Neural representations of movement in primary motor cortex

Movement is arguably the single most important output of the nervous system, as it is the main way complex organisms interact with their environment. The learning and execution of both simple locomotion and of intricate volitional movements requires an elaborate orchestration from the motor system, which is comprised of several distinct brain regions. Deficits in the capacities of these regions lead to a loss of different modalities of motor control, and ultimately underlie motor disorders.
The primary motor cortex (M1) is of particular importance to motor control, as its layer 5B pyramidal tract (PT) cells project directly to the spinal cord to generate motion. M1 is hence thought to evoke signals for the planning and execution of movement. It is also believed to be required for the learning of skilled behaviours. However, the exact breadth of control it exerts, as well as how exactly it generates behaviourally relevant commands, remains unresolved.
M1 receives input from two main sources: the thalamus, which relays information from other subcortical centres, and from other cortical areas, including somatosensory and prefrontal areas. The latter mainly refers to the secondary motor cortex (M2), a broad area associated with movement preparation and action selection in goal-directed behaviour. Recent findings in the Duguid lab have pinpointed a discrete anatomical subzone of M2, the anterior lateral forelimb area (ALFA), that projects directly to the forelimb area of M1. Using pharmacology and optogenetics, ALFA has been shown to be necessary for the execution of movement in a skilled motor discrimination task.

Therefore, this project will focus on determining how movement command patterns are represented in the activity of ALFA and M1. Specific aspects of motor behaviour will be decoded from the computations of neurons between and within these regions.
To address this, we will employ state of the art Neuropixel probes, patch-clamp electrophysiology, viral-based manipulation strategies (such as optogenetics), mesoscale calcium imaging, 3D kinematic analysis of movement, and Bayesian decoders of population data on mice performing a learned motor task.

The project has three 3 aims. Firstly, the connections between ALFA and M1 will be mapped using dyes and viral tracing techniques to characterise their precise anatomy.
Secondly, the organisation of population-level representations of movement in ALFA and M1 neurons will be determined. To do this, changes in extracellular population electrophysiology will be recorded in ALFA and M1 from mice performing a skilled behavioural task. Viral-based manipulation strategies will be used to investigate causality between the activity of corticocortical neurons and behaviour.
The final aim involves characterising the link between neuronal activity and forelimb kinematics, both recorded in previous experiments. Using the population electrophysiological data, Bayesian decoding algorithms will be developed to predict limb trajectories from neuronal population activity. By applying advanced Bayesian decoders of population data and computer vision algorithms, we will develop an in-depth understanding of how laminar and single-cell dynamics in ALFA and M1 are combined to generate accurate, skilled forelimb movements.

This project will provide me with practical skills in experimental design, population and single-cell electrophysiological techniques, mesoscale imaging, statistics and advanced computational methods for data analysis, with the overarching aim of characterising the cellular and circuit computations performed by motor cortex during behaviour.