Resting State, Default Mode Networks

This study examined the effect of mood states on mind wandering. Positive, neutral, and negative moods were induced in participants prior to them completing a sustained attention task. Mind wandering was measured by using the frequencies of both behavioral lapses and retrospective indices of subjective experience. Relative to a positive mood, induction of a negative mood led participants to make more lapses, report a greater frequency of task irrelevant thoughts, and become less inclined to reengage attentional resources following a lapse. Positive mood, by contrast, was associated with a better ability to adjust performance after a lapse. These results provide further support for the notion that a negative mood reduces the amount of attentional commitment to the task in hand and may do so by enhancing the focus on task irrelevant personal concerns.

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A great American psychologist summarizes one of the most difficult of subjects--the nature of dreaming--after decades of lifting matters out of the morass of Freudianism. The result nonetheless is a thin gruel that misses the main thing about dreams: their unworldly imaginative power. But he is not the only one. Who defends the psyche in modern science? Who knows what it is, where it resides, and how it controls the brain? The true theory of dreaming will emerge only by facing and answering these questions, which can be said to have baffled ancient, medieval, and modern investigators alike. At present materialism stands confused, pathetically benighted in its own shadow.

Readers are now advised that a new approach to the true theory of dreaming, as well as the first mechanistic explanation of Night Terrors in scientific history, is contained in the reviewer's illustrated essay on this page called 'The Last Day.' Both this late 2017 review and the new 2020 essay concern the same foundational ideas within idealism and can be said to blend smoothly together to produce an increasingly coherent view of the phenomenology as well as the fundamental nature of dreaming, the achievement of which depends on isolating and identifying the cosmic generator of dreams.

See also 'Sartre on Dreaming' (2022) and 'On the Materialization of Being' (2022) for deeper insights into the nature of dreaming according to idealism and in the context of the embodiment of the psyche, which reaches far deeper inwardly than the farthest galaxies are from the Solar System.

Dreams are often believed to be “symbolic” and thus categorically distinct from the “ordinary” thoughts of waking cognition. But to the contrary, emerging evidence suggests that dreams and waking cognition share a common origin at the neurobiological level, which is reflected in similarity of form, content, and function at the phenomenological level. In both dreams and daydreams, memories of the past form the basis of novel imaginary scenarios. Neural networks that support remembering the past, imagining the future, and creating fictitious scenes remain active across conscious states of wake and sleep. Taken together, this evidence suggests that dreaming is a natural extension of waking conscious experience. This empirically supported conception of dreaming has important clinical applications concerning the “interpretability” of dreams in the therapeutic setting.

Networks have become an increasingly central theme within the field of neuroscience as research takes a more global approach as opposed to a localised one (Fair et al., 2009; Menon, 2015). Converging data in systems neuroscience suggest a high functional connectivity (FC) between the salience network and other neural networks (Seeley et al., 2007; Manoliu et al., 2013). There is often an overlap of nodes between networks, an anatomical link that appendages to their functional correlation (Heuvel and Sporns, 2013; Menon, 2015), and in absence of an anatomical overlap, correlation is derived from functional inter-network edges such as the afferent link between the ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC) in triggering affective response.
In this paper I aim to extend the established connection between the default mode network and the salience network of the brain and present that anti correlation along which they interact in the neural processes of emotional feeling and decision making. As per the James-Lange theory, visceral afferents are necessary in creating a unique and discrete emotional moment in the brain which then leads to an actionable emotional response. Thus, predicated on this theory, emotion becomes the neural foundation of decision making. The salience network and the default mode network are known to activate simultaneously during moral reasoning tasks and as schizophrenia results in aberrant insular functioning, there is a simultaneous impairment in the default mode network functioning and switching of salience.
Through Damasio’s somatic marker hypothesis (SMH) and top-down (Seth 2013, 2014) and bottom up models (AD Craig, 2004) of cognition I attempt to model the anti correlation between activity of the two networks and their inversely related functions of prediction and arousal. Through this I wish to prove the role of the SN and DMN in the related neural processes of affect and decision making.

The neurobiological mechanisms underlying the maintenance of the conscious state have been extensively investigated with functional brain imaging techniques, in particular in relation to the alterations to consciousness associated with sleep and neurological and neuropsychiatric disorders. A consistent observation in these studies is the modification of activity and connectivity in distributed networks of cortical and subcortical brain regions, often associated with resting-state networks (RSNs). Several RSNs can be identified from functional imaging data, with separate networks associated with primary sensory domains and higher level cognitive functions. One of the RSNs that has been consistently implicated in alterations to consciousness is the default mode network (DMN), with studies across diverse neurological and neuropsychiatric disorders identifying differences in DMN connectivity between control subjects and patients. While the data required to examine resting functional networks is easily acquired, and the functional networks themselves are reproducible and reliable, quantifying networks of distributed brain activity and identifying the most informative features in a particular disorder remains a challenge. Progress has been made in this direction in recent years, with the adoption of mathematical tools from network engineering, and the hope is that these methods will lead to additional techniques for the diagnosis and management of neurological and neuropsychiatric disorders of consciousness.

