Inverse problems in dynamic cognitive modeling

Inverse problems for dynamical system models of cognitive processes comprise the determination of synaptic weight matrices or kernel functions for neural networks or neural/dynamic field models, respectively. We introduce dynamic cognitive modeling as a three tier top-down approach where cognitive processes are first described as algorithms that operate on complex symbolic data structures. Second, symbolic expressions and operations are represented by states and transformations in abstract vector spaces. Third, prescribed trajectories through representation space are implemented in neurodynamical systems. We discuss the Amari equation for a neural/dynamic field theory as a special case and show that the kernel construction problem is particularly ill-posed. We suggest a Tikhonov-Hebbian learning method as regularization technique and demonstrate its validity and robustness for basic examples of cognitive computations.

What does a transdiagnostic approach have to offer the treatment of anxiety disorders?

Purpose: The purpose of this paper is to review the rationale for 'transdiagnostic' approaches to the understanding and treatment of anxiety disorders. Methods: Databases searches and examination of the reference lists of relevant studies were used to identify papers of relevance. Results: There is increasing recognition that diagnosis-specific interventions for single anxiety-disorders are of less value than might appear since a large proportion of patients have more than one co-existing anxiety disorder and the treatment of one anxiety disorder does not necessarily lead to the resolution of others. As transdiagnostic approaches have the potential to address multiple co-existing anxiety disorders they are potentially more clinically relevant than single anxiety disorder interventions. They may also have advantages in ease of dissemination and in treating anxiety disorder not otherwise specified. Conclusions: The merits of the various transdiagnostic cognitive-behavioral approaches that have been proposed are reviewed. Such approaches have potential benefits, particularly in striking the balance between completely idiosyncratic formulations and diagnosis-driven treatments of anxiety disorders. However, caution is needed to ensure that transdiagnostic theories and treatments benefit from progress made by research on diagnosis-specific treatments, and further empirical work is needed to identify the shared maintaining processes that need to be targeted in the treatment of anxiety disorders.

The effects of maternal postnatal depression and child sex on academic performance at age 16 years: a developmental approach

Background: Postnatal depression (PND) is associated with poor cognitive functioning in infancy and the early school years; long-term effects on academic outcome are not known. Method: Children of postnatally depressed (N = 50) and non-depressed mothers (N = 39), studied from infancy, were followed up at 16 years. We examined the effects on General Certificate of Secondary Education (GCSE) exam performance of maternal depression (postnatal and subsequent) and IQ, child sex and earlier cognitive development, and mother–child interactions, using structural equation modelling (SEM). Results: Boys, but not girls, of PND mothers had poorer GCSE results than control children. This was principally accounted for by effects on early child cognitive functioning, which showed strong continuity from infancy. PND had continuing negative effects on maternal interactions through childhood, and these also contributed to poorer GCSE performance. Neither chronic, nor recent, exposure to maternal depression had significant effects. Conclusions: The adverse effects of PND on male infants’ cognitive functioning may persist through development. Continuing difficulties in mother–child interactions are also important, suggesting that both early intervention and continuing monitoring of mothers with PND may be warranted.

Cognitive tests used in chronic adult human randomised controlled trial micronutrient and phytochemical intervention studies

In recent years there has been a rapid growth of interest in exploring the relationship between nutritional therapies and the maintenance of cognitive function in adulthood. Emerging evidence reveals an increasingly complex picture with respect to the benefits of various food constituents on learning, memory and psychomotor function in adults. However, to date, there has been little consensus in human studies on the range of cognitive domains to be tested or the particular tests to be employed. To illustrate the potential difficulties that this poses, we conducted a systematic review of existing human adult randomised controlled trial (RCT) studies that have investigated the effects of 24 d to 36 months of supplementation with flavonoids and micronutrients on cognitive performance. There were thirty-nine studies employing a total of 121 different cognitive tasks that met the criteria for inclusion. Results showed that less than half of these studies reported positive effects of treatment, with some important cognitive domains either under-represented or not explored at all. Although there was some evidence of sensitivity to nutritional supplementation in a number of domains (for example, executive function, spatial working memory), interpretation is currently difficult given the prevailing 'scattergun approach' for selecting cognitive tests. Specifically, the practice means that it is often difficult to distinguish between a boundary condition for a particular nutrient and a lack of task sensitivity. We argue that for significant future progress to be made, researchers need to pay much closer attention to existing human RCT and animal data, as well as to more basic issues surrounding task sensitivity, statistical power and type I error.

