Biology subjects

Gallego, J. A.

Publications and source records attributed to Gallego, J. A..

4 recordsLinked to original sources

bioRxiv2018

A stable, long-term cortical signature underlying consistent behavior

Animals readily execute learned motor behaviors in a consistent manner over long periods of time, yet similarly stable neural correlates remained elusive up to now. How does the cortex achieve this stable control? Using the sensorimotor system as a model of cortical processing, we investigated the hypothesis that the dynamics of neural latent activity, which capture the dominant co-variation patterns within the neural population, are preserved across time. We recorded from populations of neurons in premotor, primary motor, and somatosensory cortices for up to two years as monkeys performed a reaching task. Intriguingly, despite steady turnover in the recorded neurons, the low-dimensional latent dynamics remained stable. Such stability allowed reliable decoding of behavioral features for the entire timespan, while fixed decoders based on the recorded neural activity degraded substantially. We posit that latent cortical dynamics within the manifold are the fundamental and stable building blocks underlying consistent behavioral execution.

neuroscience↗

bioRxiv2018

Mechanical vibration does not systematically reduce the tremor in Essential Tremor patients

Essential tremor (ET) is a major cause of disability and is not effectively managed in half of the patients. We investigated whether mechanical vibration could reduce tremor in ET by selectively recruiting afferent pathways. We used piezoelectric actuators to deliver vibratory stimuli to the hand and forearm during long trials (4 min), while we monitored the tremor using inertial sensors. We analyzed the effect of four stimulation strategies, including different constant and variable vibration frequencies, in 18 ET patients. Although there was not a clear homogeneous response to vibration across patients and strategies, in most cases (50-72%) mechanical vibration was associated with an increase in the amplitude of their tremor. In contrast, the tremor was reduced in 5-22% of the patients, depending on the strategy. However, these results are hard to interpret given the intrinsic variability of the tremor: during equally long trials without vibration, the tremor changed significantly in 67% of the patients (increased in 45%; decreased in 22%). We conclude that mechanical vibration of the limb does not have a systematic effect on tremor in ET. Moreover, the observed intrinsic variability of the tremor should be taken into account when designing future experiments to assess tremor in ET and how it responds to any intervention.

bioengineering↗

bioRxiv2017

Multiple tasks viewed from the neural manifold: Stable control of varied behavior

How do populations of cortical neurons have the flexibility to perform different functions? We investigated this question in primary motor cortex (M1), where populations of neurons are able to generate a rich repertoire of motor behaviors. We recorded neural activity while monkeys performed a variety of wrist and reach-to-grasp motor tasks, each requiring a different pattern of neural activity. We characterized the flexibility of M1 movement control by comparing the \"neural modes\" that capture covariation across neurons, believed to arise from network connectivity. We found large similarities in the structure of the neural modes across tasks, as well as striking similarities in their temporal activation dynamics. These similarities were only apparent at the population level. Moreover, a subset of these well-preserved modes captured a task-independent mapping onto muscle commands. We hypothesize that this system of flexibly combined, stable neural modes gives M1 the flexibility to generate our wide-ranging behavioral repertoire.

neuroscience↗

bioRxiv2017

A Neural Population Mechanism For Rapid Learning

Long-term learning of language, mathematics, and motor skills likely requires plastic changes in the cortex, but behavior often requires faster changes, sometimes based even on single errors. Here, we show evidence of one mechanism by which the brain can rapidly develop new motor output, seemingly without altering the functional connectivity between or within cortical areas. We recorded simultaneously from hundreds of neurons in the premotor (PMd) and primary motor (M1) cortices, and computed models relating these neural populations throughout adaptation to reaching movement perturbations. We found a signature of learning in the \"null subspace\" of PMd with respect to M1. Earlier experiments have shown that null subspace activity allows the motor cortex to alter preparatory activity without directly influencing M1. In our experiments, the null subspace planning activity evolved with the adaptation, yet the \"potent\" mapping that captures information sent to M1 was preserved. Our results illustrate a population-level mechanism within the motor cortices to adjust the output from one brain area to its downstream structures that could be exploited throughout the brain for rapid, online behavioral adaptation.

neuroscience↗