Globally elevated excitation–inhibition ratio in children with autism spectrum disorder and below-average intelligence

Abstract

Background Altered neuronal excitation–inhibition (E–I) balance is strongly implicated in ASD. However, it is not known whether the direction and degree of changes in the E–I ratio in individuals with ASD correlates with intellectual disability often associated with this developmental disorder. The spectral slope of the aperiodic 1/f activity reflects the E–I balance at the scale of large neuronal populations and may uncover its putative alternations in individuals with ASD with and without intellectual disability. Methods Herein, we used magnetoencephalography (MEG) to test whether the 1/f slope would differentiate ASD children with average and below–average (< 85) IQ. MEG was recorded at rest with eyes open/closed in 49 boys with ASD aged 6–15 years with IQ ranging from 54 to 128, and in 49 age-matched typically developing (TD) boys. The cortical source activity was estimated using the beamformer approach and individual brain models. We then extracted the 1/f slope by fitting a linear function to the log–log-scale power spectra in the high-frequency range. Results The global 1/f slope averaged over all cortical sources demonstrated high rank-order stability between the two conditions. Consistent with previous research, it was steeper in the eyes-closed than in the eyes-open condition and flattened with age. Regardless of condition, children with ASD and below-average IQ had flatter slopes than either TD or ASD children with average or above-average IQ. These group differences could not be explained by differences in signal-to-noise ratio or periodic (alpha and beta) activity. Limitations Further research is needed to find out whether the observed changes in E–I ratios are characteristic of children with below-average IQ of other diagnostic groups. Conclusions The atypically flattened spectral slope of aperiodic activity in children with ASD and below-average IQ suggests a shift of the global E–I balance toward hyper-excitation. The spectral slope can provide an accessible noninvasive biomarker of the E–I ratio for making objective judgments about treatment effectiveness in people with ASD and comorbid intellectual disability.

Effects of neural noise on predictive model updating across the adult lifespan

“…in schizophrenia or autism) (see Voytek & Knight, 2015, for further details). Changes in aperiodic slope may also reflect a shift in the balance between excitatory and inhibitory activity (Gao et al, 2017), which is in line with the proposal that individuals with autism and schizophrenia show altered excitation-to-inhibition ratios (Rubenstein & Merzenich, 2003) and aperiodic slope characteristics (Manyukhina et al, 2022;Molina et al, 2020) in comparison to neurotypical individuals. In contrast to the aperiodic slope, the aperiodic intercept has been shown to reflect aggregate population spiking activity across widespread brain regions (Manning et al, 2009) and correlates with the fMRI BOLD response (Winawer et al, 2013).…”

Combining Aperiodic 1/f Slopes and Brain Simulation: An EEG/MEG Proxy Marker of Excitation/Inhibition Imbalance in Alzheimer’s Disease

“…These markers represent a key translational link across species and recording scales and can be applied in resting-state experiments and tasks that do not require extensive cognitive processing. They have been used to make inferences of E/I disruptions across many psychiatric and neurodevelopmental disorders, often combined with pharmacological or chemogenetic manipulations that modulate the level of inhibition and excitation (Manyukhina et al 2022;Trakoshis et al 2020;Molina et al 2020), or to uncover the neural circuit basis of some key brain processes such as development (Chini, Pfeffer, and Hanganu-Opatz 2022;Schaworonkow and Voytek 2021) or aging (Tran et al 2020;Voytek et al 2015). Some of these novel E/I markers are aperiodic 1/f signal (Trakoshis et al 2020;Gao, Peterson, and Voytek 2017), neuronal avalanches (Varley et al 2020;Lombardi, Herrmann, and de Arcangelis 2017), long-range temporal correlations (LRTC) (Bruining et al 2020), neural entropy (Yang et al 2012;Shew et al 2011) and microstates (Fingelkurts et al 2004).…”

“…For these reasons, current MRS approaches have limited utility for tracking variations of E/I across cortical regions or behavioural states. Recently, a range of novel features derived from electroencephalography (EEG) and magnetoencephalography (MEG) recordings have been described as robust proxy makers for noninvasive real-time measurements of changes in E/I balance (Ahmad et al 2022;Manyukhina et al 2022;Pablo Martínez-Cañada, Noei, and Panzeri 2021;Molina et al 2020;Gao, Peterson, and Voytek 2017). One of the most promising candidate E/I biomarkers is the exponent of the 1/f spectral power law, often referred to in the literature as the '1/f slope'.…”

“…One of the most promising candidate E/I biomarkers is the exponent of the 1/f spectral power law, often referred to in the literature as the '1/f slope'. Converging evidence from neuroimaging, pharmacological, chemogenetic and computational modelling studies has linked changes in this marker to conditions related to altered E/I balance (Pani, Saba, and Fraschini 2022), such as autism (Manyukhina et al 2022;Trakoshis et al 2020), schizophrenia (Molina et al 2020), epilepsy (van Heumen et al 2021Pani et al 2021) and attentiondeficit/hyperactivity disorder (Karalunas et al 2022;Robertson et al 2019). The 1/f slope has been additionally shown to exhibit strong changes both across healthy aging (Tran et al 2020;Voytek et al 2015) and during early development (Chini, Pfeffer, and Hanganu-Opatz 2022;Schaworonkow and Voytek 2021), which have been associated to alterations in the relative E/I ratio.…”

Unveiling age-independent spectral markers of propofol-induced loss of consciousness by decomposing the electroencephalographic spectrum into its periodic and aperiodic components

“…Long considered as noise, aperiodic activity delivers information about cerebral activity states with clinical correlates. Changes in aperiodic activity have been described in physiological processes like sleep ( Lendner et al, 2020 ) and ageing ( Voytek et al, 2015 ) but also in neurological ( Lanzone et al, 2022 ; Zhang et al, 2022 ) and psychiatric disorders ( Arnett et al, 2022 ; Manyukhina et al, 2022 ). Aperiodic parametrization has been undertaken in non-geriatric patients under general anesthesia: propofol-induced unconsciousness engenders an increase in the aperiodic activity ( Brake et al, 2021 ).…”