NEW APPROACHES FOR ESTIMATING HEMISPHERIC LATERALIZATION FROM RESTING STATE FMRI DATA WITH RELATIONSHIP TO AGE, GENDER AND MENTAL DISORDERS

Lateralization is specialization of the brain hemispheres in certain tasks, such as language, mathematics, cognition and motor skills. It is one of the most queried topics related to the human brain. After the invention of modern medical imaging techniques including functional magnetic resonance imaging (fMRI), scientific research about the human brain, including lateralization, gained huge momentum. There have been a remarkable numbers of studies about lateralization and most of these studies focused on investigating which part of the brain dominates in which tasks. However, there have been very few lateralization studies on brain intrinsic activity, i.e., resting state activity where subjects are asked to stay awake while resting without performing any specific tasks. Independent component analysis (ICA), a data-driven blind source separation method, has become one of the conventional data analysis tools for brain imaging data. ICA can separate the brain imaging data into functional regions that are temporally coherent, and functional network connectivity (FNC) of these regions can be computed. FNC is a measure that captures the temporal covariance of the brain networks. In this dissertation, we focus on the lateralization during the resting state and assess hemispheric differences during the resting state. The lateralization of the resting state networks and their association with age and gender is presented using a large resting state fMRI dataset. A novel approach for generating hemisphere specific time-courses and computing FNC inside the hemispheres and between hemispheres is proposed and the relationship of these FNC values with age, gender and mental illness, schizophrenia is reported. Finally, a new framework to estimate power spectral density of 4D brain imaging data and a dimension reduction method to reduce dimensionality from 4D frequency domain to 2D frequency domain has been proposed. This framework helps us to reveal spatiotemporal organization differences between hemispheres. In summary, our work has made several contributions to advance lateralization analysis and has improved our understanding of various aspects of hemispheric differences during the resting stat

Doctor of Philosophy

dissertationSystematic differences in functional connectivity magnetic resonance imaging metrics have been consistently observed in autism. I attempted to predict group membership using data provided by the Autism Brain Imaging Data Exchange, including resting state functional magnetic resonance imaging data obtained from 964 subjects and 16 separate international sites. For each of 964 subjects, I obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the gray matter and attempted to classify the subjects using a leave-one-out classifier with the 26.4 million connections as features. Classification accuracy significantly outperformed chance but was much lower for multisite prediction than for previous single site results. As high as 60% accuracy was obtained for whole brain classification. Classification accuracy was significantly higher for sites with longer blood oxygen-level dependent imaging times. Attempts to use multisite classifiers will likely require improved classification algorithms, longer blood oxygen-level dependent imaging times, and standardized acquisition parameters for possible future clinical utility. Lateralization of brain structure and function occurs in typical development and subserves functions such as language and visuospatial processing. Abnormal lateralization is present in various neuropsychiatric disorders. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such iv phenotypic differences in the strength of left-dominant or right-dominant networks exist. I evaluated whether strongly lateralized connections covaried within the same typically developing individuals (n = 1011). I also compared lateralization of functional connections in typical development and in autism. In typical development, left- and rightlateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Our data are not consistent with a whole-brain phenotype of greater "left-brained" or greater "rightbrained" network strength across individuals. The autism group lacked left lateralization in three connections involving language regions and regions from the default mode network. Abnormal language lateralization in autism may be due to abnormal language development rather than a deficit in hemispheric specialization of the entire brain

Task Residual Functional Connectivity in Language and Attention Networks

The present study compared network specificity between task-residual and resting state data types. Task-residual data capitalizes on the remaining variance after the mean task-related signal is removed from the time series. This study also examined how inter- and intrahemispheric connectivity (bilateral homologous regions and regions contained within the same hemisphere, respectively) within the language and attention networks change as a result of age. Task-residual functional connectivity evidenced stronger laterality of the language and attention connections and thus greater network specificity than resting state functional connectivity of the same connections. Using task-residual data may be optimal for characterizing the synchronized fluctuations between regions of discrete networks. Furthermore, alterations in intrahemispheric functional connectivity can be observed as early as middle age within the domain-general attention domain

