Corrigendum: The effect of antipsychotics on glutamate levels in the anterior cingulate cortex and clinical response: a 1H-MRS study in first-episode psychosis patients.

[This corrects the article DOI: 10.3389/fpsyt.2022.967941.].

Histamine-3 Receptor Availability and Glutamate Levels in the Brain: A PET-1H-MRS Study of Patients With Schizophrenia and Healthy Controls.

BACKGROUND: The histamine-3 receptor (H3R) may have a role in cognitive processes through its action as a presynaptic heteroreceptor inhibiting the release of glutamate in the brain. To explore this, we examined anterior cingulate cortex (ACC) and striatum H3R availability in patients with schizophrenia and characterized their relationships with glutamate levels in corresponding brain regions. METHODS: We employed a cross-sectional study, recruiting 12 patients with schizophrenia and 12 healthy volunteers. Participants underwent positron emission tomography using the H3R-specific radio ligand [11C]MK-8278, followed by proton magnetic resonance spectroscopy to measure glutamate levels, recorded as Glu and Glx. Based on existing literature, the ACC and striatum were selected as regions of interest. RESULTS: We found significant inverse relationships between tracer uptake and Glu (r = -0.66, P = .02) and Glx (r = -0.62, P = .04) levels in the ACC of patients, which were absent in healthy volunteers (Glu: r = -0.19, P = .56, Glx: r = 0.10, P = .75). We also found a significant difference in striatal (F1,20 = 6.00, P = .02) and ACC (F1,19 = 4.75, P = .04) Glx levels between groups. CONCLUSIONS: These results provide evidence of a regionally specific relationship between H3Rs and glutamate levels, which builds on existing preclinical literature. Our findings add to a growing literature indicating H3Rs may be a promising treatment target in schizophrenia, particularly for cognitive impairment, which has been associated with altered glutamate signaling.

Development of the Japanese version of the Ego-Dissolution Inventory (EDI).

AIM: Psychedelics have recently gained attention as potential therapeutic agents for various psychiatric disorders. Previous research has highlighted that a diminished sense of self, commonly termed "ego-dissolution" is a pivotal feature of the psychedelic-induced state. While the Ego-Dissolution Inventory (EDI) is a widely acknowledged instrument for measuring this phenomenon, no Japanese version has been available. This study aimed to develop a Japanese version of the EDI. METHODS: We adhered to the "Guidelines for Best Practices in the Translation and Cultural Modification Process for Patient-Reported Outcomes Instruments: Document from the ISPOR Committee on Translation and Cultural Modification" during our translation approach. Two Japanese psychiatrists independently conducted initial translations, and a consolidated version was achieved via mutual agreement. This version was then back-translated to English and assessed by the original authors for consistency. The repetitive modification process was conducted in continuous dialogues with the original authors until they accepted the concluding back-translated version. RESULTS: The finalized, approved back-translated version of the EDI is presented in the accompanying figure. In addition, the authorized Japanese version of the EDI is included in the Appendix. CONCLUSIONS: In this study, we successfully developed the Japanese version of the EDI. This instrument will assist in assessing ego-dissolution experiences associated with psychedelic-assisted therapy among Japanese speakers. Additional studies are necessary to evaluate the reliability and validity of this newly translated instrument.

Trajectories through semantic spaces in schizophrenia and the relationship to ripple bursts.

Human cognition is underpinned by structured internal representations that encode relationships between entities in the world (cognitive maps). Clinical features of schizophrenia-from thought disorder to delusions-are proposed to reflect disorganization in such conceptual representations. Schizophrenia is also linked to abnormalities in neural processes that support cognitive map representations, including hippocampal replay and high-frequency ripple oscillations. Here, we report a computational assay of semantically guided conceptual sampling and exploit this to test a hypothesis that people with schizophrenia (PScz) exhibit abnormalities in semantically guided cognition that relate to hippocampal replay and ripples. Fifty-two participants [26 PScz (13 unmedicated) and 26 age-, gender-, and intelligence quotient (IQ)-matched nonclinical controls] completed a category- and letter-verbal fluency task, followed by a magnetoencephalography (MEG) scan involving a separate sequence-learning task. We used a pretrained word embedding model of semantic similarity, coupled to a computational model of word selection, to quantify the degree to which each participant's verbal behavior was guided by semantic similarity. Using MEG, we indexed neural replay and ripple power in a post-task rest session. Across all participants, word selection was strongly influenced by semantic similarity. The strength of this influence showed sensitivity to task demands (category > letter fluency) and predicted performance. In line with our hypothesis, the influence of semantic similarity on behavior was reduced in schizophrenia relative to controls, predicted negative psychotic symptoms, and correlated with an MEG signature of hippocampal ripple power (but not replay). The findings bridge a gap between phenomenological and neurocomputational accounts of schizophrenia.

