White matter matters—-Gf and white matter connectivity

A neuromarker of individual general fluid intelligence from the white-matter functional connectome.  Link.

Jiao Li1, Bharat B. Biswal, Yao Meng, Siqi Yang, Xujun Duan, Qian Cui, Huafu Chen, and Wei Liao

Abstract

Neuroimaging studies have uncovered the neural roots of individual differences in human general fluid intelligence (Gf). Gf is characterized by the function of specific neural circuits in brain gray-matter; however, the association between Gf and neural function in brain white-matter (WM) remains unclear. Given reliable detection of blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD-fMRI) signals in WM, we used a functional, rather than an anatomical, neuromarker in WM to identify individual Gf. We collected longitudinal BOLD-fMRI data (in total three times, ~11 months between time 1 and time 2, and ~29 months between time 1 and time 3) in normal volunteers at rest, and identified WM functional connectomes that predicted the individual Gf at time 1 (n = 326). From internal validation analyses, we demonstrated that the constructed predictive model at time 1 predicted an individual's Gf from WM functional connectomes at time 2 (time 1 ∩ time 2: n = 105) and further at time 3 (time 1 ∩ time 3: n = 83). From external validation analyses, we demonstrated that the predictive model from time 1 was generalized to unseen individuals from another center (n = 53). From anatomical aspects, WM functional connectivity showing high predictive power predominantly included the superior longitudinal fasciculus system, deep frontal WM, and ventral frontoparietal tracts. These results thus demonstrated that WM functional connectomes offer a novel applicable neuromarker of Gf and supplement the gray-matter connectomes to explore brain–behavior relationships.

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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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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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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.

Research Byte: Strong working memory (WM)--fluid intelligence (Gf) relationship not due to time allowed on both sets of tasks

Very good article that does not support Chuderski's research that had suggested a relationship between time on task (not the same as cognitive processing speed-Gs) and fluid reasoning or working memory. The current study reinforces the very high (but not 1.0) effect size from working memory to Gf. However, how much time an individual (at least for young adults) spends on working memory or fluid tasks does not explain the strong WM--Gf relation. Generalization to children and the elderly cannot be made without further research.

What I find particularly interesting is the authors hypothesis that one possible general mechanism explanation for the WM-->Gf link is temporal based processing of information. This is consistent with the temporal power resolution hypotheses (or temporal g) of Rammsayer and colleagues and a large body of research I have reported at the Brain Clock blog. If you visit that link, pay particular attention to the MindHub Pub2 that presents a three-level hypothesized model for understanding the IM effect. Note that at the lowest neurocognitive and biological level of intelligence research, I have hypothesized that temporal g (and not Jensen's reaction time g) may be one of the key domain-general mechanisms driving critical cognitive abilities, especially working memory and fluid intelligence.

As per the recent four-level reductionistic framework (see brief 10 minute video explanation) I have offered to organize intelligence related research (adapted from Earl Hunt's work), the current study links research at the psychometric, information processing, and neurocognitive and biological (neural efficiency) levels.

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Working memory training (n-back task) improves fluid intelligence (Gf) 3-4 IQ points

Interesting meta-analysis suggestingthat working memory training, via the n-back task, over a relatively short period of time, can improve fluid intelligence/reasoning (Gf). Conservative estimate of 3-4 Gf IQ points improvement. Click on images to enlarge.









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White matter matters: Brain synchronization via the brain's communication subway system

White matter, in contrast to the grey squiggly mass (the cerebrum) that most people associate with the human brain, was for many years the research step-child to the cerebrum. That is no more. White matter, which has been called the brain's subway, super information system, or interstate highway communication system, now has a glass slipper. Research during the past decade has implicated white matter as performing the critical task of connecting and synchronizing different brain regions or networks so they can perform a wide variety of complex human cognitive or motor behaviors. The white matter system is considered the communication backbone system for the flow of information in the brain. Of particular interest (to me) is the parietal-frontal network, which is implicated as central to abstract human intelligence, fluid intelligence (Gf), working memory and attentional control (see prior posts re: the P-FIT model).

In a MindHub white paper I hypothesized that increasing white matter tract integrity may be a key mechanism behind the efficacy of the Interactive Metronome neuro-timing intervention (see figure below). I have gone as far as suggesting that the efficacy of many brain training/fitness programs may stem from a common domain-general effect--improving communication between and within various brain network(s) via more efficient white matter tract speed and communication. [Click on image to enlarge]

White matter integrity or dysfunction as been implicated in a wide variety of cognitive disorders or abilities, including cognitive control, math and intellectual giftedness, fluid intelligence or reasoning, processing speed, reading, decrease in cognitive functioning, meditation, working memory, vascular cognitive impairment, ADHD, autism, and cognitve and language maturation in infants. A sampling of recent white matter research article abstracts I have accumulated can be found by clicking here.
White matter matters!

