The geometry of neural population activity during motor learning and memory

 The human brain is a marvel of complexity, with billions of neurons and trillions
of connections that allow us to perform an astounding array of behaviors, from basic
movements like walking and grasping to complex cognitive processes like decision-
making and language. However, despite decades of research, much about how the
brain learns and remembers remains a mystery.

One challenge in understanding the neural basis of learning and memory is that
seemingly simple acts, like taking a sip of water, are in fact immensely complex
processes that require an intricate coordination of neural activity. Yet humans are
able to learn and remember how to perform a vast array of new skills, suggesting
that the brain has the capacity to produce neural activity appropriate for a wide
variety of tasks.

To better understand how the brain learns and remembers new behaviors, it is
important to investigate the interplay between learning and memory. However, this
relationship is not well understood, and a better understanding of it could shed light
on how the brain is able to learn new tasks without forgetting familiar ones.

A difficulty in probing how the brain learns and remembers different tasks is that
the relationship between neural activity and behavior is very complex and difficult to
estimate. To circumvent this obstacle, we employ a brain-computer interface (BCI).
A BCI allows the experimenters to specify the causal relationship between neural
activity and behavior, which can provide insights into the underlying mechanisms of
learning and memory. This is in contrast to traditional arm-reaching experiments,
where the relationship between neural activity and behavior is largely unknown.

The focus of this thesis is to explore the geometry of neural population activity
during motor learning and memory. By leveraging the causal relationship between
neural activity and behavior, we aim to shed light on the complex processes that
underlie motor memories, and to provide insights into how the brain is able to learn
and retain new behaviors. The pinnacle result of this thesis is that learning alters
neural activity to simultaneously support both memory and action - i.e. learning
leaves a “memory trace” in neural population activity.