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Record W2522403327 · doi:10.1002/ana.24778

Physiology of freezing of gait

2016· review· en· W2522403327 on OpenAlexaff
Anke H. Snijders, Kaoru Takakusaki, Bettina Debû, Andrés M. Lozano, Vibhor Krishna, Alfonso Fasano, Tipu Z. Aziz, Stella M. Papa, Stewart A. Factor, Mark Hallett

Bibliographic record

VenueAnnals of Neurology · 2016
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsToronto Western HospitalUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsPedunculopontine nucleusGaitNeuroscienceBalance (ability)Deep brain stimulationPhysical medicine and rehabilitationStriatumAfferentMovement disordersPsychologyParkinson's diseaseDiseaseMedicinePathology

Abstract

fetched live from OpenAlex

Freezing of gait (FOG) is a common and debilitating, but largely mysterious, symptom of Parkinson disease. In this review, we will discuss the cerebral substrate of FOG focusing on brain physiology and animal models. Walking is a combination of automatic movement processes, afferent information processing, and intentional adjustments. Thus, normal gait requires a delicate balance between various interacting neuronal systems. To further understand gait control and specifically FOG, we will discuss the basic physiology of gait, animal models of gait disturbance including FOG, alternative etiologies of FOG, and functional magnetic resonance studies investigating FOG. The outcomes of these studies point to a dynamic network of cortical areas such as the supplementary motor area, as well as subcortical areas such as the striatum and the mesencephalic locomotor region including the pedunculopontine nucleus (PPN). Additionally, we will review PPN (area) stimulation as a possible treatment for FOG, and ponder whether PPN stimulation truly is the right step forward. Ann Neurol 2016;80:644-659.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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)0.0000.000

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 head0.128
GPT teacher head0.394
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations202
Published2016
Admission routes1
Has abstractyes

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