Axonal and synaptic failure suppress the transfer of firing rate oscillations, synchrony and information during high frequency deep brain stimulation

A Computational Study on the Activation of Neural Transmission in Deep Brain Stimulation

Deep brain stimulation (DBS) is an established treatment for neurodegenerative movement disorders such as Parkinson's disease that mitigates symptoms by overwriting pathological signals from the central nervous system to the motor system. Nearly all computational models of DBS, directly or indirectly, associate clinical improvements with the extent of fiber activation in the vicinity of the stimulating electrode. However, it is not clear how such activation modulates information transmission. Here, we use the exact cable equation for straight or curved axons and show that DBS segregates the signaling pathways into one of the three communicational modes: complete information blockage, uni-, and bi-directional transmission. Furthermore, all these modes respond to the stimulating pulse in an asynchronous but frequency-locked fashion. Asynchrony depends on the geometry of the axon, its placement and orientation, and the stimulation protocol. At the same time, the electrophysiology of the nerve determines frequency-locking. Such a trimodal response challenges the notion of activation as a binary state and studies that correlate it with the DBS outcome. Importantly, our work suggests that a mechanistic understanding of DBS action relies on distinguishing between these three modes of information transmission.

The mechanisms of electrical neuromodulation

The central and peripheral nervous systems are specialized to conduct electrical currents that underlie behaviour. When this multidimensional electrical system is disrupted by degeneration, damage, or disuse, externally applied electrical currents may act to modulate neural structures and provide therapeutic benefit. The administration of electrical stimulation can exert precise and multi-faceted effects at cellular, circuit and systems levels to restore or enhance the functionality of the central nervous system by providing an access route to target specific cells, fibres of passage, neurotransmitter systems, and/or afferent/efferent communication to enable positive changes in behaviour. Here we examine the neural mechanisms that are thought to underlie the therapeutic effects seen with current neuromodulation technologies. To gain further insights into the mechanisms associated with electrical stimulation, we summarize recent findings from genetic dissection studies conducted in animal models. KEY POINTS: Electricity is everywhere around us and is essential for how our nerves communicate within our bodies. When nerves are damaged or not working properly, using exogenous electricity can help improve their function at distinct levels - inside individual cells, within neural circuits, and across entire systems. This method can be tailored to target specific types of cells, nerve fibres, neurotransmitters and communication pathways, offering significant therapeutic potential. This overview explains how exogenous electricity affects nerve function and its potential benefits, based on research in animal studies. Understanding these effects is important because electrical neuromodulation plays a key role in medical treatments for neurological conditions.

Effects and mechanisms of anterior thalamus nucleus deep brain stimulation for epilepsy: A scoping review of preclinical studies

Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is a safe and effective intervention for the treatment of certain forms of epilepsy. In preclinical models, electrical stimulation of the ANT has antiepileptogenic effects but its underlying mechanisms remain unclear. In this review, we searched multiple databases for studies that described the effects and mechanisms of ANT low or high frequency stimulation (LFS or HFS) in models of epilepsy. Out of 289 articles identified, 83 were pooled for analysis and 34 were included. Overall, ANT DBS was most commonly delivered at high frequency to rodents injected with kainic acid, pilocarpine, or pentylenetetrazole. In most studies, this therapy increased the latency to the first spontaneous seizure and reduced the frequency of seizures by 20%-80%. Electrophysiology data suggested that DBS reduces the severity of electrographic seizures, decreases the duration and increases the threshold of afterdischarges, reduces the power of low-frequency and increase the power high-frequency bands. Mechanistic studies revealed that ANT DBS leads to a series of short- and long-term changes at multiple levels. Some of its anticonvulsant effects were proposed to occur via the modulation of serotonergic and adenosinergic transmission. The latter seems to be derived from the downregulation of adenosine kinase (ADK). ANT DBS was also shown to increase hippocampal levels of lactate, alter the expression of genes involved in calcium signaling, synaptic glutamate, and the NOD-like receptor signaling pathway. When delivered during status epilepticus or following the injection of convulsant agents, DBS was found to reduce the expression of proinflammatory cytokines and apoptosis. When administered chronically, ANT DBS increased the expression of proteins involved in axonal guidance, changed functional connectivity in limbic circuits, and increased the number of hippocampal cells in epileptic animals, suggesting a neuroprotective effect.

Evoked resonant neural activity long-term dynamics can be reproduced by a computational model with vesicle depletion

Subthalamic deep brain stimulation (DBS) robustly generates high-frequency oscillations known as evoked resonant neural activity (ERNA). Recently the importance of ERNA has been demonstrated through its ability to predict the optimal DBS contact in the subthalamic nucleus in patients with Parkinson's disease. However, the underlying mechanisms of ERNA are not well understood, and previous modelling efforts have not managed to reproduce the wealth of published data describing the dynamics of ERNA. Here, we aim to present a minimal model capable of reproducing the characteristics of the slow ERNA dynamics published to date. We make biophysically-motivated modifications to the Kuramoto model and fit its parameters to the slow dynamics of ERNA obtained from data. Our results demonstrate that it is possible to reproduce the slow dynamics of ERNA (over hundreds of seconds) with a single neuronal population, and, crucially, with vesicle depletion as one of the key mechanisms behind the ERNA frequency decay in our model. We further validate the proposed model against experimental data from Parkinson's disease patients, where it captures the variations in ERNA frequency and amplitude in response to variable stimulation frequency, amplitude, and to stimulation pulse bursting. We provide a series of predictions from the model that could be the subject of future studies for further validation.

Nonlinear analysis of neuronal firing modulated by sinusoidal stimulation at axons in rat hippocampus

Introduction

Electrical stimulation of the brain has shown promising prospects in treating various brain diseases. Although biphasic pulse stimulation remains the predominant clinical approach, there has been increasing interest in exploring alternative stimulation waveforms, such as sinusoidal stimulation, to improve the effectiveness of brain stimulation and to expand its application to a wider range of brain disorders. Despite this growing attention, the effects of sinusoidal stimulation on neurons, especially on their nonlinear firing characteristics, remains unclear.

Methods

To address the question, 50 Hz sinusoidal stimulation was applied on Schaffer collaterals of the rat hippocampal CA1 region in vivo. Single unit activity of both pyramidal cells and interneurons in the downstream CA1 region was recorded and analyzed. Two fractal indexes, namely the Fano factor and Hurst exponent, were used to evaluate changes in the long-range correlations, a manifestation of nonlinear dynamics, in spike sequences of neuronal firing.

Results

The results demonstrate that sinusoidal electrical stimulation increased the firing rates of both pyramidal cells and interneurons, as well as altered their firing to stimulation-related patterns. Importantly, the sinusoidal stimulation increased, rather than decreased the scaling exponents of both Fano factor and Hurst exponent, indicating an increase in the long-range correlations of both pyramidal cells and interneurons.

Discussion

The results firstly reported that periodic sinusoidal stimulation without long-range correlations can increase the long-range correlations of neurons in the downstream post-synaptic area. These results provide new nonlinear mechanisms of brain sinusoidal stimulation and facilitate the development of new stimulation modes.

A neurocomputational view of the effects of Parkinson's disease on speech production

The purpose of this article is to review the scientific literature concerning speech in Parkinson's disease (PD) with reference to the DIVA/GODIVA neurocomputational modeling framework. Within this theoretical view, the basal ganglia (BG) contribute to several different aspects of speech motor learning and execution. First, the BG are posited to play a role in the initiation and scaling of speech movements. Within the DIVA/GODIVA framework, initiation and scaling are carried out by initiation map nodes in the supplementary motor area acting in concert with the BG. Reduced support of the initiation map from the BG in PD would result in reduced movement intensity as well as susceptibility to early termination of movement. A second proposed role concerns the learning of common speech sequences, such as phoneme sequences comprising words; this view receives support from the animal literature as well as studies identifying speech sequence learning deficits in PD. Third, the BG may play a role in the temporary buffering and sequencing of longer speech utterances such as phrases during conversational speech. Although the literature does not support a critical role for the BG in representing sequence order (since incorrectly ordered speech is not characteristic of PD), the BG are posited to contribute to the scaling of individual movements in the sequence, including increasing movement intensity for emphatic stress on key words. Therapeutic interventions for PD have inconsistent effects on speech. In contrast to dopaminergic treatments, which typically either leave speech unchanged or lead to minor improvements, deep brain stimulation (DBS) can degrade speech in some cases and improve it in others. However, cases of degradation may be due to unintended stimulation of efferent motor projections to the speech articulators. Findings of spared speech after bilateral pallidotomy appear to indicate that any role played by the BG in adult speech must be supplementary rather than mandatory, with the sequential order of well-learned sequences apparently represented elsewhere (e.g., in cortico-cortical projections).

