Default and control network connectivity dynamics track the stream of affect at multiple timescales

In everyday life, the stream of affect results from the interaction between past experiences, expectations and the unfolding of events. How the brain represents the relationship between time and affect has been hardly explored, as it requires modeling the complexity of everyday life in the laboratory setting. Movies condense into hours a multitude of emotional responses, synchronized across subjects and characterized by temporal dynamics alike real-world experiences. Here, we use time-varying intersubject brain synchronization and real-time behavioral reports to test whether connectivity dynamics track changes in affect during movie watching. The results show that polarity and intensity of experiences relate to the connectivity of the default mode and control networks and converge in the right temporoparietal cortex. We validate these results in two experiments including four independent samples, two movies and alternative analysis workflows. Finally, we reveal chronotopic connectivity maps within the temporoparietal and prefrontal cortex, where adjacent areas preferentially encode affect at specific timescales.     

Competition between frontoparietal control and default networks supports social working memory and empathy

An extensive body of literature has indicated that there is increased activity in the frontoparietal control network (FPC) and decreased activity in the default mode network (DMN) during working memory (WM) tasks. The FPC and DMN operate in a competitive relationship during tasks requiring externally directed attention. However, the association between this FPC-DMN competition and performance in social WM tasks has rarely been reported in previous studies. To investigate this question, we measured FPC-DMN connectivity during resting state and two emotional face recognition WM tasks using the 2-back paradigm. Thirty-four individuals were instructed to perform the tasks based on either the expression [emotion (EMO)] or the identity (ID) of the same set of face stimuli. Consistent with previous studies, an increased anti-correlation between the FPC and DMN was observed during both tasks relative to the resting state. Specifically, this anti-correlation during the EMO task was stronger than during the ID task, as the former has a higher social load. Intriguingly, individual differences in self-reported empathy were significantly correlated with the FPC-DMN anti-correlation in the EMO task. These results indicate that the top-down signals from the FPC suppress the DMN to support social WM and empathy.     

Fast Clustered Radial Basis Function Network as an adaptive predictive controller

This paper presents a novel artificial neural network with the Radial Basis Function (RBF) as an activation function of neurons and clustered neurons in the hidden layer which has a high learning speed, thus it is called Fast Clustered Radial Basis Function Network (FCRBFN). The weights of the network are determined by solving a number of linear equation systems. In addition, new training data can be given to the network on-line and the re-training is done at high speed using the Least Squares method. In order to test the validity of the FCRBFN, it is applied to 4 classical regression applications, and also used to build the functional adaptive predictive controller. Experimental results show that, compared with other methods, the FCRBFN with a small amount of hidden neurons could achieve good or better regression precision and generalization, as well as adaptive ability at a much faster learning speed.     

Judgment before principle: engagement of the frontoparietal control network in condemning harms of omission

Ordinary people make moral judgments that are consistent with philosophical and legal principles. Do those judgments derive from the controlled application of principles, or do the principles derive from automatic judgments? As a case study, we explore the tendency to judge harmful actions morally worse than harmful omissions (the ‘omission effect’) using fMRI. Because ordinary people readily and spontaneously articulate this moral distinction it has been suggested that principled reasoning may drive subsequent judgments. If so, people who exhibit the largest omission effect should exhibit the greatest activation in regions associated with controlled cognition. Yet, we observed the opposite relationship: activation in the frontoparietal control network was associated with condemning harmful omissions—that is, with overriding the omission effect. These data suggest that the omission effect arises automatically, without the application of controlled cognition. However, controlled cognition is apparently used to overcome automatic judgment processes in order to condemn harmful omissions.     

