Spatiotemporal neuroscience - what is it and why we need it

Motor versus Psychomotor? Deciphering the Neural Source of Psychomotor Retardation in Depression

Major depressive disorder (MDD) is characterized by psychomotor retardation whose underlying neural source remains unclear. Psychomotor retardation may either be related to a motor source like the motor cortex or, alternatively, to a psychomotor source with neural changes outside motor regions, like input regions such as visual cortex. These two alternative hypotheses in main (n = 41) and replication (n = 18) MDD samples using 7 Tesla MRI are investigated. Analyzing both global and local connectivity in primary motor cortex (BA4), motor network and middle temporal visual cortex complex (MT+), the main findings in MDD are: 1) Reduced local and global synchronization and increased local-to-global output in motor regions, which do not correlate with psychomotor retardation, though. 2) Reduced local-to-local BA4 - MT+ functional connectivity (FC) which correlates with psychomotor retardation. 3) Reduced global synchronization and increased local-to-global output in MT+ which relate to psychomotor retardation. 4) Reduced variability in the psychophysical measures of MT+ based motion perception which relates to psychomotor retardation. Together, it is shown that visual cortex MT+ and its relation to motor cortex play a key role in mediating psychomotor retardation. This supports psychomotor over motor hypothesis about the neural source of psychomotor retardation in MDD.

The nested hierarchical model of self and its non-relational vs relational posttraumatic manifestation: an fMRI meta-analysis of emotional processing

Different kinds of traumatic experiences like natural catastrophes vs. relational traumatic experiences (e.g., sex/physical abuse, interpersonal partner violence) are involved in the development of the self and PTSD psychopathological manifestations. Looking at a neuroscience approach, it has been proposed a nested hierarchical model of self, which identifies three neural-mental networks: (i) interoceptive; (ii) exteroceptive; (iii) mental. However, it is still unclear how the self and its related brain networks might be affected by non-relational vs relational traumatic experiences. Departing from this background, the current study aims at conducting a meta-analytic review of task-dependent fMRI studies (i.e., emotional processing task) among patients with PTSD due to non-relational (PTSD-NR) and relational (PTSD-R) traumatic experiences using two approaches: (i) a Bayesian network meta-analysis for a region-of-interest-based approach; (ii) a coordinated-based meta-analysis. Our findings suggested that the PTSD-NR mainly recruited areas ascribed to the mental self to process emotional stimuli. Whereas, the PTSD-R mainly activated regions associated with the intero-exteroceptive self. Accordingly, the PTSD-R compared to the PTSD-NR might not reach a higher symbolic capacity to process stimuli with an emotional valence. These results are also clinically relevant in support of the development of differential treatment approaches for non-relational vs. relational PTSD.

Dynamic mechanisms that couple the brain and breathing to the external environment

Brain and breathing activities are closely related. However, the exact neurophysiological mechanisms that couple the brain and breathing to stimuli in the external environment are not yet agreed upon. Our data support that synchronization and dynamic attunement are two key mechanisms that couple local brain activity and breathing to external periodic stimuli. First, we review the existing literature, which provides strong evidence for the synchronization of brain and breathing in terms of coherence, cross-frequency coupling and phase-based entrainment. Second, using EEG and breathing data, we show that both the lungs and localized brain activity at the Cz channel attune the temporal structure of their power spectra to the periodic structure of external auditory inputs. We highlight the role of dynamic attunement in playing a key role in coordinating the tripartite temporal alignment of localized brain activity, breathing and input dynamics across longer timescales like minutes. Overall, this perspective sheds light on potential mechanisms of brain-breathing coupling and its alignment to stimuli in the external environment.

An Unavoidable Mind-Set Reversal: Consciousness in Vision Science

In recent decades, the debate on consciousness has been conditioned by the idea of bottom-up emergence, which has influenced scientific research and raised a few obstacles to any attempt to bridge the explanatory gap. The analysis and explanation of vision conducted according to the accredited methodologies of scientific research in terms of physical stimuli, objectivity, methods, and explanation has encountered the resistance of subjective experience. Moreover, original Gestalt research into vision has generally been merged with cognitive neuroscience. Experimental phenomenology, building on the legacy of Gestalt psychology, has obtained new results in the fields of amodal contours and color stratifications, light perception, figurality, space, so-called perceptual illusions, and subjective space and time. Notwithstanding the outcomes and the impulse given to neuroscientific analyses, the research carried out around these phenomena has never directly confronted the issue of what it means to be conscious or, in other words, the nature of consciousness as self-referentiality. Research has tended to focus on the percept. Therefore, explaining the non-detachability of parts in subjective experience risks becoming a sort of impossible achievement, similar to that of Baron Munchausen, who succeeds in escaping unharmed from this quicksand by pulling himself out by his hair. This paper addresses how to analyze seeing as an undivided whole by discussing several basic dimensions of phenomenal consciousness on an experimental basis and suggesting an alternative way of escaping this quicksand. This mind-set reversal also sheds light on the organization and dependence relationships between phenomenology, psychophysics, and neuroscience.

Beyond task response-Pre-stimulus activity modulates contents of consciousness

The current discussion on the neural correlates of the contents of consciousness (NCCc) focuses mainly on the post-stimulus period of task-related activity. This neglects the substantial impact of the spontaneous or ongoing activity of the brain as manifest in pre-stimulus activity. Does the interaction of pre- and post-stimulus activity shape the contents of consciousness? Addressing this gap in our knowledge, we review and converge two recent lines of findings, that is, pre-stimulus alpha power and pre- and post-stimulus alpha trial-to-trial variability (TTV). The data show that pre-stimulus alpha power modulates post-stimulus activity including specifically the subjective features of conscious contents like confidence and vividness. At the same time, alpha pre-stimulus variability shapes post-stimulus TTV reduction including the associated contents of consciousness. We propose that non-additive rather than merely additive interaction of the internal pre-stimulus activity with the external stimulus in the alpha band is key for contents to become conscious. This is mediated by mechanisms on different levels including neurophysiological, neurocomputational, neurodynamic, neuropsychological and neurophenomenal levels. Overall, considering the interplay of pre-stimulus intrinsic and post-stimulus extrinsic activity across wider timescales, not just evoked responses in the post-stimulus period, is critical for identifying neural correlates of consciousness. This is well in line with both processing and especially the Temporo-spatial theory of consciousness (TTC).

Event segmentation in ADHD: neglect of social information and deviant theta activity point to a mechanism underlying ADHD

Background

Attention-deficit/hyperactivity disorder (ADHD) is one of the most frequently diagnosed psychiatric conditions in children and adolescents. Although the symptoms appear to be well described, no coherent conceptual mechanistic framework integrates their occurrence and variance and the associated problems that people with ADHD face.

