Reentry: a key mechanism for integration of brain function

Could Relationship-Based Learnt Beliefs and Expectations Contribute to Physiological Vulnerability of Chronic Pain? Making a Case to Consider Attachment in Pain Research

Pain is an interpersonal and inherently social experience. Pain perception and administration of medical treatment all occur in a particular environmental and social context. Early environmental influences and early learning experiences and interactions condition the body's response to different threats (like pain), ultimately shaping the underlying neurophysiology. These early interactions and experiences also determine what situations are perceived as threatening, as well as our belief in our own ability to self-manage, and our belief in others to offer support, during perceived threats. These beliefs intrinsically drive the combination of behaviors that emerge in response to perceived threats, including pain. Such behaviors can be categorized into attachment styles. In this interdisciplinary review, we synthesize and summarize evidence from the neurobiological, psychobiological, psychosocial, and psychobehavioral fields, to describe how these beliefs are embedded in the brain's prediction models to generate a series of expectations/perceptions around the level of safety/threat in different contexts. As such, these beliefs may predict how one experiences and responds to pain, with potentially significant implications for the development and management of chronic pain. Little attention has been directed to the effect of adult attachment style on pain in research studies and in the clinical setting. Using interdisciplinary evidence, we argue why we think this interaction merits further consideration and research. PERSPECTIVE: This review explores the influence of attachment styles on pain perception, suggesting a link between social connections and chronic pain development. It aligns with recent calls to emphasize the social context in pain research and advocates for increased focus on adult attachment styles in research and clinical practice.

Complex activity and short-term plasticity of human cerebral organoids reciprocally connected with axons

An inter-regional cortical tract is one of the most fundamental architectural motifs that integrates neural circuits to orchestrate and generate complex functions of the human brain. To understand the mechanistic significance of inter-regional projections on development of neural circuits, we investigated an in vitro neural tissue model for inter-regional connections, in which two cerebral organoids are connected with a bundle of reciprocally extended axons. The connected organoids produced more complex and intense oscillatory activity than conventional or directly fused cerebral organoids, suggesting the inter-organoid axonal connections enhance and support the complex network activity. In addition, optogenetic stimulation of the inter-organoid axon bundles could entrain the activity of the organoids and induce robust short-term plasticity of the macroscopic circuit. These results demonstrated that the projection axons could serve as a structural hub that boosts functionality of the organoid-circuits. This model could contribute to further investigation on development and functions of macroscopic neuronal circuits in vitro.

Hierarchical consciousness: the Nested Observer Windows model

Foremost in our experience is the intuition that we possess a unified conscious experience. However, many observations run counter to this intuition: we experience paralyzing indecision when faced with two appealing behavioral choices, we simultaneously hold contradictory beliefs, and the content of our thought is often characterized by an internal debate. Here, we propose the Nested Observer Windows (NOW) Model, a framework for hierarchical consciousness wherein information processed across many spatiotemporal scales of the brain feeds into subjective experience. The model likens the mind to a hierarchy of nested mosaic tiles-where an image is composed of mosaic tiles, and each of these tiles is itself an image composed of mosaic tiles. Unitary consciousness exists at the apex of this nested hierarchy where perceptual constructs become fully integrated and complex behaviors are initiated via abstract commands. We define an observer window as a spatially and temporally constrained system within which information is integrated, e.g. in functional brain regions and neurons. Three principles from the signal analysis of electrical activity describe the nested hierarchy and generate testable predictions. First, nested observer windows disseminate information across spatiotemporal scales with cross-frequency coupling. Second, observer windows are characterized by a high degree of internal synchrony (with zero phase lag). Third, observer windows at the same spatiotemporal level share information with each other through coherence (with non-zero phase lag). The theoretical framework of the NOW Model accounts for a wide range of subjective experiences and a novel approach for integrating prominent theories of consciousness.

A three-dimensional model of neural activity and phenomenal-behavioral patterns

How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.

Causality methods to study the functional connectivity in brain networks: the basal ganglia - thalamus causal interactions

This study uses methods recently developed to study the complex evolution of atmospheric phenomena which have some similarities with the dynamics of the human brain. In both cases, it is possible to record the activity of particular centers (geographic regions or brain nuclei) but not to make an experimental modification of their state. The study of "causality", which is necessary to understand the dynamics of these complex systems and to develop robust models that can predict their evolution, is hampered by the experimental restrictions imposed by the nature of both systems. The study was performed with data obtained in the thalamus and basal ganglia of awake humans executing different tasks. This work studies the linear, non-linear and more complex relationships of these thalamic centers with the cortex and main BG nuclei, using three complementary techniques: the partial correlation regression method, the Gaussian process regression/distance correlation and a model-free method based on nearest-neighbor that computes the conditional mutual information. These causality methods indicated that the basal ganglia present a different functional relationship with the anterior-ventral (motor), intralaminar and medio-dorsal thalamic centers, and that more than 60% of these thalamus-basal ganglia relationships present a non-linear dynamic (35 of the 57 relationships found). These functional interactions were observed for basal ganglia nuclei with direct structural connections with the thalamus (primary somatosensory and motor cortex, striatum, internal globus pallidum and substantia nigra pars reticulata), but also for basal ganglia without structural connections with the thalamus (external globus pallidum and subthalamic nucleus). The motor tasks induced rapid modifications of the thalamus-basal ganglia interactions. These findings provide new perspectives of the thalamus - BG interactions, many of which may be supported by indirect functional relationships and not by direct excitatory/inhibitory interactions.

Neural perspectives on morality due to beguiling mechanisms

We consider deception an example of behavior that challenges traditional explanations of moral behavior. Beguiling mechanisms, by which we mean deceptiveness with charming seduction for diversion, subtly influence moral sensitivity and judgment in moral dilemma situations. The duality of beguiling mechanisms is important to grasp, including how they relate to the ambiguity of situations. Further, we view moral behavior as quasi-adaptive, affectively based, and reliant on the processes of social cognition, arising out of a set of domain-general primitive predispositions that aggregate to produce moral "mindsets" and increasingly complex moral actions. Building on recent theoretical developments, contend that morality involves a complex heterarchical-hierarchical neurological architecture, where activity is dynamically and contextually dependent, as well as dependent on evolved brain structures and early life year socialization. We contribute to conceptualizing moral behavior from an integrated modern neural perspective. This provides a balance between moral decisions as situational, emotional, and genetically completed non-conscious processes, and the more traditional view of conscious reasoning. Beguiling mechanisms illustrate an integrative model of morality, consistent with emerging insights from affective and cognitive neuroscience.

The Geometry of Low- and High-Level Perceptual Spaces

Low-level features are typically continuous (e.g., the gamut between two colors), but semantic information is often categorical (there is no corresponding gradient between dog and turtle) and hierarchical (animals live in land, water, or air). To determine the impact of these differences on cognitive representations, we characterized the geometry of perceptual spaces of five domains: a domain dominated by semantic information (animal names presented as words), a domain dominated by low-level features (colored textures), and three intermediate domains (animal images, lightly texturized animal images that were easy to recognize, and heavily texturized animal images that were difficult to recognize). Each domain had 37 stimuli derived from the same animal names. From 13 participants (9F), we gathered similarity judgments in each domain via an efficient psychophysical ranking paradigm. We then built geometric models of each domain for each participant, in which distances between stimuli accounted for participants' similarity judgments and intrinsic uncertainty. Remarkably, the five domains had similar global properties: each required 5-7 dimensions, and a modest amount of spherical curvature provided the best fit. However, the arrangement of the stimuli within these embeddings depended on the level of semantic information: dendrograms derived from semantic domains (word, image, and lightly texturized images) were more "tree-like" than those from feature-dominated domains (heavily texturized images and textures). Thus, the perceptual spaces of domains along this feature-dominated to semantic-dominated gradient shift to a tree-like organization when semantic information dominates, while retaining a similar global geometry.