Reward processing in schizophrenia and its relation to Mu opioid receptor availability and negative symptoms: A [11C]-carfentanil PET and fMRI study.

BACKGROUND: Reward processing deficits are a core feature of schizophrenia and are thought to underlie negative symptoms. Pre-clinical evidence suggests that opioid neurotransmission is linked to reward processing. However, the contribution of Mu Opioid Receptor (MOR) signalling to the reward processing abnormalities in schizophrenia is unknown. Here, we examined the association between MOR availability and the neural processes underlying reward anticipation in patients with schizophrenia using multimodal neuroimaging. METHOD: 37 subjects (18 with Schizophrenia with moderate severity negative symptoms and 19 age and sex-matched healthy controls) underwent a functional MRI scan while performing the Monetary Incentive Delay (MID) task to measure the neural response to reward anticipation. Participants also had a [11C]-carfentanil PET scan to measure MOR availability. RESULTS: Reward anticipation was associated with increased neural activation in a widespread network of brain regions including the striatum. Patients with schizophrenia had both significantly lower MOR availability in the striatum as well as striatal hypoactivation during reward anticipation. However, there was no association between MOR availability and striatal neural activity during reward anticipation in either patient or controls (Pearson's Correlation, controls df = 17, r = 0.321, p = 0.18, patients df = 16, r = 0.295, p = 0.24). There was no association between anticipation-related neural activation and negative symptoms (r = -0.120, p = 0.14) or anhedonia severity (social r = -0.365, p = 0.14 physical r = -0.120, p = 0.63). CONCLUSIONS: Our data suggest reduced MOR availability in schizophrenia might not underlie striatal hypoactivation during reward anticipation in patients with established illness. Therefore, other mechanisms, such as dopamine dysfunction, warrant further investigation as treatment targets for this aspect of the disorder.

The histamine system and cognitive function: An in vivo H3 receptor PET imaging study in healthy volunteers and patients with schizophrenia.

BACKGROUND: The histamine-3 receptor (H3R) is an auto- and heteroreceptor that inhibits the release of histamine and other neurotransmitters. Post-mortem evidence has found altered H3R expression in patients with psychotic disorders, which may underlie cognitive impairment associated with schizophrenia (CIAS). AIMS: We used positron emission tomography (PET) imaging to compare brain uptake of an H3R selective tracer between patients with schizophrenia and matched controls (healthy individuals). Regions of interest included the dorsolateral prefrontal cortex (DLPFC) and striatum. We explored correlations between tracer uptake and symptoms, including cognitive domains. METHODS: A total of 12 patients and 12 matched controls were recruited to the study and were assessed with psychiatric and cognitive rating scales. They received a PET scan using the H3R-specific radioligand [11C]MK-8278 to determine H3R availability. RESULTS: There was no statistically significant difference in tracer uptake between patients and controls in the DLPFC (t19 = 0.79, p = 0.44) or striatum (t21 = 1.18, p = 0.25). An exploratory analysis found evidence for lower volume of distribution in the left cuneus (pFWE-corrected = 0.01). DLPFC tracer uptake was strongly correlated with cognition in controls (trail making test (TMT) A: r = 0.77, p = 0.006; TMT B: rho = 0.74, p = 0.01), but not in patients (TMT A: r = -0.18, p = 0.62; TMT B: rho = -0.06, p = 0.81). CONCLUSIONS: These findings indicate H3R in the DLPFC might play a role in executive function and this is disrupted in schizophrenia in the absence of major alterations in H3R availability as assessed using a selective radiotracer for H3R. This provides further evidence for the role of H3R in CIAS.