Aims

The current study proposes that altered event segmentation processes provide a novel mechanistic framework for understanding deficits in ADHD.

Methods

Adolescents with ADHD and neurotypically developing (NT) peers watched a short movie and were then asked to indicate the boundaries between meaningful segments of the movie. Concomitantly recorded electroencephalography (EEG) data were analysed for differences in frequency band activity and effective connectivity between brain areas.

Results

Compared with their NT peers, the ADHD group showed less dependence of their segmentation behaviour on social information, indicating that they did not consider social information to the same extent as their unaffected peers. This divergence was accompanied by differences in EEG theta band activity and a different effective connectivity network architecture at the source level. Specifically, NT adolescents primarily showed error signalling in and between the left and right fusiform gyri related to social information processing, which was not the case in the ADHD group. For the ADHD group, the inferior frontal cortex associated with attentional sampling served as a hub instead, indicating problems in the deployment of attentional control.

Conclusions

This study shows that adolescents with ADHD perceive events differently from their NT peers, in association with a different brain network architecture that reflects less adaptation to the situation and problems in attentional sampling of environmental information. The results call for a novel conceptual view of ADHD, based on event segmentation theory.

Neural representations of statistical and rule-based predictions in Gilles de la Tourette syndrome

Gilles de la Tourette syndrome (GTS) is a disorder characterised by motor and vocal tics, which may represent habitual actions as a result of enhanced learning of associations between stimuli and responses (S-R). In this study, we investigated how adults with GTS and healthy controls (HC) learn two types of regularities in a sequence: statistics (non-adjacent probabilities) and rules (predefined order). Participants completed a visuomotor sequence learning task while EEG was recorded. To understand the neurophysiological underpinnings of these regularities in GTS, multivariate pattern analyses on the temporally decomposed EEG signal as well as sLORETA source localisation method were conducted. We found that people with GTS showed superior statistical learning but comparable rule-based learning compared to HC participants. Adults with GTS had different neural representations for both statistics and rules than HC adults; specifically, adults with GTS maintained the regularity representations longer and had more overlap between them than HCs. Moreover, over different time scales, distinct fronto-parietal structures contribute to statistical learning in the GTS and HC groups. We propose that hyper-learning in GTS is a consequence of the altered sensitivity to encode complex statistics, which might lead to habitual actions.

A measure centrality index for systematic empirical comparison of consciousness theories

Consciousness science is marred by disparate constructs and methodologies, making it challenging to systematically compare theories. This foundational crisis casts doubts on the scientific character of the field itself. Addressing it, we propose a framework for systematically comparing consciousness theories by introducing a novel inter-theory classification interface, the Measure Centrality Index (MCI). Recognizing its gradient distribution, the MCI assesses the degree of importance a specific empirical measure has for a given consciousness theory. We apply the MCI to probe how the empirical measures of the Global Neuronal Workspace Theory (GNW), Integrated Information Theory (IIT), and Temporospatial Theory of Consciousness (TTC) would fare within the context of the other two. We demonstrate that direct comparison of IIT, GNW, and TTC is meaningful and valid for some measures like Lempel-Ziv Complexity (LZC), Autocorrelation Window (ACW), and possibly Mutual Information (MI). In contrast, it is problematic for others like the anatomical and physiological neural correlates of consciousness (NCC) due to their MCI-based differential weightings within the structure of the theories. In sum, we introduce and provide proof-of-principle of a novel systematic method for direct inter-theory empirical comparisons, thereby addressing isolated evolution of theories and confirmatory bias issues in the state-of-the-art neuroscience of consciousness.

Arthur Schopenhauer: An underappreciated philosopher in psychiatry and his applied epistemology of body and self- experience

BACKGROUND

Arthur Schopenhauer (1788-1860) was one of the most important thinkers of the 19th century. Although his writings have exerted great influence in many different disciplines, his epistemological concepts and analysis of the body and self-experience were rarely considered in the context of psychiatric research of schizophrenia spectrum disorders (SSD) and depression (MDD).

METHODS

The method applied for the study of anomalous self and body-experience first consists in the close reading and analysis of Schopenhauer's most influential writings, namely his opus magnus "The World as Will and Representation" and his dissertation "On the Fourfold Root of the Principle of Sufficient Reason". Second, psychopathological and phenomenological aspects of the anomalous body and self, as well as altered space and time experience, are discussed by means of Schopenhauer's philosophy and four patient cases.

RESULTS

Schopenhauer's insights contribute to contemporary psychiatry by (1) unifying materialistic (neurobiological) and idealistic (subjective) conceptions of psychiatric disorders and improving the awareness of methods in psychiatric research; (2) emphasizing the integral significance of the body as a gateway to the surrounding world and basal self-experience; (3) delineating subjective space and time-experience as crucial dimensions of the conditio humana in SSD and MDD; and (4) demonstrating the feasibility of transferring his theories directly to clinical case vignettes stemming from the daily clinical routine.

CONCLUSION

Close reading of Schopenhauer's texts might help bridge the gap between different scientific methods in psychiatry and overcome the translational crisis of contemporary psychiatry by unifying neurobiological and subjective approaches to SSD and MDD.

Repertoire of timescales in uni - and transmodal regions mediate working memory capacity

Working memory (WM) describes the dynamic process of maintenance and manipulation of information over a certain time delay. Neuronally, WM recruits a distributed network of cortical regions like the visual and dorsolateral prefrontal cortex as well as the subcortical hippocampus. How the input dynamics and subsequent neural dynamics impact WM remains unclear though. To answer this question, we combined the analysis of behavioral WM capacity with measuring neural dynamics through task-related power spectrum changes, e.g., median frequency (MF) in functional magnetic resonance imaging (fMRI). We show that the processing of the input dynamics, e.g., the task structure's specific timescale, leads to changes in the unimodal visual cortex's corresponding timescale which also relates to working memory capacity. While the more transmodal hippocampus relates to working memory capacity through its balance across multiple timescales or frequencies. In conclusion, we here show the relevance of both input dynamics and different neural timescales for WM capacity in uni - and transmodal regions like visual cortex and hippocampus for the subject's WM performance.

