Neural synchrony in cortical networks: mechanisms and implications for neural information processing and coding

Area of Science:

• Neuroscience
• Computational Neuroscience
• Cognitive Neuroscience

Background:

• Neuronal synchronization on the millisecond scale is a key feature of neural activity.
• Understanding the mechanisms of synchronized neural discharges in cortical networks is essential for grasping coding and cognitive functions.

Purpose of the Study:

• To review classical concepts and evidence for mechanisms governing synchronized neural discharges.
• To propose a new hypothesis, "synchrony through synaptic plasticity," explaining selective, directed synchronization of neurons.

Main Methods:

• Review of existing literature on neural synchronization mechanisms.
• Formulation of the "synchrony through synaptic plasticity" hypothesis based on spike-timing-dependent plasticity (STDP).
• Deduction of testable predictions from the proposed hypothesis.

Main Results:

• Proposes that STDP, by associating cells with temporally coherent inputs, drives selective neuronal synchronization.
• Predicts that network position and input source are irrelevant for synchronization if inputs are simultaneous.
• Suggests that repeating discharge patterns compress and sparsify signals, leading to synchronized cell groups.

Conclusions:

• Synchronous neuronal firing can be a learned response mediated by STDP.
• The hypothesis offers a framework for understanding how neural networks achieve selective and directed synchronization.
• Suggests experimental avenues to validate the "synchrony through synaptic plasticity" hypothesis.