Synopsis

Intra-individual variability of processing speed (IIV-PS) is a more sensitive discriminator between controls and MS patients in early disease stage than the normative mean scores of PS. We used rsfMRI to interrogate the neural correlates of IIV-PS and means of PS in MS patients with young-adult onset. Significant correlation of the amplitude of low-frequency fluctuations (ALFF) was found with IIV-PS but not with mean PS. Seed-to-voxel functional connectivity analysis showed significant connections associated with altered IIV of identification task, but not the IIV of detection task. This approach identified the neural networks associated with altered IIV-PS in MS.

Introduction

Processing speed (PS) is a consistent and sensitive marker of neurocognitive deficits in multiple sclerosis (MS) patients. However, mean PS is not an effective discriminator between controls and MS patients in the early stage of the disease ¹. Intra-individual variability (IIV) of PS – a measure of variability within an individual subject’s PS across multiple trials of a specific task – has been suggested to be a more sensitive discriminator between controls and MS patients in early stages of the disease compared to the mean scores².

Amplitude of low-frequency fluctuations (ALFF) and seed-based rsfMRI functional connectivity (FC) are known to be altered in many degenerative diseases such as Alzheimer’s disease³ and MS⁴. rsfMRI analysis of IIV has not been studied to our knowledge. The goal of this study was to use rsfMRI to interrogate the neural correlates of IIV-PS in MS patients with young adult onset, a less common MS population.

Methods

Studies were performed on 22 relapsing-remitting MS patients (26.4±5.5yo, age of onset 20-25), along with 23 age- and gender-matched healthy controls (22.2±2.6yo). Reaction times were measured using the CogState brief battery (https://www.cogstate.com/) on two tasks: Detection (DET, simple reaction time) and Identification (IDN, choice reaction time). IIV was then calculated for all study participants as an individual standard deviation of subjects’ scores.

fMRI analysis was carried out using the CONN toolbox. Preprocessing included motion and slice-timing correction, outlier removal, segmentation, normalization and smoothing using a 6mm Gaussian kernel. Denoising of smoothed data included linear detrending, band pass (0.01-0.1 Hz) and regression of motion parameters as nuisance variables. ALFF was calculated for all voxels and correlated with normative mean and IIV scores. Significantly correlated voxel clusters were then used in the seed-to-voxel FC analysis.

Results

Table 1 and Figure 1 show the ALFF correlation with mean (normative) and IIV PS. No significant clusters were observed when mean measures of PS were correlated with ALFF. Significant clusters were observed in the bilateral superior frontal gyrus (SFG) when DET-IIV was correlated with ALFF, and in the precuneus cortex and right postcentral gyrus (postCG) when IDN-IIV was correlated with ALFF.

Using SFG, precuneus and PostCG as seeds, connectivity with voxels in the brain were computed. Resulting connectivity strengths were then correlated with the corresponding IIV scores. Table 2 and Figure 2 show the correlation between FC strengths and IIV. No significant correlation was found with DET-IIV and FC when SFG was used as the seed. When precuneus (associated with IDN-IIV) was used as a seed, FC to the bilateral cuneal cortices, left lingual gyrus and bilateral post central gyrus were significantly correlated with IDN-IIV. When postCG (associated with IND-IIV) was used as the seed, FC to the right precentral gyrus, right superior parietal lobule and right anterior supramarginal gyrus were significantly correlated with IDN-IIV.

Discussion

Three brain regions showed significant positive ALFF correlation with IIV-PS: SFG bilaterally, the right postCG, and the precuneus. SFG is thought to play a role in working memory⁵. Ventral precuneus is part of the default mode network and plays an important role in shifting attention between objects and targets⁶. PostCG is the primary somatosensory cortex, responsible for processing tactile stimuli.

Of these 3 brain regions, only the latter two showed correlations between IDN-IIV and FC to other brain regions. These brain regions are involved in high-order visuomotor and executive functions, relevant to the identification tasks that MS patients exhibited deficits. FC with the precuneus and several neighboring regions including the postCG and superior parietal lobule significantly correlated with IDN-IIV. The precuneus cortex is involved in a wide range of cognitive processes, with its dorsal part functionally connected to pre and postcentral gyri, and ventral part connected to SFG⁷.

It has been suggested that in early stages of neural dysfunction in MS, increased recruitment of cognitive control areas occurs as a compensation mechanism to preserve cognitive function^8,9. ALFF and FC correlations with poorer cognitive performance (high IIV) could be indicative of such compensation. rsfMRI association only with IIV but not mean PS suggests that IIV may be more sensitive to such functional compensation.

Conclusion

Acknowledgements

References

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