Rex E. Jung

A Baseline for the Multivariate Comparison of Resting-State Networks

As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease.

Structural brain variation and general intelligence

Total brain volume accounts for about 16% of the variance in general intelligence scores (IQ), but how volumes of specific regions-of-interest (ROIs) relate to IQ is not known. We used voxel-based morphometry (VBM) in two independent samples to identify substantial gray matter (GM) correlates of IQ. Based on statistical conjunction of both samples (N = 47; P < 0.05 corrected for multiple comparisons), more gray matter is associated with higher IQ in discrete Brodmann areas (BA) including frontal (BA 10, 46, 9), temporal (BA 21, 37, 22, 42), parietal (BA 43 and 3), and occipital (BA 19) lobes and near BA 39 for white matter (WM). These results underscore the distributed neural basis of intelligence and suggest a developmental course for volume--IQ relationships in adulthood.

The neuroanatomy of general intelligence: sex matters

We examined the relationship between structural brain variation and general intelligence using voxel-based morphometric analysis of MRI data in men and women with equivalent IQ scores. Compared to men, women show more white matter and fewer gray matter areas related to intelligence. In men IQ/gray matter correlations are strongest in frontal and parietal lobes (BA 8, 9, 39, 40), whereas the strongest correlations in women are in the frontal lobe (BA10) along with Brocas area. Men and women apparently achieve similar IQ results with different brain regions, suggesting that there is no singular underlying neuroanatomical structure to general intelligence and that different types of brain designs may manifest equivalent intellectual performance.

Neuroanatomy of creativity

Creativity has long been a construct of interest to philosophers, psychologists and, more recently, neuroscientists. Recent efforts have focused on cognitive processes likely to be important to the manifestation of novelty and usefulness within a given social context. One such cognitive process – divergent thinking – is the process by which one extrapolates many possible answers to an initial stimulus or target data set. We sought to link well established measures of divergent thinking and creative achievement (Creative Achievement Questionnaire – CAQ) to cortical thickness in a cohort of young (23.7 ± 4.2 years), healthy subjects. Three independent judges ranked the creative products of each subject using the consensual assessment technique (Amabile, 1982) from which a “composite creativity index” (CCI) was derived. Structural magnetic resonance imaging was obtained at 1.5 Tesla Siemens scanner. Cortical reconstruction and volumetric segmentation were performed with the FreeSurfer image analysis suite. A region within the lingual gyrus was negatively correlated with CCI; the right posterior cingulate correlated positively with the CCI. For the CAQ, lower left lateral orbitofrontal volume correlated with higher creative achievement; higher cortical thickness was related to higher scores on the CAQ in the right angular gyrus. This is the first study to link cortical thickness measures to psychometric measures of creativity. The distribution of brain regions, associated with both divergent thinking and creative achievement, suggests that cognitive control of information flow among brain areas may be critical to understanding creative cognition. Hum Brain Mapp, 2010.

Distributed brain sites for the g-factor of intelligence

The general factor of intelligence (g) results from the empirical fact that almost all cognitive tests are positively correlated with one another. Individual tests can be classified according to the degree to which they involve g. Here, regional brain volumes associated with g are investigated by means of structural magnetic resonance imaging and voxel-based morphometry. First, individual differences in the amount of regional gray matter volumes across the entire brain were correlated with eight cognitive tests showing distinguishable g-involvement. Results show that increasing g-involvement of individual tests was associated with increased gray matter volume throughout the brain. Second, it is shown that two prototypical measures of verbal and non-verbal g (i.e., vocabulary and block design) correlate with the amount of regional gray matter across frontal, parietal, temporal, and occipital lobes, suggesting that the general factor of intelligence relates to areas distributed across the brain as opposed to the view that g derives exclusively from the frontal lobes.

Quantitative proton MRS predicts outcome after traumatic brain injury

Objective: To determine whether proton MRS (1H-MRS) neurochemical measurements predict neuropsychological outcome of patients with traumatic brain injury (TBI). Background: Although clinical indices and conventional imaging techniques provide critical information for TBI patient triage and acute care, none accurately predicts individual patient outcome. Methods: The authors studied 14 patients with TBI soon after injury (45 ± 21 days postinjury) and again at 6 months (172 ± 43 days) and 14 age-, sex-, and education-matched control subjects. N-acetylaspartate (NAA), creatine, and choline were measured in normal-appearing occipitoparietal white and gray matter using quantitative 1H-MRS. Outcome was assessed with the Glasgow Outcome Scale (GOS) and a battery of neuropsychological tests. A composite measure of neuropsychological function was calculated from individual test z-scores probing the major functional domains commonly impaired after head trauma. Results: Early NAA concentrations in gray matter predicted overall neuropsychological performance (r = 0.74, p = 0.01) and GOS (F = 11.93, p = 0.007). Other metabolite measures were not related to behavioral function at outcome. Conclusion: 1H-MRS provides a rapid, noninvasive tool to assess the extent of diffuse injury after head trauma, a component of injury that may be the most critical factor in evaluating resultant neuropsychological dysfunction. 1H-MRS can be added to conventional MR examinations with minimal additional time, and may prove useful in assessing injury severity, guiding patient care, and predicting patient outcome.

Metabolic and Cognitive Response to Human Traumatic Brain Injury: A Quantitative Proton Magnetic Resonance Study

Proton magnetic resonance spectroscopy (1H-MRS) offers a unique insight into brain cellular metabolism following traumatic brain injury (TBI). The aim of the present study was to assess change in neurometabolite markers of brain injury during the recovery period following TBI. We studied 19 TBI patients at 1.5, 3, and 6 months postinjury and 28 controls. We used 1H-MRS to quantify N-acetylaspartate (NAA), creatine (Cre), choline (Cho), and myoinositol (mIns) in occipitoparietal gray matter (GM) and white matter (WM) remote from the primary injury focus. Neuropsychological testing quantified cognitive impairment and recovery. At 1.5 months, we found cognitive impairment (mean z score = -1.36 vs. 0.18,p < 0.01), lower NAA (GM: 12.42 mM vs. 13.03, p = 0.01; WM: 11.75 vs. 12.81, p < 0.01), and elevated Cho (GM: 1.51 vs. 1.25, p < 0.01; WM: 1.98 vs. 1.79, p < 0.01) in TBI patients compared with controls. GM NAA at 1.5 months predicted cognitive function at outcome (6 months postinjury; r = 0.63, p = 0.04). GM NAA continued to fall by 0.46 mM between 1.5 and 3 months (p = 0.02) indicating continuing neuronal loss, metabolic dysfunction, or both. Between 3 and 6 months, WM NAA increased by 0.55 mM (p = 0.06) suggesting metabolic recovery. Patients with poorer outcomes had elevated mean GM Cho at 3 months postinjury, suggesting active inflammation, as compared to patients with better outcomes (p = 0.002). 1H-MRS offers a noninvasive approach to assessing neuronal injury and inflammation following TBI, and may provide unique data for patient management and assessment of therapeutic efficacy.

Use of tissue water as a concentration reference for proton spectroscopic imaging

A strategy for using tissue water as a concentration standard in 1H magnetic resonance spectroscopic imaging studies on the brain is presented, and the potential errors that may arise when the method is used are examined. The sensitivity of the method to errors in estimates of the different water compartment relaxation times is shown to be small at short echo times (TEs). Using data from healthy human subjects, it is shown that different image segmentation approaches that are commonly used to account for partial volume effects (SPM2, FSLs FAST, and K‐means) lead to different estimates of metabolite levels, particularly in gray matter (GM), owing primarily to variability in the estimates of the cerebrospinal fluid (CSF) fraction. While consistency does not necessarily validate a method, a multispectral segmentation approach using FAST yielded the lowest intersubject variability in the estimates of GM metabolites. The mean GM and white matter (WM) levels of N‐acetyl groups (NAc, primarily N‐acetylaspartate), choline (Ch), and creatine (Cr) obtained in these subjects using the described method with FAST multispectral segmentation are reported: GM [NAc] = 17.16 ± 1.19 mM; WM [NAc] = 14.26 ± 1.38 mM; GM [Ch] = 3.27 ± 0.47 mM; WM [Ch] = 2.65 ± 0.25 mM; GM [Cr] = 13.98 ± 1.20 mM; and WM [Cr] = 7.10 ± 0.67 mM. Magn Reson Med, 2006.

Neuroimaging creativity: A psychometric view

Many studies of creative cognition with a neuroimaging component now exist; what do they say about where and how creativity arises in the brain? We reviewed 45 brain-imaging studies of creative cognition. We found little clear evidence of overlap in their results. Nearly as many different tests were used as there were studies; this test diversity makes it impossible to interpret the different findings across studies with any confidence. Our conclusion is that creativity research would benefit from psychometrically informed revision, and the addition of neuroimaging methods designed to provide greater spatial localization of function. Without such revision in the behavioral measures and study designs, it is hard to see the benefit of imaging. We set out eight suggestions in a manifesto for taking creativity research forward.

The structure of creative cognition in the human brain

Creativity is a vast construct, seemingly intractable to scientific inquiry—perhaps due to the vague concepts applied to the field of research. One attempt to limit the purview of creative cognition formulates the construct in terms of evolutionary constraints, namely that of blind variation and selective retention (BVSR). Behaviorally, one can limit the “blind variation” component to idea generation tests as manifested by measures of divergent thinking. The “selective retention” component can be represented by measures of convergent thinking, as represented by measures of remote associates. We summarize results from measures of creative cognition, correlated with structural neuroimaging measures including structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (1H-MRS). We also review lesion studies, considered to be the “gold standard” of brain-behavioral studies. What emerges is a picture consistent with theories of disinhibitory brain features subserving creative cognition, as described previously (Martindale, 1981). We provide a perspective, involving aspects of the default mode network (DMN), which might provide a “first approximation” regarding how creative cognition might map on to the human brain.