Default Mode Network Disruption Secondary to a Lesion in the Anterior Thalamus

Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.
Archives of neurology (Impact Factor: 7.42). 10/2010; 68(2):242-7. DOI: 10.1001/archneurol.2010.259
Source: PubMed


To describe the neuroanatomical correlations of an isolated lesion in the anterior thalamus using functional imaging in a 40-year-old man with multiple sclerosis.
Case report with 10 cognitively normal controls.
Mayo Clinic, Rochester, Minnesota.
A 40-year-old man with a 2-week course of acute-onset amnesia, abulia, poor concentration, hypersomnolence, and reclusiveness.
Functional magnetic resonance imaging.
Magnetic resonance imaging demonstrated a large gadolinium-enhancing plaque in the left anterior thalamus and other demyelinating plaques in the subcortical and periventricular white matter, consistent with the diagnosis of multiple sclerosis. His symptoms persisted at the 7-month follow-up. The patient's resting state functional magnetic resonance image demonstrated an asymmetric disruption of the posterior cingulate portion of the default mode network ipsilateral to the left thalamic lesion.
A large multiple sclerosis plaque in the deep gray matter altered the resting state functional connectivity in a patient presenting with pure cognitive dysfunction. Such altered connectivity may underlie cognitive symptoms in neurologic disease. In addition, this case provides lesional evidence of default mode network circuitry involving the pathways of the circuit of Papez.

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    • "Evidence for the impact of a single typical MS lesion on FC changes has been reported by Jones et al. (2011). In a case study based on a 40-year-old male presenting with a gadolinium-enhancing lesion at the anterior thalamus, rsfMRI revealed alterations in DMN circuitry that was attributed to this lesion, while FC in the posterior cingulate cortex (PCC), precuneus and the left inferior parietal lobe was reduced compared to healthy controls (Jones et al. 2011). "
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    ABSTRACT: Multiple sclerosis (MS), a variable and diffuse disease affecting white and gray matter, is known to cause functional connectivity anomalies in patients. However, related studies published to-date are post hoc; our hypothesis was that such alterations could discriminate between patients and healthy controls in a predictive setting, laying the groundwork for imaging-based prognosis. Using functional magnetic resonance imaging resting state data of 22 minimally disabled MS patients and 14 controls, we developed a predictive model of connectivity alterations in MS: a whole-brain connectivity matrix was built for each subject from the slow oscillations (<0.11 Hz) of region-averaged time series, and a pattern recognition technique was used to learn a discriminant function indicating which particular functional connections are most affected by disease. Classification performance using strict cross-validation yielded a sensitivity of 82% (above chance at p<0.005) and specificity of 86% (p<0.01) to distinguish between MS patients and controls. The most discriminative connectivity changes were found in subcortical and temporal regions, and contralateral connections were more discriminative than ipsilateral connections. The pattern of decreased discriminative connections can be summarized post hoc in an index that correlates positively (ρ=0.61) with white matter lesion load, possibly indicating functional reorganisation to cope with increasing lesion load. These results are consistent with a subtle but widespread impact of lesions in white matter and in gray matter structures serving as high-level integrative hubs. These findings suggest that predictive models of resting state fMRI can reveal specific anomalies due to MS with high sensitivity and specificity, potentially leading to new non-invasive markers.
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