The serotonin transporter and the serotonin 1B receptor in relation to social cognition in healthy adults - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice EJNMMI Res . 2026 Apr 17;16:66. doi: 10.1186/s13550-026-01435-7 Search in PMC Search in PubMed View in NLM Catalog Add to search The serotonin transporter and the serotonin 1B receptor in relation to social cognition in healthy adults Gina Griffioen Gina Griffioen 1 Centre for Psychiatry Research and Centre for Cognitive and Computational Neuropsychiatry (CCNP), Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, Stockholm, 113 64 Sweden Find articles by Gina Griffioen 1, ✉, # , Ämma Tangen Ämma Tangen 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden Find articles by Ämma Tangen 2, # , Emma Veldman Emma Veldman 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden Find articles by Emma Veldman 2 , Jonas E Svensson Jonas E Svensson 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden Find articles by Jonas E Svensson 2 , Mikael Tiger Mikael Tiger 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden Find articles by Mikael Tiger 2 , Magdalena Nord Magdalena Nord 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden Find articles by Magdalena Nord 2 , Max Andersson Max Andersson 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden Find articles by Max Andersson 2 , Kimmo Sorjonen Kimmo Sorjonen 3 Department of Clinical Neuroscience, Division of Psychology, Karolinska Institutet, K8 Psykologi Melin, 171 77, Stockholm, Sweden Find articles by Kimmo Sorjonen 3 , Andrea Varrone Andrea Varrone 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden Find articles by Andrea Varrone 2 , Christer Halldin Christer Halldin 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden Find articles by Christer Halldin 2 , Katarina Varnäs Katarina Varnäs 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden Find articles by Katarina Varnäs 2 , Jacqueline Borg Jacqueline Borg 1 Centre for Psychiatry Research and Centre for Cognitive and Computational Neuropsychiatry (CCNP), Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, Stockholm, 113 64 Sweden Find articles by Jacqueline Borg 1, # , Johan Lundberg Johan Lundberg 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden Find articles by Johan Lundberg 2, # Author information Article notes Copyright and License information 1 Centre for Psychiatry Research and Centre for Cognitive and Computational Neuropsychiatry (CCNP), Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, Stockholm, 113 64 Sweden 2 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm health care services, Region Stockholm, K8 CPF Farde/Halldin, 171 77, Stockholm, Sweden 3 Department of Clinical Neuroscience, Division of Psychology, Karolinska Institutet, K8 Psykologi Melin, 171 77, Stockholm, Sweden ✉ Corresponding author. # Contributed equally. Received 2025 Oct 17; Accepted 2026 Apr 6; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . PMC Copyright notice PMCID: PMC13090403 PMID: 41995929 Abstract Background Social cognition is impaired across multiple psychiatric disorders and varies dimensionally in the general population. Studying healthy adults can therefore inform mechanisms relevant for social cognition. This study aimed to extend prior findings of associations between social cognition and serotonin transporter (5-HTT) within autistic and non-autistic controls to healthy adults, and to examine serotonin 1B (5-HT 1B ) receptor binding. Results Thirty-one healthy adults (15 males, 16 females) underwent PET imaging with [¹¹C]MADAM to quantify 5-HTT binding. In the replication cohort ( n = 17), MASC performance correlated positively with putaminal 5-HTT binding (ρ = 0.61, p = 0.011, BFR = 15.2) and negatively with brainstem binding (ρ = −0.64, p = 0.008, BFR = 6.1). A similar positive association with putaminal 5-HTT binding was observed in the pooled sample ( n = 31, ρ = 0.53, p = 0.003). However, no correlations survived correction for multiple comparisons. In a separate sample of 32 healthy adults (13 males, 20 females) examined with [¹¹C]AZ10419369 to assess 5-HT 1B receptor binding, no significant associations with measures of social cognition or central coherence were found. Conclusions Results conceptually replicate an association between putaminal 5-HTT binding and social cognition in healthy adults, supporting a role of 5-HTT—but not 5-HT 1B —in social cognitive processes. Keywords: Social cognition, Positron Emission Tomography, Serotonin transporter (5-HTT), Serotonin 1B receptor (5-HT 1B ), Transdiagnostic, Healthy subjects Background As human beings, social cognition has played a pivotal role in the evolution of our species [ 1 , 2 ]. Social cognition refers to a complex set of mental abilities underlying social stimulus perception, processing, interpretation, and response [ 3 ], and is an important determinant of mental health [ 4 , 5 ] and emotional problems [ 6 , 7 ]. Given the involvement of social cognition across multiple psychiatric conditions [ 8 – 16 ] and its normal distribution in the general population [ 17 , 18 ], employing a dimensional approach promises a deeper understanding of social cognition’s role in psychiatric conditions. Being one of the constructs within The Research Domain Criteria (R-DoC) framework [ 19 ], studying social cognition might facilitate the identification of biomarkers associated with this trait and thereby enhancing the development of more precise diagnostic tools and treatments. A central aspect of social cognition is Theory of Mind (ToM): the cognitive capacity to attribute mental states—such as beliefs, intentions, desires, emotions, and knowledge—to oneself and others, and to understand that these mental states may differ between individuals. While deficits in ToM long has been established as core feature in individuals with autism and their relatives [ 20 , 21 ], poorer performance in ToM tests has also been observed in persons with schizophrenia and their siblings [ 9 , 11 ], in those with bipolar disorder and their first-degree relatives [ 22 , 23 ], and in subjects with depression - even during remission [ 24 , 25 ]. Consequently, variations in social cognition are evident not only within specific psychiatric conditions, but also within healthy relatives and the general population, underscoring the relevance to study biomarkers for social cognition within a sample of healthy subjects. In a study published by our group, we employed the molecular imaging technique positron emission tomography (PET) with the radioligand [ 11 C]MADAM to quantify serotonin transporter (5-HTT) binding in vivo. This investigation revealed significantly lower 5-HTT binding in 15 participants with autism diagnosis compared to 15 controls, with reductions of 14.6% in total gray matter and similar decreases observed across cortical regions, subcortical areas, and in the brain stem [ 12 ]. Beyond these group differences, we identified meaningful correlations between 5-HTT binding and social cognition performance across the combined sample of individuals with and without autism. Specifically, 5-HTT availability correlated positively to performance on the Reading the Mind in the Eyes Test (RMET) in total gray matter, brain stem and 7 of 18 subregions, including nucleus accumbens. In addition, performance on Movie for Assessment of Social Cognition (MASC) and Faux Pas also correlated to 5-HTT availability in nucleus accumbens and putamen, whereas Faux Pas performance also correlated positively with anterior cingulate cortex 5-HTT binding. However, only the correlation between RMET and 5-HTT availability in anterior cingulate cortex survived correction for multiple comparisons. Importantly, these correlation patterns were also observed when analysing the non-autistic control participants independently. These findings align with another PET study that reported positive correlations between Faux Pas performance and 5-HTT availability within several parts of the cingulate cortex in autistic participants [ 26 ], suggesting consistent involvement of the serotonin system in social cognitive processes across different populations. In addition, previous research has demonstrated that healthy participants demonstrated enhanced facial expression recognition and faster response times following acute administration of selective serotonin reuptake inhibitors (SSRIs, which