Mapping Functional Architecture in Neocortical Epileptic Networks

Epilepsy is a debilitating brain disorder that causes recurring seizures in approximately 60 million people worldwide. For the one-third of epilepsy patients whose seizures are refractory to medication, effective therapy relies on reliably localizing where seizures originate and spread. This clinical practice amounts to delineating the epileptic network through neural sensors recording the electrocorticogram. Mapping functional architecture in the epileptic network is promising for objectively localizing cortical targets for therapy in cases of neocortical refractory epilepsy, where post-surgical seizure freedom is unfavorable when cortical structures responsible for generating seizures are difficult to delineate. In this work, we develop and apply network models for analyzing and interrogating the role of fine-grain functional architecture during epileptic events in human neocortical networks. We first develop and validate a model for objectively identifying regions of the epileptic network that drive seizure dynamics. We then develop and validate a model for disentangling network pathways traversed during ``normal\u27\u27 function from pathways that drive seizures. Lastly, we devise and apply a novel platform for predicting network response to targeted lesioning of neocortical structures, revealing key control areas that influence the spread of seizures to broader network regions. The outcomes of this work demonstrate network models can objectively identify and predict targets for treating neocortical epilepsy, blueprint potential control strategies to limit seizure spread, and are poised for further validation prior to near-term clinical translation

Integrating EEG and MEG signals to improve motor imagery classification in brain-computer interfaces

We propose a fusion approach that combines features from simultaneously recorded electroencephalographic (EEG) and magnetoencephalographic (MEG) signals to improve classification performances in motor imagery-based brain-computer interfaces (BCIs). We applied our approach to a group of 15 healthy subjects and found a significant classification performance enhancement as compared to standard single-modality approaches in the alpha and beta bands. Taken together, our findings demonstrate the advantage of considering multimodal approaches as complementary tools for improving the impact of non-invasive BCIs

Breast cancer therapies and cardiomyopathy.

The prevalence of chemotherapy-related cardiac disease is increasing and management demands a multidisciplinary approach from cardiologists and oncologists. Pretreatment identification of predisposing risk factors and assessment of cardiac function before and at intervals during and after therapy with cardiotoxic agents are necessary. In clinical practice, surveillance is largely performed using transthoracic echocardiography or multi-gated radionuclide angiography. Imaging strategies that detect cardiac injury before overt left ventricular systolic dysfunction provide an opportunity for early intervention and improved cardiac outcomes

Synthesis of thiophene, selenophene and thiophene-s-dioxide based organic semiconductors for organic electronics

Solid materials having electrical conductivity greater than insulators but less than metals are semiconductors. Carbon-based materials that exhibit semiconductor properties are known as organic semiconductors (OSCs). These materials hold promise for flexible, lightweight, inexpensive and easy to fabricate devices. Due to these advantages, OSCs have gained tremendous interest in recent decades for their use in solar cells, thin film transistors and light emitting diodes. OSCs can be broadly classified in two categories: conjugated polymers (CPs) and small molecules.(1) CPs: Organic macromolecules which have a backbone chain of alternating double/triple- and single-Bonds are known as CP. Application and device fabrication is dictated by the Energy gap between highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO). Therefore it is a vital parameter for CPs. Here, the synthesis a narrow bandgap conjugated polymer- Poly(3- alkoxy selenophene), inspired from poly(3-alkoxythiophene), will be discussed.Li ion batteries may catch fire due to the conventionally used cathode material, LiCoOn. We have formed a mixture, comprised of poly(3-alkoxy thiophene) and Li salt, as an alternative material for the cathode in Li ion batteries.(2) Small molecules: Small molecules were synthesized based on the electron deficient moiety of Benzodithiophene-S,S-tetraoxide (BDTT) via Cu catalyzed C-H activated direct arylation. Reaction conditions were optimized for various parameters like catalysts, ligands and base. Also, the optoelectronic properties of these molecules were studied

Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy

Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention

Evidence of state-dependence in the effectiveness of responsive neurostimulation for seizure modulation

An implanted device for brain-responsive neurostimulation (RNS System) is approved as an effective treatment to reduce seizures in adults with medically-refractory focal epilepsy. Clinical trials of the RNS System demonstrate population-level reduction in average seizure frequency, but therapeutic response is highly variable. Recent evidence links seizures to cyclical fluctuations in underlying risk. We tested the hypothesis that effectiveness of responsive neurostimulation varies based on current state within cyclical risk fluctuations. We analyzed retrospective data from 25 adults with medically-refractory focal epilepsy implanted with the RNS System. Chronic electrocorticography was used to record electrographic seizures, and hidden Markov models decoded seizures into fluctuations in underlying risk. State-dependent associations of RNS System stimulation parameters with changes in risk were estimated. Higher charge density was associated with improved outcomes, both for remaining in a low seizure risk state and for transitioning from a high to a low seizure risk state. The effect of stimulation frequency depended on initial seizure risk state: when starting in a low risk state, higher stimulation frequencies were associated with remaining in a low risk state, but when starting in a high risk state, lower stimulation frequencies were associated with transition to a low risk state. Findings were consistent across bipolar and monopolar stimulation configurations. The impact of RNS on seizure frequency exhibits state-dependence, such that stimulation parameters which are effective in one seizure risk state may not be effective in another. These findings represent conceptual advances in understanding the therapeutic mechanism of RNS, and directly inform current practices of RNS tuning and the development of next-generation neurostimulation systems

Field studies on the deterioration of microplastic films from ultra-thin compostable bags in soil

In recent years, some countries have replaced single-use plastic bags with bags manufactured from compostable plastic film that can be used for collecting food wastes and composted together with the waste. Because industrial compost contains undeteriorated fragments of these bags, application to field soil is a potential source of small-sized residues from these bags. This study was undertaken to examine deterioration of these compostable film microplastics (CFMPs) in field soil at three different localities in Italy. Deterioration of CFMPs did not exceed 5.7% surface area reduction during the 12-month experimental period in two sites located in Northern Italy. More deterioration was observed in the Southern site, with 7.2% surface area reduction. Deterioration was significantly increased when fields were amended with industrial compost (up to 9.6%), but not with home compost. Up to 92.9% of the recovered CFMPs were associated with the soil fungus Aspergillus flavus, with 20.1%–71.2% aflatoxin-producing isolates. Application of industrial compost resulted in a significant increase in the percentage of CFMPs associated with A. flavus. This observation provides an argument for government regulation of accumulation of CFMPs and elevation of hazardous fungi levels in agricultural soils that receive industrial compost