Neurology

What do we know about the autistic brain?

Autism is a behaviorally-defined syndrome, and no biological markers exist to identify autism at this time.  As a result, it has yet to be proven that the core autistic behaviors are directly or exclusively linked to specific modular brain or biological factors, i.e. we don’t know that it’s solely hardwired.  The DSM-IV Criteria for Autistic Disorder lists several traits of behavior associated with autism, but there are also multiple immune impairments as well.  For example, around 30% of children diagnosed with autism have some sort of seizure activity in the brain, cognitive deficits, motor abnormalities, savant skills, and impairment of the immune system.  At least 50-75% of autistic kids have gastrointestinal abnormalities, and at least half of these kids have food allergies.

We know that certain areas of the brain correspond to different endophenotypes, which are traits that may be intermediate on the chain of causality from genes to disease, or in other words a sort of ‘proxy’ measure.  For example, we know that some of our kids have trouble with face processing, but have no problem at all climbing all over the couches.  This is presumably because face processing is associated with the fusiform gyrus, the superior temporal sulcus, and the amygdala, while motor imitation is associated with Broca’s area and the inferior parietal cortex (Dawson).

We also know that autistic kids, on average, have big brains.  This has been well documented by comparing head circumference, brain weight, and brain volume, although the state of the art is not to the point of being able to use these measures as early diagnostic tools.

Myelination

“The human brain is not a finished organ at birth — in fact, another 10 or 12 years are needed before even a general development is completed. Structural maturation of individual brain regions and their connecting pathways is required for the successful development of cognitive, motor, and sensory functions. This maturation eventually provides for a smooth flow of neural impulses throughout the brain, which allows for information to be integrated across the many spatially segregated brain regions involved in these functions. The speed of neural transmission is an important factor, and this depends not only on the junctions between nerve cells (synapses), but also on the structural properties of the connecting fibers (axons). Critical axon structural properties include their diameters and the thickness of the special insulation (myelin) around many fibers. Large groups of myelinated axons, which connect various regions in the brain, appear visibly as “white matter”. Axons of the major pathways in the human brain, such as those of the corpus callosum (which connects the two halves of the brain) or the corticospinal tract (which connects the brain to the spinal cord and the rest of the body), continue to develop throughout childhood and adolescence. Postmortem studies suggest that axon diameters and myelin sheaths undergo conspicuous growth during the first two years of life, but may not be fully mature before adolescence or even late adulthood. The scarcity of human brain specimens for postmortem analysis has made it difficult to draw definite conclusions about the timetable of myelinization during childhood and adolescence.

Our understanding of the propagation of nerve impulses represents an interesting convergence of physics and biology. The nerve impulse is a rapid propagating wave (approximately 1 millisecond in duration) of depolarization followed by repolarization. In the language of physics, the neuron axon behaves as an electrical transmission line with a transverse time-variant and voltage-dependent negative conductance element in parallel with a high capacitance. In fact, the equations describing the propagation of neuron action potentials derive from the classical equations for wave propagation along electrical transmission lines developed by Maxwell and Kelvin. As expected from these equations, the cross- sectional diameter of an axon is an important determinant of impulse propagation velocity: the larger the diameter, the greater the velocity of propagation. The myelin sheath that surrounds certain types of axons is a periodically interrupted electrical insulation, and on physical grounds it can be demonstrated that the effect of this type of insulation, considering the known electrical properties of the axon, is a substantial increase in pulse propagation velocity over that of a bare axon of the same diameter. Myelinization is thus a major aspect of the workings of neural circuits.

T. Paus et al. (2000) report a computational analysis of structural magnetic resonance images (see note below) obtained in 111 living children and adolescents. The authors report the analysis reveals age-related increases in white-matter density in fiber tracts constituting apparent corticospinal and frontotemporal pathways. The maturation of the corticospinal tract was bilateral, but that of the frontotemporal pathway was found predominantly in the left (speech-dominant) hemisphere. The authors suggest these findings provide evidence for a gradual maturation, during late childhood and adolescence, of fiber pathways presumably supporting motor and speech functions. The authors also suggest their finding may provide guidance for further investigations of neurodevelopmental disorders such as schizophrenia: “the abnormal rate of myelinization during childhood or adolescence may very well underlie the emergence of psychotic symptomatology.” Finally, the authors suggest that the demonstrated possibility of detecting subtle structural variations in white matter in the living human brain opens up new avenues of research on normal and abnormal cognitive development and in the evaluation of the long-term effects of various treatment strategies.”

