Abstract
Coordinated excitatory- inhibitory (E-I) signalling is fundamental to efficient brain function. Alterations in E-I circuitry are hypothesised in multiple neurodevelopmental conditions which may explain symptom overlap between conditions. Within conditions however, the nature and extent of individual E-I differences are heterogeneous. Untangling this complexity is challenging because researchers are limited in the methods available that can capture E-I information in living humans. For example, the methods available such as Positron Emission Tomography (PET) and Proton Magnetic Resonance Spectroscopy [1H] MRS are expensive and/or invasive and cannot capture E-I signalling at fast timescales due to their poor temporal resolution.In contrast, electroencephalography (EEG) is a cheap, non-invasive method with a high temporal resolution that could offer a hugely valuable tool to study E-I. In Ahmad*, Ellis* et al. (2022), I identified several EEG metrics with potential as proxy markers of E-I signalling in humans. However, I also noted a gap between preclinical and clinical neuroscience. The underlying E-I neurobiology of candidate markers has largely been informed by animal studies without verifying that EEG recorded from the scalp in humans is sampling the same E-I processes. Therefore, the aim of this PhD was to address that gap by examining whether E-I signalling is indeed captured in candidate EEG markers in humans namely; beta power and the aperiodic 1/f exponent.
Furthermore, I identified some key obstacles to investigating the E-I mechanisms underpinning candidate markers (beta power and the aperiodic 1/f signal) in humans and provided solutions to these. First, both markers are captured in the EEG power spectral density (PSD), they co-exist and can confound one another. Therefore, I used spectral parameterisation to isolate each EEG PSD feature and examined their E-I mechanisms 3 separately. Second, E-I differences are predicted in multiple neuropsychiatric and neurodevelopmental conditions, such as autism. Yet, the E-I theory of autism has been inconsistently supported, possibly due to the limitations of current methods to capture dynamic E-I differences. Therefore, I investigated each marker, and their relationship to E-I signalling, in autistic and non-autistic people. Finally, direct and invasive techniques like optogenetic imaging are used to study E-I mechanisms in animals, but are not ethical in humans. Therefore, I investigated each marker and its relationship to E-I, non-invasively, using proton Magnetic Resonance Spectroscopy ([1H] MRS) E-I neurotransmitter concentrations and E-I pharmacological challenge with arbaclofen.
Starting with the aperiodic 1/f exponent. I observed that this is related to [1H] MRS Glx/ GABA+ concentrations (chapter 3 and 5). This relationship was the same for autistic and non-autistic people with on average no between-group difference in aperiodic exponents at baseline. However, E-I signalling is dynamic, and potential differences in E-I in autistic people may be masked by assessing average measures at baseline which do not tell us about differences in E-I ‘responsivity’ or homeostatic regulation (see Ellis*, Ahmad*, in prep). To probe E-I responsivity, I administered an E-I pharmacological challenge with arbaclofen, a GABAB receptor agonist, and evaluated whether any between-group differences in E-I responsivity differentially shift the aperiodic 1/f exponent. I discovered, for the first time in humans, that, across groups, aperiodic exponents increased in response to a high dose of arbaclofen (chapter 4 and 6). However, in response to a low dose of arbaclofen, there was a group by drug interaction where aperiodic exponents increased in the autistic individuals but decreased or did not change in non-autistic people (chapter 6).
Next, I examined how E-I signalling might be captured with beta power. Since, I found that arbaclofen alters aperiodic power it was important to control for this effect in the analyses. At baseline (chapter 7), I found that beta power was higher in autistic than non-4 autistic participants. Furthermore, there was a positive relationship between beta power-GABA+ in neurotypical people but this relationship was significantly different (negative) in autistic people. This may indicate that GABAergic activity modulates beta power differently in autistic and non-autistic people- but correlations provide limited explanatory evidence.
To directly test this hypothesis, I examined how beta power behaves when GABAergic activity is enhanced by GABAB receptor activation with arbaclofen (chapter 8). However, in contrast to prior study results, I observed no drug effects on beta power. The relationship between beta power and bulk measures of GABA as measured by spectroscopy does not appear to reflect a (GABAergic) dynamic relationship as previously assumed. Moreover, the failure of previous studies to control for co-occurring aperiodic power in their beta power measures is an important methodological flaw and spectral parameterisation is a necessary step to avoid methodological artifacts in EEG biomarker research.
In conclusion, the work described in this thesis demonstrates that the aperiodic 1/f exponent is a readily quantifiable metric; is robust to measurement error; relates to bulk [1H] MRS metrics of E-I; and is capable of revealing dynamic differences in E-I in neurodiverse cohorts (comprising autistic and non-autistic people). These discoveries provide a solid platform for the future use of this metric. The drug challenge design has also proven useful to extend our understanding of how E-I differences contribute toward neurodiversity. Finally, they may also help assess target engagement by candidate E-I based interventions at the level of the individual, paving the way for individualised pharmacological support options for those autistic people who would like that choice.
| Date of Award | 1 Oct 2023 |
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| Original language | English |
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| Supervisor | Declan Murphy (Supervisor), Jumana Ahmad (Supervisor) & Grainne McAlonan (Supervisor) |