| Project/Area Number |
23KJ2131
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| Research Category |
Grant-in-Aid for JSPS Fellows
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| Allocation Type | Multi-year Fund |
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| Section | 国内 |
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| Review Section |
Basic Section 61040:Soft computing-related
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| Research Institution | Okinawa Institute of Science and Technology Graduate University |
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Principal Investigator |
Koshkin Roman 沖縄科学技術大学院大学, 科学技術研究科, 特別研究員(DC2)
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| Project Period (FY) |
2023-04-25 – 2025-03-31
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| Project Status |
Granted (Fiscal Year 2023)
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| Budget Amount *help |
¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 2024: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2023: ¥900,000 (Direct Cost: ¥900,000)
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| Keywords | spontaneous activity / spiking neural network / memory / cell assembly / pattern detection |
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| Outline of Research at the Start |
I aim to study spontaneous activity in a biologically realistic memory model (SNN), focusing on the role of cell assemblies for encoding of sequential information (e.g. spatial trajectories), using only a limited number of samples. I will also explore if and how spontaneous activity can serve as a natural mechanism to counter catastrophic forgetting (loss learned information on exposure to new stimuli). I seek to demonstrate that a recurrent network using biologically plausible local learning rules can create durable memory traces, which could have practical applications for the future of AI.
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| Outline of Annual Research Achievements |
Line of work (1) The study of the emergence and properties of structured spontaneous activity in a biologically plausible episodic memory model, with a focus on the role of short-term plasticity and astrocytes for the properties of cell assemblies.
Line of work (2) Development of methods for the detection of patterns in spike data. Published two peer-reviewed papers: (1) Unsupervised Detection of Cell Assemblies with Graph Neural Networks (ICLR 2023) and (2) convSeq: Fast and Scalable Method for Detecting Patterns in Spike Data (ICML 2024).
Line of work (3) Using large language models for simultaneous translation. Status: wrote a paper (posted on arXiv, currently in review at ACL).
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Line of work (1) Status: The work is mostly finished, I continue to improve the draft of the paper reporting the key findings. Progress on the line of work was slightly slower than expected (the paper should be in review by now). This slight delay is due to the fact that finishing my other work (now published) on the detection of patterns in spike data took significantly more.
Line of work (2) status: Finished, papers published.
Line of work (3) status: Mostly finished, paper in review.
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| Strategy for Future Research Activity |
I plan to finalize my line of work 1 (The study of the emergence and properties of structured spontaneous activity), and submit the manuscript. Time permitting, I intend to do one more related project (on sequence learning in recurrent networks under biologically realistic plasticity, which will be a logical continuation of the current one).
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