Targeting papez circuit for cognitive dysfunction- insights into deep brain stimulation for Alzheimer's disease

Hippocampus is the most widely studied brain area coupled with impairment of memory in a variety of neurological diseases and Alzheimer's disease (AD). The limbic structures within the Papez circuit have been linked to various aspects of cognition. Unfortunately, the brain regions that include this memory circuit are often ignored in terms of understanding cognitive decline in these diseases. To properly comprehend where cognition problems originate, it is crucial to clarify any aberrant contributions from all components of a specific circuit -on both a local and a global level. The pharmacological treatments currently available are not long lasting. Deep Brain Stimulation (DBS) emerged as a new powerful therapeutic approach for alleviation of the cognitive dysfunctions. Metabolic, functional, electrophysiological, and imaging studies helped to find out the crucial nodes that can be accessible for DBS. Targeting these nodes within the memory circuit produced significant improvement in learning and memory by disrupting abnormal circuit activity and restoring the physiological network. Here, we provide an overview of the neuroanatomy of the circuit of Papez along with the mechanisms and various deep brain stimulation targets of the circuit structures which could be significant for improving cognitive dysfunctions in AD.

Model-based closed-loop control of thalamic deep brain stimulation

Introduction: Closed-loop control of deep brain stimulation (DBS) is beneficial for effective and automatic treatment of various neurological disorders like Parkinson's disease (PD) and essential tremor (ET). Manual (open-loop) DBS programming solely based on clinical observations relies on neurologists' expertise and patients' experience. Continuous stimulation in open-loop DBS may decrease battery life and cause side effects. On the contrary, a closed-loop DBS system uses a feedback biomarker/signal to track worsening (or improving) of patients' symptoms and offers several advantages compared to the open-loop DBS system. Existing closed-loop DBS control systems do not incorporate physiological mechanisms underlying DBS or symptoms, e.g., how DBS modulates dynamics of synaptic plasticity. Methods: In this work, we propose a computational framework for development of a model-based DBS controller where a neural model can describe the relationship between DBS and neural activity and a polynomial-based approximation can estimate the relationship between neural and behavioral activities. A controller is used in our model in a quasi-real-time manner to find DBS patterns that significantly reduce the worsening of symptoms. By using the proposed computational framework, these DBS patterns can be tested clinically by predicting the effect of DBS before delivering it to the patient. We applied this framework to the problem of finding optimal DBS frequencies for essential tremor given electromyography (EMG) recordings solely. Building on our recent network model of ventral intermediate nuclei (Vim), the main surgical target of the tremor, in response to DBS, we developed neural model simulation in which physiological mechanisms underlying Vim-DBS are linked to symptomatic changes in EMG signals. By using a proportional-integral-derivative (PID) controller, we showed that a closed-loop system can track EMG signals and adjust the stimulation frequency of Vim-DBS so that the power of EMG reaches a desired control target. Results and discussion: We demonstrated that the model-based DBS frequency aligns well with that used in clinical studies. Our model-based closed-loop system is adaptable to different control targets and can potentially be used for different diseases and personalized systems.

Modeling Instantaneous Firing Rate of Deep Brain Stimulation Target Neuronal Ensembles in the Basal Ganglia and Thalamus

OBJECTIVE

Deep brain stimulation (DBS) is an effective treatment for movement disorders, including Parkinson disease and essential tremor. However, the underlying mechanisms of DBS remain elusive. Despite the capability of existing models in interpreting experimental data qualitatively, there are very few unified computational models that quantitatively capture the dynamics of the neuronal activity of varying stimulated nuclei-including subthalamic nucleus (STN), substantia nigra pars reticulata (SNr), and ventral intermediate nucleus (Vim)-across different DBS frequencies.

MATERIALS AND METHODS

Both synthetic and experimental data were used in the model fitting; the synthetic data were generated by an established spiking neuron model that was reported in our previous work, and the experimental data were provided using single-unit microelectrode recordings (MERs) during DBS (microelectrode stimulation). Based on these data, we developed a novel mathematical model to represent the firing rate of neurons receiving DBS, including neurons in STN, SNr, and Vim-across different DBS frequencies. In our model, the DBS pulses were filtered through a synapse model and a nonlinear transfer function to formulate the firing rate variability. For each DBS-targeted nucleus, we fitted a single set of optimal model parameters consistent across varying DBS frequencies.

RESULTS

Our model accurately reproduced the firing rates observed and calculated from both synthetic and experimental data. The optimal model parameters were consistent across different DBS frequencies.

CONCLUSIONS

The result of our model fitting was in agreement with experimental single-unit MER data during DBS. Reproducing neuronal firing rates of different nuclei of the basal ganglia and thalamus during DBS can be helpful to further understand the mechanisms of DBS and to potentially optimize stimulation parameters based on their actual effects on neuronal activity.

POTENTIATION OF CORTICO-SPINAL OUTPUT VIA TARGETED ELECTRICAL STIMULATION OF THE MOTOR THALAMUS

Cerebral white matter lesions prevent cortico-spinal descending inputs from effectively activating spinal motoneurons, leading to loss of motor control. However, in most cases, the damage to cortico-spinal axons is incomplete offering a potential target for new therapies aimed at improving volitional muscle activation. Here we hypothesized that, by engaging direct excitatory connections to cortico-spinal motoneurons, stimulation of the motor thalamus could facilitate activation of surviving cortico-spinal fibers thereby potentiating motor output. To test this hypothesis, we identified optimal thalamic targets and stimulation parameters that enhanced upper-limb motor evoked potentials and grip forces in anesthetized monkeys. This potentiation persisted after white matter lesions. We replicated these results in humans during intra-operative testing. We then designed a stimulation protocol that immediately improved voluntary grip force control in a patient with a chronic white matter lesion. Our results show that electrical stimulation targeting surviving neural pathways can improve motor control after white matter lesions.

Neurophysiological mechanisms of deep brain stimulation across spatiotemporal resolutions

Deep brain stimulation is a neuromodulatory treatment for managing the symptoms of Parkinson's disease and other neurological and psychiatric disorders. Electrodes are chronically implanted in disease-relevant brain regions and pulsatile electrical stimulation delivery is intended to restore neurocircuit function. However, the widespread interest in the application and expansion of this clinical therapy has preceded an overarching understanding of the neurocircuit alterations invoked by deep brain stimulation. Over the years, various forms of neurophysiological evidence have emerged which demonstrate changes to brain activity across spatiotemporal resolutions; from single neuron, to local field potential, to brain-wide cortical network effects. Though fruitful, such studies have often led to debate about a singular putative mechanism. In this Update we aim to produce an integrative account of complementary instead of mutually exclusive neurophysiological effects to derive a generalizable concept of the mechanisms of deep brain stimulation. In particular, we offer a critical review of the most common historical competing theories, an updated discussion on recent literature from animal and human neurophysiological studies, and a synthesis of synaptic and network effects of deep brain stimulation across scales of observation, including micro-, meso- and macroscale circuit alterations.

The Therapeutic Frequency Profile of Subthalamic Nucleus Deep Brain Stimulation in Rats Is Shaped by Antidromic Spike Failure

The therapeutic mechanisms of subthalamic nucleus (STN) deep brain stimulation (DBS) may depend on antidromic activation of cortex via the hyperdirect pathway. However, hyperdirect pathway neurons cannot reliably follow high-stimulation frequencies, and the spike failure rate appears to correlate with symptom relief as a function of stimulation frequency. We hypothesized that antidromic spike failure contributes to the cortical desynchronization caused by DBS. We measured in vivo evoked cortical activity in female Sprague Dawley rats and developed a computational model of cortical activation from STN DBS. We modeled stochastic antidromic spike failure to determine how spike failure affected the desynchronization of pathophysiological oscillatory activity in cortex. We found that high-frequency STN DBS desynchronized pathologic oscillations via the masking of intrinsic spiking through a combination of spike collision, refractoriness, and synaptic depletion. Antidromic spike failure shaped the parabolic relationship between DBS frequency and cortical desynchronization, with maximum desynchronization at ∼130 Hz. These findings reveal that antidromic spike failure plays a critical role in mediating the dependency of symptom relief on stimulation frequency.SIGNIFICANCE STATEMENT Deep brain stimulation (DBS) is a highly effective neuromodulation therapy, yet it remains uncertain why conventionally used stimulation frequencies (e.g., ∼130 Hz) are optimal. In this study, we demonstrate a potential explanation for the stimulation frequency dependency of DBS through a combination of in vivo experimental measurements and computational modeling. We show that high-frequency stimulation can desynchronize pathologic firing patterns in populations of neurons by inducing an informational lesion. However, sporadic spike failure at these high frequencies limits the efficacy of the informational lesion, yielding a parabolic profile with optimal effects at ∼130 Hz. This work provides a potential explanation for the therapeutic mechanism of DBS, and highlights the importance of considering spike failure in mechanistic models of DBS.

Alternative patterns of deep brain stimulation in neurologic and neuropsychiatric disorders

Deep brain stimulation (DBS) is a widely used clinical therapy that modulates neuronal firing in subcortical structures, eliciting downstream network effects. Its effectiveness is determined by electrode geometry and location as well as adjustable stimulation parameters including pulse width, interstimulus interval, frequency, and amplitude. These parameters are often determined empirically during clinical or intraoperative programming and can be altered to an almost unlimited number of combinations. Conventional high-frequency stimulation uses a continuous high-frequency square-wave pulse (typically 130-160 Hz), but other stimulation patterns may prove efficacious, such as continuous or bursting theta-frequencies, variable frequencies, and coordinated reset stimulation. Here we summarize the current landscape and potential clinical applications for novel stimulation patterns.

