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

Neural dynamic foundations of a theory of higher cognition: the case of grounding nested phrases

Because cognitive competences emerge in evolution and development from the sensory-motor domain, we seek a neural process account for higher cognition in which all representations are necessarily grounded in perception and action. The challenge is to understand how hallmarks of higher cognition, productivity, systematicity, and compositionality, may emerge from such a bottom-up approach. To address this challenge, we present key ideas from Dynamic Field Theory which postulates that neural populations are organized by recurrent connectivity to create stable localist representations. Dynamic instabilities enable the autonomous generation of sequences of mental states. The capacity to apply neural circuitry across broad sets of inputs that emulates the function call postulated in symbolic computation emerges through coordinate transforms implemented in neural gain fields. We show how binding localist neural representations through a shared index dimension enables conceptual structure, in which the interdependence among components of a representation is flexibly expressed. We demonstrate these principles in a neural dynamic architecture that represents and perceptually grounds nested relational and action phrases. Sequences of neural processing steps are generated autonomously to attentionally select the referenced objects and events in a manner that is sensitive to their interdependencies. This solves the problem of 2 and the massive binding problem in expressions such as "the small tree that is to the left of the lake which is to the left of the large tree". We extend earlier work by incorporating new types of grammatical constructions and a larger vocabulary. We discuss the DFT framework relative to other neural process accounts of higher cognition and assess the scope and challenges of such neural theories.

Individual differences in executive attention and inhibitory control are related to spatial memory biases in adults

Executive attention is involved in working memory; however, the role of executive attention in the maintenance of information in spatial working memory is debated. This study examined whether inhibitory control was related to spatial working memory biases in adults in a simple spatial memory task where participants had to remember one location on an otherwise blank computer screen. On some trials, a distractor was presented during the maintenance period. Eighty-four participants completed the spatial working memory task and a battery of cognitive control measures. When a distractor was presented during the maintenance period of the spatial memory task, performance on two of the cognitive control measures, a measure of overall attention and a measure of inhibitory control was related to memory errors. When a distractor was not presented during the spatial memory task, memory errors were not related to performance on the cognitive control tasks. Overall, these effects demonstrated that attention is related to maintaining locations in spatial working memory in adults, and inhibitory control may also be related such that those with more efficient inhibitory control were less influenced by distractors presented during the maintenance period.

Discrete Dynamics of Dynamic Neural Fields

Large and small cortexes of the brain are known to contain vast amounts of neurons that interact with one another. They thus form a continuum of active neural networks whose dynamics are yet to be fully understood. One way to model these activities is to use dynamic neural fields which are mathematical models that approximately describe the behavior of these congregations of neurons. These models have been used in neuroinformatics, neuroscience, robotics, and network analysis to understand not only brain functions or brain diseases, but also learning and brain plasticity. In their theoretical forms, they are given as ordinary or partial differential equations with or without diffusion. Many of their mathematical properties are still under-studied. In this paper, we propose to analyze discrete versions dynamic neural fields based on nearly exact discretization schemes techniques. In particular, we will discuss conditions for the stability of nontrivial solutions of these models, based on various types of kernels and corresponding parameters. Monte Carlo simulations are given for illustration.

Connecting the Dots: Finding Continuity Across Visuospatial Tasks and Development

The study of cognition and its development has long been partitioned into sub-domains, with different tasks designed to assess different constructs and for use during different developmental periods. A central challenge is to understand how a single cognitive system organizes itself across many contexts and developmental periods in which we study it. This article takes a step toward tackling this challenge through a theoretical review of simulations of a dynamic neural field (DNF) model of visuospatial cognitive development. The DNF model simulates basic neurocognitive processes of encoding, maintenance, and long-term memory formation that are coupled to different behavioral systems to generate behaviors required across different tasks used with different age groups. The model simulations reviewed here were initially focused on explaining performance in specific experimental conditions within a developmental period. This article brings to the forefront the larger theoretical goal to understand how a set of basic neurocognitive processes can underlie performance in a wide array of contexts. This review connects behavioral signatures and developmental phenomena from spatial cognition, infant visual exploration, and capacity limits in visual working memory into a single theoretical account of the development of basic visuospatial cognitive processes. Our synthesis yielded three new insights not evident when considering the model simulations in isolation. First, we identified behavior as an emergent product of the neurocognitive processes at work in the model, task context, and development. Second, we show the role of stability of perceptual and memory representations to support behavior within a task and across development. Third, we highlight continuity of ongoing real-time processes at work within and across tasks and over development.

