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Cognitive correlates of psychosis in patients with Parkinson's disease abc

Ahmed A. Moustafa f

d

e

, Rakhee Krishna , Michael J. Frank , Abeer

M. Eissa & Doaa H. Hewedi

f

a

Department of Veterans Affairs, New Jersey Health Care System, East Orange, NJ, USA b

School of Social Sciences and Psychology, University of Western Sydney, Sydney, NSW, Australia c

Marcs Institute for Brain and Behaviour, University of Western Sydney, Sydney, NSW, Australia d

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Department of Psychology, Rutgers University, New Brunswick, NJ, USA e

Department of Cognitive, Linguistic Sciences and Psychological Sciences, Brown Institute for Brain Science, Brown University, Providence, RI, USA f

Psychogeriatric Research Center, Institute of Psychiatry, Faculty of Medicine, Ain Shams University, Cairo, Egypt Published online: 21 Jan 2014.

To cite this article: Ahmed A. Moustafa, Rakhee Krishna, Michael J. Frank, Abeer M. Eissa & Doaa H. Hewedi (2014) Cognitive correlates of psychosis in patients with Parkinson's disease, Cognitive Neuropsychiatry, 19:5, 381-398, DOI: 10.1080/13546805.2013.877385 To link to this article: http://dx.doi.org/10.1080/13546805.2013.877385

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Cognitive Neuropsychiatry, 2014 Vol. 19, No. 5, 381–398, http://dx.doi.org/10.1080/13546805.2013.877385

Cognitive correlates of psychosis in patients with Parkinson’s disease Ahmed A. Moustafaa,b,c*, Rakhee Krishnad, Michael J. Franke, Abeer M. Eissaf and Doaa H. Hewedif

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a

Department of Veterans Affairs, New Jersey Health Care System, East Orange, NJ, USA; bSchool of Social Sciences and Psychology, University of Western Sydney, Sydney, NSW, Australia; cMarcs Institute for Brain and Behaviour, University of Western Sydney, Sydney, NSW, Australia; d Department of Psychology, Rutgers University, New Brunswick, NJ, USA; eDepartment of Cognitive, Linguistic Sciences and Psychological Sciences, Brown Institute for Brain Science, Brown University, Providence, RI, USA; fPsychogeriatric Research Center, Institute of Psychiatry, Faculty of Medicine, Ain Shams University, Cairo, Egypt (Received 16 August 2013; accepted 16 December 2013) Introduction. Psychosis and hallucinations occur in 20–30% of patients with Parkinson’s disease (PD). In the current study, we investigate cognitive functions in relation to the occurrence of psychosis in PD patients. Methods. We tested three groups of subjects – PD with psychosis, PD without psychosis and healthy controls – on working memory, learning and transitive inference tasks, which are known to assess prefrontal, basal ganglia and hippocampal functions. Results. In the working memory task, results show that patients with and without psychosis were more impaired than the healthy control group. In the transitive inference task, we did not find any difference among the groups in the learning phase performance. Importantly, PD patients with psychosis were more impaired than both PD patients without psychosis and controls at transitive inference. We also found that the severity of psychotic symptoms in PD patients [as measured by the Unified Parkinson Disease Rating Scale Thought Disorder (UPDRS TD) item] is directly associated with the severity of cognitive impairment [as measured by the mini-mental status exam (MMSE)], sleep disturbance [as measured by the Scales for Outcome in Parkinson Disease (SCOPA) sleep scale] and transitive inference (although the latter did not reach significance). Conclusions. Although hypothetical, our data may suggest that the hippocampus is a neural substrate underlying the occurrence of psychosis, sleep disturbance and cognitive impairment in PD patients. Keywords: cognition; psychosis; Parkinson’s disease; working memory; learning; transitive inference

Psychosis and visual and olfactory hallucinations occur in approximately 20–30% of Parkinson’s disease (PD) patients (Rabey, 2009). In PD patients, visual hallucinations are more common than auditory or olfactory hallucinations (Diederich, Fenelon, Stebbins, & Goetz, 2009). Although it was previously believed that the administration of dopaminergic drugs is the main cause of psychosis and hallucinations, recent studies additionally show that sleep disturbance, longer disease duration and advanced stage of the disease are also risk factors for the occurrence of psychotic symptoms in PD patients (Bannier et al., *Corresponding author. Email: [email protected] © 2014 Taylor & Francis

