Collaborating Authors


FDA clears Synchron's brain-computer interface device for human trials


A company that makes an implantable brain-computer interface (BCI) has been given the go-ahead by the Food and Drug Administration to run a clinical trial with human patients. Synchron plans to start an early feasibility study of its Stentrode implant later this year at Mount Sinai Hospital, New York with six subjects. The company said it will assess the device's "safety and efficacy in patients with severe paralysis." Before such companies can sell BCIs commercially in the US, they need to prove that the devices work and are safe. The FDA will provide guidance for trials of BCI devices for patients with paralysis or amputation during a webinar on Thursday.

New York company gets jump on Elon Musk's Neuralink with brain-computer interface in clinical trials

Daily Mail - Science & tech

Elon Musk might be well positioned in space travel and electric vehicles, but the world's second-richest person is taking a backseat when it comes to a brain-computer interface (BCI). New York-based Synchron announced Wednesday that it has received approval from the Food and Drug Administration to begin clinical trials of its Stentrode motor neuroprosthesis - a brain implant it is hoped could ultimately be used to cure paralysis. The FDA approved Synchron's Investigational Device Exemption (IDE) application, according to a release, paving the way for an early feasibility study of Stentrode to begin later this year at New York's Mount Sinai Hospital. New York-based Synchron announced Wednesday that it has received FDA approval to begin clinical trials of Stentrode, its brain-computer interface, beating Elon Musk's Neuralink to a crucial benchmark. The study will analyze the safety and efficacy of the device, smaller than a matchstick, in six patients with severe paralysis. Meanwhile, Musk has been touting Neuralink, his brain-implant startup, for several years--most recently showing a video of a monkey with the chip playing Pong using only signals from its brain.

Mind and Matter: Modeling the Human Brain With Machine Learning - Neuroscience News


Summary: Researchers created a new human brain model using machine learning-based optimization of required user profile information. We all like to think that we know ourselves best, but, given that our brain activity is largely governed by our subconscious mind, it is probably our brain that knows us better! While this is only a hypothesis, researchers from Japan have already proposed a content recommendation system that assumes this to be true. Essentially, such a system makes use of its user's brain signals (acquired using, say, an MRI scan) when exposed to particular content and eventually, by exploring various users and contents, builds up a general model of brain activity. "Once we obtain the'ultimate' brain model, we should be able to perfectly estimate the brain activity of a person exposed to a specific content," says Prof. Ryoichi Shinkuma from Shibaura Institute of Technology, Japan, who was a part of the team that came up with the idea.

