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Examining Intrinsic Brain Variability and Neurotransmitter Balance in Adults with Dyslexia Using fMRI and MRS: Implications of the Neural Noise Hypothesis of Dyslexia
Poster Session C, Saturday, September 13, 11:00 am - 12:30 pm, Field House
This poster is part of the Sandbox Series.
Jie luo1, Zhichao Xia1, Nikki Arrington2, Brianna Kinnie1, Fumiko Hoeft1,3; 1Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States, 2Department of Psychology, Georgia State University, Atlanta, GA, United States, 3Department of Neuropsychiatry, Keio University, School of Medicine, Shinanomachi Shinjuku Tokyo, Tokyo, Japan
The Neural Noise Hypothesis (NNH) of dyslexia (Hancock, Pugh, & Hoeft, 2017) posits that their core deficits in phonological awareness (PA), grapheme-phoneme mapping, and multisensory integration may arise from imbalances in cortical excitation and inhibition (E/I), mediated by neurotransmitters such as gamma-aminobutyric acid (GABA) and glutamate. Such an imbalance can substantially elevate neural noise beyond levels optimal for cognition, thereby affecting brain variability. Recent electroencephalogram (EEG)–magnetic resonance spectroscopy (MRS) study (Glica et al., 2025) found that the Glu/GABA+ ratio (indictor of E/I balance) in the left superior temporal sulcus were associated with multisensory integration in dyslexia. However, as that study focused on a single region, it remains unclear whether other brain regions also contribute to E/I imbalance. At the microscale, neural noise can disrupt synchrony through E/I dysregulation, potentially manifest at the macroscale as abnormal brain variability–moment-to-moment fluctuations in neural activity detectable via functional magnetic resonance imaging (fMRI) (Garrett et al., 2013). Brain variability has theoretical foundations (e.g., stochastic resonance theory) explaining how optimal variability enhances neural communication. Once regarded as random noise, brain variability is now understood to reflect meaningful cognitive processes, and its implications in neurodevelopmental conditions such as autism spectrum disorder (ASD) (Uddin, 2020). Despite its relevance, brain variability has received little empirical attention in dyslexia particularly during resting states, and has mostly been studied using between-session brain variability (Malins et al., 2018). Building upon the NNH framework, this study presents a conceptual model integrating neurotransmitter balance and intrinsic brain variability to better understand dyslexia in adults, an often-overlooked population (Vender & Delfitto, 2025). We will examine within-session intra-regional brain variability during resting-state fMRI in young adults with reading disability (RD, aka specific reading disability or developmental dyslexia; N = 45) and typical readers (N = 45), classified via the Test of Word Reading Efficiency - Second Edition and Adult Reading History Questionnaire. Brain variability is assessed using validated metrics: standard deviation of BOLD (SDBOLD) and mean squared successive difference (MSSDBOLD) (Wehrheim et al., 2024). This study addresses two primary questions: (1) Do individuals with and without dyslexia differ in intra-regional brain variability? Whole-brain voxel-wise and reading-related region-of-interest (ROI) group comparisons will assess whether intrinsic brain variability distinguishes the groups, reflecting either domain-general disruptions (as seen in ASD) or dyslexia-specific mechanisms. We hypothesize group differences particularly in regions related to PA (e.g. temporal cortex), grapheme-phoneme mapping (temporoparietal cortex), and multisensory integration (e.g. temporal cortex and frontal lobe) . The Partial Least Squares (PLS) analysis will further identify specific regions where the brain variability correlates with reading-related skills, followed by an examination of spatial overlap with group-level differences. (2) How are neurotransmitter concentrations related to brain variability? Using MRS, we will measure GABA and glutamate concentrations in key reading-related regions (left/right temporoparietal cortex, left precentral gyrus) and a control region (vertex). We hypothesize that indicators of E/I balance— Glu/GABA+ imbalance and the Glu/GABA+ ratio in reading-relevant regions will correlate intra-regional brain variability, with no such associations expected in the control region.
Topic Areas: Disorders: Developmental, Reading