In children with autism and developmental language disorder (DLD), Martha Herbert has found that the amount of white matter in the brains of these kids disproportionately accounts for bigger brains in both autism and DLD.  In addition, all parts of the autistic brain are larger than in the DLD brain, but both the autistic kids and the children with DLD had larger brains than the control group.  What does this tell us?  Many have argued that this points to an ongoing chronic abnormality, rather than only early developmental changes that affect wiring and then disappear.  This might suggest a pathophysiological cascade in which the brain suffers the consequences of inflammation.

Models

What happens to the development of the brain when the body is chronically inflamed from infancy?  Some studies have shown that disordered brain organization leads to atypical brain activation, which leads to diminished connections between regions.  In other words, the different parts of the brain can’t communicate normally (Horwitz, Critchley, Luna. Castelli, Starkstein, Ring, Hubl, Hall, Belmonte, Muller, Muller, Peirce, Rumsey, Devolder, Hah, Belmonte).

Immune impairment might also increase the body’s vulnerability to toxins (Hornig) and contribute to the injury of the immune system, or worsen immune impairment (Silbergeld).    In Hornig’s study, mice indicated disturbances in behavior and brain architecture following postnatal Thimerosal exposures that paralleled strain sensitivity to autoimmune disease.  In Silbergeld’s work, the exposure to low-dose inorganic mercury accelerated disease and mortality in acquired lupus.

What remains to be seen is how biological underpinnings matter, or how the metabolism between genes and the brain affect brain development.  Essentially, however, the state of the art says that core-autism behaviors probably come from errors of processing in the brain that have various biological underpinnings, rather than genetic programming, which might explain why no two children with autism share exactly the same symptoms.  For cognitive neuroscience, we need to know why you can injure the system in so many different ways and still end up with a somewhat common set of behaviors.

Bibliography

Allred M , Wilbur S: Hazardous substance exposures and autism. , in DeRosa C , Holler J , Mehlman M (eds): Advances in Modern Toxicology. Princeton NJ, International Toxicology Books, Inc; 2002:

Belmonte MK, Yurgelun-Todd DA: Functional anatomy of impaired selective attention and compensatory processing in autism. Brain Res Cogn Brain Res 2003; 17:651-64.

BressJer SL, Kelso JA. Cortical coordination dynamics and cognition. Trends Cogn Sci 2001 Jan;5(1):26- 36.

Boulanger LM, Shatz CJ. Immune signalling in neural development, synaptic plasticity and disease. Nat Rev Neurosci 2004 Jul;5(7):521-31.

Brock J, Brown CC, Boucher J, Rippon G: The temporal binding deficit hypothesis of autism. Dev PsychopathoI2002;14:209-24.

Carper RA, Moses P, Tigue ZD, Courd”lesn.e E: Cerebral lobes in autism: early hyperplasia and abnormal age effects. Neuroimage 2002;16:1038-51.

Casanova MF, Buxhoeveden D, Gomez J: Disruption in the inhibitory architecture of the cell minicolumn. implications for autisim. Neuroscientist 2003;9:496-507.

Chauhan, A.; Chauhan, V.; Brown, W. T., and Cohen, I. Oxidative stress in autism: increased lipid peroxidation and reduced serum levels of ceruloplasmin and transferrin-the antioxidant proteins. Life Sci. 2004 Oct 8; 75(21 ):2539-49.

Chir0n C, Leboyer M, Leon F, Jambaque 1, Nut tin C, Syrota ASPECT of the brain in d”lildhood autism: evidence for a lack of normal hemispheric asymmetry. Dev Med Child NeuroI1995;37:849-60.

Cohen IL: An artificial neural network analogue of learning in autism. Bioi Psychiatry 1994;36:5-20-

Comi AM, Zimmerman AW, Frye VH, Law PA, Peeden IN. Familial Clustering of Autoimmune Disorders and Evaluation of Medical Risk Factors in Autism. J Child Neurol1999 Jun;14(6):388-94.

Courchesne E, Karns CM, Davis HR, et al: Unusual brain growth patterns in early life in patients with autistic disorder: An MRI study. Neurology 2001 ;57:245-54.

Dalton P, Deacon R, Blamire A, et al: Maternal neuronal antibodies associated with autism and a language disorder .Ann NeuroI2003;53:533-7 .