Connecting the dots in the zona incerta: A study of neural assemblies and motifs of inter-area coordination in mice

The zona incerta (ZI), a subthalamic area connected to numerous brain regions, has raised clinical interest because its stimulation alleviates the motor symptoms of Parkinson's disease. To explore its coordinative nature, we studied the assembly formation in a dataset of neural recordings in mice and quantified the degree of functional coordination of ZI with other 24 brain areas. We found that the ZI is a highly integrative area. The analysis in terms of "loop-like" motifs, directional assemblies composed of three neurons spanning two areas, has revealed reciprocal functional interactions with reentrant signals that, in most cases, start and end with the activation of ZI units. In support of its proposed integrative role, we found that almost one-third of the ZI's neurons formed assemblies with more than half of the other recorded areas and that loop-like assemblies may stand out as hyper-integrative motifs compared to other types of activation patterns.

Towards modern post-coma care based on neuroscientific evidence

Background

Understanding the mechanisms underlying human consciousness is pivotal to improve the prognostication and treatment of severely brain-injured patients. Consciousness remains an elusive concept and the identification of its neural correlates is an active subject of research, however recent neuroscientific advances have allowed scientists to better characterize disorders of consciousness. These breakthroughs question the historical nomenclature and our current management of post-comatose patients.

Method

This review examines the contribution of consciousness neurosciences to the current clinical management of severe brain injury. It investigates the major impact of consciousness disorders on healthcare systems, the scientific frameworks employed to identify their neural correlates and how evidence-based data from neuroimaging research have reshaped the landscape of post-coma care in recent years.

Results

Our increased ability to detect behavioral and neurophysiological signatures of consciousness has led to significant changes in taxonomy and clinical practice. We advocate for a multimodal framework for the management of severely brain-injured patients based on precision medicine and evidence-based decisions, integrating epidemiology, health economics and neuroethics.

Conclusions

Major progress in brain imaging and clinical assessment have opened the door to a new era of post-coma care based on standardized neuroscientific evidence. We highlight its implications in clinical applications and call for improved collaborations between researchers and clinicians to better translate findings to the bedside.

Thalamocortical loops as temporal demodulators across senses

Sensory information is coded in space and in time. The organization of neuronal activity in space maintains straightforward relationships with the spatial organization of the perceived environment. In contrast, the temporal organization of neuronal activity is not trivially related to external features due to sensor motion. Still, the temporal organization shares similar principles across sensory modalities. Likewise, thalamocortical circuits exhibit common features across senses. Focusing on touch, vision, and audition, we review their shared coding principles and suggest that thalamocortical systems include circuits that allow analogous recoding mechanisms in all three senses. These thalamocortical circuits constitute oscillations-based phase-locked loops, that translate temporally-coded sensory information to rate-coded cortical signals, signals that can integrate information across sensory and motor modalities. The loop also allows predictive locking to the onset of future modulations of the sensory signal. The paper thus suggests a theoretical framework in which a common thalamocortical mechanism implements temporal demodulation across senses.

Backward masking reveals coarse-to-fine dynamics in human V1

Natural images exhibit luminance variations aligned across a broad spectrum of spatial frequencies (SFs). It has been proposed that, at early stages of processing, the coarse signals carried by the low SF (LSF) of the visual input are sent rapidly from primary visual cortex (V1) to ventral, dorsal and frontal regions to form a coarse representation of the input, which is later sent back to V1 to guide the processing of fine-grained high SFs (i.e., HSF). We used functional resonance imaging (fMRI) to investigate the role of human V1 in the coarse-to-fine integration of visual input. We disrupted the processing of the coarse and fine content of full-spectrum human face stimuli via backward masking of selective SF ranges (LSFs: <1.75cpd and HSFs: >1.75cpd) at specific times (50, 83, 100 or 150ms). In line with coarse-to-fine proposals, we found that (1) the selective masking of stimulus LSF disrupted V1 activity in the earliest time window, and progressively decreased in influence, while (2) an opposite trend was observed for the masking of stimulus' HSF. This pattern of activity was found in V1, as well as in ventral (i.e. the Fusiform Face area, FFA), dorsal and orbitofrontal regions. We additionally presented subjects with contrast negated stimuli. While contrast negation significantly reduced response amplitudes in the FFA, as well as coupling between FFA and V1, coarse-to-fine dynamics were not affected by this manipulation. The fact that V1 response dynamics to strictly identical stimulus sets differed depending on the masked scale adds to growing evidence that V1 role goes beyond the early and quasi-passive transmission of visual information to the rest of the brain. It instead indicates that V1 may yield a 'spatially registered common forum' or 'blackboard' that integrates top-down inferences with incoming visual signals through its recurrent interaction with high-level regions located in the inferotemporal, dorsal and frontal regions.

TMS-evoked responses are driven by recurrent large-scale network dynamics

A compelling way to disentangle the complexity of the brain is to measure the effects of spatially and temporally synchronized systematic perturbations. In humans, this can be non-invasively achieved by combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG). Spatiotemporally complex and long-lasting TMS-EEG evoked potential (TEP) waveforms are believed to result from recurrent, re-entrant activity that propagates broadly across multiple cortical and subcortical regions, dispersing from and later re-converging on, the primary stimulation site. However, if we loosely understand the TEP of a TMS-stimulated region as the impulse response function of a noisy underdamped harmonic oscillator, then multiple later activity components (waveform peaks) should be expected even for an isolated network node in the complete absence of recurrent inputs. Thus emerges a critically important question for basic and clinical research on human brain dynamics: what parts of the TEP are due to purely local dynamics, what parts are due to reverberant, re-entrant network activity, and how can we distinguish between the two? To disentangle this, we used source-localized TMS-EEG analyses and whole-brain connectome-based computational modelling. Results indicated that recurrent network feedback begins to drive TEP responses from 100 ms post-stimulation, with earlier TEP components being attributable to local reverberatory activity within the stimulated region. Subject-specific estimation of neurophysiological parameters additionally indicated an important role for inhibitory GABAergic neural populations in scaling cortical excitability levels, as reflected in TEP waveform characteristics. The novel discoveries and new software technologies introduced here should be of broad utility in basic and clinical neuroscience research.