Individual differences in pain sensitivity are associated with cognitive network functional connectivity following one night of experimental sleep disruption

Previous work suggests that sleep disruption can contribute to poor pain modulation. Here, we used experimental sleep disruption to examine the relationship between sleep disruption‐induced pain sensitivity and functional connectivity (FC) of cognitive networks contributing to pain modulation. Nineteen healthy individuals underwent two counterbalanced experimental sleep conditions for one night each: uninterrupted sleep versus sleep disruption. Following each condition, participants completed functional MRI including a simple motor task and a noxious thermal stimulation task. Pain ratings and stimulus temperatures from the latter task were combined to calculate a pain sensitivity change score following sleep disruption. This change score was used as a predictor of simple motor task FC changes using bilateral executive control networks (RECN, LECN) and the default mode network (DMN) masks as seed regions of interest (ROIs). Increased pain sensitivity after sleep disruption was positively associated with increased RECN FC to ROIs within the DMN and LECN (F_(4,14) = 25.28, pFDR = 0.05). However, this pain sensitivity change score did not predict FC changes using LECN and DMN masks as seeds (pFDR > 0.05). Given that only RECN FC was associated with sleep loss‐induced hyperalgesia, findings suggest that cognitive networks only partially contribute to the sleep‐pain dyad.     

Breathing control in neurological diseases

Control of ventilation depends on a brainstem neuronal network that controls activity of the motor neurons innervating the respiratory muscles. This network includes the pontine respiratory group and the dorsal and ventral respiratory groups in the medulla, which contain neurons that fire primarily during inspiration, post-inspiration, or expiration. The ventral respiratory group includes the pre-B?tzinger complex, which contains neurokinin-1 receptor immunoreactive neurons critical for respiratory rhythmogenesis. Structural and degenerative disorders affecting this network produce abnormalities of respiration, including sleep apnea and various patterns of dysrhythmic breathing, not infrequently associated with disturbances of cardiovagal and sympathetic vasomotor control. This emphasizes the important interactions between the respiratory and cardiovascular control networks in the medulla. Common disorders associated with impaired cardiorespiratory control include brainstem stroke or compression, syringobulbia, Chiari malformation, high cervical spinal cord injuries, and multiple system atrophy. This review focuses on the functional organization of the respiratory control network and common causes of impaired control of respiration. Received: 23 April 2002, Accepted: 5 September 2002 Correspondence to Dr. Martín A. Nogués     

A Precuneal Causal Loop Mediates External and Internal Information Integration in the Human Brain

Human brains interpret external stimuli based on internal representations. One untested hypothesis is that the default-mode network (DMN), widely considered responsible for internally oriented cognition, can decode external information. Here, we posit that the unique structural and functional fingerprint of the precuneus (PCu) supports a prominent role for the posterior part of the DMN in this process. By analyzing the imaging data of 100 participants performing two attention-demanding tasks, we found that the PCu is functionally divided into dorsal and ventral subdivisions. We then conducted a comprehensive examination of their connectivity profiles and found that at rest, both the ventral PCu (vPCu) and dorsal PCu (dPCu) are mainly connected with the DMN but also are differentially connected with internally oriented networks (IoN) and externally oriented networks (EoN). During tasks, the double associations between the v/dPCu and the IoN/EoN are correlated with task performance and can switch depending on cognitive demand. Furthermore, dynamic causal modeling (DCM) revealed that the strength and direction of the effective connectivity (EC) between v/dPCu is modulated by task difficulty in a manner potentially dictated by the balance of internal versus external cognitive demands. Our study provides evidence that the posterior medial part of the DMN may drive interactions between large-scale networks, potentially allowing access to stored representations for moment-to-moment interpretation of an ever-changing environment.SIGNIFICANCE STATEMENT The default-mode network (DMN) is widely known for its association with internalized thinking processes, e.g., spontaneous thoughts, which is the most interesting but least understood component in human consciousness. The precuneus (PCu), a posteromedial DMN hub, is thought to play a role in this, but a mechanistic explanation has not yet been established. In this study we found that the associations between ventral PCu (vPCu)/dorsal PCu (dPCu) subdivisions and internally oriented network (IoN)/externally oriented network (EoN) are flexibly modulated by cognitive demand and correlate with task performance. We further propose that the recurrent causal connectivity between the ventral and dorsal PCu supports conscious processing by constantly interpreting external information based on an internal model, meanwhile updating the internal model with the incoming information.     

