Biology subjects

Gluckman, B. J.

Publications and source records attributed to Gluckman, B. J..

9 recordsLinked to original sources

bioRxiv2025

Tissue Oxygenation Dynamics During Seizure to Spreading Depolarization in Rat Brain

ObjectiveSpreading depolarization (SD) is a phenomenon underlying various neurological conditions, including epilepsy. Researchers have suspected that local tissue oxygenation breakdown induces spontaneous SD. In this study, we investigated the relationship between spontaneous epileptic seizures and SD, with a focus on the role of local tissue oxygenation during the transition from seizure to seizure-associated SD. MethodsWe applied a long pulse voltametric method to characterize local tissue oxygenation and extracellular space volume in the hippocampus (HC) of freely moving epileptic rats (male 6, female 3). Recordings were performed during the normal state of vigilance, spontaneous seizures, and seizure-associated SD events, as well as during their transitions. ResultsNo significant breakdown in local tissue oxygenation of HC was detected before SD onset during the seizure to SD transition. In contrast, a decreased ECS volume in the HC was observed before SD onset during this transition. SignificanceUsing a novel electrochemical approach in freely behaving rats with intact cerebral autoregulation, we demonstrate that ECS shrinkage, rather than breakdown of local tissue oxygenation, plays a leading role in SD initiation during seizure to SD transition. These findings refine our understanding of the mechanisms driving seizure-associated SD and suggest that ECS dynamics may represent an important therapeutic target in epilepsy and other SD-associated neurological disorders

neuroscience↗

bioRxiv2025

A DC-sensitive video/electrophysiology monitoring unit for long-term continuous study of seizures and seizure-associated spreading depolarization in a rat model

There has been a long-term need for a low-cost, highly efficient, and high-fidelity epilepsy monitoring unit (EMU) suitable for home-cage monitoring of small-animal models of epilepsy. We show an accessible, scalable, highly space and energy-efficient EMU capable of fulfilling chronic, continuous synchronized multiple animal monitoring jobs. Each rig within the EMU can provide 16-channel high-fidelity, DC-sensitive biopotential recordings, head acceleration monitoring, synchronized voltammetry applications, and video recording on one freely moving rat. We present the overall EMU architecture design and subsystem details in each recording rig. We demonstrate long-term continuous in vivo recordings of spontaneous seizure and seizure-associated spreading depolarization (SD) from freely moving rats prepared under the tetanus toxin model of temporal lobe epilepsy. Significance StatementLong-term continuous DC-sensitive biopotential and video recordings are essential for capturing the dynamics of epileptic seizures and seizure-related spreading depolarizations (SD), providing a deeper understanding of their underlying mechanisms. These recordings are invaluable for developing animal models of epilepsy, studying seizure prediction, drug testing, and investigating related neurological conditions such as mental health, aging, and dementia. They also reveal rare phenomena that short-duration recordings might miss. However, traditional methods are resource intensive. The new epilepsy monitoring unit (EMU) introduced in this paper offers a cost-effective and space-saving solution for high-fidelity chronic monitoring of freely moving animals, utilizing compact single-board computers and standard cages without interrupting the recordings.

neuroscience↗

bioRxiv2023

Dissecting Multiparametric Cerebral Hemodynamics using Integrated Ultrafast Ultrasound and Multispectral Photoacoustic Imaging

Understanding brain-wide hemodynamic responses to different stimuli at high spatiotemporal resolutions can help study neuro-disorders and brain functions. However, the existing brain imaging technologies have limited resolution, sensitivity, imaging depth and provide information about only one or two hemodynamic parameters. To address this, we propose a multimodal functional ultrasound and photoacoustic (fUSPA) imaging platform, which integrates ultrafast ultrasound and multispectral photoacoustic imaging methods in a compact head-mountable device, to quantitatively map cerebral blood volume (CBV), cerebral blood flow (CBF), oxygen saturation (SO2) dynamics as well as contrast agent enhanced brain imaging with high spatiotemporal resolutions. After systematic characterization, the fUSPA system was applied to quantitatively study the changes in brain hemodynamics and vascular reactivity at single vessel resolution in response to hypercapnia stimulation. Our results show an overall increase in brain-wide CBV, CBF, and SO2, but regional differences in singular cortical veins and arteries and a reproducible anti-correlation pattern between venous and cortical hemodynamics, demonstrating the capabilities of the fUSPA system for providing multiparametric cerebrovascular information at high-resolution and sensitivity, that can bring insights into the complex mechanisms of neurodiseases.