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2012; Fenelon, 2008; Gibson et al., 2012; Poewe, 2003). This suggests that there might also be a non-dopaminergic neural pathway involved in the occurrence of psychotic episodes in at least a subset of PD patients. Studies also show that isolated delusions and delusional jealousy occur in PD (Poletti et al., 2012; Stefanis et al., 2010), although they are less common than the occurrence of hallucinations (Poletti et al., 2012). Frequency of hallucinations and delusions varies in PD depending on many factors, including cognitive impairment and dementia severity (Leroi, Pantula, McDonald, & Harbishettar, 2012). For example, studies found that delusions are less common in PD patients with intact cognitive function (Debs et al., 2010; Stefanis et al., 2010). Studies also show that hallucinations (more than delusional jealousy) are more related to the occurrence of dementia (Poletti et al., 2012). Recent studies show that isolated delusions and delusional jealousy are closely related to the administration of dopamine medications (Poletti et al., 2012). These studies suggest that different psychotic phenomena are associated with different clinical and potentially different neural substrates in PD. Psychosis in PD is also a risk factor for the occurrence of severe cognitive dysfunctions such as dementia (Factor et al., 2003) and is associated with a diminished quality of life (Rabey, 2009; Zahodne & Fernandez, 2008b). However, there have been very few studies investigating the neurocognitive correlates of psychosis and PD. For example, studies have shown that PD patients with hallucinations are more impaired than PD patients without hallucination on recognition memory (Barnes, Boubert, Harris, Lee, & David, 2003), executive functions (Grossi et al., 2005), cognitive functions as measured using the frontal assessment battery, attentional processes (Meppelink, Koerts, Borg, Leenders, & van Laar, 2008) and semantic fluency (Ramirez-Ruiz, Junque, Marti, Valldeoriola, & Tolosa, 2006). For example, in schizophrenia and other psychoses it has been suggested that psychosis and hallucinations can stem from dysfunction to either the prefrontal cortex (Corlett, Honey, & Fletcher, 2007; Fletcher & Frith, 2008), basal ganglia (Frank, 2008; Howes et al., 2012) or hippocampal region (Bogerts, Meertz, & Schonfeldt-Bausch, 1985; Goldman & Mitchell, 2004; Grace, 2010; Keri, 2008; Weinberger, 1999). There are fewer studies investigating the neural underpinnings of the occurrence of psychosis and hallucinations in PD. Prior studies suggest that hallucinations in PD patients can be due to either cortical or subcortical atrophy (Papapetropoulos, McCorquodale, Gonzalez, Jean-Gilles & Mash, 2006). Studies report impaired temporal lobe function (Botha & Carr, 2012; Harding, Broe, & Halliday, 2002; Oishi et al., 2005) and increased activation of visual association cortex (Holroyd & Wooten, 2006) in PD patients with visual hallucination. Other studies showed increased activations in various cortical areas and the striatum in PD patients with hallucinations (Stebbins et al., 2004). Structural imaging studies also showed grey matter volume reductions in the parietal lobe in PD patients with hallucinations (Ramirez-Ruiz et al., 2007). To our knowledge, we are not aware of any studies implicating the prefrontal cortex in the occurrence in psychosis and hallucinations in PD patients. Considering the paucity of research in studying cognition in PD patients with psychosis, we proposed to investigate the association of some cognitive functions with psychosis in PD. These cognitive functions (including working memory, associative learning and transitive inference) have been shown to be involved with some of the neural structures implicated in psychosis as well as PD. Various studies have shown that working memory performance relies on the integrity of the prefrontal cortex (Goldman-Rakic, 1995; Perlstein, Dixit, Carter, Noll, & Cohen, 2003; Sawaguchi, 2001). Both animal and human studies have found a strong relationship

