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Discrete attractor dynamics underlies persistent activity in the frontal cortex

Author

Listed:
  • Hidehiko K. Inagaki

    (Janelia Research Campus, HHMI)

  • Lorenzo Fontolan

    (Janelia Research Campus, HHMI)

  • Sandro Romani

    (Janelia Research Campus, HHMI)

  • Karel Svoboda

    (Janelia Research Campus, HHMI)

Abstract

Short-term memories link events separated in time, such as past sensation and future actions. Short-term memories are correlated with slow neural dynamics, including selective persistent activity, which can be maintained over seconds. In a delayed response task that requires short-term memory, neurons in the mouse anterior lateral motor cortex (ALM) show persistent activity that instructs future actions. To determine the principles that underlie this persistent activity, here we combined intracellular and extracellular electrophysiology with optogenetic perturbations and network modelling. We show that during the delay epoch, the activity of ALM neurons moved towards discrete end points that correspond to specific movement directions. These end points were robust to transient shifts in ALM activity caused by optogenetic perturbations. Perturbations occasionally switched the population dynamics to the other end point, followed by incorrect actions. Our results show that discrete attractor dynamics underlie short-term memory related to motor planning.

Suggested Citation

  • Hidehiko K. Inagaki & Lorenzo Fontolan & Sandro Romani & Karel Svoboda, 2019. "Discrete attractor dynamics underlies persistent activity in the frontal cortex," Nature, Nature, vol. 566(7743), pages 212-217, February.
    • Handle: RePEc:nat:nature:v:566:y:2019:i:7743:d:10.1038_s41586-019-0919-7
    DOI: 10.1038/s41586-019-0919-7
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    Cited by:

    1. Christopher M. Kim & Arseny Finkelstein & Carson C. Chow & Karel Svoboda & Ran Darshan, 2023. "Distributing task-related neural activity across a cortical network through task-independent connections," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    2. Guihua Xiao & Yeyi Cai & Yuanlong Zhang & Jingyu Xie & Lifan Wu & Hao Xie & Jiamin Wu & Qionghai Dai, 2024. "Mesoscale neuronal granular trial variability in vivo illustrated by nonlinear recurrent network in silico," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    3. Oren Amsalem & Hidehiko Inagaki & Jianing Yu & Karel Svoboda & Ran Darshan, 2024. "Sub-threshold neuronal activity and the dynamical regime of cerebral cortex," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    4. Vahid Rostami & Thomas Rost & Felix Johannes Schmitt & Sacha Jennifer Albada & Alexa Riehle & Martin Paul Nawrot, 2024. "Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    5. Alyse Thomas & Weiguo Yang & Catherine Wang & Sri Laasya Tipparaju & Guang Chen & Brennan Sullivan & Kylie Swiekatowski & Mahima Tatam & Charles Gerfen & Nuo Li, 2023. "Superior colliculus bidirectionally modulates choice activity in frontal cortex," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    6. Jérémie Naudé & Matthieu X. B. Sarazin & Sarah Mondoloni & Bernadette Hannesse & Eléonore Vicq & Fabrice Amegandjin & Alexandre Mourot & Philippe Faure & Bruno Delord, 2024. "Dopamine builds and reveals reward-associated latent behavioral attractors," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    7. Xin Wei Chia & Jian Kwang Tan & Lee Fang Ang & Tsukasa Kamigaki & Hiroshi Makino, 2023. "Emergence of cortical network motifs for short-term memory during learning," Nature Communications, Nature, vol. 14(1), pages 1-17, December.

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