Keywords: Neurotransmission, Spectroscopy, Hurst Exponent, Excitatory-Inhibitory Balance, Brain Criticality
Motivation: Animal and computational studies have been used as a basis to assume a link between excitatory-inhibitory (E/I) ratio and Hurst exponent (H) in the human brain; however, it has yet to be sufficiently demonstrated in healthy human subjects.
Goal(s): We seek to test the E/I-Hurst link in the visual cortex during rest and movie-watching.
Approach: Multi-echo functional MRI, sLASER, and MEGAPRESS sequences are used in 17 healthy human adults (ages 21-53 years; 13 female, 4 male) with MRS voxel ROI in visual cortex.
Results: E/I and Hurst are not significantly correlated in either the MRS voxel ROI or visual network.
Impact: Hurst exponent (H) is assumed to correlated with excitatory-inhibitory (E/I) ratio without sufficient human evidence. Given the role of E/I imbalance in neuropsychiatric illness and the technical difficulty to measure it, understanding if H acts as its proxy is critical.
1. Rubenstein JLR, Merzenich MM. Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes Brain Behav. 2003;2(5):255-267.
2. He H Yan, Cline HT. What Is Excitation/Inhibition and How Is It Regulated? A Case of the Elephant and the Wisemen. J Exp Neurosci. 2019;13:1179069519859371. doi:10.1177/1179069519859371
3. Ajram LA, Pereira AC, Durieux AMS, Velthius HE, Petrinovic MM, McAlonan GM. The contribution of [1H] magnetic resonance spectroscopy to the study of excitation-inhibition in autism. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 2019;89:236-244. doi:10.1016/j.pnpbp.2018.09.010
4. Brix MK, Ersland L, Hugdahl K, et al. Brain MR spectroscopy in autism spectrum disorder—the GABA excitatory/inhibitory imbalance theory revisited. Frontiers in Human Neuroscience. 2015;9. Accessed January 10, 2023. https://www.frontiersin.org/articles/10.3389/fnhum.2015.00365
5. Canitano R, Pallagrosi M. Autism Spectrum Disorders and Schizophrenia Spectrum Disorders: Excitation/Inhibition Imbalance and Developmental Trajectories. Front Psychiatry. 2017;8:69. doi:10.3389/fpsyt.2017.00069
6. Maestú F, de Haan W, Busche MA, DeFelipe J. Neuronal excitation/inhibition imbalance: core element of a translational perspective on Alzheimer pathophysiology. Ageing Research Reviews. 2021;69:101372. doi:10.1016/j.arr.2021.101372
7. Harris AD, Puts NAJ, Edden RAE. Tissue correction for GABA-edited MRS: Considerations of voxel composition, tissue segmentation, and tissue relaxations. Journal of Magnetic Resonance Imaging. 2015;42(5):1431-1440. doi:10.1002/jmri.24903
8. Choi IY, Lee SP, Merkle H, Shen J. In vivo detection of gray and white matter differences in GABA concentration in the human brain. NeuroImage. 2006;33(1):85-93. doi:10.1016/j.neuroimage.2006.06.016
9. Gao R, Peterson EJ, Voytek B. Inferring synaptic excitation/inhibition balance from field potentials. NeuroImage. 2017;158:70-78. doi:10.1016/j.neuroimage.2017.06.078
10. Lombardi F, Herrmann HJ, de Arcangelis L. Balance of excitation and inhibition determines 1/f power spectrum in neuronal networks. Chaos: An Interdisciplinary Journal of Nonlinear Science. 2017;27(4):047402. doi:10.1063/1.4979043
11. Baumgarten L, Bornholdt S. Critical excitation-inhibition balance in dense neural networks. Phys Rev E. 2019;100(1):010301. doi:10.1103/PhysRevE.100.010301
12. Poil SS, Hardstone R, Mansvelder HD, Linkenkaer-Hansen K. Critical-State Dynamics of Avalanches and Oscillations Jointly Emerge from Balanced Excitation/Inhibition in Neuronal Networks. J Neurosci. 2012;32(29):9817-9823. doi:10.1523/JNEUROSCI.5990-11.2012
13. Deco G, Jirsa VK, McIntosh AR. Resting brains never rest: computational insights into potential cognitive architectures. Trends in Neurosciences. 2013;36(5):268-274. doi:10.1016/j.tins.2013.03.001
14. Bruining H, Hardstone R, Juarez-Martinez EL, et al. Measurement of excitation-inhibition ratio in autism spectrum disorder using critical brain dynamics. Sci Rep. 2020;10(1):9195. doi:10.1038/s41598-020-65500-4
15. Manyukhina VO, Prokofyev AO, Galuta IA, et al. Globally elevated excitation–inhibition ratio in children with autism spectrum disorder and below-average intelligence. Molecular Autism. 2022;13(1):20. doi:10.1186/s13229-022-00498-2
16. Trakoshis S, Martínez-Cañada P, Rocchi F, et al. Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women. eLife. 9:e55684. doi:10.7554/eLife.55684
17. Beggs J, Timme N. Being Critical of Criticality in the Brain. Frontiers in Physiology. 2012;3. Accessed May 3, 2023. https://www.frontiersin.org/articles/10.3389/fphys.2012.00163
18. Campbell O, Vanderwal T, Weber AM. Fractal-Based Analysis of fMRI BOLD Signal During Naturalistic Viewing Conditions. Frontiers in Physiology. 2022;12. Accessed August 31, 2023. https://www.frontiersin.org/articles/10.3389/fphys.2021.809943
19. Thomas Yeo BT, Krienen FM, Sepulcre J, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol. 2011;106(3):1125-1165. doi:10.1152/jn.00338.2011
20. Zou QH, Zhu CZ, Yang Y, et al. An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF. Journal of Neuroscience Methods. 2008;172(1):137-141. doi:10.1016/j.jneumeth.2008.04.012
21. Pasanta D, He JL, Ford T, Oeltzschner G, Lythgoe DJ, Puts NA. Functional MRS studies of GABA and glutamate/Glx – A systematic review and meta-analysis. Neuroscience & Biobehavioral Reviews. 2023;144:104940. doi:10.1016/j.neubiorev.2022.104940
22. Taylor PA, Gohel S, Di X, Walter M, Biswal BB. Functional Covariance Networks: Obtaining Resting-State Networks from Intersubject Variability. Brain Connect. 2012;2(4):203-217. doi:10.1089/brain.2012.0095