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between the prefrontal cortex and working memory (Barch et al., 1997; Castner & Goldman-Rakic, 2004; Gazzaley, Rissman, & Desposito, 2004; Goldman-Rakic, Muly, & Williams, 2000; Perlstein, Carter, Noll, & Cohen, 2001). On the contrary, associative learning, which involves learning to associate novel stimuli with certain responses, based on corrective feedback recruits the basal ganglia (Atallah, Lopez-Paniagua, Rudy, & O’Reilly, 2007; Howe, Atallah, McCool, Gibson, & Graybiel, 2011). Functional imaging studies also found that the basal ganglia is activated during the performance of learning tasks in human subjects (Poldrack et al., 2001; Rodriguez, Aron, & Poldrack, 2006). In addition, learning has been associated with the dopaminergic system and its projection to the basal ganglia (Beeler et al., 2010; D’Ardenne, McClure, Nystrom, & Cohen, 2008; Kerr & Wickens, 2001; Matsumoto, Hanakawa, Maki, Graybiel, & Kimura, 1999; Waelti, Dickinson, & Schultz, 2001). Transitive inference is a cognitive function that has been shown to rely on the hippocampal system in both animals and humans (Dusek & Eichenbaum, 1997; Frank, Rudy, & O’Reilly, 2003; Greene, Gross, Elsinger, & Rao, 2006; Heckers, Zalesak, Weiss, Ditman, & Titone, 2004). For example, transitive inference is used when one is told that Daniel is older than Peter, who is older than John, and then one logically infers that Daniel is also older than John. Computational models also show that hippocampal damage can impair transitive inference performance but not other cognitive processes (Siekmeier, Hasselmo, Howard, & Coyle, 2007). Working memory and transitive memory were found to correlate with psychotic episodes in other patient populations (e.g., schizophrenia; see Cohen, Barch, Carter, & Servan-Schreiber, 1999; Titone, Ditman, Holzman, Eichenbaum, & Levy, 2004), but it has not been studied in PD. These tasks have been previously known to probe the function of the prefrontal cortex, basal ganglia and hippocampus. Further, most prior studies on hallucinations and psychosis in PD patients did not include healthy control subjects (Grossi et al., 2005) and usually tend to use clinical questionnaires rather than computerised cognitive tasks (Baydas, Ozer, Yasar, Tuzcu, & Koz, 2005). In the current study, we use computerised cognitive tasks to assess working memory, associative learning and transitive inference in healthy controls, PD patients with psychosis and PD patients without psychosis, in an attempt to understand the potential neurocognitive correlates of psychosis in PD. Methods Subjects We tested three groups of subjects: healthy controls, PD patients with psychosis and PD patients without psychosis (Table 1). As in our prior studies (Moustafa, Cohen, Sherman, & Frank, 2008; Moustafa, Sherman, & Frank, 2008), healthy control subjects were spouses of patients who tended to be fairly well matched demographically. We recruited all subjects from the Psychogeriatric Research Centre, Institute of Psychiatry, Ain Shams University. All subjects signed statements of informed consent before testing was initiated. The ethics committee at Ain Shams University’s School of Medicine approved this study, and research conformed to the guidelines for the protection of human subjects established by the university. Eligible subjects who declined to participate were not disadvantaged in any way by not participating in the study. The testing session lasted approximately 50–60 minutes for healthy controls and 65–75 minutes for PD patients. We evaluated psychosis using clinician-rated questionnaire. Specifically, based on prior studies, psychosis was defined as involving one of the following symptoms: illusions

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Table 1. Group demographic, clinical and behavioural data for medicated PD patients, unmedicated PD patients and healthy control groups.

N Age Sex (M/F) Education (years) Apathy BDI MMSE SCOPA-sleep NAART LEDD H&Y UPDRS Disease duration

Controls

PD patients with psychosis

PD patients without psychosis

P value

22 66.4 (4.9) 16/8 14.3 (1.2) 36.5 (6.9) 7.8 (1.5) 26.3 (2.4) 4.5 (4.1) 35.3 (6.5) – – – –

21 68.2 (4.1) 14/7 14.1 (1.6) 37.2 (8.2) 7.9 (2.3) 23.8 (2.5) 8.9 (7.2) 32.6 (11.3) 943.5 (72.8) 2.81 (0.73) 21.8 (6.3) 11.1 (3.4)

23 66.7 (4.0) 16/7 13.6 (1.9) 38.2 (7.4) 7.6 (1.5) 25.7 (1.8) 7.3 (6.4) 33.2 (12.4) 883.1 (78.9) 2.37 (0.51) 20.8 (5.6) 9.61 (2.9)

0.164 0.43 0.123 0.482 0.321 0.212 0.103 0.301 0.121 0.401 0.24 0.113

Note: Values here represent mean (SD). Abbreviations: BDI, Beck Depression Inventory; MMSE, Mini-Mental State Examination; SCOPA-sleep, Scales for Outcome in Parkinson Disease Sleep questionnaire; NAART, North American Adult Reading Test; LEDD, levodopa equivalent daily dose; H&Y, Hoehn & Yahr staging of PD; UPDRS, Unified Parkinson’s Disease Rating Scale.