Astrocytes control the critical period of circuit wiring


One of the most extraordinary qualities of the mammalian nervous system is its ability to change with experience and throughout its life span. Mammalian brain plasticity is thought to be mainly mediated by neurons. Increased plasticity during specific windows of time during development called “critical periods” allows neuronal circuitry to be shaped. How this phase ends, however, has not been clear. On page 77 of this issue, Ribot et al. ([ 1 ][1]) show that an unsuspected cellular player—astrocytes—control when experience-dependent wiring of brain circuits is permitted in the developing primary visual cortex (V1). This finding points to possible similar roles of astrocytes or other nonneuronal cells in other neural circuits. The primary visual cortex has long served as a model system to study brain plasticity, since the pioneering work by Hubel and Wiesel in the 1960s, when they showed that the V1 circuit is powerfully shaped by the visual experience during development ([ 2 ][2]). Their seminal studies in kittens revealed that, in response to transient eyelid closure to provoke monocular deprivation (blocking visual stimulation through one eye), the V1 circuits remodel to shift the preference of cortical neurons for the eye that remains open. This results in the so-called ocular dominance ([ 3 ][3], [ 4 ][4]). Notably, this influence of sensory activity on the organization of neural circuits is restricted to a critical period ([ 4 ][4]), which highlights the importance of early life experiences for the optimal functioning of the brain. Anomalous critical periods are also largely detrimental and associated with various neurodevelopmental disorders ([ 5 ][5]). Hence, how the critical period of ocular dominance plasticity is opened and closed is of fundamental importance for understanding brain development and function. A new and fruitful development in this area of investigation has been the mouse model ([ 6 ][6]). Ribot et al. report that the ocular dominance plasticity in mice is determined by astrocytes. These nonneuronal cells have long been associated with housekeeping functions in the brain, such as regulation of the extracellular ionic environment, reuptake and recycling of neurotransmitters, and structural support ([ 7 ][7]). However, more recently, astrocytes have also been shown to control synapse formation and connectivity ([ 8 ][8]), synaptic transmission and plasticity ([ 9 ][9]), and even animal behavior ([ 10 ][10]). Ribot et al. found that grafting immature astrocytes from newborn mice in the V1 of adult mice enhanced the ocular dominance plasticity that occurred after visual stimulation of one eye. The ∼200 genes differentially expressed in immature and mature astrocytes include the gene encoding connexin 30 (Cx30). Cx30 is a subunit of a gap junction channel—a specialized intercellular connection between cells. The authors observed that the expression of Cx30 in the V1 peaked approximately when the critical period for ocular dominance plasticity ended. This prompted the authors to assess plasticity in a mouse model genetically engineered to lack Cx30. Although ocular dominance plasticity peaked at about postnatal day 28 (P28) in wild-type mice, it continued to increase in mice lacking Cx30 until P50, indicating impairment in the closure of the critical period. ![Figure][11] Astrocytes influence plasticity During development of the mammalian brain's primary visual cortex, astrocytes regulate the so-called critical period during which plasticity allows the neural network to form. This depends on a signaling pathway controlled by connexin 30. GRAPHIC: C. BICKEL/ SCIENCE Electrophysiological recordings of excitatory and inhibitory synaptic transmission in cortical slices revealed that mice lacking Cx30 had reduced inhibitory transmission. Moreover, perineuronal nets were smaller in these animals. Perineuronal nets are a highly organized form of extracellular matrix that contains chondroitin sulfate proteoglycans. They tend to coalesce around inhibitory neurons ([ 11 ][12]) and are thought to contribute to the closure of ocular dominance plasticity ([ 12 ][13]). Altogether, these results indicate that astrocytes control the visual critical period by promoting the maturation of inhibitory circuits through signaling pathways that involve Cx30. What about a relevant signaling pathway associated with Cx30? Ribot et al. discovered that Cx30 is physically associated with the protein-phosphorylating enzyme ROCK2 (Rho-associated coiled-coil–containing protein kinase 2). The expression of the small guanosine triphosphatase (GTPase) RhoA, ROCK2, and the extracellular matrix–degrading enzyme matrix metalloproteinase 9 (MMP9) were all increased by either monocular deprivation or the lack of Cx30, indicating a common signaling pathway. The authors therefore propose that astrocytes control the visual critical period by promoting the maturation of inhibitory circuits through signaling pathways that involve Cx30 and inactivation of RhoA and MMP9. This promotes the formation of perineuronal nets, the enhancement of inhibitory transmission, and the closure of ocular dominance plasticity (see the figure). Cx30 is a member of a large family of proteins that form intercellular channels that enable the direct transfer of ions and molecules between adjacent cells, but whether a Cx30-RhoA-ROCK2 signaling pathway involves ion and molecule permeation into astrocytes remains unknown. Moreover, several human deafness diseases have been associated with Cx30 mutations ([ 13 ][14]). It is unknown whether any changes in critical-period plasticity are found in these patients. Notably, astrocytes in the fruit fly Drosophila melanogaster regulate the maturation of the motor circuit and are essential for proper critical-period closure ([ 14 ][15]). In this case, interaction between the cell adhesion proteins neuroligin and neurexin is the likely signaling pathway. Thus, there may be a diversity of molecular and signaling pathways in which astrocytes influence the use-dependent plasticity of neural circuits during development. 1. [↵][16]1. J. Ribot et al ., Science 373, 77 (2021). [OpenUrl][17][Abstract/FREE Full Text][18] 2. [↵][19]1. D. M. Hubel, 2. T. N. Wiesel , Brain and Visual Perception: The Story of a 25-Year Collaboration (Oxford Univ. Press, 2004). 3. [↵][20]1. D. H. Hubel, 2. T. N. Wiesel , J. Physiol. 206, 419 (1970). 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Deep Probabilistic Decision Learning Returns Perfect Flow to Operations


FlowOps enables optimal experience, predictions and decisions in the operations of factories and supply chains. In human brains, there are three key learning functions related to how we sense, predict and decide. Findings in computational neuroscience [1, 2] suggest that different parts of brain areas play a distinct but connected role in each function. These can be equated with the three Explainable AI (XAI) engines in's The interplay between deep learning and probabilistic learning are similar to a human brain's thinking fast and slow like in Kahneman's System 1 and System 2. System 1 is a fast, intuitive, heuristic, deterministic, differentiable, and more affective mind, whereas System 2 is a slow, deliberate, logical, probabilistic, integrating, and more cognitive mind. Deep learning (Sentinel) enables fast, scalable, and associative pattern detections from high-dimensional, noisy and temporally correlated data, using differential optimizations on flexible functions with deterministic model parameters.