Dawson G, Webb S, Schellenberg GD, Dager S, Friedman S, Aylward E, et al. Defining the broader phenotype of autism: genetic, brain, and behavioral perspectives. Dev Psychopathol 2002 Summer;14(3):581-611.

Eigsti IM, Shapiro T: A systems neuroscience approad”l to autism: biological, cognitive, and clinical perspectives. Ment Retard Dev Disabil Res Rev 2003;9:205-15.

Hashimoto, T., M. Sasaki, M. Fukumizu, S. Hanaoka, K Sugai, and H. Matsuda. 2000. Single-Photon Emission Computed Tomography of the Brain in Autism: Effect of the Developmental Level. Pediatric Neurology 23, no.5: 416-20.

Herbert MR, Ziegler DA, Deutsd”l CK, et al: Dissociations of cerebral cortex, subcortical and cerebral white matter volumes in autistic boys. Brain 2003;126:1182-1192.

Herbert MR, Ziegler DA, Makris N, et al. Larger Brain and White Matter Volumes in Children with Developmental Language Disorder. Developmental Science 2003;6:F11-F22

Herbert MR, Ziegler DA, Makris N, et al: Localization of white matter volume increase in autism and developmental language disorder. Annals of Neurology in press, April, 2004.

Herbert MR. Neuroimaging in disorders of social and emotional functioning. what is the question? J Child Neurol 2004 Oct;19(10):772-84.

Herbert MR, Ziegler DA, Deutsd”l CK, O’brien LM, Kennedy DN, Filipek PA, et al. Brain asymmetries in autism and developmental language disorder: a nested whole-brain analysis. Brain 2005 Jan; 128(Pt 1):213-26.

Herbert M, Ziegler D. Volumetric Neuroimaging and Low-Dose Early-Life exposures: Loose Coupling of Pathogenesis-Brain-Behavior Links. Neurotoxicology 2005, in press.

Hornig M, Lipkin WI: Infectious and immune factors in the pathogenesis of neurodevelopmental disorders’ Epidemiology, hypotheses, and animal models. Ment Retard Dev Disabil Res Rev 2001 ;7:200-10.

Hornig M, Chian D, Lipkin WI. Neurotoxic effects of postnatal thimerosal are mouse strain dependent. Mol Psyd”liatry 2004 Sep;9(9):833-45.

James SJ, Cutler P, Melnyk S, Jemigan S, Janak L, Gaylor DW, et al. Metabolic biomarkers of increased oxidative stress and impaired methylation capacity in d”lildren with autism. Am J Clin Nutr 2004 Dec;80(6):1611-7.

Kakita, A.; Inenaga, C.; Sakamoto, M., and Takahashi, H. Disruption of postnatal progenitor migration and ~;~J/j consequent abnormal pattern of glial distribution in the cerebrum following administration of methylmercury. J Neuropathol Exp Neurol. 2003 Aug; 62(8):835-47. _f:

Kaya, M., S. Karasalihoglu, F. Ustun, A. Gultekin, T. F. Cermik, Y. Fazlioglu, M. Ture, 0. N. Yigitbasi, and S. Berkarda. 2002. The Relationship Between Tc-99m-Hmpao Brain Spect and the Scores of Real-life Rating Scale in Autistic Children. Brain Development 24, no.2: 77 -81. -.

Makris N, Meyer JW, Bates JF, Yeterian EH, Kennedy DN, Caviness VS: MRI-Based topographic parcellation of human cerebral white matter and nuclei II. Rationale and applications with systematics of cerebral connectivity. Neuroimage 1999;9:18-45.

Mesulam MM: large-scale neurocognitive netwdrks and distributed processing for attention, language, and memory. Annals of Neurology 1990;28:597-613.

Minshew NJ, Goldstein G, Dombrowski SM, Panchalingam K, Pettegrew JW. A preliminary 31 P MRS study of autism: Evidence for undersynthesis and increased degradation of brain membranes. Bioi Psychiatry 1993;33(762-773).

Morton J, Frith U. Causal modelling: a structural approach to developmental psychopathology, in Cicchetti D, Cohen DJ (eds): Manual of Developmental Psychopathology. New York, John Wiley; 1995:357 – 390.

Mountz, J. M., l. C. Tolbert, D. W. lill, C. R. Katholi, and H. G. liu. 1995. Functional Deficits in Autistic Disorder- Characterization by Technetium-99m-Hmpao and Spect .Journal of Nuclear Medicine 36, no.7: 1156-Q2.

