tnet.cls TFJI040-03-144486 November 22, 2005 6:24 Network: Computation in Neural Systems xxx 2005; 16(1): 1–24 Integrating neuronal coding into cognitive models: Predicting reaction time distributions MIKE W. ORAM School of Psychology, University of St Andrews, Fife, KY16 9JP, UK (Received XXX; revised XXX; accepted XXX) 5 Abstract Neurophysiological studies have examined many aspects of neuronal activity in terms of neuronal codes and postulated roles for these codes in brain processing. There has been relatively little work, however, examining the relationship between different neuronal codes and the behavioural phenomena associated with cognitive processes. Here, predictions about reaction time distributions derived from an accumulator model incorporating known neurophysiological data in temporal lobe visual areas of the macaque are examined. Results from human experimental studies examining the effects of changing stimulus orientation, size and contrast are consistent with the model, including qualitatively different changes in reaction time distributions with different stimulus manipulations. The different changes in reaction time distributions depend on whether the image manipulation changes neuronal response latency or magnitude and can be related to parallel or serial cognitive processes respectively. The results indicate that neuronal coding can be productively incorporated into computational models to provide mechanistic accounts of behavioural results related to cognitive phenomena. 10 15 Keywords: Introduction 20 Understanding visual brain function requires precise knowledge of the information present at Q1 Q2 each stage of processing, how this information is encoded (the neuronal code), how different signals associated with different stages of processing are combined (integration of neuronal codes) and how neuronal signals are decoded to produce behaviour. While the general prop- erties of many cortical and sub-cortical areas of both human and non-human primate brains 25 are known, the way in which neurones encode inputs and process information to generate output signals is still under debate. Neuronal codes As the processing ability of the brain is limited by the number of neurones and their con- nections, the presence of additional neuronal codes (signals) within the response of a single 30 neurone (channel) would increase the total information processing power of the brain without Q3 Q4 requiring an increase in the number of neurones. Both spike count assessed over hundreds of milliseconds and fine temporal resolution codes (∼1 ms precision) in visual system neuronal responses have been postulated to carry stimulus related information. Response strength is Correspondence: Mike Oram, School of Psychology, University of St Andrews, Fife, KY16 9JP, UK. Tel: xxxxx. Fax: xxxxx. E-mail: mwo@st-andrews.ac.uk ISSN: 0954-898X print / ISSN 1361-6536 online c  2005 Taylor & Francis DOI: