Sixty Hertz Neurostimulation Amplifies Subthalamic Neural Synchrony in Parkinson’s Disease

High frequency subthalamic nucleus (STN) deep brain stimulation (DBS) improves the cardinal motor signs of Parkinson’s disease (PD) and attenuates STN alpha/beta band neural synchrony in a voltage-dependent manner. While there is a growing interest in the behavioral effects of lower frequency (60 Hz) DBS, little is known about its effect on STN neural synchrony. Here we demonstrate for the first time that during intra-operative 60 Hz STN DBS, one or more bands of resting state neural synchrony were amplified in the STN in PD. We recorded intra-operative STN resting state local field potentials (LFPs) from twenty-eight STNs in seventeen PD subjects after placement of the DBS lead (model 3389, Medtronic, Inc.) before and during three randomized neurostimulation sets (130 Hz/1.35V, 130 Hz/2V, 60 Hz/2V). During 130 Hz/2V DBS, baseline (no DBS) STN alpha (8 – 12 Hz) and beta (13 – 35 Hz) band power decreased (N=14, P < 0.001 for both), whereas during 60 Hz/2V DBS, alpha band and peak frequency power increased (P = 0.012, P = 0.007, respectively). The effect of 60 Hz/2V DBS opposed that of power-equivalent (130 Hz/1.35V) DBS (alpha: P < 0.001, beta: P = 0.006). These results show that intra-operative 60 Hz STN DBS amplified whereas 130 Hz STN DBS attenuated resting state neural synchrony in PD; the effects were frequency-specific. We demonstrate that neurostimulation may be useful as a tool to selectively modulate resting state resonant bands of neural synchrony and to investigate its influence on motor and non-motor behaviors in PD and other neuropsychiatric diseases.     

Subthalamic local field beta oscillations during ongoing deep brain stimulation in Parkinson's disease in hyperacute and chronic phases

In the past years, local field potential (LFP) signals recorded from the subthalamic nucleus (STN) in patients undergoing deep brain stimulation (DBS) for Parkinson's disease (PD) disclosed that DBS has a controversial effect on STN beta oscillations recorded 2-7 days after surgery for macroelectrode implantation. Nothing is known about these DBS-induced oscillatory changes 30 days after surgery. We recorded STN LFPs during ongoing DBS in 7 patients with PD, immediately (hyperacute phase) and 30 days (chronic phase) after surgery. STN LFP recordings showed stationary intranuclear STN beta LFP activity in hyperacute and chronic phases, confirming that beta peaks were also present in chronic recordings. Power spectra of nuclei with significant beta activity (54% of the sample) showed that it decreased significantly during DBS (p=0.021) under both recording conditions. The time course of beta activity showed more evident DBS-induced changes in the chronic than in the hyperacute phase (p=0.014). DBS-induced changes in STN beta LFPs in patients undergoing DBS in chronic phase provide useful information for developing a new neurosignal-controlled adaptive DBS system.     

A computational modelling approach to investigate different targets in deep brain stimulation for Parkinson’s disease

We investigated by a computational model of the basal ganglia the different network effects of deep brain stimulation (DBS) for Parkinson’s disease (PD) in different target sites in the subthalamic nucleus (STN), the globus pallidus pars interna (GPi), and the globus pallidus pars externa (GPe). A cellular-based model of the basal ganglia system (BGS), based on the model proposed by Rubin and Terman (J Comput Neurosci 16:211–235, 2004), was developed. The original Rubin and Terman model was able to reproduce both the physiological and pathological activities of STN, GPi, GPe and thalamo-cortical (TC) relay cells. In the present study, we introduced a representation of the direct pathway of the BGS, allowing a more complete framework to simulate DBS and to interpret its network effects in the BGS. Our results suggest that DBS in the STN could functionally restore the TC relay activity, while DBS in the GPe and in the GPi could functionally over-activate and inhibit it, respectively. Our results are consistent with the experimental and the clinical evidences on the network effects of DBS.     

