A dynamic neural field model of temporal order judgments

Temporal ordering of events is biased, or influenced, by perceptual organization—figure–ground organization—and by spatial attention. For example, within a region assigned figural status or at an attended location, onset events are processed earlier (Lester, Hecht, & Vecera, 2009; Shore, Spence, & Klein, 2001), and offset events are processed for longer durations (Hecht & Vecera, 2011; Rolke, Ulrich, & Bausenhart, 2006). Here, we present an extension of a dynamic field model of change detection (Johnson, Spencer, Luck, & Schöner, 2009; Johnson, Spencer, & Schöner, 2009) that accounts for both the onset and offset performance for figural and attended regions. The model posits that neural populations processing the figure are more active, resulting in a peak of activation that quickly builds toward a detection threshold when the onset of a target is presented. This same enhanced activation for some neural populations is maintained when a present target is removed, creating delays in the perception of the target’s offset. We discuss the broader implications of this model, including insights regarding how neural activation can be generated in response to the disappearance of information. (PsycINFO Database Record (c) 2015 APA, all rights reserved

The Development of Working Memory

Working memory is a central cognitive system that plays a key role in development, with working memory capacity and speed of processing increasing as children move from infancy through adolescence. Here, I focus on two questions: What neural processes underlie working memory, and how do these processes change over development? Answers to these questions lie in computer simulations of neural-network models that shed light on how development happens. These models open up new avenues for optimizing clinical interventions aimed at boosting the working memory abilities of at-risk infants

Making sense of developmental dynamics

This commentary on the developmental dynamics special issue in Human Development identifies a set of common principles shared in the target articles. These common principles highlight how the dynamic approach has matured in the last 20 years into a mainstream developmental perspective. The commentary then discusses three core challenges facing the dynamic approach – the challenge of clear communication, the challenge of clearly defining learning in development, and the challenge of embracing the dynamics of neural systems. The commentary concludes with a charge inspired by Esther Thelen’s work – to be relevant in the lives of children

Prefrontal cortex activation supports the emergence of early stone age toolmaking skill

Trends toward encephalization and technological complexity ∼1.8 million years ago may signify cognitive development in the genus Homo. Using functional near-infrared spectroscopy, we measured relative brain activity of 33 human subjects at three different points as they learned to make replicative Oldowan and Acheulian Early Stone Age tools. Here we show that the more complex early Acheulian industry recruits left dorsolateral prefrontal cortex when skills related to this task are first being learned. Individuals with increased activity in this area are the most proficient at the Acheulian task. The Oldowan task, on the other hand, transitions to automatic processing in less than 4 h of training. Individuals with increased sensorimotor activity demonstrate the most skill at this task. We argue that enhanced working memory abilities received positive selection in response to technological needs during the early Pleistocene, setting Homo on the path to becoming human

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

Evaluating motion processing algorithms for use with functional near-infrared spectroscopy data from young children

Motion artifacts are often a significant component of the measured signal in functional near-infrared spectroscopy (fNIRS) experiments. A variety of methods have been proposed to address this issue, including principal components analysis (PCA), correlation-based signal improvement (CBSI), wavelet filtering, and spline interpolation. The efficacy of these techniques has been compared using simulated data; however, our understanding of how these techniques fare when dealing with task-based cognitive data is limited. Brigadoi et al. compared motion correction techniques in a sample of adult data measured during a simple cognitive task. Wavelet filtering showed the most promise as an optimal technique for motion correction. Given that fNIRS is often used with infants and young children, it is critical to evaluate the effectiveness of motion correction techniques directly with data from these age groups. This study addresses that problem by evaluating motion correction algorithms implemented in HomER2. The efficacy of each technique was compared quantitatively using objective metrics related to the physiological properties of the hemodynamic response. Results showed that targeted PCA (tPCA), spline, and CBSI retained a higher number of trials. These techniques also performed well in direct head-to-head comparisons with the other approaches using quantitative metrics. The CBSI method corrected many of the artifacts present in our data; however, this approach produced sometimes unstable HRFs. The targeted PCA and spline methods proved to be the most robust, performing well across all comparison metrics. When compared head to head, tPCA consistently outperformed spline. We conclude, therefore, that tPCA is an effective technique for correcting motion artifacts in fNIRS data from young children

Reaching Into Response Selection: Stimulus and Response Similarity Influence Central Operations

To behave adaptively in complex and dynamic environments, one must link perception and action to satisfy internal states, a process known as response selection (RS). A largely unexplored topic in the study of RS is how interstimulus and interresponse similarity affect performance. To examine this issue, we manipulated stimulus similarity by using colors that were either similar or dissimilar and manipulated response similarity by having participants move a mouse cursor to locations that were either close together or far apart. Stimulus and response similarity produced an interaction such that the mouse trajectory showed the greatest curvature when both were similar, a result obtained under task conditions emphasizing speed and conditions emphasizing accuracy. These findings are inconsistent with symbolic look-up accounts of RS but are consistent with central codes incorporating metrical properties of both stimuli and responses

Empirical tests of a brain-based model of executive function development

Executive function (EF) plays a foundational role in development. A brain-based model of EF development is probed for the experiences that strengthen EF in the dimensional change card sort task in which children sort cards by one rule and then are asked to switch to another. Three-year-olds perseverate on the first rule, failing the task, whereas 4-year-olds pass. Three predictions of the model are tested to help 3-year-olds (N = 54) pass. Experiment 1 shows that experience with shapes and the label “shape” helps children. Experiment 2 shows that experience with colors—without a label—helps children. Experiment 3 shows that experience with colors induces dimensional attention. The implications of this work for early intervention are discussed