Developmental cognitive neuroscience: progress and potential

Developmental cognitive neuroscience is an evolving field that investigates the relations between neural and cognitive development. Lying at the intersection of diverse disciplines, work in this area promises to shed light on classic developmental questions, mechanisms subserving developmental change, diagnosis and treatment of developmental disorders, and cognitive and neuroscientific topics traditionally considered outside the domain of development. Fundamental questions include: What are the interrelations between developmental changes in the brain (e.g. in connectivity, chemistry, morphology) and developmental changes in children's behavior and cognitive abilities (e.g. representational complexity, ability to sustain selective attention, speed of processing)? Why, and how, is learning enhanced during certain periods in development? How is our knowledge organized, and how does this change with development? We discuss preliminary investigations of such questions and directions for future work.     

The Implications of Brain Connectivity in the Neuropsychology of Autism

Autism is a neurodevelopmental disorder that has been associated with atypical brain functioning. Functional connectivity MRI (fcMRI) studies examining neural networks in autism have seen an exponential rise over the last decade. Such investigations have led to the characterization of autism as a distributed neural systems disorder. Studies have found widespread cortical underconnectivity, local overconnectivity, and mixed results suggesting disrupted brain connectivity as a potential neural signature of autism. In this review, we summarize the findings of previous fcMRI studies in autism with a detailed examination of their methodology, in order to better understand its potential and to delineate the pitfalls. We also address how a multimodal neuroimaging approach (incorporating different measures of brain connectivity) may help characterize the complex neurobiology of autism at a global level. Finally, we also address the potential of neuroimaging-based markers in assisting neuropsychological assessment of autism. The quest for a neural marker for autism is still ongoing, yet new findings suggest that aberrant brain connectivity may be a promising candidate.     

Imaging the developing brain with fMRI

Advancements in magnetic imaging techniques have revolutionized our ability to study the developing human brain in vivo. The ability to noninvasively image both anatomy and function in healthy volunteers, including young children, has already enhanced our understanding of brain and behavior relations. The application of these techniques to developmental research offers the opportunity to further explore these relationships and allows us to ask questions about where, when and how cognitive abilities develop in relation to changes in underlying brain systems. It is also possible to explore the contributions of maturation versus learning in the development of these abilities through cross-sectional and longitudinal research involving training and intervention procedures. Current imaging methodologies, in conjunction with new and rapidly evolving techniques, hold the promise of even greater insights into developmental issues in the near future. These methodologies and their application to development and learning are discussed in the current paper.     

A shift from diffuse to focal cortical activity with development

Recent imaging studies have suggested that developmental changes may parallel aspects of adult learning in cortical activation becoming less diffuse and more focal over time. However, while adult learning studies examine changes within subjects, developmental findings have been based on cross-sectional samples and even comparisons across studies. Here, we used functional MRI in children to test directly for shifts in cortical activity during performance of a cognitive control task, in a combined longitudinal and cross-sectional study. Our longitudinal findings, relative to our cross-sectional ones, show attenuated activation in dorsolateral prefrontal cortical areas, paralleled by increased focal activation in ventral prefrontal regions related to task performance.     

Development of the Brain’s Functional Network Architecture

A full understanding of the development of the brain’s functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks.     

网络游戏成瘾与海洛因成瘾存在相同的神经机制吗?——基于MRI的证据

网游成瘾与海洛因成瘾具有许多相似的临床表现,但其神经机制是否相同还不得而知。综合近5年来的MRI研究发现,两类成瘾存在部分相同区域的脑结构和功能损害,且在成瘾线索诱发下二者的4个成瘾相关环路(认知控制环路、奖赏环路、动机环路和记忆-学习环路)均出现了广泛而增强的脑区激活反应。但海洛因成瘾的脑损害区域偏向更高级的认知控制环路和奖赏环路,损害范围也更广(4个环路的功能连通性均降低),而网游成瘾的脑损害主要发生在相对低级的记忆-学习环路和动机环路,损害范围也较窄(功能连通性降低只发生在认知控制和记忆-学习环路之间)。这些结果说明,两类成瘾行为的神经机制既有相同点,又有差异性。     

Mapping gray matter development: Implications for typical development and vulnerability to psychopathology

