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SUMMARY:Adaptive feedback control as a mechanism for sequence learning - P
 rofessor Seng Bum Michael Yoo (Sungkyunkwan University\, South Korea)
DTSTART;VALUE=DATE-TIME:20251003T140000
DTEND;VALUE=DATE-TIME:20251003T150000
UID:https://talks.ox.ac.uk/talks/id/7ff5ae87-4a23-4ba9-8185-85b8b4b2671f/
DESCRIPTION:Humans and other animals can rapidly learn sequences of events
  and subsequently retrieve them with minimal repetition. By recording neur
 onal activity from four brain areas in human epilepsy patients performing 
 a sequence learning task\, we investigated how neuronal populations suppor
 t this process. We examined two candidate sequencing algorithms\, inspired
  by computer science: indexing and queuing. During learning\, population a
 ctivity occupied subspaces consistent with queuing and credit assignment. 
 Once the sequence was fully learned\, however\, the overall neural geometr
 y reorganized: the queue subspace became nonlinear\, the enqueue subspace 
 diminished\, and the representation shifted toward an indexing-like format
 . Using network modeling\, we further explored the governing principles un
 derlying this transition\, demonstrating that adaptive feedback control pr
 ovides a plausible mechanism for the modulation of neural geometry during 
 learning. Finally\, we found that\, upon successful learning\, the hippoca
 mpus broadcasts sequence information to other regions through a low-dimens
 ional subspace. Together\, these findings suggest that sequence learning c
 an be understood in terms of algorithmic neural subspaces and their dynami
 c reorganization across the course of learning.\nSpeakers:\nProfessor Seng
  Bum Michael Yoo (Sungkyunkwan University\, South Korea)
LOCATION:Seminar Room 7/8 (Lower ground floor) Life and Mind Building Sout
 h Parks Road\, OX1 3EL https://lifeandmind.web.ox.ac.uk/ 
TZID:Europe/London
URL:https://talks.ox.ac.uk/talks/id/7ff5ae87-4a23-4ba9-8185-85b8b4b2671f/
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DESCRIPTION:Talk:Adaptive feedback control as a mechanism for sequence lea
 rning - Professor Seng Bum Michael Yoo (Sungkyunkwan University\, South Ko
 rea)
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SUMMARY:Programmable Attractors in the Mouse Frontal Cortex: a Natural Alg
 orithm for Encoding New Sequences - Mohamady El-Gaby (University of Oxford
 )
DTSTART;VALUE=DATE-TIME:20230131T130000Z
DTEND;VALUE=DATE-TIME:20230131T140000Z
UID:https://talks.ox.ac.uk/talks/id/0d209c1a-393e-4e22-b8f6-ccf9d5270f58/
DESCRIPTION:A plethora of studies in humans\, non-human primates and roden
 ts implicate the medial frontal cortex (mFC) in executing sequences of act
 ions\, encoding transitions between goals and representing abstract task s
 tates. Our empirical findings directly reveal a single algorithm\, down to
  the cellular level\, that unifies these disparate mFC functions. We desig
 ned a new behavioural paradigm for mice\, the ABCD task\, which allows sim
 ultaneously investigating action sequences (one-step transitions in a spat
 ial maze)\, goal sequences (transitions between rewarded locations) and ab
 stract task structure (...ABCDABCD…).\n\nNeuronal firing in mFC was prim
 arily determined by the phase of the animal’s progress between any two g
 oals. Intriguingly\, we discovered a new class of neurons that build upon 
 this basic phase scaffold to represent the animal’s latent position in t
 ask space. Individual mFC neurons tracked position in task space relative 
 to a specific spatial goal or subgoal. At the population level\, these neu
 rons were organised into modules of programmable CANs: new tasks were mapp
 ed by activating a subset of pre-formed CANs in a task-specific order. Suc
 h CANs were internally organised\, maintaining their sequential relationsh
 ips during sleep\, in analogy to ring and toroidal attractors in the head 
 direction and grid cell system respectively. Moreover\, the activity bumps
  along these CANs predicted the animals’ subsequent behavioural choices 
 in a manner that revealed the underlying algorithm. The movement of an act
 ivity bump along some CANs tracked task progress relative to a given goal 
 location\, allowing zero-shot inference on new tasks without needing new p
 lasticity. Other CANs tracked progress relative to an intermediate action.
  These collectively allowed mice to rapidly converge on long action sequen
 ces without the need for continual planning. Programmable frontal CANs the
 refore provide a biological algorithm for optimally encoding new sequences
 .\nSpeakers:\nMohamady El-Gaby (University of Oxford)
LOCATION:New Radcliffe House (2nd Floor Seminar Room)\, Walton Street OX2 
 6NW
TZID:Europe/London
URL:https://talks.ox.ac.uk/talks/id/0d209c1a-393e-4e22-b8f6-ccf9d5270f58/
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ACTION:display
DESCRIPTION:Talk:Programmable Attractors in the Mouse Frontal Cortex: a Na
 tural Algorithm for Encoding New Sequences - Mohamady El-Gaby (University 
 of Oxford)
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