Technological advances in electrospinning of nanofibers

Progress in the electrospinning techniques has brought new methods for the production and construction of various nanofibrous assemblies. The parameters affecting electrospinning include electrical charges on the emerging jet, charge density and removal, as well as effects of external perturbations. The solvent and the method of fiber collection also affect the construction of the final nanofibrous architecture. Various techniques of yarn spinning using solid and liquid surfaces as well as surface-free collection are described and compared in this review. Recent advances allow production of 3D nanofibrous scaffolds with a desired microstructure. In the area of tissue regeneration and bioengineering, 3D scaffolds should bring nanofibrous technology closer to clinical applications. There is sufficient understanding of the electrospinning process and experimental results to suggest that precision electrospinning is a real possibility.

Hierarchical self-assembly of gold nanoparticles into patterned plasmonic nanostructures

The integration of nanoparticle superstructures into daily life applications faces major challenges including the simplification of the self-assembly process, reduced cost, and scalability. It is, however, often difficult to improve on one aspect without losing on another. We present in this paper a benchtop method that allows patterning a macroscopic substrate with gold nanoparticle supercrystals in a one-step process. The method allows parallelization, and patterned substrates can be made with high-throughput. The self-assembly of a variety of building blocks into crystalline superstructures takes place upon solvent evaporation, and their precise placement over millimeter scale areas is induced by confinement of the colloidal suspension in micron-sized cavities. We mainly focus on gold nanorods and demonstrate their hierarchical organization up to the device scale. The height of the formed nanorod supercrystals can be tuned by simply varying nanorod concentration, so that the topography of the substrate and the resulting optical properties can be readily modulated. The crystalline order of the nanorods results in homogeneous and high electric field enhancements over the assemblies, which is demonstrated by surface-enhanced Raman scattering spectroscopy.

Nested Neuronal Dynamics Orchestrate a Behavioral Hierarchy across Timescales

Classical and modern ethological studies suggest that animal behavior is organized hierarchically across timescales, such that longer-timescale behaviors are composed of specific shorter-timescale actions. Despite progress relating neuronal dynamics to single-timescale behavior, it remains unclear how different timescale dynamics interact to give rise to such higher-order behavioral organization. Here, we show, in the nematode Caenorhabditis elegans, that a behavioral hierarchy spanning three timescales is implemented by nested neuronal dynamics. At the uppermost hierarchical level, slow neuronal population dynamics spanning brain and motor periphery control two faster motor neuron oscillations, toggling them between different activity states and functional roles. At lower hierarchical levels, these faster oscillations are further nested in a manner that enables flexible behavioral control in an otherwise rigid hierarchical framework. Our findings establish nested neuronal activity patterns as a repeated dynamical motif of the C. elegans nervous system, which together implement a controllable hierarchical organization of behavior.

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Slow dynamics across brain and motor circuits drive upper-hierarchy motor states

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Fast dynamics in motor circuits drive lower-hierarchy movements within these states

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Slower dynamics tightly constrain the state and function of faster ones

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This rigid hierarchy nevertheless enables flexible behavioral control

Porphyrin Supramolecular 1D Structures via Surfactant-Assisted Self-Assembly

One-dimensional (1D) solid-state supramolecular structures based on porphyrin chromophores arouse numerous expectations from the interdisciplinary scientific communities of supramolecular chemistry and advanced soft materials science. This stems from the intrinsic assembly capability of porphyrins to form various well-defined 1D assemblies, which have broad opportunities in the fields of advanced soft matter. A brief review on 1D porphyrin micro-/nanoassemblies constructed via surfactant-assisted self-assembly is presented here, in terms of addressing new ideas recently developed for controlled assembly, hierarchical organization, and new-type functional surfactants etc. The functionalization of the as-assembled 1D structures with regard to supramolecular photocatalysis, non-linear optics, nanoelectronic gas sensors, photoelectrochemical solar cells, etc. is highlighted.

