J. Vincent Filoteo 1,2, W. Todd Maddox 3, David P. Salmon 3, Stephanie L. Lessig 1,2, and David D. Song 1,2 1 VA San Diego Healthcare System; 2 University.

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J. Vincent Filoteo 1,2, W. Todd Maddox 3, David P. Salmon 3, Stephanie L. Lessig 1,2, and David D. Song 1,2 1 VA San Diego Healthcare System; 2 University of California San Diego; 3 University of Texas at Austin Apathy and Perceptual Category Learning in Parkinson's Disease: Possible Role of the Ventral Striatum Apathy is significantly associated with cognitive deficits in patients with Parkinson's disease (PD) and results in greater impairment than depression alone. (1,2) Apathy in PD is also associated with ventral striatal dysfunction (3), a region known to be involved in reinforcement-based learning. (4) No study, however, has examined whether PD patients with high levels of apathy are impaired on such tasks. We examines reinforcement-based learning in high apathy PD patients using an implicit category learning task that is believed to rely on striatal dopamine and has been shown to be sensitive to the cognitive deficits observed in PD patients. (5) BACKGROUND PARTICIPANTS Sixty seven nondemented PD patients were classified as either having clinical levels of apathy (high apathy PD, or PD-HA; n=31) or low apathy (low apathy PD, or PD-LA; n=36) using a cut-off score (>14) from the Apathy Scale (AS) (6). Forty four normal controls (NC) also participated. The mean (SD) for age, years of education (ED), total scores on the Mattis Dementia Rating Scale (MDRS) (7), the AS, and the Geriatric Depression Scale (GDS) (8), for the PD-HA, PD-LA, and NC groups are displayed below. PD-HAPD-LANC PD-HAPD-LANC Age (8.0)(6.1)(8.8) ED (2.7)(2.8)(2.5) MDRS (4.9)(3.9)(3.6) AS (3.2)(3.3)(5.1) GDS (5.6)(4.2)(4.1) The reinforcement-based learning task administered was an implicit learning task developed by Ashby and Gott. (9) Participants were shown stimuli consisting of Gabor patches (see below) and were asked to classify each into one of two categories by pressing one of two computer keys. Six, 80 trial blocks were presented. Following each response, participants were given corrective feedback. A sample trial is displayed below. REINFORCEMENT-BASED LEARNING TASK 1. Aarsland, D., Marsh, L. and Schrag, A. (2009). Neuropsychiatric symptoms in Parkinson's disease. Mov Disord, 24(15): Zgaljardic, D.J., Borod, J.C., Foldi, N.S., Rocco, M., Mattis, P.J., Gordon, M.F., Feigin, A.S., and Eidelberg, D. (2007). Relationship between self-reported apathy and executive dysfunction in nondemented patients with Parkinson disease. Cogn Behav Neurol, 20(3): Remy, P., Doder, M., Lees, A., Turjanski, N. and Brooks, D. (2005). Depression in Parkinson's disease: loss of dopamine and noradrenaline innervation in the limbic system. Brain, 128(Pt 6): Haber, S.N. and Knutson, B. (2010). The reward circuit: linking primate anatomy and human imaging. Neuropsychopharmacology. 35(1): Filoteo, J.V., Maddox, W.T., Salmon, D.P., & Song, D.D. (2005). Information integration category learning in patients with striatal dysfunction. Neuropsychology, 19, Starkstein, S.E., Mayberg, H.S., Preziosi, T.J., Andrezejewski, P., Leiguarda, R., and Robinson, R.G. (1992) Reliability, validity, and clinical correlates of apathy in Parkinson's disease. J Neuropsychiatry Clin Neurosci, 4(2): Mattis, S., Dementia Rating Scale. 1988, Odessa, FL: Psychological Assessment Resources. 8. Yesavage, J.A., Brink, T.L., Rose, T.L., Lum, O., Huang, V., Adey, M., & Leirer, V.O.. (1982). Development and validation of a geriatic depression screening scale: A preliminary report. J Psychiatr Res, 17(1): Ashby, F. G., & Gott, R. E. (1988). Decision rules in the perception and categorization of multidimensional stimuli. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14, REFERENCES REGRESSION ANALYSES CONCLUSIONS The rule that dictated category membership was a nonlinear relationship between the width and orientation of the bars comprising the Gabor patch. The distribution of stimuli is displayed below. Open circles represent Category A exemplars, and closed circles represent Category B exemplars. A or B? Response Correct or Wrong Orientation Spatial Frequency REINFORCEMENT-BASED LEARNING RESULTS Accuracy results are displayed below for the three groups. PD-HA patients were significantly impaired in reinforcement-based learning relative to both PD-LA and NCs, whereas the latter two groups did not differ. Several regression analyses indicated that apathy levels, but not depression levels, predicted performance on the reinforcement-based learning task. Neither apathy or depression predicted performance on the rule-based task PD patients with apathy are impaired in reinforcement-based learning, but not rule- based learning. Although PD patients with apathy also report greater symptoms of depression, depression is not associated with impaired reinforcement- based or rule-based learning. Apathy and impaired reinforcement based learning may share the same neural substrate and could be due to dysfunction within the ventral striatum. Groups did not differ in Age or ED, but PD- HA and PD-LA groups had lower MDRS scores than NCs. PD-HA had greater AS scores than PD-LA and NCs, whereas both PD groups had greater GDS scores than NCs. RULE-BASED LEARNING TASK To examine the specificity of the PD-HA patients’ deficit, we administered a second category learning task where subjects had to categorize single line that varied in length and orientation into one of 4 categories. The rule that dictated category membership depended on the length of the line and orientation was irrelevant. The figure below displays the category exemplars, with squares representing Category A exemplars, circles representing Category B exemplars, closed triangles representing Category C exemplars, and open triangles representing Category D exemplars. RULE-BASED LEARNING RESULTS PD-HA and PD-LA differed from controls but not from one another.