Formal theories clarify the complex: Generalizing a neural process account of the interaction of visual exploration and word learning in infancy.

The interaction of visual exploration and auditory processing is central to early cognitive development, supporting object discrimination, categorization, and word learning. Research has shown visual-auditory interactions to be complex, created from multiple processes and changing over multiple timescales. To better understand these interactions, we generalize a formal neural process model of early word learning to two studies examining how words impact 9- to 22-month-olds' attention to novelty. These simulations clarify the origin and nature of previously demonstrated effects of labels on visual exploration and the basis of mutual exclusivity effects in word learning. We use our findings to discuss key questions for this special section: what makes a good theory and how should formal theories interface with empirical paradigms and findings?

Stunting in infancy is associated with atypical activation of working memory and attention networks.

Stunting is associated with poor long-term cognitive, academic and economic outcomes, yet the mechanisms through which stunting impacts cognition in early development remain unknown. In a first-ever neuroimaging study conducted on infants from rural India, we demonstrate that stunting impacts a critical, early-developing cognitive system-visual working memory. Stunted infants showed poor visual working memory performance and were easily distractible. Poor performance was associated with reduced engagement of the left anterior intraparietal sulcus, a region involved in visual working memory maintenance and greater suppression in the right temporoparietal junction, a region involved in attentional shifting. When assessed one year later, stunted infants had lower problem-solving scores, while infants of normal height with greater left anterior intraparietal sulcus activation showed higher problem-solving scores. Finally, short-for-age infants with poor physical growth indices but good visual working memory performance showed more positive outcomes suggesting that intervention efforts should focus on improving working memory and reducing distractibility in infancy.

Language Exposure and Brain Myelination in Early Development.

The language environment to which children are exposed has an impact on later language abilities as well as on brain development; however, it is unclear how early such impacts emerge. This study investigates the effects of children's early language environment and socioeconomic status (SES) on brain structure in infancy at 6 and 30 months of age (both sexes included). We used magnetic resonance imaging to quantify concentrations of myelin in specific fiber tracts in the brain. Our central question was whether Language Environment Analysis (LENA) measures from in-home recording devices and SES measures of maternal education predicted myelin concentrations over the course of development. Results indicate that 30-month-old children exposed to larger amounts of in-home adult input showed more myelination in the white matter tracts most associated with language. Right hemisphere regions also show an association with SES, with older children from more highly educated mothers and exposed to more adult input, showing greater myelin concentrations in language-related areas. We discuss these results in relation to the current literature and implications for future research.SIGNIFICANCE STATEMENT This is the first study to look at how brain myelination is impacted by language input and socioeconomic status early in development. We find robust relationships of both factors in language-related brain areas at 30 months of age.

Poor air quality is associated with impaired visual cognition in the first two years of life: A longitudinal investigation.

Background: Poor air quality has been linked to cognitive deficits in children, but this relationship has not been examined in the first year of life when brain growth is at its peak. Methods: We measured in-home air quality focusing on particulate matter with diameter of <2.5 µm (PM2.5) and infants' cognition longitudinally in a sample of families from rural India. Results: Air quality was poorer in homes that used solid cooking materials. Infants from homes with poorer air quality showed lower visual working memory scores at 6 and 9 months of age and slower visual processing speed from 6 to 21 months when controlling for family socio-economic status. Conclusions: Thus, poor air quality is associated with impaired visual cognition in the first two years of life, consistent with animal studies of early brain development. We demonstrate for the first time an association between air quality and cognition in the first year of life using direct measures of in-home air quality and looking-based measures of cognition. Because indoor air quality was linked to cooking materials in the home, our findings suggest that efforts to reduce cooking emissions should be a key target for intervention. Funding: Bill & Melinda Gates Foundation grant OPP1164153.

Neural interactions in working memory explain decreased recall precision and similarity-based feature repulsion.

Over the last several years, the study of working memory (WM) for simple visual features (e.g., colors, orientations) has been dominated by perspectives that assume items in WM are stored independently of one another. Evidence has revealed, however, systematic biases in WM recall which suggest that items in WM interact during active maintenance. In the present study, we report two experiments that replicate a repulsion bias between metrically similar colors during active storage in WM. We also observed that metrically similar colors were stored with lower resolution than a unique color held actively in mind at the same time. To account for these effects, we report quantitative simulations of two novel neurodynamical models of WM. In both models, the unique behavioral signatures reported here emerge directly from laterally-inhibitory neural interactions that serve to maintain multiple, distinct neural representations throughout the WM delay period. Simulation results show that the full pattern of empirical findings was only obtained with a model that included an elaborated spatial pathway with sequential encoding of memory display items. We discuss implications of our findings for theories of visual working memory more generally.