Optimal deep brain stimulation of the subthalamic nucleus—a computational study

Deep brain stimulation (DBS) of the subthalamic nucleus, typically with periodic, high frequency pulse trains, has proven to be an effective treatment for the motor symptoms of Parkinson’s disease (PD). Here, we use a biophysically-based model of spiking cells in the basal ganglia (Terman et al., Journal of Neuroscience, 22, 2963–2976, 2002; Rubin and Terman, Journal of Computational Neuroscience, 16, 211–235, 2004) to provide computational evidence that alternative temporal patterns of DBS inputs might be equally effective as the standard high-frequency waveforms, but require lower amplitudes. Within this model, DBS performance is assessed in two ways. First, we determine the extent to which DBS causes Gpi (globus pallidus pars interna) synaptic outputs, which are burstlike and synchronized in the unstimulated Parkinsonian state, to cease their pathological modulation of simulated thalamocortical cells. Second, we evaluate how DBS affects the GPi cells’ auto- and cross-correlograms. In both cases, a nonlinear closed-loop learning algorithm identifies effective DBS inputs that are optimized to have minimal strength. The network dynamics that result differ from the regular, entrained firing which some previous studies have associated with conventional high-frequency DBS. This type of optimized solution is also found with heterogeneity in both the intrinsic network dynamics and the strength of DBS inputs received at various cells. Such alternative DBS inputs could potentially be identified, guided by the model-free learning algorithm, in experimental or eventual clinical settings. Action Editor: Steven J. Schiff Xiao-Jiang Feng and Eric Shea-Brown contributed equally to this work.     

Relative contributions of local cell and passing fiber activation and silencing to changes in thalamic fidelity during deep brain stimulation and lesioning: a computational modeling study

Deep brain stimulation (DBS) and lesioning are two surgical techniques used in the treatment of advanced Parkinson’s disease (PD) in patients whose symptoms are not well controlled by drugs, or who experience dyskinesias as a side effect of medications. Although these treatments have been widely practiced, the mechanisms behind DBS and lesioning are still not well understood. The subthalamic nucleus (STN) and globus pallidus pars interna (GPi) are two common targets for both DBS and lesioning. Previous studies have indicated that DBS not only affects local cells within the target, but also passing axons within neighboring regions. Using a computational model of the basal ganglia-thalamic network, we studied the relative contributions of activation and silencing of local cells (LCs) and fibers of passage (FOPs) to changes in the accuracy of information transmission through the thalamus (thalamic fidelity), which is correlated with the effectiveness of DBS. Activation of both LCs and FOPs during STN and GPi-DBS were beneficial to the outcome of stimulation. During STN and GPi lesioning, effects of silencing LCs and FOPs were different between the two types of lesioning. For STN lesioning, silencing GPi FOPs mainly contributed to its effectiveness, while silencing only STN LCs did not improve thalamic fidelity. In contrast, silencing both GPi LCs and GPe FOPs during GPi lesioning contributed to improvements in thalamic fidelity. Thus, two distinct mechanisms produced comparable improvements in thalamic function: driving the output of the basal ganglia to produce tonic inhibition and silencing the output of the basal ganglia to produce tonic disinhibition. These results show the importance of considering effects of activating or silencing fibers passing close to the nucleus when deciding upon a target location for DBS or lesioning.     

Closed-loop deep brain stimulation is superior in ameliorating parkinsonism

Continuous high-frequency deep brain stimulation (DBS) is a widely used therapy for advanced Parkinson's disease (PD) management. However, the mechanisms underlying DBS effects remain enigmatic and are the subject of an ongoing debate. Here, we present and test a closed-loop stimulation strategy for PD in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) primate model of PD. Application of pallidal closed-loop stimulation leads to dissociation between changes in basal ganglia (BG) discharge rates and patterns, providing insights into PD pathophysiology. Furthermore, cortico-pallidal closed-loop stimulation has a significantly greater effect on akinesia and on cortical and pallidal discharge patterns than standard open-loop DBS and matched control stimulation paradigms. Thus, closed-loop DBS paradigms, by modulating pathological oscillatory activity rather than the discharge rate of the BG-cortical networks, may afford more effective management of advanced PD. Such strategies have the potential to be effective in additional brain disorders in which a pathological neuronal discharge pattern can be recognized.     

