Articles tagged with Neuroinformatics
The FENS Forum 2026 will be Europe's largest neuroscience congress, covering areas of basic to translational research. Journalists can register for free and attend symposia and poster sessions.
The EBRAINS Summit 2025 will bring together experts to assess how neuroscience can drive medical progress, digital innovation, and responsible data use. Preliminary results from the EPINOV clinical trial, integrating virtual brain technology for epilepsy surgery planning, will be presented.
Researchers developed a novel topology-aware multiscale feature fusion network to enhance EEG-based motor imagery decoding. The TA-MFF network achieves excellent classification performance, outperforming state-of-the-art methods by leveraging spectral-topological data analysis-processing and inter-spectral recursive attention.
Researchers have developed a microscale optoelectronic tetherless electrode that can transmit brain activity data wirelessly for more than a year. Powered by red and infrared laser beams, the device transmits data back using tiny pulses of infrared light.
A researcher is exploring the hidden functions of vascular-neuronal interfaces to uncover how blood vessels influence brain development and connectivity. The study aims to develop new therapeutic strategies for diseases caused by disrupted communication between blood vessels and neurons.
Researchers have identified a group of cells called Y1 receptor-expressing neurons in the brainstem's lateral parabrachial nucleus as critical for regulating long-term pain states. These neurons integrate information about hunger, fear and thirst, allowing pain signals to be modulated by other brain circuits signaling more urgent needs.
The largest neuroscience event will convene in San Diego from November 15-19, featuring over 10,000 presentations on various topics. Registered journalists will gain access to cutting-edge research, expert interviews, and press-only events.
A NUS-led global study reveals that 30-minute functional MRI scans deliver up to 22% in cost savings while retaining or improving prediction accuracy. This finding could reshape how researchers design neuroscience and mental health studies, especially for hard-to-recruit populations.
Gene coexpression analysis reveals optimal markers of cell types and states, providing opportunities for developing novel biomarkers and targeted treatment strategies for glioma patients. Dr. Oldham's work tackles the reproducibility crisis in science, emphasizing data metadata standardization.
A recent study found that caffeine increases brain signal complexity and enhances criticality during sleep, with effects more pronounced in young adults. This can lead to a state where the brain is neither fully awake nor relaxed, potentially interfering with restful recovery.
A study at the University of Trento has observed the brain activity of honey bees during sleep and identified similarities with human sleep patterns. The researchers used a combination of optical brain imaging, machine learning analysis, and computational neural modelling to analyze how sleep influences sensory perception in bees.
Researchers from the University of Texas at San Antonio discovered a significant link between REM sleep disturbances and increased PTSD severity. The study suggests that targeting REM sleep could be a promising approach for improving PTSD treatment outcomes.
A University of Ottawa-led research team has deciphered the message that serotonin conveys to the brain, discovering a 'prospective code for value' that explains why neurons are activated by rewards and punishments. This finding has implications across multiple fields, including neuroscience, psychology, and psychiatry.
The Open Brain Institute launches a groundbreaking platform to simulate and study digital brains, empowering researchers to explore brain complexity and diseases. With its virtual neuroscience laboratories, the OBI enables global collaboration and access to cutting-edge virtual labs.
A new AI algorithm, DPAD, developed by Maryam Shanechi's lab, can dissociate brain patterns related to specific behaviors, improving brain-computer interfaces for paralyzed patients. The algorithm can also discover new patterns in the brain that may be missed by prior methods.
Researchers at EPFL developed a next-generation miniaturized brain-machine interface capable of direct brain-to-text communication on tiny silicon chips. The MiBMI system can decode neural signals generated when a person imagines writing letters or words with high accuracy and low power consumption.
FutureNeuro, a leading SFI Research Centre, is expanding its research programme with a focus on diagnostics, therapeutics, and digital health. The centre aims to develop precision diagnostics, future treatments, and systems using real-time health data.
