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To explore the phenomenology of auditory verbal hallucinations (AVHs) in a clinical sample of young people who have a ‘non-psychotic’ diagnosis.
Ten participants aged 17–31 years with presentation of emotionally unstable personality disorder or post-traumatic stress disorder and frequent AVHs were recruited and participated in a qualitative study exploring their subjective experience of hearing voices. Photo-elicitation and ethnographic diaries were used to stimulate discussion in an otherwise unstructured walking interview.
‘Non-psychotic’ voices comprised auditory qualities such as volume and clarity. Participants commonly personified their voices, viewing them as distinct characters with which they could interact and form relationships. There appeared to be an intimate and unstable relationship between participant and voice, whereby voices changed according to the participants’ mood, insecurities, distress and circumstance. Equally, participants reacted to provocation by the voice, leading to changes in mood and circumstance through emotional and physical disturbances. In contrast to our previous qualitative work in psychosis, voice hearing was not experienced with a sense of imposition or control.
This phenomenological research yielded in-depth and novel accounts of ‘non-psychotic’ voices which were intimately linked to emotional experience. In contrast to standard reports of voices in disorders such as schizophrenia, participants described a complex and bi-directional relationship with their voices. Many other features were in common with voice hearing in psychosis. Knowledge of the phenomenology of hallucinations in non-psychotic disorders has the potential to inform future more successful management strategies. This report gives preliminary evidence for future research.
Object working memory performance is abnormal in the early stages of schizophrenia. Such tasks recruit frontal and temporal cortices, possible sites of progressive change over the early illness course. We wanted to clarify if functional changes can be detected in the early stages of schizophrenia, to identify their anatomical location and their relationship to the stage of illness using a functional object working memory task in which the length of memory delay was manipulated.
40 subjects contributed: 10 first episode psychosis (FEp) patients, 16 with an at risk mental state (ARMS) and 14 healthy controls. We collected functional MRI data while the subjects performed a version of the delayed matching to sample (DMTS) task from the Cambridge Automated Neuropsychological Test Battery (CANTAB).
Behaviourally there was a trend to a group by delay interaction, the two patient groups making more errors at longer memory delays. At successful recognition a main effect of group was detected in the medial temporal lobe bilaterally, while a main effect of delay was detected in the left medial temporal lobe. At each length of memory delay the patient groups showed consistently greater activation of medial temporal regions when performing the task accurately.
Both ARMS & FEp groups showed greater activation than controls in the medial temporal cortex across all lengths of memory delay. These differences were not related to poorer task performance, but suggest an inefficiency mechanism that may correlate with the vulnerability to psychosis rather than pychosis per se.
People with ‘prodromal’ symptoms have a very high risk of developing psychosis. We used functional MRI to examine the neurocognitive basis of this vulnerability.
Cross-sectional comparison of subjects with an ARMS (n=17), first episode schizophreniform psychosis (n=10) and healthy volunteers (n=15). Subjects were studied using functional MRI while they performed an overt verbal fluency task, a random movement generation paradigm and an N-Back working memory task.
During an N-Back task the ARMS group engaged inferior frontal and posterior parietal cortex less than controls but more than the first episode group. During a motor generation task, the ARMS group showed less activation in the left inferior parietal cortex than controls, but greater activation than the first episode group. During verbal fluency using ‘Easy’ letters, the ARMS group demonstrated intermediate activation in the left inferior frontal cortex, with first episode groups showing least, and controls most, activation. When processing ‘Hard’ letters, differential activation was evident in two left inferior frontal regions. In its dorsolateral portion, the ARMS group showed less activation than controls but more than the first episode group, while in the opercular part of the left inferior frontal gyrus / anterior insula activation was greatest in the first episode group, weakest in controls and intermediate in the ARMS group.
The ARMS is associated with abnormalities of regional brain function that are qualitatively similar to those in patients who have just developed psychosis but less severe.