Mimicking the Hierarchical Organization of Natural Collagen: Toward the Development of Ideal Scaffolding Material for Tissue Regeneration

Biological materials found in living organisms, many of which are proteins, feature a complex hierarchical organization. Type I collagen, a fibrous structural protein ubiquitous in the mammalian body, provides a striking example of such a hierarchical material, with peculiar architectural features ranging from the amino acid sequence at the nanoscale (primary structure) up to the assembly of fibrils (quaternary structure) and fibers, with lengths of the order of microns. Collagen plays a dominant role in maintaining the biological and structural integrity of various tissues and organs, such as bone, skin, tendons, blood vessels, and cartilage. Thus, "artificial" collagen-based fibrous assemblies, endowed with appropriate structural properties, represent ideal substrates for the development of devices for tissue engineering applications. In recent years, with the ultimate goal of developing three-dimensional scaffolds with optimal bioactivity able to promote both regeneration and functional recovery of a damaged tissue, numerous studies focused on the capability to finely modulate the scaffold architecture at the microscale and the nanoscale in order to closely mimic the hierarchical features of the extracellular matrix and, in particular, the natural patterning of collagen. All of these studies clearly show that the accurate characterization of the collagen structure at the submolecular and supramolecular levels is pivotal to the understanding of the relationships between the nanostructural/microstructural properties of the fabricated scaffold and its macroscopic performance. Several studies also demonstrate that the selected processing, including any crosslinking and/or sterilization treatments, can strongly affect the architecture of collagen at various length scales. The aim of this review is to highlight the most recent findings on the development of collagen-based scaffolds with optimized properties for tissue engineering. The optimization of the scaffolds is particularly related to the modulation of the collagen architecture, which, in turn, impacts on the achieved bioactivity.

The modeling of internalizing disorders on the basis of patterns of lifetime comorbidity: associations with psychosocial functioning and psychiatric disorders among first-degree relatives

Two broadband latent factors--internalizing and externalizing--have frequently been identified in studies of the hierarchical structure of psychopathology. In the present research, 3 competing measurement models of putative internalizing disorders (i.e., a parsimonious single-factor model, a model based on the Diagnostic and Statistical Manual of Mental Disorders [4th ed., American Psychiatric Association, 1994], and an alternative model proposed by Krueger, 1999, and Watson, 2005) were evaluated in terms of their ability to account for lifetime patterns of diagnostic comorbidity. Four diagnostic assessments were performed on an age-based cohort of 816 persons over a 15-year interval. Each of the 3 measurement models demonstrated adequate or good fit to the data and similar approximating abilities. Additional analyses, however, suggested that nonspecific aspects of lifetime mood/anxiety or distress/fear disorders (i.e., general negative affect) largely accounted for indicators of psychosocial functioning at age 30 as well as densities of specific psychiatric disorders among the 1st-degree relatives of probands. The relevance of these findings for theoretical and descriptive models of internalizing disorders is discussed.

Peptide-directed spatial organization of biomolecules in dynamic gradient scaffolds

Specific binding peptides are used to spatially organize biomolecule gradients within an electrospun fiber scaffold. Different biomolecule-binding peptide-polymer conjugates are sequentially co-electrospun with a fiber-forming host polymer to generate opposing gradients of peptide functionalization. The binding peptides specifically and non-covalently guide the spatial arrangement of biomolecules into dynamic gradients within the scaffold, mimicking biological gradients found in native tissues.

Multiscale temporal integration organizes hierarchical computation in human auditory cortex

To derive meaning from sound, the brain must integrate information across many timescales. What computations underlie multiscale integration in human auditory cortex? Evidence suggests that auditory cortex analyses sound using both generic acoustic representations (for example, spectrotemporal modulation tuning) and category-specific computations, but the timescales over which these putatively distinct computations integrate remain unclear. To answer this question, we developed a general method to estimate sensory integration windows-the time window when stimuli alter the neural response-and applied our method to intracranial recordings from neurosurgical patients. We show that human auditory cortex integrates hierarchically across diverse timescales spanning from ~50 to 400 ms. Moreover, we find that neural populations with short and long integration windows exhibit distinct functional properties: short-integration electrodes (less than ~200 ms) show prominent spectrotemporal modulation selectivity, while long-integration electrodes (greater than ~200 ms) show prominent category selectivity. These findings reveal how multiscale integration organizes auditory computation in the human brain.