Decoupling of interacting neuronal populations by time-shifted stimulation through spike-timing-dependent plasticity

The synaptic organization of the brain is constantly modified by activity-dependent synaptic plasticity. In several neurological disorders, abnormal neuronal activity and pathological synaptic connectivity may significantly impair normal brain function. Reorganization of neuronal circuits by therapeutic stimulation has the potential to restore normal brain dynamics. Increasing evidence suggests that the temporal stimulation pattern crucially determines the long-lasting therapeutic effects of stimulation. Here, we tested whether a specific pattern of brain stimulation can enable the suppression of pathologically strong inter-population synaptic connectivity through spike-timing-dependent plasticity (STDP). More specifically, we tested how introducing a time shift between stimuli delivered to two interacting populations of neurons can effectively decouple them. To that end, we first used a tractable model, i.e., two bidirectionally coupled leaky integrate-and-fire (LIF) neurons, to theoretically analyze the optimal range of stimulation frequency and time shift for decoupling. We then extended our results to two reciprocally connected neuronal populations (modules) where inter-population delayed connections were modified by STDP. As predicted by the theoretical results, appropriately time-shifted stimulation causes a decoupling of the two-module system through STDP, i.e., by unlearning pathologically strong synaptic interactions between the two populations. Based on the overall topology of the connections, the decoupling of the two modules, in turn, causes a desynchronization of the populations that outlasts the cessation of stimulation. Decoupling effects of the time-shifted stimulation can be realized by time-shifted burst stimulation as well as time-shifted continuous simulation. Our results provide insight into the further optimization of a variety of multichannel stimulation protocols aiming at a therapeutic reshaping of diseased brain networks.

Adding a single pulse into high-frequency pulse stimulations can substantially alter the following episode of neuronal firing in rat hippocampus

Background. High-frequency stimulation (HFS) sequences of electrical pulses are commonly utilized in many types of neuromodulation therapies. The temporal pattern of pulse sequences characterized by varying inter-pulse intervals (IPI) has emerged as an adjustable dimension to generate diverse effects of stimulations to meet the needs for developing the therapies.Objective:To explore the hypothesis that a simple manipulation of IPI by inserting a pulse in HFS with a constant IPI can substantially change the neuronal responses.Approach. Antidromic HFS (A-HFS) and orthodromic HFS (O-HFS) sequences were respectively applied at the alveus (the efferent axons) and the Schaffer collaterals (the afferent axons) of hippocampal CA1 region in anesthetized ratsin-vivo. The HFS sequences lasted 120 s with a pulse frequency of 100 Hz and an IPI of 10 ms. In the late steady period (60-120 s) of the HFS, additional pulses were inserted into the original pulse sequences to investigate the alterations of neuronal responses to the changes in IPI. The amplitudes and latencies of antidromic/orthodromic population spikes (APS/OPS) evoked by pulses were measured to evaluate the alterations of the evoked firing of CA1 pyramidal neurons caused by the pulse insertions.Main Results. During the steady period of A-HFS at efferent axons, the evoked APSs were suppressed due to intermittent axonal block. Under this situation, inserting a pulse to shorten an IPI was able to redistribute the following neuronal firing thereby generating an episode of oscillation in the evoked APS sequence including APSs with significantly increased and decreased amplitudes. Also, during the steady period of O-HFS without obvious OPS, a pulse insertion was able to generate a large OPS, indicating a synchronized firing of a large population of post-synaptic neurons induced by a putative redistribution of activations at the afferent axons under O-HFS.Significance. This study firstly showed that under the situation of HFS-induced axonal block, changing an IPI by a single-pulse insertion can substantially redistribute the evoked neuronal responses to increase synchronized firing of neuronal populations during both antidromic and O-HFS with a constant IPI originally. The finding provides a potential way to enhance the HFS action on neuronal networks without losing some other functions of HFS such as generating axonal block.

Continuous high-frequency deep brain stimulation of the anterior insula modulates autism-like behavior in a valproic acid-induced rat model

BACKGROUND

Until now, the treatment of patients with autism spectrum disorder (ASD) remain a difficult problem. The insula is involved in empathy and sensorimotor integration, which are often impaired in individuals with ASD. Deep brain stimulation, modulating neuronal activity in specific brain circuits, has recently been considered as a promising intervention for neuropsychiatric disorders. Valproic acid (VPA) is a potential teratogenic agent, and prenatal exposure can cause autism-like symptoms including repetitive behaviors and defective sociability. Herein, we investigated the effects of continuous high-frequency deep brain stimulation in the anterior insula of rats exposed to VPA and explored cognitive functions, behavior, and molecular proteins connected to autism spectrum disorder.

METHODS

VPA-exposed offspring were bilaterally implanted with electrodes in the anterior insula (Day 0) with a recovery period of 1 week. (Day 0-7). High-frequency deep brain stimulation was applied from days 11 to 29. Three behavioral tests, including three-chamber social interaction test, were performed on days 7, 13, 18, 25 and 36, and several rats were used for analysis of immediate early genes and proteomic after deep brain stimulation intervention. Meanwhile, animals were subjected to a 20 day spatial learning and cognitive rigidity test using IntelliCage on day 11.

RESULTS

Deep brain stimulation improved the sociability and social novelty preference at day 18 prior to those at day 13, and the improvement has reached the upper limit compared to day 25. As for repetitive/stereotypic-like behavior, self- grooming time were reduced at day 18 and reached the upper limit, and the numbers of burried marbles were reduced at day 13 prior to those at day 18 and day 25. The improvements of sociability and social novelty preference were persistent after the stimulation had ceased. Spatial learning ability and cognitive rigidity were unaffected. We identified 35 proteins in the anterior insula, some of which were intimately linked to autism, and their expression levels were reversed upon administration of deep brain stimulation.

CONCLUSIONS

Autism-like behavior was ameliorated and autism-related proteins were reversed in the insula by deep brain stimulation intervention, these findings reveal that the insula may be a potential target for DBS in the treatment of autism, which provide a theoretical basis for its clinical application., although future studies are still warranted.

Inferring stimulation induced short-term synaptic plasticity dynamics using novel dual optimization algorithm

Experimental evidence in both human and animal studies demonstrated that deep brain stimulation (DBS) can induce short-term synaptic plasticity (STP) in the stimulated nucleus. Given that DBS-induced STP may be connected to the therapeutic effects of DBS, we sought to develop a computational predictive model that infers the dynamics of STP in response to DBS at different frequencies. Existing methods for estimating STP–either model-based or model-free approaches–require access to pre-synaptic spiking activity. However, in the context of DBS, extracellular stimulation (e.g. DBS) can be used to elicit presynaptic activations directly. We present a model-based approach that integrates multiple individual frequencies of DBS-like electrical stimulation as pre-synaptic spikes and infers parameters of the Tsodyks-Markram (TM) model from post-synaptic currents of the stimulated nucleus. By distinguishing between the steady-state and transient responses of the TM model, we develop a novel dual optimization algorithm that infers the model parameters in two steps. First, the TM model parameters are calculated by integrating multiple frequencies of stimulation to estimate the steady state response of post-synaptic current through a closed-form analytical solution. The results of this step are utilized as the initial values for the second step in which a non-derivative optimization algorithm is used to track the transient response of the post-synaptic potential across different individual frequencies of stimulation. Moreover, in order to confirm the applicability of the method, we applied our algorithm–as a proof of concept–to empirical data recorded from acute rodent brain slices of the subthalamic nucleus (STN) during DBS-like stimulation to infer dynamics of STP for inhibitory synaptic inputs.

Dynamics of phase oscillator networks with synaptic weight and structural plasticity

We study the dynamics of Kuramoto oscillator networks with two distinct adaptation processes, one varying the coupling strengths and the other altering the network structure. Such systems model certain networks of oscillatory neurons where the neuronal dynamics, synaptic weights, and network structure interact with and shape each other. We model synaptic weight adaptation with spike-timing-dependent plasticity (STDP) that runs on a longer time scale than neuronal spiking. Structural changes that include addition and elimination of contacts occur at yet a longer time scale than the weight adaptations. First, we study the steady-state dynamics of Kuramoto networks that are bistable and can settle in synchronized or desynchronized states. To compare the impact of adding structural plasticity, we contrast the network with only STDP to one with a combination of STDP and structural plasticity. We show that the inclusion of structural plasticity optimizes the synchronized state of a network by allowing for synchronization with fewer links than a network with STDP alone. With non-identical units in the network, the addition of structural plasticity leads to the emergence of correlations between the oscillators' natural frequencies and node degrees. In the desynchronized regime, the structural plasticity decreases the number of contacts, leading to a sparse network. In this way, adding structural plasticity strengthens both synchronized and desynchronized states of a network. Second, we use desynchronizing coordinated reset stimulation and synchronizing periodic stimulation to induce desynchronized and synchronized states, respectively. Our findings indicate that a network with a combination of STDP and structural plasticity may require stronger and longer stimulation to switch between the states than a network with STDP only.

