Processing of Stimulus Repetition and Change in the Somatosensory System: Recordings of Electrical and Magnetic Brain Responses

In the present work, effects of stimulus repetition and change in a continuous stimulus stream on the processing of somatosensory information in the human brain were studied. Human scalp-recorded somatosensory event-related potentials (ERPs) and magnetoencephalographic (MEG) responses rapidly diminished with stimulus repetition when mechanical or electric stimuli were applied to fingers. On the contrary, when the ERPs and multi-unit a ctivity (MUA) were directly recorded from the primary (SI) and secondary (SII) somatosensory cortices in a monkey, there was no marked decrement in the somatosensory responses as a function of stimulus repetition. These results suggest that this rate effect is not due to the response diminution in the SI and SII cortices. Obviously the responses to the first stimulus after a long "silent" period are nhanced due to unspecific initial orientation, originating in more broadly distributed and/or deeper neural structures, perhaps in the prefrontal cortices. With fast repetition rates not only the late unspecific but also some early specific somatosensory ERPs were diminished in amplitude. The fast decrease of the ERPs as a function of stimulus repetition is mainly due to the disappearance of the orientation effect and with faster repetition rates additively due to stimulus specific refractoriness. A sudden infrequent change in the continuous stimulus stream also enhanced somatosensory MEG responses to electric stimuli applied to different fingers. These responses were quite similar to those elicited by the deviant stimuli alone when the frequent standard stimuli were omitted. This enhancement was obviously due to the release from refractoriness because the neural structures generating the responses to the infrequent deviants had more time to recover from the refractoriness than the respective structures for the standards. Infrequent deviant mechanical stimuli among frequent standard stimuli also enhanced somatosensory ERPs and, in addition, they elicited a new negative wave which did not occur in the deviants-alone condition. This extra negativity could be recorded to deviations in the stimulation site and in the frequency of the vibratory stimuli. This response is probably a somatosensory analogue of the auditory mismatch negativity (MMN) which has been suggested to reflect a neural mismatch process between the sensory input and the sensory memory trace.

Developmental, functional brain imaging and electrophysiological evidence of visual and auditory working memory

Intact function of working memory (WM) is essential for children and adults to cope with every day life. Children with deficits in WM mechanisms have learning difficulties that are often accompanied by behavioral problems. The neural processes subserving WM, and brain structures underlying this system, continue to develop during childhood till adolescence and young adulthood. With functional magnetic resonance imaging (fMRI) it is possible to investigate the organization and development of WM. The present thesis aimed to investigate, using behavioral and neuroimaging methods, whether mnemonic processing of spatial and nonspatial visual information is segregated in the developing and mature human brain. A further aim in this research was to investigate the organization and development of audiospatial and visuospatial information processing in WM. The behavioral results showed that spatial and nonspatial visual WM processing is segregated in the adult brain. The fMRI result in children suggested that memory load related processing of spatial and nonspatial visual information engages common cortical networks, whereas selective attention to either type of stimuli recruits partially segregated areas in the frontal, parietal and occipital cortices. Deactivation mechanisms that are important in the performance of WM tasks in adults are already operational in healthy school-aged children. Electrophysiological evidence suggested segregated mnemonic processing of visual and auditory location information. The results of the development of audiospatial and visuospatial WM demonstrate that WM performance improves with age, suggesting functional maturation of underlying cognitive processes and brain areas. The development of the performance of spatial WM tasks follows a different time course in boys and girls indicating a larger degree of immaturity in the male than female WM systems. Furthermore, the differences in mastering auditory and visual WM tasks may indicate that visual WM reaches functional maturity earlier than the corresponding auditory system. Spatial WM deficits may underlie some learning difficulties and behavioral problems related to impulsivity, difficulties in concentration, and hyperactivity. Alternatively, anxiety or depressive symptoms may affect WM function and the ability to concentrate, being thus the primary cause of poor academic achievement in children.

