Critical comments on EEG sensor space dynamical connectivity analysis

Many different analysis techniques have been developed and applied to EEG recordings that allow one to investigate how different brain areas interact. One particular class of methods, based on the linear parametric representation of multiple interacting time series, is widely used to study causal connectivity in the brain. However, the results obtained by these methods should be interpreted with great care. The goal of this paper is to show, both theoretically and using simulations, that results obtained by applying causal connectivity measures on the sensor (scalp) time series do not allow interpretation in terms of interacting brain sources. This is because 1) the channel locations cannot be seen as an approximation of a source's anatomical location and 2) spurious connectivity can occur between sensors. Although many measures of causal connectivity derived from EEG sensor time series are affected by the latter, here we will focus on the well-known time domain index of Granger causality (GC) and on the frequency domain directed transfer function (DTF). Using the state-space framework and designing two simulation studies we show that mixing effects caused by volume conduction can lead to spurious connections, detected either by time domain GC or by DTF. Therefore, GC/DTF causal connectivity measures should be computed at the source level, or derived within analysis frameworks that model the effects of volume conduction. Since mixing effects can also occur in the source space, it is advised to combine source space analysis with connectivity measures that are robust to mixing

Tensor Analysis and Fusion of Multimodal Brain Images

Current high-throughput data acquisition technologies probe dynamical systems with different imaging modalities, generating massive data sets at different spatial and temporal resolutions posing challenging problems in multimodal data fusion. A case in point is the attempt to parse out the brain structures and networks that underpin human cognitive processes by analysis of different neuroimaging modalities (functional MRI, EEG, NIRS etc.). We emphasize that the multimodal, multi-scale nature of neuroimaging data is well reflected by a multi-way (tensor) structure where the underlying processes can be summarized by a relatively small number of components or "atoms". We introduce Markov-Penrose diagrams - an integration of Bayesian DAG and tensor network notation in order to analyze these models. These diagrams not only clarify matrix and tensor EEG and fMRI time/frequency analysis and inverse problems, but also help understand multimodal fusion via Multiway Partial Least Squares and Coupled Matrix-Tensor Factorization. We show here, for the first time, that Granger causal analysis of brain networks is a tensor regression problem, thus allowing the atomic decomposition of brain networks. Analysis of EEG and fMRI recordings shows the potential of the methods and suggests their use in other scientific domains.Comment: 23 pages, 15 figures, submitted to Proceedings of the IEE

Cognitive and white-matter compartment models reveal selective relations 1 between corticospinal tract microstructure and simple reaction time

The speed of motor reaction to an external stimulus varies substantially between individuals and is slowed in ageing. However, the neuroanatomical origins of inter-individual variability in reaction time (RT) remain unclear. Here, we combined a cognitive model of RT and a biophysical compartment model of diffusion-weighted MRI (DWI) to characterize the relationship between RT and microstructure of the corticospinal tract (CST) and the optic radiation (OR), the primary motor output and visual input pathways associated with visual-motor responses. We fitted an accumulator model of RT to 46 female human participants' behavioral performance in a simple reaction time task. The non-decision time parameter (Ter) derived from the model was used to account for the latencies of stimulus encoding and action initiation. From multi-shell DWI data, we quantified tissue microstructure of the CST and OR with the neurite orientation dispersion and density imaging (NODDI) model as well as the conventional diffusion tensor imaging (DTI) model. Using novel skeletonization and segmentation approaches, we showed that DWI-based microstructure metrics varied substantially along CST and OR. The Ter of individual participants was negatively correlated with the NODDI measure of the neurite density in the bilateral superior CST. Further, we found no significant correlation between the microstructural measures and mean RT. Thus, our findings suggest a link between inter-individual differences in sensorimotor speed and selective microstructural properties in white matter tracts

Critical comments on EEG sensor space dynamical connectivity analysis

any different analysis techniques have been developed and applied to EEG recordings that allow one to investigate how different brain areas interact. One particular class of methods, based on the linear parametric representation of multiple interacting time series, is widely used to study causal connectivity in the brain. However, the results obtained by these methods should be interpreted with great care. The goal of this paper is to show, both theoretically and using simulations, that results obtained by applying causal connectivity measures on the sensor (scalp) time series do not allow interpretation in terms of interacting brain sources. This is because (1) the channel locations cannot be seen as an approximation of a source's anatomical location and (2) spurious connectivity can occur between sensors. Although many measures of causal connectivity derived from EEG sensor time series are affected by the latter, here we will focus on the well-known time domain index of Granger causality (GC) and on the frequency domain directed transfer function (DTF). Using the state-space framework and designing two simulation studies we show that mixing effects caused by volume conduction can lead to spurious connections, detected either by time domain GC or by DTF. Therefore, GC/DTF causal connectivity measures should be computed at the source level, or derived within analysis frameworks that model the effects of volume conduction. Since mixing effects can also occur in the source space, it is advised to combine source space analysis with connectivity measures that are robust to mixing

Peroneal Tendon Rekonstrüksiyonunda Otogreft Olarak Hamstring Tendonları Kullanılabilir mi? Kadavra Çalışması

