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UID:20250315T214737EDT-0664NSFPDk@132.216.98.100
DTSTAMP:20250316T014737Z
DESCRIPTION:Brain-Wide Compositionality and Learning Dynamics in Biological
Agents\n\nKanaka Rajan\, Harvard University\n Tuesday January 21\, 12-1pm
\n Zoom Link:聽https://mcgill.zoom.us/j/89914150820\n In Person: 550 Sherbroo
ke\, Room 189\n \n Abstract:聽Biological agents continually reconcile the int
ernal states of their brain circuits with incoming sensory and environment
al evidence to evaluate when and how to act. The brains of biological agen
ts\, including animals and humans\, exploit many evolutionary innovations\
, chiefly modularity鈥攐bservable at the level of anatomically-defined brain
regions\, cortical layers\, and cell types among others鈥攖hat can be repur
posed in a compositional manner to endow the animal with a highly flexible
behavioral repertoire. Accordingly\, their behaviors show their own modul
arity\, yet such behavioral modules seldom correspond directly to traditio
nal notions of modularity in brains. It remains unclear how to link neural
and behavioral modularity in a compositional manner. We propose a compreh
ensive framework鈥攃ompositional modes鈥攖o identify overarching compositional
ity spanning specialized submodules\, such as brain regions. Our framework
directly links the behavioral repertoire with distributed patterns of pop
ulation activity\, brain-wide\, at multiple concurrent spatial and tempora
l scales.\n Using whole-brain recordings of zebrafish brains\, we introduce
an unsupervised pipeline based on neural network models\, constrained by
biological data\, to reveal highly conserved compositional modes across in
dividuals despite the naturalistic (spontaneous or task-independent) natur
e of their behaviors. These modes provided a scaffolding for other modes t
hat account for the idiosyncratic behavior of each fish. We then demonstra
te experimentally that compositional modes can be manipulated in a consist
ent manner by behavioral and pharmacological perturbations. Our results de
monstrate that even natural behavior in different individuals can be decom
posed and understood using a relatively small number of neurobehavioral mo
dules鈥攖he compositional modes鈥攁nd elucidate a compositional neural basis o
f behavior. This approach aligns with recent progress in understanding how
reasoning capabilities and internal representational structures develop o
ver the course of learning or training\, offering insights into the modula
rity and flexibility in artificial and biological agents.\n
DTSTART:20250121T170000Z
DTEND:20250121T180000Z
SUMMARY:QLS Seminar Series - Kanaka Rajan
URL:/channels/channels/event/qls-seminar-series-kanaka
-rajan-362481
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