The generation of cortical novelty responses through inhibitory plasticity
| Autor: | Julijana Gjorgjieva, Auguste Schulz, Michael J. Berry, Christoph Miehl |
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| Rok vydání: | 2020 |
| Předmět: |
Periodicity
Signal Detection Psychological Time Factors QH301-705.5 Science Models Neurological Action Potentials Sensory system adaptation Biology Plasticity Inhibitory postsynaptic potential Synaptic Transmission General Biochemistry Genetics and Molecular Biology inhibitory plasticity novelty Mice recurrent network None medicine Reaction Time Animals Computer Simulation Biology (General) Cerebral Cortex Neuronal Plasticity General Immunology and Microbiology Behavior Animal Mechanism (biology) General Neuroscience Novelty Neural Inhibition General Medicine Disinhibition Synaptic plasticity Excitatory postsynaptic potential Exploratory Behavior Medicine Adaptation medicine.symptom Neuroscience Research Article |
| Zdroj: | eLife eLife, Vol 10 (2021) |
| ISSN: | 2050-084X |
| Popis: | Animals depend on fast and reliable detection of novel stimuli in their environment. Indeed, neurons in multiple sensory areas respond more strongly to novel in comparison to familiar stimuli. Yet, it remains unclear which circuit, cellular and synaptic mechanisms underlie those responses. Here, we show that inhibitory synaptic plasticity readily generates novelty responses in a recurrent spiking network model. Inhibitory plasticity increases the inhibition onto excitatory neurons tuned to familiar stimuli, while inhibition for novel stimuli remains low, leading to a network novelty response. Generated novelty responses do not depend on the exact temporal structure but rather on the distribution of presented stimuli. By including tuning of inhibitory neurons, the network further captures stimulus-specific adaptation. Finally, we suggest that disinhibition can control the amplification of novelty responses. Therefore, inhibitory plasticity provides a flexible, biologically-plausible mechanism to detect the novelty of bottom-up stimuli, enabling us to make numerous experimentally testable predictions. |
| Databáze: | OpenAIRE |
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