Navigation and the developing brain

As babies rapidly acquire motor skills that give them increasingly independent and wide-ranging access to the environment over the first two years of human life, they decrease their reliance on habit systems for spatial localization, switching to their emerging inertial navigation system and to allocentric frameworks. Initial place learning is evident towards the end of the period. From 3 to 10 years, children calibrate their ability to encode various sources of spatial information (inertial information, geometric cues, beacons, proximal landmarks and distal landmarks) and begin to combine cues, both within and across systems. Geometric cues are important, but do not constitute an innate and encapsulated module. In addition, from 3 to 10 years, children build the capacity to think about frames of reference different from their current one (i.e. to perform perspective taking). By around 12 years, we see adult-level performance and adult patterns of individual differences on cognitive mapping tasks requiring the integration of vista views of space into environmental space. These lines of development are continuous rather than stage-like. Spatial development builds on important beginnings in the neural systems of newborns, but changes in experience-expectant ways with motor development, action in the world and success–failure feedback. Human systems for integrating and manipulating spatial information also benefit from symbolic capacities and technological inventions.

Visual working memory in early development: a developmental cognitive neuroscience perspective

In this article, we review the literature on the development of visual working memory (VWM). We focus on two major periods of development, infancy and early childhood. First, we discuss the innovative methods that have been devised to understand how the development of selective attention and perception provide the foundation of VWM abilities. We detail the behavioral and neural data associated with the development of VWM during infancy. Next, we discuss various signatures of development in VWM during early childhood in the context of spatial and featural memory processes. We focus on the developmental transition to more adult-like VWM properties. Finally, we discuss computational frameworks that have explained the complex patterns of behavior observed in VWM tasks from infancy to adulthood and attempt to explain links between measures of infant VWM and childhood VWM.

Age-related Decline of Visual Working Memory: Behavioral Results Simulated with a Dynamic Neural Field Model

Visual working memory (VWM) is essential for executive function and is known to be compromised in older adults. Yet, the cognitive and neural processes associated with these age-related changes remain inconclusive. The purpose of this study was to explore such factors with a dynamic neural field (DNF) model that was manipulated to replicate the behavioral performances of younger and older adults in a change detection task. Although previous work has successfully modeled children and younger adult VWM performance, this study represents the first attempt to model older adult VWM performance within the DNF architecture. In the behavioral task, older adults performed worse than younger adults and exhibited a characteristic response bias that favored "same" over "different" responses. The DNF model was modified to capture the age group differences, with three parameter manipulations producing the best fit for the behavioral performances. The best-fitting model suggests that older adults operate through altered excitatory and inhibitory coupling and decreased inhibitory signals, resulting in wider and weaker neural signals. These results support a dedifferentiation account of brain aging, with older adults operating with wider and weaker neural signals because of decreased intracortical inhibition rather than increased stochastic neural noise.

Evidence of gradual loss of precision for simple features and complex objects in visual working memory

Previous studies have suggested that people can maintain prioritized items in visual working memory for many seconds, with negligible loss of information over time. Such findings imply that working memory representations are robust to the potential contaminating effects of internal noise. However, once visual information is encoded into working memory, one might expect it to inevitably begin degrading over time, as this actively maintained information is no longer tethered to the original perceptual input. Here, we examined this issue by evaluating working memory for single central presentations of an oriented grating, color patch, or face stimulus, across a range of delay periods (1, 3, 6, or 12 s). We applied a mixture-model analysis to distinguish changes in memory precision over time from changes in the frequency of outlier responses that resemble random guesses. For all 3 types of stimuli, participants exhibited a clear and consistent decline in the precision of working memory as a function of temporal delay, as well as a modest increase in guessing-related responses for colored patches and face stimuli. We observed a similar loss of precision over time while controlling for temporal distinctiveness. Our results demonstrate that visual working memory is far from lossless: while basic visual features and complex objects can be maintained in a quite stable manner over time, these representations are still subject to noise accumulation and complete termination. (PsycINFO Database Record

The development of real-time stability supports visual working memory performance: Young children's feature binding can be improved through perceptual structure