Increased bradykinesia in Parkinson’s disease with increased movement complexity: elbow flexion–extension movements

The present research investigates factors contributing to bradykinesia in the control of simple and complex voluntary limb movement in Parkinson’s disease (PD) patients. The functional scheme of the basal ganglia (BG)–thalamocortical circuit was described by a mathematical model based on the mean firing rates of BG nuclei. PD was simulated as a reduction in dopamine levels, and a loss of functional segregation between two competing motor modules. In order to compare model simulations with performed movements, flexion and extension at the elbow joint is taken as a test case. Results indicated that loss of segregation contributed to bradykinesia due to interference between competing modules and a reduced ability to suppress unwanted movements. Additionally, excessive neurotransmitter depletion is predicted as a possible mechanism for the increased difficulty in performing complex movements. The simulation results showed that the model is in qualitative agreement with the results from movement experiments on PD patients and healthy subjects. Furthermore, based on changes in the firing rate of BG nuclei, the model demonstrated that the effective mechanism of Deep Brain Stimulation (DBS) in STN may result from stimulation induced inhibition of STN, partial synaptic failure of efferent projections, or excitation of inhibitory afferent axons even though the underlying methods of action may be quite different for the different mechanisms.     

Time and Frequency-Dependent Modulation of Local Field Potential Synchronization by Deep Brain Stimulation

High-frequency electrical stimulation of specific brain structures, known as deep brain stimulation (DBS), is an effective treatment for movement disorders, but mechanisms of action remain unclear. We examined the time-dependent effects of DBS applied to the entopeduncular nucleus (EP), the rat homolog of the internal globus pallidus, a target used for treatment of both dystonia and Parkinson’s disease (PD). We performed simultaneous multi-site local field potential (LFP) recordings in urethane-anesthetized rats to assess the effects of high-frequency (HF, 130 Hz; clinically effective), low-frequency (LF, 15 Hz; ineffective) and sham DBS delivered to EP. LFP activity was recorded from dorsal striatum (STR), ventroanterior thalamus (VA), primary motor cortex (M1), and the stimulation site in EP. Spontaneous and acute stimulation-induced LFP oscillation power and functional connectivity were assessed at baseline, and after 30, 60, and 90 minutes of stimulation. HF EP DBS produced widespread alterations in spontaneous and stimulus-induced LFP oscillations, with some effects similar across regions and others occurring in a region- and frequency band-specific manner. Many of these changes evolved over time. HF EP DBS produced an initial transient reduction in power in the low beta band in M1 and STR; however, phase synchronization between these regions in the low beta band was markedly suppressed at all time points. DBS also enhanced low gamma synchronization throughout the circuit. With sustained stimulation, there were significant reductions in low beta synchronization between M1-VA and STR-VA, and increases in power within regions in the faster frequency bands. HF DBS also suppressed the ability of acute EP stimulation to induce beta oscillations in all regions along the circuit. This dynamic pattern of synchronizing and desynchronizing effects of EP DBS suggests a complex modulation of activity along cortico-BG-thalamic circuits underlying the therapeutic effects of GPi DBS for conditions such as PD and dystonia.     

