From the article: Abstract Over the last decades, philosophers and cognitive scientists have argued that the brain constitutes only one of several contributing factors to cognition, the other factors being the body and the world. This position we refer to as Embodied Embedded Cognition (EEC). The main purpose of this paper is to consider what EEC implies for the task interpretation of the control system. We argue that the traditional view of the control system as involved in planning and decision making based on beliefs about the world runs into the problem of computational intractability. EEC views the control system as relying heavily on the naturally evolved fit between organism and environment. A ‘lazy’ control structure could be ‘ignorantly successful’ in a ‘user friendly’ world, by facilitating the transitory creation of a flexible and integrated set of behavioral layers that are constitutive of ongoing behavior. We close by discussing the types of questions this could imply for empirical research in cognitive neuroscience and robotics.
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This study provides an illustration of a research design complementary to randomized controlled trial to evaluate program effects, namely, participatory peer research (PPR). The PPR described in current study was carried out in a small sample (N = 10) of young adults with mild intellectual disabilities (MID) and severe behavioral problems. During the PPR intervention, control and feedback to individuals is restored by training them to become participant-researchers, who collaborate in a small group of people with MID. Their research is aimed at the problems the young adults perceive and/or specific subjects of their interest. The study was designed as a multiple case study with an experimental and comparison group. Questionnaires and a semistructured interview were administered before and after the PPR project. Results of Reliable Change Index (RCI) analyses showed a decrease in self-serving cognitive distortions in the PPR group, but not in the comparison group. These results indicate that PPR helps to compensate for a lack of adequate feedback and control, and in turn may decrease distorted thinking and thereby possibly later challenging behavior.
Hematological malignancies and treatment with hematopoietic SCT are known to affect patients’ quality of life. The problem profile and care needs of this patient group need clarification, however. This study aimed to assess distress, problems and care needs after allo- or auto-SCT, and to identify risk factors for distress, problems or care needs. In this cross-sectional study, patients treated with allo-SCT or auto-SCT for hematological malignancies completed the Distress Thermometer and Problem List. Three patient groups were created: 0–1, 1–2.5 and 2.5–5.5 years after transplantation. After allo-SCT, distress and the number of problems tended to be lower with longer follow-up. After auto-SCT, distress was highest at 1–2.5 year(s). Patients mainly reported physical problems, followed by cognitive-emotional and practical problems. A minority reported care needs. Risk factors for distress as well as problems after allo-SCT included younger age, shorter time after transplantation and GVHD. A risk factor for distress as well as problems after auto-SCT was the presence of comorbid diseases. Up to 5 years after auto-SCT or allo-SCT, patients continue to experience distress and problems. Judged by prevalence, physical problems are first priority in supportive care, followed by cognitive-emotional and practical problems.
Our unilateral diet has resulted in a deficiency of specific elements/components needed for well-functioning of the human body. Especially the element magnesium is low in our processed food and results in neuronal and muscular malfunctioning, problems in bone heath/strength, and increased chances of diabetes, depression and cardiovascular diseases. Furthermore, it has also been recognized that magnesium plays an important role in cognitive functioning (impairment and enhancement), especially for people suffering from neurodegenerative diseases (Parkinson disease, Alzheimer, etc). Recently, it has been reported that magnesium addition positively effects sleep and calmness (anti-stress). In order to increase the bioavailability of magnesium cations, organic acids such as citrate, glycerophosphate and glycinate are often used as counterions. However, the magnesium supplements that are currently on the market still suffer from low bio-availability and often do not enter the brain significantly.The preparation of dual/multiple ligands of magnesium in which the organic acid not only functions as a carrier but also has synergistically/complementary biological effects is widely unexplored and needs further development. As a result, there is a strong need for dual/multiple magnesium supplements that are non-toxic, stable, prepared via an economically and ecologically attractive route, resulting in high bioavailability of magnesium in vivo, preferably positively influencing cognition/concentration
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
Examining in-class activities to facilitate academic achievement in higher educationThere is an increasing interest in how to create an effective and comfortable indoor environment for lecturers and students in higher education. To achieve evidence-based improvements in the indoor environmental quality (IEQ) of higher education learning environments, this research aimed to gain new knowledge for creating optimal indoor environmental conditions that best facilitate in-class activities, i.e. teaching and learning, and foster academic achievement. The academic performance of lecturers and students is subdivided into short-term academic performance, for example, during a lecture and long-term academic performance, during an academic course or year, for example. First, a systematic literature review was conducted to reveal the effect of indoor environmental quality in classrooms in higher education on the quality of teaching, the quality of learning, and students’ academic achievement. With the information gathered on the applied methods during the literature review, a systematic approach was developed and validated to capture the effect of the IEQ on the main outcomes. This approach enables research that aims to examine the effect of all four IEQ parameters, indoor air quality, thermal conditions, lighting conditions, and acoustic conditions on students’ perceptions, responses, and short-term academic performance in the context of higher education classrooms. Next, a field experiment was conducted, applying the validated systematic approach, to explore the effect of multiple indoor environmental parameters on students and their short-term academic