Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.

Tests of the Dynamic Field Theory and the Spatial Precision Hypothesis: Capturing a Qualitative Developmental Transition in Spatial Working Memory

This study tested a dynamic field theory (DFT) of spatial working memory and an associated spatial precision hypothesis (SPH). Between 3 and 6 years of age, there is a qualitative shift in how children use reference axes to remember locations: 3-year-olds’ spatial recall responses are biased toward reference axes after short memory delays, whereas 6-year-olds’ responses are biased away from reference axes. According to the DFT and the SPH, quantitative improvements over development in the precision of excitatory and inhibitory working memory processes lead to this qualitative shift. Simulations of the DFT in Experiment 1 predict that improvements in precision should cause the spatial range of targets attracted toward a reference axis to narrow gradually over development, with repulsion emerging and gradually increasing until responses to most targets show biases away from the axis. Results from Experiment 2 with 3- to 5-year-olds support these predictions. Simulations of the DFT in Experiment 3 quantitatively fit the empirical results and offer insights into the neural processes underlying this developmental change.

Spatial modelling and prediction on river networks: up model, down model or hybrid?

Preservation of rivers and water resources is crucial in most environmental policies and many efforts are made to assess water quality. Environmental monitoring of large river networks are based on measurement stations. Compared to the total length of river networks, their number is often limited and there is a need to extend environmental variables that are measured locally to the whole river network. The objective of this paper is to propose several relevant geostatistical models for river modeling. These models use river distance and are based on two contrasting assumptions about dependency along a river network. Inference using maximum likelihood, model selection criterion and prediction by kriging are then developed. We illustrate our approach on two variables that differ by their distributional and spatial characteristics: summer water temperature and nitrate concentration. The data come from 141 to 187 monitoring stations in a network on a large river located in the Northeast of France that is more than 5000 km long and includes Meuse and Moselle basins. We first evaluated different spatial models and then gave prediction maps and error variance maps for the whole stream network.

MATERIAL MODELING AND ANALYSIS FOR THE DEVELOPMENT OF A REALISTIC BLAST HEADFORM

Blast traumatic brain injury (BTBI) has become an important topic of study because of the increase of such incidents, especially due to the recent growth of improvised explosive devices (IEDs). This thesis discusses a project in which laboratory testing of BTBI was made possible by performing blast loading on experimental models simulating the human head. Three versions of experimental models were prepared – one having a simple geometry and the other two having geometry similar to a human head. For developing the head models, three important parts of the head were considered for material modeling and analysis – the skin, skull and brain. The materials simulating skin, skull and brain went through many testing procedures including dynamic mechanical analysis (DMA). For finding a suitable brain simulant, several materials were tested under low and high frequencies. Step response analysis, rheometry and DMA tests were performed on materials such as water based gels, oil based mixtures and silicone gels cured at different temperatures. The gelatins and silicone gels showed promising results toward their use as brain surrogate materials. Temperature degradation tests were performed on gelatins, indicating the fast degradation of gelatins at room temperature. Silicone gels were much more stable compared to the water based gels. Silicone gels were further processed using a thinner-type additive gel to bring the dynamic modulus values closer to those of human brain matter. The obtained values from DMA were compared to the values for human brain as found in literature. Then a silicone rubber brain mold was prepared to give the brain model accurate geometry. All the components were put together to make the entire head model. A steel mount was prepared to attach the head for testing at the end of the shock tube. Instrumentation was implemented in the head model to obtain effective results for understanding more about the possible mechanisms of BTBI. The final head model was named the Realistic Explosive Dummy Head or the “RED Head.” The RED Head offered potential for realistic experimental testing in blast loading conditions by virtue of its material properties and geometrical accuracy.

Planning “Discrete” Movements Using a Continuous System: Insights from a Dynamic Field Theory of Movement Preparation

The timed-initiation paradigm developed by Ghez and colleagues (1997) has revealed two modes of motor planning: continuous and discrete. Continuous responding occurs when targets are separated by less than 60° of spatial angle, and discrete responding occurs when targets are separated by greater than 60°. Although these two modes are thought to reflect the operation of separable strategic planning systems, a new theory of movement preparation, the Dynamic Field Theory, suggests that two modes emerge flexibly from the same system. Experiment 1 replicated continuous and discrete performance using a task modified to allow for a critical test of the single system view. In Experiment 2, participants were allowed to correct their movements following movement initiation (the standard task does not allow corrections). Results showed continuous planning performance at large and small target separations. These results are consistent with the proposal that the two modes reflect the time-dependent “preshaping” of a single planning system.