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Record W4415421495 · doi:10.1186/s12984-025-01754-1

Functional motor mapping of domestic pig lumbar spinal cord using penetrating microelectrodes

2025· article· en· W4415421495 on OpenAlexafffund
Soroush Mirkiani, Amirali Toossi, Amin Arefadib, Carly L. O’Sullivan, Dirk G. Everaert, Peter Seres, David S Hu, Richard R. E. Uwiera, Kevin Robinson, Peter E. Konrad, Vivian K. Mushahwar

Bibliographic record

VenueJournal of NeuroEngineering and Rehabilitation · 2025
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of Alberta
FundersCanadian Institutes of Health ResearchCanada Research ChairsCanada Foundation for InnovationUniversity of AlbertaAlberta Innovates - Health SolutionsFondation Brain CanadaAlberta InnovatesU.S. Department of Defense
KeywordsSpinal cordMicrostimulationLumbarNeuroprostheticsSpinal cord injuryAnkleLumbar Spinal CordStimulation

Abstract

fetched live from OpenAlex

The restoration of standing and walking after spinal cord injury (SCI) remains a top priority for individuals with paraplegia. Despite significant advancements in neuromodulation techniques, challenges such as limited selectivity and inconsistent outcomes highlight the need for innovative approaches. Intraspinal microstimulation (ISMS) has emerged as a promising method for restoring motor function as demonstrated in various preclinical models. This study aimed to investigate the functional neural networks within the ventral lumbar spinal cord of pigs. We explored 134 stimulation sites inside the spinal cord in 13 domestic pigs. Post-mortem magnetic resonance imaging (MRI) revealed the location of microelectrode tips inside the spinal cord. The recorded kinematics and electromyographical muscle activity associated with each microelectrode allowed the creation of a functional map of the neural networks activated with ISMS. In addition, we performed anatomical measurements of the lumbar spine and spinal column. Our results revealed a somatotopic organization of motor networks responsible for distinct movements and muscle activations. Differences in activation patterns were primarily observed along the rostrocaudal axis (P < 0.05), where specific stimulation sites were associated with unique movements and muscle responses. In contrast, no notable variations were seen along the mediolateral or dorsoventral directions. Knee extension (KE) was the most frequently observed movement, occurring in 78% of the stimulated sites in the lumbar enlargement, followed by extensor synergy (Ext Syn, 64%), hip flexion (HF, 50%), ankle flexion (AF, 50%), ankle extension (AE, 43%), and hip extension (HE, 43%). Stimulation along the rostrocaudal axis of the lumbar spinal cord elicited a sequence of movements, beginning with HF in the rostral region and transitioning to KE, AF, AE, and HE in the caudal region across animals. Stimulation in the rostral lumbar enlargement produced stronger normalized EMG signals exceeding 50% of the maximum in vastus lateralis (VL) compared to tibialis anterior (TA) gastrocnemius (GS), gluteus medius (GL), and biceps femoris (BF; P < 0.05). Co-activation, defined as simultaneous activity above 50% of normalized maximum EMG activity, occurred at 27.4% of stimulation sites, resulting in synergistic movements and joint stiffening. The resulting map of spinal cord motor networks is important for improving device design and the efficiency of neuroprosthetic interventions. While motor maps exist for other species, they are absent for domestic pigs, a critical model for preclinical testing of SCI treatments. The functional motor maps provided here serve as a foundation for designing and optimizing intraspinal interventions, advancing their translation to clinical application.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.337
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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