block 5-HTT) [ 27 ], while tryptophan depletion—which reduces serotonin levels—led participants to perceive social relationships as less intimate [ 28 ]. Moreover, involvement of the central serotonin system has been implicated in several of the above-mentioned psychiatric disorders, including autism [ 12 , 29 ], schizophrenia [ 30 ], depression [ 31 – 33 ], ADHD [ 34 ], but also in borderline personality disorder [ 35 ], anorexia nervosa [ 36 ], and OCD [ 37 ]. Altogether, these findings indicate that serotonin is relevant for social cognition, even beyond the traditional diagnostic boundaries. Similar to the observed correlations between 5-HTT availability and social cognition in our mixed sample of autistic and non-autistic participants, we identified correlations with central coherence - both an autistic trait and a transdiagnostic endophenotype characterized by detail-focused processing, rather than the whole picture (weak central coherence). In our previous study, we observed two correlations [ 12 ], which did not survive correction for multiple comparisons: performance on the Embedded Figures Test correlated with 5-HTT availability in nucleus accumbens and insula, while no correlations were found for the Fragmented Pictures Test. Weak central coherence, like social cognition impairments, are well-documented in individuals with autism and their relatives [ 38 , 39 ]. However, altered central coherence extends beyond the autism spectrum, manifesting in obsessive compulsive disorder (OCD) [ 40 ], in individuals with borderline traits [ 14 ], and eating disorders, including among their unaffected family members [ 41 ]. Importantly, central coherence varies continuously within the general population [ 17 , 42 ], supporting its conceptualization as a dimensional trait, rather than a categorical deficit within the autistic population. Given our exploratory finding suggesting a possible relationship between central coherence and 5-HTT in a mixed clinical sample, confirmation of this association within a sample of solely healthy subjects represents a critical next step in establishing the generalizability of this neurobiological mechanism within the general population. Aims . Building upon our previous explorative finding, where higher 5-HTT binding correlated with enhanced performance on tests for social cognition and central coherence across both autistic and healthy adults [ 12 ], the first aim was to replicate this within a sample of solely healthy volunteers. Given that both social cognition and central coherence exhibit a normal distribution in the general population [ 17 ], we hypothesize that higher 5-HTT binding would predict superior performance in tests for both social cognition and central coherence. To further investigate the serotonergic bases of these endophenotypes, we extended our research to examine a specific serotonin receptor subtype. 5-HT exerts its diverse effects through 14 receptor subtypes [ 43 ], with extracellular 5-HT being transported back into neurons by the 5-HTT. 5-HTT serves as a global marker of serotonergic function, and selective serotonin reuptake inhibitors (SSRI), targeting 5-HTT, do not significantly affect social cognition or central coherence [ 44 ], suggesting that specific receptor subtypes may be more directly involved in these processes. Given the limited availability of radioligands for human neuroimaging of the serotonin system, we focussed our investigation on the 5-HT 1B receptor. This receptor subtype represents a particularly relevant target for several reasons. First, both 5-HTT and 5-HT 1B serve as regulators of serotonin concentrations in the synapse [ 45 ], positioning them as key candidates for testing whether the serotonin hypothesis of autism can be extended to social cognitive processes. Second, 5-HT 1B receptors are highly expressed in cortical regions implicated in social cognition and central coherence, making them mechanistically plausible mediators for these functions. To our knowledge, this represents the first study investigating a potential relationship between 5-HT 1B and social cognition or central coherence in humans. Based on previous findings demonstrating correlations between 5- HT 1B and 5-HTT availability within the cortical regions [ 46 ], we hypothesized that higher 5-HT 1B binding would correlate to superior performance on measures of social cognition and central coherence, particularly in cortical regions. Methods Participants All participants were enrolled as control subjects in four independent PET studies between 2013 and 2017 [ 12 , 46 – 48 ]. A total of 47 control subjects were pooled, of which 17 participants were investigated with both radioligands. For analysis of 5-HTT binding, 31 participants were included, comprising 15 control participants from study [ 12 ] and 17 from study [ 46 ]. For analysis of 5-HT 1B receptor binding, 33 participants were included, comprising the same 17 controls from study [ 46 ], 4 controls from study [ 47 ] and 12 controls from study [ 48 ]. Given the resource-intensive nature of PET studies, it is standard practice to compile such a database and administer a consistent test battery. All studies were approved by the Regional Ethical Review Board in Stockholm and by the Radiation safety committee of the Karolinska University Hospital. All participants provided written informed consent. Inclusion criteria All participants underwent a comprehensive assessment to ensure their eligibility. This included a clinical interview using the Mini International Neuropsychiatric Interview (M.I.N.I.), a physical examination conducted by a medical doctor, and negative results in urine toxicology screenings before the PET examinations. Exclusion criteria encompassed a medical history of substance abuse, chronic psychiatric disorders, previous head trauma, brain pathology detected via magnetic resonance imaging (MRI), significant medical conditions, and pregnancy. The recruitment and examination of participants were conducted by members of the PET research group at Karolinska Institutet, Stockholm, Sweden. Assessment of social cognition and central coherence The study assessed the dimensional aspect of social cognition through various social-cognitive tests. Behavioural testing was scheduled to coincide with the PET examination on the same day; however, in a small number of participants from diffferent studies, assessments were conducted a few days after PET due to logistical constraints. These assessments included the Movie for Assessment of Social Cognition (MASC [ 49 ]), Reading the Mind in the Eyes Test (RMET [ 50 ]) and Faux Pas [ 51 ]. The MASC test involves a 15 min video portraying four characters at a dinner party. It aims to assess ToM by posing questions related to the thoughts, beliefs and intentions of the characters. The RMET task requires participants to discern the appropriate emotion expressed by each eye pair from four alternatives. Faux Pas assesses ToM through inquiries about social situations and unintentional social rule violations. For the assessment of central coherence, two visual tasks, one focusing on global perception and the other on local details, were employed. The Fragmented Pictures Test (PFT [ 52 ], , required participants to identify progressively revealed drawings of common objects with as little information as possible. The Embedded Figures Test (EFT [ 53 ], , tasks participants with detecting simpler shapes embedded within larger and more complex pictures. Image acquisition and analysis Magnetic resonance imaging (MRI; 3T, GE Healthcare) was conducted for exclusion of brain anomalies and for delineation of brain regions. For each participant, the MR image was co-registered to a summated PET image as previously described using Statistical parametric mapping (SPM12; Wellcome Department of Cognitive Neurology, University College, London, U.K). During PET examinations, subjects were positioned recumbent with their heads inside the PET system and wore a plastic helmet to minimize head movement. Radioligands [ 11 C]MADAM and [ 11 C]AZ10419369 were synthesized as previously reported [ 54 , 55 ]. 