Initially described as task-induced deactivations during goal-directed paradigms of high attentional load, the unresolved
functionality of default mode regions has long been assumed to interfere with task performance. However,
recent evidence suggests a potential defaultmode network involvement in fulfilling cognitive demands.We
tested this hypothesis in a finger opposition paradigmwith task and fixation periodswhichwe compared with an
independent resting state scan using functional magnetic resonance imaging and a comprehensive analysis pipeline
including activation, functional connectivity, behavioural and graph theoretical assessments. The results indicate
task specific changes in the default mode network topography. Behaviourally, we show that increased
connectivity of the posterior cingulate cortex with the left superior frontal gyrus predicts faster reaction times.
Moreover, interactive and dynamic reconfiguration of the default mode network regions' functional connections
illustrates their involvement with the task at hand with higher-level global parallel processing power, yet preserved
small-world architecture in comparison with rest. These findings demonstrate that the default mode network
does not disengage during this paradigm, but instead may be involved in task relevant processing.

Humans readily adopt an intentional stance to other people, comprehending their behavior as guided by unobservable mental states such as belief, desire, and intention.We used fMRI in healthy adults to test the hypothesis that this stance is primed by the default mode of human brain function present when the mind is at rest. We report three findings that support this hypothesis. First, brain regions activated by actively adopting an intentional rather than nonintentional stance to a social stimulus were anatomically similar to those demonstrating default responses to fixation baseline in the same task. Second, moment-to-moment variation in default activity during fixation in the dorsomedial PFC was related to the ease with which participants applied an intentional— but not nonintentional—stance to a social stimulus presentedmoments later. Finally, individuals who showed stronger dorsomedial PFC activity at baseline in a separate task were generally more efficient when adopting the intentional stance and reported having greater social skills. These results identify a biological basis for the human tendency to adopt the intentional stance. More broadly, they suggest that the brain’s default mode of function may have evolved, in part, as a response to life in a social world.

Il fenomeno del mind-wandering indica la tendenza della mente a vagare e a spostare l'attenzione su altro e questo ha dei costi ma anche dei vantaggi.
Il mind-wandering riflette la nostra tendenza e capacità di sganciare l’attenzione dalla percezione senza un’intenzione chiaramente definita e viene chiamato nel linguaggio scientifico “perceptual decoupling” ovvero disaccopiamento percettivo.
La ricerca sul disaccoppiamento dimostra che gli eventi mentali che si presentano come pensieri indipendenti dallo stimolo spesso interferiscono con l'elaborazione delle informazioni sensoriali nel qui e ora.
I risultati riguardanti la meta-consapevolezza rivelano che la mente è solo intermittente nella consapevolezza di impegnarsi nel vagare nella mente.

Although mind-wandering occupies up to half of our waking thoughts, it is seldom discussed in philosophy. My paper brings these neglected thoughts into focus. I propose that mind-wandering is unguided attention. Guidance in my sense concerns how attention is monitored and regulated as it unfolds over time. Roughly speaking, someone's attention is guided if she would feel pulled back, were she distracted from her current focus. Because our wandering thoughts drift unchecked from topic to topic, they are unguided. One motivation for my theory is what I call the "Puzzle of The Purposeful Wanderer". On the one hand, mind-wandering seems essentially purposeless; almost by definition, it contrasts with goal-directed cognition. On the other hand, empirical evidence suggests that our minds frequently wander to our goals. My solution to the puzzle is this: mind-wandering is purposeless in one way---it is unguided---but purposeful in another---it is frequently caused, and thus motivated, by our goals. Another motivation for my theory is to distinguish mind-wandering from two antithetical forms of cognition: absorption (e.g. engrossment in an intellectual idea) and rumination (e.g. fixation on one's distress). Surprisingly, previous theories cannot capture these distinctions. I can: on my view, absorption and rumination are guided; mind-wandering is not. My paper has four parts. Section 1 spells out the puzzle. Sections 2 and 3 explicate two extant views of mind-wandering--the first held by most cognitive scientists, the second by Thomas Metzinger. Section 4 uses the limitations of these theories to motivate my own: mind-wandering is unguided attention.

What does it mean to be an aesthetic beholder? Is it different than simply being a perceiver? Most theories of aesthetic perception focus on 1) features of the perceived object and its presentation or 2) on psychological evaluative or emotional responses and intentions of perceiver and artist. I propose that we need to look at the process of engaged perception itself, and further that this temporal process of becoming a beholder must be understood in its embodied, contextual and dynamic specificity. Through both phenomenological and neuroscientific explorations I analyze what is characteristic about a more “aesthetic stance” and argue that there is a certain asymmetry between beholder and beheld, which has to do with a disengagement of goal-directed action, and which allows for other kinds of perceptual involvement than in a more “practical stance”. It is a multi-disciplinary project integrating a sensorimotor notion of aesthetic affordances, 18th century philosophy, and large-scale brain network findings. What ensues is a new dynamic framework that hopefully can support fruitful interdisciplinary research of aesthetic perception.