Theory-Driven Analysis of Natural Language Processing Measures of Thought Disorder Using Generative Language Modeling.

BACKGROUND: Natural language processing (NLP) holds promise to transform psychiatric research and practice. A pertinent example is the success of NLP in the automatic detection of speech disorganization in formal thought disorder (FTD). However, we lack an understanding of precisely what common NLP metrics measure and how they relate to theoretical accounts of FTD. We propose tackling these questions by using deep generative language models to simulate FTD-like narratives by perturbing computational parameters instantiating theory-based mechanisms of FTD. METHODS: We simulated FTD-like narratives using Generative-Pretrained-Transformer-2 by either increasing word selection stochasticity or limiting the model's memory span. We then examined the sensitivity of common NLP measures of derailment (semantic distance between consecutive words or sentences) and tangentiality (how quickly meaning drifts away from the topic) in detecting and dissociating the 2 underlying impairments. RESULTS: Both parameters led to narratives characterized by greater semantic distance between consecutive sentences. Conversely, semantic distance between words was increased by increasing stochasticity, but decreased by limiting memory span. An NLP measure of tangentiality was uniquely predicted by limited memory span. The effects of limited memory span were nonmonotonic in that forgetting the global context resulted in sentences that were semantically closer to their local, intermediate context. Finally, different methods for encoding the meaning of sentences varied dramatically in performance. CONCLUSIONS: This work validates a simulation-based approach as a valuable tool for hypothesis generation and mechanistic analysis of NLP markers in psychiatry. To facilitate dissemination of this approach, we accompany the paper with a hands-on Python tutorial.

Reduced coupling between offline neural replay events and default mode network activation in schizophrenia.

Schizophrenia is characterized by an abnormal resting state and default mode network brain activity. However, despite intense study, the mechanisms linking default mode network dynamics to neural computation remain elusive. During rest, sequential hippocampal reactivations, known as 'replay', are played out within default mode network activation windows, highlighting a potential role of replay-default mode network coupling in memory consolidation and model-based mental simulation. Here, we test a hypothesis of reduced replay-default mode network coupling in schizophrenia, using magnetoencephalography and a non-spatial sequence learning task designed to elicit off-task (i.e. resting state) neural replay. Participants with a diagnosis of schizophrenia (n = 28, mean age 28.2 years, range 20-40, 6 females, 13 not taking antipsychotic medication) and non-clinical control participants (n = 29, mean age 28.1 years, range 18-45, 6 females, matched at group level for age, intelligence quotient, gender, years in education and working memory) underwent a magnetoencephalography scan both during task completion and during a post-task resting state session. We used neural decoding to infer the time course of default mode network activation (time-delay embedding hidden Markov model) and spontaneous neural replay (temporally delayed linear modelling) in resting state magnetoencephalography data. Using multiple regression, we then quantified the extent to which default mode network activation was uniquely predicted by replay events that recapitulated the learned task sequences (i.e. 'task-relevant' replay-default mode network coupling). In control participants, replay-default mode network coupling was augmented following sequence learning, an augmentation that was specific for replay of task-relevant (i.e. learned) state transitions. This task-relevant replay-default mode network coupling effect was significantly reduced in schizophrenia (t(52) = 3.93, P = 0.018). Task-relevant replay-default mode network coupling predicted memory maintenance of learned sequences (ρ(52) = 0.31, P = 0.02). Importantly, reduced task-relevant replay-default mode network coupling in schizophrenia was not explained by differential replay or altered default mode network dynamics between groups nor by reference to antipsychotic exposure. Finally, task-relevant replay-default mode network coupling during rest correlated with stimulus-evoked default mode network modulation as measured in a separate task session. In the context of a proposed functional role of replay-default mode network coupling, our findings shed light on the functional significance of default mode network abnormalities in schizophrenia and provide for a consilience between task-based and resting state default mode network findings in this disorder.

Effect of polygenic risk for schizophrenia on cardiac structure and function: a UK Biobank observational study.

