Biology subjects

Shine, J.

Publications and source records attributed to Shine, J..

4 recordsLinked to original sources

bioRxiv2017

Hippocampal atrophy and intrinsic brain network alterations relate to impaired capacity for mind wandering in neurodegeneration

Mind wandering represents the human capacity for internally focussed thought, and relies upon the brains default network and its interactions with attentional networks. Studies have characterised mind wandering in healthy people, yet there is limited understanding of how this capacity is affected in clinical populations. This study used a validated thought-sampling task to probe mind wandering capacity in two neurodegenerative disorders: behavioural variant frontotemporal dementia (bvFTD; n=35) and Alzheimers disease (AD; n=24), compared to older controls (n=37). These patient groups were selected due to canonical structural and functional changes across sites of the default and frontoparietal networks, and well-defined impairments in cognitive processes that support mind wandering. Relative to controls, bvFTD patients displayed significantly reduced mind wandering capacity, offset by a significant increase in stimulus-bound thought. In contrast, AD patients demonstrated comparable levels of mind wandering to controls, in the context of a relatively subtle shift towards stimulus-/task-related forms of thought. In the patient groups, mind wandering was associated with grey matter integrity in the hippocampus/parahippocampus, striatum, insula and orbitofrontal cortex. Resting state functional connectivity revealed associations between mind wandering capacity and connectivity within and between regions of the frontoparietal and default networks, with distinct patterns evident in patients vs. controls. These findings support a relationship between altered mind wandering capacity in neurodegenerative disorders, and structural and functional integrity of the default and frontoparietal networks. This study highlights a dimension of cognitive dysfunction not well documented in neurodegenerative disorders, and validates current models of mind wandering in a clinical population.\n\nSignificance statementHumans spend much of their waking life engaged in mind wandering. Underlying brain systems supporting this complex ability have been established in healthy individuals, yet it remains unclear how mind wandering is altered in neuropsychiatric populations. We reveal changes in the thought profiles elicited during periods of low cognitive demand in dementia, resulting in reduced mind wandering and an increased propensity towards stimulus-bound thought. These altered thought profiles were associated with structural and functional brain changes in the hippocampus, default and frontoparietal networks; key regions implicated in internal mentation in healthy individuals. Our findings provide a unique clinical validation of current theoretical models of mind wandering, and reveal a dimension of cognitive dysfunction that has received scant attention in dementia.

neuroscience↗

bioRxiv2017

Catecholaminergic Manipulation Alters Dynamic Network Topology Across Behavioral States

The human brain is able to flexibly adapt its information processing capacity to meet a variety of cognitive challenges. Recent evidence suggests that this flexibility is reflected in the dynamic reorganization of the functional connectome. The ascending catecholaminergic arousal systems of the brain are a plausible candidate mechanism for driving alterations in network architecture, enabling efficient deployment of cognitive resources when the environment demands them. We tested this hypothesis by analyzing both task-free and task-based fMRI data following the administration of atomoxetine, a noradrenaline reuptake inhibitor, compared to placebo, in two separate human fMRI studies. Our results demonstrate that the manipulation of central catecholamine levels leads to a reorganization of the functional connectome in a manner that is sensitive to ongoing cognitive demands.

neuroscience↗

bioRxiv2017

Accumulation of sensory evidence is impaired in Parkinson’s disease with visual hallucinations

Models of hallucinations across disorders emphasise an imbalance between sensory input and top-down influences over perception. However, the psychological and mechanistic correlates of this imbalance remain underspecified. Visual hallucinations in Parkinsons disease (PD) are associated with impairments in lower level visual processes and attention, accompanied by over activity and connectivity in higher-order association brain networks. PD therefore provides an attractive framework to explore the relative contributions of bottom-up versus top-down disturbances in hallucinations. Here, we characterised sensory processing in PD patients with and without visual hallucinations, and in healthy controls, by fitting a hierarchical drift diffusion model (hDDM) to an attentional task. The hDDM uses Bayesian estimates to decompose reaction time and response output into parameters reflecting drift rates of evidence accumulation, decision thresholds and non-decision time. We observed slower drift rates in PD patients with hallucinations, which were insensitive to changes in task demand. In contrast, wider decision boundaries and shorter non-decision times relative to controls were found in PD regardless of hallucinator status. Inefficient and less flexible sensory evidence accumulation emerge as unique features of PD hallucinators. We integrate these results with current models of hallucinations, suggesting that slow and inefficient sensory input in PD is less informative, and may therefore be down-weighted leading to an over reliance on top-down influences. Our findings provide a novel computational framework to better specify the impairments in dynamic sensory processing that are a risk factor for visual hallucinations.

neuroscience↗

bioRxiv2017

The GridCAT: A toolbox for automated analysis of human grid cell codes in fMRI

Human fMRI studies examining the putative firing of grid cells (i.e., the grid code) suggest that this cellular mechanism supports not only spatial navigation, but also more abstract cognitive processes. This research area, however, remains relatively unexplored, perhaps us to the complexities of data analysis. To overcome this, we have developed the Matlab-based Grid Code Analysis Toolbox (GridCAT), providing a graphical user interface, and open-source code, for the analysis of fMRI data. The GridCAT performs all analyses, from estimation and fitting of the grid code in the general linear model, to the generation of grid code metrics and plots. Moreover, it is flexible in allowing the specification of bespoke analysis pipelines; example data are provided to demonstrate the GridCATs main functionality. We believe the GridCAT is essential to opening this research area to the imaging community, and helping to elucidate the role of human grid codes in higher-order cognitive processes.\n\nHighlightsO_LIThe putative firing of grid cells (i.e., the grid code) can be examined using fMRI\nC_LIO_LINecessary steps for grid code analysis are reviewed\nC_LIO_LIThe Matlab-based grid code analysis toolbox (GridCAT) is introduced\nC_LIO_LIAutomated grid code analysis can be conducted either via a graphical user interface or open-source code\nC_LIO_LIA detailed manual and an example dataset are provided\nC_LI

neuroscience↗