Rodent Medial Frontal Control of Temporal Processing in the Dorsomedial Striatum

The frontal cortex adjusts striatal integrator dynamics for flexible motor timing

Flexible control of motor timing is crucial for behavior. Before movement begins, the frontal cortex and striatum exhibit ramping spiking activity, with variable ramp slopes anticipating movement onsets. This activity may function as an adjustable 'timer,' triggering actions at the desired timing. However, because the frontal cortex and striatum share similar ramping dynamics and are both necessary for timing behaviors, distinguishing their individual roles in this timer function remains challenging. To address this, we conducted perturbation experiments combined with multi-regional electrophysiology in mice performing a lick-timing task. Following transient silencing of the frontal cortex, cortical and striatal activity swiftly returned to pre-silencing levels and resumed ramping, leading to a shift in lick timing close to the silencing duration. Conversely, briefly inhibiting the striatum caused a gradual decrease in ramping activity in both regions, with ramping resuming from post-inhibition levels, shifting lick timing beyond the inhibition duration. Thus, inhibiting the frontal cortex and striatum effectively paused and rewound the timer, respectively. Additionally, the frontal cortex, but not the striatum, encodes trial-history information guiding lick timing. These findings suggest specialized functional allocations within the forebrain: the striatum temporally integrates input from the frontal cortex to generate ramping activity that regulates motor timing.

Representation of rhythmic chunking in striatum of mice executing complex continuous movement sequences

We used a step-wheel system to examine the activity of striatal projection neurons as mice practiced stepping on complexly arranged foothold pegs in this Ferris-wheel-like device to receive reward. Sets of dorsolateral striatal projection neurons were sensitive to specific parameters of repetitive motor coordination during the runs. They responded to combinations of the parameters of continuous movements (interval, phase, and repetition), forming "chunking responses"-some for combinations of these parameters across multiple body parts. Recordings in sensorimotor cortical areas exhibited notably fewer such responses but were documented for smaller neuron sets whose heterogeneity was significant. Striatal movement encoding via chunking responsivity could provide insight into neural strategies governing effective motor control by the striatum. It is possible that the striking need for external rhythmic cuing to allow movement sequences by Parkinson's patients could, at least in part, reflect dysfunction in such striatal coding.

Complementary opposing D2-MSNs and D1-MSNs dynamics during interval timing

The role of striatal pathways in cognitive processing is unclear. We studied dorsomedial striatal cognitive processing during interval timing, an elementary cognitive task that requires mice to estimate intervals of several seconds and involves working memory for temporal rules as well as attention to the passage of time. We harnessed optogenetic tagging to record from striatal D2-dopamine receptor-expressing medium spiny neurons (D2-MSNs) in the indirect pathway and from D1-dopamine receptor-expressing MSNs (D1-MSNs) in the direct pathway. We found that D2-MSNs and D1-MSNs exhibited distinct dynamics over temporal intervals as quantified by principal component analyses and trial-by-trial generalized linear models. MSN recordings helped construct and constrain a four-parameter drift-diffusion computational model. This model predicted that disrupting either D2-MSNs or D1-MSNs would increase interval timing response times and alter MSN firing. In line with this prediction, we found that optogenetic inhibition or pharmacological disruption of either D2-MSNs or D1-MSNs increased interval timing response times. Pharmacologically disrupting D2-MSNs or D1-MSNs also changed MSN dynamics and degraded trial-by-trial temporal decoding. Together, our findings demonstrate that D2-MSNs and D1-MSNs make complementary contributions to interval timing despite opposing dynamics, implying that striatal direct and indirect pathways work together to shape temporal control of action. These data provide novel insight into basal ganglia cognitive operations beyond movement and have implications for human striatal diseases and therapies targeting striatal pathways.

Goal-Directed Learning is Multidimensional and Accompanied by Diverse and Widespread Changes in Neocortical Signaling

New tasks are often learned in stages with each stage reflecting a different learning challenge. Accordingly, each learning stage is likely mediated by distinct neuronal processes. And yet, most rodent studies of the neuronal correlates of goal-directed learning focus on individual outcome measures and individual brain regions. Here, we longitudinally studied mice from naïve to expert performance in a head-fixed, operant conditioning whisker discrimination task. In addition to tracking the primary behavioral outcome of stimulus discrimination, we tracked and compared an array of object-based and temporal-based behavioral measures. These behavioral analyses identify multiple, partially overlapping learning stages in this task, consistent with initial response implementation, early stimulus-response generalization, and late response inhibition. To begin to understand the neuronal foundations of these learning processes, we performed widefield Ca2+ imaging of dorsal neocortex throughout learning and correlated behavioral measures with neuronal activity. We found distinct and widespread correlations between neocortical activation patterns and various behavioral measures. For example, improvements in sensory discrimination correlated with target stimulus evoked activations of licking-related cortices along with distractor stimulus evoked global cortical suppression. Our study reveals multidimensional learning for a simple goal-directed learning task and generates hypotheses for the neuronal modulations underlying these various learning processes.

Sub-second and multi-second dopamine dynamics underlie variability in human time perception

Timing behaviour and the perception of time are fundamental to cognitive and emotional processes in humans. In non-human model organisms, the neuromodulator dopamine has been associated with variations in timing behaviour, but the connection between variations in dopamine levels and the human experience of time has not been directly assessed. Here, we report how dopamine levels in human striatum, measured with sub-second temporal resolution during awake deep brain stimulation surgery, relate to participants' perceptual judgements of time intervals. Fast, phasic, dopaminergic signals were associated with underestimation of temporal intervals, whereas slower, tonic, decreases in dopamine were associated with poorer temporal precision. Our findings suggest a delicate and complex role for the dynamics and tone of dopaminergic signals in the conscious experience of time in humans.

