The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry

Nooner, Kate B.; Colcombe, Stanley J.; Tobe, Russell H.; Mennes, Maarten; Benedict, Melissa M.; Moreno, Alexis L.; Panek, Laura J.; Brown, Shaquanna; Zavitz, Stephen T.; Li, Qingyang; Sikka, Sharad; Gutman, David; Bangaru, Saroja; Schlachter, Rochelle Tziona; Kamiel, Stephanie M.; Anwar, Ayesha; Hinz, Caitlin M.; Kaplan, Michelle S.; Rachlin, Anna B.; Adelsberg, Samantha; Cheung, Brian; Khanuja, Ranjit; Chen, Yan; Craddock, R. Cameron; Calhoun, Vincent; Courtney, William; King, Margaret D.; Wood, Dylan; Cox, Christine L.; Kelly, Clare; Martino, Adriana Di; Petkova, Eva; Reiss, Philip T.; Duan, Nancy; Thomsen, Dawn; Biswal, Bharat B.; Coffey, Barbara J.; Hoptman, Matthew J.; Javitt, Daniel C.; Pomara, Nunzio; Sidtis, John J.; Koplewicz, Harold S.; Castellanos, F. Xavier; Leventhal, Bennett L.; Milham, Michael P.

doi:10.3389/fnins.2012.00152

Cited by 673 publications

(593 citation statements)

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“…All the subject data used for the current study were obtained from the open-sharing data repository Enhanced Nathan Kline Institute-Rockland (NKI) Sample (Nooner et al, 2012). For this study, we used resting-state data scanned at TR = 645 msec.…”

Section: Subjectsmentioning

confidence: 99%

Functional Integration Between Brain Regions at Rest Occurs in Multiple-Frequency Bands

2015

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Studies of resting-state fMRI have shown that blood oxygen level dependent (BOLD) signals giving rise to temporal correlation across voxels (or regions) are dominated by low-frequency fluctuations in the range of *0.01-0.1 Hz. These low-frequency fluctuations have been further divided into multiple distinct frequency bands (slow-5 and -4) based on earlier neurophysiological studies, though low sampling frequency of fMRI (*0.5 Hz) has substantially limited the exploration of other known frequency bands of neurophysiological origins (slow-3, -2, and -1). In this study, we used resting-state fMRI data acquired from 21 healthy subjects at a higher sampling frequency of 1.5 Hz to assess the presence of resting-state functional connectivity (RSFC) across multiple frequency bands: slow-5 to slow-1. The effect of different frequency bands on spatial extent and connectivity strength for known resting-state networks (RSNs) was also evaluated. RSNs were derived using independent component analysis and seed-based correlation. Commonly known RSNs, such as the default mode, the fronto-parietal, the dorsal attention, and the visual networks, were consistently observed at multiple frequency bands. Significant inter-hemispheric connectivity was observed between each seed and its contra lateral brain region across all frequency bands, though overall spatial extent of seed-based correlation maps decreased in slow-2 and slow-1 frequency bands. These results suggest that functional integration between brain regions at rest occurs over multiple frequency bands and RSFC is a multiband phenomenon. These results also suggest that further investigation of BOLD signal in multiple frequency bands for related cognitive processes should be undertaken.

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Section: Subjectsmentioning

confidence: 99%

Functional Integration Between Brain Regions at Rest Occurs in Multiple-Frequency Bands

2015

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“…We used the cross-sectional dataset (39) and only included the subset of healthy subjects. The NKI data (40) have been obtained from the NKI Rockland Sample. The ADNI data have been obtained from the ADNI.…”

