Cortical functional connectivity related to endurance cycling performance: a single subject study

Aim: Brain cortical activity may change in relation to exercise preference, mode, and intensity during cycling. We aimed at verifying whether specific cortical functional connectivity patterns underlieassociative and dissociative attention-based strategies as derived from the multi-action plan (MAP) model, and demonstrated by other psychophysiological measures. Method: A 26-year-old cyclist participated in the study, organized in five visits. First visit: the participant performed an incremental test to determine his anaerobic threshold (AT) and individual optimal pedaling rate (IOPR). Second visit: the estimated AT and IOPR were verified and a reference EEG (32-channel system by ANT) acquired during a time-to-exhaustion test. Last three visits: the participant performed a time-to-exhaustion test at IOPR with a workload defined as AT +5 %, during which EEG was recorded; a series of manipulation check questions verified adherence to the protocol; three different attentional strategies were randomly implemented, with the participant’s attentional focus directed to either: (1) a metronome reproducing his IOPR (dissociative strategy) to try to induce a type 1 performance state, (2) his IOPR (associative strategy on the core component of action) to elicit a type 2 performance condition, (3) feelings of muscular fatigue (associative strategy on internal feelings) theoretically related to a type 3 dysfunctional performance state. Results: Coherence analysis on EEG data was performed to detect functional connectivity patterns related to the different attentional strategies. Only coherence values [0.6 were retained. Coherence maps were calculated for the alpha (7.5–12.5 Hz) and beta (12.5–30 Hz) bands during the time to exhaustion test. The following cortico-cortical networks among the tested electrodes emerged from the data: Type 1 (a) = F3-O1; FC6-C4-CP2-P3; FC6-CP6-O2; FC6- FC2-FC1; FC6-P3; (b) = F8-FC6-C4-CP2-P3; FC6-FC1; FC6- F4;C3-O1; F3-O1; Type 2 (a) = C3-P4; CP6-F3-F7; (b) = no coherence; Type 3 (a) = Fz-Cz; C3-Pz; (b) = Fz-Cz;C3-Pz, CP6- O2. Conclusion: Our results suggest that specific functional connectivity patterns may be associated with different intervention strategies, and warrant further investigation. Noteworthy, the a coherence pattern for type 1 manipulation suggests that only a dissociative strategy engages functional connectivity across all brain areas. This result seems to confirm the notion that fronto-occipital and inter-frontal coherence in the a band discriminates among different brain functional states as related to particular arousal levels.