CHOLINERGIC INNERVATION OF SOCIAL COGNTION
IN RECENT ONSET PSYCHOTIC DISORDER
Final Report for the Master Internship project of Iris Marchal
at the
Department of Nuclear Medicine Academic Medical Centre, Amsterdam
Supervisor: Geor Bakker, PhD
Co-assessor/ UvA Representative: Dr. Harm Krugers
Background: Current treatment for psychotic disorders shows little to no improvement of cognitive symptoms. Patients show deficits on cognitive domains such as working memory, processing speed and attention. More recently, studies also identified deficits in social cognition. Patients show specifically deficits in recognition and perception of facial expressions of disgust. Recent research has identified the M1 receptor of the muscarinic system to play a critical role in cognitive functioning. A postmortem study found lowered levels of M1 expression and in-vivo studies found decreased levels of acetylcholine in schizophrenic patients, indicating this system is affected in psychotic disorders. To date, M1 expression has never been assessed in-vivo and deficits in cholinergic neurotransmission have only been assessed in schizophrenia, not at the begin stages of psychosis. Therefore, the current study seeks to investigate the role of cholinergic neurotransmission and M1 receptor expression in relation social cognitive functioning in patients which recently developed psychosis.
Methods: We included 36 normal intelligence adults; 18 with recent onset psychotic disorder and 18 healthy controls who did not differ significantly in age, IQ or gender. All participants underwent a neuropsychological Emotion Recognition Test (ERT) to assess impairments in emotion recognition of the six universal basic emotions (anger, sadness, disgust, happiness, surprise, fear). Additionally, we used event-related functional magnetic resonance imaging (fMRI) to examine neural responses when participants processed facial expressions of disgust. Lastly, M1 receptor binding potential was assessed in patients using single-photon emission
computed tomography (SPECT) imaging.
Results: The ERT showed that patients most often misidentified facial expressions of disgust and were significantly worse in identifying disgust stimuli compared to healthy control subjects. Results from fMRI task revealed a significant hypoactivation of the superior and medial frontal gyrus under cholinergic challenge during emotion recognition of disgust in patients. Degree of hypoactivation in these regions also positively correlated with M1 receptor expression in this area. We found no indication of differences in activation patterns between psychosis patients and matched healthy control subjects in emotion recognition or effect of cholinergic challenge during emotion recognition processing.
Conclusions: Superior and medial frontal gyrus are hypoactivated under a cholinergic challenge during emotion recognition in recent onset psychotic patients, and lower M1 binding is correlated with a lower activation of these areas. Abnormal brain activation and M1 expression might help explain deficits in social cognition in early phases of development of psychotic disorders and are a possible new target for antipsychotic treatment. Future studies should aim to further investigate whether treatment with M1 agonists will be able to normalize brain responses in affected areas and alleviate social cognitive deficits.
2
1. Introduction
Psychotic disorders, with Schizophrenia being the most severe form, affect almost 1% of the world population (McGrath, Saha, Chant, & Welham, 2008). It has been classically described in three classes of symptoms, namely, positive (e.g. delusions, hallucinations), negative (e.g. social withdrawal, anhedonia) and cognitive symptoms (e.g. attention and memory deficits). Current antipsychotic treatment primarily shows therapeutic effects on the positive and negative symptoms, with little to no improvement of the cognitive symptoms (Miyamoto, Duncan, Marx, & Lieberman, 2005). Studies found 75-85 percent of patients with psychotic disorders show decreased cognitive functioning, scoring 1-2 standard deviation lower in general IQ in comparison to healthy control subjects (Reichenberg et al., 2006). Factor analytic studies show multiple domains of cognition are affected with most prominent deficits in processing speed, attention and vigilance, working memory, verbal and visual learning, and reasoning and problem solving (Nuechterlein et al., 2004). Studies also identified imperative deficits in social cognition that are strongly related to functional outcome (Green, Kern, & Heaton, 2004; Kim et al., 2011). Due to the fact that deficits are treatment resistant and associated with high attrition rates there is an urgent need to understand the underlying neuropathology of these symptoms.
Social cognition is operationalized as “the mental operations underlying social interactions, which include the human ability to perceive the intentions and dispositions of others” (Pinkham, Penn, Perkins, & Lieberman, 2003). It provides the ability to recognize various emotions exhibited by others or the reasons persons act as they do (Lewis, 2012). Social cognition draws upon neural mechanisms for perceiving, recognizing and evaluating (emotional) stimuli. Together, these mechanisms provide the required information to construct accurate representations of the social environment (Adolphs, 2002).
Numerous studies have indicated deficits in emotion perception and recognition in schizophrenic patients (Kohler, Walker, Martin, Healey, & Moberg, 2010). In particular negative emotions are often misidentified. Several reports have stated that this might be specifically the case for facial expressions of disgust (Chambon, Baudouin, & Franck, 2006; Kohler et al., 2003). Kohler et al. (2003) performed an emotion discrimination test that presented mild and extreme intensities of happy, sad, angry, fearful, disgusted, and neutral faces. They found impairment in overall emotion recognition in patients with schizophrenia compared to healthy controls. Disgust was most often misidentified, and did not – in contrast to other emotions – benefit from increased emotional intensity.