5-HTT sample 14 control subjects from the original study underwent examination of 5-HTT binding using [ 11 C]MADAM and the High Resolution (HR) ECAT PET system (Siemens, Knoxville, TN), while the additional 17 subjects were examined with the High Resolution Research Tomograph (HRRT) ECAT PET system (Siemens Molecular Imaging). The acquisition time for all examinations was 93 min. The PET data from the 14 subjects investigated with the HR system were divided into 31 time frames (4 × 15 s, 4 × 30 s, 6 × 60 s, 6 × 180 s, and 11 × 360 s), reconstructed using filtered back projection, and corrected for head motion using a frame-to-first-frame approach. For the 17 subjects investigated with the HRRT PET system, the PET data was divided into 38 frames (9 × 10 s, 2 × 15 s, 3 × 20 s, 4 × 30 s, 4 × 60 s, 4 × 180 s, and 12 × 360 s). Dynamic PET images were corrected for head motion using a between frame-correction algorithm implemented in SPM12 (Wellcome Department of Cognitive Neurology, University College, London, UK). Injected radioactivity and molar (specific) activity were within previously reported ranges for these datasets. Injected activity was typically ~ 370–410 MBq, with molar activity in the range of approximately 230–240 GBq/µmol at the time of injection [ 12 , 46 ]. For delineation of brain regions in the 5-HTT sample, Freesurfer (versions 5.0 and 6.0 [ 56 ]) was employed, and brain region anatomy was defined using the cortical atlas of Desikan-Killany [ 57 ]. 5-HTT binding potential (BP ND ) was quantified using the simplified reference tissue model (SRTM [ 58 ]), with the cerebellar gray matter serving as the reference region [ 59 , 60 ]. For the replication sample, this differs from the quantification methods previously reported [ 46 ]. Regions of interest (ROIs) were selected based on where correlations between social cognition and 5-HTT were found in our original study, and included gray matter, putamen, brain stem, frontal cortex, anterior cingulate cortex, posterior cingulate cortex, insula, amygdala, and nucleus accumbens. 5-HT 1B receptor sample 33 subjects underwent examination of 5-HT 1B receptor binding using the radioligand [ 11 C]AZ10419369 and the HRRT PET system. Data from the first 63 min were used for quantification to enable data pooling, to ensure consistent frame definitions across all data. Injected radioactivity and molar (specific) activity were consistent with previously published values. Injected activity was typically ~ 380–414 MBq, with molar activity in the range of approximately 265–330 GBq/µmol at the time of injection [ 46 – 48 ]. Brain regions were automatically defined using Freesurfer (version 6.0 [ 56 ]), except for the dorsal brainstem (DBS), which was defined based on [ 11 C]AZ10419369 PET template data [ 61 , 62 ], and gray matter defined by SPM segmentation. The cerebellum, with negligible 5-HT 1B receptor density [ 63 ], served as the reference region for both BP ND quantification using SRTM and an algorithm for wavelet-aided parametric imaging (WAPI) to reduce noise [ 64 ] for smaller ROIs, including the amygdala, and hippocampus. ROIs were selected based on existing literature related to social cognition and 5-HTT, and included gray matter, putamen, brain stem, striatum, frontal cortex, temporal cortex, anterior cingulate cortex, posterior cingulate cortex, insula, orbitofrontal cortex, caudatus, thalamus, nucleus accumbens, hippocampus, occipital cortex, amygdala, and pallidum. Statistical analysis Descriptive statistics for both samples are presented in Table 1 . Table 1. Descriptive statistics for the samples examined with [ 11 C]MADAM (5-HTT sample) and [ 11 C]AZ10419369 (5-HT 1B sample) 5-HTT sample 5-HT 1B receptor sample n Range Mean (SD) n Range Mean (SD) Age 31 21–75 40.7 (13.8) 33 20–75 38.3 (14.91) Sex assigned at birth Female 16 20 Male 15 13 MASC 31 27–42 35.2 (4.1) 33 25–42 34 (4.34) RMET 31 20–33 28.2 (3.3) 32 20–32 28 (3.24) Faux Pas 31 41–60 54 (4.9) 17 46–60 55 (4.55) EFT 31 31-1509 473 (322) 33 31-1509 514 (330.44) FPT 31 80–460 185 (79.8) 33 87–538 197 (87.59) Open in a new tab 5-HTT serotonin transporter, 5-HT 1B serotonin 1B receptor, MASC movie for assessment of social cognition, RMET reading mind in the eyes test, EFT embedded figure test (seconds), FPT fragmented picture test (seconds), n number of participants, SD standard deviation Due to the non-normally distributed test data, Spearman’s correlations were employed to explore inter-regional relationships, associations between behavioural tasks and demographic variables (age and education), as well as associations between radioligand binding and demographic variables within each sample, corrected for age. Given the partially exploratory nature of the study, and for ease of interpretation, findings are presented without correction for multiple comparisons. In addition, the false discovery rate [ 65 ] was applied. All statistical tests were two-tailed, and the significance level was set at p ≤ 0.05 and were corrected for multiple comparisons using Benjamini-Hochberg method [ 65 ]. Statistical analyses were conducted using R Studio [ 66 ]. Raw data and code are available at https://osf.io/z6mbn/?view_only=d4028579be2143d3b077f408f65e78ce . 5-HTT sample Given the inclusion of the 14 controls from our original study [ 12 ], where correlations between social cognition or central coherence and 5-HTT binding were identified, and the potential confounding factors related to disparities in PET systems, several methodological steps were taken. First, an analysis by excluding the 14 subjects from the original study was conducted, resulting in a distinct replication sample comprising 17 new subjects examined using the same PET system. Spearman’s correlations were employed for this replication sample, as well as for the healthy controls from of the original study (where autistic subjects also were included in the analysis). Subsequently, to provide a robust assessment of the correlation’s replicability, we employed Bayesian analysis, which yielded a Bayes Replication Factor. This test compares the predictive adequacy of the null hypothesis (H 0 (i.e., no correlation) versus the alternative hypothesis (H r , representing the original correlation). The Bayes Replication Factor quantifies the likelihood of observing the original correlation versus no correlation, given the additional data [ 67 , 68 ]. Importantly, this approach allows for the integration of additional data, providing a comprehensive evaluation of the correlation’s replicability. Lastly, BP ND values were standardized (with mean = 0 and standard deviation = 1) within both groups to address potential variations arising from the utilization of the different PET systems. Then, the Spearman’s correlation test was conducted for the whole sample. These methodological steps were taken to ensure the reliability and validity of our findings, considering the potential impact of varying PET systems and the specific composition of the study population. 5-HT 1B receptor sample Partial Spearman´s correlations, corrected for age, were used to investigate associations between cognitive performance and 5-HT 1B BP ND values. For non-significant correlations, a Bayes Factor for correlation was calculated, to quantify evidence in favor of the null hypothesis (i.e. no correlation) [ 68 , 69 ] . During the preparation of this work, the author(s) used ChatGPT-3.5 (OpenAI, 2024) to improve coding guidance, readability, and language, as well as Claude.ai (Anthropic, 2024) to improve readability and language. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article. Results 5-HTT sample Correlations between 5-HTT binding and performance on social cognition tests Controls from the original sample In the control participants from the original sample ( n = 14), significant positive correlations were observed between RMET test scores and 5-HTT binding across several limbic and cortical regions: anterior cingulate cortex (Spearman’s rho = 0.72, p = 0.012), insula (Spearman’s rho = 0.64, p = 0.033), and posterior cingulate cortex (Spearman’s rho = 0.73, p = 0.010). However, none of these correlations remained statistically significant following correction for multiple comparisons, using the Benjamini-Hochberg procedure. Replication sample In the replication sample consisting of 17 participants, significant correlations were identified between MASC performance and 5-HTT availability in two brain regions. Specifically, positive correlations were observed in the putamen (Spearman’s rho = 0.61, p = 0.011), while a negative correlation was found in the brain stem (Spearman’s rho = -0.64, p = 0.008, Fig. 1 ). Similar to the results from the original sample, these correlations did not remain significant after correction for multiple comparisons, using the Benjamini-Hochberg procedure. No significant correlations were detected between 5-HTT binding on other social cognitive tests in the replication sample. Fig. 1. Open in a new tab correlations between 5-HTT binding and MASC scores in control participants from original and replication sample. Partial pearsons correlations between 5-HTT binding potential (BP ND ) and MASC scores in the control participants from the original sample and the replication sample, corrected for age. Abbrevations: MASC Movie for Assessment of Social Cognition, BP ND binding potential Figure 1 displays the correlations between 5-HTT BP ND and MASC scores for both the original and replication sample, with separate panels illustrating findings in the brain stem, nucleus accumbens and putamen – regions where significant uncorrected correlations were identified in at least one sample. Note that the correlation in nucleus accumbens was previously observed in the original study when analysing the complete sample including participants with autism. Bayes replication analysis Replication Bayes Factors were computed for the correlations between test scores and 5-HTT BP ND for regions where significant effects were observed in either study. For MASC performance, the probability that the data represent a replication of the correlation obtained in the original study is 15.2 times more likely than that of a correlation of 0 (BF 0r = 15.2) in the putamen, and 6.1 times more likely in the brain stem. For the significant correlations observed in the original study (between performance on RMET and 5-HTT binding in anterior cingulate cortex, posterior cingulate cortex and insula, the Bayes Factors ranged from 0.02 to 0.16, indicating moderate to strong evidence in favour of the null-hypothesis (i.e. no correlation). Pooled sample analysis Figure 2 illustrates the correlations between 5-HTT binding and performance on social cognition tasks for the pooled sample, containing control participants from the original study ( n = 14) and the replication sample ( n = 17). A positive correlation between 5-HTT BP ND and MASC was observed in the putamen (Spearman’s rho = 0.53, p = 0.003), while a negative correlation was observed in brain stem (Spearman’s rho = -0.40, p = 0.028); For RMET and 5-HTT BP ND in anterior cingulate cortex a positive correlation was observed (Spearman’s rho = 0.37, p = 0.04). None of these correlations remained significant after correction for multiple comparisons. Fig. 2. Open in a new tab Correlations between 5-HTT binding and social cognitions and central coherence tests in the pooled sample. Spearman’s correlation between the standardized 5-HTT binding potential (BP ND ) and performance on tests for social cognition and central coherence in the pooled sample of 14 controls from original study, plus 17 additional healthy subjects. Abbreviations: GM gray matter, PUT putamen, BS brain stem, FC frontal cortex, ACC anterior cingulate cortex, INS insula, AMG amygdala, PCC posterior cingulate cortex, NAC nucleus accumbens, MASC Movie for Assessment of Social Cognition, RMET Reading the Mind in the Eyes Test, EFT Embedded Figures Test, FPT Fragmented Pictures Test. * significant result ( p < 0.05), before correction for multiple comparisons. None of the correlations remained significant after multiple comparison correction Correlations between 5-HTT binding and performance on central coherence tests No significant correlations between 5-HTT binding and performance on EFT or FPT were observed in the controls from the original sample ( n = 14), the replication sample ( n = 17), or in the pooled sample (Fig. 2 ). The original study, including autistic participants, found significant correlations between performance on EFT and 5-HTT binding in insula and nucleus accumbens. The Bayes Replication Factors were 0.17 and 0.19 for these regions, respectively, indicating that the absence of a correlation was (1/0.17 =) 5.9 and (1/0.19 =) 5.3 times more likely than the correlations observed in the controls from the original study. 5-HT 1B sample Correlations between 5-HT 1B receptor binding and performance on tests for social cognition and central coherence 5-HT 1B receptor binding in thalamus correlated positively to EFT performance (Spearman´s rho = 0.41; p = 0.02) and negatively to performance on RMET (Spearmans rho = -0.45, p = 0.02). However, these correlations were no longer statistically significant after multiple comparison correction. Bayesian analysis revealed mostly evidence in favor of the null hypothesis (i.e. no correlation). The Bayes Factors for correlation ranged from 0.015 to 4.5, with the majority falling below 1/3 indicating moderate evidence in favor of the null-hypothesis [ 70 ]. Only the correlations between thalamic 5-HTT binding and both EFT and RMET performance provided anecdotal and moderate evidence in favor of the alternative hypothesis (i.e. the presence of a correlation). Discussion In the present study, we examined the relationship between social cognition and serotonergic markers in healthy adults using PET imaging of the 5-HTT and 5-HT 1B receptor. Building on our previous work in a mixed sample of autistic and neurotypical participants [ 12 ], we sought to evaluate the robustness and generalizability of previously reported associations within a non-clinical population. We replicated the positive correlation between performance on MASC and 5-HTT binding in the putamen in a sample of healthy adults, extending findings from our prior study that included both autistic and healthy participants [ 12 ]. Despite the correlation not retaining significance after correction for multiple comparisons, the Bayes Replication Factor of 15.2 indicates that the correlation found in the original study is 15.2 times more likely than the null hypothesis (no correlation), providing evidence for a genuine association [ 70 ]. However, our replication efforts were not uniformly successful. We were unable to replicate correlations between 5-HTT binding and social cognition in other brain regions, nor for the other tests for social cognition or central coherence. Notably, despite stronger and more numerous correlations for the RMET test in our original study, we could not replicate these findings in the current sample of healthy controls. This selective replication pattern may reflect differences in test sensitivity and score distributions within non-clinical populations, but alternative explanations, including limited statistical power, cannot be excluded. In our original study, correlations between RMET performance and regional 5-HTT binding were primarily driven by autistic participants, whereas the MASC-5-HTT correlation was evident across both autistic and neurotypical participants. Examination of score distributions reveals that MASC performance shows greater variability among healthy controls compared to RMET performance (MASC: range 27–42, median 36; RMET: range 20–33, median 29). This superior score distribution for MASC may indicate that it is more sensitive to individual differences in social cognitive abilities within the general population, whereas RMET may show ceiling effects or restricted range in neurotypical samples. These findings suggest that different social cognition measures may have varying utility for detecting neurobiological correlates in clinical versus non-clinical populations. While RMET may be particularly sensitive to the more pronounced social cognitive differences observed in autism spectrum conditions, MASC appears better suited for capturing the subtler variations in social cognition present within neurotypical populations. Furthermore, though we observed a correlation between tests for central coherence and 5-HTT binding in our previous study, we were unable to replicate this within the current sample of healthy controls. In contrast, we found evidence in favour of the null hypothesis (i.e. no correlation was about 5 times more likely than the correlation of the original study). These findings imply that 5-HTT is not involved in central coherence in healthy adults. In contrast to our original findings, we observed a negative correlation for MASC scores and 5-HTT binding in brain stem, whereas the original study showed a positive correlation in this