Frequency dependence of behavioral modulation by hippocampal electrical stimulation

Principal dynamic mode analysis of neural mass model for the identification of epileptic states

The detection of epileptic seizures in Electroencephalography (EEG) signals is significant for the diagnosis and treatment of epilepsy. In this paper, in order to obtain characteristics of various epileptiform EEGs that may differentiate different states of epilepsy, the concept of Principal Dynamic Modes (PDMs) was incorporated to an autoregressive model framework. First, the neural mass model was used to simulate the required intracerebral EEG signals of various epileptiform activities. Then, the PDMs estimated from the nonlinear autoregressive Volterra models, as well as the corresponding Associated Nonlinear Functions (ANFs), were used for the modeling of epileptic EEGs. The efficient PDM modeling approach provided physiological interpretation of the system. Results revealed that the ANFs of the 1st and 2nd PDMs for the auto-regressive input exhibited evident differences among different states of epilepsy, where the ANFs of the sustained spikes' activity encountered at seizure onset or during a seizure were the most differentiable from that of the normal state. Therefore, the ANFs may be characteristics for the classification of normal and seizure states in the clinical detection of seizures and thus provide assistance for the diagnosis of epilepsy.

Two Distinct Stimulus Frequencies Delivered Simultaneously at Low Intensity Generate Robust Locomotor Patterns

OBJECTIVES

Explore the primary characteristics of afferent noisy stimuli, which optimally activate locomotor patterns at low intensity.

MATERIALS AND METHODS

Intracellular and extracellular electrophysiological traces were derived from single motoneurons and from ventral roots, respectively. From these recordings, we obtained noisy stimulating protocols, delivered to a dorsal root (DR) of an isolated neonatal rat spinal cord, while recording fictive locomotion (FL) from ventral roots.

RESULTS

We decreased complexity of efficient noisy stimulating protocols down to single cell spikes. Then, we identified four main components within the power spectrum of these signals and used them to construct a basic multifrequency protocol of rectangular impulses, able to induce FL. Further disassembling generated the minimum stimulation paradigm that activated FL, which consisted of a pair of 35 and 172 Hz frequency pulse trains, strongly effective at low intensity when delivered either jointly to one lumbosacral DR or as single simultaneous trains to two distinct DRs. This simplified pulse schedule always activated a locomotor rhythm, even when delivered for a very short time (500 ms). One prerequisite for the two-frequency protocol to activate FL at low intensity when applied to sacrocaudal afferents was the ability to induce ascending volleys of greater amplitude.

CONCLUSION

Multifrequency protocols can support future studies in defining the most effective characteristics for electrical stimulation to reactivate stepping following motor injury.

Modeling sequence and quasi-uniform assumption in computational neurostimulation

Computational neurostimulation aims to develop mathematical constructs that link the application of neuromodulation with changes in behavior and cognition. This process is critical but daunting for technical challenges and scientific unknowns. The overarching goal of this review is to address how this complex task can be made tractable. We describe a framework of sequential modeling steps to achieve this: (1) current flow models, (2) cell polarization models, (3) network and information processing models, and (4) models of the neuroscientific correlates of behavior. Each step is explained with a specific emphasis on the assumptions underpinning underlying sequential implementation. We explain the further implementation of the quasi-uniform assumption to overcome technical limitations and unknowns. We specifically focus on examples in electrical stimulation, such as transcranial direct current stimulation. Our approach and conclusions are broadly applied to immediate and ongoing efforts to deploy computational neurostimulation.

Invasive neurostimulation in stroke rehabilitation

The last decade has seen a growing interest in adjuvant treatments that synergistically influence mechanisms underlying rehabilitation of paretic upper limb in stroke. One such approach is invasive neurostimulation of spared cortices at the periphery of a lesion. Studies in animals have shown that during training of paretic limb, adjuvant stimulation targeting the peri-infarct circuitry enhances mechanisms of its reorganization, generating functional advantage. Success of early animal studies and clinical reports, however, failed to translate to a phase III clinical trial. As lesions in humans are diffuse, unlike many animal models, peri-infarct circuitry may not be a feasible, or consistent target across most. Instead, alternate mechanisms, such as changing transcallosal inhibition between hemispheres, or reorganization of other viable regions in motor control, may hold greater potential. Here, we review comprehensive mechanisms of clinical recovery and factors that govern which mechanism(s) become operative when. We suggest novel approaches that take into account a patient's initial clinical-functional state, and findings from neuroimaging and neurophysiology to guide to their most suitable mechanism for ideal targeting. Further, we suggest new localization schemes, and bypass strategies that indirectly target peri-lesional circuitry, and methods that serve to counter technical and theoretical challenge in identifying and stimulating such targets at the periphery of infarcts in humans. Last, we describe how stimulation may modulate mechanisms differentially across varying phases of recovery- a temporal effect that may explain missed advantage in clinical trials and help plan for the next stage. With information presented here, future trials would effectively be able to target patient's specific mechanism(s) with invasive (or noninvasive) neurostimulation for the greatest, most consistent benefit.

Age-related weakness of proximal muscle studied with motor cortical mapping: a TMS study

Aging-related weakness is due in part to degeneration within the central nervous system. However, it is unknown how changes to the representation of corticospinal output in the primary motor cortex (M1) relate to such weakness. Transcranial magnetic stimulation (TMS) is a noninvasive method of cortical stimulation that can map representation of corticospinal output devoted to a muscle. Using TMS, we examined age-related alterations in maps devoted to biceps brachii muscle to determine whether they predicted its age-induced weakness. Forty-seven right-handed subjects participated: 20 young (22.6±0.90 years) and 27 old (74.96±1.35 years). We measured strength as force of elbow flexion and electromyographic activation of biceps brachii during maximum voluntary contraction. Mapping variables included: 1) center of gravity or weighted mean location of corticospinal output, 2) size of map, 3) volume or excitation of corticospinal output, and 4) response density or corticospinal excitation per unit area. Center of gravity was more anterior in old than in young (p<0.001), though there was no significant difference in strength between the age groups. Map size, volume, and response density showed no significant difference between groups. Regardless of age, center of gravity significantly predicted strength (β = −0.34, p = 0.005), while volume adjacent to the core of map predicted voluntary activation of biceps (β = 0.32, p = 0.008). Overall, the anterior shift of the map in older adults may reflect an adaptive change that allowed for the maintenance of strength. Laterally located center of gravity and higher excitation in the region adjacent to the core in weaker individuals could reflect compensatory recruitment of synergistic muscles. Thus, our study substantiates the role of M1 in adapting to aging-related weakness and subtending strength and muscle activation across age groups. Mapping from M1 may offer foundation for an examination of mechanisms that preserve strength in elderly.