ECSS Paris 2023: OP-BM02
INTRODUCTION: Emotions significantly influence sports performance via modulation of motor control. A previous study indicated that negative autobiographical memories increase corticospinal excitability (CSE), which plays a crucial role in motor control [1]. However, we need to deal with various emotions, such as happiness, sadness, fear, and anger. Therefore, it is essential to explore the effect of discrete emotions for a better understanding of the relationship between emotions and motor control. Furthermore, it may provide valuable insight into improving responsiveness to various situations during sports performance by identifying the muscles in which CSE is likely to be modulated by emotions. Thus, this study aimed to investigate: (1) the modulation of CSE by discrete autobiographical emotional memories and (2) the muscle-specificity of CSE modulation in response to emotions. METHODS: Sixteen healthy individuals (22–30 years old) participated in this study. Participants were seated on a chair. Electromyographic activity was recorded from the flexor carpi radialis (FCR), extensor carpi radialis (ECR), first dorsal interosseous (FDI), and abductor pollicis brevis (APB) muscles. CSE was evaluated by motor-evoked potential (MEP) amplitudes which were elicited by transcranial magnetic stimulation (TMS) to the primary motor cortex. Initially, participants were asked to write down situations in which they had experienced happiness, sadness, fear, and anger. For the neutral condition, participants were asked to describe their typical morning routine. We recorded 12 MEPs as they recalled the written situations for each emotion. MEP amplitudes during the recall of happiness, sadness, fear, and anger were normalized to the MEP amplitudes in the neutral condition. A statistical analysis was conducted using a two-way analysis of variance (ANOVA) with aligned rank transform. The ANOVA included two factors: 4 muscles and 5 emotions. Contrast tests were used as subsequent post-hoc tests. The level of significance was set to p < 0.05. RESULTS: The two-way ANOVA showed a significant main effect for emotions (p = 0.004), but not for muscles (p = 0.183) and the interaction between muscles and emotions (p = 0.502). Subsequent post-hoc tests on emotions showed that the fear emotion significantly increased MEP amplitudes more than the neutral condition (p = 0.001, + 39.3%). On the other hand, there were no significant differences between any of the other emotions (p > 0.05). CONCLUSION: Our results indicated that although no significant difference in MEP amplitudes was found between upper-limb muscles, the recall of autobiographical fear memories significantly increased MEP amplitudes. These suggest that the fear memories facilitate CSE and that this facilitation is non-specific to upper-limb muscles. Our finding enhances our comprehension of the interplay between emotions and motor control. REFERENCE: 1. Mineo et al., Neuropsychologia, 2018.
Read CV Yume MashikiECSS Paris 2023: OP-BM02
Although highly automated, human gait is dependent on cortical resources and can be observed in spectral features such as sustained beta band (18-30Hz) desynchronization and gait-phase dependent modulation in the low gamma-band (24–40 Hz) recorded over central sensorimotor cortices. Contrary, Parkinson’s disease (PD) is characterized by beta-band hypersynchrony which is positively associated with the symptoms of bradykinesia. However, this cortical phenomenon has never been noninvasively investigated in ecologically valid conditions during unrestricted overground walking and concurrent performance of a cognitive task. This study aimed to elucidate the mechanisms subserving full-body movement execution in conditions where attentional resources are simultaneously allocated to both cognitive and motor tasks mimicking real-life scenarios in PD patients. Sixteen early on-medication PD patients (aged M = 62.75 ± 5.9 years; 8 women) and 16 healthy controls (HC; aged M = 64.1 ± 6.5 years; 8 women) performed a self-paced overground walking task in a wide (80 cm) and narrow (40 cm) lanes both as single-task conditions (STwide, STnarrow) and with a secondary visual discrimination task as dual-task conditions (DTwide, DTnarrow). A mobile 128-channel EEG and full-body kinematics were recorded to compute gait-phase-dependent spectral modulation at the Cz electrode. Nonparametric cluster-based permutation testing correcting for multiple comparisons across all time-frequency space was used (1000 iteration, α≤.05). We observed faster walking speed for HC versus PD patients (F(1, 30)=8.10, p=.008) and for ST as opposed to DT conditions (F(1, 30)=41.61, p<.001). No significantly different clusters of cortical signatures would discriminate PD patients and HC or wide and narrow lane walking conditions. However, PD patients demonstrated greater synchronization in the beta and low gamma activity in both DT conditions compared to their respective ST variants. The differences were observed in the phase of gait following the heel strikes indicating preparation for shifting the weight to a single leg. The effect was more pronounced in the narrow walk conditions. The PD patients exhibit similar cortical signatures to HC during overground walking but seem to become prone to the cortical signature related to movement inefficiency upon performing cognitive-motor dual-tasking. In PD patients but not HC a secondary cognitive task evoked a gait-phase-locked synchronization in the high spectral frequencies, which could suggest the limited availability of cognitive resources at that particular time during the gait phase while the attention had to be continuously divided between the two tasks. These results indicate that movement execution in PD could be impeded by increasing the load on the cognitive systems. These outcomes provide valuable insights into mechanisms of simple real-life cognitive-motor dual-tasking in PD and can inform intervention and fall prevention strategies.