There is increasing evidence that changes in connections linking brain regions, as well as grey matter volumetric abnormalities are important in schizophrenia. The extent to which these are related to being at risk of psychosis as opposed to having a psychotic disorder is unclear. We will review the diffusion tensor imaging (DTI) findings which inform us about white matter integrity and organization, and relate it to our own work which compares grey matter volumes and white matter integrity in people at high risk of psychosis, patients with first episode psychosis, and healthy volunteers. We will also discuss the relationship of these findings to clinical symptoms and outcome.
30 subjects with an ‘at risk mental state’ (PACE criteria), 15 first psychotic episode patients and 30 controls were studied using an SPGR sequence and DTI.
Both the volumetric and DTI datasets were analysed using voxel based techniques in standard space. There were frontal and temporal grey matter reductions in the first episode group and more modest temporo-parietal volume reductions in the ‘at risk’ group. The first episode group had reduced fractional anisotropy in the superior longitudinal fasciculus bilaterally, left anterior corpus callosal and right superior fronto-occiptal tracts relative to controls, with qualitatively similar but less severe reductions in the ‘at risk’ subjects.
Abnormalities in the frontal and temporal grey matter and the tracts connecting them were evident in patients with first episode schizophrenia, with similar but less marked abnormalities in subjects with an ‘at risk’ mental state.
Impaired working memory is a core feature of schizophrenia and is linked with altered engagement the lateral prefrontal cortex. Although altered PFC activation has been reported in people with increased risk of psychosis, at present it is not clear if this neurofunctional alteration differs between familial and clinical risk states and/or increases in line with the level of psychosis risk. We addressed this issue by using functional MRI and a working memory paradigm to study familial and clinical high-risk groups. We recruited 17 subjects at ultra-high-risk (UHR) for psychosis, 10 non-affected siblings of patients with schizophrenia (familial high risk [FHR]) and 15 healthy controls. Subjects were scanned while performing the N-back working memory task. There was a relationship between the level of task-related deactivation in the medial PFC and precuneus and the level of psychosis risk, with deactivation weakest in the UHR group, greatest in healthy controls, and at an intermediate level in the FHR group. In the high-risk groups, activation in the precuneus was associated with the level of negative symptoms. These data suggest that increased vulnerability to psychosis is associated with a failure to deactivate in the medial PFC and precuneus during a working memory task, and appears to be most evident in subjects at clinical, as opposed to familial high risk.
Evidence suggests that the subjective experience of AVHs cannot be explained by any of the existing cognitive models, highlighting the obvious need to properly investigate the actual, lived experience of AVHs, and derive models/theories that fit the complexity of this.
Via phenomenological interviews and ethnographic diary methods, we aim to gain a deeper insight into the experience of AVHs.
To explore the phenomenological quality of AVHs, as they happen/reveal themselves to consciousness,   without relying on existing suppositions.
Participants with First Episode Psychosis were recruited from the Birmingham Early Intervention Service (EIS), BSMHFT. In-depth 'walking interviews' were carried out with each participant, together with standardised assessment measures of voices. Prior to interviews, participants were asked to complete a dairy and take photographs, further capturing aspects of their AVH experiences.
20 participants have completed interviews to date. Emerging themes cover the form and quality of voices (i.e. as being separate to self, imposing, compelling etc.), and participants' understanding and management of these experiences.
Authentic descriptions gleaned from participants have the potential to increase our understanding of the relationship between the phenomenology and neurobiology of AVHs and, in turn, the experience as a whole.
Whilst cannabis use appears to be a causal risk factor for the development of schizophrenia-related psychosis, associations with mania remain relatively unknown.
This review aimed to examine the impact of cannabis use on the incidence of manic symptoms and on their occurrence in those with pre-existing bipolar disorder
A systematic review of the scientific literature using the PRISMA guidelines. PsychINFO, Cochrane, Scopus, Embase and MEDLINE databases were searched for prospective studies.
Six articles met inclusion criteria. These sampled 2,391 individuals who had experienced mania symptoms. The mean length of follow up was 3.9 years. Studies support an association between cannabis use and the exacerbation of manic symptoms in those with previously diagnosed bipolar disorder. Furthermore, a meta-analysis of two studies suggests that cannabis use is associated with an approximately 3-fold (Odds Ratio: 2.97; 95% CI: 1.80 to 4.90) increased risk for the new onset of manic symptoms.
