Spontaneous activity in default-mode network predicts ascription of self-relatedness to stimuli

Decoding individual differences in self-prioritization from the resting-state functional connectome

Although the self has traditionally been viewed as a higher-order mental function by most theoretical frameworks, recent research advocates a fundamental self hypothesis, viewing the self as a baseline function of the brain embedded within its spontaneous activities, which dynamically regulates cognitive processing and subsequently guides behavior. Understanding this fundamental self hypothesis can reveal where self-biased behaviors emerge and to what extent brain signals at rest can predict such biased behaviors. To test this hypothesis, we investigated the association between spontaneous neural connectivity and robust self-bias in a perceptual matching task using resting-state functional magnetic resonance imaging (fMRI) in 348 young participants. By decoding whole-brain connectivity patterns, the support vector regression model produced the best predictions of the magnitude of self-bias in behavior, which was evaluated via a nested cross-validation procedure. The out-of-sample generalizability was further authenticated using an external dataset of older adults. The functional connectivity results demonstrated that self-biased behavior was associated with distinct connections between the default mode, cognitive control, and salience networks. Consensus network and computational lesion analyses further revealed contributing regions distributed across six networks, extending to additional nodes, such as the thalamus, whose role in self-related processing remained unclear. These results provide evidence that self-biased behavior derives from spontaneous neural connectivity, supporting the fundamental self hypothesis. Thus, we propose an integrated neural network model of this fundamental self that synthesizes previous theoretical models and portrays the brain mechanisms by which the self emerges at rest internally and regulates responses to the external environment.

Brain State Relays Self-Processing and Heartbeat-Evoked Cortical Responses

The self has been proposed to be grounded in interoceptive processing, with heartbeat-evoked cortical activity as a neurophysiological marker of this processing. However, inconsistent findings have been reported on the relationship between heartbeat-evoked cortical responses and self-processing (including exteroceptive- and mental-self-processing). In this review, we examine previous research on the association between self-processing and heartbeat-evoked cortical responses and highlight the divergent temporal-spatial characteristics and brain regions involved. We propose that the brain state relays the interaction between self-processing and heartbeat-evoked cortical responses and thus accounts for the inconsistency. The brain state, spontaneous brain activity which highly and continuously changes in a nonrandom way, serves as the foundation upon which the brain functions and was proposed as a point in an extremely high-dimensional space. To elucidate our assumption, we provide reviews on the interactions between dimensions of brain state with both self-processing and heartbeat-evoked cortical responses. These interactions suggest the relay of self-processing and heartbeat-evoked cortical responses by brain state. Finally, we discuss possible approaches to investigate whether and how the brain state impacts the self-heart interaction.

Intrinsic neural timescales mediate the cognitive bias of self - temporal integration as key mechanism

Our perceptions and decisions are not always objectively correct as they are featured by a bias related to our self. What are the behavioral, neural, and computational mechanisms of such cognitive bias? Addressing this yet unresolved question, we here investigate whether the cognitive bias is related to temporal integration and segregation as mediated by the brain's Intrinsic neural timescales (INT). Using Signal Detection Theory (SDT), we operationalize the cognitive bias by the Criterion C as distinguished from the sensitivity index d'. This was probed in a self-task based on morphed self- and other faces. Behavioral data demonstrate clear cognitive bias, i.e., Criterion C. That was related to the EEG-based INT as measured by the autocorrelation window (ACW) in especially the transmodal regions dorsolateral prefrontal cortex (dlPFC) and default-mode network (DMN) as distinct from unimodal visual cortex. Finally, simulation of the same paradigm in a large-scale network model shows high degrees of temporal integration of temporally distinct inputs in CMS/DMN and dlPFC while temporal segregation predominates in visual cortex. Together, we demonstrate a key role of INT-based temporal integration in CMS/DMN and dlPFC including its relation to the brain's uni-transmodal topographical organization in mediating the cognitive bias of our self.

Dual interaction between heartbeat-evoked responses and stimuli

Heartbeat-evoked responses (HERs) can interact with external stimuli and play a crucial role in shaping perception, self-related processes, and emotional processes. On the one hand, the external stimulus could modulate HERs. On the other hand, the HERs could affect cognitive processing of the external stimulus. Whether the same neural mechanism underlies these two processes, however, remains unclear. Here, we investigated this interactive mechanism by measuring HERs using magnetoencephalography (MEG) and two name perception tasks. Specifically, we tested (1) how hearing a subject's own name (SON) modulates HERs and (2) how the judgment of an SON is biased by prestimulus HERs. The results showed a dual interaction between HERs and SON. In particular, SON can modulate HERs for heartbeats occurring from 200 to 1200 ms after SON presentation. In addition, prestimulus HERs can bias the SON judgment when a stimulus is presented. Importantly, MEG activities from these two types of interactions differed in spatial and temporal patterns, suggesting that they may be associated with distinct neural pathways. These findings extend our understanding of brain-heart interactions.