Is the tendency to maximise energy distribution an optimal collective activity for biological purposes? A proposal for a global principle of biological organization

Our purpose is to address the biological problem of finding foundations of the organization in the collective activity among cell networks in the nervous system, at the meso/macroscale, giving rise to cognition and consciousness. But in doing so, we encounter another problem related to the interpretation of methods to assess the neural interactions and organization of the neurodynamics, because thermodynamic notions, which have precise meaning only under specific conditions, have been widely employed in these studies. The consequence is that apparently contradictory results appear in the literature, but these contradictions diminish upon the considerations of the specific circumstances of each experiment. After clarifying some of these controversial points and surveying some experimental results, we propose that a necessary condition for cognition/consciousness to emerge is to have available enough energy, or cellular activity; and a sufficient condition is the multiplicity of configurations in which cell networks can communicate, resulting in non-uniform energy distribution, the generation and dissipation of energy gradients due to the constant activity. The diversity of sensorimotor processing of higher animals needs a flexible, fluctuating web on neuronal connections, and we review results supporting such multiplicity of configurations among brain regions associated with conscious awareness and healthy brain states. These ideas may reveal possible fundamental principles of brain organization that could be extended to other natural phenomena and how healthy activity may derive to pathological states.

Coupled Dynamics of Stimulus-Evoked Gustatory Cortical and Basolateral Amygdalar Activity

Gustatory cortical (GC) single-neuron taste responses reflect taste quality and palatability in successive epochs. Ensemble analyses reveal epoch-to-epoch firing-rate changes in these responses to be sudden, coherent transitions. Such nonlinear dynamics suggest that GC is part of a recurrent network, producing these dynamics in concert with other structures. Basolateral amygdala (BLA), which is reciprocally connected to GC and central to hedonic processing, is a strong candidate partner for GC, in that BLA taste responses evolve on the same general clock as GC and because inhibition of activity in the BLA→GC pathway degrades the sharpness of GC transitions. These facts motivate, but do not test, our overarching hypothesis that BLA and GC act as a single, comodulated network during taste processing. Here, we provide just this test of simultaneous (BLA and GC) extracellular taste responses in female rats, probing the multiregional dynamics of activity to directly test whether BLA and GC responses contain coupled dynamics. We show that BLA and GC response magnitudes covary across trials and within single responses, and that changes in BLA-GC local field potential phase coherence are epoch specific. Such classic coherence analyses, however, obscure the most salient facet of BLA-GC coupling: sudden transitions in and out of the epoch known to be involved in driving gaping behavior happen near simultaneously in the two regions, despite huge trial-to-trial variability in transition latencies. This novel form of inter-regional coupling, which we show is easily replicated in model networks, suggests collective processing in a distributed neural network.SIGNIFICANCE STATEMENT There has been little investigation into real-time communication between brain regions during taste processing, a fact reflecting the dominant belief that taste circuitry is largely feedforward. Here, we perform an in-depth analysis of real-time interactions between GC and BLA in response to passive taste deliveries, using both conventional coherence metrics and a novel methodology that explicitly considers trial-to-trial variability and fast single-trial dynamics in evoked responses. Our results demonstrate that BLA-GC coherence changes as the taste response unfolds, and that BLA and GC specifically couple for the sudden transition into (and out of) the behaviorally relevant neural response epoch, suggesting (although not proving) that: (1) recurrent interactions subserve the function of the dyad as (2) a putative attractor network.

A blinking focal pattern of re-entrant activity in the avian tectum

Re-entrant connections are inherent to nervous system organization; however, a comprehensive understanding of their operation is still lacking. In birds, topographically organized re-entrant signals, carried by axons from the nucleus-isthmi-parvocellularis (Ipc), are distinctly recorded as bursting discharges across the optic tectum (TeO). Here, we used up to 48 microelectrodes regularly spaced on the superficial tectal layers of anesthetized pigeons to characterize the spatial-temporal pattern of this axonal re-entrant activity in response to different visual stimulation. We found that a brief luminous spot triggered repetitive waves of bursting discharges that, appearing from initial sources, propagated horizontally to areas representing up to 28° of visual space, widely exceeding the area activated by the retinal fibers. In response to visual motion, successive burst waves started along and around the stimulated tectal path, tracking the stimulus in discontinuous steps. When two stimuli were presented, the burst-wave sources alternated between the activated tectal loci, as if only one source could be active at any given time. Because these re-entrant signals boost the retinal input to higher visual areas, their peculiar dynamics mimic a blinking "spotlight," similar to the internal searching mechanism classically used to explain spatial attention. Tectal re-entry from Ipc is thus highly structured and intrinsically discontinuous, and higher tectofugal areas, which lack retinotopic organization, will thus receive incoming visual activity in a sequential and piecemeal fashion. We anticipate that analogous re-entrant patterns, perhaps hidden in less bi-dimensionally organized topographies, may organize the flow of neural activity in other parts of the brain as well.

Ensemble size perception: Its neural signature and the role of global interaction over individual items

To efficiently process complex visual scenes, the visual system often summarizes statistical information across individual items and represents them as an ensemble. However, due to the lack of techniques to disentangle the representation of the ensemble from that of the individual items constituting the ensemble, whether there exists a specialized neural mechanism for ensemble processing and how ensemble perception is computed in the brain remain unknown. To address these issues, we used a frequency-tagging EEG approach to track brain responses to periodically updated ensemble sizes. Neural responses tracking the ensemble size were detected in parieto-occipital electrodes, revealing a global and specialized neural mechanism of ensemble size perception. We then used the temporal response function to isolate neural responses to the individual sizes and their interactions. Notably, while the individual sizes and their local and global interactions were encoded in the EEG signals, only the global interaction contributed directly to the ensemble size perception. Finally, distributed attention to the global stimulus pattern enhanced the neural signature of the ensemble size, mainly by modulating the neural representation of the global interaction between all individual sizes. These findings advocate a specialized, global neural mechanism of ensemble size perception and suggest that global interaction between individual items contributes to ensemble perception.

Twenty years of investigation with the case of prosopagnosia PS to understand human face identity recognition. Part II: Neural basis

Patient PS sustained her dramatic brain injury in 1992, the same year as the first report of a neuroimaging study of human face recognition. The present paper complements the review on the functional nature of PS's prosopagnosia (part I), illustrating how her case study directly, i.e., through neuroimaging investigations of her brain structure and activity, but also indirectly, through neural studies performed on other clinical cases and neurotypical individuals, inspired and constrained neural models of human face recognition. In the dominant right hemisphere for face recognition in humans, PS's main lesion concerns (inputs to) the inferior occipital gyrus (IOG), in a region where face-selective activity is typically found in normal individuals ('Occipital Face Area', OFA). Her case study initially supported the criticality of this region for face identity recognition (FIR) and provided the impetus for transcranial magnetic stimulation (TMS), intracerebral electrical stimulation, and cortical surgery studies that have generally supported this view. Despite PS's right IOG lesion, typical face-selectivity is found anteriorly in the middle portion of the fusiform gyrus, a hominoid structure (termed the right 'Fusiform Face Area', FFA) that is widely considered to be the most important region for human face recognition. This finding led to the original proposal of direct anatomico-functional connections from early visual cortices to the FFA, bypassing the IOG/OFA (lulu), a hypothesis supported by further neuroimaging studies of PS, other neurological cases and neuro-typical individuals with original visual stimulation paradigms, data recordings and analyses. The proposal of a lack of sensitivity to face identity in PS's right FFA due to defective reentrant inputs from the IOG/FFA has also been supported by other cases, functional connectivity and cortical surgery studies. Overall, neural studies of, and based on, the case of prosopagnosia PS strongly question the hierarchical organization of the human neural face recognition system, supporting a more flexible and dynamic view of this key social brain function.

Does Machine Understanding Require Consciousness?