Working memory is a basic cognitive process that predicts higher-level skills. A central question in theories of working memory development is the generality of the mechanisms proposed to explain improvements in performance. Prior theories have been closely tied to particular tasks and/or age groups, limiting their generalizability. The cognitive dynamics theory of visual working memory development has been proposed to overcome this limitation. From this perspective, developmental improvements arise through the coordination of cognitive processes to meet demands of different behavioral tasks. This notion is described as real-time stability, and can be probed through experiments that assess how changing task demands impact children's performance. The current studies test this account by probing visual working memory for colors and shapes in a change detection task that compares detection of changes to new features versus swaps in color-shape binding. In Experiment 1, 3- to 4-year-old children showed impairments specific to binding swaps, as predicted by decreased real-time stability early in development; 5- to 6-year-old children showed a slight advantage on binding swaps, but 7- to 8-year-old children and adults showed no difference across trial types. Experiment 2 tested the proposed explanation of young children's binding impairment through added perceptual structure, which supported the stability and precision of feature localization in memory-a process key to detecting binding swaps. This additional structure improved young children's binding swap detection, but not new-feature detection or adults' performance. These results provide further evidence for the cognitive dynamics and real-time stability explanation of visual working memory development. (PsycINFO Database Record

Applications of Dynamic Systems Theory to Cognition and Development: New Frontiers

A central goal in developmental science is to explain the emergence of new behavioral forms. Researchers consider potential sources of behavioral change depending partly on their theoretical perspective. This chapter reviews one perspective, dynamic systems theory, which emphasizes the interactions among multiple components to drive behavior and developmental change. To illustrate the central concepts of dynamic systems theory, we describe empirical and computational studies from a range of domains, including motor development, the Piagetian A-not-B task, infant visual recognition, visual working memory capacity, and language learning. We conclude by advocating for a broader application of dynamic systems approaches to understanding cognitive and behavioral development, laying out the remaining barriers we see and suggested ways to overcome them.

A complementary role of intracortical inhibition in age-related tactile degradation and its remodelling in humans

Many attempts are currently underway to restore age-related degraded perception, however, the link between restored perception and remodeled brain function remains elusive. To understand remodeling of age-related cortical reorganization we combined functional magnetic resonance imaging (fMRI) with assessments of tactile acuity, perceptual learning, and computational modeling. We show that aging leads to tactile degradation parallel to enhanced activity in somatosensory cortex. Using a neural field model we reconciled the empirical age-effects by weakening of cortical lateral inhibition. Using perceptual learning, we were able to partially restore tactile acuity, which however was not accompanied by the expected attenuation of cortical activity, but by a further enhancement. The neural field model reproduced these learning effects solely through a weakening of the amplitude of inhibition. These findings suggest that the restoration of age-related degraded tactile acuity on the cortical level is not achieved by re-strengthening lateral inhibition but by further weakening intracortical inhibition.

The Development of Attention Systems and Working Memory in Infancy

In this article, we review research and theory on the development of attention and working memory in infancy using a developmental cognitive neuroscience framework. We begin with a review of studies examining the influence of attention on neural and behavioral correlates of an earlier developing and closely related form of memory (i.e., recognition memory). Findings from studies measuring attention utilizing looking measures, heart rate, and event-related potentials (ERPs) indicate significant developmental change in sustained and selective attention across the infancy period. For example, infants show gains in the magnitude of the attention related response and spend a greater proportion of time engaged in attention with increasing age (Richards and Turner, 2001). Throughout infancy, attention has a significant impact on infant performance on a variety of tasks tapping into recognition memory; however, this approach to examining the influence of infant attention on memory performance has yet to be utilized in research on working memory. In the second half of the article, we review research on working memory in infancy focusing on studies that provide insight into the developmental timing of significant gains in working memory as well as research and theory related to neural systems potentially involved in working memory in early development. We also examine issues related to measuring and distinguishing between working memory and recognition memory in infancy. To conclude, we discuss relations between the development of attention systems and working memory.