Ongoing Brain Activity and Its Role in Cognition: Dual versus Baseline Models

What is the role of the brain's ongoing activity for cognition? The predominant perspectives associate ongoing brain activity with resting state, the default-mode network (DMN), and internally oriented mentation. This triad is often contrasted with task states, non-DMN brain networks, and externally oriented mentation, together comprising a "dual model" of brain and cognition. In opposition to this duality, however, we propose that ongoing brain activity serves as a neuronal baseline; this builds upon Raichle's original search for the default mode of brain function that extended beyond the canonical default-mode brain regions. That entails what we refer to as the "baseline model." Akin to an internal biological clock for the rest of the organism, the ongoing brain activity may serve as an internal point of reference or standard by providing a shared neural code for the brain's rest as well as task states, including their associated cognition. Such shared neural code is manifest in the spatiotemporal organization of the brain's ongoing activity, including its global signal topography and dynamics like intrinsic neural timescales. We conclude that recent empirical evidence supports a baseline model over the dual model; the ongoing activity provides a global shared neural code that allows integrating the brain's rest and task states, its DMN and non-DMN, and internally and externally oriented cognition.

Intrinsic neural activity predisposes susceptibility to a body illusion

Susceptibility to the rubber hand illusion (RHI) varies. To date, however, there is no consensus explanation of this variability. Previous studies, focused on the role of multisensory integration, have searched for neural correlates of the illusion. But those studies have failed to identify a sufficient set of functionally specific neural correlates. Because some evidence suggests that frontal α power is one means of tracking neural instantiations of self, we hypothesized that the higher the frontal α power during the eyes-closed resting state, the more stable the self. As a corollary, we infer that the more stable the self, the less susceptible are participants to a blurring of boundaries—to feeling that the rubber hand belongs to them. Indeed, we found that frontal α amplitude oscillations negatively correlate with susceptibility. Moreover, since lower frequencies often modulate higher frequencies, we explored the possibility that this might be the case for the RHI. Indeed, some evidence suggests that high frontal α power observed in low-RHI participants is modulated by δ frequency oscillations. We conclude that while neural correlates of multisensory integration might be necessary for the RHI, sufficient explanation involves variable intrinsic neural activity that modulates how the brain responds to incompatible sensory stimuli.

The Temporally-Integrated Causality Landscape: Reconciling Neuroscientific Theories With the Phenomenology of Consciousness

In recent years, there has been a proliferation of neuroscientific theories of consciousness. These include theories which explicitly point to EM fields, notably Operational Architectonics and, more recently, the General Resonance Theory. In phenomenological terms, human consciousness is a unified composition of contents. These contents are specific and meaningful, and they exist from a subjective point of view. Human conscious experience is temporally continuous, limited in content, and coherent. Based upon those phenomenal observations, pre-existing theories of consciousness, and a large body of experimental evidence, I derived the Temporally-Integrated Causality Landscape (TICL). In brief, the TICL proposes that the neural correlate of consciousness is a structure of temporally integrated causality occurring over a large portion of the thalamocortical system. This structure is composed of a large, integrated set of neuronal elements (the System), which contains some subsystems, defined as having a higher level of temporally-integrated causality than the System as a whole. Each Subsystem exists from the point of view of the System, in the form of meaningful content. In this article, I review the TICL and consider the importance of EM forces as a mechanism of neural causality. I compare the fundamentals of TICL to those of several other neuroscientific theories. Using five major characteristics of phenomenal consciousness as a standard, I compare the basic tenets of Integrated Information Theory, Global Neuronal Workspace, General Resonance Theory, Operational Architectonics, and the Temporo-spatial Theory of Consciousness with the framework of the TICL. While the literature concerned with these theories tends to focus on different lines of evidence, there are fundamental areas of agreement. This means that, in time, it may be possible for many of them to converge upon the truth. In this analysis, I conclude that a primary distinction which divides these theories is the feature of spatial and temporal nesting. Interestingly, this distinction does not separate along the fault line between theories explicitly concerned with EM fields and those which are not. I believe that reconciliation is possible, at least in principle, among those theories that recognize the following: just as the contents of consciousness are distinctions within consciousness, the neural correlates of conscious content should be distinguishable from but fall within the spatial and temporal boundaries of the full neural correlates of consciousness.