Recognition and perception of facial emotions activates limbic regions, putamen, inferior frontal gyrus, and medial prefrontal gyrus (Adolphs, 2002; Fusar-Poli et al., 2009; Phan, Wager, Taylor, & Liberzon, 2002). Functional MRI studies have identified overall hypoactivation of these network regions in schizophrenia patients compared to healthy controls (Habel et al., 2010; Phillips, Drevets, Rauch, & Lane, 2003). Processing of disgust stimuli has been found to elicit a significantly larger insula activation compared to the processing of the other emotion stimuli. Pathological disgust recognition in schizophrenia has been related to blunting of this insular response (Habel et al., 2010). Meta-analytical studies show little to no therapeutic response of antipsychotic medication on social cognitive functioning, including for the second generation atypical antipsychotic therapies (Chakos, Lieberman, Hoffman, Bradford, & Sheitman, 2001; Sergi et al., 2007) . Atypical antipsychotic medication have shown greater efficacy in treating symptoms of psychotic disorders due to more extensive binding profile than typical antipsychotic treatment, involving serotonergic, histaminergic, adrenergic and muscarinergic systems. Of these systems, the muscarinergic system is implicated to play a critical role in cognitive functioning, although these effects seem to be mediated through the M1
receptor subtype, rather than the M4 receptor subtype that the atypical antipsychotics target (Raedler,
Bymaster, Tandon, Copolov, & Dean, 2007). This may explain why social cognitive deficits don’t improve under pharmacological treatment.
3 The M1 receptor subtype is highly expressed in the cortex with highest rates in the dorsolateral
prefrontal cortex, limbic structures and hippocampus (Caulfield, 1993; Levey, Kitt, Simonds, Price, & Brann, 1991). These regions are critical for cognition and as before mentioned are also involved in processing of disgust stimuli. Knock out mice for M1 have been found to have severe learning and
memory problems which were not seen in the knock out mice for the other subtypes (Anagnostaras et al., 2002). Additionally, the several studies have shown that blocking the M1 receptor selectively with
biperiden gives rise to learning and memory problem in healthy controls (Wezenberg, Verkes, Sabbe, Ruigt, & Hulstijn, 2005). A post-mortem study investigating M1 receptor expression in schizophrenia
patients found indications that the M1 receptor expression rates in these critical regions may be
abnormally low in these patient (Scarr et al., 2009). They found a sub-group of patients that had up to 75 percent reduction in M1 receptors. However it is unclear from this study whether this in present
already in-vivo at onset of psychosis or an effect of chronic psychosis over lifetime.
Aside from possible lower rates of M1 receptor expression, lowered levels of acetylcholine available in
the M1 projection pathways may also lead to functional pathology leading to incapacity to identify
disgust emotions. Lower levels of acetylcholine transferase have been found in psychosis patients signifying lower acetylcholine levels in the system of these patients compared to healthy controls, unfortunately, cognitive performance in these patients was not assessed (Bird et al., 1977).
To date cholinergic neurotransmission in relation to cognitive symptoms has only been investigated in schizophrenia, and not in at the begin phases of psychosis. Moreover, M1 receptor expression has
never been assessed in-vivo, let alone at early development of psychotic disorders. Studies seem to find these cognitive symptoms to be trait-like as they have been found in prodromal, early phases and chronic phase making them critical to study at onset of psychosis. Therefore, the current study seeks to investigate the role of cholinergic neurotransmission and M1 receptor expression in relation to
functional brain activation during disgust identification in patients which recently developed psychosis. We anticipate that patients will perform worse in identifying disgust stimuli, and show hypoactivation in regions associated with emotion perception and recognition in comparison to healthy controls. Additionally we anticipate that these regions will also show lower functional response in disgust processing under a cholinergic challenge. Lastly, we anticipate M1 receptor expression rates in
these regions to be related to degree of activation of these regions in recognition and identification of disgust.
4
Methods
2.1 Participants
Eighteen recent onset psychosis patients (mean age ± standard deviation, 28 ± 5 years; IQ 102 (± 15)); and 18 age, gender and IQ matched healthy controls (mean age ± standard deviation, 26 ± 4 years; IQ 106 (± 12)) were included in the current study. Demographics are displayed in Table 1. There were no significant group differences in age, gender and IQ. The Shortened Wechsler Adult Intelligence Scale (Wechsler, 2008) was used to estimate IQ.
Table 1. Demographics of patients and controls. Outcome of independent t-test for age and IQ and chi-square test for gender. No significant differences for any of the demographics were found.