Beyond slots and resources: grounding cognitive concepts in neural dynamics

Research over the past decade has suggested that the ability to hold information in visual working memory (VWM) may be limited to as few as three to four items. However, the precise nature and source of these capacity limits remains hotly debated. Most commonly, capacity limits have been inferred from studies of visual change detection, in which performance declines systematically as a function of the number of items that participants must remember. According to one view, such declines indicate that a limited number of fixed-resolution representations are held in independent memory "slots." Another view suggests that such capacity limits are more apparent than real, but emerge as limited memory resources are distributed across more to-be-remembered items. Here we argue that, although both perspectives have merit and have generated and explained impressive amounts of empirical data, their central focus on the representations--rather than processes--underlying VWM may ultimately limit continuing progress in this area. As an alternative, we describe a neurally grounded, process-based approach to VWM: the dynamic field theory. Simulations demonstrate that this model can account for key aspects of behavioral performance in change detection, in addition to generating novel behavioral predictions that have been confirmed experimentally. Furthermore, we describe extensions of the model to recall tasks, the integration of visual features, cognitive development, individual differences, and functional imaging studies of VWM. We conclude by discussing the importance of grounding psychological concepts in neural dynamics, as a first step toward understanding the link between brain and behavior.

The emergent executive: a dynamic field theory of the development of executive function

Executive function (EF) is a central aspect of cognition that undergoes significant changes in early childhood. Changes in EF in early childhood are robustly predictive of academic achievement and general quality of life measures later in adulthood. We present a dynamic neural field (DNF) model that provides a process-based account of behavior and developmental change in a key task used to probe the early development of executive function—the Dimensional Change Card Sort (DCCS) task. In the DCCS, children must flexibly switch from sorting cards either by shape or color to sorting by the other dimension. Typically, 3-year-olds, but not 5-year-olds, lack the flexibility to do so and perseverate on the first set of rules when instructed to switch. Using the DNF model, we demonstrate how rule-use and behavioral flexibility come about through a form of dimensional attention. Further, developmental change is captured by increasing the robustness and precision of dimensional attention. Note that although this enables the model to effectively switch tasks, the dimensional attention system does not “know” the details of task-specific performance. Rather, correct performance emerges as a property of system–wide interactions. We show how this captures children’s behavior in quantitative detail across 14 versions of the DCCS task. Moreover, we successfully test a set of novel predictions with 3-year-old children from a version of the task not explained by other theories.

Temporal resolution of figures and grounds

Recent studies have demonstrated that establishing figure-ground organization influences other perceptual processes. Specifically, figures undergo perceptual processing earlier than ground regions (Lester, Hecht, & Vecera, 2009), and they are processed for longer durations relative to ground regions (Hecht & Vecera, 2011). One potential consequence of figures' extended processing is degraded temporal resolution compared to ground regions. To test this hypothesis, observers completed a modified flicker-fusion task while viewing either displays that contained well-defined figures and grounds or displays that were ambiguous. As evidenced by increased sensitivity for flickering targets on the ground regions, the current results support the claim that figures have poorer temporal resolution than ground regions.

The co-development of looking dynamics and discrimination performance

The study of looking dynamics and discrimination form the backbone of developmental science and are central processes in theories of infant cognition. Looking dynamics and discrimination change dramatically across the 1st year of life. Surprisingly, developmental changes in looking and discrimination have not been studied together. Recent simulations of a dynamic neural field (DNF) model of infant looking and memory suggest that looking and discrimination do change together over development and arise from a single neurodevelopmental mechanism. We probed this claim by measuring looking dynamics and discrimination along continuous, metrically organized dimensions in 5-, 7-, and 10-month-old infants (N = 119). The results showed that looking dynamics and discrimination changed together over development and are linked within individuals. Quantitative simulations of a DNF model provide insights into the processes that underlie developmental change in looking dynamics and discrimination. Simulation results support the view that these changes might arise from a single neurodevelopmental mechanism.

Autonomous visual exploration creates developmental change in familiarity and novelty seeking behaviors

What motivates children to radically transform themselves during early development? We addressed this question in the domain of infant visual exploration. Over the first year, infants' exploration shifts from familiarity to novelty seeking. This shift is delayed in preterm relative to term infants and is stable within individuals over the course of the first year. Laboratory tasks have shed light on the nature of this familiarity-to-novelty shift, but it is not clear what motivates the infant to change her exploratory style. We probed this by letting a Dynamic Neural Field (DNF) model of visual exploration develop itself via accumulating experience in a virtual world. We then situated it in a canonical laboratory task. Much like infants, the model exhibited a familiarity-to-novelty shift. When we manipulated the initial conditions of the model, the model's performance was developmentally delayed much like preterm infants. This delay was overcome by enhancing the model's experience during development. We also found that the model's performance was stable at the level of the individual. Our simulations indicate that novelty seeking emerges with no explicit motivational source via the accumulation of visual experience within a complex, dynamical exploratory system.

