Support vector classification analysis of resting state functional connectivity fMRI

Since its discovery in 1995 resting state functional connectivity derived from functional MRI data has become a popular neuroimaging method for study psychiatric disorders. Current methods for analyzing resting state functional connectivity in disease involve thousands of univariate tests, and the specification of regions of interests to employ in the analysis. There are several drawbacks to these methods. First the mass univariate tests employed are insensitive to the information present in distributed networks of functional connectivity. Second, the null hypothesis testing employed to select functional connectivity dierences between groups does not evaluate the predictive power of identified functional connectivities. Third, the specification of regions of interests is confounded by experimentor bias in terms of which regions should be modeled and experimental error in terms of the size and location of these regions of interests. The objective of this dissertation is to improve the methods for functional connectivity analysis using multivariate predictive modeling, feature selection, and whole brain parcellation. A method of applying Support vector classification (SVC) to resting state functional connectivity data was developed in the context of a neuroimaging study of depression. The interpretability of the obtained classifier was optimized using feature selection techniques that incorporate reliability information. The problem of selecting regions of interests for whole brain functional connectivity analysis was addressed by clustering whole brain functional connectivity data to parcellate the brain into contiguous functionally homogenous regions. This newly developed famework was applied to derive a classifier capable of correctly seperating the functional connectivity patterns of patients with depression from those of healthy controls 90% of the time. The features most relevant to the obtain classifier match those previously identified in previous studies, but also include several regions not previously implicated in the functional networks underlying depression.Ph.D.Committee Chair: Hu, Xiaoping; Committee Co-Chair: Vachtsevanos, George; Committee Member: Butera, Robert; Committee Member: Gurbaxani, Brian; Committee Member: Mayberg, Helen; Committee Member: Yezzi, Anthon

High Field fMRI Reveals Thalamocortical Integration of Segregated Cognitive and Emotional Processing in Mediodorsal and Intralaminar Thalamic Nuclei

Thalamocortical loops, connecting functionally segregated, higher order cortical regions, and basal ganglia, have been proposed not only for well described motor and sensory regions, but also for limbic and prefrontal areas relevant for affective and cognitive processes. These functions are, however, more specific to humans, rendering most invasive neuroanatomical approaches impossible and interspecies translations difficult. In contrast, non-invasive imaging of functional neuroanatomy using fMRI allows for the development of elaborate task paradigms capable of testing the specific functionalities proposed for these circuits. Until recently, spatial resolution largely limited the anatomical definition of functional clusters at the level of distinct thalamic nuclei. Since their anatomical distinction seems crucial not only for the segregation of cognitive and limbic loops but also for the detection of their functional interaction during cognitive–emotional integration, we applied high resolution fMRI on 7 Tesla. Using an event-related design, we could isolate thalamic effects for preceding attention as well as experience of erotic stimuli. We could demonstrate specific thalamic effects of general emotional arousal in mediodorsal nucleus and effects specific to preceding attention and expectancy in intralaminar centromedian/parafascicular complex. These thalamic effects were paralleled by specific coactivations in the head of caudate nucleus as well as segregated portions of rostral or caudal cingulate cortex and anterior insula supporting distinct thalamo–striato–cortical loops. In addition to predescribed effects of sexual arousal in hypothalamus and ventral striatum, high resolution fMRI could extent this network to paraventricular thalamus encompassing laterodorsal and parataenial nuclei. We could lend evidence to segregated subcortical loops which integrate cognitive and emotional aspects of basic human behavior such as sexual processing

