Royal Melbourne Hospital 3 articles published in JoVE Behavior An Instrumented Pull Test to Characterize Postural Responses Joy Tan1,2,4, Wesley Thevathasan2,3,4,5, Jennifer McGinley6, Peter Brown7, Thushara Perera1,4 1Department of Medical Bionics, The University of Melbourne, 2Department of Neurology, The Royal Melbourne Hospital, 3Department of Neurology, Austin Hospital, 4The Bionics Institute, 5Department of Medicine, The University of Melbourne, 6Department of Physiotherapy, The University of Melbourne, 7Medical Research Council Brain Network Dynamics Unit, University of Oxford Impairment of postural reflexes, termed postural instability, is difficult to quantify. Clinical assessments such as the pull test suffer issues with reliability and scaling. Here, we present an instrumented version of the pull test to objectively characterize postural responses. Neuroscience Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents Mojtaba Kermani*1,3, Zahra Fatahi*2, Dechuan Sun3, Abbas Haghparast2, Chris French3,4 1Department of Optometry and Vision Science, The University of Melbourne, 2Neuroscience Research Center, Shahid Beheshti University of Medical Science, 3Department of Medicine, The University of Melbourne, 4Royal Melbourne Hospital A cost-benefit analysis is a weighing-scale approach that the brain performs during the course of decision making. Here, we propose a protocol to train rats on an operant-based decision-making paradigm where rats choose higher rewards at the expense of waiting for 15 s to receive them. Medicine A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data Tim Spelman1,2, Orla Gray3, Robyn Lucas4, Helmut Butzkueven1,2 1Department of Neurology, Royal Melbourne Hospital, 2Department of Medicine (RMH), The University of Melbourne, 3Department of Neurology, Ulster Hospital, 4National Centre for Epidemiology and Population Health, Australian National University Combining plot analysis with trigonometric regression is a robust method for exploring complex, cyclical phenomena such as relapse onset timing in multiple sclerosis (MS). This method enabled unbiased characterisation of seasonal trends in relapse onset permitting novel inferences around the influence of seasonal variation, ultraviolet radiation (UVR) and latitude.
