NeuroGate: waveform translation between brain
- 1Istanbul Medipol University
Abstract
The brain processes information across distributed circuits, yet a typical experiment records only a few regions, leaving the rest unobserved. Connectivity and latent-embedding methods relate brain regions but do not return the waveform of an unrecorded one. Here we introduce NeuroGate, a framework for cross-regional neural signal translation that recovers an unrecorded region's waveform from a recorded one. Across 56 pathways spanning rodent LFP, human sEEG and ECoG, and scalp EEG, NeuroGate predicts waveforms more accurately than 13 deep-learning and linear baselines, with low across-session variance and high median accuracy. We tested the predictions against a circuit perturbation: silencing piriform-cortex output with tetanus toxin light chain collapsed piriform-to-bulb predictions in 8 of 8 folds while the reverse was preserved, matching the monosynaptic anatomy. We demonstrate two applications: quantifying how recording redundancy bounds the information from each added source, and a reusable perturbation protocol for verifying directional translation in any circuit.
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BibTeX
@misc{zareh2026neurogate,
title = {{NeuroGate: waveform translation between brain}},
author = {A. Zareh and M. K. Ozdemir and R. Yagci},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.09.750499},
url = {https://www.biorxiv.org/content/10.64898/2026.09.09.750499v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - NeuroGate: waveform translation between brain
AU - A. Zareh
AU - M. K. Ozdemir
AU - R. Yagci
PY - 2026
DA - 2026/09/09
PB - bioRxiv
DO - 10.64898/2026.09.09.750499
UR - https://www.biorxiv.org/content/10.64898/2026.09.09.750499v1
AB - The brain processes information across distributed circuits, yet a typical experiment records only a few regions, leaving the rest unobserved. Connectivity and latent-embedding methods relate brain regions but do not return the waveform of an unrecorded one. Here we introduce NeuroGate, a framework for cross-regional neural signal translation that recovers an unrecorded region's waveform from a recorded one. Across 56 pathways spanning rodent LFP, human sEEG and ECoG, and scalp EEG, NeuroGate predicts waveforms more accurately than 13 deep-learning and linear baselines, with low across-session variance and high median accuracy. We tested the predictions against a circuit perturbation: silencing piriform-cortex output with tetanus toxin light chain collapsed piriform-to-bulb predictions in 8 of 8 folds while the reverse was preserved, matching the monosynaptic anatomy. We demonstrate two applications: quantifying how recording redundancy bounds the information from each added source, and a reusable perturbation protocol for verifying directional translation in any circuit.
ER -