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The problem of the self has been of increasing interest in recent neuroscience. Brain imaging studies have raised the question of whether neural activity in cortical midline regions is self-specific and whether self-specific activity is related to resting state activity (RSA). A quantitative meta-analysis that included 87 studies, representing 1433 participants, was conducted to discuss these questions. First, the specificity of the self (e.g. hearing one's own name, seeing one's own face) was tested and compared across familiar (using stimuli from personally known people) and other (non-self–non-familiar, i.e. strangers and widely-known figures) conditions. Second, the relationship between the self and resting state activity, as reflected by the default-mode network (DMN), was tested. The results indicated that the perigenual anterior cingulate cortex (PACC) is specifically involved in self-processing when compared to familiarity, other, and task/stimulus effects. On the contrary, other midline regions, i.e., medial prefrontal cortex (MPFC) and posterior cingulate cortex (PCC) were functionally unspecific as they were recruited during the processing of both self-specific and familiar stimuli. Finally, the PACC was recruited during self-specific stimuli and this activity overlapped with DMN activity during resting state, thus distinguishing the self-related processing from both that of the familiar and other conditions. Taken together, our data suggest that our sense of self may result from a specific kind of interaction between resting state activity and stimulus-induced activity, i.e., rest–stimulus interaction, within the midline regions. ►Neuronal specificity of self vs. familiarity and non-self. ►Relationship between self and neural activity in the cortical midline structures. ►Relation between self and resting state activity in the default-mode network.

Schizophrenia (SCZ) is a complex disorder in which various pathophysiological models have been postulated. Brain imaging studies using EEG/MEG and fMRI show altered amplitude and, more recently, decrease in phase coherence in response to external stimuli. What are the dynamic mechanisms of such phase incoherence, and can it serve as a differential-diagnostic marker? Addressing this gap in our knowledge, we uniquely combine a review of previous findings, novel empirical data, and computational-dynamic simulation. The main findings are: ( i ) the review shows decreased phase coherence in SCZ across a variety of different tasks and frequencies, e.g., task- and frequency-unspecific, which is further supported by our own novel data; ( ii ) our own data demonstrate diagnostic specificity of decreased phase coherence for SCZ as distinguished from major depressive disorder; ( iii ) simulation data exhibit increased phase offset in SCZ leading to a precision index, in the millisecond range, of the phase coherence relative to the timing of the external stimulus. Together, we demonstrate the key role of temporal imprecision in phase coherence of SCZ, including its mechanisms (phase offsets, precision index) on the basis of which we propose a phase-based temporal imprecision model of psychosis (PTP). The PTP targets a deeper dynamic layer of a basic disturbance. This converges well with other models of psychosis like the basic self-disturbance and time-space experience changes, as discussed in phenomenological and spatiotemporal psychopathology, as well as with the models of aberrant predictive coding and disconnection as in computational psychiatry. Finally, our results show that temporal imprecision as manifest in decreased phase coherence is a promising candidate biomarker for clinical differential diagnosis of SCZ, and more broadly, psychosis.