This article addresses the question of whether machine understanding requires consciousness. Some researchers in the field of machine understanding have argued that it is not necessary for computers to be conscious as long as they can match or exceed human performance in certain tasks. But despite the remarkable recent success of machine learning systems in areas such as natural language processing and image classification, important questions remain about their limited performance and about whether their cognitive abilities entail genuine understanding or are the product of spurious correlations. Here I draw a distinction between natural, artificial, and machine understanding. I analyse some concrete examples of natural understanding and show that although it shares properties with the artificial understanding implemented in current machine learning systems it also has some essential differences, the main one being that natural understanding in humans entails consciousness. Moreover, evidence from psychology and neurobiology suggests that it is this capacity for consciousness that, in part at least, explains for the superior performance of humans in some cognitive tasks and may also account for the authenticity of semantic processing that seems to be the hallmark of natural understanding. I propose a hypothesis that might help to explain why consciousness is important to understanding. In closing, I suggest that progress toward implementing human-like understanding in machines—machine understanding—may benefit from a naturalistic approach in which natural processes are modelled as closely as possible in mechanical substrates.

From Analog to Digital Computing: Is Homo sapiens’ Brain on Its Way to Become a Turing Machine?

The abstract basis of modern computation is the formal description of a finite state machine, the Universal Turing Machine, based on manipulation of integers and logic symbols. In this contribution to the discourse on the computer-brain analogy, we discuss the extent to which analog computing, as performed by the mammalian brain, is like and unlike the digital computing of Universal Turing Machines. We begin with ordinary reality being a permanent dialog between continuous and discontinuous worlds. So it is with computing, which can be analog or digital, and is often mixed. The theory behind computers is essentially digital, but efficient simulations of phenomena can be performed by analog devices; indeed, any physical calculation requires implementation in the physical world and is therefore analog to some extent, despite being based on abstract logic and arithmetic. The mammalian brain, comprised of neuronal networks, functions as an analog device and has given rise to artificial neural networks that are implemented as digital algorithms but function as analog models would. Analog constructs compute with the implementation of a variety of feedback and feedforward loops. In contrast, digital algorithms allow the implementation of recursive processes that enable them to generate unparalleled emergent properties. We briefly illustrate how the cortical organization of neurons can integrate signals and make predictions analogically. While we conclude that brains are not digital computers, we speculate on the recent implementation of human writing in the brain as a possible digital path that slowly evolves the brain into a genuine (slow) Turing machine.

Network dynamics scale with levels of awareness

Small world topologies are thought to provide a valuable insight into human brain organisation and consciousness. However, functional magnetic resonance imaging studies in consciousness have not yielded consistent results. Given the importance of dynamics for both consciousness and cognition, here we investigate how the diversity of small world dynamics (quantified by sample entropy; dSW-E¹) scales with decreasing levels of awareness (i.e., sedation and disorders of consciousness). Paying particular attention to result reproducibility, we show that dSW-E is a consistent predictor of levels of awareness even when controlling for the underlying functional connectivity dynamics. We find that dSW-E of subcortical and cortical areas are predictive, with the former showing higher and more robust effect sizes across analyses. We find that the network dynamics of intermodular communication in the cerebellum also have unique predictive power for levels of awareness. Consequently, we propose that the dynamic reorganisation of the functional information architecture, in particular of the subcortex, is a characteristic that emerges with awareness and has explanatory power beyond that of the complexity of dynamic functional connectivity.

A Unified Software/Hardware Scalable Architecture for Brain-Inspired Computing Based on Self-Organizing Neural Models

The field of artificial intelligence has significantly advanced over the past decades, inspired by discoveries from the fields of biology and neuroscience. The idea of this work is inspired by the process of self-organization of cortical areas in the human brain from both afferent and lateral/internal connections. In this work, we develop a brain-inspired neural model associating Self-Organizing Maps (SOM) and Hebbian learning in the Reentrant SOM (ReSOM) model. The framework is applied to multimodal classification problems. Compared to existing methods based on unsupervised learning with post-labeling, the model enhances the state-of-the-art results. This work also demonstrates the distributed and scalable nature of the model through both simulation results and hardware execution on a dedicated FPGA-based platform named SCALP (Self-configurable 3D Cellular Adaptive Platform). SCALP boards can be interconnected in a modular way to support the structure of the neural model. Such a unified software and hardware approach enables the processing to be scaled and allows information from several modalities to be merged dynamically. The deployment on hardware boards provides performance results of parallel execution on several devices, with the communication between each board through dedicated serial links. The proposed unified architecture, composed of the ReSOM model and the SCALP hardware platform, demonstrates a significant increase in accuracy thanks to multimodal association, and a good trade-off between latency and power consumption compared to a centralized GPU implementation.

Different measures of holistic face processing tap into distinct but partially overlapping mechanisms

Holistic processing, which includes the integration of facial features and analysis of their relations to one another, is a hallmark of what makes faces 'special'. Various experimental paradigms purport to measure holistic processing but these have often produced inconsistent results. This has led researchers to question the nature and structure of the mechanism(s) underlying holistic processing. Using an individual differences approach, researchers have examined relations between various measures of holistic processing in an attempt to resolve these questions. In keeping with this, we examined relationships between four commonly used measures of holistic face processing in a large group of participants (N = 223): (1) The Face Inversion Effect, (2) the Part Whole Effect (PWE), (3) the Composite Face Effect, and (4) the Configural Featural Detection Task (CFDT). Several novel methodological and analytical elements were introduced, including the use of factor analysis and the inclusion of control conditions to confirm the face specificity of all of the effects measured. The four indexes of holistic processing derived from each measure loaded onto two factors, one encompassing the PWE and the CFDT, and one encompassing the CE. The 16 conditions tested across the four tasks loaded onto four factors, each factor corresponding to a different measure. These results, together with those of other studies, suggest that holistic processing is a multifaceted construct and that different measures tap into distinct but partially overlapping elements of it.

The causal interaction in human basal ganglia

The experimental study of the human brain has important restrictions, particularly in the case of basal ganglia, subcortical centers whose activity can be recorded with fMRI methods but cannot be directly modified. Similar restrictions occur in other complex systems such as those studied by Earth system science. The present work studied the cause/effect relationships between human basal ganglia with recently introduced methods to study climate dynamics. Data showed an exhaustive (identifying basal ganglia interactions regardless of their linear, non-linear or complex nature) and selective (avoiding spurious relationships) view of basal ganglia activity, showing a fast functional reconfiguration of their main centers during the execution of voluntary motor tasks. The methodology used here offers a novel view of the human basal ganglia which expands the perspective provided by the classical basal ganglia model and may help to understand BG activity under normal and pathological conditions.

A Connectomic Hypothesis for the Hominization of the Brain

Cognitive abilities of the human brain, including language, have expanded dramatically in the course of our recent evolution from nonhuman primates, despite only minor apparent changes at the gene level. The hypothesis we propose for this paradox relies upon fundamental features of human brain connectivity, which contribute to a characteristic anatomical, functional, and computational neural phenotype, offering a parsimonious framework for connectomic changes taking place upon the human-specific evolution of the genome. Many human connectomic features might be accounted for by substantially increased brain size within the global neural architecture of the primate brain, resulting in a larger number of neurons and areas and the sparsification, increased modularity, and laminar differentiation of cortical connections. The combination of these features with the developmental expansion of upper cortical layers, prolonged postnatal brain development, and multiplied nongenetic interactions with the physical, social, and cultural environment gives rise to categorically human-specific cognitive abilities including the recursivity of language. Thus, a small set of genetic regulatory events affecting quantitative gene expression may plausibly account for the origins of human brain connectivity and cognition.