Neste texto, que serve de leitura complementar de apoio a um curso de psicopatologia, é discutido o modo de funcionamento cerebral de repouso, ou espontâneo, atualmente denominado modo "default", bem como de que forma alterações de conectividade das estruturas que o compõem podem estar por trás de sintomas psicológicos.

An emerging field of human brain imaging deals with the characterization of the connectome, a comprehensive global description of structural and functional connectivity within the human brain. However, the question of how functional and structural connectivity are related has not been fully answered yet. Here, we used different methods to estimate the connectivity between each voxel of the cerebral cortex based on functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data in order to obtain observer-independent functional-structural connectomes of the human brain. Probabilistic fiber-tracking and a novel global fiber-tracking technique were used to measure structural connectivity whereas for functional connectivity, full and partial correlations between each voxel pair's fMRI-timecourses were calculated. For every voxel, two vectors consisting of functional and structural connectivity estimates to all other voxels in the cortex were correlated with each other. In this way, voxels structurally and functionally connected to similar regions within the rest of the brain could be identified. Areas forming parts of the 'default mode network' (DMN) showed the highest agreement of structurefunction connectivity. Bilateral precuneal and inferior parietal regions were found using all applied techniques, whereas the global tracking algorithm additionally revealed bilateral medial prefrontal cortices and early visual areas. There were no significant differences between the results obtained from full and partial correlations. Our data suggests that the DMN is the functional brain network, which uses the most direct structural connections. Thus, the anatomical profile of the brain seems to shape its functional repertoire and the computation of the whole-brain functional-structural connectome appears to be a valuable method to characterize global brain connectivity within and between populations.

Previous research suggests overlap between brain regions that show task-induced deactivations and those activated during the performance of social-cognitive tasks. Here, we present results of quantitative meta-analyses of neuroimaging studies, which confirm a statistical convergence in the neural correlates of social and resting state cognition. Based on the idea that both social and unconstrained cognition might be characterized by introspective processes, which are also thought to be highly relevant for emotional experiences, a third meta-analysis was performed investigating studies on emotional processing. By using conjunction analyses across all three sets of studies, we can demonstrate significant overlap of task-related signal change in dorso-medial prefrontal and medial parietal cortex, brain regions that have, indeed, recently been linked to introspective abilities. Our findings, therefore, provide evidence for the existence of a core neural network, which shows task-related signal change during socio-emotional tasks and during resting states.

Scientists have only recently begun to explore spontaneous thinking. It might appear that as elusive a phenomenon as it is in the laboratory, it would be impossible to detect in the historical record. This essay argues that it is possible to make space for accounts of spontaneous thinking in historical accounts of creativity and discovery, and that with diligence and imagination, it would be possible to reconstruct the place of spontaneous thinking in the history of ideas.

An emerging field of research focused on fluctuations in brain signals has provided evidence that the complexity of those signals, as measured by entropy, conveys important information about network dynamics (e.g., local and distributed processing). While much research has focused on how neural complexity differs in populations with different age groups or clinical disorders, substantially less research has focused on the basic understanding of neural complexity in populations with young and healthy brain states. The present study used resting-state fMRI data from the Human Connectome Project (Van Essen et al., 2013) to test the extent that neural complexity in the BOLD signal, as measured by multiscale entropy (1) would differ from random noise, (2) would differ between four major resting-state networks previously associated with higher-order cognition, and (3) would be associated with the strength and extent of functional connectivity—a complementary method of estimating information processing. We found that complexity in the BOLD signal exhibited different patterns of complexity from white, pink, and red noise and that neural complexity was differentially expressed between resting-state networks, including the default mode, cingulo-opercular, left and right frontoparietal networks. Lastly, neural complexity across all networks was negatively associated with functional connectivity at fine scales, but was positively associated with functional connectivity at coarse scales. The present study is the first to characterize neural complexity in BOLD signals at a high temporal resolution and across different networks and might help clarify the inconsistencies between neural complexity and functional connectivity, thus informing the mechanisms underlying neural complexity.

Adult attention-deficit/hyperactivity disorder (ADHD) is a serious and frequent psychiatric disorder of multifactorial pathogenesis. Several lines of evidence support the idea that ADHD is, in its core, a disorder of dysfunctional brain connectivity within and between several neurofunctional networks. The primary aim of this study was to investigate associations between the functional connectivity within resting state brain networks and the individual severity of core ADHD symptoms (inattention, hyperactivity, and impulsivity).

