Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI

Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach are demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility

Interactive Visualization of Multimodal Brain Connectivity: Applications in Clinical and Cognitive Neuroscience

Magnetic resonance imaging (MRI) has become a readily available prognostic and diagnostic method, providing invaluable information for the clinical treatment of neurological diseases. Multimodal neuroimaging allows integration of complementary data from various aspects such as functional and anatomical properties; thus, it has the potential to overcome the limitations of each individual modality. Specifically, functional and diffusion MRI are two non-invasive neuroimaging techniques customized to capture brain activity and microstructural properties, respectively. Data from these two modalities is inherently complex, and interactive visualization can assist with data comprehension. The current thesis presents the design, development, and validation of visualization and computation approaches that address the need for integration of brain connectivity from functional and structural domains. Two contexts were considered to develop these approaches: neuroscience exploration and minimally invasive neurosurgical planning. The goal was to provide novel visualization algorithms and gain new insights into big and complex data (e.g., brain networks) by visual analytics. This goal was achieved through three steps: 3D Graphical Collision Detection: One of the primary challenges was the timely rendering of grey matter (GM) regions and white matter (WM) fibers based on their 3D spatial maps. This challenge necessitated pre-scanning those objects to generate a memory array containing their intersections with memory units. This process helped faster retrieval of GM and WM virtual models during the user interactions. Neuroscience Enquiry (MultiXplore): A software interface was developed to display and react to user inputs by means of a connectivity matrix. This matrix displays connectivity information and is capable to accept selections from users and display the relevant ones in 3D anatomical view (with associated anatomical elements). In addition, this package can load multiple matrices from dynamic connectivity methods and annotate brain fibers. Neurosurgical Planning (NeuroPathPlan): A computational method was provided to map the network measures to GM and WM; thus, subject-specific eloquence metric can be derived from related resting state networks and used in objective assessment of cortical and subcortical tissue. This metric was later compared to apriori knowledge based decisions from neurosurgeons. Preliminary results show that eloquence metric has significant similarities with expert decisions

Dynamic Thermal Imaging for Intraoperative Monitoring of Neuronal Activity and Cortical Perfusion

Neurosurgery is a demanding medical discipline that requires a complex interplay of several neuroimaging techniques. This allows structural as well as functional information to be recovered and then visualized to the surgeon. In the case of tumor resections this approach allows more fine-grained differentiation of healthy and pathological tissue which positively influences the postoperative outcome as well as the patient's quality of life. In this work, we will discuss several approaches to establish thermal imaging as a novel neuroimaging technique to primarily visualize neural activity and perfusion state in case of ischaemic stroke. Both applications require novel methods for data-preprocessing, visualization, pattern recognition as well as regression analysis of intraoperative thermal imaging. Online multimodal integration of preoperative and intraoperative data is accomplished by a 2D-3D image registration and image fusion framework with an average accuracy of 2.46 mm. In navigated surgeries, the proposed framework generally provides all necessary tools to project intraoperative 2D imaging data onto preoperative 3D volumetric datasets like 3D MR or CT imaging. Additionally, a fast machine learning framework for the recognition of cortical NaCl rinsings will be discussed throughout this thesis. Hereby, the standardized quantification of tissue perfusion by means of an approximated heating model can be achieved. Classifying the parameters of these models yields a map of connected areas, for which we have shown that these areas correlate with the demarcation caused by an ischaemic stroke segmented in postoperative CT datasets. Finally, a semiparametric regression model has been developed for intraoperative neural activity monitoring of the somatosensory cortex by somatosensory evoked potentials. These results were correlated with neural activity of optical imaging. We found that thermal imaging yields comparable results, yet doesn't share the limitations of optical imaging. In this thesis we would like to emphasize that thermal imaging depicts a novel and valid tool for both intraoperative functional and structural neuroimaging

Network Dynamics of Visual Object Recognition

Visual object recognition is the principal mechanism by which humans and many animals interpret their surroundings. Despite the complexity of neural computation required, object recognition is achieved with such rapidity and accuracy that it appears to us almost effortless. Extensive human and non-human primate research has identified putative category-selective regions within higher-level visual cortex, which are thought to mediate object recognition. Despite decades of study, however, the functional organization and network dynamics within these regions remain poorly understood, due to a lack of appropriate animal models as well as the spatiotemporal limitations of current non-invasive human neuroimaging techniques (e.g. fMRI, scalp EEG). To better understand these issues, we leveraged the high spatiotemporal resolution of intracranial EEG (icEEG) recordings to study rapid, transient interactions between the disseminated cortical substrates within category-specific networks. Employing novel techniques for the topologically accurate and statistically robust analysis of grouped icEEG, we found that category-selective regions were spatially arranged with respect to cortical folding patterns, and relative to each other, to generate a hierarchical information structuring of visual information within higher-level visual cortex. This may facilitate rapid visual categorization by enabling the extraction of different levels of object detail across multiple spatial scales. To characterize network interactions between distributed regions sharing the same category-selectivity, we evaluated feed-forward, hierarchal and parallel, distributed models of information flow during face perception via measurements of cortical activation, functional and structural connectivity, and transient disruption through electrical stimulation. We found that input from early visual cortex (EVC) to two face-selective regions – the occipital and fusiform face areas (OFA and FFA, respectively) – occurred in a parallelized, distributed fashion: Functional connectivity between EVC and FFA began prior to the onset of subsequent re-entrant connectivity between the OFA and FFA. Furthermore, electrophysiological measures of structural connectivity revealed independent cortico- cortical connections between the EVC and both the OFA and FFA. Finally, direct disruption of the FFA, but not OFA, impaired face-perception. Given that the FFA is downstream of the OFA, these findings are incompatible with the feed-forward, hierarchical models of visual processing, and argue instead for the existence of parallel, distributed network interactions