region. The Bayes Replication Factor of 6.1 indicates that the positive correlation observed in the original study is 6.1 times more likely than the null hypothesis of no correlation. Bayes Factors below 3 are typically considered to provide ambiguous support, whereas Bayes Factors above 10 are considered to offer strong support in favor of a hypothesis [ 70 ]. Notably, we failed to replicate the findings from Nakamura et al. [ 26 ] regarding the correlation between performance on Faux Pas within autistic participants and 5-HTT availability in several parts of the cingulate cortex, within a sample of healthy subjects. Altogether, these findings provide conceptual replication evidence for a possible role of putaminal 5-HTT in social cognition, within the general population, while the role of other brain regions remains less certain and warrants further investigation. Although the literature on this topic is limited, several studies suggest a potential involvement of the putamen in social cognition. Lesion, neurodegenerative, and functional imaging studies have linked putaminal involvement to TOM performance, primarily through dopaminergic mechanisms [ 71 – 74 ]. While these findings primarily implicate dopaminergic mechanisms, serotonin may also play a crucial role in putaminal modulation of social cognition. The putamen represents one of three brain regions with the highest 5-HTT binding potential values, which may have provided sufficient statistical power to detect serotonergically-mediated correlations that were obscured in cortical regions where [ 11 C]MADAM binding is substantially lower. However, this power-based explanation is challenged by by the absence of comparable findings in other high-binding regions, including the thalamus and pallidum. The putamen’s role in social cognition may involve complex interactions between dopaminergic and serotonergic systems within cortico-striatal circuits. Given the well-established co-regulation and functional interactions between these neurotransmitter systems [ 75 ], serotonergic modulation through 5-HTT could complement or modulate dopaminergic influences on social cognitive performance. In conclusion, while dopaminergic involvement in putaminal social cognition is better established, our findings suggest that serotonergic mechanisms may represent an important but underexplored pathway warranting further investigation. In our exploratory part, we found that 5-HT 1B receptor binding in the thalamus showed opposing relationships with two measures: it correlated positively with performance on EFT, reflecting greater accuracy and detail-focussed processing, but negatively with RMET performance, which indexes the ability to infer mental states from eye-region photographs (i.e. superior social cognition). However, none of the observed correlations remained statistically significant after correcting for multiple comparisons. Bayesian analysis further indicated that the data provided mostly moderate evidence in favour of no correlation. The only exceptions were thalamic 5-HTT 1B binding with EFT and RMET performance, where the presence of a correlation was 2.8 and 4.5 times more likely, respectively, then the null hypothesis. While these results suggest a potential role for thalamic 5-HT 1B in both social cognition and central coherence, replication in larger, independent samples is required. 5-HTT and 5-HT 1B receptors are both expressed in serotonergic neurons, regulating presynaptic 5-HT release. However, 5-HT 1B receptors are also expressed in non-serotonergic neurons as heteroreceptors, regulating neurotransmitter release [ 45 ]. While 5-HTT binding and 5-HT 1B binding are highly correlated in most cortical regions, this was not observed for subcortical regions (including putamen), which are lacking 5-HT 1B heteroreceptors [ 46 ]. In addition, in contrast to 5-HTT, the 5-HT 1B receptor is more dynamic: it changes following cognitive behavior therapy, tryptophan depletion or acute SSRI administration for example [ 76 ]. Although the 5-HT 1B receptor has been associated with social behaviors, these primarily involve states such as anxiety, reward or dependence-driven behaviors [ 76 ], rather than a stable trait such as social cognition. While no human studies have been published examining social cognition in relation to the 5-HT 1B receptor, autistic mouse model studies demonstrate that administration of a 5-HT 1B receptor antagonist can rescue sociability deficits [ 77 ]. However, it is questionable whether these social deficits observed in mice accurately reflect human social cognition abilities. Therefore, with no previously reported link to 5-HT 1B in human behavior, the dynamic nature of it and our null-finding, we pose that the 5-HT 1B receptor is probably not involved in social cognition. Limitations Several limitations warrant consideration. First, the inclusion of 14 controls from the original study violates assumptions for frequentist statistical analysis, raising concerns about the validity of the combined results. However, in the separate replication sample we obtained a correlation between MASC and 5-HTT binding in putamen, although this did not survive multiple comparison correction. The subsequent implementation of Bayes Replication Factors supported a replication of the correlation between MASC and 5-HTT binding in putamen, in contrast to the other brain regions or cognitive tests. Second, combining datasets from two distinct PET systems can pose several challenges due to variations in system-specific characteristics, such as scanner sensitivity, spatial resolution and reconstruction algorithms. These differences can lead to inconsistencies in the data, affecting the accuracy and reliability of the pooled results. We tried to overcome these PET system differences by a separate analysis and standardization of the datasets. Also, the Bayesian approach is resilient to differences in PET systems, as it utilizes correlation coefficients from each study independently. This ensures that potential variations stemming from PET system disparities do not unduly influence the assessment of the correlation’s reproducibility. Finally, limited statistical power is an inherent challenge in PET research. The emphasis on the inherent challenges in this research is crucial. The complexity of studying the brain and behaviour, compounded by the inherent limitations in the reliability of PET measures and cognitive testing, underscores the difficulty of drawing definitive conclusions. The potential for false positives (false discovery rate) is commonly estimated as 5% in frequentist statistics. With the examination of 17 brain regions and 5 cognitive tests, the likelihood of obtaining 4–5 significant results is anticipated, as observed in our study. Employing the Bayesian analysis, we were able to identify some possible false positive findings from our original study. Conclusions Our hypothesis, asserting a connection between social cognition and 5-HTT binding, finds partial confirmation. Replication in a sample of healthy controls substantiates our previous findings, with the strongest evidence emerging for putaminal 5-HTT involvement in social cognition within the general population. However, the role of other brain regions remains less certain and warrants further investigation. In contrast, our exploratory analysis revealed no evidence for of 5-HT 1B receptor involvement in social cognition. In addition, we found no convincing evidence for 5-HTT or for 5-HT 1B involvement in central coherence. The divergent findings between 5-HTT and 5-HT 1B receptor binding are particularly noteworthy and highlight the complexity of serotonergic modulation of social cognition. The observation that a global marker of serotonergic function (5-HTT) correlates with social cognitive performance while a specific receptor subtype (5-HT 1B ) does not suggests several possible mechanisms. First, putaminal involvement in social cognition may be mediated through broad serotonergic tone rather than through specific receptor-mediated pathways. This could indicate that social cognitive performance is more sensitive to overall serotonin availability and reuptake efficiency than to the activation of particular receptor subtypes. Alternatively, 5-HTT binding may reflect upstream regulatory processes or compensatory mechanisms that influence multiple downstream serotonergic pathways