Suppression of Neuronal Firing Following Antidromic High-Frequency Stimulations on the Neuronal Axons in Rat Hippocampal CA1 Region

High-frequency stimulation (HFS) of electrical pulses has been used to treat certain neurological diseases in brain with commonly utilized effects within stimulation periods. Post-stimulation effects after the end of HFS may also have functions but are lack of attention. To investigate the post-stimulation effects of HFS, we performed experiments in the rat hippocampal CA1 region in vivo. Sequences of 1-min antidromic-HFS (A-HFS) were applied at the alveus fibers. To evaluate the excitability of the neurons, separated orthodromic-tests (O-test) of paired pulses were applied at the Schaffer collaterals in the period of baseline, during late period of A-HFS, and following A-HFS. The evoked potentials of A-HFS pulses and O-test pulses were recorded at the stratum pyramidale and the stratum radiatum of CA1 region by an electrode array. The results showed that the antidromic population spikes (APS) evoked by the A-HFS pulses persisted through the entire 1-min period of 100 Hz A-HFS, though the APS amplitudes decreased significantly from the initial value of 9.9 ± 3.3 mV to the end value of 1.6 ± 0.60 mV. However, following the cessation of A-HFS, a silent period without neuronal firing appeared before the firing gradually recovered to the baseline level. The mean lengths of both silent period and recovery period of pyramidal cells (21.9 ± 22.9 and 172.8 ± 91.6 s) were significantly longer than those of interneurons (11.2 ± 8.9 and 45.6 ± 35.9 s). Furthermore, the orthodromic population spikes (OPS) and the field excitatory postsynaptic potentials (fEPSP) evoked by O-tests at ∼15 s following A-HFS decreased significantly, indicating the excitability of pyramidal cells decreased. In addition, when the pulse frequency of A-HFS was increased to 200, 400, and 800 Hz, the suppression of neuronal activity following A-HFS decreased rather than increased. These results indicated that the neurons with axons directly under HFS can generate a post-stimulation suppression of their excitability that may be due to an antidromic invasion of axonal A-HFS to somata and dendrites. The finding provides new clues to utilize post-stimulation effects generated in the intervals to design intermittent stimulations, such as closed-loop or adaptive stimulations.

The cortical evoked potential corresponds with deep brain stimulation efficacy in rats

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) antidromically activates the motor cortex (M1), and this cortical activation appears to play a role in the treatment of hypokinetic motor behaviors (Gradinaru V, Mogri M, Thompson KR, Henderson JM, Deisseroth K. Science 324: 354-359, 2009; Yu C, Cassar IR, Sambangi J, Grill WM. J Neurosci 40: 4323-4334, 2020). The synchronous antidromic activation takes the form of a short-latency cortical evoked potential (cEP) in electrocorticography (ECoG) recordings of M1. We assessed the utility of the cEP as a biomarker for STN DBS in unilateral 6-hydroxydopamine-lesioned female Sprague Dawley rats, with stimulating electrodes implanted in the STN and the ECoG recorded above M1. We quantified the correlations of the cEP magnitude and latency with changes in motor behavior from DBS and compared them to the correlation between motor behaviors and several commonly used spectral-based biomarkers. The cEP features correlated strongly with motor behaviors and were highly consistent across animals, whereas the spectral biomarkers correlated weakly with motor behaviors and were highly variable across animals. The cEP may thus be a useful biomarker for assessing the therapeutic efficacy of DBS parameters, as its features strongly correlate with motor behavior, it is consistent across time and subjects, it can be recorded under anesthesia, and it is simple to quantify with a large signal-to-noise ratio, enabling rapid, real-time evaluation. Additionally, our work provides further evidence that antidromic cortical activation mediates changes in motor behavior from STN DBS and that the dependence of DBS efficacy on stimulation frequency may be related to antidromic spike failure.NEW & NOTEWORTHY We characterize a new potential biomarker for deep brain stimulation (DBS), the cortical evoked potential (cEP), and demonstrate that it exhibits a robust correlation with motor behaviors as a function of stimulation frequency. The cEP may thus be a useful clinical biomarker for changes in motor behavior. This work also provides insight into the cortical mechanisms of DBS, suggesting that motor behaviors are strongly affected by the rate of antidromic spike failure during DBS.

Improved alpha-beta power reduction via combined electrical and ultrasonic stimulation in a parkinsonian cortex-basal ganglia-thalamus computational model

Objective. To investigate computationally the interaction of combined electrical and ultrasonic modulation of isolated neurons and of the parkinsonian cortex-basal ganglia-thalamus loop.Approach. Continuous-wave or pulsed electrical and ultrasonic neuromodulation is applied to isolated Otsuka plateau-potential generating subthalamic nucleus (STN) and Pospischil regular, fast and low-threshold spiking cortical cells in a temporally alternating or simultaneous manner. Similar combinations of electrical/ultrasonic waveforms are applied to a parkinsonian biophysical cortex-basal ganglia-thalamus neuronal network. Ultrasound-neuron interaction is modelled respectively for isolated neurons and the neuronal network with the NICE and SONIC implementations of the bilayer sonophore underlying mechanism. Reduction inα-βspectral energy is used as a proxy to express improvement in Parkinson's disease by insonication and electrostimulation.Main results. Simultaneous electro-acoustic stimulation achieves a given level of neuronal activity at lower intensities compared to the separate stimulation modalities. Conversely, temporally alternating stimulation with50 Hzelectrical and ultrasound pulses is capable of eliciting100 HzSTN firing rates. Furthermore, combination of ultrasound with hyperpolarizing currents can alter cortical cell relative spiking regimes. In the parkinsonian neuronal network, continuous-wave and pulsed ultrasound reduce pathological oscillations by different mechanisms. High-frequency pulsed separated electrical and ultrasonic deep brain stimulation (DBS) reduce pathologicalα-βpower by entraining STN-neurons. In contrast, continuous-wave ultrasound reduces pathological oscillations by silencing the STN. Compared to the separated stimulation modalities, temporally simultaneous or alternating electro-acoustic stimulation can achieve higher reductions inα-βpower for the same safety contraints on electrical/ultrasonic intensity.Significance. Focused ultrasound has the potential of becoming a non-invasive alternative of conventional DBS for the treatment of Parkinson's disease. Here, we elaborate on proposed benefits of combined electro-acoustic stimulation in terms of improved dynamic range, efficiency, spatial resolution, and neuronal selectivity.

Variance of filtered signals: Characterization for linear reaction networks and application to neurotransmission dynamics

Neurotransmission at chemical synapses relies on the calcium-induced fusion of synaptic vesicles with the presynaptic membrane. The distance of the synaptic vesicle to the calcium channels determines the release probability and consequently the postsynaptic signal. Suitable models of the process need to capture both the mean and the variance observed in electrophysiological measurements of the postsynaptic current. In this work, we propose a method to directly compute the exact first- and second-order moments for signals generated by a linear reaction network under convolution with an impulse response function, rendering computationally expensive numerical simulations of the underlying stochastic counting process obsolete. We show that the autocorrelation of the process is central for the calculation of the filtered signal's second-order moments, and derive a system of PDEs for the cross-correlation functions (including the autocorrelations) of linear reaction networks with time-dependent rates. Finally, we employ our method to efficiently compare different spatial coarse graining approaches for a specific model of synaptic vesicle fusion. Beyond the application to neurotransmission processes, the developed theory can be applied to any linear reaction system that produces a filtered stochastic signal.

Neuromodulation in the Treatment of Alzheimer's Disease: Current and Emerging Approaches

Neuromodulation as a treatment strategy for psychiatric and neurological diseases has grown in popularity in recent years, with the approval of repetitive transcranial magnetic stimulation (rTMS) for the treatment of depression being one such example. These approaches offer new hope in the treatment of diseases that have proven largely intractable to traditional pharmacological approaches. For this reason, neuromodulation is increasingly being explored for the treatment of Alzheimer's disease. However, such approaches have variable, and, in many cases, very limited evidence for safety and efficacy, with most human evidence obtained in small clinical trials. Here we review work in animal models and humans with Alzheimer's disease exploring emerging neuromodulation modalities. Approaches reviewed include deep brain stimulation, transcranial magnetic stimulation, transcranial electrical stimulation, ultrasound stimulation, photobiomodulation, and visual or auditory stimulation. In doing so, we clarify the current evidence for these approaches in treating Alzheimer's disease and identify specific areas where additional work is needed to facilitate their clinical translation.

Two-photon calcium imaging of neuronal and astrocytic responses: the influence of electrical stimulus parameters and calcium signaling mechanisms

Objective. Electrical brain stimulation has been used to ameliorate symptoms associated with neurologic and psychiatric disorders. The astrocytic activation and its interaction with neurons may contribute to the therapeutic effects of electrical stimulation. However, how the astrocytic activity is affected by electrical stimulation and its calcium signaling mechanisms remain largely unknown. This study is to explore the influence of electrical stimulus parameters on cellular calcium responses and corresponding calcium signaling mechanisms, with a focus on the heretofore largely overlooked astrocytes.Approach. Usingin vivotwo-photon microscopy in mouse somatosensory cortex, the calcium activity in neurons and astrocytes were recorded.Main results. The cathodal stimulation evoked larger responses in both neurons and astrocytes than anodal stimulation. Both neuronal and astrocytic response profiles exhibited the unimodal frequency dependency, the astrocytes prefer higher frequency stimulation than neurons. Astrocytes need longer pulse width and higher current intensity than neurons to activate. Compared to neurons, the astrocytes were not capable of keeping sustained calcium elevation during prolonged electrical stimulation. The neuronal Ca²⁺influx involves postsynaptic effects and direct depolarization. The Ca²⁺surge of astrocytes has a neuronal origin, the noradrenergic and glutamatergic signaling act synergistically to induce astrocytic activity.Significance. The astrocytic activity can be regulated by manipulating stimulus parameters and its calcium activation should be fully considered when interpreting the mechanisms of action of electrical neuromodulation. This study brings considerable benefits in the application of electrical stimulation and provides useful insights into cortical signal transduction, which contributes to the understanding of mechanisms underlying the therapeutic efficacy of electrical stimulation for neurorehabilitation applications.