White matter and human behavior


One of the most enduring themes in human neuroscience is the association of higher brain functions with gray matter. In particular, the cerebral cortex—the gray matter of the brain's surface—has been the primary focus of decades of work aiming to understand the neurobiological basis of cognition and emotion. Yet, the cerebral cortex is only a few millimeters thick, so the relative neglect of the rest of the brain below the cortex has prompted the term “corticocentric myopia” ([ 1 ][1]). Other regions relevant to behavior include the deep gray matter of the basal ganglia and thalamus, the brainstem and cerebellum, and the white matter that interconnects all of these structures. On page 1304 of this issue, Zhao et al. ([ 2 ][2]) present compelling evidence for the importance of white matter by demonstrating genetic influences on structural connectivity that invoke a host of provocative clinical implications. Insight into the importance of white matter in human behavior begins with its anatomy ([ 3 ][3]–[ 5 ][4]) (see the figure). White matter occupies about half of the adult human brain, and some 135,000 km of myelinated axons course through a wide array of tracts to link gray matter regions into distributed neural networks that serve cognitive and emotional functions ([ 3 ][3]). The human brain is particularly well interconnected because white matter has expanded more in evolution than gray matter, which has endowed the brain of Homo sapiens with extensive structural connectivity ([ 6 ][5]). The myelin sheath, white matter's characteristic feature, appeared late in vertebrate evolution and greatly increased axonal conduction velocity. This development enhanced the efficiency of distributed neural networks, expanding the transfer of information throughout the brain ([ 5 ][4]). Information transfer serves to complement the information processing of gray matter, where neuronal cell bodies, synapses, and a variety of neurotransmitters are located ([ 5 ][4]). The result is a brain with prodigious numbers of both neurons and myelinated axons, which have evolved to subserve the domains of attention, memory, emotion, language, perception, visuospatial processing, executive function ([ 5 ][4]), and social cognition ([ 7 ][6]). White matter is important in clinical medicine, and knowledge of its normal structure and function informs the clinical interpretation of acquired brain lesions to which it is vulnerable. Because all brain regions are interconnected by white matter, an understanding of the genetic architecture of normal tracts is crucial for advancing the neurobiology of human behavior ([ 2 ][2]). Combined with data from major initiatives such as the Human Connectome Project, launched in 2010 by the National Institutes of Health with the goal of mapping all the long-distance connections in the brain ([ 8 ][7]), the role of genetics is pivotal in building a more complete understanding of normal white matter and its connectivity. ![Figure][8] White matter tracts Select white matter tracts in the human brain are shown. These fibers connect gray matter regions to mediate complex human behaviors. The corpus callosum connects the cerebral hemispheres to enable cognitive and emotional information transfer, the corona radiata contributes to motor functions, and the posterior thalamic radiation is involved in visual processing. GRAPHIC: V. ALTOUNIAN/ SCIENCE , (DATA) CHENG ET AL. ([ 5 ][4]) AND RESEARCH IMAGING INSTITUTE, UTHSCSA Damage to white matter can disrupt any brain function and produce profound clinical consequences. Neurology has long appreciated the effects of such damage on sensory and motor function, but more-recent work has amply demonstrated the capacity of white matter lesions to affect cognition and emotion ([ 4 ][9], [ 5 ][4], [ 9 ][10]–[ 11 ][11]). White matter pathology with neurobehavioral consequences can occur in a wide variety of acquired and genetic disorders affecting myelin and has also been recognized to occur in neurodegenerative disorders such as Alzheimer's disease (AD) that have long been thought to originate in cortical gray matter ([ 4 ][9], [ 5 ][4]). A particularly instructive category of white matter disorder is toxic leukoencephalopathy (TL), in which toxic white matter injury can produce devastating clinical sequelae ([ 9 ][10]). The best example of TL is toluene leukoencephalopathy, in which long-term abusers of paint fumes sustain diffuse damage to lipid-rich myelin, owing to the lipophilicity of toluene, and often develop a disabling cognitive syndrome called white matter dementia ([ 10 ][12]). As toluene abuse causes widespread myelin loss while sparing the gray matter, this disorder illustrates the profound cognitive effects of selective white matter damage ([ 9 ][10]–[ 11 ][11]). Zhao et al. add to our knowledge of white matter with an analysis of genetic and neuroimaging data from nearly 44,000 individuals within five data resources. Focusing on 21 predefined tracts, they identified 109 loci associated with white matter microstructure. Genetic correlations were observed between white matter microstructure and a wide spectrum of diseases, and genetic variation was found to alter the function of oligodendrocytes—the glial cells responsible for myelination. Among the many diseases identified was AD, adding to mounting evidence that white matter dysfunction may be key to its pathogenesis. An influential “myelin model” postulates early white matter involvement in late-onset disease ([ 12 ][13]), and, even in early-onset autosomal dominant AD, microstructural white matter changes have been observed to precede symptom onset ([ 13 ][14]). Other neuropsychiatric conditions also implicate white matter, including schizophrenia, depression, attention deficit hyperactivity disorder, autism, amyotrophic lateral sclerosis, glioma, and stroke. Relevant to both stroke and AD, white matter hyperintensities often seen on magnetic resonance imaging scans of older people ([ 5 ][4]) have been associated with a locus on chromosome 17 ([ 14 ][15]). Zhao et al. found that many commonly used centrally-active medications exert effects on genes associated with white matter microstructure—an observation that may lead to improvements in the treatment of many brain diseases. The pharmacology of drugs used for neuropsychiatric disorders is not well understood, and knowledge of the interactions of these drugs with white matter neurobiology may substantially bolster the clinician's armamentarium. The emerging recognition of white matter and its contribution to human behavior will advance medicine as well as neuroscience. Considering both environmental and genetic factors clarifies the structure and function of normal and abnormal tracts, and this knowledge promises in turn to improve the diagnosis and treatment of people in whom white matter dysfunction may be disturbing neurobehavioral capacity. 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Neurable Introduces 'Enten', Their First Pair of Headphones Capable of Brain-Computer Interface Headphones (BCI)


