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      Differential Functional Connectivity along the Long Axis of the Hippocampus Aligns with Differential Role in Memory Specificity and Generalization

      1 , 1 , 1
      Journal of Cognitive Neuroscience
      MIT Press - Journals

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          Abstract

          The hippocampus contributes to both remembering specific events and generalization across events. Recent work suggests that information may be represented along the longitudinal axis of the hippocampus at varied levels of specificity: detailed representations in the posterior hippocampus and generalized representations in the anterior hippocampus. Similar distinctions are thought to exist within neocortex, with lateral prefrontal and lateral parietal regions supporting memory specificity and ventromedial prefrontal and lateral temporal cortices supporting generalized memory. Here, we tested whether functional connectivity of anterior and posterior hippocampus with cortical memory regions is consistent with these proposed dissociations. We predicted greater connectivity of anterior hippocampus with putative generalization regions and posterior hippocampus with putative memory specificity regions. Furthermore, we tested whether differences in connectivity are stable under varying levels of task engagement. Participants learned to categorize a set of stimuli outside the scanner, followed by an fMRI session that included a rest scan, passive viewing runs, and category generalization task runs. Analyses revealed stronger connectivity of ventromedial pFC to anterior hippocampus and of angular gyrus and inferior frontal gyrus to posterior hippocampus. These differences remained relatively stable across the three phases (rest, passive viewing, category generalization). Whole-brain analyses further revealed widespread cortical connectivity with both anterior and posterior hippocampus, with relatively little overlap. These results contribute to our understanding of functional organization along the long axis of the hippocampus and suggest that distinct hippocampal–cortical connections are one mechanism by which the hippocampus represents both individual experiences and generalized knowledge.

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          Most cited references99

          • Record: found
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          Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.

          Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements. Copyright © 2011 Elsevier Inc. All rights reserved.
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            • Record: found
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            • Article: not found

            Control of goal-directed and stimulus-driven attention in the brain.

            We review evidence for partially segregated networks of brain areas that carry out different attentional functions. One system, which includes parts of the intraparietal cortex and superior frontal cortex, is involved in preparing and applying goal-directed (top-down) selection for stimuli and responses. This system is also modulated by the detection of stimuli. The other system, which includes the temporoparietal cortex and inferior frontal cortex, and is largely lateralized to the right hemisphere, is not involved in top-down selection. Instead, this system is specialized for the detection of behaviourally relevant stimuli, particularly when they are salient or unexpected. This ventral frontoparietal network works as a 'circuit breaker' for the dorsal system, directing attention to salient events. Both attentional systems interact during normal vision, and both are disrupted in unilateral spatial neglect.
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              • Record: found
              • Abstract: found
              • Article: not found

              Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization.

              Resting state functional connectivity MRI (fcMRI) is widely used to investigate brain networks that exhibit correlated fluctuations. While fcMRI does not provide direct measurement of anatomic connectivity, accumulating evidence suggests it is sufficiently constrained by anatomy to allow the architecture of distinct brain systems to be characterized. fcMRI is particularly useful for characterizing large-scale systems that span distributed areas (e.g., polysynaptic cortical pathways, cerebro-cerebellar circuits, cortical-thalamic circuits) and has complementary strengths when contrasted with the other major tool available for human connectomics-high angular resolution diffusion imaging (HARDI). We review what is known about fcMRI and then explore fcMRI data reliability, effects of preprocessing, analysis procedures, and effects of different acquisition parameters across six studies (n = 98) to provide recommendations for optimization. Run length (2-12 min), run structure (1 12-min run or 2 6-min runs), temporal resolution (2.5 or 5.0 s), spatial resolution (2 or 3 mm), and the task (fixation, eyes closed rest, eyes open rest, continuous word-classification) were varied. Results revealed moderate to high test-retest reliability. Run structure, temporal resolution, and spatial resolution minimally influenced fcMRI results while fixation and eyes open rest yielded stronger correlations as contrasted to other task conditions. Commonly used preprocessing steps involving regression of nuisance signals minimized nonspecific (noise) correlations including those associated with respiration. The most surprising finding was that estimates of correlation strengths stabilized with acquisition times as brief as 5 min. The brevity and robustness of fcMRI positions it as a powerful tool for large-scale explorations of genetic influences on brain architecture. We conclude by discussing the strengths and limitations of fcMRI and how it can be combined with HARDI techniques to support the emerging field of human connectomics.
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                Author and article information

                Journal
                Journal of Cognitive Neuroscience
                Journal of Cognitive Neuroscience
                MIT Press - Journals
                0898-929X
                1530-8898
                December 2019
                December 2019
                : 31
                : 12
                : 1958-1975
                Affiliations
                [1 ]University of Oregon
                Article
                10.1162/jocn_a_01457
                e993c54e-b57e-44a7-b760-7e758121eeff
                © 2019

                Quantitative & Systems biology,Biophysics
                Quantitative & Systems biology, Biophysics

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