Somatic inhibition by microscopic magnetic stimulation

Electric currents can produce quick, reversible control of neural activity. Externally applied electric currents have been used in inhibiting certain ganglion cells in clinical practices. Via electromagnetic induction, a miniature-sized magnetic coil could provide focal stimulation to the ganglion neurons. Here we report that high-frequency stimulation with the miniature coil could reversibly block ganglion cell activity in marine mollusk Aplysia californica, regardless the firing frequency of the neurons, or concentration of potassium ions around the ganglion neurons. Presence of the ganglion sheath has minimal impact on the inhibitory effects of the coil. The inhibitory effect was local to the soma, and was sufficient in blocking the neuron's functional output. Biophysical modeling confirmed that the miniature coil induced a sufficient electric field in the vicinity of the targeted soma. Using a multi-compartment model of Aplysia ganglion neuron, we found that the high-frequency magnetic stimuli altered the ion channel dynamics that were essential for the sustained firing of action potentials in the soma. Results from this study produces several critical insights to further developing the miniature coil technology for neural control by targeting ganglion cells. The miniature coil provides an interesting neural modulation strategy in clinical applications and laboratory research.

A theoretical framework for the site-specific and frequency-dependent neuronal effects of deep brain stimulation

BACKGROUND

Deep brain stimulation is an established therapy for several neurological disorders; however, its effects on neuronal activity vary across brain regions and depend on stimulation settings. Understanding these variable responses can aid in the development of physiologically-informed stimulation paradigms in existing or prospective indications.

OBJECTIVE

Provide experimental and computational insights into the brain-region-specific and frequency-dependent effects of extracellular stimulation on neuronal activity.

METHODS

In patients with movement disorders, single-neuron recordings were acquired from the subthalamic nucleus, substantia nigra pars reticulata, ventral intermediate nucleus, or reticular thalamus during microstimulation across various frequencies (1-100 Hz) to assess single-pulse and frequency-response functions. Moreover, a biophysically-realistic computational framework was developed which generated postsynaptic responses under the assumption that electrical stimuli simultaneously activated all convergent presynaptic inputs to stimulation target neurons. The framework took into consideration the relative distributions of excitatory/inhibitory afferent inputs to model site-specific responses, which were in turn embedded within a model of short-term synaptic plasticity to account for stimulation frequency-dependence.

RESULTS

We demonstrated microstimulation-evoked excitatory neuronal responses in thalamic structures (which have predominantly excitatory inputs) and inhibitory responses in basal ganglia structures (predominantly inhibitory inputs); however, higher stimulation frequencies led to a loss of site-specificity and convergence towards neuronal suppression. The model confirmed that site-specific responses could be simulated by accounting for local neuroanatomical/microcircuit properties, while suppression of neuronal activity during high-frequency stimulation was mediated by short-term synaptic depression.

CONCLUSIONS

Brain-region-specific and frequency-dependant neuronal responses could be simulated by considering neuroanatomical (local microcircuitry) and neurophysiological (short-term plasticity) properties.

Adjust Neuronal Reactions to Pulses of High-Frequency Stimulation with Designed Inter-Pulse-Intervals in Rat Hippocampus In Vivo

Sequences of electrical pulses have been applied in the brain to treat certain disorders. In recent years, altering inter-pulse-interval (IPI) regularly or irregularly in real time has emerged as a promising way to modulate the stimulation effects. However, algorithms to design IPI sequences are lacking. This study proposed a novel strategy to design pulse sequences with varying IPI based on immediate neuronal reactions. Firstly, to establish the correlationship between the neuronal reactions with varying IPIs, high-frequency stimulations with varying IPI in the range of 5–10 ms were applied at the alveus of the hippocampal CA1 region of anesthetized rats in vivo. Antidromically-evoked population spikes (APS) following each IPI were recorded and used as a biomarker to evaluate neuronal reactions to each pulse. A linear mapping model was established to estimate the varied APS amplitudes by the two preceding IPIs. Secondly, the mapping model was used to derive an algorithm for designing an IPI sequence that would be applied for generating a desired neuronal reaction pre-defined by a particular APS distribution. Finally, examples of stimulations with different IPI sequences designed by the algorithm were verified by rat experiments. The results showed that the designed IPI sequences were able to reproduce the desired APS responses of different distributions in the hippocampal stimulations. The novel algorithm of IPI design provides a potential way to obtain various stimulation effects for brain stimulation therapies.

Suppressing synchronous firing of epileptiform activity by high-frequency stimulation of afferent fibers in rat hippocampus

Aims

Deep brain stimulation (DBS) is a promising technology for treating epilepsy. However, the efficacy and underlying mechanisms of the high‐frequency stimulation (HFS) utilized by DBS to suppress epilepsy remain uncertain. Previous studies have shown that HFS can desynchronize the firing of neurons. In this study, we investigated whether the desynchronization effects of HFS can suppress epileptiform events.

Methods

HFS trains with seconds of duration (short) and a minute of duration (long) were applied at the afferent fibers (ie, Schaffer collaterals) of the hippocampal CA1 region in anesthetized rats in vivo. The amplitude and the rate of population spikes (PS) appeared in the downstream of stimulation were calculated to evaluate the intensity of synchronized firing of neuronal populations between short and long HFS groups. A test of paired‐pulse depression (PPD) was used to assess the alteration of inhibitory neuronal circuits.

Results

The sustained stimulation of a 60‐s long HFS suppressed the afterdischarges that were induced by a 5‐s short HFS to impair the local inhibitions. During the sustained HFS, the mean PS amplitude reduced significantly and the burst firing decreased, while the amount of neuronal firing did not change significantly. The paired‐pulse tests showed that with a similar baseline level of small PS2/PS1 ratio indicating a strong PPD, the 5‐s HFS increased the PS2/PS1 ratio to a value that was significantly greater than the corresponding ratio during sustained HFS, indicating that the PPD impaired by a short HFS may be restored by a sustained HFS.

Conclusions

The sustained HFS can desynchronize the population firing of epileptiform activity and accelerate a recovery of inhibitions to create a balance between the excitation and the inhibition of local neuronal circuits. The study provides new clues for further understanding the mechanism of DBS and for advancing the clinical application of DBS in treating epilepsy.

Analysis of neural clusters due to deep brain stimulation pulses

Deep brain stimulation (DBS) is an established method for treating pathological conditions such as Parkinson's disease, dystonia, Tourette syndrome, and essential tremor. While the precise mechanisms which underly the effectiveness of DBS are not fully understood, several theoretical studies of populations of neural oscillators stimulated by periodic pulses have suggested that this may be related to clustering, in which subpopulations of the neurons are synchronized, but the subpopulations are desynchronized with respect to each other. The details of the clustering behavior depend on the frequency and amplitude of the stimulation in a complicated way. In the present study, we investigate how the number of clusters and their stability properties, bifurcations, and basins of attraction can be understood in terms of one-dimensional maps defined on the circle. Moreover, we generalize this analysis to stimuli that consist of pulses with alternating properties, which provide additional degrees of freedom in the design of DBS stimuli. Our results illustrate how the complicated properties of clustering behavior for periodically forced neural oscillator populations can be understood in terms of a much simpler dynamical system.

Axonal blockage with microscopic magnetic stimulation

Numerous neurological dysfunctions are characterized by undesirable nerve activity. By providing reversible nerve blockage, electric stimulation with an implanted electrode holds promise in the treatment of these conditions. However, there are several limitations to its application, including poor bio-compatibility and decreased efficacy during chronic implantation. A magnetic coil of miniature size can mitigate some of these problems, by coating it with biocompatible material for chronic implantation. However, it is unknown if miniature coils could be effective in axonal blockage and, if so, what the underlying mechanisms are. Here we demonstrate that a submillimeter magnetic coil can reversibly block action potentials in the unmyelinated axons from the marine mollusk Aplysia californica. Using a multi-compartment model of the Aplysia axon, we demonstrate that the miniature coil causes a significant local depolarization in the axon, alters activation dynamics of the sodium channels, and prevents the traveling of the invading action potentials. With improved biocompatibility and capability of emitting high-frequency stimuli, micro coils provide an interesting alternative for electric blockage of axonal conductance in clinical settings.