Testing predictions of a neural process model of visual attention in infancy across competitive and non-competitive contexts.

A key question in early development is how changes in neural systems give rise to changes in infants' behavior. We examine this question by testing predictions of a dynamic field (DF) model of infant spatial attention. We tested 5-, 7-, and 10-month-old infants in the Infant Orienting With Attention (IOWA) task containing the original non-competitive cue conditions (when a central stimulus disappeared before a cue onset) and new competitive cue conditions (when a central stimulus remained visible throughout the trial). This allowed testing of five model predictions: (1) that orienting accuracy would be higher and (2) reaction times would be slower for all competitive conditions; (3) that all infants would be slower to orient in the competitive conditions, though (4) older infants would show the strongest competition costs; and (5) that reaction times would be particularly slow for un-cued competitive conditions. Four of these five predictions were supported, and the remaining prediction was supported in part. We next examined fits of the model to the expanded task. New simulation results reveal close fits to the present findings after parameter modification. Critically, developmental parameters of the model were not altered, providing support for the DF model's account of neuro-developmental change.

Word-Object Learning via Visual Exploration in Space (WOLVES): A neural process model of cross-situational word learning.

Infants, children, and adults have been shown to track co-occurrence across ambiguous naming situations to infer the referents of new words. The extensive literature on this cross-situational word learning (CSWL) ability has produced support for two theoretical accounts-associative learning (AL) and hypothesis testing (HT)-but no comprehensive model of the behavior. We propose Word-Object Learning via Visual Exploration in Space (WOLVES), an implementation-level account of CSWL grounded in real-time psychological processes of memory and attention that explicitly models the dynamics of looking at a moment-to-moment scale and learning across trials. We use WOLVES to capture data from 12 studies of CSWL with adults and children, thereby providing a comprehensive account of data purported to support both AL and HT accounts. Direct model comparison shows that WOLVES performs well relative to two competitor models. In particular, WOLVES captures more data than the competitor models (132 vs. 69 data values) and fits the data better than the competitor models (e.g., lower percent error scores for 12 of 17 conditions). Moreover, WOLVES generalizes more accurately to three "held-out" experiments, although a model by Kachergis et al. (2012) fares better on another metric of generalization (Akaike Information Criterion [AIC]/Bayesian Information Criterion [BIC]). Critically, we offer the first developmental account of CSWL, providing insights into how memory processes change from infancy through adulthood. WOLVES shows that visual exploration and selective attention in CSWL are both dependent on and indicative of learning within a task-specific context. Furthermore, learning is driven by real-time synchrony of words and gaze and constrained by memory processes over multiple timescales. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Probing the Neural Systems Underlying Flexible Dimensional Attention.

Flexibly shifting attention between stimulus dimensions (e.g., shape and color) is a central component of regulating cognition for goal-based behavior. In the present report, we examine the functional roles of different cortical regions by manipulating two demands on task switching that have been confounded in previous studies-shifting attention between visual dimensions and resolving conflict between stimulus-response representations. Dimensional shifting was manipulated by having participants shift attention between dimensions (either shape or color; dimension shift) or keeping the task-relevant dimension the same (dimension same). Conflict between stimulus-response representations was manipulated by creating conflict between response-driven associations from the previous set of trials and the stimulus-response mappings on the current set of trials (e.g., making a leftward response to a red stimulus during the previous task, but being required to make a rightward response to a red stimulus in the current task; stimulus-response conflict), or eliminating conflict by altering the features of the dimension relevant to the sorting rule (stimulus-response no-conflict). These manipulations revealed activation along a network of frontal, temporal, parietal, and occipital cortices. Specifically, dimensional shifting selectively activated frontal and parietal regions. Stimulus-response conflict, on the other hand, produced decreased activation in temporal and occipital cortices. Occipital regions demonstrated a complex pattern of activation that was sensitive to both stimulus-response conflict and dimensional attention switching. These results provide novel information regarding the distinct role that frontal cortex plays in shifting dimensional attention and posterior cortices play in resolving conflict at the stimulus level.

Speech planning and execution in children who stutter: Preliminary findings from a fNIRS investigation.

Few studies have investigated the neural mechanisms underlying speech production in children who stutter (CWS), despite the critical importance of understanding these mechanisms closer to the time of stuttering onset. The relative contributions of speech planning and execution in CWS therefore are also unknown. Using functional near-infrared spectroscopy, the current study investigated neural mechanisms of planning and execution in a small sample of 9-12 year-old CWS and controls (N = 12) by implementing two tasks that manipulated speech planning and execution loads. Planning was associated with atypical activation in bilateral inferior frontal gyrus and right supramarginal gyrus. Execution was associated with atypical activation in bilateral precentral gyrus and inferior frontal gyrus, as well as right supramarginal gyrus and superior temporal gyrus. The CWS exhibited some activation patterns that were similar to the adults who stutter (AWS) as reported in our previous study: atypical planning in frontal areas including left inferior frontal gyrus and atypical execution in fronto-temporo-parietal regions including left precentral gyrus, and right inferior frontal, superior temporal, and supramarginal gyri. However, differences also emerged. Whereas CWS and AWS both appear to exhibit atypical activation in right inferior and supramarginal gyri during execution, only CWS appear to exhibit this same pattern during planning. In addition, the CWS appear to exhibit atypical activation in left inferior frontal and right precentral gyri related to execution, whereas AWS do not. These preliminary results are discussed in the context of possible impairments in sensorimotor integration and inhibitory control for CWS.

Learning words in space and time: Contrasting models of the suspicious coincidence effect.

In their 2007b Psychological Review paper, Xu and Tenenbaum found that early word learning follows the classic logic of the "suspicious coincidence effect:" when presented with a novel name ('fep') and three identical exemplars (three Labradors), word learners generalized novel names more narrowly than when presented with a single exemplar (one Labrador). Xu and Tenenbaum predicted the suspicious coincidence effect based on a Bayesian model of word learning and demonstrated that no other theory captured this effect. Recent empirical studies have revealed, however, that the effect is influenced by factors seemingly outside the purview of the Bayesian account. A process-based perspective correctly predicted that when exemplars are shown sequentially, the effect is eliminated or reversed (Spencer, Perone, Smith, & Samuelson, 2011). Here, we present a new, formal account of the suspicious coincidence effect using a generalization of a Dynamic Neural Field (DNF) model of word learning. The DNF model captures both the original finding and its reversal with sequential presentation. We compare the DNF model's performance with that of a more flexible version of the Bayesian model that allows both strong and weak sampling assumptions. Model comparison results show that the dynamic field account provides a better fit to the empirical data. We discuss the implications of the DNF model with respect to broader contrasts between Bayesian and process-level models.

How do neural processes give rise to cognition? Simultaneously predicting brain and behavior with a dynamic model of visual working memory.

There is consensus that activation within distributed functional brain networks underlies human thought. The impact of this consensus is limited, however, by a gap that exists between data-driven correlational analyses that specify where functional brain activity is localized using functional magnetic resonance imaging (fMRI), and neural process accounts that specify how neural activity unfolds through time to give rise to behavior. Here, we show how an integrative cognitive neuroscience approach may bridge this gap. In an exemplary study of visual working memory, we use multilevel Bayesian statistics to demonstrate that a neural dynamic model simultaneously explains behavioral data and predicts localized patterns of brain activity, outperforming standard analytic approaches to fMRI. The model explains performance on both correct trials and incorrect trials where errors in change detection emerge from neural fluctuations amplified by neural interaction. Critically, predictions of the model run counter to cognitive theories of the origin of errors in change detection. Results reveal neural patterns predicted by the model within regions of the dorsal attention network that have been the focus of much debate. The model-based analysis suggests that key areas in the dorsal attention network such as the intraparietal sulcus play a central role in change detection rather than working memory maintenance, counter to previous interpretations of fMRI studies. More generally, the integrative cognitive neuroscience approach used here establishes a framework for directly testing theories of cognitive and brain function using the combined power of behavioral and fMRI data. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Processing pipeline for image reconstructed fNIRS analysis using both MRI templates and individual anatomy.

Significance: Image reconstruction of fNIRS data is a useful technique for transforming channel-based fNIRS into a volumetric representation and managing spatial variance based on optode location. We present an innovative integrated pipeline for image reconstruction of fNIRS data using either MRI templates or individual anatomy. Aim: We demonstrate a pipeline with accompanying code to allow users to clean and prepare optode location information, prepare and standardize individual anatomical images, create the light model, run the 3D image reconstruction, and analyze data in group space. Approach: We synthesize a combination of new and existing software packages to create a complete pipeline, from raw data to analysis. Results: This pipeline has been tested using both templates and individual anatomy, and on data from different fNIRS data collection systems. We show high temporal correlations between channel-based and image-based fNIRS data. In addition, we demonstrate the reliability of this pipeline with a sample dataset that included 74 children as part of a longitudinal study taking place in Scotland. We demonstrate good correspondence between data in channel space and image reconstructed data. Conclusions: The pipeline presented here makes a unique contribution by integrating multiple tools to assemble a complete pipeline for image reconstruction in fNIRS. We highlight further issues that may be of interest to future software developers in the field.

The functional brain networks that underlie visual working memory in the first two years of life.

Visual working memory (VWM) is a central cognitive system used to compare views of the world and detect changes in the local environment. This system undergoes dramatic development in the first two years; however, we know relatively little about the functional organization of VWM at the level of the brain. Here, we used image-based functional near-infrared spectroscopy (fNIRS) to test four hypotheses about the spatial organization of the VWM network in early development. Four-month-olds, 1-year-olds, and 2-year-olds completed a VWM task while we recorded neural activity from 19 cortical regions-of-interest identified from a meta-analysis of the adult fMRI literature on VWM. Results showed significant task-specific functional activation near 6 of 19 ROIs, revealing spatial consistency in the brain regions activated in our study and brain regions identified to be part of the VWM network in adult fMRI studies. Working memory related activation was centered on bilateral anterior intraparietal sulcus (aIPS), left temporoparietal junction (TPJ), and left ventral occipital complex (VOC), while visual exploratory measures were associated with activation in right dorsolateral prefrontal cortex, left TPJ, and bilateral IPS. Results show that a distributed brain network underlies functional changes in VWM in infancy, revealing new insights into the neural mechanisms that support infants' improved ability to remember visual information and to detect changes in an on-going visual stream.

The development of working memory.

Working memory is a central cognitive system that plays key role in development, with increases in working memory capacity and speed of processing 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 artificial 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.

Homosexual not Homogeneous: A Motivation-Based Typology of Gay Leisure Travelers Holidaying in Cape Town, South Africa.

The gay traveler, a segment of the lesbian, gay, bisexual, and transgender (LGBT) travel market, is perceived to be a homogeneous market segment as a result of the assumption that gay men have a unique "homosexual lifestyle." This assumption is problematic as it conceals many other important variables, and it may hinder effective destination marketing. A Web-based electronic survey was completed by 469 gay male travelers, and attribute-based benefit segmentation was carried out by applying a hierarchical cluster analysis using Ward's procedure with Euclidean distances. The typology is based on the push and pull framework; the motivations of travelers were assessed both in terms of their socio-psychological motivations and destination attributes of Cape Town. The typology empirically suggests that gay travelers are not homogeneous, and that sexuality influences the travel behavior of a minority of gay men. Consequently, not all gay travelers or activities by these travelers can be labeled as "gay" tourism.

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.

A fNIRS Investigation of Speech Planning and Execution in Adults Who Stutter.

Our study aimed to determine the neural correlates of speech planning and execution in adults who stutter (AWS). Fifteen AWS and 15 controls (CON) completed two tasks that either manipulated speech planning or execution processing loads. Functional near-infrared spectroscopy (fNIRS) was used to measure changes in blood flow concentrations during each task, thus providing an indirect measure of neural activity. An image-based reconstruction technique was used to analyze the results and facilitate their interpretation in the context of previous functional neuroimaging studies of AWS that used positron emission tomography (PET) or functional magnetic resonance imaging (fMRI). For planning, we compared neural activity associated with high versus low planning load in AWS and CON. For execution, we compared the neural activity associated with overt versus covert naming in AWS and CON. Broadly, group level effects corroborate previous PET/fMRI findings including under-activation in left-hemisphere perisylvian speech-language networks and over-activation in right-hemisphere homologs. Increased planning load revealed atypical left-hemisphere activation in AWS, whereas increased execution load yielded atypical right fronto-temporo-parietal and bilateral motor activation in AWS. Our results add to the limited literature differentiating speech planning versus execution processes in AWS.

Early adversity in rural India impacts the brain networks underlying visual working memory.

There is a growing need to understand the global impact of poverty on early brain and behavioural development, particularly with regard to key cognitive processes that emerge in early development. Although the impact of adversity on brain development can trap children in an intergenerational cycle of poverty, the massive potential for brain plasticity is also a source of hope: reliable, accessible, culturally agnostic methods to assess early brain development in low resource settings might be used to measure the impact of early adversity, identify infants for timely intervention and guide the development and monitor the effectiveness of early interventions. Visual working memory (VWM) is an early marker of cognitive capacity that has been assessed reliably in early infancy and is predictive of later academic achievement in Western countries. Here, we localized the functional brain networks that underlie VWM in early development in rural India using a portable neuroimaging system, and we assessed the impact of adversity on these brain networks. We recorded functional brain activity as young children aged 4-48 months performed a VWM task. Brain imaging results revealed localized activation in the frontal cortex, replicating findings from a Midwestern US sample. Critically, children from families with low maternal education and income showed weaker brain activity and poorer distractor suppression in canonical working memory areas in the left frontal cortex. Implications of this work are far-reaching: it is now cost-effective to localize functional brain networks in early development in low-resource settings, paving the way for novel intervention and assessment methods.

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.

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.