Burst firing creates an attractor in synaptic weight dynamics.

Area of Science:

• Computational Neuroscience
• Systems Neuroscience
• Neuroplasticity

Background:

• Neural circuits exhibit tonic and burst firing, impacting network excitability and neuromodulation.
• Synaptic plasticity research has largely focused on single activity regimes, leaving the dynamics across alternating regimes unclear.

Purpose of the Study:

• To investigate how synaptic weights evolve across tonic and burst firing regimes.
• To understand the emergent properties of synaptic plasticity during collective bursting.
• To explore the role of neuromodulation and synaptic tagging in shaping synaptic configurations.

Main Methods:

• Utilized a conductance-based network model with calcium-based and spike-timing-based plasticity rules.
• Analyzed synaptic weight evolution during tonic and burst firing simulations.
• Derived analytical predictions for the burst-induced attractor and validated them experimentally.

Main Results:

• Tonic firing leads to diverse synaptic weight distributions driven by external inputs.
• Collective burst firing induces a "burst-induced attractor," converging synaptic weights to a narrow region.
• Neuromodulation and synaptic tagging can modulate the burst-induced attractor, selectively stabilizing or weakening synapses.

Conclusions:

• Burst-induced attractors are a robust emergent property of collective bursting in neural circuits.
• Alternating firing regimes provide a framework for consolidating or down-selecting synaptic configurations.
• This work offers a computational framework linking firing state transitions, synaptic plasticity, and memory organization.