Ageing, Grey Matter Loss and Resting-State Effective Connectivity

Aldring påvirker kroppen på forskjellige måter. Ikke-patologisk aldring karakteriseres av asymmetrisk tap av grå materie, som påvirker den tjukkere hemisfæren sterkere (Roe et al., 2021). Det er ukjent hvordan disse strukturelle forandringene kan relateres til intrinsisk aktivitet som måles med «resting state» funksjonell magnetresonanstomografi (fMRI). Derfor undersøkte vi sammenhengen mellom sannsynlighetsverdier for grå materie (GMPV) og effektiv konnektivet (EC). De observerte dataene inneholder to tidspunkter, T5 og T6, fra det longitudinelle BETULA prosjektet (N = 227). Canonical Correlation Analysis indikerer relasjoner mellom EC og GMPV innom Default Mode Network og Central Executive Network. Sammenhengen mellom EC og GMPV ble spesifisert ved hjelp av generalized additive models. I tillegg fant vi forskjeller i EC mellom T5 og T6, fra venstre dorsal Prefrontal Cortex til høyre medial Temporal Gyrus og høyre Prefrontal Cortex til venstre Precuneus. Videre predikerte GMPV EC bedre enn kronologisk alder. Sammenhengen mellom strukturell og funksjonell lateralisering i de aktuelle dataene var svak. Det ble funnet markører for sammenhengen mellom hjernestruktur og -funksjon.Master's Thesis in PsychologyMAPSYK360INTL-HFINTL-MNINTL-PSYKINTL-MEDMAPS-PSYKINTL-KMDINTL-SVINTL-JU

Dynamic funcitonal reorganizations and relationships with working memory performance in healthy aging

In recent years, several theories have been proposed in attempts to identify the neural mechanisms underlying successful cognitive aging. Old subjects show increased neural activity during the performance of tasks, mainly in prefrontal areas, which is interpreted as a compensatory mechanism linked to functional brain efficiency. Moreover, resting-state studies have concluded that elders show disconnection or disruption of large-scale functional networks. We used functional MRI during resting-state and a verbal n-back task with different levels of memory load in a cohort of young and old healthy adults to identify patterns of networks associated with working memory and brain default mode. We found that the disruption of resting-state networks in the elderly coexists with task-related overactivations of certain brain areas and with reorganizations within these functional networks. Moreover, elders who were able to activate additional areas and to recruit a more bilateral frontal pattern within the task-related network achieved successful performance on the task. We concluded that the balanced and plastic reorganization of brain networks underlies successful cognitive aging. This observation allows the integration of several theories that have been proposed to date regarding the aging brain

The Functional Connectivity Landscape of the Human Brain

Functional brain networks emerge and dissipate over a primarily static anatomical foundation. The dynamic basis of these networks is inter-regional communication involving local and distal regions. It is assumed that inter-regional distances play a pivotal role in modulating network dynamics. Using three different neuroimaging modalities, 6 datasets were evaluated to determine whether experimental manipulations asymmetrically affect functional relationships based on the distance between brain regions in human participants. Contrary to previous assumptions, here we show that short- and long-range connections are equally likely to strengthen or weaken in response to task demands. Additionally, connections between homotopic areas are the most stable and less likely to change compared to any other type of connection. Our results point to a functional connectivity landscape characterized by fluid transitions between local specialization and global integration. This ability to mediate functional properties irrespective of spatial distance may engender a diverse repertoire of cognitive processes when faced with a dynamic environment.</p

FMRI resting slow fluctuations correlate with the activity of fast cortico-cortical physiological connections