All psychosis patients were medication free and were recruited from early detection and intervention programs and teams (“VIP” and “ABC” teams), the national first episodic psychosis network, and advertisements in newspapers. Diagnosis of a psychotic disorder was assessed according to the standardized criteria of the Comprehensive Assessment of Symptoms and History (CASH) semi-structured interview. Duration of untreated psychosis was not allowed to be longer than 1 year. In order to participate patients and healthy controls subjects needed to be 18 years or older. Subjects were excluded if they had contraindications for MRI, severe neurological or endocrine disorders, current use of recreational drugs, and pregnancy – which were checked through urine samples. Due to the administration of biperiden subjects with tardive dyskinesia, or narrow angle glaucoma were excluded. Symptom severity was determined using the Positive and Negative Syndrome Scale (PANSS) (Kay, Fiszbein, & Opler, 1987). Patients and comparison subjects were matched according to gender, age and IQ. Ethical approval was obtained from the Medical Ethical Committee of the Academic Medical Centre of Amsterdam. Written informed consent was obtained from all participants after complete description of the study.
2.2 Emotion Recognition Task – outside the scanner
In order to assess the ability to identify facial emotional expressions all subjects participated in the Emotion Recognition Task (ERT) subtest of the Cambridge Neuropsychological Test Automated Battery (CANTAB) (Fray, Robbins, & Sahakian, 1996). The test was presented on a high-resolution touch-screen monitor under computer control. Subjects were instructed to evaluate facial expressions by assigning one of the six universal basic emotions (happiness, fear, disgust, anger, sadness, surprise) to the image. Subjects were instructed to look at a fixation cross depicted in the middle of the screen in order to ascertain attention to the displayed faces. Faces were displayed for a short amount of time (± 450 ms). A response could be generated by touching the box describing the corresponding emotion. Each emotion was divided into a range of intensities with a total of 15 different intensity levels. Each intensity level was shown twice, resulting in a total of 30 presentations of each emotion. In total a number of 180 facial expressions (30 presentations x 6 emotions) were shown. Differences between groups in performance on cognitive tasks were determined using SPSS using independent samples t-test and univariate analysis.
5 2.3 Emotion Recognition Task – functional neuroimaging
The previously described ERT task was made suitable to be performed during scanning. In the fMRI task, each intensity was presented only once, resulting in a total of 90 stimulus presentations. All stimuli were presented in a randomized order. The duration of the Inter Stimulus Interval (ISI) was 1000 ms. During the ISI subjects viewed the fixation cross as described above. In subsequent analysis, the fixation cross was used as the baseline condition. For a detailed description of the task see supplementary Figure 1. Participants were placed horizontally in the scanner. Subjects were presented with the facial expressions via a screen placed behind the MRI-scanner which was connected to a conventional PC. A response to the facial expressions was generated via a MR-compatible response key box. In order to minimize motion, the key boxes were placed on the subject’s thighs positioned in the way that was reported as most comfortable. To further reduce motion artifacts, the subject’s head was immobilized using foam pads.
2.4 Cholinergic Challenge
Each volunteer participated in the functional neuroimaging task twice; once under placebo condition and once under a cholinergic challenge. The cholinergic challenge was established by oral administration of 4 mg biperiden. Biperiden is a competitive M1 antagonist usually prescribed to treat medication-induced extrapyramidal disorders in Parkinson’s disease. Previous research has established that the central pharmacodynamics effects of biperiden peak between 60 and 90 minutes. Therefore, fMRI scanning took place at 90 minutes post administration (Grimaldi et al., 1986).
2.5 Image Acquisition
Magnetic resonance (MR) images were acquired using a Philips Ingenia 3.0 Tesla system with an operating console and software for gradient echo echoplanar imaging (EPI) at the Academic Medical Centre, Amsterdam, the Netherlands. A 32 channel head coil was used for RF transmission and reception. An EPI dataset was acquired at 37 3-mm-thick planes (voxel size 3 x 3 x 3 mm, matrix size: 80 x 80, FOV: 240 x 240, TR: 2000 ms, TE: 27 ms) which provided whole brain coverage. Additionally, a structural scan sequence (MPRAGE) was used to obtain a T1 weighted anatomical image (180 slices, voxel size 1 x 1 x 1 mm, matrix size: 256 x 256, FOV: 256 x 240, TR: 7.0 ms, TE: 3.2 ms) for co-registration of single photon emission computed tomography (SPECT) scan for anatomical localization of the dorsolateral prefrontal cortex (dlPFC).
Visual stimuli were presented via a screen placed behind the MRI-scanner that was connected to a conventional PC. The screen was made visible for the subject via a well-positioned mirror on the head-coil. The presentations of the stimuli as well as the recordings of the subject’s responses were synchronized to the imaging system. Total MRI procedure took 1 hour, of which the ERT took approximately 10 minutes.
2.6 Neuroimaging Data Analysis
Images were preprocessed by means of Statistical Parametric Mapping 12 (Wellcome Dept. of Neurology, 2014) implemented in Matlab (Mathworks Inc., Sherborn, MA, USA). The imaging time series was realigned to the first volume to remove subject-induced motion artifacts. Following realignment, all images were subjected to slice timing correction, co-registration, spatial normalization to the Montreal Neurological Institute (MNI) template implemented in SPM12, and spatial smoothing with an 8 mm full-width-at-half-maximum (FWHM) Gaussian kernel.
