Connectivity Architecture Research Articles

Principles of ipsilateral and contralateral cortico-cortical connectivity in the mouse.

Structural connectivity among cortical areas provides the substrate for information exchange in the cerebral cortex and is characterized by systematic patterns of presence or absence of connections. What principles govern this cortical wiring diagram? Here, we investigate the relation of physical distance and cytoarchitecture with the connectional architecture of the mouse cortex. Moreover, we examine the relation between patterns of ipsilateral and contralateral connections. Our analysis reveals a mirrored and attenuated organization of contralateral connections when compared with ipsilateral connections. Both physical distance and cytoarchitectonic similarity of cortical areas are related to the presence or absence of connections. Notably, our analysis demonstrates that the combination of these factors relates better to cortico-cortical connectivity than each factor in isolation and that the two factors relate differently to ipsilateral and contralateral connectivity. Physical distance is more tightly related to the presence or absence of ipsilateral connections, but its relevance greatly diminishes for contralateral connections, while the contribution of cytoarchitectonic similarity remains relatively stable. Our results, together with similar findings in the cat and macaque cortex, suggest that a common set of principles underlies the macroscale wiring of the mammalian cerebral cortex.

Pre-seizure architecture of the local connections of the epileptic focus examined via graph-theory.

Epilepsy is characterized by unpredictable and sudden paroxysmal neuronal firing occurrences and sometimes evolving in clinically evident seizure. To predict seizure event, small-world characteristic in nine minutes before seizure, divided in three 3-min periods (T0, T1, T2) were investigated. Intracerebral recordings were obtained from 10 patients with drug resistant focal epilepsy examined by means of stereotactically implanted electrodes; analysis was focused in a period of low spiking (Baseline) and during two seizures. Networks' architecture is undirected and weighted. Electrodes' contacts close to epileptic focus are the vertices, edges are weighted by mscohere (=magnitude squared coherence). Differences were observed between Baseline and T1 and between Baseline and T2 in theta band; and between Baseline and T1, Baseline and T2, and near-significant difference between T0 and T2 in Alpha 2 band. Moreover, an intra-band index was computed for small worldness as difference between Theta and Alpha 2. It was found a growing index trend from Baseline to T2. Cortical network features a specific pre-seizure architecture which could predict the incoming epileptic seizure. Through this study future researches could investigate brain connectivity modifications approximating a clinical seizure also in order to address a preventive therapy.

Constituents and functional implications of the rat default mode network

The default mode network (DMN) has been suggested to support a variety of self-referential functions in humans and has been fractionated into subsystems based on distinct responses to cognitive tasks and functional connectivity architecture. Such subsystems are thought to reflect functional hierarchy and segregation within the network. Because preclinical models can inform translational studies of neuropsychiatric disorders, partitioning of the DMN in nonhuman species, which has previously not been reported, may inform both physiology and pathophysiology of the human DMN. In this study, we sought to identify constituents of the rat DMN using resting-state functional MRI (rs-fMRI) and diffusion tensor imaging. After identifying DMN using a group-level independent-component analysis on the rs-fMRI data, modularity analyses fractionated the DMN into an anterior and a posterior subsystem, which were further segregated into five modules. Diffusion tensor imaging tractography demonstrates a close relationship between fiber density and the functional connectivity between DMN regions, and provides anatomical evidence to support the detected DMN subsystems. Finally, distinct modulation was seen within and between these DMN subcomponents using a neurocognitive aging model. Taken together, these results suggest that, like the human DMN, the rat DMN can be partitioned into several subcomponents that may support distinct functions. These data encourage further investigation into the neurobiological mechanisms of DMN processing in preclinical models of both normal and disease states.

The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture.

The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states.