Electroencephalographic (EEG) oscillations predominantly appear with periods between 1 s (1 Hz) and 20 ms (50 Hz), and are subdivided into distinct frequency bands which appear to correspond to distinct cognitive processes. A variety of blind source separation (BSS) approaches have been developed and implemented within the past few decades, providing an improved isolation of these distinct processes. Within the present study, we demonstrate the feasibility of multi-subject BSS for deriving distinct EEG spatiospectral maps. Multi-subject spatiospectral EEG decompositions were implemented using the EEGIFT toolbox (http://mialab.mrn.org/software/ eegift/) with real and realistic simulated datasets (the simulation code is available at http://mialab.mrn.org/soft ware/simeeg). Twelve different decomposition algorithms were evaluated. Within the simulated data, WASOBI and COMBI appeared to be the best performing algorithms, as they decomposed the four sources across a range of component numbers and noise levels. RADICAL ICA, ERBM, INFOMAX ICA, ICA EBM, FAST ICA, and JADE OPAC decomposed a subset of sources within a smaller range of component numbers and noise levels. INFOMAX ICA, FAST ICA, WASOBI, and COMBI generated the largest number of stable sources within the real dataset and provided partially distinct views of underlying spatiospectral maps. We recommend the multi-subject BSS approach and the selected algorithms for further studies examining distinct spatiospectral networks within healthy and clinical populations.

Abstract: The degree of correlation of resting state activity within the brain is a measure of the functional connectivity (FC) of those regions. One such resting state network is the default mode network (DMN). The DMN consist of the posterior cingulate/Precuneus cortex (PCC), the left inferior parietal/angular gyrus (lIPC), the right inferior parietal/angular gyrus (rIPC) and medial prefrontal/anterior cingulate cortex (mPFC). The PCC is thought to form the central core of the DMN and  is believed to be involved in the maintenance of consciousness within the alert resting brain. Numerous studies have been performed to investigate the FC of the DMN, but less is known about the structural connectivity (SC). The aim of this study was to: 1) demonstrate structural connections between nodes (mPFC,lIPC, rIPC) of the DMN and the PCC. 2) To determine if there was a significant variation in the strength of structural and functional connections to the PCC from each node of the DMN. 3) To determine if there was a significant relationship between SC and FC of the nodes of the DMN to the PCC. We used functional magnetic resonance imaging (fMRI), group independent component analysis (GICA) and diffusion tensor imaging (DTI) to produce FC correlation maps and structural white matter tracts to demonstrate structural connections of the nodes of the DMN to the PCC. Repeated measures one-way ANOVA statistical tests were performed to determine variation in the strength of FC and SC from each of the individual nodes of the DMN to the PCC. Bivariate Pearson’s correlation analysis was used to measure the degree of overall correlation between FC and SC. Pairwise structural connections were demonstrated in all 15 subjects for mPFC-PCC regions, and in 11 of 15 subjects for the rIPC-PCC regions and in 8 of 15 subjects for the lIPC-PCC regions in our study. FC of all nodes of the DMN  was found with respect to the PCC. The weakest FC correlation to the PCC was the lIPC, which was found to be significant (p=0.018). The degree of SC to the PCC demonstrated a similar pattern to the FC, although the SC variations were not found to be significant (P=0.414). FC-SC correlation with respect to the PCC  was found to be significant at (r=0.46) P= < 0.01. We can conclude our findings have demonstrated structural connections between the functionally connected regions of the DMN and a significant relationship between DMN FC and SC to the PCC. This reinforces the view that the PCC forms the central core of the DMN. A better understanding of how structural connections relate to functional connectivity is imperative in order to enhance our understanding of long term changes of SC and FC as a consequence of Psychiatric pathology and sleep disorders.

Von Economo’s neurons (VENs) are large,
bipolar or corkscrew-shaped neurons located in layers III
and V of the frontoinsular and the anterior cingulate
cortices. VENs are reported to be altered in pathologies
such as frontotemporal dementia and autism, in which
the individual’s self control is seriously compromised. To
investigate the role of VENs in the active human brain,
we have explored the functional connectivity of brain
areas containing VENs by analyzing resting state functional
connectivity (rsFC) in 20 healthy volunteers. Our
results show that cortical areas containing VENs form a
network of frontoparietal functional connectivity. With
the use of fuzzy clustering techniques, we find that this
network comprises four sub-networks: the first network
cluster resembles a ‘‘saliency detection’’ attentional network,
which includes superior frontal cortex (Brodmann’s
Area, BA 10), inferior parietal lobe, anterior
insula, and dorsal anterior cingulate cortex; the second
cluster, part of a ‘‘sensory-motor network’’, comprises
the superior temporal, precentral and postcentral areas;
the third cluster consists of frontal ventromedial and
ventrodorsal areas constituted by parts of the ‘‘anterior
default mode network’’; and the fourth cluster encompasses
dorsal anterior cingulate cortex, dorsomedial prefrontal,
and superior frontal (BA 10) areas, resembling
the anterior part of the ‘‘dorsal attentional network’’.
Thus, the network that emerges from analyzing functional
connectivity among areas that are known to contain
VENs is primarily involved in functions of saliency
detection and self-regulation. In addition, parts of this
network constitute sub-networks that partially overlap
with the default mode, the sensory-motor and the dorsal
attentional networks.

