Neurometric function
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In neuroscience, a Neurometric function is a mathematical formula relating the activity of brain cells to aspects of an animal's sensory experience or motor behavior. Neurometric functions provide a quantitative summary of the neural code of a particular brain region.
In sensory neuroscience, examples of neurometric functions include tuning curves: formulae that predict a single neuron's firing rate from features such as the contrast of a visual stimulus [1]. Comparing neurometric functions to psychometric functions can reveal whether the neural representation in the recorded region constrains perceptual accuracy [2].
In motor neuroscience, neurometric functions are used to predict body movements from the activity of neuronal populations in regions such as motor cortex. Such neurometric functions are used in the design of brain-computer interfaces.
See also
References
- ^ Tolhurst, D.J.; Movshon, J.A.; Dean, A.F. (January 1983). "The statistical reliability of signals in single neurons in cat and monkey visual cortex". Vision Research. 23 (8): 775–785. doi:https://doi.org/10.1016/0042-6989(83)90200-6.
{{cite journal}}: Check|doi=value (help); External link in|doi= - ^ Parker, A. J.; Newsome, W. T. (1998). "SENSE AND THE SINGLE NEURON: Probing the Physiology of Perception". Annual Review of Neuroscience. 21 (1): 227–277. doi:10.1146/annurev.neuro.21.1.227.