Cees van Leeuwen

A Century of Gestalt Psychology in Visual Perception: II. Conceptual and Theoretical Foundations.

Our first review article (Wagemans et al., 2012) on the occasion of the centennial anniversary of Gestalt psychology focused on perceptual grouping and figure-ground organization. It concluded that further progress requires a reconsideration of the conceptual and theoretical foundations of the Gestalt approach, which is provided here. In particular, we review contemporary formulations of holism within an information-processing framework, allowing for operational definitions (e.g., integral dimensions, emergent features, configural superiority, global precedence, primacy of holistic/configural properties) and a refined understanding of its psychological implications (e.g., at the level of attention, perception, and decision). We also review 4 lines of theoretical progress regarding the law of Prägnanz-the brains tendency of being attracted towards states corresponding to the simplest possible organization, given the available stimulation. The first considers the brain as a complex adaptive system and explains how self-organization solves the conundrum of trading between robustness and flexibility of perceptual states. The second specifies the economy principle in terms of optimization of neural resources, showing that elementary sensors working independently to minimize uncertainty can respond optimally at the system level. The third considers how Gestalt percepts (e.g., groups, objects) are optimal given the available stimulation, with optimality specified in Bayesian terms. Fourth, structural information theory explains how a Gestaltist visual system that focuses on internal coding efficiency yields external veridicality as a side effect. To answer the fundamental question of why things look as they do, a further synthesis of these complementary perspectives is required.

Symbiotic relationship between brain structure and dynamics

BackgroundBrain structure and dynamics are interdependent through processes such as activity-dependent neuroplasticity. In this study, we aim to theoretically examine this interdependence in a model of spontaneous cortical activity. To this end, we simulate spontaneous brain dynamics on structural connectivity networks, using coupled nonlinear maps. On slow time scales structural connectivity is gradually adjusted towards the resulting functional patterns via an unsupervised, activity-dependent rewiring rule. The present model has been previously shown to generate cortical-like, modular small-world structural topology from initially random connectivity. We provide further biophysical justification for this model and quantitatively characterize the relationship between structure, function and dynamics that accompanies the ensuing self-organization.ResultsWe show that coupled chaotic dynamics generate ordered and modular functional patterns, even on a random underlying structural connectivity. Consequently, structural connectivity becomes more modular as it rewires towards these functional patterns. Functional networks reflect the underlying structural networks on slow time scales, but significantly less so on faster time scales. In spite of ordered functional topology, structural networks remain robustly interconnected – and therefore small-world – due to the presence of central, inter-modular hub nodes. The noisy dynamics of these hubs enable them to persist despite ongoing rewiring and despite their comparative absence in functional networks.ConclusionOur results outline a theoretical mechanism by which brain dynamics may facilitate neuroanatomical self-organization. We find time scale dependent differences between structural and functional networks. These differences are likely to arise from the distinct dynamics of central structural nodes.

Affordances, perceptual complexity, and the development of tool use.

Perceiving the affordance of a tool requires the integration of several complementary relationships among actor, tool, and target. Highers order affordance structures are introduced to deal with these forms of complex action from an ecological-realist point of view. The complexity of the higher order affordance structure was used to predict the difficulty of perceiving the tool function. Predictions were tested in 3 experiments involving children between 9 months and 4 years old. In a classical tool use task dating back to W. Köhler, a desirable target was obtained by using a hook as a tool. The relative positions of the hook and the target were systematically varied to obtain structures differing in complexity. The observed difficulty of the task was found essentially in accordance with the theoretical complexity of the higher order affordance structures involved in perceiving the tool function.

Scale-invariant fluctuations of the dynamical synchronization in human brain electrical activity

The dynamical properties of large-scale, long-term phase synchronization behavior in the alpha range of electroencephalographic signals were investigated. We observed dynamical phase synchronization and presented evidence of an underlying spatiotemporal ordering. Fluctuations in the duration of episodes of intermittent synchrony are scale-invariant. Moreover, the exponent used to describe this behavior is stable across different normal subjects. The results provide a new feature of self-organization in human brain activity and constitute a quantitative basis for modeling its dynamics.