Recent studies with brain magnetic resonance imaging (MRI) have scanned large numbers of children and adolescents repeatedly over time, as their brains develop, tracking volumetric changes in gray and white matter in remarkable detail. Focusing on gray matter changes specifically, here we explain how earlier studies using lobar volumes of specific anatomical regions showed how different lobes of the brain matured at different rates. With the advent of more sophisticated brain mapping methods, it became possible to chart the dynamic trajectory of cortical maturation using detailed 3D and 4D (dynamic) models, showing spreading waves of changes evolving through the cortex. This led to a variety of time-lapse films revealing characteristic deviations from normal development in schizophrenia, bipolar illness, and even in siblings at genetic risk for these disorders. We describe how these methods have helped clarify how cortical development relates to cognitive performance, functional recovery or decline in illness, and ongoing myelination processes. These time-lapse maps have also been used to study effects of genotype and medication on cortical maturation, presenting a powerful framework to study factors that influence the developing brain.     

Developmental Changes in the Relative Weighting of Geometric and Experience-Dependent Location Cues

This article introduces a promising new methodology called optical imaging. Optical imaging is used for measuring changes in cortical blood flow due to functional activation. The article outlines the pros and cons of using optical imaging for studying the brain correlates of perceptual, cognitive, and language development in infants and young children.     

The functional role of cross-frequency coupling

Recent studies suggest that cross-frequency coupling (CFC) might play a functional role in neuronal computation, communication and learning. In particular, the strength of phase-amplitude CFC differs across brain areas in a task-relevant manner, changes quickly in response to sensory, motor and cognitive events, and correlates with performance in learning tasks. Importantly, whereas high-frequency brain activity reflects local domains of cortical processing, low-frequency brain rhythms are dynamically entrained across distributed brain regions by both external sensory input and internal cognitive events. CFC might thus serve as a mechanism to transfer information from large-scale brain networks operating at behavioral timescales to the fast, local cortical processing required for effective computation and synaptic modification, thus integrating functional systems across multiple spatiotemporal scales.     

The developmental cognitive neuroscience of functional connectivity

Developmental cognitive neuroscience is a rapidly growing field that examines the relationships between biological development and cognitive ability. In the past decade, there has been ongoing refinement of concepts and methodology related to the study of ‘functional connectivity’ among distributed brain regions believed to underlie cognition and behavioral control. Due to the recent availability of relatively easy-to-use tools for functional connectivity analysis, there has been a sharp upsurge of studies that seek to characterize normal and psychopathologically abnormal brain functional integration. However, relatively few studies have applied functional and effective connectivity analysis techniques to developmental cognitive neuroscience. Functional and effective connectivity analysis methods are ideally suited to advance our understanding of the neural substrates of cognitive development, particularly in understanding how and why changes in the functional ‘wiring’ of neural networks promotes optimal cognitive control throughout development. The purpose of this review is to summarize the central concepts, methods, and findings of functional integration neuroimaging research to discuss key questions in the field of developmental cognitive neuroscience. These ideas will be presented within a context that merges relevant concepts and proposals from different developmental theorists. The review will outline a few general predictions about likely relationships between typical ‘executive’ cognitive maturation and changes in brain network functional integration during adolescence. Although not exhaustive, this conceptual review also will showcase some of recent findings that have emerged to support these predictions.     

Imaging the developing brain: what have we learned about cognitive development?

The human brain undergoes significant changes in both its structural architecture and functional organization across the life span. Advances in neuroimaging techniques over the past decade have allowed us to track these changes safely in the human in vivo. We review the imaging literature on the neurobiology of cognitive development, focusing specifically on cognitive task-dependent changes observed in brain physiology and anatomy across childhood and adolescence. The findings suggest that cortical function becomes fine-tuned with development. Brain regions associated with more basic functions such as sensory and motor processes mature first, followed by association areas involved in top-down control of behavior.     

