Coupling between gamma-band power and cerebral blood volume during recurrent acute neocortical seizures

Characterization of neural and hemodynamic biomarkers of epileptic activity that can be measured using non-invasive techniques is fundamental to the accurate identification of the epileptogenic zone (EZ) in the clinical setting. Recently, oscillations at gamma-band frequencies and above (>30 Hz) have been suggested to provide valuable localizing information of the EZ and track cortical activation associated with epileptogenic processes. Although a tight coupling between gamma-band activity and hemodynamic-based signals has been consistently demonstrated in non-pathological conditions, very little is known about whether such a relationship is maintained in epilepsy and the laminar etiology of these signals. Confirmation of this relationship may elucidate the underpinnings of perfusion-based signals in epilepsy and the potential value of localizing the EZ using hemodynamic correlates of pathological rhythms. Here, we use concurrent multi-depth electrophysiology and 2-dimensional optical imaging spectroscopy to examine the coupling between multi-band neural activity and cerebral blood volume (CBV) during recurrent acute focal neocortical seizures in the urethane-anesthetized rat. We show a powerful correlation between gamma-band power (25-90 Hz) and CBV across cortical laminae, in particular layer 5, and a close association between gamma measures and multi-unit activity (MUA). Our findings provide insights into the laminar electrophysiological basis of perfusion-based imaging signals in the epileptic state and may have implications for further research using non-invasive multi-modal techniques to localize epileptogenic tissue

Multimodal imaging of human brain activity: rational, biophysical aspects and modes of integration

Until relatively recently the vast majority of imaging and electrophysiological studies of human brain activity have relied on single-modality measurements usually correlated with readily observable or experimentally modified behavioural or brain state patterns. Multi-modal imaging is the concept of bringing together observations or measurements from different instruments. We discuss the aims of multi-modal imaging and the ways in which it can be accomplished using representative applications. Given the importance of haemodynamic and electrophysiological signals in current multi-modal imaging applications, we also review some of the basic physiology relevant to understanding their relationship

Analysis of resting-state neurovascular coupling and locomotion-associated neural dynamics using wide-field optical mapping

Understanding the relationship between neural activity and cortical hemodynamics, or neurovascular coupling is the foundation to interpret neuroimaging signals such as functional magnetic resonance imaging (fMRI) which measure local changes in hemodynamics as a proxy for underlying neural activity. Even though the stereotypical stimulus-evoked hemodynamic response pattern with increased concentration of oxy- and total-hemoglobin and decrease in concentration of deoxy-hemoglobin has been well-recognized, the linearity of neurovascular coupling and its variances depending on brain state and tasks haven’t been thoroughly evaluated. To directly assess the cortical neurovascular coupling, simultaneous recordings of neural and hemodynamic activity were imaged by wide-field optical mapping (WFOM) over the bilateral dorsal surface of the mouse brain through a bilateral thinned-skull cranial window. Neural imaging is achieved through wide-field fluorescence imaging in animals expressing genetically encoded calcium sensor (Thy1-GCaMP). Hemodynamics are recorded via simultaneous imaging of multi-spectral reflectance. Significant hemodynamic crosstalk was found in the detected fluorescence signal and the physical model of the contamination, methods of correction as well as electrophysiological verification are presented. A linear model between neural and hemodynamic signals was used to fit spatiotemporal hemodynamics can be predicted by convolving local fluorescence changes with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Beyond confirming that the resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying neural activity, the patterns of bilaterally symmetric spontaneous neural activity observed by WFOM emulate the functionally connected networks detected by fMRI. This result provides reassurance that resting-state functional connectivity has neural origins. With the access to cortical neural activity at mesoscopic level, we further explore the cortical neural representations preceding and during spontaneous locomotion

Interpreting BOLD: towards a dialogue between cognitive and cellular neuroscience

Cognitive neuroscience depends on the use of blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to probe brain function. Although commonly used as a surrogate measure of neuronal activity, BOLD signals actually reflect changes in brain blood oxygenation. Understanding the mechanisms linking neuronal activity to vascular perfusion is, therefore, critical in interpreting BOLD. Advances in cellular neuroscience demonstrating differences in this neurovascular relationship in different brain regions, conditions or pathologies are often not accounted for when interpreting BOLD. Meanwhile, within cognitive neuroscience, increasing use of high magnetic field strengths and the development of model-based tasks and analyses have broadened the capability of BOLD signals to inform us about the underlying neuronal activity, but these methods are less well understood by cellular neuroscientists. In 2016, a Royal Society Theo Murphy Meeting brought scientists from the two communities together to discuss these issues. Here we consolidate the main conclusions arising from that meeting. We discuss areas of consensus about what BOLD fMRI can tell us about underlying neuronal activity, and how advanced modelling techniques have improved our ability to use and interpret BOLD. We also highlight areas of controversy in understanding BOLD and suggest research directions required to resolve these issues

Functional Imaging of Autonomic Regulation: Methods and Key Findings.

