Biology subjects

Hayward, W.

Publications and source records attributed to Hayward, W..

2 recordsLinked to original sources

bioRxiv2024

Cingulate and striatal hubs are linked to early skill learning

Early skill learning develops in the context of activity changes in distributed cortico-subcortical regions. Here, we investigated network hubs--centers of information integration and transmission--within the brain network supporting early skill learning. We recorded magnetoencephalographic (MEG) brain activity in healthy human subjects who learned a moderately difficult sequence skill with their non-dominant left hand. We then computed network hub strength by summing top 10% functional connectivity over 86 parcellated brain regions (AAL3 atlas) and five brain oscillatory frequency bands (alpha, low-, high-beta, low- and high-gamma). Virtually all skill gains developed during rest intervals of early learning (micro-offline gains). MEG hub strength in the alpha band (8-13Hz) in bilateral anterior cingulate (ACC) and caudate and in the low-beta band (13-16Hz) in bilateral caudate and right putamen correlated with micro-offline gains. These regions linked strongly with the hippocampus, parahippocampal cortex, and lingual and fusiform gyri. Thus, alpha and low-beta brain oscillatory activity in cingulate and striatal regions appear to contribute as hubs of information integration and transmission during early skill learning. Significance StatementEarly learning of moderately difficult skill sequences develops over periods of rest interspersed with practice (micro-offline gains). We demonstrate here a link between alpha and low-beta oscillatory activity in a cingulate-hippocampo-striato network hubs and rest intervals of early learning.

neuroscience↗

bioRxiv2024

Sequence action representations contextualize during rapid skill learning

Activities of daily living rely on our ability to acquire new motor skills composed of precise action sequences. Here, we asked if the millisecond-level neural representation of an action performed at different contextual sequence locations within a skill differentiates or remains stable during early motor learning. We first optimized machine learning decoders predictive of sequence-embedded finger movements from magnetoencephalographic (MEG) activity. Using this approach, we found that the neural representation of the same action performed in different contextual sequence locations, progressively differentiated--primarily during rest intervals of early learning (offline)--correlating with skill gains. In contrast, representational differentiation during practice (online) did not reflect learning. The regions contributing to this representational differentiation evolved with learning, shifting from the contralateral pre- and post-central cortex during early learning (trials 1-11) to increased involvement of the superior and middle frontal cortex once skill performance plateaued (trials 12-36). Thus, the neural substrates supporting finger movements and their representational differentiation during early skill learning differ from those supporting stable performance during the subsequent skill plateau period. Representational contextualization extended to Day 2, exhibiting specificity for the practiced skill sequence. Altogether, our findings indicate that sequence action representations contextually differentiate during early skill learning, an issue relevant to brain-computer interface applications in neurorehabilitation.

neuroscience↗