Neuromodulation and Robustness of Neurons and Networks

神经元和网络的神经调节和鲁棒性

• 批准号: 10307082
• 负责人: EVE E MARDER
• 金额: $ 96.04万
• 依托单位: BRANDEIS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10307082
• 关键词: Address; Animals; Behavior; Biological; Brain; Computer Models; Crustacea; Financial compensation; Funding; Future; Ganglia; Goals; Human; Individual; Invertebrates; Ion Channel; Light; Measures; Membrane Proteins; Modeling; National Institute of Neurological Disorders and Stroke; Nervous system structure; Neuromodulator Receptors; Neurons; Regulation; Synapses; Temperature; Time; Work; experimental study; flexibility; neuroregulation; receptor; response

Project Summary/Abstract This is a request to consolidate three ongoing NINDS-funded proposals that deal with neuromodulation (R37 NS 17813), temperature compensation (R01 NS 81012), and computational models of homeostatic regulation of intrinsic excitability (Project #4 of P01 NS07949). Together these projects comprise a coherent attempt to understand brain circuit stability in the face of: a) extensive neuromodulation, b) constant and rapid turnover of ion channels and receptors, and c) degenerate and multiple solutions at the single neuron and circuit level. These questions arise from years of computational and experimental work using the small circuits of the crustacean stomatogastric ganglion (STG), but address general problems relevant to all nervous systems, from invertebrates to humans. Future experiments will combine experimental and computational work to understand the correlations in biological parameters in neurons and networks that allow any given parameter to be variable while the circuit itself retains robustness. Animal to animal variability in response to perturbations will be measured, the strengths of all of the synapses in STG circuits will be measured, and the regulation of multiple neuromodulator receptors by single neurons will be studied. Additionally, self-tuning models will be developed to find sets of neuronal parameters that allow neurons to maintain stability in response to perturbations. This work will illuminate the extent to which the same animal can potentially generate similar behavior by substantially different (degenerate) circuit mechanisms at different times. If so, this can shed light on how larger circuits may switch between a number of degenerate circuit mechanisms to generate stable behaviors over time.

项目总结/文摘