Review of EEG Affective Recognition with a Neuroscience Perspective

Emotions are a series of subconscious, fleeting, and sometimes elusive manifestations of the human innate system. They play crucial roles in everyday life-influencing the way we evaluate ourselves, our surroundings, and how we interact with our world. To date, there has been an abundance of research on the domains of neuroscience and affective computing, with experimental evidence and neural network models, respectively, to elucidate the neural circuitry involved in and neural correlates for emotion recognition. Recent advances in affective computing neural network models often relate closely to evidence and perspectives gathered from neuroscience to explain the models. Specifically, there has been growing interest in the area of EEG-based emotion recognition to adopt models based on the neural underpinnings of the processing, generation, and subsequent collection of EEG data. In this respect, our review focuses on providing neuroscientific evidence and perspectives to discuss how emotions potentially come forth as the product of neural activities occurring at the level of subcortical structures within the brain's emotional circuitry and the association with current affective computing models in recognizing emotions. Furthermore, we discuss whether such biologically inspired modeling is the solution to advance the field in EEG-based emotion recognition and beyond.

What does the mean mean? A simple test for neuroscience

Trial-averaged metrics, e.g. tuning curves or population response vectors, are a ubiquitous way of characterizing neuronal activity. But how relevant are such trial-averaged responses to neuronal computation itself? Here we present a simple test to estimate whether average responses reflect aspects of neuronal activity that contribute to neuronal processing. The test probes two assumptions implicitly made whenever average metrics are treated as meaningful representations of neuronal activity: Reliability: Neuronal responses repeat consistently enough across trials that they convey a recognizable reflection of the average response to downstream regions.Behavioural relevance: If a single-trial response is more similar to the average template, it is more likely to evoke correct behavioural responses. We apply this test to two data sets: (1) Two-photon recordings in primary somatosensory cortices (S1 and S2) of mice trained to detect optogenetic stimulation in S1; and (2) Electrophysiological recordings from 71 brain areas in mice performing a contrast discrimination task. Under the highly controlled settings of Data set 1, both assumptions were largely fulfilled. In contrast, the less restrictive paradigm of Data set 2 met neither assumption. Simulations predict that the larger diversity of neuronal response preferences, rather than higher cross-trial reliability, drives the better performance of Data set 1. We conclude that when behaviour is less tightly restricted, average responses do not seem particularly relevant to neuronal computation, potentially because information is encoded more dynamically. Most importantly, we encourage researchers to apply this simple test of computational relevance whenever using trial-averaged neuronal metrics, in order to gauge how representative cross-trial averages are in a given context.

Intrinsic timescales and predictive allostatic interoception in brain health and disease

The cognitive neuroscience of brain diseases faces challenges in understanding the complex relationship between brain structure and function, the heterogeneity of brain phenotypes, and the lack of dimensional and transnosological explanations. This perspective offers a framework combining the predictive coding theory of allostatic interoceptive overload (PAIO) and the intrinsic neural timescales (INT) theory to provide a more dynamic understanding of brain health in psychiatry and neurology. PAIO integrates allostasis and interoception to assess the interaction between internal patterns and environmental stressors, while INT shows that different brain regions operate on different intrinsic timescales. The allostatic overload can be understood as a failure of INT, which involves a breakdown of proper temporal integration and segregation. This can lead to dimensional disbalances between exteroceptive/interoceptive inputs across brain and whole-body levels (cardiometabolic, cardiovascular, inflammatory, immune). This approach offers new insights, presenting novel perspectives on brain spatiotemporal hierarchies and interactions. By integrating these theories, the paper opens innovative paths for studying brain health dynamics, which can inform future research in brain health and disease.

Spatiotemporal Psychopathology - An integrated brain-mind approach and catatonia

Catatonia is featured by complex symptoms combining motor, affective and behavioral phenomena as well as by its syndrome character with trans-diagnostic occurrence. It paradigmatically shows the limits of current forms of psychopathology like affective and cognitive approaches with respect to both clinical symptoms and brain mechanisms. We therefore suggest Spatiotemporal Psychopathology (STPP) which, as recently introduced, is here developed further following the latest findings in both clinical psychiatry and neuroscience. STPP is characterized by two core features: (i) an experience-based approach that accounts for symptoms primarily in terms of first-person experience of time-space as distinct from third-person observation of specific functions and related behavior; (ii) an integrated brain-mind approach where the brain's neural topography and dynamic, e.g., inner time and space, are shared by the mind's mental topography and dynamic, e.g., time-space experience, as their "common currency". We demonstrate how these two features can well account for both symptom complexity and trans-diagnostic nature of catatonia. In conclusion, catatonia can serve as paradigmatic example for the need to develop a more comprehensive psychopathological approach in psychiatry. This is provided by STPP that allows integrating subjective experience, clinical symptoms and the brain's neural activity in terms of their inner space-time, e.g., topography and dynamic.

Intrinsic neural timescales relate to the dynamics of infraslow neural waves

The human brain is a highly dynamic organ that operates across a variety of timescales, the intrinsic neural timescales (INT). In addition to the INT, the neural waves featured by its phase-related processes including their cycles with peak/trough and rise/fall play a key role in shaping the brain's neural activity. However, the relationship between the brain's ongoing wave dynamics and INT remains yet unclear. In this study, we utilized functional magnetic resonance imaging (fMRI) rest and task data from the Human Connectome Project (HCP) to investigate the relationship of infraslow wave dynamics [as measured in terms of speed by changes in its peak frequency (PF)] with INT. Our findings reveal that: (i) the speed of phase dynamics (PF) is associated with distinct parts of the ongoing phase cycles, namely higher PF in peak/trough and lower PF in rise/fall; (ii) there exists a negative correlation between phase dynamics (PF) and INT such that slower PF relates to longer INT; (iii) exposure to a movie alters both PF and INT across the different phase cycles, yet their negative correlation remains intact. Collectively, our results demonstrate that INT relates to infraslow phase dynamics during both rest and task states.

Brain mechanisms underlying catatonia: A systematic review

BACKGROUND

Catatonia is a complex psychomotor disorder characterized by motor, affective, and behavioral symptoms. Despite being known for almost 150 years, its pathomechanisms are still largely unknown.

METHODS

A systematic research on PubMed, Web of Science, and Scopus was conducted to identify neuroimaging studies conducted on group or single individuals with catatonia. Overall, 33 studies employing structural magnetic resonance imaging (sMRI, n = 11), functional magnetic resonance imaging (fMRI, n = 10), sMRI and fMRI (n = 2), functional near-infrared spectroscopy (fNIRS, n = 1), single positron emission computer tomography (SPECT, n = 4), positron emission tomography (PET, n = 4), and magnetic resonance spectroscopy (MRS, n = 1), and 171 case reports were retrieved.