Spontaneous thought-related network connectivity predicts sertraline effect on major depressive disorder

Sertraline is one of the most commonly prescribed antidepressants. Major depressive disorder (MDD) is characterized by spontaneous thoughts that are laden with negative affect-a "malignant sadness". Prior neuroimaging studies have identified abnormal resting-state functional connectivity (rsFC) in the spontaneous brain networks of MDD patients. But how antidepressant medication acts to relieve the experience of depression as well as adjust its associated spontaneous networks and mood-regulation circuits remains an open question. In this study, we recruited 22 drug-naïve MDD patients along with 35 normal controls and investigated whether the functional integrity of cortical networks associated with spontaneous thoughts is modulated by sertraline treatment. We attempted to predict post-treatment effects based upon what we observed in the pre-treatment rsFC of drug-naïve MDD patients. In the result, we demonstrated that (1) after the sertraline treatment, the medial temporal lobe of default network (DN_MTL) and mood regulation pathway-the fronto-parietal control network (FPCN), the thalamus, and the salience network (SN)-were restored to normal connectivity, relative to the pre-treatment condition; however, the altered connections of FPCN-core DN (DN_CORE), FPCN-SN, and intra-FPCN among MDD patients remained impaired; (2) thalamo-prefrontal connectivity provides moderate predictive power (r² = 0.63) for the effectiveness of sertraline treatment. In summary, our findings contribute to a body of evidence that suggests salubrious effects of sertraline treatment primarily involve the FPCN-thalamus-SN pathway. The pre-treatment rsFC in this pathway could serve as a predictor of sertraline treatment outcome.

Dynamic relationships between spontaneous and evoked electrophysiological activity

Spontaneous neural activity fluctuations have been shown to influence trial-by-trial variation in perceptual, cognitive, and behavioral outcomes. However, the complex electrophysiological mechanisms by which these fluctuations shape stimulus-evoked neural activity remain largely to be explored. Employing a large-scale magnetoencephalographic dataset and an electroencephalographic replication dataset, we investigate the relationship between spontaneous and evoked neural activity across a range of electrophysiological variables. We observe that for high-frequency activity, high pre-stimulus amplitudes lead to greater evoked desynchronization, while for low frequencies, high pre-stimulus amplitudes induce larger degrees of event-related synchronization. We further decompose electrophysiological power into oscillatory and scale-free components, demonstrating different patterns of spontaneous-evoked correlation for each component. Finally, we find correlations between spontaneous and evoked time-domain electrophysiological signals. Overall, we demonstrate that the dynamics of multiple electrophysiological variables exhibit distinct relationships between their spontaneous and evoked activity, a result which carries implications for experimental design and analysis in non-invasive electrophysiology.

Self-Dependent Neural Variability Predicts Recovery from Depressive Symptoms

Researchers have increasingly paid attention to the neural dynamics of depression. This study examined whether self-dependent neural variability predicts recovery from depressive symptoms. Sixty adults with depressive symptoms who were not officially diagnosed with major depressive disorder participated in this study. Participants completed functional magnetic resonance imaging (fMRI) scanning, including a resting-state and a self-reflection task. The fMRI data were used to estimate neural variability, which refers to the temporal variability in regional functional connectivity patterns. Participants then completed the Self-Construal Scale and the Beck Depression Inventory (BDI). The change in BDI scores over 3 months indicated the degree of recovery from depressive symptoms. Self-construal moderated the effects of general neural variability on predicting recovery from depressive symptoms. Interdependent individuals became less depressive with higher general neural variability, but the relationship was not significant in independent individuals. The differences in neural variability between self-related and other-related conditions also predicted recovery from depressive symptoms. The regions contributing to the prediction were mainly distributed in the default-mode network. Based on these results, the harmony between individuals’ neural dynamics and self-concept is important for recovery from depressive symptoms, which might be a foundation for individualized treatment and counseling.

The perspectives of mapping and monitoring of the sense of self in neurosurgical patients

Surgical treatment of tumors, epileptic foci or of vascular origin, requires a detailed individual pre-surgical workup and intra-operative surveillance of brain functions to minimize the risk of post-surgical neurological deficits and decline of quality of life. Most attention is attributed to language, motor functions, and perception. However, higher cognitive functions such as social cognition, personality, and the sense of self may be affected by brain surgery. To date, the precise localization and the network patterns of brain regions involved in such functions are not yet fully understood, making the assessment of risks of related post-surgical deficits difficult. It is in the interest of neurosurgeons to understand with which neural systems related to selfhood and personality they are interfering during surgery. Recent neuroscience research using virtual reality and clinical observations suggest that the insular cortex, medial prefrontal cortex, and temporo-parietal junction are important components of a neural system dedicated to self-consciousness based on multisensory bodily processing, including exteroceptive and interoceptive cues (bodily self-consciousness (BSC)). Here, we argue that combined extra- and intra-operative approaches using targeted cognitive testing, functional imaging and EEG, virtual reality, combined with multisensory stimulations, may contribute to the assessment of the BSC and related cognitive aspects. Although the usefulness of particular biomarkers, such as cardiac and respiratory signals linked to virtual reality, and of heartbeat evoked potentials as a surrogate marker for intactness of multisensory integration for intra-operative monitoring has to be proved, systemic and automatized testing of BSC in neurosurgical patients will improve future surgical outcome.

