Adaptive reliance on the most stable sensory predictions enhances the accuracy of perceptual decisions

by Neeraj Kumar And Pratik Mutha

60 Years of cognitive neuroscience research: tracking changes through data mining

by Dinesh Kumar and Pratik Muth

Adaptive reliance on the most stable sensory predictions enhances perceptual feature extraction of moving stimuli

Predicting the sensory outcomes of action is thought to be useful for distinguishing self- versus externally-generated sensations, correcting movements when sensory feedback is delayed and learning predictive models for motor behavior. Here we show that aspects of another fundamental function, perception, are enhanced when they entail the contribution of predicted sensory outcomes, and that this enhancement relies on the adaptive use of the most stable predictions available. We combined a motor learning paradigm that imposes new sensory predictions with a dynamic visual search task to first show that perceptual feature extraction of a moving stimulus is poorer when it is based on sensory feedback that is misaligned with those predictions. This was possible because our novel experimental design allowed us to override the "natural" sensory predictions present when any action is performed, and separately examine the influence of these two sources on perceptual feature extraction. We then show that if the new predictions induced via motor learning are unreliable, rather than relying just on sensory information for perceptual judgments as is conventionally thought, subjects adaptively transition to using other, stable sensory predictions to maintain greater accuracy in their perceptual judgments. Finally, we show that when sensory predictions are not modified at all, these judgments are sharper when subjects combine their natural predictions with sensory feedback. Collectively, our results highlight the crucial contribution of sensory predictions to perception and also suggest that the brain intelligently integrates the most stable predictions available with sensory information to maintain high fidelity in perceptual decisions.by Neeraj Kumar and Pratik K Muth

Learning of bimanual motor sequences in normal aging

While it is well accepted that motor performance declines with age, the ability to learn simple procedural motor tasks appears to remain intact to some extent in normal aging. Here we examined the impact of aging on the acquisition of a simple sequence of bimanual actions. We further asked whether such learning results from an overall decrease in response time or is also associated with improved coordination between the hands. Healthy young and old individuals performed a bimanual version of the classic serial reaction time task. We found no learning deficit in older adults and noted that older subjects were able to learn as much as young participants. We also observed that learning in both groups was associated with an overall decrease in response time, but switch cost, the increase in response time when a switch in hands was required during sequence execution, did not decrease with learning. Surprisingly however, overall switch cost was lower in the older group compared to the younger subjects. These findings are discussed in the context of interactions between procedural and declarative memory, reduced interhemispheric inhibition and more symmetric cortical activation during motor performance in normal aging

The influence of visual target information on the online control of movements

International audienceThe continuously changing properties of our environment require constant monitoring of our actions and updating of our motor commands based on the task goals. Such updating relies upon our predictions about the sensory consequences of our movement commands, as well as sensory feedback received during movement execution. Here we focus on how visual information about target location is used to update and guide ongoing actions so that the task goal is successfully achieved. We review several studies that have manipulated vision of the target in a variety of ways, ranging from complete removal of visual target information to changes in visual target properties after movement onset to examine how such changes are accounted for during motor execution. We also examined the specific role of a critical neural structure, the parietal cortex, and argue that a fundamental challenge for the future is to understand how visual information about target location is integrated with other streams of information, during movement execution, to estimate the state of the body and the environment in order to ensure optimal motor performance. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/)

Error detection is critical for visual-motor corrections

The target article (Smeets, Oostwoud Wijdenes, & Brenner, 2016) proposes that short latency responses to changes in target location during reaching reflect an unconscious, continuous, and incremental minimization of the distance between the hand and the target, which does not require detection of the change in target location. We, instead, propose that short-latency visuomotor responses invoke reflex- or startle-like mechanisms, an idea supported by evidence that such responses are both automatic and resistant to cognitive influences. In addition, the target article fails to address the biological underpinnings for the range of response latencies reported across the literature, including the circuits that might underlie the proposed sensorimotor loops. When considering the range of latencies reported in the literature, we propose that mechanisms grounded in neurophysiology should be more informative than the simple information processing perspective adopted by the target article.by Robert L. Sainburg and Pratik K. Muth

Cognitive aspects of motor control

by Pratik K. Mutha and Kathleen Y. Haalan

Selective suppression of adaptation to motor errors irrelevant to task success

by Pratik Mutha, Neeraj Kumar, and Nishant Ra

Effects of normal aging on online and offline bimanual motor sequence learning

by Sampada Gharpure et.a