A first level model for each subject was defined within the general linear model (GLM) framework of SPM12. The effects were modeled using a canonical hemodynamic response function. Contrast
6 images were generated for each condition vs. baseline (fixation cross) for three levels of emotion intensity (low, middle and high). In second level analysis these contrasts were included in two ANOVA’s for a Group by Treatment and A Treatment by Intensity Analysis. First, a group by treatment ANOVA was performed. This three factor flexible factorial design consisted of the between-subject factor ‘between-subject’, the between-group factor ‘group’ (with two levels: patients and healthy controls (HC)) and the within-subjects factor ‘treatment’ (with two levels: placebo and biperiden). Additionally, a 2 x 3 repeated-measures ANOVA was performed. This three-factor flexible factorial design consisted of the between subject factor ‘subject’ and the within-subject factors ‘treatment’ (with two levels: placebo and biperiden) and ‘intensity’ (with three levels: low, middle and high). To control for age effects it was included as a nuisance regressor in both designs. See supplementary Figures 2 – 4 for design matrices of first and second levels. M1 receptor expression (measured as binding potential) was added as regressor to the model to assess regions of activation associated with M1 receptor expression.
2.7 [123I]-IDEX SPECT Acquisition and Measurements
In addition to the fMRI procedure, all patients underwent a SPECT scan to assess M1 binding affinity using a selective M1 receptor radiotracer [123I]-IDEX (Bakker et al 2015). Patients received two 100
mg iodide tablets the night before and one tablet in the morning of the day of scanning to prevent thyroid uptake of free radio-active iodide. [123I]-IDEX was obtained from the specialized laboratory of the department of nuclear medicine. Each patient received a bolus injection of 185 MBq (5mCi) 6 hours pre-testing. Since [123I]-IDEX has a high specific activity only a low dose was needed to be administered. Because of the trace amounts of [123I]-IDEX used, pharmacological effects were unlikely to occur; no effects were observed. SPECT images were obtained using a brain-dedicated camera (Strichman Medical Equipment Inc., Medfield, Mass.). This camera consisted of 12 individual crystals each equipped with a focusing collimator. The transaxial resolution was 6.8 mm full width at half maximum (FWHM) of a line source in air. All images were acquired in a period of 150 s from the orbitomeatal to the vertex with an inter-slice distance of 5 mm. The energy window was set at 135-190 keV. Data acquisition took place in a 64x64 matrix. The measured concentration of radioactivity was expressed as Strichman Medical Units (SMUs; 1 SMU = 100 Bq/ml as specified by the Strichman Medical Equipment Inc.)
2.8 SPECT Data Analysis
An adult head CT template was used to generate attenuation-corrected images and a 3 mm filter was applied for spatial smoothing. SPECT image volumes were co-registered with a structural T1 weighted anatomical MRI scan obtained from each individual. Based on fMRI results, the dlPFC was taken as region of interest (ROI). The ROI as well as cerebellar masks were created using Freesurfer segmentation images (Fischl et al., 2002). M1 receptor binding potential in the ROI was calculated as a
ratio of specific to nonspecific binding. It was assumed that ROI uptake represents total radioligand binding (specific + nonspecific binding + free radioligand). Since the cerebellum is devoid of muscarinic receptors, cerebellar activity was used as a reference region to correct for background activity (nonspecific binding + free radioligand).
7
2. Results
3.1 Facial Expression Recognition – outside the scanner
Patients performed significantly worse on emotion recognition of disgust for low (t= (1.48) = 2.847, p=0.006) and high (t= (1, 48) = 3,262, p= 0.003) intensities and showed a trend towards middle intensities (t= (1.48) = 1.963, p = 0.055). Other emotions significantly more often misidentified were low intensities of fear (t= (1.48) = 2.348, p= 0.023) and high intensities of sadness (t= (1, 48) = 2,376, p= 0.022). No significant differences were found for any intensity of surprise, happiness and anger. 3.2 Group by Treatment Analysis – main effects and interaction
Main effects and interaction of group and treatment were first examined. No significant clusters were found in interaction and main effects of group on neural responses to disgusted faces in both placebo and biperiden conditions.
3.3 Within Subject Analysis – main effects and interaction
No significant clusters were found in treatment by intensity interaction and main effect of intensity. Main effect of treatment was found, with right frontal superior gyrus and left medial frontal gyrus showing a greater response in placebo conditions compared to biperiden (p= 0.001, FWE uncorrected). Figure 1 depicts location of significant clusters, and Table 2 cluster sizes and p-values at peak level.
Figure 1. In yellow depicted regions of significantly decreased activation under biperiden during disgust recognition in recent onset psychosis patients.
8 M1 binding potential in the dlPFC was found to be correlated with brain activation in emotion
recognition of disgust in patients under placebo conditions (p= 0.001 uncorrected). Figure 2 shows the brain activation map of M1 correlation with neural responses to emotional stimuli of disgust. Higher
M1 binding potential was correlated with greater responses in bilateral superior frontal gyrus, left
medial frontal gyrus, left middle frontal gyrus and left precentral gyrus. MNI coordinates and p-values are shown in Table 3.
