Response of human thalamic neurons to high-frequency stimulation

Computational modeling of frequency-dependent neocortical response to thalamic neurostimulation in epilepsy

The therapeutic application of centromedian nucleus stimulation (CMS) has been limited by uncertainties regarding its mechanism of action. In this study, we used stereoelectro-encephalography (SEEG) signals recorded from a patient with refractory epilepsy, caused by focal cortical dysplasia, which is a malformation of cortical development. SEEG recordings revealed that neocortical interictal discharges could be suppressed by CMS. These effects were found to be frequency-dependent: while 50 Hz CMS induced no change in neocortical epileptiform activity, CMS at 70 Hz, 100 Hz and 150 Hz led to periods of suppression of neocortical epileptiform activity. These periods were shown to have different durations depending on the stimulation protocol. We developed a neurophysiologically-plausible thalamocortical model to explain these observations. This model included glutamatergic subpopulations and GABAergic subpopulations in the neocortical and the thalamic compartments. Synaptic inhibition and short-term plasticity mechanisms were integrated into the latter compartment. We hypothesized that the enhanced activation of thalamic inhibitory subpopulations during high frequency CMS (>70Hz) would result in GABA spillover which activated synaptic GABAergic receptors on the thalamocortical relay cells. This decreased the thalamic driving-input to the neocortex, hence suppressing interictal discharges in the dysplastic neocortical tissue. While inhibition of thalamocortical relay cells was maximal for CMS at 70 Hz and 100 Hz, this was not the case for 150 Hz CMS, suggesting that presynaptic GABAergic receptors were activated and that the rate of GABA reuptake was increased. Thus, our model suggests that the transient suppression of the neocortical epileptic activity with CMS may be primarily due to extra-synaptic tonic inhibition in the thalamocortical relay cells. These findings contribute to a deeper understanding of high-frequency CMS in epilepsy and pave the way for further research and optimization of this therapeutic approach.

Microscale multicircuit brain stimulation: Achieving real-time brain state control for novel applications

Neurological and psychiatric disorders typically result from dysfunction across multiple neural circuits. Most of these disorders lack a satisfactory neuromodulation treatment. However, deep brain stimulation (DBS) has been successful in a limited number of disorders; DBS typically targets one or two brain areas with single contacts on relatively large electrodes, allowing for only coarse modulation of circuit function. Because of the dysfunction in distributed neural circuits - each requiring fine, tailored modulation - that characterizes most neuropsychiatric disorders, this approach holds limited promise. To develop the next generation of neuromodulation therapies, we will have to achieve fine-grained, closed-loop control over multiple neural circuits. Recent work has demonstrated spatial and frequency selectivity using microstimulation with many small, closely-spaced contacts, mimicking endogenous neural dynamics. Using custom electrode design and stimulation parameters, it should be possible to achieve bidirectional control over behavioral outcomes, such as increasing or decreasing arousal during central thalamic stimulation. Here, we discuss one possible approach, which we term microscale multicircuit brain stimulation (MMBS). We discuss how machine learning leverages behavioral and neural data to find optimal stimulation parameters across multiple contacts, to drive the brain towards desired states associated with behavioral goals. We expound a mathematical framework for MMBS, where behavioral and neural responses adjust the model in real-time, allowing us to adjust stimulation in real-time. These technologies will be critical to the development of the next generation of neurostimulation therapies, which will allow us to treat problems like disorders of consciousness and cognition.

Neuron matters: neuromodulation with electromagnetic stimulation must consider neurons as dynamic identities

Neuromodulation with electromagnetic stimulation is widely used for the control of abnormal neural activity, and has been proven to be a valuable alternative to pharmacological tools for the treatment of many neurological diseases. Tremendous efforts have been focused on the design of the stimulation apparatus (i.e., electrodes and magnetic coils) that delivers the electric current to the neural tissue, and the optimization of the stimulation parameters. Less attention has been given to the complicated, dynamic properties of the neurons, and their context-dependent impact on the stimulation effects. This review focuses on the neuronal factors that influence the outcomes of electromagnetic stimulation in neuromodulation. Evidence from multiple levels (tissue, cellular, and single ion channel) are reviewed. Properties of the neural elements and their dynamic changes play a significant role in the outcome of electromagnetic stimulation. This angle of understanding yields a comprehensive perspective of neural activity during electrical neuromodulation, and provides insights in the design and development of novel stimulation technology.

Temporal interference stimulation targets deep brain regions by modulating neural oscillations

BACKGROUND

Temporal interference (TI) stimulation of the brain generates amplitude-modulated electric fields oscillating in the kHz range with the goal of non-invasive targeted deep brain stimulation. Yet, the current intensities required in human (sensitivity) to modulate deep brain activity and if superficial brain region are spared (selectivity) at these intensities remains unclear.