Ramping dynamics and theta oscillations reflect dissociable signatures during rule-guided human behavior

Contextual cues and prior evidence guide human goal-directed behavior. The neurophysiological mechanisms that implement contextual priors to guide subsequent actions in the human brain remain unclear. Using intracranial electroencephalography (iEEG), we demonstrate that increasing uncertainty introduces a shift from a purely oscillatory to a mixed processing regime with an additional ramping component. Oscillatory and ramping dynamics reflect dissociable signatures, which likely differentially contribute to the encoding and transfer of different cognitive variables in a cue-guided motor task. The results support the idea that prefrontal activity encodes rules and ensuing actions in distinct coding subspaces, while theta oscillations synchronize the prefrontal-motor network, possibly to guide action execution. Collectively, our results reveal how two key features of large-scale neural population activity, namely continuous ramping dynamics and oscillatory synchrony, jointly support rule-guided human behavior.

Keeping time and rhythm by internal simulation of sensory stimuli and behavioral actions

Effective behavior often requires synchronizing our actions with changes in the environment. Rhythmic changes in the environment are easy to predict, and we can readily time our actions to them. Yet, how the brain encodes and maintains rhythms is not known. Here, we trained primates to internally maintain rhythms of different tempos and performed large-scale recordings of neuronal activity across the sensory-motor hierarchy. Results show that maintaining rhythms engages multiple brain areas, including visual, parietal, premotor, prefrontal, and hippocampal regions. Each recorded area displayed oscillations in firing rates and oscillations in broadband local field potential power that reflected the temporal and spatial characteristics of an internal metronome, which flexibly encoded fast, medium, and slow tempos. The presence of widespread metronome-related activity, in the absence of stimuli and motor activity, suggests that internal simulation of stimuli and actions underlies timekeeping and rhythm maintenance.

Distinct neural adaptations to time demand in the striatum and the hippocampus

How do neural codes adjust to track time across a range of resolutions, from milliseconds to multi-seconds, as a function of the temporal frequency at which events occur? To address this question, we studied time-modulated cells in the striatum and the hippocampus, while macaques categorized three nested intervals within the sub-second or the supra-second range (up to 1, 2, 4, or 8 s), thereby modifying the temporal resolution needed to solve the task. Time-modulated cells carried more information for intervals with explicit timing demand, than for any other interval. The striatum, particularly the caudate, supported the most accurate temporal prediction throughout all time ranges. Strikingly, its temporal readout adjusted non-linearly to the time range, suggesting that the striatal resolution shifted from a precise millisecond to a coarse multi-second range as a function of demand. This is in line with monkey's behavioral latencies, which indicated that they tracked time until 2 s but employed a coarse categorization strategy for durations beyond. By contrast, the hippocampus discriminated only the beginning from the end of intervals, regardless of the range. We propose that the hippocampus may provide an overall poor signal marking an event's beginning, whereas the striatum optimizes neural resources to process time throughout an interval adapting to the ongoing timing necessity.

Alpha-Synuclein Pre-Formed Fibrils Injected into Prefrontal Cortex Primarily Spread to Cortical and Subcortical Structures

BACKGROUND

Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB) are characterized by diffuse spread of alpha-synuclein (α-syn) throughout the brain. Patients with PDD and DLB have a neuropsychological pattern of deficits that include executive dysfunction, such as abnormalities in planning, timing, working memory, and behavioral flexibility. The prefrontal cortex (PFC) plays a major role in normal executive function and often develops α-syn aggregates in DLB and PDD.

OBJECTIVE

To investigate the long-term behavioral and cognitive consequences of α-syn pathology in the cortex and characterize pathological spread of α-syn.

METHODS

We injected human α-syn pre-formed fibrils into the PFC of wild-type male mice. We then assessed the behavioral and cognitive effects between 12- and 21-months post-injection and characterized the spread of pathological α-syn in cortical, subcortical, and brainstem regions.

RESULTS

We report that PFC PFFs: 1) induced α-syn aggregation in multiple cortical and subcortical regions with sparse aggregation in midbrain and brainstem nuclei; 2) did not affect interval timing or spatial learning acquisition but did mildly alter behavioral flexibility as measured by intraday reversal learning; and 3) increased open field exploration.

CONCLUSIONS

This model of cortical-dominant pathology aids in our understanding of how local α-syn aggregation might impact some symptoms in PDD and DLB.

Neurocomputational Models of Interval Timing: Seeing the Forest for the Trees

Extracting temporal regularities and relations from experience/observation is critical for organisms' adaptiveness (communication, foraging, predation, prediction) in their ecological niches. Therefore, it is not surprising that the internal clock that enables the perception of seconds-to-minutes-long intervals (interval timing) is evolutionarily well-preserved across many species of animals. This comparative claim is primarily supported by the fact that the timing behavior of many vertebrates exhibits common statistical signatures (e.g., on-average accuracy, scalar variability, positive skew). These ubiquitous statistical features of timing behaviors serve as empirical benchmarks for modelers in their efforts to unravel the processing dynamics of the internal clock (namely answering how internal clock "ticks"). In this chapter, we introduce prominent (neuro)computational approaches to modeling interval timing at a level that can be understood by general audience. These models include Treisman's pacemaker accumulator model, the information processing variant of scalar expectancy theory, the striatal beat frequency model, behavioral expectancy theory, the learning to time model, the time-adaptive opponent Poisson drift-diffusion model, time cell models, and neural trajectory models. Crucially, we discuss these models within an overarching conceptual framework that categorizes different models as threshold vs. clock-adaptive models and as dedicated clock/ramping vs. emergent time/population code models.

