What are the 3 medical applications of Computational Neuroscience? 

Computational Neuroscience is a specific field of neuroscience that attempts to understand how the brain computes information. But how does it helps us specifically in the field of medicine? In this brief guide, we are going to answer that question as well as elaborate on its usefulness. Below are the three medical applications of this discipline.

What are the 3 medical applications of Computational Neuroscience?

The 3 medical applications of Computational Neuroscience: 

  • Rehabilitation
  • Psychology and psychiatric disorder
  • Brain-computer interface

Computational neuroscience has many applications in different fields but if we are to talk about its importance in the diagnosis, treatment, and prevention of diseases, the following are its major medical application: rehabilitation, psychology and psychiatric disorder, and brain-computer interface. 

What is Computational Neuroscience? 

The interdisciplinary study of Computational Neuroscience is an emerging research-specific field in the late 1980s. It utilizes mathematical models, theoretical analysis, and simulation of the brain work starting from the molecules all the way to cognitive behavior to study the cognitive capacities of the nervous system. To be able to understand how the nervous system processes information, it also integrates different applications from physics, computer science, and surprisingly electrical engineering. 

The application of Computational Neuroscience in rehabilitation

Integrating computational neuroscience in rehabilitation is a newly emerging field. For the past 30 years, there have been attempts to replicate the operations fundamental to sensorimotor rehabilitation. 

Thus computational neurorehabilitation arises. Its goal is to understand and improve movement recovery of patience with neurologic impairment by modeling plasticity and motor learning. 

This is seen through the emergence of robots and wearable sensors for people who suffered from upper body mild strokes. As of this writing, the initial focus of computational neurorehabilitation is neurologic injuries that may result in different motor-related diseases. 

The use of Computational Neuroscience in Psychology and psychiatric disorder

As of late, the use of computational neuroscience in psychiatry research has shown extraordinary guarantee in laying out a connection among phenomenological and pathophysiological parts of mental issues, in this way reevaluating momentum nosology in additional organically significant aspects. 

The information-driven approach is an arising field in computational neuroscience trying to distinguish jumble explicit highlights among high-layered enormous information. Surprisingly, different AI procedures have been applied to neuroimaging information, and the separated issue explicit highlights have been utilized for programmed case-control characterization. 

For some issues, the detailed exactnesses have arrived at 90% or more. 

This approach, including support learning models, assumes an integrative part in quantitatively portraying the instruments of mental issues by empowering correspondence among conduct and confusion explicit changes at different degrees of mind association, going from particles to cells to circuits. 

Past investigations have elucidated plenty of characterizing side effects of mental problems, including anhedonia, negligence, and unfortunate chief capacity.

Computational Neuroscience in creating a brain-computer interface

In 2006, the school of computer and engineering at the University of Washington became one of the first groups to demonstrate the control of a humanoid robot using a non-invasive brain-computer interface (BCI). 

The primary goal of this group is to discover the computational principles underlying the brain’s remarkable ability to learn, process, and store information by focusing the research on understanding the brain using computational models and simulations. The system consists of a robot, an electrode cap for sensing brainwaves, and a graphical user interface for controlling the robot remotely. 

Their original research demonstrated that the BCI can be used to command a humanoid robot to select and fetch desired objects from remote locations. They have recently proposed a framework for adaptive hierarchical brain-computer interfacing that allows the user to teach a robot new behaviors on-the-fly. 

National Bernstein Network Computational Neuroscience

Understanding the capacity of the human cerebrum still remains a significant scientific challenge. ComputationalNeuroscience handles this issue a stringently between disciplinary methodology. Joining tests, data analysis, numerical models, and computer simulations permit to test speculations about brain function in a quantitative way deliberately. 

Involving this approach offers a tremendous advancement potential for medicine. The National Bernstein Network Computational Neuroscience is a financing drive of the German Federal Ministry of Education and Research (BMBF). It targets grasping the mind’s capacity through the interdisciplinary methodology of Computational Neuroscience. 

In a joint cooperative exertion, scholars, doctors, analysts, physicists, mathematicians, and computer researchers make an interpretation of exploratory outcomes into numerical models that can be tried in virtual experiences. 

Their experiences with ordinary and obsessively changed cerebrum capacities open new points of view for inventive medicines as well as innovative applications. Their knowledge of typical and neurotically adjusted brain functions opens new points of view for creative treatments as well as innovative applications. 

Conclusion

This short guide answers the question “What are the three medical applications of computational neuroscience?” We identified rehabilitation, psychology and psychiatric diseases, and brain-computer interface as this discipline’s application in medicine. Please feel free to comment on the content or ask any questions in the comments section below.

Frequently Asked Questions (FAQs): what are the medical applications of computational neuroscience?

What is computational neuroscience used for?

A definitive objective of computational neuroscience is to make sense of how electrical and synthetic signs are utilized in the cerebrum to address and handle data. It makes sense of the biophysical systems of calculation in neurons, virtual experiences of brain circuits, and models of learning.

What is the field of computational neuroscience?

Computational neuroscience is the field study wherein numerical apparatuses and speculations are utilized to explore mind work. It can likewise consolidate assorted comes nearer from electrical designing, software engineering, and physical science to comprehend how the sensory system processes data.

Is computational neuroscience a growing field?

Computational neuroscience is one of the most quickly developing subfields in neuroscience. New examination and demonstrating methods are earnestly expected to sort out the reams of information delivered by original enormous scope recording advancements.

References 

Hosseini SA, Naghibi-Sistani MB, Akbarzadeh-T MR. A two-dimensional brain-computer interface based on visual selective attention by Magnetoencephalograph (MEG) signals. Tabriz Journal of Electrical Engineering. 2015;45(2):65-74

Swanson J, Castellanos FX, Murias M, LaHoste G, Kennedy J. Cognitive neuroscience of attention deficit hyperactivity disorder and hyperkinetic disorder. Current Opinion in Neurobiology. 1998;8(2):263-271

Schwarzwaelder, Kerstin & Cardoso de Oliveira, Simone. (2010). National Bernstein Network Computational Neuroscience (Nationales Bernstein Netzwerk Computational Neuroscience).. it – Information Technology. 52. 39-44. 10.1524/itit.2010.0569. 

Hosseini SA, Akbarzadeh-T MR, Naghibi-Sistani MB. Hybrid approach in recognition of visual covert selective spatial attention based on MEG signals. In: IEEE International Conference on Fuzzy Systems (FUZZ). Istanbul: IEEE; 2015. DOI: 10.1109/FUZZ-IEEE.2015.7337958

David J. Reinkensmeyer, Etienne Burdet, Maura Casadio, John W. Krakauer, Gert Kwakkel, Catherine E. Lang, Stephan P. Swinnen, Nick S. Ward & Nicolas Schweighofer 

Journal of NeuroEngineering and Rehabilitation volume 13, Article number: 42 (2016)

Noriaki Yahata (2017 Mar 27) Computational neuroscience approach to biomarkers and treatments for mental disorders. Computational neuroscience approach to biomarkers and treatments for mental disorders – PubMed (nih.gov)

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