Yuranny Cabral-Calderin -  Auditory Neuroscience
Freie Universität Berlin

Rhythmic structure is a central feature of natural sounds. In this talk, I use controlled experimental paradigms to examine how temporal regularity relates to auditory perception, neural activity, and physiology, before extending this approach to vocal production.

I first present studies using near-threshold gap detection in frequency-modulated sounds. EEG recordings show that auditory detection varies with low-frequency neural phase and alpha amplitude. Experiments combining these sounds with transcranial alternating current stimulation show that electrical stimulation can modulate sound-driven behavioural entrainment, although the effects vary across individuals and depend partly on properties of the induced electric field. When auditory and electrical rhythms compete, however, the auditory stimulus remains the stronger influence on behaviour.

I then present findings from simultaneous MEG, respiration, and ECG recordings. Rhythmic sounds facilitate near-threshold detection and produce reliable cortical phase locking, while respiration also aligns with stimulus onset. However, the strength of neural or respiratory alignment does not predict whether a target is detected.

Finally, I move from auditory perception to vocal production by comparing neutral speech with screamed words. Scream preparation is associated with stronger respiratory adjustments and differences in neural activity, including greater alpha suppression. Together, EEG and respiratory features distinguish the upcoming type of vocalization with over 80% accuracy.

Taken together, these studies examine how external, neural, and physiological rhythms relate to auditory perception and vocal preparation, while showing that measurable synchronization does not necessarily predict behaviour 

Omid Abbasi

University of Münster & Virgobit GmbH

Remote, high-frequency monitoring is reshaping how we study brain and behavior beyond the laboratory, yet turning heterogeneous wearable signals into time-synchronized, analysis-ready datasets remains a practical bottleneck. I will present Spica, a remote monitoring platform for continuous, multimodal data collection in real-world environments. Spica integrates three components: (1) a flexible ecosystem of wearable devices — mobile EEG, ECG belts, cardiowatches, activity and smart-ring trackers, motion sensors, and continuous glucose monitoring — enabling simultaneous, time-synchronized recording of EEG, ECG/HRV, accelerometry, sleep, and activity; (2) a mobile app for scheduled ecological momentary assessment of affect, symptoms, and context; and (3) a suite of gamified cognitive-behavioral tasks that extract quantitative markers from smartphone interactions. The platform is currently deployed across multiple clinical centers — within CRC/TRR 393 (affective disorders; Marburg, Münster, Dresden) and TRR 295 (Parkinson's disease; Charité and Düsseldorf University Hospital) — supporting longitudinal recording over weeks to months with systematic logging of adherence, data loss, and technical issues. Using these deployments as concrete examples, I will discuss what it takes to run robust multimodal "brains-in-the-wild" studies, from sensor synchronization and patient engagement to handling data quality under real-world conditions.