Cerelog-X: A Real-Time EEG-Driven Affective Layer for Social Communication and Emotion-Conditioned Large Language Models on the X Platform

We present Cerelog-X, a conceptual end-to-end framework that integrates affordable, research-grade multi-channel electroencephalography (EEG) acquired via the Cerelog ESP-EEG biosensing board with the X (formerly Twitter) social platform and the Grok Large Language Model (Grok LLM). Real-time EEG signals carrying affective information are processed to estimate continuous valence-arousal or discrete emotional states. These states are temporally aligned with linguistic content generated by the user, enabling two simultaneous outcomes: (i) an animated facial avatar that provides the communication partner with a continuous visual representation of the sender’s emotional state, and (ii) the construction of paired language-emotion datasets that can be used to train or condition an additional behavioural layer in Grok. The architecture leverages BrainFlow and Lab Streaming Layer (LSL) for low-latency streaming, edge or near-edge emotion inference based on contemporary deep-learning models, and privacy-preserving opt-in data pipelines. Building on recent advances in EEG-based emotion recognition [1-5], multimodal affective computing with LLMs [6-9], and visual feedback in brain-computer interfaces (BCIs) [10-12], Cerelog-X extends these lines of research into a practical social-media and conversational-AI setting. We further outline scientifically grounded pathways for multimodal sensory extension (vision, touch, olfaction) and for pure thought-based communication with Grok and other X users via private-call channels. We highlight the system architecture, signal-processing pipeline, avatar rendering, training paradigm, ethical safeguards, and a phased development roadmap. The framework is intended as a research platform rather than a medical device and aims to enrich human-human and human-AI interaction with physiologically grounded affective context. Furthermore, this framework is a conceptual synthesis intended to stimulate collaborative implementation. All hardware and software components referenced are either commercially available research instruments or open-source frameworks. Experimental validation remains the focus of the future work.