Our behaviour is guided by the ability to predict future events. The predictive saccade paradigm has been shown to be a valuable tool that uses eye movements to measure the control of predictive behaviour. In this task, subjects follow a visual target that alternates or “steps” between two fixed locations at either predictable or unpredictable inter-stimulus time intervals (ISIs). Response times can be measured by subtracting the time of saccade initiation from the time of target appearance. When the ISI is predictable, saccadic reaction times (SRTs) become predictive (SRT <100ms) within 3-4 target steps, but when the ISI is unpredictable, the SRTs remain reactive to target appearance (SRT >100ms). The goal of our study was to investigate neural mechanisms controlling prediction by contrasting areas in the brain that were more active for predictive (PRED) versus reactive (REACT) saccades in young healthy adults using functional magnetic resonance imaging (fMRI). fMRI analysis revealed two distinct neural networks more recruited for REACT and PRED tasks. We observed greater activation for the REACT task compared to the PRED task in oculomotor network areas including the frontal, supplementary, parietal eye fields, dorsolateral prefrontal cortex, thalamus, and putamen. These structures are all involved with the control of saccades. We also observed greater activation for the PRED task compared to the REACT task in default network areas, including the medial prefrontal cortex, posterior cingulate cortex, inferior parietal lobule, and hippocampus. These structures are known to be involved with passive thinking when subjects are not focused on their external environments. We also observed greater activation for the PRED task in the cerebellum (crus I), which may serve as the internal clock that drives the regular rhythmic behaviour observed for predictive saccades. In summary, our findings suggest brain activation in the PRED task reflects automated and motor-timed responses, while that for the REACT task reflects externally-driven responses. Therefore, the predictive saccade task is an excellent tool for measuring prediction involving fast internally-guided responses. / Thesis (Master, Neuroscience Studies) -- Queen's University, 2011-08-12 10:21:37.744

The Default Mode Network (DMN) is a large-scale brain network implicated in the control and monitoring of internal modes of cognition. The aim of this research was to investigate DMN function and its relationship to other large-scale cognitive control networks through functional connectivity analysis and analysis of combined electroencephalographic (EEG) recordings. Data utilised across a series of three experiments were obtained from combined EEG-functional Magnetic Resonance Imaging recordings acquired during technical development of a new scanner in the Clinical Research Centre, Ninewells Hospital, Dundee. Analyses were based on data acquired from neurologically healthy participants while they rested with their eyes-closed for five minutes. Following this, participants completed a 14-minute auditory attention task, designed to engage the dorsal and ventral attention networks. In this task, participants responded to task-relevant stimuli (odd/even numbers) and attempted to inhibit their responses to task-irrelevant ‘oddballs’ (the number ‘0’) and task-irrelevant/distractor stimuli (environment sounds). Experiment 1 utilised the simultaneous acquired EEG-fMRI resting-state data in order to establish whether EEG frequency content in the beta range (13-30 Hz) was a significant predictor of DMN activity (regions of which were identified on an individual basis using functional connectivity analysis). Results were comparable to existing literature showing there is inconsistency in establishing a reliable electrophysiological signature of the DMN. Experiment 1 also employed region-of-interest (ROI)-to-ROI functional connectivity analysis as a method of exploring the functional relationship between the DMN and: (1) a task-positive resting-state network; (2) other commonly identified DMN regions; and (3) regions covering the whole of the cerebral cortex. Results revealed networks were correlated at a component-based level and challenged existing literature which appears to over-generalise results from exploration of network interaction. Findings also revealed activation of specific DMN components were coupled with down-regulation of sensory-associated cortical regions. Experiment 2 analysed the fMRI data that were obtained from the auditory attention task in order to: (1) determine whether DMN activity was observed when participants were engaged in an externally-directed task; and (2) explore changes in DMN activity associated with increasing task duration. Results revealed that activation of the DMN was prominent and did not vary over three equal time periods. This supports existing research showing the DMN is a continuously active system (whose activity is modulated based on external-task demands). Results also hinted at the existence of possible relationships between the DMN and components of several other large-scale control networks. Therefore, in Experiment 3 potential interactions were explored using ROI-to-ROI functional connectivity analysis of the whole 14-minute time series. Firstly, functional connectivity within the dorsal/ventral attention, executive/frontoparietal control and salience networks was analysed; secondly, the relationships between putative regions of these networks and the DMN were analysed. Overall, results revealed that networks were functionally connected with one another at a component-based level only. This suggests flexible interaction between several large-scale control networks allows neurologically healthy participants to allocate resources to the simultaneous monitoring of the internal and external worlds.

