Lifeboat Foundation

Research by neuroscientists at the University of Chicago shows how short-term, working memory uses networks of neurons differently depending on the complexity of the task at hand.

The researchers used modern artificial intelligence (AI) techniques to train computational neural networks to solve a range of complex behavioral tasks that required storing information in short term memory. The AI networks were based on the biological structure of the brain and revealed two distinct processes involved in short-term memory. One, a “silent” process where the brain stores short-term memories without ongoing neural activity, and a second, more active process where circuits of neurons fire continuously.

The study, led by Nicholas Masse, Ph.D., a senior scientist at UChicago, and senior author David Freedman, Ph.D., professor of neurobiology, was published this week in Nature Neuroscience.

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Will Europe’s Human Brain Project simulate a human brain?

Opinion: Progress in deep learning research will come from the convergence of engineering and neuroscience.

Chemical engineers at UCLA have been demonstrating what they argue is scientific evidence that bunches of synthetically grown nanowires exhibit behaviors similar to that of memory in a living brain. Whether you believe their claim depends on what you think memory actually is.

Neuromorphic systems carry out robust and efficient neural computation using hardware implementations that operate in physical time. Typically they are event- or data-driven, they employ low-power, massively parallel hybrid analog/digital VLSI circuits, and they operate using the same physics of computation used by the nervous system. Although there are several forums for presenting research achievements in neuromorphic engineering, none are exclusively dedicated to this increasingly large research community. Either because they are dedicated to single disciplines, such as electrical engineering or computer science, or because they serve research communities which focus on analogous areas (such as biomedical engineering or computational neuroscience), but with fundamentally different goals and objectives. The mission of Neuromorphic Engineering is to provide a publication medium dedicated exclusively and specifically to this field. Topics covered by this publication include:  Analog and hybrid analog/digital electronic circuits for implementing neural processes, such as conductances, neurons, synapses, plasticity mechanisms, photoreceptors, cochleae, etc.  Neuromorphic circuits and systems for implementing real-time event-based neural processing architectures.  Hardware models of neural and sensorimotor processing systems, such as selective attention systems, coordinate transformation systems, auditory and/or visual processing systems, sensory fusion systems, etc.  Implementations of neural computational systems found in insects, birds, mammals, etc.  Embedded neuromorphic systems, including actuated or robotic platforms which process sensory signals and interact with the environment using event-based sensors and circuits. To ensure high quality and state-of-the-art material, publications should demonstrate experimental results, using physical implementations of neuromorphic systems, and possibly show the links between the artificial system and the neural/biological one they model.

Maybe we can’t keep packing transistors onto substrates the way Gordon Moore showed us how to do. So how about if we replaced those millions of transistors with components “inspired by the true story” of the brain?

A worldwide team of senior scientists and clinicians have come together to produce an editorial which indicates that certain microbes — a specific virus and two specific types of bacteria — are major.

A MIND reading brain computer chip has been announced at the World Intelligence Congress in China.

The breakthrough device is called Brain Talker and allows a person to control a computer with just their brainwaves.

Brain-computer interfaces (BCIs) are devices that have been designed to create simple communication between the human brain and computers.

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The double helix of dna and transferring for information and energy by torsion field in quantum beings.

Every human is a complex, multi-dimensional energy being.

THE HUMAN BIOFIELD DEFINED:

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