Towards a cognitive computer architecture based on memristive devices: developing Short- and Long-Term Memory
The goal of this project is to build a pattern-completion memory, which we believe is a critical component in developing novel cognitive computing architectures. We will accomplish this by building a neural network in which we use memristive devices that will act as synapses, and potentially also as soma. The overarching goal of the project is to build a pattern-completion system based on memristive devices that can operate both in the short- and in the long-term. This system should be able to memorize an input pattern (visual, auditive, motor program, etc.), and be able to reproduce it based on a part of the pattern. This component is of key importance for the construction of a larger-scale cognitive computer.
The project is cross-disciplinary with the Zernike Institute for Advanced Materials as part of the Cognigron Center for Cognitive Systems and Materials.
Cognitive Models of Persistent Cognition:
Is the whole of human cognitive ability an integrated system of knowledge, strategies and skills, or a collection of individual tasks and goals? Even though most people would gravitate towards the former point of view, the tradition of psychology, cognitive science and cognitive modeling adopts at least the research stance of the latter.
Understanding how, when, and why mind wandering affects cognition (ERC 283597 MULTITASK)
In this research project, we will examine the mechanisms of mind wandering with both behavioral data (e.g. eye-tracking, pupillometry) and cognitive models (PRIMs). We believe that combining both, fundamental research on mind wandering and modeling its mechanisms, will provide more insight in how, when, and why we mind wander.
Modeling the mechanisms underlying meditation
In this project, I am developing a computational model of of the neural mechanisms underlying meditation. In the summer of 2013, I started this project as a Mind and Life visiting scholar at Amherst college, and it involves a continuous collaboration between psychologists and cognitive scientists, but also Buddhist scholars and philosophers.
Understanding the cognitive mechanisms underlying depression (CSC scholarship to Hang Yang, NWA Idea Generator, FSS PhD scholarship, SPARC)
A core component of depression is ruminative thinking, which we can consider to be a maladaptive form of mind-wandering. In this project, we create ACT-R models of rumination to examine its effects in a variety of different tasks. In addition, we attempt to track rumination in brain activity and examine how it may be reduced by interventions such as mindfulness and preventative cognitive therapy.
Time perception (EU Horizon 2020 grant TIMESTORM)
An important part of the current work in progress focuses on different aspects of time. How do humans perceive time, and how do they incorporate their knowledge of task-related timing in their behavior.
Understanding Problem Solving in the Brain: Mapping the Flow of Information with Model-Based Analyses and Hidden semi-Markov Models (NWO Veni Grant 451-15-040)
The key cognitive functions that are involved in problem solving have been mapped onto the fronto-parietal brain network. However, it is unclear how these crucial functions are implemented at an algorithmic level, and how the flow of information is directed within the network. In this project, I will develop a detailed computational model of problem solving in the fronto-parietal network. To this end, I will apply and extend two innovative analysis techniques: model-based fMRI analysis and Hidden semi-Markov Model (HSMM) analysis. Both techniques will be used to analyze data of the same experiment measured with three different neuroimaging methods (fMRI, EEG, and MEG).
Discovering memory retrievals with MEG
Numerous studies in cognitive science have attempted to discover processing stages in particular tasks (Donders, 1969; Sternberg, 1969). To overcome the limitations of conventional behavioral measures, Hidden semi-Markov Model analysis (HSMM) in combination with multivariate pattern analysis (MVPA) was developed and applied to EEG (Anderson, Zhang, Borst, & Walsh, 2016). Recently, to allow for a better localization of the cognitive processes this analysis was extended to MEG because of its very high temporal and good spatial resolution (Anderson et al., 2018). In this project, we investigate how memory strength develops with repeated presentations of facts. As a proxy for memory strength we will measure the length of the memory retrieval stage on a trial-by-trial basis. To identify processing stages, we will use HsMM-MVPA analysis applied to MEG data.
People: Jelmer Borst, Hermine Berberyan in collaboration with Hedderik van Rijn (Dept. of Psychology, University of Groningen) and Tilmann Sander-Thömmes (Physikalisch-Technische Bundesanstalt, Berlin).
Uncovering the information processing underlying the interactions between brain areas (ERC starting grant)
The main aim of this project is to understand the role of oscillatory synchronization in information processing by combining cognitive modeling with a cognitive architecture and a dynamical systems analysis of EEG recorded during the same task.
People: People: Marieke van Vugt,Jelmer Borst, and Oscar Portoles Marin in collaboration with Ming Cao (ENgineering and TEchnology institute Groningen, ENTEG) under the Data Science and Systems Complexity theme in the University of Groningen.
