Biology subjects

Cesanek, E.

Publications and source records attributed to Cesanek, E..

2 recordsLinked to original sources

bioRxiv2019

Cue-selective adaptation operates on a separable encoding of stereo and texture information

To perform accurate movements, the sensorimotor system must maintain a delicate calibration of the mapping between visual inputs and motor outputs. Previous work has focused on the mapping between visual inputs and individual locations in egocentric space, but little attention has been paid to the mappings that support interactions with 3D objects. In this study, we investigated sensorimotor adaptation of grasping movements targeting the depth dimension of 3D paraboloid objects. Object depth was specified by separately manipulating binocular disparity (stereo) and texture gradients. At the end of each movement, the fingers closed down on a physical object consistent with one of the two cues, depending on the condition (haptic-for-texture or haptic-for-stereo). Unlike traditional adaptation paradigms, where relevant spatial properties are determined by a single dimension of visual information, this method enabled us to investigate whether adaptation processes can selectively adjust the influence of different sources of visual information depending on their relationship to physical depth. In two experiments, we found short-term changes in grasp performance consistent with a process of cue-selective adaptation: the slope of the grip aperture with respect to a reliable cue (correlated with physical reality) increased, whereas the slope with respect to the unreliable cue (uncorrelated with physical reality) decreased. In contrast, slope changes did not occur during exposure to a set of stimuli where both cues remained correlated with physical reality, but one was rendered with a constant bias of 10 mm; the grip aperture simply became uniformly larger or smaller, as in standard adaptation paradigms. Overall, these experiments support a model of cue-selective adaptation driven by correlations between error signals and input values (i.e., supervised learning), rather than mismatched haptic and visual signals.

neuroscience↗

bioRxiv2019

Sensorimotor adaptation compensates for distortions of 3D shape information

Visual perception often fails to recover the veridical 3D shape of objects in the environment due to ambiguity and variability in the available depth cues. However, we rely heavily on 3D shape estimates when planning movements, for example reaching to pick up an object from a slanted surface. Given the wide variety of distortions that can affect 3D perception, how do our actions remain accurate across different environments? One hypothesis is that the visuomotor system performs selective filtering of 3D information to minimize distortions. Indeed, some studies have found that actions appear to preferentially target stereo information when it is put in conflict with texture information. However, since these studies analyze averages over multiple trials, this apparent preference could be produced by sensorimotor adaptation. In Experiment 1, we create a set of cue-conflict stimuli where one available depth cue is affected by a constant bias. Sensory feedback rapidly aligns the motor output with physical reality in just a few trials, which can make it seem as if action planning selectively relies on the reinforced cue--yet no change in the relative influences of the cues is necessary to eliminate the constant errors. In contrast, when one depth cue becomes less correlated with physical reality, variable movement errors will occur, causing canonical adaptation to fail as the opposite error corrections cancel out. As a result, canonical adaptation cannot explain the preference for stereo found in studies with variable errors. However, Experiment 2 shows that persistent errors can produce a novel form of adaptation that gradually reduces the relative influence of an unreliable depth cue. These findings show that grasp control processes are continuously modified based on sensory feedback to compensate for both biases and noise in 3D visual processing, rather than having a hardwired preference for one type of depth information.

neuroscience↗