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The cost of cortical computation.

¹Center for Neural Science, New York University, 4 Washington Place, New York, NY 10003, USA. pl@cns.nyu.edu

Current Biology : CB

|March 21, 2003

Summary

The high energy cost of neural spikes limits concurrent neuronal activity in the human cortex to less than 1%. This energy constraint shapes how the brain encodes information and allocates resources during cognitive tasks.

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Area of Science:

Neuroscience
Computational Neuroscience
Systems Neuroscience

Background:

Individual neuron activity is known, but the scale of neuronal engagement in cognitive tasks remains unclear.
Understanding the number of concurrently active neurons is crucial for deciphering cortical information processing.

Purpose of the Study:

To estimate the energetic cost of individual neuronal spikes in the human cortex.
To determine the maximum number of neurons that can be active simultaneously given cortical energy constraints.

Main Methods:

Calculation of the energetic cost per action potential (spike).
Estimation of concurrently active neurons based on total cortical energy consumption and spike cost.

Main Results:

The energetic cost of a single action potential is substantial.
This high cost restricts the proportion of substantially active neurons to below 1% of the total neuronal population.

Conclusions:

Cortical computation relies on sparse coding strategies, utilizing very few active neurons.
Energy limitations necessitate flexible allocation of resources across cortical regions based on task demands.
These constraints may explain the physiological basis for functional magnetic resonance imaging (fMRI) and the evolution of selective attention mechanisms.

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