BACKGROUND: Cardiovascular disease is a major cause of excess mortality in people with schizophrenia. Several factors are responsible, including lifestyle and metabolic effects of antipsychotics. However, variations in cardiac structure and function are seen in people with schizophrenia in the absence of cardiovascular disease risk factors and after accounting for lifestyle and medication. Therefore, we aimed to explore whether shared genetic causes contribute to these cardiac variations. METHODS: For this observational study, we used data from the UK Biobank and included White British or Irish individuals without diagnosed schizophrenia with variable polygenic risk scores for the condition. To test the association between polygenic risk score for schizophrenia and cardiac phenotype, we used principal component analysis and regression. Robust regression was then used to explore the association between the polygenic risk score for schizophrenia and individual cardiac phenotypes. We repeated analyses with fibro-inflammatory pathway-specific polygenic risk scores for schizophrenia. Last, we investigated genome-wide sharing of common variants between schizophrenia and cardiac phenotypes using linkage disequilibrium score regression. The primary outcome was principal component regression. FINDINGS: Of 33 353 individuals recruited, 32 279 participants had complete cardiac MRI data and were included in the analysis, of whom 16 625 (51·5%) were female and 15 654 (48·5%) were male. 1074 participants were excluded on the basis of incomplete cardiac MRI data (for all phenotypes). A model regressing polygenic risk scores for schizophrenia onto the first five cardiac principal components of the principal components analysis was significant (F=5·09; p=0·00012). Principal component 1 captured a pattern of increased cardiac volumes, increased absolute peak diastolic strain rates, and reduced ejection fractions; polygenic risk scores for schizophrenia and principal component 1 were negatively associated (ß=-0·01 [SE 0·003]; p=0·017). Similar to the principal component analysis results, for individual cardiac phenotypes, we observed negative associations between polygenic risk scores for schizophrenia and indexed right ventricular end-systolic volume (ß=-0·14 [0·04]; p=0·0013, pFDR=0·015), indexed right ventricular end-diastolic volume (ß=-0·17 [0·08]); p=0·025; pFDR=0·082), and absolute longitudinal peak diastolic strain rates (ß=-0·01 [0·003]; p=0·0024, pFDR=0·015), and a positive association between polygenic risk scores for schizophrenia and right ventricular ejection fraction (ß=0·09 [0·03]; p=0·0041, pFDR=0·015). Models examining the transforming growth factor-ß (TGF-ß)-specific and acute inflammation-specific polygenic risk scores for schizophrenia found significant associations with the first five principal components (F=2·62, p=0·022; F=2·54, p=0·026). Using linkage disequilibrium score regression, we observed genetic overlap with schizophrenia for right ventricular end-systolic volume and right ventricular ejection fraction (p=0·0090, p=0·0077). INTERPRETATION: High polygenic risk scores for schizophrenia are associated with decreased cardiac volumes, increased ejection fractions, and decreased absolute peak diastolic strain rates. TGF-ß and inflammatory pathways might be implicated, and there is evidence of genetic overlap for some cardiac phenotypes. Reduced absolute peak diastolic strain rates indicate increased myocardial stiffness and diastolic dysfunction, which increases risk of cardiac disease. Thus, genetic risk for schizophrenia is associated with cardiac structural changes that can worsen cardiac outcomes. Further work is required to determine whether these associations are specific to schizophrenia or are also seen in other psychiatric conditions. FUNDING: National Institute for Health Research, Maudsley Charity, Wellcome Trust, Medical Research Council, Academy of Medical Sciences, Edmond J Safra Foundation, British Heart Foundation.

The effects of AUT00206, a novel Kv3.1/3.2 potassium channel modulator, on task-based reward system activation: a test of mechanism in schizophrenia.