The functional anatomy of cognitive control: A domain-general brain network for uncertainty processing

Cognitive control is the coordination of mental operations under conditions of uncertainty in accordance with goal-directed behaviors, and plays a key role in the domains of executive control, working memory, and decision-making. Although there is emerging evidence of common involvement of the cognitive control network (CCN) of the brain in these domains, this network has mostly been linked to the processing of conflict, which is just one case of an increase in uncertainty. Here, we conducted an activation-likelihood-estimation-based large-scale meta-analysis of 289 functional magnetic resonance imaging studies in the three domains to examine the common involvement of the CCN in uncertainty processing by contrasting the high-uncertainty versus low-uncertainty conditions. We found a general association between increase in uncertainty and an activation increase in regions of the CCN, including the frontoparietal network (comprising the frontal eye fields, the areas near and along the intraparietal sulcus, and the dorsolateral prefrontal cortex), the cingulo-opercular network (including the anterior cingulate cortex extending to the supplementary motor area, and the anterior insular cortex), and a subcortical structure (the striatum). These results demonstrate that the CCN is a domain-general construct underlying uncertainty processing to support goal-directed behaviors.     

Projective synchronization for fractional neural networks

In this paper, the global projective synchronization of fractional-order neural networks is investigated. First, a sufficient condition in the sense of Caputo’s fractional derivation to ensure the monotonicity of the continuous and differential functions and a new fractional-order differential inequality are derived, which play central roles in the investigation of the fractional adaptive control. Based on the preparation and some analysis techniques, some novel criteria are obtained to realize projective synchronization of fractional-order neural networks via combining open loop control and adaptive control. As some special cases, several control strategies are given to ensure the realization of complete synchronization, anti-synchronization and the stabilization of the addressed neural networks. Finally, an example with numerical simulations is given to show the effectiveness of the obtained results.     

Emotion perception and executive control interact in the salience network during emotionally charged working memory processing

Processing of emotional stimuli can either hinder or facilitate ongoing working memory (WM); however, the neural basis of these effects remains largely unknown. Here we examined the neural mechanisms of these paradoxical effects by implementing a novel emotional WM task in an fMRI study. Twenty‐five young healthy participants performed an N‐back task with fearful and neutral faces as stimuli. Participants made more errors when performing 0‐back task with fearful versus neutral faces, whereas they made fewer errors when performing 2‐back task with fearful versus neutral faces. These emotional impairment and enhancement on behavioral performance paralleled significant interactions in distributed regions in the salience network including anterior insula (AI) and dorsal cingulate cortex (dACC), as well as in emotion perception network including amygdala and temporal‐occipital association cortex (TOC). The dorsal AI (dAI) and dACC were more activated when comparing fearful with neutral faces in 0‐back task. Contrarily, dAI showed reduced activation, while TOC and amygdala showed stronger responses to fearful as compared to neutral faces in the 2‐back task. These findings provide direct neural evidence to the emerging dual competition model suggesting that the salience network plays a critical role in mediating interaction between emotion perception and executive control when facing ever‐changing behavioral demands. Hum Brain Mapp 35:5606–5616, 2014. © 2014 Wiley Periodicals, Inc.     