The role of inter-brain synchronization in social cognition (YAG PhD project, AFOSR)
In recent years it has been shown that brain activity can synchronize between two individuals when they perform tasks together. In this study, we attempt to uncover what drives inter-brain synchronization, especially in real-life contexts. We collaborate with Dance ensembleRandom Collision to see how movement affects inter-brain synchrony, examine inter-brain synchrony in the context of Tibetan monastic debate, but also look in more conventional laboratory settings how inter-brain synchrony changes as participants learn to predict each other’s choices in a tacit coordination task.
Tibetan analytic meditation through the lens of neuroscience: A cross-cultural scientific collaboration (supported by the Hershey Family Foundation, Science for Monks, and a Teaching Excellence Fellowship)
This project explores the neural and behavioral effects of debate and analytical meditation. It is embedded in a program of research that fosters cross-fertilization of Eastern and Western scholarship.
People: Marieke van Vugt in collaboration with David Fresco (Kent State University), Joshua Pollock (Kent State University), Geshe Ngawang Norbu (Sera Jay Monastery), Amir Moye (University of Bern), and Bryce Johnson (Science for Monks).
Brain plasticity and training of psychomotor and cognitive skills in cardiovascular interventional medicine (funded by Ubbo Ermines and the Max-Planck Institute for Human Cognitive and Brain Sciences)
In this project we aim to advance our understanding of skill acquisition in catheter-based cardiovascular procedures. The goals of the project are: (1) to understand the brain plasticity that underlies the development of a complex skill, and (2) to test whether our cognitive approach to training leads to superior training outcomes compared to more traditional hands-on practice in the clinic.
People: Katja I. Paul, Fokie Cnossen, Niels Taatgen, in collaboration with Arno Villringer (Dpt. of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences) and Peter Lanzer (Akademisches Lehrkrankenhaus of Martin Luther University Halle-Wittenberg) .
Aspects of Quantification of Dutch and Serbian (Ubbo Emmius grant)
We investigate how and why children's interpretations of quantified expressions differ from adults' interpretations. We also look at how to create a cognitive model of child and adult interpretations.
People: Ana Bosnic, Jennifer Spenader, in collaboration with Hamida Demirdache (Département sciences du langage, University of Nantes).
Cognitive models of Persistent Cognition:
People have the remarkable ability to do many things at the same time. The things that people do at the same time often interact with each other. This can lead to interference, where the performance on individual tasks suffers. But in other cases, interference is minimal or absent, and there are even cases where there is a positive effect of multitasking on performance (see the blog for details). Our research focuses on two questions: when does multitasking lead to interference, and why are people multitasking in the first place.
In this project, we study the development of second-order theory of mind (e.g. "She believes that he knows that ...") by using behavioral experiments and computational cognitive models (ACT-R/PRIMs).
In this project we examine to what extent evidence accumulation processes that are known to underlie perpetual decisions also generalize to other decisions, such as those involving memory retrievals. We investigate the dynamics of these decisions using modeling, behavioral studies, EEG and intracranial EEG.
People: Marieke van Vugt, Marijke Beulen.
The goal of this project is the validation and implementation of optimized Human-Computer Interaction in healthcare. Specifically, we aim to improve the PACS (Picture Archiving and Communication System) that provides the user interface through which radiologists interact with patient images and create their reports.
The influence of the testing and spacing effect on declarative and procedure knowledge in transthoracic echocardiogram simulation training (CAPES – Brazilian Federal Agency for Support and Evaluation of Graduate Education - grant 9568-13-1)
This project aims to better understand the way declarative and procedural knowledge is obtained in medical skill acquisition, and how they interact. We explore the relationship between declarative and procedural knowledge by studying the testing and spacing effects in medical skills simulation training.
People: Fokie Cnossen, Dario Cecilio Ferandes, in collaboration with R.A. Tio (Center for Educational Development and Research in health sciences (CEDAR), University Medical Center Groningen).
Predicting the Optimal Time for Interruption to Minimize the Cost of Attentional Workload using Pupil Dilation and EEG
The goal of our project is to develop an interruption management system that will determine the best moment to present interruptions to minimize the attentional cost during multitasking. To this end, we combine our theoretical work with a real-world environment such as air traffic control (ATC). To determine workload we apply psychophysical methods (pupil dilation and EEG).
Multiperspective Multimodal Dialogue (EU seventh framework grant METALOGUE)
The goal of this project is to develop cognitive agents that can negotiate with people and other agents in single and multi-issue tasks. Moreover, these agents should possess the ability to engage in metacognitive reasoning about other players.
A list of all bachelor and master theses completed at the department of artificial intelligence can be found here: http://scripties.fse.eldoc.ub.rug.nl/(...)unstmatigeintellige/
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