Neuralink Compression Challenge

"Compression is essential: N1 implant generates ~200Mbps of eletrode data (1024 electrodes @ 20kHz, 10b resolution) and can transmit ~1Mbps wirelessly.
So > 200x compression is needed.
Compression must run in real time (< 1ms) at low power (< 10mW, including radio)."

https://content.neuralink.com/compression-challenge/README.html

here search on arxiv about 'increase working memory using EEG neurofeedback' then on base of timeflux yaml generated json with modifications from science article

https://github.com/neuroidss/create_function_chat

Brain-JEPA: Brain Dynamics Foundation Model with Gradient Positioning and Spatiotemporal Masking

https://www.arxiv.org/abs/2409.19407

https://github.com/Eric-LRL/Brain-JEPA

Sculpting new visual categories into the human brain

https://doi.org/10.1073/pnas.2410445121

Друзья, рады поделиться отличной новостью! 🎉 Мы завершили важное исследование, посвящённое анализу сенсомоторного ритма с использованием перспективной технологии  магнитоэнцефалографии на основе сенсоров с оптической накачкой  (OPM-MEG), результаты уже доступны на платформе arXiv в статье Low count of optically pumped magnetometers furnishes a reliable real-time access to sensorimotor rhythm.

В работе мы рассмотрели реализацию интерфейса "мозг-компьютер" на основе моторного воображения и продемонстрировали потенциал OPM-сенсоров для управления внешними устройствами в реальном времени.

🔗 Ознакомиться с нашей статьёй можно здесь: https://doi.org/10.48550/arXiv.2412.18353

🧐 Подискутировать можно здесь:
https://www.alphaxiv.org/abs/2412.18353

📩 Будем рады вашим вопросам, комментариям и обсуждениям!

Спасибо, что следите за нашими проектами и поддерживаете нас! 🙌

Decoding semantics from natural speech using human intracranial EEG

https://doi.org/10.1101/2025.02.10.637051

Musical neurodynamics
DOI:10.1038/s41583-025-00915-4

https://doi.org/10.48550/arXiv.2508.10409

AnalogSeeker: An Open-source Foundation Language Model for Analog Circuit Design

In this paper, we propose AnalogSeeker, an effort toward an open-source foundation language model for analog circuit design, with the aim of integrating domain knowledge and giving design assistance. To overcome the scarcity of data in this field, we employ a corpus collection strategy based on the domain knowledge framework of analog circuits. High-quality, accessible textbooks across relevant subfields are systematically curated and cleaned into a textual domain corpus. To address the complexity of knowledge of analog circuits, we introduce a granular domain knowledge distillation method. Raw, unlabeled domain corpus is decomposed into typical, granular learning nodes, where a multi-agent framework distills implicit knowledge embedded in unstructured text into question-answer data pairs with detailed reasoning processes, yielding a fine-grained, learnable dataset for fine-tuning. To address the unexplored challenges in training analog circuit foundation models, we explore and share our training methods through both theoretical analysis and experimental validation. We finally establish a fine-tuning-centric training paradigm, customizing and implementing a neighborhood self-constrained supervised fine-tuning algorithm. This approach enhances training outcomes by constraining the perturbation magnitude between the model's output distributions before and after training. In practice, we train the Qwen2.5-32B-Instruct model to obtain AnalogSeeker, which achieves 85.04% accuracy on AMSBench-TQA, the analog circuit knowledge evaluation benchmark, with a 15.67% point improvement over the original model and is competitive with mainstream commercial models. Furthermore, AnalogSeeker also shows effectiveness in the downstream operational amplifier design task. AnalogSeeker is open-sourced at this https://huggingface.co/analogllm/analogseeker URL for research use.

https://doi.org/10.1101/2025.08.25.671937

40 Hz Audiovisual Stimulation Improves Sustained Attention and Related Brain Oscillations

Gamma oscillations (30-100 Hz) have long been theorized to play a key role in sensory processing and attention by coordinating neural firing across distributed neurons. Gamma oscillations can be generated internally by neural circuits during attention or exogenously by stimuli that turn on and off at gamma frequencies. However, it remains unknown if driving gamma activity via exogenous sensory stimulation affects attention. We tested the hypothesis that non-invasive audiovisual stimulation in the form of flashing lights and sounds (flicker) at 40 Hz improves attention in an attentional vigilance task and affects neural oscillations associated with attention. We recorded scalp EEG activity of healthy adults (n=62) during one hour of either 40 Hz audiovisual flicker, no flicker as control, or randomized flicker as sham stimulation, while subjects performed a psychomotor vigilance task. Participants exposed to 40 Hz flicker stimulation had better accuracy and faster reaction times than participants in the control groups. The 40 Hz group showed increased 40 Hz activity compared to the control groups in agreement with previous studies. Surprisingly, 40 Hz subjects had significantly lower delta power (2-4 Hz), which is associated with arousal, and higher functional connectivity in lower alpha (8-10 Hz), which is associated with attention processes. Furthermore, decreased delta power and increased lower alpha functional connectivity were correlated with better attention task performance. This study reveals how gamma audiovisual stimulation improves attention performance with potential implications for therapeutic interventions for attention disorders and cognitive enhancement.