The pathophysiology of schizophrenia involves abnormal reward processing, thought to be due to disrupted striatal and dopaminergic function. Consistent with this hypothesis, functional magnetic resonance imaging (fMRI) studies using the monetary incentive delay (MID) task report hypoactivation in the striatum during reward anticipation in schizophrenia. Dopamine neuron activity is modulated by striatal GABAergic interneurons. GABAergic interneuron firing rates, in turn, are related to conductances in voltage-gated potassium 3.1 (Kv3.1) and 3.2 (Kv3.2) channels, suggesting that targeting Kv3.1/3.2 could augment striatal function during reward processing. Here, we studied the effect of a novel potassium Kv3.1/3.2 channel modulator, AUT00206, on striatal activation in patients with schizophrenia, using the MID task. Each participant completed the MID during fMRI scanning on two occasions: once at baseline, and again following either 4 weeks of AUT00206 or placebo treatment. We found a significant inverse relationship at baseline between symptom severity and reward anticipation-related neural activation in the right associative striatum (r = -0.461, p = 0.035). Following treatment with AUT00206, there was a significant increase in reward anticipation-related activation in the left associative striatum (t(13) = 4.23, peak-level p(FWE) < 0.05)), but no significant effect in the ventral striatum. This provides preliminary evidence that the Kv3.1/3.2 potassium channel modulator, AUT00206, may address reward-related striatal abnormalities in schizophrenia.

Relationship Between Replay-Associated Ripples and Hippocampal N-Methyl-D-Aspartate Receptors: Preliminary Evidence From a PET-MEG Study in Schizophrenia.

Background and Hypotheses: Hippocampal replay and associated high-frequency ripple oscillations are among the best-characterized phenomena in resting brain activity. Replay/ripples support memory consolidation and relational inference, and are regulated by N-methyl-D-aspartate receptors (NMDARs). Schizophrenia has been associated with both replay/ripple abnormalities and NMDAR hypofunction in both clinical samples and genetic mouse models, although the relationship between these 2 facets of hippocampal function has not been tested in humans. Study Design: Here, we avail of a unique multimodal human neuroimaging data set to investigate the relationship between the availability of (intrachannel) NMDAR binding sites in hippocampus, and replay-associated ripple power, in 16 participants (7 nonclinical participants and 9 people with a diagnosis of schizophrenia, PScz). Each participant had both a [18F]GE-179 positron emission tomography (PET) scan (to measure NMDAR availability, V T ) and a magnetoencephalography (MEG) scan (to measure offline neural replay and associated high-frequency ripple oscillations, using Temporally Delayed Linear Modeling). Study Results: We show a positive relationship between hippocampal NMDAR availability and replay-associated ripple power. This linkage was evident across control participants (r(5) = .94, P = .002) and PScz (r(7) = .70, P = .04), with no group difference. Conclusions: Our findings provide preliminary evidence for a relationship between hippocampal NMDAR availability and replay-associated ripple power in humans, and haverelevance for NMDAR hypofunction theories of schizophrenia.

The Watts Connectedness Scale: a new scale for measuring a sense of connectedness to self, others, and world.

RATIONALE: A general feeling of disconnection has been associated with mental and emotional suffering. Improvements to a sense of connectedness to self, others and the wider world have been reported by participants in clinical trials of psychedelic therapy. Such accounts have led us to a definition of the psychological construct of 'connectedness' as 'a state of feeling connected to self, others and the wider world'. Existing tools for measuring connectedness have focused on particular aspects of connectedness, such as 'social connectedness' or 'nature connectedness', which we hypothesise to be different expressions of a common factor of connectedness. Here, we sought to develop a new scale to measure connectedness as a construct with these multiple domains. We hypothesised that (1) our scale would measure three separable subscale factors pertaining to a felt connection to 'self', 'others' and 'world' and (2) improvements in total and subscale WCS scores would correlate with improved mental health outcomes post psychedelic use. OBJECTIVES: To validate and test the 'Watts Connectedness Scale' (WCS). METHODS: Psychometric validation of the WCS was carried out using data from three independent studies. Firstly, we pooled data from two prospective observational online survey studies. The WCS was completed before and after a planned psychedelic experience. The total sample of completers from the online surveys was N = 1226. Exploratory and confirmatory factor analysis were performed, and construct and criterion validity were tested. A third dataset was derived from a double-blind randomised controlled trial (RCT) comparing psilocybin-assisted therapy (n = 27) with 6 weeks of daily escitalopram (n = 25) for major depressive disorder (MDD), where the WCS was completed at baseline and at a 6-week primary endpoint. RESULTS: As hypothesised, factor analysis of all WCS items revealed three main factors with good internal consistency. WCS showed good construct validity. Significant post-psychedelic increases were observed for total connectedness scores (η2 = 0.339, p < 0.0001), as well as on each of its subscales (p < 0.0001). Acute measures of 'mystical experience', 'emotional breakthrough', and 'communitas' correlated positively with post-psychedelic changes in connectedness (r = 0.42, r = 0.38, r = 0.42, respectively, p < 0.0001). In the RCT, psilocybin therapy was associated with greater increases in WCS scores compared with the escitalopram arm (ηp2 = 0.133, p = 0.009). CONCLUSIONS: The WCS is a new 3-dimensional index of felt connectedness that may sensitively measure therapeutically relevant psychological changes post-psychedelic use. We believe that the operational definition of connectedness captured by the WCS may have broad relevance in mental health research.