Diverse Time Encoding Strategies Within the Medial Premotor Areas of the Primate

The measurement of time in the subsecond scale is critical for many sophisticated behaviors, yet its neural underpinnings are largely unknown. Recent neurophysiological experiments from our laboratory have shown that the neural activity in the medial premotor areas (MPC) of macaques can represent different aspects of temporal processing. During single interval categorization, we found that preSMA encodes a subjective category limit by reaching a peak of activity at a time that divides the set of test intervals into short and long. We also observed neural signals associated with the category selected by the subjects and the reward outcomes of the perceptual decision. On the other hand, we have studied the behavioral and neurophysiological basis of rhythmic timing. First, we have shown in different tapping tasks that macaques are able to produce predictively and accurately intervals that are cued by auditory or visual metronomes or when intervals are produced internally without sensory guidance. In addition, we found that the rhythmic timing mechanism in MPC is governed by different layers of neural clocks. Next, the instantaneous activity of single cells shows ramping activity that encodes the elapsed or remaining time for a tapping movement. In addition, we found MPC neurons that build neural sequences, forming dynamic patterns of activation that flexibly cover all the produced interval depending on the tapping tempo. This rhythmic neural clock resets on every interval providing an internal representation of pulse. Furthermore, the MPC cells show mixed selectivity, encoding not only elapsed time, but also the tempo of the tapping and the serial order element in the rhythmic sequence. Hence, MPC can map different task parameters, including the passage of time, using different cell populations. Finally, the projection of the time varying activity of MPC hundreds of cells into a low dimensional state space showed circular neural trajectories whose geometry represented the internal pulse and the tapping tempo. Overall, these findings support the notion that MPC is part of the core timing mechanism for both single interval and rhythmic timing, using neural clocks with different encoding principles, probably to flexibly encode and mix the timing representation with other task parameters.

Striatum-projecting prefrontal cortex neurons support working memory maintenance

Neurons in the medial prefrontal cortex (mPFC) are functionally linked to working memory (WM) but how distinct projection pathways contribute to WM remains unclear. Based on optical recordings, optogenetic perturbations, and pharmacological interventions in male mice, we report here that dorsomedial striatum (dmStr)-projecting mPFC neurons are essential for WM maintenance, but not encoding or retrieval, in a T-maze spatial memory task. Fiber photometry of GCaMP6m-labeled mPFC→dmStr neurons revealed strongest activity during the maintenance period, and optogenetic inhibition of these neurons impaired performance only when applied during this period. Conversely, enhancing mPFC→dmStr pathway activity-via pharmacological suppression of HCN1 or by optogenetic activation during the maintenance period-alleviated WM impairment induced by NMDA receptor blockade. Moreover, cellular-resolution miniscope imaging revealed that >50% of mPFC→dmStr neurons are active during WM maintenance and that this subpopulation is distinct from neurons active during encoding and retrieval. In all task periods, neuronal sequences were evident. Striatum-projecting mPFC neurons thus critically contribute to spatial WM maintenance.

Amodal population clock in the primate medial premotor system for rhythmic tapping

The neural substrate for beat extraction and response entrainment to rhythms is not fully understood. Here we analyze the activity of medial premotor neurons in monkeys performing isochronous tapping guided by brief flashing stimuli or auditory tones. The population dynamics shared the following properties across modalities: the circular dynamics of the neural trajectories form a regenerating loop for every produced interval; the trajectories converge in similar state space at tapping times resetting the clock; and the tempo of the synchronized tapping is encoded in the trajectories by a combination of amplitude modulation and temporal scaling. Notably, the modality induces displacement in the neural trajectories in the auditory and visual subspaces without greatly altering the time-keeping mechanism. These results suggest that the interaction between the medial premotor cortex's amodal internal representation of pulse and a modality-specific external input generates a neural rhythmic clock whose dynamics govern rhythmic tapping execution across senses.

The PrLGlu→avBNSTGABA circuit rapidly modulates depression-like behaviors in male mice

Depression is a global disease with a high prevalence. Here, we examine the role of the circuit from prelimbic mPFC (PrL) to the anterior ventral bed nucleus of the stria terminalis (avBNST) in depression-like mice through behavioral tests, immunofluorescence, chemogenetics, optogenetics, pharmacology, and fiber photometry. Mice exposed to chronic restraint stress with individual housing displayed depression-like behaviors. Optogenetic or chemogenetic activation of the avBNST-projecting glutamatergic neurons in the PrL had an antidepressant effect. Moreover, we found that α-amino-3-hydroxy-5-methyl-4-isoxazole-propionicacid receptors (AMPARs) play a dominant role in this circuit. Systemic administration of ketamine profoundly alleviated depression-like behaviors in the mice and rapidly rescued the decreased activity in the PrLGlu→avBNSTGABA circuit. Furthermore, the fast-acting effect of ketamine on depressive behaviors was diminished when the circuit was inhibited. To summarize, activating the PrLGlu→avBNSTGABA circuit quickly ameliorated depression-like behaviors. Thus, we propose the PrLGlu→avBNSTGABA circuit as a target for fast regulation of depression.

Rhythm Receptive Fields in Striatum of Mice Executing Complex Continuous Movement Sequences

By the use of a novel experimental system, the step-wheel, we investigated the neural underpinnings of complex and continuous movements. We recorded neural activities from the dorsolateral striatum and found neurons sensitive to movement rhythm parameters. These neurons responded to specific combinations of interval, phase, and repetition of movement, effectively forming what we term "rhythm receptive fields." Some neurons even responsive to the combination of movement phases of multiple body parts. In parallel, cortical recordings in sensorimotor areas highlighted a paucity of neurons responsive to multiple parameter combinations, relative to those in the striatum. These findings have implications for comprehending motor coordination deficits seen in brain disorders including Parkinson's disease. Movement encoding by rhythm receptive fields should streamline the brain's capacity to encode temporal patterns, help to resolve the degrees of freedom problem. Such rhythm fields hint at the neural mechanisms governing effective motor control and processing of rhythmic information.

