The h current is a candidate mechanism for regulating the sliding 1 modification threshold in a BCM - like synaptic learning rule

In a Bcm-like Synaptic Learning Rule the H Current Is a Candidate Mechanism for Regulating the Sliding Modification Threshold

The h current is a candidate mechanism for regulating the sliding modification threshold in a BCM-like synaptic learning rule.

Hebbian synaptic plasticity acts as a positive feedback mechanism and can destabilize a neuronal network unless concomitant homeostatic processes that counterbalance this instability are activated. Within a Bienenstock-Cooper-Munro (BCM)-like plasticity framework, such compensation is achieved through a modification threshold that slides in an activity-dependent fashion. Although the BCM-like p...

Emergent Dynamical Properties of the BCM Learning Rule

The Bienenstock-Cooper-Munro (BCM) learning rule provides a simple setup for synaptic modification that combines a Hebbian product rule with a homeostatic mechanism that keeps the weights bounded. The homeostatic part of the learning rule depends on the time average of the post-synaptic activity and provides a sliding threshold that distinguishes between increasing or decreasing weights. There ...

Synergies Between Intrinsic and Synaptic Plasticity Mechanisms

We propose a model of intrinsic plasticity for a continuous activation model neuron based on information theory. We then show how intrinsic and synaptic plasticity mechanisms interact and allow the neuron to discover heavy-tailed directions in the input. We also demonstrate that intrinsic plasticity may be an alternative explanation for the sliding threshold postulated in the BCM theory of syna...

The Role of Constraints in the Development of Receptive Field Structure of Simple Cells Using BCM Learning

Experimentally studies have shown that visual cortical neurons apply BCM (Binenstock Cooper and Munro) learning rule for modifications in synaptic strength. BCM rule uses adaptive threshold and in this both long term potentiation (LTP) and long term depression (LTD) is automatically taken care of. This overcomes the major disadvantage of Hebbian learning in which there is a mechanism only for L...