A dataset of multiresolution functional brain parcellations in an elderly population with no or mild cognitive impairment.
|Title||A dataset of multiresolution functional brain parcellations in an elderly population with no or mild cognitive impairment.|
|Publication Type||Journal Article|
|Year of Publication||2016|
|Authors||Tam A, Dansereau C, Badhwar AP, Orban P, Belleville S, Chertkow H, Dagher A, Hanganu A, Monchi O, Rosa-Neto P, Shmuel A, Breitner JCS, Bellec P|
|Corporate Authors||Alzheimer׳s Disease Neuroimaging Initiative|
|Date Published||2016 Dec|
We present group eight resolutions of brain parcellations for clusters generated from resting-state functional magnetic resonance images for 99 cognitively normal elderly persons and 129 patients with mild cognitive impairment, pooled from four independent datasets. This dataset was generated as part of the following study: Common Effects of Amnestic Mild Cognitive Impairment on Resting-State Connectivity Across Four Independent Studies (Tam et al., 2015) . The brain parcellations have been registered to both symmetric and asymmetric MNI brain templates and generated using a method called bootstrap analysis of stable clusters (BASC) (Bellec et al., 2010) . We present two variants of these parcellations. One variant contains bihemisphereic parcels (4, 6, 12, 22, 33, 65, 111, and 208 total parcels across eight resolutions). The second variant contains spatially connected regions of interest (ROIs) that span only one hemisphere (10, 17, 30, 51, 77, 199, and 322 total ROIs across eight resolutions). We also present maps illustrating functional connectivity differences between patients and controls for four regions of interest (striatum, dorsal prefrontal cortex, middle temporal lobe, and medial frontal cortex). The brain parcels and associated statistical maps have been publicly released as 3D volumes, available in .mnc and .nii file formats on figshare and on Neurovault. Finally, the code used to generate this dataset is available on Github.
|Alternate Journal||Data Brief|
|PubMed Central ID||PMC5128734|
|Grant List||U01 AG024904 / AG / NIA NIH HHS / United States|