Alterations in brain intrinsic activity—as organized in resting-state networks (RSNs) such as sensorimotor network (SMN), salience network (SN), and default-mode network (DMN)—and in neurotransmitters signaling—such as dopamine (DA) and serotonin (5-HT)—have been independently detected in psychiatric disorders like bipolar disorder and schizophrenia. Thus, the aim of this work was to investigate the relationship between such neurotransmitters and RSNs in healthy, by reviewing the relevant work on this topic and performing complementary analyses, in order to better understand their physiological link, as well as their alterations in psychiatric disorders. According to the reviewed data, neurotransmitters nuclei diffusively project to subcortical and cortical regions of RSNs. In particular, the dopaminergic substantia nigra (SNc)-related nigrostriatal pathway is structurally and functionally connected with core regions of the SMN, whereas the ventral tegmental area (VTA)-related mesocorticolimbic pathway with core regions of the SN. The serotonergic raphe nuclei (RNi) connections involve regions of the SMN and DMN. Coherently, changes in neurotransmitters activity impact the functional configuration and level of activity of RSNs, as measured by functional connectivity (FC) and amplitude of low-frequency fluctuations/temporal variability of BOLD signal. Specifically, DA signaling is associated with increase in FC and activity in the SMN (hypothetically via the SNc-related nigrostriatal pathway) and SN (hypothetically via the VTA-related mesocorticolimbic pathway), as well as concurrent decrease in FC and activity in the DMN. By contrast, 5-HT signaling (via the RNi-related pathways) is associated with decrease in SMN activity along with increase in DMN activity. Complementally, our empirical data showed a positive correlation between SNc-related FC and SMN activity, whereas a negative correlation between RNi-related FC and SMN activity (along with tilting of networks balance toward the DMN). According to these data, we hypothesize that the activity of neurotransmitter-related neurons synchronize the low-frequency oscillations within different RSNs regions, thus affecting the baseline level of RSNs activity and their balancing. In our model, DA signaling favors the predominance of SMN-SN activity, whereas 5-HT signaling favors the predominance of DMN activity, manifesting in distinct behavioral patterns. In turn, alterations in neurotransmitters signaling (or its disconnection) may favor a correspondent functional reorganization of RSNs, manifesting in distinct psychopathological states. The here suggested model carries important implications for psychiatric disorders, providing novel and well testable hypotheses especially on bipolar disorder and schizophrenia.

The connection of the brain to the mind remains one of the most persistent mysteries in philosophy and neuroscience. Georg Northoff proposes a new approach to the so-called mind-body problem, drawing on an insight from physics: time structures all objects and events in the world, and all objects and events are in dynamic relationship. This also shapes the brain as it is part of the dynamic of the world as whole. In Neurowaves Northoff posits that the entire world is structured by waves of time and argues that the passing of these waves through our brains – neurowaves – produces mental experience. The brain's neural waves transform into mental waves; time and its dynamics are shared by brain and mind as their common currency. As in physics and biology, that radically changes our view. Copernicus showed how the earth moves and that its movements are just a tiny part of the universe's passage of time. Darwin showed that the human species is one among many species passing through evolution's timescales. Northoff calls for another Copernican revolution, replacing the mind-body problem with questions about the temporal-dynamic relationship between brain and world. Illustrated with vivid examples from different facets of the physical and biological world, Neurowaves provides captivating insights and an innovative, entertaining unravelling of the temporal connection of brain and mind.

Abstract Schizophrenia is a complex psychiatric disorder exhibiting alterations in spontaneous and task-related cerebral activity whose relation (termed “state dependence”) remains unclear. For unraveling their relationship, we review recent electroencephalographic (and a few functional magnetic resonance imaging) studies in schizophrenia that assess and compare both rest/prestimulus and task states, ie, rest/prestimulus–task modulation. Results report reduced neural differentiation of task-related activity from rest/prestimulus activity across different regions, neural measures, cognitive domains, and imaging modalities. Together, the findings show reduced rest/prestimulus–task modulation, which is mediated by abnormal temporospatial dynamics of the spontaneous activity. Abnormal temporospatial dynamics, in turn, may lead to abnormal prediction, ie, predictive coding, which mediates cognitive changes and psychopathological symptoms, including confusion of internally and externally oriented cognition. In conclusion, reduced rest/prestimulus–task modulation in schizophrenia provides novel insight into the neuronal mechanisms that connect task-related changes to cognitive abnormalities and psychopathological symptoms.

