Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: computing – Page 592

Virtual reality boosts brain rhythms crucial for neuroplasticity, learning and memory

This is interesting. 😃

A new discovery in rats shows that the brain responds differently in immersive virtual reality environments versus the real world. The finding could help scientists understand how the brain brings together sensory information from different sources to create a cohesive picture of the world around us. It could also pave the way for “virtual reality therapy” for learning and memory-related disorders ranging including ADHD, Autism, Alzheimer’s disease, epilepsy and depression.

Mayank Mehta, PhD, is the head of W. M. Keck Center for Neurophysics and a professor in the departments of physics, neurology, and electrical and computer engineering at UCLA. His laboratory studies a brain region called the hippocampus, which is a primary driver of learning and memory, including spatial navigation. To understand its role in learning and memory, the hippocampus has been extensively studied in rats as they perform spatial navigation tasks.

When rats walk around, neurons in this part of the brain synchronize their electrical activity at a rate of 8 pulses per second, or 8 Hz. This is a type of brain wave known as the “theta rhythm,” and it was discovered more than six decades ago.

Engineers make critical advance in quantum computer design

Quantum engineers from UNSW Sydney have removed a major obstacle that has stood in the way of quantum computers becoming a reality. They discovered a new technique they say will be capable of controlling millions of spin qubits—the basic units of information in a silicon quantum processor.

Until now, quantum computer engineers and scientists have worked with a proof-of-concept model of quantum processors by demonstrating the control of only a handful of qubits.

But with their latest research, published today in Science Advances, the team have found what they consider “the missing jigsaw piece” in the quantum computer architecture that should enable the control of the millions of qubits needed for extraordinarily complex calculations.

Classical variational simulation of the Quantum Approximate Optimization Algorithm

In this work, we introduce a classical variational method for simulating QAOA, a hybrid quantum-classical approach for solving combinatorial optimizations with prospects of quantum speedup on near-term devices. We employ a self-contained approximate simulator based on NQS methods borrowed from many-body quantum physics, departing from the traditional exact simulations of this class of quantum circuits.

We successfully explore previously unreachable regions in the QAOA parameter space, owing to good performance of our method near optimal QAOA angles. Model limitations are discussed in terms of lower fidelities in quantum state reproduction away from said optimum. Because of such different area of applicability and relative low computational cost, the method is introduced as complementary to established numerical methods of classical simulation of quantum circuits.

Classical variational simulations of quantum algorithms provide a natural way to both benchmark and understand the limitations of near-future quantum hardware. On the algorithmic side, our approach can help answer a fundamentally open question in the field, namely whether QAOA can outperform classical optimization algorithms or quantum-inspired classical algorithms based on artificial neural networks48,49,50.

The Amazing Brain: Visualizing Data to Understand Brain Networks

The NIH-led Brain Research through Advancing Innovative Neurotechnologies¼ (BRAIN) Initiative continues to teach us about the world’s most sophisticated computer: the human brain. This striking image offers a spectacular case in point, thanks to a new tool called Visual Neuronal Dynamics (VND).

VND is not a camera. It is a powerful software program that can display, animate, and analyze models of neurons and their connections, or networks, using 3D graphics. What you’re seeing in this colorful image is a strip of mouse primary visual cortex, the area in the brain where incoming sensory information gets processed into vision.

This strip contains more than 230,000 neurons of 17 different cell types. Long and spindly excitatory neurons that point upward (purple, blue, red, orange) are intermingled with short and stubby inhibitory neurons (green, cyan, magenta). Slicing through the neuronal landscape is a neuropixels probe (silver): a tiny flexible silicon detector that can record brain activity in awake animals [1].

/* */