Multiple Brains Research Articles

Attachment Reminders Trigger Widespread Synchrony across Multiple Brains.

Infant stimuli elicit widespread neural and behavioral response in human adults, and such massive allocation of resources attests to the evolutionary significance of the primary attachment. Here, we examined whether attachment reminders also trigger cross-brain concordance and generate greater neural uniformity, as indicated by intersubject correlation. Human mothers were imaged twice in oxytocin/placebo administration design, and stimuli included four ecological videos of a standard unfamiliar mother and infant: two infant/mother alone (Alone) and two mother-infant dyadic contexts (Social). Theory-driven analysis measured cross-brain synchrony in preregistered nodes of the parental caregiving network (PCN), which integrates subcortical structures underpinning mammalian mothering with cortical areas implicated in simulation, mentalization, and emotion regulation, and data-driven analysis assessed brain-wide concordance using whole-brain parcellation. Results demonstrated widespread cross-brain synchrony in both the PCN and across the neuroaxis, from primary sensory/somatosensory areas, through insular-cingulate regions, to temporal and prefrontal cortices. The Social context yielded significantly more cross-brain concordance, with PCNs striatum, parahippocampal gyrus, superior temporal sulcus, ACC, and PFC displaying cross-brain synchrony only to mother-infant social cues. Moment-by-moment fluctuations in mother-infant social synchrony, ranging from episodes of low synchrony to tightly coordinated positive bouts, were tracked online by cross-brain concordance in the preregistered ACC. Findings indicate that social attachment stimuli, representing evolutionary-salient universal cues that require no verbal narrative, trigger substantial interbrain concordance and suggest that the mother-infant bond, an icon standing at the heart of human civilization, may function to glue brains into a unified experience and bind humans into social groups.SIGNIFICANCE STATEMENT Infant stimuli elicit widespread neural response in human adults, attesting to their evolutionary significance, but do they also trigger cross-brain concordance and induce neural uniformity among perceivers? We measured cross-brain synchrony to ecological mother-infant videos. We used theory-driven analysis, measuring cross-brain concordance in the parenting network, and data-driven analysis, assessing brain-wide concordance using whole-brain parcellation. Attachment cues triggered widespread cross-brain concordance in both the parenting network and across the neuroaxis. Moment-by-moment fluctuations in behavioral synchrony were tracked online by cross-brain variability in ACC. Attachment reminders bind humans' brains into a unitary experience and stimuli characterized by social synchrony enhance neural similarity among participants, describing one mechanism by which attachment bonds provide the neural template for the consolidation of social groups.

Measuring variability of local brain volume using improved volume preserved warping.

Measuring local brain volume is clinically important in neuroimaging studies. Voxel preserved warping (VPW) and Jacobian determinant are effective methods for studying local brain volume changes and variations (LBVCV) across multiple brains. However, these LBVCV methods typically depend on the local deformation without using the global deformation, while both deformations are needed in co-registering the brains under examination so that the brains can be compared on a common and fair basis. However, instead of employing a uniformed strategy, different co-registration methods have developed their own unique strategy in performing global and local transformation of the co-registration of the brains, and how the global and local transformations may combine to achieve the final goal of co-registration is not their concern, as long as the final registration may accomplish the co-registering job satisfactorily. The aforementioned inconsistency thus makes the LBVCV measurement that relies on the registration methods for studying local brain volumes totally unstable and actually unreliable. To address the uncertainty in measuring local brain volume variability caused by the un-uniqueness of performing global and local deformations during co-registration, the present study proposes new VPW approaches (VPWα and VPWβ), which no longer require the separation of the global and local transformation components but employ only the general deformation concatenating both components, as long as the general registration may achieve the task of co-registering brain images. The new VPW methods are validated in theory and in practice, using both simulated and real-world imaging data, respectively, based on two registration methods popularly in use by the neuroimaging research community, i.e., the Automatic Registration Toolbox (ART) and Symmetric Image Normalization Method (SyN) registration methods. Experiments using simulated data demonstrated that the proposed new VPW methods may reliably measure local brain volume changes and variability. In contrast, traditional methods typically may result in LBVCV maps containing significantly inconsistent even false findings. In the experiments using real neuroimaging datasets from a schizophrenia study, the results based on the proposed new VPW methods were highly consistent, no matter which registration method was employed. Otherwise, the LBVCV results based on traditional approaches would show significant difference, depending on the individual registration method that the analysis employed. LBVCV assessments based on traditional methods appear to be unreliable. The proposed new VPW methods for measuring local volume changes is independent of registration methods, and therefore can serve as alternative approaches for assessing LBVCV reliably.

