iiinova — where your digital self keeps evolving

Please read our paper to find out more! This work was co-led by @luakoenig.bsky.social and Thomas Baumgarten. Many thanks to our funders and collaborators! @nyulhneuro.bsky.social

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Directed influences in the dorsal auditory pathway (parietal->frontal) increased as the auditory sequence evolved, while directed influences across the rest of the brain generally decreased over time. This suggests that the dorsal aud pathway might play a special role in time-forward predictions.

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That is, we did not find a spatial and spectral segregation as postulated by the theory (namely, alpha/beta carries top-down prediction; gamma carries bottom-up PE). Prediction and PE-related neural signals overlapped spatially and occupied similar frequency bands.

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Using intracranial EEG, we identified neural signatures for history-dependent sequence processing, predictive content, and prediction error (PE). However, the neural signatures for prediction and PE did not follow certain predictions made by the predictive coding theory.

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Neural mechanisms of time-forward predictions for naturalistic auditory tone sequences - Nature Communications

New paper alert from our lab! nature.com/articles/s41... We used stimuli sequences following 1/f statistical patterns—an ubiquitous statistical structure in natural stimuli—to probe predictive processing in the human brain. How does the brain predict upcoming sensory inputs based on past inputs?

nature.com

A longstanding question is how the brain predicts complex, naturalistic sensory events and updates those predictions when expectations are violated. Using intracranial recordings, the authors show tha...

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Reposted by Biyu Jade He

Thomas Andrillon @thomasandrillon.bsky.social · 23/05/2026

Discover 40+ chapters on the science of consciousness: humans, babies, animals, artificial systems, etc! Experts from various disciplines and views came together under the lead of Umberto Olcese and Lucia Melloni A precious resource for anyone interested in #consciousness! www.horizon-minds.com

horizon-minds.com

Horizon Minds

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Reposted by Biyu Jade He

Ignacio Saez, PhD @ignaciosaezphd.bsky.social · 09/02/2026

💡The neural mechanisms behind "aha!" moments are revealed in @natcomms.nature.com. Bridging computational neuroscience and AI, this approach offers insights into learning in biological and artificial systems. Congrats to @biyuhe.bsky.social and team! Proud to be part of this work. Learn more 👇

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We hope you enjoy the paper! This was a multi-year team effort, co-led by @ayakahach.bsky.social , @jonathanshor.bsky.social , Chris Liu, and co-supervised by Eric Oermann and me. Many thanks to funding from NSF and W.M. Keck Foundation, and support by NYU Grossman School of Medicine!

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We evaluated the similarity between the prior information learnt by the ANN and the neural activity in the brain. IT shows the highest correspondence. Moreover, the strength of this ANN-informed learning signal in IT predicts the reliability of the learning effect for a given image in humans.

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Our novel DNN captures the magnitude of humans’ one-shot perceptual learning effect, has excellent trial-to-trial error alignment with humans, and the model’s internal features predict whether humans will successfully learn a particular image.

To elucidate potential computational mechanisms, we built a novel ANN to capture the one-shot perceptual learning phenomenon. This ANN combines top-down signaling with a transformer-based vision backbone. Top-down signaling conveys information accumulated from past experiences.

The invariance properties of the stored information match the invariance properties of neuronal coding in inferotemporal (IT) cortex. With iEEG, we asked which brain region has the earliest-onset activity changes before vs. after learning. IT cortex shows the earliest change.

In this study, we combined psychophysics in healthy human subjects, intracranial EEG (iEEG) in neurosurgical patients, and artificial neural networks (ANN) to tackle this question. With psychophysics, we asked what kind of information is stored in the knowledge encoded by the brain.

Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...

We previously showed that this dramatic one-shot learning ability does not require the hippocampus, the most famous brain structure for L&M. (www.pnas.org/doi/10.1073/...) There are widespread activity changes in the neocortex after learning. But where and how learning occurs was mysterious.

pnas.org

PNAS

We used a one-shot perceptual learning task inspired by the Dalmatian Dog picture. Degraded two-tone images are initially difficult to recognize but effortlessly recognized once the corresponding original picture is viewed. This learning effect is both fast and long-lasting in humans.

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“Aha” moments, flashes of insight, and one-shot perceptual learning are impressive feats of the human brain. With intertwined empirical and modeling investigation, this paper takes us a step closer to understanding this singular human capability and building it in machines.

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