Figure 2. Patients: Correlation of M1 binding potential with neural responses to facial expressions of disgust. Increases at peak level in activation correlated to M1 binding are demonstrated within the bilateral superior frontal gyrus, left medial frontal gyrus, left middle frontal gyrus and left precentral gyrus. For MNI coordinates of activated regions see Table 3.
9 Table 3. Correlation of M1 binding potential with brain activation in patients under placebo conditions.
3. Discussion
The current study is the first to assess underlying cholinergic neurotransmission in relation to processing of emotion recognition in medication free recent onset psychosis patients. Key results showed that a cholinergic challenge led to hypoactivate functional response of the superior and medial frontal gyrus at the onset stage of psychosis. The degree of hypoactivation in these regions was also positively correlated to M1 receptor expression in this area. We found no indication of differences in activation patterns between psychosis patients and matched healthy control subjects in emotion recognition or effect of cholinergic challenge during emotion recognition processing.
In line with previous studies and expectation, the current study indeed found that patients were significantly worse in identifying facial expression of disgust in comparison to matched healthy control subjects (Kohler et al., 2010). This finding thus seems robust in psychotic disorders. Being able to process information from facial expressions is essential for proper interpersonal interactions. Research has shown that maintaining a stable social environment such as family life and employment have positive impact on clinical outcome (Burns et al., 2009; Tas, Danaci, Cubukcuoglu, & Brüne, 2012). Current findings indicate that deficits in emotional processing are already present in begin stages of the development of psychosis. Thus, to improve clinical outcome it is important to target these deficits already in early stages of disease.
In contrast to expectation the current study found no differences in functional response during disgust processing between patients and matched healthy controls. These results suggest no abnormal pattern of brain activation in the psychosis patients compared to healthy controls. The sample size of 18 patients and healthy controls may not have been large enough to have power to detect between group differences (Desmond & Glover, 2002). Moreover, there may have been a selection bias toward somewhat more stable patients that were medication free. Interesting post-hoc investigation would be to rerun the analysis to evaluate explained variance due to psychotic symptom severity at time of scanning. This would help to elucidate whether hypoactivation is more a state- like factor.
Findings did show that the functional response of frontal regions, but no other regions involved in disgust identification, were affected by changes in cholinergic levels in patients with recent development of psychosis. Research shows that the superior and medial frontal gyri are part of a network associated with social cognition on a whole, and critical to the evaluation of emotional significance of a stimulus and for the production of affective states (Phillips et al., 2003). Although only disgust stimuli were assessed these regions are also involved in assessing other emotions and thus this finding is likely not specific to disgust processing. Findings suggest a role for cholinergic
10 dysregulation in begin stages of the development of psychosis that may be associated with reduced social cognition and isolation.
In light of previous studies that have looked in chronic schizophrenia patients (Brunet-Gouet & Decety, 2006; Habel et al., 2010), the current study failed to find aberrant insula activation under cholinergic challenge at the begin stage of psychosis during disgust processing. Therefore, disgust processing may not be affected in early stages of psychosis and does not seem affected by reduced cholinergic innervation of the insula. It is of importance to investigate when and how brain areas such as the insula – that are functionally connected to the frontal regions affected in begin stages – might be affected in later stages of disease. Previous studies found that network connectivity can be affected by changes in activation of single brain regions (Caria, Sitaram, Veit, Begliomini, & Birbaumer, 2010; Ruiz et al., 2013), indicating that cholinergic pathology might indeed spread through the brain during disease progression. In order to potentially target cholinergic dysregulation in future treatments, longitudinal research should clarify the course of this pathological process.
Interestingly, the current study also found preliminary results showing rates of M1 expression in the superior and medial frontal gyrus are related to activation of these regions. Results show that lower M1
receptor expression is associated with hypoactivation. Research on transcranial direct current stimulation (tDCS) has provided evidence that increased activation of these regions is related to enhanced processing of facial expressions of emotion (Conson et al., 2015; Nitsche et al., 2012). Treatment with M1 agonists might therefore greatly benefit evaluation and processing of emotional
intentions in psychotic disorders.
Of all the antipsychotic treatments currently available only one, clozapine, uniquely agonizes the muscarinic system at the type 4 (M4) receptor. Studies assessing the effect of clozapine treatment on
cognition have found small improvement on domains of working memory, processing speed and motor skills (Bilder et al., 2002; Woodward, Purdon, Meltzer, & Zald, 2005). Although clozapine agonizes the muscarinic system at the M4 receptor, it exhibits an antagonistic effect at M1. It is
therefore in line with current findings that clozapine has failed to improve social cognition (Kucharska-Pietura & Mortimer, 2013).
In the past two decades, selective muscarinic agonists have been developed that show promising preclinical results (Felder, Bymaster, Ward, & Delapp, 2000). Shekhar et al. (2008) found improvements in neuro-cognition in schizophrenic patients after treatment with xanomeline, a selective muscarinic type 1 and 4 (M1 and M4) receptor agonist. Despite the fact that Shekhar and
colleagues did only assess neuro-cognitive domains in patients that had been chronically ill, results support further investigation of xanomeline as a novel M1 neuroleptic. Based on results from current
investigation, it is expected that xanomeline treatment may lead to increased activation of frontal regions, resulting in improved emotion recognition. Future studies should clarify exact effects of xanomeline on social cognition. Additionally, xanomeline treatment should be assessed in recent onset psychosis patients in order to uncover treatment effectiveness at begin stages of disease.
