Progress to restore movement in people with neuromotor disabilities

May 20, 2019

A study published in the advanced edition of 12 April in the journal Neural Computation shows that approaches based on Long Short-Term Memory decoders could provide better algorithms for neuroprostheses that employ Brain-Machine Interfaces to restore movement in patients with severe neuromotor disabilities.

This investigation was carried out by researchers of Duke University (USA) and has involved Núria Armengol, an alumna of the bachelor's degree in Biomedical Engineering at UPF who initiated this research topic for her end-of-degree project under the supervision of Ruben Moreno Bote, a researcher at the Center for Brain and Cognition (CBC) of the Department of Information and Communication Technologies (DTIC) at UPF, which she developed at Duke University (Durham, USA). Currently, Armengol is pursuing a master's degree at the Swiss Federal Institute of Technology in Zurich (ETH, Switzerland).

Although over the years many real-time neural decoding algorithms have been proposed for brain-machine interface (BMI) applications, recent advances in deep learning algorithms have improved the design of brain activity decoders involving recurrent artificial neural networks capable of decoding the activity of all neurons in real time.

As Núria Armengol explains, "for this study, we developed an LSTM decoder to extract the kinematics of the movement of the activity of large populations of neurons (N = 134-402), sampled simultaneously from multiple cortical areas of micus rhesus while they performed motor tasks".

The brain regions studied include primary motor areas and primary somatosensory cortical areas. The LSTM's capacity to retain information for extended periods of time enabled accurate decoding for tasks that required both movements and periods of immobility.

"Our LSTM algorithm significantly outperformed the Kalman filter (an analytical method that enables estimating unobservable state variables from observable variables) while the monkeys were performing different tasks on a treadmill (raising an arm, raising both arms or walking)", Armengol adds.

Notably, LSTM units exhibited a variety of well-known physiological features of cortical neuronal activity, such as directional tuning and neuronal dynamics during tasks. LSTM modelled several key physiological attributes of the cortical circuits involved in motor tasks. These discoveries suggest that LSTM-based approaches could provide a better algorithm strategy for neuroprostheses that employ Brain-Machine Interfaces to restore movement in patients with severe neuromotor disabilities.
-end-


Universitat Pompeu Fabra - Barcelona

Related Algorithms Articles from Brightsurf:

A multidisciplinary policy design to protect consumers from AI collusion
Legal scholars, computer scientists and economists must work together to prevent unlawful price-surging behaviors from artificial intelligence (AI) algorithms used by rivals in a competitive market, argue Emilio Calvano and colleagues in this Policy Forum.

Students develop tool to predict the carbon footprint of algorithms
Within the scientific community, it is estimated that artificial intelligence -- otherwise meant to serve as a means to effectively combat climate change -- will become one of the most egregious CO2 culprits should current trends continue.

Machine learning takes on synthetic biology: algorithms can bioengineer cells for you
Scientists at Lawrence Berkeley National Laboratory have developed a new tool that adapts machine learning algorithms to the needs of synthetic biology to guide development systematically.

Algorithms uncover cancers' hidden genetic losses and gains
Limitations in DNA sequencing technology make it difficult to detect some major mutations often linked to cancer, such as the loss or duplication of parts of chromosomes.

Managing data flow boosts cyber-physical system performance
Researchers have developed a suite of algorithms to improve the performance of cyber-physical systems - from autonomous vehicles to smart power grids - by balancing each component's need for data with how fast that data can be sent and received.

New theory hints at more efficient way to develop quantum algorithms
A new theory could bring a way to make quantum algorithm development less of an accidental process, say Purdue University scientists.

AI as good as the average radiologist in identifying breast cancer
Researchers at Karolinska Institutet and Karolinska University Hospital in Sweden have compared the ability of three different artificial intelligence (AI) algorithms to identify breast cancer based on previously taken mammograms.

Context reduces racial bias in hate speech detection algorithms
When it comes to accurately flagging hate speech on social media, context matters, says a new USC study aimed at reducing errors that could amplify racial bias.

Researchers discover algorithms and neural circuit mechanisms of escape responses
Prof. WEN Quan from School of Life Sciences, University of Science and Technology of China (USTC) of the Chinese Academy of Sciences (CAS) has proposed the algorithms and circuit mechanisms for the robust and flexible motor states of nematodes during escape responses.

Lightning fast algorithms can lighten the load of 3D hologram generation
Tokyo, Japan - Researchers from Tokyo Metropolitan University have developed a new way of calculating simple holograms for heads-up displays (HUDs) and near-eye displays (NEDs).

Read More: Algorithms News and Algorithms Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.