Biology subjects

Crompton, D.

Publications and source records attributed to Crompton, D..

8 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2026

Differentiating filter-induced oscillations from physiological stimulation-evoked potentials in intracranial recordings

IntroductionStimulation-evoked potentials (SEPs), recorded both during and after deep brain stimulation (DBS) surgery, have shown promise for guiding DBS targeting and programming. However, filtering protocols applied to stimulation trains produce an artifact we call a filter-induced oscillation (FIO) which closely mimics physiological SEPs. Hence, we outline the mechanistic origins of this distortion and describe a means of differentiating it from valid SEP activity. MethodsWe recorded in 18 patients undergoing DBS surgery targeting the subthalamic nucleus or globus pallidus internus. We stimulated target nuclei with cathode-first (CF) and anode-first (AF) pulses to record native SEPs, and in white matter tracts (null condition). Recordings were subsequently filtered to illustrate FIO. Next, we filtered harmonic frequencies of an artificial stimulation train to demonstrate FIO origins. Finally, FIO was deliberately generated in white matter recordings with a notch filter, and its behaviour contrasted with SEPs during AF and CF stimulation. ResultsFiltering stimulation trains produced FIOs that depended on filter order and corner frequency. We also showed that FIO emerges from filter-induced attenuations of harmonic frequencies which compose stimulation trains, producing oscillations of like frequency around pulses. Finally, FIOs reverse in polarity depending on AF or CF stimulation, whereas SEPs do not. ConclusionsGiven the potential for widespread adoption of SEPs in DBS targeting and programming, safe analytical protocols are imperative to avoid the induction of processing-related artifacts which can be misinterpreted as biological signals. Here we establish the necessary theory for identifying FIOs and tuning analytical pipelines to avoid their generation.

neuroscience↗

bioRxiv2025

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 ([≥]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↗

bioRxiv2024

FiNNpy 2.0: Fast MEG source reconstruction

Herein, we present the 2.0 update of FiNNpy, which expands the toolkits initial scope from the analysis of multi-site electrophysiological activity to track information propagation to include source reconstruction capability for MEG signals. Following the toolkits de- sign guidelines, the new functionality has been optimized towards minimal resource consumption, making source reconstruction much faster, especially when executed in a parallelized fashion. Furthermore, several quality-of-life aspects are introduced to support source reconstruction, such as grouping source-space activity into cortical areas, a cohesive documentation & in-code extensive literature references, and wrapping of previously terminal exclusive functions of FreeSurfer.

neuroscience↗

bioRxiv2023

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 ([≥]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↗

bioRxiv2022

Reduced oriens-lacunosum/moleculare (OLM)cell model identifies biophysical currentbalances for in vivo theta frequency spikingresonance

Conductance-based models have played an important role in the development of modern neuroscience. These mathematical models are powerful "tools" that enable theoretical explorations in experimentally untenable situations, and can lead to the development of novel hypotheses and predictions. With advances in cell imaging and computational power, multi-compartment models with morphological accuracy are becoming common practice. However, as more biological details are added, they make extensive explorations and analyses more challenging largely due to their huge computational expense. Here, we focus on oriens-lacunosum/moleculare (OLM) cell models. OLM cells can contribute to functionally relevant theta rhythms in the hippocampus by virtue of their ability to express spiking resonance at theta frequencies, but what characteristics underlie this is far from clear. We converted a previously developed detailed multi-compartment OLM cell model into a reduced single compartment model that retained biophysical fidelity with its underlying ion currents. We showed that the reduced OLM cell model can capture complex output that includes spiking resonance in in vivo-like scenarios as previously obtained with the multi-compartment model. Using the reduced model, we were able to greatly expand our in vivo-like scenarios. Applying spike-triggered average analyses, we were thus able to to determine that it is a combination of hyperpolarization-activated cation and muscarinic type potassium currents that specifically allow OLM cells to exhibit spiking resonance at theta frequencies. Further, we developed a robust Kalman Filtering (KF) method to estimate parameters of the reduced model in real-time. We showed that it may be possible to directly estimate conductance parameters from experiments since this KF method can reliably extract parameter values from model voltage recordings. Overall, our work showcases how the contribution of cellular biophysical current details could be determined and assessed for spiking resonance. As well, our work shows that it may be possible to directly extract these parameters from current clamp voltage recordings.

neuroscience↗

bioRxiv2022

Adaptive Unscented Kalman Filter for Neuronal State and Parameter Estimation

Data assimilation techniques for state and parameter estimation are frequently applied in the context of computational neuroscience. In this work, we show how an adaptive variant of the unscented Kalman filter (UKF) performs on the tracking of a conductance-based neuron model. Unlike standard recursive filter implementations, the robust adaptive unscented Kalman filter (RAUKF) jointly estimates the states and parameters of the neuronal model while adjusting noise covariance matrices online based on innovation and residual information. We benchmark the adaptive filters performance against existing nonlinear Kalman filters and explore the sensitivity of the filter parameters to the system being modelled. To evaluate the robustness of the proposed solution, we simulate practical settings that challenge tracking performance, such as a model mismatch and measurement faults. Compared to standard variants of the Kalman filter the adaptive variant implemented here is more accurate and robust to faults.

neuroscience↗

bioRxiv2021

Loss-of-function variants in the cardiac Kv11.1 channel as a genetic biomarker for SUDEP

ObjectiveTo compare the frequency and impact on channel function of KCNH2 variants in SUDEP patients with epilepsy controls comprising patients older than 50 years, a group with low SUDEP risk, and establish loss-of-function KCNH2 variants as predictive biomarkers of SUDEP risk. MethodsWe searched for KCNH2 variants with a minor allele frequency of < 5%. Functional analysis in Xenopus laevis oocytes was performed for all KCNH2 variants identified. ResultsKCNH2 variants were found in 11.1% (10/90) of SUDEP individuals compared to 6.0% (20/332) of epilepsy controls (p = 0.11). Loss-of-function KCNH2 variants, defined as causing > 20% reduction in maximal amplitude, were observed in 8.9% (8/90) SUDEP patients compared to 3.3% (11/332) epilepsy controls suggesting about three-fold enrichment (nominal p = 0.04). KCNH2 variants that did not change channel function occurred at a similar frequency in SUDEP (2.2%; 2/90) and epilepsy control (2.7%; 9/332) cohorts (p > 0.99). Rare KCNH2 variants (< 1% allele frequency) associated with greater loss of function and an [~]11-fold enrichment in the SUDEP cohort (nominal p = 0.03). In silico tools were unable to predict the impact of a variant on function highlighting the need for electrophysiological analysis. ConclusionsThese data show that loss-of-function KCNH2 variants are enriched in SUDEP patients and suggest that cardiac mechanisms contribute to SUDEP risk. We propose that genetic screening in combination with functional analysis can identify loss-of-function KCNH2 variants that could act as biomarkers of an individuals SUDEP risk.

neuroscience↗