Biology subjects

Sendhilnathan, N.

Publications and source records attributed to Sendhilnathan, N..

12 recordsLinked to original sources

bioRxiv2024

Purkinje cells in Crus I and II encode the visual stimulus and the impending choice as monkeys learn a reinforcement based visuomotor association task

Visuomotor association involves linking an arbitrary visual cue to a well-learned movement. Transient inactivation of Crus I/II impairs primates ability to learn new associations and delays motor responses without affecting the kinematics of the movement. The simple spikes of Purkinje cells in the Crus regions signal cognitive errors as monkeys learn to associate specific fractal stimuli with movements of the left or right hand. Here we show that as learning progresses, the simple spike activity of individual neurons becomes more selective for stimulus-response associations, with selectivity developing closer to the appearance of visual stimuli. Initially, most neurons respond to both associations, irrespective of the identity of the stimulus and the associated movement, but as learning advances, more neurons distinguish between specific stimulus-hand associations. Using a linear decoder, it was found that in early learning stages, the visual stimulus can be decoded only when the choice can also be decoded. As learning improves, the visual stimulus is decoded earlier than the choice. A simple model can replicate the observed simple spike signals and the monkeys behavior in both the early and late learning stages.

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bioRxiv2023

Motor "laziness" constrains fixation selection in real-world tasks

AO_SCPLOWBSTRACTC_SCPLOWPeople coordinate their eye, head, and body movements to gather information from a dynamic environment while maximizing reward and minimizing biomechanical and energetic costs. Such natural behavior is not possible in a laboratory setting where the head and body are usually restrained and the tasks and stimuli used often lack ecological validity. Therefore, its unclear to what extent principles of fixation selection derived from lab studies, such as inhibition-of-return (IOR), apply in a real-world setting. To address this gap, participants performed nine real-world tasks, including driving, grocery shopping, and building a lego set, while wearing a mobile eye tracker (169 recordings; 26.6 hours). Surprisingly, spatial and temporal IOR were absent in all tasks. Instead, participants most often returned to what they just viewed, and saccade latencies were shorter preceding return than forward saccades. We hypothesized that participants minimize the time their eyes spend in an eccentric position to conserve eye and head motor effort. Correspondingly, we observed center biases in the distributions of fixation location and duration, relative to the heads orientation. A model that generates scanpaths by randomly sampling these distributions reproduced the spatial and temporal return phenomena seen in the data, including distinct 3-fixation sequences for forward versus return saccades. The amount of the orbit used in each task traded off with fixation duration, as if both incur costs in the same space. Conservation of effort ("laziness") explains all these behaviors, demonstrating that motor costs shape how people extract and act on relevant visual information from the environment. Significance StatementHumans display remarkably precise yet flexible control of eye and body movements, allowing for a wide range of activities. However, most studies of gaze behavior use the same setup: a head-restrained participant views small images on a computer. Such lab studies find that people avoid looking at the same thing twice, and hesitate in cases when they do. We had people perform nine everyday activities while wearing glasses with embedded eye tracking, and surprisingly found that they did the opposite, often returning to what they just viewed and expediting these "return" eye movements over others. A tendency to keep the eyes centered in the head, which we speculate helps to conserve motor effort, explained these behaviors for all tasks.

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bioRxiv2021

Neck motor unit activity displays neural signatures of temporal control during sequential saccade planning

Goal-directed behavior involves the transformation of neural movement plans into appropriate muscle activity patterns. Studies involving single saccades have shown that a rapid, direct pathway links saccade planning in frontal eye fields (FEF) to neck muscle activity. It is unknown if the rapid connection between FEF and neck muscle is maintained during sequential saccade planning. We show that sequence planning signals in the FEF are preserved in the neck EMG, although the activity is delayed specifically for the second saccade. Our results suggest that while the direct link between FEF and neck muscle facilitates downstream continuation of FEF response patterns, an indirect route exists through an inhibitory control center like the basal ganglia, limiting the information flow during processing of saccade sequences. Thus, the indirect and direct pathways from the FEF may function together to enable rapid synchronous, but controlled eye-head responses to sequential gaze shifts.

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bioRxiv2021

Mixed selectivity in the cerebellar Purkinje-cell response during visuomotor association learning

Although the cerebellum has been traditionally considered to be exclusively involved in motor control, recent anatomical and clinical studies show that it also has a role in reward-processing. However, the way in which the movement related and the reward related neural activity interact at the level of the cerebellar cortex and contribute towards learning is still unclear. Here, we studied the simple spike activity of Purkinje cells in the mid-lateral cerebellum when monkeys learned to associate a right or left-hand movement with one of two visual symbolic cues. These cells had distinctly different discharge patterns between an overtrained symbol-hand association and a novel symbol-hand association, responding in association with the movement of both hands, although the kinematics of the movement did not change between the two conditions. The activity change was not related to the pattern of the visual symbols, the movement kinematics, the monkeys reaction times or the novelty of the visual symbols. The simple spike activity changed with throughout the learning process, but the concurrent complex spikes did not instruct that change. Although these neurons also have reward-related activity, the reward-related and movement-related signals were independent. We suggest that this mixed-selectivity may facilitate the flexible learning of difficult reinforcement learning problems.