RESULTS

Observational sMRI studies showed numerous brain changes in catatonia, including diffuse atrophy and signal hyperintensities, while case-control studies reported alterations in fronto-parietal and limbic regions, the thalamus, and the striatum. Task-based and resting-state fMRI studies found abnormalities located primarily in the orbitofrontal, medial prefrontal, motor cortices, cerebellum, and brainstem. Lastly, metabolic and perfusion changes were observed in the basal ganglia, prefrontal, and motor areas. Most of the case-report studies described widespread white matter lesions and frontal, temporal, or basal ganglia hypoperfusion.

CONCLUSIONS

Catatonia is characterized by structural, functional, perfusion, and metabolic cortico-subcortical abnormalities. However, the majority of studies and case reports included in this systematic review are affected by considerable heterogeneity, both in terms of populations and neuroimaging techniques, which calls for a cautious interpretation. Further elucidation, through future neuroimaging research, could have great potential to improve the description of the neural motor and psychomotor mechanisms underlying catatonia.

The self and our perception of its synchrony - Beyond internal and external cognition

The self is the core of our mental life which connects one's inner mental life with the external perception. Since synchrony is a key feature of the biological world and its various species, what role does it play for humans? We conducted a large-scale psychological study (n = 1072) combining newly developed visual analogue scales (VAS) for the perception of synchrony and internal and external cognition complemented by several psychological questionnaires. Overall, our findings showed close connection of the perception of synchrony of the self with both internal (i.e., body and cognition) and external (i.e., others, environment/nature) synchrony being associated positively with adaptive and negatively with maladaptive traits of self. Moreover, we have demonstrated how external (i.e., life events like the COVID-19 pandemic) variables modulate the perception of the self's internal-external synchrony. These findings suggest how synchrony with self plays a central role during times of uncertainty.

Overcoming the translational crisis of contemporary psychiatry - converging phenomenological and spatiotemporal psychopathology

Despite all neurobiological/neurocomputational progress in psychiatric research, recent authors speak about a 'crisis of contemporary psychiatry'. Some argue that we do not yet know the computational mechanisms underlying the psychopathological symptoms ('crisis of mechanism') while others diagnose a neglect of subjectivity, namely first-person experience ('crisis of subjectivity'). In this perspective, we propose that Phenomenological Psychopathology, due to its focus on first-person experience of space and time, is in an ideal position to address the crisis of subjectivity and, if extended to the brain's spatiotemporal topographic-dynamic structure as key focus of Spatiotemporal Psychopathology, the crisis of mechanism. We demonstrate how the first-person experiences of space and time differ between schizophrenia, mood disorders and anxiety disorders allowing for their differential-diagnosis - this addresses the crisis of subjectivity. Presupposing space and time as shared features of brain, experience, and symptoms as their "common currency", the structure of abnormal space and time experience may also serve as template for the structure of the brain's spatiotemporal neuro-computational mechanisms - this may address the crisis of mechanism. Preliminary scientific evidence in our examples of schizophrenia, bipolar disorder, anxiety disorder, and depression support such clinically relevant spatiotemporal determination of both first-person experience (crisis of subjectivity) and the brain's neuro-computational structure (crisis of mechanism). In conclusion, converging Phenomenological Psychopathology with Spatiotemporal Psychopathology might help to overcome the translational crisis in psychiatry by delineating more fine-grained neuro computational and -phenomenal mechanisms; this offers novel candidate biomarkers for diagnosis and therapy including both pharmacological and non-pharmacological treatment.

From Lung to Brain: Respiration Modulates Neural and Mental Activity

Respiration protocols have been developed to manipulate mental states, including their use for therapeutic purposes. In this systematic review, we discuss evidence that respiration may play a fundamental role in coordinating neural activity, behavior, and emotion. The main findings are: (1) respiration affects the neural activity of a wide variety of regions in the brain; (2) respiration modulates different frequency ranges in the brain's dynamics; (3) different respiration protocols (spontaneous, hyperventilation, slow or resonance respiration) yield different neural and mental effects; and (4) the effects of respiration on the brain are related to concurrent modulation of biochemical (oxygen delivery, pH) and physiological (cerebral blood flow, heart rate variability) variables. We conclude that respiration may be an integral rhythm of the brain's neural activity. This provides an intimate connection of respiration with neuro-mental features like emotion. A respiratory-neuro-mental connection holds the promise for a brain-based therapeutic usage of respiration in mental disorders.

Theories of consciousness and psychiatric disorders - A comparative analysis

Disorders of consciousness represent an efficient way to test theories of consciousness' (ToCs) predictions. So far, ToCs have mostly focused on disorders of quantitative awareness such as coma, vegetative state, spatial neglect and hemianopia. Psychiatric disorders, by contrast, have received little attention, leaving their contribution to consciousness research almost unexplored. Therefore, this paper aims to assess the relation between ToCs and psychiatric disorders - that is, the extent to which current ToCs can account for psychiatric symptomatology. First, I review direct and indirect evidence linking each ToC to psychiatry disorders. Next, I differentiate ToCs based on their theoretical and methodological ground, highlighting how they distinctively address neural, cognitive, and phenomenological aspects of conscious experience and, in turn, psychiatric symptoms. Finally, I refer to one specific symptom to directly compare ToCs' explanatory power. Overall, Temporospatial Theory of Consciousness (TTC) appears to provide a more comprehensive account of psychiatric disorders, suggesting that a novel dimension of consciousness (i.e., form of consciousness) may be needed to address more qualitative alterations in conscious experience.

Comparative analysis of multifaceted neural effects associated with varying endogenous cognitive load

Contemporary neuroscience has firmly established that mental state variation concurs with changes in neural dynamic activity in a complex way that a one-to-one mapping cannot describe. To explore the scenario of the multifaceted changes in neural dynamics associated with simple mental state variation, we took cognitive load - a common cognitive manipulation in psychology - as a venue to characterize how multiple neural dynamic features are simultaneously altered by the manipulation and how their sensitivity differs. Electroencephalogram was collected from 152 participants performing stimulus-free tasks with different demands. The results show that task demand alters wide-ranging neural dynamic features, including band-specific oscillations across broad frequency bands, scale-free dynamics, and cross-frequency phase-amplitude coupling. The scale-free dynamics outperformed others in indexing cognitive load variation. This study demonstrates a complex relationship between cognitive dynamics and neural dynamics, which points to a necessity to integrate multifaceted neural dynamic features when studying mind-brain relationship in the future.