OBJECTIVE

We developed an experimentally constrained theory for TI sensitivity to kHz electric field given the attenuation by membrane low-pass filtering property, and for TI selectivity to deep structures given the distribution of modulated and unmodulated electric fields in brain.

METHODS

The electric field threshold to modulate carbachol-induced gamma oscillations in rat hippocampal slices was determined for unmodulated 0.05-2 kHz sine waveforms, and 5 Hz amplitude-modulated waveforms with 0.1-2 kHz carrier frequencies. The neuronal effects are replicated with a computational network model to explore the underlying mechanisms, and then coupled to a validated current-flow model of the human head.

RESULTS

Amplitude-modulated electric fields are stronger in deep brain regions, while unmodulated electric fields are maximal at the cortical regions. Both experiment and model confirmed the hypothesis that spatial selectivity of temporal interference stimulation depends on the phasic modulation of neural oscillations only in deep brain regions. Adaptation mechanism (e.g. GABA_b) enhanced sensitivity to amplitude modulated waveform in contrast to unmodulated kHz and produced selectivity in modulating gamma oscillation (i.e. Higher gamma modulation in amplitude modulated vs unmodulated kHz stimulation). Selection of carrier frequency strongly affected sensitivity to amplitude modulation stimulation. Amplitude modulated stimulation with 100 Hz carrier frequency required ∼5 V/m (corresponding to ∼13 mA at the scalp surface), whereas, 1 kHz carrier frequency ∼60 V/m (∼160 mA) and 2 kHz carrier frequency ∼80 V/m (∼220 mA) to significantly modulate gamma oscillation. Sensitivity is increased (scalp current required decreased) for theoretical neuronal membranes with faster time constants.

CONCLUSION

The TI sensitivity (current required at the scalp) depends on the neuronal membrane time-constant (e.g. axons) approaching the kHz carrier frequency. TI selectivity is governed by network adaption (e.g. GABA_b) that is faster than the amplitude-modulation frequency. Thus, we show neuronal and network oscillations time-constants determine the scalp current required and the selectivity achievable with TI in humans.

Physiological mechanisms of thalamic ventral intermediate nucleus stimulation for tremor suppression

Ventral intermediate thalamic deep brain stimulation is a standard therapy for the treatment of medically refractory essential tremor and tremor-dominant Parkinson's disease. Despite the therapeutic benefits, the mechanisms of action are varied and complex, and the pathophysiology and genesis of tremor remain unsubstantiated. This intraoperative study investigated the effects of high frequency microstimulation on both neuronal firing and tremor suppression simultaneously. In each of nine essential tremor and two Parkinson's disease patients who underwent stereotactic neurosurgery, two closely spaced (600 µm) microelectrodes were advanced into the ventral intermediate nucleus. One microelectrode recorded action potential firing while the adjacent electrode delivered stimulation trains at 100 Hz and 200 Hz (2-5 s, 100 µA, 150 µs). A triaxial accelerometer was used to measure postural tremor of the contralateral hand. At 200 Hz, stimulation led to 68 ± 8% (P < 0.001) inhibition of neuronal firing and a 53 ± 5% (P < 0.001) reduction in tremor, while 100 Hz reduced firing by 26 ± 12% (not significant) with a 17 ± 6% (P < 0.05) tremor reduction. The degree of cell inhibition and tremor suppression were significantly correlated (P < 0.001). We also found that the most ventroposterior stimulation sites, closest to the border of the ventral caudal nucleus, had the best effect on tremor. Finally, prior to the inhibition of neuronal firing, microstimulation caused a transient driving of neuronal activity at stimulus onset (61% of sites), which gave rise to a tremor phase reset (73% of these sites). This was likely due to activation of the excitatory glutamatergic cortical and cerebellar afferents to the ventral intermediate nucleus. Temporal characteristics of the driving responses (duration, number of spikes, and onset latency) significantly differed between 100 Hz and 200 Hz stimulation trains. The subsequent inhibition of neuronal activity was likely due to synaptic fatigue. Thalamic neuronal inhibition seems necessary for tremor reduction and may function in effect as a thalamic filter to uncouple thalamo-cortical from cortico-spinal reflex loops. Additionally, our findings shed light on the gating properties of the ventral intermediate nucleus within the cerebello-thalamo-cortical tremor network, provide insight for the optimization of deep brain stimulation technologies, and may inform controlled clinical studies for assessing optimal target locations for the treatment of tremor.