Neuronal glutamate transporters control reciprocal inhibition and gain modulation in D1 medium spiny neurons

Understanding the function of glutamate transporters has broad implications for explaining how neurons integrate information and relay it through complex neuronal circuits. Most of what is currently known about glutamate transporters, specifically their ability to maintain glutamate homeostasis and limit glutamate diffusion away from the synaptic cleft, is based on studies of glial glutamate transporters. By contrast, little is known about the functional implications of neuronal glutamate transporters. The neuronal glutamate transporter EAAC1 is widely expressed throughout the brain, particularly in the striatum, the primary input nucleus of the basal ganglia, a region implicated with movement execution and reward. Here, we show that EAAC1 limits synaptic excitation onto a population of striatal medium spiny neurons identified for their expression of D1 dopamine receptors (D1-MSNs). In these cells, EAAC1 also contributes to strengthen lateral inhibition from other D1-MSNs. Together, these effects contribute to reduce the gain of the input-output relationship and increase the offset at increasing levels of synaptic inhibition in D1-MSNs. By reducing the sensitivity and dynamic range of action potential firing in D1-MSNs, EAAC1 limits the propensity of mice to rapidly switch between behaviors associated with different reward probabilities. Together, these findings shed light on some important molecular and cellular mechanisms implicated with behavior flexibility in mice.

Multiplexing working memory and time in the trajectories of neural networks

Working memory (WM) and timing are generally considered distinct cognitive functions, but similar neural signatures have been implicated in both. To explore the hypothesis that WM and timing may rely on shared neural mechanisms, we used psychophysical tasks that contained either task-irrelevant timing or WM components. In both cases, the task-irrelevant component influenced performance. We then developed recurrent neural network (RNN) simulations that revealed that cue-specific neural sequences, which multiplexed WM and time, emerged as the dominant regime that captured the behavioural findings. During training, RNN dynamics transitioned from low-dimensional ramps to high-dimensional neural sequences, and depending on task requirements, steady-state or ramping activity was also observed. Analysis of RNN structure revealed that neural sequences relied primarily on inhibitory connections, and could survive the deletion of all excitatory-to-excitatory connections. Our results indicate that in some instances WM is encoded in time-varying neural activity because of the importance of predicting when WM will be used.

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.

Influence of Recent Trial History on Interval Timing

Interval timing is involved in a variety of cognitive behaviors such as associative learning and decision-making. While it has been shown that time estimation is adaptive to the temporal context, it remains unclear how interval timing behavior is influenced by recent trial history. Here we found that, in mice trained to perform a licking-based interval timing task, a decrease of inter-reinforcement interval in the previous trial rapidly shifted the time of anticipatory licking earlier. Optogenetic inactivation of the anterior lateral motor cortex (ALM), but not the medial prefrontal cortex, for a short time before reward delivery caused a decrease in the peak time of anticipatory licking in the next trial. Electrophysiological recordings from the ALM showed that the response profiles preceded by short and long inter-reinforcement intervals exhibited task-engagement-dependent temporal scaling. Thus, interval timing is adaptive to recent experience of the temporal interval, and ALM activity during time estimation reflects recent experience of interval.

The neural representation of time distributed across multiple brain regions differs between implicit and explicit time demands

Animals appear to possess an internal timer during action, based on the passage of time. However, the neural underpinnings of the perception of time, ranging from seconds to minutes, remain unclear. Herein, we considered the neural representation of time based on mounting evidence on the neural correlates of time perception. The passage of time in the brain is represented by two types of neural encoding as follows: (i) the modulation of firing rates in single neurons and (ii) the sequential activity in neural ensembles. Time-dependent neural activity reflects the relative time rather than the absolute time, similar to a clock. They emerge in multiple regions, including the hippocampus, medial and lateral entorhinal cortices, medial prefrontal cortex, and dorsal striatum. Moreover, they involve different brain regions, depending on an implicit or explicit event duration. Thus, the two types of internal timers distributed across multiple brain regions simultaneously engage in time perception, in response to implicit or explicit time demands.

Temporal encoding: Relative and absolute representations of time guide behavior

Temporal information-processing is critical for adaptive behavior and goal-directed action. It is thus crucial to understand how the temporal distance between behaviorally relevant events is encoded to guide behavior. However, research on temporal representations has yielded mixed findings as to whether organisms utilize relative versus absolute judgments of time intervals. To address this fundamental question about the timing mechanism, we tested mice in a duration discrimination procedure in which they learned to correctly categorize tones of different durations as short or long. After being trained on a pair of target intervals, the mice were transferred to conditions in which cue durations and corresponding response locations were systematically manipulated so that either the relative or absolute mapping remained constant. The findings indicate that transfer occurred most readily when relative relationships of durations and response locations were preserved. In contrast, when subjects had to re-map these relative relations, even when positive transfer initially occurred based on absolute mappings, their temporal discrimination performance was impaired, and they required extensive training to re-establish temporal control. These results demonstrate that mice can represent experienced durations both as having a certain magnitude (absolute representation) and as being shorter or longer of the two durations (an ordinal relation to other cue durations), with relational control having a more enduring influence in temporal discriminations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Temporal scaling and computing time in neural circuits: Should we stop watching the clock and look for its gears?

Timing underlies a variety of functions, from walking to perceiving causality. Neural timing models typically fall into one of two categories-"ramping" and "population-clock" theories. According to ramping models, individual neurons track time by gradually increasing or decreasing their activity as an event approaches. To time different intervals, ramping neurons adjust their slopes, ramping steeply for short intervals and vice versa. In contrast, according to "population-clock" models, multiple neurons track time as a group, and each neuron can fire nonlinearly. As each neuron changes its rate at each point in time, a distinct pattern of activity emerges across the population. To time different intervals, the brain learns the population patterns that coincide with key events. Both model categories have empirical support. However, they often differ in plausibility when applied to certain behavioral effects. Specifically, behavioral data indicate that the timing system has a rich computational capacity, allowing observers to spontaneously compute novel intervals from previously learned ones. In population-clock theories, population patterns map to time arbitrarily, making it difficult to explain how different patterns can be computationally combined. Ramping models are viewed as more plausible, assuming upstream circuits can set the slope of ramping neurons according to a given computation. Critically, recent studies suggest that neurons with nonlinear firing profiles often scale to time different intervals-compressing for shorter intervals and stretching for longer ones. This "temporal scaling" effect has led to a hybrid-theory where, like a population-clock model, population patterns encode time, yet like a ramping neuron adjusting its slope, the speed of each neuron's firing adapts to different intervals. Here, we argue that these "relative" population-clock models are as computationally plausible as ramping theories, viewing population-speed and ramp-slope adjustments as equivalent. Therefore, we view identifying these "speed-control" circuits as a key direction for evaluating how the timing system performs computations. Furthermore, temporal scaling highlights that a key distinction between different neural models is whether they propose an absolute or relative time-representation. However, we note that several behavioral studies suggest the brain processes both scales, cautioning against a dichotomy.