Temporal imprecision and phase instability in schizophrenia resting state EEG

Schizophrenia is characterized by temporal imprecision and irregularities on neuronal, psychological cognitive, and behavioral levels which are usually tested during task-related activity. This leaves open whether analogous temporal imprecision and irregularities can already be observed in the brain's spontaneous activity as measured during the resting state; this is the goal of our study. Building on recent task-related data, we, using EEG, aimed to investigate the temporal precision and regularity of phase coherence over time in healthy, schizophrenia, and bipolar disorder participants. To this end, we developed a novel methodology, nominal frequency phase stability (NFPS), that allows to measure stability over phase angles in selected frequencies. By applying sample entropy quantification to the time-series of the nominal frequency phase angle time series, we found increased irregularities in theta activity over a frontocentral electrode in schizophrenia but not in bipolar disorder. We therefore assume that temporal imprecision and irregularity already occur in the brain's spontaneous activity in schizophrenia.

A generic neural factor linking resting-state neural dynamics and the brain's response to unexpectedness in multilevel cognition

The brain's response to change is fundamental to learning and adaptation; this implies the presence of a universal neural mechanism under various contexts. We hypothesized that this mechanism manifests in neural activity patterns across low and high levels of cognition during task processing as well as in resting-state neural dynamics, because both these elements are different facets of the same dynamical system. We tested our hypothesis by (i) characterizing (a) the neural response to changes in low-level continuous information stream and unexpectedness at different cognitive levels and (b) the spontaneous neural dynamics in resting state, and (ii) examining the associations among the dynamics according to cross-individual variability (n = 200). Our results showed that the brain's response magnitude was monotonically correlated with the magnitude of information fluctuation in a low-level task, forming a simple psychophysical function; moreover, this effect was found to be associated with the brain's response to unexpectedness in high-level cognitive tasks (including language processing). These coherent multilevel neural effects in task processing were also shown to be strongly associated with resting-state neural dynamics characterized by the waxing and waning of Alpha oscillation. Taken together, our results revealed large-scale consistency between the neural dynamic system and multilevel cognition.

Topographic-dynamic reorganisation model of dreams (TRoD) - A spatiotemporal approach

Dreams are one of the most bizarre and least understood states of consciousness. Bridging the gap between brain and phenomenology of (un)conscious experience, we propose the Topographic-dynamic Re-organization model of Dreams (TRoD). Topographically, dreams are characterized by a shift towards increased activity and connectivity in the default-mode network (DMN) while they are reduced in the central executive network, including the dorsolateral prefrontal cortex (except in lucid dreaming). This topographic re-organization is accompanied by dynamic changes; a shift towards slower frequencies and longer timescales. This puts dreams dynamically in an intermediate position between awake state and NREM 2/SWS sleep. TRoD proposes that the shift towards DMN and slower frequencies leads to an abnormal spatiotemporal framing of input processing including both internally- and externally-generated inputs (from body and environment). In dreams, a shift away from temporal segregation to temporal integration of inputs results in the often bizarre and highly self-centric mental contents as well as hallucinatory-like states. We conclude that topography and temporal dynamics are core features of the TroD, which may provide the connection of neural and mental activity, e.g., brain and experience during dreams as their "common currency".

Default mode network mediates low-frequency fluctuations in brain activity and behavior during sustained attention

The low-frequency (<0.1 Hz) fluctuation in sustained attention attracts enormous interest in cognitive neuroscience and clinical research since it always leads to cognitive and behavioral lapses. What is the source of the spontaneous fluctuation in sustained attention in neural activity, and how does the neural fluctuation relate to behavioral fluctuation? Here, we address these questions by collecting and analyzing two independent fMRI and behavior datasets. We show that the neural (fMRI) fluctuation in a key brain network, the default-mode network (DMN), mediate behavioral (reaction time) fluctuation during sustained attention. DMN shows the increased amplitude of fluctuation, which correlates with the behavioral fluctuation in a similar frequency range (0.01-0.1 Hz) but not in the lower (<0.01 Hz) or higher (>0.1 Hz) frequency range. This was observed during both auditory and visual sustained attention and was replicable across independent datasets. These results provide a novel insight into the neural source of attention-fluctuation and extend the former concept that DMN was deactivated in cognitive tasks. More generally, our findings highlight the temporal dynamic of the brain-behavior relationship.

Beyond noise to function: reframing the global brain activity and its dynamic topography

How global and local activity interact with each other is a common question in complex systems like climate and economy. Analogously, the brain too displays 'global' activity that interacts with local-regional activity and modulates behavior. The brain's global activity, investigated as global signal in fMRI, so far, has mainly been conceived as non-neuronal noise. We here review the findings from healthy and clinical populations to demonstrate the neural basis and functions of global signal to brain and behavior. We show that global signal (i) is closely coupled with physiological signals and modulates the arousal level; and (ii) organizes an elaborated dynamic topography and coordinates the different forms of cognition. We also postulate a Dual-Layer Model including both background and surface layers. Together, the latest evidence strongly suggests the need to go beyond the view of global signal as noise by embracing a dual-layer model with background and surface layer.

The complexity of the stream of consciousness

Typical consciousness can be defined as an individual-specific stream of experiences. Modern consciousness research on dynamic functional connectivity uses clustering techniques to create common bases on which to compare different individuals. We propose an alternative approach by combining modern theories of consciousness and insights arising from phenomenology and dynamical systems theory. This approach enables a representation of an individual's connectivity dynamics in an intrinsically-defined, individual-specific landscape. Given the wealth of evidence relating functional connectivity to experiential states, we assume this landscape is a proxy measure of an individual's stream of consciousness. By investigating the properties of this landscape in individuals in different states of consciousness, we show that consciousness is associated with short term transitions that are less predictable, quicker, but, on average, more constant. We also show that temporally-specific connectivity states are less easily describable by network patterns that are distant in time, suggesting a richer space of possible states. We show that the cortex, cerebellum and subcortex all display consciousness-relevant dynamics and discuss the implication of our results in forming a point of contact between dynamical systems interpretations and phenomenology.

A transitive perspective on the relief of psychosomatic symptoms

A key element of successful psychotherapy for the treatment of psychosomatic disorders is that patients recognize and change the meaning of their experiences. Such changes are brought about by appropriate verbal referencing of symptoms currently experienced within a given narrative. The present theoretical paper argues that changes are not based on better, more adaptive narratives per se, but on the transition (or linkage) process itself that is experienced between different narratives. This view is theoretically justified in various ways: first, it is accounted for through contemporary spatiotemporal neuroscience, which aims to connect mental and structural aspects via a common dynamic property or, according to Northoff, the "common currency" of a brain's orientation along its embeddedness in its contextual world, i.e., body and environment. Second, it is justified through the physics concept of "spontaneous symmetry breaking," which is used analogously to "suffering from symptoms." If the sufferer is willing to experience a process of "going back," that is, moving away from the previous narrative (or aspect) by verbally relating to the felt aspects of the symptom in question (i.e., approaching its meaning), they are moving toward symmetry or an underlying dynamic alignment with their world context. Clinical predictions are derived from the theoretical arguments.