The Lost Neural Hierarchy of the Autistic Self-Locked-Out of the Mental Self and Its Default-Mode Network

Autism spectrum disorder (ASD) is characterized by a fundamental change in self-awareness including seemingly paradoxical features like increased ego-centeredness and weakened self-referentiality. What is the neural basis of this so-called "self-paradox"? Conducting a meta-analytic review of fMRI rest and task studies, we show that ASD exhibits consistent hypofunction in anterior and posterior midline regions of the default-mode network (DMN) in both rest and task with decreased self-non-self differentiation. Relying on a multilayered nested hierarchical model of self, as recently established (Qin et al. 2020), we propose that ASD subjects cannot access the most upper layer of their self, the DMN-based mental self-they are locked-out of their own DMN and its mental self. This, in turn, results in strong weakening of their self-referentiality with decreases in both self-awareness and self-other distinction. Moreover, this blocks the extension of non-DMN cortical and subcortical regions at the lower layers of the physical self to the DMN-based upper layer of the mental self, including self-other distinction. The ASD subjects remain stuck and restricted to their intero- and exteroceptive selves as manifested in a relative increase in ego-centeredness (as compared to self-referentiality). This amounts to what we describe as "Hierarchical Model of Autistic Self" (HAS), which, characterizing the autistic self in hierarchical and spatiotemporal terms, aligns well with and extends current theories of ASD including predictive coding and weak central coherence.

Abnormal ERPs and Brain Dynamics Mediate Basic Self Disturbance in Schizophrenia: A Review of EEG and MEG Studies

Background: Interest in disordered sense of self in schizophrenia has recently re-emerged in the literature. It has been proposed that there is a basic self disturbance, underlying the diagnostic symptoms of schizophrenia, in which the person's sense of being a bounded individual continuous through time loses stability. This disturbance has been documented phenomenologically and at the level of cognitive tasks. However, the neural correlates of basic self disorder in schizophrenia are poorly understood. Methods: A search of PubMed was used to identify studies on self and schizophrenia that reported EEG or MEG data. Results: Thirty-three studies were identified, 32 using EEG and one using MEG. Their operationalizations of the self were divided into six paradigms: self-monitoring for errors, proprioception, self-other integration, self-referential processing, aberrant salience, and source monitoring. Participants with schizophrenia were less accurate on self-referential processing tasks and had slower response times across most studies. Event-related potential amplitudes differed across many early and late components, with reduced N100 suppression in source monitoring paradigms being the most replicated finding. Several studies found differences in one or more frequency band, but no coherent overall finding emerged in this area. Various other measures of brain dynamics also showed differences in single studies. Only some of the study designs were adequate to establish a causal relationship between the self and EEG or MEG measures. Conclusion: The broad range of changes suggests a global self disturbance at the neuronal level, possibly carried over from the resting state. Further studies that successfully isolate self-related effects are warranted to better understand the temporal-dynamic and spatial-topographic basis of self disorder and its relationship to basic self disturbance on the phenomenological level.

Self-reference Network-Related Interactions During the Process of Cognitive Impairment in the Early Stages of Alzheimer's Disease

Background: Normal establishment of cognition occurs after forming a sensation to stimuli from internal or external cues, in which self-reference processing may be partially involved. However, self-reference processing has been less studied in the Alzheimer’s disease (AD) field within the self-reference network (SRN) and has instead been investigated within the default-mode network (DMN). Differences between these networks have been proven in the last decade, while ultra-early diagnoses have increased. Therefore, investigation of the altered pattern of SRN is significantly important, especially in the early stages of AD.

Methods: A total of 65 individuals, including 43 with mild cognitive impairment (MCI) and 22 cognitively normal individuals, participated in this study. The SRN, dorsal attention network (DAN), and salience network (SN) were constructed with resting-state functional magnetic resonance imaging (fMRI), and voxel-based analysis of variance (ANOVA) was used to explore significant regions of network interactions. Finally, the correlation between the network interactions and clinical characteristics was analyzed.

Results: We discovered four interactions among the three networks, with the SRN showing different distributions in the left and right hemispheres from the DAN and SN and modulated interactions between them. Group differences in the interactions that were impaired in MCI patients indicated that the degree of damage was most severe in the SRN, least severe in the SN, and intermediate in the DAN. The two SRN-related interactions showed positive effects on the executive and memory performances of MCI patients with no overlap with the clinical assessments performed in this study.