Paradoxical Enhancement of Letter Recognition in Developmental Dyslexia

In a number of studies, children diagnosed with developmental dyslexia reached normal scores in standard visual processing tasks, and some researchers concluded that visual processing deficits are not involved in the syndrome. The tasks used, however, may be insensitive to anomalous visual information processing strategies used to compensate for an underlying deficit. To determine whether children with dyslexia use anomalous visual processing strategies, a same-differenttask was applied, in which 2 items identical under rotation and reflection were judged as same. Pairs of letters or dot patterns were used, which were either symmetric or asymmetric in shape. Children with dyslexia performed faster than normal-reading children—in particular, remarkably, with letters. Symmetry of dot patterns facilitated performance in both children with dyslexia and normal-reading children; symmetry of letters facilitated performance in children with dyslexia but not in normal-reading children. Children with dyslexia, therefore, fail to adequately differentiate visual processing of linguistic and nonlinguistic materials; they process symmetry in letters similarly to that in shapes, which leads in this particular task to the paradoxical observation of children with dyslexia outperforming normal readers with letters.

Spatial and temporal structure of phase synchronization of spontaneous alpha EEG activity

Spatiotemporal characteristics of spontaneous alpha EEG activity patterns are analyzed in terms of large-scale phase synchronization. During periods with strong phase synchronization over the entire scalp, phase patterns take either of two forms; one is a gradual phase shift between frontal and occipital regions and the other is a stepwise pattern with a sudden phase shift in the central region. The former is regarded as a traveling wave of electrocortical activity, of which the direction of propagation is predominantly from anterior to posterior in three out of four subjects, and opposite in the remaining one. The other activity pattern observed may correspond to a standing wave composed of two traveling waves propagating in opposite directions. The duration distributions of these patterns have similar forms within a subject, which suggests that they share the same mechanism for their generation.

Dynamics of spontaneous transitions between global brain states

Phase patterns of human scalp alpha EEG activity show spontaneous transitions between different globally phase‐synchronized states. We studied the dynamical properties of these transitions using the method of symbolic dynamics. We found greater predictability (deterministicity) and heterogeneity in the dynamics than what was expected from corresponding surrogate series in which linear correlations are retained. A possible explanation of these observations within the framework of chaotic itinerancy is discussed. Hum Brain Mapp, 2007.

Negative and positive congruence effects in letters and shapes

In six experiments in which a binary classification task was used, letter and nonletter (geometrical shapes, pseudoletters, or rotated letters) targets were presented either in isolation or surrounded by a geometrical shape. The surrounding shape could be congruent or incongruent with the target. When the classification required a distinction between letters and nonletters, either explicitly (Experiments 1–3) or implicitly (Experiment 4), a negative congruence effect was obtained for letters, contrasting with a regular, positive congruence effect for nonletters. When no distinction was to be made, letters and nonletters invariably showed a positive congruence effect (Experiments 5 and 6). In particular, between Experiments 1–4 and Experiments 5 and 6, the occurrence of negative or positive congruence effects for the same stimuli depended on the task. Feature interaction, target selection, and response competition explanations were tested against a feature integration approach. The results are explained in terms of different feature integration strategies for letters and nonletters.

Robust emergence of small-world structure in networks of spiking neurons

Spontaneous activity in biological neural networks shows patterns of dynamic synchronization. We propose that these patterns support the formation␣of a small-world structure—network connectivity␣optimal for distributed information processing. We␣present numerical simulations with connected Hindmarsh–Rose neurons in which, starting from random connection distributions, small-world networks evolve as a result of applying an adaptive rewiring rule. The rule connects pairs of neurons that tend fire in synchrony, and disconnects ones that fail to synchronize. Repeated application of the rule leads to small-world structures. This mechanism is robustly observed for bursting and irregular firing regimes.

Adaptive observers and parameter estimation for a class of systems nonlinear in the parameters

We consider the problem of asymptotic reconstruction of the state and parameter values in systems of ordinary differential equations. A solution to this problem is proposed for a class of systems of which the unknowns are allowed to be nonlinearly parameterized functions of state and time. Reconstruction of state and parameter values is based on the concepts of weakly attracting sets and non-uniform convergence and is subjected to persistency of excitation conditions. In the absence of nonlinear parametrization the resulting observers reduce to standard estimation schemes. In this respect, the proposed method constitutes a generalization of the conventional canonical adaptive observer design.