No description available.

This thesis considers the importance of the inferior parietal lobe for calculation and Arabic number comparison. The first experiment demonstrates that repetitive Transcranial Magnetic Stimulation (rTMS) can be used on normal subjects to replicate findings from studies of patients whose ability to calculate after brain injury was impaired. While subjects were solving addition tasks, rTMS was applied over anterior and posterior areas of the inferior parietal lobule and the adjoining intraparietal sulcus (aIPL+S, pIPL+S). In line with results from patient studies, magnetic stimulation showed a disruptive effect only over left IPL+S. It had no disruptive effect when delivered over right inferior parietal lobule and the adjoining intraparietal sulcus. To investigate the representation of number magnitude in the human brain rTMS was subsequently applied to the same inferior parietal regions while subjects performed a number comparison task. With numbers between 31 and 99, repetitive TMS over the pIPL+S disrupted organisation of the putative "number line". rTMS had no disruptive effect when delivered over aIPL+S, in either the left or right hemisphere. With numbers between 1 and 9, however, TMS over the pIPL+S did not impair task performance. Here, TMS had a disruptive effect when delivered over aIPL+S, in either the left or right hemisphere, thus suggesting that areas in the inferior parietal lobes might be specialised for certain number sizes. The idea of a spatial mental number line was further investigated in a detailed single-case description of a person with an automatic mental number line. In the last experiment, functional Magnetic Resonance Imaging (fMRI) was used to investigate number comparison. The fMRI study gave some indication that small numbers might be represented in the aIPL+S region. In general, the fMRI results suggest that parietal cortical contribution to number magnitude representation is intimately related to its role in basic sensorimotor processes.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 131-154).

No description available.

Thesis (Ph.D.)--York University, 2006. Graduate Programme in Psychology. / Typescript. Includes bibliographical references (leaves 148-172). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:NR19801

Thesis (M.Sc.)--York University, 2008. Graduate Programme in Kinesiology and Health Science. / Typescript. Includes bibliographical references (leaves 69-81). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR51534

Research on numerical cognition proposes that there are two systems for the perception of numerical quantity, a small-number system (1~3) invoking parallel individuation, or “subitizing”, and a large-number system (4+) that is based on Weberian magnitude estimation (Hyde, 2011). Many numerical cognitive neuroscientists have focused on studying how the magnitude of numerosities (small vs. large numbers) and numerical distance (close vs. far differences between numbers) are influential factors when processing numbers and change detection. However, is there a difference when numerosities are increasing or decreasing? The effects of direction on numerical change processing are lesser known. This 128-channel EEG study investigated the neurobehavioral basis of differentiation between small vs. large-number perception and effects of change directionality. During EEG data collection, participants were sequentially presented with stimulus arrays of 1 to 6 dots, with parameters like size and location controlled for, to minimize varying non-numerical visual cues during habituation. Participants were instructed to press a key whenever they detect a change in the number of dots presented. The current study adapts a dot-stimuli numerical change study design from Hyde and Spelke (2009, 2012). In their EEG study, the researchers examined event-related-potential (ERP) differences during the processing of small (1, 2, 3) and large (8, 16, 24) numbers. For this study, we chose to examine a narrower numerical range from 1~6, so that small (1, 2, 3) vs. large (4, 5, 6) contrasts were along a numerical continuum. In contrast to Hyde and Spelke (2009, 2012), where participants passively-viewed the sequential presentation of dot arrays, this study employed an active change detection paradigm, where participants’ reaction time (RT) and accuracy in detecting change in the number of dots were recorded. We investigated the effects of Direction and Size in numerical change detection, where Direction is operationally defined as Decreasing and Increasing change in numeric set size, while Size is divided into Small-to-Small, Large-to-Large and Crossovers. Numerical change conditions were categorized into six groups: “Increasing Small-to-Small” (e.g., 1-to-2, 2-to-3), “Decreasing Small-to-Small” (e.g., 2-to-1, 3-to-2), “Increasing Large-Large” (e.g., 4-to-6, 5-to-6), “Decreasing Large-Large” (e.g., 5-to-4, 6-to-5), Increasing Small-to-Large” (e.g., 2-to-4, 3-to-5, 3-to-6) and “Decreasing Large-to-Small” (e.g., 4-to-2, 5-to-2, 6-to-3), where the last two groups are operationally defined as Crossovers. There was also a “No Change” condition, where the number of dots remain the same for up to five presentations. ERP analyses were conducted for the N1 component (125-200 ms) over the left and right occipital-temporal-parietal (POT) junction and for the P3b component (435-535 ms) over the midline parietal area (Pz). During the No Change condition, results show that the N1 amplitude was modulated by the cardinal values of the habituated numbers 1~6. Within this continuous range, we found N1 amplitudes commensurate with cardinal values in the small range (1, 2, 3), but not in the large range (4, 5, 6), suggesting that numbers in the subitizing range are individuated as objects in working memory. Meanwhile, in the Change condition, there was a significant main effect of Direction on N1 peak latency, where the Increasing condition showed earlier peaks. In the Decreasing Small-to-Small condition, N1 amplitudes were the lowest (even lower than N1 peaks for No Change conditions), while the other five Change conditions all produced higher N1 negativities than No Change conditions. These results imply that when the number of dots get small enough to parallel individuate, instead of encoding items into visual short-term memory, the brain is “off-loading” items from our perceptual load. Intriguingly, although the Decreasing Small-to-Small condition had the lowest N1 negativities, it produced the highest P3b positivity. Distinctions in P3b waveforms reflect a clear categorical break between small vs. large numbers, where easier/small number change conditions have higher amplitudes than harder, large number conditions, suggesting more difficulty with updating the context in the latter. However, in contrast to the earlier N1, there was no main effect of Direction on P3b peak latency, but there was an interaction effect of Direction by Size. Interestingly, there was also a similar interaction effect of Direction by Size for reaction times, with similar trends showing that Decreasing conditions produced shorter reaction times for the Large-to-Large and Crossover conditions, yet this pattern was reversed in the Small-to-Small condition. This lends more support to the implication of the “off-loading” phenomenon when processing decreases of numerosities in the small range (1~3). Meanwhile, when it comes to context-updating at later stages, and a behavioral response is required for this change detection task, the Large-to-Large condition prove to be the most difficult, as there was lower accuracy, longer reaction times, later and lower P3b peaks. N1 and P3b amplitudes are complementary to each other, with the early N1 being more sensitive to Direction, and the later P3b being more sensitive to Size. This suggests that the posterior parietal cortex might encode Direction first, followed by Size. This study proposes a model that is an adaptation to the P3b context-updating model (Donchin, 1981), where the early, sensory N1 interplays with the later, cognitive P3b. These findings suggest a neurobehavioral basis for the differentiation of small vs. large number perception at early stages of processing that is sensitive to encoding vs. off-loading objects from perceptual load and visual short-term memory, as well as a later stage that involve higher-order cognitive processing on the magnitude of set size that is employed in numerical change detection tasks.

