Biology subjects

Kordjazi, N.

Publications and source records attributed to Kordjazi, N..

2 recordsLinked to original sources

bioRxiv2020

The planning horizon for movement sequences

When performing a long chain of actions in rapid sequence, future movements need to be planned concurrently with ongoing action. However, how far ahead we plan, and whether this ability improves with practice, is currently unknown. Here we designed an experiment in which healthy volunteers produced sequences of 14 finger presses quickly and accurately on a keyboard in response to numerical stimuli. On every trial, participants were only shown a fixed number of stimuli ahead of the current keypress. The size of this viewing window varied between 1 (next digit revealed with the pressing of the current key) and 14 (full view of the sequence). Participants practiced the task for five days and their performance was continuously assessed on random sequences. Our results indicate that participants used the available visual information to plan multiple actions into the future, but that the planning horizon was limited: receiving information about more than 3 movements ahead did not result in faster sequence production. Over the course of practice, we found larger performance improvements for larger viewing windows and an expansion of the planning horizon. These findings suggest that the ability to plan future responses during ongoing movement constitutes an important aspect of skillful movement. Based on the results, we propose a framework to investigate the neuronal processes underlying simultaneous planning and execution. Significance StatementAlthough skill learning has typically focused on the training of specific movement sequences, practice improves performance even for random sequences. Here we hypothesize that a fundamental aspect of skilled sequential behavior is the ability to plan multiple actions into the future, both before and during execution. By controlling the amount of visual information available for motor planning, we show that people plan at least three movements beyond current action and that this planning horizon expands with practice. Our findings suggest that coordinating ongoing movement and planning of future actions is an essential component of skilled sequential behavior and offer testable predictions for the neural implementation of online motor planning.

neuroscience↗

bioRxiv2017

Enhancing the Representational Similarity Between Execution and Imagination of Movement Using Network-Based Brain Computer Interfacing

Motor imagery-based brain computer interfacing (MI-BCI) as a neuro-rehabilitation tool aims at facilitating motor improvement using mental practice. However, the effectiveness of MI-BCI in producing clinically meaningful functional outcome is debated. Aside from computational shortcomings, a main limiting obstacle seems to be the substantial representational dissimilarity between movement imagination (MI) and movement execution (ME) on the level of engaged neural networks. This dissimilarity renders inducing functionally effective and long lasting changes in motor behavior through MI challenging. Moreover, the quality and intensity of imagination is highly prone to change on a trial-to-trial basis, based on the subject's state of mind and mental fatigue. This leads to an inconsistent profile of neural activity throughout training, limiting learning in a Hebbian sense. To address these issues, we propose a neuroconnectivity-based paradigm, as a systematic priming technique to be utilized pre-BCI training. In the proposed paradigm, ME-idle representational dissimilarity network (RDN) features are used to detect MI in real-time. This means that to drive the virtual environment, an ME-like activation pattern has to be learned and generated in the brain through MI. This contrasts with conventional BCIs which consider a successful MI, one that results in higher than a threshold change in the power of sensorimotor rhythms. Our results show that four out of five participants achieved a consistent session-to-session enhancement in their net MI-ME network-level similarity (mean change rate of 6.16% {+/-} 4.64 per session). We suggest that the proposed paradigm, if utilized as a priming technique pre-BCI training, can potentially enhance the neural and functional effectiveness. This can be achieved through 1- shifting MI towards engaging ME-related networks to a higher extent, and 2- inducing consistency in MI quality by using the ME-related networks as the ground-truth and thus enhancing the robustness of the activity pattern in the brain. This would in turn lend to the clinical acceptability of BCI as a neurorehabilitation tool.

bioinformatics↗