Contributions of cortical neuron firing patterns, synaptic connectivity, and plasticity to task performance

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Neuronal responses exhibit diverse properties, from reliable to irregular firing patterns.
• The synaptic origins and functional contributions of this response heterogeneity remain largely unknown.
• Understanding these diverse responses is key to comprehending network function, perception, and behavior.

Purpose of the Study:

• To investigate the synaptic mechanisms underlying diverse neuronal response properties.
• To determine how these diverse responses contribute to network function and task performance.
• To model heterogeneous neural responses using a novel spiking neural network.

Main Methods:

• Developed a novel task-performing spiking recurrent neural network with spike-timing-dependent plasticity.
• Analyzed differential contributions of reliable and irregular units to task performance.
• Investigated the roles of excitatory plasticity and inhibitory constraints on response diversity.
• Compared network unit response properties with in vivo whole-cell recordings from rodent auditory cortex.

Main Results:

• Reliable and irregular neuronal units differentially impact task performance through distinct connection types.
• Excitatory synaptic plasticity modifies the distribution of neuronal responses.
• Inhibitory connections constrain response diversity, enhancing overall network function.
• Local synaptic input patterns predict neuronal response properties in both the model and biological data.

Conclusions:

• Diverse neuronal responses are not random but emerge from specific synaptic plasticity rules.
• Synaptic plasticity dynamically shapes neuronal response heterogeneity, contributing to improved network performance.
• The findings provide a mechanistic link between synaptic dynamics, response diversity, and behavioral outcomes.