Section: Methodsmentioning

confidence: 99%

Universality in human cortical folding in health and disease

Wang

Necus

Kaiser

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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The folding of the cortex in mammalian brains across species has recently been shown to follow a universal scaling law that can be derived from a simple physics model. However, it was yet to be determined whether this law also applies to the morphological diversity of different individuals in a single species, in particular with respect to factors, such as age, sex, and disease. To this end, we derived and investigated the cortical morphology from magnetic resonance images (MRIs) of over 1,000 healthy human subjects from three independent public databases. Our results show that all three MRI datasets follow the scaling law obtained from the comparative neuroanatomical data, which strengthens the case for the existence of a common mechanism for cortical folding. Additionally, for comparable age groups, both male and female brains scale in exactly the same way, despite systematic differences in size and folding. Furthermore, age introduces a systematic shift in the offset of the scaling law. In the model, this shift can be interpreted as changes in the mechanical forces acting on the cortex. We also applied this analysis to a dataset derived from comparable cohorts of Alzheimer's disease patients and healthy subjects of similar age. We show a systematically lower offset and a possible change in the exponent for Alzheimer's disease subjects compared with the control cohort. Finally, we discuss implications of the changes in offset and exponent in the data and relate it to existing literature. We, thus, provide a possible mechanistic link between previously independent observations. brain morphogenesis | cortical gyrification | folding | aging | Alzheimer's disease T he expansion of the cerebral cortex is the most obvious feature of mammalian brain evolution and generally accompanied by increasing degrees of folding of the cortical surface. The mechanisms that drive gyrification have been a matter of intense research interest lately (1-4), with a number of proposals being put forward to explain it. Most such studies have focused on human cortices, using detailed MRI data to postulate folding as driven by the [possibly differential (5) or multilayered (6)] expansion of the cortical surface. In contrast, we have recently proposed a model (7), in which folding is a consequence of the dynamics of surface expansion and self-avoidance coupled with a negative tension term. This model was partly inspired by the axonal tension hypothesis by Van Essen (8) and the statistical physics of membranes (9). By assuming that healthy adult mammalian cortices have a shape that minimizes an effective free energy term that takes into account these effects, this model predicts a power law relation between cortical average thickness T, exposed area A e , and total area A t , namely[1]The only free parameter is k, or offset, a dimensionless coefficient that is presumed to be related to both the axonal tension and the pressure of cerebral spinal fluid (CSF) (supplemental text in ref. 7). In geometric terms, the variables T, A t , and A e ass...

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“…Methods II.1. Subjects Structural brain behavior correlations were based on data acquired at the Research Centre Jülich (FZJ), Germany, and at the Nathan S. Klein Institute (NKI), New York, USA (Nooner et al 2012). …”

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confidence: 99%

Searching for behavior relating to grey matter volume in a-priori defined right dorsal premotor regions: Lessons learned

et al. 2017

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(max 250 words)Recently, we showed that the functional heterogeneity of the right dorsal premotor (PMd) cortex could be better understood by dividing it into five subregions that showed different behavioral associations according to task-based activations studies. The present study investigated whether the revealed behavioral profile could be corroborated and complemented by a structural brain behavior correlation approach in two healthy adults cohorts.Grey matter volume within the five volumes of interest (VOI-GM) was computed using voxelbased morphometry. Associations between the inter-individual differences in VOI-GM and performance across a range of neuropsychological tests were assessed in the two cohorts with and without correction for demographical variables. Additional analyses were performed in random smaller subsamples drawn from each of the two cohorts.In both cohorts, correlation coefficients were low; only few were significant and a considerable number of correlations were counterintuitive in their directions (i.e., higher performance related to lower GMV). Furthermore, correlation patterns were inconsistent between the two cohorts.Subsampling revealed that correlation patterns could vary widely across small samples and that negative correlations were as likely as positive correlations.Thus, the structural brain/behavior approach did not corroborate the functional profiles of the PMd subregions inferred from activation studies, suggesting that local recruitment by fMRI studies does not necessarily imply covariance of local structure with behavioral performance in healthy adults.We discuss the limitations of such studies and related recommendations for future studies.

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The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry

Cited by 673 publications

References 73 publications

Functional Integration Between Brain Regions at Rest Occurs in Multiple-Frequency Bands

Functional Integration Between Brain Regions at Rest Occurs in Multiple-Frequency Bands

Universality in human cortical folding in health and disease

Searching for behavior relating to grey matter volume in a-priori defined right dorsal premotor regions: Lessons learned

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