Biology subjects

Giszter, S. F.

Publications and source records attributed to Giszter, S. F..

3 recordsLinked to original sources

bioRxiv2024

Covert actions of epidural stimulation on spinal locomotor circuits

Spinal circuitry produces the rhythm and patterning of locomotion. However, both descending and sensory inputs are required to initiate and adapt locomotion to the environment. Spinal cord injury (SCI) disrupts descending controls of the spinal cord, producing paralysis. Epidural stimulation (ES) is a promising clinical therapy for motor control recovery and is capable of reactivating the lumbar spinal locomotor networks, yet little is known about the effects of ES on locomotor neurons. Previously, we found that both sensory afferent pathways and serotonin exert mixed excitatory and inhibitory actions on lumbar interneurons involved in the generation of the locomotor rhythm, identified by the transcription factor Shox2. However, after chronic complete SCI, sensory afferent inputs to Shox2 interneurons become almost exclusively excitatory and Shox2 interneurons are supersensitive to serotonin. Here, we investigated the effects of ES on these SCI-induced changes. Inhibitory input from sensory pathways to Shox2 interneurons was maintained and serotonin supersensitivity was not observed in SCI mice that received daily sub-motor threshold ES. Interestingly, the effects of ES were maintained for at least three weeks after the ES was discontinued. In contrast, the effects of ES were not observed in Shox2 interneurons from mice that received ES after the establishment of the SCI-induced changes. Our results demonstrate mechanistic actions of ES at the level of identified spinal locomotor circuit neurons and the effectiveness of early treatment with ES on preservation of spinal locomotor circuitry after SCI, suggesting possible therapeutic benefits prior to the onset of motor rehabilitation.

neuroscience↗

bioRxiv2024

A Stochastic Dynamic Operator framework that improves the precision of analysis and prediction relative to the classical spike-triggered average method, extending the toolkit.

Here we test the Stochastic Dynamic Operator (SDO) as a new framework for describing physiological signal dynamics relative to spiking or stimulus events. The SDO is a natural extension of existing spike-triggered averaging (STA), or stimulus-triggered averaging, methods currently used in neural analysis. It extends the classic STA to cover state-dependent and probabilistic responses where STA may fail. SDO methods are more sensitive and specific than the STA for identifying state-dependent relationships in simulated data. We have tested SDO analysis for interactions between electrophysiological recordings of spinal interneurons, single motor units, and aggregate muscle electromyograms (EMG) of major muscles in the spinal frog hindlimb. When predicting target signal behavior relative to spiking events, the SDO framework outperformed or matched classical spike-triggered averaging methods. SDO analysis permits more complicated spike-signal relationships to be captured, analyzed, and interpreted visually and intuitively. SDO methods can be applied at different scales of interest where spike-triggered averaging methods are currently employed, and beyond, from single neurons to gross motor behaviors. SDOs may be readily generated and analyzed using the provided SDO Analysis Toolkit. We anticipate this method will be broadly useful for describing dynamical signal behavior and uncovering state-dependent relationships of stochastic signals relative to discrete event times. SIGNIFICANCEHere the authors introduce new tools and demonstrate data analysis using a new probabilistic and state-dependent technique, which is an expansion and extension of the classical spike-triggered average, the Stochastic Dynamic Operator. Stochastic Dynamic Operator methods extend application into domains where classical spike triggered averages fail, capture more information on spike correlations, and match or outperform the spike-triggered average when generating predictions of signal amplitude based on spiking events. A data and code package toolkit for utilizing and interpreting Stochastic Dynamic Operator methods is provided together with example analyses. Both the method and the associated toolkit are thus expected to be broadly useful in research domains where the spike triggered average is currently used for analysis, and beyond.

neuroscience↗

bioRxiv2024

Activity of spinal RORβ neurons is related to functional improvements following combination treatment after complete SCI

Various strategies targeting spinal locomotor circuitry have been associated with functional improvements after spinal cord injury (SCI). However, the neuronal populations mediating beneficial effects remain largely unknown. In a mouse model of complete SCI, virally-delivered BDNF (AAV-BDNF) activates hindlimb stepping and causes hyperreflexia, whereas sub-motor threshold epidural stimulation (ES) reduced BDNF-induced hyperreflexia. Given their role in gating proprioceptive afferents and potential convergence point of BDNF and ES, we hypothesized that an enhanced excitability of inhibitory ROR{beta} neurons would be associated with locomotor improvements. Ex vivo spinal slice recordings revealed that the excitability of ROR{beta} neurons was decreased in mice with poor locomotor function after SCI, but was similar between the uninjured and best stepping SCI groups. Further, chemogenetic excitation of ROR{beta} neurons reduced BDNF-induced hyperreflexia and improved stepping, similar to ES. Our findings identify inhibitory ROR{beta} neurons as a target population to limit hyperreflexia and enhance locomotor function after SCI.

neuroscience↗