Title |
Sherlock Holmes and the curious case of the human locomotor central pattern generator
|
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Published in |
Journal of Neurophysiology, March 2018
|
DOI | 10.1152/jn.00554.2017 |
Pubmed ID | |
Authors |
Taryn Klarner, E Paul Zehr |
Abstract |
Evidence first described in reduced animal models over 100 years ago led to deductions about the control of locomotion through spinal locomotor central pattern generating (CPG) networks. These discoveries in nature were contemporaneous with another form of deductive reasoning found in popular culture-that of Arthur Conan Doyle's detective "Sherlock Holmes". Since the invasive methods used in reduced non-human animal preparations are not amenable to study in humans, we are left instead with deducing from other measures and observations. Using the deductive reasoning approach of Sherlock Holmes as a metaphor for framing research into human CPGs, we speculate and weigh the evidence that should be observable in humans based on knowledge from other species. This review summarizes indirect inference to assess "observable evidence" of pattern generating activity which leads to the logical deduction of CPG contributions to arm and leg activity during locomotion in humans. The question of where a CPG may be housed in the human nervous system remains incompletely resolved at this time. Ongoing understanding, elaboration and application of functioning locomotor CPGs in humans is important for gait rehabilitation strategies in those with neurological injuries. |
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Geographical breakdown
Country | Count | As % |
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Canada | 8 | 17% |
United Kingdom | 8 | 17% |
Italy | 1 | 2% |
Finland | 1 | 2% |
Australia | 1 | 2% |
Ireland | 1 | 2% |
Netherlands | 1 | 2% |
Brazil | 1 | 2% |
Other | 2 | 4% |
Unknown | 12 | 26% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 27 | 57% |
Scientists | 12 | 26% |
Science communicators (journalists, bloggers, editors) | 7 | 15% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 154 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 25 | 16% |
Student > Bachelor | 19 | 12% |
Researcher | 17 | 11% |
Student > Master | 15 | 10% |
Student > Doctoral Student | 9 | 6% |
Other | 34 | 22% |
Unknown | 35 | 23% |
Readers by discipline | Count | As % |
---|---|---|
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Medicine and Dentistry | 17 | 11% |
Nursing and Health Professions | 15 | 10% |
Engineering | 14 | 9% |
Agricultural and Biological Sciences | 10 | 6% |
Other | 17 | 11% |
Unknown | 40 | 26% |