3.1 Study limitations
The sample size in this study was modest, though comparable to that of other neuroimaging studies assessing psychiatric disorders. Strength of this study was that all patients were free of medication, excluding the possibility that results are influenced by pharmacological or side effects of antipsychotics.
Within the cognitive domains known to be affected in schizophrenia, social cognition has received the least attention (Vingerhoets, Bloemen, Bakker, & van Amelsvoort, 2015). This is partly because social cognition has been inconsistently defined (Couture, Penn, & Roberts, 2006). No consensus has been reached whether social cognition should be conceptualized as one of the neuro-cognitive domains (such as attention or memory) or as a separate cognitive dimension. Social cognition is seen as a broad
11 construct and a large number of tasks have been used to study social deficits in psychotic disorders. The design of emotion recognition task as used in the study suffered from some limitations.
Firstly, only facial expressions of disgust have been investigated. Since the hypoactivation of frontal areas does not seem to be specific for disgust processing future studies should assess processing of other emotions known to be affected in schizophrenia – such as fear, anger and sadness – in order to validate results for emotion recognition as a whole. Additionally, it was not taken into account whether facial expressions during the functional MRI task were correctly identified. In order to further clarify the current findings, future studies should investigate whether effects on neural response are different for correctly identified versus misidentified emotional stimuli.
3.2 Conclusions
Notwithstanding its limitations, the current study established hypoactivation of the superior and medial frontal gyrus under a cholinergic challenge during emotion recognition, and found that lower M1 binding is associated with lower activation of these areas. Abnormal brain activation and M1 expression in these areas might help explain deficits in social cognition in early phases of development of psychotic disorders and are a possible new target for antipsychotic treatment. Future studies should aim to further investigate whether treatment with M1 agonists such as xanomeline will normalize brain responses in affected areas and alleviate social cognitive deficits.
12
References
Adolphs, R. (2002). Neural systems for recognizing emotion. Current Opinion in Neurobiology, 12(2), 169–177.
Anagnostaras, S. G., Murphy, G. G., Hamilton, S. E., Mitchell, S. L., Rahnama, N. P., Nathanson, N. M., & Silva, A. J. (2002). Selective cognitive dysfunction in acetylcholine M1 muscarinic receptor mutant mice. Nature Neuroscience, 6(1), 51–58.
Bilder, R. M., Goldman, R. S., Volavka, J., Czobor, P., Hoptman, M., Sheitman, B., … Lieberman, J. A. (2002). Neurocognitive effects of clozapine, olanzapine, risperidone, and haloperidol in patients with chronic schizophrenia or schizoaffective disorder. American Journal of Psychiatry, 159(6), 1018–1028.
Bird, E., Barnes, J., Iversen, L., Spokes, E., Mackay, A. P., & Shepherd, M. (1977). Increased Brain Dopamine And Reduced Glutamic Acid Decarboxylase And Choline Acetyl Transferase Activity In Schizophrenia And Related Psychoses. The Lancet, 310(8049), 1157–1159.
Brunet-Gouet, E., & Decety, J. (2006). Social brain dysfunctions in schizophrenia: A review of neuroimaging studies. Psychiatry Research - Neuroimaging, 148(2-3), 75–92.
Burns, T., Catty, J., White, S., Becker, T., Koletsi, M., Fioritti, A., … Lauber, C. (2009). The impact of supported employment and working on clinical and social functioning: results of an international study of individual placement and support. Schizophrenia Bulletin, 35(5), 949–58. Caria, A., Sitaram, R., Veit, R., Begliomini, C., & Birbaumer, N. (2010). Volitional control of anterior
insula activity modulates the response to aversive stimuli. A real-time functional magnetic resonance imaging study. Biological Psychiatry, 68(5), 425–32.
Caulfield, M. P. (1993). Muscarinic receptors--characterization, coupling and function. Pharmacology & Therapeutics, 58(3), 319–379.
Chakos, M., Lieberman, J., Hoffman, E., Bradford, D., & Sheitman, B. (2001). Effectiveness of second-generation antipsychotics in patients with treatment-resistant schizophrenia: a review and meta-analysis of randomized trials. The American Journal of Psychiatry, 158(4), 518–526. Chambon, V., Baudouin, J.-Y., & Franck, N. (2006). The role of configural information in facial
emotion recognition in schizophrenia. Neuropsychologia, 44(12), 2437–44.
Conson, M., Errico, D., Mazzarella, E., Giordano, M., Grossi, D., & Trojano, L. (2015). Transcranial Electrical Stimulation over Dorsolateral Prefrontal Cortex Modulates Processing of Social Cognitive and Affective Information. PloS One, 10(5), e0126448.