Background: The spontaneous component of neuropathic pain (NP) has not been explored sufficiently with neuroimaging
techniques, given the difficulty to coax out the brain components that sustain background ongoing pain. Here, we address
for the first time the correlates of this component in an fMRI study of a group of eight patients suffering from diabetic
neuropathic pain and eight healthy control subjects. Specifically, we studied the functional connectivity that is associated
with spontaneous neuropathic pain with spatial independent component analysis (sICA).
Principal Findings: Functional connectivity analyses revealed a cortical network consisting of two anti-correlated patterns:
one includes the left fusiform gyrus, the left lingual gyrus, the left inferior temporal gyrus, the right inferior occipital gyrus,
the dorsal anterior cingulate cortex bilaterally, the pre and postcentral gyrus bilaterally, in which its activity is correlated
negatively with pain and positively with the controls; the other includes the left precuneus, dorsolateral prefrontal,
frontopolar cortex (both bilaterally), right superior frontal gyrus, left inferior frontal gyrus, thalami, both insulae, inferior
parietal lobuli, right mammillary body, and a small area in the left brainstem, in which its activity is correlated positively with
pain and negatively with the controls. Furthermore, a power spectra analyses revealed group differences in the frequency
bands wherein the sICA signal was decomposed: patients’ spectra are shifted towards higher frequencies.
Conclusion: In conclusion, we have characterized here for the first time a functional network of brain areas that mark the
spontaneous component of NP. Pain is the result of aberrant default mode functional connectivity.

Understanding ourselves has been a fundamental topic for psychologists and philosophers alike. In this paper we review the evidence linking specific brain structures to self-reflection. The brain regions most associated with self-reflection are the posterior cingulate and medial prefrontal (mPFC) cortices, together known as the cortical midline structures (CMSs). We review evidence arguing that self-reflection is special in memory, while noting that these brain regions are often engaged when we think about others in our social worlds. Based on the CMSs’ patterns of connectivity and activity, we speculate about three possible interpretations of their role in supporting self-reflection that are somewhat overlapping, and not intended to be mutually exclusive. First, self may be a powerful, but ordinary case for a cognitive system specialized for thinking about people. Second, mPFC may serve as a processing “hub,” binding together information from all sensory modalities with internally generated information. Third, mPFC may serve as a cortical director of thought, helping to guide moment-by-moment conscious processing. Suggestions are made for future research avenues aimed at testing such possibilities.

Background

Intracortical electrode arrays that can record extracellular action potentials from small, targeted groups of neurons are critical for basic neuroscience research and emerging clinical applications. In general, these electrode devices suffer from reliability and variability issues, which have led to comparative studies of existing and emerging electrode designs to optimize performance. Comparisons of different chronic recording devices have been limited to single-unit (SU) activity and employed a bulk averaging approach treating brain architecture as homogeneous with respect to electrode distribution.
New method

In this study, we optimize the methods and parameters to quantify evoked multi-unit (MU) and local field potential (LFP) recordings in eight mice visual cortices.
Results

These findings quantify the large recording differences stemming from anatomical differences in depth and the layer dependent relative changes to SU and MU recording performance over 6-months. For example, performance metrics in Layer V and stratum pyramidale were initially higher than Layer II/III, but decrease more rapidly. On the other hand, Layer II/III maintained recording metrics longer. In addition, chronic changes at the level of layer IV are evaluated using visually evoked current source density.
Comparison with existing method(s)

The use of MU and LFP activity for evaluation and tracking biological depth provides a more comprehensive characterization of the electrophysiological performance landscape of microelectrodes.
Conclusions

A more extensive spatial and temporal insight into the chronic electrophysiological performance over time will help uncover the biological and mechanical failure mechanisms of the neural electrodes and direct future research toward the elucidation of design optimization for specific applications.
Keywords

    Electrophysiology; Microelectrode arrays; Gamma oscillations; Firing rate; Power density spectra; Electrochemical impedance spectroscopy; Signal-to-noise; Visual evoked activity; Visual cortex

Objetivos: discutir a relação entre alterações de conectividade entre estruturas da rede default observadas em estudos de neuroimagem e o aparecimento de sintomas
psicopatológicos com viés cognitivo social na depressão, ansiedade e esquizofrenia.
Método: revisão narrativa de artigos. Resultados: maior ou menor conectividade de estruturas cerebrais em repouso podem comprometer a formação de representações mentais sociais, produzindo sintomas psicopatológicos. Conclusão: o estudo por imagem da conectividade cerebral no repouso é uma ferramenta útil para a compreensão da formação de vários sintomas psiquiátricos.
Palavras chave: psicopatologia, conectividade cerebral, cognição, cognição social.