Our findings whilst tentative, suggest that cannabis use may worsen the occurrence of manic symptoms in those diagnosed with bipolar disorder and may also act as a causal risk factor in the incidence of manic symptoms. This underscores the importance of discouraging cannabis use among youth and those with bipolar disorder to help prevent chronic psychiatric morbidity. More high quality prospective studies are required to fully elucidate how cannabis use may contribute to the development of mania over time.
We used British national survey data to test specific hypotheses that mood instability 1) is associated with psychosis and individual psychotic phenomena, 2) predicts the later emergence of auditory hallucinations and paranoid ideation, and 3) mediates the link between child sexual abuse and psychosis.
We analysed data from the 2000 and 2007 UK national surveys of psychiatric morbidity (N=8580 and 7403 respectively). The 2000 survey included an 18-month follow-up of a subsample (N=2406). Mood instability was assessed from the Structured Clinical Interview for DSMIV Axis II (SCID-II) questionnaire. Our dependent variables comprised auditory hallucinations, paranoid ideation, the presence of psychosis overall, and a 15-item paranoia scale
Mood Instability was strongly associated in cross-sectional analyses with psychosis (2000 OR: 7.5; 95% CI: I 4.1–13.8; 2007: OR 21.4; CI 9.7–41.2), paranoid ideation (2000: OR: 4.7; CI 4.1–5.4; 2007: OR 5.7; CI 4.9–6.7), auditory hallucinations (2000: OR: 3.4; CI 2.6–4.4; 2007: OR 3.5; CI 2.7–4.7) and paranoia total score (2000: Coefficient: 3.6;CI 3.3–3.9), remaining so after adjustment for current mood state. Baseline mood instability significantly predicted 18-month inceptions of paranoid ideation (OR: 2.3;CI 1.6–3.3) and of auditory hallucinations (OR: 2.6;CI 1.5–4.4). Finally it mediated a third of the total association of child sexual abuse with psychosis and persecutory ideation, and a quarter of that with auditory hallucinations.
Mood instability is a prominent feature of psychotic experience, and may have a role in its genesis. Targeting mood instability could lead to innovative treatments for psychosis.
Psychosis and adult Attention Deficit Hyperactivity Disorder (ADHD) have shared attributes, but evidence that they are associated is sparse and inconsistent.
We tested hypotheses that 1] adult ADHD symptoms are associated with psychosis and individual psychotic symptoms 2] links between ADHD symptoms and psychosis are mediated by prescribed ADHD medications, use of illicit drugs, and dysphoric mood (depression and anxiety).
The Adult Psychiatric Morbidity Survey 2007 (N=7403) provided data for regression and multiple mediation analyses. ADHD symptoms were coded from the ADHD Self-Report Scale (ASRS). Dependent variables comprised auditory hallucinations, paranoid ideation, and identified psychosis.
Higher ASRS total score was significantly associated with psychosis (O.R: 1.11; 95% CI 1.02-1.20; p = 0.013), paranoid ideation (O.R:1.12; CI 1.09-1.14; p<0.001) and auditory hallucinations (O.R 1.11; CI 1.08-1.15; p<0.001) even after controlling for socio-demographic variables, verbal IQ, autism spectrum disorder traits, childhood conduct problems, hypomanic mood and dysphoric mood. The link between higher ADHD symptoms and psychosis variables was significantly mediated by dysphoric mood (psychosis, 21%; paranoid ideation, 23%; auditory hallucination, 11%), but not by prescribed ADHD medication or use of amphetamine, cocaine or cannabis.
Higher levels of adult ADHD symptoms and psychosis are linked, and dysphoric mood may form part of the mechanism. Those with greater levels of ADHD symptoms in adulthood may be at higher risk of psychosis. Our analyses contradict the clinical view that the main explanation for people with ADHD symptoms developing psychosis is abuse of illicit drugs or ADHD medications.
