The development of constrained source localisation algorithms for human brain imaging

This work sets out to evaluate the potential benefits and pit-falls in using a priori information to help solve the Magnetoencephalographic (MEG) inverse problem. In chapter one the forward problem in MEG is introduced, together with a scheme that demonstrates how a priori information can be incorporated into the inverse problem. Chapter two contains a literature review of techniques currently used to solve the inverse problem. Emphasis is put on the kind of a priori information that is used by each of these techniques and the ease with which additional constraints can be applied. The formalism of the FOCUSS algorithm is shown to allow for the incorporation of a priori information in an insightful and straightforward manner. In chapter three it is described how anatomical constraints, in the form of a realistically shaped source space, can be extracted from a subject’s Magnetic Resonance Image (MRI). The use of such constraints relies on accurate co-registration of the MEG and MRI co-ordinate systems. Variations of the two main co-registration approaches, based on fiducial markers or on surface matching, are described and the accuracy and robustness of a surface matching algorithm is evaluated. Figures of merit introduced in chapter four are shown to given insight into the limitations of a typical measurement set-up and potential value of a priori information. It is shown in chapter five that constrained dipole fitting and FOCUSS outperform unconstrained dipole fitting when data with low SNR is used. However, the effect of errors in the constraints can reduce this advantage. Finally, it is demonstrated in chapter six that the results of different localisation techniques give corroborative evidence about the location and activation sequence of the human visual cortical areas underlying the first 125ms of the visual magnetic evoked response recorded with a whole head neuromagnetometer.

Cognitive systems associated with the hippocampus of the human brain and their role in behaviour and neurodegenerative disease

Cognitive systems research involves the synthesis of ideas from natural and artificial systems in the analysis, understanding, and design of all intelligent systems. This chapter discusses the cognitive systems associated with the hippocampus (HC) of the human brain and their possible role in behaviour and neurodegenerative disease. The hippocampus (HC) is concerned with the analysis of highly abstract data derived from all sensory systems but its specific role remains controversial. Hence, there have been three major theories concerning its function, viz., the memory theory, the spatial theory, and the behavioral inhibition theory. The memory theory has its origin in the surgical destruction of the HC, which results in severe anterograde and partial retrograde amnesia. The spatial theory has its origin in the observation that neurons in the HC of animals show activity related to their location within the environment. By contrast, the behavioral inhibition theory suggests that the HC acts as a ‘comparator’, i.e., it compares current sensory events with expected or predicted events. If a set of expectations continues to be verified then no alteration of behavior occurs. If, however, a ‘mismatch’ is detected then the HC intervenes by initiating appropriate action by active inhibition of current motor programs and initiation of new data gathering. Understanding the cognitive systems of the hippocampus in humans may aid in the design of intelligent systems involved in spatial mapping, memory, and decision making. In addition, this information may lead to a greater understanding of the course of clinical dementia in the various neurodegenerative diseases in which there is significant damage to the HC.

Human brain slices for epilepsy research:pitfalls, solutions and future challenges

Increasingly, neuroscientists are taking the opportunity to use live human tissue obtained from elective neurosurgical procedures for electrophysiological studies in vitro. Access to this valuable resource permits unique studies into the network dynamics that contribute to the generation of pathological electrical activity in the human epileptic brain. Whilst this approach has provided insights into the mechanistic features of electrophysiological patterns associated with human epilepsy, it is not without technical and methodological challenges. This review outlines the main difficulties associated with working with epileptic human brain slices from the point of collection, through the stages of preparation, storage and recording. Moreover, it outlines the limitations, in terms of the nature of epileptic activity that can be observed in such tissue, in particular, the rarity of spontaneous ictal discharges, we discuss manipulations that can be utilised to induce such activity. In addition to discussing conventional electrophysiological techniques that are routinely employed in epileptic human brain slices, we review how imaging and multielectrode array recordings could provide novel insights into the network dynamics of human epileptogenesis. Acute studies in human brain slices are ultimately limited by the lifetime of the tissue so overcoming this issue provides increased opportunity for information gain. We review the literature with respect to organotypic culture techniques that may hold the key to prolonging the viability of this material. A combination of long-term culture techniques, viral transduction approaches and electrophysiology in human brain slices promotes the possibility of large scale monitoring and manipulation of neuronal activity in epileptic microcircuits.

