Humans and animals can effortlessly coordinate their movements with external stimuli. This capacity indicates that sensory inputs can rapidly and flexibly reconfigure the ongoing dynamics in the neural circuits that control movements. Here, we develop a circuit-level model that coordinates movement times with expected and unexpected temporal events. The model consists of two interacting modules, a motor planning module that controls movement times and a sensory anticipation module that anticipates external events. Both modules harbor a reservoir of latent dynamics, and their interaction forms a control system whose output is adjusted adaptively to minimize timing errors. We show that the model's output matches human behavior in a range of tasks including time interval production, periodic production, synchronization/continuation, and Bayesian time interval reproduction. These results demonstrate how recurrent interactions in a simple and modular neural circuit could create the dynamics needed to control timing behavior.

Flexibly selecting appropriate actions in response to complex, ever-changing environments requires both cortical and subcortical regions, which are typically described as participating in a strict hierarchy. In this traditional view, highly specialized subcortical circuits allow for efficient responses to salient stimuli, at the cost of adaptability and context-specificity, which are attributed to the neocortex. Their interactions are often described as the cortex providing top-down command signals for subcortical structures to implement; however, as available technologies develop, studies increasingly demonstrate that behavior is represented by brain-wide activity and that even subcortical structures contain early signals of choice, suggesting that behavioral functions emerge as a result of different regions interacting as truly collaborative networks. In this review, we discuss the field's evolving understanding of how cortical and subcortical regions in placental mammals interact cooperatively- not only via top-down cortical-subcortical inputs, but through bottom-up interactions, especially via the thalamus. We describe our current understanding of the circuitry of both the cortex and two exemplar subcortical structures- the superior colliculus and striatum- to identify which information is prioritized by which regions. We then describe the functional circuits these regions form with one another- and the thalamus- to create parallel loops and complex networks for brain-wide information flow. Finally, we challenge the classic view that functional modules are contained within specific brain regions; instead, we propose that certain regions prioritize specific types of information over others, but the subnetworks they form- defined by their anatomical connections and functional dynamics- are the basis of true specialization.

The structure of brain regions is assumed to correlate with their function, but there are very few instances in which the relationship has been demonstrated in the live brain. This is due to the difficulty of simultaneously measuring functional and structural properties of brain areas, particularly at cellular resolution. Here, we performed label-free, third-harmonic generation (THG) microscopy to obtain a key structural signature of cortical areas, their effective attenuation lengths (EAL), in the vertical columns of functionally defined primary visual cortex and five adjacent visual areas in awake mice. EALs measured by THG microscopy in the cortex and white matter showed remarkable correspondence with the functional retinotopic sign map of each area. Structural features such as cytoarchitecture, myeloarchitecture and blood vessel architecture were correlated with areal EAL values, suggesting that EAL is a function of these structural features as an optical property of these areas. These results demonstrate for the first time a strong relationship between structural substrates of visual cortical areas and their functional representation maps in vivo. This study may also help in understanding the coupling between structure and function in other animal models as well as in humans.

Humans can rapidly and flexibly coordinate their movements with external stimuli. Theoretical considerations suggest that this flexibility can be understood in terms of how sensory responses reconfigure the neural circuits that control movements. However, because external stimuli can occur at unexpected times, it is unclear how the corresponding sensory inputs can be used to exert flexible control over the ongoing activity of recurrent neural circuits. Here, we tackle this problem in the domain of sensorimotor timing and develop a circuit-level model that provides insight into how the brain coordinates movement times with expected and unexpected temporal events. The model consists of two interacting modules, a motor planning module that controls movement times and a sensory anticipation module that anticipates external events. Both modules harbor a reservoir of latent dynamics and their interaction forms a control system whose output is adjusted adaptively to minimize timing errors. We show that the model's output matches human behavior in a range of tasks including time interval production, periodic production, synchronization/continuation, and Bayesian time interval reproduction. These results demonstrate how recurrent interactions in a simple and modular neural circuit could create the dynamics needed to control temporal aspects of behavior.can be viewed as a control signal that reconfigures the system's latent dynamics and allows the system to generate different outputs. However, recurrent neural network models are typically complex and do not offer the level of interpretability needed to engineer circuits that could use inputs for flexible sensorimotor coordination.Here, we tackle this question within the domain of time, asking how a simple and interpretable neural circuit could flexibly coordinate the timing of its output to external temporal events. Timing provides a prime example of sensorimotor coordination and is crucial in behaviors that demand the generation of delayed motor responses, generation of rhythmic movements with a desired tempo, and synchronization of movements to anticipated events. Early experiments found that when animals are asked to delay their motor responses, many neurons exhibit ramping activity during the delay period; i.e., activity that increases or decreases monotonically over time [21][22][23] . These experiments inspired a simple ramp-to-threshold model for action initiation. According to this model, actions are initiated reliably when the ramping activity reaches a fixed threshold 24,25 . When the threshold is fixed, flexible temporal control requires the system to adjust the rate of change, or speed, at which neural dynamics evolve. Indeed, it has been shown that neural circuits generate dynamics with a speed that has an inverse relationship to the instructed interval duration 9,20,26 .While the adjustment of speed is a common empirical observation, the mechanisms by which this is achieved is not fully understood. Recently, it was shown that flexible control of speed can be ...