Couture, S. M., Penn, D. L., & Roberts, D. L. (2006). The functional significance of social cognition in schizophrenia: a review. Schizophrenia Bulletin, 32 Suppl 1(suppl 1), S44–63.
Desmond, J. E., & Glover, G. H. (2002). Estimating sample size in functional MRI (fMRI) neuroimaging studies: Statistical power analysis. Journal of Neuroscience Methods, 118(2), 115– 128.
Felder, C. C., Bymaster, F. P., Ward, J., & Delapp, N. (2000). Therapeutic Opportunities for Muscarinic Receptors in the Central Nervous System. Journal of Medicinal Chemistry, 43(23), 4333–4353.
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., … Dale, A. M. (2002). Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain. Neuron, 33(3), 341–355.
Fray, J. P., Robbins, W. T., & Sahakian, J. B. (1996). Neuorpsychiatyric applications of CANTAB. International Journal of Geriatric Psychiatry, 11(4), 329–336.
Fusar-Poli, P., Placentino, A., Carletti, F., Landi, P., Allen, P., Surguladze, S., … Politi, P. (2009). Functional atlas of emotional faces processing: a voxel-based meta-analysis of 105 functional magnetic resonance imaging studies. Journal of Psychiatry & Neuroscience : JPN, 34(6), 418– 32.
Green, M. F., Kern, R. S., & Heaton, R. K. (2004). Longitudinal studies of cognition and functional outcome in schizophrenia: implications for MATRICS. Schizophrenia Research, 72(1), 41–51. Grimaldi, R., Perucca, E., Ruberto, G., Gelmi, C., Trimarchi, F., Hollmann, M., & Crema, A. (1986).
Pharmacokinetic and pharmacodynamic studies following the intravenous and oral administration of the antiparkinsonian drug biperiden to normal subjects. European Journal of
13 Clinical Pharmacology, 29(6), 735–737.
Habel, U., Chechko, N., Pauly, K., Koch, K., Backes, V., Seiferth, N., … Kellermann, T. (2010). Neural correlates of emotion recognition in schizophrenia. Schizophrenia Research, 122(1-3), 113–23.
Kay, S. R., Fiszbein, A., & Opler, L. A. (1987). The Positive and Negative Syndrome Scale (PANSS) for Schizophrenia. Schizophrenia Bulletin, 13(2), 261–276.
Kim, H. S., Shin, N. Y., Jang, J. H., Kim, E., Shim, G., Park, H. Y., … Kwon, J. S. (2011). Social cognition and neurocognition as predictors of conversion to psychosis in individuals at ultra-high risk. Schizophrenia Research, 130(1-3), 170–5.
Kohler, C. G., Turner, T. H., Bilker, W. B., Brensinger, C. M., Siegel, S. J., Kanes, S. J., … Gur, R. C. (2003). Facial emotion recognition in schizophrenia: Intensity effects and error pattern. American Journal of Psychiatry, 160, 1768–1774.
Kohler, C. G., Walker, J. B., Martin, E. A., Healey, K. M., & Moberg, P. J. (2010). Facial emotion perception in schizophrenia: A meta-analytic review. Schizophrenia Bulletin, 36(5), 1009–1019. Kucharska-Pietura, K., & Mortimer, A. (2013). Can antipsychotics improve social cognition in
patients with schizophrenia? CNS Drugs, 27(5), 335–343.
Levey, A. I., Kitt, C. a, Simonds, W. F., Price, D. L., & Brann, M. R. (1991). Identification and localization of muscarinic acetylcholine receptor proteins in brain with subtype-specific antibodies. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 11(10), 3218–3226.
Lewis, M. (2012). Social Cognition and the Acquisition of Self. Springer Science And Business Media. McGrath, J., Saha, S., Chant, D., & Welham, J. (2008). Schizophrenia: a concise overview of
incidence, prevalence, and mortality. Epidemiologic Reviews, 30(1), 67–76.
Miyamoto, S., Duncan, G. E., Marx, C. E., & Lieberman, J. A. (2005). Treatments for schizophrenia: a critical review of pharmacology and mechanisms of action of antipsychotic drugs. Molecular Psychiatry, 10(1), 79–104.
Nitsche, M. A., Koschack, J., Pohlers, H., Hullemann, S., Paulus, W., & Happe, S. (2012). Effects of Frontal Transcranial Direct Current Stimulation on Emotional State and Processing in Healthy Humans. Frontiers in Psychiatry, 3, 58.
Nuechterlein, K. H., Barch, D. M., Gold, J. M., Goldberg, T. E., Green, M. F., & Heaton, R. K. (2004). Identification of separable cognitive factors in schizophrenia. Schizophrenia Research, 72(1), 29–39.
Phan, K. L., Wager, T., Taylor, S. F., & Liberzon, I. (2002). Functional neuroanatomy of emotion: a meta-analysis of emotion activation studies in PET and fMRI. NeuroImage, 16(2), 331–48. Phillips, M. L., Drevets, W. C., Rauch, S. L., & Lane, R. (2003). Neurobiology of emotion perception
II: Implications for major psychiatric disorders. Biological Psychiatry, 54(5), 515–28.
