Nolan, M. F.

O'Donnell, Cian

Neuron types are classically defined by anatomical and physiological properties that determine how synaptic inputs are integrated. Here, we provide an overview of the evidence that, among neurons of a single type, integration of synaptic responses is further tuned according to the particular function that individual neurons carry out. Recent data suggest that tuning of synaptic responses is not restricted to sensory pathways, but extends to cognitive and motor circuits. We propose that tuning of synaptic integration results from general cellular mechanisms for optimization of information processing that are distinct from, but complementary to, homeostasis and memory storage. These cellular tuning mechanisms might be crucial for distributed computations underlying sensory, motor and cognitive functions.</p

Nolan, Matthew F

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Tuning of synaptic responses:an organizing principle for optimization of neural circuits

Neuron types are classically defined by anatomical and physiological properties that determine how synaptic inputs are integrated. Here, we provide an overview of the evidence that, among neurons of a single type, integration of synaptic responses is further tuned according to the particular function that individual neurons carry out. Recent data suggest that tuning of synaptic responses is not restricted to sensory pathways, but extends to cognitive and motor circuits. We propose that tuning of synaptic integration results from general cellular mechanisms for optimization of information processing that are distinct from, but complementary to, homeostasis and memory storage. These cellular tuning mechanisms might be crucial for distributed computations underlying sensory, motor and cognitive functions

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Tuning of synaptic responses: an organizing principle for optimization of neural circuits

https://www.pure.ed.ac.uk/ws/files/10295303/Tuning_of_synaptic_responses_an_organizing_principle_for_optimization_of_neural_circuit_function.pdf

Tuning of synaptic responses: an organizing principle for optimization of neural circuits

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