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Hodaie, M.

Publications and source records attributed to Hodaie, M..

9 recordsLinked to original sources

Inhibitory Evoked Potentials as a Spatially Dependent Intraoperative Marker of Clinical Tremor Reduction

Deep brain stimulation (DBS) of the ventral intermediate nucleus (Vim) of the thalamus may be used to treat medication refractory essential tremor. Using recordings from in vivo human Vim neurons, our previous work has suggested that evoked potentials (that we termed quasi-evoked inhibition) ~2 ms following high frequency microstimulation pulses may be related to inhibitory synapses onto the Vim. Here, we investigate whether (i) quasi-evoked inhibition is related to clinical tremor reduction, and (ii) if quasi-evoked inhibition is dependent on the stimulation location within the Vim. By developing an objective determination of the presence or absence of quasi-evoked inhibition and utilizing accelerometer recordings, we showed that recordings with quasi-evoked inhibition at 100 Hz microstimulation exhibit greater tremor reduction than those without (P < 0.05, BF > 30). The number of stimulation pulses with quasi-evoked inhibition is also correlated with tremor reduction (rho = 0.18, P < 0.05) at all stimulation frequencies >=100 Hz. Furthermore, by analyzing microelectrode trajectories reconstructed from structural MRIs, we found that proximity to the ventral caudal border (P < 0.005) and to a previously established sweet spot (P < 0.05) are anti-correlated with the number of stimulation pulses with quasi-evoked inhibition. Our findings suggest that quasi-evoked inhibition is a potential biomarker of tremor reduction by means of network inhibition, and the more posterior regions of the Vim may allow for better recruitment of inhibition. This may be useful for closed-loop stimulation design.

neuroscience↗

Frequency-dependent Inhibition during Deep Brain Stimulation of Thalamic Ventral Intermediate Nuclei

Deep brain stimulation (DBS) of the thalamic ventral intermediate nucleus (Vim) has been a standard therapy for essential tremor. It has been shown that high frequency ([&ge;]100Hz) DBS suppresses Vim neuronal firing and tremor activity, however, the underlying mechanisms are not fully understood. Here, we use in vivo recordings (single-unit) of Vim neurons (n=19, people with essential tremor) during different DBS frequencies to investigate whether neuronal suppression during high-frequency DBS occurs at synaptic/cellular levels (e.g., cell inhibition due to synaptic depression/fatigue during high-frequency DBS) or is influenced by network-level effects (e.g., recurrent inhibition). We propose a theoretical framework that explains DBS effects at both cellular and network levels, i.e., (continuous) high-frequency DBS not only depresses synapses projecting to Vim but also enables the recruitment of inhibitory neurons. A transient burst in the spiking activity of Vim during high-frequency DBS, prior to neuronal suppression, is likely providing sufficient network engagement to recruit inhibitory neurons that are silent during low-frequency DBS. Further, we detected a positive-going evoked-field potential effect, hereafter referred to as quasi-evoked inhibition, during high-frequency (100 Hz and 200 Hz) Vim-DBS in four out of 19 recording sites. Interestingly, it was observed that (i) neuronal suppression is stronger in these four neurons (P < 0.05), implying that inhibitory engagement during high-frequency DBS can further suppress neuronal firing, and (ii) quasi-evoked inhibition emerges after the transient burst (P < 1.00 x 10-7), i.e., the latter may give rise to the former. By removing DBS artifacts with a novel algorithm and characterizing the dynamics of quasi-evoked inhibitory activity, we showed that the likelihood of occurrence of this inhibitory activity negatively correlated with the instantaneous firing rate (P < 1.00 x 10-5). These results suggest that an excitatory-inhibitory balance is likely regulating Vim activities during high-frequency DBS. Our findings shed light on potential network mechanisms underlying Vim-DBS, which can provide insight for optimizing DBS by designing new stimulation patterns.

neuroscience↗

Uncovering network mechanism underlying thalamic Deep Brain Stimulation using a novel firing rate model