Hyperscanning Alone Cannot Prove Causality. Multibrain Stimulation Can.

Brains that work together, couple together through interbrain synchrony. Does interbrain synchrony causally facilitate social interaction? This question cannot be answered by simply recording from multiple brains (hyperscanning). It instead requires causal protocols entailing their simultaneous stimulation (multibrain stimulation). We highlight promising findings and future horizons of this nascent field.

The integration of social and neural synchrony: a case for ecologically valid research using MEG neuroimaging.

The recent decade has seen a shift from artificial and environmentally deprived experiments in neuroscience to real-life studies on multiple brains in interaction, coordination and synchrony. In these new interpersonal synchrony experiments, there has been a growing trend to employ naturalistic social interactions to evaluate mechanisms underlying synchronous neuronal communication. Here, we emphasize the importance of integrating the assessment of neural synchrony with measurement of nonverbal behavioral synchrony as expressed in various social contexts: relaxed social interactions, planning a joint pleasurable activity, conflict discussion, invocation of trauma, or support giving and assess the integration of neural and behavioral synchrony across developmental stages and psychopathological conditions. We also showcase the advantages of magnetoencephalography neuroimaging as a promising tool for studying interactive neural synchrony and consider the challenge of ecological validity at the expense of experimental rigor. We review recent evidence of rhythmic information flow between brains in interaction and conclude with addressing state-of-the-art developments that may contribute to advance research on brain-to-brain coordination to the next level.

Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).

Magnetic resonance imaging (MRI) is a key technology in multimodal animal studies of brain connectivity and disease pathology. In vivo MRI provides non-invasive, whole brain macroscopic images containing structural and functional information, thereby complementing invasive in vivo high-resolution microscopy and ex vivo molecular techniques. Brain mapping, the correlation of corresponding regions between multiple brains in a standard brain atlas system, is widely used in human MRI. For small animal MRI, however, there is no scientific consensus on pre-processing strategies and atlas-based neuroinformatics. Thus, it remains difficult to compare and validate results from different pre-clinical studies which were processed using custom-made code or individual adjustments of clinical MRI software and without a standard brain reference atlas. Here, we describe AIDAmri, a novel Atlas-based Imaging Data Analysis pipeline to process structural and functional mouse brain data including anatomical MRI, fiber tracking using diffusion tensor imaging (DTI) and functional connectivity analysis using resting-state functional MRI (rs-fMRI). The AIDAmri pipeline includes automated pre-processing steps, such as raw data conversion, skull-stripping and bias-field correction as well as image registration with the Allen Mouse Brain Reference Atlas (ARA). Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. Each processing step was optimized for efficient data processing requiring minimal user-input and user programming skills. The raw data is analyzed and results transferred to the ARA coordinate system in order to allow an efficient and highly-accurate region-based analysis. AIDAmri is intended to fill the gap of a missing open-access and cross-platform toolbox for the most relevant mouse brain MRI sequences thereby facilitating data processing in large cohorts and multi-center studies.

Mapping Histological Slice Sequences to the Allen Mouse Brain Atlas Without 3D Reconstruction.

Histological brain slices are widely used in neuroscience to study the anatomical organization of neural circuits. Systematic and accurate comparisons of anatomical data from multiple brains, especially from different studies, can benefit tremendously from registering histological slices onto a common reference atlas. Most existing methods rely on an initial reconstruction of the volume before registering it to a reference atlas. Because these slices are prone to distortions during the sectioning process and often sectioned with non-standard angles, reconstruction is challenging and often inaccurate. Here we describe a framework that maps each slice to its corresponding plane in the Allen Mouse Brain Atlas (2015) to build a plane-wise mapping and then perform 2D nonrigid registration to build a pixel-wise mapping. We use the L2 norm of the histogram of oriented gradients difference of two patches as the similarity metric for both steps and a Markov random field formulation that incorporates tissue coherency to compute the nonrigid registration. To fix significantly distorted regions that are misshaped or much smaller than the control grids, we train a context-aggregation network to segment and warp them to their corresponding regions with thin plate spline. We have shown that our method generates results comparable to an expert neuroscientist and is significantly better than reconstruction-first approaches. Code and sample dataset are available at sites.google.com/view/brain-mapping.

