Convolutional neural networks for the segmentation of small rodent brain MRI

Image segmentation is a common step in the analysis of preclinical brain MRI, often performed manually. This is a time-consuming procedure subject to inter- and intra- rater variability. A possible alternative is the use of automated, registration-based segmentation, which suffers from a bias owed to the limited capacity of registration to adapt to pathological conditions such as Traumatic Brain Injury (TBI). In this work a novel method is developed for the segmentation of small rodent brain MRI based on Convolutional Neural Networks (CNNs). The experiments here presented show how CNNs provide a fast, robust and accurate alternative to both manual and registration-based methods. This is demonstrated by accurately segmenting three large datasets of MRI scans of healthy and Huntington disease model mice, as well as TBI rats. MU-Net and MU-Net-R, the CCNs here presented, achieve human-level accuracy while eliminating intra-rater variability, alleviating the biases of registration-based segmentation, and with an inference time of less than one second per scan. Using these segmentation masks I designed a geometric construction to extract 39 parameters describing the position and orientation of the hippocampus, and later used them to classify epileptic vs. non-epileptic rats with a balanced accuracy of 0.80, five months after TBI. This clinically transferable geometric approach detects subjects at high-risk of post-traumatic epilepsy, paving the way towards subject stratification for antiepileptogenesis studies

Mining Biomarkers Of Epilepsy From Large-Scale Intracranial Electroencephalography

Epilepsy is a chronic neurological disorder characterized by seizures. Affecting over 50 million people worldwide, the quality of life of a patient with uncontrolled epilepsy is degraded by medical, social, cognitive, and psychological dysfunction. Fortunately, two-thirds of these patients can achieve adequate seizure control through medications. Unfortunately, one-third cannot. Improving treatment for this patient population depends upon improving our understanding of the underlying epileptic network. Clinical therapies modulate this network to some degree of success, including surgery to remove the seizure onset zone or neuromodulation to alter the brain\u27s dynamics. High resolution intracranial EEG (iEEG) is often employed to study the dynamics of cortical networks, from interictal patterns to more complex quantitative features. These interictal patterns include epileptiform biomarkers whose detection and mapping, along with seizures and neuroimaging, form the mainstay of data for clinical decision making around drug therapy, surgery, and devices. They are also increasingly important to assess the effects of epileptic physiology on brain functions like behavior and cognition, which are not well characterized. In this work, we investigate the significance and trends of epileptiform biomarkers in animal and human models of epilepsy. We develop reliable methods to quantify interictal patterns, applying state of the art techniques from machine learning, signal processing, and EEG analysis. We then validate these tools in three major applications: 1. We study the effect of interictal spikes on human cognition, 2. We assess trends of interictal epileptiform bursts and their relationship to seizures in prolonged recordings from canines and rats, and 3. We assess the stability of long-term iEEG spanning several years. These findings have two main impacts: (1) they inform the interpretation of interictal iEEG patterns and elucidate the timescale of post-implantation changes. These findings have important implications for research and clinical care, particularly implantable devices and evaluating patients for epilepsy surgery. (2) They provide an analytical framework to enable others to mine large-scale iEEG datasets. In this way we hope to make a lasting contribution to accelerate collaborative research not only in epilepsy, but also in the study of animal and human electrophysiology in acute and chronic conditions

Underlying Mechanisms of Epilepsy

This book is a very provocative and interesting addition to the literature on Epilepsy. It offers a lot of appealing and stimulating work to offer food of thought to the readers from different disciplines. Around 5% of the total world population have seizures but only 0.9% is diagnosed with epilepsy, so it is very important to understand the differences between seizures and epilepsy, and also to identify the factors responsible for its etiology so as to have more effective therapeutic regime. In this book we have twenty chapters ranging from causes and underlying mechanisms to the treatment and side effects of epilepsy. This book contains a variety of chapters which will stimulate the readers to think about the complex interplay of epigenetics and epilepsy

Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation.