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bioRxiv2021

Preparatory activity links frontal eye field activity with small amplitude motor unit recruitment of neck muscles during gaze planning

A hallmark of intelligent behavior is that we can separate intention from action. To understand the mechanism that gates the flow of information between motor planning and execution, we compared the activity of frontal eye field neurons with motor unit activity from neck muscles in the presence of an intervening delay period in which spatial information regarding the target was available to plan a response. Whereas we could infer spatially-specific delayed period activity from the activity of frontal eye field neurons, neck motor unit activity during the delay period could not be used to infer the direction of an upcoming movement, Nonetheless, motor unit activity was correlated with the time it took to initiate saccades. Interestingly, we observed a heterogeneity of responses amongst motor units, such that only units with smaller amplitudes showed a clear modulation during the delay period. These small amplitude motor units also had higher spontaneous activity compared to the units which showed modulation only during the movement epoch. Taken together, our results suggest that the temporal information is visible in the periphery amongst smaller motor units during eye movement planning and explains how the delay period primes muscle activity leading to faster reaction times. Significance statementThis study shows that the temporal aspects of a motor plan in the oculomotor circuitry can be accessed by peripheral neck muscles hundreds of milliseconds prior to the instruction to initiate a saccadic eye movement. The coupling between central and peripheral processes during the delay time is mediated by the recruitment pattern of motor units with smaller amplitude in the periphery. Besides giving insight into how information processed in cortical areas is read out by the muscles, these findings could be useful to decode intentional signals from the periphery to control brain machine interface devices.

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bioRxiv2020

Capacity sharing between concurrent movement plans in the frontal eye field during the planning of sequential saccades

Sequences of saccadic eye movements are instrumental in navigating our visual environment. While neural activity has been shown to ramp up to a threshold before single saccades, the neural underpinnings of multiple saccades is unknown. To understand the neural control of rapid saccade sequences, we recorded from the frontal eye field (FEF) of macaque monkeys while they performed a sequential saccade task. We show that concurrent planning of two saccade plans brings forth processing bottlenecks, specifically by decreasing the growth rate and increasing the threshold of saccade-related ramping activity. The rate disruption affected both saccade plans, and a computational model wherein activity related to the two saccade plans bilaterally and asymmetrically inhibited each other, predicted the behavioral and neural results observed experimentally. Borrowing from models in psychology, our results demonstrate a capacity-sharing mechanism of processing bottlenecks, wherein multiple saccade plans in a sequence, compete for the processing capacity by perturbation of the saccade-related ramping activity. Finally, we show that in contrast to movement related neurons, visual activity in FEF neurons is not affected by the presence of multiple saccade targets, indicating that for perceptually simple tasks, inhibition amongst movement-related neurons mainly instantiates capacity sharing. Taken together, we show how psychology-inspired models of capacity sharing can be mapped onto neural responses to understand the control of rapid saccade sequences.

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bioRxiv2020

The mid-lateral cerebellum is necessary for reinforcement learning

The cerebellum has long been considered crucial for supervised motor learning and its optimization1-3. However, new evidence has also implicated the cerebellum in reward based learning4-8, executive function9-12, and frontal-like clinical deficits13. We recently showed that the simple spikes of Purkinje cells (P-cells) in the mid-lateral cerebellar hemisphere (Crus I and II) encode a reinforcement error signal when monkeys learn to associate arbitrary symbols with hand movements4. However, it is unclear if the cerebellum is necessary for any process beyond motor learning. To investigate if the mid-lateral cerebellum is actually necessary for learning visuomotor associations, we reversibly inactivated the mid-lateral cerebellum of two primates with muscimol while they learned to associate arbitrary symbols with hand movements. Here we show that cerebellar inactivation impaired the monkeys ability to learn new associations, although it had no effect on the monkeys performance on a task with overtrained symbols. A computational model corroborates our results. Cerebellar inactivation increased the reaction time, but there were no deficits in any motor kinematics such as the hand movement, licking or eye movement. There was no loss of function when we inactivated a more anterior region of the cerebellum that is implicated in motor control. We suggest that the mid-lateral cerebellum, which provides a reinforcement learning error signal4, is necessary for visuomotor association learning. Our results have implications for the involvement of cerebellum in cognitive control, and add critical constraints to brain models of non-motor learning14,15.