Optic flow in human vision: MEG reveals a foveo-fugal bias in V1, specialization for spiral space in hMSTs, and global motion sensitivity in the IPS

Abstract We recorded MEG responses from 17 participants viewing random-dot patterns simulating global optic flow components (expansion, contraction, rotation, deformation, and translation) and a random motion control condition. Theta-band (3–7 Hz), MEG signal power was greater for expansion than the other optic flow components in a region concentrated along the calcarine sulcus, indicating an ecologically valid, foveo-fugal bias for unidirectional motion sensors in V1. When the responses to the optic flow components were combined, a decrease in MEG beta-band (17–23 Hz) power was found in regions extending beyond the calcarine sulcus to the posterior parietal lobe (inferior to IPS), indicating the importance of structured motion in this region. However, only one cortical area, within or near the V5/hMT+ complex, responded to all three spiral-space components (expansion, contraction, and rotation) and showed no selectivity for global translation or deformation: we term this area hMSTs. This is the first demonstration of an exclusive region for spiral space in the human brain and suggests a functional role better suited to preliminary analysis of ego-motion than surface pose, which would involve deformation. We also observed that the rotation condition activated the cerebellum, suggesting its involvement in visually mediated control of postural adjustment.

Neuronal network pharmacodynamics of GABAergic modulation in the human cortex determined using pharmaco-magnetoencephalography

Neuronal network oscillations are a unifying phenomenon in neuroscience research, with comparable measurements across scales and species. Cortical oscillations are of central importance in the characterization of neuronal network function in health and disease and are influential in effective drug development. Whilst animal in vitro and in vivo electrophysiology is able to characterize pharmacologically induced modulations in neuronal activity, present human counterparts have spatial and temporal limitations. Consequently, the potential applications for a human equivalent are extensive. Here, we demonstrate a novel implementation of contemporary neuroimaging methods called pharmaco-magnetoencephalography. This approach determines the spatial profile of neuronal network oscillatory power change across the cortex following drug administration and reconstructs the time course of these modulations at focal regions of interest. As a proof of concept, we characterize the nonspecific GABAergic modulator diazepam, which has a broad range of therapeutic applications. We demonstrate that diazepam variously modulates ? (4–7 Hz), a (7–14 Hz), ß (15–25 Hz), and ? (30–80 Hz) frequency oscillations in specific regions of the cortex, with a pharmacodynamic profile consistent with that of drug uptake. We examine the relevance of these results with regard to the spatial and temporal observations from other modalities and the various therapeutic consequences of diazepam and discuss the potential applications of such an approach in terms of drug development and translational neuroscience.

Contrast matching and discrimation in human vision

The aim of this work was to investigate human contrast perception at various contrast levels ranging from detection threshold to suprathreshold levels by using psychophysical techniques. The work consists of two major parts. The first part deals with contrast matching, and the second part deals with contrast discrimination. Contrast matching technique was used to determine when the perceived contrasts of different stimuli were equal. The effects of spatial frequency, stimulus area, image complexity and chromatic contrast on contrast detection thresholds and matches were studied. These factors influenced detection thresholds and perceived contrast at low contrast levels. However, at suprathreshold contrast levels perceived contrast became directly proportional to the physical contrast of the stimulus and almost independent of factors affecting detection thresholds. Contrast discrimination was studied by measuring contrast increment thresholds which indicate the smallest detectable contrast difference. The effects of stimulus area, external spatial image noise and retinal illuminance were studied. The above factors affected contrast detection thresholds and increment thresholds measured at low contrast levels. At high contrast levels, contrast increment thresholds became very similar so that the effect of these factors decreased. Human contrast perception was modelled by regarding the visual system as a simple image processing system. A visual signal is first low-pass filtered by the ocular optics. This is followed by spatial high-pass filtering by the neural visual pathways, and addition of internal neural noise. Detection is mediated by a local matched filter which is a weighted replica of the stimulus whose sampling efficiency decreases with increasing stimulus area and complexity. According to the model, the signals to be compared in a contrast matching task are first transferred through the early image processing stages mentioned above. Then they are filtered by a restoring transfer function which compensates for the low-level filtering and limited spatial integration at high contrast levels. Perceived contrasts of the stimuli are equal when the restored responses to the stimuli are equal. According to the model, the signals to be discriminated in a contrast discrimination task first go through the early image processing stages, after which signal dependent noise is added to the matched filter responses. The decision made by the human brain is based on the comparison between the responses of the matched filters to the stimuli, and the accuracy of the decision is limited by pre- and post-filter noises. The model for human contrast perception could accurately describe the results of contrast matching and discrimination in various conditions.