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.

Neural population clocks: Encoding time in dynamic patterns of neural activity

The ability to predict and prepare for near- and far-future events is among the most fundamental computations the brain performs. Because of the importance of time for prediction and sensorimotor processing, the brain has evolved multiple mechanisms to tell and encode time across scales ranging from microseconds to days and beyond. Converging experimental and computational data indicate that, on the scale of seconds, timing relies on diverse neural mechanisms distributed across different brain areas. Among the different encoding mechanisms on the scale of seconds, we distinguish between neural population clocks and ramping activity as distinct strategies to encode time. One instance of neural population clocks, neural sequences, represents in some ways an optimal and flexible dynamic regime for the encoding of time. Specifically, neural sequences comprise a high-dimensional representation that can be used by downstream areas to flexibly generate arbitrarily simple and complex output patterns using biologically plausible learning rules. We propose that high-level integration areas may use high-dimensional dynamics such as neural sequences to encode time, providing downstream areas information to build low-dimensional ramp-like activity that can drive movements and temporal expectation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Time encoding migrates from prefrontal cortex to dorsal striatum during learning of a self-timed response duration task

Although time is a fundamental dimension of life, we do not know how brain areas cooperate to keep track and process time intervals. Notably, analyses of neural activity during learning are rare, mainly because timing tasks usually require training over many days. We investigated how the time encoding evolves when animals learn to time a 1.5 s interval. We designed a novel training protocol where rats go from naive- to proficient-level timing performance within a single session, allowing us to investigate neuronal activity from very early learning stages. We used pharmacological experiments and machine-learning algorithms to evaluate the level of time encoding in the medial prefrontal cortex and the dorsal striatum. Our results show a double dissociation between the medial prefrontal cortex and the dorsal striatum during temporal learning, where the former commits to early learning stages while the latter engages as animals become proficient in the task.

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.

Medial prefrontal cortex lesions disrupt prepotent action selection signals in dorsomedial striatum

The ability to inhibit or adapt unwanted actions or movements is a critical feature of almost all forms of behavior. Many have attributed this ability to frontal brain areas such as the anterior cingulate cortex (ACC) and the medial prefrontal cortex (mPFC), but the exact contribution of each brain region is often debated because their functions are not examined in animals performing the same task. Recently, we have shown that ACC signals a need for cognitive control and is crucial for the adaptation of action selection signals in dorsomedial striatum (DMS) in rats performing a stop-change task. Here, we show that unlike ACC, the prelimbic region of mPFC does not disrupt the inhibition or adaption of an action plan at either the level of behavior or downstream firing in DMS. Instead, lesions to mPFC correlate with changes in DMS signals involved in action initiation and disrupt performance on GO trials while improving performance on STOP trials.

Ramping activity in the striatum

Control of the timing of behavior is thought to require the basal ganglia (BG) and BG pathologies impair performance in timing tasks. Temporal interval discrimination depends on the ramping activity of medium spiny neurons (MSN) in the main BG input structure, the striatum, but the underlying mechanisms driving this activity are unclear. Here, we combine an MSN dynamical network model with an action selection system applied to an interval discrimination task. We find that when network parameters are appropriate for the striatum so that slowly fluctuating marginally stable dynamics are intrinsically generated, up and down ramping populations naturally emerge which enable significantly above chance task performance. We show that emergent population activity is in very good agreement with empirical studies and discuss how MSN network dysfunction in disease may alter temporal perception.

Oscillation/Coincidence-Detection Models of Reward-Related Timing in Corticostriatal Circuits

The major tenets of beat-frequency/coincidence-detection models of reward-related timing are reviewed in light of recent behavioral and neurobiological findings. This includes the emphasis on a core timing network embedded in the motor system that is comprised of a corticothalamic-basal ganglia circuit. Therein, a central hub provides timing pulses (i.e., predictive signals) to the entire brain, including a set of distributed satellite regions in the cerebellum, cortex, amygdala, and hippocampus that are selectively engaged in timing in a manner that is more dependent upon the specific sensory, behavioral, and contextual requirements of the task. Oscillation/coincidence-detection models also emphasize the importance of a tuned ‘perception’ learning and memory system whereby target durations are detected by striatal networks of medium spiny neurons (MSNs) through the coincidental activation of different neural populations, typically utilizing patterns of oscillatory input from the cortex and thalamus or derivations thereof (e.g., population coding) as a time base. The measure of success of beat-frequency/coincidence-detection accounts, such as the Striatal Beat-Frequency model of reward-related timing (SBF), is their ability to accommodate new experimental findings while maintaining their original framework, thereby making testable experimental predictions concerning diagnosis and treatment of issues related to a variety of dopamine-dependent basal ganglia disorders, including Huntington’s and Parkinson’s disease.

A VTA GABAergic computational model of dissociated reward prediction error computation in classical conditioning

Classical Conditioning is a fundamental learning mechanism where the Ventral Striatum is generally thought to be the source of inhibition to Ventral Tegmental Area (VTA) Dopamine neurons when a reward is expected. However, recent evidences point to a new candidate in VTA GABA encoding expectation for computing the reward prediction error in the VTA. In this system-level computational model, the VTA GABA signal is hypothesised to be a combination of magnitude and timing computed in the Peduncolopontine and Ventral Striatum respectively. This dissociation enables the model to explain recent results wherein Ventral Striatum lesions affected the temporal expectation of the reward but the magnitude of the reward was intact. This model also exhibits other features in classical conditioning namely, progressively decreasing firing for early rewards closer to the actual reward, twin peaks of VTA dopamine during training and cancellation of US dopamine after training.

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.