Researchers developed chronological age prediction models by analyzing gene expression changes in the prefrontal cortex, identifying genes associated with aging and potential mechanisms. The models showed high correlation with age and demonstrated female and male-specific differences.
Researchers developed a new machine learning method to analyze brain data, separating intrinsic neural patterns from sensory inputs. The method revealed surprisingly consistent hidden patterns in three subjects' neural activity despite different tasks.
Researchers at Salk Institute assembled the most complete atlas of the mouse brain by analyzing over 2 million brain cells. The detailed atlas reveals thousands of cell types, their connections, genes, and regulatory programs active in each cell, providing new insights into human disease vulnerabilities.
Researchers used new software to compare MRI scans from 300 babies and found that myelin, a fatty sheath around axons, develops much slower after birth. The study supports the idea that gestational age at birth and scan time matter for brain development.
Researchers have developed a high-resolution MRI microscope capable of capturing human embryos with a resolution of one-hundredth of a millimeter. This breakthrough enables detailed visualization and analysis of brain development and organ growth, paving the way for a high-resolution atlas of brain and other organs.
Researchers used a mathematical theory called the free energy principle to predict how real neural networks learn and organize themselves. The study successfully mimicked this process in rat embryo neurons grown in a culture dish, demonstrating the principle's guiding force behind biological neural network learning.
The UC Santa Cruz Genomics Institute will run the Data Coordination Center for the Scalable and Systematic Neurobiology of Psychiatric and Neurodevelopmental Disorder Risk Genes (SSPsyGene) Consortium. The team will coordinate an initial selection of 250 relevant genes from nearly 30,000 protein coding genes in the human genome.
A UTEP researcher has received a prestigious NSF grant to support his research on the neural mechanisms of decision-making. The award will also fund educational components and undergraduate/graduate courses focused on computational and biological science.
A team from McGill University has created a database called neuromaps, which combines over 40 existing brain maps to help scientists find correlations between patterns across different brain regions. The tool provides standardized space to view and compare each map, improving reproducibility of results.
The CMU Array, a new microelectrode array, offers customized treatments for neurological disorders by allowing for three-dimensional sampling and ultra-high-density configurations. This technology has the potential to transform how doctors treat conditions like epilepsy and limb function loss.
Scientists have identified two areas of the auditory cortex specialized to recognize human voice sounds without linguistic meaning. These regions help react to sound cues allowing people to identify characteristics of the person speaking, such as gender, age, and height. This discovery sheds light on neurological disorders affecting vo...
The Human Brain Project (HBP) has brought together neuroscientists from different disciplines to work collaboratively on common goals. The HBP researchers outline their scientific approach and illustrate the potential of EBRAINS infrastructure for neuroscience research.
Professor Alexander Ecker is awarded a Starting Grant to develop machine-learning methods to describe neurons' shape and function, leveraging a large dataset from the US Brain Initiative. The research aims to uncover how a neuron's shape relates to its role in sensory information processing.
The Tanenbaum Open Science Institute at The Neuro has partnered with the Hotchkiss Brain Institute to promote collaboration and information sharing in brain research. This partnership aims to accelerate the pace of discovery and bring novel treatments to patients with neurological disorders.
A recent study published in PLOS Medicine found that people with mental illnesses have poorer sleep quality compared to the general population. The study analyzed data from 89,205 participants and discovered significant differences in sleep patterns, including increased waking frequency and duration.
A Mount Sinai study found that polygenic risk scores were no better at predicting worsening symptoms than written reports in schizophrenia patients. The results raise questions about the use of polygenic risk scores in real-world situations, suggesting a doctor's report may be an untapped source of predictive information.
Researchers analyzed how juvenile male zebra finches learn to sing using a novel framework that revealed multilayered changes in brain wiring. Good songs improve slowly over time, while bad ones change quickly but are often forgotten the next day.
The Neuroscience Information Framework (NIF) is a dynamic inventory of web-based neurosciences data, resources, and tools. The NIF enables discovery and access to public research data and tools worldwide through an open source, networked environment.