Although great progress has been made in the search for the neural correlates of consciousness, this endeavour has several blind spots. These relate to the fact that there are two, not one, concepts that the term ‘consciousness’ refers to. Conscious content, the subjective character of our experience, and conscious state, the fluctuations in the overall conscious condition, for example alert wakefulness versus sleep. Problematically, conscious content and conscious state are typically studied in isolation. In this proposal, we explore their dynamic interaction to unravel how ongoing, and unexplored, fluctuations in state affect sensory information processing and therefore our conscious experience.

The proposed project aims at creating a database that encourages sharing, reusing, and extending computational implementations of formal models in psychology. Through creating a platform designed for productive exchange both within modelling groups and between those modellers and empirical researchers, modelling practices among researchers will be nurtured and further developed. This platform will augment traditional publication formats with a structured database that makes computational implementations more FAIR, supplement open code sharing practices, and make communication between theoretical and empirical psychologists easier.

To enable sound diagnosis, training and advice, this project takes a multi-level/multi-function perspective on representative negotiation in inter-group conflict in policy and industry. Three core outcomes ? (a) the development of creative agreements, (b) within-constituency conflict and consensus, and (c) inter-group perceptions and hostility ? are considered to depend on (1) the representative?s individual-level cognition, affect, and motivation, (2) within-constituency dynamics, and (3) the broader inter-group relations. In 2 PhD and 1 Postdoc project hypotheses will be tested using experiments, case studies, and quantitative surveys. Results will be communicated in academic and professional publications and will serve as input for training and development programs.

Yearly textile waste adds up to 110 million tons globally1 (13 kg per person globally), the majority going to landfill or incineration. Mechanical and chemical textile recycling requires relatively pure waste streams. The Netherlands is a technology leader for textile sorting and mechanical recycling,2 but unfortunately a large-volume fraction of textile waste consists of blends or inseparable mixtures of different materials. For cotton/polyester(PET) mixtures (the largest volumes in textiles), no techno-economic recycling options exist today.3 A breakthrough proof-of-principle was obtained (using Avantium’s DAWN Biorefinery technology4) for hydrolyzing cotton (cellulose) to valuable building blocks, even when mixed with polyester. The residual PET could be recycled to rPET, in close to quantitative yield. Avantium is a technology partner that can plug the cotton (cellulose) hydrolysis into their DAWN technology. Avantium will host and guide the 2 Technology PhD students in their Amsterdam labs. CuRe is a technology partner for plugging-in the PET chemical recycling into their technology.5 With Modint,6 Wieland7 and Groenendijk8 the consortium has relevant partners across the textiles value chain (including sorting and recycling). If successful, the resulting technology can convert millions of kg of Dutch waste textiles and 10s of millions of tons of textile waste globally to valuable polyester building blocks (monomers) and to rPET. Finally, for every ton of waste textile saved from incineration by MIWATEX, about 2 tons* of CO2 emissions will be avoided just from material incineration alone. *Cotton (C6H10O5)n and PET (C10H8O4)n yield 1.63 and 2.29 ton CO2/ton waste textile upon incineration, respectively.

Response inhibition refers to the ability to stop an ongoing response, such as rapidly halting when the traffic light turns red. Response inhibition is the hallmark of executive functions and has received-and continues to receive-considerable attention in the field of experimental, clinical, and neuropsychology. The proposed project focuses on two recently developed cognitive process models of inhibition: the stop-signal race diffusion model (SS-RDM) and the stop-signal linear ballistic accumulator (SS-LBA). Both models conceptualize inhibition as a race between a set of evidence accumulators: one set that is associated with the ongoing response, and another that is associated with the stop response. The difference between the models lies in the mathematical formulation of evidence accumulation. Contrary to traditional models of response inhibition, process models provide parameter estimates that can be directly interpreted in terms of well-defined cognitive processes, such as the rate of evidence accumulation and response caution. Despite this conceptual advantage, the applicability of the SS-RDM and SS-LBA is limited by the large number of observations that are necessary for accurate parameter estimation and by the lack of adequate hypothesis testing techniques. The current project proposes to overcome these limitations with Bayesian inference. My first goal is to provide a Bayesian hierarchical implementation of the SS-RDM and SS-LBA that can substantially decrease the necessary number of observations. My second goal is to develop a Bayesian model selection method that allows researchers to formally evaluate nested and non-nested hypotheses in the SS-RDM and SS-LBA using reversible jump Markov chain Monte Carlo sampling. My overall objective is to create an integrated framework and corresponding software that will enable investigators to address fundamental and applied research questions about the nature and development of response inhibition using relatively small data sets and state-of-the-art Bayesian hypothesis testing techniques.