How Beat Perception Co-opts Motor Neurophysiology

Beat perception offers cognitive scientists an exciting opportunity to explore how cognition and action are intertwined in the brain even in the absence of movement. Many believe the motor system predicts the timing of beats, yet current models of beat perception do not specify how this is neurally implemented. Drawing on recent insights into the neurocomputational properties of the motor system, we propose that beat anticipation relies on action-like processes consisting of precisely patterned neural time-keeping activity in the supplementary motor area (SMA), orchestrated and sequenced by activity in the dorsal striatum. In addition to synthesizing recent advances in cognitive science and motor neuroscience, our framework provides testable predictions to guide future work.

Associations between performance-based and self-reported prospective memory, impulsivity and encoding support

Prospective memory (PM) is the ability to execute future intended actions and may be negatively affected by impulsivity. The current study aimed to address questions on (1) relationships of PM with facets of impulsivity; (2) psychometric properties of a PM task, in particular convergent validity with self-reported PM; and (3) whether external support of the encoding process would improve PM or affect relationships with impulsivity. 245 participants performed the experiment online. Participants completed either a baseline version of the task, which combined blocks of an ongoing working memory task with PM trials involving a varying stimulus requiring an alternative response; or a version that provided external support of encoding by requesting that participants visualize and execute the intended prospective action before each block. The Prospective-Retrospective Memory Questionnaire (PRMQ) and Short Version of the UPPS-P Impulsive Behavior Scale (SUPPS) were used to assess self-reported prospective memory and facets of impulsivity. Reliability of PM performance was good and remained acceptable even with the exclusion of participants with low scores. PM performance was associated with self-reported PM, explaining variance in addition to that explained by working memory performance. PM performance was also negatively associated with impulsivity, in particular sensation seeking and positive urgency, but only in the baseline task. Support did not cause overall improvements in performance. In conclusion, results provided further evidence for a relationship between facets of impulsivity and PM. PM as assessed via the current task has good psychometric properties.

International Health Practices: A Multidisciplinary Approach to Therapeutic Mediations With an Artistic Medium Based on the Model of Play

This article, corresponding to a part of the restitution of a financed international research project between France, Brazil, Canada, Italy and Belgium, aims to offer a modelisation and qualitative evaluation of mediation care settings based on an original methodological tool that involves identifying the typical games at the foundations of creativity, following a multidisciplinary perspective. Therapeutic mediations are settings or devices organized around a “pliable medium,” often artistic, like painting, modeling, writing and theater, which are very widespread in institutional practices, both in France and abroad. The scientific objectives of this research consist in a multi-disciplinary exploration (anthropology, criminology, neuroscience, clinical psychology) of the process of creative symbolization understood as a process of transformation involving play. According to this orientation, play can be defined as a psychic process whereby a subjective experience can be explored with pleasure, and consequently symbolized and appropriated. Our fundamental and original hypothesis is that play is at the source of the creative process, conceived as a work of metabolization by the psyche of playful experiences during the different stages of life. The review of the understanding of play in psychoanalysis, anthropology, criminology and neuroscience emphasizes the richness of this model and the importance of reflecting on the typical games in the field of psychic care. A clinical example of treatment in a pictorial therapeutic mediation setting of a child with psychotic disorders makes it possible to identify a number of typical games as well as the modalities of interpretation of the therapists through play. These multidisciplinary studies lead to the presentation of a general table of typical games, and these first results highlight the richness of identifying typical games in clinical settings. Ultimately, the multidisciplinary approach shows the interest of the model of play in the evaluation of therapeutic mediation settings, with a convergence of the different disciplines emphasizing the pertinence of this model. The scientific impact of this research overlaps with its societal impact, through the development of innovative tools for evaluating therapeutic mediations, in order to take account of the evolution of the different forms of social expression of psychic suffering.

On the emergence of cognition: from catalytic closure to neuroglial closure

In an analogous manner as occurred during the development of a connected metabolism that at some point reached characteristics associated with what is called "life"-due mainly to a catalytic closure phenomenon when chemicals started to autocatalyze themselves forming a closed web of chemical reactions-it is here proposed that cognition and consciousness (or features associated with them) arose as a consequence of another type of closure within the nervous system, the brain especially. Proper brain function requires an efficient web of connections and once certain complexity is attained due to the number and coordinated activities of the brain cell networks, the emergent properties of cognition and consciousness take place. Seeking to identify main features of the nervous system organization for optimal function, it is here proposed that while catalytic closure yielded life, neuroglial closure produced cognition/consciousness.

Cortical stimulation in aphasia following ischemic stroke: toward model-guided electrical neuromodulation

The aim of this paper is to integrate different bodies of research including brain traveling waves, brain neuromodulation, neural field modeling and post-stroke language disorders in order to explore the opportunity of implementing model-guided, cortical neuromodulation for the treatment of post-stroke aphasia. Worldwide according to WHO, strokes are the second leading cause of death and the third leading cause of disability. In ischemic stroke, there is not enough blood supply to provide enough oxygen and nutrients to parts of the brain, while in hemorrhagic stroke, there is bleeding within the enclosed cranial cavity. The present paper focuses on ischemic stroke. We first review accumulating observations of traveling waves occurring spontaneously or triggered by external stimuli in healthy subjects as well as in patients with brain disorders. We examine the putative functions of these waves and focus on post-stroke aphasia observed when brain language networks become fragmented and/or partly silent, thus perturbing the progression of traveling waves across perilesional areas. Secondly, we focus on a simplified model based on the current literature in the field and describe cortical traveling wave dynamics and their modulation. This model uses a biophysically realistic integro-differential equation describing spatially distributed and synaptically coupled neural networks producing traveling wave solutions. The model is used to calculate wave parameters (speed, amplitude and/or frequency) and to guide the reconstruction of the perturbed wave. A stimulation term is included in the model to restore wave propagation to a reasonably good level. Thirdly, we examine various issues related to the implementation model-guided neuromodulation in the treatment of post-stroke aphasia given that closed-loop invasive brain stimulation studies have recently produced encouraging results. Finally, we suggest that modulating traveling waves by acting selectively and dynamically across space and time to facilitate wave propagation is a promising therapeutic strategy especially at a time when a new generation of closed-loop cortical stimulation systems is about to arrive on the market.

Age-related changes in amplitude, latency and specialization of ERP responses to faces and watches

Healthy aging is associated with impairments in face recognition. While earlier research suggests that these impairments arise during memory retrieval, more recent findings suggest that earlier mechanisms, at the perceptual stage, may also be at play. However, results are often inconsistent and very few studies have included a non-face control stimulus to facilitate interpretation of results with respect to the implication of specialized face mechanisms vs. general cognitive factors. To address these issues, P100, N170 and P200 event-related potentials (ERPs) were measured during processing of faces and watches. For faces, age-related differences were found for P100, N170 and P200 ERPs. For watches, age-related differences were found for N170 and P200 ERPs. Older adults showed less selective and less lateralized N170 responses to faces, suggesting that ERPs can detect age-related de-differentiation of specialized face networks. We conclude that age-related impairments in face recognition arise in part from difficulties in the earliest perceptual stages of visual information processing. A working model is presented based on coarse-to-fine analysis of visually similar exemplars.