Pinkham, A. E., Penn, D. L., Perkins, D. O., & Lieberman, J. (2003). Implications for the neural basis of social cognition for the study of schizophrenia. American Journal of Psychiatry, 160(5), 815– 824.
Raedler, T., Bymaster, F., Tandon, R., Copolov, D., & Dean, B. (2007). Towards a muscarinic hypothesis of schizophrenia. Molecular Psychiatry, (12), 232–246.
Reichenberg, A., Weiser, M., Caspi, A., Knobler, H. Y., Lubin, G., Harvey, P. D., … Davidson, M. (2006). Premorbid intellectual functioning and risk of schizophrenia and spectrum disorders. Journal of Clinical and Experimental Neuropsychology, 28(2), 193–207.
Ruiz, S., Lee, S., Soekadar, S. R., Caria, A., Veit, R., Kircher, T., … Sitaram, R. (2013). Acquired self-control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia. Human Brain Mapping, 34(1), 200–212.
Scarr, E., Cowie, T. F., Kanellakis, S., Sundram, S., Pantelis, C., & Dean, B. (2009). Decreased cortical muscarinic receptors define a subgroup of subjects with schizophrenia. Molecular Psychiatry, 14(11), 1017–23.
Sergi, M. J., Green, M. F., Widmark, C., Reist, C., Erhart, S., Braff, D. L., … Mintz, J. (2007). Cognition and neurocognition: Effects of risperidone, olanzapine, and haloperidol. American Journal of Psychiatry, 164(10), 1585–1592.
14 Muscarinic Receptor Agonist Xanomeline as a Novel Treatment Approach for Schizophrenia, (August), 1033–1039.
Tas, C., Danaci, A. E., Cubukcuoglu, Z., & Brüne, M. (2012). Impact of family involvement on social cognition training in clinically stable outpatients with schizophrenia -- a randomized pilot study. Psychiatry Research, 195(1-2), 32–8.
Vingerhoets, W. A., Bloemen, O. J., Bakker, G., & van Amelsvoort, T. A. (2015). Pharmacological interventions for the MATRICS cognitive domains in schizophrenia: what’s the evidence?. Neuropsychopharmacology of Psychosis: Relation of Brain Signals, Cognition and
Chemistry, 44.
Wechsler, D. (2008). Wechsler Adult Intelligence Scale - Fourth Edition, 1–3.
Wezenberg, E., Verkes, R. J., Sabbe, B. G. C., Ruigt, G. S. F., & Hulstijn, W. (2005). Modulation of memory and visuospatial processes by biperiden and rivastigmine in elderly healthy subjects. Psychopharmacology, 181(3), 582–594.
Woodward, N. D., Purdon, S. E., Meltzer, H. Y., & Zald, D. H. (2005). A meta-analysis of neuropsychological change to clozapine, olanzapine, quetiapine, and risperidone in schizophrenia. The International Journal of Neuropsychopharmacology, 8(3), 457–472.
15
Supplementary Data
Figure 1. Overview of the Emotion Recognition Task (ERT) as performed during scanning. During control phase subjects watched a baseline stimulus (fixation cross) for 1000 ms. Subsequently, an emotional stimulus was shown for ± 450 ms. The emotional stimuli were shown in a randomized order of different intensities ranging from low to high (e.g. disgust) and were followed by a mask after which a response was given by the subject. The onset of the emotional stimulus until the subject’s response (via the response key box) was defined as the condition phase.
16 Figure 2. Example of a single subject’s first level design. Regressors from right to left: timing data per level of intensity (low, middle, and high) for the condition phase, and corresponding control phase (fixation crosses).
17 Figure 3. Second level matrix design of 2*3 repeated measures ANOVA. Main effect of treatment and intensity as well as treatment by intensity interaction was included in the matrix. Age was entered as a covariate to correct for age-induced differences. Contrast images of emotion vs baseline for all three intensities separately (low, middle, high) were entered for each patient for both conditions (placebo and biperiden). To assess the effect of M1 binding potential and PANSS total score, these scores were included in subsequent analysis as covariates (not depicted here).
18 Figure 4. Second level matrix design of 2*2 repeated measures ANOVA. Main effect of group and treatment as well as group by treatment interaction was included in the matrix. Age was entered as a covariate to correct for age-induced differences. Contrast images of emotion vs baseline for all three intensities together were entered for each subject (patients and HCs) for each condition (placebo and biperiden).
19 Figure 5. Patients: Correlation of PANSS total score with neural responses to facial expressions of disgust. Increases at peak level in activation correlated to PANSS total score are demonstrated within the left medial frontal gyrus and left subcallosal gyrus. Bilateral responses were found in inferior frontal gyrus. For MNI coordinates of activated regions see supplementary Table 1.
20 Figure 6. Patients: superimposed brain activation maps of M1 binding potential and PANSS correlation with emotion recognition of disgust. Common regions demonstrate bilateral superior frontal gyrus, left middle frontal gyrus and left medial frontal gyrus.
21 Table 1. Correlation of PANSS total score with brain activation in patients under placebo conditions.
