Differentiating normal and abnormal ageing using a combined functional connectivity and neuropsychological biomarker
The impetus of this thesis is to ascertain the extent to which resting state neuroimaging reveals neuropsychologically relevant and clinically salient biomarkers to distinguish normal and abnormal ageing. Section 1. A literature review was undertaken to characterise the neuropsychological correlates...
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ndltd-bl.uk-oai-ethos.bl.uk-5892532017-10-04T03:25:49ZDifferentiating normal and abnormal ageing using a combined functional connectivity and neuropsychological biomarkerBruen, Peita D.Venneri, Annalena2013The impetus of this thesis is to ascertain the extent to which resting state neuroimaging reveals neuropsychologically relevant and clinically salient biomarkers to distinguish normal and abnormal ageing. Section 1. A literature review was undertaken to characterise the neuropsychological correlates of resting state networks in persons with Mild Cognitive Impairment (MCI). The results suggest episodic memory performance decreases as a function of decreased coherence of the spontaneous correlations between medial parietal, temporal and frontal regions of the default mode network and that the posterior cingulate cortex (PCC) may be the most salient biomarker for cognitive decline due to Alzheimer's pathology. The conclusions suggest further work is needed to characterise the relationship between resting state imaging markers and semantic memory and to understand how semantic and episodic memory are mediated by resting state network connectivity in normal ageing. Section 2. Based on the conclusions of the literature review an empirical study was devised to ascertain if clinical and age related variance in semantic and episodic memory is associated with disrupted connectivity of the PCC. The results demonstrated that whilst semantic memory is sensitive and specific to abnormal ageing, episodic memory impairment is more sensitive and specific to PCC connectivity in normal ageing and disease. The correlates of PCC connectivity and episodic memory in MCI were associated with disrupted connectivity with posterior memory structures, whereas in healthy ageing the connections between these regions were preserved. In those ageing normally, the inverse association with PCC connectivity with the caudate and insula may suggest cognitive efficiency, the association with frontal regions is in line with the frontal theories of ageing. These findings suggest the episodic memory correlates of PCC connectivity could indicate a clinically relevant biomarker for normal and abnormal ageing.612.6University of Sheffieldhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.589253http://etheses.whiterose.ac.uk/4884/Electronic Thesis or Dissertation |
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612.6 Bruen, Peita D. Differentiating normal and abnormal ageing using a combined functional connectivity and neuropsychological biomarker |
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The impetus of this thesis is to ascertain the extent to which resting state neuroimaging reveals neuropsychologically relevant and clinically salient biomarkers to distinguish normal and abnormal ageing. Section 1. A literature review was undertaken to characterise the neuropsychological correlates of resting state networks in persons with Mild Cognitive Impairment (MCI). The results suggest episodic memory performance decreases as a function of decreased coherence of the spontaneous correlations between medial parietal, temporal and frontal regions of the default mode network and that the posterior cingulate cortex (PCC) may be the most salient biomarker for cognitive decline due to Alzheimer's pathology. The conclusions suggest further work is needed to characterise the relationship between resting state imaging markers and semantic memory and to understand how semantic and episodic memory are mediated by resting state network connectivity in normal ageing. Section 2. Based on the conclusions of the literature review an empirical study was devised to ascertain if clinical and age related variance in semantic and episodic memory is associated with disrupted connectivity of the PCC. The results demonstrated that whilst semantic memory is sensitive and specific to abnormal ageing, episodic memory impairment is more sensitive and specific to PCC connectivity in normal ageing and disease. The correlates of PCC connectivity and episodic memory in MCI were associated with disrupted connectivity with posterior memory structures, whereas in healthy ageing the connections between these regions were preserved. In those ageing normally, the inverse association with PCC connectivity with the caudate and insula may suggest cognitive efficiency, the association with frontal regions is in line with the frontal theories of ageing. These findings suggest the episodic memory correlates of PCC connectivity could indicate a clinically relevant biomarker for normal and abnormal ageing. |
author2 |
Venneri, Annalena |
author_facet |
Venneri, Annalena Bruen, Peita D. |
author |
Bruen, Peita D. |
author_sort |
Bruen, Peita D. |
title |
Differentiating normal and abnormal ageing using a combined functional connectivity and neuropsychological biomarker |
title_short |
Differentiating normal and abnormal ageing using a combined functional connectivity and neuropsychological biomarker |
title_full |
Differentiating normal and abnormal ageing using a combined functional connectivity and neuropsychological biomarker |
title_fullStr |
Differentiating normal and abnormal ageing using a combined functional connectivity and neuropsychological biomarker |
title_full_unstemmed |
Differentiating normal and abnormal ageing using a combined functional connectivity and neuropsychological biomarker |
title_sort |
differentiating normal and abnormal ageing using a combined functional connectivity and neuropsychological biomarker |
publisher |
University of Sheffield |
publishDate |
2013 |
url |
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.589253 |
work_keys_str_mv |
AT bruenpeitad differentiatingnormalandabnormalageingusingacombinedfunctionalconnectivityandneuropsychologicalbiomarker |
_version_ |
1718543600054173696 |