A Multi-Scale Computational Model of Excitotoxic Loss of Dopaminergic Cells in Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disorder caused by loss of dopaminergic neurons in substantia nigra pars compacta (SNc). Although the exact cause of cell death is not clear, the hypothesis that metabolic deficiency is a key factor has been gaining attention in recent years. In the present study, we investigated this hypothesis using a multi-scale computational model of the subsystem of the basal ganglia comprising the subthalamic nucleus (STN), globus pallidus externa (GPe), and SNc. The proposed model is a multiscale model in that interaction among the three nuclei are simulated using more abstract Izhikevich neuron models, while the molecular pathways involved in cell death of SNc neurons are simulated in terms of detailed chemical kinetics. Simulation results obtained from the proposed model showed that energy deficiencies occurring at cellular and network levels could precipitate the excitotoxic loss of SNc neurons in PD. At the subcellular level, the models show how calcium elevation leads to apoptosis of SNc neurons. The therapeutic effects of several neuroprotective interventions are also simulated in the model. From neuroprotective studies, it was clear that glutamate inhibition and apoptotic signal blocker therapies were able to halt the progression of SNc cell loss when compared to other therapeutic interventions, which only slowed down the progression of SNc cell loss.

Local field potential activity dynamics in response to deep brain stimulation of the subthalamic nucleus in Parkinson's disease

Local field potentials (LFPs) may afford insight into the mechanisms of action of deep brain stimulation (DBS) and potential feedback signals for adaptive DBS. In Parkinson's disease (PD) DBS of the subthalamic nucleus (STN) suppresses spontaneous activity in the beta band and drives evoked resonant neural activity (ERNA). Here, we investigate how STN LFP activities change over time following the onset and offset of DBS. To this end we recorded LFPs from the STN in 14 PD patients during long (mean: 181.2 s) and short (14.2 s) blocks of continuous stimulation at 130 Hz. LFP activities were evaluated in the temporal and spectral domains. During long stimulation blocks, the frequency and amplitude of the ERNA decreased before reaching a steady state after ~70 s. Maximal ERNA amplitudes diminished over repeated stimulation blocks. Upon DBS cessation, the ERNA was revealed as an under-damped oscillation, and was more marked and lasted longer after short duration stimulation blocks. In contrast, activity in the beta band suppressed within 0.5 s of continuous DBS onset and drifted less over time. Spontaneous activity was also suppressed in the low gamma band, suggesting that the effects of high frequency stimulation on spontaneous oscillations may not be selective for pathological beta activity. High frequency oscillations were present in only six STN recordings before stimulation onset and their frequency was depressed by stimulation. The different dynamics of the ERNA and beta activity with stimulation imply different DBS mechanisms and may impact how these activities may be used in adaptive feedback.

A Causal Network Analysis of Neuromodulation in the Mood Processing Network

Neural decoding and neuromodulation technologies hold great promise for treating mood and other brain disorders in next-generation therapies that manipulate functional brain networks. Here we perform a novel causal network analysis to decode multiregional communication in the primate mood processing network and determine how neuromodulation, short-burst tetanic microstimulation (sbTetMS), alters multiregional network communication. The causal network analysis revealed a mechanism of network excitability that regulates when a sender stimulation site communicates with receiver sites. Decoding network excitability from neural activity at modulator sites predicted sender-receiver communication, whereas sbTetMS neuromodulation temporarily disrupted sender-receiver communication. These results reveal specific network mechanisms of multiregional communication and suggest a new generation of brain therapies that combine neural decoding to predict multiregional communication with neuromodulation to disrupt multiregional communication.

The Appearance Order of Varying Intervals Introduces Extra Modulation Effects on Neuronal Firing Through Non-linear Dynamics of Sodium Channels During High-Frequency Stimulations

Electrical pulse stimulation in the brain has shown success in treating several brain disorders with constant pulse frequency or constant inter-pulse interval (IPI). Varying IPI may offer a variety of novel stimulation paradigms and may extend the clinical applications. However, a lack of understanding of neuronal responses to varying IPI limits its informed applications. In this study, to investigate the effects of varying IPI, we performed both rat experiments and computational modeling by applying high-frequency stimulation (HFS) to efferent axon fibers of hippocampal pyramidal cells. Antidromically evoked population spikes (PSs) were used to evaluate the neuronal responses to pulse stimulations with different IPI patterns including constant IPI, gradually varying IPI, and randomly varying IPI. All the varying IPI sequences were uniformly distributed in the same interval range of 10 to 5 ms (i.e., 100 to 200 Hz). The experimental results showed that the mean correlation coefficient of PS amplitudes to the lengths of preceding IPI during HFS with random IPI (0.72 ± 0.04, n = 7 rats) was significantly smaller than the corresponding correlation coefficient during HFS with gradual IPI (0.92 ± 0.03, n = 7 rats, P < 0.001, t-test). The PS amplitudes induced by the random IPI covered a wider range, over twice as much as that induced by the gradual IPI, indicating additional effects induced by merely changing the appearance order of IPI. The computational modeling reproduced these experimental results and provided insights into these modulatory effects through the mechanism of non-linear dynamics of sodium channels and potassium accumulation in the narrow peri-axonal space. The simulation results showed that the HFS-induced increase of extracellular potassium ([K⁺] _o ) elevated the membrane potential of axons, delayed the recovery course of sodium channels that were repeatedly activated and inactivated during HFS, and resulted in intermittent neuronal firing. Because of non-linear membrane dynamics, random IPI recruited more neurons to fire together following specific sub-sequences of pulses than gradual IPI, thereby widening the range of PS amplitudes. In conclusion, the study demonstrated novel HFS effects of neuronal modulation induced by merely changing the appearance order of the same group of IPI of pulses, which may inform the development of new stimulation patterns to meet different demands for treating various brain diseases.

Neuronal Activity and Synaptic Plasticity in a Reimplanted STN-DBS Patient with Parkinson's Disease: Recordings from Two Surgeries

The authors report the case of an elderly male in his 60s who, after 5 months of efficacious treatment with chronic deep brain stimulation of the subthalamic nucleus (STN-DBS), developed a hardware-related erosion necessitating removal of the complete DBS system. One and a half years following the first implantation, a new STN-DBS system was implanted along an immediately adjacent trajectory, and reproduction of clinical efficacy was reported. Additionally, 2 microstimulation protocols were compared between the 2 surgeries, i.e., one to assess the stimulation frequency response of STN neurons and another to assess inhibitory synaptic plasticity in the substantia nigra pars reticulata (SNr). The spontaneous neuronal firing rates of STN neurons in each hemisphere were also compared between the 2 surgeries. The results suggest that the frequency-sensitivity of STN neurons may have been reduced (i.e., more resistant to neuronal suppression), while the spontaneous baseline firing rates of STN neurons and the plasticity measured in the SNr remained unchanged (2 factors that may be indicative of neurodegenerative processes).

Focal Suppression of Epileptiform Activity in the Hippocampus by a High-frequency Magnetic Field

Electric current has been used for epilepsy treatment by targeting specific neural circuitries. Despite its success, direct contact between the electrode and tissue could cause side effects including pain, inflammation, and adverse biological reactions. Magnetic stimulation overcomes these limitations by offering advantages over biocompatibility and operational feasibility. However, the underlying neurological mechanisms of its action are largely unknown. In this work, a magnetic generating system was assembled that included a miniature coil. The coil was positioned above the CA3 area of mouse hippocampal slices. Epileptiform activity (EFA) was induced with low Mg²⁺/high K⁺ perfusion or with 100 µM 4-aminopyridine (4-AP). The miniature coil generated a sizable electric field that suppressed the local EFA in the hippocampus in the low-Mg²⁺/high-K⁺ model. The inhibition effect was dependent on the frequency and duration of the magnetic stimulus, with high frequency being more effective in suppressing EFA. EFA suppression by the magnetic field was also observed in the 4-AP model, in a frequency and duration - dependent manner. The study provides a platform for further investigation of cellular and molecular mechanisms underlying epilepsy treatment with time varying magnetic fields.

Deep brain stimulation: current challenges and future directions

The clinical use of deep brain stimulation (DBS) is among the most important advances in the clinical neurosciences in the past two decades. As a surgical tool, DBS can directly measure pathological brain activity and can deliver adjustable stimulation for therapeutic effect in neurological and psychiatric disorders correlated with dysfunctional circuitry. The development of DBS has opened new opportunities to access and interrogate malfunctioning brain circuits and to test the therapeutic potential of regulating the output of these circuits in a broad range of disorders. Despite the success and rapid adoption of DBS, crucial questions remain, including which brain areas should be targeted and in which patients. This Review considers how DBS has facilitated advances in our understanding of how circuit malfunction can lead to brain disorders and outlines the key unmet challenges and future directions in the DBS field. Determining the next steps in DBS science will help to define the future role of this technology in the development of novel therapeutics for the most challenging disorders affecting the human brain.

Resting-state functional connectivity modulates the BOLD activation induced by nucleus accumbens stimulation in the swine brain

INTRODUCTION

While the clinical efficacy of deep brain stimulation (DBS) the treatment of motor-related symptoms is well established, the mechanism of action of the resulting cognitive and behavioral effects has been elusive.

METHODS

By combining functional magnetic resonance imaging (fMRI) and DBS, we investigated the pattern of blood-oxygenation-level-dependent (BOLD) signal changes induced by stimulating the nucleus accumbens in a large animal model.