Neurable had revealed plans for brain-computer interface (BCI) headphones. Neurable creates brain-enabled control directed towards virtual and augmented reality. The headphones are similar to previous products designed to learn from human movement and predict intent. This idea was proposed by the product lead, Dr. Ramses Alcaide. He was inspired by his uncle's successful engineering of his prosthetic legs following a horrific automobile accident. After the incident, Alcaide realized the usefulness of technology that could assist users with physical mobility.

Is the Brain a Useful Model for Artificial Intelligence?


In the summer of 2009, the Israeli neuroscientist Henry Markram strode onto the TED stage in Oxford, England, and made an immodest proposal: Within a decade, he said, he and his colleagues would build a complete simulation of the human brain inside a supercomputer. They'd already spent years mapping the cells in the neocortex, the supposed seat of thought and perception. "It's a bit like going and cataloging a piece of the rain forest," Markram explained. "How many trees does it have? What shapes are the trees?"

Pinaki Laskar on LinkedIn: #neuroscience #machinelearning #artificialintelligence


AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner Studies on brain-computer interfaces have demonstrated the ability to execute mostly limited, pre-established actions such as two-dimensional cursor movement on a computer screen or typing a specific letter of the alphabet. The typical solution uses a computer system to interpret brain-signals linked with stimuli to model mental states. Seeking to create a more flexible, adaptable system, the researchers created an artificial system that can imagine and output what a person is visualising based on brain signals. The researchers report that their neuro-adaptive generative modeling approach is "a new paradigm that may strongly impact experimental psychology and cognitive #neuroscience. Researchers used a combination of a generative neural network with neuro-adaptive brain interfacing to create a new BCI paradigm.

Release of stem cells from quiescence reveals gliogenic domains in the adult mouse brain


Neural stem cells in the adult mouse brain can generate both neurons and glia. Exactly where each stem cell is positioned can determine what type of neurons it generates. Delgado et al. show that neural stem cells are also choosy about what sorts of glia they make and when (see the Perspective by Baldwin and Silver). Injury or selective deletion of platelet-derived growth factor receptor β (PDGFRβ) from the stem cells kicked them into overdrive and revealed their selectivity with respect to gliogenesis. An unusual type of glial progenitor cell, intraventricular oligodendrocyte progenitors, are found nestled between the cilia of ependymal cells derived from tight clusters of PDGFRβ-expressing stem cells. Science , abg8467, this issue p. [1205][1]; see also abj1139, p. [1151][2] Quiescent neural stem cells (NSCs) in the adult mouse ventricular-subventricular zone (V-SVZ) undergo activation to generate neurons and some glia. Here we show that platelet-derived growth factor receptor beta (PDGFRβ) is expressed by adult V-SVZ NSCs that generate olfactory bulb interneurons and glia. Selective deletion of PDGFRβ in adult V-SVZ NSCs leads to their release from quiescence, uncovering gliogenic domains for different glial cell types. These domains are also recruited upon injury. We identify an intraventricular oligodendrocyte progenitor derived from NSCs inside the brain ventricles that contacts supraependymal axons. Together, our findings reveal that the adult V-SVZ contains spatial domains for gliogenesis, in addition to those for neurogenesis. These gliogenic NSC domains tend to be quiescent under homeostasis and may contribute to brain plasticity. [1]: /lookup/doi/10.1126/science.abg8467 [2]: /lookup/doi/10.1126/science.abj1139