Rebound or Entrainment? The Influence of Alternating Current Stimulation on Individual Alpha

Alternating current stimulation (ACS) is an established means to manipulate intrinsic cortical oscillations. While working towards clinical impact, ACS mechanisms of action remain unclear. For ACS’s well-documented influence on occipital alpha, hypotheses include neuronal entrainment as well as rebound phenomena. As a retinal origin is also discussed, we employed a novel form of ACS with the advantage that it specifically targets occipital alpha-oscillations via retinofugal pathways retinofugal ACS (rACS). We aimed to confirm alpha-enhancement outlasting the duration of stimulation with 10 Hz rACS. To distinguish entrainment from rebound effects, we investigated the correlation between alpha peak frequency change and alpha-enhancement strength. We quantified the alpha band power before and after 10 Hz rACS in 15 healthy subjects. Alpha power enhancement and alpha peak frequency change were assessed over the occipital electrodes and compared to sham stimulation. RACS significantly enhanced occipital alpha power in comparison to sham stimulation (p < 0.05). Alpha peak frequency changed by a mean 0.02 Hz (± 0.04). A greater change in alpha peak frequency did not correlate with greater effects on alpha power. Our findings show an alpha-enhancement consistent with studies conducted for transcranial ACS (tACS) and contribute evidence for a retinal involvement in tACS effects on occipital alpha. Furthermore, the lack of correlation between alpha peak frequency change and alpha-enhancement strength provides an argument against entrainment effects and in favor of a rebound phenomenon.

A Computational Model of Deep-Brain Stimulation for Acquired Dystonia in Children

The mechanism by which deep brain stimulation (DBS) improves dystonia is not understood, partly heterogeneity of the underlying disorders leads to differing effects of stimulation in different locations. Similarity between the effects of DBS and the effects of lesions has led to biophysical models of blockade or reduced transmission of involuntary activity in individual cells in the pathways responsible for dystonia. Here, we expand these theories by modeling the effect of DBS on populations of neurons. We emphasize the important observation that the DBS signal itself causes surprisingly few side effects and does not normally appear in the electromyographic signal. We hypothesize that, at the population level, massively synchronous rhythmic firing caused by DBS is only poorly transmitted through downstream populations. However, the high frequency of stimulation overwhelms incoming dystonic activity, thereby substituting an ineffectively transmitted exogenous signal for the endogenous abnormal signal. Changes in sensitivity can occur not only at the site of stimulation, but also at downstream sites due to synaptic and homeostatic plasticity mechanisms. The mechanism is predicted to depend strongly on the stimulation frequency. We provide preliminary data from simultaneous multichannel recordings in basal ganglia and thalamus in children with secondary dystonia. We also provide illustrative simulations of the effect of stimulation frequency on the transmission of the DBS pulses through sequential populations of neurons in the dystonia pathway. Our experimental results and model provide a new hypothesis and computational framework consistent with the clinical features of DBS in childhood acquired dystonia.

Deep brain stimulation induces sparse distributions of locally modulated neuronal activity

Deep brain stimulation (DBS) therapy is a potent tool for treating a range of brain disorders. High frequency stimulation (HFS) patterns used in DBS therapy are known to modulate neuronal spike rates and patterns in the stimulated nucleus; however, the spatial distribution of these modulated responses are not well understood. Computational models suggest that HFS modulates a volume of tissue spatially concentrated around the active electrode. Here, we tested this theory by investigating modulation of spike rates and patterns in non-human primate motor thalamus while stimulating the cerebellar-receiving area of motor thalamus, the primary DBS target for treating Essential Tremor. HFS inhibited spike activity in the majority of recorded cells, but increasing stimulation amplitude also shifted the response to a greater degree of spike pattern modulation. Modulated responses in both categories exhibited a sparse and long-range spatial distribution within motor thalamus, suggesting that stimulation preferentially affects afferent and efferent axonal processes traversing near the active electrode and that the resulting modulated volume strongly depends on the local connectome of these axonal processes. Such findings have important implications for current clinical efforts building predictive computational models of DBS therapy, developing directional DBS lead technology, and formulating closed-loop DBS strategies.

Neurophysiology and neural engineering: a review

Neurophysiology is the branch of physiology concerned with understanding the function of neural systems. Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties and functions of neural systems. In most cases neural engineering involves the development of an interface between electronic devices and living neural tissue. This review describes the origins of neural engineering, the explosive development of methods and devices commencing in the late 1950s, and the present-day devices that have resulted. The barriers to interfacing electronic devices with living neural tissues are many and varied, and consequently there have been numerous stops and starts along the way. Representative examples are discussed. None of this could have happened without a basic understanding of the relevant neurophysiology. I also consider examples of how neural engineering is repaying the debt to basic neurophysiology with new knowledge and insight.

