Incorporation of Motor Response Time in Simple Reaction Tasks
Zhao, Ye 1 ; Wong, Willy 1, 2, 3 ; Norwich, Kenneth1, 3, 4
1. Institute of Biomaterials and Biomedical Engineering, University of Toronto; 2. Department of Electrical and Computer Engineering, University of Toronto; 3. Collaborative Program in Neuroscience, University of Toronto; 4. Department of Physiology, University of Toronto
Simple reaction time (SRT) is the minimum time required for an individual to make a motor response in recognition of a given sensory stimulus, such as the time elapsed from the onset of an auditory or visual stimulus to the subject's action of pressing a button. The SRT performance is largely influenced by the structural integrity of the central nervous system due to its dependence on various sensory, motor and cognitive variables. Hence it is commonly used as an important test in probing cognitive issue in development (e.g. Down syndrome, mental retardation) as well as assessing the effects of aging in adults (e.g. dementia, cardiovascular diseases). Moreover, SRT also plays a significant role in the engineering design of driver information systems (e.g. when a driver brakes in front of a stop sign) and in sports science (e.g. when an athlete starts sprinting upon firing of the starting pistol). Therefore, the development of a theoretical framework for SRT, coupled with a study of its neurophysiological underpinning, has considerable importance in biomedical research. A number of empirical laws have been developed to account for SRT performance including Pieron’s law, which describes the relationship between reaction time and stimulus intensity. The equation captures the decreasing pattern of SRT in response to higher stimulus intensity through a power function relationship. Pieron’s law was shown to be effective across different sensory modalities and this universality suggests that it can be derived from a more fundamental approach. Consequently, a theoretical model that describes the universal relationship between the intensity of a given physical stimulus and the corresponding neural response was developed by Norwich et al using an information theory approach. This sensory model was able to give rise to a new SRT equation that is structurally identical to the empirical formula derived by Pieron and was able to provide accurate fits to data obtained from past reaction response experiments. However, this new SRT time model lacks a component that describes the conduction process in sensory and motor neuron and therefore can be potentially improved to give a more physiologically realistic prediction on SRT values. Hence, this study aims to augment this model based on several recent findings on motor pathway conduction. To do this, basic sensory laws as well as statistical properties of the neural response pattern will also be utilized. By comparing it to different sets of experimental data, the advanced SRT model is expected to unite the SRT pattern across the same sensory modality with one unique set of parameters. The result of this study will not only contribute to our knowledge of the physiological basis of neural coding during SRT performance, but more importantly, it will help in the development of clinical assessment tools for cognitive function related diagnosis as well as in other aspects of engineering design for our everyday life.