Neuroscience provides major insights into the neural correlates of mental features like consciousness and sense of self. Despite these major advancements, we do not know the mechanisms connecting neuronal and mental states, the neuro-mental mechanisms that allow transforming neuronal activity into mental states. We propose that neuroscience may benefit from the kind of Copernican turn that, initiated by Copernicus and Darwin, revolutionized the fields of physics and biology. Specifically, I claim that we need to abandon our currently rather anthropocentric ‘vantage point from within brain’ by a more allo-centric ‘vantage point from beyond brain’. I first show how Copernicus and Darwin, due to the shift of their vantage point from within to beyond earth and humans, were able to take into view the non-specialness of earth and humans, e.g., what is shared between earth and other planets as well as between human and non-human species. Such specialness is still presupposed in current neuroscience which regards the neural correlates of mental features like consciousness that are supposed to be special when compared to those of non-mental features. That is possible only by presupposing a pre-Copernican ‘vantage point from within brain’. Recent data as illustrated in this paper, show a neuronal continuum between conscious and unconscious states; that defies the supposed specialness of the neuronal mechanisms underlying mental features. Mental features like consciousness may then signify rather a specific degree on a broader neuronal continuum that ranges from non-consciousness over unconsciousness and consciousness to extended consciousness. The neuronal mechanisms underlying mental features can then be characterized by non-specialness (rather than specialness) which presupposes a ‘vantage point from beyond brain’. Such vantage point from beyond brain, in turn, allows taking into view the shared features between neuronal and mental features, i.e., their “common currency”. That same “common currency” may, in turn, allow addressing and searching for those mechanisms that allow transforming neuronal activity into mental states, e.g., neuro-mental transformation. In conclusion, I propose that neuroscience may benefit in its search for the neural basis of mind from a Copernican turn analogous to the one initiated by Copernicus and Darwin in physics and biology.

Major depressive disorder (MDD) is characterized by a multitude of psychopathological symptoms including affective, cognitive, perceptual, sensorimotor, and social. The neuronal mechanisms underlying such co-occurrence of psychopathological symptoms remain yet unclear. Rather than linking and localizing single psychopathological symptoms to specific regions or networks, this perspective proposes a more global and dynamic topographic approach. We first review recent findings on global brain activity changes during both rest and task states in MDD showing topographic reorganization with a shift from unimodal to transmodal regions. Next, we single out two candidate mechanisms that may underlie and mediate such abnormal uni-/transmodal topography, namely dynamic shifts from shorter to longer timescales and abnormalities in the excitation-inhibition balance. Finally, we show how such topographic shift from unimodal to transmodal regions relates to the various psychopathological symptoms in MDD including their co-occurrence. This amounts to what we describe as ‘Topographic dynamic reorganization’ which extends our earlier ‘Resting state hypothesis of depression’ and complements other models of MDD.

Major depressive disorder (MDD) is a psychiatric disorder characterized by abnormal resting state functional connectivity (rsFC) in various neural networks and especially in default-mode network (DMN). However, inconsistent findings, i.e., increased and decreased DMN rsFC, have been reported, which raise the question for the source of DMN changes in MDD. Testing whether the DMN abnormalities in MDD can be traced to either a local, i.e., intra-network, or a global, i.e., inter-network, source, we conducted a novel sequence of rsFC analyses, i.e., global FC, intra-network FC, and inter-network FC. Moreover, all analyses were conducted without global signal regression (non-GSR) and with GSR in order to identify the impact of specifically the global component of functional connectivity on within-network functional connectivity within specifically the DMN. In MDD our findings demonstrate (i) increased representation of global signal correlation (GSCORR) in DMN regions, as confirmed independently by degree of centrality (DC) and by an independent DMN template, (ii) increased within-network DMN rsFC, (iii) highly increased inter-network rsFC of both lower- and higher order non-DMN networks with DMN, (iv) high accuracy in classifying MDD vs. healthy subjects by using GSCORR as predictor. Further supporting the global, i.e., non-DMN source of within-network rsFC of the DMN, all results were obtained only when including the global signal, i.e., non-GSR, but not when conducting GSR. Together, we show for the first time increased global signal representation within rsFC of DMN as stemming from inter-network sources as distinguished from local sources, i.e., within- or intra-DMN.