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Record W4317585544 · doi:10.1038/s41598-022-26093-2

Exercising is good for the brain but exercising outside is potentially better

2023· article· en· W4317585544 on OpenAlexafffund
Katherine Boere, Kelsey Lloyd, Gordon Binsted, Olave E. Krigolson

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsYork UniversityUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCognitionElectroencephalographyPhysical medicine and rehabilitationOddball paradigmPsychologyEvent-related potentialFunction (biology)Effects of sleep deprivation on cognitive performanceTask (project management)UrbanizationCognitive psychologyMedicineNeuroscience

Abstract

fetched live from OpenAlex

It is well known that exercise increases cognitive function. However, the environment in which the exercise is performed may be just as important as the exercise itself. Time spent in natural outdoor environments has been found to lead to increases in cognition similar to those resulting from acute exercise. Therefore, the benefits of both exercise and nature exposure suggest an additive impact on brain function when both factors are combined. This raises the question: what is the interaction between acute exercise and environment on cognition? We answered this question using electroencephalography to probe cognitive function using the oddball task before and after brief indoor and outdoor walks on 30 participants (average 21 years old, 95% CI [20, 22]). Our results demonstrate improved performance and an increase in the amplitude of the P300, an event-related neural response commonly associated with attention and working memory, following a 15-min walk outside; a result not seen following a 15-min walk inside. Importantly, this finding indicates that the environment may play a more substantial role in increasing cognitive function such as attention than exercise, at least in terms of acute exercise (i.e., a brief walk). With the world's growing urbanization and the associated increase in sedentary time indoors, a deeper understanding of how these factors interact and influence cognition may be critical to combat adverse health effects.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.273
Teacher spread0.246 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations52
Published2023
Admission routes2
Has abstractyes

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