A neural surveyor to map touch on the body.
Proc Natl Acad Sci U S A
; 119(1)2022 01 04.
Article
em En
| MEDLINE
| ID: mdl-34983835
ABSTRACT
Perhaps the most recognizable sensory map in all of neuroscience is the somatosensory homunculus. Although it seems straightforward, this simple representation belies the complex link between an activation in a somatotopic map and the associated touch location on the body. Any isolated activation is spatially ambiguous without a neural decoder that can read its position within the entire map, but how this is computed by neural networks is unknown. We propose that the somatosensory system implements multilateration, a common computation used by surveying and global positioning systems to localize objects. Specifically, to decode touch location on the body, multilateration estimates the relative distance between the afferent input and the boundaries of a body part (e.g., the joints of a limb). We show that a simple feedforward neural network, which captures several fundamental receptive field properties of cortical somatosensory neurons, can implement a Bayes-optimal multilateral computation. Simulations demonstrated that this decoder produced a pattern of localization variability between two boundaries that was unique to multilateration. Finally, we identify this computational signature of multilateration in actual psychophysical experiments, suggesting that it is a candidate computational mechanism underlying tactile localization.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Tato
/
Redes Neurais de Computação
/
Percepção do Tato
Tipo de estudo:
Prognostic_studies
Limite:
Adult
/
Animals
/
Female
/
Humans
Idioma:
En
Revista:
Proc Natl Acad Sci U S A
Ano de publicação:
2022
Tipo de documento:
Article