144 research outputs found
Autism and Computer Assisted Learning
Autism is a learning and social disorder that has seen increased diagnosis within school-age populations. As educators grapple with overwhelmed and understaffed classrooms, finding ways to address the educational needs of this particular population can be very challenging. However, technology may serve to create alternative “virtual” world opportunities and thus, begin to expand learning possibilities for these students
McNair Research Journal - Summer 2015
Journal articles based on research conducted by undergraduate students in the McNair Scholars Program
Table of Contents
Biography of Dr. Ronald E. McNair
Statements:
Dr. Neal J. Smatresk, UNLV President
Dr. Juanita P. Fain, Vice President of Student Affairs
Dr. William W. Sullivan, Associate Vice President for Retention and Outreach
Mr. Keith Rogers, Deputy Executive Director of the Center for Academic Enrichment and Outreach
McNair Scholars Institute Staf
Short Term Synaptic Depression Imposes a Frequency Dependent Filter on Synaptic Information Transfer
Depletion of synaptic neurotransmitter vesicles induces a form of short term depression in synapses throughout the nervous system. This plasticity affects how synapses filter presynaptic spike trains. The filtering properties of short term depression are often studied using a deterministic synapse model that predicts the mean synaptic response to a presynaptic spike train, but ignores variability introduced by the probabilistic nature of vesicle release and stochasticity in synaptic recovery time. We show that this additional variability has important consequences for the synaptic filtering of presynaptic information. In particular, a synapse model with stochastic vesicle dynamics suppresses information encoded at lower frequencies more than information encoded at higher frequencies, while a model that ignores this stochasticity transfers information encoded at any frequency equally well. This distinction between the two models persists even when large numbers of synaptic contacts are considered. Our study provides strong evidence that the stochastic nature neurotransmitter vesicle dynamics must be considered when analyzing the information flow across a synapse
Biomaterial bridges enable regeneration and re-entry of corticospinal tract axons into the caudal spinal cord after SCI: Association with recovery of forelimb function
Severed axon tracts fail to exhibit robust or spontaneous regeneration after spinal cord injury (SCI). Regeneration failure reflects a combination of factors, including the growth state of neuronal cell bodies and the regeneration-inhibitory environment of the central nervous system. However, while spared circuitry can be retrained, target reinnervation depends on longitudinally directed regeneration of transected axons. This study describes a biodegradable implant using poly(lactideco-glycolide) (PLG) bridges as a carrier scaffold to support regeneration after injury. In order to detect regeneration of descending neuronal tracts into the bridge, and beyond into intact caudal parenchyma, we developed a mouse cervical implantation model and employed Crym:GFP transgenic mice. Characterization of Crym:GFP mice revealed that descending tracts, including the corticospinal tract, were labeled by green fluorescent protein (GFP), while ascending sensory neurons and fibers were not. Robust co-localization between GFP and neurofilament-200 (NF-200) as well as GFP and GAP-43 was observed at both the rostral and caudal bridge/tissue interface. No evidence of similar regeneration was observed in mice that received gelfoam at the lesion site as controls. Minimal co-localization between GFP reporter labeling and macrophage markers was observed. Taken together, these data suggest that axons originating from descending fiber tracts regenerated, entered into the PLG bridge at the rostral margin, continued through the bridge site, and exited to re-enter host tissue at the caudal edge of the intact bridge. Finally, regeneration through implanted bridges was associated with a reduction in ipsilateral forelimb errors on a horizontal ladder task
Population, resources, and environment: Implications of human behavioral ecology for conservation
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43481/1/11111_2005_Article_BF02207996.pd
25th annual computational neuroscience meeting: CNS-2016
The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong
25th Annual Computational Neuroscience Meeting: CNS-2016
Abstracts of the 25th Annual Computational Neuroscience
Meeting: CNS-2016
Seogwipo City, Jeju-do, South Korea. 2–7 July 201
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