Functional neuroimaging in psychiatry and the case for failing better.

Psychiatric disorders encompass complex aberrations of cognition and affect and are among the most debilitating and poorly understood of any medical condition. Current treatments rely primarily on interventions that target brain function (drugs) or learning processes (psychotherapy). A mechanistic understanding of how these interventions mediate their therapeutic effects remains elusive. From the early 1990s, non-invasive functional neuroimaging, coupled with parallel developments in the cognitive neurosciences, seemed to signal a new era of neurobiologically grounded diagnosis and treatment in psychiatry. Yet, despite three decades of intense neuroimaging research, we still lack a neurobiological account for any psychiatric condition. Likewise, functional neuroimaging plays no role in clinical decision making. Here, we offer a critical commentary on this impasse and suggest how the field might fare better and deliver impactful neurobiological insights.

The effect of antipsychotics on glutamate levels in the anterior cingulate cortex and clinical response: A 1H-MRS study in first-episode psychosis patients.

Introduction: Glutamatergic dysfunction is implicated in the pathophysiology of schizophrenia. It is unclear whether glutamatergic dysfunction predicts response to treatment or if antipsychotic treatment influences glutamate levels. We investigated the effect of antipsychotic treatment on glutamatergic levels in the anterior cingulate cortex (ACC), and whether there is a relationship between baseline glutamatergic levels and clinical response after antipsychotic treatment in people with first episode psychosis (FEP). Materials and methods: The sample comprised 25 FEP patients; 22 completed magnetic resonance spectroscopy scans at both timepoints. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). Results: There was no significant change in glutamate [baseline 13.23 ± 2.33; follow-up 13.89 ± 1.74; t(21) = -1.158, p = 0.260], or Glx levels [baseline 19.64 ± 3.26; follow-up 19.66 ± 2.65; t(21) = -0.034, p = 0.973]. There was no significant association between glutamate or Glx levels at baseline and the change in PANSS positive (Glu r = 0.061, p = 0.777, Glx r = -0.152, p = 0.477), negative (Glu r = 0.144, p = 0.502, Glx r = 0.052, p = 0.811), general (Glu r = 0.110, p = 0.607, Glx r = -0.212, p = 0.320), or total scores (Glu r = 0.078, p = 0.719 Glx r = -0.155, p = 0.470). Conclusion: These findings indicate that treatment response is unlikely to be associated with baseline glutamatergic metabolites prior to antipsychotic treatment, and there is no major effect of antipsychotic treatment on glutamatergic metabolites in the ACC.

The relationship between glutamate, dopamine, and cortical gray matter: A simultaneous PET-MR study.