Neurobiological models of auditory verbal hallucination (AVH) have been advanced by symptom capture functional magnetic resonance imaging (fMRI), where participants self-report hallucinations during scanning. To date, regions implicated are those involved with language, memory and emotion. However, previous studies focus on chronic schizophrenia, thus are limited by factors, such as medication use and illness duration. Studies also lack detailed phenomenological descriptions of AVHs. This study investigated the neural correlates of AVHs in patients with first episode psychosis (FEP) using symptom capture fMRI with a rich description of AVHs. We hypothesised that intrusive AVHs would be associated with dysfunctional salience network activity.
Sixteen FEP patients with frequent AVH completed four psychometrically validated tools to provide an objective measure of the nature of their AVHs. They then underwent fMRI symptom capture, utilising general linear models analysis to compare activity during AVH to the resting brain.
Symptom capture of AVH was achieved in nine patients who reported intrusive, malevolent and uncontrollable AVHs. Significant activity in the right insula and superior temporal gyrus (cluster size 141 mm3), and the left parahippocampal and lingual gyri (cluster size 121 mm3), P < 0.05 FDR corrected, were recorded during the experience of AVHs.
These results suggest salience network dysfunction (in the right insula) together with memory and language processing area activation in intrusive, malevolent AVHs in FEP. This finding concurs with others from chronic schizophrenia, suggesting these processes are intrinsic to psychosis itself and not related to length of illness or prolonged exposure to antipsychotic medication.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
Childhood abuse is a risk factor for poorer illness course in bipolar disorder, but the reasons why are unclear. Trait-like features such as affective instability and impulsivity could be part of the explanation. We aimed to examine whether childhood abuse was associated with clinical features of bipolar disorder, and whether associations were mediated by affective instability or impulsivity.
We analysed data from 923 people with bipolar I disorder recruited by the Bipolar Disorder Research Network. Adjusted associations between childhood abuse, affective instability and impulsivity and eight clinical variables were analysed. A path analysis examined the direct and indirect links between childhood abuse and clinical features with affective instability and impulsivity as mediators.
Affective instability significantly mediated the association between childhood abuse and earlier age of onset [effect estimate (θ)/standard error (SE): 2.49], number of depressive (θ/SE: 2.08) and manic episodes/illness year (θ/SE: 1.32), anxiety disorders (θ/SE: 1.98) and rapid cycling (θ/SE: 2.25). Impulsivity significantly mediated the association between childhood abuse and manic episodes/illness year (θ/SE: 1.79), anxiety disorders (θ/SE: 1.59), rapid cycling (θ/SE: 1.809), suicidal behaviour (θ/SE: 2.12) and substance misuse (θ/SE: 3.09). Measures of path analysis fit indicated an excellent fit to the data.
Affective instability and impulsivity are likely part of the mechanism of why childhood abuse increases risk of poorer clinical course in bipolar disorder, with each showing some selectivity in pathways. They are potential novel targets for intervention to improve outcome in bipolar disorder.
Mood instability is common, and an important feature of several psychiatric
disorders. We discuss the definition and measurement of mood instability,
and review its prevalence, characteristics, neurobiological correlates and
clinical implications. We suggest that mood instability has underappreciated
transdiagnostic potential as an investigational and therapeutic target.
The majority of people at ultra high risk (UHR) of psychosis also present with co-morbid affective disorders such as depression or anxiety. The neuroanatomical and clinical impact of UHR co-morbidity is unknown.
We investigated group differences in grey matter volume using baseline magnetic resonance images from 121 participants in four groups: UHR with depressive or anxiety co-morbidity; UHR alone; major depressive disorder; and healthy controls. The impact of grey matter volume on baseline and longitudinal clinical/functional data was assessed with regression analyses.
The UHR-co-morbidity group had lower grey matter volume in the anterior cingulate cortex than the UHR-alone group, with an intermediate effect between controls and patients with major depressive disorder. In the UHR-co-morbidity group, baseline anterior cingulate volume was negatively correlated with baseline suicidality/self-harm and obsessive–compulsive disorder symptoms.
Co-morbid depression and anxiety disorders contributed distinctive grey matter volume reductions of the anterior cingulate cortex in people at UHR of psychosis. These volumetric deficits were correlated with baseline measures of depression and anxiety, suggesting that co-morbid depressive and anxiety diagnoses should be carefully considered in future clinical and imaging studies of the psychosis high-risk state.
We introduce a game theoretical model of stealing interactions. We model the situation as
an extensive form game when one individual may attempt to steal a valuable item from
another who may in turn defend it. The population is not homogeneous, but rather each
individual has a different Resource Holding Potential (RHP). We assume that RHP not only
influences the outcome of the potential aggressive contest (the individual with the larger
RHP is more likely to win), but that it also influences how an individual values a
particular resource. We investigate several valuation scenarios and study the prevalence
of aggressive behaviour. We conclude that the relationship between RHP and resource value
is crucial, where some cases lead to fights predominantly between pairs of strong
individuals, and some between pairs of weak individuals. Other cases lead to no fights
with one individual conceding, and the order of strategy selection is crucial, where the
individual which picks its strategy first often has an advantage.
The majority of species are under predatory risk in their natural habitat and targeted by
predators as part of the food web. During the evolution of ecosystems, manifold mechanisms
have emerged to avoid predation. So called secondary defences, which are used after a
predator has initiated prey-catching behaviour, commonly involve the expression of toxins
or deterrent substances which are not observable by the predator. Hence, the possession of
such secondary defence in many prey species comes with a specific signal of that defence
(aposematism). This paper builds on the ideas of existing models of such signalling
behaviour, using a model of co-evolution and generalisation of aversive information and
introduces a new methodology of numerical analysis for finite populations. This new
methodology significantly improves the accessibility of previous models.
In finite populations, investigating the co-evolution of defence and signalling requires
an understanding of natural selection as well as an assessment of the effects of drift as
an additional force acting on stability. The new methodology is able to reproduce the
predicted solutions of preceding models and finds additional solutions involving negative
correlation between signal strength and the extent of secondary defence. In addition,
genetic drift extends the range of stable aposematic solutions through the introduction of
a new pseudo-stability and gives new insights into the diversification of aposematic
Affective instability (AI) is poorly defined but considered clinically important. The aim of this study was to examine definitions and measures of AI employed in clinical populations.
This study was a systematic review using the PRISMA guidelines. MEDLINE, Embase, PsycINFO, PsycArticles and Web of Science databases were searched. Also five journals were hand searched. Primary empirical studies involving randomized controlled trials (RCTs), non-RCTs, controlled before and after, and observational investigations were included. Studies were selected, data extracted and quality appraised. A narrative synthesis was completed.
A total of 11 443 abstracts were screened and 37 studies selected for final analysis on the basis that they provided a definition and measure of AI. Numbers of definitions for each of the terms employed in included studies were: AI (n = 7), affective lability (n = 6), affective dysregulation (n = 1), emotional dysregulation (n = 4), emotion regulation (n = 2), emotional lability (n = 1), mood instability (n = 2), mood lability (n = 1) and mood swings (n = 1); however, these concepts showed considerable overlap in features. A total of 24 distinct measures were identified that could be categorized as primarily measuring one of four facets of AI (oscillation, intensity, ability to regulate and affect change triggered by environment) or as measuring general emotional regulation.
A clearer definition of AI is required. We propose AI be defined as ‘rapid oscillations of intense affect, with a difficulty in regulating these oscillations or their behavioural consequences’. No single measure comprehensively assesses AI and a combination of current measures is required for assessment. A new short measure of AI that is reliable and validated against external criteria is needed.