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Different imaging modalities capture different aspects of brain activity. Functional magnetic resonance imaging (fMRI) reveals intrinsic networks whose BOLD signals have periods from 100 s (0.01 Hz) to about 10s (0.1 Hz). Electroencephalographic (EEG) recordings, in contrast, commonly reflect cortical electrical fluctuations with periods up to 20 ms (50 Hz) or above. We examined the correspondence between intrinsic fMRI and EEG network activity at rest in order to characterize brain networks both spatially (with fMRI) and spectrally (with EEG). Brain networks were separately identified within the concurrently recorded fMRI and EEG at the aggregate group level with group independent component analysis and the association between spatial fMRI and frequency by spatial EEG sources was examined by deconvolving their component time courses. The two modalities are considered linked if the estimated impulse response function (IRF) is significantly non-zero at biologically plausible delays. We found that negative associations were primarily present within two of five alpha components, which highlights the importance of considering multiple alpha sources in EEG-fMRI. Positive associations were primarily present within the lower (e.g. delta and theta) and higher (e.g. upper beta and lower gamma) spectral regions, sometimes within the same fMRI components. Collectively, the results demonstrate a promising approach to characterize brain networks spatially and spectrally, and reveal that positive and negative associations appear within partially distinct regions of the EEG spectrum.Copyright © 2012 Elsevier Inc. All rights reserved.

Age-related effects on the default mode network (DMN) connectivity as measured at rest using functional magnetic resonance imaging (fMRI) are now well described. Little is known however about the relationships between these changes and age-related effects on cognition or on the unconstrained thoughts which occur during the resting-state scan, called inner experience. Brain resting-state activity, inner experience, and cognitive ability measurements were obtained in 70 participants aged 19-80 years. The anterior-posterior disruption of DMN activity with age reported in previous studies was recovered here. A significant effect of age was also found on cognitive abilities but not on inner experience. Finally, age-related changes in DMN connectivity were found to correlate with cognitive abilities, and more specifically with autobiographical memory performance. These findings provide new information to fuel the debate on the role of the brain default mode and more specifically on the effect of age-related changes in resting-state activity as measured with fMRI.

The default mode network (DMN) is assumed as a set of brain regions that show increased activity during the resting-state condition and suppressed activity during the demanding task condition. Accumulating evidence from functional imaging studies such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) has revealed that alterations in DMN is present in many psychiatric and neurological disorders. In Alzheimer’s disease (AD), for example, the distribution of A-amyloid protein (A) deposition in the brain is considerably overlapped over the DMN. It is now considered that this Aaccumulation is not only specific to the AD brain but to some cognitively normal elderly people. The Aaccumulation seen in the DMN may be an unwelcome sign in the seemingly normal persons because there are pieces of evidence that those subjects with high Adeposition are very likely to develop AD in the future. Our recent study of the cognitive and physiological impact of A accumulation on the DMN function in normal elderly people using PET has shown that the amount of A deposits is negatively correlated with the DMN function, and the lower function of DMN is associated with poorer working memory performance. As expected, A deposition in the brain, however minute the degree of its accumulation can be, may cause neuronal discoordination in the DMN along with poor working memory in normal aging. Although articles on fMRI-based DMN activity are profuse, few papers on molecular imaging-based study on the DMN exist. In the present review, we introduce alterations in metabolism and neurochemical responses present in the DMN in aging and diseases.

Background: Impaired awareness of the self and others (i.e., metacognitive evaluations) are seen in schizophrenia. We compared patterns of activation in schizophrenia (SZ) and nonclinical subjects during a functional magnetic resonance imaging (fMRI) task of metacognitive evaluations that has been demonstrated to engage the neural circuitry of the self in healthy subjects. Methods: Eleven SZ subjects (7 males, mean age 26.6± 8) and 10 healthy control subjects (4 males, mean age 29.6 ± 8.4) were enrolled. Participants completed two runs of a metacognitive evaluation task (self vs. other vs. word meaning). fMRI data was obtained using a full body Bruker MedSped 4.0 Tesla system. Group contrasts were performed using an uncorrected p b 0.005 with a 50 voxel extent threshold. Results: We observed a significant hypoactivation in the left superior temporal sulcus (STS) during metacognitive evaluations of others (OE) vs. semantic positivity evaluations (SPE) and a trend toward significant hypoactivation in the OE vs. self evaluations (SE) in the SZ group. Significant hypoactivation was also seen in the right inferior temporal gyrus (ITG) in the OE vs. SE contrasts in the SZ group. A trendworthy hypoactivation was seen in the SZ group in the right middle frontal gyrus and pole of the left STS during OE vs. SPE and SE contrasts respectively. Conclusions: These results extend previous findings of impaired metacognitive evaluative processes in schizophrenia to aberrations of the neural circuitry implicated in self/other awareness among SZ patients. Greater understanding of the neural basis of deficits of self/other awareness in early schizophrenia may contribute to improvements in the identification and treatment of individuals at risk for the illness.