bioengineering↗

bioRxiv2022

Mechanistic Neural Mass Modeling: from physiology to pathophysiological brain activity

Brain rhythms emerge from the mean-field activity of networks of neurons. There have been many efforts to build mathematical and computational embodiments in the form of discrete cell-group activities - termed neural masses - to understand particular the origins of evoked potentials, intrinsic patterns of activities such as theta, regulation of sleep, Parkinsons disease related dynamics, and instabilities such as seizure dynamics. As originally utilized, standard neural masses convert input through a sigmoidal function to a firing rate, and firing rate through a synaptic alpha function to other masses. Here we define a process to build almost from first principles (i.e. Hodgkin Huxley type models) mean field models of different neuron types that duplicate the stability, firing rate, and associated bifurcations as function of relevant slow variables - such as extracellular potassium - and synaptic current; and whose output is both firing rate and impact on the slow variables - such as transmembrane potassium flux. Small networks composed of just excitatory and inhibitory masses demonstrate expected dynamical states including stable firing, runaway excitation and depolarization block, and these transitions change in biologically observed ways with changes in extracellular potassium and excitatory-inhibitory balance.

neuroscience↗

bioRxiv2022

Optimization of an unscented Kalman filter for an embedded platform

The unscented Kalman filter (UKF) is finding increased application in biological fields. While realizing a complex UKF system in a low-power embedded platform offers many potential benefits including wearability, it also poses significant design challenges. Here we present a method for optimizing a UKF system for realization in an embedded platform. The method seeks to minimize both computation time and error in UKF state reconstruction and forecasting. As a case study, we applied the method to a model for the rat sleep-wake regulatory system in which 432 variants of the UKF over six different variables are considered. The optimization method is divided into three stages that assess computation time, state forecast error, and state reconstruction error. We apply a cost function to variants that pass all three stages to identify a variant that computes 27 times faster than the reference variant and maintains required levels of state estimation and forecasting accuracy. We draw the following insights: 1) process noise provides leeway for simplifying the model and its integration in ways that speed computation time while maintaining state forecasting accuracy, 2) the assimilation of observed data during the UKF correction step provides leeway for simplifying the UKF structure in ways that speed computation time while maintaining state reconstruction accuracy, and 3) the optimization process can be accelerated by decoupling variables that directly impact the underlying model from variables that impact the UKF structure. Author summaryPowerful statistical tools can be used to estimate unmeasured information in biological systems and predict the systems future state. Translating these tools from a desktop computer to small, wearable or implantable platforms can unlock many benefits, but presents many design challenges, because tradeoffs between computational simplicity and system accuracy must be balanced. We present an approach to translating one such widely used statistical tool, the unscented Kalman filter, from a desktop computer to a miniature device. We demonstrate the approach with a case study centering on the neural circuits governing the mammalian sleep-wake cycle. By exploiting uncertainty in the biology being estimated and the corrective influence of biological measurements, we arrive at a design that is easily computable on the miniature device and maintains a high level of accuracy. We anticipate that our approach will aid others in designing such miniaturized systems for a broad range of applications.

neuroscience↗

bioRxiv2020

Probing Causality of the Brainstem-Hypothalamic Murine Models of Sleep-Wake Regulation

Sleep-wake regulation is thought to be governed by interactions among several nuclei in midbrain, pons, and hypothalamic regions. Determination of the causal role of these nuclei in state transitions requires simultaneous measurements from the nuclei with sufficient spatial and temporal resolution. We obtained long-term experimental single- and multi-unit measurements simultaneously from multiple nuclei of the putative hypothalamic and brainstem sleep-wake regulatory network in freely behaving rats. Cortical and hippocampal activity, along with head acceleration were also acquired to assess behavioral state. Here, we confirm that the general activity profile of the recorded sleep-wake regulatory nuclei is similar to the patterns presented previously in brief recordings of individual nuclei in head-fixed animals. However, we found that these activity profiles when studied with respect to cortical and behavioral signs of state transitions differ significantly from previous reports. Our findings pose fundamental questions about the neural mechanisms that maintain specific states and the neural interactions that lead to the emergence of sleep-wake states.

