In previous blogs I have discussed the presence of abnormally constructed cortical structures called minicolumns in the brains of autistic individuals. These cortical modules are units of information processing much akin to the microprocessor of a computer. In the case of a PC or Mac a given computer has 1 or 2 of these microprocessors. By way of contrast, the human brain has several hundred million minicolumns, all of them capable of performing parallel processing.
In several publications we have been able to describe and corroborate that the brains of autistic individuals have more minicolumns as compared to those of the neurotypical brain. Unfortunately in the case of autistic individuals these modular units are abnormal in terms of how they are constructed. According to our findings the “shower curtain of inhibition” that surrounds minicolumns does not develop properly. The latter finding, which was discussed in a previous blog, gave rise to my idea of using transcranial magnetic stimulation (TMS) as a potential therapeutic intervention for autism. In this blog I would like to discuss 2 consequences for when a brain has more minicolumns than normal.
Minicolumns, just as microprocessors, release energy whenever they perform work. This energy must be dissipated as minute changes in temperature affect the rates at which chemical processes occur in biological systems. In the case of microprocessors, computers have small fans just for this purpose. In the case of the human brain, biological anthropologists believe that the apposition of radial blood vessels crisscrossing the cortex may act as radiators or heat exchangers, transferring heat from tissue into blood vessels. If the energy of a computer’s microprocessor is not dissipated, it may cause overheating and malfunction of the computer In similar fashion, a brain with supernumerary minicolumns is more prone to overheating when challenged by metabolic exigencies. This is similar to cases of mitochondrial disorders (mitochondria providing the powerhouse for the cell) where viral infections, seizures, or violent postvaccine reactions may overtax the system and produce brain damage. Although I am aware of a publication suggesting improvement in autistic behaviors during high fevers, my experience has been quite the opposite. I attribute any so-called improvement during high fevers to the fact that the patients may be somnolent or even listless.
Another important consequence of too many minicolumns relates to connectivity. In order for a minicolumn to work properly it needs to be connected to a large number of adjacent modules. In effect, estimates of cortical interconnectivity indicate that each minicolumn is connected to a 1,000 similar modules. Adding supernumerary minicolumns follows a power law wherein, as an example, a fourfold increase in modular units requires an eightfold increase of interconnecting fibers. The additional white matter takes the form of short-range association fibers. Researchers postulate that the spatial layout of the brain minimizes total connections costs. Long-range connectivity incurs the penalties of increased conduction time and the requirement of a large volume of metabolically active tissue. As the brain enlarges, the distance between cells and columns increases so that attempts to maintain connectivity results in signal transmission delays and inefficiencies. Modules with short-range interconnections reduce both conduction time and metabolic requirements (Casanova, 2004).
The figure illustrates the proliferation of connections (lines) needed to maintain constant connectivity as the number of modular units (points) increases. Each module communicates with 50% of the other modules in each instance. n= number of modules, m= number of interconnections.
Reports of an increased number of minicolumns and the presence of smaller neurons biases corticocortical connectivity in favor of shorter subcortical projections (e.g., arcuate fibers) at the expense of longer ones (e.g., commissural fibers) (Casanova et al., 2006). This blueprint of connectivity offers important clinicopathological correlates to autism; e.g., difficulties with the big picture, perseverating on details. This has led some people to suggest that the brains of autistic individuals process information in a way that favors local over global information.
A bias in the corticocortical connectivity in autism was first hypothesized by Belmonte and colleagues in 2004. Physiological studies tend to confirm the presence of a local bias and global performance impairment in autistic individuals. Recent anatomical findings suggestive of diminished neuronal cell soma size and increased outer radiate white matter seemingly validate the presence of supernumerary short corticocortical projections (Casanova et al., 2006). Similarly, anatomical and/or structural studies suggestive of a diminished corpus callosum, despite larger brains, indicate a reduction in the total number of longer corticocortical projections.
Parcellating the white matter of the brain into different compartments. In patients with autism the outer radiate white matter compartment (composed of short arcuate fibers) appears to be increased in size. This occurs at the expense of longer fibers that connect homologous aspects of both hemispheres.
In future blogs I will describe how this ratio of long to short intercortical connections is distributed in the population at large. It seems that autistic individuals fall at one tail end of the distribution while dyslexics and ADHD fall at the opposite tail end (see figure below) (Williams and Casanova, 2010). This difference in the overall blueprint of connectivity in the brain of autistic individuals helps explain why they may exhibit a different cognitive style as compared to neurotypicals. The difference may have practical applications when developing screening tests or when used as outcome measurements, e.g., following patients longitudinally. A good book to read about cortical connectivity which was written for the layperson is Olaf Sporns: “Discovering the Human Connectome”, MIT Press 2012.
As a parting note there are some studies on “functional” connectivity that suggest reduced communication among nearby cortical regions (short range projections). Comparing anatomical and functional connectivity is analogous to comparing apples and pears. Some of the disagreement between anatomical methods and functional techniques relate to the fact that results of functional studies may reflect compensatory or autoregulatory changes to variations in the brain’s blueprint of connectivity directed at the homeostatic recovery of “normal” neural network activity. Thus anatomical methods provide a quantitative estimation of structural components along with their spatial arrangement while functional methods portray similar phenomena with added secondary or adaptive changes.
Casanova MF. White matter volume increase and minicolumns in autism. Ann Neurol, 56(3):453, 2004.
Casanova MF, van Kooten IAJ, Switala AE, van Engeland H, Heinsen H, Steinbusch HWM, Hof PR, Trippe J, Stone J, Schmitz C. Minicolumnar abnormalities in autism. Acta Neuropathologica 112(3):287-303, 2006.
Williams EL, Casanova MF, Autism and dyslexia: a spectrum of cognitive styles as defined by minicolumnar morphometry. Med Hypothesis 74(1):59-62, 2010.
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