Beyond the veil of duality-topographic reorganization model of meditation

Meditation can exert a profound impact on our mental life, with proficient practitioners often reporting an experience free of boundaries between a separate self and the environment, suggesting an explicit experience of "nondual awareness." What are the neural correlates of such experiences and how do they relate to the idea of nondual awareness itself? In order to unravel the effects that meditation has on the brain's spatial topography, we review functional magnetic resonance imaging brain findings from studies specific to an array of meditation types and meditator experience levels. We also review findings from studies that directly probe the interaction between meditation and the experience of the self. The main results are (i) decreased posterior default mode network (DMN) activity, (ii) increased central executive network (CEN) activity, (iii) decreased connectivity within posterior DMN as well as between posterior and anterior DMN, (iv) increased connectivity within the anterior DMN and CEN, and (v) significantly impacted connectivity between the DMN and CEN (likely a nonlinear phenomenon). Together, these suggest a profound organizational shift of the brain's spatial topography in advanced meditators-we therefore propose a topographic reorganization model of meditation (TRoM). One core component of the TRoM is that the topographic reorganization of DMN and CEN is related to a decrease in the mental-self-processing along with a synchronization with the more nondual layers of self-processing, notably interoceptive and exteroceptive-self-processing. This reorganization of the functionality of both brain and self-processing can result in the explicit experience of nondual awareness. In conclusion, this review provides insight into the profound neural effects of advanced meditation and proposes a result-driven unifying model (TRoM) aimed at identifying the inextricably tied objective (neural) and subjective (experiential) effects of meditation.

An integrative perspective on the role of touch in the development of intersubjectivity

Touch concerns a fundamental component of sociality. In this review, we examine the hypothesis that somatomotor development constitutes a crucial psychophysiological element in the ontogeny of intersubjectivity. An interdisciplinary perspective is provided on how the communication channel of touch contributes to the sense of self and extends to the social self. During gestation, the transformation of random movements into organized sequences of actions with sensory consequences parallels the development of the brain's functional architecture. Brain subsystems shaped by the coordinated activity of somatomotor circuits to support these first body-environment interactions are the first brain functional arrangements to develop. We propose that tactile self-referring behaviour during gestation constitutes a prototypic mode of interpersonal exchange that supports the subsequent development of intersubjective exchange. The reviewed research suggests that touch constitutes a pivotal bodily experience that in early stages builds and later filters self-other interactions. This view is corroborated by the fact that aberrant social-affective touch experiences appear fundamentally associated with attachment anomalies, interpersonal trauma, and personality disorders. Given the centrality of touch for the development of intersubjectivity and for psychopathological conditions in the social domain, dedicated research is urged to elucidate the role of touch in the evolution of subjective self-other coding.

The nested hierarchy of self and its trauma: In search for a synchronic dynamic and topographical re-organization

The sense of self has always been a topic of high interest in both psychoanalysis and most recently in neuroscience. Nowadays, there is an agreement in psychoanalysis that the self emerges from the relationship with the other (e.g., the caregiver) in terms of his/her capacity to attune, regulate, and synchronize with the emergent self of the infant. The outcome of this relational/intersubjective synchronization is the development of the sense of self and its regulatory processes both in dynamic psychology and neuroscience. In this work, we propose that synchrony is a fundamental biobehavioral factor in these dialectical processes between self and others which shapes the brain-body-mind system of the individuals, including their sense of self. Recently in neuroscience, it has been proposed by the research group around Northoff that the self is constituted by a brain-based nested hierarchical three-layer structure, including interoceptive, proprio-exteroceptive, and mental layers of self. This may be disrupted, though, when traumatic experiences occur. Following the three levels of trauma theorized by Mucci, we here suggest how different levels of traumatic experiences might have an enduring effect in yielding a trauma-based topographic and dynamic re-organization of the nested model of self featured by dissociation. In conclusion, we propose that different levels and degrees of traumatic experience are related to corresponding disruptions in the topography and dynamic of the brain-based three-layer hierarchical structure of the self.

From temporal to spatial topography: hierarchy of neural dynamics in higher- and lower-order networks shapes their complexity

The brain shows a topographical hierarchy along the lines of lower- and higher-order networks. The exact temporal dynamics characterization of this lower-higher-order topography at rest and its impact on task states remains unclear, though. Using 2 functional magnetic resonance imaging data sets, we investigate lower- and higher-order networks in terms of the signal compressibility, operationalized by Lempel-Ziv complexity (LZC). As we assume that this degree of complexity is related to the slow-fast frequency balance, we also compute the median frequency (MF), an estimation of frequency distribution. We demonstrate (i) topographical differences at rest between higher- and lower-order networks, showing lower LZC and MF in the former; (ii) task-related and task-specific changes in LZC and MF in both lower- and higher-order networks; (iii) hierarchical relationship between LZC and MF, as MF at rest correlates with LZC rest-task change along the lines of lower- and higher-order networks; and (iv) causal and nonlinear relation between LZC at rest and LZC during task, with MF at rest acting as mediator. Together, results show that the topographical hierarchy of lower- and higher-order networks converges with their temporal hierarchy, with these neural dynamics at rest shaping their range of complexity during task states in a nonlinear way.

From Shorter to Longer Timescales: Converging Integrated Information Theory (IIT) with the Temporo-Spatial Theory of Consciousness (TTC)

Time is a key element of consciousness as it includes multiple timescales from shorter to longer ones. This is reflected in our experience of various short-term phenomenal contents at discrete points in time as part of an ongoing, more continuous, and long-term ‘stream of consciousness.’ Can Integrated Information Theory (IIT) account for this multitude of timescales of consciousness? According to the theory, the relevant spatiotemporal scale for consciousness is the one in which the system reaches the maximum cause-effect power; IIT currently predicts that experience occurs on the order of short timescales, namely, between 100 and 300 ms (theta and alpha frequency range). This can well account for the integration of single inputs into a particular phenomenal content. However, such short timescales leave open the temporal relation of specific phenomenal contents to others during the course of the ongoing time, that is, the stream of consciousness. For that purpose, we converge the IIT with the Temporo-spatial Theory of Consciousness (TTC), which, assuming a multitude of different timescales, can take into view the temporal integration of specific phenomenal contents with other phenomenal contents over time. On the neuronal side, this is detailed by considering those neuronal mechanisms driving the non-additive interaction of pre-stimulus activity with the input resulting in stimulus-related activity. Due to their non-additive interaction, the single input is not only integrated with others in the short-term timescales of 100–300 ms (alpha and theta frequencies) (as predicted by IIT) but, at the same time, also virtually expanded in its temporal (and spatial) features; this is related to the longer timescales (delta and slower frequencies) that are carried over from pre-stimulus to stimulus-related activity. Such a non-additive pre-stimulus-input interaction amounts to temporo-spatial expansion as a key mechanism of TTC for the constitution of phenomenal contents including their embedding or nesting within the ongoing temporal dynamic, i.e., the stream of consciousness. In conclusion, we propose converging the short-term integration of inputs postulated in IIT (100–300 ms as in the alpha and theta frequency range) with the longer timescales (in delta and slower frequencies) of temporo-spatial expansion in TTC.