(misinterpretations of existing stimuli), hallucinations (defined as hallucinatory symptoms) and/or delusional symptoms. Psychosis was confirmed using the Parkinson’s Psychosis Rating Scale (Friedberg, Zoldan, Weizman, & Melamed, 1998) and the Unified Parkinson Disease Rating Scale Thought Disorder (UPDRS TD) item (Forsaa et al., 2010). Psychosis associated with PD was defined as a UPDRS TD score of 2 or more, as in prior studies (Forsaa et al., 2010). We recruited PD patients who must have had one of these psychotic symptoms for at least one month to be included in our PD with psychosis group. In addition, we also limited our recruitment to patients who had PD for at least one year prior to the onset of psychotic symptoms. All subjects were required to obtain a score of at least 23 in the mini-mental status exam (MMSE; Folstein, Folstein, & McHugh, 1975) to be considered for the study, as in prior studies of hallucinations in PD patients (Grossi et al., 2005). Unlike our prior studies on PD (where we used MMSE score cut-off of 26), in the present study we recruited PD patients with lower MMSE scores to allow for a greater variance in the distribution of MMSE scores for the group and thus test the relationship between cognitive impairment, dementia and psychosis (Factor et al., 2003). We excluded subjects who scored more than 10 in the Beck Depression Inventory (BDI) to minimise confounding effects of depression. Furthermore, we also excluded all PD patients who were on cholinergic or serotonergic medications. Altogether, we excluded six subjects based on the abovementioned criteria (four patients with psychosis and two patients without psychosis). In addition, two subjects did not learn one of the tasks mentioned here (one patient without psychosis and one patient with psychosis), so we did not include their data in the analysis here. After excluding these subjects from further analysis, the final study sample consisted of 22 healthy controls, 21 PD patients with psychosis and 23 PD patients without psychosis (see Table 1). We further assessed quality of sleep in all subjects using the Scales for Outcome in Parkinson Disease (SCOPA) sleep scale (Marinus, Visser, van

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Hilten, Lammers, & Stiggelbout, 2003), which measures sleep quality and disturbance during the day and night. All groups were matched in age, education, memory performance (as measured by MMSE), verbal intellectual abilities (as measured by North American Adult Reading Test, NAART), Levodopa Equivalent Daily Dose (LEDD), severity of motor symptoms (as measured by UPDRS), PD stage (as measured by Hoehn & Yahr) and sleep disturbance (as measured by SCOPA-sleep). Although non-significant, disease duration (i.e., number of years with PD) was larger in PD patients with psychosis than in PD patients without psychosis (Table 1), which is in agreement with prior empirical results (Diederich et al., 2009). Cognitive tasks We tested all subjects on three cognitive tasks: short-delay working memory, long-delay working memory (as used in our prior study; Moustafa, Bell, Eissa, & Hewedi, 2013) and transitive inference. Short-delay working memory task (Moustafa et al., 2013) The task used here is a variation of delayed-response task used extensively in animal (Goldman-Rakic, 1995) and human (Paxton, Barch, Racine, & Braver, 2007) studies. Subjects were presented with a sequence of letter stimuli (H,K,Z,P) on a computer screen and were instructed to press one of two keys to each letter presentation. Subjects were presented with H before Z, H before P, K before Z and K before P. Here, subjects had to discover the target sequence by trial and error (i.e., correct or incorrect feedback). Subjects were instructed to press the left button for each cue and the right button when they think they have seen the target sequence. In this task, correct response to a stimulus depends on which stimulus preceded it before the delay interval – thus, it is a working memory task. The delay interval between stimulus presentations was 1 second. After each probe stimulus, feedback (correct vs. incorrect) informed the subjects whether they were correct or incorrect. To receive correct feedback, the subjects pressed one key to indicate “target sequence”, whereas they pressed another key for all other sequences of stimuli to indicate “non-target sequences”. All other responses lead to incorrect feedback. For similar task designs, see Barch et al. (1997), Cohen et al. (1999), Moustafa et al. (2008) and Paxton et al. (2007). Long-delay working memory task This task is identical to the short-delay working memory task, except that here we used different letters (M,T,R,S) and the delay interval was 5 seconds (for more details, see Moustafa et al., 2013). The purpose of manipulating the length of the delay interval is to test the effects of PD and psychosis on maintenance of information in working memory. Transitive inference task The transitive inference task consists of training and test phases (Moses, Villate, & Ryan, 2006). The training phase consisted of four subphases of blocked trials, followed by a fourth subphase of randomly interleaved trials. As in prior studies by Frank et al. (2003), each training subphase was terminated after the subject achieved criterion performance of at least 75% correct across all pairs and at least 60% correct on each individual pair. In the first training subphase, the premise pairs were presented in blocks of five trials, such

