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Ghavampour, A.

Publications and source records attributed to Ghavampour, A..

3 recordsLinked to original sources

Encoding of bimanual movement directions across the human sensorimotor system

Bimanual coordination requires the control of each hand to account for movements of the other hand. To enable such coordination, it has been hypothesized that the brain has a representation of bimanual movements that supersedes a linear combination of the unimanual movements. To test for such a representation, we mapped the encoding of movement direction during unimanual and bimanual wrist movements in the human brain using functional magnetic resonance imaging (fMRI). For unimanual movements, we found that both the contralateral and ipsilateral movement directions were represented across most cortical motor regions. The representations were similar for mirror-symmetric movements across the hands, revealing an intrinsic (body-centric) code in premotor and parietal regions. For bimanual movements, the neural representations of movement directions could be explained by three components. First, the contralateral movement direction was represented as in the unimanual condition, whereas the representation of the ipsilateral movement direction disappeared. Second, in higher-order regions (rostral premotor and posterior parietal cortex) we found relatively elevated activity when the two movements were directed in unrelated directions. This activity was likely caused by the extra effort to deal with incongruent spatial targets across the hands. Third, and independent of this congruency effect, we found a non-linear interaction between contra- and ipsilateral movement that encoded the specific bimanual movement combination across sensorimotor, premotor, and parietal regions. This representation was suited to facilitate bimanual coordination and learning.

neuroscience↗

A paradigm to study the learning of muscle activity patterns outside of the natural repertoire

The acquisition of novel muscle activity patterns is a key aspect of motor skill learning which can be seen at play, for example, when beginner musicians learn new guitar or piano chords. To study this process, here we introduce a new paradigm that requires quick and synchronous flexion and extension of multiple fingers. First, participants practiced all the 242 possible combinations of isometric finger flexion and extension around the metacarpophalangeal joint (i.e., chords). We found that some chords were initially extremely challenging, but participants could eventually achieve them with practice, showing that the initial difficulty did not reflect hard biomechanical constraints imposed by the interaction of tendons and ligaments. In a second experiment we found that chord learning was largely chord-specific and did not generalize to untrained chords. Finally, we explored which factors make some chords more difficult than others. Difficulty was well predicted by the muscle activity pattern required by that chord. Interestingly, difficulty related to how similar chords muscle activity patterns are to the muscle activity patterns required by everyday hand use, and to the overall size of the muscle activity. Together, our results suggest that the new paradigm introduced in this work may provide a valuable tool to study the neural processes underlying the acquisition of novel muscle activity patterns in the human motor system.

neuroscience↗

Prefrontal Cortex Encodes Value Pop-out in Visual Search

Recent evidence shows that long-term object value association can lead to efficient visual search. However, the neural mechanism of this value pop-out has yet to be understood. Given the known role of the ventrolateral prefrontal cortex (vlPFC) in visual search and value memory, we recorded its single-unit activity (n=526) in two macaque monkeys while they engaged in the value-driven search. Monkeys had to determine whether a high-value target was present within a variable number of low-value objects. Interestingly, differential neural firing, as well as gamma-band power, indicated the presence of a target within [~]150ms of display onset. This differential activity was negatively correlated with search time and became less display size-dependent for more efficient searches. On the other hand, neural firing and its variability were higher in inefficient searches. These findings reveal the neural code within vlPFC for rapid detection of valuable targets, which can be crucial for animals faced with competition. Significance StatementSearch for rewarding objects is ubiquitous and crucial for animals and humans alike. Up until recently, it was thought that visual search for valuable targets that were otherwise not distinct by low-level features should be serial and slow. Contrary to this belief, we showed that given sufficient reward training, valuable objects can be found efficiently in search suggesting a value pop-out neural mechanism. Importantly, we reveal the neural activity in the prefrontal cortex (PFC) to be predictive of the degree of value-driven search efficiency. Given the role of PFC in object value memory, these results show how PFC can translate such memories to emulate the parallel processing of visual information independent of low-level visual features.

neuroscience↗