Case Studies in Neuroscience: an epidural stimulating interface unveils the intrinsic modulation of electrically motor evoked potentials in behaving rats.

In intact and spinal injured anesthetized animals, stimulation levels that did not induce any visible muscle twitches, were used to elicit motor evoked potentials (MEPs) of varying amplitude, reflecting the temporal and amplitude dynamics of the background excitability of spinal networks. To characterize the physiological excitability states of neuronal networks driving movement, we designed five experiments in awake rats chronically implanted with an epidural stimulating interface, with and without a spinal cord injury (SCI). Firstly, an uninjured rat at rest underwent a series of single electrical pulses at sub motor-threshold intensity, which generated responses that were continuously recorded from flexor and extensor hindlimb muscles, showing an intrinsic patterned modulation of MEPs. Responses were recruited by increasing strengths of stimulation and the amplitudes were moderately correlated between flexors and extensors. Next, after SCI, four awake rats at rest showed electrically induced MEPs, varying largely in amplitude of both flexors and extensors that were mainly synchronously modulated. After full anesthesia, MEP amplitudes were largely reduced, although stimulation still generated random baseline changes, unveiling an intrinsic stochastic modulation. The current five cases demonstrate a methodology that can be feasibly replicated in a broader group of awake and behaving rats to further define experimental treatments involving neuroplasticity. Beside validating a new technology for a neural stimulating interface, the present data support the broader message that there were intrinsic patterned and stochastic modulation of baseline excitability reflecting the dynamics of physiological states of spinal networks.

Targeted comodulation supports flexible and accurate decoding in V1

Sensory-guided behavior requires reliable encoding of stimulus information in neural responses, and task-specific decoding through selective combination of these responses. The former has been the topic of intensive study, but the latter remains largely a mystery. We propose a framework in which shared stochastic modulation of task-informative neurons serves as a label to facilitate downstream decoding. Theoretical analysis and computational simulations demonstrate that a decoder that exploits such a signal can achieve flexible and accurate readout. Using this theoretical framework, we analyze behavioral and physiological data obtained from monkeys performing a visual orientation discrimination task. The responses of recorded V1 neurons exhibit strongly correlated modulation. This modulation is stronger in those neurons that are most informative for the behavioral task and it is substantially reduced in a control condition where recorded neurons are uninformative. We demonstrate that this modulator label can be used to improve downstream decoding within a small number of training trials, consistent with observed behavior. Finally, we find that the trial-by-trial modulatory signal estimated from V1 populations is also present in the activity of simultaneously recorded MT units, and preferentially so if they are task-informative, supporting the hypothesis that it serves as a label for the selection and decoding of relevant downstream neurons.

An adaptive algorithm for restoring image corrupted by mixed noise

In this work, numerical results of a nonlinear switching system that presents bistable attractors subjected to stochastic modulation are shown. The system exhibits a dynamical modification of the bistable attractor, giving rise to an intermit behavior, which depends of modulation strength. The resulting attractor converge to an intermittent double-scroll, for low amplitude modulation, and a 9-scroll attractor for a higher applied noise amplitude. A Detrended Fluctuation Analysis (DFA) applied to the x state variable, shows a perturbations robustness region, since the increase of noise does not present changes. Due to the applied noise, the final obtained system has higher randomness, compared with the original one. The understanding of the dynamical behavior of multiscrolls systems is highly important for advancing technology in communications, as well in memory systems applications.

Effect of stochastic modulation of inter-pulse interval during stimulated isokinetic leg extension

Recumbent cycling exercise achieved by functional electrical stimulation (FES) of the paralyzed leg muscles is effective for cardiopulmonary and musculoskeletal conditioning after spinal cord injury, but its full potential has not yet been realized. Mechanical power output and efficiency is very low and endurance is limited due to early onset of muscle fatigue. The aim of this work was to compare stochastic modulation of the inter-pulse interval (IPI) to constant-frequency stimulation during an isokinetic leg extension task similar to FES-cycling. Seven able-bodied subjects participated: both quadriceps muscles were stimulated (n = 14) with two activation patterns (P1-constant frequency, P2-stochastic IPI). There was significantly higher power output with P2 during the first 30 s (p = 0.0092), the last 30 s (p = 0.018) and overall (p = 0.0057), but there was no overall effect on fatiguability when stimulation frequency was randomly modulated.