Cortical patterning of morphometric similarity gradient reveals diverged hierarchical organization in sensory-motor cortices

The topological organization of the cerebral cortex provides hierarchical axes, namely gradients, which reveal systematic variations of brain structure and function. However, the hierarchical organization of macroscopic brain morphology and how it constrains cortical function along the organizing axes remains unclear. We map the gradient of cortical morphometric similarity (MS) connectome, combining multiple features conceptualized as a "fingerprint" of an individual's brain. The principal MS gradient is anchored by motor and sensory cortices at two extreme ends, which are reliable and reproducible. Notably, divergences between motor and sensory hierarchies are consistent with the laminar histological thickness gradient but contrary to the canonical functional connectivity (FC) gradient. Moreover, the MS dissociates with FC gradients in the higher-order association cortices. The MS gradient recapitulates fundamental properties of cortical organization, from gene expression and cyto- and myeloarchitecture to evolutionary expansion. Collectively, our findings provide a heuristic hierarchical organization of cortical morphological neuromarkers.

Technological advances in electrospinning of nanofibers

Progress in the electrospinning techniques has brought new methods for the production and construction of various nanofibrous assemblies. The parameters affecting electrospinning include electrical charges on the emerging jet, charge density and removal, as well as effects of external perturbations. The solvent and the method of fiber collection also affect the construction of the final nanofibrous architecture. Various techniques of yarn spinning using solid and liquid surfaces as well as surface-free collection are described and compared in this review. Recent advances allow production of 3D nanofibrous scaffolds with a desired microstructure. In the area of tissue regeneration and bioengineering, 3D scaffolds should bring nanofibrous technology closer to clinical applications. There is sufficient understanding of the electrospinning process and experimental results to suggest that precision electrospinning is a real possibility.

Spatial relations and spatial locations are dissociated within prefrontal and parietal cortex

Item-specific spatial information is essential for interacting with objects and for binding multiple features of an object together. Spatial relational information is necessary for implicit tasks such as recognizing objects or scenes from different views but also for explicit reasoning about space such as planning a route with a map and for other distinctively human traits such as tool construction. To better understand how the brain supports these two different kinds of information, we used functional MRI to directly contrast the neural encoding and maintenance of spatial relations with that for item locations in equivalent visual scenes. We found a double dissociation between the two: whereas item-specific processing implicates a frontoparietal attention network, including the superior frontal sulcus and intraparietal sulcus, relational processing preferentially recruits a cognitive control network, particularly lateral prefrontal cortex (PFC) and inferior parietal lobule. Moreover, pattern classification revealed that the actual meaning of the relation can be decoded within these same regions, most clearly in rostrolateral PFC, supporting a hierarchical, representational account of prefrontal organization.

Emergence, hierarchy and top-down causation in evolutionary biology

The concept of emergence and the related notion of 'downward causation' have arisen in numerous branches of science, and have also been extensively discussed in philosophy. Here, I examine emergence and downward causation in relation to evolutionary biology. I focus on the old, but ongoing discussion in evolutionary biology over the 'levels of selection' question: which level(s) of the biological hierarchy natural selection acts at, e.g. the gene, individual, group or species level? The concept of emergence has arisen in the levels-of-selection literature as a putative way of distinguishing between 'true' selection at a higher level from cases where selection acts solely at the lower level but has effects that percolate up the biological hierarchy, generating the appearance of higher level selection. At first blush, this problem seems to share a common structure with debates about emergence in other areas, but closer examination shows that it turns on issues that are sui generis to biology.

Organizing principles of astrocytic nanoarchitecture in the mouse cerebral cortex

Astrocytes are increasingly understood to be important regulators of central nervous system (CNS) function in health and disease; yet, we have little quantitative understanding of their complex architecture. While broad categories of astrocytic structures are known, the discrete building blocks that compose them, along with their geometry and organizing principles, are poorly understood. Quantitative investigation of astrocytic complexity is impeded by the absence of high-resolution datasets and robust computational approaches to analyze these intricate cells. To address this, we produced four ultra-high-resolution datasets of mouse cerebral cortex using serial electron microscopy and developed astrocyte-tailored computer vision methods for accurate structural analysis. We unearthed specific anatomical building blocks, structural motifs, connectivity hubs, and hierarchical organizations of astrocytes. Furthermore, we found that astrocytes interact with discrete clusters of synapses and that astrocytic mitochondria are distributed to lie closer to larger clusters of synapses. Our findings provide a geometrically principled, quantitative understanding of astrocytic nanoarchitecture and point to an unexpected level of complexity in how astrocytes interact with CNS microanatomy.