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that the first block consisted of AB trials, the second block consisted of BC trials, and so on. AB and BC represent the pair of stimuli (fractals) presented to the subjects (see Figure 1). In the second subphase, we used blocks of six trials, but distractor pairs from other blocks were inserted in the middle and end of each block. As in prior studies with the same task (Frank, O’Reilly, & Curran, 2006), such trials disrupt the descending order of hierarchical presentation, making the stimulus hierarchy less obvious. We used a similar method for the third subphase, except that there were 4 trials per block and a distractor pair only in the fourth trial, and in the fourth subphase, stimulus pairs were randomly interleaved for a total of 20 trials before criterion performance was evaluated. If the criterion was not met, the random sequence was repeated. The test phase was similar to the final training phase in that all pairs were randomly interleaved. However, no feedback was provided, and the novel test pairs AE and BD were added to the other randomly ordered pairs. Each pair was presented six times. Importantly, successful AE performance is trivial, because A was always reinforced during training and E was never reinforced. In contrast, because B and D were reinforced equally often during training, the selection of B over D is taken to indicate that an inference has been made (see Frank et al., 2006). Subjects were given the following instructions: “Two figures will appear simultaneously on the computer screen. You are to select the ‘correct’ figure as quickly and accurately as possible”. For each stimulus pair, subjects used the “z” and “m” keys to select the stimulus on the left or right, respectively. The position of each character was

Figure 1.

Examples of the stimuli used in the transitive inference task.

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counterbalanced across trials. Feedback consisted of the word “Correct!” written in blue letters or the word “Incorrect” written in red letters. Our task is similar to other transitive inference tasks used in the literature (Frank et al., 2006; Frank, Rudy, Levy, & O’Reilly 2003, 2005; Frankland et al., 2004; Greene, Spellman, Dusek, Eichenbaum, & Levy, 2001), except here we used fractals instead of letters (Figure 1; also see for example, Moses et al., 2006). Statistical analysis We performed between-subjects analysis of variance (ANOVA) to compare working memory and transitive inference performance among PD patients with psychosis, PD patients without psychosis and healthy control subjects. For all analyses, we used SPSS19.0 (SPSS Inc., Chicago, IL, USA) to examine between-subject differences. Where indicated, we additionally tested for specific planned contrasts. Further, given that MMSE score might influence working memory and learning performance, we have conducted an analysis of covariance (ANCOVA) using MMSE as a covariate.

Results Group differences Working memory Results show no difference among the groups at performing the short-delay working memory task (p > 0.23; Figure 2a). However, we found that both patients with and without psychosis were more impaired than healthy controls at the long-delay working memory task (p’s < 0.02; Figure 2b). We did not find any difference between the two PD patient groups at performing the long-delay working memory task (p > 0.34; Figure 2b). Transitive inference We found no difference among the groups at performing the learning phase of the task (all p’s > 0.32; Figure 3a). In the transfer phase, there was no difference among the groups at performing the AE pair (all p’s > 0.17; Figure 3b), which is a simple control condition because A was always reinforced and E was never reinforced.

Figure 2. Working memory performance in healthy controls, psychotic and non-psychotic PD patients. (a) Working memory short-delay: there was no effect among all groups in the short-delay working memory task. (b) Working memory long-delay: both psychotic and non-psychotic PD patients were more impaired than healthy controls at the long-delay working memory task. Abbreviations: PD-Psy, PD patients with psychosis; PD-nonPsy, PD patients without psychosis.

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Figure 3. Transitive inference performance in healthy controls, psychotic and non-psychotic PD patients. (a) Learning: there was no effect among all groups in the learning phase. (b) Transfer phase (AE pair): there was no difference among the group on performing the AE pair. (c) Transfer phase (BD pair): psychotic PD patients were more impaired than non-psychotic and healthy controls at performing the BD pair.

