scholarly journals Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients

2019 ◽  
Author(s):  
Emmanouil Giannakakis ◽  
Frances Hutchings ◽  
Christoforos A. Papasavvas ◽  
Cheol E. Han ◽  
Bernd Weber ◽  
...  
Keyword(s):  
Focal Epilepsy ◽  
Brain Connectivity ◽  
Diffusion Imaging ◽  
Structural Connectivity ◽  
Computational Modelling ◽  
Brain Regions ◽  
Long Term Effects ◽  
Surgery Outcome ◽  
Epileptic Patients

AbstractIn patients with drug resistant focal epilepsy, targeted weak stimulation of the affected brain regions has been proposed as an alternative to surgery. However, the effectiveness of stimulation as a treatment presents great variation from patient to patient. In this study, brain activity is simulated for a period of one day using a network of Wilson-Cowan oscillators coupled according to diffusion imaging based structural connectivity. We use this computational model to examine the potential long-term effects of stimulation on brain connectivity. Our findings indicate that the overall simulated effect of stimulation is heavily dependent on the excitability of the stimulated regions. Additionally, stimulation seems to lead to long-term effects in the connectivity of secondary (non-stimulated) regions in epileptic patients. These effects are correlated with a worse surgery outcome in some patients, which suggests that long-term simulations could be used as a tool to determine suitability for surgery/stimulation.

scholarly journals Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients

PLoS ONE ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. e0221380
Author(s):  
Emmanouil Giannakakis ◽  
Frances Hutchings ◽  
Christoforos A. Papasavvas ◽  
Cheol E. Han ◽  
Bernd Weber ◽  
...  
Keyword(s):  
Brain Stimulation ◽  
Structural Connectivity ◽  
Computational Modelling ◽  
Long Term Effects ◽  
Epileptic Patients

scholarly journals Brain Metabolic Correlates of Persistent Olfactory Dysfunction after SARS-Cov2 Infection

Biomedicines ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 287
Author(s):  
Maria Isabella Donegani ◽  
Alberto Miceli ◽  
Matteo Pardini ◽  
Matteo Bauckneht ◽  
Silvia Chiola ◽  
...  
Keyword(s):  
Fdg Pet ◽  
Structural Connectivity ◽  
Statistical Parametric Mapping ◽  
Brain Regions ◽  
Olfactory Dysfunction ◽  
Whole Body ◽  
Mapping Software ◽  
18F Fdg ◽  
Left Insula

We aimed to evaluate the brain hypometabolic signature of persistent isolated olfactory dysfunction after SARS-CoV-2 infection. Twenty-two patients underwent whole-body [18F]-FDG PET, including a dedicated brain acquisition at our institution between May and December 2020 following their recovery after SARS-Cov2 infection. Fourteen of these patients presented isolated persistent hyposmia (smell diskettes olfaction test was used). A voxel-wise analysis (using Statistical Parametric Mapping software version 8 (SPM8)) was performed to identify brain regions of relative hypometabolism in patients with hyposmia with respect to controls. Structural connectivity of these regions was assessed (BCB toolkit). Relative hypometabolism was demonstrated in bilateral parahippocampal and fusiform gyri and in left insula in patients with respect to controls. Structural connectivity maps highlighted the involvement of bilateral longitudinal fasciculi. This study provides evidence of cortical hypometabolism in patients with isolated persistent hyposmia after SARS-Cov2 infection. [18F]-FDG PET may play a role in the identification of long-term brain functional sequelae of COVID-19.

scholarly journals Fundamental Dynamical Modes Underlying Human Brain Synchronization

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Catalina Alvarado-Rojas ◽  
Michel Le Van Quyen
Keyword(s):  
Large Scale ◽  
Brain Regions ◽  
Electrode Placement ◽  
High Dimensional ◽  
Sleep Cycle ◽  
Epileptic Patients ◽  
Brain States ◽  
Intracranial Recordings ◽  
Characteristic Dynamic

Little is known about the long-term dynamics of widely interacting cortical and subcortical networks during the wake-sleep cycle. Using large-scale intracranial recordings of epileptic patients during seizure-free periods, we investigated local- and long-range synchronization between multiple brain regions over several days. For such high-dimensional data, summary information is required for understanding and modelling the underlying dynamics. Here, we suggest that a compact yet useful representation is given by a state space based on the first principal components. Using this representation, we report, with a remarkable similarity across the patients with different locations of electrode placement, that the seemingly complex patterns of brain synchrony during the wake-sleep cycle can be represented by a small number of characteristic dynamic modes. In this space, transitions between behavioral states occur through specific trajectories from one mode to another. These findings suggest that, at a coarse level of temporal resolution, the different brain states are correlated with several dominant synchrony patterns which are successively activated across wake-sleep states.