Targeting Reciprocally Connected Brain Regions Through CAV-2 Mediated Interventions

An important issue in contemporary neuroscience is to identify functional principles at play within neural circuits. The reciprocity of the connections between two distinct brain areas appears as an intriguing feature of some of these circuits. This organization has been viewed as "re-entry," a process whereby two or more brain regions concurrently stimulate and are stimulated by each other, thus supporting the synchronization of neural firing required for rapid neural integration. However, until relatively recently, it was not possible to provide a comprehensive functional assessment of such reciprocal pathways. In this Brief Research Report, we highlight the use of a chemogenetic strategy to target projection-defined neurons in reciprocally connected areas through CAV-2 mediated interventions in the rat. Specifically, we targeted the bidirectional pathways between the dorsomedial prefrontal cortex (dmPFC) and the mediodorsal thalamus, as well as those connecting the insular cortex (IC) and the basolateral complex of the amygdala (BLA). These data showcase the usefulness of CAV-2-related strategies to address circuit-level issues. Moreover, we illustrate the inherent limitation of Cre-dependent adeno-associated virues (AAVs) with "leaked" expression of the gene of interest in the absence of Cre and highlight the need for appropriate control conditions.

The Predictive Processing Model of EMDR

Eye Movement Desensitization and Reprocessing Therapy (EMDR) is an effective treatment for Post-traumatic Stress Disorder (PTSD). The Adaptive Information Processing Model (AIP) guides the development and practice of EMDR. The AIP postulates inadequately processed memory as the foundation of PTSD pathology. Predictive Processing postulates that the primary function of the brain is prediction that serves to anticipate the next moment of experience in order to resist the dissipative force of entropy thus facilitating continued survival. Memory is the primary substrate of prediction, and is optimized by an ongoing process of precision weighted prediction error minimization that refines prediction by updating the memories on which it is based. The Predictive Processing model of EMDR postulates that EMDR facilitates the predictive processing of traumatic memory by overcoming the bias against exploration and evidence accumulation. The EMDR protocol brings the traumatic memory into an active state of re-experiencing. Defensive responding and/or low sensory precision preclude evidence accumulation to test the predictions of the traumatic memory in the present. Sets of therapist guided eye movements repeatedly challenge the bias against evidence accumulation and compel sensory sampling of the benign present. Eye movements reset the theta rhythm organizing the flow of information through the brain, facilitating the deployment of both overt and covert attention, and the mnemonic search for associations. Sampling of sensation does not support the predictions of the traumatic memory resulting in prediction error that the brain then attempts to minimize. The net result is a restoration of the integrity of the rhythmic deployment of attention, a recalibration of sensory precision, and the updating (reconsolidation) of the traumatic memory. Thus one prediction of the model is a decrease in Attention Bias Variability, a core dysfunction in PTSD, following successful treatment with EMDR.

Continuous Theta Burst Stimulation Over the Right Orbitofrontal Cortex Impairs Conscious Olfactory Perception

The right orbitofrontal cortex (rOFC) has been proposed as the region where conscious olfactory perception arises; however, evidence supporting this hypothesis has all been collected from neuroimaging and lesion studies in which only correlation and not a temporal pattern can be established. Continuous theta burst stimulation (cTBS) causes a reversible disruption of cortical activity and has been used successfully to disrupt orbitofrontal activity. To overcome intrinsic limitations of current experimental research, a crossover, double-blind, prospective and longitudinal study was carried out in which cTBS was applied over the rOFC to evaluate its effect on odorant stimuli detection. All subjects received real and sham cTBS. Experimental procedures were done in two different sessions with a separation of at least one week between them to avoid carryover and learning effects. A total of 15 subjects completed the experiment, and their data were included in the final analysis (10 women, 5 men, mean age 22.40 ± 3.41). Every session consisted of two different measures of the conscious olfactory perception task: A baseline measure and one 5 min after cTBS/sham. Compared to baseline, marks in the olfactory task during the sham cTBS session increased (p = 0.010), while marks during the real cTBS session decreased (p = 0.017). Our results support the hypothesis that rOFC is an important node of a complex network required for conscious olfactory perception to arise. However, the exact mechanism that explains our results is unclear and could be explained by the disruption of other cognitive functions related to the rOFC.

Dynamic Computation in Visual Thalamocortical Networks

Contemporary neurodynamical frameworks, such as coordination dynamics and winnerless competition, posit that the brain approximates symbolic computation by transitioning between metastable attractive states. This article integrates these accounts with electrophysiological data suggesting that coherent, nested oscillations facilitate information representation and transmission in thalamocortical networks. We review the relationship between criticality, metastability, and representational capacity, outline existing methods for detecting metastable oscillatory patterns in neural time series data, and evaluate plausible spatiotemporal coding schemes based on phase alignment. We then survey the circuitry and the mechanisms underlying the generation of coordinated alpha and gamma rhythms in the primate visual system, with particular emphasis on the pulvinar and its role in biasing visual attention and awareness. To conclude the review, we begin to integrate this perspective with longstanding theories of consciousness and cognition.

Intrinsic Rivalry. Can White Bears Help Us With the Other Side of Consciousness?

Studies of consciousness have traditionally been based mainly upon the perceptual domains of consciousness. However, there is another side of consciousness, represented by various types of intrinsic conscious experiences. Even though intrinsic experiences can represent up to 50% of our conscious experiences, they are still largely neglected in conscious studies. We assume there are two reasons for this. First, the field of intrinsic conscious experiences is methodologically far more problematic than any other. Second, specific paradigms for capturing the correlates of intrinsic conscious experiences are almost nonexistent. Nevertheless, we expect the intrinsic side of consciousness to soon take its place in conscious studies, but first new experimental paradigms will have to be devised, which would be of a similar design to the paradigms used in studies of perceptual consciousness. In this hypothesis and theory article, we propose such a hypothetical paradigm, presenting the exploratory data of our proof-of-concept study, discussing its use, and addressing its shortcomings and their possible remediation.

The Cognitive Thalamus as a Gateway to Mental Representations

Historically, the thalamus has been viewed as little more than a relay, simply transferring information to key players of the cast, the cortex and hippocampus, without providing any unique functional contribution. In recent years, evidence from multiple laboratories researching different thalamic nuclei has contradicted this idea of the thalamus as a passive structure. Dated models of thalamic functions are being pushed aside, revealing a greater and far more complex contribution of the thalamus for cognition. In this Viewpoints article, we show how recent data support novel views of thalamic functions that emphasize integrative roles in cognition, ranging from learning and memory to flexible adaption. We propose that these apparently separate cognitive functions may indeed be supported by a more general role in shaping mental representations. Several features of thalamocortical circuits are consistent with this suggested role, and we highlight how divergent and convergent thalamocortical and corticothalamic pathways may complement each other to support these functions. Furthermore, the role of the thalamus for subcortical integration is highlighted as a key mechanism for maintaining and updating representations. Finally, we discuss future areas of research and stress the importance of incorporating new experimental findings into existing knowledge to continue developing thalamic models. The presence of thalamic pathology in a number of neurological conditions reinforces the need to better understand the role of this region in cognition.