Uranium distribution as a proxy for basin-scale fluid flow in distributive fluvial systems

We infer system-scale fluid flow in the Late Jurassic Salt Wash fluvial succession (SW USA) by plotting uranium deposit distribution against sedimentological data, using uranium distribution as a proxy for subsurface fluid flow. More than 90% of uranium deposits in the Salt Wash occur where sandstone forms 40–55% and sand-rich channel-belts form 20–50% of the succession, which coincides with changes in channel-belt connectivity and gross-scale architecture. The paucity of uranium below these cut-off values suggests that fluid flow is related directly to predictable downstream fining and facies variations in distributive fluvial systems. Supplementary material: A summary table of location data, key trends and the amalgamation ratio method is available at https://doi.org/10.6084/m9.figshare.c.2849581 .

Genetic and Environmental Contributions to Functional Connectivity Architecture of the Human Brain.

One of the grand challenges faced by neuroscience is to delineate the determinants of interindividual variation in the comprehensive structural and functional connection matrices that comprise the human connectome. At present, this endeavor appears most tractable at the macroanatomic scale, where intrinsic brain activity exhibits robust patterns of synchrony that recapitulate core functional circuits at the individual level. Here, we use a classical twin study design to examine the heritability of intrinsic functional network properties in 101 twin pairs, including network activity (i.e., variance of a network's specific temporal fluctuations) and internetwork coherence (i.e., correlation between networks' specific temporal fluctuations). Five of 7 networks exhibited significantly heritable (23.3–65.2%) network activity, 6 of the 21 internetwork coherences were significantly heritable (25.6–42.0%), and 11 of the 21 internetwork coherences were significantly influenced by common environmental factors (18.0–47.1%). These results suggest that the source of interindividual variation in functional connectome has a modular architecture: individual modules represented by intrinsic connectivity networks are genetic controlled, while environmental factors influence the interplays between the modules. This work further provides network-specific hypotheses for discovery of the specific genetic and environmental factors influencing functional specialization and integration of the human brain.

Functional connectivity in cortico-subcortical brain networks underlying reward processing in attention-deficit/hyperactivity disorder.

BackgroundMany patients with attention-deficit/hyperactivity disorder (ADHD) display aberrant reward-related behavior. Task-based fMRI studies have related atypical reward processing in ADHD to altered BOLD activity in regions underlying reward processing such as ventral striatum and orbitofrontal cortex. However, it remains unclear whether the observed effects are region-specific or related to changes in functional connectivity of networks supporting reward processing. Here we use resting-state fMRI to comprehensively delineate the functional connectivity architecture underlying aberrant reward processing in ADHD.MethodsWe assessed resting-state functional connectivity of four networks that support reward processing. These networks showed high spatial overlap with the default mode, fronto-parietal, lateral visual, and salience networks, yet only activity within the salience network was effectively sensitive to reward value. We parcelled these networks into their functional cortical and subcortical subregions and obtained functional connectivity matrices by computing Pearson correlations between the regional time series. We compared functional connectivity within each of the four networks between participants with ADHD and controls, and related functional connectivity to dimensional ADHD symptom scores across all participants (N = 444; age range: 8.5–30.5; mean age: 17.7).ResultsWe did not observe significant ADHD-related alterations in functional connectivity of the salience network, which included key reward regions. Instead, levels of inattention symptoms modulated functional connectivity of the default-mode and fronto-parietal networks, which supported general task processing.ConclusionsThe present study does not corroborate previous childhood evidence for functional connectivity alterations between key reward processing regions in adolescents and young adults with ADHD. Our findings could point to developmental normalization or indicate that reward-processing deficits result from functional connectivity alterations in general task-related networks.

A series connection architecture for large-area organic photovoltaic modules with a 7.5% module efficiency.

The fabrication of organic photovoltaic modules via printing techniques has been the greatest challenge for their commercial manufacture. Current module architecture, which is based on a monolithic geometry consisting of serially interconnecting stripe-patterned subcells with finite widths, requires highly sophisticated patterning processes that significantly increase the complexity of printing production lines and cause serious reductions in module efficiency due to so-called aperture loss in series connection regions. Herein we demonstrate an innovative module structure that can simultaneously reduce both patterning processes and aperture loss. By using a charge recombination feature that occurs at contacts between electron- and hole-transport layers, we devise a series connection method that facilitates module fabrication without patterning the charge transport layers. With the successive deposition of component layers using slot-die and doctor-blade printing techniques, we achieve a high module efficiency reaching 7.5% with area of 4.15 cm2.