After an initial period of recovery, human neurological injury has long been thought to be static. In order to improve quality of life for those suffering from stroke, spinal cord injury, or traumatic brain injury, researchers have been working to restore the nervous system and reduce neurological deficits through a number of mechanisms. For example, neurobiologists have been identifying and manipulating components of the intra- and extracellular milieu to alter the regenerative potential of neurons, neuro-engineers have been producing brain-machine and neural interfaces that circumvent lesions to restore functionality, and neurorehabilitation experts have been developing new ways to revitalize the nervous system even in chronic disease. While each of these areas holds promise, their individual paths to clinical relevance remain difficult. Nonetheless, these methods are now able to synergistically enhance recovery of native motor function to levels which were previously believed to be impossible. Furthermore, such recovery can even persist after training, and for the first time there is evidence of functional axonal regrowth and rewiring in the central nervous system of animal models. To attain this type of regeneration, rehabilitation paradigms that pair cortically-based intent with activation of affected circuits and positive neurofeedback appear to be required-a phenomenon which raises new and far reaching questions about the underlying relationship between conscious action and neural repair. For this reason, we argue that multi-modal therapy will be necessary to facilitate a truly robust recovery, and that the success of investigational microscopic techniques may depend on their integration into macroscopic frameworks that include task-based neurorehabilitation. We further identify critical components of future neural repair strategies and explore the most updated knowledge, progress, and challenges in the fields of cellular neuronal repair, neural interfacing, and neurorehabilitation, all with the goal of better understanding neurological injury and how to improve recovery

Point process modeling as a framework to dissociate intrinsic and extrinsic components in neural systems

Understanding the factors shaping neuronal spiking is a central problem in neuroscience. Neurons may have complicated sensitivity and, often, are embedded in dynamic networks whose ongoing activity may influence their likelihood of spiking. One approach to characterizing neuronal spiking is the point process generalized linear model (GLM), which decomposes spike probability into explicit factors. This model represents a higher level of abstraction than biophysical models, such as Hodgkin-Huxley, but benefits from principled approaches for estimation and validation. Here we address how to infer factors affecting neuronal spiking in different types of neural systems. We first extend the point process GLM, most commonly used to analyze single neurons, to model population-level voltage discharges recorded during human seizures. Both GLMs and descriptive measures reveal rhythmic bursting and directional wave propagation. However, we show that GLM estimates account for covariance between these features in a way that pairwise measures do not. Failure to account for this covariance leads to confounded results. We interpret the GLM results to speculate the mechanisms of seizure and suggest new therapies. The second chapter highlights flexibility of the GLM. We use this single framework to analyze enhancement, a statistical phenomenon, in three distinct systems. Here we define the enhancement score, a simple measure of shared information between spike factors in a GLM. We demonstrate how to estimate the score, including confidence intervals, using simulated data. In real data, we find that enhancement occurs prominently during human seizure, while redundancy tends to occur in mouse auditory networks. We discuss implications for physiology, particularly during seizure. In the third part of this thesis, we apply point process modeling to spike trains recorded from single units in vitro under external stimulation. We re-parameterize models in a low-dimensional and physically interpretable way; namely, we represent their effects in principal component space. We show that this approach successfully separates the neurons observed in vitro into different classes consistent with their gene expression profiles. Taken together, this work contributes a statistical framework for analyzing neuronal spike trains and demonstrates how it can be applied to create new insights into clinical and experimental data sets

IDENTIFYING THE GENETIC MECHANISMS IN SEIZURE THRESHOLD REGULATION

Epilepsy is a brain disease defined by having recurrent and spontaneous seizures. The susceptibility to seizure is determined by seizure threshold, which describes the balance between excitatory and inhibitory neurotransmission in the brain. Epileptogenesis, the transition from normal brain to epileptic brain, is accompanied by a progressive reduction of seizure threshold and has been shown to have genetic influences. Expression of neuronal cyclooxygenase-2 (COX-2) gene, PTGS2, a primary gene that regulates prostaglandin synthesis in the normal brain, is enhanced by excitatory neurotransmission and is under tight regulation of N-Methyl-D-Aspartate type glutamate receptor (NMDAR) activity in cortical neurons. The 3’ untranslated region (3’UTR) of PTGS2 gene was found to be a key site of post-transcriptional regulation by NMDAR activity. However, deletion of T-cell intracellular antigen-1 (TIA-1), an RNA binding protein of COX-2 mRNA 3’UTR, did not affect COX-2 protein expression in mouse brain. Although TIA-1 deletion did not alter innate seizure threshold, it facilitated the acquisition of epilepsy and enhanced epileptogenesis-associated mortality. Further investigation revealed that TIA-1 knockout mice have an altered transcriptome in their hippocampi. Together, my findings illustrate an NMDAR-dependent regulatory mechanism of a known modulator of seizure threshold (COX-2) in neurons, and provide insight into the regulation of epileptogenesis by a novel genetic modifier (TIA-1)

The alteration of chloride homeostasis/GABAergic signaling in brain disorders: Could oxidative stress play a role?

