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Studies of hemispheric specialization have traditionally cast the left hemisphere as specialized for language and the right hemisphere for spatial function. Much of the supporting evidence for this separation of function comes from studies of healthy adults and those who have sustained lesions to the right or left hemisphere. However, we know little about the developmental origins of lateralization. Recent evidence suggests that the young brain represents language bilaterally, with 4–6‐year‐olds activating the left‐hemisphere regions known to support language in adults as well as homotopic regions in the right hemisphere. This bilateral pattern changes over development, converging on left‐hemispheric activation in late childhood. In the present study, we ask whether this same developmental trajectory is observed in a spatial task that is strongly right‐lateralized in adults—the line bisection (or "Landmark") task. We examined fMRI activation among children ages 5–11 years as they were asked to judge which end of a bisected vertical line was longer. We found that young children showed bilateral activation, with activation in the same areas of the right hemisphere as has been shown among adults, as well as in the left hemisphere homotopic regions. By age 10, activation was right‐lateralized. This strongly resembles the developmental trajectory for language, moving from bilateral to lateralized activation. We discuss potential underlying mechanisms and suggest that understanding the development of lateralization for a range of cognitive functions can play a crucial role in understanding general principles of how and why the brain comes to lateralize certain functions. [ABSTRACT FROM AUTHOR]

Routine action sequences can share a great deal of similarity in terms of their stimulus response mappings. As a consequence, their correct execution relies crucially on the ability to preserve contextual and temporal information. However, there are few empirical studies on the neural mechanism and the brain areas maintaining such information. To address this gap in the literature, we recently recorded the blood‐oxygen level dependent (BOLD) response in a newly developed coffee–tea making task. The task involves the execution of four action sequences that each comprise six consecutive decision states, which allows for examining the maintenance of contextual and temporal information. Here, we report a reanalysis of this dataset using a data‐driven approach, namely multivariate pattern analysis, that examines context‐dependent neural activity across several predefined regions of interest. Results highlight involvement of the inferior‐temporal gyrus and lateral prefrontal cortex in maintaining temporal and contextual information for the execution of hierarchically organized action sequences. Furthermore, temporal information seems to be more strongly encoded in areas over the left hemisphere. Routine action sequences critically rely on neural mechanisms maintaining contextual and temporal information to disambiguate similar tasks (e.g. making coffee or tea). In this study we show the involvement of areas in temporal and lateral prefrontal cortices in maintaining temporal and contextual information for the execution of hierarchically‐organized action sequences. [ABSTRACT FROM AUTHOR]

Task‐based functional magnetic resonance imaging (MRI) neuroimaging for the study of cognitive neuroscience provides insight into how the brain responds to increasing cognitive demands. Theoretical models of neural–cognitive relationships define neural efficiency and neural capacity as two parameters to describe the rate of gain of brain activity and the upper limits of the increases, respectively. Although qualitatively well described, there are limited discussions and demonstrations of estimating these parameters from data. The current work presents a method using a quadratic equation model of cognitive demands. The methods were applied to 21 healthy young adults while engaging in four levels of the verbal n‐back working memory task (0, 1, 2 and 3‐back). Measures of the area under the curve captured both linear and curvilinear responses to quantify the locations and amounts of task‐related increases in brain activity. In addition, we calculated voxel‐wise maps of neural efficiency and neural capacity. Results showed increases in brain activation in regions typically involved in working memory. The relationships between increasing cognitive demands and brain activity also differed across the brain within and between individuals, as indicated by differential neural efficiency and neural capacity values. This approach provides tools for evaluating current theories about the relationships between brain activity and cognition. Neural efficiency and neural capacity provide physiological measures of brain activity, which will help evaluate how age, disease and intervention processes affect brain activity. Finally, all presented methods are readily applicable using standard current software packages for neuroimaging. [ABSTRACT FROM AUTHOR]

