Stability and Adaptability in Balance: A Dual Mechanism for Metaplasticity in Cortical Networks DOI Creative Commons

Tea Tompos,

Fleur Zeldenrust, Tansu Celikel

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Апрель 3, 2025

1. Abstract Metaplasticity dynamically adjusts how synaptic efficacy and connectivity change, helping neural circuits adapt to experience. However, the interaction between changes in weight (W) connection probability (P) remains poorly understood. We explored their using a biologically-inspired, multi-layer spiking network. found that while W controls network excitability, P exerts layer-specific time-dependent control, crucial for stability. Simultaneous P, i.e. metaplasticity, revealed complex, non-additive interactions, shaping response timing recruitment, resulting emergence of functionally distinct neuronal subtypes: input-invariant neurons maintaining responsiveness variant enabling adaptation, based on differential E-I dynamics. This allows achieve functional homeostasis input layer preserving flexibility superficial layers. provide novel framework understanding metaplasticity balances competing demands stability adaptability cortical circuits, with significant implications learning, memory, coding.

Язык: Английский

Stability and Adaptability in Balance: A Dual Mechanism for Metaplasticity in Cortical Networks DOI Creative Commons

Tea Tompos,

Fleur Zeldenrust, Tansu Celikel

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Апрель 3, 2025

1. Abstract Metaplasticity dynamically adjusts how synaptic efficacy and connectivity change, helping neural circuits adapt to experience. However, the interaction between changes in weight (W) connection probability (P) remains poorly understood. We explored their using a biologically-inspired, multi-layer spiking network. found that while W controls network excitability, P exerts layer-specific time-dependent control, crucial for stability. Simultaneous P, i.e. metaplasticity, revealed complex, non-additive interactions, shaping response timing recruitment, resulting emergence of functionally distinct neuronal subtypes: input-invariant neurons maintaining responsiveness variant enabling adaptation, based on differential E-I dynamics. This allows achieve functional homeostasis input layer preserving flexibility superficial layers. provide novel framework understanding metaplasticity balances competing demands stability adaptability cortical circuits, with significant implications learning, memory, coding.

Язык: Английский

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