Dorsal striatum coding for the timely execution of action sequences

The automatic initiation of actions can be highly functional. But occasionally these actions cannot be withheld and are released at inappropriate times, impulsively. Striatal activity has been shown to participate in the timing of action sequence initiation and it has been linked to impulsivity. Using a self-initiated task, we trained adult male rats to withhold a rewarded action sequence until a waiting time interval has elapsed. By analyzing neuronal activity we show that the striatal response preceding the initiation of the learned sequence is strongly modulated by the time subjects wait before eliciting the sequence. Interestingly, the modulation is steeper in adolescent rats, which show a strong prevalence of impulsive responses compared to adults. We hypothesize this anticipatory striatal activity reflects the animals’ subjective reward expectation, based on the elapsed waiting time, while the steeper waiting modulation in adolescence reflects age-related differences in temporal discounting, internal urgency states, or explore–exploit balance.

Distributed coding of duration in rodent prefrontal cortex during time reproduction

As we interact with the external world, we judge magnitudes from sensory information. The estimation of magnitudes has been characterized in primates, yet it is largely unexplored in nonprimate species. Here, we use time interval reproduction to study rodent behavior and its neural correlates in the context of magnitude estimation. We show that gerbils display primate-like magnitude estimation characteristics in time reproduction. Most prominently their behavioral responses show a systematic overestimation of small stimuli and an underestimation of large stimuli, often referred to as regression effect. We investigated the underlying neural mechanisms by recording from medial prefrontal cortex and show that the majority of neurons respond either during the measurement or the reproduction of a time interval. Cells that are active during both phases display distinct response patterns. We categorize the neural responses into multiple types and demonstrate that only populations with mixed responses can encode the bias of the regression effect. These results help unveil the organizing neural principles of time reproduction and perhaps magnitude estimation in general.

Slowly evolving dopaminergic activity modulates the moment-to-moment probability of reward-related self-timed movements

Clues from human movement disorders have long suggested that the neurotransmitter dopamine plays a role in motor control, but how the endogenous dopaminergic system influences movement is unknown. Here we examined the relationship between dopaminergic signaling and the timing of reward-related movements in mice. Animals were trained to initiate licking after a self-timed interval following a start-timing cue; reward was delivered in response to movements initiated after a criterion time. The movement time was variable from trial-to-trial, as expected from previous studies. Surprisingly, dopaminergic signals ramped-up over seconds between the start-timing cue and the self-timed movement, with variable dynamics that predicted the movement/reward time on single trials. Steeply rising signals preceded early lick-initiation, whereas slowly rising signals preceded later initiation. Higher baseline signals also predicted earlier self-timed movements. Optogenetic activation of dopamine neurons during self-timing did not trigger immediate movements, but rather caused systematic early-shifting of movement initiation, whereas inhibition caused late-shifting, as if modulating the probability of movement. Consistent with this view, the dynamics of the endogenous dopaminergic signals quantitatively predicted the moment-by-moment probability of movement initiation on single trials. We propose that ramping dopaminergic signals, likely encoding dynamic reward expectation, can modulate the decision of when to move.

Cortical alpha-synuclein preformed fibrils do not affect interval timing in mice

One hallmark feature of Parkinson's disease (PD) is Lewy body pathology associated with misfolded alpha-synuclein. Previous studies have shown that striatal injection of alpha-synuclein preformed fibrils (PFF) can induce misfolding and aggregation of native alpha-synuclein in a prion-like manner, leading to cell death and motor dysfunction in mouse models. Here, we tested whether alpha-synuclein PFFs injected into the medial prefrontal cortex results in deficits in interval timing, a cognitive task which is disrupted in human PD patients and in rodent models of PD. We injected PFF or monomers of human alpha-synuclein into the medial prefrontal cortex of mice pre-injected with adeno-associated virus (AAV) coding for overexpression of human alpha-synuclein or control protein. Despite notable medial prefrontal cortical synucleinopathy, we did not observe consistent deficits in fixed-interval timing. These results suggest that cortical alpha-synuclein does not reliably disrupt fixed-interval timing.

Dorsomedial Striatal Activity Tracks Completion of Behavioral Sequences in Rats

For proper execution of goal-directed behaviors, individuals require both a general representation of the goal and an ability to monitor their own progress toward that goal. Here, we examine how dorsomedial striatum (DMS), a region pivotal for forming associations among stimuli, actions, and outcomes, encodes the execution of goal-directed action sequences that require self-monitoring of behavior. We trained rats to complete a sequence of at least five consecutive lever presses (without visiting the reward port) to obtain a reward and recorded the activity of individual cells in DMS while rats performed the task. We found that the pattern of DMS activity gradually changed during the execution of the sequence, permitting accurate decoding of sequence progress from neural activity at a population level. Moreover, this sequence-related activity was blunted on trials where rats did not complete a sufficient number of presses. Overall, these data suggest a link between DMS activity and the execution of behavioral sequences that require monitoring of ongoing behavior.

Interval timing and midfrontal delta oscillations are impaired in Parkinson's disease patients with freezing of gait

Gait abnormalities and cognitive dysfunction are common in patients with Parkinson's disease (PD) and get worse with disease progression. Recent evidence has suggested a strong relationship between gait abnormalities and cognitive dysfunction in PD patients and impaired cognitive control could be one of the causes for abnormal gait patterns. However, the pathophysiological mechanisms of cognitive dysfunction in PD patients with gait problems are unclear. Here, we collected scalp electroencephalography (EEG) signals during a 7-s interval timing task to investigate the cortical mechanisms of cognitive dysfunction in PD patients with (PDFOG +, n = 34) and without (PDFOG-, n = 37) freezing of gait, as well as control subjects (n = 37). Results showed that the PDFOG +  group exhibited the lowest maximum response density at around 7 s compared to PDFOG- and control groups, and this response density peak correlated with gait abnormalities as measured by FOG scores. EEG data demonstrated that PDFOG +  had decreased midfrontal delta-band power at the onset of the target cue, which was also correlated with maximum response density and FOG scores. In addition, our classifier performed better at discriminating PDFOG + from PDFOG- and controls with an area under the curve of 0.93 when midfrontal delta power was chosen as a feature. These findings suggest that abnormal midfrontal activity in PDFOG + is related to cognitive dysfunction and describe the mechanistic relationship between cognitive and gait functions in PDFOG + . Overall, these results could advance the development of novel biosignatures and brain stimulation approaches for PDFOG + .