抑郁症的脑功能整合异常-来自有效连接的证据

摘 要：抑郁症是一种常见的精神障碍。从疾病负担看,目前抑郁症已经成为世界第四大疾病,患病人数呈逐年上升的态势,给家庭和社会带来了沉重的负担。以往大多数对抑郁症的研究关注的是单个脑区结构或功能的损伤,而抑郁症通常伴随多脑区、多系统的异常,而不是单一脑区的损伤。近年来研究者开始关注抑郁症多个脑区之间的功能整合。利用功能整合的方法,动态监测抑郁症多个脑区间的相互作用,能进一步揭示抑郁症的脑网络机制。功能整合的研究方法主要包括功能连接和有效连接。有效连接刻画的是两个（或多个）脑区之间相互作用的因果关系,主要包括结构方程模型、动态因果模型、Granger 因果分析、生理心理交互作用等方法。通过对新近研究的梳理,总体而言,抑郁症的认知控制系统(如背外侧前额叶)和边缘系统（如杏仁核）的之间的有效连接减弱,即背外侧前额叶对杏仁核的抑制作用减弱,使得杏仁核对负性刺激的反应增强,出现了情绪加工偏差和认知偏差。认知控制系统和边缘系统之间有效连接的减弱能够解释抑郁症执行认知控制任务和情绪任务中的异常表现。     

Functional Brain Connectivity Using fMRI in Aging and Alzheimer’s Disease

Normal aging and Alzheimer’s disease (AD) cause profound changes in the brain’s structure and function. AD in particular is accompanied by widespread cortical neuronal loss, and loss of connections between brain systems. This degeneration of neural pathways disrupts the functional coherence of brain activation. Recent innovations in brain imaging have detected characteristic disruptions in functional networks. Here we review studies examining changes in functional connectivity, measured through fMRI (functional magnetic resonance imaging), starting with healthy aging and then Alzheimer’s disease. We cover studies that employ the three primary methods to analyze functional connectivity—seed-based, ICA (independent components analysis), and graph theory. At the end we include a brief discussion of other methodologies, such as EEG (electroencephalography), MEG (magnetoencephalography), and PET (positron emission tomography). We also describe multi-modal studies that combine rsfMRI (resting state fMRI) with PET imaging, as well as studies examining the effects of medications. Overall, connectivity and network integrity appear to decrease in healthy aging, but this decrease is accelerated in AD, with specific systems hit hardest, such as the default mode network (DMN). Functional connectivity is a relatively new topic of research, but it holds great promise in revealing how brain network dynamics change across the lifespan and in disease.     

Development of brain functional connectivity and its relation to infant sustained attention in the first year of life

The study of brain functional connectivity is crucial to understanding the neural mechanisms underlying the improved behavioral performance and amplified ERP responses observed during infant sustained attention. Previous investigations on the development of functional brain connectivity during infancy are primarily confined to the use of functional and structural MRI techniques. The current study examined the relation between infant sustained attention and brain functional connectivity and their development during infancy with high‐density EEG recordings. Fifty‐nine infants were tested at 6 (N = 15), 8 (N =14), 10 (N = 17), and 12 (N = 13) months. Infant sustained attention was defined by measuring infant heart rate changes during infants’ looking. Functional connectivity was estimated from the electrodes on the scalp and with reconstructed cortical source activities in brain regions. It was found that infant sustained attention was accompanied by attenuated functional connectivity in the dorsal attention and default mode networks in the alpha band. Graph theory analyses showed that there was an increase in path length and a decrease in clustering coefficient during infant sustained attention. The functional connectivity within the visual, somatosensory, dorsal attention, and ventral attention networks and graph theory measures of path length and clustering coefficient were found to increase with age. These findings suggest that infant sustained attention is accompanied by distinct patterns of brain functional connectivity. The current findings also suggest the rapid development of functional connectivity in brain networks during infancy.     

How do memory systems interact? Evidence from human classification learning

Studies of human classification learning using functional neuroimaging have suggested that basal ganglia and medial temporal lobe memory systems may interact during learning. We review these results and outline a set of possible mechanisms for such interactions. Effective connectivity analyses suggest that interaction between basal ganglia and medial temporal lobe are mediated by prefrontal cortex rather than by direct connectivity between regions. A review of possible neurobiological mechanisms suggests that interactions may be driven by neuromodulatory systems in addition to mediation by interaction of inputs to prefrontal cortical neurons. These results suggest that memory system interactions may reflect multiple mechanisms that combine to optimize behavior based on experience.     