Deep brain stimulation

During the last decade deep brain stimulation (DBS) has become a routine method for the treatment of advanced Parkinsons disease (PD), leading to striking improvements in motor function and quality of life of PD patients. It is associated with minimal morbidity. The rationale of targeting specific structures within basal ganglia such as the subthalamic nucleus (STN) or the internal segment of the globus pallidus (GPi) is strongly supported by the current knowledge of the basal ganglia pathophysiology, which is derived from extensive experimental work and which provides the theoretical basis for surgical therapy in PD. In particular, the STN has advanced to the worldwide most used target for DBS in the treatment of PD, due to the marked improvement of all cardinal symptoms of the disease. Moreover on-period dyskinesias are reduced in parallel with a marked reduction of the equivalent daily levodopa dose following STN–DBS. The success of the therapy largely depends on the selection of the appropriate candidate patients and on the precise implantation of the stimulation electrode, which necessitates careful imaging-based pre-targeting and extensive electrophysiological exploration of the target area. Despite the clinical success of the therapy, the fundamental mechanisms of high-frequency stimulation are still not fully elucidated. There is a large amount of evidence from experimental and clinical data that stimulation frequency represents a key factor with respect to clinical effect of DBS. Interestingly, high-frequency stimulation mimics the functional effects of ablation in various brain structures. The main hypotheses for the mechanism of high-frequency stimulation are: (1) depolarization blocking of neuronal transmission through inactivation of voltage dependent ion-channels, (2) jamming of information by imposing an efferent stimulation-driven high-frequency pattern, (3) synaptic inhibition by stimulation of inhibitory afferents to the target nucleus, (4) synaptic failure by stimulation-induced neurotransmitter depletion. As the hyperactivity of the STN is considered a functional hallmark of PD and as there is experimental evidence for STN-mediated glutamatergic excitotoxicity on neurons of the substantia nigra pars compacta (SNc), STN–DBS might reduce glutamatergic drive, leading to neuroprotection. Further studies will be needed to elucidate if STN–DBS indeed provides a slow-down of disease progression.     

Modeling shifts in the rate and pattern of subthalamopallidal network activity during deep brain stimulation

Deep brain stimulation (DBS) of the subthlamic nucleus (STN) represents an effective treatment for medically refractory Parkinson’s disease; however, understanding of its effects on basal ganglia network activity remains limited. We constructed a computational model of the subthalamopallidal network, trained it to fit in vivo recordings from parkinsonian monkeys, and evaluated its response to STN DBS. The network model was created with synaptically connected single compartment biophysical models of STN and pallidal neurons, and stochastically defined inputs driven by cortical beta rhythms. A least mean square error training algorithm was developed to parameterize network connections and minimize error when compared to experimental spike and burst rates in the parkinsonian condition. The output of the trained network was then compared to experimental data not used in the training process. We found that reducing the influence of the cortical beta input on the model generated activity that agreed well with recordings from normal monkeys. Further, during STN DBS in the parkinsonian condition the simulations reproduced the reduction in GPi bursting found in existing experimental data. The model also provided the opportunity to greatly expand analysis of GPi bursting activity, generating three major predictions. First, its reduction was proportional to the volume of STN activated by DBS. Second, GPi bursting decreased in a stimulation frequency dependent manner, saturating at values consistent with clinically therapeutic DBS. And third, ablating STN neurons, reported to generate similar therapeutic outcomes as STN DBS, also reduced GPi bursting. Our theoretical analysis of stimulation induced network activity suggests that regularization of GPi firing is dependent on the volume of STN tissue activated and a threshold level of burst reduction may be necessary for therapeutic effect.     

Origins and suppression of oscillations in a computational model of Parkinson’s disease

Efficacy of deep brain stimulation (DBS) for motor signs of Parkinson’s disease (PD) depends in part on post-operative programming of stimulus parameters. There is a need for a systematic approach to tuning parameters based on patient physiology. We used a physiologically realistic computational model of the basal ganglia network to investigate the emergence of a 34 Hz oscillation in the PD state and its optimal suppression with DBS. Discrete time transfer functions were fit to post-stimulus time histograms (PSTHs) collected in open-loop, by simulating the pharmacological block of synaptic connections, to describe the behavior of the basal ganglia nuclei. These functions were then connected to create a mean-field model of the closed-loop system, which was analyzed to determine the origin of the emergent 34 Hz pathological oscillation. This analysis determined that the oscillation could emerge from the coupling between the globus pallidus external (GPe) and subthalamic nucleus (STN). When coupled, the two resonate with each other in the PD state but not in the healthy state. By characterizing how this oscillation is affected by subthreshold DBS pulses, we hypothesize that it is possible to predict stimulus frequencies capable of suppressing this oscillation. To characterize the response to the stimulus, we developed a new method for estimating phase response curves (PRCs) from population data. Using the population PRC we were able to predict frequencies that enhance and suppress the 34 Hz pathological oscillation. This provides a systematic approach to tuning DBS frequencies and could enable closed-loop tuning of stimulation parameters.     