A precise and adaptive neural mechanism for predictive temporal processing in the frontal cortex

The theory of predictive processing posits that the brain computes expectations to process information predictively. Empirical evidence in support of this theory, however, is scarce and largely limited to sensory areas. Here, we report a precise and adaptive mechanism in the frontal cortex of non-human primates consistent with predictive processing of temporal events. We found that the speed of neural dynamics is precisely adjusted according to the average time of an expected stimulus. This speed adjustment, in turn, enables neurons to encode stimuli in terms of deviations from expectation. This lawful relationship was evident across multiple experiments and held true during learning: when temporal statistics underwent covert changes, neural responses underwent predictable changes that reflected the new mean. Together, these results highlight a precise mathematical relationship between temporal statistics in the environment and neural activity in the frontal cortex that may serve as a mechanism for predictive temporal processing.

Experience-related enhancements in striatal temporal encoding

Temporal control of action is key for a broad range of behaviors and is disrupted in human diseases such as Parkinson's disease and schizophrenia. A brain structure that is critical for temporal control is the dorsal striatum. Experience and learning can influence dorsal striatal neuronal activity, but it is unknown how these neurons change with experience in contexts which require precise temporal control of movement. We investigated this question by recording from medium spiny neurons (MSNs) via dorsal striatal microelectrode arrays in mice as they gained experience controlling their actions in time. We leveraged an interval timing task optimized for mice which required them to "switch" response ports after enough time had passed without receiving a reward. We report three main results. First, we found that time-related ramping activity and response-related activity increased with task experience. Second, temporal decoding by MSN ensembles improved with experience and was predominantly driven by time-related ramping activity. Finally, we found that a subset of MSNs had differential modulation on error trials. These findings enhance our understanding of dorsal striatal temporal processing by demonstrating how MSN ensembles can evolve with experience. Our results can be linked to temporal habituation and illuminate striatal flexibility during interval timing, which may be relevant for human disease.

Concomitant Processing of Choice and Outcome in Frontal Corticostriatal Ensembles Correlates with Performance of Rats

The frontal cortex-basal ganglia network plays a pivotal role in adaptive goal-directed behaviors. Medial frontal cortex (MFC) encodes information about choices and outcomes into sequential activation of neural population, or neural trajectory. While MFC projects to the dorsal striatum (DS), whether DS also displays temporally coordinated activity remains unknown. We studied this question by simultaneously recording neural ensembles in the MFC and DS of rodents performing an outcome-based alternative choice task. We found that the two regions exhibited highly parallel evolution of neural trajectories, transforming choice information into outcome-related information. When the two trajectories were highly correlated, spike synchrony was task-dependently modulated in some MFC-DS neuron pairs. Our results suggest that neural trajectories concomitantly process decision-relevant information in MFC and DS with increased spike synchrony between these regions.

Minute-encoding neurons in hippocampal-striatal circuits

Animals process temporal information in an ever-changing environment, but the neuronal mechanisms of this process, especially on timescales longer than seconds, remain unresolved. Here, we designed a hippocampus-dependent task in which rats prospectively increased their reward-seeking behavior over a duration of minutes. During this timing behavior, hippocampal and striatal neurons represented successive time points on the order of minutes by gradually changing their firing rates and transiently increasing their firing rates at specific time points. These minute-encoding patterns progressively developed as the rats learned a time-reward relationship, and the patterns underwent flexible scaling in parallel with timing behavior. These observations suggest a neuronal basis in the hippocampal-striatal circuits that enables temporal processing and formation of episodic memory on a timescale of minutes.

Activation of VTA GABA neurons disrupts reward seeking by altering temporal processing

The role of ventral tegmental area (VTA) dopamine in reward, cue processing, and interval timing is well characterized. Using a combinatorial viral approach to target activating DREADDs (Designer Receptors Exclusively Activated by Designer Drugs, hM3D) to GABAergic neurons in the VTA of male rats, we previously showed that activation disrupts responding to reward-predictive cues. Here we explored how VTA GABA neurons influence the perception of time in two fixed interval (FI) tasks, one where the reward or interval is not paired with predictive cues (Non-Cued FI), and another where the start of the FI is signaled by a constant tone that continues until the rewarded response is emitted (Cued FI). Under vehicle conditions in both tasks, responding was characterized by "scalloping" over the 30 s FI, in which responding increased towards the end of the FI. However, when VTA GABA neurons were activated in the Non-Cued FI, the time between the end of the 30 s interval and when the rats made a reinforced response increased. Additionally, post-reinforcement pauses and overall session length increased. In the Cued FI task, VTA GABA activation produced erratic responding, with a decrease in earned rewards. Thus, while both tasks were disrupted by VTA GABA activation, responding that is constrained by a cue was more sensitive to this manipulation, possibly due to convergent effects on timing and cue processing. Together these results demonstrate that VTA GABA activity disrupts the perception of interval timing, particularly when the timing is set by cues.