Previous work has shown that hunger and food intake are lower in individuals on high-protein (HP) diets when combined with low carbohydrate (LC) intakes rather than with moderate carbohydrate (MC) intakes and where a more ketogenic state occurs. The aim of the present study was to investigate whether the difference between HPLC and HPMC diets was associated with changes in glucose and ketone body metabolism, particularly within key areas of the brain involved in appetite control. A total of twelve men, mean BMI 34·9 kg/m2, took part in a randomised cross-over trial, with two 4-week periods when isoenergetic fixed-intake diets (8·3 MJ/d) were given, with 30 % of the energy being given as protein and either (1) a very LC (22 g/d; HPLC) or (2) a MC (182 g/d; HPMC) intake. An 18fluoro-deoxyglucose positron emission tomography scan of the brain was conducted at the end of each dietary intervention period, following an overnight fast (n 4) or 4 h after consumption of a test meal (n 8). On the next day, whole-body ketone and glucose metabolism was quantified using [1,2,3,4-13C]acetoacetate, [2,4-13C]3-hydroxybutyrate and [6,6-2H2]glucose. The composite hunger score was 14 % lower (P= 0·013) for the HPLC dietary intervention than for the HPMC diet. Whole-body ketone flux was approximately 4-fold greater for the HPLC dietary intervention than for the HPMC diet (P< 0·001). The 9-fold difference in carbohydrate intakes between the HPLC and HPMC dietary interventions led to a 5 % lower supply of glucose to the brain. Despite this, the uptake of glucose by the fifty-four regions of the brain analysed remained similar for the two dietary interventions. In conclusion, differences in the composite hunger score observed for the two dietary interventions are not associated with the use of alternative fuels by the brain.
The Cancer Genome Atlas (TCGA) is an ambitious undertaking of the National Institutes of Health (NIH), jointly led by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), to identify all key genomic changes in the major types and subtypes of cancer. In the following section, we briefly review the history and goals of the TCGA project. Section 2.3 describes how samples are collected and analyzed by the TCGA. Section 2.4 details how data are processed, stored, and made available to qualified researchers. Section 2.5 briefly surveys several widely available tools that can be used to analyze TCGA data. Section 2.6 summarizes the chapter.
History and Goals of the TCGA Project
At the turn of the century, it was clear (Balmain et al., 2003) that genomic alterations played a key role in cancer development and progression and that understanding these changes would be enormously important for devising improved methods for diagnosing clinically relevant cancer subtypes and for developing novel molecular therapies aimed at a specific cancer subtype. Several successful treatments for targeting cancer cells with specific genomic changes had been developed – for instance, Gleevec for chronic myeloid leukemia and Herceptin for breast cancer. Early experiments to determine the genomic basis of specific cancers had made it clear that the scope of the genomic changes concerned was enormously complex: an individual cancer could involve hundreds or thousands of genomic alterations, and these changes were for the most part specific to the cancer concerned.
Cancers are fundamentally caused by genomic changes in the cancer cells that lead to their uncontrolled growth (Balmain et al., 2003; Stratton et al., 2009). Understanding these changes, which include DNA copy number alterations, is an intense focus of current research into the causes of, and potential therapies for, every type of cancer. Major research projects, such as the Cancer Genome Atlas (TCGA) project (The Cancer Genome Atlas Research Network, 2008), aim to comprehensively catalog all genomic changes in cancer. This chapter discusses the problem of interpreting copy number data, specifically in the context of cancer research.
To measure copy number, whole-genome genotyping array assays hybridize sample DNA to oligonucleotides deposited on the array. Modern designs use synthetic oligonucleotides to measure copy number at frequent intervals along the genome, especially in regions of known copy number variation. Modern arrays also include many probes that target both alleles of a large number of common single-nucleotide polymorphisms (SNPs). These platforms are therefore widely used in genotyping studies. Array-based assays available for measuring genome-wide copy number include arrays from Illumina, Sentrix, Agilent, and Affymetrix. Data from next-generation sequencing of DNA can also be used to detect copy number alterations and is rapidly becoming cost competitive with array-based platforms.
Molecular inversion probe (MIP) arrays (Wang et al., 2007, 2009; Ji and Welch, 2009) are another platform that can be used for large-scale copy number analysis and genotyping. MIP technology uses less DNA, can handle lower quality DNA, has a greater dynamic range, has higher quality markers, and better separates allelic information than other array-based approaches.