A neural model of basal ganglia-thalamocortical relations in normal and parkinsonian movement

 Anatomical, neurophysiological, and neurochemical evidence supports the notion of parallel basal ganglia–thalamocortical motor systems. We developed a neural network model for the functioning of these systems during normal and parkinsonian movement. Parkinson’s disease (PD), which results predominantly from nigrostriatal pathway damage, is used as a window to examine basal ganglia function. Simulations of dopamine depletion produce motor impairments consistent with motor deficits observed in PD that suggest the basal ganglia play a role in motor initiation and execution, and sequencing of motor programs. Stereotaxic lesions in the model’s globus pallidus and subthalamic nucleus suggest that these lesions, although reducing some PD symptoms, may constrain the repertoire of available movements. It is proposed that paradoxical observations of basal ganglia responses reported in the literature may result from regional functional neuronal specialization, and the non-uniform distributions of neurochemicals in the basal ganglia. It is hypothesized that dopamine depletion produces smaller-than-normal pallidothalamic gating signals that prevent rescalability of these signals to control variable movement speed, and that in PD can produce smaller-than-normal movement amplitudes. Received: 1 September 1994/Accepted in revised form: 16 May 1995     

Computational modeling of epileptiform activities in medial temporal lobe epilepsy combined with <Emphasis Type="Italic">in vitro</Emphasis> experiments

Electrical stimulation of sub-cortical brain regions (the basal ganglia), known as deep brain stimulation (DBS), is an effective treatment for Parkinson’s disease (PD). Chronic high frequency (HF) DBS in the subthalamic nucleus (STN) or globus pallidus interna (GPi) reduces motor symptoms including bradykinesia and tremor in patients with PD, but the therapeutic mechanisms of DBS are not fully understood. We developed a biophysical network model comprising of the closed loop cortical-basal ganglia-thalamus circuit representing the healthy and parkinsonian rat brain. The network properties of the model were validated by comparing responses evoked in basal ganglia (BG) nuclei by cortical (CTX) stimulation to published experimental results. A key emergent property of the model was generation of low-frequency network oscillations. Consistent with their putative pathological role, low-frequency oscillations in model BG neurons were exaggerated in the parkinsonian state compared to the healthy condition. We used the model to quantify the effectiveness of STN DBS at different frequencies in suppressing low-frequency oscillatory activity in GPi. Frequencies less than 40 Hz were ineffective, low-frequency oscillatory power decreased gradually for frequencies between 50 Hz and 130 Hz, and saturated at frequencies higher than 150 Hz. HF STN DBS suppressed pathological oscillations in GPe/GPi both by exciting and inhibiting the firing in GPe/GPi neurons, and the number of GPe/GPi neurons influenced was greater for HF stimulation than low-frequency stimulation. Similar to the frequency dependent suppression of pathological oscillations, STN DBS also normalized the abnormal GPi spiking activity evoked by CTX stimulation in a frequency dependent fashion with HF being the most effective. Therefore, therapeutic HF STN DBS effectively suppresses pathological activity by influencing the activity of a greater proportion of neurons in the output nucleus of the BG.     

Glutamate and Parkinson’s disease

Altered glutamatergic neurotransmission and neuronal metabolic dysfunction appear to be central to the pathophysiology of Parkinson’s disease (PD). The substantia nigra pars compacta—the area where the primary pathological lesion is located—is particularly exposed to oxidative stress and toxic and metabolic insults. A reduced capacity to cope with metabolic demands, possibly related to impaired mitochondrial function, may render nigral neurons highly vulnerable to the effects of glutamate, which acts as a neurotoxin in the presence of impaired cellular energy metabolism. In this way, glutamate may participate in the pathogenesis of PD. Degeneration of dopamine nigral neurons is followed by striatal dopaminergic denervation, which causes a cascade of functional modifications in the activity of basal ganglia nuclei. As an excitatory neurotransmitter, glutamate plays a pivotal role in normal basal ganglia circuitry. With nigrostriatal dopaminergic depletion, the glutamatergic projections from subthalamic nucleus to the basal ganglia output nuclei become overactive and there are regulatory changes in glutamate receptors in these regions. There is also evidence of increased glutamatergic activity in the striatum. In animal models, blockade of glutamate receptors ameliorates the motor manifestations of PD. Therefore, it appears that abnormal patterns of glutamatergic neurotransmission are important in the symptoms of PD. The involvement of the glutamatergic system in the pathogenesis and symptomatology of PD provides potential new targets for therapeutic intervention in this neuro-degenerative disorder.     

