Representational Drift and Learning-Induced Stabilization in the Olfactory Cortex
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
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2024
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| _version_ | 1866910751364481024 |
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| author | Morales, Guillermo B. Muñoz, Miguel A. Tu, Yuhai |
| author_facet | Morales, Guillermo B. Muñoz, Miguel A. Tu, Yuhai |
| contents | The brain encodes external stimuli through patterns of neural activity, forming internal representations of the world. Recent experiments show that neural representations for a given stimulus change over time. However, the mechanistic origin for the observed "representational drift" (RD) remains unclear. Here, we propose a biologically-realistic computational model of the piriform cortex to study RD in the mammalian olfactory system by combining two mechanisms for the dynamics of synaptic weights at two separate timescales: spontaneous fluctuations on a scale of days and spike-time dependent plasticity (STDP) on a scale of seconds. Our study shows that, while spontaneous fluctuations in synaptic weights induce RD, STDP-based learning during repeated stimulus presentations can reduce it. Our model quantitatively explains recent experiments on RD in the olfactory system and offers a mechanistic explanation for the emergence of drift and its relation to learning, which may be useful to study RD in other brain regions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_13713 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Representational Drift and Learning-Induced Stabilization in the Olfactory Cortex Morales, Guillermo B. Muñoz, Miguel A. Tu, Yuhai Neurons and Cognition Disordered Systems and Neural Networks Adaptation and Self-Organizing Systems The brain encodes external stimuli through patterns of neural activity, forming internal representations of the world. Recent experiments show that neural representations for a given stimulus change over time. However, the mechanistic origin for the observed "representational drift" (RD) remains unclear. Here, we propose a biologically-realistic computational model of the piriform cortex to study RD in the mammalian olfactory system by combining two mechanisms for the dynamics of synaptic weights at two separate timescales: spontaneous fluctuations on a scale of days and spike-time dependent plasticity (STDP) on a scale of seconds. Our study shows that, while spontaneous fluctuations in synaptic weights induce RD, STDP-based learning during repeated stimulus presentations can reduce it. Our model quantitatively explains recent experiments on RD in the olfactory system and offers a mechanistic explanation for the emergence of drift and its relation to learning, which may be useful to study RD in other brain regions. |
| title | Representational Drift and Learning-Induced Stabilization in the Olfactory Cortex |
| topic | Neurons and Cognition Disordered Systems and Neural Networks Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2412.13713 |