The functional network of the brain continually adapts to changing environmental demands. The consequence of behavioral automation for task-related functional network architecture remains far from understood. We investigated the neural reflections of behavioral automation as participants mastered a dual n-back task. In four fMRI scans equally spanning a 6-week training period, we assessed brain network modularity, a substrate for adaptation in biological systems. We found that whole-brain modularity steadily increased during training for both conditions of the dual n-back task. In a dynamic analysis,we found that the autonomy of the default mode system and integration among task-positive systems were modulated by training. The automation of the n-back task through training resulted in non-linear changes in integration between the fronto-parietal and default mode systems, and integration with the subcortical system. Our findings suggest that the automation of a cognitively demanding task may result in more segregated network organization.

(1) to examine changes in the whole-brain functional network under increased cognitive demands of working memory during an n-back task, and their relationship with behavioral outcomes; and (2) to provide a comprehensive description of local changes that may be involved in the formation of the global workspace, using hub detection and network-based statistic. Our results show that network modularity decreased with increasing cognitive demands, and this change allowed us to predict behavioral performance. The number of connector hubs increased, whereas the number of provincial hubs decreased when the task became more demanding. We also found that the default mode network (DMN) increased its connectivity to other networks while decreasing connectivity between its own regions. These results, apart from replicating previous findings, provide a valuable insight into the mechanisms of the formation of the global workspace, highlighting the role of the DMN in the processes of network integration. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.

Early sensory deprivation, such as deafness, shapes brain development in multiple ways. Deprived auditory areas become engaged in the processing of stimuli from the remaining modalities and in high-level cognitive tasks. Yet, structural and functional changes were also observed in non-deprived brain areas, which may suggest the whole-brain network changes in deaf individuals. To explore this possibility, we compared the resting-state functional network organization of the brain in early deaf adults and hearing controls and examined global network segregation and integration. Relative to hearing controls, deaf adults exhibited decreased network segregation and an altered modular structure. In the deaf, regions of the salience network were coupled with the fronto-parietal network, while in the hearing controls, they were coupled with other large-scale networks. Deaf adults showed weaker connections between auditory and somatomotor regions, stronger coupling between the fronto-parietal network and several other large-scale networks (visual, memory, cingulo-opercular and somatomotor), and an enlargement of the default mode network. Our findings suggest that brain plasticity in deaf adults is not limited to changes in the auditory cortex but additionally alters the coupling between other large-scale networks and the development of functional brain modules. These widespread functional connectivity changes may provide a mechanism for the superior behavioral performance of the deaf in visual and attentional tasks.

The functional meaning and neural basis of the P3b component of ERPs are still under debate. One of the main issues is whether P3b reflects only stimulus-related processes (stimulus evaluation hypothesis) or response-related processes as well (stimulus-response or S-R link activation hypothesis). Here, we conducted an EEG experiment examining whether P3b may indeed reflect an S-R link activation, followed by an fMRI experiment in which we explored the brain areas and functional connectivity possibly constituting the neural basis of these sensorimotor links. In both experiments, two successive visual stimuli, S1 and S2, were presented with a 1 sec interval, and responses were defined either by S1 or S2, while participants responded only after S2 onset. The obtained EEG results suggest that P3b may be interpreted in terms of the S-R link activation account, although further studies are needed to disentangle P3-related activity from overlapping anticipatory activity. The obtained fMRI results showed that processing of the relevant S1 involved activation of a distributed postero-anterior sensorimotor network, and increased strength of functional connectivity within this network. This network may underlie activation of the S-R links, thus possibly also the P3b component, forming a bridging step between sensory encoding and response execution. In the present study, we conducted two experiments: an EEG experiment aimed at examining the issue of whether P3b may reflect processes related to activation of stimulus-response (S-R) links or "event files", followed by an fMRI experiment aimed at exploring what may constitute the neural basis of these sensorimotor links. EEG Experiment Introduction. Over four decades have passed since Squires, Squires, and Hillyard 1 described the P3b component (that we will further refer to as P3)-a major centro-parietal part of the P300 complex in the human event-related EEG potential (ERP) with a maximal positive deflection at parietal midline (usually the Pz site) at about 300-700 ms after stimulus onset. Years of extensive studies have shown that P3 emerges whenever a task-related or behaviorally-relevant stimulus is perceived, regardless of stimulus and response modalities, and changes in P3 amplitude and latency are related to a wide range of higher-level cognitive processes 2-4. Yet, the functional meaning of P3 as well as its neural underpinnings are still under debate. Answers to the question of "what is the underlying process reflected by P3?" usually fall into one of two general views. The first view is that P3 reflects stimulus processing only, and is neither related to nor affected by processes of response selection and preparation 5,6. Seminal for this approach, the stimulus evaluation account maintains that P3 is a signature of comprehensive evaluation of perceived events. This evaluation entails processes of allocation of perceptual and/or attentional resources to event encoding and categorization 7-9 , and it is often assumed here that P3 amplitude reflects the amount of these...

The functional network of the human brain continually adapts to changing environmental demands. Such adaptation spans multiple time scales, from seconds during task performance to days and weeks during motor or cognitive training. Yet the precise consequence of behavioral automation for functional network architecture, particularly in the context of complex tasks, remains far from understood. Here we investigated the neural reflections of behavioral adaptation as human participants mastered a dual n-back task over 6 weeks of training. In four fMRI scans equally spanning the training period, we assessed the level of brain network modularity, a common substrate for adaptation in biological systems. Specifically, we investigated both static and dynamic modularity to probe the segregation between task-relevant fronto-parietal and default mode systems, and to assess their time-evolving recruitment and integration. We found that whole-brain modularity was higher during the resting state than during the dual n-back task, and increased as demands heightened from the 1-back to the 2-back condition. Modularity also steadily increased in response to training for both task conditions. In an explicitly dynamic analysis, we found that the recruitment of both the default mode and fronto-parietal systems during the dual n-back task was modulated by training. Moreover, the change in default mode recruitment from the first scanning session to the last was positively correlated with behavioral improvement after training. Reliably across static and dynamic network analyses, our findings suggest that the automation of a cognitively demanding task may result in more segregated network organization.