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Retinotopic Mechanics

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File:RMechanics.png
A force field perturbs a cell's receptive field, constrained by its neural elastic field, in space and time

Retinotopic mechanics is a mathematical framework derived using classical mechanics. This framework is widely used in the research field of neurophysics to model how cells in retinotopic brain areas change their response properties during active sensing[1] [2]. It predicts that the canonical computations biological systems undergo and the architecture that supports these computations is mediated by a biologically inspired force field[3]. For example, many empirical studies have shown that before the onset of a saccade, visual and motor signals generated by the brain manifests as three temporally overlapping forces - a centripetal force () directed towards the center of gaze, a convergent force() directed towards a peripheral target and translational force () parallel to the impending saccadic eye movement, perturb cells in retinotopic brain areas [4]. The linear summation of these forces and corresponding normalization constants () gives rise to a neural force field that govern the spatio-temporal response properties of cells during active vision [5].

Fundamental properties[edit]

Models of retinotopic mechanics typically include three fundamental properties. The first is a cell and its receptive field, which makes up a hexagonally configured retinotopic field. The second is the receptive field's elastic extent, known as an elastic field. It is posited that elastic fields are self-generated by the visual system and constitute the spatial degrees of freedom within which receptive fields are allowed to transiently shift beyond their classical extent. The third are time varying masses modelled as stochastic and or deterministic putative neural signals that drive the retinotopic field. Forces in these models are exerted by corresponding time varying masses which gives rise to a force field. Depending on the context, a retinotopic force field, determined by the (alpha) parameter can obey either an inverse-distance rule, akin to Newton's law of universal gravitation or a proportional-distance rule.[6].

References[edit]

  1. Duhamel, J; Colby, C; Goldberg, M (1992). "The updating of the representation of visual space in parietal cortex by intended eye movements". Science. 255 (5040): 90–92. Bibcode:1992Sci...255...90D. doi:10.1126/science.1553535. PMID 1553535. Unknown parameter |s2cid= ignored (help)
  2. Gottlieb, J; Oudeyer, P (2018). "Towards a neuroscience of active sampling and curiosity". Nature. doi:10.1038/s41583-018-0078-0.
  3. Yang, S; Lengyel, M; Wolpert, D (2016). "Active sensing in the categorization of visual patterns". eLife. 5: e12215. doi:10.7554/eLife.12215. PMC 4764587. PMID 26880546.
  4. Adeyefa-Olasupo, IE (2021). "Retinotopic Mechanics derived using classical physics". arXiv:2109.11632 [physics.bio-ph].
  5. Zirnsak, M; Steinmetz, N; Noudoost, E; Xu, K; Tirin, M (2014). "Visual Space is Compressed in Prefrontal Cortex Before Eye Movements". Nature. 507 (7493): 504–507. doi:10.1038/nature13149.
  6. Adeyefa-Olasupo, IE; Zixuan, X. "Visual space curves before eye movement". bioRxiv.

See also[edit]


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