Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Neuroscience

Supervisor

Diedrichsen, Jörn

2nd Supervisor

Pruszynski, Andrew

Co-Supervisor

Abstract

Using our hands to manipulate objects in our daily life requires both dexterous movements and the integration of somatosensory information across fingers. Although the primary motor (M1) and somatosensory cortices (S1) are critical for these two complementary roles, it is unclear how neural populations in these regions functionally represent these processes. This thesis examined the functional organization of brain representations (the representational geometry) in M1 and S1 for dexterous hand control and somatosensory processing. To that end, representational geometries were estimated from fine-grained brain activity patterns measured with functional MRI (fMRI). Since fMRI measures a blood-based proxy of neural activity, any non-linearities in the coupling between neural activity and the fMRI signal could distort the representational geometries. Chapter 2 therefore evaluated the stability of representational geometries. Human participants made individuated finger presses at varying pressing speeds, such that overall activity was modulated across a broad range. Representational geometries were relatively stable across pressing speeds in M1 and S1, validating the use of this analysis framework with fMRI data. Chapter 3 then explored how M1 is organized for dexterous hand control. In agreement with previous research, representations of each finger were quite distinct. However, representations of the same finger moving in different directions were very similar. Insight into this observation was gained by comparing the fMRI results to neural spiking data recorded in monkeys trained to perform an identical task. By leveraging the complementary perspectives offered by fMRI and spiking, a new organization of M1 for finger control was proposed. Chapter 4 then examined how somatosensory inputs from multiple fingers are integrated in S1. The full nature of this integration is unknown. Here, human participants experienced simulation of all possible single- and multi-finger combinations. Representational model analyses revealed that unique non-linear interactions between finger sensory inputs occur throughout S1, with stronger (and more spatially distant) interactions occurring in posterior S1. Altogether, these results provide new insight into how M1 and S1 are functionally organized to serve the motoric and sensory processes of the hand, and more broadly demonstrate how fMRI can be used to make inferences about the underlying functional organization of brain representations.

Summary for Lay Audience

Hand movements, like playing the piano or typing, are central in our everyday lives. These movements require fine control of individual fingers. Moreover, hand movements require that we also use sensory information from our fingers to better control object(s) in our hands. Although this sounds laborious, using our hands often feels effortless, suggesting that neurons in the brain are organized in such a way as to support these processes. In this thesis, I investigated how two brain regions, the primary motor cortex (M1) and primary somatosensory cortex (S1), are organized to control dexterous hand movements and integrate sensory information from the fingers. Understanding how M1 and S1 are organized for hand control is important because these regions are often damaged in brain diseases such as stroke. To study this, I used functional magnetic resonance imaging (fMRI) in healthy human participants. This technique non-invasively measures brain activity. However, fMRI does not measure neural activity directly. Therefore, there are several caveats that we must be aware of when using fMRI to draw conclusions about neural processes in the brain. Therefore, in my first project, I validated my analysis framework for fMRI data to ensure that some of the assumptions I make in my analyses are not violated. Having validated my analysis framework, I then investigated the relationships between patterns of brain activity (i.e., representations) in M1 that are evoked by movements of individual fingers in different directions. I found that the representations for different fingers were organized according to how we move our fingers in our daily lives. In other words, fingers that commonly move together are represented more similarly in M1. Furthermore, representations of the same finger moving in opposing directions were more similar than expected, given that such movements cannot co-occur in daily life. My findings suggest that groups of neurons that are involved in controlling opposing muscular patterns are closely linked in M1. In my last project, I used fMRI to study how sensory inputs from different fingers are integrated in S1. This integration process is important because it allows us to build information about an object in our hand (e.g., shape, size). To study how sensory inputs from the fingers are integrated, I stimulated all 31 possible single- and multi-finger combinations. I found that inputs from the fingers are integrated in unique ways depending on which fingers are stimulated, and that these inputs are entirely integrated in S1. Together, my work provides insight into how M1 and S1 are organized to enable dexterous hand control.

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