Holistic processing of hierarchical structures in connectionist networks

Despite the success of connectionist systems to model some aspects of cognition, critics argue that the lack of symbol processing makes them inadequate for modelling high-level cognitive tasks which require the representation and processing of hierarchical structures. In this thesis we investigate four mechanisms for encoding hierarchical structures in distributed representations that are suitable for processing in connectionist systems: Tensor Product Representation, Recursive Auto-Associative Memory (RAAM), Holographic Reduced Representation (HRR), and Binary Spatter Code (BSC). In these four schemes representations of hierarchical structures are either learned in a connectionist network or constructed by means of various mathematical operations from binary or real-value vectors.It is argued that the resulting representations carry structural information without being themselves syntactically structured. The structural information about a represented object is encoded in the position of its representation in a high-dimensional representational space. We use Principal Component Analysis and constructivist networks to show that well-separated clusters consisting of representations for structurally similar hierarchical objects are formed in the representational spaces of RAAMs and HRRs. The spatial structure of HRRs and RAAM representations supports the holistic yet structure-sensitive processing of them. Holistic operations on RAAM representations can be learned by backpropagation networks. However, holistic operators over HRRs, Tensor Products, and BSCs have to be constructed by hand, which is not a desirable situation. We propose two new algorithms for learning holistic transformations of HRRs from examples. These algorithms are able to generalise the acquired knowledge to hierarchical objects of higher complexity than the training examples. Such generalisations exhibit systematicity of a degree which, to our best knowledge, has not yet been achieved by any other comparable learning method.Finally, we outline how a number of holistic transformations can be learned in parallel and applied to representations of structurally different objects. The ability to distinguish and perform a number of different structure-sensitive operations is one step towards a connectionist architecture that is capable of modelling complex high-level cognitive tasks such as natural language processing and logical inference

The significance of work allocation in the professional apprenticeship of solicitors

It is a peculiarity of the solicitors’ profession that it has historically relied on methods of pre-qualification ‘training’ by way of apprenticeship and that an entirely respectable non-graduate route into the profession remains. In a political context, however, where the profession is called upon positively to demonstrate its standards of performance, the professional regulator seeks to attach a competence framework to the existing model; shifting the focus from how the trainee learns to what the trainee learns. This paper will explore the period of traineeship from the perspective of the trainees themselves, drawing on two small qualitative studies, focussing on the fundamental context factor of the allocation and structuring of their work. In the first study the context for this evaluation is the set of outcomes being tested by the professional regulator and in the second, the perceptions of qualified individuals looking back at their apprenticeship, The paper concludes that there remains work for the profession to do not only in fostering supportive and expansive apprenticeships, but in attending, however, supportive the surrounding environment, to the work being carried out by trainees and its relationship with the work carried out by newly qualified solicitors

Combined Imaging Markers Dissociate Alzheimer's Disease and Frontotemporal Lobar Degeneration – An ALE Meta-Analysis

To compare and dissociate the neural correlates of Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD), we combine and synthesize here recent comprehensive meta-analyses. Systematic and quantitative meta-analyses were conducted according to the QUOROM statement by calculating anatomical likelihood estimates (ALE). AD (n = 578) and the three subtypes of FTLD, frontotemporal dementia, semantic dementia (SD), and progressive non-fluent aphasia (n = 229), were compared in conjunction analyses, separately for atrophy and reductions in glucose metabolism. Atrophy coincided in the amygdala and hippocampal head in AD and the FTLD subtype SD. The other brain regions did not show any overlap between AD and FTLD subtypes for both atrophy and changes in glucose metabolism. For AD alone (n = 826), another conjunction analysis revealed a regional dissociation between atrophy and hypoperfusion/hypometabolism, whereby hypoperfusion and hypometabolism coincided in the angular/supramarginal gyrus and inferior precuneus/posterior cingulate gyrus. Our data together with other imaging studies suggest a specific dissociation of AD and FTLD if, beside atrophy, additional imaging markers in AD such as abnormally low parietal glucose utilization and perfusion are taken into account. Results support the incorporation of standardized imaging inclusion criteria into future diagnostic systems, which is crucial for early individual diagnosis and treatment in the future

Year 7 and 8 Teachers' Understandings, Beliefs and Practices around the Teaching of Grammar in Relation to the Teaching of Writing