Amaç: Kronik peroneal tendon yırtıklarının rekonstrüksiyonunda tendon transferleri ve otogreftler kullanılabilir. Bu kadavra çalışmasında peroneal tendonların rekonstrüksiyonu için otogreft hamstring tendonlarının kullanımının çap uygunluğu açısından değerlendirilmesi amaçlandı. Gereç ve Yöntem: Çalışmada 13 (4 kadın, 9 erkek) taze donmuş kadavra alt ekstremitesinden otogreft olarak 13 adet makroskopik yaralanması ve dejenerasyonu olmayan, hamstring tendonları (gracilis, semitendinosus) standart yöntemler ile elde edildi ve ölçüme alındı. Ardından aynı kadavraların peroneal tendonları (peroneus longus, peroneus brevis) standart yöntemler ile elde edilerek ölçüme alındı. Tendon çap ölçümleri tendonların en kalın olduğu orta bölgesinden dijital mikro kumpas yardımıyla yapıldı. Ölçümler sonucunda hamstring tendonları ile her iki peroneal tendon kalınlıkları istatistiksel olarak değerlendirildi. Bulgular: Çalışmaya dahil edilen kadavraların yaş ortalaması 74,07±12,25 (minimum: 51, maksimum: 94) yıl iken vücut kitle indeksi ortalaması 25,38±6,07 olarak bulundu. Çapları değerlendirilen tendonlar ile cinsiyet arasında istatistiksel olarak anlamlı bir fark bulunmadı (her biri için p>0,05). Hamstring tendonları (grasilis ve semitendinosus) boyutları ile, peroneus longus ve brevis tendonları arasında pozitif bir korelasyon mevcuttu (her biri için p<0,01). Ayrıca tendon orta çap değerlendirmesi sonucuna göre semitendinozus tendon çap ortalamasının peroneal tendonların çap ortalamasına daha yakın olduğu tespit edilmiştir. Sonuç: Kronik peroneal tendon yırtıklarının rekonstrüksiyonunda otogreft olarak, her iki peroneal tendonun rekonstrüksiyonu için semitendinozus tendonunun kullanılması tendon orta çapları değerlendirmesine göre daha uygun olabileceği kanaatine varıldı

The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure

Humans differ from each other in a wide range of biometrics, but to what extent brain connectivity varies between individuals remains largely unknown. By combining diffusion-weighted imaging (DWI) and magnetoencephalography (MEG), this study characterizes the inter-subject variability (ISV) of multimodal brain connectivity. Structural connectivity is characterized by higher ISV in association cortices including the core multiple-demand network and lower ISV in the sensorimotor cortex. MEG ISV exhibits frequency-dependent signatures, and the extent of MEG ISV is consistent with that of structural connectivity ISV in selective macroscopic cortical clusters. Across the cortex, the ISVs of structural connectivity and beta-band MEG functional connectivity are negatively associated with cortical myelin content indexed by the quantitative T1 relaxation rate measured by high-resolution 7 T MRI. Furthermore, MEG ISV from alpha to gamma bands relates to the hindrance and restriction of the white-matter tissue estimated by DWI microstructural models. Our findings depict the inter-relationship between the ISV of brain connectivity from multiple modalities, and highlight the role of tissue microstructure underpinning the ISV

Achromatic temporal-frequency responses of human lateral geniculate nucleus and primary visual cortex

The sensitivity of the sensory systems to temporal changes of the environment constitutes one of the critical issues in perception. In the present study, we investigated the human early visual system's dependency on the temporal frequency of visual input using fMRI. Blood oxygen level-dependent (BOLD) responses of the lateral geniculate nucleus (LGN) and primary visual cortex (V1) were investigated in a wide frequency range (6-46 Hz) with fine frequency sampling (13 frequencies). Subject-specific functional-anatomic ROIs were derived from the combination of the anatomic template masks and the functional maps derived from multi-session fMRI analyses across all 13 stimulation conditions. Using functional-anatomic ROIs, average responses of LGN and V1 were calculated for each frequency. The V1 surface area was further parsed into 7 eccentricity sectors to detail central and peripheral responses. LGN's response revealed fluctuations on a background of non-significant decrease of the BOLD response with increasing stimulation frequency, while V1 response displayed similar fluctuations with a global maximum in the range of 8-12 Hz, but a rapid and significant decrease with increasing stimulation frequency especially above 14 Hz. This behavior of V1 response valid for both central and peripheral vision emphasizes that the profound low-pass effect of the visual system to visual input emerges in V1, presumably generated by the intra-cortical circuitry of V1 or projections from extra-striate areas. Besides, the high correlation between LGN and V1 BOLD responses across all visual stimulation frequencies supports the oscillatory tuning in thalamo-cortical interactions as previously claimed in electrophysiological studies. (C) 2016 Elsevier Ltd. All rights reserved

Achromatic temporal-frequency responses of human lateral geniculate nucleus and primary visual cortex

The sensitivity of the sensory systems to temporal changes of the environment constitutes one of the critical issues in perception. In the present study, we investigated the human early visual system’s dependency on the temporal frequency of visual input using fMRI. Blood oxygen level-dependent (BOLD) responses of the lateral geniculate nucleus (LGN) and primary visual cortex (V1) were investigated in a wide frequency range (6–46 Hz) with fine frequency sampling (13 frequencies). Subject-specific functional-anatomic ROIs were derived from the combination of the anatomic template masks and the functional maps derived from multi-session fMRI analyses across all 13 stimulation conditions. Using functional-anatomic ROIs, average responses of LGN and V1 were calculated for each frequency. The V1 surface area was further parsed into 7 eccentricity sectors to detail central and peripheral responses. LGN’s response revealed fluctuations on a background of non-significant decrease of the BOLD response with increasing stimulation frequency, while V1 response displayed similar fluctuations with a global maximum in the range of 8–12 Hz, but a rapid and significant decrease with increasing stimulation frequency especially above 14 Hz. This behavior of V1 response valid for both central and peripheral vision emphasizes that the profound low-pass effect of the visual system to visual input emerges in V1, presumably generated by the intra-cortical circuitry of V1 or projections from extra-striate areas. Besides, the high correlation between LGN and V1 BOLD responses across all visual stimulation frequencies supports the oscillatory tuning in thalamo-cortical interactions as previously claimed in electrophysiological studies