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#neuroscience

60 posts53 participants3 posts today
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Psychedelic Institute

jneurosci.org/content/early/20 Electrophysiological correlates of lucid dreaming: sensor and source level signatures (Demeril, et al, 2025) #consciousness #luciddreaming #psychedelic #psychedelics #lsd #sleep #neuroscience

Journal of Neuroscience · Electrophysiological correlates of lucid dreaming: sensor and source level signaturesLucid dreaming (LD) is a state of conscious awareness of the ongoing oneiric state, predominantly linked to REM sleep. Progress in understanding its neurobiological basis has been hindered by small sample sizes, diverse EEG setups, and artifacts like saccadic eye movements. To address these challenges in the characterization of the electrophysiological correlates of LD, we introduced an adaptive multi-stage preprocessing pipeline, applied to human data (male and female) pooled across laboratories, allowing us to explore sensor- and source-level markers of LD. We observed that, while sensor-level differences between LD and non-lucid REM sleep were minimal, mixed-frequency analysis revealed broad low-alpha to gamma power reductions during LD compared to wakefulness. Source-level analyses showed significant beta power (12-30 Hz) reductions in right central and parietal areas, including the temporo-parietal junction, during LD. Moreover, functional connectivity in the alpha band (8-12 Hz) increased during LD compared to non-lucid REM sleep. During initial LD eye signaling compared to baseline, source-level gamma1 power (30-36 Hz) increased in right temporo-occipital regions, including the right precuneus. Finally, functional connectivity analysis revealed increased inter-hemispheric and inter-regional gamma1 connectivity during LD, reflecting widespread network engagement. These results suggest that distinct source-level power and connectivity patterns characterize the dynamic neural processes underlying LD, including shifts in network communication and regional activation that may underlie the specific changes in perception, memory processing, self-awareness, and cognitive control. Taken together, these findings illuminate the electrophysiological correlates of LD, laying the groundwork for decoding the mechanisms of this intriguing state of consciousness. Significance statement Lucid dreaming (LD) is a unique state of oneiric awareness, where individuals recognize they are dreaming while still in the dream. LD neural correlates remain elusive, as it is very rare and difficult to reproduce in the laboratory. Using an advanced preprocessing pipeline, we harmonized diverse EEG datasets to analyze the largest LD sample to date. We observed gamma power increases in the precuneus during initial eye lucidity signaling, beta power reductions in parietal areas, including the temporo-parietal junction, and enhanced alpha and gamma connectivity during LD over non-lucid REM sleep. These findings shed light on how the brain generates self-referential awareness and volitional action even during sleep.
Public
Laurent Perrinet

Science can be lots of fun, especially when you design novel stimuli to challenge the visual system. Take a breath and get into the tunnel !

Here's an infinite tunnel where you move along the axis, with some perturbations to the center of your gaze with respect to the focus of expansion. It's serious though! Think of having to orient yourself with that optic flow and how difficult life may be without this feat!

Code : laurentperrinet.github.io/scib

GIF
#vision#neuroscience#opticflow
Public
Dan Goodman

How do babies and blind people learn to localise sound without labelled data? We propose that innate mechanisms can provide coarse-grained error signals to boostrap learning.

New preprint from @yang_chu.

arxiv.org/abs/2001.10605

Thread below 👇

arXiv logo
arXiv.orgLearning spatial hearing via innate mechanismsThe acoustic cues used by humans and other animals to localise sounds are subtle, and change during and after development. This means that we need to constantly relearn or recalibrate the auditory spatial map throughout our lifetimes. This is often thought of as a "supervised" learning process where a "teacher" (for example, a parent, or your visual system) tells you whether or not you guessed the location correctly, and you use this information to update your map. However, there is not always an obvious teacher (for example in babies or blind people). Using computational models, we showed that approximate feedback from a simple innate circuit, such as that can distinguish left from right (e.g. the auditory orienting response), is sufficient to learn an accurate full-range spatial auditory map. Moreover, using this mechanism in addition to supervised learning can more robustly maintain the adaptive neural representation. We find several possible neural mechanisms that could underlie this type of learning, and hypothesise that multiple mechanisms may be present and interact with each other. We conclude that when studying spatial hearing, we should not assume that the only source of learning is from the visual system or other supervisory signal. Further study of the proposed mechanisms could allow us to design better rehabilitation programmes to accelerate relearning/recalibration of spatial maps.
#neuroscience#computationalneuroscience#compneuro
Public
Dana Foundation

The Chicago Council on Science and Technology piloted event-based models to explore what brain health means to Chicago communities and to help bridge the disconnect between science and society.

Using a human-centered approach to engage and benefit local residents, the collaboration organized three in-person events focused on brain health.

Discover more about these events and this model.

#brainhealth #neurosociety #neuroscience #publicengagement

dana.org/article/a-community-b

Dana FoundationA Community-Based Approach to Science Outreach
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