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Versteeg C, Chowdhury RH, Miller LE. Cuneate nucleus: The somatosensory gateway to the brain. CURRENT OPINION IN PHYSIOLOGY 2021; 20:206-215. [PMID: 33869911 DOI: 10.1016/j.cophys.2021.02.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Much remains unknown about the transformation of proprioceptive afferent input from the periphery to the cortex. Until recently, the only recordings from neurons in the cuneate nucleus (CN) were from anesthetized animals. We are beginning to learn more about how the sense of proprioception is transformed as it propagates centrally. Recent recordings from microelectrode arrays chronically implanted in CN have revealed that CN neurons with muscle-like properties have a greater sensitivity to active reaching movements than to passive limb displacement, and we find that these neurons have receptive fields that resemble single muscles. In this review, we focus on the varied uses of proprioceptive input and the possible role of CN in processing this information.
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Affiliation(s)
- Christopher Versteeg
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern 7 University, Evanston, IL, USA
| | - Raeed H Chowdhury
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, 10 Pittsburgh, PA, USA
| | - Lee E Miller
- Department of Biomedical Engineering, McCormick School of Engineering, Northwestern 7 University, Evanston, IL, USA.,Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, 13 IL, USA.,Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, 16 Northwestern University, Chicago, IL, USA.,Shirley Ryan AbilityLab, Chicago, IL, USA
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Huang L, Xian Q, Shen N, Shi L, Qu Y, Zhou L. Congenital absence of corticospinal tract does not severely affect plastic changes of the developing postnatal spinal cord. Neuroscience 2015; 301:338-50. [DOI: 10.1016/j.neuroscience.2015.06.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2015] [Revised: 06/06/2015] [Accepted: 06/08/2015] [Indexed: 11/25/2022]
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Clowry GJ, Basuodan R, Chan F. What are the Best Animal Models for Testing Early Intervention in Cerebral Palsy? Front Neurol 2014; 5:258. [PMID: 25538677 PMCID: PMC4255621 DOI: 10.3389/fneur.2014.00258] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2014] [Accepted: 11/21/2014] [Indexed: 11/13/2022] Open
Abstract
Interventions to treat cerebral palsy should be initiated as soon as possible in order to restore the nervous system to the correct developmental trajectory. One drawback to this approach is that interventions have to undergo exceptionally rigorous assessment for both safety and efficacy prior to use in infants. Part of this process should involve research using animals but how good are our animal models? Part of the problem is that cerebral palsy is an umbrella term that covers a number of conditions. There are also many causal pathways to cerebral palsy, such as periventricular white matter injury in premature babies, perinatal infarcts of the middle cerebral artery, or generalized anoxia at the time of birth, indeed multiple causes, including intra-uterine infection or a genetic predisposition to infarction, may need to interact to produce a clinically significant injury. In this review, we consider which animal models best reproduce certain aspects of the condition, and the extent to which the multifactorial nature of cerebral palsy has been modeled. The degree to which the corticospinal system of various animal models human corticospinal system function and development is also explored. Where attempts have already been made to test early intervention in animal models, the outcomes are evaluated in light of the suitability of the model.
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Affiliation(s)
- Gavin John Clowry
- Institute of Neuroscience, Newcastle University , Newcastle upon Tyne , UK
| | - Reem Basuodan
- Institute of Neuroscience, Newcastle University , Newcastle upon Tyne , UK
| | - Felix Chan
- Institute of Neuroscience, Newcastle University , Newcastle upon Tyne , UK
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Gravem D, Singh M, Chen C, Rich J, Vaughan J, Goldberg K, Waffarn F, Chou P, Cooper D, Reinkensmeyer D, Patterson D. Assessment of Infant Movement With a Compact Wireless Accelerometer System. J Med Device 2012. [DOI: 10.1115/1.4006129] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
There is emerging data that patterns of motor activity early in neonatal life can predict impairments in neuromotor development. However, current techniques to monitor infant movement mainly rely on observer scoring, a technique limited by skill, fatigue, and inter-rater reliability. Consequently, we tested the use of a lightweight, wireless, accelerometer system that measures movement and can be worn by premature babies without interfering with routine care. We hypothesized that this system would be useful in assessing motor activity, in identifying abnormal movement, and in reducing the amount of video that a clinician would need to review for abnormal movements. Ten preterm infants in the NICU were monitored for 1 h using both the accelerometer system and video. A physical therapist trained to recognize cramped-synchronized general movements scored all of the video data by labeling each abnormal movement observed. The parameters of three different computer models were then optimized based on correlating features computed from accelerometer data and the observer’s annotations. The annotations were compared to the model’s prediction on unseen data. The trained observer identified cramped-synchronized general movements in 6 of the 10 infants. The computer models attained between 70% and 90% accuracy when predicting the same observer label for each data point. Our study suggests that mini-accelerometers may prove useful as a clinical tool assessing patterns of movement in preterm infants.
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Affiliation(s)
| | - M. Singh
- Department of Pediatrics and Institute for Clinical and Translational Science, University of California, Irvine, 101 The City Drive South, Building 25, 2nd floor Orange, Irvine, CA 92868
| | - C. Chen
- Department of Pediatrics and Institute for Clinical and Translational Science, University of California, Irvine, 101 The City Drive South, Building 25, 2nd floor Orange, Irvine, CA 92868
| | - J. Rich
- Department of Pediatrics and Institute for Clinical and Translational Science, University of California, Irvine, 101 The City Drive South, Building 25, 2nd floor Orange, Irvine, CA 92868
| | - J. Vaughan
- Department of Pediatrics and Institute for Clinical and Translational Science, University of California, Irvine, 101 The City Drive South, Building 25, 2nd floor Orange, Irvine, CA 92868
| | - K. Goldberg
- Danbury Hospital, 24 Hospital Avenue, Danbury, CT 06810
| | - F. Waffarn
- Department of Pediatrics and Institute for Clinical and Translational Science, University of California, Irvine, 101 The City Drive South, Building 25, 2nd floor Orange, Irvine, CA 92868
| | - P. Chou
- Department of Pediatrics and Institute for Clinical and Translational Science, University of California, Irvine, 101 The City Drive South, Building 25, 2nd floor Orange, Irvine, CA 92868
| | - D. Cooper
- Department of Pediatrics and Institute for Clinical and Translational Science, University of California, Irvine, 101 The City Drive South, Building 25, 2nd floor Orange, Irvine, CA 92868
| | - D. Reinkensmeyer
- Department of Mechanical and Aerospace Engineering, Henry Samuelli School of Engineering, University of California, Irvine, 5200 Engineering Hall, Irvine, CA 92697
| | - D. Patterson
- Department of Informatics, Donald Bren School of Information and Computer Sciences, 5084 Donald Bren Hall, Irvine, CA 92697
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