performance in higher education. Finally, a qualitative case study gathered lecturers’ and students’ perceptions related to the IEQ. Furthermore, how these users interact with the environment to maintain an acceptable IEQ was studied.During the systematic literature review, multiple scientific databases were searched to identify relevant scientific evidence. After the screening process, 21 publications were included. The collected evidence showed that IEQ can contribute positively to students’ academic achievement. However, it can also affect the performance of students negatively, even if the IEQ meets current standards for classrooms’ IEQ conditions. Not one optimal IEQ was identified after studying the evidence. Indoor environmental conditions in which students perform at their best differ and are task depended, indicating that classrooms should facilitate multiple indoor environmental conditions. Furthermore, the evidence provides practical information for improving the design of experimental studies, helps researchers in identifying relevant parameters, and lists methods to examine the influence of the IEQ on users.The measurement methods deduced from the included studies of the literature review, were used for the development of a systematic approach measuring classroom IEQ and students’ perceived IEQ, internal responses, and short-term academic performance. This approach allowed studying the effect of multiple IEQ parameters simultaneously and was tested in a pilot study during a regular academic course. The perceptions, internal responses, and short-term academic performance of participating students were measured. The results show associations between natural variations of the IEQ and students’ perceptions. These perceptions were associated with their physiological and cognitive responses. Furthermore, students’ perceived cognitive responses were associated with their short-term academic performance. These observed associations confirm the construct validity of the composed systematic approach. This systematic approach was then applied in a field experiment, to explore the effect of multiple indoor environmental parameters on students and their short-term academic performance in higher education. A field study, with a between-groups experimental design, was conducted during a regular academic course in 2020-2021 to analyze the effect of different acoustic, lighting, and indoor air quality (IAQ) conditions. First, the reverberation time was manipulated to 0.4 s in the intervention condition (control condition 0.6 s). Second, the horizontal illuminance level was raised from 500 to 750 lx in the intervention condition (control condition 500 lx). These conditions correspond with quality class A (intervention condition) and B (control condition), specified in Dutch IEQ guidelines for school buildings (2015). Third, the IAQ, which was ~1100 ppm carbon dioxide (CO2), as a proxy for IAQ, was improved to CO2 concentrations under 800 ppm, meeting quality class A in both conditions. Students’ perceptions were measured during seven campaigns with a questionnaire; their actual cognitive and short-term academic performances were evaluated with validated tests and an academic test, composed by the lecturer, as a subject-matter-expert on the taught topic, covered subjects discussed during the lecture. From 201 students 527 responses were collected and analyzed. A reduced RT in combination with raised HI improved students’ perceptions of the lighting environment, internal responses, and quality of learning. However, this experimental condition negatively influenced students’ ability to solve problems, while students' content-related test scores were not influenced. This shows that although quality class A conditions for RT and HI improved students’ perceptions, it did not influence their short-term academic performance. Furthermore, the benefits of reduced RT in combination with raised HI were not observed in improved IAQ conditions. Whether the sequential order of the experimental conditions is relevant in inducing these effects and/or whether improving two parameters is already beneficial, is unknownFinally, a qualitative case study explored lecturers’ and students’ perceptions of the IEQ of classrooms, which are suitable to give tutorials with a maximum capacity of about 30 students. Furthermore, how lecturers and students interact with this indoor environment to maintain an acceptable IEQ was examined. Eleven lecturers of the Hanze University of Applied Sciences (UAS), located in the northern part of the Netherlands, and twenty-four of its students participated in three focus group discussions. The findings show that lecturers and students experience poor thermal, lighting, acoustic, and IAQ conditions which may influence teaching and learning performance. Furthermore, maintaining acceptable thermal and IAQ conditions was difficult for lecturers as opening windows or doors caused noise disturbances. In uncomfortable conditions, lecturers may decide to pause earlier or shorten a lecture. When students experienced discomfort, it may affect their ability to concentrate, their emotional status, and their quality of learning. Acceptable air and thermal conditions in classrooms will mitigate the need to open windows and doors. This allows lecturers to keep doors and windows closed, combining better classroom conditions with neither noise disturbances nor related distractions. Designers and engineers should take these end users’ perceptions into account, often monitored by facility management (FM), during the renovation or construction of university buildings to achieve optimal IEQ conditions in higher education classrooms.The results of these four studies indicate that there is not a one-size fits all indoor environmental quality to facilitate optimal in-class activities. Classrooms’ thermal environment should be effectively controlled with the option of a local (manual) intervention. Classrooms’ lighting conditions should also be adjustable, both in light color and light intensity. This enables lecturers to adjust the indoor environment to facilitate in-class activities optimally. Lecturers must be informed by the building operator, for example, professionals of the Facility Department, how to change classrooms’ IEQ settings. And this may differ per classroom because each building, in which the classroom is located, is operated differently apart from the classroom location in the building, exposure to the environment, and its use. The knowledge that has come available from this study, shows that optimal indoor environmental conditions can positively influence lecturers’ and students’ comfort, health, emotional balance, and performance. These outcomes have the capacity to contribute to an improved school climate and thus academic achievement.
