TY  - GEN
AB  - The underlying mechanisms of computation in sensorimotor cortex must be both flexibleand robust to support the range of skilled, dynamic forelimb movements observed in natural
primate behavior. To understand the full richness of these mechanisms, it is important to
study motor behavior in the most natural context possible using analytical tools that account for relationships between movement and both single-unit and population activity. In
this work, I demonstrate that accurately capturing naturalistic motor behavior – specifically
dynamic forelimb movements during foraging and prey-capture – is both critical and feasible.
I leverage natural forelimb movements and pairwise precise spike time structure (represented
as a functional network) in marmoset sensorimotor cortex to develop a network encoding
model that links single-unit spiking activity with kinematic tuning properties and functional
network interactions. I use this model to investigate the computational mechanisms that
generate varied and naturalistic motor behavior. I show that a trajectory-based encoding
model predicts single-unit activity during naturalistic forelimb movements more accurately
than a simpler model. I demonstrate that tuning to kinematics depends on functional interactions between units – particularly on structured strong connections. Finally, I identify
a reach-specific functional group that reorganizes to produce dynamic forelimb movements
during prey capture. This reach-specific functional group is strongly interconnected and
comprises units tightly linked to kinematics with strong, positively correlated preferred trajectories. By examination of the reach-specific functional group and remaining non-specific
units, I suggest a potential framework linking single-unit properties to the neural population
dynamics that generate movement.
AD  - University of Chicago
AU  - Moore, Dalton D.
DA  - 2023-12
DO  - 10.6082/uchicago.10110
DO  - doi
ED  - Nicholas G. Hatsopoulos
ED  - Jason N. MacLean
ED  - Daniel Margoliash
ED  - Matthew T. Kaufman
ID  - 10110
KW  - Neurosciences
KW  - motor control
KW  - natural behavior
KW  - network science
KW  - neuroethology
KW  - pose estimation
L1  - https://knowledge.uchicago.edu/record/10110/files/Moore_uchicago_0330D_17215.pdf
L2  - https://knowledge.uchicago.edu/record/10110/files/Moore_uchicago_0330D_17215.pdf
L4  - https://knowledge.uchicago.edu/record/10110/files/Moore_uchicago_0330D_17215.pdf
LA  - en
LK  - https://knowledge.uchicago.edu/record/10110/files/Moore_uchicago_0330D_17215.pdf
N2  - The underlying mechanisms of computation in sensorimotor cortex must be both flexibleand robust to support the range of skilled, dynamic forelimb movements observed in natural
primate behavior. To understand the full richness of these mechanisms, it is important to
study motor behavior in the most natural context possible using analytical tools that account for relationships between movement and both single-unit and population activity. In
this work, I demonstrate that accurately capturing naturalistic motor behavior – specifically
dynamic forelimb movements during foraging and prey-capture – is both critical and feasible.
I leverage natural forelimb movements and pairwise precise spike time structure (represented
as a functional network) in marmoset sensorimotor cortex to develop a network encoding
model that links single-unit spiking activity with kinematic tuning properties and functional
network interactions. I use this model to investigate the computational mechanisms that
generate varied and naturalistic motor behavior. I show that a trajectory-based encoding
model predicts single-unit activity during naturalistic forelimb movements more accurately
than a simpler model. I demonstrate that tuning to kinematics depends on functional interactions between units – particularly on structured strong connections. Finally, I identify
a reach-specific functional group that reorganizes to produce dynamic forelimb movements
during prey capture. This reach-specific functional group is strongly interconnected and
comprises units tightly linked to kinematics with strong, positively correlated preferred trajectories. By examination of the reach-specific functional group and remaining non-specific
units, I suggest a potential framework linking single-unit properties to the neural population
dynamics that generate movement.
PB  - The University of Chicago
PY  - 2023-12
T1  - A Network Encoding Model for Natural Forelimb Movements in Marmoset Sensorimotor Cortex
TI  - A Network Encoding Model for Natural Forelimb Movements in Marmoset Sensorimotor Cortex
UR  - https://knowledge.uchicago.edu/record/10110/files/Moore_uchicago_0330D_17215.pdf
Y1  - 2023-12
ER  -