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Leandro R. D. Sanz

3 papers in the library · 142 citations · publishing 2021-2024

Papers

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning

Nature Communications February 25, 2022 Minji Lee, Leandro R. D. Sanz, Alice Barra et al. 120 citations

A deep-learning-based explainable consciousness indicator (ECI) uses EEG responses to transcranial magnetic stimulation and resting-state EEG to separately quantify arousal and awareness. Tested during sleep (n=6), general anesthesia (n=16), and severe brain injury (n=34), ECI distinguishes states such as ketamine-induced anesthesia and rapid eye movement sleep, which combine low arousal with high awareness. Parietal brain regions are most relevant for these measurements. The indicator offers a way to disentangle the two components of consciousness across physiological, pharmacological, and pathological conditions.

Mapping the functional brain state of a world champion freediver in static dry apnea

Brain Structure and Function January 1, 2021 Jitka Annen, Rajanikant Panda, Charlotte Martial et al. 15 citations

A world champion free diver's brain activity and connectivity shift markedly during a 6.5-minute breath-hold. EEG shows increased alpha wave power and connectivity, with decreased delta band connectivity. fMRI reveals heightened connectivity within the default mode network and visual areas, but reduced connectivity in sensorimotor cortices. These changes overlap with some meditation-related brain signatures but also include unique features suggesting altered somatosensory integration. Self-reports indicate that elite free divers may achieve a state of sensory dissociation during prolonged apnea, reflecting their ability to adapt psychologically and physiologically to extreme breath-holding.

Phenomenology of auto-induced cognitive trance using text mining: a prospective and exploratory group study.

Neuroscience of Consciousness January 1, 2024 Audrey Vanhaudenhuyse, Marie-Carmen Castillo, Charlotte Martial et al. 7 citations

Auto-induced cognitive trance (AICT) produces richer and more distinct subjective experiences than ordinary rest, auditory stimulation, or imagination. In 27 trained participants, free recalls of experiences were longer during AICT than in other conditions. Text mining identified four distinct classes of discourse, with AICT forming its own class clearly separate from ordinary conscious states. Nine content categories emerged, including nature, animals, body modifications, and difficulty describing thoughts. AICT was specifically characterized by reports of nature, animals, body modifications, and difficulty describing thoughts. These findings indicate that AICT generates a unique and richer phenomenology compared to other conscious states.