Thalamic ventral intermediate nucleus (Vim) is the primary surgical target of deep brain stimulation (DBS) for reducing symptoms of essential tremor. High-frequency Vim-DBS ([&ge;]100Hz) has been clinically effective, generating two experimentally-observed features in Vim spiking activity: 1) a large transient excitatory response (lasting <1s), followed by 2) a suppressed steady-state consisting of oscillations. Yet, mechanisms underlying these observations have not been fully understood by previous studies. In this work, we developed a network rate model and a novel parameter optimization method that accurately fit in-vivo single-unit recordings of Vim in human patients with essential tremor receiving a wide range of DBS frequencies (5[~]200Hz). Our model incorporates both the DBS-induced synaptic plasticity of Vim neurons, and the recurrent connections among excitatory and inhibitory neurons in Vim-network. We hypothesized that besides inducing synaptic depression, the therapeutic mechanism of high-frequency Vim-DBS could be to engage more inhibitory neurons in stabilizing the underlying circuits. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=86 SRC="FIGDIR/small/570924v2_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@1e78cbcorg.highwire.dtl.DTLVardef@c8bde1org.highwire.dtl.DTLVardef@12a3bb3org.highwire.dtl.DTLVardef@1b5a0dd_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

Interrogating basal ganglia circuit function in Parkinson's disease and dystonia

BackgroundThe dichotomy between the hypo-versus hyperkinetic nature of Parkinsons disease (PD) and dystonia, respectively, is thought to be reflected in the underlying basal ganglia pathophysiology. ObjectiveInvestigate differences in globus pallidus internus (GPi) neuronal activity, and short- and long-term plasticity of direct pathway projections. ResultsGPi neurons were slower, burstier, and less regular in dystonia. In PD, symptom severity positively correlated with the power of low-beta frequency spiketrain oscillations. In dystonia, symptom severity negatively correlated with firing rate, and positively correlated with neuronal variability and the power of theta frequency spiketrain oscillations. Dystonia was moreover associated with less long-term plasticity and slower synaptic depression. ConclusionWe substantiated claims of hyper-versus hypofunctional GPi output in PD versus dystonia, and provided cellular-level validation of the pathological nature of theta and low-beta oscillations in respective disorders. Such circuit changes may be underlain by disease-related differences in plasticity of striato-pallidal synapses.

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Modelling Instantaneous Firing Rate of DBS Target Neuronal Ensembles in Basal Ganglia and Thalamus

ObjectiveDeep Brain Stimulation (DBS) is an effective treatment for movement disorders, including Parkinsons 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 MethodsBoth synthetic and experimental data were utilized in the model fitting; the synthetic data were generated by an established spiking neuron model that was reported in our previous work 1, and the experimental data were provided using single-unit microelectrode recordings (MER) 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. ResultsOur 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. ConclusionThe result of our model fitting were in agreement with experimental single-unit microelectrode recording 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.

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Single-neuron bursts encode pathological oscillations in Parkinson's disease and essential tremor

Deep brain stimulation procedures offer an invaluable opportunity to study disease through intracranial recordings from awake patients. Herein, we address the relationship between singleneuron and aggregate-level (local field potential; LFP) activities in the subthalamic nucleus (STN) and thalamic ventral intermediate nucleus (Vim) of patients with Parkinsons disease (n=19) and essential tremor (n=16), respectively. Both disorders have been characterized by pathologically elevated LFP oscillations, as well as an increased tendency for neuronal bursting. Our findings suggest that periodic single-neuron bursts encode both pathophysiological beta (13-33Hz; STN) and tremor (4-10Hz; Vim) LFP oscillations, evidenced by strong time-frequency and phase-coupling relationships between the bursting and LFP signals. Spiking activity occurring outside of bursts had no relationship to the LFP. In STN, bursting activity most commonly preceded the LFP oscillation, suggesting that neuronal bursting generated within STN may give rise to an aggregate-level LFP oscillation. In Vim, LFP oscillations most commonly preceded bursting activity, suggesting that neuronal firing may be entrained by periodic afferent inputs. In both STN and Vim, the phasecoupling relationship between LFP and high-frequency oscillation (HFO) signals closely resembled the relationships between the LFP and single-neuron bursting. This suggests that periodic singleneuron bursting is likely representative of a higher spatial and temporal resolution readout of periodic increases in the amplitude of HFOs, which themselves may be a higher resolution readout of aggregate-level LFP oscillations. Overall, our results may reconcile "rate" and "oscillation" models of Parkinsons disease and shed light onto the single-neuron basis and origin of pathophysiological oscillations in movement disorders. SignificanceIn surgical patients with Parkinsons disease and essential tremor, we leverage intracranial recordings to establish a link between pathophysiological phenomena across various scales of observation (spatio-temporal resolutions). We provide insights and reconcile theories about aberrant neurocircuit phenomena which underly theses debilitating, medically refractory movement disorders. Furthermore, our connectivity analyses between single-neuron and local field potential activities may shed light on the origin of the deleterious neural oscillations underlying these disorders. Ultimately, our findings may aid in the development or investigation of targeted therapies to address or correct underlying neurocircuit dysfunction, which can include neuropharmaceuticals, but also novel neuromodulatory strategies like closed-loop deep brain stimulation targeting pathophysiological oscillations and phase-dependent stimulation methods seeking to stimulate "at the right time/phase."