Conclusion: This study is the first and primary evidence of SRN interactions related to MCI patients’ functional performance. The influence of the SRN in the ultra-early stages of AD is nonnegligible. There are still many unknowns regarding the contribution of the SRN in AD progression, and we strongly recommend future research in this area.

The minimal self hypothesis

For millennia self has been conjectured to be necessary for consciousness. But scant empirical evidence has been adduced to support this hypothesis. Inconsistent explications of "self" and failure to design apt experiments have impeded progress. Advocates of phenomenological psychiatry, however, have helped explicate "self," and employed it to explain some psychopathological symptoms. In those studies, "self" is understood in a minimalist sense, sheer "for-me-ness." Unfortunately, explication of the "minimal self" (MS) has relied on conceptual analysis, and applications to psychopathology have been hermeneutic, allowing for many degrees of interpretive latitude. The result is that MS's current scientific status is analogous to that of the "atom," at the time when "atom" was just beginning to undergo transformation from a philosophical to a scientific concept. Fortunately, there is now an opportunity to promote a similar transformation for "MS." Discovery of the brain's Default Mode Network (DMN) opened the door to neuroimaging investigations of self. Taking the DMN and other forms of intrinsic activity as a starting point, an empirical foothold can be established, one that spurs experimental research and that enables extension of research into multiple phenomena. New experimental protocols that posit "MS" can help explain phenomena hitherto not thought to be related to self, thereby hastening development of a mature science of self. In particular, targeting phenomena wherein consciousness is lost and recovered, as in some cases of Unresponsive Wakefulness Syndrome (UWS), allow for design of neuroimaging probes that enable detection of MS during non-conscious states. These probes, as well as other experimental protocols applied to NREM Sleep, General Anesthesia (GA), and the waking state, provide some evidence to suggest that not only can self and consciousness dissociate, MS might be a necessary precondition for conscious experience. Finally, these findings have implications for the science of consciousness: it has been suggested that "levels of consciousness" (LoC) is not a legitimate concept for the science of consciousness. But because we have the conceptual and methodological tools with which to refine investigations of MS, we have the means to identify a possible foundation-a bifurcation point-for consciousness, as well as the means by which to measure degrees of distance from that foundation. These neuroimaging investigations of MS position us to better assess whether LoC has a role to play in a mature science of consciousness.

Diminished self-monitoring in hallucinations - Aberrant anterior insula connectivity differentiates auditory hallucinations in schizophrenia from subjective tinnitus

Auditory hallucinations in schizophrenia (SCZ-AH) and subjective tinnitus (TN) are two conditions that share a superficial resemblance, namely the presence of phantom sounds produced by the brain. A crucial difference between them lies in the self-processing of the phantom signals, which is intact in TN patients but lost in SCZ-AH. Our study sets out to investigate the potential neural mechanisms for this crucial psychotic symptom of SCZ-AH under the framework of self. We gathered resting-state fMRI data from three participant groups: SCZ-AH, TN and healthy controls. Focusing on predefined self-related regions-of-interest, we found that SCZ-AH had reduced degree centrality in the right anterior insula (rAI) compared to both TN and healthy controls. Further functional connectivity analysis showed a reduced connectivity between the rAI and right superior temporal gyrus. Our finding indicates that compromised self-processing in SCZ-AH could be due to aberrant connectivity in rAI, which interacted with the decreased connectivity between rAI and auditory cortex, and jointly contributed to the misattribution of the source of the phantom sound. Our findings provided preliminary evidence for the neural mechanism of self-disorder underlying SCZ-AH, and could provide implications for investigating other modalities of hallucinations in schizophrenia.

Spatiotemporal neuroscience - what is it and why we need it

The excellent commentaries to our target paper hint upon three main issues, (i) spatiotemporal neuroscience; (ii) neuro-mental relationship; and (iii) mind, brain, and world relationship. (i) We therefore discuss briefly the history of Spatiotemporal Neuroscience. Distinguishing it from Cognitive Neuroscience and related branches (like Affective, Social, etc. Neuroscience), Spatiotemporal Neuroscience can be characterized by focus on brain activity (rather than brain function), spatiotemporal relationship (rather than input-cognition-output relationship), and structure (rather than stimuli/contents). (ii) Taken in this sense, Spatiotemporal Neuroscience allows one to conceive the neuro-mental relationship in dynamic spatiotemporal terms that complement and extend (rather than contradict) their cognitive characterization. (iii) Finally, more philosophical issues like the need to dissolve the mind-body problem (and replace it by the world-brain relation) and the question for different levels of time including their nestedness are discussed.