Cognitive behaviour therapy for low self-esteem: A preliminary randomized controlled trial in a primary care setting

Background and Objectives Low self-esteem (LSE) is associated with psychiatric disorder, and is distressing and debilitating in its own right. Hence, it is frequent target for treatment in cognitive behavioural interventions, yet it has rarely been the primary focus for intervention. This paper reports on a preliminary randomized controlled trial of cognitive behaviour therapy (CBT) for LSE using Fennell’s (1997) cognitive conceptualisation and transdiagnostic treatment approach ( [Fennell, 1997] and [Fennell, 1999]). Methods Twenty-two participants were randomly allocated to either immediate treatment (IT) (n = 11) or to a waitlist condition (WL) (n = 11). Treatment consisted of 10 sessions of individual CBT accompanied by workbooks. Participants allocated to the WL condition received the CBT intervention once the waitlist period was completed and all participants were followed up 11 weeks after completing CBT. Results The IT group showed significantly better functioning than the WL group on measures of LSE, overall functioning and depression and had fewer psychiatric diagnoses at the end of treatment. The WL group showed the same pattern of response to CBT as the group who had received CBT immediately. All treatment gains were maintained at follow-up assessment. Limitations The sample size is small and consists mainly of women with a high level of educational attainment and the follow-up period was relatively short. Conclusions These preliminary findings suggest that a focused, brief CBT intervention can be effective in treating LSE and associated symptoms and diagnoses in a clinically representative group of individuals with a range of different and co-morbid disorders.

Predicting outcomes following cognitive behavior therapy in child anxiety disorders: the influence of genetic, demographic and clinical information

Background. Within a therapeutic gene by environment (GxE) framework, we recently demonstrated that variation in the Serotonin Transporter Promoter Polymorphism; 5HTTLPR and marker rs6330 in Nerve Growth Factor gene; NGF is associated with poorer outcomes following cognitive behaviour therapy (CBT) for child anxiety disorders. The aim of this study was to explore one potential means of extending the translational reach of G×E data in a way that may be clinically informative. We describe a ‘risk-index’ approach combining genetic, demographic and clinical data and test its ability to predict diagnostic outcome following CBT in anxious children. Method. DNA and clinical data were collected from 384 children with a primary anxiety disorder undergoing CBT. We tested our risk model in five cross-validation training sets. Results. In predicting treatment outcome, six variables had a minimum mean beta value of 0.5: 5HTTLPR, NGF rs6330, gender, primary anxiety severity, comorbid mood disorder and comorbid externalising disorder. A risk index (range 0-8) constructed from these variables had moderate predictive ability (AUC = .62-.69) in this study. Children scoring high on this index (5-8) were approximately three times as likely to retain their primary anxiety disorder at follow-up as compared to those children scoring 2 or less. Conclusion. Significant genetic, demographic and clinical predictors of outcome following CBT for anxiety-disordered children were identified. Combining these predictors within a risk-index could be used to identify which children are less likely to be diagnosis free following CBT alone or thus require longer or enhanced treatment. The ‘risk-index’ approach represents one means of harnessing the translational potential of G×E data.

Cognitive and environmental factors influencing the process of spatial knowledge acquisition within virtual reality environments