simultaneously, effects that would not be captured by measuring individual receptor subtypes. The global nature of 5-HTT function—regulating synaptic serotonin availability across multiple receptor systems—may be more relevant for complex cognitive processes like social cognition that likely depend on coordinated activity across various serotonergic circuits. In conclusion, these findings suggest that global serotonergic function, as indexed by 5-HTT binding, may be more relevant than specific receptor mechanisms for social cognitive processes, providing partial support for serotonergic involvement in social cognition even within healthy populations. Acknowledgements We would like to thank all staff at KI PET center, and all participants. Abbreviations 5-HT Serotonin 5-HTT Serotonin transporter 5-HT 1B Serotonin receptor 1B PET Positron emission tomography BP ND Binding potential BFR Bayes replication factors ToM Theory of mind R-DoC Research domain criteria [ 11 C]MADAM [¹¹C]N, N-Dimethyl-2-(2-amino-4-methylphenylthio)benzylamine (carbon 11) [¹¹C]AZ10419369 [¹¹C]2-(1,4-Biazepan-1-yl)-N-(4-methoxybenzyl)-N-(1,3-thiazol-4-yl)acetamide MASC Movie for the assessment of social cognitio RMET Reading the mind in the eyes test EFT Embedded figures test FPT Fragmented pictures test GM Gray matter PUT Putamen BS Brain stem FC Frontal cortex ACC Anterior cingulate cortex INS Insula AMG Amygdala PCC Posterior cingulate cortex NAC Nucleus accumbens Author contributions GG contributed to the methodology, performed the formal analysis including PET image and statistical analyses, and was involved in visualization and in writing, reviewing, and editing the manuscript. ÄT contributed to the methodology, conducted the investigation and data curation, and was a major contributor in writing the original draft as well as reviewing and editing the manuscript. EV performed the formal PET image analysis. JS contributed to the investigation and formal PET image analysis, and participated in writing, reviewing, and editing the manuscript. MT provided supervision and contributed to writing, reviewing, and editing. MN contributed to the investigation and participated in writing and reviewing the manuscript. MA contributed to the investigation and formal PET image analysis. KS provided supervision and contributed to writing, reviewing, and editing. AV participated in writing, reviewing, and editing the manuscript. CH was responsible for project administration. KV contributed to writing and reviewing the manuscript. JB contributed to the conceptualization and methodology, participated in writing, reviewing, and editing, and provided supervision, project administration, and funding acquisition. JL contributed to the conceptualization and methodology, participated in writing, reviewing, and editing, and provided supervision, project administration, and funding acquisition. All authors read and approved the final manuscript. Funding Open access funding provided by Karolinska Institute. The results leading to this publication have received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115300 and No 777394 for the projects EU-AIMS and AIMS-2-TRIALS. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA and AUTISM SPEAKS, Autistica, SFARI. Furthermore, the work was funded by the Swedish Research Council (2013–09304), StratNeuro, and a donation from Birgitta and Sten Westerberg. Additional support was received from Region Stockholm (ALF project Y00166 , Clinical research appointment 2020 − 0735, and Clinical research appointment K2017-4579). Ämma Tangen was supported by a grant from Fonden för psykisk hälsa. Jonas Svensson was supported by a postdoctoral grant from The Swedish Brain Foundation. Mikael Tiger was supported by Region Stockholm (clinical research appointment). Data availability The datasets generated and/or analysed during the current study are available in the Open Science Framework repository, https://osf.io/z6mbn/?view_only=d4028579be2143d3b077f408f65e78ce . Declarations Ethics approval and consent to participate All studies were approved by the Regional Ethical Review Board in Stockholm and by the Radiation safety committee of the Karolinska University Hospital. All participants provided written informed consent. Consent for publication Not applicable. Competing interests JL has received speaker’s fee from Janssen-Cilag AB, Sweden, at one occasion in the previous three years. JB receives royalties for textbooks from Hogrefe. GG, ÄT, EV, JS, MT, MN, MA, KS, AV, CH and KV declare no potential conflict of interest. Research funds were granted before the study was summarized and not dependent on the results of this study. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Gina Griffioen and Ämma Tangen contributed equally to this work. Jacqueline Borg and Johan Lundberg contributed equally to this work. References 1. Herrmann E, Call J, Hernàndez-Lloreda MV, Hare B, Tomasello M. Humans Have Evolved Specialized Skills of Social Cognition: The Cultural Intelligence Hypothesis. Science. 2007;317:1360–6. 10.1126/science.1146282. [ DOI ] [ PubMed ] [ Google Scholar ] 2. Togher L, Douglas J, Turkstra LS, Welch-West P, Janzen S, Harnett A, et al. INCOG 2.0 Guidelines for Cognitive Rehabilitation Following Traumatic Brain Injury, Part IV: Cognitive-Communication and Social Cognition Disorders. J Head Trauma Rehabilitation. 2023;38:65–82. 10.1097/htr.0000000000000835. [ DOI ] [ PubMed ] [ Google Scholar ] 3. Beaudoin C, Beauchamp MH. Chapter 21 Social cognition. Handb Clin Neurol. 2020;173:255–64. 10.1016/b978-0-444-64150-2.00022-8. [ DOI ] [ PubMed ] [ Google Scholar ] 4. Santamaría-García H, Baez S, Gómez C, Rodríguez-Villagra O, Huepe D, Portela M, et al. The role of social cognition skills and social determinants of health in predicting symptoms of mental illness. Transl Psychiatry. 2020;10:165. 10.1038/s41398-020-0852-4. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 5. Fusar-Poli P, de Pablo GS, Micheli AD, Nieman DH, Correll CU, Kessing LV, et al. What is good mental health? A scoping review. Eur Neuropsychopharmacol. 2020;31:33–46. 10.1016/j.euroneuro.2019.12.105. [ DOI ] [ PubMed ] [ Google Scholar ] 6. Tsomokos DI, Flouri E. The role of social cognition in mental health trajectories from childhood to adolescence. Eur Child Adolesc Psychiatry. 2023;1–16. 10.1007/s00787-023-02187-8. [ DOI ] [ PMC free article ] [ PubMed ] 7. Holt-Lunstad J, Smith TB, Layton JB. Social Relationships and Mortality Risk: A Meta-analytic Review. PLoS Med. 2010;7:e1000316. 10.1371/journal.pmed.1000316. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 8. Plana I, Lavoie M-A, Battaglia M, Achim AM. A meta-analysis and scoping review of social cognition performance in social phobia, posttraumatic stress disorder and other anxiety disorders. J Anxiety Disord [Internet]. 2014;28:169–77. 10.1016/j.janxdis.2013.09.005. [ DOI ] [ PubMed ] [ Google Scholar ] 9. Deng F, Bueber MA, Cao Y, Tang J, Bai X, Cho Y, et al. Assessing social cognition in patients with schizophrenia and healthy controls using the reading the mind in the eyes test (RMET): a systematic review and meta-regression. Psychol Med. 2024;1–27. 10.1017/s0033291723003501. [ DOI ] [ PMC free article ] [ PubMed ] 10. Gillissie ES, Lui LMW, Ceban F, Miskowiak K, Gok S, Cao B, et al. Deficits of social cognition in bipolar disorder: Systematic review and meta-analysis. Bipolar Disord. 2022;24:137–48. 10.1111/bdi.13163. [ DOI ] [ PubMed ] [ Google Scholar ] 11. Łoś R, Gajowiec A. Impairment of social cognition in comparative studies of patients with schizophrenia and their healthy siblings. Psychiatr Polska. 2023;57:967–82. 10.12740/pp/152271. [ DOI ] [ PubMed ] [ Google Scholar ] 12. Andersson M, Tangen Ä, Farde L, Bölte S, Halldin C, Borg J, et al. Serotonin transporter availability in adults with autism—a positron emission tomography study. Mol Psychiatry. 2020;26:1647–58. 10.1038/s41380-020-00868-3. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 13. Ortega-Díaz E, García-Campos J, Rico-Gomis JM, Cuesta-Moreno C, Palazón-Bru A, Estañ-Cerezo G, et al. Social cognition and social functioning in people with borderline personality disorder and their first-degree relatives. PeerJ. 2020;8:e10212. 10.7717/peerj.10212. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 14. Goueli T, Nasreldin M, Madbouly N, Dziobek I, Farouk M. Social cognition in adolescent females with borderline personality traits. Psychol Psychother: Theory Res Pr. 2020;93:739–53. 