Thesis (Ph. D. in Psychology)--Vanderbilt University, Dec. 2008. / Title from title screen. Includes bibliographical references.

The hippocampal formation has been implicated in spatial formation for many decades. The hippocampus proper has received the most attention but other regions of the hippocampal formation contribute largely to spatial cognition. This thesis concentrated on one such region, the postsubiculum. The postsubiculum is considered important because it contains head direction cells and because it thought to be a major input to the hippocampus, via the entorhinal cortex. This thesis aims to test the functional role of the rat postsubiculum under two types of situation: one where the rat must rely on idiothetic cues for navigation, and another where the rat has visual cues present and can rely on these for orientation. The thesis also investigates hippocampal place cells and their stability over time after short exposures to novel environments. Chapter 3 of this thesis aimed to test whether the postsubiculum is necessary for path integration during a homing task. Rats were trained on a homing task on a circular platform maze. Once the task was acquired, rats were given lesions of the postsubiculum or sham lesions and then re-tested on the path integration task. The homing performance of rats with lesions of the postsubiculum was as good as that of the sham rats. A series of manipulations suggests that the rats were homing by path integration, confirmed by probe tests. The rats were then tested on a forced-choice delayed alternation T-maze task that revealed a significant impairment in alternation with delays of 5, 30, and 60 seconds. This suggests that the postsubiculum is not necessary for path integration in a homing task but is necessary for avoiding previously visited locations as is necessary in an alternation task. The experiments in Chapters 4 and 5 of this thesis aimed to investigate the effects of postsubiculum pharmacological inactivation on hippocampal CA1 place cells when rats were introduced to a novel environment with visual cues. A necessary first step was to assess place cells without any manipulation of the postsubiculum (Chapter 4) and then use information gained from this in the design of experiments in Chapter 5. Rats chronically implanted with recording electrodes in the CA1 region of the hippocampus were exposed to novel cue-rich environments whilst place fields were recorded. Following delays of 3, 6, or 24 hours, the same cells were recorded again in the same environment but with the cues rotated by 90°. Pixel-by-pixel correlations of the place fields show that stability of the place fields was significantly lower at 24 hours than at 3 hours. Stability after 6 hours was not significantly different from 3 hours. In the third set of experiments, rats were implanted with drug infusion cannulae in the postsubiculum and recording electrodes in CA1. Following infusions of either the AMPA receptor antagonist CXQX, the NMDA receptor antagonist D-AP5 or a control infusion of ACSF, place field stability was assessed as rats were exposed to a cylindrical environment with a single polarising cue card for 3 x 10 minute sessions and then again 6 hours later. There were no differences in place field correlations between the 3 drug conditions, although there was evidence of larger changes in spatial information content between cells in the CNQX and AP5 drug condition, but not the ACSF condition. The results suggest that, under the present testing conditions, place fields stability did not depend upon AMPA receptor-mediated transmission nor did it depend on NMDA receptor-mediated synaptic plasticity.

In real-world settings, decision-making typically resembles a stepwise process in which one decides which information to sample before deciding to which decision option to commit. The former step is called instrumental information-seeking, and theoretical and empirical findings indicate that it is mediated by the value of information (VOI), the extent to which obtaining information increases the expected value of future actions and decisions. Economic theory predicts that to estimate VOI, decision-makers conduct a preposterior analysis in which they prospect what they would expect to know about the decision options after observing the information—or, in terms of Bayesian inference, they should prospect the future posterior probabilities. But the neural mechanisms underlying this early step of the computation of VOI remain an open question. Therefore, to further investigate the neural substrates of instrumental information-seeking, we used functional magnetic resonance imaging (fMRI) in conjunction with two interrelated behavioral tasks in humans. With one task, we examined the demand for instrumental information, but since preposterior analysis relies on the prospection of potential future posterior beliefs, we included another task to examine how people form posterior beliefs after receiving information. We found that regions of posterior parietal cortex and occipital fusiform gyrus appear to support a preposterior analysis through the prospection of expected posterior certainty. This aligned with our finding of a region of parieto-occipital cortex that appears to support Bayesian inference by integrating the prior probability of a hypothesis with the likelihood of observed information. These results imply that parietal cortex plays a key role in Bayesian inference, supporting preposterior analysis during information-seeking in addition to Bayesian inference during categorical decision-making.