Modeling the influences of nanoparticles on neural field oscillations in thalamocortical networks

The purpose of this study is twofold. First, we present a simplified multiscale modeling approach integrating activity on the scale of ionic channels into the spatiotemporal scale of neural field potentials: Resting upon a Hodgkin-Huxley based single cell model we introduced a neuronal feedback circuit based on the Llinás-model of thalamocortical activity and binding, where all cell specific intrinsic properties were adopted from patch-clamp measurements. In this paper, we expand this existing model by integrating the output to the spatiotemporal scale of field potentials. Those are supposed to originate from the parallel activity of a variety of synchronized thalamocortical columns at the quasi-microscopic level, where the involved neurons are gathered together in units. Second and more important, we study the possible effects of nanoparticles (NPs) that are supposed to interact with thalamic cells of our network model. In two preliminary studies we demonstrated in vitro and in vivo effects of NPs on the ionic channels of single neurons and thereafter on neuronal feedback circuits. By means of our new model we assumed now NPs induced changes on the ionic currents of the involved thalamic neurons. Here we found extensive diversified pattern formations of neural field potentials when comparing to the modeled activity without neuromodulating NPs addition. This model provides predictions about the influences of NPs on spatiotemporal neural field oscillations in thalamocortical networks. These predictions can be validated by high spatiotemporal resolution electrophysiological measurements like voltage sensitive dyes and multiarray recordings.

Autonomy in action: linking the act of looking to memory formation in infancy via dynamic neural fields

Looking is a fundamental exploratory behavior by which infants acquire knowledge about the world. In theories of infant habituation, however, looking as an exploratory behavior has been deemphasized relative to the reliable nature with which looking indexes active cognitive processing. We present a new theory that connects looking to the dynamics of memory formation and formally implement this theory in a Dynamic Neural Field model that learns autonomously as it actively looks and looks away from a stimulus. We situate this model in a habituation task and illustrate the mechanisms by which looking, encoding, working memory formation, and long-term memory formation give rise to habituation across multiple stimulus and task contexts. We also illustrate how the act of looking and the temporal dynamics of learning affect each other. Finally, we test a new hypothesis about the sources of developmental differences in looking.

Models provide specificity: Testing a proposed mechanism of visual working memory capacity development

Numerous studies have established that visual working memory has a limited capacity, and that capacity increases during childhood. However, debate continues over the source of capacity limits and its developmental increase. Simmering (2008) adapted a computational model of spatial cognitive development, the Dynamic Field Theory, to explain not only the source of capacity limitations but also the developmental mechanism. According to the model, capacity is limited by the balance between excitation and inhibition that maintains multiple neural representations simultaneously. Moreover, development is implemented according to the Spatial Precision Hypothesis, which proposes that excitatory and inhibitory connections strengthen throughout early childhood. Critically, these changes in connectivity result in increasing precision and stability of neural representations over development. Here we test this developmental mechanism by probing children's memory in a single-item change detection task. Results confirmed the model's predictions, providing further support for this account of visual working memory capacity development.

A neurobehavioral model of flexible spatial language behaviors

We propose a neural dynamic model that specifies how low-level visual processes can be integrated with higher level cognition to achieve flexible spatial language behaviors. This model uses real-word visual input that is linked to relational spatial descriptions through a neural mechanism for reference frame transformations. We demonstrate that the system can extract spatial relations from visual scenes, select items based on relational spatial descriptions, and perform reference object selection in a single unified architecture. We further show that the performance of the system is consistent with behavioral data in humans by simulating results from 2 independent empirical studies, 1 spatial term rating task and 1 study of reference object selection behavior. The architecture we present thereby achieves a high degree of task flexibility under realistic stimulus conditions. At the same time, it also provides a detailed neural grounding for complex behavioral and cognitive processes.