Hourly Electricity Price Forecasting for the Next Month Using Multilayer Neural Network

Load and price forecasting are key challenges for current electricity market participants. Load and price in electricity markets have complex peculiarities, such as nonlinearity, being nonstationary and irregular. Accurate short-term forecasting, such as hourly electricity price forecasting (EPF) for the next month gives pivotal information to power producers and consumers to enhance precise techniques to maximize their profit. This paper deals with short-term hourly EPF for the next month (January 2006), using the historical hourly data for the year 2005 as a training set. A new approach of multilayer neural networks is applied in composite topologies in order to improve forecasting accuracy. The intent is to study the behavior of diverse composite topologies to compare the best performance indices evaluated by the mean absolute percentage error and mean square error. The performance of different topologies is compared to identify the best connection architecture. The data used in the forecasting are hourly historical data of the temperature, electricity load, and natural gas price from the Australian electricity markets.

Altered modular organization in schizophrenia patients and analysis using supervised association rule mining

Complex neuro-degenerative disorders affect the intrinsic topological architecture of brain connectivity. There are very few studies concentrating on the occurrence of modular changes in the structural and functional connectome of people diagnosed with Schizophrenia. In this study, group averaged analysis on modular organization of 15 healthy and 12 Schizophrenic subjects were performed to understand the topological alterations occurring in brain networks of diseased against normal. The major contributing regions for changes in optimal brain architecture were also identified. It also involves the investigation of individual subject's functional connectivity and the attempts were made to extract the modular specific roles of brain regions through supervised association rule mining. On comparison with group average measurements, it was found to produce similar results and it was understood that inter and intra-module connections evidently varied in Schizophrenia because of alterations in extremely organized modular architecture. This is believed to provide new insights in understanding the complex neuro-degenerative disorder through analysis on modular organization of functional brain networks. Highly influential regions were also determined. These regions were found to be potential biomarkers for Schizophrenia diagnosis.

A symmetry-based method to infer structural brain networks from probabilistic tractography data.

A symmetry-based method to infer structural brain networks from probabilistic tractography data.

Performance Evaluation for Local Anchor-Based Dual Connectivity in 5G User-Centric Network

Ultra-dense network (UDN) is considered as one of the most promising techniques in achieving the increasingly explosive growth of data rates for future 5G system. However, a large number of small cells lead to the increased cell edges and the rugged inter-cell interference, which cause frequent handover events and more radio link failure. In this paper, a local anchor-based dual connectivity (DC) architecture is proposed for a user-centric network based on the analysis of mobility management challenges of UDN. Under the proposed architecture, the local anchor acts as the master eNodeB (MeNB) with neighboring small cells acting as slave eNodeBs (SeNBs) to provide DC transmission for user-centric service following each user’s movement. Key procedures for mobility management are correspondingly provided and both the MeNBs and SeNBs are selected from the small cells to investigate the potential of them, which are different from the mobility management methods under the traditional cellular architecture. Performance evaluations are conducted under different parameter configurations to evaluate the maximum potential of the proposed scheme. Simulation results show that in our proposed scheme, the handover failure rate shows a maximum decrease of more than 53% and the average user spectrum efficiency achieves an increase of 5% gains over the current LTE system when the user equipment speed is 3 km/h.

Working Memory Models: Insights From Neuroimaging.

