RESUMEN
Temporal interference (TI) stimulation is a popular non-invasive neurostimulation technique that utilizes the following salient neural behavior: pure sinusoid (generated in off-target brain regions) appears to cause no stimulation, whereas modulated sinusoid (generated in target brain regions) does. To understand its effects and mechanisms, we examine responses of different cell types, excitatory pyramidal (Pyr) and inhibitory parvalbumin-expressing (PV) neurons, to pure and modulated sinusoids, in intact network as well as in isolation. In intact network, we present data showing that PV neurons are much less likely than Pyr neurons to exhibit TI stimulation. Remarkably, in isolation, our data shows that almost all Pyr neurons stop exhibiting TI stimulation. We conclude that TI stimulation is largely a network phenomenon. Indeed, PV neurons actively inhibit Pyr neurons in the off-target regions due to pure sinusoids (in off-target regions) generating much higher PV firing rates than modulated sinusoids in the target regions. Additionally, we use computational studies to support and extend our experimental observations.
Asunto(s)
Neuronas , Animales , Ratones , Neuronas/fisiología , Potenciales de Acción , Células Piramidales/fisiología , Corteza Cerebral/fisiología , Parvalbúminas/metabolismo , Masculino , Modelos NeurológicosRESUMEN
OBJECTIVE: Using data-driven methods to design stimuli (e.g., electrical currents) which evoke desired neural responses in different neuron-types for applications in treating neural disorders. METHODS: The problem of stimulus design is formulated as estimating the inverse of a many-to-one non-linear "forward" mapping, which takes as input the parameters of waveform and outputs the corresponding neural response, directly from the data. A novel optimization framework "PATHFINDER" is proposed in order to estimate the previously mentioned inverse mapping. A comparison with existing data-driven methods, namely conditional density estimation methods and numerical inversion of an estimated forward mapping is performed with different dataset sizes in toy examples and in detailed computational models of biological neurons. RESULTS: Using data from toy examples, as well as computational models of biological neurons, we show that PATHFINDER can outperform existing methods when the number of samples is low (i.e., a few hundred). SIGNIFICANCE: Traditionally, the design of such stimuli has been model-driven and/or uses simplistic intuition, often aided by trial-and-error. Due to the inherent challenges in accurately modeling neural responses, as well as the sophistication of stimuli's effect on neural membrane potentials, data-driven approaches offer an attractive alternative. Our results suggest that PATHFINDER can be applied for optimizing stimulation parameters in experiments and treatments of neural disorders due to it requiring low number of data points.
Asunto(s)
Algoritmos , Neuronas , Neuronas/fisiología , Potenciales de Acción/fisiología , Potenciales de la MembranaRESUMEN
Transcranial electrical neuromodulation of the central nervous system is used as a non-invasive method to induce neural and behavioral responses, yet targeted non-invasive electrical stimulation of the brain with high spatial resolution remains elusive. This work demonstrates a focused, steerable, high-density epicranial current stimulation (HD-ECS) approach to evoke neural activity. Custom-designed high-density (HD) flexible surface electrode arrays are employed to apply high-resolution pulsed electric currents through skull to achieve localized stimulation of the intact mouse brain. The stimulation pattern is steered in real time without physical movement of the electrodes. Steerability and focality are validated at the behavioral, physiological, and cellular levels using motor evoked potentials (MEPs), intracortical recording, and c-fos immunostaining. Whisker movement is also demonstrated to further corroborate the selectivity and steerability. Safety characterization confirmed no significant tissue damage following repetitive stimulation. This method can be used to design novel therapeutics and implement next-generation brain interfaces.
Asunto(s)
Encéfalo , Potenciales Evocados Motores , Ratones , Animales , Encéfalo/fisiología , Electrodos , Estimulación Eléctrica , Potenciales Evocados Motores/fisiología , Músculo EsqueléticoRESUMEN
Transcranial Electrical Stimulation (TES) is a promising tool for treating many neurological disorders, but it classically results in diffused stimulation. Many optimization algorithms have been proposed for focusing TES, commonly by creating multi-electrode arrangements and choosing current amplitudes such that the resulting current fields in the brain are focused in the target region, and are as small as possible outside the target region. Consequently, it is likely that such optimization does not harness the non-linear nature of neural dynamics, particularly their thresholding phenomenon, i.e., the observation that neurons fire only when the stimulating currents are above a certain threshold. In this work, we propose HingePlace which explicitly harnesses this thresholding phenomenon by designing multi-electrode arrangements which allow the electric fields outside the target region to be non-zero but still below the stimulation threshold. In idealized simulated models, we compare HingePlace with existing algorithms and find that HingePlace performs strictly better, in some cases providing ~20% reduction in stimulated area for a specified limit on maximum injected current.
Asunto(s)
Estimulación Transcraneal de Corriente Directa , Algoritmos , Encéfalo , Electrodos , NeuronasRESUMEN
Objective.When currents are injected into the scalp, e.g. during transcranial current stimulation, the resulting currents generated in the brain are substantially affected by the changes in conductivity and geometry of intermediate tissue. In this work, we introduce the concept of 'skull-transparent' currents, for which the changing conductivity does not significantly alter the field while propagating through the head.Approach.We establish transfer functions relating scalp currents to head potentials in accepted simplified models of the head, and find approximations for which skull-transparency holds. The current fields resulting from specified current patterns are calculated in multiple head models, including MRI heads and compared with homogeneous heads to characterize the transparency. Experimental validation is performed by measuring the current field in head phantoms.Main results.The main theoretical result is derived from observing that at high spatial frequencies, in the transfer function relating currents injected into the scalp to potential generated inside the head, the conductivity terms form a multiplicative factor and do not otherwise influence the transfer function. This observation is utilized to design injected current waveforms that maintain nearly identical focusing patterns independently of the changes in skull conductivity and thickness for a wide range of conductivity and thickness values in an idealized spherical head model as well as in a realistic MRI-based head model. Experimental measurements of the current field in an agar-based head phantom confirm the transparency of these patterns.Significance.Our results suggest the possibility that well-chosen patterns of current injection result in precise focusing inside the brain even withouta prioriknowledge of exact conductivities of intermediate layers.