Contributions of Dynamic Systems Theory to Cognitive Development

This paper examines the contributions of dynamic systems theory to the field of cognitive development, focusing on modeling using dynamic neural fields. A brief overview highlights the contributions of dynamic systems theory and the central concepts of dynamic field theory (DFT). We then probe empirical predictions and findings generated by DFT around two examples-the DFT of infant perseverative reaching that explains the Piagetian A-not-B error, and the DFT of spatial memory that explain changes in spatial cognition in early development. A systematic review of the literature around these examples reveals that computational modeling is having an impact on empirical research in cognitive development; however, this impact does not extend to neural and clinical research. Moreover, there is a tendency for researchers to interpret models narrowly, anchoring them to specific tasks. We conclude on an optimistic note, encouraging both theoreticians and experimentalists to work toward a more theory-driven future.

Connecting neural coding to number cognition: a computational account

The current study presents a series of computational simulations that demonstrate how the neural coding of numerical magnitude may influence number cognition and development. This includes behavioral phenomena cataloged in cognitive literature such as the development of numerical estimation and operational momentum. Though neural research has begun to describe neural coding of number, it is unclear how specific characteristics of the neural coding may relate to the expansive list of behavioral phenomena in the development of number cognition. The following study considers several possibilities.

A neural mechanism for coordinate transformation predicts pre-saccadic remapping

Whenever we shift our gaze, any location information encoded in the retinocentric reference frame that is predominant in the visual system is obliterated. How is spatial memory retained across gaze changes? Two different explanations have been proposed: Retinocentric information may be transformed into a gaze-invariant representation through a mechanism consistent with gain fields observed in parietal cortex, or retinocentric information may be updated in anticipation of the shift expected with every gaze change, a proposal consistent with neural observations in LIP. The explanations were considered incompatible with each other, because retinocentric update is observed before the gaze shift has terminated. Here, we show that a neural dynamic mechanism for coordinate transformation can also account for retinocentric updating. Our model postulates an extended mechanism of reference frame transformation that is based on bidirectional mapping between a retinocentric and a body-centered representation and that enables transforming multiple object locations in parallel. The dynamic coupling between the two reference frames generates a shift of the retinocentric representation for every gaze change. We account for the predictive nature of the observed remapping activity by using the same kind of neural mechanism to generate an internal representation of gaze direction that is predictively updated based on corollary discharge signals. We provide evidence for the model by accounting for a series of behavioral and neural experimental observations.

Grounding word learning in space

Humans and objects, and thus social interactions about objects, exist within space. Words direct listeners' attention to specific regions of space. Thus, a strong correspondence exists between where one looks, one's bodily orientation, and what one sees. This leads to further correspondence with what one remembers. Here, we present data suggesting that children use associations between space and objects and space and words to link words and objects—space binds labels to their referents. We tested this claim in four experiments, showing that the spatial consistency of where objects are presented affects children's word learning. Next, we demonstrate that a process model that grounds word learning in the known neural dynamics of spatial attention, spatial memory, and associative learning can capture the suite of results reported here. This model also predicts that space is special, a prediction supported in a fifth experiment that shows children do not use color as a cue to bind words and objects. In a final experiment, we ask whether spatial consistency affects word learning in naturalistic word learning contexts. Children of parents who spontaneously keep objects in a consistent spatial location during naming interactions learn words more effectively. Together, the model and data show that space is a powerful tool that can effectively ground word learning in social contexts.

Stronger neural dynamics capture changes in infants' visual working memory capacity over development

Visual working memory (VWM) capacity has been studied extensively in adults, and methodological advances have enabled researchers to probe capacity limits in infancy using a preferential looking paradigm. Evidence suggests that capacity increases rapidly between 6 and 10 months of age. To understand how the VWM system develops, we must understand the relationship between the looking behavior used to study VWM and underlying cognitive processes. We present a dynamic neural field model that captures both real-time and developmental processes underlying performance. Three simulation experiments show how looking is linked to VWM processes during infancy and how developmental changes in performance could arise through increasing neural connectivity. These results provide insight into the sources of capacity limits and VWM development more generally.

A New Clustering Approach on the Basis of Dynamical Neural Field

In this letter, we present a new hierarchical clustering approach based on the evolutionary process of Amari's dynamical neural field model. Dynamical neural field theory provides a theoretical framework macroscopically describing the activity of neuron ensemble. Based on it, our clustering approach is essentially close to the neurophysiological nature of perception. It is also computationally stable, insensitive to noise, flexible, and tractable for data with complex structure. Some examples are given to show the feasibility.