FIGURE 1. The Atkinson and Shiffrin Model of memory is diagramed in the gray panel. Sensory information is perceived and suppressed via selective attention processes, then briefly held in the limited-capacity modality-specific sensory register. Information enhanced by selective attention enters into short term memory (STM). The process of rehearsal (maintenance) can sustain information in STM. Information in STM is automatically encoded (stored, consolidated) into long term memory (LTM). Although flawed, this model continues to provide a simple and easy approach to understanding memory. Assumptions that proved to be inconsistent with research included that any information in STM will transfer to LTM and that STM is required

A survey of current trends in diffusion MRI for structural brain connectivity

In this paper, we review the state of the art in diffusion magnetic resonance imaging (dMRI) and we present current trends in modelling the brain's tissue microstructure and the human connectome. dMRI is today the only tool that can probe the brain's axonal architecture in vivo and non-invasively, and has grown in leaps and bounds in the last two decades since its conception. A plethora of models with increasing complexity and better accuracy have been proposed to characterise the integrity of the cerebral tissue, to understand its microstructure and to infer its connectivity. Here, we discuss a wide range of the most popular, important and well-established local microstructure models and biomarkers that have been proposed from these models. Finally, we briefly present the state of the art in tractography techniques that allow us to understand the architecture of the brain's connectivity.

Interferon-α acutely impairs whole-brain functional connectivity network architecture – A preliminary study

Interferon-alpha (IFN-α) is a key mediator of antiviral immune responses used to treat Hepatitis C infection. Though clinically effective, IFN-α rapidly impairs mood, motivation and cognition, effects that can appear indistinguishable from major depression and provide powerful empirical support for the inflammation theory of depression. Though inflammation has been shown to modulate activity within discrete brain regions, how it affects distributed information processing and the architecture of whole brain functional connectivity networks have not previously been investigated.Here we use a graph theoretic analysis of resting state functional magnetic resonance imaging (rfMRI) to investigate acute effects of systemic interferon-alpha (IFN-α) on whole brain functional connectivity architecture and its relationship to IFN-α-induced mood change. Twenty-two patients with Hepatitis-C infection, initiating IFN-α-based therapy were scanned at baseline and 4h after their first IFN-α dose. The whole brain network was parcellated into 110 cortical and sub-cortical nodes based on the Oxford-Harvard Atlas and effects assessed on higher-level graph metrics, including node degree, betweenness centrality, global and local efficiency.IFN-α was associated with a significant reduction in global network connectivity (node degree) (p=0.033) and efficiency (p=0.013), indicating a global reduction of information transfer among the nodes forming the whole brain network. Effects were similar for highly connected (hub) and non-hub nodes, with no effect on betweenness centrality (p>0.1). At a local level, we identified regions with reduced efficiency of information exchange and a sub-network with decreased functional connectivity after IFN-α. Changes in local and particularly global functional connectivity correlated with associated changes in mood measured on the Profile of Mood States (POMS) questionnaire.IFN-α rapidly induced a profound shift in whole brain network structure, impairing global functional connectivity and the efficiency of parallel information exchange. Correlations with multiple indices of mood change support a role for global changes in brain functional connectivity architecture in coordinated behavioral responses to IFN-α.

Decreased functional connectivity density in pain-related brain regions of female migraine patients without aura

Migraine is one of the most prevalent neurological disorders which is suggested to be associated with dysfunctions of the central nervous system. The purpose of the present study was to detect the altered functional connectivity architecture in the large-scale network of the whole brain in migraine without aura (MWoA). Meanwhile, the brain functional hubs which are targeted by MWoA could be identified. A new voxel-based method named functional connectivity density (FCD) mapping was applied to resting-state functional magnetic resonance imaging data of 55 female MWoA patients and 44 age-matched female healthy controls (HC). Comparing to HC, MWoA patients showed abnormal short-range FCD values in bilateral hippocampus, bilateral insula, right amygdale, right anterior cingulate cortex, bilateral putamen, bilateral caudate nucleus and the prefrontal cortex. The results suggested decreased intraregional connectivity of these pain-related brain regions in female MWoA. In addition, short-range FCD values in left prefrontal cortex, putamen and caudate nucleus were significantly negatively correlated with duration of disease in MWoA group, implying the repeated migraine attacks over time may consistently affect the resting-state functional connectivity architecture of these brain hubs. Our findings revealed the dysfunction of brain hubs in female MWoA, and suggested the left prefrontal cortex, putamen and caudate nucleus served as sensitive neuroimaging markers for reflecting the disease duration of female MWoA. This may provide us new insights into the changes in the organization of the large-scale brain network in MWoA.