Temporo-spatial Theory of Consciousness (TTC) - Bridging the gap of neuronal activity and phenomenal states

Consciousness and its neural mechanisms remain a mystery. Current neuroscientific theories focus predominantly on the external input/stimulus and the associated stimulus-related activity during conscious contents. Despite all progress, we encounter two gaps: (i) a gap between spontaneous and stimulus-related activity; (ii) a gap between neuronal and phenomenal features. A novel, different, and unique approach, Temporo-spatial theory of consciousness (TTC) aims to bridge both gaps. The TTC focuses on the brain's spontaneous activity and how its spatial topography and temporal dynamic shape stimulus-related activity and resurface in the corresponding spatial and temporal features of consciousness, i.e., 'common currency'. The TTC introduces four temporo-spatial mechanisms: expansion, globalization, alignment, and nestedness. These are associated with distinct dimensions of consciousness including phenomenal content, access, form/structure, and level/state, respectively. Following up on the first introduction of the TTC in 2017, we review updates, further develop these temporo-spatial mechanisms, and postulate specific neurophenomenal hypotheses. We conclude that the TTC offers a viable approach for (i) linking spontaneous and stimulus-related activity in conscious states; (ii) determining specific neuronal and neurophenomenal mechanisms for the distinct dimensions of consciousness; (iii) an integrative and unifying framework of different neuroscientific theories of consciousness; and (iv) offers novel empirically grounded conceptual assumptions about the biological and ontological nature of consciousness and its relation to the brain.

Intrinsic dynamics and topography of sensory input systems

The brain is continuously bombarded by external stimuli, which are processed in different input systems. The intrinsic features of these sensory input systems remain yet unclear. Investigating topography and dynamics of input systems is the goal of our study in order to better understand the intrinsic features that shape their neural processing. Using a functional magnetic resonance imaging dataset, we measured neural topography and dynamics of the input systems during rest and task states. Neural dynamics were probed by scale-free activity, measured with the power-law exponent (PLE), as well as by order/disorder as measured with sample entropy (SampEn). Our main findings during both rest and task states are: 1) differences in neural dynamics (PLE, SampEn) between regions within each of the three sensory input systems 2) differences in topography and dynamics among the three input systems; 3) PLE and SampEn correlate and, as demonstrated in simulation, show non-linear relationship in the critical range of PLE; 4) scale-free activity during rest mediates the transition of SampEn from rest to task as probed in a mediation model. We conclude that the sensory input systems are characterized by their intrinsic topographic and dynamic organization which, through scale-free activity, modulates their input processing.

Scale for Space and Time Experience in Psychosis: Converging Phenomenological and Psychopathological Perspectives

INTRODUCTION

Abnormalities in the experience of space and time are fundamental to understanding schizophrenia spectrum disorders, but the precise relation between such abnormalities and psychopathological symptoms is still unclear. Therefore, the aim of our study was to introduce a novel scale for space and time experience in psychosis (STEP), specifically devised to assess schizophrenia spectrum disorders.

METHODS

The STEP scale is a semiquantitative instrument developed on the basis of several items from previous scales and phenomenological reports addressing the experience of space and time. We applied the STEP scale to three groups of subjects (patients with schizophrenia spectrum disorders, patients with predominant affective symptoms, and healthy control subjects), to whom we also applied other more general psychopathological scales, such as the Positive and Negative Syndrome Scale and the Ego-Psychopathology Inventory.

RESULTS

Patients with schizophrenia spectrum disorders scored significantly higher on general psychopatho<X00_Del_TrennDivis>--</X00_Del_TrennDivis>logical scales relative to subjects belonging to the other groups. The STEP scale provided good psychometric properties regarding reliability. We also tested convergent and divergent validity of the STEP scale and found that space and time subscale scores of STEP significantly correlated with each other, as well as with the remaining general psychopathological scores.

DISCUSSION/CONCLUSION

We introduced the STEP scale as a novel instrument for the assessment of experience of space and time. Its psychometric properties showed high validity and reliability to identify psychopathological symptoms and enabled to differentiate patients with predominantly psychotic symptoms from those with predominantly affective symptoms. The STEP scale provides a standardized measure for assessing disturbances in the experience of space and time. Furthermore, it probably represents a leap forward toward the establishment of an additional dimension of symptoms proposed as "spatiotemporal psychopathology."

Progress in sensorimotor neuroscience of schizophrenia spectrum disorders: Lessons learned and future directions

The number of neuroimaging studies on movement disorders, sensorimotor, and psychomotor functioning in schizophrenia spectrum disorders (SSD) has steadily increased over the last two decades. Accelerated by the addition of the "sensorimotor domain" to the Research Domain Criteria (RDoC) framework in January 2019, neuroscience research on the role of sensorimotor dysfunction in SSD has gained greater scientific and clinical relevance. To draw attention to recent rapid progress in the field, we performed a triennial systematic review (PubMed search from January 1st^, 2018 through December 31st^, 2020), in which we highlight recent neuroimaging findings and discuss methodological pitfalls as well as challenges for future research. The identified magnetic resonance imaging (MRI) studies suggest that sensorimotor abnormalities in SSD are related to cerebello-thalamo-cortico-cerebellar network dysfunction. Longitudinal and interventional studies highlight the translational potential of the sensorimotor domain as putative biomarkers for treatment response and as targets for non-invasive neurostimulation techniques in SSD.