The orbitofrontal cortex in temporal cognition

One of the most important factors in decision-making is estimating the value of available options. Subregions of the prefrontal cortex, including the orbitofrontal cortex (OFC), have been deemed essential for this process. Value computations require a complex integration across numerous dimensions, including, reward magnitude, effort, internal state, and time. The importance of the temporal dimension is well illustrated by temporal discounting tasks, in which subjects select between smaller-sooner versus larger-later rewards. The specific role of OFC in telling time and integrating temporal information into decision-making remains unclear. Based on the current literature, in this review we reevaluate current theories of OFC function, accounting for the influence of time. Incorporating temporal information into value estimation and decision-making requires distinct, yet interrelated, forms of temporal information including the ability to tell time, represent time, create temporal expectations, and the ability to use this information for optimal decision-making in a wide range of tasks, including temporal discounting and wagering. We use the term "temporal cognition" to refer to the integrated use of these different aspects of temporal information. We suggest that the OFC may be a critical site for the integration of reward magnitude and delay, and thus important for temporal cognition. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Bi-directional regulation of cognitive control by distinct prefrontal cortical output neurons to thalamus and striatum

The medial prefrontal cortex (mPFC) steers goal-directed actions and withholds inappropriate behavior. Dorsal and ventral mPFC (dmPFC/vmPFC) circuits have distinct roles in cognitive control, but underlying mechanisms are poorly understood. Here we use neuroanatomical tracing techniques, in vitro electrophysiology, chemogenetics and fiber photometry in rats engaged in a 5-choice serial reaction time task to characterize dmPFC and vmPFC outputs to distinct thalamic and striatal subdomains. We identify four spatially segregated projection neuron populations in the mPFC. Using fiber photometry we show that these projections distinctly encode behavior. Postsynaptic striatal and thalamic neurons differentially process synaptic inputs from dmPFC and vmPFC, highlighting mechanisms that potentially amplify distinct pathways underlying cognitive control of behavior. Chemogenetic silencing of dmPFC and vmPFC projections to lateral and medial mediodorsal thalamus subregions oppositely regulate cognitive control. In addition, dmPFC neurons projecting to striatum and thalamus divergently regulate cognitive control. Collectively, we show that mPFC output pathways targeting anatomically and functionally distinct striatal and thalamic subregions encode bi-directional command of cognitive control.

Formalin-induced pain prolongs sub- to supra-second time estimation in rats

Background

Temporal estimation can be influenced by pain, which is a complex psychological and physiological phenomenon. However, the time range in which perception is most sensitive to pain remains unclear.

Methods

In the present study, we explored the effects of acute inflammatory pain on time perception in the sub- to supra-second (0.6–2.4-s) and supra-second (2–8-s) ranges in rats. Plantar formalin injection was used to induce acute inflammatory pain, and a temporal bisection task was used to measure time perception. Task test sessions were held for five consecutive days (one per day): the day before injection (baseline), immediately after injection, and the three post-injection days. The point of subjective equality (PSE, which reflects the subjective duration) and Weber fraction (which reflects temporal sensitivity) were calculated and analysed.

Results

In the 0.6–2.4-s range, the PSE was significantly lower, indicating prolonged subjective duration, in the formalin group relative to the saline group (p = 0.049) immediately after injection. Formalin-induced pain also tended to lengthened time perception in the 0.6–2.4-s range on post-injection days 2 (p = 0.06) and 3 (p = 0.054). In the 2–8-s range, formalin injection did not affect the PSE or Weber fraction.

Conclusions

The enhanced effect of pain on temporal perception in the sub- to supra-second range is observed in this study and this effect is attenuated with the prolongation of estimated time, even in rats.

Premotor Ramping of Thalamic Neuronal Activity Is Modulated by Nigral Inputs and Contributes to Control the Timing of Action Release

The ventromedial (VM)/ventro-anterior-lateral (VAL) motor thalamus is a key junction within the brain circuits sustaining normal and pathologic motor control functions and decision-making. In this area of thalamus, on one hand, the inhibitory nigro-thalamic pathway provides a main output from the basal ganglia, and, on the other hand, motor thalamo-cortical loops are involved in the maintenance of ramping preparatory activity before goal-directed movements. To better understand the nigral impact on thalamic activity, we recorded electrophysiological responses from VM/VAL neurons while male and female mice were performing a delayed right/left decision licking task. Analysis of correct (corr) and error trials revealed that thalamic ramping activity was stronger for premature licks (impulsive action) and weaker for trials with no licks [omission (omi)] compared with correct trials. Suppressing ramping activity through optogenetic activation of nigral terminals in the motor thalamus during the delay epoch of the task led to a reduced probability of impulsive action and an increased amount of omissions trials. We propose a parsimonious model explaining our data and conclude that a thalamic ramping mechanism contributes to the control of proper timing of action release and that inhibitory nigral inputs are sufficient to interrupt this mechanism and modulate the amount of motor impulsivity in this task.SIGNIFICANCE STATEMENT Coordinated neural activity in motor circuits is essential for correct movement preparation and execution, and even slight imbalances in neural processing can lead to failure in behavioral tasks or motor disorders. Here we focused on how failure to regulate the control of activity balance in the motor thalamus can be implicated in impulsive action release or omissions to act, through an activity ramping mechanism that is required for proper action release. Using optogenetic activation of inhibitory basal ganglia terminals in motor thalamus we show that basal ganglia input is well positioned to control this ramping activity and determine the timing of action initiation.

Striatal activity topographically reflects cortical activity

The cortex projects to the dorsal striatum topographically^1,2 to regulate behaviour^3-5, but spiking activity in the two structures has previously been reported to have markedly different relations to sensorimotor events^6-9. Here we show that the relationship between activity in the cortex and striatum is spatiotemporally precise, topographic, causal and invariant to behaviour. We simultaneously recorded activity across large regions of the cortex and across the width of the dorsal striatum in mice that performed a visually guided task. Striatal activity followed a mediolateral gradient in which behavioural correlates progressed from visual cue to response movement to reward licking. The summed activity in each part of the striatum closely and specifically mirrored activity in topographically associated cortical regions, regardless of task engagement. This relationship held for medium spiny neurons and fast-spiking interneurons, whereas the activity of tonically active neurons differed from cortical activity with stereotypical responses to sensory or reward events. Inactivation of the visual cortex abolished striatal responses to visual stimuli, supporting a causal role of cortical inputs in driving the striatum. Striatal visual responses were larger in trained mice than untrained mice, with no corresponding change in overall activity in the visual cortex. Striatal activity therefore reflects a consistent, causal and scalable topographical mapping of cortical activity.