Neural mechanisms for self-motion perception in area MST.
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Animals↗
Biomedical subjects
K V Shenoy
Publications and source records attributed to K V Shenoy.
The contributions of vestibular signals to the representations of space in the posterior parietal cortex.
Vestibular signals play an important role in spatial orientation, perception of object location, and control of self-motion. Prior physiological research on vestibular information processing has focused on brainstem mechanisms; relatively little is known about the processing of vestibular information at the level of the cerebral cortex. Recent electrophysiological experiments examining the use of vestibular canal signals in two different perceptual tasks are described: computation of self motion and localization of visual stimuli in a world-centered reference frame. These two perceptual functions are mediated by different parts of the posterior parietal cortex, the former in the dorsal aspect of the medial superior temporal area (MSTd) and the latter in area 7a.
Animals↗
Influence of gaze rotation on the visual response of primate MSTd neurons.
When we move forward, the visual image on our retina expands. Humans rely on the focus, or center, of this expansion to estimate their direction of heading and, as long as the eyes are still, the retinal focus corresponds to the heading. However, smooth rotation of the eyes adds nearly uniform visual motion to the expanding retinal image and causes a displacement of the retinal focus. In spite of this, humans accurately judge their heading during pursuit eye movements and during active, smooth head rotations even though the retinal focus no longer corresponds to the heading. Recent studies in macaque suggest that correction for pursuit may occur in the dorsal aspect of the medial superior temporal area (MSTd) because these neurons are tuned to the retinal position of the focus and they modify their tuning during pursuit to compensate partially for the focus shift. However, the question remains whether these neurons also shift focus tuning to compensate for smooth head rotations that commonly occur during gaze tracking. To investigate this question, we recorded from 80 MSTd neurons while monkeys tracked a visual target either by pursuing with their eyes or by vestibulo-ocular reflex cancellation (VORC; whole-body rotation with eyes fixed in head and head fixed on body). VORC is a passive, smooth head rotation condition that selectively activates the vestibular canals. We found that neurons shift their focus tuning in a similar way whether focus displacement is caused by pursuit or by VORC. Across the population, compensation averaged 88 and 77% during pursuit and VORC, respectively (tuning shift divided by the retinal focus to true heading difference). Moreover the degree of compensation during pursuit and VORC was correlated in individual cells (P < 0.001). Finally neurons that did not compensate appreciably tended to be gain-modulated during pursuit and VORC and may constitute an intermediate stage in the compensation process. These results indicate that many MSTd cells compensate for general gaze rotation, whether produced by eye-in-head or head-in-world rotation, and further implicate MSTd as a critical stage in the computation of heading. Interestingly vestibular cues present during VORC allow many cells to compensate even though humans do not accurately judge their heading in this condition. This suggests that MSTd may use vestibular information to create a compensated heading representation within at least a subpopulation of cells, which is accessed perceptually only when additional cues related to active head rotations are also present.
Action Potentials↗
Visual self-motion perception during head turns.
Extra-retinal information is critical in the interpretation of visual input during self-motion. Turning our eyes and head to track objects displaces the retinal image but does not affect our ability to navigate because we use extra-retinal information to compensate for these displacements. We showed observers animated displays depicting their forward motion through a scene. They perceived the simulated self-motion accurately while smoothly shifting the gaze by turning the head, but not when the same gaze shift was simulated in the display; this indicates that the visual system also uses extra-retinal information during head turns. Additional experiments compared self-motion judgments during active and passive head turns, passive rotations of the body and rotations of the body with head fixed in space. We found that accurate perception during active head turns is mediated by contributions from three extra-retinal cues: vestibular canal stimulation, neck proprioception and an efference copy of the motor command to turn the head.
Cues↗
Mechanisms of heading perception in primate visual cortex.
When we move forward while walking or driving, what we see appears to expand. The center or focus of this expansion tells us our direction of self-motion, or heading, as long as our eyes are still. However, if our eyes move, as when tracking a nearby object on the ground, the retinal image is disrupted and the focus is shifted away from the heading. Neurons in primate dorso-medial superior temporal area responded selectively to an expansion focus in a certain part of the visual field, and this selective region shifted during tracking eye movements in a way that compensated for the retinal focus shift. Therefore, these neurons account for the effect of eye movements on what we see as we travel forward through the world.
Animals↗
Neural mechanisms for heading and structure-from-motion perception.
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Animals↗
Learning by selection in the trion model of cortical organization.
The basic issue of whether mammalian learning in cortex proceeds via a selection principle, as stressed by Edelman, versus an instructional one is of major importance. We present here a realization of selection learning in the trion model, which is based on the Mountcastle columnar organizational principle of cortex. We suggest that mammalian cortex starts out with an a priori connectivity between minicolumns that is highly structured in time and in space, competing between excitation and inhibition. This provides a "naive" repertoire of spatial-temporal firing patterns that stimuli and internal processing map onto. These patterns can be learned with small modifications to the connectivity strengths determined by a Hebbian learning rule. As various patterns are learned, the repertoire changes somewhat in order to respond properly to various stimuli, but the majority of all possible stimuli still map onto spatial-temporal firing patterns of the original repertoire. In order to show that the example presented here is showing true selectivity and is not an artifact of more stimuli evolving into the learned pattern, we develop a selectivity measure. We suggest that some form of instructional learning (in which connectivities are finely tuned) is present for difficult tasks requiring many trials, whereas very rapid learning involves selectional learning. Both types of learning must be considered to understand behavior.
Animals↗