Synapse-type-specific competitive Hebbian learning forms functional recurrent networks.

ABSTRACT: Cortical networks exhibit complex stimulus-response patterns that are based on specific recurrent interactions between neurons. For example, the balance between excitatory and inhibitory currents has been identified as a central component of cortical computations. However, it remains unclear how the required synaptic connectivity can emerge in developing circuits where synapses between excitatory and inhibitory neurons are simultaneously plastic. Using theory and modeling, we propose that a wide range of cortical response properties can arise from a single plasticity paradigm that acts simultaneously at all excitatory and inhibitory connections-Hebbian learning that is stabilized by the synapse-type-specific competition for a limited supply of synaptic resources. In plastic recurrent circu

SUBMITTER: Eckmann S 

PROVIDER: S-EPMC11194505 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature