Multivariate Associations of Fluid Intelligence and NAA

Ask your doctor what testing they have done to make sure this wasn't damaged in the stroke and the protocols necessary to recover fluid intelligence.
http://cercor.oxfordjournals.org/content/early/2016/03/18/cercor.bhw070.abstract?

1. Aki Nikolaidis1,2,
2. Pauline L. Baniqued1,3,4,
3. Michael B. Kranz1,3,
4. Claire J. Scavuzzo2,5,
5. Aron K. Barbey1,
6. Arthur F. Kramer1,2,3 and
7. Ryan J. Larsen1

+ Author Affiliations

1. ¹Beckman Institute for Advanced Science and Technology
2. ²Neuroscience Program and
3. ³Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA
4. ⁴Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
5. ⁵Psychology Department, University of Alberta, Edmonton, Alberta, Canada

1. Address correspondence to Aki Nikolaidis. Email: g.aki.nikolaidis@gmail.com

Abstract

Understanding the neural and metabolic correlates of fluid intelligence not only aids scientists in characterizing cognitive processes involved in intelligence, but it also offers insight into intervention methods to improve fluid intelligence. Here we use magnetic resonance spectroscopic imaging (MRSI) to measure N-acetyl aspartate (NAA), a biochemical marker of neural energy production and efficiency. We use principal components analysis (PCA) to examine how the distribution of NAA in the frontal and parietal lobes relates to fluid intelligence. We find that a left lateralized frontal-parietal component predicts fluid intelligence, and it does so independently of brain size, another significant predictor of fluid intelligence. These results suggest that the left motor regions play a key role in the visualization and planning necessary for spatial cognition and reasoning, and we discuss these findings in the context of the Parieto-Frontal Integration Theory of intelligence.

Peri Infarct N-Acetylaspartic Acid Predicts White Matter Atrophy After Ischemic Stroke

Finally someone thinking about objectively measuring white matter damage. What does your doctor think of that?
http://stroke.ahajournals.org/content/45/Suppl_1/ATP73.short

1. Nawaf Yassi1;
2. Andrew Bivard1;
3. Bruce C Campbell1;
4. Mark W Parsons2;
5. Geoffrey A Donnan3;
6. Patricia M Desmond4;
7. Stephen M Davis1

+ Author Affiliations

1. ¹Melbourne Brain Cntr, Univ of Melbourne, Parkville, Australia
2. ²Priority Rsch Cntr for Translational Neuroscience and Mental Health, Univ of Newcastle, Newcastle, Australia
3. ³Univ of Melbourne, Parkville, Australia
4. ⁴Dept of Radiology, Univ of Melbourne, Parkville, Australia

Abstract

Objective: Cerebral volume changes post stroke have recently been described and may correlate with clinical outcome. We aimed to determine whether peri infarct measurement of the neuronal marker N-Acetylaspartic acid (NAA) on Magnetic Resonance Spectroscopy (MRS) predicts progressive cerebral volume change after stroke.

Methods: 11 patients (7 male) with supratentorial ischemic stroke underwent serial MRI within 1 week of onset, and at 1 and 3 months. Imaging was performed on a 3T Siemens Trio scanner. Structural imaging utilized a T1-weighted axial MPRAGE acquisition (1mm slices, TR1.9sec, TE2.82msec). NAA estimation was performed at the baseline scan using single voxel MRS (TE30msec, 3x3x3cm voxels). The voxel was placed in the peri infarct region as determined by assessment of the diffusion weighted image. Quantitative MRS analysis was performed using LCmodel using water referencing. Brain tissue volume, normalized for subject head size, was estimated with SIENAX, part of FSL. Due to anticipated effects of edema on initial cerebral volume, changes in grey, white and total brain volume were assessed as percentage change between the 1 and 3 month scans.

Results: Mean age was 71yr (IQR 62-79yr). Median baseline NIHSS was 11 (IQR 6-14). Mean baseline grey, white and total brain volume were 713ml (IQR 683-749), 731mL (IQR 721-747) and 1444mL (IQR 1384-1503) respectively. There was a significant correlation between age and baseline grey matter volume (r2=0.73, p=0.001) and total brain volume (r2=0.74, p=0.001). Mean peri infarct NAA concentration was 6.2mM (SD 1.3) compared with 7.0mM (SD 1.2) in the contralateral hemisphere (p=0.09, paired t-test). Mean percentage grey, white and total brain volume changes were 1.2% (IQR -1.8-4.1), 0.4% (IQR -2.2-3.7) and 0.8% (IRQ -1.0-2.6) respectively. There was a significant correlation between baseline NAA in the peri infarct region and change in white matter volume between the 1 and 3 month time points (r2=0.26, p=0.008).

Conclusions: Estimation of the neuronal marker NAA using MRS may signify varying degrees of neuronal damage after stroke which may correlate with the severity of axonal degeneration and subsequent white matter volume changes. Further validation and correlation with clinical outcomes is required.