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bioRxiv2019

Neural correlates of goal-directed and non-goal-directed movements

What are the neural correlates that distinguish goal-directed (G) from non-goal-directed movements (nG)? We investigated this question in the monkey frontal eye field, which is implicated in voluntary control of saccades. We found that only for G-saccades, the variability in spike rate across trials decreased, the regularity of spike timings within trials increased, the neural activity increased earlier from baseline and had a concurrent reduction of LFP beta band power.

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bioRxiv2019

Complex spikes encode reward expectation signals during visuomotor association learning

Climbing fiber input to Purkinje cells has been thought to instruct learning related changes in simple spikes and cause behavioral changes through an error-based learning mechanism. Although, this framework explains simple motor learning, it cannot be extended to learning higher-order skills. Recently the cerebellum has been implicated in a variety of cognitive tasks and reward-based learning. Here we show that when a monkey learns a new visuomotor association, complex spikes predict the time of the beginning of the trial in a learning independent manner as well as encode a learning contingent reward expectation signal after the stimulus onset and reward delivery. These complex spike signals are unrelated to and were unlikely to instruct the reward based signal found in the simple spikes. Our results provide a more general role of complex spikes in learning and higher-order processing while gathering evidence for their participation in reward based learning.

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bioRxiv2019

Decrease in within-trial variability contributes to a decrease in across-trial variability of neural firing in the primate cortex during neural computations

The conventional approach to understanding neural responses underlying complex computations is to study across-trial averages of repeatedly performed computations from single neurons. When a brain region performs complex computations, such as processing stimulus related information or motor planning, it has been repeatedly shown through measures such as the Fano factor (FF) that neural variability across trials in the network decreases. However, in reality, multiple neurons contribute to a common computation on a single trial, rather than a single neuron contributing to a computation on multiple trials. Therefore, on individual trials the concept of FF loses significance. In this study, we extended previous work using measures of variability that are confined to a single trial and found that neurons perform a common computation, they briefly fire with increased regularity in spike timings, with similar inter-spike interval durations. We propose that this decrease in within-trial variability in neural spiking contributes to a decrease in across-trial variability in neural firing rates during network level computations. We confirmed our hypothesis by testing it on the activity of frontal eye field neurons recorded as two monkeys performed a memory-guided saccade task, and also on simulated spike trains. Furthermore, this phenomenon also has important behavioral correlates: the reaction time of the animal was faster when the within-trial variability was lower. We show that a decrease in within-trial variability is linked to a decrease in across-trial variability in neural response and indicates stationarity of neural network variability across time.\n\nNew & NoteworthyDuring computations, neural variability across trials decreases. In reality, multiple neurons contribute to a common computation on a single trial, rather than a single neuron contributing to a computation on multiple trials. We found that when a network of neurons performs a common computation, they briefly fire with increased regularity in spike timings. We propose that this decrease in within-trial variability in neural spiking contributes to a decrease in the observed across-trial variability.

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bioRxiv2019

Mid-lateral Cerebellar Purkinje Cells Provide a Cognitive Error Signal When Monkeys Learn a New Visuomotor Association

How do we learn to establish associations between arbitrary visual cues (like a red light) and movements (like braking the car)? We investigated the neural correlates of visuomotor association learning in the monkey mid-lateral cerebellum. Here we show that, during learning but not when the associations were overlearned, individual Purkinje cells reported the outcome of the monkeys most recent decision, an error signal, which was independent of changes in hand movement or reaction time. At the population level, Purkinje cells collectively maintained a memory of the most recent decision throughout the entire trial period, updating it after every decision. This error signal decreased as the performance improved. Our results suggest a role of mid-lateral cerebellum in visuomotor associative learning and provide evidence that cerebellum could be a generalized learning system, essential in non-motor learning as well as motor learning.

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bioRxiv2018

Electrophysiological evidence for cerebellar involvement in higher-order cognitive processing

Although the cerebellum has been traditionally considered to be exclusively involved in motor control and learning, recent anatomical and clinical studies suggest that it may also have a role in cognition. However, no electrophysiological evidence exists to support this claim. Here we studied the activity of simple spikes of hand-movement related Purkinje cells in the mid-lateral cerebellum when monkeys learned to associate a well-learned right or left-hand movement with one of two visual symbolic cues. The cells had distinctly different discharge patterns between an overtrained symbol-hand association and a novel symbol-hand association although the kinematics of the movement did not change between the two conditions. The activity change was not related to the pattern of the visual symbols, the hand making the movement, the monkeys reaction times or the novelty of the visual symbols. We suggest that mid-lateral cerebellum is involved in higher-order cognitive processing related to learning a new visuomotor association.\n\nOne Sentence SummaryHand-movement related Purkinje neurons in midlateral cerebellum, which discharge during an overtrained visuomotor association task, change their activity when the monkey has to associate the same movements with new cues, even though the kinematics of the movements do not change.

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