Associations of hemodynamics, morphology, and patient characteristics with aneurysm rupture stratified by aneurysm location.

PURPOSE: The mechanisms of cerebral aneurysm rupture are not fully understood. We analyzed the associations of hemodynamics, morphology, and patient age and gender with aneurysm rupture stratifying by location. METHODS: Using image-based models, 20 hemodynamic and 17 morphological parameters were compared in 1931 ruptured and unruptured aneurysms with univariate logistic regression. Rupture rates were compared between males and females as well as younger and older patients and bifurcation versus sidewall aneurysms for different aneurysm locations. Subsequently, associations between hemodynamics and morphology and patient as well as aneurysm characteristics were analyzed for aneurysms at five locations. RESULTS: Compared to unruptured aneurysms, ruptured aneurysms were characterized by a more irregular shape and were exposed to a more adverse hemodynamic environment described by faster flow, higher wall shear stress, more oscillatory shear, and more unstable and complex flows. These associations with rupture status were consistent for different aneurysm locations. Rupture rates were significantly higher in males at the internal carotid artery (ICA) bifurcation, ophthalmic ICA, and the middle cerebral artery (MCA) bifurcation. At the anterior communicating artery (ACOM) and MCA bifurcation, they were significantly higher for younger patients. Bifurcation aneurysms had significantly larger rupture rates at the MCA and posterior communicating artery (PCOM). In these groups with higher rupture rates, aneurysms were characterized by adverse hemodynamics and more complex shapes. CONCLUSION: Hemodynamic and morphological differences between ruptured and unruptured aneurysms are consistent across locations. Adverse morphology and hemodynamics are related to rupture as well as younger age, male gender, and bifurcation aneurysms.

Development and internal validation of an aneurysm rupture probability model based on patient characteristics and aneurysm location, morphology, and hemodynamics.

PURPOSE: Unruptured cerebral aneurysms pose a dilemma for physicians who need to weigh the risk of a devastating subarachnoid hemorrhage against the risk of surgery or endovascular treatment and their complications when deciding on a treatment strategy. A prediction model could potentially support such treatment decisions. The aim of this study was to develop and internally validate a model for aneurysm rupture based on hemodynamic and geometric parameters, aneurysm location, and patient gender and age. METHODS: Cross-sectional data from 1061 patients were used for image-based computational fluid dynamics and shape characterization of 1631 aneurysms for training an aneurysm rupture probability model using logistic group Lasso regression. The model's discrimination and calibration were internally validated based on the area under the curve (AUC) of the receiver operating characteristic and calibration plots. RESULTS: The final model retained 11 hemodynamic and 12 morphological variables, aneurysm location, as well as patient age and gender. An adverse hemodynamic environment characterized by a higher maximum oscillatory shear index, higher kinetic energy and smaller low shear area as well as a more complex aneurysm shape, male gender and younger age were associated with an increased rupture risk. The corresponding AUC of the model was 0.86 (95% CI [0.85, 0.86], after correction for optimism 0.84). CONCLUSION: The model combining variables from various domains was able to discriminate between ruptured and unruptured aneurysms with an AUC of 86%. Internal validation indicated potential for the application of this model in clinical practice after evaluation with longitudinal data.

Development of a statistical model for discrimination of rupture status in posterior communicating artery aneurysms.

BACKGROUND: Intracranial aneurysms at the posterior communicating artery (PCOM) are known to have high rupture rates compared to other locations. We developed and internally validated a statistical model discriminating between ruptured and unruptured PCOM aneurysms based on hemodynamic and geometric parameters, angio-architectures, and patient age with the objective of its future use for aneurysm risk assessment. METHODS: A total of 289 PCOM aneurysms in 272 patients modeled with image-based computational fluid dynamics (CFD) were used to construct statistical models using logistic group lasso regression. These models were evaluated with respect to discrimination power and goodness of fit using tenfold nested cross-validation and a split-sample approach to mimic external validation. RESULTS: The final model retained maximum and minimum wall shear stress (WSS), mean parent artery WSS, maximum and minimum oscillatory shear index, shear concentration index, and aneurysm peak flow velocity, along with aneurysm height and width, bulge location, non-sphericity index, mean Gaussian curvature, angio-architecture type, and patient age. The corresponding area under the curve (AUC) was 0.8359. When omitting data from each of the three largest contributing hospitals in turn, and applying the corresponding model on the left-out data, the AUCs were 0.7507, 0.7081, and 0.5842, respectively. CONCLUSIONS: Statistical models based on a combination of patient age, angio-architecture, hemodynamics, and geometric characteristics can discriminate between ruptured and unruptured PCOM aneurysms with an AUC of 84%. It is important to include data from different hospitals to create models of aneurysm rupture that are valid across hospital populations.

