Browsing by Subject "BRAIN NETWORKS"

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  • Roine, Ulrika; Roine, Timo; Salmi, Juha; Nieminen-von Wendt, Taina; Tani, Pekka; Leppämäki, Sami; Rintahaka, Pertti; Caeyenberghs, Karen; Leemans, Alexander; Sams, Mikko (2015)
    Background: Recent brain imaging findings suggest that there are widely distributed abnormalities affecting the brain connectivity in individuals with autism spectrum disorder (ASD). Using graph theoretical analysis, it is possible to investigate both global and local properties of brain's wiring diagram, i.e., the connectome. Methods: We acquired diffusion-weighted magnetic resonance imaging data from 14 adult males with high-functioning ASD and 19 age-, gender-, and IQ-matched controls. As with diffusion tensor imaging-based tractography, it is not possible to detect complex (e.g., crossing) fiber configurations, present in 60-90 % of white matter voxels; we performed constrained spherical deconvolution-based whole brain tractography. Unweighted and weighted structural brain networks were then reconstructed from these tractography data and analyzed with graph theoretical measures. Results: In subjects with ASD, global efficiency was significantly decreased both in the unweighted and the weighted networks, normalized characteristic path length was significantly increased in the unweighted networks, and strength was significantly decreased in the weighted networks. In the local analyses, betweenness centrality of the right caudate was significantly increased in the weighted networks, and the strength of the right superior temporal pole was significantly decreased in the unweighted networks in subjects with ASD. Conclusions: Our findings provide new insights into understanding ASD by showing that the integration of structural brain networks is decreased and that there are abnormalities in the connectivity of the right caudate and right superior temporal pole in subjects with ASD.
  • Tokariev, Anton; Vanhatalo, Sampsa; Palva, J. Matias (2016)
    Objective: To assess how the recording montage in the neonatal EEG influences the detection of cortical source signals and their phase interactions. Methods: Scalp EEG was simulated by forward modeling 20-200 simultaneously active sources covering the cortical surface of a realistic neonatal head model. We assessed systematically how the number of scalp electrodes (11-85), analysis montage, or the size of cortical sources affect the detection of cortical phase synchrony. Statistical metrics were developed for quantifying the resolution and reliability of the montages. Results: The findings converge to show that an increase in the number of recording electrodes leads to a systematic improvement in the detection of true cortical phase synchrony. While there is always a ceiling effect with respect to discernible cortical details, we show that the average and Laplacian montages exhibit superior specificity and sensitivity as compared to other conventional montages. Conclusions: Reliability in assessing true neonatal cortical synchrony is directly related to the choice of EEG recording and analysis configurations. Because of the high conductivity of the neonatal skull, the conventional neonatal EEG recordings are spatially far too sparse for pertinent studies, and this loss of information cannot be recovered by re-montaging during analysis. Significance: Future neonatal EEG studies will need prospective planning of recording configuration to allow analysis of spatial details required by each study question. Our findings also advice about the level of details in brain synchrony that can be studied with existing datasets or by using conventional EEG recordings. (C) 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
  • Tokariev, Anton; Vanhatalo, Sampsa; Palva, J. Matias (ELSEVIER IRELAND LTD, 2016)
    Objective: To assess how the recording montage in the neonatal EEG influences the detection of cortical source signals and their phase interactions. Methods: Scalp EEG was simulated by forward modeling 20-200 simultaneously active sources covering the cortical surface of a realistic neonatal head model. We assessed systematically how the number of scalp electrodes (11-85), analysis montage, or the size of cortical sources affect the detection of cortical phase synchrony. Statistical metrics were developed for quantifying the resolution and reliability of the montages. Results: The findings converge to show that an increase in the number of recording electrodes leads to a systematic improvement in the detection of true cortical phase synchrony. While there is always a ceiling effect with respect to discernible cortical details, we show that the average and Laplacian montages exhibit superior specificity and sensitivity as compared to other conventional montages. Conclusions: Reliability in assessing true neonatal cortical synchrony is directly related to the choice of EEG recording and analysis configurations. Because of the high conductivity of the neonatal skull, the conventional neonatal EEG recordings are spatially far too sparse for pertinent studies, and this loss of information cannot be recovered by re-montaging during analysis. Significance: Future neonatal EEG studies will need prospective planning of recording configuration to allow analysis of spatial details required by each study question. Our findings also advice about the level of details in brain synchrony that can be studied with existing datasets or by using conventional EEG recordings. (C) 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
  • Siebenhuhner, Felix; Wang, Sheng H.; Palva, J. Matias; Palva, Satu (2016)
    Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions.