Identification of key target genes and biological pathways in multiple sclerosis brains using microarray data obtained from the Gene Expression Omnibus database

ABSTRACTObjective: The purpose of this study was to investigate critical genes in multiple sclerosis (MS) using microarray data from brain tissue in MS.Materials: The expression profile data set of MS (GSE38010) downloaded from the Gene Expression Omnibus database contained gene information from five plaque tissues from MS brains and two white matter tissues from healthy controls. An R package was applied to process these raw chip data. Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and protein–protein interaction (PPI) network analysis were performed to investigate interactions between differentially expressed genes (DEGs) in MS brain tissues.Results: This study identified a total of 1065 DEGs, including 530 up-regulated genes and 535 down-regulated genes, in MS brain tissue samples compared to those in normal white matter tissue samples. GO and KEGG pathway enrichment analyses showed that the up-regulated DEGs were mainly related to neuron development, neuron projection morphogenesis and neuron differentiation. Furthermore, the down-regulated DEGs were largely related to axon ensheathment, ensheathment of neurons and nervous system development. Seven key genes were found as hub genes in the maintenance of the PPI network.Conclusion: Several key target genes and their GO and KEGG pathway enrichment identified in the present study may serve as feasible targets for MS therapies.

Personal memory: Is it personal, is it memory?

Recollection of personal events is a major activity of the human mind and is considered essential for maintaining the cohesiveness of the self-concept. Yet evidence from cognitive psychology and brain research converge to raise doubts concerning the veridicality of the events recalled. Furthermore, even information encoded and recalled correctly seems to be prone to significant and long-lasting distortion by exposure to new input at the time of retrieval. A major source of such new input is inter-personal. From early infancy, we tend to look to others as a primary source of information and may reevaluate our own perceptions, preferences, and memories when they contradict a larger consensus. Circuits in our brain can modify our memory in response to such information even under conditions in which our original memory is accurate and our confidence is strong. Part of what we believe we know is in fact a product of the amalgamation of the internal representations originating in multiple brains. Personal memory may hence be considered conceptually as a node in a highly distributed multi-dimensional memory space, in which the contribution of the individual is only part of an informational syncytium that transcends the personal. This may provide our species with a phylogenetic advantage ensuring that, on one hand, accumulated information can be fitted to the real-time requirements of the locale, but on the other hand, that the storage capacity and availability of information markedly exceeds the capacity and the life span of the individual brain. In consequence, however, individuals may be unreliable narrators of their own history.

Wearable near-infrared spectroscopy neuroimaging and its applications.

Wearable near-infrared spectroscopy (NIRS) systems are expected to be applied in various fields such as health care (medical use), education (teaching), and biofeedback. An investigation on hyperscanning by using NIRS is discussed first, where multiple brains were simultaneously measured for investigating and evaluating important social interactions, such as communication. The relationship between interacting brain activities and performance in cooperation has been demonstrated. An investigation on mood-state measurements in a return-to-work program is next discussed. It has been reported that a specified index calculated using NIRS signals obtained during performance of a working memory task correlated with a mood score. Using this index, the mood states of volunteers who participated in a return-to-work program after psychiatric clinical treatment were monitored. It has been suggested that the relationship between brain activities and subjective assessment of depression mood will be useful for evaluating the recovery stage for return-to-work programs. These techniques open new applications of wearable NIRS systems in mental health care.

The spatial intersection of minds

Spatial formats of information are ubiquitous in the cognitive and neural sciences. There are neural uses of space in the topographic maps found throughout cortex. There are metaphorical uses of space in cognitive linguistics, physical uses of space in ecological psychology, and mathematical uses of space in dynamical systems theory. These varied informational uses of space each provide a single contiguous medium through which cognitive processes can be shared across subsystems. As we further develop our understanding of how the human mind processes information in real time, the continuous sharing and cascading of information patterns between brain areas can be extended to a sharing and cascading of information between multiple brains and bodies to produce coordinated behavior. Essentially, the way you and the people around you negotiate your shared space affects the way you think, because space is a fundamental part of how you think. It is via space that the mental processes of one mind can form an intersection with the mental processes of another mind.

