Characterizing hemodynamic response alterations during basketball dribbling

Abstract

Knowledge on neural processing during complex non-stationary motion sequences of sportspecific movements still remains elusive. Hence, we aimed at investigating hemodynamic response alterations during a basketball slalom dribbling task (BSDT) using multi-distance functional near-infrared spectroscopy (fNIRS) in 23 participants (12 females). Additionally, we quantified how the brain adapts its processing as a function of altered hand use (dominant right hand (DH) vs. non-dominant left hand (NDH) vs. alternating hands (AH)) and pace of execution (slow vs. fast) in BSDT. We found that BSDT activated bilateral premotor cortex (PMC), supplementary motor cortex (SMA), primary motor cortex (M1) as well as inferior parietal cortex and somatosensory association cortex. Slow dominant hand dribbling (DH slow) evoked lower contralateral hemodynamic responses in sensorimotor regions compared to fast dribbling (DH fast). Furthermore, during DH slow dribbling, we found lower hemodynamic responses in ipsilateral M1 as compared to dribbling with alternating hands (AH slow). Hence, altered task complexity during BSDT induced differential hemodynamic response patterns. Furthermore, a correlation analysis revealed that lower levels of perceived task complexity are associated with lower hemodynamic responses in ipsilateral PMC-SMA, which is an indicator for neuronal efficiency in participants with better basketball dribbling skills. The present study extends previous findings by showing that varying levels of task complexity are reflected by specific hemodynamic response alterations even during sports-relevant motor behavior. Taken together, we suggest that quantifying brain activation during complex movements is a prerequisite for assessing brain-behavior relations and optimizing motor performance.

Sensorimotor cortex activity during basketball dribbling and its relation to creativity

“…The fact that there was no significant hemispheric difference in activation in the NDH group, reflects the comparably high spread of activation in the LH and the RH, meaning that there was no significant shift in activation towards the RH in the NDH group. It was shown in previous studies, that higher complexity of a motor task [ 32 , 57 – 59 ] results in higher bilateral cortical activation intensity. Carius et al [ 32 ] showed that different levels of task complexity of a basketball dribbling task induce altering hemodynamic response patterns, and that a higher level of perceived difficulty is associated with higher hemodynamic response in ipsilateral sensorimotor regions.…”

“…It was shown in previous studies, that higher complexity of a motor task [ 32 , 57 – 59 ] results in higher bilateral cortical activation intensity. Carius et al [ 32 ] showed that different levels of task complexity of a basketball dribbling task induce altering hemodynamic response patterns, and that a higher level of perceived difficulty is associated with higher hemodynamic response in ipsilateral sensorimotor regions. The results of Verstynen et al [ 57 ] and Haaland et al [ 58 ] reveal that ipsilateral SMC activation during left-hand movement is stronger during the execution of a more complex motor task, relative to a more simple motor task and Alahmadi et al [ 59 ] found that higher complexity of a hand-gripping task resulted in stronger involvement of the left hemisphere.…”

“…Furthermore, fNIRS yields better spatial resolution than EEG and better temporal resolution than fMRI, as well as the possibility to measure both oxy-Hb and deoxy-Hb simultaneously [ 31 ]. Carius et al [ 32 ] already demonstrated the use of fNIRS to record sensorimotor activity simultaneously to basketball dribbling. Furthermore, our group previously investigated the signal quality of a subset of the present study’s data and found that good contrast-to-noise ratio of the fNIRS signal was achieved during basketball dribbling [ 33 ].…”

Multimodal assessment of the spatial correspondence between fNIRS and fMRI hemodynamic responses in motor tasks

“…The hemodynamic response function (HRF) was modeled using a consecutive sequence of Gaussian functions, each with a standard deviation of 1.0 s and temporally spaced 1.0 s apart, as done by Yücel 32 . For each source-detector pair, the influence of systemic physiology and extracerebral contaminations from superficial layers were mitigated by performing short separation regression (SSR) 32 using as a regressor the data from the most correlated short channel 33 . The beta values (weight of regressors) were obtained using ordinary least squares fit.…”

“…For each source-detector pair, the influence of systemic physiology and extracerebral contaminations from superficial layers were mitigated by performing short separation regression (SSR) 32 using as a regressor the data from the most correlated short channel 33 . The beta values (weight of regressors) were obtained using ordinary least squares fit.…”