Maddalena Castelletti^1*, Enrico Bernè¹, Gloria Crocetti² and Larissa Meani³

¹Clinical Neuromodulation Department, Magenta Medical Center, Italy
²Neuropsychology Service, IPSE Clinical Center, Italy
³Apilombardia Association, Italy

*Corresponding Author: Maddalena Castelletti, Clinical Neuromodulation Depart- ment, Magenta Medical Center, Italy.

Received: July 20, 2026; Published: July 29, 2026

Abstract

 Goal-directed attention relies on distributed frontoparietal systems that support the selection and prioritization of behaviorally relevant information in complex and dynamic environments. Quantitative EEG (qEEG) provides a non-invasive method for investigating the electrophysiological correlates of cognitive processes, particularly through oscillatory dynamics associated with attentional allocation, cognitive control, and sensorimotor integration. However, its application to ecologically valid real-world behaviors remain limited. This pilot study investigated whether a structured period of beekeeping activity is associated with measurable changes in resting- state qEEG markers consistent with attentional network engagement. Fifty experienced beekeepers underwent resting-state EEG recordings before and after approximately one hour of active apicultural work involving hive inspection, colony monitoring, and environmental adaptation. EEG was recorded in eyes-closed conditions and analyzed using standard preprocessing pipelines including band-pass filtering, artifact rejection, and independent component analysis (ICA). Spectral analysis using Welch’s method revealed a significant reduction in posterior alpha power following beekeeping activity (p < 0.001), accompanied by increased frontal theta activity (p = 0.001) and a smaller increase in beta-band power (p = 0.019). These findings suggest that ecologically valid cognitive-motor engagement induces transient modulation of intrinsic oscillatory dynamics consistent with activation of attentional and cognitive control systems [1-4,6- 8].

Keywords: Beekeeping; Quantitative EEG; Dorsal Attention Network; Neuroergonomics; Alpha Oscillations; Theta Activity; Naturalistic Cognition; Attentional Control

References

1. Corbetta M and Shulman GL. “Control of goal-directed and stimulus-driven attention in the brain”. Nature Reviews Neuroscience 3 (2002): 201-215.
2. Corbetta M., et al. “The reorienting system of the human brain: from environment to theory of mind”. Neuron3 (2008): 306-324.
3. Vossel S., et al. “Dorsal and ventral attention systems: distinct neural circuits but collaborative roles”. Neuroscientist 2 (2014): 150-159.
4. Petersen SE and Posner MI. “The attention system of the human brain: 20 years after”. Annual Review of Neuroscience 35 (2012): 73-89.
5. Posner MI and Petersen SE. “The attention system of the human brain”. Annual Review of Neuroscience 13 (1990): 25-42.
6. Hanslmayr S., et al. “The role of alpha oscillations in temporal attention”. Brain Research Review 67 (2011): 331–343.
7. Foxe JJ and Snyder AC. “The role of alpha-band brain oscillations as a sensory suppression mechanism during selective attention”. Frontiers in Psychology 2 (2011): 154.
8. Van Diepen RM., et al. “The functional role of alpha-band activity in attentional processing: the current zeitgeist and future outlook”. Current Opinion in Psychology 29 (2019): 229-238.
9. Klimesch W. “Alpha-band oscillations, attention, and controlled access to stored information”. Trends in Cognitive Sciences 16 (2012): 606-617.
10. Keitel C., et al. “Stimulus-driven brain rhythms within the alpha band: the attentional-modulation conundrum”. Journal of Neuroscience 39 (2019): 3119–3129.
11. Mathewson KE., et al. “Pulsed out of awareness: EEG alpha oscillations represent a pulsed-inhibition of ongoing cortical processing”. Frontiers in Psychology 2 (2011): 99.
12. Paquola C., et al. “The architecture of the human default mode network explored through cytoarchitecture, wiring and signal flow”. Nature Neuroscience 28 (2025): 654-664.
13. Alves PN., et al. “L'organizzazione subcorticale e neurochimica delle reti ventrali e dorsali dell'attenzione”. Communication Biology 5 (2022): 1343.
14. Esposito R., et al. “Modifications in resting state functional anticorrelation between default mode network and dorsal attention network: comparison among young adults, healthy elders and mild cognitive impairment patients”. Brain Imaging Behavior1 (2018): 127-141.
15. Knyazev GG., et al. “Task-positive and task-negative networks and their relation to depression: EEG beamformer analysis”. Behavioural Brain Research 306 (2016): 160-169.
16. Menon V. “20 years of the default mode network: A review and synthesis”. Neuron 16 (2023): 2469-2487.
17. Barnett K and Vasiu F. “Enhanced functional connectivity between the default mode network and executive control network during flow states may facilitate creativity and emotional regulation, and may improve health outcomes”. Frontiers in Behavioral Neuroscience 19 (2026): 1690499.

Citation

Citation: Maddalena Castelletti., et al. “Resting-State qEEG Correlates of Attentional Network Engagement Following Beekeeping Activity: A Pilot Study". Acta Scientific Neurology 9.8 (2026): 10-19.

Copyright

Copyright: ©2026 Maddalena Castelletti., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.