  • Siebenhühner, Felix; Wang, Sheng H.; Arnulfo, Gabriele; Lampinen, Anna; Nobili, Lino; Palva, J. Matias; Palva, Satu (2020)
    Phase synchronization of neuronal oscillations in specific frequency bands coordinates anatomically distributed neuronal processing and communication. Typically, oscillations and synchronization take place concurrently in many distinct frequencies, which serve separate computational roles in cognitive functions. While within-frequency phase synchronization has been studied extensively, less is known about the mechanisms that govern neuronal processing distributed across frequencies and brain regions. Such integration of processing between frequencies could be achieved via cross-frequency coupling (CFC), either by phase-amplitude coupling (PAC) or by n:m-cross-frequency phase synchrony (CFS). So far, studies have mostly focused on local CFC in individual brain regions, whereas the presence and functional organization of CFC between brain areas have remained largely unknown. We posit that interareal CFC may be essential for large-scale coordination of neuronal activity and investigate here whether genuine CFC networks are present in human resting-state (RS) brain activity. To assess the functional organization of CFC networks, we identified brain-wide CFC networks at mesoscale resolution from stereoelectroencephalography (SEEG) and at macroscale resolution from source-reconstructed magnetoencephalography (MEG) data. We developed a novel, to our knowledge, graph-theoretical method to distinguish genuine CFC from spurious CFC that may arise from nonsinusoidal signals ubiquitous in neuronal activity. We show that genuine interareal CFC is present in human RS activity in both SEEG and MEG data. Both CFS and PAC networks coupled theta and alpha oscillations with higher frequencies in large-scale networks connecting anterior and posterior brain regions. CFS and PAC networks had distinct spectral patterns and opposing distribution of low- and high-frequency network hubs, implying that they constitute distinct CFC mechanisms. The strength of CFS networks was also predictive of cognitive performance in a separate neuropsychological assessment. In conclusion, these results provide evidence for interareal CFS and PAC being 2 distinct mechanisms for coupling oscillations across frequencies in large-scale brain networks.
  • Lobier, Muriel; Palva, J. Matias; Palva, Satu (2018)
    Visuospatial attention prioritizes processing of attended visual stimuli. It is characterized by lateralized alpha-band (8-14 Hz) amplitude suppression in visual cortex and increased neuronal activity in a network of frontal and parietal areas. It has remained unknown what mechanisms coordinate neuronal processing among frontoparietal network and visual cortices and implement the attention-related modulations of alpha-band amplitudes and behavior. We investigated whether large-scale network synchronization could be such a mechanism. We recorded human cortical activity with magnetoencephalography (MEG) during a visuospatial attention task. We then identified the frequencies and anatomical networks of inter-areal phase synchronization from source localized MEG data. We found that visuospatial attention is associated with robust and sustained long-range synchronization of cortical oscillations exclusively in the high-alpha (10-14 Hz) frequency band. This synchronization connected frontal, parietal and visual regions and was observed concurrently with amplitude suppression of low-alpha (6-9 Hz) band oscillations in visual cortex. Furthermore, stronger high-alpha phase synchronization was associated with decreased reaction times to attended stimuli and larger suppression of alpha-band amplitudes. These results thus show that high-alpha band phase synchronization is functionally significant and could coordinate the neuronal communication underlying the implementation of visuospatial attention.
  • Wang, Sheng H.; Lobier, Muriel; Siebenhuhner, Felix; Puoliväli, Tuomas; Palva, Satu; Palva, J. Matias (2018)
    Inter-areal functional connectivity (FC), neuronal synchronization in particular, is thought to constitute a key systems-level mechanism for coordination of neuronal processing and communication between brain regions. Evidence to support this hypothesis has been gained largely using invasive electrophysiological approaches. In humans, neuronal activity can be non-invasively recorded only with magneto-and electroencephalography (MEG/EEG), which have been used to assess FC networks with high temporal resolution and whole-scalp coverage. However, even in source-reconstructed MEG/EEG data, signal mixing, or "source leakage", is a significant confounder for FC analyses and network localization. Signal mixing leads to two distinct kinds of false-positive observations: artificial interactions (AI) caused directly by mixing and spurious interactions (SI) arising indirectly from the spread of signals from true interacting sources to nearby false loci. To date, several interaction metrics have been developed to solve the AI problem, but the SI problem has remained largely intractable in MEG/EEG all-to-all source connectivity studies. Here, we advance a novel approach for correcting SIs in FC analyses using source-reconstructed MEG/EEG data. Our approach is to bundle observed FC connections into hyperedges by their adjacency in signal mixing. Using realistic simulations, we show here that bundling yields hyperedges with good separability of true positives and little loss in the true positive rate. Hyperedge bundling thus significantly decreases graph noise by minimizing the false-positive to true-positive ratio. Finally, we demonstrate the advantage of edge bundling in the visualization of large-scale cortical networks with real MEG data. We propose that hypergraphs yielded by bundling represent well the set of true cortical interactions that are detectable and dissociable in MEG/EEG connectivity analysis.