In recent times, and in fact over the past five decades, the importance of teachers’ knowledge of grammar and the teaching of grammar has encountered a resurgence of interest on the world stage as it has done within the research and educational communities of New Zealand (Hudson, 2004; Andrews, Torgerson, Beverton, Locke, Low, Robinson & Zhu 2004; Gordon, 2005; Locke, 2010; Myhill, Jones, Lines & Watson, 2012). Various contemporary studies into teachers’ understandings of grammar and the ways it is taught have utilised the knowledge and experiences of ESL (English as a Second Language) and pre-service teachers (Borg, 1999, 2001; Farrell, 1999; Burgess, Turvey & Quarshie, 2000; Nicholson, 2007; Harper & Rennie, 2008; Basturkmen, 2010). Some studies have emphasised linguistic elements related to the teaching of reading and spelling (Nicholson, 2007; Stainthorp, 2010; Cheesman, McGuire, Shankweiler & Coyne, 2009). However, there appears to be little research involving practising teacher participants, with a specific focus on grammar and its relationship to the teaching of writing. This study explores the broad grammatical knowledge and teaching practices within writing of in-service, generalist teachers of intermediate-aged (year 7 and 8) children. It addresses issues of importance regarding the grammatical understandings, beliefs and teaching practices of teachers within a specific New Zealand educational context. A mixed methods approach to gathering data was utilised in this study. A survey involving 26 year 7 and 8 intermediate school teachers was implemented, followed by a series of semi-structured interviews with a sub-group of six of these participants. The findings of this case study strongly suggest that, although many of the participants were uncertain of how to define grammar and lacked confidence in teaching grammar, their understandings and teaching pedagogies were stronger than they had perceived them to be. A clear majority of participants considered grammatical instruction to be important in improving student writing outcomes, and most revealed that this was an element included within their teaching practices. Findings also indicate that teachers experience distinct limitations in developing their understandings around grammar and grammatical instruction and that their perception of these limitations affects their confidence in teaching grammar. This study also points to a lack of conformity or standard of learning around teacher professional development in grammar. Moving forward, it would be interesting to determine whether there is, in fact, any form of standardised training around the teaching of grammar within and/or across other New Zealand schools, and what this might look like. Evidence from this study suggests that we need to understand more about what New Zealand teachers know about grammar and the teaching of grammar, specifically within school and classroom writing programmes. Future studies in this vein would benefit from including an element of observation as a methodological tool to help validate reported findings, particularly when investigating teachers’ approaches to teaching grammar.

Dopamine release, diffusion and uptake : A computational model for synaptic and volume transmission

Computational modeling of dopamine transmission is challenged by complex underlying mechanisms. Here we present a new computational model that (I) simultaneously regards release, diffusion and uptake of dopamine, (II) considers multiple terminal release events and (III) comprises both synaptic and volume transmission by incorporating the geometry of the synaptic cleft. We were able to validate our model in that it simulates concentration values comparable to physiological values observed in empirical studies. Further, although synaptic dopamine diffuses into extra-synaptic space, our model reflects a very localized signal occurring on the synaptic level, i.e. synaptic dopamine release is negligibly recognized by neighboring synapses. Moreover, increasing evidence suggests that cognitive performance can be predicted by signal variability of neuroimaging data (e.g. BOLD). Signal variability in target areas of dopaminergic neurons (striatum, cortex) may arise from dopamine concentration variability. On that account we compared spatio-temporal variability in a simulation mimicking normal dopamine transmission in striatum to scenarios of enhanced dopamine release and dopamine uptake inhibition. We found different variability characteristics between the three settings, which may in part account for differences in empirical observations. From a clinical perspective, differences in striatal dopaminergic signaling contribute to differential learning and reward processing, with relevant implications for addictive- and compulsive-like behavior. Specifically, dopaminergic tone is assumed to impact on phasic dopamine and hence on the integration of reward-related signals. However, in humans DA tone is classically assessed using PET, which is an indirect measure of endogenous DA availability and suffers from temporal and spatial resolution issues. We discuss how this can lead to discrepancies with observations from other methods such as microdialysis and show how computational modeling can help to refine our understanding of DA transmission. Author summary The dopaminergic system of the brain is very complex and affects various cognitive domains like memory, learning and motor control. Alterations have been observed e.g. in Parkinson's or Huntington's Disease, ADHD, addiction and compulsive disorders, such as pathological gambling and also in obesity. We present a new computational model that allows to simulate the process of dopamine transmission from dopaminergic neurons originated in source brain regions like the VTA to target areas such as the striatum on a synaptic and on a larger, volume-spanning level. The model can further be used for simulations of dopamine related diseases or pharmacological interventions. In general, computational modeling helps to extend our understanding, gained from empirical research, to situations were in vivo measurements are not feasible.Peer reviewe

Enhanced Go and NoGo Learning in Individuals With Obesity

Overeating in individuals with obesity is hypothesized to be partly caused by automatic action tendencies to food cues that have the potential to override goal-directed dietary restriction. Individuals with obesity are often characterized by alterations in the processing of such rewarding food, but also of non-food stimuli, and previous research has suggested a stronger impact on the execution of goal-directed actions in obesity. Here, we investigated whether Pavlovian cues can also corrupt the learning of new approach or withdrawal behavior in individuals with obesity. We employed a probabilistic Pavlovian-instrumental learning paradigm in which participants (29 normal-weight and 29 obese) learned to actively respond (Go learning) or withhold a response (NoGo learning) in order to gain monetary rewards or avoid losses. Participants were better at learning active approach responses (Go) in the light of anticipated rewards and at learning to withhold a response (NoGo) in the light of imminent punishments. Importantly, there was no evidence for a stronger corruption of instrumental learning in individuals with obesity. Instead, they showed better learning across conditions than normal-weight participants. Using a computational reinforcement learning model, we additionally found an increased learning rate in individuals with obesity. Previous studies have mostly reported a lower reinforcement learning performance in individuals with obesity. Our results contradict this and suggest that their performance is not universally impaired: Instead, while previous studies found reduced stimulus-value learning, individuals with obesity may show better action-value learning. Our findings highlight the need for a broader investigation of behavioral adaptation in obesity across different task designs and types of reinforcement learning.Peer Reviewe

