6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Abnormal Nutritive Sucking as an Indicator of Neonatal Brain Injury

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          A term neonate is born with the ability to suck; this neuronal network is already formed and functional by 28 weeks gestational age and continues to evolve into adulthood. Because of the necessity of acquiring nutrition, the complexity of the neuronal network needed to suck, and neuroplasticity in infancy, the skill of sucking has the unique ability to give insight into areas of the brain that may be damaged either during or before birth. Interpretation of the behaviors during sucking shows promise in guiding therapies and how to potentially repair the damage early in life, when neuroplasticity is high. Sucking requires coordinated suck-swallow-breathe actions and is classified into two basic types, nutritive and non-nutritive. Each type of suck has particular characteristics that can be measured and used to learn about the infant's neuronal circuitry. Basic sucking and swallowing are present in embryos and further develop to incorporate breathing ex utero. Due to the rhythmic nature of the suck-swallow-breathe process, these motor functions are controlled by central pattern generators. The coordination of swallowing, breathing, and sucking is an enormously complex sensorimotor process. Because of this complexity, brain injury before birth can have an effect on these sucking patterns. Clinical assessments allow evaluators to score the oral-motor pattern, however, they remain ultimately subjective. Thus, clinicians are in need of objective measures to identify the specific area of deficit in the sucking pattern of each infant to tailor therapies to their specific needs. Therapeutic approaches involve pacifiers, cheek/chin support, tactile, oral kinesthetic, auditory, vestibular, and/or visual sensorimotor inputs. These therapies are performed to train the infant to suck appropriately using these subjective assessments along with the experience of the therapist (usually a speech therapist), but newer, more objective measures are coming along. Recent studies have correlated pathological sucking patterns with neuroimaging data to get a map of the affected brain regions to better inform therapies. The purpose of this review is to provide a broad scope synopsis of the research field of infant nutritive and non-nutritive feeding, their underlying neurophysiology, and relationship of abnormal activity with brain injury in preterm and term infants.

          Related collections

          Most cited references117

          • Record: found
          • Abstract: found
          • Article: not found

          Movement smoothness changes during stroke recovery.

          Smoothness is characteristic of coordinated human movements, and stroke patients' movements seem to grow more smooth with recovery. We used a robotic therapy device to analyze five different measures of movement smoothness in the hemiparetic arm of 31 patients recovering from stroke. Four of the five metrics showed general increases in smoothness for the entire patient population. However, according to the fifth metric, the movements of patients with recent stroke grew less smooth over the course of therapy. This pattern was reproduced in a computer simulation of recovery based on submovement blending, suggesting that progressive blending of submovements underlies stroke recovery.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            White matter injury in the preterm infant: pathology and mechanisms.

            The human preterm brain is particularly susceptible to cerebral white matter injury (WMI) that disrupts the normal progression of developmental myelination. Advances in the care of preterm infants have resulted in a sustained reduction in the severity of WMI that has shifted from more severe focal necrotic lesions to milder diffuse WMI. Nevertheless, WMI remains a global health problem and the most common cause of chronic neurological morbidity from cerebral palsy and diverse neurobehavioral disabilities. Diffuse WMI involves maturation-dependent vulnerability of the oligodendrocyte (OL) lineage with selective degeneration of late oligodendrocyte progenitors (preOLs) triggered by oxidative stress and other insults. The magnitude and distribution of diffuse WMI are related to both the timing of appearance and regional distribution of susceptible preOLs. Diffuse WMI disrupts the normal progression of OL lineage maturation and myelination through aberrant mechanisms of regeneration and repair. PreOL degeneration is accompanied by early robust proliferation of OL progenitors that regenerate and augment the preOL pool available to generate myelinating OLs. However, newly generated preOLs fail to differentiate and initiate myelination along their normal developmental trajectory despite the presence of numerous intact-appearing axons. Disrupted preOL maturation is accompanied by diffuse gliosis and disturbances in the composition of the extracellular matrix and is mediated in part by inhibitory factors derived from reactive astrocytes. Signaling pathways implicated in disrupted myelination include those mediated by Notch, WNT-beta catenin, and hyaluronan. Hence, there exists a potentially broad but still poorly defined developmental window for interventions to promote white matter repair and myelination and potentially reverses the widespread disturbances in cerebral gray matter growth that accompanies WMI.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              On the analysis of movement smoothness

              Quantitative measures of smoothness play an important role in the assessment of sensorimotor impairment and motor learning. Traditionally, movement smoothness has been computed mainly for discrete movements, in particular arm, reaching and circle drawing, using kinematic data. There are currently very few studies investigating smoothness of rhythmic movements, and there is no systematic way of analysing the smoothness of such movements. There is also very little work on the smoothness of other movement related variables such as force, impedance etc. In this context, this paper presents the first step towards a unified framework for the analysis of smoothness of arbitrary movements and using various data. It starts with a systematic definition of movement smoothness and the different factors that influence smoothness, followed by a review of existing methods for quantifying the smoothness of discrete movements. A method is then introduced to analyse the smoothness of rhythmic movements by generalising the techniques developed for discrete movements. We finally propose recommendations for analysing smoothness of any general sensorimotor behaviour. Electronic supplementary material The online version of this article (doi:10.1186/s12984-015-0090-9) contains supplementary material, which is available to authorized users.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Pediatr
                Front Pediatr
                Front. Pediatr.
                Frontiers in Pediatrics
                Frontiers Media S.A.
                2296-2360
                12 January 2021
                2020
                : 8
                : 599633
                Affiliations
                [1] 1Jane and John Justin Neurosciences Center, Cook Children's Health Care System , Fort Worth, TX, United States
                [2] 2Department of Communication Sciences and Disorders, University of Kentucky , Lexington, KY, United States
                [3] 3NFANT Labs, LLC , Marietta, GA, United States
                [4] 4Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School , Boston, MA, United States
                [5] 5Neonatal Intensive Care Unit, Cook Children's Health Care System , Fort Worth, TX, United States
                [6] 6School of Medicine, Texas Christian University and University of North Texas Health Science Center , Fort Worth, TX, United States
                [7] 7Neonatal Intensive Care Unit Early Support and Transition (NEST), Developmental Follow-Up Center, Neonatology Department, Cook Children's Health Care System , Fort Worth, TX, United States
                [8] 8Department of Bioengineering, University of Texas at Arlington , Arlington, TX, United States
                Author notes

                Edited by: Daniel Alonso-Alconada, University of the Basque Country, Spain

                Reviewed by: Ivan Leslie Hand, SUNY Downstate Medical Center, United States; Kevin Donald Broad, University College London, United Kingdom

                *Correspondence: Sabrina Shandley sabrina.shandley@ 123456cookchildrens.org

                This article was submitted to Neonatology, a section of the journal Frontiers in Pediatrics

                Article
                10.3389/fped.2020.599633
                7835320
                33511093
                02109ee3-a5be-499f-9d2d-42870cbee109
                Copyright © 2021 Shandley, Capilouto, Tamilia, Riley, Johnson and Papadelis.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 27 August 2020
                : 24 November 2020
                Page count
                Figures: 8, Tables: 0, Equations: 0, References: 117, Pages: 13, Words: 11096
                Categories
                Pediatrics
                Review

                sucking,brain injury,neuroimaging,nutritive,non-nutritive
                sucking, brain injury, neuroimaging, nutritive, non-nutritive

                Comments

                Comment on this article