  • Sami, Saber; Williams, Nitin; Hughes, Laura E.; Cope, Thomas E.; Rittman, Timothy; Coyle-Gilchrist, Ian T. S.; Henson, Richard N.; Rowe, James B. (2018)
    The disruption of brain networks is characteristic of neurodegenerative dementias. However, it is controversial whether changes in connectivity reflect only the functional anatomy of disease, with selective vulnerability of brain networks, or the specific neurophysiological consequences of different neuropathologies within brain networks. We proposed that the oscillatory dynamics of cortical circuits reflect the tuning of local neural interactions, such that different pathologies are selective in their impact on the frequency spectrum of oscillations, whereas clinical syndromes reflect the anatomical distribution of pathology and physiological change. To test this hypothesis, we used magnetoencephalography from five patient groups, representing dissociated pathological subtypes and distributions across frontal, parietal and temporal lobes: amnestic Alzheimer's disease, posterior cortical atrophy, and three syndromes associated with frontotemporal lobar degeneration. We measured effective connectivity with graph theory-based measures of local efficiency, using partial directed coherence between sensors. As expected, each disease caused large-scale changes of neurophysiological brain networks, with reductions in local efficiency compared to controls. Critically however, the frequency range of altered connectivity was consistent across clinical syndromes that shared a likely underlying pathology, whilst the localization of changes differed between clinical syndromes. Multivariate pattern analysis of the frequency-specific topographies of local efficiency separated the disorders from each other and from controls (accuracy 62% to 100%, according to the groups' differences in likely pathology and clinical syndrome). The data indicate that magnetoencephalography has the potential to reveal specific changes in neurophysiology resulting from neurodegenerative disease. Our findings confirm that while clinical syndromes have characteristic anatomical patterns of abnormal connectivity that may be identified with other methods like structural brain imaging, the different mechanisms of neurodegeneration also cause characteristic spectral signatures of physiological coupling that are not accessible with structural imaging nor confounded by the neurovascular signalling of functional MRI. We suggest that these spectral characteristics of altered connectivity are the result of differential disruption of neuronal microstructure and synaptic physiology by Alzheimer's disease versus frontotemporal lobar degeneration.
  • Tokariev, Anton; Stjerna, Susanna; Lano, Aulikki; Metsäranta, Marjo; Palva, J. Matias; Vanhatalo, Sampsa (2019)
    Preterm birth is the greatest risk factor for lifelong neurocognitive deficits, globally. The effect of prematurity on early cortical network function has, however, remained poorly understood. Here, we developed a novel methodology that allows reliable assessment of functional connectivity in neonatal brain activity at millisecond and multisecond scales in terms of cortical phase and amplitude correlations, respectively. We measured scalp electroencephalography at term-equivalent age in infants exposed to very early prematurity as well as in healthy controls. We found that newborn cortical activity organizes into multiplex networks that differ significantly between vigilance states. As compared with healthy control infants, prematurity was found to cause frequency-specific patterns of dysconnectivity in cortical network, changes that were distinct for networks of phase and amplitude correlations. Neuroanatomically, the most prominent markers of prematurity were found in connections involving the frontal regions. Phase synchrony in frontally connected networks was correlated with newborn neurological performance, suggesting the first measure of cortical functional coupling that correlates with neurological performance in human infant.
