Biology subjects

MacDowell, C. J.

Publications and source records attributed to MacDowell, C. J..

4 recordsLinked to original sources

bioRxiv2023

Multiplexed Subspaces Route Neural Activity Across Brain-wide Networks

Cognition is flexible. Behaviors can change on a moment-by-moment basis. Such flexibility is thought to rely on the brains ability to route information through different networks of brain regions in order to support different cognitive computations. However, the mechanisms that determine which network of brain regions is engaged are unknown. To address this, we combined cortex-wide calcium imaging with high-density electrophysiological recordings in eight cortical and subcortical regions of mice. Different dimensions within the population activity of each brain region were functionally connected with different cortex-wide subspace networks of regions. These subspace networks were multiplexed, allowing a brain region to simultaneously interact with multiple independent, yet overlapping, networks. Alignment of neural activity within a region to a specific subspace network dimension predicted how neural activity propagated between regions. Thus, changing the geometry of the neural representation within a brain region could be a mechanism to selectively engage different brain-wide networks to support cognitive flexibility.

neuroscience↗

bioRxiv2022

Variability in sampling of cortex-wide neural dynamics explains individual differences in functional connectivity and behavioral phenotype

Individual differences in behavior are associated with changes in the correlation of neural activity between brain areas. Such differences in functional connectivity are thought to reflect individual differences in brain structure that alter the flow of neural activity between regions. Here, in contrast, we show that individual differences in functional connectivity and behavior can be explained by differences in how frequently an individual expresses distinct cortex-wide spatiotemporal patterns of neural activity. This suggests variability in sampling of cortex-wide neural dynamics may underlie individuals unique behavioral phenotypes.

neuroscience↗

bioRxiv2020

Learning to Control the Brain through Adaptive Closed-Loop Patterned Stimulation

Stimulation of neural activity is an important scientific and clinical tool, causally testing hypotheses and treating neurodegenerative and neuropsychiatric diseases. However, current stimulation approaches cannot flexibly control the pattern of activity in populations of neurons. To address this, we developed an adaptive, closed-loop stimulation (ACLS) system that uses patterned, multi-site electrical stimulation to control the pattern of activity in a population of neurons. Importantly, ACLS is a learning system; it monitors the response to stimulation and iteratively updates the stimulation pattern to produce a specific neural response. In silico and in vivo experiments showed ACLS quickly learns to produce specific patterns of neural activity ([~]15 minutes) and was robust to noise and drift in neural responses. In visual cortex of awake mice, ACLS learned electrical stimulation patterns that produced responses similar to the natural response evoked by visual stimuli. Similar to how repetition of a visual stimulus causes an adaptation in the neural response, the response to electrical stimulation was adapted when it was preceded by the associated visual stimulus. Altogether, our results show ACLS can learn, in real-time, to generate specific patterns of neural activity, providing a framework for using closed-loop learning to control neural activity.

neuroscience↗

bioRxiv2020

Low-Dimensional Spatio-Temporal Dynamics Underlie Cortex Wide Neural Activity

Cognition arises from the dynamic flow of neural activity through the brain. To capture these dynamics, we used mesoscale calcium imaging to record neural activity across the dorsal cortex of awake mice. We found that the large majority of variance in cortex-wide activity ([~]75%) could be explained by a limited set of [~]14 motifs of neural activity. Each motif captured a unique spatio-temporal pattern of neural activity across the cortex. These motifs generalized across animals and were seen in multiple behavioral environments. Motif expression differed across behavioral states and specific motifs were engaged by sensory processing, suggesting the motifs reflect core cortical computations. Together, our results show that cortex-wide neural activity is highly dynamic, but that these dynamics are restricted to a low-dimensional set of motifs, potentially to allow for efficient control of behavior.

neuroscience↗