Functional imaging of peripheral vision and dorsal stream function in the human cerebral cortex

Visual information processing in brain proceeds in both serial and parallel fashion throughout various functionally distinct hierarchically organised cortical areas. Feedforward signals from retina and hierarchically lower cortical levels are the major activators of visual neurons, but top-down and feedback signals from higher level cortical areas have a modulating effect on neural processing. My work concentrates on visual encoding in hierarchically low level cortical visual areas in human brain and examines neural processing especially in cortical representation of visual field periphery. I use magnetoencephalography and functional magnetic resonance imaging to measure neuromagnetic and hemodynamic responses during visual stimulation and oculomotor and cognitive tasks from healthy volunteers. My thesis comprises six publications. Visual cortex forms a great challenge for modeling of neuromagnetic sources. My work shows that a priori information of source locations are needed for modeling of neuromagnetic sources in visual cortex. In addition, my work examines other potential confounding factors in vision studies such as light scatter inside the eye which may result in erroneous responses in cortex outside the representation of stimulated region, and eye movements and attention. I mapped cortical representations of peripheral visual field and identified a putative human homologue of functional area V6 of the macaque in the posterior bank of parieto-occipital sulcus. My work shows that human V6 activates during eye-movements and that it responds to visual motion at short latencies. These findings suggest that human V6, like its monkey homologue, is related to fast processing of visual stimuli and visually guided movements. I demonstrate that peripheral vision is functionally related to eye-movements and connected to rapid stream of functional areas that process visual motion. In addition, my work shows two different forms of top-down modulation of neural processing in the hierachically lowest cortical levels; one that is related to dorsal stream activation and may reflect motor processing or resetting signals that prepare visual cortex for change in the environment and another local signal enhancement at the attended region that reflects local feed-back signal and may perceptionally increase the stimulus saliency.

Neuromagnetic studies on cortical somatosensory functions in infants and children : Normal development and effect of early brain lesions

Until recently, objective investigation of the functional development of the human brain in vivo was challenged by the lack of noninvasive research methods. Consequently, fairly little is known about cortical processing of sensory information even in healthy infants and children. Furthermore, mechanisms by which early brain insults affect brain development and function are poorly understood. In this thesis, we used magnetoencephalography (MEG) to investigate development of cortical somatosensory functions in healthy infants, very premature infants at risk for neurological disorders, and adolescents with hemiplegic cerebral palsy (CP). In newborns, stimulation of the hand activated both the contralateral primary (SIc) and secondary somatosensory cortices (SIIc). The activation patterns differed from those of adults, however. Some of the earliest SIc responses, constantly present in adults, were completely lacking in newborns and the effect of sleep stage on SIIc responses differed. These discrepancies between newborns and adults reflect the still developmental stage of the newborns’ somatosensory system. Its further maturation was demonstrated by a systematic transformation of the SIc response pattern with age. The main early adult­like components were present by age two. In very preterm infants, at term age, the SIc and SIIc were activated at similar latencies as in healthy fullterm newborns, but the SIc activity was weaker in the preterm group. The SIIc response was absent in four out of the six infants with brain lesions of the underlying hemisphere. Determining the prognostic value of this finding remains a subject for future studies, however. In the CP adolescents with pure subcortical lesions, contrasting their unilateral symptoms, the SIc responses of both hemispheres differed from those of controls: For example the distance between SIc representation areas for digits II and V was shorter bilaterally. In four of the five CP patients with cortico­subcortical brain lesions, no normal early SIc responses were evoked by stimulation of the palsied hand. The varying differences in neuronal functions, underlying the common clinical symptoms, call for investigation of more precisely designed rehabilitation strategies resting on knowledge about individual functional alterations in the sensorimotor networks.

Tactile processing in human somatosensory and auditory cortices

Tactile sensation plays an important role in everyday life. While the somatosensory system has been studied extensively, the majority of information has come from studies using animal models. Recent development of high-resolution anatomical and functional imaging techniques has enabled the non-invasive study of human somatosensory cortex and thalamus. This thesis provides new insights into the functional organization of the human brain areas involved in tactile processing using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). The thesis also demonstrates certain optimizations of MEG and fMRI methods. Tactile digit stimulation elicited stimulus-specific responses in a number of brain areas. Contralateral activation was observed in somatosensory thalamus (Study II), primary somatosensory cortex (SI; I, III, IV), and post-auditory belt area (III). Bilateral activation was observed in secondary somatosensory cortex (SII; II, III, IV). Ipsilateral activation was found in the post-central gyrus (area 2 of SI cortex; IV). In addition, phasic deactivation was observed within ipsilateral SI cortex and bilateral primary motor cortex (IV). Detailed investigation of the tactile responses demonstrated that the arrangement of distal-proximal finger representations in area 3b of SI in humans is similar to that found in monkeys (I). An optimized MEG approach was sufficient to resolve such fine detail in functional organization. The SII region appeared to contain double representations for fingers and toes (II). The detection of activations in the SII region and thalamus improved at the individual and group levels when cardiac-gated fMRI was used (II). Better detection of body part representations at the individual level is an important improvement, because identification of individual representations is crucial for studying brain plasticity in somatosensory areas. The posterior auditory belt area demonstrated responses to both auditory and tactile stimuli (III), implicating this area as a physiological substrate for the auditory-tactile interaction observed in earlier psychophysical studies. Comparison of different smoothing parameters (III) demonstrated that proper evaluation of co-activation should be based on individual subject analysis with minimal or no smoothing. Tactile input consistently influenced area 3b of the human ipsilateral SI cortex (IV). The observed phasic negative fMRI response is proposed to result from interhemispheric inhibition via trans-callosal connections. This thesis contributes to a growing body of human data suggesting that processing of tactile stimuli involves multiple brain areas, with different spatial patterns of cortical activation for different stimuli.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