Ohnishi, T., H. Matsuda, T. Hashimoto, T. Kunihiro, M. Nishikawa, T. Uema, and M. Sasaki. 2000. Abnormal Regional Cerebral Blood Flow in Childhood Autism. Brain 123: 1838-44

Perry VH. The influence of systemic inflammation on inflammation in the brain implications for chronic neurodegenerative disease. Brain Behav Immun 2004 Sep;18(5)407-13.

Perry VH, Newman TA, Cunningham C. The impact of systemic infection on the progression of neurodegenerative disease. Nat Rev Neurosci 2003 Feb;4(2)103-12.

Porges S: The Vagus: A mediator of behavioral and visceral features associated with autism, in Bauman M, Kemper T (eds): The Neurobiology of Autism. in press.

l. Qin, X. Wu, M. Block, D.J. Knapp, G. Breese, J.S. Hong, F. Crews. SYSTEMIC INFLAMMATION ACTIVATES BRAIN CYTOKINE SYNTHESIS Program No. 560.12.. Society for Neuroscience, 2004, abstract. Online.

Rubenstein Jl, Merzenich MM: Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes Brain Behav 2003;2:255-67.

Smith lB, Thelen E: Development as a Dynamic System. Trends in Cognitive Sciences 2003;7:343-348. Rampton S, Stauber J, Trust Us, We’re Experts: How Industry Manipulates Science and Gambles with Your Future. httD:I/www.Drwatch.ora/booksleXDerts.html

Ryu, Y. H., J. D. lee, P. H. Yoon, D. I. Kim, H. B. lee, and Y. J. Shin. 1999. Perfusion Impairments in Infantile Autism on T echnetium-99m Ethyl Cysteinate Dimer Brain Single-Photon Emission

Tomography. Comparison With Findings on Magnetic Resonance Imaging. European Journalof Nuclear Medicine 26, no.3: 253-59.

Silverman C, Herbert M. Autism and Genetics: Genes are not the cause of an emerging epidemic. GeneWatch 2003; 16:4-Q. http:llwww .gene-watch.org/genewatchlarticlesI16-2herbert_silverman. html

Sogut, S.; Zoroglu, S. S.; Ozyurt, H.; Yilmaz, H. R.; Ozugurlu, F.; Sivasli, E.; Yetkin, 0.; Yanik, M.; Tutkun, H.; Savas, H. A.; Tarakcioglu, M., and Akyol, 0. Changes in nitric oxide levels and antioxidant enzyme activities may have a role in the pathophysiological mechanisms involved in autism. Clin Chim Acta. 2003 May; 331(1-2):111-7.Starkstein, S. E., S. Vazquez, D. Vrancic, V. Nanclares, F.

Manes, J. Piven, and C. Plebst. 2000. Spect Findings in Mentally Retarded Autistic Individuals. ‘ Journal of Neuropsychiatry and Clinical Neurosciences 12, no.3: 370-375.

Stein J, Schettler T, Wallinga D, Valenti M: In harm’s way: toxic threats to child development. J Dev Behav Pediatr2002;23:S13-22., See also www.preventinaharm,ora .Tucker DM: Developing emotions and cortical networks, in Gunnar MR, Nelson CA (eds): Developmental Behavioral Neuroscience. Hillsdale, NJ, Lawrence Erlbaum Associates; 1992:75-128.

Vargas DL, Nascimbene C, Krishnan C, Zimmerman AW, Pardo CA. Neuroglial activation and neuroinflammation in the brain of patients with autism. Ann Neurol 2005 Jan;57(1 ):67-81.

Wilcox, J., M. T. Tsuang, E, Ledger, J. Algeo, and T. Schnurr. 2002. Brain Perfusion in Autism Varies With Age. Neuropsychobiology46, no.1: 13-16.

Yorbik, 0.; Sayal, A.; Akay, C.; Akbiyik, D. I., and Sohmen, T. Investigation of antioxidant enzymes in children with autistic disorder. Prostaglandins Leukot Essent Fatty Acids. 2002 Nov; 67(5):341- 3Zoroglu, S. S.; Armutcu, F.; Ozen, S.; Gurel, A.; Sivasli, E.; Yetkin, 0., and Meram, I. Increased oxidative stress and altered activities of erythrocyte free radical scavenging enzymes in autism. Eur Arch Psychiatry Clin Neurosci. 2004 JUf1; 254(3):143-7.