Prefrontal cortex has been shown to regulate striatal dopaminergic function via glutamatergic mechanisms in preclinical studies. Concurrent disruption of these systems is also often seen in neuropsychiatric disease. The simultaneous measurement of striatal dopamine signaling, cortical gray matter, and glutamate levels is therefore of major interest, but has not been previously reported. In the current study, twenty-eight healthy subjects underwent 2 simultaneous [11C]-( + )-PHNO PET-MRI scans, once after placebo and once after amphetamine in a double-blind randomized cross-over design, to measure striatal dopamine release, striatal dopamine receptor (D2/3R) availability, anterior cingulate glutamate+glutamine (Glx) levels, and cortical gray matter volumes at the same time. Voxel-based morphometry was used to investigate associations between neurochemical measures and gray matter volumes. Whole striatum D2/3R availability was positively associated with prefrontal cortex gray matter volume (pFWE corrected = 0.048). This relationship was mainly driven by associative receptor availability (pFWE corrected = 0.023). In addition, an interaction effect was observed between sensorimotor striatum D2/3R availability and anterior cingulate Glx, such that in individuals with greater anterior cingulate Glx concentrations, D2/3R availability was negatively associated with right frontal cortex gray matter volumes, while a positive D2/3R-gray matter association was observed in individuals with lower anterior cingulate Glx levels (pFWE corrected = 0.047). These results are consistent with the hypothesis that the prefrontal cortex is involved in regulation of striatal dopamine function. Furthermore, the observed associations raise the possibility that this regulation may be modulated by anterior cingulate glutamate concentrations.

Decoding cognition from spontaneous neural activity.

In human neuroscience, studies of cognition are rarely grounded in non-task-evoked, 'spontaneous' neural activity. Indeed, studies of spontaneous activity tend to focus predominantly on intrinsic neural patterns (for example, resting-state networks). Taking a 'representation-rich' approach bridges the gap between cognition and resting-state communities: this approach relies on decoding task-related representations from spontaneous neural activity, allowing quantification of the representational content and rich dynamics of such activity. For example, if we know the neural representation of an episodic memory, we can decode its subsequent replay during rest. We argue that such an approach advances cognitive research beyond a focus on immediate task demand and provides insight into the functional relevance of the intrinsic neural pattern (for example, the default mode network). This in turn enables a greater integration between human and animal neuroscience, facilitating experimental testing of theoretical accounts of intrinsic activity, and opening new avenues of research in psychiatry.

Assessing the impact of different penalty factors of the Bayesian reconstruction algorithm Q.Clear on in vivo low count kinetic analysis of [11C]PHNO brain PET-MR studies.

INTRODUCTION: Q.Clear is a Bayesian penalised likelihood (BPL) reconstruction algorithm available on General Electric (GE) Positron Emission Tomography (PET)-Computed Tomography (CT) and PET-Magnetic Resonance (MR) scanners. This algorithm is regulated by a ß value which acts as a noise penalisation factor and yields improvements in signal to noise ratio (SNR) in clinical scans, and in contrast recovery and spatial resolution in phantom studies. However, its performance in human brain imaging studies remains to be evaluated in depth. This pilot study aims to investigate the impact of Q.Clear reconstruction methods using different ß value versus ordered subset expectation maximization (OSEM) on brain kinetic modelling analysis of low count brain images acquired in the PET-MR. METHODS: Six [11C]PHNO PET-MR brain datasets were reconstructed with Q.Clear with ß100-1000 (in increments of 100) and OSEM. The binding potential relative to non-displaceable volume (BPND) were obtained for the Substantia Nigra (SN), Striatum (St), Globus Pallidus (GP), Thalamus (Th), Caudate (Cd) and Putamen (Pt), using the MIAKAT™ software. Intraclass correlation coefficients (ICC), repeatability coefficients (RC), coefficients of variation (CV) and bias from Bland-Altman plots were reported. Statistical analysis was conducted using a 2-way ANOVA model with correction for multiple comparisons. RESULTS: When comparing a standard OSEM reconstruction of 6 iterations/16 subsets and 5 mm filter with Q.Clear with different ß values under low counts, the bias and RC were lower for Q.Clear with ß100 for the SN (RC = 2.17), Th (RC = 0.08) and GP (RC = 0.22) and with ß200 for the St (RC = 0.14), Cd (RC = 0.18)and Pt (RC = 0.10). The p-values in the 2-way ANOVA model corroborate these findings. ICC values obtained for Th, St, GP, Pt and Cd demonstrate good reliability (0.87, 0.99, 0.96, 0.99 and 0.96, respectively). For the SN, ICC values demonstrate poor reliability (0.43). CONCLUSION: BPND results obtained from quantitative low count brain PET studies using [11C]PHNO and reconstructed with Q.Clear with ß < 400, which is the value used for clinical [18F]FDG whole-body studies, demonstrate the lowest bias versus the typical iterative reconstruction method OSEM.