Khairiah Abdul Hamid

Effective connectivity between superior temporal gyrus and Heschl's gyrus during white noise listening: linear versus non-linear models.

Purpose: This fMRI study is about modelling the effective connectivity between Heschl’s gyrus (HG) and the superior temporal gyrus (STG) in human primary auditory cortices. Materials & methods: Ten healthy male participants were required to listen to white noise stimuli during functional magnetic resonance imaging (fMRI) scans. Statistical parametric mapping (SPM) was used to generate individual and group brain activation maps. For input region determination, two intrinsic connectivity models comprising bilateral HG and STG were constructed using dynamic causal modelling (DCM). The models were estimated and inferred using DCM while Bayesian Model Selection (BMS) for group studies was used for model comparison and selection. Based on the winning model, six linear and six non-linear causal models were derived and were again estimated, inferred, and compared to obtain a model that best represents the effective connectivity between HG and the STG, balancing accuracy and complexity. Results: Group results indicated significant asymmetrical activation (puncorr < 0.001) in bilateral HG and STG. Model comparison results showed strong evidence of STG as the input centre. The winning model is preferred by 6 out of 10 participants. The results were supported by BMS results for group studies with the expected posterior probability, r = 0.7830 and exceedance probability, ϕ = 0.9823. One-sample t-tests performed on connection values obtained from the winning model indicated that the valid connections for the winning model are the unidirectional parallel connections from STG to bilateral HG (p < 0.05). Subsequent model comparison between linear and non-linear models using BMS prefers non-linear connection (r = 0.9160, ϕ = 1.000) from which the connectivity between STG and the ipsi- and contralateral HG is gated by the activity in STG itself. Conclusion: We are able to demonstrate that the effective connectivity between HG and STG while listening to white noise for the respective participants can be explained by a non-linear dynamic causal model with the activity in STG influencing the STG-HG connectivity non-linearly.

Comparing Intrinsic Connectivity Models for the Primary Auditory Cortices

This fMRI study is about modeling the intrinsic connectivity between Heschl’ gyrus (HG) and superior temporal gyrus (STG) in human primary auditory cortices. Ten healthy male subjects participated and required to listen to white noise stimulus during the fMRI scans. Two intrinsic connectivity models comprising bilateral HG and STG were constructed using statistical parametric mapping (SPM) and dynamic causal modeling (DCM). Group Bayes factor (GBF), positive evidence ratio (PER) and Bayesian model selection (BMS) for group studies were used in model comparison. Group results indicated significant bilateral asymmetrical activation (puncorr < 0.001) in HG and STG. Comparison results showed strong evidence of Model 2 as the preferred model (STG as the input center) with GBF value of 5.77 × 1073 The model is preferred by 6 out of 10 subjects. The results were supported by BMS results for group studies. One‐sample t‐test on connection values obtained from Model 2 indicates unidirectional parallel connections f...

Modeling Brain Responses in an Arithmetic Working Memory Task

Functional magnetic resonance imaging (fMRI) was used to investigate brain responses due to arithmetic working memory. Nine healthy young male subjects were given simple addition and subtraction instructions in noise and in quiet. The general linear model (GLM) and random field theory (RFT) were implemented in modelling the activation. The results showed that addition and subtraction evoked bilateral activation in Heschl’s gyrus (HG), superior temporal gyrus (STG), inferior frontal gyrus (IFG), supramarginal gyrus (SG) and precentral gyrus (PCG). The HG, STG, SG and PCG activate higher number of voxels in noise as compared to in quiet for addition and subtraction except for IFG that showed otherwise. The percentage of signal change (PSC) in all areas is higher in quiet as compared to in noise. Surprisingly addition (not subtraction) exhibits stronger activation.