scholarly journals Functional Connectivity within Brain Networks of Long Term and Short term Meditators

2019 ◽  
Vol 9 (2S) ◽  
pp. 29-34
Keyword(s):  
Functional Connectivity ◽  
Temporal Correlation ◽  
Brain Regions ◽  
Invasive Technique ◽  
Long Term Effects ◽  
Short Term ◽  
Statistical Concept ◽  
The Brain ◽  
Meditative Practices

Meditation refers to a state of mind of relaxation and concentration, where generally the mind and body is at rest. The process of meditation reflects the state of the brain which is distinct from sleep or typical wakeful states of consciousness. Meditative practices usually involve regulation of emotions and monitoring of attention. Over the past decade there has been a tremendous increase in an interest to study the neural mechanisms involved in meditative practices. It could also be beneficial to explore if the effect of meditation is altered by the number of years of meditation practice. Functional Magnetic Resonance Imaging (fMRI) is a very useful imaging technique which can be used to perform this analysis due to its inherent benefits, mainly it being a non-invasive technique. Functional activation and connectivity analysis can be performed on the fMRI data to find the active regions and the connectivity in the brain regions. Functional connectivity is defined as a simple temporal correlation between anatomically separate, active neural regions. Functional connectivity gives the statistical dependencies between regional time series. It is a statistical concept and is quantified using metrics like Correlation. In this study, a comparison is made between functional connectivity in the brain regions of long term meditation practitioners (LTP) and short-term meditation practitioners (STP) to see the differences and similarities in the connectivity patterns. From the analysis, it is evident that in fact there is a difference in connectivity between long term and short term practitioners and hence continuous practice of meditation can have long term effects.

scholarly journals Asymmetric high-order anatomical brain connectivity sculpts effective connectivity

2020 ◽  
Vol 4 (3) ◽  
pp. 871-890
Author(s):  
Arseny A. Sokolov ◽  
Peter Zeidman ◽  
Adeel Razi ◽  
Michael Erb ◽  
Philippe Ryvlin ◽  
...  
Keyword(s):  
White Matter ◽  
Dynamic Range ◽  
Diffusion Processes ◽  
Brain Connectivity ◽  
Effective Connectivity ◽  
Structural Connectivity ◽  
Laplacian Matrix ◽  
Graph Laplacian ◽  
Brain Regions ◽  
High Order

Bridging the gap between symmetric, direct white matter brain connectivity and neural dynamics that are often asymmetric and polysynaptic may offer insights into brain architecture, but this remains an unresolved challenge in neuroscience. Here, we used the graph Laplacian matrix to simulate symmetric and asymmetric high-order diffusion processes akin to particles spreading through white matter pathways. The simulated indirect structural connectivity outperformed direct as well as absent anatomical information in sculpting effective connectivity, a measure of causal and directed brain dynamics. Crucially, an asymmetric diffusion process determined by the sensitivity of the network nodes to their afferents best predicted effective connectivity. The outcome is consistent with brain regions adapting to maintain their sensitivity to inputs within a dynamic range. Asymmetric network communication models offer a promising perspective for understanding the relationship between structural and functional brain connectomes, both in normalcy and neuropsychiatric conditions.

scholarly journals Undernutrition and Overnutrition in the Neonatal Rat: Long-Term Effects on Noradrenergic Pathways in Brain Regions

1990 ◽  
Vol 27 (2) ◽  
pp. 191-197 ◽  
Author(s):  
Frederic J Seidler ◽  
Joanne M Bell ◽  
Theodore A Slotkin
Keyword(s):  
Brain Regions ◽  
Neonatal Rat ◽  
Long Term Effects

scholarly journals Acute action of DSP-4 on central norepinephrine axons: biochemical and immunohistochemical evidence for differential effects.