Single-unit analysis of the human posterior hypothalamus and red nucleus during deep brain stimulation for aggressivity

OBJECTIVE

Deep brain stimulation (DBS) of the posterior hypothalamus (PH) has been reported to be effective for aggressive behavior in a number of isolated cases. Few of these case studies have analyzed single-unit recordings in the human PH and none have quantitatively analyzed single units in the red nucleus (RN). The authors report on the properties of ongoing neuronal discharges in bilateral trajectories targeting the PH and the effectiveness of DBS of the PH as a treatment for aggressive behavior.

METHODS

DBS electrodes were surgically implanted in the PH of 1 awake patient with Sotos syndrome and 3 other anesthetized patients with treatment-resistant aggressivity. Intraoperative extracellular recordings were obtained from the ventral thalamus, PH, and RN and analyzed offline to discriminate single units and measure firing rates and firing patterns. Target location was based on the stereotactic coordinates used by Sano et al. in their 1970 study and the location of the dorsal border of the RN.

RESULTS

A total of 138 units were analyzed from the 4 patients. Most of the PH units had a slow, irregular discharge (mean [± SD] 4.5 ± 2.7 Hz, n = 68) but some units also had a higher discharge rate (16.7 ± 4.7 Hz, n = 15). Two populations of neurons were observed in the ventral thalamic region as well, one with a high firing rate (mean 16.5 ± 6.5 Hz, n = 5) and one with a low firing rate (mean 4.6 ± 2.8 Hz, n = 6). RN units had a regular firing rate with a mean of 20.4 ± 9.9 Hz and displayed periods of oscillatory activity in the beta range. PH units displayed a prolonged period of inhibition following microstimulation compared with RN units that were not inhibited. Patients under anesthesia showed a trend for lower firing rates in the PH but not in the RN. All 4 patients displayed a reduction in their aggressive behavior after surgery.

CONCLUSIONS

During PH DBS, microelectrode recordings can provide an additional mechanism to help identify the PH target and surrounding structures to be avoided such as the RN. PH units can be distinguished from ventral thalamic units based on their response to focal microstimulation. The RN has a characteristic higher firing rate and a pattern of beta oscillations in the spike trains. The effect of the anesthetic administered should be considered when using microelectrode recordings. The results of this study, along with previous reports, suggest that PH DBS may be an effective treatment for aggression.

Computational modeling to improve treatments for essential tremor

Essential tremor (ET) is a neurological disorder of unknown etiology that is typically characterized by an involuntary periodic movement of the upper limbs. No longer considered monosymptomatic, ET patients often have additional motor and even cognitive impairments. Although there are several pharmacological treatments, no drugs have been developed specifically for ET [1], and 30-70% of patients are medication-refractory [2]. A subset of medication-refractory patients may benefit from electrical deep brain stimulation (DBS) of the ventral intermediate nucleus of the thalamus (VIM), which receives cerebellar inputs. Abnormal cerebellar input to VIM is presumed to be a major contributor to tremor symptoms, which is alleviated by DBS. Computational modeling of the effects of DBS in VIM has been a powerful tool to design DBS protocols to reduce tremor activity. However, far less is known about how these therapies affect non-tremor symptoms, and more experimental and computational modeling work is required to address these growing considerations. Models capable of addressing multiple facets of ET will lead to novel, more efficient treatment.

The midbrain central gray best suppresses chronic pain with electrical stimulation at very low pulse rates in two human cases

Deep brain stimulation in the midbrain׳s central gray can relieve neuropathic pain in man, but for unclear reasons sometimes fails intraoperatively or in early weeks. Here we describe continuous bilateral stimulation in the central gray of two subjects with longstanding, severe neuropathic pain from spinal cord injury. Stimulation parameters were recursively adjusted over many weeks to optimize analgesia while minimizing adverse effects. In early weeks, adjustments were made in periodic office visits; subjects later selected ad libitum at home among several blinded choices while rating pain twice daily. Both subjects received significantly better pain relief when stimulus pulse rates were low. The best relief occurred with 2 Hz cycled on for 1s and off for 2s. After inferior parameters were set, pain typically climbed slowly over 1-2 days; superior parameters led to both slow and fast improvements. Over many weeks of stimulation at low pulse rates, both subjects experienced significantly less interference from pain with sleep. One subject, with major pain relief, also showed less interference with social/recreational ability and mood; the other subject, despite minor pain relief, experienced a significantly positive global impression of change. Oscillopsia, the only observed complication of stimulation, disappeared at low mean pulse rates (≤ 3/s). These subjects׳ responses are not likely to be unique even if they are uncommon. Thus daily or more frequent pain assessment, combined with slower periodic adjustment of stimulation parameters that incorporate mean pulse rates about one per second, will likely improve success with this treatment.