Connectivity and Neuronal Synchrony During Seizures

2021 ◽  
pp. JN-RM-0669-21
Author(s):  
Xin Ren ◽  
Anastasia Brodovskaya ◽  
John L. Hudson ◽  
Jaideep Kapur
Keyword(s):  
2019 ◽  
Vol 19 (10) ◽  
pp. 211d ◽  
Author(s):  
Eline R Kupers ◽  
Noah C Benson ◽  
Jonathan Winawer

2017 ◽  
Author(s):  
Thanos Manos ◽  
Magteld Zeitler ◽  
Peter A. Tass

AbstractIn this paper, we computationally generate hypotheses for dose-finding studies in the context of desynchronizing neuromodulation techniques. Abnormally strong neuronal synchronization is a hallmark of several brain disorders. Coordinated Reset (CR) stimulation is a spatio-temporally patterned stimulation technique that specifically aims at disrupting abnormal neuronal synchrony. In networks with spike-timing-dependent plasticity CR stimulation may ultimately cause an anti-kindling, i.e. an unlearning of abnormal synaptic connectivity and neuronal synchrony. This long-lasting desynchronization was theoretically predicted and verified in several pre-clinical and clinical studies. We have shown that CR stimulation with rapidly varying sequences (RVS) robustly induces an anti-kindling at low intensities e.g. if the CR stimulation frequency (i.e. stimulus pattern repetition rate) is in the range of the frequency of the neuronal oscillation. In contrast, CR stimulation with slowly varying sequences (SVS) turned out to induce an anti-kindling more strongly, but less robustly with respect to variations of the CR stimulation frequency. Motivated by clinical constraints and inspired by the spacing principle of learning theory, in this computational study we propose a short-term dosage regimen that enables a robust anti-kindling effect of both RVS and SVS CR stimulation, also for those parameter values where RVS and SVS CR stimulation previously turned out to be ineffective. Intriguingly, for the vast majority of parameter values tested, spaced multishot CR stimulation with demand-controlled variation of stimulation frequency and intensity caused a robust and pronounced anti-kindling. In contrast, spaced CR stimulation with fixed stimulation parameters as well as singleshot CR stimulation of equal integral duration failed to improve the stimulation outcome. In the model network under consideration, our short-term dosage regimen enables to robustly induce long-term desynchronization at comparably short stimulation duration and low integral stimulation duration. Currently, clinical proof of concept is available for deep brain CR stimulation for Parkinson’s therapy and acoustic CR stimulation for tinnitus therapy. Promising first in human data is available for vibrotactile CR stimulation for Parkinson’s treatment. For the clinical development of these treatments it is mandatory to perform dose-finding studies to reveal optimal stimulation parameters and dosage regimens. Our findings can straightforwardly be tested in human dose-finding studies.


2021 ◽  
Author(s):  
Olli Paul Einari Rajasilta ◽  
Suvi Häkkinen ◽  
Malin Björnsdotter ◽  
Noora Scheinin ◽  
Satu Lehtola ◽  
...  

Abstract Introduction: Maternal obesity/overweight during pregnancy has reached epidemic proportions and has been linked with adverse outcomes for the offspring, including cognitive impairment and increased risk for neuropsychiatric disorders. Prior neuroimaging investigations have reported widespread aberrant functional connectivity and white matter tract abnormalities in neonates born to obese mothers. Here we explored whether maternal pre-pregnancy adiposity is associated with alterations in local neuronal synchrony in the neonate brain. Methods: 21 healthy mother-neonate dyads from uncomplicated pregnancies were included in this study (age at scanning 26.14 ± 6.28 days, 12 male). The neonates were scanned with a 6-minute resting-state functional magnetic resonance imaging (rs-fMRI) during natural sleep. Regional homogeneity (ReHo) maps were computed from obtained rs-fMRI data. Multiple regression analysis was performed to assess the association of pre-pregnancy maternal body-mass-index (BMI) and ReHo. Results: Maternal adiposity measured by pre-pregnancy BMI was positively associated with neonate ReHo values within the left superior frontal gyrus (FDR/FWE –corrected p < 0.005). Conclusions: Our results imply that maternal pre-pregnancy BMI associates with local functional synchrony within the neonate left superior frontal gyrus. In line with previous studies, our findings indicate that maternal pre-pregnancy BMI has a programming influence on the developing neonate brain functional networks.


Author(s):  
Kazuhiro Sakamoto ◽  
Katsutoshi Yamamoto ◽  
Naohiro Saito ◽  
Kazuyuki Aihara ◽  
Jun Tanji ◽  
...  

2010 ◽  
Vol 104 (6) ◽  
pp. 3557-3567 ◽  
Author(s):  
Bartosz Telenczuk ◽  
Vadim V. Nikulin ◽  
Gabriel Curio

Evoked EEG/MEG responses are a primary real-time measure of perceptual and cognitive activity in the human brain, but their neuronal generator mechanisms are not yet fully understood. Arguments have been put forward in favor of either “phase-reset” of ongoing oscillations or “added-energy” models. Instead of advocating for one or the other model, here we show theoretically that the differentiation between these two generation mechanisms might not be possible if based solely on macroscopic EEG/MEG recordings. Using mathematical modeling, we show that a simultaneous phase reset of multiple oscillating neuronal (microscopic) sources contributing to EEG/MEG can produce evoked responses in agreement with both, the “added-energy” and the “phase-reset” model. We observe a smooth transition between the two models by just varying the strength of synchronization between the multiple microscopic sources. Consequently, because precise knowledge about the strength of microscopic ensemble synchronization is commonly not available in noninvasive EEG/MEG studies, they cannot, in principle, differentiate between the two mechanisms for macroscopic-evoked responses.


2000 ◽  
Vol 12 (11) ◽  
pp. 2597-2620 ◽  
Author(s):  
Stuart N. Baker ◽  
George L. Gerstein

We outline two improvements to the technique of gravitational clustering for detection of neuronal synchrony, which are capable of improving the method's detection of weak synchrony with limited data. The advantages of the enhancements are illustrated using data with known levels of synchrony and different interspike interval distributions. The novel simulation method described can easily generate such test data. An important dependence of the sensitivity of gravitational clustering to the interspike interval distribution of the analysed spike trains is described.


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