The human insula is hidden in the depth of the cerebral hemisphere by the overlying frontal and temporal opercula, and consists of three cytoarchitectonically distinct regions: the anterior agranular area, posterior
granular area, and the transitional dysgranular zone; each has distinct histochemical staining patterns and specific connectivity. Even though there are several studies reporting the functional connectivity of the insula
with the cingulated cortex, its relationships with other brain areas remain elusive in humans. Therefore, we decided to use resting state functional connectivity to elucidate in details its connectivity, in terms of cortical
and subcortical areas, and also of lateralization. We investigated correlations in BOLD fluctuations between specific regions of interest of the insula and other brain areas of right-handed healthy volunteers, on both sides of the brain. Our findings document two major complementary networks involving the ventral-anterior and dorsal-posterior insula: one network links the anterior insula to the middle and inferior temporal cortex and anterior cingulate cortex, and is primarily related to limbic regions which play a role in emotional aspects; the second links the middle-posterior insula to premotor, sensorimotor, supplementary motor and middleposterior cingulate cortices, indicating a role for the insula in sensorimotor integration. The clear bipartition of the insula was confirmed by negative correlation analysis. Correlation maps are partially lateralized: the salience network, related to the ventral anterior insula, displays stronger connections with the anterior
cingulate cortex on the right side, and with the frontal cortex on the left side; the posterior network has stronger connections with the superior temporal cortex and the occipital cortex on the right side. These results are in agreement with connectivity studies in primates, and support the use of resting state functional analysis to investigate connectivity in the living human brain.

Converging theories and data suggest that atypical patterns of functional and structural connectivity are a hallmark neurobiological feature of autism. However, empirical studies of functional connectivity, or, the correlation of MRI signal between brain regions, have largely been conducted during task performance and/or focused on group differences within one network (e.g., the default mode network). This narrow focus on task-based connectivity and single network analyses precludes investigation of whole-brain intrinsic network organization in autism. To assess whole-brain network properties in adolescents with autism, we collected resting-state functional connectivity MRI (rs-fcmri) data from neurotypical adolescents (NT) and adolescents with autism spectrum disorder (ASD). We used graph theory metrics on rs-fcmri data with 34 regions of interest (i.e., nodes) that encompass 4 different functionally-defined networks: cingulo-opercular, cerebellar, fronto-parietal, and default mode (DMN) (Fair et al., 2009). Contrary to our hypotheses, network analyses revealed minimal differences between groups with one exception. Betweenness centrality, which indicates the degree to which a seed (or node) functions as a hub within and between networks was greater for participants with autism for the right lateral parietal region of the DMN. Follow-up seed-based analyses demonstrated greater functional connectivity in ASD than NT groups between the right lateral parietal seed and another region of the DMN, the anterior medial prefrontal cortex. Greater connectivity between these regions was related to lower ADOS scores (i.e. lower impairment) in autism. These findings do not support current theories of underconnectivity in autism, but, rather, underscore the need for future studies to systematically examine factors that can influence patterns of intrinsic connectivity such as autism severity, age, and head motion.

When the sensory cortex is stimulated and directly receiving afferent input, modulations can also be observed in the activity of other brain regions comprising spatially distributed, yet intrinsically connected networks, suggesting that these networks support brain function during task performance. Such networks can exhibit subtle or unpredictable task responses which can pass undetected by conventional general linear modelling (GLM). Additionally, the metabolic demand of these networks in response to stimulation remains incompletely understood. Here, we recorded concurrent BOLD and CBF measurements during median nerve stimulation (MNS) and compared GLM analysis with independent component analysis (ICA) for identifying the spatial, temporal and metabolic properties of responses in the primary sensorimotor cortex (S1/M1), and in the default mode (DMN) and fronto-parietal (FPN) networks. Excellent spatial and temporal agreement was observed between the positive BOLD and CBF responses to MNS detected by GLM and ICA in contralateral S1/M1. Values of the change in cerebral metabolic rate of oxygen consumption (Δ%CMRO 2 ) and the Δ%CMRO 2 /Δ%CBF coupling ratio were highly comparable when using either GLM analysis or ICA to extract the contralateral S1/M1 responses, validating the use of ICA for estimating changes in CMRO 2 . ICA identified DMN and FPN network activity that was not detected by GLM analysis. Using ICA, spatially coincident increases/decreases in both BOLD and CBF signals to MNS were found in the FPN/DMN respectively. Calculation of CMRO 2 changes in these networks during MNS showed that the Δ%CMRO 2 /Δ%CBF ratio is comparable between the FPN and S1/M1 but is larger in the DMN than in the FPN, assuming an equal value of the parameter M in the DMN, FPN and S1/M1. This work suggests that metabolism-flow coupling may differ between these two fundamental brain networks, which could originate from differences between task-positive and task-negative fMRI responses, but might also be due to intrinsic differences between the two networks.