No gender differences in brain activation during the N-back task:An fMRI study in healthy individuals

Gender differences have been well established in verbal and spatial abilities but few studies have examined if these differences also extend into the domain of working memory in terms of behavioural differences and brain activation. The conclusions that can be drawn from these studies are not clear cut but suggest that even though gender differences might not be apparent from behavioural measures, the underlying neural substrate associated with working memory might be different in men and women. Previous research suggests activation in a network of frontal and parietal regions during working memory tasks. This study aimed to investigate gender differences in patterns of brain activation during a verbal version of the N-back working memory task, which incorporates the effects of increased demands on working memory. A total of 50 healthy subjects, aged 18 to 58 years, that were equally split by gender were recruited matched for age, levels of education and ethnicity. All subjects underwent functional magnetic resonance imaging. We found that men and women performed equally well in terms of accuracy and response times, while using similar brain regions to the same degree. Our observations indicate that verbal working memory is not affected by gender at the behavioural or neural level, and support the findings of a recent meta-analysis by Hyde ([2005]: Sex Roles 53:717-725) that gender differences are generally smaller than intra-gender differences in many cognitive domains. © 2009 Wiley-Liss, Inc.

The human hippocampus and its significance in neuropsychology and disease

This article discusses the structure, anatomical connections, and functions of the hippocampus (HC) of the human brain and its significance in neuropsychology and disease. The HC is concerned with the analysis of highly abstract data derived from all sensory systems but its specific role remains controversial. Hence, there have been three major theories concerning its function, viz., the memory theory, the spatial theory, and the behavioral inhibition system (BIS) theory. The memory theory has its origin in the surgical destruction of the HC, which results in severe anterograde and partial retrograde amnesia. The spatial theory has its origin in the observation that neurons in the HC of animals show activity related to their location within the environment. By contrast, the behavioral inhibition theory suggests that the HC acts as a ‘comparator’, i.e., it compares current sensory events with expected or predicted events. If a set of expectations continues to be verified then no alteration of behavior occurs. If, however, a ‘mismatch’ is detected then the HC intervenes by initiating appropriate action by active inhibition of current motor programs and initiation of new data gathering. Understanding the anatomical connections of the hippocampus may lead to a greater understanding of memory, spatial orientation, and states of anxiety in humans. In addition, HC damage is a feature of neurodegenerative diseases such as Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), Pick’s disease (PiD), and Creutzfeldt-Jakob disease (CJD) and understanding HC function may help to explain the development of clinical dementia in these disorders.

The human hippocampus:structure, function and its significance in neuropsychology and disease

This article discusses the structure, anatomical connections, and functions of the hippocampus (HC) of the human brain and its significance in neuropsychology and disease. The HC is concerned with the analysis of highly abstract data derived from all sensory systems but its specific role remains controversial. Hence, there have been three major theories concerning its function, viz., the memory theory, the spatial theory, and the behavioral inhibition system (BIS) theory. The memory theory has its origin in the surgical destruction of the HC, which results in severe anterograde and partial retrograde amnesia. The spatial theory has its origin in the observation that neurons in the HC of animals show activity related to their location within the environment. By contrast, the behavioral inhibition theory suggests that the HC acts as a 'comparator', i.e., it compares current sensory events with expected or predicted events. If a set of expectations continues to be verified then no alteration of behavior occurs. If, however, a 'mismatch' is detected then the HC intervenes by initiating appropriate action by active inhibition of current motor programs and initiation of new data gathering. Understanding the anatomical connections of the hippocampus may lead to a greater understanding of memory, spatial orientation, and states of anxiety in humans. In addition, HC damage is a feature of neurodegenerative diseases such as Alzheimer's disease (AD), dementia with Lewy bodies (DLB), Pick's disease (PiD), and Creutzfeldt-Jakob disease (CJD) and understanding HC function may help to explain the development of clinical dementia in these disorders.