Twenty years and going strong: A dynamic systems revolution in motor and cognitive development

This article reviews the major contributions of dynamic systems theory in advancing thinking about development, the empirical insights the theory has generated, and the key challenges for the theory on the horizon. The first section discusses the emergence of dynamic systems theory in developmental science, the core concepts of the theory, and the resonance it has with other approaches that adopt a systems metatheory. The second section reviews the work of Esther Thelen and colleagues, who revolutionized how researchers think about the field of motor development. It also reviews recent extensions of this work to the domain of cognitive development. Here, the focus is on dynamic field theory, a formal, neurally grounded approach that has yielded novel insights into the embodied nature of cognition. The final section proposes that the key challenge on the horizon is to formally specify how interactions among multiple levels of analysis interact across multiple time scales to create developmental change.

Biased feedback in spatial recall yields a violation of delta rule learning

This study investigates whether inductive processes influencing spatial memory performance generalize to supervised learning scenarios with differential feedback. After providing a location memory response in a spatial recall task, participants received visual feedback showing the target location. In critical blocks, feedback was systematically biased either 4 degrees toward the vertical axis (toward condition) or 4 degrees farther away from the vertical axis (away condition). Results showed that the weaker teaching signal (i.e., a smaller difference between the remembered location and the feedback location) produced a stronger experience-dependent change over blocks in the away condition than in the toward condition. This violates delta rule learning. Subsequent simulations of the dynamic field theory of spatial cognition provide a theoretically unified account of these results.

Selective attention and attention switching: towards a unified developmental approach

We review and relate two literatures on the development of attention in children: one concerning flexible attention switching and the other concerning selective attention. The first is a growing literature on preschool children's performances in an attention-switching task indicating that children become more flexible in their attentional control during the preschool years. The second literature encompasses a large and robust set of phenomena for the same developmental period that indicates a protracted course of development for selective attention in children. We ask whether developmental changes in processes of selective attention may contribute to more flexible attention switching. We consider the two sets of phenomena with respect to this question and propose an empirical agenda for their joint study that may lead ultimately to a unified account of the development of selective attention and attention switching.

The relationship between the perception of axes of symmetry and spatial memory during early childhood

Early in development, there is a transition in spatial working memory (SWM). When remembering a location in a homogeneous space (e.g., in a sandbox), young children are biased toward the midline symmetry axis of the space. Over development, a transition occurs that leads to older children being biased away from midline. The dynamic field theory (DFT) explains this transition in biases as being caused by a change in the precision of neural interaction in SWM and improvements in the perception of midline. According to the DFT, young children perceive midline, but there is a quantitative improvement in the perception of midline over development. In the experiment reported here, children and adults needed to determine on which half of a large monitor a target was located. In support of the DFT, even the youngest children performed above chance at most locations, but performance also improved gradually with age.

The role of experience in location estimation: Target distributions shift location memory biases

Research based on the Category Adjustment model concluded that the spatial distribution of target locations does not influence location estimation responses [Huttenlocher, J., Hedges, L., Corrigan, B., & Crawford, L. E. (2004). Spatial categories and the estimation of location. Cognition, 93, 75-97]. This conflicts with earlier results showing that location estimation is biased relative to the spatial distribution of targets [Spencer, J. P., & Hund, A. M. (2002). Prototypes and particulars: Geometric and experience-dependent spatial categories. Journal of Experimental Psychology: General, 131, 16-37]. Here, we resolve this controversy by using a task based on Huttenlocher et al. (Experiment 4) with minor modifications to enhance our ability to detect experience-dependent effects. Results after the first block of trials replicate the pattern reported in Huttenlocher et al. After additional experience, however, participants showed biases that significantly shifted according to the target distributions. These results are consistent with the Dynamic Field Theory, an alternative theory of spatial cognition that integrates long-term memory traces across trials relative to the perceived structure of the task space.

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.

