Foundation model

ZUNA: results on public EEG datasets

ZUNA 1.1 is a channel-wise EEG encoder from Zyphra. Its authors describe the pretraining data only at repository level — the TUH EEG corpus and OpenNeuro collections — and publish no list of datasets, so whether each core dataset was in it is unknown. BCI Report ran the encoder alone, frozen, with no channel upsampling or reconstruction, and adapted it on EEGMAT. Its model card says research use only, not for diagnosis or clinical use.

Measured on: ds003810; EEGMAT; BETA; ds006593; TMNRED / ds005383; EESM19 scalp subset; ds005342 · Protocols: Motor imagery & rest; Arithmetic & rest; SSVEP · 8 channels; SSVEP · 4 channels; P300 target ERP; Semantic target ERP; Sleep staging; Idle & command

Also known as ZUNA 1.1 · ZUNA1.1 · Zyphra/ZUNA1.1

Reference ZUNA 1.1, arXiv:2607.27308 ↗

Directory status: Evaluated · Official code ↗ · Description sources arxiv.org · huggingface.co

Published results

Grouped by dataset. Compare figures within a group only: across groups the task, cohort, chance level and electrode layout all change.

ds003810 · v9 foundation encoders, frozen · motor imagery & rest

Read with its protocol: Core-matrix protocol: Motor imagery & rest · Chance level 50.0% · foundation-models-mi-rest.csv

MethodConditionMetricValuePeople
ZUNA 1.1Frozen encoder + ridge headBalanced accuracy50.7%49.2%–52.1%Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.10

Weights terms: ZUNA under Apache-2.0. No model’s authors endorse these results. Every weights licence and its terms →

EEGMAT · v9 foundation encoders, frozen · arithmetic & rest

Read with its protocol: Core-matrix protocol: Arithmetic & rest · Chance level 50.0% · foundation-models-arithmetic-rest.csv

MethodConditionMetricValuePeople
ZUNA 1.1Frozen encoder + ridge headBalanced accuracy53.3%49.5%–57.1%Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.36

Weights terms: ZUNA under Apache-2.0. No model’s authors endorse these results. Every weights licence and its terms →

EEGMAT · Model adaptation, v9 · new people, same task, one fixed recipe (not a ranking)

Read with its protocol: Core-matrix protocol: Arithmetic & rest · Chance level 50.0% · foundation-models-update.json

ZUNA 1.1 · Frozen encoder + trained head
51.2% (49.8%–52.7%)
ZUNA 1.1 · LoRA rank 4 + head
56.9% (53.7%–60.1%)
Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.
MethodConditionMetricValuePeople
ZUNA 1.1Frozen encoder + trained headBalanced accuracy51.2%49.8%–52.7%1,218 trainable parameters. Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.36
ZUNA 1.1LoRA rank 4 + headBalanced accuracy56.9%53.7%–60.1%296,130 trainable parameters. Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.36
ZUNA 1.1LoRA minus frozen + head, same people and foldsPaired difference+5.7 pp+2.5 pp–+8.7 pp28 people improved, 7 got worse, 1 unchanged. The interval excludes zero. Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.36

Weights terms: ZUNA under Apache-2.0. No model’s authors endorse these results. Every weights licence and its terms →

BETA · v9 foundation encoders, frozen · SSVEP, 8 channels

Read with its protocol: Core-matrix protocol: SSVEP · 8 channels · Chance level 2.5% · foundation-models-beta-8ch.csv

MethodConditionMetricValuePeople
ZUNA 1.1Frozen encoder + ridge headBalanced accuracy11.9%10.8%–13.0%Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.70

Weights terms: ZUNA under Apache-2.0. No model’s authors endorse these results. Every weights licence and its terms →

BETA · v9 foundation encoders, frozen · SSVEP, 4 channels

Read with its protocol: Core-matrix protocol: SSVEP · 4 channels · Chance level 2.5% · foundation-models-beta-4ch.csv

MethodConditionMetricValuePeople
ZUNA 1.1Frozen encoder + ridge headBalanced accuracy8.4%7.5%–9.4%Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.70

Weights terms: ZUNA under Apache-2.0. No model’s authors endorse these results. Every weights licence and its terms →

ds006593 · v9 foundation encoders, frozen · P300 target ERP

Read with its protocol: Core-matrix protocol: P300 target ERP · Chance level 50.0% · foundation-models-p300-target.csv

MethodConditionMetricValuePeople
ZUNA 1.1Frozen encoder + ridge headBalanced accuracy51.6%50.3%–53.0%Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.21

Weights terms: ZUNA under Apache-2.0. No model’s authors endorse these results. Every weights licence and its terms →

TMNRED / ds005383 · v9 foundation encoders, frozen · semantic target ERP

Read with its protocol: Core-matrix protocol: Semantic target ERP · Chance level 50.0% · foundation-models-semantic-target.csv

MethodConditionMetricValuePeople
ZUNA 1.1Frozen encoder + ridge headBalanced accuracy53.9%52.2%–55.6%Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.30

