporal learning and provide insight into corticostriatal circuits.
Frontiers in Systems Neuroscience, 2021
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 ...
Time course of amygdala activation during aversive conditioning depends on attention
2007
The time course of amygdala activation during aversive conditioning is a matter of debate. While some researchers reported rapid habituation, others found stable or no amygdalar responses to conditioned stimuli at all. In the present event-related fMRI study, we investigated whether the activity of the amygdala during aversive conditioning depends on attentional conditions. Subjects underwent aversive delay conditioning by pairing an electrical shock (unconditioned aversive stimulus) with a visual conditioned stimulus (CS+). For each singular presentation of the CS+ or a nonconditioned visual stimulus (CS−), subjects attended in random order to features that either differed between both stimuli (identification task) or that did not differ (distraction task). For the identification task trials, increased responses of the left amygdala to CS+ versus CS− were rapidly established but absent at the end of the conditioning trials. In contrast, under the distraction condition, amygdala activation to CS+ versus CS− was present during the late but not the early phase of conditioning. The results suggest that the time course of amygdala activity during aversive associative learning is strongly modulated by an interaction of attention and time.
Time determines the neural circuit underlying associative fear learning
Frontiers in …, 2011
Ultimately associative learning is a function of the temporal features and relationships between experienced stimuli. Nevertheless how time affects the neural circuit underlying this form of learning remains largely unknown. To address this issue, we used single-trial auditory trace fear conditioning and varied the length of the interval between tone and foot-shock. Through temporary inactivation of the amygdala, medial prefrontal-cortex (mPFC), and dorsal-hippocampus in rats, we tested the hypothesis that different temporal intervals between the tone and the shock influence the neuronal structures necessary for learning. With this study we provide the first experimental evidence showing that temporarily inactivating the amygdala before training impairs auditory fear learning when there is a temporal gap between the tone and the shock. Moreover, imposing a short interval (5 s) between the two stimuli also relies on the mPFC, while learning the association across a longer interval (40 s) becomes additionally dependent on a third structure, the dorsal-hippocampus. Thus, our results suggest that increasing the interval length between tone and shock leads to the involvement of an increasing number of brain areas in order for the association between the two stimuli to be acquired normally. These findings demonstrate that the temporal relationship between events is a key factor in determining the neuronal mechanisms underlying associative fear learning.
Learning reward timing in cortex through reward dependent expression of synaptic plasticity
Proceedings of The National Academy of Sciences, 2009
The ability to represent time is an essential component of cognition but its neural basis is unknown. Although extensively studied both behaviorally and electrophysiologically, a general theoretical framework describing the elementary neural mechanisms used by the brain to learn temporal representations is lacking. It is commonly believed that the underlying cellular mechanisms reside in high order cortical regions but recent studies show sustained neural activity in primary sensory cortices that can represent the timing of expected reward. Here, we show that local cortical networks can learn temporal representations through a simple framework predicated on reward dependent expression of synaptic plasticity. We assert that temporal representations are stored in the lateral synaptic connections between neurons and demonstrate that reward-modulated plasticity is sufficient to learn these representations. We implement our model numerically to explain reward-time learning in the primary visual cortex (V1), demonstrate experimental support, and suggest additional experimentally verifiable predictions. reinforcment learning ͉ visual cortex O ur brains process time with such instinctual ease that the difficulty of defining what time is, in a neural sense, seems paradoxical. There is a rich literature in experimental neuroscience describing the temporal dynamics of both cellular and system-level neuronal processes and many insightful psychophysical studies have revealed perceptual correlates of time. Despite this, and the clear importance of accurate temporal processing at all levels of behavior, we still know little about how time is represented or used by the brain (1). Temporal processing is classically understood as a higher order function, and although there is some disagreement (2, 3), it is often argued that dedicated structures or regions in the brain are responsible for representing time (4). Because different mechanisms are likely responsible for computing timing at different time scales (1, 5, 6), and because there is evidence for modality specific temporal mechanisms , an alternative possibility is that timing processes develop locally within different brain regions.