Skip to main content

Analytical Model: Growing Cortex on growing subcortex

In the analytical model of brain development, the scenario of a growing cortex on a growing subcortex is considered. Here are the key aspects of this analytical model:


1. Model Description: The model involves representing the cortex as a morphogenetically growing outer layer and the subcortex as a strain-driven growing inner core. This dual-layered approach captures the dynamic nature of both layers as they interact and influence the folding patterns of the brain.


2.  Mechanical Interactions: The model accounts for the mechanical interactions between the growing cortex and subcortex, considering how their respective growth rates and properties influence the deformation and folding of the brain tissue. This approach integrates both axonal tension-driven and differential growth-driven hypotheses of cortical folding.


3.  Continuum Theory of Finite Growth: The model is based on the continuum theory of finite growth, which describes the growth and deformation of biological tissues over time. By incorporating growth mechanisms into the model, researchers can simulate the evolving morphology of the brain surface during development.


4.  Parameter Exploration: The model explores the effects of varying parameters such as cortical thickness, stiffness ratios, and growth rates between the cortex and subcortex. By systematically varying these parameters, researchers can analyze how different growth dynamics impact the folding patterns and surface morphologies of the brain.


5. Analytical Estimates: The model provides analytical estimates for critical parameters such as the critical time, pressure, and wavelength at the onset of folding. These estimates offer insights into the conditions under which cortical folding initiates and how the growth dynamics of the cortex and subcortex contribute to this process.


6. Integration with Cellular Mechanisms: The model aims to connect the macroscopic mechanical behavior of the cortex-subcortex system with underlying cellular mechanisms such as axon elongation. By bridging the gap between macroscopic and microscopic scales, researchers can better understand the biological processes driving cortical folding.


In summary, the analytical model of a growing cortex on a growing subcortex offers a comprehensive framework for studying the mechanical and morphological aspects of brain development. By incorporating growth dynamics and mechanical interactions into the model, researchers can simulate the complex folding patterns observed in the developing brain and gain insights into the underlying mechanisms shaping brain morphology.

 

Comments

Popular posts from this blog

Human Connectome Project

The Human Connectome Project (HCP) is a large-scale research initiative that aims to map the structural and functional connectivity of the human brain. Launched in 2009, the HCP utilizes advanced neuroimaging techniques to create detailed maps of the brain's neural pathways and networks in healthy individuals. The project focuses on understanding how different regions of the brain communicate and interact with each other, providing valuable insights into brain function and organization. 1.      Structural Connectivity : The HCP uses diffusion MRI to map the white matter pathways in the brain, revealing the structural connections between different brain regions. This information helps researchers understand the physical wiring of the brain and how information is transmitted between regions. 2.      Functional Connectivity : Functional MRI (fMRI) is employed to study the patterns of brain activity and connectivity while individuals are at rest (...

Clinical Significance of Hypnopompic, Hypnagogic, and Hedonic Hypersynchron

Hypnopompic, hypnagogic, and hedonic hypersynchrony are normal pediatric phenomena with no significant clinical relevance. These types of hypersynchrony are considered variations in brain activity that occur during specific states such as arousal from sleep (hypnopompic), transition from wakefulness to sleep (hypnagogic), or pleasurable activities (hedonic). While these patterns may be observed on an EEG, they are not indicative of any underlying pathology or neurological disorder. Therefore, the presence or absence of hypnopompic, hypnagogic, and hedonic hypersynchrony does not carry any specific clinical implications. It is important to differentiate these normal variations in brain activity from abnormal patterns that may be associated with neurological conditions, such as epileptiform discharges or other pathological findings. Understanding the clinical significance of these normal phenomena helps in accurate EEG interpretation and clinical decision-making.  

Distinguishing Features of Alpha Activity

Alpha activity in EEG recordings has distinguishing features that differentiate it from other brain wave patterns.  1.      Frequency Range : o   Alpha activity typically occurs in the frequency range of 8 to 13 Hz. o   The alpha rhythm is most prominent in the posterior head regions during relaxed wakefulness with eyes closed. 2.    Location : o   Alpha activity is often observed over the occipital regions of the brain, known as the occipital alpha rhythm or posterior dominant rhythm. o   In drowsiness, the alpha rhythm may extend anteriorly to include the frontal region bilaterally. 3.    Modulation : o   The alpha rhythm can attenuate or disappear with drowsiness, concentration, stimulation, or visual fixation. o   Abrupt loss of the alpha rhythm due to visual or cognitive activity is termed blocking. 4.    Behavioral State : o   The presence of alpha activity is associated with a state of relax...

Alpha Activity

Alpha activity in electroencephalography (EEG) refers to a specific frequency range of brain waves typically observed in relaxed and awake individuals. Here is an overview of alpha activity in EEG: 1.      Frequency Range : o Alpha waves are oscillations in the frequency range of approximately 8 to 12 Hz (cycles per second). o They are most prominent in the posterior regions of the brain, particularly in the occipital area. 2.    Characteristics : o Alpha waves are considered to be a sign of a relaxed but awake state, often observed when individuals are awake with their eyes closed. o They are typically monotonous, monomorphic, and symmetric, with a predominant anterior distribution. 3.    Variations : o Alpha activity can vary based on factors such as age, mental state, and neurological conditions. o Variations in alpha frequency, amplitude, and distribution can provide insights into brain function and cognitive processes. 4.    Clinica...

The expression of Notch-related genes in the differentiation of BMSCs into dopaminergic neuron-like cells.

  The expression of Notch-related genes plays a crucial role in the differentiation of human bone marrow mesenchymal stem cells (h-BMSCs) into dopaminergic neuron-like cells. The Notch signaling pathway is involved in regulating cell fate decisions, including the differentiation of BMSCs. In the study discussed in the PDF file, changes in the expression of Notch-related genes were observed during the differentiation process. Specifically, the study utilized a human Notch signaling pathway PCR array to detect the expression levels of 84 genes related to the Notch signaling pathway, including ligands, receptors, target genes, cell proliferation and differentiation-related genes, and neurogenesis-related genes. The array also included genes from other signaling pathways that intersect with the Notch pathway, such as Sonic hedgehog and Wnt receptor signaling pathway members. During the differentiation of h-BMSCs into dopaminergic neuron-like cells, the expression levels of Notch-re...