However, in the transfer phase, we found that PD patients with psychosis, but not PD patients without psychosis, were more impaired than healthy controls at performing the critical BD pair (p < 0.006; Figure 3c), indicating impaired transfer performance in PD patients with psychosis. Given that MMSE, rather than group or occurrence of psychosis, might affect working memory and learning performance, we ran an ANCOVA with MMSE as a covariate on all the scores reported earlier (working memory tasks and transitive inference task phases). Results show that p values show minor changes to prior results, which suggests prior patterns of results hold regardless of the effect of MMSE scores. Effects of psychosis severity on memory, sleep and transitive inference We also tested the effect of psychosis severity on memory and sleep function. We found that the severity of psychosis – as measured by the Unified Parkinson’s Disease Rating Scale thought disorder (UPDRS TD) item – is associated with more increased cognitive impairment symptoms and sleep disturbance. Specifically, MMSE scores were significantly lower in PD patients with severe psychosis (UPDRS TD = 4) than in PD patients with less severe psychosis (UPDRS TD = 2) (p < 0.02; Figure 4a). There was no difference in MMSE scores between PD patients with UPDRS TD = 3 and the other PD patient groups with psychosis (all p’s > 0.14). Similarly, SCOPA-sleep scores were significantly larger in PD patients with severe psychosis (UPDRS TD = 4) than in PD patients with less severe psychosis (UPDRS TD = 2)

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Figure 4. The relationship between severity of psychosis and (a) cognitive impairment and (b) sleep disturbance. Increased psychotic symptoms in PD are associated with (a) lower memory performance and (b) higher sleep disturbance. Abbreviation: UPDRS TD, Unified Parkinson’s Disease Rating Scale Thought Disorder item.

(p < 0.01, Figure 4b). There was no difference in SCOPA-sleep scores between PD patients with UPDRS TD = 3 and other PD patient groups with psychosis (all p’s > 0.12). We further tested the effects of psychosis severity on transitive inference performance (Figure 5). There was no difference in learning scores between any of the PD patients with psychosis (Figure 5a; all p’s > 0.17). Same pattern of results was true for transfer performance on the AE pair, as there was no difference among the patients with psychosis (Figure 5b; all p’s > 0.2). There was no difference in BD pair performance scores between PD patients with UPDRS TD = 3 and the other PD patient groups with psychosis (all

Figure 5. The relationship between severity of psychosis and transitive inference. (a) Learning: there was no effect among all groups in the learning phase. (b) Transfer phase (AE pair): there was no difference among the group on performing the AE pair. (c) Transfer phase (BD pair): although non-significant, here we found that PD patients with UPDRS TD = 4 were more impaired than PD patients with UPDRS TD = 2 at performing the critical BD pair (p < 0.061), indicating impaired transfer performance in PD patients with more severe psychosis.

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p’s > 0.18). Although non-significant, in the transfer phase, we found that PD patients with UPDRS TD = 4 were more impaired than PD patients with UPDRS TD = 2 at performing the critical BD pair (p < 0.061; Figure 5c), indicating impaired transfer performance in PD patients with more severe psychosis.

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Discussion In the current study, we tested the cognitive correlates of psychosis in PD patients. Our data show that psychosis in PD patients is associated with impaired transitive inference, and perhaps suggest hippocampal dysfunction in PD patients with psychosis. Our data are similar to results from studies on transitive inference in schizophrenia, where patients also showed impairment at performing the BD pair, as found by Titone et al. (2004). Our data are in agreement with prior data showing a relationship between psychosis, dementia and cognitive impairment in PD. Prior studies identified a complex relationship among these variables in PD. For example, studies suggest that psychosis in PD is a risk factor for the development of dementia (Factor et al., 2003). On the other hand, other studies showed that cognitive impairment (Fenelon, Mahieux, Huon, & Ziegler, 2000; Zahodne & Fernandez, 2008b) and dementia (Papapetropoulos, Argyriou, & Ellul, 2005) are risk factors for the development of psychosis in PD patients. Further, one study suggested that spatial working memory impairment is a risk factor for the occurrence of psychosis in PD patients (Wood et al., 2003). It is also important to note that the relationship between cognitive impairment, dementia and psychosis depends on the type of psychosis, as it was shown that hallucinations are more related to the occurrence of dementia than delusions (Perugi et al., 2013; Poletti et al., 2012). Interestingly, empirical studies suggest that cholinesterase inhibitors (which are standard medications for dementia and memory dysfunction) are efficient for the treatment of psychosis in PD (Weintraub & Burn, 2011; Williams-Gray, Foltynie, Lewis, & Barker, 2006; Zahodne & Fernandez, 2008a). Given that cholinesterase inhibitors act on the hippocampus as well as on other neural structures (Autio et al., 2011; Tanaka, Mizukawa, Ogawa, & Mori, 1995; Wu et al., 2003), this is in agreement with our hypothesis that psychosis in PD may be related to hippocampal dysfunction. Along the same lines, studies found a relationship between MMSE measures and the hippocampus in individuals with mild cognitive impairment (Slavin, Sandstrom, Tran, Doraiswamy, & Petrella, 2007) and PD patients (Bruck, Kurki, Kaasinen, Vahlberg, & Rinne, 2004; Camicioli et al., 2003). Our findings on the relationship between psychosis and putative hippocampal function explain links between psychosis, sleep disturbance and cognitive impairment, although further studies are needed to test their links to dementia. It is possible that hippocampal dysfunction is a common factor among all of these symptoms in PD patients (although motor dysfunction stems from basal ganglia dysfunction as reported in a multitude of studies). Other theories suggest that the occurrence of hallucinations in PD patients can be due to prefrontal cortex, basal ganglia and dopamine abnormalities (Botha & Carr, 2012). Specifically, Botha and Carr (2012) argue that the gating of irrelevant information to working memory is the mechanism underlying the occurrence of hallucinations. It is possible that we did not find significant behavioural differences between PD patients with and without psychosis on working memory as our tasks assess the maintenance of information in working memory rather than gating of information into working memory.