Amyloid β 1-42 induces hypometabolism in human stem cell-derived neuron and astrocyte networks

Alzheimer's disease (AD) is the most common form of dementia, affecting more than 35 million people worldwide. Brain hypometabolism is a major feature of AD, appearing decades before cognitive decline and pathologic lesions. To date, the majority of studies on hypometabolism in AD have used transgenic animal models or imaging studies of the human brain. As it is almost impossible to validate these findings using human tissue, alternative models are required. In this study, we show that human stem cell-derived neuron and astrocyte cultures treated with oligomers of amyloid beta 1-42 (Aβ1-42) also display a clear hypometabolism, particularly with regard to utilization of substrates such as glucose, pyruvate, lactate, and glutamate. In addition, a significant increase in the glycogen content of cells was also observed. These changes were accompanied by changes in NAD+ /NADH, ATP, and glutathione levels, suggesting a disruption in the energy-redox axis within these cultures. The high energy demands associated with neuronal functions such as memory formation and protection from oxidative stress put these cells at particular risk from Aβ-induced hypometabolism. Further research using this model may elucidate the mechanisms associated with Aβ-induced hypometabolism.

Are there theory of mind regions in the brain? A review of the neuroimaging literature

There have been many functional imaging studies of the brain basis of theory of mind (ToM) skills, but the findings are heterogeneous and implicate anatomical regions as far apart as orbitofrontal cortex and the inferior parietal lobe. The functional imaging studies are reviewed to determine whether the diverse findings are due to methodological factors. The studies are considered according to the paradigm employed (e.g., stories vs. cartoons and explicit vs. implicit ToM instructions), the mental state(s) investigated, and the language demands of the tasks. Methodological variability does not seem to account for the variation in findings, although this conclusion may partly reflect the relatively small number of studies. Alternatively, several distinct brain regions may be activated during ToM reasoning, forming an integrated functional "network." The imaging findings suggest that there are several "core" regions in the network-including parts of the prefrontal cortex and superior temporal sulcus-while several more "peripheral" regions may contribute to ToM reasoning in a manner contingent on relatively minor aspects of the ToM task. © 2008 Wiley-Liss, Inc.

Causality and synchronisation in complex systems with applications to neuroscience

This thesis presents an investigation, of synchronisation and causality, motivated by problems in computational neuroscience. The thesis addresses both theoretical and practical signal processing issues regarding the estimation of interdependence from a set of multivariate data generated by a complex underlying dynamical system. This topic is driven by a series of problems in neuroscience, which represents the principal background motive behind the material in this work. The underlying system is the human brain and the generative process of the data is based on modern electromagnetic neuroimaging methods . In this thesis, the underlying functional of the brain mechanisms are derived from the recent mathematical formalism of dynamical systems in complex networks. This is justified principally on the grounds of the complex hierarchical and multiscale nature of the brain and it offers new methods of analysis to model its emergent phenomena. A fundamental approach to study the neural activity is to investigate the connectivity pattern developed by the brain’s complex network. Three types of connectivity are important to study: 1) anatomical connectivity refering to the physical links forming the topology of the brain network; 2) effective connectivity concerning with the way the neural elements communicate with each other using the brain’s anatomical structure, through phenomena of synchronisation and information transfer; 3) functional connectivity, presenting an epistemic concept which alludes to the interdependence between data measured from the brain network. The main contribution of this thesis is to present, apply and discuss novel algorithms of functional connectivities, which are designed to extract different specific aspects of interaction between the underlying generators of the data. Firstly, a univariate statistic is developed to allow for indirect assessment of synchronisation in the local network from a single time series. This approach is useful in inferring the coupling as in a local cortical area as observed by a single measurement electrode. Secondly, different existing methods of phase synchronisation are considered from the perspective of experimental data analysis and inference of coupling from observed data. These methods are designed to address the estimation of medium to long range connectivity and their differences are particularly relevant in the context of volume conduction, that is known to produce spurious detections of connectivity. Finally, an asymmetric temporal metric is introduced in order to detect the direction of the coupling between different regions of the brain. The method developed in this thesis is based on a machine learning extensions of the well known concept of Granger causality. The thesis discussion is developed alongside examples of synthetic and experimental real data. The synthetic data are simulations of complex dynamical systems with the intention to mimic the behaviour of simple cortical neural assemblies. They are helpful to test the techniques developed in this thesis. The real datasets are provided to illustrate the problem of brain connectivity in the case of important neurological disorders such as Epilepsy and Parkinson’s disease. The methods of functional connectivity in this thesis are applied to intracranial EEG recordings in order to extract features, which characterize underlying spatiotemporal dynamics before during and after an epileptic seizure and predict seizure location and onset prior to conventional electrographic signs. The methodology is also applied to a MEG dataset containing healthy, Parkinson’s and dementia subjects with the scope of distinguishing patterns of pathological from physiological connectivity.

