Recent years have led to a rapid increase in the development of neurotechnologies for diagnosis, monitoring, and treatment of conditions with neurological targets. The central driving force has been the need for next-generation devices to treat neural injury and disease, where current pharmaceutical or conventional bioelectronics have been unable to impart sufficient therapeutic effects. The advent of new therapies and advanced technologies has resulted in a reemergence of the concept of superhuman performance. This is a hypothetical possibility that is enabled when bionics are used to augment the neural system and has included the notions of improved cognitive ability and enhancement of hearing and seeing beyond the limitations of a healthy human. It is quite conceivable that a bionic eye could be used for night vision; however, the damage to both the neural system and surrounding tissues in placing such a device is only considered acceptable in the case of a patient that can obtain improvement in quality of life. There are also critical limitations that have hindered clinical translation of high-resolution neural interfaces, despite significant advances in biomaterial and bioelectronics technologies, including the advent of biohybrid devices. Surgical damage and foreign body reactions to such devices can be reduced but not eliminated, and these engineering solutions to reduce inflammation present additional challenges to the long-term performance and medical regulation. As a result, while bioelectronics has seen concepts from science fiction realized, there remains a significant gap to their use as enhancements beyond medical therapies.
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http://dx.doi.org/10.1063/5.0079530 | DOI Listing |
Atten Percept Psychophys
January 2025
U.S. DEVCOM Army Research Laboratory, Humans in Complex Systems, Aberdeen Proving Ground, MD, USA.
Historically, electrophysiological correlates of scene processing have been studied with experiments using static stimuli presented for discrete timescales where participants maintain a fixed eye position. Gaps remain in generalizing these findings to real-world conditions where eye movements are made to select new visual information and where the environment remains stable but changes with our position and orientation in space, driving dynamic visual stimulation. Co-recording of eye movements and electroencephalography (EEG) is an approach to leverage fixations as time-locking events in the EEG recording under free-viewing conditions to create fixation-related potentials (FRPs), providing a neural snapshot in which to study visual processing under naturalistic conditions.
View Article and Find Full Text PDFJ Neural Transm (Vienna)
January 2025
Institut für Zellbiochemie, OE 4310, Medizinische Hochschule Hannover, 30623, Hannover, Germany.
Botulinum neurotoxins (BoNT) are established biopharmaceuticals for neuromuscular and secretory conditions based on their ability to block neurotransmitter release from neurons by proteolyzing specific soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins. Recently, a mutant catalytic domain of serotype E (LC/E) exhibiting 16 mutations was reported to cleave the phosphatase and tensin homolog (PTEN). This molecule represents an attractive new target in neurons as several reports support PTEN knockdown as a strategy to stimulate axonal regeneration after injury.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Department of Anesthesiology, E-Da Cancer Hospital, I-Shou University, Kaohsiung, Taiwan.
Parkinson's disease (PD), a degenerative disorder of the central nervous system, is commonly diagnosed using functional medical imaging techniques such as single-photon emission computed tomography (SPECT). In this study, we utilized two SPECT data sets (n = 634 and n = 202) from different hospitals to develop a model capable of accurately predicting PD stages, a multiclass classification task. We used the entire three-dimensional (3D) brain images as input and experimented with various model architectures.
View Article and Find Full Text PDFSci Rep
January 2025
Amity Institute of Environmental Sciences (AIES), Amity University Uttar Pradesh (AUUP), Sector-125, Gautam Budh Nagar, Noida, 201313, India.
This study focused on simulating the adsorption-based separation of Methylene Blue (MB) dye utilising Oryza sativa straw biomass (OSSB). Three distinct modelling approaches were employed: artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and response surface methodology (RSM). To evaluate the adsorbent's potential, assessments were conducted using Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM).
View Article and Find Full Text PDFSci Rep
January 2025
Institute for Anthropological Research, 10000, Zagreb, Croatia.
Modelling of pollutants provides valuable insights into air quality dynamics, aiding exposure assessment where direct measurements are not viable. Machine learning (ML) models can be employed to explore such dynamics, including the prediction of air pollution concentrations, yet demanding extensive training data. To address this, techniques like transfer learning (TL) leverage knowledge from a model trained on a rich dataset to enhance one trained on a sparse dataset, provided there are similarities in data distribution.
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