Autism: Balancing excitation and inhibition in the autistic brain

A metric called the Hurst exponent could be a useful biomarker for studies exploring brain differences between men and women with autism spectrum disorder.
  1. Charlotte M Pretzsch
  2. Dorothea L Floris  Is a corresponding author
  1. Department of Forensic and Neurodevelopmental Sciences, Kings' College London, United Kingdom
  2. Donders Centre for Cognitive Neuroimaging, Netherlands

Balance and stability are important for the human body. This is clearly true for some physical tasks, such as walking or running without falling over, but it is also true inside the brain. Neurons receive both excitatory and inhibitory inputs, and maintaining a balance between the two – that is, maintaining what is known as the excitation-inhibition or E:I balance – is crucial for the brain to work properly (Yizhar et al., 2011).

Disruptions to the E:I balance, such as increased levels of excitatory inputs, have been linked to autism and a number of other neurological conditions, and can affect brain function and social behavior (Rubenstein and Merzenich, 2003). It has also been shown that the E:I balance can depend on sex, especially in regions of the brain that support social behavior, such as the ventromedial prefrontal cortex (Lai et al., 2019). However, research into the relationships between autism, sex and social behavior have been hampered by a lack of non-invasive tools. Now, in eLife, Michael Lombardo (Istituto Italiano di Tecnologia and University of Cambridge) and colleagues – including Stavros Trakoshis and Pablo Martínez-Cañada as joint first authors – report how it may be possible to measure the E:I balance without causing damage to the brain (Trakoshis et al., 2020).

The researchers – who are based in Italy, Cyprus, South Korea, the United Kingdom, Switzerland, and Canada – first created a computational model of the brain and used data from this model to calculate a metric called the Hurst exponent. This metric is a measure of the long-term memory of a time series of data. The model was then tweaked to simulate the effect of a ligand called CNO (which is short for clozapine-N-oxide) on two receptors hM3Dq and hM4Di, which are synthetic proteins designed to bind synthetic drugs. When CNO binds to hM3Dq it increases excitation, and when it binds to hM4Di it reduces both excitation and inhibition. Trakoshis et al. found that the change in the E:I balance caused by CNO also changed the Hurst exponent: specifically, an increase in excitation decreased the Hurst exponent (Figure 1).

Maintaining a balance of excitatory and inhibitory input in neurons.

An imbalance between excitatory and inhibitory inputs to neurons in certain regions of the brain has been linked to neuropsychiatric conditions such as autism spectrum disorder (ASD). However, it is not possible to measure such imbalances directly, so it would be useful to have a proxy marker. Based on computer simulations and experiments on genetically manipulated mice (top), Trakoshis et al. found that a metric called the Hurst exponent, which can be determined using non-invasive electrical and magnetic measurements, can provide information on imbalances between excitatory and inhibitory input. In particular, an increase in excitation (E) led to a decrease in the Hurst exponent (H). Experiments on autistic and typically developing (TD) men and women show that: i) the value of H for men with autism is much lower than the value for TD men; ii) the value of H for women with autism is higher than the value for TD women; iii) in women with autism, the value of H further correlated with social behavior.

Second, the researchers tested if they could replicate these computational results in mice that had undergone chemogenetic manipulation to express hM3Dq and hM4Di. This involved measuring electrical activity in the prefrontal cortex of the mice before, during and after the administration of CNO, and then computing the Hurst exponent. They found that the in vivo results in mice confirmed the predictions of their computational model. Specifically, a drug-induced increase in excitation led to a decrease in the Hurst exponent.

Third, Trakoshis et al. wanted to find out why E:I processes may differ between males and females. They found that genes associated with autism that also affect the E:I balance (especially excitation) overlapped with genes that are sensitive to male-specific hormones. A comparison of these results with a gene expression map called the Allan Human Brain Atlas (Hawrylycz et al., 2012) further revealed that these genes are expressed in many regions of the brain, including the ventromedial prefrontal cortex.