Cytochrome P450-mediated metabolism in brain: functional roles and their implications

Introduction: Cytochromes P450 (P450) and associated monooxygenases are a family of heme proteins involved in metabolism of endogenous compounds (arachidonic acid, eicosanoids and prostaglandins) as also xenobiotics including drugs and environmental chemicals. Liver is the major organ involved in P450-mediated metabolism and hepatic enzymes have been characterized. Extrahepatic organs, such as lung, kidney and brain have the capability for biotransformation through P450 enzymes. Brain, including human brain, expresses P450 enzymes that metabolize xenobiotics and endogenous compounds. Areas covered: An overview of P450-mediated metabolism in brain is presented focusing on distinct differences seen in expression of P450 enzymes, generation of unique P450 enzymes in brain through alternate splicing and their consequences in terms of metabolism of psychoactive drugs and inflammatory prompts, such as leukotrienes, thus modulating inflammatory response. Expert opinion: The brain possesses unique P450s that metabolize drugs and endogenous compounds through pathways that are markedly different from that seen in liver indicating that extrapolation directly from liver to brain is not appropriate. It is therefore necessary to characterize the unique brain P450s and their ability to metabolize xenobiotics and endogenous compounds to better understand the functions of this important class of enzymes in brain, especially human brain.

Infection of Human Endothelial Cells by Japanese Encephalitis Virus: Increased Expression and Release of Soluble HLA-E

Japanese encephalitis virus (JEV) is a single stranded RNA virus that infects the central nervous system leading to acute encephalitis in children. Alterations in brain endothelial cells have been shown to precede the entry of this flavivirus into the brain, but infection of endothelial cells by JEV and their consequences are still unclear. Productive JEV infection was established in human endothelial cells leading to IFN-beta and TNF-alpha production. The MHC genes for HLA-A, -B, -C and HLA-E antigens were upregulated in human brain microvascular endothelial cells, the endothelial-like cell line, ECV 304 and human foreskin fibroblasts upon JEV infection. We also report the release/shedding of soluble HLA-E (sHLA-E) from JEV infected human endothelial cells for the first time. This shedding of sHLA-E was blocked by an inhibitor of matrix metalloproteinases (MMP). In addition, MMP-9, a known mediator of HLA solubilisation was upregulated by JEV. In contrast, human fibroblasts showed only upregulation of cell-surface HLA-E. Addition of UV inactivated JEV-infected cell culture supernatants stimulated shedding of sHLA-E from uninfected ECV cells indicating a role for soluble factors/cytokines in the shedding process. Antibody mediated neutralization of TNF-alpha as well as IFNAR receptor together not only resulted in inhibition of sHLA-E shedding from uninfected cells, it also inhibited HLA-E and MMP-9 gene expression in JEV-infected cells. Shedding of sHLA-E was also observed with purified TNF-alpha and IFN-beta as well as the dsRNA analog, poly (I:C). Both IFN-beta and TNF-alpha further potentiated the shedding when added together. The role of soluble MHC antigens in JEV infection is hitherto unknown and therefore needs further investigation.

Infection of human amniotic and endothelial cells by Japanese encephalitis virus: Increased expression of HLA-F

Productive infection of human amniotic and endothelial cell lines with Japanese encephalitis virus (JEV) was established leading to the induction of NF kappa B and HLA-F, a non-classical MHC molecule. Induction of the HLA-F gene and protein in JEV-infected cells was shown to be NF kappa B dependent since it was blocked by inhibitors of NF kappa B activation. ShRNA targeting lentivirus-mediated stable knockdown of the p65 subunit of NF kappa B inhibited JEV-mediated induction of HLA-F both in the amniotic cell line, AV-3 as well as the human brain microendothelial cell line, HBMEC. The induction of HLA-F by treatment of AV-3 with TNF-alpha was also inhibited by ShRNA mediated knockdown of NF kappa B. TNF-alpha treatment of HEK293T cells that were transfected with reporter plasmids under the control of HLA-F enhancer A elements resulted in significant transactivation of the luciferase reporter gene. NF kappa B-mediated induction of HLA-F following JEV infection and TNF-alpha exposure is being suggested for the first time. (C) 2014 Elsevier Inc. All rights reserved.