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Future work should assess the contribution of different working memory sub-processes to the occurrence of psychotic episodes and hallucinations in PD patients.

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Hippocampus, medial temporal lobe and psychosis Psychosis and hallucinations in various psychiatric disorders, including schizophrenia, were found to be associated with hippocampal dysfunction (Bogerts et al., 1985; DeRosse et al., 2007; Goldman & Mitchell, 2004; Grace, 2010; Keri, 2008; Weinberger, 1999). For example, a body of data suggest that psychosis in schizophrenia results from hyperdopaminergic activity in the hippocampus (for experimental support, see DeRosse et al., 2007; Krieckhaus, Donahoe, & Morgan, 1992; Tamminga, Stan, & Wagner, 2010; Zierhut et al., 2010). In addition to empirical results, various computational and theoretical models argue that psychosis may be caused by hippocampal damage (Chen, 1995; Grace, 2010; Lisman, Pi, Zhang, & Otmakhova, 2010; Moustafa & Gluck, 2011). Chen (1995) proposed an attractor neural network which shows that psychosis is related to aberrant retrieval of information from memory. Chen’s model shows that an increase of correlation of encoding inputs in the hippocampus interferes with retrieval processes, such that the model will retrieve wrong information at the wrong time. Chen argues that the retrieval of wrong information from the hippocampus’s long-term memory store corresponds to psychotic symptoms. Lisman et al. (2010) have provided an alternative theory to how hippocampal dysfunction leads to psychotic episodes. Lisman et al. argue that N-methyl-D-aspartate receptor (NMDA) dysfunction increases the activity of CA1, which in turn increases firing of dopamine, and thus causes psychosis. Similarly, Grace (2010) argues that hippocampal damage is responsible for increased dopamine levels and thus psychotic episodes in schizophrenia. Other theoretical models argue that the pattern completion function explains psychosis (Tamminga et al., 2010). Specifically, Tamminga et al. argue that excessive pattern completion, due to hippocampal dysfunction, could lead to illusions and psychotic episodes. Tamminga et al.’s data are in agreement with our results in that the hippocampus seems to be the neural substrate for the occurrence of psychosis across different brain disorders. The occurrence of psychosis in our samples may stem from aberrant processing in the hippocampus, including excessive pattern completion or wrong retrieval of information from long-term memory. Although not explicitly measured in the present study, we (DHH and AME) observed long-term memory impairment (including forgetting and confabulation) in many PD patients with psychosis in our sample; we did not observe these symptoms in PD patients without psychosis. Our data are also in line with prior clinical reports on temporal lobe dysfunction in PD patients with visual hallucination (Botha & Carr, 2012) and also with studies showing that early onset of hallucinations in PD patients is associated with dysfunction to the parahippocampus and inferior temporal cortex (Harding et al., 2002). Interestingly, it was found that carrying the APOE ε4 allele, which is associated with a small hippocampal volume in healthy older subjects (Alexopoulos et al., 2011), is also a risk factor for the development of psychotic episodes in PD patients (de la Fuente-Fernandez, Nunez, & Lopez, 1999; Feldman, Chapman, & Korczyn, 2006; J. G. Goldman, Goetz, BerryKravis, Leurgans, & Zhou, 2004). Like hallucinations, many studies in schizophrenia and other psychotic disorders suggest that the occurrence of delusions is related to temporal lobe dysfunctions (Cummings, 1992; Pankow, Knobel, Voss, & Heinz, 2012). These

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studies also suggest that the hippocampus is possibly associated with the occurrence of psychosis in PD patients.

