RESUMEN
Spinal motor neurons and the peripheral muscle fibers they innervate form discrete motor units that execute movements of varying force and speed. Subsets of spinal motor neurons also exhibit axon collaterals that influence motor output centrally. Here, we have used in vivo imaging to anatomically characterize the central and peripheral innervation patterns of axial motor units in larval zebrafish. Using early born "primary" motor neurons and their division of epaxial and hypaxial muscle into four distinct quadrants as a reference, we define three distinct types of later born "secondary" motor units. The largest is "m-type" units, which innervate deeper fast-twitch muscle fibers via medial nerves. Next in size are "ms-type" secondaries, which innervate superficial fast-twitch and slow fibers via medial and septal nerves, followed by "s-type" units, which exclusively innervate superficial slow muscle fibers via septal nerves. All types of secondaries innervate up to four axial quadrants. Central axon collaterals are found in subsets of primaries based on soma position and predominantly in secondary fast-twitch units (m, ms) with increasing likelihood based on number of quadrants innervated. Collaterals are labeled by synaptophysin-tagged fluorescent proteins, but not PSD95, consistent with their output function. Also, PSD95 dendrite labeling reveals that larger motor units receive more excitatory synaptic input. Collaterals are largely restricted to the neuropil, however, perisomatic connections are observed between motor units. These observations suggest that recurrent interactions are dominated by motor neurons recruited during stronger movements and set the stage for functional investigations of recurrent motor circuitry in larval zebrafish.
Asunto(s)
Neuronas Motoras/citología , Músculo Esquelético/inervación , Animales , Larva , Pez CebraRESUMEN
OBJECTIVE: The Cognition Battery of the National Institutes of Heath Toolbox is a commonly utilized set of assessments of neuropsychological abilities, evaluating executive function, attention, working memory, processing speed, and episodic memory. We highlight the utility of an advanced statistical model in providing nuanced characterization of neurocognition in an adolescent population. We propose that partially ordered set (POSET) models are well suited to analyze polyfactorial tasks and identify distinct profiles of cognitive functioning. METHOD: Two models were considered using POSET classification. The first modeled 5 distinct cognitive functions and allowed for multiple functions to contribute to task performance. The second simpler model involved only 2 broader-based functions without polyfactorial task specifications. Existing performance data from 745 adolescents aged 14-17 years were analyzed. Posterior probabilities of classification performance and the discriminatory properties of the estimated response distributions indicated how well the modeling approaches fit the data. RESULTS: The larger first model resulted in 8 profiles or states characterized by combinations of high or low functioning in 5 distinct functions. The simpler second model involved 2 broader-based functions that resulted in 4 states. Comparing model fit criteria, we believe that the finer-grained first model may better reflect the cognitive constructs associated with the tasks. Notably, POSET modeling did not always provide adequate classification of working memory because of the limited design of the Cognition Battery. CONCLUSIONS: We demonstrate that the use of POSET models is a feasible approach for detailed analysis of neurocognitive data that can extract information on cognitive functions, even when provided with limited task batteries. (PsycINFO Database Record (c) 2019 APA, all rights reserved).