Swing it to the left, swing it to the right: enacting flexible spatial language using a neurodynamic framework

Research is continually expanding the empirical and theoretical picture of embodiment and dynamics in language. To date, however, a formalized neural dynamic framework for embodied linguistic processes has yet to emerge. To advance embodied theories of language, the present work develops a formalized neural dynamic framework of spatial language that explicitly integrates linguistic processes and dynamic sensory-motor systems. We then implement and test our spatial language architecture on a robotic platform continuously linked to real-time camera input. In a suite of tasks using everyday objects we demonstrate the framework's capacity for both contextually-dependent behavioral flexibility and the seamless integration of spatial, non-spatial, and symbolic representations. To our knowledge this is the first unified, neurally-grounded architecture integrating these processes and behaviors.

Corresponding delay-dependent biases in spatial language and spatial memory

The present study addresses the relationship between linguistic and non-linguistic spatial representations. In three experiments we probe spatial language and spatial memory at the same time points in the task sequence. Experiments 1 and 2 show analogous delay-dependent biases in spatial language and spatial memory. Experiment 3 extends this correspondence, showing that additional perceptual structure along the vertical axis reduces delay-dependent effects in both tasks. These results indicate that linguistic and non-linguistic spatial systems depend on shared underlying representational processes. In addition, we also address how these delay-dependent biases can arise within a single theoretical framework without positing differing prototypes for linguistic and non-linguistic spatial systems.

Estimating distance in real and virtual environments: Does order make a difference?

In this investigation, we examined how the order in which people experience real and virtual environments influences their distance estimates. Participants made two sets of distance estimates in one of the following conditions: (1) real environment first, virtual environment second; (2) virtual environment first, real environment second; (3) real environment first, real environment second; or (4) virtual environment first, virtual environment second. In Experiment 1, the participants imagined how long it would take to walk to targets in real and virtual environments. The participants' first estimates were significantly more accurate in the real than in the virtual environment. When the second environment was the same as the first environment (real-real and virtual-virtual), the participants' second estimates were also more accurate in the real than in the virtual environment. When the second environment differed from the first environment (real-virtual and virtual-real), however, the participants' second estimates did not differ significantly across the two environments. A second experiment, in which the participants walked blindfolded to targets in the real environment and imagined how long it would take to walk to targets in the virtual environment, replicated these results. These subtle yet persistent order effects suggest that memory can play an important role in distance perception.

A layered neural architecture for the consolidation, maintenance, and updating of representations in visual working memory

Many everyday tasks rely on our ability to hold information about a perceived stimulus in mind after that stimulus is no longer visible and to compare this information with incoming perceptual information. This ability has been shown to rely on a short-term form of visual memory that has come to be known as visual working memory. Research and theory at both the behavioral and neural levels has begun to provide important insights into the basic properties of the neuro-cognitive systems underlying specific aspects of this form of memory. However, to date, no neurally-plausible theory has been proposed that addresses both the storage of information in working memory and the comparison process in a single framework. The present paper presents a layered neural field architecture that addresses these limitations. In a series of simulations, we show how the model can be used to capture each of the components underlying performance in simple visual comparison tasks--from the encoding, consolidation, and maintenance of information in working memory, to comparison and updating in response to changed inputs. Importantly, the proposed model demonstrates how these elementary perceptual and cognitive functions emerge from the coordinated activity of an integrated, dynamic neural system.

Redundancy, self-motion, and motor control

Outside the laboratory, human movement typically involves redundant effector systems. How the nervous system selects among the task-equivalent solutions may provide insights into how movement is controlled. We propose a process model of movement generation that accounts for the kinematics of goal-directed pointing movements performed with a redundant arm. The key element is a neuronal dynamics that generates a virtual joint trajectory. This dynamics receives input from a neuronal timer that paces end-effector motion along its path. Within this dynamics, virtual joint velocity vectors that move the end effector are dynamically decoupled from velocity vectors that do not. Moreover, the sensed real joint configuration is coupled back into this neuronal dynamics, updating the virtual trajectory so that it yields to task-equivalent deviations from the dynamic movement plan. Experimental data from participants who perform in the same task setting as the model are compared in detail to the model predictions. We discover that joint velocities contain a substantial amount of self-motion that does not move the end effector. This is caused by the low impedance of muscle joint systems and by coupling among muscle joint systems due to multiarticulatory muscles. Back-coupling amplifies the induced control errors. We establish a link between the amount of self-motion and how curved the end-effector path is. We show that models in which an inverse dynamics cancels interaction torques predict too little self-motion and too straight end-effector paths.