Recording of slow spontaneous fluctuations at rest using functional magnetic resonance imaging (fMRI) allows distinct long-range cortical networks to be identified. The neuronal basis of connectivity as assessed by resting-state fMRI still needs to be fully clarified, considering that these signals are an indirect measure of neuronal activity, reflecting slow local variations in de-oxyhaemoglobin concentration. Here, we combined fMRI with multifocal transcranial magnetic stimulation (TMS), a technique that allows the investigation of the causal neurophysiological interactions occurring in specific cortico-cortical connections. We investigated whether the physiological properties of parieto-frontal circuits mapped with short-latency multifocal TMS at rest may have some relationship with the resting-state fMRI measures of specific resting-state functional networks (RSNs). Results showed that the activity of fast cortico-cortical physiological interactions occurring in the millisecond range correlated selectively with the coupling of fMRI slow oscillations within the same cortical areas that form part of the dorsal attention network, i.e., the attention system believed to be involved in reorientation of attention. We conclude that resting-state fMRI ongoing slow fluctuations likely reflect the interaction of underlying physiological cortico-cortical connections

Functional Disconnection and Compensation in Mild Cognitive Impairment: Evidence from DLPFC Connectivity Using Resting-State fMRI

The known regional abnormality of the dorsolateral prefrontal cortex (DLPFC) and its role in various neural circuits in mild cognitive impairment (MCI) has given prominence to its importance in studies on the disconnection associated with MCI. The purpose of the current study was to examine the DLPFC functional connectivity patterns during rest in MCI patients and the impact of regional grey matter (GM) atrophy on the functional results. Structural and functional MRI data were collected from 14 MCI patients and 14 age, gender-matched healthy controls. We found that both the bilateral DLPFC showed reduced functional connectivity with the inferior parietal lobule (IPL), superior/medial frontal gyrus and sub-cortical regions (e.g., thalamus, putamen) in MCI patients when compared with healthy controls. Moreover, the DLPFC connectivity with the IPL and thalamus significantly correlated with the cognitive performance of patients as measured by mini-mental state examination (MMSE), clock drawing test (CDT), and California verbal learning test (CVLT) scores. When taking GM atrophy as covariates, these results were approximately consistent with those without correction, although there may be a decrease in the statistical power. These results suggest that the DLPFC disconnections may be the substrates of cognitive impairments in MCI patients. In addition, we also found enhanced functional connectivity between the left DLPFC and the right prefrontal cortex in MCI patients. This is consistent with previous findings of MCI-related increased activation during cognitive tasks, and may represent a compensatory mechanism in MCI patients. Together, the present study demonstrated the coexistence of functional disconnection and compensation in MCI patients using DLPFC functional connectivity analysis, and thus might provide insights into biological mechanism of the disease

Domain-general Stroop Performance and Hemispheric Asymmetries: A Resting-state EEG Study

The ability to suppress irrelevant information while executing a task or interference resistance is a function of pFC that is critical for successful goal-directed human behavior. In the study of interference resistance and, more generally, executive functions, two key questions are still open: Does pFC contribute to cognitive control abilities through lateralized but domain-general mechanisms or through hemispheric specialization of domain-specific processes? And what are the underlying causes of interindividual differences in executive control performance? To shed light on these issues, here we employed an interindividual difference approach to investigate whether participants' hemispheric asymmetry in resting-state electrophysiological brain dynamics may reflect their variability in domain-general interference resistance. We recorded participants' resting-state electroencephalographic activity and performed spectral power analyses on the estimated cortical source activity. To measure participants' lateralized brain dynamics at rest, we computed the right-left hemispheric asymmetry score for the \u3b2/\u3b1 power ratio. To measure their domain-general interference resistance ability, verbal and spatial Stroop tasks were used. Robust correlations followed by intersection analyses showed that participants with stronger resting-state-related left-lateralized activity in different pFC regions, namely the mid-posterior superior frontal gyrus, middle and posterior middle frontal gyrus, and inferior frontal junction, were more able to inhibit irrelevant information in both domains. The present results confirm and extend previous findings showing that neurophysiological difference factors may explain interindividual differences in executive functioning. They also provide support for the hypothesis of a left pFC hemispheric specialization for domain-independent phasic cognitive control processes mediating Stroop performance