Default Mode Dynamics for Global Functional Integration.

The default mode network (DMN) has been shown to increase its activity during the absence of external stimulation, and hence was historically assumed to disengage during goal-directed tasks. Recent evidence, however, implicates the DMN in self-referential and memory-based processing. We provide robust evidence for this network's active contribution to working memory by revealing dynamic reconfiguration in its interactions with other networks and offer an explanation within the global workspace theoretical framework. These promising findings may help redefine our understanding of the exact DMN role in human cognition.

Editorial: Bridging the gap before and after birth: methods and technologies to explore the functional neural development in humans.

Editorial: Bridging the gap before and after birth: methods and technologies to explore the functional neural development in humans.

Estimating Directed Connectivity from Cortical Recordings and Reconstructed Sources

In cognitive neuroscience, electrical brain activity is most commonly recorded at the scalp. In order to infer the contributions and connectivity of underlying neuronal sources within the brain, it is necessary to reconstruct sensor data at the source level. Several approaches to this reconstruction have been developed, thereby solving the so-called implicit inverse problem Michel et al. (Clin Neurophysiol 115:2195–2222, 2004). However, a unifying premise against which to validate these source reconstructions is seldom available. The dataset provided in this work, in which brain activity is simultaneously recorded on the scalp (non-invasively) by electroencephalography (EEG) and on the cortex (invasively) by electrocorticography (ECoG), can be of a great help in this direction. These multimodal recordings were obtained from a macaque monkey under wakefulness and sedation. Our primary goal was to establish the connectivity architecture between two sources of interest (frontal and parietal), and to assess how their coupling changes over the conditions. We chose these sources because previous studies have shown that the connections between them are modified by anaesthesia Boly et al. (J Neurosci 32:7082–7090, 2012). Our secondary goal was to evaluate the consistency of the connectivity results when analyzing sources recorded from invasive data (128 implanted ECoG sources) and source activity reconstructed from scalp recordings (19 EEG sensors) at the same locations as the ECoG sources. We conclude that the directed connectivity in the frequency domain between cortical sources reconstructed from scalp EEG is qualitatively similar to the connectivity inferred directly from cortical recordings, using both data-driven (directed transfer function) and biologically grounded (dynamic causal modelling) methods. Furthermore, the connectivity changes identified were consistent with previous findings Boly et al. (J Neurosci 32:7082–7090, 2012). Our findings suggest that inferences about directed connectivity based upon non-invasive electrophysiological data have construct validity in relation to invasive recordings.

Stroke Connectome and Its Implications for Cognitive and Behavioral Sequela of Stroke.

Systems-based approaches to neuroscience, using network analysis and the human connectome, have been adopted by many researchers by virtue of recent progress in neuroimaging and computational technologies. Various neurological disorders have been evaluated from a network perspective, including stroke, Alzheimer’s disease, Parkinson’s disease, and traumatic brain injury. Until now, dynamic processes after stroke and during recovery were investigated through multimodal neuroimaging techniques. Many studies have shown disruptions in structural and functional connectivity, including in large-scale neural networks, in patients with stroke sequela such as motor weakness, aphasia, hemianopia, neglect, and general cognitive dysfunction. A connectome-based approach might shed light on the underlying mechanisms of stroke sequela and the recovery process, and could identify candidates for individualized rehabilitation programs. In this review, we briefly outline the basic concepts of structural and functional connectivity, and the connectome. Then, we explore current evidence regarding how stroke lesions cause changes in connectivity and network architecture parameters. Finally, the clinical implications of perspectives on the connectome are discussed in relation to the cognitive and behavioral sequela of stroke.