White matter matters: Changes in white matter tracts due to reading intervention

More research supporting “white matter matters”.




Rapid and widespread white matter plasticity during an intensive reading intervention

Nature Communications

Elizabeth Huber, Patrick M. Donnelly, Ariel Rokem & Jason D. Yeatman

ABSTRACT

White matter tissue properties are known to correlate with performance across domains ranging from reading to math, to executive function. Here, we use a longitudinal intervention design to examine experience-dependent growth in reading skills and white matter in grade school-aged, struggling readers. Diffusion MRI data were collected at regular intervals during an 8-week, intensive reading intervention. These measurements reveal large-scale changes throughout a collection of white matter tracts, in concert with growth in reading skill. Additionally, we identify tracts whose properties predict reading skill but remain fixed throughout the intervention, suggesting that some anatomical properties stably predict the ease with which a child learns to read, while others dynamically reflect the effects of experience. These results underscore the importance of considering recent experience when interpreting cross-sectional anatomy–behavior correlations. Widespread changes throughout the white matter may be a hallmark of rapid plasticity associated with an intensive learning experience.

Very interesting. The arcuate fasciculus tracts have also been implicated in higher order thinking (Gf) such as in the P-FIT model of intelligence. Also see white paper that implicates the AF in temporal processing “brain clock” timing interventions




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Higher intelligence related to more efficiently organized brains-bigger/larger not always better

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Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence. Article link.

Erhan Genç, Christoph Fraenz, Caroline Schlüter, Patrick Friedrich, Rüdiger Hossiep, Manuel C. Voelkle, Josef M. Ling, Onur Güntürkün, & Rex E. Jung

Abstract

Previous research has demonstrated that individuals with higher intelligence are more likely to have larger gray matter volume in brain areas predominantly located in parieto-frontal regions. These findings were usually interpreted to mean that individuals with more cortical brain volume possess more neurons and thus exhibit more computational capacity during reasoning. In addition, neuroimaging studies have shown that intelligent individuals, despite their larger brains, tend to exhibit lower rates of brain activity during reasoning. However, the microstructural architecture underlying both observations remains unclear. By combining advanced multi-shell diffusion tensor imaging with a culture-fair matrix-reasoning test, we found that higher intelligence in healthy individuals is related to lower values of dendritic density and arborization. These results suggest that the neuronal circuitry associated with higher intelligence is organized in a sparse and efficient manner, fostering more directed information processing and less cortical activity during reasoning.

From discussion

Taken together, the results of the present study contribute to our understanding of human intelligence differences in two ways. First, our findings confirm an important observation from previous research, namely, that bigger brains with a higher number of neurons are associated with higher intelligence. Second, we demonstrate that higher intelligence is associated with cortical mantles with sparsely and well-organized dendritic arbor, thereby increasing processing speed and network efficiency. Importantly, the findings obtained from our experimental sample were confirmed by the analysis of an independent validation sample from the Human Connectome Project25



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The importance of differential psychology for school learning: 90% of school achievement variance is due to student characteristics

This is why the study of individual differences/differential psychology is so important. If you don’t want to read the article you can watch a video of Dr. Detterman where he summarizes his thinking and this paper.

Education and Intelligence: Pity the Poor Teacher because Student Characteristics are more Significant than Teachers or Schools. Article link.

Douglas K. Detterman

Case Western Reserve University (USA)

Abstract

Education has not changed from the beginning of recorded history. The problem is that focus has been on schools and teachers and not students. Here is a simple thought experiment with two conditions: 1) 50 teachers are assigned by their teaching quality to randomly composed classes of 20 students, 2) 50 classes of 20 each are composed by selecting the most able students to fill each class in order and teachers are assigned randomly to classes. In condition 1, teaching ability of each teacher and in condition 2, mean ability level of students in each class is correlated with average gain over the course of instruction. Educational gain will be best predicted by student abilities (up to r = 0.95) and much less by teachers' skill (up to r = 0.32). I argue that seemingly immutable education will not change until we fully understand students and particularly human intelligence. Over the last 50 years in developed countries, evidence has accumulated that only about 10% of school achievement can be attributed to schools and teachers while the remaining 90% is due to characteristics associated with students. Teachers account for from 1% to 7% of total variance at every level of education. For students, intelligence accounts for much of the 90% of variance associated with learning gains. This evidence is reviewed


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Research Byte: Is General Intelligence Little More Than the Speed of Higher-Order Processing?