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Fluid reasoning (Gf) influenced by processing speed (Gs) via white matter tract organization/integriety

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Interesting study that gets at the previously demonstrated causal relation between processing speed (Gs) and fluid reasoning (Gf), with the causal mechanism suggested to be white matter tract organization/integrity. I find this study interesting as it is consistent with a white paper I have writtten that implicates white matter integrity and cognitive functioninng (g an Gf). It is my working hypothesis that those brain training programs that demonstrate effectivness may be modifying underlying white matter tract integrity....and thus better brain network communication....especially the executive control and salience networks involved in the attentional control system, and thus working memory capacity. Remember...this is a "working paper"....it can be downloaded here.

 

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Brain anatomy and processing speed (Gs) index for predicting reading

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Research bytes: Two new brain fitness/training studies in the elderly

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The brain clock and IQ: Another supporting article

I've blogged extensively on the intriguing relation between the hypothesized internal brain clock and intelligence. I've found the research supporting the notion of a temporal g (temporal general intelligence mechanism) particularly intriguing.

There is a new article "in press" in the journal Intelligence that adds support to the hypothesis that temporal processing may be more related to general intelligence than the "holy grail" research that attempts to explain g via reaction time (RT). The focus of the article is an attempt to identify the underlying mechanisms that explain the relation between general intelligence and temporal processing (in this case, the authors used a isochronous serial interval production task as the measure of temporal processing). The article is rather technical, so I'll cut to the bottom line take-away messages.

The authors argue that their findings support a bottom-up (BU) explanation of temporal processing, in contrast to the alternative top-down (TD) explanation. The supported BU explanation suggests that the aspect of temporal processing related to general intelligence is grounded in certain basic neural properties that influence temporal variability in neural activity. The alternative TD hypothesis suggests that some form of higher-order component of the neural system (e.g., the construct of attention) is responsible for the link. The authors suggest that the support for the BU hypothesis, and not the TD hypothesis, supports a biological underpinning for intelligence and, more importantly, the hypothesis that temporal accuracy of neural activity has a causal effect on the neural processes that are involved in cognition (intelligence).

Also of interest was the authors suggestion that this basic underlying mechanism (of the brain clock?) is the result of a network of brain regions (sensorimotor cortx, supplementary and pre-supplementary motor areas, later premotor areas of the frontal lobe, auditory regions in the superious temporal gyrus, the basal ganglia and cerebellum). The efficient networked interaction of many of these brain regions have been implicated in other research discussed at this blog.

Of course, the small sample (n=36) and the reliance on a single psychometric measure (Raven's matrix test) of fluid intelligence (Gf) to define intelligence are significant limitations that argue for caution and the need for replication in larger samples and a broader array of indicators of the construct of intelligence. Click here for a prior discussion of my concerns for the reliance on the Raven's Gf test.

Madison, G., Forsman, L., Blom, O., Karabanov, A & Ullén, F. (2009) Correlations between intelligence and components of serial timing variability. Intelligence,37, 68–75 (click to view)

• Abstract: Psychometric intelligence correlates with reaction time in elementary cognitive tasks, as well as with performance in time discrimination and judgment tasks. It has remained unclear, however, to what extent these correlations are due to top–down mechanisms, such as attention, and bottom–up mechanisms, i.e. basic neural properties that in?uence both temporal accuracy and cognitive processes. Here, we assessed correlations between intelligence (Raven SPM Plus) and performance in isochronous serial interval production, a simple, automatic timing task where participants ?rst make movements in synchrony with an isochronous sequence of sounds and then continue with self-paced production to produce a sequence of intervals with the same inter-onset interval (IOI). The target IOI varied across trials. A number of different measures of timing variability were considered, all negatively correlated with intelligence. Across all stimulus IOIs, local interval-to-interval variability correlated more strongly with intelligence than drift, i.e. gradual changes in response IOI. The strongest correlations with intelligence were found for IOIs between 400 and 900 ms, rather than above 1 s, which is typically considered a lower limit for cognitive timing. Furthermore, poor trials, i.e. trials arguably most affected by lapses in attention, did not predict intelligence better than the most accurate trials. We discuss these results in relation to the human timing literature, and argue that they support a bottom–up model of the relation between temporal variability of neural activity and intelligence.
  