In neuronal precursors and immature neurons, the depolarizing (excitatory) effect of γ-Aminobutyric acid (GABA) signaling is associated with elevated [Cl−]i; as brain cells mature, a developmental switch occurs, leading to the decrease of [Cl−]i and to the hyperpolarizing (inhibi-tory) effect of GABAergic signaling. [Cl−]i is controlled by two chloride co-transporters: NKCC1, which causes Cl− to accumulate into the cells, and KCC2, which extrudes it. The ontogenetic up-regulation of the latter determines the above-outlined switch; however, many other factors contribute to the correct [Cl−]i in mature neurons. The dysregulation of chloride homeostasis is involved in seizure generation and has been associated with schizophrenia, Down’s Syndrome, Autism Spectrum Disorder, and other neurodevelopmental disorders. Recently, much effort has been put into developing new drugs intended to inhibit NKCC1 activity, while no attention has been paid to the origin of [Cl−]i dysregulation. Our study examines the pathophysiology of Cl− homeo-stasis and focuses on the impact of oxidative stress (OS) and inflammation on the activity of Cl− co-transporters, highlighting the relevance of OS in numerous brain abnormalities and diseases. This hypothesis supports the importance of primary prevention during pregnancy. It also inte-grates the therapeutic framework addressed to restore normal GABAergic signaling by counter-acting the alteration in chloride homeostasis in central nervous system (CNS) cells, aiming at lim-iting the use of drugs that potentially pose a health risk

Going the extra (synaptic) mile: excitotoxicity as the road toward neurodegenerative diseases

Copyright © 2020 Armada-Moreira, Gomes, Pina, Savchak, Gonçalves-Ribeiro, Rei, Pinto, Morais, Martins, Ribeiro, Sebastião, Crunelli and Vaz. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Excitotoxicity is a phenomenon that describes the toxic actions of excitatory neurotransmitters, primarily glutamate, where the exacerbated or prolonged activation of glutamate receptors starts a cascade of neurotoxicity that ultimately leads to the loss of neuronal function and cell death. In this process, the shift between normal physiological function and excitotoxicity is largely controlled by astrocytes since they can control the levels of glutamate on the synaptic cleft. This control is achieved through glutamate clearance from the synaptic cleft and its underlying recycling through the glutamate-glutamine cycle. The molecular mechanism that triggers excitotoxicity involves alterations in glutamate and calcium metabolism, dysfunction of glutamate transporters, and malfunction of glutamate receptors, particularly N-methyl-D-aspartic acid receptors (NMDAR). On the other hand, excitotoxicity can be regarded as a consequence of other cellular phenomena, such as mitochondrial dysfunction, physical neuronal damage, and oxidative stress. Regardless, it is known that the excessive activation of NMDAR results in the sustained influx of calcium into neurons and leads to several deleterious consequences, including mitochondrial dysfunction, reactive oxygen species (ROS) overproduction, impairment of calcium buffering, the release of pro-apoptotic factors, among others, that inevitably contribute to neuronal loss. A large body of evidence implicates NMDAR-mediated excitotoxicity as a central mechanism in the pathogenesis of many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), and epilepsy. In this review article, we explore different causes and consequences of excitotoxicity, discuss the involvement of NMDAR-mediated excitotoxicity and its downstream effects on several neurodegenerative disorders, and identify possible strategies to study new aspects of these diseases that may lead to the discovery of new therapeutic approaches. With the understanding that excitotoxicity is a common denominator in neurodegenerative diseases and other disorders, a new perspective on therapy can be considered, where the targets are not specific symptoms, but the underlying cellular phenomena of the disease.This work was funded by Fundação para a Ciência e Tecnologia (FCT), Portugal (PTDC/BTM-SAL/32147/2017, PD/BD/114278/2016, IMM/BI/2-2020), and by FCT/Ministério da Ciência, Tecnologia e Ensino Superior (MCTES) through Fundos do Orçamento de Estado (UID/BIM/50005/2019). TM was funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska/Curie grant agreement No. 722053.info:eu-repo/semantics/publishedVersio