As the fidelity of virtual environments (VE) continues to increase, the possibility of using them as training platforms is becoming increasingly realistic for a variety of application domains, including military and emergency personnel training. In the past, there was much debate on whether the acquisition and subsequent transfer of spatial knowledge from VEs to the real world is possible, or whether the differences in medium during training would essentially be an obstacle to truly learning geometric space. In this paper, the authors present various cognitive and environmental factors that not only contribute to this process, but also interact with each other to a certain degree, leading to a variable exposure time requirement in order for the process of spatial knowledge acquisition (SKA) to occur. The cognitive factors that the authors discuss include a variety of individual user differences such as: knowledge and experience; cognitive gender differences; aptitude and spatial orientation skill; and finally, cognitive styles. Environmental factors discussed include: Size, Spatial layout complexity and landmark distribution. It may seem obvious that since every individual's brain is unique - not only through experience, but also through genetic predisposition that a one size fits all approach to training would be illogical. Furthermore, considering that various cognitive differences may further emerge when a certain stimulus is present (e.g. complex environmental space), it would make even more sense to understand how these factors can impact spatial memory, and to try to adapt the training session by providing visual/auditory cues as well as by changing the exposure time requirements for each individual. The impact of this research domain is important to VE training in general, however within service and military domains, guaranteeing appropriate spatial training is critical in order to ensure that disorientation does not occur in a life or death scenario.

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging due to reinforcing feedbacks between multiple drivers. We conducted semi-structured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision-making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. All scenarios showed increased wildfire risk in the event of more droughts. The ‘Hands-off’ scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production. The ‘Fire management’ scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared to the ‘Fire suppression’ scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decision-support tool and serve as a ‘boundary object’ to facilitate collaboration and integration of different forms of knowledge and perceptions of fire in the region. This approach has also the potential to support decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.

A BDI-based approach for the assessment of driver's decision-making in commuter scenarios

The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.

Graph analysis of verbal fluency test discriminate between patients with Alzheimer’s disease, Mild Cognitive Impairment and normal elderly controls

Verbal fluency is the ability to produce a satisfying sequence of spoken words during a given time interval. The core of verbal fluency lies in the capacity to manage the executive aspects of language. The standard scores of the semantic verbal fluency test are broadly used in the neuropsychological assessment of the elderly, and different analytical methods are likely to extract even more information from the data generated in this test. Graph theory, a mathematical approach to analyze relations between items, represents a promising tool to understand a variety of neuropsychological states. This study reports a graph analysis of data generated by the semantic verbal fluency test by cognitively healthy elderly (NC), patients with Mild Cognitive Impairment – subtypes amnestic(aMCI) and amnestic multiple domain (a+mdMCI) - and patients with Alzheimer’s disease (AD). Sequences of words were represented as a speech graph in which every word corresponded to a node and temporal links between words were represented by directed edges. To characterize the structure of the data we calculated 13 speech graph attributes (SGAs). The individuals were compared when divided in three (NC – MCI – AD) and four (NC – aMCI – a+mdMCI – AD) groups. When the three groups were compared, significant differences were found in the standard measure of correct words produced, and three SGA: diameter, average shortest path, and network density. SGA sorted the elderly groups with good specificity and sensitivity. When the four groups were compared, the groups differed significantly in network density, except between the two MCI subtypes and NC and aMCI. The diameter of the network and the average shortest path were significantly different between the NC and AD, and between aMCI and AD. SGA sorted the elderly in their groups with good specificity and sensitivity, performing better than the standard score of the task. These findings provide support for a new methodological frame to assess the strength of semantic memory through the verbal fluency task, with potential to amplify the predictive power of this test. Graph analysis is likely to become clinically relevant in neurology and psychiatry, and may be particularly useful for the differential diagnosis of the elderly.

Pré-fabricados lingüísticos: estrutura e funcionamento de sintagmas verbais idiomatizados - por uma abordagem cognitivo-funcional em sala de aula

This work aims at under the cognitive-functional perspective describing, inside the vast domain of the linguistic prefabs, the structure and the functioning of the Idiomatic Verb Phrases (SVIs), produced by speakers of the Portuguese from Brazil, located in Natal (RN). From the functionalist presupposition that the language is used essentially to assist to communicative demands, it is observed that its morphologic-syntactic structure is conditioned to the inherent pragmatic vicissitudes to the verbal interaction of subjects, socially heterogeneous and historically established. It is focalized, in the composition of SVIs, the relationships VT + OD (transitive verb + direct object), characterizing the syntactic-semantic nature of the verb and of the respective verbal complement. Those verb combinations + complement can be interpreted as lexical structures, reflexes of the idiomaticity inherent to conventional constructions already systematized in the users' of the language cultural repertoire. It is sought, still, to glimpse the cognitive and discursive motivations pertinent to that linguistic phenomenon. In the investigative process, are analyzed exclusive data of speech collected in Corpus Discurso & Gramática a lingua falada e escrita na cidade do Natal, organized by Furtado da Cunha (1998). The adopted methodological procedures configure as methods of empiric analysis and use of the intuition, being emphasized the qualitative approach (explanatory) of the data with quantitative support of statistical indicators. It shows, finally, a grating of didactic suggestions on SVIs, for Portuguese's classes, as subsidies to the educational practice in the Medium Teaching and in the course of Letters.