Dopamine drives left-hemispheric lateralization of neural networks during human speech.

Although the concept of left-hemispheric lateralization of neural processes during speech production has been known since the times of Broca, its physiological underpinnings still remain elusive. We sought to assess the modulatory influences of a major neurotransmitter, dopamine, on hemispheric lateralization during real-life speaking using a multimodal analysis of functional MRI, intracranial EEG recordings, and large-scale neural population simulations based on diffusion-weighted MRI. We demonstrate that speech-induced phasic dopamine release into the dorsal striatum and speech motor cortex exerts direct modulation of neuronal activity in these regions and drives left-hemispheric lateralization of speech production network. Dopamine-induced lateralization of functional activity and networks during speaking is not dependent on lateralization of structural nigro-striatal and nigro-motocortical pathways. Our findings provide the first mechanistic explanation for left-hemispheric lateralization of human speech that is due to left-lateralized dopaminergic modulation of brain activity and functional networks.

High-frequency brain networks undergo modular breakdown during epileptic seizures.

OBJECTIVE: Cortical high-frequency oscillations (HFOs; 100-500 Hz) play a critical role in the pathogenesis of epilepsy; however, whether they represent a true epileptogenic process remains largely unknown. HFOs have been recorded in the human cortex but their network dynamics during the transitional period from interictal to ictal phase remain largely unknown. We sought to determine the high-frequency network dynamics of these oscillations in patients with epilepsy who were undergoing intracranial electroencephalographic recording for seizure localization. METHODS: We applied a graph theoretical analysis framework to high-resolution intracranial electroencephalographic recordings of 24 interictal and 24 seizure periods to identify the spatiotemporal evolution of community structure of high-frequency cortical networks at rest and during multiple seizure episodes in patients with intractable epilepsy. RESULTS: Cortical networks at all examined frequencies showed temporally stable community architecture in all 24 interictal periods. During seizure periods, high-frequency networks showed a significant breakdown of their community structure, which was characterized by the emergence of numerous small nodal communities, not limited to seizure foci and encompassing the entire recorded network. Such network disorganization was observed on average 225 s before the electrographic seizure onset and extended on average 190 s after termination of the seizure. Gamma networks were characterized by stable community dynamics during resting and seizure periods. SIGNIFICANCE: Our findings suggest that the modular breakdown of high-frequency cortical networks represents a distinct functional pathology that underlies epileptogenesis and corresponds to a cortical state of highest propensity to generate seizures.

Mixed Electrical-Chemical Synapses in Adult Rat Hippocampus are Primarily Glutamatergic and Coupled by Connexin-36.

Dendrodendritic electrical signaling via gap junctions is now an accepted feature of neuronal communication in mammalian brain, whereas axodendritic and axosomatic gap junctions have rarely been described. We present ultrastructural, immunocytochemical, and dye-coupling evidence for "mixed" (electrical/chemical) synapses on both principal cells and interneurons in adult rat hippocampus. Thin-section electron microscopic images of small gap junction-like appositions were found at mossy fiber (MF) terminals on thorny excrescences of CA3 pyramidal neurons (CA3pyr), apparently forming glutamatergic mixed synapses. Lucifer Yellow injected into weakly fixed CA3pyr was detected in MF axons that contacted four injected CA3pyr, supporting gap junction-mediated coupling between those two types of principal cells. Freeze-fracture replica immunogold labeling revealed diverse sizes and morphologies of connexin-36-containing gap junctions throughout hippocampus. Of 20 immunogold-labeled gap junctions, seven were large (328-1140 connexons), three of which were consistent with electrical synapses between interneurons; but nine were at axon terminal synapses, three of which were immediately adjacent to distinctive glutamate receptor-containing postsynaptic densities, forming mixed glutamatergic synapses. Four others were adjacent to small clusters of immunogold-labeled 10-nm E-face intramembrane particles, apparently representing extrasynaptic glutamate receptor particles. Gap junctions also were on spines in stratum lucidum, stratum oriens, dentate gyrus, and hilus, on both interneurons and unidentified neurons. In addition, one putative GABAergic mixed synapse was found in thin-section images of a CA3pyr, but none were found by immunogold labeling, suggesting the rarity of GABAergic mixed synapses. Cx36-containing gap junctions throughout hippocampus suggest the possibility of reciprocal modulation of electrical and chemical signals in diverse hippocampal neurons.

Gap junctions on hippocampal mossy fiber axons demonstrated by thin-section electron microscopy and freeze fracture replica immunogold labeling.