Sensori‐motor experience leads to changes in visual processing in the developing brain

Since Broca’s studies on language processing, cortical functional specialization has been considered to be integral to efficient neural processing. A fundamental question in cognitive neuroscience concerns the type of learning that is required for functional specialization to develop. To address this issue with respect to the development of neural specialization for letters, we used functional magnetic resonance imaging (fMRI) to compare brain activation patterns in pre‐school children before and after different letter‐learning conditions: a sensori‐motor group practised printing letters during the learning phase, while the control group practised visual recognition. Results demonstrated an overall left‐hemisphere bias for processing letters in these pre‐literate participants, but, more interestingly, showed enhanced blood oxygen‐level‐dependent activation in the visual association cortex during letter perception only after sensori‐motor (printing) learning. It is concluded that sensori‐motor experience augments processing in the visual system of pre‐school children. The change of activation in these neural circuits provides important evidence that ‘learning‐by‐doing’ can lay the foundation for, and potentially strengthen, the neural systems used for visual letter recognition.     

Infant speech perception bootstraps word learning

By their first birthday, infants can understand many spoken words. Research in cognitive development has long focused on the conceptual changes that accompany word learning, but learning new words also entails perceptual sophistication. Several developmental steps are required as infants learn to segment, identify and represent the phonetic forms of spoken words, and map those word forms to different concepts. We review recent research on how infants' perceptual systems unfold in the service of word learning, from initial sensitivity for speech to the learning of language-specific sound patterns. Building on a recent theoretical framework and emerging new methodologies, we show how speech perception is crucial for word learning, and suggest that it bootstraps the development of a separate but parallel phonological system that links sound to meaning.     

Application of deep transfer learning for automated brain abnormality classification using MR images

Magnetic resonance imaging (MRI) is the most common imaging technique used to detect abnormal brain tumors. Traditionally, MRI images are analyzed manually by radiologists to detect the abnormal conditions in the brain. Manual interpretation of huge volume of images is time consuming and difficult. Hence, computer-based detection helps in accurate and fast diagnosis. In this study, we proposed an approach that uses deep transfer learning to automatically classify normal and abnormal brain MR images. Convolutional neural network (CNN) based ResNet34 model is used as a deep learning model. We have used current deep learning techniques such as data augmentation, optimal learning rate finder and fine-tuning to train the model. The proposed model achieved 5-fold classification accuracy of 100% on 613 MR images. Our developed system is ready to test on huge database and can assist the radiologists in their daily screening of MR images.     

Task-related functional connectivity of the caudate mediates the association between trait mindfulness and implicit learning in older adults

Accumulating evidence shows a positive relationship between mindfulness and explicit cognitive functioning, i.e., that which occurs with conscious intent and awareness. However, recent evidence suggests that there may be a negative relationship between mindfulness and implicit types of learning, or those that occur without conscious awareness or intent. Here we examined the neural mechanisms underlying the recently reported negative relationship between dispositional mindfulness and implicit probabilistic sequence learning in both younger and older adults. We tested the hypothesis that the relationship is mediated by communication, or functional connectivity, of brain regions once traditionally considered to be central to dissociable learning systems: the caudate, medial temporal lobe (MTL), and prefrontal cortex (PFC). We first replicated the negative relationship between mindfulness and implicit learning in a sample of healthy older adults (60–90 years old) who completed three event-related runs of an implicit sequence learning task. Then, using a seed-based connectivity approach, we identified task-related connectivity associated with individual differences in both learning and mindfulness. The main finding was that caudate-MTL connectivity (bilaterally) was positively correlated with learning and negatively correlated with mindfulness. Further, the strength of task-related connectivity between these regions mediated the negative relationship between mindfulness and learning. This pattern of results was limited to the older adults. Thus, at least in healthy older adults, the functional communication between two interactive learning-relevant systems can account for the relationship between mindfulness and implicit probabilistic sequence learning.     

青少年风险决策的发展认知神经机制

随着认知神经科学技术的发展, 青少年风险决策的发展认知神经机制成为了新近的一个热点课题。从双系统理论模型(社会情感神经网络系统、认知控制神经网络系统)出发, 对与青少年风险决策相关的大脑结构、功能的变化进行了阐述, 重点分析了新近的大脑功能连接、脑网络的研究; 阐述了青少年风险决策认知神经机制的主要理论模型：双系统模型和三角模型。未来研究还应加强对认知神经机制理论模型的检验、整合和创新, 从社会认知神经科学的角度深入研究社会参照系统(同伴关系、亚文化等)在青少年风险决策中的作用及机制, 以及从认知神经层面如何预防和干预青少年高风险行为。