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Biology subjects

Weber, F.

Publications and source records attributed to Weber, F..

2 recordsLinked to original sources

Variable training but not sleep improves consolidation of motor adaptation

How motor memory consolidates still remains elusive. Motor tasks consolidation were shown to depend on periods of sleep, whereas pure non-hippocampal dependent tasks, like motor adaptation, might not. Some research suggests that the mode of training might affect the sleep dependency of motor adaptation tasks. Here we investigated whether sleep differentially impacts memory consolidation dependent on the variability during training. Healthy men were trained with their dominant, right hand on a force field adaptation task and re-tested after an 11-h consolidation period either involving overnight sleep (Sleep) or daytime wakefulness (Wake). Retesting also included a transfer to the non-dominant hand. Half of the subjects in each group adapted to different force field magnitudes with low inter-trial variability (Sleep-Blocked; Wake-Blocked), the other half with high variability (Sleep-Random; Wake-Random). EEG was recorded during task execution and overnight polysomnography. Motor adaptation was comparable between Wake and Sleep groups, although performance changes over sleep correlated with sleep spindles nesting in slow wave upstates. Higher training variability improved retest, including transfer learning, and these improvements correlated with higher alpha power in contralateral parietal areas. Enhanced consolidation after training might foster the ability to correct ongoing movements by responsive feedback rather than their pre-execution prediction.

neuroscience

Two C++ Libraries for Counting Trees on a Phylogenetic Terrace

MotivationThe presence of terraces in phylogenetic tree space, that is, a potentially large number of distinct tree topologies that have exactly the same analytical likelihood score, was first described by Sanderson et al, (2011). However, popular software tools for maximum likelihood and Bayesian phylogenetic inference do not yet routinely report, if inferred phylogenies reside on a terrace, or not. We believe, this is due to the unavailability of an efficient library implementation to (i) determine if a tree resides on a terrace, (ii) calculate how many trees reside on a terrace, and (iii) enumerate all trees on a terrace.\n\nResultsIn our bioinformatics programming practical we developed two efficient and independent C++ implementations of the SUPERB algorithm by Constantinescu and Sankoff (1995) for counting and enumerating the trees on a terrace. Both implementations yield exactly the same results and are more than one order of magnitude faster and require one order of magnitude less memory than a previous 3rd party python implementation.\n\nAvailabilityThe source codes are available under GNU GPL at https://github.com/terraphast\n\nContactAlexandros.Stamatakis@h-its.org

evolutionary biology