Schizophrenia and depression are prevalent psychiatric disorders, but their underlying neural bases remains poorly understood. Neuroimaging evidence has pointed towards the relevance of functional connectivity aberrations in default mode network (DMN) hubs, dorso-medial prefrontal cortex and precuneus, in both disorders, but commonalities and differences in resting state functional connectivity of those two regions across disorders has not been formally assessed. Here, we took a transdiagnostic approach to investigate resting state functional connectivity of those two regions in 75 patients with schizophrenia and 82 controls from 4 scanning sites and 102 patients with depression and 106 controls from 3 sites. Our results demonstrate
common dysconnectivity patterns as indexed by a significant reduction of functional connectivity between precuneus and bilateral superior parietal lobe in schizophrenia and depression. Furthermore, our findings highlight diagnosis-specific connectivity
reductions of the parietal operculum in schizophrenia relative to depression. In light of evidence that points towards the importance of the DMN for social cognitive abilities and
well documented impairments of social interaction in both patient groups, it is conceivable that the observed transdiagnostic connectivity alterations may contribute to interpersonal difficulties, but this could not be assessed directly in our study as
measures of social behavior were not available. Given the operculum’s role in somatosensory integration, diagnosis-specific connectivity reductions may indicate a pathophysiological mechanism for basic self-disturbances that is characteristic of
schizophrenia, but not depression.

Human minds often wander away from their immediate sensory environment. It remains unknown whether such mind wandering is unsystematic or whether it lawfully relates to an individual's tendency to attend to salient stimuli such as pain and their associated brain structure/function. Studies of pain-cognition interactions typically examine explicit manipulation of attention rather than spontaneous mind wandering. Here we sought to better represent natural fluctuations in pain in daily life, so we assessed behavioral and neural aspects of spontaneous disengagement of attention from pain. We found that an individual's tendency to attend to pain related to the disruptive effect of pain on his or her cognitive task performance. Next, we linked behavioral findings to neural networks with strikingly convergent evidence from functional magnetic resonance imaging during pain coupled with thought probes of mind wandering, dynamic resting state activity fluctuations, and diffusion MRI. We found that (i) pain-induced default mode network (DMN) deactivations were attenuated during mind wandering away from pain; (ii) functional connectivity fluctuations between the DMN and periaqueductal gray (PAG) dynamically tracked spontaneous attention away from pain; and (iii) across individuals, stronger PAG-DMN structural connectivity and more dynamic resting state PAG-DMN functional connectivity were associated with the tendency to mind wander away from pain. These data demonstrate that individual tendencies to mind wander away from pain, in the absence of explicit manipulation, are subserved by functional and structural connectivity within and between default mode and antinociceptive descending modulation networks.

Two hypotheses of autism spectrum disorder (ASD) propose that this condition is characterized by deficits in Theory of Mind and by hypoconnectivity between remote cortical regions with hyperconnectivity locally. The default mode network (DMN) is a set of remote, functionally connected cortical nodes less active during executive tasks than at rest and is implicated in Theory of Mind, episodic memory, and other self-reflective processes. We show that children with ASD have reduced connectivity between DMN nodes and increased local connectivity within DMN nodes and the visual and motor resting-state networks. We show that, like the trajectory of synaptogenesis, internodal DMN functional connectivity increased as a quadratic function of age in typically developing children, peaking between, 11 and 13 years. In children with ASD, these long-distance connections fail to develop during adolescence. These findings support the ''developmental disconnection model'' of ASD, provide a possible mechanistic explanation for the Theory-of-Mind hypothesis of ASD, and show that the window for effectively treating ASD could be wider than previously thought. Hum Brain Mapp 00:000-000,

Metacognition is usually construed as a conscious, intentional process whereby people reflect upon their own mental activity. Here, we instead suggest that metacognition is but an instance of a larger class of representational redescription processes that we assume occur unconsciously and automatically. From this perspective, the brain continuously and unconsciously learns to anticipate the consequences of action or activity on itself, on the world, and on other people through three predictive loops: An inner loop, a perception-action loop, and a self-other (social cognition) loop, which together form a tangled hierarchy. We ask what kinds of mechanisms may subtend this form of enactive metacognition. We extend previous neural network simulations and compare the model with Signal Detection Theory, highlighting that while the latter approach assumes that both Type I (objective) and Type II (subjective, metacognition-based) decisions tap into the same signal at different hierarchical levels, our approach is closer to dual-route models in that it assumes that the redescriptions made possible by the emergence of metarepresentations occur independently and outside of the first-order causal chain. We close by reviewing relevant neurological evidence for the idea that awareness, self-awareness and social cognition involve the same mechanisms.