A mutual information approach to automate identification of neuronal clusters in Drosophila brain images.

Mapping neural circuits can be accomplished by labeling a small number of neural structures per brain, and then combining these structures across multiple brains. This sparse labeling method has been particularly effective in Drosophila melanogaster, where clonally related clusters of neurons derived from the same neural stem cell (neuroblast clones) are functionally related and morphologically highly stereotyped across animals. However identifying these neuroblast clones (approximately 180 per central brain hemisphere) manually remains challenging and time consuming. Here, we take advantage of the stereotyped nature of neural circuits in Drosophila to identify clones automatically, requiring manual annotation of only an initial, smaller set of images. Our procedure depends on registration of all images to a common template in conjunction with an image processing pipeline that accentuates and segments neural projections and cell bodies. We then measure how much information the presence of a cell body or projection at a particular location provides about the presence of each clone. This allows us to select a highly informative set of neuronal features as a template that can be used to detect the presence of clones in novel images. The approach is not limited to a specific labeling strategy and can be used to identify partial (e.g., individual neurons) as well as complete matches. Furthermore this approach could be generalized to studies of neural circuits in other organisms.

Neural decoding of collective wisdom with multi-brain computing

Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally, our methods highlight the potential of multi-brain computing as a technique to rapidly and in parallel gather increased information about the environment as well as to access collective perceptual/cognitive choices and mental states.

Extracting Brain Connectivity from Diffusion MRI [Life Sciences

This article gives a short introduction to dMRI tractography methods. Diffusion magnetic resonance imaging (dMRI) is an MRI modality that has gained tremendous popularity the past five years and is especially promising for imaging the white matter in brain. The dMRI technique has raised hopes in the neuroscience community for a better understanding of the fiber tract anatomy of the human brain. Various methods have been proposed to visualize the anatomy of fiber pathways and to derive connectivity between different parts of the brain in vivo. While there are strong indications that dMRI reveals information about the fiber pathways in the brain, it is important to stress that the explicit measurements are of water diffusion, and not of the axons themselves. This technique allows us to use fibers from multiple brains as input, and thereby obtain a simultaneous clustering and matching of the bundles in all brains.

Mapping techniques for aligning sulci across multiple brains

Visualization and mapping of function on the cortical surface is difficult because of its sulcal and gyral convolutions. Methods to unfold and flatten the cortical surface for visualization and measurement have been described in the literature. This makes visualization and measurement possible, but comparison across multiple subjects is still difficult because of the lack of a standard mapping technique. In this paper, we describe two methods that map each hemisphere of the cortex to a portion of a sphere in a standard way. To quantify how accurately the geometric features of the cortex – i.e., sulci and gyri – are mapped into the same location, sulcal alignment across multiple brains is analyzed, and probabilistic maps for different sulcal regions are generated to be used in automatic labelling of segmented sulcal regions.

Bayesian Construction of Geometrically Based Cortical Thickness Metrics

This paper describes the construction of cortical metrics quantifying the probabilistic occurrence of gray matter, white matter, and cerebrospinal fluid compartments in their correlation to the geometry of the neocortex as measured in 0.5–1.0 mm magnetic resonance imagery. These cortical profiles represent the density of the tissue types as a function of distance to the cortical surface. These metrics are consistent when generated across multiple brains indicating a fundamental property of the neocortex. Methods are proposed for incorporating such metrics into automated Bayes segmentation.

HSP70-myelin basic protein complexes in multiple sclerosis brains

HSP70-myelin basic protein complexes in multiple sclerosis brains

Phospholipid vesicle aggregation induced by human myelin basic protein.

Human myelin basic protein isolated from the brains of individuals who died with multiple sclerosis was more potent in inducing the aggregation of egg phosphatidylcholine vesicles than was the basic protein isolated from the brains of normal individuals. The portion of myelin basic protein which bound to egg phosphatidylcholine vesicles was separated from the free protein by sucrose density gradient centrifugation. Similar amounts of basic protein from normal or from multiple sclerosis brains are bound to the lipid and no consistent differences in the NG, N'G dimethyl-arginine content of the protein fractions have been found.