Causal Interactions between Frontal(θ) - Parieto-Occipital(α2) Predict Performance on a Mental Arithmetic Task

Many neuroimaging studies have demonstrated the different functional contributions of spatially distinct brain areas to working memory (WM) subsystems in cognitive tasks that demand both local information processing and interregional coordination. In WM cognitive task paradigms employing electroencephalography (EEG), brain rhythms such as θ and α have been linked to specific functional roles over given brain areas, but their functional coupling has not been extensively studied. Here we analyzed an arithmetic task with five cognitive workload levels (CWLs) and demonstrated functional/effective coupling between the two WM subsystems: the central executive located over frontal (F) brain areas that oscillates on the dominant θ rhythm (Frontal^θ/F^θ) and the storage buffer located over parieto-occipital (PO) brain areas that operates on the α₂ dominant brain rhythm (Parieto-Occipital^α2/PO^α2). We focused on important differences between and within WM subsystems in relation to behavioral performance. A repertoire of brain connectivity estimators was employed to elucidate the distinct roles of amplitude, phase within and between frequencies, and the hierarchical role of functionally specialized brain areas related to the task. Specifically, for each CWL, we conducted a) a conventional signal power analysis within both frequency bands at F^θ and PO^α2, b) the intra- and inter-frequency phase interactions between F^θ and PO^α2, and c) their causal phase and amplitude relationship. We found no significant statistical difference of signal power or phase interactions between correct and wrong answers. Interestingly, the study of causal interactions between F^θ and PO^α2 revealed frontal brain region(s) as the leader, while the strength differentiated between correct and wrong responses in every CWL with absolute accuracy. Additionally, zero time-lag between bilateral F^θ and right PO^a2 could serve as an indicator of mental calculation failure. Overall, our study highlights the significant role of coordinated activity between F^θ and PO^α2 via their causal interactions and the timing for arithmetic performance.

Inverted central auditory hierarchies for encoding local intervals and global temporal patterns

In sensory systems, representational features of increasing complexity emerge at successive stages of processing. In the mammalian auditory pathway, the clearest change from brainstem to cortex is defined by what is lost, not by what is gained, in that high-fidelity temporal coding becomes increasingly restricted to slower acoustic modulation rates.^1,2 Here, we explore the idea that sluggish temporal processing is more than just an inability for fast processing, but instead reflects an emergent specialization for encoding sound features that unfold on very slow timescales.^3,4 We performed simultaneous single unit ensemble recordings from three hierarchical stages of auditory processing in awake mice - the inferior colliculus (IC), medial geniculate body of the thalamus (MGB) and primary auditory cortex (A1). As expected, temporal coding of brief local intervals (0.001 - 0.1 s) separating consecutive noise bursts was robust in the IC and declined across MGB and A1. By contrast, slowly developing (∼1 s period) global rhythmic patterns of inter-burst interval sequences strongly modulated A1 spiking, were weakly captured by MGB neurons, and not at all by IC neurons. Shifts in stimulus regularity were not represented by changes in A1 spike rates, but rather in how the spikes were arranged in time. These findings show that low-level auditory neurons with fast timescales encode isolated sound features but not the longer gestalt, while the extended timescales in higher-level areas can facilitate sensitivity to slower contextual changes in the sensory environment.

