Altered motor dynamics in type 1 diabetes modulate behavioral performance

Abstract

Type 1 diabetes (T1D) has been linked to alterations in both brain structure and function. However, the neural basis of the most commonly reported neuropsychological deficit in T1D, psychomotor speed, remains severely understudied. To begin to address this, the current study focuses on the neural dynamics underlying motor control using magnetoencephalographic (MEG) imaging. Briefly, 40 young adults with T1D who were clear of common comorbidities (e.g., vascular disease, retinopathy, etc.) and a demographically-matched group of 40 controls without T1D completed an arrow-based flanker movement task during MEG. The resulting signals were examined in the time-frequency domain and imaged using a beamforming approach, and then voxel time series were extracted from peak responses to evaluate the dynamics. The resulting time series were statistically examined for group and conditional effects using a rigorous permutation testing approach. Our primary hypothesis was that participants with T1D would have altered beta and gamma oscillatory dynamics within the primary motor cortex during movement, and that these alterations would reflect compensatory processing to maintain adequate performance. Our results indicated that the group with T1D had a significantly stronger post-movement beta rebound (PMBR) contralateral to movement compared to controls, and a smaller neural flanker effect (i.e., difference in neural activity between conditions). In addition, a significant group-by-condition interaction was observed in the ipsilateral beta event-related desynchronization (bERD) and the ipsilateral PMBR. We also examined the relationship between oscillatory motor response amplitude and reaction time, finding a differential effect of the driving oscillatory responses on behavioral performance by group. Overall, our findings suggest compensatory activity in the motor cortices is detectable early in the disease in a relatively healthy sample of adults with T1D. Future studies are needed to examine how these subtle effects on neural activity in young, otherwise healthy patients affect outcomes in aging.

Type 1 diabetes affects the brain functional connectivity underlying working memory processing

“…Our behavioral results confirm that despite adequate clinical development of T1D, several cognitive processes are progressively affected by this disease, as revealed by the tendency toward a deterioration in the behavioral performance of T1D patients (e.g., Embury et al, 2019;Gallardo-Moreno et al, 2015;González-Garrido et al, 2019). Brands et al (2005) reported that cognitive dysfunction in T1D patients is characterized by a slowing of mental speed.…”

The age-related trajectory of visual attention neural function is altered in adults living with HIV: A cross-sectional MEG study

“…Thus, increased gamma activity in HAND during reorienting may reflect a compensatory mechanism with increasing age, such that those with HAND recruit brain reserve networks in VAN cortices to a comparatively greater extent during high attentional demands. A large body of literature focuses on compensatory processes in older adults [ 68 , 120 , 121 ], as well as in pathological conditions like diabetes [ 122 , 123 ] and HIV [ 37 , 76 ], and/or a similar framework may be at play here. Our behavioral findings would certainly support such a conclusion.…”

Spontaneous beta power, motor-related beta power and cortical thickness in major depressive disorder with psychomotor disturbance

“…For the direct effect, patients with higher spontaneous beta power tend to have poorer psychomotor performance. For the indirect effect, patients with higher spontaneous beta power tend to have greater MRBD ( Heinrichs-Graham et al, 2018 , Heinrichs-Graham and Wilson, 2016 , Trevarrow et al, 2019 , Wilson et al, 2014 ), and greater MRBD predicts better psychomotor performance ( Babiloni et al, 2000 , Embury et al, 2019 , Heinrichs-Graham et al, 2020 , Trevarrow et al, 2022b , Van Hoornweder et al, 2022a , Van Hoornweder et al, 2022b ). The indirect effect partially offsets the negative effects of the direct effects.…”

“…Furthermore, we found that response time was related to MRBD in healthy people, while the correlation was impaired in MDD ( Jiang et al, 2019 ). Notably, studies from other groups have found that more pronounced MRBD predicted better task performance in individuals with ( Embury et al, 2019 , Trevarrow et al, 2022b ) or without pathological conditions ( Babiloni et al, 2000 , Heinrichs-Graham et al, 2020 , Van Hoornweder et al, 2022a , Van Hoornweder et al, 2022b ). However, some researchers observed no significant relationship between behavioural performance and MRBD ( Heinrichs-Graham et al, 2018 , Hübner et al, 2018 , Rossiter et al, 2014 , Schmiedt-Fehr et al, 2016 , Spooner et al, 2022 , Spooner et al, 2021 , Vallesi et al, 2010 ), while others claimed that higher MRBD was associated with worse performance ( Heinrichs-Graham and Wilson, 2016 , Johari and Behroozmand, 2020 , Kurz et al, 2020 , Xifra-Porxas et al, 2019 ).…”