Diagnosing ASD with fractal analysis

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Abstract

PurposeNeuroscience is providing new tools to potentially improve diagnosis and classification of autism spectrum disorder (ASD) based on biomarkers. The purpose of this paper, is to describe certain applications of fractal analysis, a tool used to measure information complexity observed within electroencephalograph (EEG) signals and neurogenetic code. It is argued here that a better method of diagnosis of ASD may exist based on these new tools.Design/methodology/approachSelective review of literature focused on the diagnosis of ASD and recent technological advances in scientific approaches to diagnosis of ASD. It is argued that higher levels of complex, coherent data are inversely related to pathology; in biological systems, lower complexity EEG during specific tasks may reveal pathology.FindingsClinicians and researchers are exploring new ways to describe mental illness based on biomarkers to improve reliability and validity of diagnostic methods. Specific application of chaos theory in the form of fractal analysis shows promise as one possible method.Originality/valueThis is a conceptual paper addressing the advantages of employing fractal analysis of EEG and genomics for the diagnosis of ASD.

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C. Peng, S. V. Buldyrev, A Goldberger … (1992)

DNA sequences have been analysed using models, such as an n-step Markov chain, that incorporate the possibility of short-range nucleotide correlations. We propose here a method for studying the stochastic properties of nucleotide sequences by constructing a 1:1 map of the nucleotide sequence onto a walk, which we term a 'DNA walk'. We then use the mapping to provide a quantitative measure of the correlation between nucleotides over long distances along the DNA chain. Thus we uncover in the nucleotide sequence a remarkably long-range power law correlation that implies a new scale-invariant property of DNA. We find such long-range correlations in intron-containing genes and in nontranscribed regulatory DNA sequences, but not in complementary DNA sequences or intron-less genes.

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The current state of the neurogenic theory of depression and anxiety.

Michael R. Miller, Rene Hen (2015)

Newborn neurons are continuously added to the adult hippocampus. Early studies found that adult neurogenesis is impaired in models of depression and anxiety and accelerated by antidepressant treatment. This led to the theory that depression results from impaired adult neurogenesis and restoration of adult neurogenesis leads to recovery. Follow up studies yielded a complex body of often inconsistent results, and the veracity of this theory is uncertain. We propose five criteria for acceptance of this theory, we review the recent evidence for each criterion, and we draw the following conclusions: Diverse animal models of depression and anxiety have impaired neurogenesis. Neurogenesis is consistently boosted by antidepressants in animal models only when animals are stressed. Ablation of neurogenesis in animal models impairs cognitive functions relevant to depression, but only a minority of studies find that ablation causes depression or anxiety. Recent human neuroimaging and postmortem studies are consistent with the neurogenic theory, but they are indirect. Finally, a novel drug developed based on the neurogenic theory is promising in animal models. Copyright © 2014 Elsevier Ltd. All rights reserved.

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Subgrouping the Autism “Spectrum": Reflections on DSM-5

Meng-Chuan Lai, Michael V Lombardo, Bhismadev Chakrabarti … (2013)

DSM-5 has moved autism from the level of subgroups (“apples and oranges") to the prototypical level (“fruit"). But making progress in research, and ultimately improving clinical practice, will require identifying subgroups within the autism spectrum.