Distributed XQuery-based integration and visualization of multimodality data: Application to brain mapping.

This paper addresses the need for relatively small groups of collaborating investigators to integrate distributed and heterogeneous data about the brain. Although various national efforts facilitate large-scale data sharing, these approaches are generally too “heavyweight” for individual or small groups of investigators, with the result that most data sharing among collaborators continues to be ad hoc. Our approach to this problem is to create a “lightweight” distributed query architecture, in which data sources are accessible via web services that accept arbitrary query languages but return XML results. A Distributed XQuery Processor (DXQP) accepts distributed XQueries in which subqueries are shipped to the remote data sources to be executed, with the resulting XML integrated by DXQP. A web-based application called DXBrain accesses DXQP, allowing a user to create, save and execute distributed XQueries, and to view the results in various formats including a 3-D brain visualization. Example results are presented using distributed brain mapping data sources obtained in studies of language organization in the brain, but any other XML source could be included. The advantage of this approach is that it is very easy to add and query a new source, the tradeoff being that the user needs to understand XQuery and the schemata of the underlying sources. For small numbers of known sources this burden is not onerous for a knowledgeable user, leading to the conclusion that the system helps to fill the gap between ad hoc local methods and large scale but complex national data sharing efforts

Effects of intracranial stimulation and the involvement of the human parahippocampal cortex in perception

How the human brain translates photons hitting the retina into conscious perception remains an open question. Throughout the medial temporal lobe (MTL), there are neurons (called concept cells) that change their firing rate when that neuron's preferred concept, e.g., a specific person or object, is seen. The firing rate of concept cells is correlated with perception. Nevertheless, it remains unclear whether or to what extent concept cells are involved in perceptogenesis, i.e., the creation of conscious percepts. Inferring from studies in monkeys, concept-specific neurons involved in perceptogenesis would be expected along the ventral and dorsal stream of visual processing (also called the what and where pathway, respectively). Various regions that are part of the dorsal stream are connected to the parahippocampal cortex (PHC), a region within the MTL. Compared to other MTL regions, lower selectivity, the absence of multimodal responses, and especially the shorter response latencies do not exclude an involvement of the PHC in perceptogenesis. In fact, damage to the parahippocampal place area (PPA, a part of the PHC) results in topographical disorientation. The goal of this thesis is to test the involvement of the PHC in perception by using electrical stimulation during a forced-choice categorization task involving landscapes versus animals. First, we determined effective parameters for intracranial stimulation of brain tissue in epilepsy patients implanted with depth-electrodes for seizure monitoring. We investigated the effects of amplitude, phase width, frequency, and pulse-train duration on neuronal firing, the local field potential (LFP), and behavioral responses to evoked percepts. Frequency and charge per phase were the most influential parameters on all three signals. Both parameters showed a positive effect on event-related potentials (ERPs) in the LFP. Higher frequencies (especially around 200 Hz) lead to a short-term inhibition of neuronal firing, while higher charge per phase can have an inhibitory or excitatory effect on neuronal firing. All parameters had a positive effect on the reports of evoked percepts; on reports of phosphenes in response to stimulating close to the optic radiation as well as on reports of auditory verbal hallucinations in response to stimulating Heschl's gyrus. Using functional magnetic resonance imaging (fMRI), we found that the PPA, i.e., the part of the PHC that is most selective towards images of landscapes, is rather small (up to 1‰ of total brain volume per hemisphere) with varying degrees of hemispheric laterality. Stimulating the PHC outside of the PPA - using a 100 ms high-frequency pulse train delivered at the natural response latency of the PHC - had no effect on categorizing landscapes. However, stimulating inside the PPA, close to the peak activation of the fMRI cluster, resulted in a 7% to 10% increase in landscape responses to ambiguous stimuli. Furthermore, stimulating the PPA also led to an increase in behavioral response time, especially to images with a predominant landscape component. None of our patients reported visual hallucinations of places or scenes in response to our stimulation protocols. Our data suggests that the PPA is involved in the perceptogenesis of landscapes at a stage that does not reach awareness, while the rest of the PHC is unlikely to be involved in perceptogenesis, at least not as it pertains to the perception of landscapes or animals. We also developed an online spike sorting algorithm and an adaptive screening procedure for concept cells to pave the way for new paradigms involving informed feedback