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Study limitations Our study has a few limitations. One limitation of our study is that all of our patients were medicated. Thus, we did not test medication effects on the occurrence of psychosis in PD patients. Although research has shown that psychosis in PD is related to the administration of dopaminergic medications (Morgante et al., 2012), other factors including cognitive impairment, dementia, disease severity and sleep disorders are also associated with the occurrence of psychotic episodes in PD (Fenelon, Goetz, & Karenberg, 2006; Lee & Weintraub, 2012; Morgante et al., 2012). Future research at our lab will test medication withdrawal on the occurrence of psychotic episodes in PD patients. Another limitation is we did not test perceptual functions in our patients. Prior studies have shown that hallucinations and psychosis in PD patients are associated with visual disturbance (Gallagher & Schrag, 2012; Shine, Halliday, Carlos, Naismith, & Lewis, 2012). However, this is unlikely to alter the interpretations of our results, given that PD patients with psychosis in our study were successful at performing some aspects of the transitive inference task (see Figure 3), and thus did not show a global cognitive dysfunction. It is possible that behavioural differences between PD patients with and without psychosis can be observed during the performance of complex perceptual tasks (Shine, Halliday, Naismith, & Lewis, 2011). Our data do not also preclude a role of attentional or prefrontal mechanism in the occurrence of psychosis in PD patients; it is possible that more demanding attentional and prefrontal tasks are needed to dissociate performance in PD patients with and without psychosis than the working memory tasks used in our study. There is a controversial body of data on the role of the hippocampus in transitive inference. One study argued that the more implicit form of transitive inference does not depend on hippocampus but mainly on the reinforcement value of stimuli, impacted by striatal dopamine (Frank et al., 2006; Frank, Seeberger, & O’Reilly, 2004). Accordingly, giving the drug midazolam (which inhibits the prefrontal cortex and hippocampus) actually resulted in improved BD performance in the transitive inference task (Frank et al., 2006). On the other hand, it is also argued that the role of the hippocampus in transitive inference may depend on awareness measures, as medicated by the hippocampal region (Frank et al., 2006; Frank, O’Reilly, & Curran, 2008; Libben & Titone, 2008). As we did not collect awareness measures, our study does not provide an answer to this point. It is also important to note that hippocampal dysfunction in our study was suggested by only one parameter of one cognitive task; therefore, our findings need to be confirmed by other cognitive tasks assessing hippocampal function. Another limitation is that the small of number of PD patients with psychosis in our study did not allow us to test the effects of individual differences of psychosis on sleep and memory. Further, some of our patients (N = 13) did not complete the Parkinson’s Psychosis Rating Scale, thus making it more difficult to dissociate the effects of psychosis type (hallucinations vs. delusions), although observations by the psychiatrists indicate most, if not all, of our patients suffer mainly from hallucinations, and thus our results are more likely to be related to the severity of hallucination symptoms in the patients. Although statistically non-significant, we found that patients with psychosis show increased sleep disruption, slightly larger cognitive impairment scores and larger medication dosage than PD patients without psychosis (see Table 1). We also found a trend for

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significance in transfer performance on BD pair in relation to psychosis severity. Our findings are in agreement with prior studies showing strong links between medication dosage, cognitive impairment, sleep disturbance and psychosis in PD patients (Bannier et al., 2012; Fenelon, 2008; Gibson et al., 2012; Poewe, 2003). In summary, our data show that psychosis in PD patients is associated with impaired transitive inference, and may suggest hippocampal dysfunction in the patients. In addition, we show that severe psychotic symptoms in PD patients are associated with impaired memory and sleep disturbance. Our data are in agreement with prior results showing that cognitive impairment and sleep disturbances are more common among PD patients with psychosis than in PD patients without psychosis. We hypothesise that the occurrence of psychosis, dementia and sleep disturbance might be caused by hippocampal damage in a subset of PD patients. Future imaging studies should confirm or disconfirm this hypothesis. Acknowledgements Ahmed A. Moustafa, Rakhee Krishna, Abeer M. Eissa, and Doaa H. Hewedi contributed equally to this work.

Funding This research was partially supported by a 2013 Internal UWS Research Grant Scheme award [grant number P00021210] to AAM.

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