Consciousness as a Physical Process Caused by the Organization of Energy in the Brain

To explain consciousness as a physical process we must acknowledge the role of energy in the brain. Energetic activity is fundamental to all physical processes and causally drives biological behavior. Recent neuroscientific evidence can be interpreted in a way that suggests consciousness is a product of the organization of energetic activity in the brain. The nature of energy itself, though, remains largely mysterious, and we do not fully understand how it contributes to brain function or consciousness. According to the principle outlined here, energy, along with forces and work, can be described as actualized differences of motion and tension. By observing physical systems, we can infer there is something it is like to undergo actualized difference from the intrinsic perspective of the system. Consciousness occurs because there is something it is like, intrinsically, to undergo a certain organization of actualized differences in the brain.

Threat Response System: Parallel Brain Processes in Pain vis-à-vis Fear and Anxiety

Pain is essential for avoidance of tissue damage and for promotion of healing. Notwithstanding the survival value, pain brings about emotional suffering reflected in fear and anxiety, which in turn augment pain thus giving rise to a self-sustaining feedforward loop. Given such reciprocal relationships, the present article uses neuroscientific conceptualizations of fear and anxiety as a theoretical framework for hitherto insufficiently understood pathophysiological mechanisms underlying chronic pain. To that end, searches of PubMed-indexed journals were performed using the following Medical Subject Headings' terms: pain and nociception plus amygdala, anxiety, cognitive, fear, sensory, and unconscious. Recursive sets of scientific and clinical evidence extracted from this literature review were summarized within the following key areas: (1) parallelism between acute pain and fear and between chronic pain and anxiety; (2) all are related to the evasion of sensory-perceived threats and are subserved by subcortical circuits mediating automatic threat-induced physiologic responses and defensive actions in conjunction with higher order corticolimbic networks (e.g., thalamocortical, thalamo-striato-cortical and amygdalo-cortical) generating conscious representations and valuation-based adaptive behaviors; (3) some instances of chronic pain and anxiety conditions are driven by the failure to diminish or block respective nociceptive information or unconscious treats from reaching conscious awareness; and (4) the neural correlates of pain-related conscious states and cognitions may become autonomous (i.e., dissociated) from the subcortical activity/function leading to the eventual chronicity. Identifying relative contributions of the diverse neuroanatomical sources, thus, offers prospects for the development of novel preventive, diagnostic, and therapeutic strategies in chronic pain patients.

EEG Spectral Generators Involved in Motor Imagery: A swLORETA Study

In order to characterize the neural generators of the brain oscillations related to motor imagery (MI), we investigated the cortical, subcortical, and cerebellar localizations of their respective electroencephalogram (EEG) spectral power and phase locking modulations. The MI task consisted in throwing a ball with the dominant upper limb while in a standing posture, within an ecological virtual reality (VR) environment (tennis court). The MI was triggered by the visual cues common to the control condition, during which the participant remained mentally passive. As previously developed, our paradigm considers the confounding problem that the reference condition allows two complementary analyses: one which uses the baseline before the occurrence of the visual cues in the MI and control resting conditions respectively; and the other which compares the analog periods between the MI and the control resting-state conditions. We demonstrate that MI activates specific, complex brain networks for the power and phase modulations of the EEG oscillations. An early (225 ms) delta phase-locking related to MI was generated in the thalamus and cerebellum and was followed (480 ms) by phase-locking in theta and alpha oscillations, generated in specific cortical areas and the cerebellum. Phase-locking preceded the power modulations (mainly alpha-beta ERD), whose cortical generators were situated in the frontal BA45, BA11, BA10, central BA6, lateral BA13, and posterior cortex BA2. Cerebellar-thalamic involvement through phase-locking is discussed as an underlying mechanism for recruiting at later stages the cortical areas involved in a cognitive role during MI.

A neuroanatomical predictor of mirror self-recognition in chimpanzees

The ability to recognize one's own reflection is shared by humans and only a few other species, including chimpanzees. However, this ability is highly variable across individual chimpanzees. In humans, self-recognition involves a distributed, right-lateralized network including frontal and parietal regions involved in the production and perception of action. The superior longitudinal fasciculus (SLF) is a system of white matter tracts linking these frontal and parietal regions. The current study measured mirror self-recognition (MSR) and SLF anatomy in 60 chimpanzees using diffusion tensor imaging. Successful self-recognition was associated with greater rightward asymmetry in the white matter of SLFII and SLFIII, and in SLFIII's gray matter terminations in Broca's area. We observed a visible progression of SLFIII's prefrontal extension in apes that show negative, ambiguous, and compelling evidence of MSR. Notably, SLFIII's terminations in Broca's area are not right-lateralized or particularly pronounced at the population level in chimpanzees, as they are in humans. Thus, chimpanzees with more human-like behavior show more human-like SLFIII connectivity. These results suggest that self-recognition may have co-emerged with adaptations to frontoparietal circuitry.

Brain network clustering with information flow motifs

Recent work has revealed frequency-dependent global patterns of information flow by a network analysis of magnetoencephalography data of the human brain. However, it is unknown which properties on a small subgraph-scale of those functional brain networks are dominant at different frequencies bands. Motifs are the building blocks of networks on this level and have previously been identified as important features for healthy and abnormal brain function. In this study, we present a network construction that enables us to search and analyze motifs in different frequency bands. We give evidence that the bi-directional two-hop path is the most important motif for the information flow in functional brain networks. A clustering based on this motif exposes a spatially coherent yet frequency-dependent sub-division between the posterior, occipital and frontal brain regions.

Spike-Based Functional Connectivity in Cerebral Cortex and Hippocampus: Loss of Global Connectivity Is Coupled to Preservation of Local Connectivity During Non-REM Sleep

Behavioral states are commonly considered global phenomena with homogeneous neural determinants. However, recent studies indicate that behavioral states modulate spiking activity with neuron-level specificity as a function of brain area, neuronal subtype, and preceding history. Although functional connectivity also strongly depends on behavioral state at a mesoscopic level and is globally weaker in non-REM (NREM) sleep and anesthesia than wakefulness, it is unknown how neuronal communication is modulated at the cellular level. We hypothesize that, as for neuronal activity, the influence of behavioral states on neuronal coupling strongly depends on type, location, and preceding history of involved neurons. Here, we applied nonlinear, information-theoretical measures of functional connectivity to ensemble recordings with single-cell resolution to quantify neuronal communication in the neocortex and hippocampus of rats during wakefulness and sleep. Although functional connectivity (measured in terms of coordination between firing rate fluctuations) was globally stronger in wakefulness than in NREM sleep (with distinct traits for cortical and hippocampal areas), the drop observed during NREM sleep was mainly determined by a loss of inter-areal connectivity between excitatory neurons. Conversely, local (intra-area) connectivity and long-range (inter-areal) coupling between interneurons were preserved during NREM sleep. Furthermore, neuronal networks that were either modulated or not by a behavioral task remained segregated during quiet wakefulness and NREM sleep. These results show that the drop in functional connectivity during wake-sleep transitions globally holds true at the cellular level, but confine this change mainly to long-range coupling between excitatory neurons.