  • Hautala, Sini; Tokariev, Anton; Roienko, Oleksii; Häyrinen, Taru; Ilen, Elina; Haataja, Leena; Vanhatalo, Sampsa (2021)
    Objective: To develop methods for recording and analysing infant's proximal muscle activations. Methods: Surface electromyography (sEMG) of truncal muscles was recorded in three months old infants (N = 18) during spontaneous movement and controlled postural changes. The infants were also divided into two groups according to motor performance. We developed an efficient method for removing dynamic cardiac artefacts to allow i) accurate estimation of individual muscle activations, as well as ii) quantitative characterization of muscle networks. Results: The automated removal of cardiac artefacts allowed quantitation of truncal muscle activity, which showed predictable effects during postural changes, and there were differences between high and low performing infants. The muscle networks showed consistent change in network density during spontaneous movements between supine and prone position. Moreover, activity correlations in individual pairs of back muscles linked to infant́s motor performance. Conclusions: The hereby developed sEMG analysis methodology is feasible and may disclose differences between high and low performing infants. Analysis of the muscle networks may provide novel insight to central control of motility. Significance: Quantitative analysis of infant's muscle activity and muscle networks holds promise for an objective neurodevelopmental assessment of motor system.
  • Salmela, Viljami; Salo, Emma; Salmi, Juha; Alho, Kimmo (2018)
    The fronto-parietal attention networks have been extensively studied with functional magnetic resonance imaging (fMRI), but spatiotemporal dynamics of these networks are not well understood. We measured event-related potentials (ERPs) with electroencephalography (EEG) and collected fMRI data from identical experiments where participants performed visual and auditory discrimination tasks separately or simultaneously and with or without distractors. To overcome the low temporal resolution of fMRI, we used a novel ERP-based application of multivariate representational similarity analysis (RSA) to parse time-averaged fMRI pattern activity into distinct spatial maps that each corresponded, in representational structure, to a short temporal ERP segment. Discriminant analysis of ERP-fMRI correlations revealed 8 cortical networks-2 sensory, 3 attention, and 3 other-segregated by 4 orthogonal, temporally multifaceted and spatially distributed functions. We interpret these functions as 4 spatiotemporal components of attention: modality-dependent and stimulus-driven orienting, top-down control, mode transition, and response preparation, selection and execution.
  • Rouhinen, Santeri; Siebenhühner, Felix; Palva, J. Matias; Palva, Satu (2020)
    The capacity of visual attention determines how many visual objects may be perceived at any moment. This capacity can be investigated with multiple object tracking (MOT) tasks, which have shown that it varies greatly between individuals. The neuronal mechanisms underlying capacity limits have remained poorly understood. Phase synchronization of cortical oscillations coordinates neuronal communication within the fronto-parietal attention network and between the visual regions during endogenous visual attention. We tested a hypothesis that attentional capacity is predicted by the strength of pretarget synchronization within attention-related cortical regions. We recorded cortical activity with magneto- and electroencephalography (M/EEG) while measuring attentional capacity with MOT tasks and identified large-scale synchronized networks from source-reconstructed M/EEG data. Individual attentional capacity was correlated with load-dependent strengthening of theta (3-8 Hz), alpha (8-10 Hz), and gamma-band (30-120 Hz) synchronization that connected the visual cortex with posterior parietal and prefrontal cortices. Individual memory capacity was also preceded by crossfrequency phase-phase and phase-amplitude coupling of alpha oscillation phase with beta and gamma oscillations. Our results show that good attentional capacity is preceded by efficient dynamic functional coupling and decoupling within brain regions and across frequencies, which may enable efficient communication and routing of information between sensory and attentional systems.
  • Sihvonen, Aleksi; Ripolles, Pablo; Leo, Vera; Saunavaara, Jani; Parkkola, Riitta; Rodriguez-Fornells, Antoni; Soinila, Seppo; Särkämö, Teppo (2021)
    Listening to vocal music has been recently shown to improve language recovery in stroke survivors. The neuroplasticity mechanisms supporting this effect are, however, still unknown. Using data from a three-arm, single-blind, randomized controlled trial including acute stroke patients (N = 38) and a 3 month follow-up, we set out to compare the neuroplasticity effects of daily listening to self-selected vocal music, instrumental music, and audiobooks on both brain activity and structural connectivity of the language network. Using deterministic tractography, we show that the 3 month intervention induced an enhancement of the microstructural properties of the left frontal aslant tract (FAT) for the vocal music group compared with the audiobook group. Importantly, this increase in the strength of the structural connectivity of the left FAT correlated with improved language skills. Analyses of stimulus-specific activation changes showed that the vocal music group exhibited increased activations in the frontal termination points of the left FAT during vocal music listening compared with the audiobook group from acute to 3 month poststroke stage. The increased activity correlated with the structural neuroplasticity changes in the left FAT. These results suggest that the beneficial effects of vocal music listening on poststroke language recovery are underpinned by structural neuroplasticity changes within the language network and extend our understanding of music-based interventions in stroke rehabilitation.