Distinguishing vigilance decrement and low task demands from mind-wandering: A machine learning analysis of EEG

Mind‐wandering is a ubiquitous mental phenomenon that is defined as self‐generated thought irrelevant to the ongoing task. Mind‐wandering tends to occur when people are in a low‐vigilance state or when they are performing a very easy task. In the current study, we investigated whether mind‐wandering is completely dependent on vigilance and current task demands, or whether it is an independent phenomenon. To this end, we trained support vector machine (SVM) classifiers on EEG data in conditions of low and high vigilance, as well as under conditions of low and high task demands, and subsequently tested those classifiers on participants' self‐reported mind‐wandering. Participants' momentary mental state was measured by means of intermittent thought probes in which they reported on their current mental state. The results showed that neither the vigilance classifier nor the task demands classifier could predict mind‐wandering above‐chance level, while a classifier trained on self‐reports of mind‐wandering was able to do so. This suggests that mind‐wandering is a mental state different from low vigilance or performing tasks with low demands—both which could be discriminated from the EEG above chance. Furthermore, we used dipole fitting to source‐localize the neural correlates of the most import features in each of the three classifiers, indeed finding a few distinct neural structures between the three phenomena. Our study demonstrates the value of machine‐learning classifiers in unveiling patterns in neural data and uncovering the associated neural structures by combining it with an EEG source analysis technique.

Intrinsic activity temporal structure reactivity to behavioural state change is correlated with depressive symptoms

The brain's intrinsic activity plays a fundamental role in its function. In normal conditions this activity is responsive to behavioural context, changing as an individual switches between directed tasks and task-free conditions. A key feature of such changes is the movement of the brain between corresponding critical and sub-critical states, with these dynamics supporting efficient cognitive processing. Breakdowns in processing efficiency can occur, however, in brain disorders such as depression. It was therefore hypothesised that depressive symptoms would be related to reduced intrinsic activity responsiveness to changes in behavioural state. This was tested in a mixed group of major depressive disorder patients (n = 26) and healthy participants (n = 37) by measuring intrinsic EEG activity temporal structure, quantified with detrended fluctuation analysis (DFA), in eyes-closed (EC) and eyes-open task-free states and contrasting between the conditions. The degree to which DFA values changed between the states was found to correlate negatively with depressive symptoms. DFA values did not differ between states in those with higher symptom levels, meaning that the brain remained in a less flexible sub-critical condition. This sub-critical condition in the EC state was further found to correlate with levels of maladaptive rumination. This may reflect a general cognitive inflexibility resulting from a lack in neural activity reactivity that may predispose people to overly engage in self-directed attention. These results provide an initial link between intrinsic activity reactivity and psychological features found in psychiatric disorders.

Microstructural white matter alterations in borderline personality disorder: A minireview

BACKGROUND

Borderline personality disorder (BPD) affects 1-5% of the population and is characterized by a complex symptomatology and selective functional impairments. Although brain imaging studies have contributed to better characterizing the pathophysiological mechanisms underlying BPD, the white matter (WM) deficits associated with this disorder are still unclear. Therefore, the present review aims at providing an overview of the findings emerged from the available diffusion tensor imaging (DTI) studies on BPD.

METHODS

From a bibliographic research in PubMed until May 2019, we collected 12 studies that fulfilled our inclusion criteria, including a total sample of 291 BPD subjects and 293 healthy controls.

RESULTS

Overall, the DTI studies reviewed showed impairments in selective WM tracts that are part of the prefronto-limbic system, including frontal WM (short and long tracts), anterior cingulate cortex, corpus callosum, corona radiata, hippocampal fornix and thalamic radiation, in BPD patients compared to healthy controls.

LIMITATIONS

Few DTI studies with heterogeneous findings.

CONCLUSIONS

Overall these results reported that BPD is characterized by selective structural connectivity alterations in prefronto-limbic structures, further supporting the neurobiological model of BPD that suggests the presence of an abnormal modulation of frontal regions over limbic structures. Finally, the results also highlighted that the disrupted WM integrity in selective brain regions may also explain key-aspects of BPD symptomatology, including emotional dysregulation, ambivalence, contradictory behaviors and cognitive dysfunctions.

The self in art therapy - Brain-based assessment of the drawing process

Art therapy plays important role in classical psychological assessment as it allows expressing the subject's sense of self. However, its effectiveness and validity could be impeded by lack of relationship to the patients' neuronal changes in their brain. The aim of our theoretical-empirical paper is to propose a novel brain-based quantitative objective measurement of the self and how it shapes the drawing process. We discuss recent data that how the autocorrelation window (ACW) is related to the temporal continuity of self in current neuroscience and further develop a method to use ACW to measure the temporal continuity of the drawing process, probing it in two case studies. As expected, the schizophrenic subject shows lower ACW values compared to the healthy subject and reflects the well-known deficit in the temporal continuity of the self in schizophrenia. We concluded that ACW and eventually other measures of the brain's spatiotemporal structure might be able to serve as objective markers of the self in the drawing process. As our approach connects brain, self, and drawing process, it provides the theoretical basis for the future development of a brain-based assessment of the self in the drawing process and art therapy.