The main purpose of this dissertation project was to assess the behavioral and neural correlates of Episodic Memory as a function of the APOE genotype in a healthy young adult sample. To accomplish this, 98 subjects completed behavioral tasks assessing visual memory, working memory, episodic memory, and attention. Subjects also completed questionnaires evaluating IQ, years of education, drug use, personality, and emotional traits. These subjects were also genotyped for the APOE gene, resulting in 29 APOE-ε4 carriers (subjects who had at least one ε4 allele) and 69 Non APOE-ε4 carriers (having no ε4 alleles). No differences were found between genotypic groups on any demographic characteristics, behavioral measures, or personality traits. From this larger pool of 98 subjects, a subset of 22 subjects (10 APOE-ε4, 12 Non APOE-ε4) completed additional behavioral tasks while undergoing functional magnetic resonance imaging. While being scanned, subjects were asked to learn word pairs during an encoding phase, make metamemory evaluations on their ability to later remember each word pair during a judgment of learning (JOL) task, and try to discriminate between original and recombined word pairs during a final recognition phase. Interspersed between these tasks was a rest task meant to elicit activity within the Default Network. No differences in memory or metamemory performance were found on the behavioral tasks administered during imaging based on genotype. In contrast, marked differences in brain activation were found between APOE-ε4 carriers and Non APOE-ε4 carriers across the various imaging tasks. During encoding, APOE-ε4 carriers were found to have greater activation than Non APOE-ε4 carriers in the dorsal anterior portion of the left superior temporal gyrus, cingulate gyrus, and anterior middle frontal gyrus. This same pattern - greater APOE-ε4 carrier activation as compared to Non APOE-ε4 carriers - was present in the parahippocampal gyrus and posterior middle temporal gyrus during the judgment of learning metamemory task. During the recognition task, greater activation was found for Non APOE-ε4 carriers versus APOE-ε4 carriers in the left parahippocampal gyrus, SPL, and right anterior superior frontal gyrus. During the rest task, greater activation was seen in APOE-ε4 carriers versus Non APOE-ε4 carriers in the left inferior frontal gyrus, whereas the converse comparison resulted in medial anterior cingulate activation. The lack of behavioral differences suggests that in a healthy young adult sample, as was used in the present study, there are not yet detectable behavioral differences as a function of APOE genotype. The greater neural activity seen in APOE-ε4 carriers during the encoding and judgment of learning tasks is likely to reflect neural compensation: young adult APOE-ε4 carriers compensate for declines in cognitive efficiency with greater neural activity such that this greater neural activity improves behavioral performance, particularly in memory domains (Buckner, Andrews-Hanna, & Schacter, 2008; Han & Bondi, 2008; Levy et al., 2004; Trivedi et al., 2008). The relatively lower levels of activation in APOE-ε4 carriers during the recognition task may reflect stronger memory traces for studied items as a result of greater frontal and medial temporal lobe activity during the encoding and judgment of learning tasks in the APOE-ε4 carriers (Kirwan, Wixted, & Squire, 2008; Mondadoori et al., 2007; Squire, Wixted, & Clark, 2007). In the present sample, a lack of behavioral differences accompanied by neural disparity may signal the precursors of Alzheimer's disease, highlighting the progressive deteriorating influence of the APOE-ε4 allele. The aberrant pattern of default network activity seen in APOE-ε4 carriers underlies this influence as this genotype is proposed to preferentially contribute to the causes of Alzheimer's disease in areas common to the Default Network and Episodic Memory (Buckner et al., 2008). The present results strengthen previous findings illustrating a connection between the brain activity underlying memory processes, the default network, and the APOE genotype.

