Schizophrenia is a severe neuropsychiatric disorder characterized by delusions, hallucinations, behavioral symptoms, and cognitive deficits. Roughly, 70%-80% of schizophrenia patients experience auditory verbal hallucinations (AVHs), with 25%-30% demonstrating resistance to conventional antipsychotic medications. Studies suggest a promising role for add-on transcranial direct current stimulation (tDCS) in the treatment of medication-refractory AVHs. The mechanisms through which tDCS could be therapeutic in such cases are unclear, but possibly involve neuroplastic effects. In recent years, functional near-infrared spectroscopy (fNIRS) has been used successfully to study tDCS-induced neuroplastic changes. In a double-blind, sham-controlled design, we applied fNIRS to measure task-dependent cerebral blood flow (CBF) changes as a surrogate outcome of single session tDCS-induced effects on neuroplasticity in a schizophrenia patient with persistent auditory hallucinations. The observations are discussed in this case report.

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Thesis (S.M.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 99-100). / Signal detection and synchronization in the time varying ocean environment is a difficult endeavor. The current common methods include using a linear frequency modulated chirped pulse or maximal length sequence as a detection pulse, then match filtering to that signal. In higher signal to noise ratio (SNR) environments (- 0 dB and higher) this has been a suitable solution. As the SNR drops lower however, this solution no longer provides an acceptable probability of detection for a given tolerable probability of false alarm. The issue derives from the inherent coherence issues in the ocean environment which limit the useful matched filter length. This thesis proposes an alternative method of detection based on a recursive least squares linearly adaptive equalizer which we term the Adaptive Linear Equalizer Detector (ALED). This detectors performance has demonstrated reliable probability of detection with minimal interfering false alarms with SNR as low as -20 dB. Additionally this thesis puts forth a computationally feasible method for implementing the detector. / by Ryan Thomas Gieleghem. / S.M.

京都大学 / 0048 / 新制・課程博士 / 博士(社会健康医学) / 甲第20289号 / 社医博第78号 / 社新制||医||9(附属図書館) / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 山田 亮, 教授 中山 健夫, 教授 古川 壽亮 / 学位規則第4条第1項該当 / Doctor of Public Health / Kyoto University / DFAM

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Signal detection theory (SDT) provides a theoretical framework for describing performance on decision making tasks, and fuzzy signal detection theory (FSDT) extends this description to include tasks in which there are levels of uncertainty regarding the categorization of stimulus events. Specifically, FSDT can be used to quantify the degree to which an event is 'signal-like', i.e., the degree to which a stimulus event can be characterized by both signal and non-signal properties. For instance, an improvised explosive device (IED) poses little threat when missing key elements of its assembly (a stimulus of low, but not zero, signal strength) whereas the threat is greater when all elements necessary to ignite the device are present (a stimulus of high signal strength). This research develops a link between key individual cognitive (i.e., spatial orientation and visualization) and personality (i.e., extroversion, conscientiousness, and neuroticism) differences among observers to performance on a fuzzy signal detection task, in which the items to be detected (IEDs) are presented in various states of assembly. That is, this research relates individual difference measures to task performance, uses FSDT in target detection, and provides application of the theory to vigilance tasks. In two experiments, participants viewed pictures of IEDs, not all of which are assembled or include key components, and categorize them using a fuzzy rating scale (no threat, low threat potential, moderate threat potential, or definite threat). In both experiments, there were significant interactions between the stimulus threat level category and the variability of images within each category. The results of the first experiment indicated that spatial and mechanical ability were stronger predictors of performance when the signal was ambiguous than when individuals viewed stimuli in which the signal was fully absent or fully present (and, thus, less ambiguous). The second study showed that the length of time a stimulus is viewed is greatest when the signal strength is low and there is ambiguity regarding the threat level of the stimulus. In addition, response times were substantially longer in study 2 than in study 1, although patterns of performance accuracy, as measured by the sensitivity index d', were similar across the two experiments. Together, the experiments indicate that individuals take longer to evaluate a potential threat as less critical, than to identify either an absence of threat or a high degree of threat and that spatial and mechanical ability assist decision making when the threat level is unclear. These results can be used to increase the efficiency of employees working in threat-detection positions, such as luggage screeners, provides an exemplar of use of FSDT, and contributes to the understanding of human decision making.

Source memory is our ability to relate central information (the “item”) to the context (the “source”) in which it was learned or experienced. People are often highly confident in their source judgements even when this information is incorrectly recalled. Past work has aimed to explain why source errors made with high confidence occur with a framework called the Converging Criteria (CC) account. The CC account posits that item memory can interact with source memory by altering decision criteria as item confidence increases, increasing the probability of a high confidence source judgement. This prediction differs from alternate models, like the Fixed Criteria (FC) account, where decision criteria are not expected to change with item confidence. The current study not only tests the implications of the CC account, but contrasts it to the predictions of the FC account relative to item memory, item confidence, and source discriminability, using existing data from 12 recognition memory experiments. We use a Bayesian Hierarchical model to estimate a key metric called the Item Confidence Effect (ICE) - the change in the proportion of source errors made with high confidence as item confidence increases. Results show a positive ICE, demonstrating that the proportion of source errors made with high confidence increases with item confidence, as predicted by the CC account. In the context of memory, this evidence shows that decision processes can influence behavior, regardless if evidence in memory supports it or not.

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