A fundamental question in memory research is how the hippocampus processes contextual cues to retrieve distinct mnemonic associations. Prior research has emphasized the importance of hippocampal–prefrontal interactions for context‐dependent memory. Our fMRI study examined the human medial temporal lobes (MTL) and their prefrontal interactions when retrieving memories associated with hierarchically organized task contexts. Participants learned virtual object‐location associations governed by subordinate and superordinate task rules, which could be independently cued to change. On each fMRI trial, participants retrieved the correct object for convergent rule and location contextual information. Results demonstrated that hippocampal activity and hippocampal–prefrontal functional interconnectivity distinguished retrieval under different levels of hierarchically organized task rules. In explicit contrast to the hippocampal tail, anterior (body and head) regions were recruited specifically for superordinate changes in the contextual hierarchy. The hippocampal body also differed in its functional connectivity with the prefrontal cortex for superordinate versus subordinate changes. Our findings demonstrate a gradient in MTL for associative retrieval under changing task rules, and advance understanding of hippocampal–prefrontal interactions that support flexible contextual memory. [ABSTRACT FROM AUTHOR]

The neural representation of visual‐spatial functions has traditionally been ascribed to the right hemisphere, but little is known about these representations in children, including whether and how lateralization of function changes over the course of development. Some studies suggest bilateral activation early in life that develops toward right‐lateralization in adulthood, while others find evidence of right‐hemispheric dominance in both children and adults. We used a complex visual‐spatial construction task to examine the nature of lateralization and its developmental time course in children ages 5–11 years. Participants were shown two puzzle pieces and were asked whether the pieces could fit together to make a square; responses required either mental translation of the pieces (Translation condition) or both mental translation and rotation of the pieces (Rotation condition). Both conditions were compared to a matched Luminance control condition that was similar in terms of visual content and difficulty but required no spatial analysis. Group and single‐subject analyses revealed that the Rotation and Translation conditions elicited strongly bilateral activation in the same parietal and occipital locations as have been previously found for adults. These findings show that visual‐spatial construction consistently elicits robust bilateral activation from age 5 through adulthood. This challenges the idea that spatial functions are all right‐lateralized, either during early development or in adulthood. More generally, these findings provide insights into the developmental course of lateralization across different spatial skills and how this may be influenced by the computational requirements of the particular functions involved. [ABSTRACT FROM AUTHOR]

We combined fMRI with eye tracking and speech recording to examine the neural and cognitive mechanisms that underlie reading. To simplify the study of the complex processes involved during reading, we used naming speed (NS) tasks (also known as rapid automatized naming or RAN) as a focus for this study, in which average reading right‐handed adults named sets of stimuli (letters or objects) as quickly and accurately as possible. Due to the possibility of spoken output during fMRI studies creating motion artifacts, we employed both an overt session and a covert session. When comparing the two sessions, there were no significant differences in behavioral performance, sensorimotor activation (except for regions involved in the motor aspects of speech production) or activation in regions within the left‐hemisphere‐dominant neural reading network. This established that differences found between the tasks within the reading network were not attributed to speech production motion artifacts or sensorimotor processes. Both behavioral and neuroimaging measures showed that letter naming was a more automatic and efficient task than object naming. Furthermore, specific manipulations to the NS tasks to make the stimuli more visually and/or phonologically similar differentially activated the reading network in the left hemisphere associated with phonological, orthographic and orthographic‐to‐phonological processing, but not articulatory/motor processing related to speech production. These findings further our understanding of the underlying neural processes that support reading by examining how activation within the reading network differs with both task performance and task characteristics. [ABSTRACT FROM AUTHOR]

Resting‐state fMRI has shown the ability to predict task activation on an individual basis by using a general linear model (GLM) to map resting‐state network features to activation z‐scores. The question remains whether the relatively simplistic GLM is the best approach to accomplish this prediction. In this study, several regression‐based machine‐learning approaches were compared, including GLMs, feed‐forward neural networks, and random forest bootstrap aggregation (bagging). Resting‐state and task data from 350 Human Connectome Project subjects were analyzed. First, the effect of the number of training subjects on the prediction accuracy was evaluated. In addition, the prediction accuracy and Dice coefficient were compared across models. Prediction accuracy increased with the training number up to 200 subjects; however, an elbow in the prediction curve occurred around 30–40 training subjects. All models performed well with correlation matrices, which displayed correlation between actual and predicted task activation for all subjects, exhibiting a strong diagonal trend for all tasks. Overall, the neural network and random forest bagging techniques outperformed the GLM. These approaches, however, require additional computing power and processing time. These results show that, while the GLM performs well, resting‐state fMRI prediction of task activation could benefit from more complex machine learning approaches. [ABSTRACT FROM AUTHOR]