Emeritus Professor of Oculomotor Physiology
My work is mainly concerned with the neural mechanisms that make decisions, and the relation of this to response time; it focuses particularly ion saccades, since where to look next is the single most frequent decision that we make (about 2-3 every second of our waking lives). But I am also interested in quantitative modelling generally in physiology, for instance of cardiac regulation, and have a passionate and continuing commitment to teaching, particularly in encouraging medical students to engage with fundamental concepts rather than rote-learning.
It is increasingly accepted that the brain makes decisions by accumulating information, a quasi-Bayesian process in which a neural signal representing likelihood rises steadily on presentation of a stimulus until it reaches a threshold criterion level at which a response is justified. My LATER model is probably the simplest such model, with very few parameters, and is capable of modelling data about the stochastic distribution of reaction times (which vary randomly from trial to trial) with remarkable accuracy: not just in simple tasks, but in more complex ones such as countermanding, anti-saccades and Wheeless trials, where it predicts the incidence of errors as well. As a result it is being increasingly employed all over the world as a way of obtaining accurate and quantitative measures of higher neural function, for instance in neurodegenerative disorders: with miniaturized portable equipment (a saccadometer) measurements can be made rapidly and non-invasively, and provide independent information about the two hemispheres.
One particular application that is likely to become very significant in the near future is in relation to the diagnosis and monitoring of traumatic brain injury (‘concussion’), a matter of increasing concern especially in young sportsmen and women, and also in military personnel.
IB NHB/NAB (supervisor)
Genest W, Hammond R, Carpenter RHS, (2016) The random dot tachistogram: a novel task that elucidates the functional architecture of decision. Nature Scientific Reports DOI: 10.1038/srep30787, 1-11
Noorani I, Carpenter RHS,(2016) The LATER model of reaction time and decision. Neuroscience and Biobehavioral Reviews 64, 229-251
Noorani I, Carpenter RHS, (2015) Ultra-fast initiation of a neural race by impending errors. Journal of Physiology 593, 4471-84.
Nooran I, Carpenter RHS, (2013), Antisaccades as decisions: LATER model predicts latency distributions and error responses, European Journal of Neuroscience, 37 330-338
Carpenter RHS, Reddi BAJ, (2012) Neurophysiology: a conceptual approach, 5th edition, London: Hodder Arnold
Carpenter RHS, Reddi BAJ, Anderson AJA, (2009), A simple two-stage model predicts response time distributions, Journal of Physiology 587, 4051-4062
Story GW, Carpenter RHS, (2009), Dual LATER-unit model predicts saccadic reaction time distributions in gap, step and appearance tasks, Experimental Brain Research, 193:287-296
Roos JCP, Calandrini DM, Carpenter RHS, (2008), A single mechanism for the timing of spontaneous and evoked saccades, Experimental Brain Research, 187:283-93
Temel Y, Visser-Vandewalle V, Carpenter RHS, (2008), Saccadic latency during electrical stimulation of the human subthalamic nucleus, Current Biology, 18:R412-4
Carpenter RHS, McDonald SA, (2006), LATER predicts saccade latency distributions in reading, Experimental Brain Research, 177: 176-183
Reddi BAJ, Carpenter RHS, (2004), Venous excess: a new approach to cardiovascular control and its teaching, Journal of Applied Physiology, 98: 356-364
Reddi BAJ, Carpenter RHS, (2000), The influence of urgency on decision time, Nature Neuroscience, 3: 827-831
Carpenter RHS, (1999), A neural mechanism that randomises behaviour, Journal of Consciousness Studies, 6: 13-22
Carpenter RHS, Williams MLL, (1995), Neural computation of log likelihood in the control of saccadic eye movements, Nature, 377: 59-62
Carpenter RHS, (1998), Movements of the Eyes, 2nd edition, London: Pion
Blakemore C, Carpenter RHS, Georgeson MA, (1970), Lateral inhibition between orientation detectors in the human visual system, Nature, 228: 37-39