TEMPO
TEMPO
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TEMporal Predictive brain under exercise-induced arOusal
TEMporal Predictive brain under exercise-induced arOusal
ABOUT THE PROJECT
ABOUT THE PROJECT
TEMPO addresses a fundamental question in cognitive neuroscience: how the human brain perceives and processes time in the millisecond-to-seconds range, a critical ability for sensorimotor control, learning and higher cognition. Despite extensive research, the neural and computational mechanisms of time perception remain elusive, largely because time perception lacks a dedicated sensory organ and is strongly influenced by internal physiological states such as arousal. TEMPO overcomes this challenge by conceptualizing arousal as a dynamic physiological state that continuously shapes cognitive processing and by framing time perception within the "predictive brain" framework, casting the brain as a Bayesian inference system that continuously generates and updates temporal predictions.
Combining exercise-induced arousal manipulation with advanced behavioral modeling and EEG.
Testing how fluctuations in physiological activation influence temporal predictions.
Identifying the EEG signatures that accompany arousal-driven changes in temporal prediction.
Uniting expertise in temporal processing and the physiology of arousal within CIMCYC.
Why now?
While the neural mechanisms of spatial processing are increasingly well characterized, how the brain processes time remains far less understood, despite being critical for behaviors requiring fine sensorimotor coordination such as dancing, athletic performance and music. Classic pacemaker models have inconsistently operationalized arousal, relying on emotional stimuli, pre/post-exercise comparisons or stress induction, leaving a fragmented understanding of how arousal interacts with temporal processing. At the same time, predictive coding has transformed how neuroscience understands perception, yet its application to timing remains limited.
What for?
Findings will advance current models of time perception and, more broadly, of brain function, while clarifying the dynamic interplay between physiological activation, prediction and cognition. Beyond basic science, results could inform applications in learning, decision making and performance under stress, with relevance for healthcare, sports and virtual reality, and may offer new insight into disorders involving temporal and cognitive dysfunction such as Parkinson's disease, schizophrenia and ADHD.
What's novel?
TEMPO formalizes time perception within a predictive framework while explicitly manipulating arousal as physiological activation rather than as a static or all-or-none phenomenon. It bridges two fields that are rarely integrated: Bayesian models of time perception and advanced arousal manipulations via exercise, combining computational modeling, behavioral testing and EEG to test how physiological states shape temporal prediction and its neural correlates.
Where?
The project is led by Mariagrazia Capizzi (Cognitive Neuroscience, HUM379) and Chiara Avancini (Human Brain and Cognition, HUM957) at CIMCYC María de Maeztu Unit of Excellence, University of Granada, with research team members Luis Ciria and Rodika Sokoliuk and international collaboration from Antonino Visalli (University of Modena and Reggio Emilia, Italy).
INTERDISCIPLINARY APPROACH
INTERDISCIPLINARY APPROACH
This project combines expertise in temporal processing, arousal physiology, computational modeling and neurophysiology to uncover how physiological states shape the brain's predictive mechanisms for time.
Temporal Processing
Design and implement the auditory temporal discrimination task within a Bayesian framework, characterizing the cognitive and neural markers of temporal prediction.
Arousal Physiology
Lead the physical activation protocols, including maximal effort testing and the individualization of low- and high-arousal cycling sessions, drawing on multimodal expertise combining behavioral, EEG and cardiovascular measures.
Computational Modeling
Apply hierarchical Bayesian learning models to formalize how participants adapt to volatile probabilistic contexts, providing trial-by-trial parameters that link behavior to neural activity.
Neurophysiology & Open Science
Oversee EEG data collection, preprocessing pipelines and connectivity analyses, together with the replicability, reproducibility and open-science protocols that underpin the project.
CONTACT
CONTACT
Mariagrazia Capizzi. E-mail: mgcapizzi@ugr.es
Chiara Avancini. E-mail: chiara.avancini@ugr.es
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