Data · dataset · 2026
Evidence dataset for a systematic review of explainable and energy-efficient spiking neural networks for EEG-BCI
Listed in Teesside University Research Data Repository
Description
This dataset accompanies the systematic review “Explainable and Energy-Efficient Spiking Neural Networks for EEG-BCI: A Systematic Review of Generalisation and Resource-Constrained Deployment.” It contains the definitive source-level evidence ledger used for the review synthesis, with a formal evidence cutoff of 10 August 2026. The master ledger contains 229 source records. Of these, 148 are evidence records comprising 49 primary cognitive/cognitive-affective EEG-SNN records (A1), 58 supporting direct EEG-SNN records (A2), and 41 supporting SNN/neuromorphic/hardware records (B).
The direct EEG-SNN evidence subset therefore contains 107 records. The workbook contains source metadata, evidence-boundary classifications, verification notes, generalisation coding, methodological-quality and reporting appraisal (MQRA-v2), temporal summaries, search/corpus provenance, and companion-record decisions. The A1/A2/B evidence categories, G0–G4 generalisation levels, E0–E4 energy-evidence levels, and MQRA-v2 appraisal framework are review-derived analytical structures developed for this review and should not be interpreted as established or externally validated standards.
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Counts represent publication/evidence records rather than necessarily independent participant cohorts. Historical search provenance is reported separately from later source-level reconstruction and completeness auditing because the original row-level screening/exclusion trail and exact archived literal database search histories are not fully recoverable. Missing historical information has not been reconstructed retrospectively.
Links
Where it is published
- DOI doi.org/10.17632/ddz7bwwyyr.2 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Deep learning · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/ddz7bwwyyr.2 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:461103 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Deep Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |