Synchron has implanted its BCI in a US patient for the first time—bringing it a big step closer to distribution.
Category: neuroscience – Page 484
Many efforts have been made to image the spatiotemporal electrical activity of the brain with the purpose of mapping its function and dysfunction as well as aiding the management of brain disorders. Here, we propose a non-conventional deep learning–based source imaging framework (DeepSIF) that provides robust and precise spatiotemporal estimates of underlying brain dynamics from noninvasive high-density electroencephalography (EEG) recordings. DeepSIF employs synthetic training data generated by biophysical models capable of modeling mesoscale brain dynamics. The rich characteristics of underlying brain sources are embedded in the realistic training data and implicitly learned by DeepSIF networks, avoiding complications associated with explicitly formulating and tuning priors in an optimization problem, as often is the case in conventional source imaging approaches. The performance of DeepSIF is evaluated by 1) a series of numerical experiments, 2) imaging sensory and cognitive brain responses in a total of 20 healthy subjects from three public datasets, and 3) rigorously validating DeepSIF’s capability in identifying epileptogenic regions in a cohort of 20 drug-resistant epilepsy patients by comparing DeepSIF results with invasive measurements and surgical resection outcomes. DeepSIF demonstrates robust and excellent performance, producing results that are concordant with common neuroscience knowledge about sensory and cognitive information processing as well as clinical findings about the location and extent of the epileptogenic tissue and outperforming conventional source imaging methods. The DeepSIF method, as a data-driven imaging framework, enables efficient and effective high-resolution functional imaging of spatiotemporal brain dynamics, suggesting its wide applicability and value to neuroscience research and clinical applications.
The consciousness of bees
Posted in neuroscience
Summary: Study reveals how somatostatin and copper affect amyloid beta in Alzheimer’s disease pathology.
Source: KAIST
With nearly 50 million dementia patients worldwide, and Alzheimers’s disease is the most common neurodegenerative disease. Its main symptom is the impairment of general cognitive abilities, including the ability to speak or to remember.
The importance of finding a cure is widely understood with increasingly aging population and the life expectancy being ever-extended. However, even the cause of the grim disease is yet to be given a clear definition.
For scientists searching for the brain’s ‘control room, an area called the claustrum has emerged as a compelling candidate. This little-studied deep brain structure is thought to be the place where multiple senses are brought together, attention is controlled, and consciousness arises. Observations in mice now support the role of the claustrum as a hub for coordinating activity across the brain. New research from the RIKEN Center for Brain Science (CBS) shows that slow-wave brain activity, a characteristic of sleep and resting states, is controlled by the claustrum. The synchronization of silent and active states across large parts of the brain by these slow waves could contribute to consciousness.
A serendipitous discovery actually led Yoshihiro Yoshihara, team leader at CBS, to investigate the claustrum. His lab normally studies the sense of smell and the detection of pheromones, but they chanced upon a genetically engineered mouse strain with a specific population of brain cells that was present only in the claustrum. These neurons could be turned on using optogenetic technology or selectively silenced through genetic manipulation, thus enabling the study of what turned out to be a vast, claustrum-controlled network. The study by Yoshihara and colleagues was published in Nature Neuroscience on May 11.
They started out by mapping the claustrum’s inputs and outputs and found that many higher-order brain areas send connections to the claustrum, such as those involved in sensation and motor control. Outgoing connections from the claustrum were broadly distributed across the brain, reaching numerous brain areas such as prefrontal, orbital, cingulate, motor, insular, and entorhinal cortices. “The claustrum is at the center of a widespread brain network, covering areas that are involved in cognitive processing,” says co-first author Kimiya Narikiyo. “It essentially reaches all higher brain areas and all types of neurons, making it a potential orchestrator of brain-wide activity.”
Millions of people are administered general anesthesia each year in the United States alone, but it’s not always easy to tell whether they are actually unconscious.
A small proportion of those patients regain some awareness during medical procedures, but a new study of the brain activity that represents consciousness could prevent that potential trauma. It may also help both people in comas and scientists struggling to define which parts of the brain can claim to be key to the conscious mind.
“What has been shown for 100 years in an unconscious state like sleep are these slow waves of electrical activity in the brain,” says Yuri Saalmann, a University of Wisconsin-Madison psychology and neuroscience professor. “But those may not be the right signals to tap into. Under a number of conditions—with different anesthetic drugs, in people that are suffering from a coma or with brain damage or other clinical situations—there can be high-frequency activity as well.”
What do we know about cortical columns? A neuroscience (and artificial intelligence) discussion with Jeff Hawkins of Numenta.
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Part of the cognitive neuroscience bitesize series. This is a follow-up of ‘basics of fMRI’ that considers exciting developments in mapping the human connect…
I promise you: this post is going to tell a scientifically coherent story that involves all five topics listed in the title. Not one can be omitted.
My story starts with a Zoom talk that the one and only Lenny Susskind delivered for the Simons Institute for Theory of Computing back in May. There followed a panel discussion involving Lenny, Edward Witten, Geoffrey Penington, Umesh Vazirani, and your humble shtetlmaster.
Lenny’s talk led up to a gedankenexperiment involving an observer, Alice, who bravely jumps into a specially-prepared black hole, in order to see the answer to a certain computational problem in her final seconds before being ripped to shreds near the singularity. Drawing on earlier work by Bouland, Fefferman, and Vazirani, Lenny speculated that the computational problem could be exponentially hard even for a (standard) quantum computer. Despite this, Lenny repeatedly insisted—indeed, he asked me again to stress here—that he was not claiming to violate the Quantum Extended Church-Turing Thesis (QECTT), the statement th at all of nature can be efficiently simulated by a standard quantum computer. Instead, he was simply investigating how the QECTT needs to be formulated in order to be a true statement.
Autism spectrum disorder (ASD) is a neurological and developmental condition that affects how humans communicate, learn new things and behave. Symptoms of ASD can include difficulties in interacting with others and adapting to changes in routine, repetitive behaviors, irritability and restricted or fixated interests for specific things.
While symptoms of autism can emerge at any age, the first signs generally start to show within the first two years of a child’s life. People with ASD can encounter numerous challenges, which can be addressed through support services, talk therapy and sometimes medication.
To this day, neuroscientists and medical researchers have not identified the primary causes of ASD. Nonetheless, past findings suggest that it could be caused by the interaction of specific genes with environmental factors.