Reduced executive and default network functional connectivity in cigarette smokers

Altered functional connectivity has been associated with acute and chronic nicotine use. Connectivity alterations, specifically in the right and left executive control networks (RECN/LECN) and the default mode network (DMN), may contribute to the addiction cycle. The objective of this study was to determine if executive control network (ECN) and DMN connectivity is different between non‐smokers and smokers and whether reductions in connectivity are related to chronic cigarette use. The RECN, LECN, and DMN were identified in resting state functional magnetic resonance imaging data in 650 subjects. Analyses tested for group differences in network connectivity strength, controlling for age and alcohol use. There was a significant group effect on LECN and DMN connectivity strength with smokers (n = 452) having lower network strengths than non‐smokers (n = 198). Smokers had lower connectivity than non‐smokers associated with key network hubs: the dorsolateral prefrontal cortex, and parietal nodes within ECNs. Further, ECN connectivity strength was negatively associated with pack years of cigarette use. Our data suggest that chronic nicotine use negatively impacts functional connectivity within control networks that may contribute to the difficulty smokers have in quitting. Hum Brain Mapp 36:872–882, 2015. © 2014 Wiley Periodicals, Inc.     

Neural network for solving Nash equilibrium problem in application of multiuser power control

In this paper, based on an equivalent mixed linear complementarity problem, we propose a neural network to solve multiuser power control optimization problems (MPCOP), which is modeled as the noncooperative Nash game in modern digital subscriber line (DSL). If the channel crosstalk coefficients matrix is positive semidefinite, it is shown that the proposed neural network is stable in the sense of Lyapunov and global convergence to a Nash equilibrium, and the Nash equilibrium is unique if the channel crosstalk coefficients matrix is positive definite. Finally, simulation results on two numerical examples show the effectiveness and performance of the proposed neural network.     

Functional and effective reorganization of the aging brain during unimanual and bimanual hand movements

Motor performance decline observed during aging is linked to changes in brain structure and function, however, the precise neural reorganization associated with these changes remains largely unknown. We investigated the neurophysiological correlates of this reorganization by quantifying functional and effective brain network connectivity in elderly individuals (n = 11; mean age = 67.5 years), compared to young adults (n = 12; mean age = 23.7 years), while they performed visually‐guided unimanual and bimanual handgrips inside the magnetoencephalography (MEG) scanner. Through a combination of principal component analysis and Granger causality, we observed age‐related increases in functional and effective connectivity in whole‐brain, task‐related motor networks. Specifically, elderly individuals demonstrated (i) greater information flow from contralateral parietal and ipsilateral secondary motor regions to the left primary motor cortex during the unimanual task and (ii) decreased interhemispheric temporo‐frontal communication during the bimanual task. Maintenance of motor performance and task accuracy in elderly was achieved by hyperactivation of the task‐specific motor networks, reflecting a possible mechanism by which the aging brain recruits additional resources to counteract known myelo‐ and cytoarchitectural changes. Furthermore, resting‐state sessions acquired before and after each motor task revealed that both older and younger adults maintain the capacity to adapt to task demands via network‐wide increases in functional connectivity. Collectively, our study consolidates functional connectivity and directionality of information flow in systems‐level cortical networks during aging and furthers our understanding of neuronal flexibility in motor processes.     

Putting age-related task activation into large-scale brain networks: A meta-analysis of 114 fMRI studies on healthy aging

Normal aging is associated with cognitive decline and underlying brain dysfunction. Previous studies concentrated less on brain network changes at a systems level. Our goal was to examine these age-related changes of fMRI-derived activation with a common network parcellation of the human brain function, offering a systems-neuroscience perspective of healthy aging. We conducted a series of meta-analyses on a total of 114 studies that included 2035 older adults and 1845 young adults. Voxels showing significant age-related changes in activation were then overlaid onto seven commonly referenced neuronal networks. Older adults present moderate cognitive decline in behavioral performance during fMRI scanning, and hypo-activate the visual network and hyper-activate both the frontoparietal control and default mode networks. The degree of increased activation in frontoparietal network was associated with behavioral performance in older adults. Age-related changes in activation present different network patterns across cognitive domains. The systems neuroscience approach used here may be useful for elucidating the underlying network mechanisms of various brain plasticity processes during healthy aging.     

