Biology subjects

Puthanmadam Subramaniyam, N.

Publications and source records attributed to Puthanmadam Subramaniyam, N..

2 recordsLinked to original sources

bioRxiv2023

Sensitivity analysis-guided Bayesian Parameter Estimation for Neural Mass Models: Applications in Epilepsy

It is well established that neural mass models (NMMs) can effectively simulate the mesoscopic and macroscopic dynamics of electroencephalography (EEG), including epileptic EEG. However NMMs are characterized by a high-dimensional parameter space and a lack of knowledge on what NMM parameters can be reliably estimated, thus limiting their application to clinical EEG data. In this article, we analyze the parameter sensitivity of Jansen and Rit NMM (JR NMM) in order to identify the most sensitive NMM parameters for reliable parameter estimation from EEG data. We also propose a joint estimation method for NMM states and parameters based on expectation-maximization combined with unscented Kalman smoother (UKS-EM). Global sensitivity analysis methods including Morris method and Sobol method are used to perform sensitivity analysis. Results from both the Morris and Sobol method show that the average inhibitory synaptic gain, B and the time constant of the average inhibitory post-synaptic potentials (PSPs), b-1 have significant impact on the JR NMM output along with having the least interaction with other model parameters. The UKS-EM method for estimating the parameters B and b is validated using simulations under varying levels of measurement noise. Finally we apply the UKS-EM algorithm to intracranial EEG data from 16 epileptic patients. Our results, both at individual and group-level show that the parameters B and b change significantly between the pre-seizure and seizure period, and between the seizure and post-seizure period, with transition to seizure characterized by decrease in average B and high frequency activity in seizure characterized by an increase in b. These results establish sensitivity analysis guided Bayesian parameter estimation as a powerful tool for reducing the parameter space of high dimensional NMMs enabling reliable and efficient estimation of the most sensitive NMM parameters, with the potential for online and fast tracking of NMM parameters in applications such as seizure tracking and control.

neuroscience↗

bioRxiv2023

Biohybrid restoration of the hippocampal loop re-establishes the non-seizing state in an in vitro model of limbic seizures

ObjectiveThe compromise of the hippocampal loop is a hallmark of mesial temporal lobe epilepsy (MTLE), the most frequent epileptic syndrome in the adult population and the most often refractory to medical therapy. Hippocampal sclerosis is found in >50% of drug-refractory MTLE patients and primarily involves the CA1, consequently disrupting the hippocampal output to the entorhinal cortex (EC). Closed-loop deep brain stimulation (DBS) is the latest frontier to improve drug-refractory MTLE; however, current approaches do not restore the functional connectivity of the hippocampal loop, they are designed by trial-and-error and heavily rely on seizure detection or prediction algorithms. The objective of this study is to evaluate the anti-ictogenic efficacy and robustness of an artificial bridge restoring the dialog between hippocampus and EC. ApproachIn mouse hippocampus-EC slices treated with 4-aminopyridine and in which the Schaffer Collaterals are severed, we established an artificial bridge between hippocampus and EC wherein interictal discharges originating in the CA3 triggered stimulation of the subiculum so to entrain EC networks. Combining quantification of ictal activity with tools from information theory, we addressed the efficacy of the bridge in controlling ictogenesis and in restoring the functional connectivity of the hippocampal loop. Main resultsThe bridge significantly decreased or even prevented ictal activity and proved robust to failure; when operating at 100% of its efficiency (i.e., delivering a pulse upon each interictal event), it recovered the functional connectivity of the hippocampal loop to a degree similar to what measured in the intact circuitry. The efficacy and robustness of the bridge stem in mirroring the adaptive properties of the CA3, which acts as biological neuromodulator. Significance. This work is the first stepping stone toward a paradigm shift in the conceptual design of stimulation devices for epilepsy treatment, from function control to functional restoration of the salient brain circuits.

neuroscience↗