Patterning and detailed study of human hNT astrocytes on parylene-C/silicon dioxide substrates to the single cell level.

It is estimated that the adult human brain contains 100 billion neurons with 5-10 times as many astrocytes. Although it has been generally considered that the astrocyte is a simple supportive cell to the neuron, recent research has revealed new functionality of the astrocyte in the form of information transfer to neurons of the brain. In our previous work we developed a protocol to pattern the hNT neuron (derived from the human teratocarcinoma cell line (hNT)) on parylene-C/SiO(2) substrates. In this work, we report how we have managed to pattern hNT astrocytes, on parylene-C/SiO(2) substrates to single cell resolution. This article disseminates the nanofabrication and cell culturing steps necessary for the patterning of such cells. In addition, it reports the necessary strip lengths and strip width dimensions of parylene-C that encourage high degrees of cellular coverage and single cell isolation for this cell type. The significance in patterning the hNT astrocyte on silicon chip is that it will help enable single cell and network studies into the undiscovered functionality of this interesting cell, thus, contributing to closer pathological studies of the human brain.

GFAP Isoforms in Adult Mouse Brain with a Focus on Neurogenic Astrocytes and Reactive Astrogliosis in Mouse Models of Alzheimer Disease

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Mathematical study of complex networks : brain, internet, and power grid

The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept of “power over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

A novel brain partition highlights the modular skeleton shared by structure and function

Elucidating the intricate relationship between brain structure and function, both in healthy and pathological conditions, is a key challenge for modern neuroscience. Recent progress in neuroimaging has helped advance our understanding of this important issue, with diffusion images providing information about structural connectivity (SC) and functional magnetic resonance imaging shedding light on resting state functional connectivity (rsFC). Here, we adopt a systems approach, relying on modular hierarchical clustering, to study together SC and rsFC datasets gathered independently from healthy human subjects. Our novel approach allows us to find a common skeleton shared by structure and function from which a new, optimal, brain partition can be extracted. We describe the emerging common structure-function modules (SFMs) in detail and compare them with commonly employed anatomical or functional parcellations. Our results underline the strong correspondence between brain structure and resting-state dynamics as well as the emerging coherent organization of the human brain.

Accelerated evolution of the pituitary adenylate cyclase-activating polypeptide precursor gene during human origin

Pituitary adenylate cyclase-activating polypeptide (PACAP) is a neuropeptide abundantly expressed in the central nervous system and involved in regulating neurogenesis and neuronal signal transduction. The amino acid sequence of PACAP is extremely conserved across vertebrate species, indicating a strong functional constraint during the course of evolution. However, through comparative sequence analysis, we demonstrated that the PACAP precursor gene underwent an accelerated evolution in the human lineage since the divergence from chimpanzees, and the amino acid substitution rate in humans is at least seven times faster than that in other mammal species resulting from strong Darwinian positive selection. Eleven human-specific amino acid changes were identified in the PACAP precursors, which are conserved from murine to African apes. Protein structural analysis suggested that a putative novel Deuropeptide might have originated during human evolution and functioned in the human brain. Our data suggested that the PACAP precursor gene underwent adaptive changes during human origin and may have contributed to the formation of human cognition.

Improved delineation of short cortical association fibers and gray/white matter boundary using whole-brain three-dimensional diffusion tensor imaging at submillimeter spatial resolution.

Recent emergence of human connectome imaging has led to a high demand on angular and spatial resolutions for diffusion magnetic resonance imaging (MRI). While there have been significant growths in high angular resolution diffusion imaging, the improvement in spatial resolution is still limited due to a number of technical challenges, such as the low signal-to-noise ratio and high motion artifacts. As a result, the benefit of a high spatial resolution in the whole-brain connectome imaging has not been fully evaluated in vivo. In this brief report, the impact of spatial resolution was assessed in a newly acquired whole-brain three-dimensional diffusion tensor imaging data set with an isotropic spatial resolution of 0.85 mm. It was found that the delineation of short cortical association fibers is drastically improved as well as the definition of fiber pathway endings into the gray/white matter boundary-both of which will help construct a more accurate structural map of the human brain connectome.