Read CV Manca PeskarECSS Paris 2023: OP-BM02
INTRODUCTION: Torque complexity (the torque signal’s nonlinear temporal and spatial structure) is indicative of the neuromuscular system’s ability to meet the imposed motor task, and knee extensor (KE) torque complexity has been shown to decline with fatigue (1). However, the mechanisms underlying the fatigue-induced changes in complexity are yet to be fully elucidated. It has previously been demonstrated that common synaptic inputs to the motoneuron pool, estimated by intra-muscle coherence, largely determine the structure of oscillations in the torque signal (2). This study investigated whether the proportion of common synaptic input to the vastus lateralis muscle (VL) could explain the effect of fatigue on KE torque complexity. METHODS: Fifty-seven participants completed three fresh 20 s isometric KE contractions at 20% MVC, followed by a series of repeated 3 s isometric KE contractions at 60% MVC to task failure. Immediately after failure a 20 s isometric KE contraction at 20% MVC was performed. High-density surface EMG signals were recorded from the VL during all 20% MVCs and decomposed into individual motor unit (MU) spike trains. Thirty-seven participants provided enough MUs (>6) during all 20% MVCs for coherence analysis, as such only these participants data were analysed. Intra-muscle coherence was estimated from the MU data. KE torque variability and complexity was assessed using the coefficient of variation of torque (CVT) and multiscale sample entropy (MSE; across 28 coarse-grained scales) respectively. RESULTS: The MSE analysis revealed a condition (fresh vs. fatigue) by coarse-grained scale interaction (i.e., a MSE curve cross-over; P<0.001); the fatigued 20% MVCs presented with a significantly lower sample entropy (SampEn; P<0.05) at shorter scales (<7 scales) but a significantly higher SampEn (P<0.05) at longer scales (>13 scales) when compared to the fresh 20% MVCs. Alpha coherence (5-15Hz) was significantly higher after task failure (P=0.001; fresh=1.30±0.09 vs. fatigued=1.43±0.22). The difference in Alpha coherence from fresh to fatigue was predictive of the difference in SampEn at scales 10 to 28 (all P<0.05; R2=0.11-0.19). Alpha coherence was also predictive of SampEn calculated at coarse-grained scales 7 to 28 during fresh (all P<0.05; r=0.34-0.60; R2=0.12-0.36) and fatigued (all P<0.05; r=0.34-0.52; R2=0.11-0.27) 20% MVCs. Fatigue resulted in a significantly higher CVT (P<0.001). The increase in alpha coherence with fatigue was predictive of the decline in the CVT (P<0.001; r=0.56; R2=0.31). CONCLUSION: The MSE curve cross-over captures a fatigue-related change in torque regularity at the different scales, suggestive of an alteration in structure across the oscillatory frequencies present within the torque signal. Common synaptic input in the alpha band may be able to explain some of the fatigue-related alterations in the structure of lower-frequency oscillations of the KE torque signals. 1)Pethick et al. J Physiol 2015 2)Farina & Negro. Exerc Sport Sci Rev 2015
Read CV Christopher FennellECSS Paris 2023: OP-BM02