How the Neural network circuits works in Parkinson's Disease?

In Parkinson's disease, the neural network circuits involved in motor control are disrupted, leading to characteristic motor symptoms such as tremor, bradykinesia, and rigidity. The primary brain regions affected in Parkinson's disease include the basal ganglia and the cortex. Here is an overview of how neural network circuits work in Parkinson's disease:

1. Basal Ganglia Dysfunction: The basal ganglia are a group of subcortical nuclei involved in motor control. In Parkinson's disease, there is a loss of dopamine-producing neurons in the substantia nigra, leading to decreased dopamine levels in the basal ganglia. This dopamine depletion results in abnormal signaling within the basal ganglia circuitry, leading to motor symptoms.

2. Cortical Involvement: The cortex, particularly the motor cortex, plays a crucial role in initiating and coordinating voluntary movements. In Parkinson's disease, abnormal activity in the cortex, especially in the beta and gamma frequency bands, is observed and is associated with motor symptoms.

3. Disrupted Neural Circuits: The communication between the basal ganglia, cortex, and other brain regions is disrupted in Parkinson's disease. This disruption leads to difficulties in initiating and controlling movements, resulting in the characteristic motor symptoms of the disease.

4. Deep Brain Stimulation (DBS): Deep brain stimulation is a therapeutic approach that involves the implantation of electrodes in specific brain regions, such as the subthalamic nucleus (STN) or globus pallidus, to modulate neural activity and alleviate motor symptoms in Parkinson's disease. DBS works by delivering electrical impulses to targeted brain regions to normalize neural activity and improve motor function.

5. Research Advances: Recent research has focused on decoding neural activity patterns associated with specific motor symptoms in Parkinson's disease. By understanding the neurophysiological fingerprints of tremor and bradykinesia, researchers aim to develop more targeted and personalized treatment strategies, such as closed-loop DBS paradigms that can adapt stimulation parameters based on real-time neural signals.

By studying the neural network circuits involved in Parkinson's disease and developing innovative treatment approaches, researchers aim to improve the management of motor symptoms and enhance the quality of life for individuals living with Parkinson's disease.

Lauro, P. M., Lee, S., Amaya, D. E., Liu, D. D., Akbar, U., & Asaad, W. F. (2023). Concurrent decoding of distinct neurophysiological fingerprints of tremor and bradykinesia in Parkinson’s disease. eLife, 12, e84135. https://doi.org/10.7554/eLife.84135

Comments

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...

Mashtishk Vigyan Anusandhan

Search This Blog