1989 ◽  
Vol 37 (9) ◽  
pp. 1435-1442 ◽  
Author(s):  
R Grzanna ◽  
U Berger ◽  
J M Fritschy ◽  
M Geffard
Keyword(s):  
Cerebral Cortex ◽  
High Performance ◽  
Direct Evidence ◽  
Selective Vulnerability ◽  
Brain Regions ◽  
Acute Effects ◽  
Long Term Effects ◽  
Immunohistochemical Evidence ◽  
Immunohistochemical Studies

Previous immunohistochemical studies of the long-term effects of the noradrenergic neurotoxin DSP-4 have demonstrated a remarkably selective vulnerability of norepinephrine (NE) axons of the locus coeruleus (LC). NE axons originating in non-LC NE neurons appear to be largely resistant to the neurotoxic action of DSP-4. We conducted this study to evaluate the acute effects of DSP-4 on NE axons in four different brain regions: cerebral cortex, cerebellum, ventral forebrain, and hypothalamus. NE levels were determined by high-performance liquid chromatography (HPLC) 6 and 24 hr and 14 days after DSP-4 administration. NE axons in these brain regions were visualized in brain sections at 6 and 24 hr after drug treatment, using a specific antiserum to NE. HPLC assays revealed profound reductions of NE levels in cerebral cortex and cerebellum, but only minor decreases in ventral forebrain and hypothalamus. NE immunohistochemistry showed dramatic differences in the acute effects of DSP-4 on NE axon staining: nearly complete loss of staining in cortex and cerebellum, in contrast to an almost unchanged staining pattern in ventral forebrain and hypothalamus. This study demonstrates that NE immunohistochemistry is a valuable tool to assess the acute effects of DSP-4 on NE axons in different brain regions. The results provide the first direct evidence that NE axons are not uniformly acted on by DSP-4 and suggest that the acute effects of DSP-4 are restricted to LC axons.

scholarly journals Unique mapping of structural and functional connectivity on cognition

2018 ◽  
Author(s):  
J. Zimmermann ◽  
J.G. Griffiths ◽  
A.R. McIntosh
Keyword(s):  
Functional Connectivity ◽  
Brain Connectivity ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Unique Mapping ◽  
Human Connectome Project ◽  
Behavioural Patterns ◽  
Wide Range ◽  
Psychological Tasks ◽  
New Evidence

AbstractThe unique mapping of structural and functional brain connectivity (SC, FC) on cognition is currently not well understood. It is not clear whether cognition is mapped via a global connectome pattern or instead is underpinned by several sets of distributed connectivity patterns. Moreover, we also do not know whether the pattern of SC and of FC that underlie cognition are overlapping or distinct. Here, we study the relationship between SC and FC and an array of psychological tasks in 609 subjects from the Human Connectome Project (HCP). We identified several sets of connections that each uniquely map onto different aspects of cognitive function. We found a small number of distributed SC and a larger set of cortico-cortical and cortico-subcortical FC that express this association. Importantly, SC and FC each show unique and distinct patterns of variance across subjects and differential relationships to cognition. The results suggest that a complete understanding of connectome underpinnings of cognition calls for a combination of the two modalities.Significance StatementStructural connectivity (SC), the physical white-matter inter-regional pathways in the brain, and functional connectivity (FC), the temporal co-activations between activity of brain regions, have each been studied extensively. Little is known, however, about the distribution of variance in connections as they relate to cognition. Here, in a large sample of subjects (N = 609), we showed that two sets of brain-behavioural patterns capture the correlations between SC, and FC with a wide range of cognitive tasks, respectively. These brain-behavioural patterns reveal distinct sets of connections within the SC and the FC network and provide new evidence that SC and FC each provide unique information for cognition.

scholarly journals The R1-weighted connectome: complementing brain networks with a myelin-sensitive measure

2020 ◽  
pp. 1-15
Author(s):  
Tommy Boshkovski ◽  
Ljupco Kocarev ◽  
Julien Cohen-Adad ◽  
Bratislav Mišić ◽  
Stéphane Lehéricy ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Mri ◽  
Brain Connectivity ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Added Value ◽  
Modular Organization ◽  
Sensitive Measure ◽  
Higher Order Functions ◽  
Insight Into

Myelin plays a crucial role in how well information travels between brain regions. Complementing the structural connectome, obtained with diffusion MRI tractography, with a myelin-sensitive measure could result in a more complete model of structural brain connectivity and give better insight into white-matter myeloarchitecture. In this work we weight the connectome by the longitudinal relaxation rate (R1), a measure sensitive to myelin, and then we assess its added value by comparing it with connectomes weighted by the number of streamlines (NOS). Our analysis reveals differences between the two connectomes both in the distribution of their weights and the modular organization. Additionally, the rank-based analysis shows that R1 can be used to separate transmodal regions (responsible for higher-order functions) from unimodal regions (responsible for low-order functions). Overall, the R1-weighted connectome provides a different perspective on structural connectivity taking into account white matter myeloarchitecture.

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