The Kidney Clock Contributes to Timekeeping by the Master Circadian Clock

The kidney harbors one of the strongest circadian clocks in the body. Kidney failure has long been known to cause circadian sleep disturbances. Using an adenine-induced model of chronic kidney disease (CKD) in mice, we probe the possibility that such sleep disturbances originate from aberrant circadian rhythms in kidney. Under the CKD condition, mice developed unstable behavioral circadian rhythms. When observed in isolation in vitro, the pacing of the master clock, the suprachiasmatic nucleus (SCN), remained uncompromised, while the kidney clock became a less robust circadian oscillator with a longer period. We find this analogous to the silencing of a strong slave clock in the brain, the choroid plexus, which alters the pacing of the SCN. We propose that the kidney also contributes to overall circadian timekeeping at the whole-body level, through bottom-up feedback in the hierarchical structure of the mammalian circadian clocks.

Functional connectivity gradients of the insula to different cerebral systems

The diverse functional roles of the insula may emerge from its heavy connectivity to an extensive network of cortical and subcortical areas. Despite several previous attempts to investigate the hierarchical organization of the insula by applying the recently developed gradient approach to insula-to-whole brain connectivity data, little is known about whether and how there is variability across connectivity gradients of the insula to different cerebral systems. Resting-state functional MRI data from 793 healthy subjects were used to discover and validate functional connectivity gradients of the insula, which were computed based on its voxel-wise functional connectivity profiles to distinct cerebral systems. We identified three primary patterns of functional connectivity gradients of the insula to distinct cerebral systems. The connectivity gradients to the higher-order transmodal associative systems, including the prefrontal, posterior parietal, temporal cortices, and limbic lobule, showed a ventroanterior-dorsal axis across the insula; those to the lower-order unimodal primary systems, including the motor, somatosensory, and occipital cortices, displayed radiating transitions from dorsoanterior toward both ventroanterior and dorsoposterior parts of the insula; the connectivity gradient to the subcortical nuclei exhibited an organization along the anterior-posterior axis of the insula. Apart from complementing and extending previous literature on the heterogeneous connectivity patterns of insula subregions, the presented framework may offer ample opportunities to refine our understanding of the role of the insula in many brain disorders.

Hierarchical organization of axis I psychiatric disorder comorbidity through age 30

Hierarchical models of psychopathology based on substantial numbers of lifetime diagnostic categories have not been sufficiently evaluated, even though such models have relevance for theories of disorder etiology, course, or prognosis. In this research, a hierarchical component model of 16 Axis I disorders is derived, and model elements are evaluated in terms of their ability to demonstrate distinct associations with several clinically-relevant variables. Participants were 816 randomly selected adolescents from the community who were repeatedly assessed for psychiatric disorders and associated risk and protective factors over a 14-year period. First-degree relatives were also interviewed to establish their lifetime psychiatric history. Patterns of lifetime comorbidity among 16 psychiatric disorders were described at five levels of organization. In addition to the broadest level that accounted for the most variance in disorder covariation, evidence was obtained at successive levels in the hierarchy for internalizing and externalizing broad-band domains that could be subdivided into more refined clusters. The validity and potential utility of the resultant hierarchical model were further supported by distinct associations that components at each level had with exposure to childhood adversities, psychiatric disorders among first-degree relatives, and psychosocial functioning at ~age 30. A large number of DSM Axis I disorders can be described within broad-band internalizing and externalizing domains, and further differentiation within these domains is possible and likely useful for some purposes. Implications of this research for conceptualizing relations among psychiatric disorders are discussed.

Biasing the Hierarchy Motifs of Nanotoroids: from 1D Nanotubes to 2D Porous Networks

Hierarchical organization of self-assembled structures into superstructures is omnipresent in Nature but has been rarely achieved in synthetic molecular assembly due to the absence of clear structural rules. We herein report on the self-assembly of scissor-shaped azobenzene dyads which form discrete nanotoroids that further organize into 2D porous networks. The steric demand of the peripheral aliphatic units diminishes the trend of the azobenzene dyad to constitute stackable nanotoroids in solution, thus affording isolated (unstackable) nanotoroids upon cooling. Upon drying, these nanotoroids organize at graphite surface to form well-defined 2D porous networks. The photoirradiation with UV and visible light enabled reversible dissociation and reconstruction of nanotoroids through the efficient trans↔cis isomerization of azobenzene moieties in solution.

