1. Dashed line delineates the category boundary Cat A Cat B Visual WithinAcrossAuditory Within Cat A Cat B Cat C Cat D Cat A Cat B Cat C Cat D Dashed lines delineate the category boundaries Toward a Deeper Understanding of the Involvement of the Caudate Nucleus in Perceptual Category Learning J. Scott Lauritzen & W. Todd Maddox Institute for Neuroscience and Department of Psychology, The University of Texas at Austin Introduction Procedural learning based system mediates learning of “non-verbalizable” category structures [1] 3. Summary References http://homepage.psy.utexas.edu/homepage/Group/MaddoxLAB/ [1] Maddox, W.T., Ashby, F.G. (2004). Dissociating Explicit and Procedural-Learning Based Systems of Perceptual Category Learning. Behavioral Processes. 66, 309-332. [2] Nomura, E.M., Maddox, W.T., Filoteo, J.V., Ing, A.D., Gitelman, D.R., Parrish, T.B., Mesulam, M-M., Reber, P.J. (Under Review). Neural Correlates of Rule-Based and Information-Integration Category Learning. [3] Seger, C.A., Cincotta, C.M. (2005). The Roles of the Caudate Nucleus in Human Classification Learning. The Journal of Neuroscience. 25(11), 2941-2951. [4] Saint-Cyr, J.A., Ungerleider, L.G., Desimone, R. (1990). Organization of Visual Cortical Inputs to the Striatum and Subsequent Outputs to the Pallido-Nigral Complex in the Monkey. The Journal of Comparative Neurology. 298(2), 129-156. [5] Wilson, C.J. (1995). The Contribution of Cortical Neurons to the Firing Pattern of Striatal Spiny Neurons. (pp. 29-50). Cambridge, MA: MIT Press. [6] Yeterian, E.H. & Pandya, D.N. (1998). Corticostriatal Connections of the Superior Temporal Region in Rhesus Monkeys. The Journal of Comparative Neurology. 399, 384- 402. General MethodsKey Concepts Caudate nucleus receives “many-to-one” convergence of input from perceptual areas [4] Differential input into the caudate nucleus across sensory modalities [5,6] Visual input exclusively into tail [5] Auditory input into head, body, and tail [6] Hypothesis: Perceptually dissimilar items project to different functional units in the caudate, adversely affecting “non-verbal” category learning. 192.10 Human participants view a series of images and categorize each image “Non-verbal” category learning is impaired by discontinuous category structures and cross- modal stimuli The locus of the effects for discontinuous & modality experiments are different Deficits with discontinuous stimuli appear to be due to sub-optimal caudate unit recruitment With cross-modal stimuli many participants employ an incorrect (hypothesis-testing) strategy or resort to random responding 1. Discontinuity Effects Category StructureResults Prediction: Discontinuous category structures should impair “non-verbal” category learning relative to continuous category structures Discontinuous categories impair learning Caudate has difficulty associating perceptually distinct stimuli with the same response PFC=Prefrontal Cortex GP=Globus Pallidus SN=Substantia Nigra Thal=Thalamus H=Head of Caudate B=Body of Caudate T=Tail of Caudate 2. Modality EffectsResultsCategory Structure Identical stimulus values used for generation of 3 types of stimuli Each stimulus type pairs different relevant stimulus dimensions Prediction: Across-modality stimuli should impair “non-verbal” category learning relative to within-modality stimuli Participants displayed deficits with cross- modal stimuli relative to within-modal stimuli Differential sensory input to the caudate nucleus may account for the observed deficits Abstract Two experiments provide empirical evidence that differential perceptual stimuli impair learning of “non-verbalizable” category structures SUBJECT RESPONSE STIMULUSFEEDBACK CORRECT FIXATION Sequence of Events Across Time Continuous stimulus values are immediately adjacent Discontinuous stimulus values introduce within-category separation Caudate Nucleus H B T GP Visual Areas Auditory Areas Thal PFC SN Motor Areas The caudate nucleus, in conjunction with other structures, mediates “non-verbal” category learning [2,3] Acknowledgements: This research was supported in part by National Institute of Health Grant R01 MH59196 to WTM, and a McDonnell-Pew Consortium Grant.