What the cognitive neurosciences mean to me

Cognitive Neuroscience is an interdisciplinary area of research that combines measurement of brain activity (mostly by means of neuroimaging) with a simultaneous performance of cognitive tasks by human subjects. These investigations have been successful in the task of connecting the sciences of the brain (Neurosciences) and the sciences of the mind (Cognitive Sciences). Advances on this kind of research provide a map of localization of cognitive functions in the human brain. Do these results help us to understand how mind relates to the brain? In my view, the results obtained by the Cognitive Neurosciences lead to new investigations in the domain of Molecular Neurobiology, aimed at discovering biophysical mechanisms that generate the activity measured by neuroimaging instruments. In this context, I argue that the understanding of how ionic/molecular processes support cognition and consciousness cannot be made by means of the standard reductionist explanations. Knowledge of ionic/molecular meclianisms can contribute to our understanding of the human mind as long as we assume an alternative form of explanation, based on psycho-physical similarities, together with an ontological view of mentality and spirituality as embedded in physical nature (and not outside nature, as frequently assumed in western culture).

Conceptual spaces and consciousness: Integrating cognitive and affective processes

In the book Conceptual Spaces: the Geometry of Thought [2000] Peter Gärdenfors proposes a new framework for cognitive science. Complementary to symbolic and subsymbolic [connectionist] descriptions, conceptual spaces are semantic structures constructed from empirical data representing the universe of mental states. We argue that Gärdenfors' modeling can be used in consciousness research to describe the phenomenal conscious world, its elements and their intrinsic relations. The conceptual space approach affords the construction of a universal state space of human consciousness, where all possible kinds of human conscious states could be mapped. Starting from this approach, we discuss the inclusion of feelings and emotions in conceptual spaces, and their relation to perceptual and cognitive states. Current debate on integration of affect/emotion and perception/cognition allows three possible descriptive alternatives: emotion resulting from basic cognition; cognition resulting from basic emotion, and both as relatively independent functions integrated by brain mechanisms. Finding a solution for this issue is an important step in any attempt of successful modeling of natural or artificial consciousness. After making a brief review of proposals in this area, we summarize the essentials of a new model of consciousness based on neuro-astroglial interactions. © 2011 World Scientific Publishing Company.

Mild cognitive impairment (part 1): Clinical characteristics and predictors of dementia

Objective: To critically review and evaluate existing knowledge on the conceptual limits and clinical usefulness of the diagnosis of mild cognitive impairment (MCI) and the neuropsychological assessment and short- and long-term prognosis thereof. Methods: We conducted a systematic search of the PubMed and Web of Science electronic databases, limited to articles published in English between 1999 and 2012. Based on the search terms mild cognitive impairment or MCI and epidemiology or diagnosis, we retrieved 1,698 articles, of which 248 were critically eligible (cross-sectional and longitudinal studies); the abstracts of the remaining 1,450 articles were also reviewed. Results: A critical review on the MCI construct is provided, including conceptual and diagnostic aspects; epidemiological relevance; clinical assessment; prognosis; and outcome. The distinct definitions of cognitive impairment, MCI included, yield clinically heterogeneous groups of individuals. Those who will eventually progress to dementia may present with symptoms consistent with the definition of MCI; conversely, individuals with MCI may remain stable or return to normal cognitive function. Conclusion: On clinical grounds, the cross-sectional diagnosis of MCI has limited prognostic relevance. The characterization of persistent and/or progressive cognitive deficits over time is a better approach for identification of cases at the pre-dementia stages, particularly if these cognitive abnormalities are consistent with the natural history of incipient Alzheimer's disease. © 2013 Associação Brasileira de Psiquiatria.