Show Tag: neurophysiology

Select Other Tags

Improved performance on the behavioral side due to cross-sensory integration is connected to effects of effects on the neurophysiological side.

Neuropsychology must both describe information processing in the brain and do its part in building the abstracted interface to theories of cognition at higher levels of resolution.

Simon implies that human cognition is serial or parallel depending on the level of resolution one looks at it.

Neural responses to the same stimulus are noisy.

There are two strands in multi-sensory research: mathematical modeling and modeling of neurophysiology.

Yay! I'm bridging that gulf as well!

According to Ma et al,'s work, computations in neurons doing multi-sensory integration should be additive or sub-additive. This is at odds with observed neurophysiology.

My model is normative, performs optimally and it shows super-additivity (to be shown).

Fetsch et al. explain the discrepancy between observed neurophysiology—superadditivity—and the normative solution to single-neuron cue integration proposed by Ma et al. using divisive normalization:

They propose that the network activity is normalized in order to keep neurons' activities within their dynamic range. This would lead to the apparent reliability-dependent weighting of responses found by Morgan et al. and superadditivity as described by Stanford et al.

Neurophysiology can help us understand the representations. Otherwise it is mainly concerned with the implementational side of the study of the brain as an information-processing system. Neurophysiological knowledge is hard to interpret in terms of algorithms and representations especially without a clear understanding of the task (ie. the computational theory).