Weights terms: ZUNA under Apache-2.0. No model’s authors endorse these results. Every weights licence and its terms →

EESM19 scalp subset · v9 foundation encoders, frozen · sleep staging

Read with its protocol: Core-matrix protocol: Sleep staging · Chance level 20.0% · foundation-models-sleep-scalp.csv

MethodConditionMetricValuePeople
ZUNA 1.1Frozen encoder + ridge headBalanced accuracy60.1%57.8%–62.3%Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.20

Weights terms: ZUNA under Apache-2.0. No model’s authors endorse these results. Every weights licence and its terms →

ds005342 · v9 foundation encoders, frozen · idle & command

Read with its protocol: Core-matrix protocol: Idle & command · foundation-models-idle.csv

MethodConditionMetricValuePeople
ZUNA 1.1Frozen encoder + linear headCommands detected ≤3 s11 / 600 of 4 people always abstained. Pretraining exposure: unknown: the authors do not list their pretraining data closely enough to decide. Model card: research use only, not for diagnosis or clinical use.4
ZUNA 1.1Frozen encoder + linear headIdle false activations1 / 60Model card: research use only, not for diagnosis or clinical use.4

Weights terms: ZUNA under Apache-2.0. No model’s authors endorse these results. Every weights licence and its terms →

All methods → · All datasets →

Checkpoints, inputs and terms

What was run, as the v9 release records it: each checkpoint’s revision and SHA-256, its encoder parameters, the footnote its rows carry and its weights licence. No weights, adapted weights or LoRA deltas were kept or shared, and no endorsement by the model’s authors is implied.

ZUNA 1.1

Model card: research use only, not for diagnosis or clinical use.

Panel
A row beside the core matrix on every protocol page
Encoder parameters
172.10M
Revision
Zyphra/ZUNA1.1 @ 10b9d6c8
Checkpoint SHA-256
295fcddb42ab4623dc1346fba12176798d97ab95389c666907e32cbce23f7f33
Paper
paper ↗
Weights licence
Apache-2.0; model card: research use only, not for diagnosis or clinical use
Licence note
Apache-2.0 weights; model card states research use only, not for diagnosis or clinical use.
Rights review
Apache-2.0 weights. The model card says research use only, not for diagnosis or clinical use; that sentence travels with its rows.
Row footnote
Pretraining exposure unknown for every core dataset (no published source list). Encoder only; no channel upsampling or reconstruction.
Notes
ZUNA pretraining sources are not published: exposure unknown on every core dataset. 0-4 electrode coordinates per protocol are clamped to the edge of the +-0.12 m position grid as upstream does.
EEGMAT adaptation
Run: a head trained on the frozen encoder against LoRA rank 4, three seeds.

Pretraining exposure, by dataset

Whether each core dataset is in the model authors’ published pretraining list, checked on 2026-10-04 and linked to the source. A dataset absent from the list is not proof that its recordings were never seen; recording-level audits were not done.

DatasetProtocolsStatementSource
ds003810 Motor Imagery vs Rest (low-cost EEG; Peterson et al.)Motor imagery & restunknown: the authors do not list their pretraining data closely enough to decidesource ↗ · source ↗ · source ↗ · source ↗
EEGMAT (PhysioNet EEG During Mental Arithmetic Tasks; Zyma et al. 2019)Arithmetic & restunknown: the authors do not list their pretraining data closely enough to decidesource ↗ · source ↗ · source ↗ · source ↗
ds006593 cBCI Matrix Multimodal Dataset (Celik et al.)P300 target ERPunknown: the authors do not list their pretraining data closely enough to decidesource ↗ · source ↗ · source ↗ · source ↗
ds005383 TMNRED (Bai et al. 2025, Sci. Data 12:701)Semantic target ERPunknown: the authors do not list their pretraining data closely enough to decidesource ↗ · source ↗ · source ↗ · source ↗
EESM19 Ear-EEG Sleep Monitoring 2019 (OpenNeuro ds005185; Mikkelsen et al.)Sleep stagingunknown: the authors do not list their pretraining data closely enough to decidesource ↗ · source ↗ · source ↗ · source ↗
BETA 40-target SSVEP (Liu et al. 2020, Front. Neurosci. 14:627)SSVEP · 8 channels · SSVEP · 4 channelsunknown: the authors do not list their pretraining data closely enough to decidesource ↗ · source ↗ · source ↗ · source ↗
ds005342 EEG offline/online MI for standing and sitting (Triana-Guzman et al.)Idle & commandunknown: the authors do not list their pretraining data closely enough to decidesource ↗ · source ↗ · source ↗ · source ↗

Cite this page

BCI Report (2026). ZUNA: results on public EEG datasets. https://bci.report/methods/zuna/

Figures from release foundation-models-update-20261004 (2026-10-04). Cite the upstream datasets as well: each dataset’s page gives its credit.

Every release is archived on Zenodo: doi:10.5281/zenodo.23123296. BibTeX for the site and its releases → · CITATION.cff ↗