To investigate how the E:I balance may differ between autistic men and women, and how those differences may relate to social behavior, Trakoshis et al. collected neural time series data and computed the Hurst exponent in individuals with and without autism (who were similar in age and IQ). In the ventromedial prefrontal cortex, the Hurst exponent of individuals with autism was lower than that of typically developing individuals, with the difference between the two being larger in males than in females. Moreover, in women with autism, the Hurst exponent was linked with social behavior: a higher (i.e., more typical) value was accompanied by a better ability to 'socially camouflage' – that is, the ability to compensate for social-communicative difficulties.

Taken together, these results suggest that the Hurst exponent may be a useful biomarker to examine the E:I balance and its relationship with sex and social behavior across the autism spectrum. More research is needed to investigate if shifting the E:I balance in the ventromedial prefrontal cortex could alter social behavior in people with autism. In the future, this approach could be extended into other conditions linked to E:I balance and sex-differences, such as attention deficit hyperactivity disorder.

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Author details

  1. Charlotte M Pretzsch

    Charlotte M Pretzsch is in the Department of Forensic and Neurodevelopmental Sciences, Kings' College London, United Kingdom

    Contributed equally with
    Dorothea L Floris
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2761-6628
  2. Dorothea L Floris

    Dorothea L Floris is in the Donders Centre for Cognitive Neuroimaging, Nijmegen, Netherlands

    Contributed equally with
    Charlotte M Pretzsch
    For correspondence
    D.floris@donders.ru.nl
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5838-6821

Publication history

  1. Version of Record published: August 4, 2020 (version 1)

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© 2020, Pretzsch and Floris

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Charlotte M Pretzsch
  2. Dorothea L Floris
(2020)
Autism: Balancing excitation and inhibition in the autistic brain
eLife 9:e60584.
https://doi.org/10.7554/eLife.60584

Further reading

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    Qing Shen, Huan Song ... Unnur Valdimarsdóttir
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    Background:

    The association between cardiovascular disease (CVD) and selected psychiatric disorders has frequently been suggested while the potential role of familial factors and comorbidities in such association has rarely been investigated.

    Methods:

    We identified 869,056 patients newly diagnosed with CVD from 1987 to 2016 in Sweden with no history of psychiatric disorders, and 910,178 full siblings of these patients as well as 10 individually age- and sex-matched unrelated population controls (N = 8,690,560). Adjusting for multiple comorbid conditions, we used flexible parametric models and Cox models to estimate the association of CVD with risk of all subsequent psychiatric disorders, comparing rates of first incident psychiatric disorder among CVD patients with rates among unaffected full siblings and population controls.

    Results:

    The median age at diagnosis was 60 years for patients with CVD and 59.2% were male. During up to 30 years of follow-up, the crude incidence rates of psychiatric disorder were 7.1, 4.6, and 4.0 per 1000 person-years for patients with CVD, their siblings and population controls. In the sibling comparison, we observed an increased risk of psychiatric disorder during the first year after CVD diagnosis (hazard ratio [HR], 2.74; 95% confidence interval [CI], 2.62–2.87) and thereafter (1.45; 95% CI, 1.42–1.48). Increased risks were observed for all types of psychiatric disorders and among all diagnoses of CVD. We observed similar associations in the population comparison. CVD patients who developed a comorbid psychiatric disorder during the first year after diagnosis were at elevated risk of subsequent CVD death compared to patients without such comorbidity (HR, 1.55; 95% CI, 1.44–1.67).

    Conclusions:

    Patients diagnosed with CVD are at an elevated risk for subsequent psychiatric disorders independent of shared familial factors and comorbid conditions. Comorbid psychiatric disorders in patients with CVD are associated with higher risk of cardiovascular mortality suggesting that surveillance and treatment of psychiatric comorbidities should be considered as an integral part of clinical management of newly diagnosed CVD patients.

    Funding:

    This work was supported by the EU Horizon 2020 Research and Innovation Action Grant (CoMorMent, grant no. 847776 to UV, PFS, and FF), Grant of Excellence, Icelandic Research Fund (grant no. 163362-051 to UV), ERC Consolidator Grant (StressGene, grant no. 726413 to UV), Swedish Research Council (grant no. D0886501 to PFS), and US NIMH R01 MH123724 (to PFS).

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    Individuals recently diagnosed with a cardiovascular disease are at higher risk of developing a mental illness, with mortality increasing when both conditions are present.