The Role of Semantic Gender in Name Comprehension: An Event-Related Potentials Study

It is well known that the semantic features of gender associated with peoples' names are represented in the conceptual semantic system. However, there is scant evidence that such knowledge plays a role in name comprehension, and if so, in which processing stage this occurs. The aim of this study was to provide evidence concerning the time course of the activation of semantic gender in the processing of people's names. We recorded event-related potentials when participants saw picture-name pairs. Compared with the gender congruent condition in which the priming picture and Chinese name were matched on gender, names in the gender incongruent condition showed a mismatch effect in the time windows of 300-500 ms and 500-700 ms. These findings illustrate for the first time the activation of semantic gender when processing people's names, and further specify that this access occurs in the stage of name recognition rather than person identification.

Functional connectivity pattern underlies individual differences in independent self-construal

Independent vs interdependent self-construal is a concept that reflects how people perceive the relationship between self and other people, which has been extensively examined across disciplines. However, little evidence on the whole-brain functional connectivity (FC) pattern of independent vs interdependent self-construal has been reported. Here, in a sample of 51 healthy participants, we used resting-state functional magnetic resonance imaging and voxel-based FC analysis (i.e. FC strength and seed-based FC) by measuring the temporal correlation of blood oxygen level-dependent signals between spatially separate brain regions to investigate the neural mechanism of independent vs interdependent self-construal. First, we found that FC strength of bilateral posterior cingulate cortex and precuneus, and left inferior frontal gyrus were positively correlated with the independent vs interdependent score. Seed-based FC analysis with these three regions as seeds revealed that, FC within default mode network and executive control network was positively correlated with the independent vs interdependent score. Negative correlation with independent vs interdependent score was shown in the connections between default mode network and executive control regions. Taking together, our results provide a comprehensive FC architecture of the independent vs interdependent self-construal and advance the understanding of the interplay between culture, mind and brain.

The temporal signature of self: Temporal measures of resting-state EEG predict self-consciousness

The self is the core of our mental life. Previous investigations have demonstrated a strong neural overlap between self-related activity and resting state activity. This suggests that information about self-relatedness is encoded in our brain's spontaneous activity. The exact neuronal mechanisms of such "rest-self containment," however, remain unclear. The present EEG study investigated temporal measures of resting state EEG to relate them to self-consciousness. This was obtained with the self-consciousness scale (SCS) which measures Private, Public, and Social dimensions of self. We demonstrate positive correlations between Private self-consciousness and three temporal measures of resting state activity: scale-free activity as indexed by the power-law exponent (PLE), the auto-correlation window (ACW), and modulation index (MI). Specifically, higher PLE, longer ACW, and stronger MI were related to higher degrees of Private self-consciousness. Finally, conducting eLORETA for spatial tomography, we found significant correlation of Private self-consciousness with activity in cortical midline structures such as the perigenual anterior cingulate cortex and posterior cingulate cortex. These results were reinforced with a data-driven analysis; a machine learning algorithm accurately predicted an individual as having a "high" or "low" Private self-consciousness score based on these measures of the brain's spatiotemporal structure. In conclusion, our results demonstrate that Private self-consciousness is related to the temporal structure of resting state activity as featured by temporal nestedness (PLE), temporal continuity (ACW), and temporal integration (MI). Our results support the hypothesis that self-related information is temporally contained in the brain's resting state. "Rest-self containment" can thus be featured by a temporal signature.

Why People Are Always Thinking about Themselves: Medial Prefrontal Cortex Activity during Rest Primes Self-referential Processing

Humans have a tendency to think about themselves. What generates this self-focus? One clue may come from the observation that the same part of the brain that supports self-reflection—the medial pFC (MPFC/Brodmann's area 10 [BA 10])—also spontaneously engages by default whenever the brain is free from external demands to attention. Here, we test the possibility that the default tendency to engage MPFC/BA 10 primes self-referential thinking. Participants underwent fMRI while alternating between brief periods of rest and experimental tasks in which they thought about their own traits, another person's traits, or another location's traits. Greater default engagement in MPFC/BA 10 during momentary breaks preferentially facilitated task performance on subsequent self-reflection trials on a moment-to-moment basis. These results suggest that reflexively engaging MPFC/BA 10 by default may nudge self-referential thinking, perhaps explaining why humans think about themselves so readily.

