Patients with antisocial personality disorder (ASPD) are deceptive, apathetic, and impulsive. Their social behavior is often inappropriate, and they fail to follow social norms, leading to frequent criminal behavior. Understanding the neural correlates of ASPD could alleviate issues for the patients, such as unstable living conditions, as well as financial costs for the justice system and society. Due to previous research and theoretical implications of the prefrontal cortex (PFC) and its role in emotion-regulation and decision-making, it is likely that ASPD patients would show differences in the PFC relative to healthy individuals. Therefore, emphasis is placed on this region. By systematically reviewing articles which used fMRI to examine ASPD patients, this paper aims to understand if the brain activity in the PFC or functional connectivity within these regions differs between ASPD patients and healthy controls. Decreased activity was found in the anterior cingulate cortex (ACC) and dorsolateral PFC (dlPFC) in ASPD patients compared to healthy controls. Further, decreased functional connectivity was found in the frontoparietal control network, default modenetwork, and attentional network. Other prefrontal regions implicated include the medial frontal cortex, orbitofrontal cortex, and medial prefrontal cortex. Most of these regions are important for cognitive control, enabling integration of information regarding, e.g., errors and conflict. Abnormal processing of such information can lead to the impulsive or inappropriate actions often seen in ASPD patients. The PFC seems to play an important functional role in ASPD, mainly the regions responsible for cognitive control, such as the ACC and dlPFC.

Cognitive dissonance is the uncomfortable psychological feeling that arises when something is perceived as contradictory. In 1957, Leon Festinger first developed the theory of cognitive dissonance, which has since continued to be of interest for, among other things, decision-making, moral reasoning, motivation, politics, and science. This systematic review summarises six peer-reviewed studies that use functional magnetic resonance imaging (fMRI) to measure if there is increased activity in the anterior cingulate cortex (ACC) and dorsal anterior cingulate cortex (dACC) during cognitive dissonance in adults. Four studies tested cognitive dissonance during forced choices and two during counter-attitudinal behaviours. The overall fMRI results indicate increased activity in ACC and dACC to dissonance versus control conditions, but with some inconsistency on the exact locations in the brain.

The flow state is a subjective experience that most people can relate to. It represents an optimal balance between skills and difficulty and is the state that people often refer to when performing their best, with phrases like: “I was in the zone” or “I was in the bubble”. The flow state has mainly been studied through its psychological and behavioral components; it is not until lately the neuroscientific aspects have been investigated. This review attempts to go through the existing literature and find potential neural signatures of the flow state. The studies indicate that flow is related to activity in the dorsolateral prefrontal cortex and putamen, but the findings are too divided to reach a conclusion.

The structure of regional correlation graphs built from fMRI-derived data is frequently used in algorithms to automatically classify brain data. Transformation on the data is performed during pre-processing to remove irrelevant or inaccurate information to ensure that an accurate representation of the subject's resting-state connectivity is attained. Our research suggests and confirms that such pre-processed data still exhibits inherent transitivity, which is expected to obscure the true relationships between regions. This obfuscation prevents known solutions from developing an accurate understanding of a subject’s functional connectivity. By removing correlative transitivity, connectivity between regions is made more specific and automated classification is expected to improve. The task of utilizing fMRI to automatically diagnose Attention Deficit/Hyperactivity Disorder was posed by the ADHD-200 Consortium in a competition to draw in researchers and new ideas from outside of the neuroimaging discipline. Researchers have since worked with the competition dataset to produce ever-increasing detection rates. Our approach was empirically tested with a known solution to this problem to compare processing of treated and untreated data, and the detection rates were shown to improve in all cases with a weighted average increase of 5.88%.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21919号 / 情博第702号 / 新制||情||120(附属図書館) / 京都大学大学院情報学研究科システム科学専攻 / (主査)教授 石井 信, 教授 松田 哲也, 教授 加納 学, 川人 光男 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

In this thesis we were interested in combining functional connectivity (from functional Magnetic Resonance Imaging) and structural connectivity (from Diffusion Tensor Imaging) with a data fusion approach. While data fusion approaches provide an abundance of information they are underutilized due to their complexity. To solve this problem, we integrated the ease of a neuroimaging toolbox, known as the Functional And Tractographic Analysis Toolbox (FATCAT) with a data fusion approach known as the anatomically weighted functional connectivity (awFC) approach - to produce a practical and more efficient pipeline. We studied the connectivity within resting-state networks of different populations using this novel pipeline. We performed separate analyses with traditional structural and functional connectivity for comparison with the awFC findings - across all three projects. In the first study we evaluated the awFC of participants with major depressive disorder compared to controls. We observed significant connectivity differences in the default mode network (DMN) and the ventral attention network (VAN). In the second study we studied the awFC of MDD remitters compared to non-remitters at baseline and week-8 (post antidepressant), and evaluated awFC in remitters longitudinally from baseline to to week-8. We found significant group differences in the DMN, VAN, and frontoparietal network (FPN) for remitters and non-remitters at week-8. We also found significant awFC longitudinally from baseline to week-8 in the dorsal attention network (DAN) and FPN. We also tested the associations between connectivity strength and cognition. In the third study we studied the awFC in children exposed to pre- and postnatal adversity compared to controls. We observed significant differences in the DMN, FPN, VAN, DAN, and limbic network (LIM). We also assessed the association between connectivity strength in middle childhood and motor and behavioural scores at age 3. Therefore, the FATCAT-awFC pipeline, we designed was capable of identifying group differences in RSN in a practical and more efficient manner. / Thesis / Doctor of Philosophy (PhD)

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