neuroscience↗

Persistent synaptic inhibition of the subthalamic nucleus by high frequency stimulation

BackgroundDeep brain stimulation (DBS) provides symptomatic relief in a growing number of neurological indications, but local synaptic dynamics in response to electrical stimulation that may relate to its mechanism of action have not been fully characterized. ObjectiveThe objectives of this study were to (1) study local synaptic dynamics during high frequency extracellular stimulation of the subthalamic nucleus (STN), and (2) compare STN synaptic dynamics with those of the neighboring substantia nigra pars reticulata (SNr). MethodsTwo microelectrodes were advanced into the STN and SNr of patients undergoing DBS surgery for PD. Neuronal firing and evoked field potentials (fEPs) were recorded with one microelectrode during stimulation from an adjacent microelectrode. ResultsExcitatory and inhibitory fEPs could be discerned within the STN and their amplitudes predicted bidirectional effects on neuronal firing (p = .007). There were no differences between STN and SNr inhibitory fEP dynamics at low stimulation frequencies (p > .999). However, inhibitory neuronal responses were sustained over time in STN during high frequency stimulation, but not SNr (p < .001) where depression of inhibitory input was coupled with a return of neuronal firing (p = .003). InterpretationPersistent inhibitory input to the STN suggests a local synaptic mechanism for the suppression of subthalamic firing during high frequency stimulation. Moreover, differences in the resiliency versus vulnerability of inhibitory inputs to the STN and SNr suggest a projection source- and frequency-specificity for this mechanism. The feasibility of targeting electrophysiologically-identified neural structures may provide insight into how DBS achieves frequency-specific modulation of neuronal projections.

neuroscience↗

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

With the growing interest in the expansion of deep brain stimulation indications, we aimed to provide experimental and computational insights into the brain-region-specific and frequency-dependent effects of extracellular stimulation on human neuronal activity. Experimentally, we demonstrated microstimulation-evoked excitatory neuronal responses in the ventral intermediate nucleus and reticular thalamus, and inhibitory responses in the subthalamic nucleus and substantia nigra pars reticulata; hypothesized to be the result of simultaneous activations of convergent afferent inputs. Higher stimulation frequencies led to a loss of site-specificity and convergence towards neuronal suppression; hypothesized to be mediated by synaptic depression. These experimental findings were reproduced by a computational framework in which relative distributions of convergent excitatory/inhibitory afferents were embedded within a model of short-term synaptic plasticity for the prediction of site-specific and frequency-dependent responses to extracellular stimulation. This theoretical framework may aid in the design of physiologically-informed stimulation paradigms in existing or prospective deep brain stimulation indications.

neuroscience↗

Diffusion Weighted Image Co-registration: Investigation of Best Practices

1.The registration or alignment of diffusion weighted images (DWI) with other imaging modalities is a critical step in neuroimaging analysis. Within-subject T1-DWI co-registration is particularly instrumental. DWI-derived scalar images are commonly used as intermediates for T1-DWI co-registration, and the resulting registration transforms are applied to all other scalar images for analysis. The ideal registration intermediate should register well to T1 and other multimodal images and be practically easy to obtain. It is however, currently unclear which DWI-derived scalar image serves as the best intermediate. We aim to determine the best, practical, intermediate for image co-registration. T1 and DWI images were acquired from 20 healthy subjects. DWIs were acquired with 60 directions. Six DWI-derived scalar images were compared including: 1) fractional anisotropy (FA); 2) generalized FA (GFA); 3) B0 images; 4) mean DWIs with the B0 image (MDWI); 5) anisotropic power (AP) images. AP showed the smallest variability in registration improvements across all the tested DWI derived scalar images, and show the highest average percent changes with CC registration cost function (CC=1.2%, MI=15%). In contrast, the FA and GFA transforms resulted in significantly poorer registration across DWI types. The AP image was the DWI-derived scalar image that provided the most consistent registration to all other images. Practically, it is generated easily and so could be implemented in basic and clinical research pipelines currently using other intermediates. Given these findings, it is recommended that AP images be used for T1-DWI co-registration, and that FA and GFA images in particular be avoided.

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