The effects of DBS patterns on basal ganglia activity and thalamic relay

Thalamic neurons receive inputs from cortex and their responses are modulated by the basal ganglia (BG). This modulation is necessary to properly relay cortical inputs back to cortex and downstream to the brain stem when movements are planned. In Parkinson's disease (PD), the BG input to thalamus becomes pathological and relay of motor-related cortical inputs is compromised, thereby impairing movements. However, high frequency (HF) deep brain stimulation (DBS) may be used to restore relay reliability, thereby restoring movements in PD patients. Although therapeutic, HF stimulation consumes significant power forcing surgical battery replacements, and may cause adverse side effects. Here, we used a biophysical-based model of the BG-Thalamus motor loop in both healthy and PD conditions to assess whether low frequency stimulation can suppress pathological activity in PD and enable the thalamus to reliably relay movement-related cortical inputs. We administered periodic pulse train DBS waveforms to the sub-thalamic nucleus (STN) with frequencies ranging from 0-140 Hz, and computed statistics that quantified pathological bursting, oscillations, and synchronization in the BG as well as thalamic relay of cortical inputs. We found that none of the frequencies suppressed all pathological activity in BG, though the HF waveforms recovered thalamic reliability. Our rigorous study, however, led us to a novel DBS strategy involving low frequency multi-input phase-shifted DBS, which successfully suppressed pathological symptoms in all BG nuclei and enabled reliable thalamic relay. The neural restoration remained robust to changes in the model parameters characterizing early to late PD stages.     

Functional connectivity between prefrontal cortex and striatum estimated by phase locking value

The interplay between the prefrontal cortex (PFC) and striatum has an important role in cognitive processes. To investigate interactive functions between the two areas in reward processing, we recorded local field potentials (LFPs) simultaneously from the two areas of two monkeys performing a reward prediction task (large reward vs small reward). The power of the LFPs was calculated in three frequency bands: the beta band (15–29 Hz), the low gamma band (30–49 Hz), and the high gamma band (50–100 Hz). We found that both the PFC and striatum encoded the reward information in the beta band. The reward information was also found in the high gamma band in the PFC, not in the striatum. We further calculated the phase-locking value (PLV) between two LFP signals to measure the phase synchrony between the PFC and striatum. It was found that significant differences occurred between PLVs in different task periods and in different frequency bands. The PLVs in small reward condition were significant higher than that in large reward condition in the beta band. In contrast, the PLVs in the high gamma band were stronger in large reward trials than in small trials. These results suggested that the functional connectivity between the PFC and striatum depended on the task periods and reward conditions. The beta synchrony between the PFC and striatum may regulate behavioral outputs of the monkeys in the small reward condition.     

Role of Tuberin in Neuronal Degeneration

One of the tuberous sclerosis complex (TSC) gene products, tuberin is assumed to be the functional component, being involved in a wide variety of cellular processes. Here, we report for the first time that tuberin dysfunction may represent a mechanism for neuronal damage in Alzheimer’s disease (AD), Parkinson’s disease with dementia (PD/DLB), and a mouse model of PD. Tuberin was hyperphosphorylated at Thr1462 in post-mortem frontal cortex tissue of both AD and PD/DLB patients and in mice treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine hydrochloride (MPTP). Both PTEN and Akt phosphoactivation corresponded to the hyperphosphorylation patterns of tuberin suggesting that the PTEN–Akt pathway might be the mechanism of tuberin phosphorylation. Our data provide new information regarding the possible role of tuberin dysfunction in major neurodegenerative disorders, such as AD and PD, whereby inhibition of tuberin function may trigger an onset of neuronal cell death.     