Analysis of structural and functional brain networks

The brain is a representative example of a network. It consists of numerous spatially distributed regions that continuously exchange information through structural connections. In the past decade, an increasing number of studies have explored the brain network in both structural and functional aspects; they have begun to decipher complex brain wirings, as well as elucidate how the rich functionality emerges from this architecture. Based upon previous studies, this thesis addresses three critical gaps in the field. (I) Although it is known that the community structures of brain network are spatially overlapping, conventional studies have focused on grouping brain regions into communities such that each region belongs to only one community. Therefore, a recent “link community” concept was employed to disentangle those overlapping architectures. (II) Spatial independent component analysis (sICA) and k-means clustering are two representative data-driven algorithms used to analyze functional networks. However, it is still unclear how these two methods compare to each other in terms of their theoretical basis and biological relevance. Hence, the relationship between these two methods were investigated. (III) Despite the multi-scale functional organization of the brain, previous studies have primarily examined the large-scale networks of the entire brain. Complex neural activity patterns in relatively smaller spatial scales have been poorly understood. Therefore, the fine-scale spatiotemporal patterns within visual cortex were explored. The distinguishing results obtained in this study may provide new insights regarding the brain\u27s organization, as well as a better understanding of mathematical and statistical tools for functional and structural network analysis

The homotopic connectivity of the functional brain: a meta-analytic approach

Abstract Homotopic connectivity (HC) is the connectivity between mirror areas of the brain hemispheres. It can exhibit a marked and functionally relevant spatial variability, and can be perturbed by several pathological conditions. The voxel-mirrored homotopic connectivity (VMHC) is a technique devised to enquire this pattern of brain organization, based on resting state functional connectivity. Since functional connectivity can be revealed also in a meta-analytical fashion using co-activations, here we propose to calculate the meta-analytic homotopic connectivity (MHC) as the meta-analytic counterpart of the VMHC. The comparison between the two techniques reveals their general similarity, but also highlights regional differences associated with how HC varies from task to rest. Two main differences were found from rest to task: (i) regions known to be characterized by global hubness are more similar than regions displaying local hubness; and (ii) medial areas are characterized by a higher degree of homotopic connectivity, while lateral areas appear to decrease their degree of homotopic connectivity during task performance. These findings show that MHC can be an insightful tool to study how the hemispheres functionally interact during task and rest conditions

The cingulate cortex and limbic systems for emotion, action, and memory

Evidence is provided for a new conceptualization of the connectivity and functions of the cingulate cortex in emotion, action, and memory. The anterior cingulate cortex receives information from the orbitofrontal cortex about reward and non-reward outcomes. The posterior cingulate cortex receives spatial and action-related information from parietal cortical areas. It is argued that these inputs allow the cingulate cortex to perform action–outcome learning, with outputs from the midcingulate motor area to premotor areas. In addition, because the anterior cingulate cortex connects rewards to actions, it is involved in emotion; and because the posterior cingulate cortex has outputs to the hippocampal system, it is involved in memory. These apparently multiple different functions of the cingulate cortex are related to the place of this proisocortical limbic region in brain connectivity

Papez’s Forgotten Tract: 80 Years of Unreconciled Findings Concerning the Thalamocingulate Tract

The thalamocingulate tract is a key component of the Papez circuit that connects the anterior thalamic nucleus (ATN) to the cingulum bundle. While the other white matter connections, consisting of the fornix, cingulum bundle and mammillothalamic tract, were well defined in Papez’s original 1937 paper, the anatomy of the thalamocingulate pathway was mentioned only in passing. Subsequent research has been unable to clarify the precise anatomical trajectory of this tract. In particular, the site of thalamocingulate tract interactions with the cingulum bundle have been inconsistently reported. This review aims to synthesize research on this least studied component of the Papez circuit. A systemic approach to reviewing historical anatomical dissection and neuronal tracing studies as well as contemporary diffusion magnetic resonance imaging studies of the thalamocingulate tract was undertaken across species. We found that although inconsistent, prior research broadly encompasses two differing descriptions of how the ATN interfaces with the cingulum after passing laterally through the anterior limb of the internal capsule. The first group of studies show that the pathway turns medially and rostrally and passes to the anterior cingulate region (Brodmann areas 24, 33, and 32) only. A second group suggests that the thalamocingulate tract interfaces with both the anterior and posterior cingulate (Brodmann areas 23 and 31) and retrosplenial region (Brodmann area 29). We discuss potential reasons for these discrepancies such as altering methodologies and species differences. We also discuss how these inconsistencies may be resolved in further research with refinements of terminology for the cingulate cortex and the thalamocingulate tract. Understanding the precise anatomical course of the last remaining unresolved final white matter tract in the Papez circuit may facilitate accurate investigation of the role of the complete Papez circuit in emotion and memory