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Write 3 pages with APA style on Assignment 4. 11 November Summary and implications: Hemispheric dominance for movements in humans is a subject which continues to attract a wide range of speculations f
Write 3 pages with APA style on Assignment 4. 11 November Summary and implications: Hemispheric dominance for movements in humans is a subject which continues to attract a wide range of speculations from scholars around the globe. Many findings to date are still clouded by critical suspicions or limitation of the studies. However, Okuda et al. take a unique approach to establishing facts in their study by scrutinizing the dexterity of hand movements in four right-handed subjects. Conclusions drawn by them suggest dominance of the left somatosensory cortex on intricate finger movements. It is the defect in cortical function which negatively interferes with the dexterity of hand movements leading patients to complain of clumsiness. Although the authors’ take on impaired hand movements in this study is still considered incongruous, they convincingly cite works of myriad other researchers to illustrate the truth about hemispheric dominance. Illustrating how the transfer of information to the motor cortex does not occur in a symmetric fashion, this research provides an insightful analysis of the complex mechanisms underlying human hand movements. In contrast to the role of sensory information analyzed by Okuda et al., Wasaka and Kakigi place emphasis on momentous role of the visual information to understand motor execution in humans. They argue that human body’s movements are not only regulated by somatosensory information, but also by the way visual information is perceived. Though agreeing that the connection between sensory and visual information in human brain and the affect it produces on motor behavior is still ambiguous, they confirm this much that a mismatch between the assumed and real visual feedback leads to visual conflict damaging motor execution (Wasaka and Kakigi 1506). Ijspeert in his comprehensive study digs with acute intelligence into areas where neuroscience and robotics can connect. He attempts to explain how central pattern generators (CPGs) when used as neural networks can be used in robotics to direct the locomotion of robots. It is claimed that the interaction between robotics and biology is being increasingly confirmed with passing time and better research techniques and already, robots are being labeled as indispensable scientific tools for testing myriad biological hypotheses. Viewing CPGs as intriguing building blocks for biped locomotion control in robots, it is suggested that their appropriate implementation can drastically reduce the complexity of the control problem confronted by robotics. Ijspeert’s riveting exploration of the interaction between biology and robotics is undeniably impressive in this research only limited by lack of a theoretical framework for clarifying CPGs. McCrea and Rybak also contemplate the role of CPGs in organization of motor neurons during mammalian locomotion. They attempt to remove some ambiguities concerning CPGs by using a computational model which studies interactions between the CPG and spinal neurons in the Hodgkin-Huxley style. It is strongly recommended in this study to use a combination of two-level CPG model and unit burst generator (UBG) to investigate the neural mechanism forming the bedrock of locomotion control. The UBG model is contrasted against CPG model and it is found that using the first model alone is not very advantageous because of the same neurons used for controlling locomotion, but different motoneuron activation patterns can be generated if it is added to the two-level model. A principal implication of Okuda et al.’s research concentrates on the role played by sensory information processing in controlling hand movements of subjects with left or right hemispheric damage. The authors’ claim on definitive contribution of bilateral symmetry to hand movements in humans introduces an area which could use further exploration. Wasaka and Kakigi’s study concerning the incongruence stemming from conflict in visual feedback after observing activities of multiple cortical areas implies equal importance attached to both somatosensory and visual information in commanding motor behavior. Whenever there is sensory or visual conflict, the human ability to perceive arms and legs through an input of somatosensory and visual information is impaired. This research contains important implications for neural engineering given its contribution to explaining the neural mechanism of somatosensory processing and its findings can be put into practice by facilitating the recovery of amputees. Conclusions drawn by Ijspeert concerning different media through which biology interacts with robotics can be used to engineer different innovative hypotheses and technologies to improve locomotion control in robots which are rapidly gaining importance in contemporary world. This study has important implications for biomedical engineering too given the way the author’s demonstration of CPGs’ functioning is valuable for planning treatment of patients with spinal cord damage. McCrea and Rybak make the contribution of CPGs to effective treatment of spinal cord injuries more emphatic by stressing further on this medical cause. They claim that a combination of CPG and UBG architecture can be used for better understanding of the neural mechanism in charge of locomotion in spinal cord injury patients. Works cited: Ijspeert, Auke J. “Central pattern generators for locomotion control in animals and robots: A review.” Neural Networks 21 (2008): 642–653. Print. McCrea, David A., and Rybak, Ilya A. “Organization of mammalian locomotor rhythm and pattern generation.” BRAIN RESEARCH REVIEWS 57 (2008): 134–146. Print. Okuda, B., Tanaka, H., Tomino, Y., Kawabata, K., Tachibana, H., and Sugita, M. “The role of the left somatosensory cortex in human hand movement.” Exp Brain Res 106 (1995): 493-498. Print. Wasaka, Toshiaki, and Kakigi, Ryusuke. “Con?ict caused by visual feedback modulates activation in somatosensory areas during movement execution.” NeuroImage 59: 1501–1507. Print.