RESULTS

We found that diffused BOLD activation across multiple functional networks, including the prefrontal, limbic, and thalamic regions during the stimulation, resulted in a significant change in inter-regional functional connectivity. More importantly, the magnitude of the modulation was closely related to the strength of the inter-regional resting-state functional connectivity.

CONCLUSIONS

Nucleus accumbens stimulation affects the functional activity in networks that underlie cognition and behavior. Our study provides an insight into the nature of the functional connectivity, which mediates activation effect via brain networks.

Predicting the effects of deep brain stimulation using a reduced coupled oscillator model

Deep brain stimulation (DBS) is known to be an effective treatment for a variety of neurological disorders, including Parkinson's disease and essential tremor (ET). At present, it involves administering a train of pulses with constant frequency via electrodes implanted into the brain. New 'closed-loop' approaches involve delivering stimulation according to the ongoing symptoms or brain activity and have the potential to provide improvements in terms of efficiency, efficacy and reduction of side effects. The success of closed-loop DBS depends on being able to devise a stimulation strategy that minimizes oscillations in neural activity associated with symptoms of motor disorders. A useful stepping stone towards this is to construct a mathematical model, which can describe how the brain oscillations should change when stimulation is applied at a particular state of the system. Our work focuses on the use of coupled oscillators to represent neurons in areas generating pathological oscillations. Using a reduced form of the Kuramoto model, we analyse how a patient should respond to stimulation when neural oscillations have a given phase and amplitude, provided a number of conditions are satisfied. For such patients, we predict that the best stimulation strategy should be phase specific but also that stimulation should have a greater effect if applied when the amplitude of brain oscillations is lower. We compare this surprising prediction with data obtained from ET patients. In light of our predictions, we also propose a new hybrid strategy which effectively combines two of the closed-loop strategies found in the literature, namely phase-locked and adaptive DBS.

Current and future directions of deep brain stimulation for neurological and psychiatric disorders

Deep brain stimulation (DBS) has evolved considerably over the past 4 decades. Although it has primarily been used to treat movement disorders such as Parkinson's disease, essential tremor, and dystonia, recently it has been approved to treat obsessive-compulsive disorder and epilepsy. Novel potential indications in both neurological and psychiatric disorders are undergoing active study. There have been significant advances in DBS technology, including preoperative and intraoperative imaging, surgical approaches and techniques, and device improvements. In addition to providing significant clinical benefits and improving quality of life, DBS has also increased the understanding of human electrophysiology and network interactions. Despite the value of DBS, future developments should be aimed at developing less invasive techniques and attaining not just symptom improvement but curative disease modification.

Neuromodulation with electromagnetic stimulation for seizure suppression: From electrode to magnetic coil

Non-invasive brain tissue stimulation with a magnetic coil provides several irreplaceable advantages over that with an implanted electrode, in altering neural activities under pathological situations. We reviewed clinical cases that utilized time-varying magnetic fields for the treatment of epilepsy, and the safety issues related to this practice. Animal models have been developed to foster understanding of the cellular/molecular mechanisms underlying magnetic control of epileptic activity. These mechanisms include (but are not limited to) (1) direct membrane polarization by the magnetic field, (2) depolarization blockade by the deactivation of ion channels, (3) alteration in synaptic transmission, and (4) interruption of ephaptic interaction and cellular synchronization. Clinical translation of this technology could be improved through the advancement of magnetic design, optimization of stimulation protocols, and evaluation of the long-term safety. Cellular and molecular studies focusing on the mechanisms of magnetic stimulation are of great value in facilitating this translation.

Theoretical principles of deep brain stimulation induced synaptic suppression

BACKGROUND

Deep brain stimulation (DBS) is a successful clinical therapy for a wide range of neurological disorders; however, the physiological mechanisms of DBS remain unresolved. While many different hypotheses currently exist, our analyses suggest that high frequency (∼100 Hz) stimulation-induced synaptic suppression represents the most basic concept that can be directly reconciled with experimental recordings of spiking activity in neurons that are being driven by DBS inputs.

OBJECTIVE

The goal of this project was to develop a simple model system to characterize the excitatory post-synaptic currents (EPSCs) and action potential signaling generated in a neuron that is strongly connected to pre-synaptic glutamatergic inputs that are being directly activated by DBS.

METHODS

We used the Tsodyks-Markram (TM) phenomenological synapse model to represent depressing, facilitating, and pseudo-linear synapses driven by DBS over a wide range of stimulation frequencies. The EPSCs were then used as inputs to a leaky integrate-and-fire neuron model and we measured the DBS-triggered post-synaptic spiking activity.

RESULTS

Synaptic suppression was a robust feature of high frequency stimulation, independent of the synapse type. As such, the TM equations were used to define alternative DBS pulsing strategies that maximized synaptic suppression with the minimum number of stimuli.

CONCLUSIONS

Synaptic suppression provides a biophysical explanation to the intermittent, but still time-locked, post-synaptic firing characteristics commonly seen in DBS experimental recordings. Therefore, network models attempting to analyze or predict the effects of DBS on neural activity patterns should integrate synaptic suppression into their simulations.

Simulation Study of Intermittent Responses of Neuronal Populations to Axonal High-Frequency Stimulation

Deep brain stimulation (DBS) have shown a promising future for treating various brain disorders. Studies have indicated that the high frequency stimulation (HFS) used in DBS could cause a partial block in axons thereby attenuating the responses of axon fibers to the pulses of HFS. The attenuated response of axons might play a desynchronization role in modulating activity of neuronal populations. To investigate the detail behavior of individual axons under HFS, we created a computational model of neuronal populations including 1250 neurons. Each neuron consisted of a myelinated axon, an axonal initial segment, a soma and dendrites. A 10-s HFS sequence with 100 Hz pulses was applied to the axon layer by a bipolar stimulation electrode. The membrane potentials and the extracellular potassium concentration [K⁺]_o at axons and at somata during the stimulation were investigated. The results showed that the simulation model with a mechanism of potassium accumulation could reproduce the attenuated responses of neuronal populations to persistent axonal HFS in rat experiments. The elevation of [K⁺]_o during HFS resulted in an increase of basic membrane potentials and then generated a depolarization block in the axonal membrane thereby attenuating the responses of neuronal populations. The depolarization block in axons included both complete block (~26%) and intermittent block (~74%), which generated desynchronized firing among axons in fibers and travelled to the cell bodies to induce desynchronized firing in somata. The simulation results may provide important information for revealing the modulation mechanisms of axonal HFS in the therapy of brain stimulation.

Neuronal inhibition and synaptic plasticity of basal ganglia neurons in Parkinson's disease

Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson’s disease symptoms. The therapeutic benefits of deep brain stimulation are frequency-dependent, but the underlying physiological mechanisms remain unclear. To advance deep brain stimulation therapy an understanding of fundamental mechanisms is critical. The objectives of this study were to (i) compare the frequency-dependent effects on cell firing in subthalamic nucleus and substantia nigra pars reticulata; (ii) quantify frequency-dependent effects on short-term plasticity in substantia nigra pars reticulata; and (iii) investigate effects of continuous long-train high frequency stimulation (comparable to conventional deep brain stimulation) on synaptic plasticity. Two closely spaced (600 µm) microelectrodes were advanced into the subthalamic nucleus (n = 27) and substantia nigra pars reticulata (n = 14) of 22 patients undergoing deep brain stimulation surgery for Parkinson’s disease. Cell firing and evoked field potentials were recorded with one microelectrode during stimulation trains from the adjacent microelectrode across a range of frequencies (1–100 Hz, 100 µA, 0.3 ms, 50–60 pulses). Subthalamic firing attenuated with ≥20 Hz (P < 0.01) stimulation (silenced at 100 Hz), while substantia nigra pars reticulata decreased with ≥3 Hz (P < 0.05) (silenced at 50 Hz). Substantia nigra pars reticulata also exhibited a more prominent increase in transient silent period following stimulation. Patients with longer silent periods after 100 Hz stimulation in the subthalamic nucleus tended to have better clinical outcome after deep brain stimulation. At ≥30 Hz the first evoked field potential of the stimulation train in substantia nigra pars reticulata was potentiated (P < 0.05); however, the average amplitude of the subsequent potentials was rapidly attenuated (P < 0.01). This is suggestive of synaptic facilitation followed by rapid depression. Paired pulse ratios calculated at the beginning of the train revealed that 20 Hz (P < 0.05) was the minimum frequency required to induce synaptic depression. Lastly, the average amplitude of evoked field potentials during 1 Hz pulses showed significant inhibitory synaptic potentiation after long-train high frequency stimulation (P < 0.001) and these increases were coupled with increased durations of neuronal inhibition (P < 0.01). The subthalamic nucleus exhibited a higher frequency threshold for stimulation-induced inhibition than the substantia nigra pars reticulata likely due to differing ratios of GABA:glutamate terminals on the soma and/or the nature of their GABAergic inputs (pallidal versus striatal). We suggest that enhancement of inhibitory synaptic plasticity, and frequency-dependent potentiation and depression are putative mechanisms of deep brain stimulation. Furthermore, we foresee that future closed-loop deep brain stimulation systems (with more frequent off stimulation periods) may benefit from inhibitory synaptic potentiation that occurs after high frequency stimulation.