Technorati Tags: psychology, educational psychology, school psychology, neuropsychology, neuroscience, cognition, intelligence, g, general intelligence, brain clock, mental time keeping, temporal processing, temporal g

Executive function training - does it transfer?

My recent FYI post regarding reported transfer effects (to Gf) from working memory training tasks generated a number of posted comments (go to link and see original post plus comments). Today Developing Intelligence has a nice critique of another study dealing with potential transfer (or lack thereof) from training on an executive function "updating" task and possible neurological changes based on neuroimaging data.

Technorati Tags: psychology, educational psychology, school psychology, neuropsychology, neuroscience, executive function, working memory, fMRI

Working memory training improves fluid intelligence: New research

Training working memory can increase fluid intelligence (Gf). Wow.

I've had a number of people forward the following abstract to me. After reading the article I now see why. This article, in the prestigious Proceedings of the National Academy of Sciences (PNAS), reports that a working memory training intervention produced positive transfer effects in fluid intelligence (Gf). This is a very important finding. Cognitive ability training research suffers from a paucity of studies that demonstrate positive transfer to other tasks/domains that differ from the training medium. This study also adds additional strong evidence to the link between working memory and Gf.

These findings are particularly important regarding the hypothesis that brain clock intervention training programs (e.g., Interactive Metronome) may be producing positive outcomes via an improvement in the domain-general cognitive mechanism's of working memory and executive functions. I've previously written about this hypothesis at this blog (click here).

Cool stuff. A must read. Much has been written about the link between working memory and Gf. Here are some prior related posts touching on the topics of working memory and Gf.

Jaeggi, S., Buschkuehl, M., Jonides, J. & Perrig, W. (2008). Improving fluid intelligence with training on working memory. Proceedings of the National Academic of Sciences, 105 (19), 6829-6833. (click to read)


Abstract

• Fluid intelligence (Gf) refers to the ability to reason and to solve new problems independently of previously acquired knowledge. Gf is critical for a wide variety of cognitive tasks, and it is considered one of the most important factors in learning. Moreover, Gf is closely related to professional and educational success, especially in complex and demanding environments. Although performance on tests of Gf can be improved through direct practice on the tests themselves, there is no evidence that training on any other regimen yields increased Gf in adults. Furthermore, there is a long history of research into cognitive training showing that, although performance on trained tasks can increase dramatically, transfer of this learning to other tasks remains poor. Here, we present evidence for transfer from training on a demanding working memory task to measures of Gf. This transfer results even though the trained task is entirely different from the intelligence test itself. Furthermore, we demonstrate that the extent of gain in intelligence critically depends on the amount of training: the more training, the more improvement in Gf. That is, the training effect is dosage-dependent. Thus, in contrast to many previous studies, we conclude that it is possible to improve Gf without practicing the testing tasks themselves, opening a wide range of applications.

Can we train Gf (fluid IQ)?

Check out the following from one of my favorite blogs- Sharp Brains:

• "A recent scientific study is being welcomed as a landmark that shows how fluid intelligence can be improved through training. I interviewed one of the researchers recently (Can Intelligence Be Trained? Martin Buschkuehl shows how), and contributor Dr. Pascale Michelon adds her own take with the great article that follows. Enjoy!"

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Brain fitness training success in elderly

Check out the Eide Neurolearning blog for an interesting post (with link to article) that demonstrates the effectiveness of training (the ACTIVE model) memory, reasoning, and cognitive speed on everyday cognitive functioning in adulthood

Technorati Tags: brain fitness, aging, adulthoot, educational psychology, neuropsychology, neuroscience, ACTIVE, elderly, cognitive training, cognition, intelligence, IQ, IQ scores, developmental

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How the brain processes quantitative information-new studies

New research summarized at Science Daily that is providing new insights into how the brain processes quantiative/numerical (Gq/Gf-RQ) information. Below is the first paragraph of the article.

• Two studies in the January 18, 2007, issue of the journal Neuron, published by Cell Press, shed significant light on how the brain processes numerical information--both abstract quantities and their concrete representations as symbols. The researches said their findings will contribute to understanding how the brain processes quantitative information as well as lead to studies of how numerical representation in the brain develops in children. Such studies could aid in rehabilitating people who suffer from dyscalculia--an inability to understand, remember, and manipulate numbers. The researchers also said their findings offer insight into the mystery of how the brain learns to associate abstract symbols precisely with quantities.

Scientific American also provides coverage of these two studies

Technorati Tags: psychology, educational psychology, education, school psychology, special education, LD, learning disabilities, dyscalculia, Gq, Gf, quantitative, math, numerical, neuropsychology, information processing

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