Faculty Opinions recommendation of Spatiotemporal response properties of optic-flow processing neurons.

Author(s):  
Kathleen Cullen ◽  
Mohsen Jamali
Neuron ◽  
2010 ◽  
Vol 67 (4) ◽  
pp. 629-642 ◽  
Author(s):  
Franz Weber ◽  
Christian K. Machens ◽  
Alexander Borst

2021 ◽  
Vol 118 (49) ◽  
pp. e2115772118
Author(s):  
Aneesha K. Suresh ◽  
Charles M. Greenspon ◽  
Qinpu He ◽  
Joshua M. Rosenow ◽  
Lee E. Miller ◽  
...  

Tactile nerve fibers fall into a few classes that can be readily distinguished based on their spatiotemporal response properties. Because nerve fibers reflect local skin deformations, they individually carry ambiguous signals about object features. In contrast, cortical neurons exhibit heterogeneous response properties that reflect computations applied to convergent input from multiple classes of afferents, which confer to them a selectivity for behaviorally relevant features of objects. The conventional view is that these complex response properties arise within the cortex itself, implying that sensory signals are not processed to any significant extent in the two intervening structures—the cuneate nucleus (CN) and the thalamus. To test this hypothesis, we recorded the responses evoked in the CN to a battery of stimuli that have been extensively used to characterize tactile coding in both the periphery and cortex, including skin indentations, vibrations, random dot patterns, and scanned edges. We found that CN responses are more similar to their cortical counterparts than they are to their inputs: CN neurons receive input from multiple classes of nerve fibers, they have spatially complex receptive fields, and they exhibit selectivity for object features. Contrary to consensus, then, the CN plays a key role in processing tactile information.


1993 ◽  
Vol 69 (6) ◽  
pp. 2039-2055 ◽  
Author(s):  
G. A. Bush ◽  
A. A. Perachio ◽  
D. E. Angelaki

1. Extracellular recordings were made in and around the medial vestibular nuclei in decerebrated rats. Neurons were functionally identified according to their semicircular canal input on the basis of their responses to angular head rotations around the yaw, pitch, and roll head axes. Those cells responding to angular acceleration were classified as either horizontal semicircular canal-related (HC) or vertical semicircular canal-related (VC) neurons. The HC neurons were further characterized as either type I or type II, depending on the direction of rotation producing excitation. Cells that lacked a response to angular head acceleration, but exhibited sensitivity to a change in head position, were classified as purely otolith organ-related (OTO) neurons. All vestibular neurons were then tested for their response to sinusoidal linear translation in the horizontal head plane. 2. Convergence of macular and canal inputs onto central vestibular nuclei neurons occurred in 73% of the type I HC, 79% of the type II HC, and 86% of the VC neurons. Out of the 223 neurons identified as receiving macular input, 94 neurons were further studied, and their spatiotemporal response properties to sinusoidal stimulation with pure linear acceleration were quantified. Data were obtained from 33 type I HC, 22 type II HC, 22 VC, and 17 OTO neurons. 3. For each neuron the angle of the translational stimulus vector was varied by 15, 30, or 45 degrees increments in the horizontal head plane. In all tested neurons, a direction of maximum sensitivity was identified. An interesting difference among neurons was their response to translation along the direction perpendicular to that that produced the maximum response ("null" direction). For the majority of neurons tested, it was possible to evoke a nonzero response during stimulation along the null direction always had response phases that varied as a function of stimulus direction. 4. These spatiotemporal response properties were quantified in two independent ways. First, the data were evaluated on the basis of the traditional one-dimensional principle governed by the "cosine gain rule" and constant response phase at different stimulus orientations. Second, the response gain and phase values that were empirically determined for each orientation of the applied linear stimulus vector were fitted on the basis of a newly developed formalism that treats neuronal responses as exhibiting two-dimensional spatial sensitivity. Thus two response vectors were determined for each neuron on the basis of its response gain and phase at different stimulus directions in the horizontal head plane.(ABSTRACT TRUNCATED AT 400 WORDS)


1997 ◽  
Vol 77 (2) ◽  
pp. 562-570 ◽  
Author(s):  
Kathleen Mulligan ◽  
Jong-Nam Kim ◽  
Helen Sherk

Mulligan, Kathleen, Jong-Nam Kim, and Helen Sherk. Simulated optic flow and extrastriate cortex. II. Responses to bar versus large-field stimuli. J. Neurophysiol. 77: 562–570, 1997. In the preceding paper we described the responses of cells in the cat's lateral suprasylvian visual area (LS) to large-field optic flow and texture movies. To assess response properties such as direction selectivity, cells were also tested with moving bar stimuli. We expected that there would be good agreement between response properties elicited with optic flow movies and those revealed with bar stimuli. We first asked how well bar response properties predicted responsiveness to optic flow movies. There was no correlation between responsiveness to movies and the degree of end-stopping, length summation, or preference for bars that accelerated and expanded. We then considered only the 322 cells that responded to both bars and optic flow or texture movies and asked how well the strength of their response to movies could be predicted from the direction-tuning curves generated with bar stimuli. One-third of these cells responded much more strongly to movies than could be predicted from their direction-tuning curves. Generally, such cells were rather well tuned for the direction of bar motion and preferred a direction substantially different from what they saw in optic flow movies. Optic flow movies shown in the forward direction were the most effective variety of movie for two-thirds of these cells. To see whether this outcome stemmed from differential direction tuning for bars and large multielement displays, in a second series of experiments we compared direction tuning for bars and large-field texture movies. Many cells showed substantially different direction tuning for the two kinds of stimulus: almost [Formula: see text] of 409 cells had tuning curves that overlapped each other by <50%. But only a small number of cells (<10%) responded much better to texture movies than to bars in the predominant direction of image motion in optic flow movies. This result, like that reported in the preceding paper, suggests that cells in LS respond differently to optic flow than to texture displays lacking optic flow motion cues.


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