neuroscience↗

bioRxiv2019

Functional hyperemia drives fluid exchange in the paravascular space

Maintaining the ionic and chemical composition of the extracellular spaces in the brain is extremely important for its health and function. However, the brain lacks a conventional lymphatic system to remove metabolic waste. It has been proposed that the fluid movement through the paravascular space (PVS) surrounding penetrating arteries can help remove metabolites from the brain. The dynamics of fluid movement in the PVS and its interaction with arterial dilation and brain mechanics are not well understood. Here, we performed simulations to understand how arterial pulsations and dilations interact with brain deformability to drive fluid flow in the PVS. In simulations with compliant brain tissue, arterial pulsations did not drive appreciable flows in the PVS. In contrast, when the artery dilated with dynamics like those seen during functional hyperemia, there was a marked movement of fluid through the PVS. Our simulations suggest that in addition to its other purposes, functional hyperemia may serve to increase fluid exchange between the PVS and the subarachnoid space, improving the clearance of metabolic waste. We measured displacement of the blood vessels and the brain tissue simultaneously in awake, head-fixed mice using two-photon microscopy. Our measurements show that brain tissue can deform in response to fluid movement in the PVS, as predicted by simulations. The results from our simulations and experiments show that the deformability of the soft brain tissue needs to be accounted for when studying fluid flow and metabolite transport in the brain.

neuroscience↗

bioRxiv2018

Spreading Depression and Seizure Unification Experimentally Observed in Epilepsy

Spreading depression is characterized by slow, propagating wave of cellular depolarization (SD) and is wildly associated with migraine, stroke, and traumatic brain injury. Seizures and spreading depression (or spreading depolarization, SD) have long been reported to coincide in acute seizure induction experiments. However, SD has not been observed associated with spotaneous seizures in animal or clinical recordings. Recently, advances in acquisition systems for neurointensive care units have made routine observations of SD possible. In clinical epilepsy, SD has been suggested as a candidate mechanism for migraine/headache like events following seizures as well as for post-ictal generalized suppression. In animal models of epilepsy, seizure-induced brainstem SD has also been demonstrated as a mechanism of sudden unexplained death in epilepsy (SUDEP). The interplay between seizures and SD has also been suggested in computational models, where the two are components of the repetoir of neuronal activity. However, the spatiotemporal dynamics of SD with respect to spontaneous seizures in chronically epileptic brain remains ambigous. We analyzed continuous long-term DC sensitive EEG measurements from two fundamentally different animal models of chronic epilepsy. We found that SD was associated with approximately one-third of all spontaneous seizures in each model. Additionally, SDs participated in the organization of seizure clusters. These findings demonstrate that the underlying dynamic of epileptic events is broader than seizures alone. Significance StatementSpreading depression is characterized by slow, propagating wave of cellular spreading depolarization (SD) and is wildly associated with migraine, stroke, and traumatic brain injury. Although recently the linkage between SD and induced seizures has been recognized, the mechanistic relationship between SD and spontaneous seizures remains poorly understood. Here, we utilized long-term, stable, near-DC measurements of the brain activity in two fundamentally different animal models of epilepsy to investigate the SD-seizure interplay. We found that SD is a frequent phenomenon in the epileptic brain, in these models is associated with more than a third of all seizures, and appears to connect seizures in seizure clusters. Although in one model SD stereotypically propagates out from a single focus in the hippocampus, depression of the field-potentials is observed synchronously across much of the hippocampus. These observations highlight the value of stable DC measurements for accurate understanding of SD and its propagation. We found that spontaneous ictal events that include both seizures and SD are frequent in animal models of epilepsy. These findings suggest that SD could be a valuable target for treatment and control of epilepsy.

neuroscience↗

bioRxiv2018

Control of Spreading Depression with Electrical Fields

Spreading depression or depolarization is a large-scale pathological brain phenomenon related to migraine, stroke, hemorrhage and traumatic brain injury. Once initiated, spreading depression propagates across gray matter extruding potassium and other active molecules, collapsing the resting membrane electro-chemical gradient of cells leading to spike inactivation and cellular swelling, and propagates independently of synaptic transmission. We demonstrate the modulation, suppression and prevention of spreading depression utilizing applied transcortical DC electric fields in brain slices, measured with intrinsic optical imaging and potassium dye epifluorescence. We experimentally observe a surface-positive electric field induced forcing of spreading depression propagation to locations in cortex deeper than the unmodulated propagation path, whereby further propagation is confined and arrested even after field termination. The opposite surface-negative electric field polarity produces an increase in propagation velocity and a confinement of the wave to more superficial layers of cortex than the unmodulated propagation path. These field polarities are of opposite sign to the polarity that blocks neuronal spiking and seizures, and are consistent with biophysical models of spreading depression. The results demonstrate the potential feasibility of electrical control and prevention of spreading depression.

neuroscience↗