Central nervous system processing of autonomic function involves a network of regions throughout the brain which can be visualized and measured with neuroimaging techniques, notably functional magnetic resonance imaging (fMRI). The development of fMRI procedures has both confirmed and extended earlier findings from animal models, and human stroke and lesion studies. Assessments with fMRI can elucidate interactions between different central sites in regulating normal autonomic patterning, and demonstrate how disturbed systems can interact to produce aberrant regulation during autonomic challenges. Understanding autonomic dysfunction in various illnesses reveals mechanisms that potentially lead to interventions in the impairments. The objectives here are to: (1) describe the fMRI neuroimaging methodology for assessment of autonomic neural control, (2) outline the widespread, lateralized distribution of function in autonomic sites in the normal brain which includes structures from the neocortex through the medulla and cerebellum, (3) illustrate the importance of the time course of neural changes when coordinating responses, and how those patterns are impacted in conditions of sleep-disordered breathing, and (4) highlight opportunities for future research studies with emerging methodologies. Methodological considerations specific to autonomic testing include timing of challenges relative to the underlying fMRI signal, spatial resolution sufficient to identify autonomic brainstem nuclei, blood pressure, and blood oxygenation influences on the fMRI signal, and the sustained timing, often measured in minutes of challenge periods and recovery. Key findings include the lateralized nature of autonomic organization, which is reminiscent of asymmetric motor, sensory, and language pathways. Testing brain function during autonomic challenges demonstrate closely-integrated timing of responses in connected brain areas during autonomic challenges, and the involvement with brain regions mediating postural and motoric actions, including respiration, and cardiac output. The study of pathological processes associated with autonomic disruption shows susceptibilities of different brain structures to altered timing of neural function, notably in sleep disordered breathing, such as obstructive sleep apnea and congenital central hypoventilation syndrome. The cerebellum, in particular, serves coordination roles for vestibular stimuli and blood pressure changes, and shows both injury and substantially altered timing of responses to pressor challenges in sleep-disordered breathing conditions. The insights into central autonomic processing provided by neuroimaging have assisted understanding of such regulation, and may lead to new treatment options for conditions with disrupted autonomic function

Development and Localization of Spike-Wave Seizures in Animal Models

Animal models allow for detailed investigation of neuronal function, particularly invasive localization and developmental studies not possible in humans. This thesis will review the technical challenges of simultaneous EEG-fMRI, and epileptogenesis studies in animal models, including issues related to anesthesia, movement, signal artifact, physiology, electrode compatibility, data acquisition, and data analysis, and review recent findings from simultaneous EEG-fMRI studies in epilepsy and other fields. Original research will be presented on the localization of neuronal networks involved during spike-and-wave seizures in the WAG/Rij rat, a model of human absence epilepsy. Simultaneous EEG-fMRI at 9 Tesla, complimented by parallel electrophysiology, including Multiple Unit Activity (MUA), Local Field Potential (LFP), and Cerebral Blood Flow (CBF) measurements were employed to investigate the functioning of neuronal networks. This work indicates that while BOLD signal increases in the Somaotsensory Cortex and Thalamus during SWD are associated with MUA, LFP, and CBF increases, BOLD signal decreases in the Caudate are associated with CBF decreases and relatively larger increase in LFP and smaller increase in MUA. Complimenting the localization studies, original research will also be presented on the development of spike-and-wave epilepsy in the C3H/Hej mouse, a model which will allow for more advanced genetic and molecular investigation. This work shows seizure development progressing though immature, transitional, and mature stages

Integration of EEG-FMRI in an Auditory Oddball Paradigm Using Joint Independent Component Analysis

The integration of event-related potential (ERP) and functional magnetic resonance imaging (fMRI) can contribute to characterizing neural networks with high temporal and spatial resolution. The overall objective of this dissertation is to determine the sensitivity and limitations of joint independent component analysis (jICA) within-subject for integration of ERP and fMRI data collected simultaneously in a parametric auditory oddball paradigm. The main experimental finding in this work is that jICA revealed significantly stronger and more extensive activity in brain regions associated with the auditory P300 ERP than a P300 linear regression analysis, both at the group level and within-subject. The results suggest that, with the incorporation of spatial and temporal information from both imaging modalities, jICA is more sensitive to neural sources commonly observed with ERP and fMRI compared to a linear regression analysis. Furthermore, computational simulations suggest that jICA can extract linear and nonlinear relationships between ERP and fMRI signals, as well as uncoupled sources (i.e., sources with a signal in only one imaging modality). These features of jICA can be important for assessing disease states in which the relationship between the ERP and fMRI signals is unknown, as well as pathological conditions causing neurovascular uncoupling, such as stroke