Although a small sample, this is still and interesting study. The results are consistent with the continued nexus of the g, Gf, Gwm, attentional control and speed of higher order processing (especially P300 in ERP’s), white matter tract integrity and the PFIT model of intelligence as well as the recent process overlap theory (POT) of g.

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Article link.

Anna-Lena Schubert, Dirk Hagemann, and Gidon T. Frischkorn Heidelberg University

ABSTRACT

Individual differences in the speed of information processing have been hypothesized to give rise to individual differences in general intelligence. Consistent with this hypothesis, reaction times (RTs) and latencies of event-related potential have been shown to be moderately associated with intelligence. These associations have been explained either in terms of individual differences in some brain-wide property such as myelination, the speed of neural oscillations, or white-matter tract integrity, or in terms of individual differences in specific processes such as the signal-to-noise ratio in evidence accumulation, executive control, or the cholinergic system. Here we show in a sample of 122 participants, who completed a battery of RT tasks at 2 laboratory sessions while an EEG was recorded, that more intelligent individuals have a higher speed of higher-order information processing that explains about 80% of the variance in general intelligence. Our results do not support the notion that individuals with higher levels of general intelligence show advantages in some brain-wide property. Instead, they suggest that more intelligent individuals benefit from a more efficient transmission of information from frontal attention and working memory processes to temporal-parietal processes of memory storage.

Keywords: ERP latencies, event-related potentials, intelligence, processing speed, reaction times



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More support for P-FIT model of intelligence

Abstract

The authors describe the brain regions involved in the process of intelligence using as a basis, the models of the theory of frontoparietal integration (P-FIT Model). They also correlate the model described with functional areas of Brodmann, integrating them into the tertiary brain areas and address the subcortical structures involved in cognitive processes, including the memory. The studies performed by functional magnetic resonance, also unmask various regions related with intelligence, neither previously described by Brodmann nor even in conventional models of learning. The anterior insular cortex presents itself as the most recent tertiary area to be considered. Subcortical structures, when injured, mimick injuries to the cerebral cortex, demonstrating their great participation in cognition. The topographies of aphasia and the functioning mechanisms of the bearers of learning disorders, including dyslexic, dysgraphia and dyscalculic should be reconsidered. A better understanding of this topographic anatomy may clarify the mechanisms used in those individuals with cerebral lesions.

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Research Byte: Multivariate Associations of Fluid Intelligence (Gf) and NAA - Is the P-FIT it?

When it rains--it pours.  Second posting today of research study reinforcing the importance of the P-FIT neuro-model of intelligence.

In a prior Interactive Metronome-Home blog post I provide an overview description of the P-FIT model.

 

Multivariate Associations of Fluid Intelligence and NAA

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.

Working memory training (dual n-back) study suggests improvement in white matter tract integrity: White matter matters

White matter matters.  Yes, my readers may be tiring of this common mantra. 

But, another new study has again implicated the importance of white matter integrity.  More importantly, the study suggests that a working memory training program (dual n-back) may be effective in increasing white matter integrity, thus increasing the efficiency and synchronization of communication between different brain networks.  Click on the images below to enlarge.

 

This study is consistent with my hypothesis that the effectiveness of some brain training programs may be due to increased white matter tract integrity.  An explanation, with a link to a MindHub pub white paper outlining this hypothesis, can be found here.  Other white matter related posts can be found here.