Hierarchical Order Parameters for Macromolecular Assembly Simulations I: Construction and Dynamical Properties of Order Parameters

Macromolecular assemblies often display a hierarchical organization of macromolecules or their sub-assemblies. To model this, we have formulated a space warping method that enables capturing overall macromolecular structure and dynamics via a set of coarse-grained order parameters (OPs). This article is the first of two describing the construction and computational implementation of an additional class of OPs that has built into them the hierarchical architecture of macromolecular assemblies. To accomplish this, first, the system is divided into subsystems, each of which is described via a representative set of OPs. Then, a global set of variables is constructed from these subsystem-centered OPs to capture overall system organization. Dynamical properties of the resulting OPs are compared to those of our previous nonhierarchical ones, and implied conceptual and computational advantages are discussed for a 100ns, 2 million atom solvated Human Papillomavirus-like particle simulation. In the second article, the hierarchical OPs are shown to enable a multiscale analysis that starts with the N-atom Liouville equation and yields rigorous Langevin equations of stochastic OP dynamics. The latter is demonstrated via a force-field based simulation algorithm that probes key structural transition pathways, simultaneously accounting for all-atom details and overall structure.

Hierarchical Microstructure Informed Tractography

Background: Tractography uses diffusion magnetic resonance imaging to noninvasively infer the macroscopic pathways of white matter fibers and it is the only available technique to probe in vivo the structural connectivity of the brain. However, despite this unique and compelling ability and its wide range of possible neurological applications, tractography is still limited, lacks anatomical precision, and suffers from a serious sensitivity/specificity trade-off. For this reason, in the past few years, tractography postprocessing techniques have emerged and proved effective for improving the quality of the reconstructions. Among them, the Convex Optimization Modeling for Microstructure Informed Tractography formulation allows incorporating the anatomical prior that fibers are naturally organized in fascicles, and has obtained exceptional results in increasing the accuracy of the estimated tractograms. Methods: We propose an extension to this idea and introduce a multilevel grouping of the streamlines to capture the white matter arrangement in fascicles and subfascicles. We tested our proposed formulation in synthetic and in vivo data. Results: Our experiments show that using multiple levels allows considering information about the white matter organization more adequately and helps to improve further the accuracy of the resulting tractograms. Conclusion: This new formulation represents a further important step toward a more accurate structural connectivity estimation.

Critical Evaluation of Current Hypotheses for the Pathogenesis of Hypertrophic Cardiomyopathy

Hereditary hypertrophic cardiomyopathy (HCM), due to mutations in sarcomere proteins, occurs in more than 1/500 individuals and is the leading cause of sudden cardiac death in young people. The clinical course exhibits appreciable variability. However, typically, heart morphology and function are normal at birth, with pathological remodeling developing over years to decades, leading to a phenotype characterized by asymmetric ventricular hypertrophy, scattered fibrosis and myofibrillar/cellular disarray with ultimate mechanical heart failure and/or severe arrhythmias. The identity of the primary mutation-induced changes in sarcomere function and how they trigger debilitating remodeling are poorly understood. Support for the importance of mutation-induced hypercontractility, e.g., increased calcium sensitivity and/or increased power output, has been strengthened in recent years. However, other ideas that mutation-induced hypocontractility or non-uniformities with contractile instabilities, instead, constitute primary triggers cannot yet be discarded. Here, we review evidence for and criticism against the mentioned hypotheses. In this process, we find support for previous ideas that inefficient energy usage and a blunted Frank-Starling mechanism have central roles in pathogenesis, although presumably representing effects secondary to the primary mutation-induced changes. While first trying to reconcile apparently diverging evidence for the different hypotheses in one unified model, we also identify key remaining questions and suggest how experimental systems that are built around isolated primarily expressed proteins could be useful.

