Voorzitter: Cor van Dijkum




Dynamic Animations of Journal Maps: Indicators of Structural Changes and Interdisciplinary Developments


Loet Leydesdorff

Amsterdam University


The dynamic analysis of structural change in the organization of the sciences requires methodologically the integration of multivariate and time-series analysis. Structural change—e.g., interdisciplinary development—is often an objective of government interventions. Recent developments in multi-dimensional scaling (MDS) enable us to distinguish the stress originating in each time-slice from the stress originating from the sequencing of time-slices, and thus to locally optimize the trade-offs between these two sources of variance in the animation. Furthermore, visualization programs like Pajek and Visone allow us to show not only the positions of the nodes, but also their relational attributes like betweenness centrality. Betweenness centrality in the vector space can be considered as an indicator of interdisciplinarity. Using this indicator, the dynamics of the citation impact environments of the journals Cognitive Science, Social Networks, and Nanotechnology are animated and assessed in terms of interdisciplinarity among the disciplines involved.

Validating Complex Signal Analyses of Human Cognition by Simulating Well Known Dynamical Systems:

Promises and Pitfalls

Fred Hasselman

Ralf Cox

Radboud University (Nijmegen)


Recently techniques based on Takens’ embedding theorem have been successfully used to analyse data from psychological experiments. Many of the studies show promising results for instance in the fields of language development, human postural control, ERP experiments, problem solving, dyadic interactions, tremors in Parkinson’s disease and rhythmical aiming movements.

Takens’ theorem (1981) allows for the reconstruction of the phase space of a complex dynamical system based on the measurement of just one variable of the system. Takens has shown that the reconstructed phase space will be topologically equivalent to the phase space of the original system. Recurrence Quantification Analysis is usually conducted on this reconstructed phase space, which enables a quantification of the complexity of the system in terms of stationarity, determinism, entropy and sensitivity on initial conditions. One reason why these analyses are interesting for psychology is that there are no restrictions on the data, as is the case with analyses based on the Gauss-Markov theorem. Or are there?

Of course there is the theoretical assumption that humans should be studied as a complex system. Several authors have taken the presence of 1/f noise in many cognitive tasks as a sign that we are dealing with a complex self-organising system. Its mere presence is however not enough to make this claim. Moreover, many of the studies use well known dynamical systems such as the Lorenz system to show that RQA measures are able to detect order-chaos and chaos-chaos transitions and then look for similar changes in RQA measures retrieved from their own data. I will address the promises and pitfalls of this approach by discussing several recent studies which combine fractal analysis, complex signal analysis and simulation.



Suggested reading:

Kello, C.T., Beltz, B.C., Holden, J.G., & Van Orden, G.C. (2007). The emergent

coordination of cognitive function. Journal of Experimental Psychology: General,

136, 551-568.

Richardson, D.C., Dale, R., & Kirkham, N.Z. (2007). The art of conversation is

coordination: Common ground and the coupling of eye movements during

dialogue. Psychological Science 18 , 407–413

Schinkel, S., Marwan, N. & Kurths, J. (2007). Order patterns recurrence plots in the

analysis of ERP data. Cognitive Neurodynamics, 1, 4, 317-325.

Shockley, K., Santana, M-V., Fowler, C. (2003). Mutual interpersonal postural

constraints are involved in cooperative conversation. Journal of Experimental

Psychology: Human Perception and Performance, 29, 326-323.

Stephen, D.G., Dixon, J.A., & Isenhower, R.W. (2008). Dynamics of representational

change: Entropy, action, and cognition. Manuscript submitted for publication.

Wijnants, M.L., Bosman, A.M.T., Hasselman, F., Cox, R.F.A., & Van Orden, G.C.

(2008). 1/f scaling fluctuation in movement time: Temporal structure changes

with massed practice. Manuscript submitted for publication in NLDPS.



Non-Linear Models for the Feedback between GP and Patients

Cor van Dijkum, Niek Lam

Department of Methodology and Statistics

Faculty of Social Sciences,

Utrecht University

The Netherlands

William Verheul, Jozien Bensing

Netherlands Institute for Health Services Research
Otterstraat 118 – 124
3513 CR Utrecht
The Netherlands




How can we model the interaction between a medical doctor and a patient that takes into account the dynamics and non-linearity of the communication? To answer this question we use a dataset of 101 hypertension (video-taped) consultations in Dutch General Practice.

We develop causal hypotheses about the relations between variables that are important for the communication.  A non-linear model is builded with the aid of the software STELLA that expresses those causal relations. Thereafter we explore with the more mathematical software MatLab how such a model of coupled logistic equations behaves, especially concerning coupled patterns of chaos and order. Thereby we focus on phenomena such as synchronization and selforganization in the process of communication.