The special case of self-perspective inhibition in mental, but not non-mental, representation

The ventrolateral prefrontal cortex (vlPFC) has been implicated in studies of both executive and social functions. Recent meta-analyses suggest that vlPFC plays an important but little understood role in Theory of Mind (ToM). Converging neuropsychological and functional Magnetic Resonance Imaging (fMRI) evidence suggests that this may reflect inhibition of self-perspective. The present study adapted an extensively published ToM localizer to evaluate the role of vlPFC in inhibition of self-perspective. The classic false belief, false photograph vignettes that comprise the localizer were modified to generate high and low salience of self-perspective. Using a factorial design, the present study identified a behavioural and neural cost associated with having a highly salient self-perspective that was incongruent with the representational content. Importantly, vlPFC only differentiated between high versus low salience of self-perspective when representing mental state content. No difference was identified for non-mental representation. This result suggests that different control processes are required to represent competing mental and non-mental content.

A penny for your thoughts! Patterns of fMRI activity reveal the content and the spatial topography of visual mental images

Visual mental imagery is a complex process that may be influenced by the content of mental images. Neuropsychological evidence from patients with hemineglect suggests that in the imagery domain environments and objects may be represented separately and may be selectively affected by brain lesions. In the present study, we used functional magnetic resonance imaging (fMRI) to assess the possibility of neural segregation among mental images depicting parts of an object, of an environment (imagined from a first-person perspective), and of a geographical map, using both a mass univariate and a multivariate approach. Data show that different brain areas are involved in different types of mental images. Imagining an environment relies mainly on regions known to be involved in navigational skills, such as the retrosplenial complex and parahippocampal gyrus, whereas imagining a geographical map mainly requires activation of the left angular gyrus, known to be involved in the representation of categorical relations. Imagining a familiar object mainly requires activation of parietal areas involved in visual space analysis in both the imagery and the perceptual domain. We also found that the pattern of activity in most of these areas specifically codes for the spatial arrangement of the parts of the mental image. Our results clearly demonstrate a functional neural segregation for different contents of mental images and suggest that visuospatial information is coded by different patterns of activity in brain areas involved in visual mental imagery. Hum Brain Mapp 36:945-958, 2015.

Cues and knowledge structures used by mental-health professionals when making risk assessments

Background: Research into mental-health risks has tended to focus on epidemiological approaches and to consider pieces of evidence in isolation. Less is known about the particular factors and their patterns of occurrence that influence clinicians’ risk judgements in practice. Aims: To identify the cues used by clinicians to make risk judgements and to explore how these combine within clinicians’ psychological representations of suicide, self-harm, self-neglect, and harm to others. Method: Content analysis was applied to semi-structured interviews conducted with 46 practitioners from various mental-health disciplines, using mind maps to represent the hierarchical relationships of data and concepts. Results: Strong consensus between experts meant their knowledge could be integrated into a single hierarchical structure for each risk. This revealed contrasting emphases between data and concepts underpinning risks, including: reflection and forethought for suicide; motivation for self-harm; situation and context for harm to others; and current presentation for self-neglect. Conclusions: Analysis of experts’ risk-assessment knowledge identified influential cues and their relationships to risks. It can inform development of valid risk-screening decision support systems that combine actuarial evidence with clinical expertise.

Examining the relationship between risk assessment and risk management in mental health

Risk assessment is crucial for developing risk management plans to prevent or minimize mental health patients' risks that will impede their recovery. Risk assessments and risk management plans should be closely linked. Their content and the extent to which they are linked within one Trust is explored. There is a great deal of variability in the amount and detail of risk information collected by nurses and how this is used to develop risk management plans. Keeping risk assessment information in one place rather than scattered throughout patient records is important for ensuring it can be accessed easily and linked properly to risk management plans. Strengthening the link between risk assessment and management will help ensure interventions and care is tailored to the specific needs of individual patients, thus promoting their safety and well-being. Thorough risk assessment helps in developing risk management plans that minimize risks that can impede mental health patients' recovery. Department of Health policy states that risk assessments and risk management plans should be inextricably linked. This paper examines their content and linkage within one Trust. Four inpatient wards for working age adults (18-65 years) in a large mental health Trust in England were included in the study. Completed risk assessment forms, for all patients in each inpatient ward were examined (n= 43), followed by an examination of notes for the same patients. Semi-structured interviews took place with ward nurses (n= 17). Findings show much variability in the amount and detail of risk information collected by nurses, which may be distributed in several places. Gaps in the risk assessment and risk management process are evident, and a disassociation between risk information and risk management plans is often present. Risk information should have a single location so that it can be easily found and updated. Overall, a more integrated approach to risk assessment and management is required, to help patients receive timely and appropriate interventions that can reduce risks such as suicide or harm to others. © 2011 Blackwell Publishing.

Using XML and XSLT for flexible elicitation of mental-health risk knowledge

Current tools for assessing risks associated with mental-health problems require assessors to make high-level judgements based on clinical experience. This paper describes how new technologies can enhance qualitative research methods to identify lower-level cues underlying these judgements, which can be collected by people without a specialist mental-health background. Content analysis of interviews with 46 multidisciplinary mental-health experts exposed the cues and their interrelationships, which were represented by a mind map using software that stores maps as XML. All 46 mind maps were integrated into a single XML knowledge structure and analysed by a Lisp program to generate quantitative information about the numbers of experts associated with each part of it. The knowledge was refined by the experts, using software developed in Flash to record their collective views within the XML itself. These views specified how the XML should be transformed by XSLT, a technology for rendering XML, which resulted in a validated hierarchical knowledge structure associating patient cues with risks. Changing knowledge elicitation requirements were accommodated by flexible transformations of XML data using XSLT, which also facilitated generation of multiple data-gathering tools suiting different assessment circumstances and levels of mental-health knowledge. © 2007 Informa UK Ltd All rights reserved.

Discovering knowledge structures in mind maps of mental health risks

This thesis addressed the problem of risk analysis in mental healthcare, with respect to the GRiST project at Aston University. That project provides a risk-screening tool based on the knowledge of 46 experts, captured as mind maps that describe relationships between risks and patterns of behavioural cues. Mind mapping, though, fails to impose control over content, and is not considered to formally represent knowledge. In contrast, this thesis treated GRiSTs mind maps as a rich knowledge base in need of refinement; that process drew on existing techniques for designing databases and knowledge bases. Identifying well-defined mind map concepts, though, was hindered by spelling mistakes, and by ambiguity and lack of coverage in the tools used for researching words. A novel use of the Edit Distance overcame those problems, by assessing similarities between mind map texts, and between spelling mistakes and suggested corrections. That algorithm further identified stems, the shortest text string found in related word-forms. As opposed to existing approaches’ reliance on built-in linguistic knowledge, this thesis devised a novel, more flexible text-based technique. An additional tool, Correspondence Analysis, found patterns in word usage that allowed machines to determine likely intended meanings for ambiguous words. Correspondence Analysis further produced clusters of related concepts, which in turn drove the automatic generation of novel mind maps. Such maps underpinned adjuncts to the mind mapping software used by GRiST; one such new facility generated novel mind maps, to reflect the collected expert knowledge on any specified concept. Mind maps from GRiST are stored as XML, which suggested storing them in an XML database. In fact, the entire approach here is ”XML-centric”, in that all stages rely on XML as far as possible. A XML-based query language allows user to retrieve information from the mind map knowledge base. The approach, it was concluded, will prove valuable to mind mapping in general, and to detecting patterns in any type of digital information.