The default network (DN), and specifically its sub-networks default network A (DN A) and default network B (DN B), has been strongly implicated in social cognition. This study examined its role in predicting social behavior, and also differences that may exist across diagnostic groups that may explain discrepancies in social cognition and behavior. One of the popular methods of study is functional connectivity, or analyzing correlated activity in the brain. Autism Spectrum Disorder (ASD) is a disorder characterized by social impairment and abnormal social behavior. To date, much of the functional connectivity research in ASD has focused on global connectivity, or specific but large areas of the brain. This study adds to the body of that research in attempting to understand both global functional connectivity and the functional connectivity of specific networks (DN A and DN B) that are involved in social cognition and thus implicated in ASD. A sample of 75 individuals with ASD, 85 neurotypical individuals, and 505 individuals with varying other diagnoses was examined to determine the role of global functional connectivity and the role of DN A and DN B in social cognition by the predictive ability of brain features to determine behavioral outcomes. This analysis also aimed to determine if there are group differences in these same brain features. The features we examined included functional connectivity, or the comparison of timeseries of regions of interest, network surface area, and network similarity. This study found that there was no discernible difference across diagnostic group in global or network-specific functional connectivity for DN A. The majority of features for DN B did not differ across diagnostic group, but there was one connection that was significantly different between the autism group and the others. There was no global predictive ability of functional connectivity and brain topology for social cognition measures, nor was there predictive ability for DN A features. DN B features, however, were predictive of social cognition in the autism group, but not in the control group or the other diagnostic groups examined. This study adds to the current body of research by supporting findings already reported by others, and by adding new findings about the role of DN B in social cognition in autism.

Goal-directed episodic simulation, the imaginative construction of a hypothetical personal event or series of events focused on a specific goal, is essential to our everyday lives. We often imagine how we could solve a problem or achieve a goal in the future, or how we could have avoided a misstep in the past, but many of the behavioral and neural mechanisms underlying such goal-directed simulations have yet to be explored. The three papers of this dissertation investigated the neural correlates of three types of future episodic simulations in Papers 1 and 2 and examined a fourth such simulation directed at past events as an adaptive, constructive process in Paper 3. Some research has associated default network activity with internally-focused, but not with goal-directed cognition. Papers 1 and 2 of this dissertation showed that regions of the default network could form functional networks with regions of the frontoparietal control network while participants imagined solving specific problems or going through a sequence of steps necessary to achieve a personal goal. When participants imagined events they associated with actually attaining a goal, default network regions flexibly coupled with reward-processing regions, providing evidence that the default network can join forces with other networks or components thereof to support goal-directed episodic simulations. Using two distinct paradigms with both young and older adults, Paper 3 focused on episodic counterfactual simulations of how past events could have turned out differently and tested whether counterfactual simulations could affect participants' memory of the original events. Our results revealed that episodic counterfactual simulations can act as a type of internally generated misinformation by causing source confusion between the original event and the imagined counterfactual outcome, especially in older adults. The findings of the three papers in this dissertation lay the groundwork for further research on the behavioral and neural mechanisms of goal-directed episodic simulations, as well as their adaptive functions and possible downsides. / Psychology

Individuals with Parkinson’s disease (PD) often show cognitive impairments in addition to motor symptoms, with the majority of PD patients converting to dementia as the disease progresses. The changes in the microstructural integrity of key nodes in resting state networks (RSNs) could be a good indicator of the cognitive effects of PD on brain regions as it progresses to dementia. To assess the association between cognitive effects and microstructural change, the microstructural integrity of the regions of interest (ROIs) in 4 resting state networks (RSN), specifically the default mode network (DMN), based on DTI were obtained in three separate groups of patients with PD. One group of patients (PD-N) were cognitively normal, while the second group of patients (PD-MCI) reflect the transitional phase of mild cognitive impairment prior to dementia, and the third group of patients (PD-D) possessed a clear diagnosis of dementia. A comparison group of healthy controls (HC) were included, matched across the three patient groups. The PD-D group showed worse microstructural integrity for the majority of the ROIs across the 4 networks. The loss of structural integrity in the PD-MCI group was more selective, with some ROIs showing similar changes to PD-D, and others showing similar changes to the PD-N group. The PD-N group fail to show any changes in the structural integrity of any ROIs, relative to HC. For future study, a combined structural / functional study should be performed to examine if there are similar changes across both measures.