10.1111/papt.12257. [ DOI ] [ PubMed ] [ Google Scholar ] 15. Green MF, Horan WP, Lee J. Social cognition in schizophrenia. Nat Rev Neurosci. 2015;16:620–31. 10.1038/nrn4005. [ DOI ] [ PubMed ] [ Google Scholar ] 16. Fusar-Poli L, Rodolico A, Martinez M, Fichera C, Lin BD, Basadonne I, et al. The association between polygenic risk scores for mental disorders and social cognition: A scoping review. J Psychiatr Res. 2023;164:389–401. 10.1016/j.jpsychires.2023.06.029. [ DOI ] [ PubMed ] [ Google Scholar ] 17. Lundström S, Chang Z, Råstam M, Gillberg C, Larsson H, Anckarsäter H, et al. Autism Spectrum Disorders and Autisticlike Traits: Similar Etiology in the Extreme End and the Normal Variation. Arch Gen Psychiatry [Internet]. 2012;69:46–52. 10.1001/archgenpsychiatry.2011.144. [ DOI ] [ PubMed ] [ Google Scholar ] 18. Carroll GA, Montrose VT, Burke T. Correlates of Social Cognition and Psychopathic Traits in a Community-Based Sample of Males. Front Psychol. 2021;12:656299. 10.3389/fpsyg.2021.656299. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 19. Gur RC, Gur RE. Social cognition as an RDoC domain. Am J Méd Genet Part B: Neuropsychiatr Genet. 2016;171:132–41. 10.1002/ajmg.b.32394. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 20. Baron-Cohen S, Leslie AM, Frith U. Does the autistic child have a theory of mind. ? Cognition. 1985;21:37–46. 10.1016/0010-0277(85)90022-8. [ DOI ] [ PubMed ] [ Google Scholar ] 21. Velikonja T, Fett A-K, Velthorst E. Patterns of Nonsocial and Social Cognitive Functioning in Adults With Autism Spectrum Disorder. JAMA Psychiatry. 2019;76:135–51. 10.1001/jamapsychiatry.2018.3645. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Bora E, Bartholomeusz C, Pantelis C. Meta-analysis of Theory of Mind (ToM) impairment in bipolar disorder. Psychol Med. 2016;46:253–64. 10.1017/s0033291715001993. [ DOI ] [ PubMed ] [ Google Scholar ] 23. Santos JM, Pousa E, Soto E, Comes A, Roura P, Arrufat FX, et al. Theory of Mind in Euthymic Bipolar Patients and First-Degree Relatives. J Nerv Ment Dis. 2017;205:207–12. 10.1097/nmd.0000000000000595. [ DOI ] [ PubMed ] [ Google Scholar ] 24. Ladegaard N, Videbech P, Lysaker PH, Larsen ER. The course of social cognitive and metacognitive ability in depression: Deficit are only partially normalized after full remission of first episode major depression. Br J Clin Psychol. 2016;55:269–86. 10.1111/bjc.12097. [ DOI ] [ PubMed ] [ Google Scholar ] 25. Bora E, Berk M. Theory of mind in major depressive disorder: A meta-analysis. J Affect Disord. 2016;191:49–55. 10.1016/j.jad.2015.11.023. [ DOI ] [ PubMed ] [ Google Scholar ] 26. Nakamura K, Sekine Y, Ouchi Y, Tsujii M, Yoshikawa E, Futatsubashi M, et al. Brain Serotonin and Dopamine Transporter Bindings in Adults With High-Functioning Autism. Arch Gen Psychiatry [Internet]. 2010;67:59–68. 10.1001/archgenpsychiatry.2009.137. [ DOI ] [ PubMed ] [ Google Scholar ] 27. Harmer CJ, Bhagwagar Z, Perrett DI, Völlm BA, Cowen PJ, Goodwin GM. Acute SSRI Administration Affects the Processing of Social Cues in Healthy Volunteers. Neuropsychopharmacology. 2003;28:148–52. 10.1038/sj.npp.1300004. [ DOI ] [ PubMed ] [ Google Scholar ] 28. Bilderbeck AC, McCabe C, Wakeley J, McGlone F, Harris T, Cowen PJ, et al. Serotonergic Activity Influences the Cognitive Appraisal of Close Intimate Relationships in Healthy Adults. Biol Psychiatry [Internet]. 2011;69:720–5. 10.1016/j.biopsych.2010.12.038. [ DOI ] [ PubMed ] [ Google Scholar ] 29. Schain RJ, Freedman DX. Studies on 5-hydroxyindole metabolism in autistic and other mentally retarded children. J Pediatr [Internet]. 1961;58:315–20. 10.1016/s0022-3476(61)80261-8. [ DOI ] [ PubMed ] [ Google Scholar ] 30. Rasmussen H, Erritzoe D, Andersen R, Ebdrup BH, Aggernaes B, Oranje B, et al. Decreased Frontal Serotonin2A Receptor Binding in Antipsychotic-Naive Patients With First-Episode Schizophrenia. Arch Gen Psychiatry. 2010;67:9–16. 10.1001/archgenpsychiatry.2009.176. [ DOI ] [ PubMed ] [ Google Scholar ] 31. Gryglewski G, Lanzenberger R, Kranz GS, Cumming P. Meta-Analysis of Molecular Imaging of Serotonin Transporters in Major Depression. J Cereb Blood Flow Metab [Internet]. 2014;34:1096–103. 10.1038/jcbfm.2014.82. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 32. Tiger M, Farde L, Rück C, Varrone A, Forsberg A, Lindefors N, et al. Low serotonin1B receptor binding potential in the anterior cingulate cortex in drug-free patients with recurrent major depressive disorder. Psychiatry Res: Neuroimaging. 2016;253:36–42. 10.1016/j.pscychresns.2016.04.016. [ DOI ] [ PubMed ] [ Google Scholar ] 33. Murrough JW, Henry S, Hu J, Gallezot J-D, Planeta-Wilson B, Neumaier JF, et al. Reduced ventral striatal/ventral pallidal serotonin1B receptor binding potential in major depressive disorder. Psychopharmacology. 2011;213:547–53. 10.1007/s00213-010-1881-0. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 34. Faraone SV, Ward CL, Boucher M, Elbekai R, Brunner E. Role of serotonin in psychiatric and somatic comorbidities of attention-deficit/hyperactivity disorder: a systematic literature review. Neurosci Biobehav Rev. 2025;176:106275. 10.1016/j.neubiorev.2025.106275. [ DOI ] [ PubMed ] [ Google Scholar ] 35. Soloff PH, Price JC, Meltzer CC, Fabio A, Frank GK, Kaye WH. 5HT2A Receptor Binding is Increased in Borderline Personality Disorder. Biol Psychiatry. 2007;62:580–7. 10.1016/j.biopsych.2006.10.022. [ DOI ] [ PubMed ] [ Google Scholar ] 36. Bailer UF, Frank GK, Henry SE, Price JC, Meltzer CC, Mathis CA, et al. Exaggerated 5-HT1A but Normal 5-HT2A Receptor Activity in Individuals Ill with Anorexia Nervosa. Biol Psychiatry. 2007;61:1090–9. 10.1016/j.biopsych.2006.07.018. [ DOI ] [ PubMed ] [ Google Scholar ] 37. Perani D, Garibotto V, Gorini A, Moresco RM, Henin M, Panzacchi A, et al. In vivo PET study of 5HT2A serotonin and D2 dopamine dysfunction in drug-naive obsessive-compulsive disorder. NeuroImage. 2008;42:306–14. 10.1016/j.neuroimage.2008.04.233. [ DOI ] [ PubMed ] [ Google Scholar ] 38. Happé F, Briskman J, Frith U. Exploring the cognitive phenotype of autism: weak central coherence in parents and siblings of children with autism: I. Experimental tests. J child Psychol psychiatry allied Discipl. 2001;42:299–307. [ PubMed ] [ Google Scholar ] 39. Bojda A, Srebnicki T, Konowałek Ł, Bryńska A. Weak central coherence – construct conception, development, research methods. Psychiatr Polska. 2021;55:1373–86. 10.12740/pp/onlinefirst/120931. [ DOI ] [ PubMed ] [ Google Scholar ] 40. Kuelz AK, Hohagen F, Voderholzer U. Neuropsychological performance in obsessive-compulsive disorder: a critical review. Biol Psychol. 2004;65:185–236. 10.1016/j.biopsycho.2003.07.007. [ DOI ] [ PubMed ] [ Google Scholar ] 41. Lang K, Lopez C, Stahl D, Tchanturia K, Treasure J. Central coherence in eating disorders: An updated systematic review and meta-analysis. World J Biol Psychiatry. 2014;15:586–98. 10.3109/15622975.2014.909606. [ DOI ] [ PubMed ] [ Google Scholar ] 42. Pellicano E, Maybery M, Durkin K. Central coherence in typically developing preschoolers: does it cohere and does it relate to mindreading and executive control? J Child Psychol Psychiatry. 2005;46:533–47. 10.1111/j.1469-7610.2004.00380.x. [ DOI ] [ PubMed ] [ Google Scholar ] 43. Millan MJ, Marin P, Bockaert J, la Cour CM. Signaling at G-protein-coupled serotonin receptors: recent advances and future research directions. Trends Pharmacol Sci. 2008;29:454–64. 10.1016/j.tips.2008.06.007. [ DOI ] [ PubMed ] [ Google Scholar ] 44. Kolevzon A, Mathewson KA, Hollander E. Selective Serotonin Reuptake Inhibitors in Autism: A Review of Efficacy and Tolerability. J Clin Psychiatry [Internet]. 2006;67:407–14. 10.4088/jcp.v67n0311. [ DOI ] [ PubMed ] [ Google Scholar ] 45. Sari Y. Serotonin1B receptors: from protein to physiological function and behavior. Neurosci Biobehav Rev. 2004;28:565–82. 10.1016/j.neubiorev.2004.08.008. [ DOI ] [ PubMed ] [ Google Scholar ] 46. Svensson JE, Tiger M, Plavén-Sigray P, Halldin C, Schain M, Lundberg J. In vivo correlation of serotonin transporter and 1B receptor availability in the human brain: a PET study. Neuropsychopharmacology. 2022;47:1863–8. 10.1038/s41386-022-01369-3. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 47. Nord M, Finnema SJ, Schain M, Halldin C, Farde L. Test–retest reliability of [11 C]AZ10419369 binding to 5-HT1B receptors in human brain. Eur J Nucl Med Mol Imaging. 