A horizon scan of future threats and opportunities for pollinators and pollination

Background. Pollinators, which provide the agriculturally and ecologically essential service of pollination, are under threat at a global scale. Habitat loss and homogenisation, pesticides, parasites and pathogens, invasive species, and climate change have been identified as past and current threats to pollinators. Actions to mitigate these threats, e.g., agri-environment schemes and pesticide-use moratoriums, exist, but have largely been applied post-hoc. However, future sustainability of pollinators and the service they provide requires anticipation of potential threats and opportunities before they occur, enabling timely implementation of policy and practice to prevent, rather than mitigate, further pollinator declines. Methods.Using a horizon scanning approach we identified issues that are likely to impact pollinators, either positively or negatively, over the coming three decades. Results.Our analysis highlights six high priority, and nine secondary issues. High priorities are: (1) corporate control of global agriculture, (2) novel systemic pesticides, (3) novel RNA viruses, (4) the development of new managed pollinators, (5) more frequent heatwaves and drought under climate change, and (6) the potential positive impact of reduced chemical use on pollinators in non-agricultural settings. Discussion. While current pollinator management approaches are largely driven by mitigating past impacts, we present opportunities for pre-emptive practice, legislation, and policy to sustainably manage pollinators for future generations

Translating Motivational Interviewing for the HPV Vaccine Into a Computable Ontology Model for Automated AI Conversational Interaction

Human papillomavirus (HPV) vaccinations are lower than expected. To protect the onset of head and neck cancers, innovative strategies to improve the rates are needed. Artificial intelligence may offer some solutions, specifically conversational agents to perform counseling methods. We present our efforts in developing a dialogue model for automating motivational interviewing (MI) to encourage HPV vaccination. We developed a formalized dialogue model for MI using an existing ontology-based framework to manifest a computable representation using OWL2. New utterance classifications were identified along with the ontology that encodes the dialogue model. Our work is available on GitHub under the GPL v.3. We discuss how an ontology-based model of MI can help standardize/formalize MI counseling for HPV vaccine uptake. Our future steps will involve assessing MI fidelity of the ontology model, operationalization, and testing the dialogue model in a simulation with live participants

Trees, forests and water: Cool insights for a hot world

Forest-driven water and energy cycles are poorly integrated into regional, national, continental and global decision-making on climate change adaptation, mitigation, land use and water management. This constrains humanity’s ability to protect our planet’s climate and life-sustaining functions. The substantial body of research we review reveals that forest, water and energy interactions provide the foundations for carbon storage, for cooling terrestrial surfaces and for distributing water resources. Forests and trees must be recognized as prime regulators within the water, energy and carbon cycles. If these functions are ignored, planners will be unable to assess, adapt to or mitigate the impacts of changing land cover and climate. Our call to action targets a reversal of paradigms, from a carbon-centric model to one that treats the hydrologic and climate-cooling effects of trees and forests as the first order of priority. For reasons of sustainability, carbon storage must remain a secondary, though valuable, by-product. The effects of tree cover on climate at local, regional and continental scales offer benefits that demand wider recognition. The forest- and tree-centered research insights we review and analyze provide a knowledge-base for improving plans, policies and actions. Our understanding of how trees and forests influence water, energy and carbon cycles has important implications, both for the structure of planning, management and governance institutions, as well as for how trees and forests might be used to improve sustainability, adaptation and mitigation efforts

A genome-wide association study identifies risk alleles in plasminogen and P4HA2 associated with giant cell arteritis

Giant cell arteritis (GCA) is the most common form of vasculitis in individuals older than 50 years in Western countries. To shed light onto the genetic background influencing susceptibility for GCA, we performed a genome-wide association screening in a well-powered study cohort. After imputation, 1,844,133 genetic variants were analysed in 2,134 cases and 9,125 unaffected controls from ten independent populations of European ancestry. Our data confirmed HLA class II as the strongest associated region (independent signals: rs9268905, P = 1.94E-54, per-allele OR = 1.79; and rs9275592, P = 1.14E-40, OR = 2.08). Additionally, PLG and P4HA2 were identified as GCA risk genes at the genome-wide level of significance (rs4252134, P = 1.23E-10, OR = 1.28; and rs128738, P = 4.60E-09, OR = 1.32, respectively). Interestingly, we observed that the association peaks overlapped with different regulatory elements related to cell types and tissues involved in the pathophysiology of GCA. PLG and P4HA2 are involved in vascular remodelling and angiogenesis, suggesting a high relevance of these processes for the pathogenic mechanisms underlying this type of vasculitis