Gap junctions have been postulated to exist between the axons of excitatory cortical neurons based on electrophysiological, modeling, and dye-coupling data. Here, we provide ultrastructural evidence for axoaxonic gap junctions in dentate granule cells. Using combined confocal laser scanning microscopy, thin-section transmission electron microscopy, and grid-mapped freeze-fracture replica immunogold labeling, 10 close appositions revealing axoaxonic gap junctions ( approximately 30-70 nm in diameter) were found between pairs of mossy fiber axons ( approximately 100-200 nm in diameter) in the stratum lucidum of the CA3b field of the rat ventral hippocampus, and one axonal gap junction ( approximately 100 connexons) was found on a mossy fiber axon in the CA3c field of the rat dorsal hippocampus. Immunogold labeling with two sizes of gold beads revealed that connexin36 was present in that axonal gap junction. These ultrastructural data support computer modeling and in vitro electrophysiological data suggesting that axoaxonic gap junctions play an important role in the generation of very fast (>70 Hz) network oscillations and in the hypersynchronous electrical activity of epilepsy.

Dendritic size of pyramidal neurons differs among mouse cortical regions.

Neocortical circuits share anatomical and physiological similarities among different species and cortical areas. Because of this, a 'canonical' cortical microcircuit could form the functional unit of the neocortex and perform the same basic computation on different types of inputs. However, variations in pyramidal cell structure between different primate cortical areas exist, indicating that different cortical areas could be built out of different neuronal cell types. In the present study, we have investigated the dendritic architecture of 90 layer II/III pyramidal neurons located in different cortical regions along a rostrocaudal axis in the mouse neocortex, using, for the first time, a blind multidimensional analysis of over 150 morphological variables, rather than evaluating along single morphological parameters. These cortical regions included the secondary motor cortex (M2), the secondary somatosensory cortex (S2), and the lateral secondary visual cortex and association temporal cortex (V2L/TeA). Confirming earlier primate studies, we find that basal dendritic morphologies are characteristically different between different cortical regions. In addition, we demonstrate that these differences are not related to the physical location of the neuron and cannot be easily explained assuming rostrocaudal gradients within the cortex. Our data suggest that each cortical region is built with specific neuronal components.

Quantitative morphologic classification of layer 5 neurons from mouse primary visual cortex.

The understanding of any neural circuit requires the identification and characterization of all its components. Morphologic classifications of neurons are, therefore, of central importance to neuroscience. We use a quantitative method to classify neurons from layer 5 of mouse primary visual cortex, based on multidimensional clustering. To reconstruct neurons, we used Golgi impregnations and biocytin injections, as well as DiOlistics, a novel technique of labeling neurons with lipophilic dyes. We performed computerized 3-D reconstructions of 158 layer 5 cells to measure a series of morphologic variables. Principal component analysis and cluster analysis were used for the classification of cell types. Five major classes of cells were found: group 1 includes large pyramidal neurons with apical dendrites that reach layer 1 with an apical tuft; group 2 consists of short pyramidal neurons and large multipolar cells with "polarized" dendritic trees; group 3 is composed of less extensive pyramidal neurons; group 4 includes small cells; and group 5 includes another set of short pyramidal neurons in addition to "atypically oriented" cells. Our sample included a relatively homogeneous group of 27 neurons that project to the superior colliculus, which clustered mainly in group 1, thus supporting the validity of the classification. Cluster analysis of neuronal morphologies provides an objective method to quantitatively define different neuronal phenotypes and may serve as a basis for describing neocortical circuits.

Morphological and physiological characterization of layer VI corticofugal neurons of mouse primary visual cortex.

Layer VI is the origin of the massive feedback connection from the cortex to the thalamus, yet its complement of cell types and their connections is poorly understood. The physiological and morphological properties of corticofugal neurons of layer VI of mouse primary visual cortex were investigated in slices loaded with the Ca(2+) indicator fura-2AM. To identify corticofugal neurons, electrical stimulation of the white matter (WM) was done in conjunction with calcium imaging to detect neurons that responded with changes in intracellular Ca(2+) concentrations in response to the stimulation. Subsequent whole cell recordings confirmed that they discharged antidromic action potentials after WM stimulation. Antidromically activated neurons were more excitable and had different spiking properties than neighboring nonantidromic neurons, although both groups had similar input resistances. Furthermore, antidromic neurons possessed narrower action potentials and smaller afterhyperpolarizations. Additionally, three-dimensional reconstructions indicated that antidromically activated neurons had a distinct morphology with longer apical dendrites and fewer nonprimary dendrites than nonantidromic cells. To identify the antidromic neurons, rhodamine microspheres were injected into the dorsal lateral geniculate nucleus of the thalamus and allowed to retrogradely transport back to the somata of the layer VI cortico-geniculate neurons. Physiological and anatomical analysis indicated that most antidromic neurons were likely to be cortico-geniculate neurons. Our results show that cortico-thalamic neurons represent a specific functional and morphological class of layer VI neurons.