2014;41:301–7. 10.1007/s00259-013-2529-1. [ DOI ] [ PubMed ] [ Google Scholar ] 48. Varrone A, Svenningsson P, Forsberg A, Varnäs K, Tiger M, Nakao R, et al. Positron emission tomography imaging of 5-hydroxytryptamine1B receptors in Parkinson’s disease. Neurobiol Aging. 2014;35:867–75. 10.1016/j.neurobiolaging.2013.08.025. [ DOI ] [ PubMed ] [ Google Scholar ] 49. Dziobek I, Fleck S, Kalbe E, Rogers K, Hassenstab J, Brand M, et al. Introducing MASC: A Movie for the Assessment of Social Cognition. J Autism Dev Disord. 2006;36:623–36. 10.1007/s10803-006-0107-0. [ DOI ] [ PubMed ] [ Google Scholar ] 50. Baron-Cohen S, Wheelwright S, Hill J, Raste Y, Plumb I. The Reading the Mind in the Eyes Test revised version: a study with normal adults, and adults with Asperger syndrome or high-functioning autism. J child Psychol psychiatry allied Discipl. 2001;42:241–51. 10.1017/s0021963001006643. [ PubMed ] [ Google Scholar ] 51. Baron-Cohen S, O’Riordan M, Stone V, Jones R, Plaisted K. Recognition of Faux Pas by Normally Developing Children and Children with Asperger Syndrome or High-Functioning Autism. J Autism Dev Disord [Internet]. 1999;29:407–18. 10.1023/a:1023035012436. [ DOI ] [ PubMed ] [ Google Scholar ] 52. Snodgrass JG, Smith B, Feenan K, Corwin J. Fragmenting pictures on the apple macintosh computer for experimental and clinical applications. Behav Res Methods Instrum Comput. 1987;19:270–4. 10.3758/bf03203798. [ Google Scholar ] 53. Witkin AH, Oltman KP, Raskin E et al. A manual for the embedded figures test. Alto P, Press CCP, editors. 1971. 54. Halldin C, Lundberg J, Sóvágó J, Gulyás B, Guilloteau D, Vercouillie J, et al. [11 C]MADAM, a new serotonin transporter radioligand characterized in the monkey brain by PET. Synapse [Internet]. 2005;58:173–83. 10.1002/syn.20189. [ DOI ] [ PubMed ] [ Google Scholar ] 55. Pierson ME, Andersson J, Nyberg S, McCarthy DJ, Finnema SJ, Varnäs K, et al. [11 C]AZ10419369: A selective 5-HT1B receptor radioligand suitable for positron emission tomography (PET). Characterization in the primate brain. NeuroImage. 2008;41:1075–85. 10.1016/j.neuroimage.2008.02.063. [ DOI ] [ PubMed ] [ Google Scholar ] 56. Fischl B, FreeSurfer. NeuroImage. 2012;62:774–81. 10.1016/j.neuroimage.2012.01.021. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 57. Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage. 2006;31:968–80. 10.1016/j.neuroimage.2006.01.021. [ DOI ] [ PubMed ] [ Google Scholar ] 58. Lammertsma AA, Hume SP. Simplified Reference Tissue Model for PET Receptor Studies. NeuroImage. 1996;4:153–8. 10.1006/nimg.1996.0066. [ DOI ] [ PubMed ] [ Google Scholar ] 59. Lundberg J, Odano I, Olsson H, Halldin C, Farde L. Quantification of 11 C-MADAM binding to the serotonin transporter in the human brain. J Nucl Med: Off Publ Soc Nucl Med. 2005;46:1505–15. [ PubMed ] [ Google Scholar ] 60. Varnäs K, Nyberg S, Halldin C, Varrone A, Takano A, Karlsson P, et al. Quantitative Analysis of [11 C]AZ10419369 Binding to 5-HT1B Receptors in Human Brain. J Cereb Blood Flow Metab. 2010;31:113–23. 10.1038/jcbfm.2010.55. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 61. Tiger M, Veldman ER, Ekman C-J, Halldin C, Svenningsson P, Lundberg J. A randomized placebo-controlled PET study of ketamine´s effect on serotonin1B receptor binding in patients with SSRI-resistant depression. Transl Psychiatry. 2020;10:159. 10.1038/s41398-020-0844-4. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 62. Veldman ER, Varrone A, Varnäs K, Svedberg MM, Cselényi Z, Tiger M, et al. Serotonin 1B receptor density mapping of the human brainstem using positron emission tomography and autoradiography. J Cereb Blood Flow Metab. 2021;42:630–41. 10.1177/0271678x211049185. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 63. Varnäs K, Hall H, Bonaventure P, Sedvall G. Autoradiographic mapping of 5-HT1B and 5-HT1D receptors in the post mortem human brain using [3H]GR 125743. Brain Res [Internet]. 2001;915:47–57. 10.1016/s0006-8993(01)02823-2. [ DOI ] [ PubMed ] [ Google Scholar ] 64. Cselényi Z, Olsson H, Halldin C, Gulyás B, Farde L. A comparison of recent parametric neuroreceptor mapping approaches based on measurements with the high affinity PET radioligands [11 C]FLB 457 and [11 C]WAY 100635. NeuroImage. 2006;32:1690–708. 10.1016/j.neuroimage.2006.02.053. [ DOI ] [ PubMed ] [ Google Scholar ] 65. Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc: Ser B (Methodol) [Internet]. 1995;57:289–300. 10.1111/j.2517-6161.1995.tb02031.x. [ Google Scholar ] 66. R CT. R: A Language and Environment for Statistical Computing [Computer Software] [Internet]. 2015. https://www.r-project.org 67. Verhagen J, Wagenmakers E-J. Bayesian Tests to Quantify the Result of a Replication Attempt. J Exp Psychol: Gen [Internet]. 2014;143:1457–75. 10.1037/a0036731. [ DOI ] [ PubMed ] [ Google Scholar ] 68. Wagenmakers E-J, Verhagen J, Ly A. How to quantify the evidence for the absence of a correlation. Behav Res Methods [Internet]. 2016;48:413–26. 10.3758/s13428-015-0593-0. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 69. Ly A, Verhagen J, Wagenmakers E-J. Harold Jeffreys’s default Bayes factor hypothesis tests: Explanation, extension, and application in psychology. J Math Psychol. 2016;72:19–32. 10.1016/j.jmp.2015.06.004. [ Google Scholar ] 70. Etz A, Vandekerckhove J. A Bayesian Perspective on the Reproducibility Project: Psychology. PLoS ONE. 2016;11:e0149794. 10.1371/journal.pone.0149794. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 71. Kemp J, Berthel M-C, Dufour A, Després O, Henry A, Namer IJ, et al. Caudate nucleus and social cognition: Neuropsychological and SPECT evidence from a patient with focal caudate lesion. Cortex. 2013;49:559–71. 10.1016/j.cortex.2012.01.004. [ DOI ] [ PubMed ] [ Google Scholar ] 72. Trompeta C, Gasca-Salas C, Pineda-Pardo JA, Guida P, Cohn M, Mata-Marín D, et al. Longitudinal assessment of social cognition in de novo Parkinson’s disease patients and its relationship with dopaminergic innervation. Behav Brain Res. 2023;454:114654. 10.1016/j.bbr.2023.114654. [ DOI ] [ PubMed ] [ Google Scholar ] 73. Baez S, Pinasco C, Roca M, Ferrari J, Couto B, García-Cordero I, et al. Brain structural correlates of executive and social cognition profiles in behavioral variant frontotemporal dementia and elderly bipolar disorder. Neuropsychologia. 2019;126:159–69. 10.1016/j.neuropsychologia.2017.02.012. [ DOI ] [ PubMed ] [ Google Scholar ] 74. Bodden ME, Kübler D, Knake S, Menzler K, Heverhagen JT, Sommer J, et al. Comparing the neural correlates of affective and cognitive theory of mind using fMRI: Involvement of the basal ganglia in affective theory of mind. Adv Cogn Psychol. 2013;9:32–43. 10.2478/v10053-008-0129-6. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 75. Niederkofler V, Asher TE, Dymecki SM. Functional Interplay between Dopaminergic and Serotonergic Neuronal Systems during Development and Adulthood. ACS Chem Neurosci. 2015;6:1055–70. 10.1021/acschemneuro.5b00021. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 76. Tiger M, Varnäs K, Okubo Y, Lundberg J. The 5-HT1B receptor - a potential target for antidepressant treatment. Psychopharmacology. 2018;235:1317–34. 10.1007/s00213-018-4872-1. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 77. Walsh JJ, Llorach P, Pinto DFC, Wenderski W, Christoffel DJ, Salgado JS, et al. Systemic enhancement of serotonin signaling reverses social deficits in multiple mouse models for ASD. Neuropsychopharmacology. 2021;46:2000–10. 10.1038/s41386-021-01091-6. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Data Availability Statement The datasets generated and/or analysed during the current study are available in the Open Science Framework repository, https://osf.io/z6mbn/?view_only=d4028579be2143d3b077f408f65e78ce . Articles from EJNMMI Research are provided here courtesy of Springer-Verlag ACTIONS View on publisher site PDF (1.5 MB) Cite Collections Permalink PERMALINK Copy RESOURCES Similar articles Cited by other articles Links to NCBI Databases Cite Copy Download .nbib .nbib Format: AMA APA MLA NLM Add to Collections Create a new collection Add to an existing collection Name your collection * Choose a collection Unable to load your collection due to an error Please try again Add Cancel Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top