广泛性焦虑障碍患者认知监控网络异常的功能磁共振研究

目的:通过任务态功能磁共振(f MRI)扫描,分析广泛性焦虑障碍(GAD)患者与正常人在不同情绪图片刺激下的脑功能变化,探讨GAD患者认知监控网络(CCN)的功能异常。方法:对20例GAD患者(实验组)和14名健康对照者(健康对照组)在不同的情绪图片刺激下进行f MRI扫描,比较两组被试CCN脑区的差异。结果:以中性情绪为基线对照,在观察高兴情绪图片时,实验组被试左岛盖部额下回(MNI:-51,15,21;t=-5.178;P0.05)、左顶下小叶(MNI:-42,-42,48;t=-4.055;P0.05)、左侧补充运动区(MNI:-9,12,54;t=-4.778;P0.05)激活减弱;在观察恐惧情绪图片时,实验组被试右背外侧额上回(MNI:24,24,51;t=5.375;P0.05)激活增加。结论:CCN的功能异常可能与GAD的发病机制有关。     

Neurocontroller using dynamic state feedback for compensatory control

A common technique in neurocontrol is that of controlling a plant by static state feedback using the plant's inverse dynamics, which is approximated through a learning process. It is well known that in this control mode even small approximation errors or, which is the same, small perturbations of the plant may lead to instability. Here, a novel approach is proposed to overcome the problem of instability by using the inverse dynamics both for the static and for the error-compensating dynamic state feedback control. This scheme is termed SDS feedback control. It is shown that as long as the error of the inverse dynamics model is “signproper” the SDS feedback control is stable, i.e., the error of tracking may be kept small. The proof is based on a modification of Liapunov's second method. The problem of on-line learning of the inverse dynamics when using the controller simultaneously for both forward control and for dynamic feedback is dealt with, as are questions related to noise sensitivity and robust control of robotic manipulators. Simulations of a simplified sensorimotor loop serve to illustrate the approach.     

Roles of the Default Mode and Multiple-Demand Networks in Naturalistic versus Symbolic Decisions

The default mode network (DMN) is often associated with representing semantic, social, and situational content of contexts and episodes. The DMN may therefore be important for contextual decision-making, through representing situational constraints and simulating common courses of events. Most decision-making paradigms, however, use symbolic stimuli and instead implicate cognitive control regions, such as the multiple demand (MD) system. This fMRI study aimed to contrast the brain mechanisms underlying decision-making based on rich naturalistic contexts or symbolic cues. While performing an ongoing task, 40 human participants (25 female) responded to different sounds. For one sound, the stimulus-response mapping was fixed; responses for the other sounds depended on the visual context: either lifelike scenes or letter symbols, varying across participants. Despite minimal behavioral differences between the groups, posterior DMN regions showed increased activity during context-dependent decision-making using the naturalistic scenes only, compared with symbolic cues. More anterior temporal and frontal DMN regions showed a different pattern, with sensitivity to the need for contextual control, but not to the type of context. Furthermore, in the scenes group, widespread DMN regions showed stronger representation of not just the context but also the sound whose significance it modulated. In comparison, the MD system showed strong univariate activity for every decision, but, intriguingly, somewhat reduced activity in the case of a scene-based but demanding context-dependent decision. Depending on context, we suggest, either DMN or MD regions may play a prominent role in selection and control of appropriate behavior.SIGNIFICANCE STATEMENT Contextual knowledge is widely believed to be important for guiding real-world goal-directed behavior. Much remains to be understood, however, regarding the underlying brain mechanisms. Using a novel paradigm to contrast decisions based on richly meaningful naturalistic scenes with decisions based on symbolic cues, we find that both multiple demand regions and default mode regions may contribute to the cognitive control of behavior. Rich semantic context enhances representation not just of the context itself, but also of the contents of the decision that it controls. Dependence of a decision on naturalistic context can also reverse the common pattern of multiple demand regions responding more, and default mode regions responding less, to more difficult decisions.