How spontaneous brain activity and narcissistic features shape social interaction

There is an increasing interest in how ongoing spontaneous brain activity and personality provide a predisposition for the processing of environmental demands. It further has been suggested that the brain has an inherent sensitivity to the social environment. Here we tested in healthy volunteers if spontaneous brain activity contributes to a predisposition for social behavior and how this is modulated by narcissistic personality features associated with poor interpersonal functioning. Functional magnetic resonance imaging included a resting state and an experimental paradigm focusing on the anticipation of actively touching an animate (human hand) versus an inanimate target (mannequin hand). The experimental task induced a significant modulation of neural activity in left postcentral gyrus (PostCG), right culmen and, co-varying with narcissistic features, in right anterior insula (AI). Neural activity in anticipation of the animate target significantly correlated with spontaneous activity during the resting state indexed by the Power Law Exponent (PLE) in PostCG and AI. Finally, the correlation between spontaneous and task-induced activity in AI was mediated by narcissistic features. These findings provide novel evidence for a relationship between intrinsic brain activity and social behavior and show how personality could contribute to individual differences in our predisposition to approach the animate world.

How do the brain's time and space mediate consciousness and its different dimensions? Temporo-spatial theory of consciousness (TTC)

Time and space are the basic building blocks of nature. As a unique existent in nature, our brain exists in time and takes up space. The brain's activity itself also constitutes and spreads in its own (intrinsic) time and space that is crucial for consciousness. Consciousness is a complex phenomenon including different dimensions: level/state, content/form, phenomenal aspects, and cognitive features. We propose a Temporo-spatial Theory of Consciousness (TTC) focusing primarily on the temporal and spatial features of the brain activity. We postulate four different neuronal mechanisms accounting for the different dimensions of consciousness: (i) "temporo-spatial nestedness" of the spontaneous activity accounts for the level/state of consciousness as neural predisposition of consciousness (NPC); (ii) "temporo-spatial alignment" of the pre-stimulus activity accounts for the content/form of consciousness as neural prerequisite of consciousness (preNCC); (iii) "temporo-spatial expansion" of early stimulus-induced activity accounts for phenomenal consciousness as neural correlates of consciousness (NCC); (iv) "temporo-spatial globalization" of late stimulus-induced activity accounts for the cognitive features of consciousness as neural consequence of consciousness (NCCcon).

A Historical Review of Diachrony and Semantic Dimensions of Trace in Neurosciences and Lacanian Psychoanalysis

Experience leaves a trace in the nervous system through plasticity. However, the exact meaning of the mnesic trace is poorly defined in current literature. This article provides a historical review of the term trace in neuroscience and psychoanalysis literature, to highlight two relevant aspects: the diachronic and the semantic dimensions. There has been a general interest in diachrony, or a form of evolution of the trace, but its indissociable semantic dimension remains partially disregarded. Although frequently implied, the diachronic and semantic dimensions of the trace are rarely clearly articulated. We situate this discussion into the classical opposition of syntax, or rules of inscription of the trace in the nervous system, and semantics, or the content of the trace, which takes into consideration the attempt of the human being to build coherence. A general observation is that the study of the term trace follows trends of the thought of the given epoch. This historical analysis also reveals the decay of the idea that the trace is reliable to the experience. From the articulation between neurosciences and psychoanalysis in a historical perspective, this review shows that the trend is to consider trace as a production of the subject, resulting in a permanent rewriting in an attempt to give meaning to the experience. This trend is becoming increasingly evident in light of recent research in neurosciences and psychoanalysis.

How do abnormalities in the brain's spontaneous activity translate into symptoms in schizophrenia? From an overview of resting state activity findings to a proposed spatiotemporal psychopathology

Schizophrenia is a complex neuropsychiatric disorder with a variety of symptoms that include sensorimotor, affective, cognitive, and social changes. The exact neuronal mechanisms underlying these symptoms remain unclear though. Neuroimaging has focused mainly on the brain's extrinsic activity, specifically task-evoked or stimulus-induced activity, as related to the sensorimotor, affective, cognitive, and social functions. Recently, the focus has shifted to the brain's spontaneous activity, otherwise known as its resting state activity. While various spatial and temporal abnormalities have been observed in spontaneous activity in schizophrenia, their meaning and significance for the different psychopathological symptoms in schizophrenia, are yet to be defined. The first aim in this paper is to provide an overview of recent findings concerning changes in the spatial (e.g., functional connectivity) and temporal (e.g., couplings between different frequency fluctuations) properties of spontaneous activity in schizophrenia. The second aim is to link these spatiotemporal changes to the various psychopathological symptoms of schizophrenia, with a specific focus on basic symptoms, formal thought disorder, and ego-disturbances. Based on the various findings described, we postulate that the spatiotemporal changes on the neuronal level of the brain's spontaneous activity transform into corresponding spatiotemporal changes on the psychological level which, in turn, leads to the different kinds of psychopathological symptoms. We consequently suggest a spatiotemporal rather than cognitive or sensory approach to the condition, amounting to what we describe as "Spatiotemporal Psychopathology".