A Computational Model of Loss of Dopaminergic Cells in Parkinson's Disease Due to Glutamate-Induced Excitotoxicity

Parkinson's disease (PD) is a neurodegenerative disease associated with progressive and inexorable loss of dopaminergic cells in Substantia Nigra pars compacta (SNc). Although many mechanisms have been suggested, a decisive root cause of this cell loss is unknown. A couple of the proposed mechanisms, however, show potential for the development of a novel line of PD therapeutics. One of these mechanisms is the peculiar metabolic vulnerability of SNc cells compared to other dopaminergic clusters; the other is the SubThalamic Nucleus (STN)-induced excitotoxicity in SNc. To investigate the latter hypothesis computationally, we developed a spiking neuron network-model of SNc-STN-GPe system. In the model, prolonged stimulation of SNc cells by an overactive STN leads to an increase in ‘stress' variable; when the stress in a SNc neuron exceeds a stress threshold, the neuron dies. The model shows that the interaction between SNc and STN involves a positive-feedback due to which, an initial loss of SNc cells that crosses a threshold causes a runaway-effect, leading to an inexorable loss of SNc cells, strongly resembling the process of neurodegeneration. The model further suggests a link between the two aforementioned mechanisms of SNc cell loss. Our simulation results show that the excitotoxic cause of SNc cell loss might initiate by weak-excitotoxicity mediated by energy deficit, followed by strong-excitotoxicity, mediated by a disinhibited STN. A variety of conventional therapies were simulated to test their efficacy in slowing down SNc cell loss. Among them, glutamate inhibition, dopamine restoration, subthalamotomy and deep brain stimulation showed superior neuroprotective-effects in the proposed model.

Small Changes in Inter-Pulse-Intervals Can Cause Synchronized Neuronal Firing During High-Frequency Stimulations in Rat Hippocampus

Deep brain stimulation (DBS) traditionally utilizes electrical pulse sequences with a constant frequency, i.e., constant inter-pulse-interval (IPI), to treat certain brain disorders in clinic. Stimulation sequences with varying frequency have been investigated recently to improve the efficacy of existing DBS therapy and to develop new treatments. However, the effects of such sequences are inconclusive. The present study tests the hypothesis that stimulations with varying IPI can generate neuronal activity markedly different from the activity induced by stimulations with constant IPI. And, the crucial factor causing the distinction is the relative differences in IPI lengths rather than the absolute lengths of IPI nor the average lengths of IPI. In rat experiments in vivo, responses of neuronal populations to applied stimulation sequences were collected during stimulations with both constant IPI (control) and random IPI. The stimulations were applied in the efferent fibers antidromically (in alveus) or in the afferent fibers orthodromically (in Schaffer collaterals) of pyramidal cells, the principal cells of hippocampal CA1 region. Amplitudes and areas of population spike (PS) waveforms were used to evaluate the neuronal responses induced by different stimulation paradigms. During the periods of both antidromic and orthodromic high-frequency stimulation (HFS), the HFS with random IPI induced synchronous neuronal firing with large PS even if the lengths of random IPI were limited to a small range of 5-10 ms, corresponding to a frequency range 100-200 Hz. The large PS events did not appear during control stimulations with a constant frequency at 100, 200, or 130 Hz (i.e., the mean frequency of HFS with random IPI uniformly distributed within 5-10 ms). Presumably, nonlinear dynamics in neuronal responses to random IPI might cause the generation of synchronous firing under the situation without any long pauses in HFS sequences. The results indicate that stimulations with random IPI can generate salient impulses to brain tissues and modulate the synchronization of neuronal activity, thereby providing potential stimulation paradigms for extending DBS therapy in treating more brain diseases, such as disorders of consciousness and vegetative states.

Connectivity and Dynamics Underlying Synaptic Control of the Subthalamic Nucleus

Adaptive motor control critically depends on the interconnected nuclei of the basal ganglia in the CNS. A pivotal element of the basal ganglia is the subthalamic nucleus (STN), which serves as a therapeutic target for deep brain stimulation (DBS) in movement disorders, such as Parkinson's disease. The functional connectivity of the STN at the microcircuit level, however, still requires rigorous investigation. Here we combine multiple simultaneous whole-cell recordings with extracellular stimulation and post hoc neuroanatomical analysis to investigate intrinsic and afferent connectivity and synaptic properties of the STN in acute brain slices obtained from rats of both sexes. Our data reveal an absence of intrinsic connectivity and an afferent innervation with low divergence, suggesting that STN neurons operate as independent processing elements driven by upstream structures. Hence, synchrony in the STN, a hallmark of motor processing, exclusively depends on the interactions and dynamics of GABAergic and glutamatergic afferents. Importantly, these inputs are subject to differential short-term depression when stimulated at high, DBS-like frequencies, shifting the balance of excitation and inhibition toward inhibition. Thus, we present a mechanism for fast yet transient decoupling of the STN from synchronizing afferent control. Together, our study provides new insights into the microcircuit organization of the STN by identifying its neurons as parallel processing units and thus sets new constraints for future computational models of the basal ganglia. The observed differential short-term plasticity of afferent inputs further offers a basis to better understand and optimize DBS algorithms.SIGNIFICANCE STATEMENT The subthalamic nucleus (STN) is a pivotal element of the basal ganglia and serves as target for deep brain stimulation, but information on the functional connectivity of its neurons is limited. To investigate the STN microcircuitry, we combined multiple simultaneous patch-clamp recordings and neuroanatomical analysis. Our results provide new insights into the synaptic organization of the STN identifying its neurons as parallel processing units and thus set new constraints for future computational models of the basal ganglia. We further find that synaptic dynamics of afferent inputs result in a rapid yet transient decoupling of the STN when stimulated at high frequencies. These results offer a better understanding of deep brain stimulation mechanisms, promoting the development of optimized algorithms.

Toward Electrophysiology-Based Intelligent Adaptive Deep Brain Stimulation for Movement Disorders

Deep brain stimulation (DBS) represents one of the major clinical breakthroughs in the age of translational neuroscience. In 1987, Benabid and colleagues demonstrated that high-frequency stimulation can mimic the effects of ablative neurosurgery in Parkinson's disease (PD), while offering two key advantages to previous procedures: adjustability and reversibility. Deep brain stimulation is now an established therapeutic approach that robustly alleviates symptoms in patients with movement disorders, such as Parkinson's disease, essential tremor, and dystonia, who present with inadequate or adverse responses to medication. Currently, stimulation electrodes are implanted in specific target regions of the basal ganglia-thalamic circuit and stimulation pulses are delivered chronically. To achieve optimal therapeutic effect, stimulation frequency, amplitude, and pulse width must be adjusted on a patient-specific basis by a movement disorders specialist. The finding that pathological neural activity can be sampled directly from the target region using the DBS electrode has inspired a novel DBS paradigm: closed-loop adaptive DBS (aDBS). The goal of this strategy is to identify pathological and physiologically normal patterns of neuronal activity that can be used to adapt stimulation parameters to the concurrent therapeutic demand. This review will give detailed insight into potential biomarkers and discuss next-generation strategies, implementing advances in artificial intelligence, to further elevate the therapeutic potential of DBS by capitalizing on its modifiable nature. Development of intelligent aDBS, with an ability to deliver highly personalized treatment regimens and to create symptom-specific therapeutic strategies in real-time, could allow for significant further improvements in the quality of life for movement disorders patients with DBS that ultimately could outperform traditional drug treatment.

Rapid HPLC-ESI-MS/MS Analysis of Neurotransmitters in the Brain Tissue of Alzheimer's Disease Rats before and after Oral Administration of Xanthoceras sorbifolia Bunge

In order to explore the potential therapeutic effect of Xanthoceras sorbifolia Bunge. against Alzheimer’s disease, an HPLC-MS/MS method has been developed and validated for simultaneous determination in rat brain of eight neurotransmitters, including dopamine, norepinephrine, 5-hydroxy-tryptamine, acetylcholine, l-tryptophan, γ-aminobutyric acid, glutamic acid and aspartic acid with a simple protein precipitation method for sample pre-treatment. The brain samples were separated on a polar functional group embedded column, then detected on a 4000 QTrap HPLC-MS/MS system equipped with a turbo ion spray source in positive ion and multiple reaction monitoring mode. The method was fully validated to be precise and accurate within the linearity range of the assay, and successfully applied to compare the neurotransmitters in the rat brain from four groups of normal, Alzheimer’s disease, and the oral administration group of X. sorbifolia extract and huperzine. The results indicated that brain levels of dopamine, norepinephrine and acetyl choline all decreased in the AD rats, while l-tryptophan showed an opposite trend. After administration of the Xanthoceras sorbifolia extract and huperzine, the level of acetyl choline and tryptophan returned to normal. Combination of the metabolic analysis, the results indicated that acetyl choline and l-tryptophan could be employed as therapy biomarkers for AD, and the results shown that the crude extract of the husks from Xanthoceras sorbifolia might ameliorate the impairment of learning and memory in the Alzheimer’s disease animal model with similar function of AchEI as huperzine. The established method would provide an innovative and effective way for the discovery of novel drug against Alzheimer’s disease, and stimulate a theoretical basis for the design and development of new drugs.