Functional source separation applied to induced visual gamma activity

Objective of this work was to explore the performance of a recently introduced source extraction method, FSS (Functional Source Separation), in recovering induced oscillatory change responses from extra-cephalic magnetoencephalographic (MEG) signals. Unlike algorithms used to solve the inverse problem, FSS does not make any assumption about the underlying biophysical source model; instead, it makes use of task-related features (functional constraints) to estimate source/s of interest. FSS was compared with blind source separation (BSS) approaches such as Principal and Independent Component Analysis, PCA and ICA, which are not subject to any explicit forward solution or functional constraint, but require source uncorrelatedness (PCA), or independence (ICA). A visual MEG experiment with signals recorded from six subjects viewing a set of static horizontal black/white square-wave grating patterns at different spatial frequencies was analyzed. The beamforming technique Synthetic Aperture Magnetometry (SAM) was applied to localize task-related sources; obtained spatial filters were used to automatically select BSS and FSS components in the spatial area of interest. Source spectral properties were investigated by using Morlet-wavelet time-frequency representations and significant task-induced changes were evaluated by means of a resampling technique; the resulting spectral behaviours in the gamma frequency band of interest (20-70 Hz), as well as the spatial frequency-dependent gamma reactivity, were quantified and compared among methods. Among the tested approaches, only FSS was able to estimate the expected sustained gamma activity enhancement in primary visual cortex, throughout the whole duration of the stimulus presentation for all subjects, and to obtain sources comparable to invasively recorded data.

Assessing interactions of linear and nonlinear neuronal sources using MEG beamformers:a proof of concept

Objective: This study aimed to explore methods of assessing interactions between neuronal sources using MEG beamformers. However, beamformer methodology is based on the assumption of no linear long-term source interdependencies [VanVeen BD, vanDrongelen W, Yuchtman M, Suzuki A. Localization of brain electrical activity via linearly constrained minimum variance spatial filtering. IEEE Trans Biomed Eng 1997;44:867-80; Robinson SE, Vrba J. Functional neuroimaging by synthetic aperture magnetometry (SAM). In: Recent advances in Biomagnetism. Sendai: Tohoku University Press; 1999. p. 302-5]. Although such long-term correlations are not efficient and should not be anticipated in a healthy brain [Friston KJ. The labile brain. I. Neuronal transients and nonlinear coupling. Philos Trans R Soc Lond B Biol Sci 2000;355:215-36], transient correlations seem to underlie functional cortical coordination [Singer W. Neuronal synchrony: a versatile code for the definition of relations? Neuron 1999;49-65; Rodriguez E, George N, Lachaux J, Martinerie J, Renault B, Varela F. Perception's shadow: long-distance synchronization of human brain activity. Nature 1999;397:430-3; Bressler SL, Kelso J. Cortical coordination dynamics and cognition. Trends Cogn Sci 2001;5:26-36]. Methods: Two periodic sources were simulated and the effects of transient source correlation on the spatial and temporal performance of the MEG beamformer were examined. Subsequently, the interdependencies of the reconstructed sources were investigated using coherence and phase synchronization analysis based on Mutual Information. Finally, two interacting nonlinear systems served as neuronal sources and their phase interdependencies were studied under realistic measurement conditions. Results: Both the spatial and the temporal beamformer source reconstructions were accurate as long as the transient source correlation did not exceed 30-40 percent of the duration of beamformer analysis. In addition, the interdependencies of periodic sources were preserved by the beamformer and phase synchronization of interacting nonlinear sources could be detected. Conclusions: MEG beamformer methods in conjunction with analysis of source interdependencies could provide accurate spatial and temporal descriptions of interactions between linear and nonlinear neuronal sources. Significance: The proposed methods can be used for the study of interactions between neuronal sources. © 2005 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.