Therapeutic Subthalamic Nucleus Deep Brain Stimulation Reverses Cortico-Thalamic Coupling during Voluntary Movements in Parkinson's Disease

Deep brain stimulation of the subthalamic nucleus (STN DBS) has become an accepted treatment for patients experiencing the motor complications of Parkinson''s disease (PD). While its successes are becoming increasingly apparent, the mechanisms underlying its action remain unclear. Multiple studies using radiotracer-based imaging have investigated DBS-induced regional changes in neural activity. However, little is known about the effect of DBS on connectivity within neural networks; in other words, whether DBS impacts upon functional integration of specialized regions of cortex. In this work, we report the first findings of fMRI in 10 subjects with PD and fully implanted DBS hardware receiving efficacious stimulation. Despite the technical demands associated with the safe acquisition of fMRI data from patients with implanted hardware, robust activation changes were identified in the insula cortex and thalamus in response to therapeutic STN DBS. We then quantified the neuromodulatory effects of DBS and compared sixteen dynamic causal models of effective connectivity between the two identified nodes. Using Bayesian model comparison, we found unequivocal evidence for the modulation of extrinsic (between region), i.e. cortico-thalamic and thalamo-cortical connections. Using Bayesian model parameter averaging we found that during voluntary movements, DBS reversed the effective connectivity between regions of the cortex and thalamus. This casts the therapeutic effects of DBS in a fundamentally new light, emphasising a role in changing distributed cortico-subcortical interactions. We conclude that STN DBS does impact upon the effective connectivity between the cortex and thalamus by changing their sensitivities to extrinsic afferents. Furthermore, we confirm that fMRI is both feasible and is tolerated well by these patients provided strict safety measures are adhered to.     

Theoretical Analysis of the Local Field Potential in Deep Brain Stimulation Applications

Deep brain stimulation (DBS) is a common therapy for treating movement disorders, such as Parkinson’s disease (PD), and provides a unique opportunity to study the neural activity of various subcortical structures in human patients. Local field potential (LFP) recordings are often performed with either intraoperative microelectrodes or DBS leads and reflect oscillatory activity within nuclei of the basal ganglia. These LFP recordings have numerous clinical implications and might someday be used to optimize DBS outcomes in closed-loop systems. However, the origin of the recorded LFP is poorly understood. Therefore, the goal of this study was to theoretically analyze LFP recordings within the context of clinical DBS applications. This goal was achieved with a detailed recording model of beta oscillations (∼20 Hz) in the subthalamic nucleus. The recording model consisted of finite element models of intraoperative microelectrodes and DBS macroelectrodes implanted in the brain along with multi-compartment cable models of STN projection neurons. Model analysis permitted systematic investigation into a number of variables that can affect the composition of the recorded LFP (e.g. electrode size, electrode impedance, recording configuration, and filtering effects of the brain, electrode-electrolyte interface, and recording electronics). The results of the study suggest that the spatial reach of the LFP can extend several millimeters. Model analysis also showed that variables such as electrode geometry and recording configuration can have a significant effect on LFP amplitude and spatial reach, while the effects of other variables, such as electrode impedance, are often negligible. The results of this study provide insight into the origin of the LFP and identify variables that need to be considered when analyzing LFP recordings in clinical DBS applications.     

Role of spike-frequency adaptation in shaping neuronal response to dynamic stimuli

Spike-frequency adaptation is the reduction of a neuron’s firing rate to a stimulus of constant intensity. In the locust, the Lobula Giant Movement Detector (LGMD) is a visual interneuron that exhibits rapid adaptation to both current injection and visual stimuli. Here, a reduced compartmental model of the LGMD is employed to explore adaptation’s role in selectivity for stimuli whose intensity changes with time. We show that supralinearly increasing current injection stimuli are best at driving a high spike count in the response, while linearly increasing current injection stimuli (i.e., ramps) are best at attaining large firing rate changes in an adapting neuron. This result is extended with in vivo experiments showing that the LGMD’s response to translating stimuli having a supralinear velocity profile is larger than the response to constant or linearly increasing velocity translation. Furthermore, we show that the LGMD’s preference for approaching versus receding stimuli can partly be accounted for by adaptation. Finally, we show that the LGMD’s adaptation mechanism appears well tuned to minimize sensitivity for the level of basal input. This article is part of a special issue on Neuronal Dynamics of Sensory Coding.