Hierarchical Organization Within the Ventral Premotor Cortex of the Macaque Monkey

Recent studies have revealed that the ventral premotor cortex (PMv) of nonhuman primates plays a pivotal role in various behaviors that require the transformation of sensory cues to appropriate actions. Examples include decision-making based on various sensory cues, preparation for upcoming motor behavior, adaptive sensorimotor transformation, and the generation of motor commands using rapid sensory feedback. Although the PMv has frequently been regarded as a single entity, it can be divided into at least five functionally distinct regions: F4, a dorsal convexity region immediately rostral to the primary motor cortex (M1); F5p, a cortical region immediately rostral to F4, lying within the arcuate sulcus; F5c, a ventral convexity region rostral to F4; and F5a, located in the caudal bank of the arcuate sulcus inferior limb lateral to F5p. Among these, F4 can be further divided into dorsal and ventral subregions (F4d and F4v), which are involved in forelimb and orofacial movements, respectively. F5p contains "mirror neurons" to understand others' actions based on visual and other types of information, and F4d and F5p work together as a functional complex involved in controlling forelimb and eye movements, most efficiently in the execution and completion of coordinated eye-hand movements for reaching and grasping under visual guidance. In contrast, F5c and F5a are hierarchically higher than the F4d, F5p, and F5v complexes, and play a role in decision-making based on various sensory discriminations. Hence, the PMv subregions form a hierarchically organized integral system from decision-making to eye-hand coordination under various behavioral circumstances.

Hierarchical Organization of Functional Brain Networks Revealed by Hybrid Spatiotemporal Deep Learning

Hierarchical organization of brain function has been an established concept in the neuroscience field for a long time, however, it has been rarely demonstrated how such hierarchical macroscale functional networks are actually organized in the human brain. In this study, to answer this question, we propose a novel methodology to provide an evidence of hierarchical organization of functional brain networks. This article introduces the hybrid spatiotemporal deep learning (HSDL), by jointly using deep belief networks (DBNs) and deep least absolute shrinkage and selection operator (LASSO) to reveal the temporal hierarchical features and spatial hierarchical maps of brain networks based on the Human Connectome Project 900 functional magnetic resonance imaging (fMRI) data sets. Briefly, the key idea of HSDL is to extract the weights between two adjacent layers of DBNs, which are then treated as the hierarchical dictionaries for deep LASSO to identify the corresponding hierarchical spatial maps. Our results demonstrate that both spatial and temporal aspects of dozens of functional networks exhibit multiscale properties that can be well characterized and interpreted based on existing computational tools and neuroscience knowledge. Our proposed novel hybrid deep model is used to provide the first insightful opportunity to reveal the potential hierarchical organization of time series and functional brain networks, using task-based fMRI signals of human brain.

Laminar Pattern of Projections Indicates the Hierarchical Organization of the Anterior Cingulate-Temporal Lobe Emotion System

The anterior cingulate cortex (ACC), surrounding the genu of the corpus callosum, plays important roles in emotional processing and is functionally divided into the dorsal, perigenual, and subgenual subregions (dACC, pgACC, and sgACC, respectively). Previous studies have suggested that the pgACC and sgACC have distinctive roles in the regulation of emotion. In order to elicit appropriate emotional responses, these ACC regions require sensory information from the environment. Anatomically, the ACC has rich connections with the temporal lobe, where the higher-order processing of sensory information takes place. To clarify the organization of sensory inputs into the ACC subregions, we injected neuronal tracers into the pgACC, sgACC, and dACC and compared the afferent connections. Previously, we analyzed the afferent projections from the amygdala and found a distinct pattern for the sgACC. In the present study, the patterns of the afferent projections were analyzed in the temporal cortex, especially the temporal pole (TP) and medial temporal areas. After tracers were injected into the sgACC, we observed labeled neurons in the TP and the subiculum of the hippocampal formation. The majority of the labeled cell bodies were found in the superficial layers of the TP ("feedforward" type projections). The pgACC received afferent projections from the TP, the entorhinal cortex (EC), and the parahippocampal cortex (PHC), but not from the hippocampus. In each area, the labeled cells were mainly found in the deep layers ("feedback" type projection). The pattern for the dACC was similar to that for the pgACC. Previous studies suggested that the pgACC, but not the sgACC receive projections from the dorsolateral prefrontal cortex (DLPFC). These data suggest that the sgACC plays crucial roles for emotional responses based on sensory and mnemonic inputs from the anterior temporal lobe, whereas the pgACC is more related to the cognitive control of emotion.