Intrinsic neural network dynamics in catatonia

Catatonia is a transnosologic psychomotor syndrome with high prevalence in schizophrenia spectrum disorders (SSD). There is mounting neuroimaging evidence that catatonia is associated with aberrant frontoparietal, thalamic and cerebellar regions. Large-scale brain network dynamics in catatonia have not been investigated so far. In this study, resting-state fMRI data from 58 right-handed SSD patients were considered. Catatonic symptoms were examined on the Northoff Catatonia Rating Scale (NCRS). Group spatial independent component analysis was carried out with a multiple analysis of covariance (MANCOVA) approach to estimate and test the underlying intrinsic components (ICs) in SSD patients with (NCRS total score ≥ 3; n = 30) and without (NCRS total score = 0; n = 28) catatonia. Functional network connectivity (FNC) during rest was calculated between pairs of ICs and transient changes in connectivity were estimated using sliding windowing and clustering (to capture both static and dynamic FNC). Catatonic patients showed increased static FNC in cerebellar networks along with decreased low frequency oscillations in basal ganglia (BG) networks. Catatonic patients had reduced state changes and dwelled more in a state characterized by high within-network correlation of the sensorimotor, visual, and default-mode network with respect to noncatatonic patients. Finally, in catatonic patients according to DSM-IV-TR (n = 44), there was a significant correlation between increased within FNC in cortico-striatal state and NCRS motor scores. The data support a neuromechanistic model of catatonia that emphasizes a key role of disrupted sensorimotor network control during distinct functional states.

The self and its internal thought: In search for a psychological baseline

Self-consciousness is neuronally associated with the brain's default mode network as its "neuronal baseline" while, psychologically the self is characterized by different thought modes and dynamics. We here raise the question whether they reflect the "psychological baseline" of the self. We investigate the psychological relationship of the self with thought modes (rumination, reflection) and mind-wandering dynamics (spontaneous, deliberate), as well as with depressive symptomatology. Our findings show a relationship between self-consciousness and i) mind-wandering dynamics, and ii) thought functional modes, in their respective forms. At the same time, self-consciousness is more related to spontaneous mind-wandering than deliberate and to rumination than reflection. Furthermore, iii) rumination acts as a mediator between self-consciousness and spontaneous mind-wandering dynamics; and iv) the relationship between high levels of self-consciousness and depressive symptoms is mediated by ruminative modes and spontaneous mind-wandering dynamics. Together, these findings support the view of the self as "psychological baseline".

"Project for a Spatiotemporal Neuroscience" - Brain and Psyche Share Their Topography and Dynamic

What kind of neuroscience does psychoanalysis require? At his time, Freud in his "Project for a Scientific Psychology" searched for a model of the brain that could relate to incorporate the psyche's topography and dynamic. Current neuropsychoanalysis builds on specific functions as investigated in Affective and Cognitive (and Social) Neuroscience including embodied approaches. The brain's various functions are often converged with prediction as operationalized in predictive coding (PC) and free energy principle (FEP) which, recently, have been conceived as core for a "New Project for Scientific Psychology." We propose to search for a yet more comprehensive and holistic neuroscience that focuses primarily on its topography and dynamic analogous to Freud's model of the psyche. This leads us to what we describe as "Spatiotemporal Neuroscience" that focuses on the spatial topography and temporal dynamic of the brain's neural activity including how they shape affective, cognitive, and social functions including PC and FEP (first part). That is illustrated by the temporally and spatially nested neural hierarchy of the self in the brain's neural activity (second and third part). This sets the ground for developing our proposed "Project for a Spatiotemporal Neuroscience," which complements and extends both Freud's and Solms' projects (fourth part) and also carries major practical implications as it lays the ground for a novel form of neuroscientifically informed psychotherapy, namely, "Spatiotemporal Psychotherapy." In conclusion, "Spatiotemporal Neuroscience" provides an intimate link of brain and psyche by showing topography and dynamic as their shared features, that is, "common currency."

The Self and Its Right Insula-Differential Topography and Dynamic of Right vs. Left Insula

Various studies demonstrate a special role of the right compared to the left anterior insula in mediating our self. However, the neural features of the right insula that allow for its special role remain unclear. Presupposing a spatiotemporal model of self—“Basis model of self-specificity” (BMSS)—we here address the following question: what spatial-topographic and temporal-dynamic features render neural activity in the right insula to be more suitable in mediating self-specificity than the left insula? First, applying fMRI, we demonstrate that the right insula (i) exhibits higher degrees of centrality in rest, and (ii) higher context-dependent functional connectivity in a self-specific task among regions of distinct layers of self (intero-, extero-proprioceptive, and mental). Second, using EEG in rest and task, we show that the right insula shows longer autocorrelation window (ACW) in its neural activity than both left insula and other regions of the different layers of self. Together, we demonstrate special topographic, i.e., high functional connectivity, and dynamic, i.e., long ACW, neural features of the right insula compared to both left insula and other regions of the distinct layers of self. This suits neural activity in the right insula ideally for high functional integration and temporal continuity as key features of the self including its intero-, extero-proprioceptive, and mental layers.

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.

Global Signal Topography of the Human Brain: A Novel Framework of Functional Connectivity for Psychological and Pathological Investigations

The global signal (GS), which was once regarded as a nuisance of functional magnetic resonance imaging, has been proven to convey valuable neural information. This raised the following question: what is a GS represented in local brain regions? In order to answer this question, the GS topography was developed to measure the correlation between global and local signals. It was observed that the GS topography has an intrinsic structure characterized by higher GS correlation in sensory cortices and lower GS correlation in higher-order cortices. The GS topography could be modulated by individual factors, attention-demanding tasks, and conscious states. Furthermore, abnormal GS topography has been uncovered in patients with schizophrenia, major depressive disorder, bipolar disorder, and epilepsy. These findings provide a novel insight into understanding how the GS and local brain signals coactivate to organize information in the human brain under various brain states. Future directions were further discussed, including the local-global confusion embedded in the GS correlation, the integration of spatial information conveyed by the GS, and temporal information recruited by the connection analysis. Overall, a unified psychopathological framework is needed for understanding the GS topography.

Temporal hierarchy of intrinsic neural timescales converges with spatial core-periphery organization

The human cortex exhibits intrinsic neural timescales that shape a temporal hierarchy. Whether this temporal hierarchy follows the spatial hierarchy of its topography, namely the core-periphery organization, remains an open issue. Using magnetoencephalography data, we investigate intrinsic neural timescales during rest and task states; we measure the autocorrelation window in short (ACW-50) and, introducing a novel variant, long (ACW-0) windows. We demonstrate longer ACW-50 and ACW-0 in networks located at the core compared to those at the periphery with rest and task states showing a high ACW correlation. Calculating rest-task differences, i.e., subtracting the shared core-periphery organization, reveals task-specific ACW changes in distinct networks. Finally, employing kernel density estimation, machine learning, and simulation, we demonstrate that ACW-0 exhibits better prediction in classifying a region's time window as core or periphery. Overall, our findings provide fundamental insight into how the human cortex's temporal hierarchy converges with its spatial core-periphery hierarchy.