SIGNIFICANCE STATEMENT

Studies performed at a mesoscopic level of analysis have shown that communication between cortical areas is disrupted in non-REM sleep and anesthesia. However, the neuronal determinants of this phenomenon are not known. Here, we applied nonlinear, information-theoretical measures of functional coupling to multi-area tetrode recordings from freely moving rats to investigate whether and how brain state modulates coordination between individual neurons. We found that the previously observed drop in functional connectivity during non-REM (NREM) sleep can be explained by a decrease in coupling between excitatory neurons located in distinct brain areas. Conversely, intra-area communication and coupling between interneurons are preserved. Our results provide significant new insights into the neuron-level mechanisms responsible for the loss of consciousness occurring in NREM sleep.

Disconnecting Consciousness: Is There a Common Anesthetic End Point?

A quest for a systems-level neuroscientific basis of anesthetic-induced loss and return of consciousness has been in the forefront of research for the past 2 decades. Recent advances toward the discovery of underlying mechanisms have been achieved using experimental electrophysiology, multichannel electroencephalography, magnetoencephalography, and functional magnetic resonance imaging. By the careful dosing of various volatile and IV anesthetic agents to the level of behavioral unresponsiveness, both specific and common changes in functional and effective connectivity across large-scale brain networks have been discovered and interpreted in the context of how the synthesis of neural information might be affected during anesthesia. The results of most investigations to date converge toward the conclusion that a common neural correlate of anesthetic-induced unresponsiveness is a consistent depression or functional disconnection of lateral frontoparietal networks, which are thought to be critical for consciousness of the environment. A reduction in the repertoire of brain states may contribute to the anesthetic disruption of large-scale information integration leading to unconsciousness. In future investigations, a systematic delineation of connectivity changes with multiple anesthetics using the same experimental design, and the same analytical method will be desirable. The critical neural events that account for the transition between responsive and unresponsive states should be assessed at similar anesthetic doses just below and above the loss or return of responsiveness. There will also be a need to identify a robust, sensitive, and reliable measure of information transfer. Ultimately, finding a behavior-independent measure of subjective experience that can track covert cognition in unresponsive subjects and a delineation of causal factors versus correlated events will be essential to understand the neuronal basis of human consciousness and unconsciousness.

Short-term EEG dynamics and neural generators evoked by navigational images

The ecological environment offered by virtual reality is primarily supported by visual information. The different image contents and their rhythmic presentation imply specific bottom-up and top-down processing. Because these processes already occur during passive observation we studied the brain responses evoked by the presentation of specific 3D virtual tunnels with respect to 2D checkerboard. For this, we characterized electroencephalograhy dynamics (EEG), the evoked potentials and related neural generators involved in various visual paradigms. Time-frequency analysis showed modulation of alpha-beta oscillations indicating the presence of stronger prediction and after-effects of the 3D-tunnel with respect to the checkerboard. Whatever the presented image, the generators of the P100 were situated bilaterally in the occipital cortex (BA18, BA19) and in the right inferior temporal cortex (BA20). In checkerboard but not 3D-tunnel presentation, the left fusiform gyrus (BA37) was additionally recruited. P200 generators were situated in the temporal cortex (BA21) and the cerebellum (lobule VI/Crus I) specifically for the checkerboard while the right parahippocampal gyrus (BA36) and the cerebellum (lobule IV/V and IX/X) were involved only during the 3D-tunnel presentation. For both type of image, P300 generators were localized in BA37 but also in BA19, the right BA21 and the cerebellar lobule VI for only the checkerboard and the left BA20-BA21 for only the 3D-tunnel. Stronger P300 delta-theta oscillations recorded in this later situation point to a prevalence of the effect of changing direction over the proper visual content of the 3D-tunnel. The parahippocampal gyrus (BA36) implicated in navigation was also identified when the 3D-tunnel was compared to their scrambled versions, highlighting an action-oriented effect linked to navigational content.

Reentrant Information Flow in Electrophysiological Rat Default Mode Network

Functional MRI (fMRI) studies have demonstrated that the rodent brain shows a default mode network (DMN) activity similar to that in humans, offering a potential preclinical model both for physiological and pathophysiological studies. However, the neuronal mechanism underlying rodent DMN remains poorly understood. Here, we used electrophysiological data to analyze the power spectrum and estimate the directed phase transfer entropy (dPTE) within rat DMN across three vigilance states: wakeful rest (WR), slow-wave sleep (SWS), and rapid-eye-movement sleep (REMS). We observed decreased gamma powers during SWS compared with WR in most of the DMN regions. Increased gamma powers were found in prelimbic cortex, cingulate cortex, and hippocampus during REMS compared with WR, whereas retrosplenial cortex showed a reverse trend. These changed gamma powers are in line with the local metabolic variation of homologous brain regions in humans. In the analysis of directional interactions, we observed well-organized anterior-to-posterior patterns of information flow in the delta band, while opposite patterns of posterior-to-anterior flow were found in the theta band. These frequency-specific opposite patterns were only observed in WR and REMS. Additionally, most of the information senders in the delta band were also the receivers in the theta band, and vice versa. Our results provide electrophysiological evidence that rat DMN is similar to its human counterpart, and there is a frequency-dependent reentry loop of anterior-posterior information flow within rat DMN, which may offer a mechanism for functional integration, supporting conscious awareness.

Life and Understanding: The Origins of "Understanding" in Self-Organizing Nervous Systems

This article is motivated by a formulation of biotic self-organization in Friston (2013), where the emergence of "life" in coupled material entities (e.g., macromolecules) was predicated on bounded subsets that maintain a degree of statistical independence from the rest of the network. Boundary elements in such systems constitute a Markov blanket; separating the internal states of a system from its surrounding states. In this article, we ask whether Markov blankets operate in the nervous system and underlie the development of intelligence, enabling a progression from the ability to sense the environment to the ability to understand it. Markov blankets have been previously hypothesized to form in neuronal networks as a result of phase transitions that cause network subsets to fold into bounded assemblies, or packets (Yufik and Sheridan, 1997; Yufik, 1998a). The ensuing neuronal packets hypothesis builds on the notion of neuronal assemblies (Hebb, 1949, 1980), treating such assemblies as flexible but stable biophysical structures capable of withstanding entropic erosion. In other words, structures that maintain their integrity under changing conditions. In this treatment, neuronal packets give rise to perception of "objects"; i.e., quasi-stable (stimulus bound) feature groupings that are conserved over multiple presentations (e.g., the experience of perceiving "apple" can be interrupted and resumed many times). Monitoring the variations in such groups enables the apprehension of behavior; i.e., attributing to objects the ability to undergo changes without loss of self-identity. Ultimately, "understanding" involves self-directed composition and manipulation of the ensuing "mental models" that are constituted by neuronal packets, whose dynamics capture relationships among objects: that is, dependencies in the behavior of objects under varying conditions. For example, movement is known to involve rotation of population vectors in the motor cortex (Georgopoulos et al., 1988, 1993). The neuronal packet hypothesis associates "understanding" with the ability to detect and generate coordinated rotation of population vectors-in neuronal packets-in associative cortex and other regions in the brain. The ability to coordinate vector representations in this way is assumed to have developed in conjunction with the ability to postpone overt motor expression of implicit movement, thus creating a mechanism for prediction and behavioral optimization via mental modeling that is unique to higher species. This article advances the notion that Markov blankets-necessary for the emergence of life-have been subsequently exploited by evolution and thus ground the ways that living organisms adapt to their environment, culminating in their ability to understand it.