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Unique mini-microscope provides insight into complex brain functions

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VIDEO: Researchers at the University of Minnesota College of Science and Engineering used a unique mini-microscope device to image complex brain activity of mice that show multiple areas of the brain.
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Credit: Rynes and Surinach, et al., Kodandaramaiah Lab, University of Minnesota
Researchers from the University of Minnesota Twin Cities College of Science and Engineering and Medical School have developed a unique head-mounted mini-microscope device that allows them to image complex brain functions of freely moving mice in real time over a period of more than 300 days.
The device, known as the mini-MScope, offers an important new tool for studying how neural activity from multiple regions of the outer part of the brain, called the cortex, contribute to behavior, cognition and perception. The groundbreaking study provides new insight into fundamental research that could improve human brain conditions such as concussions, autism, A ....

United States , University Of Minnesota , State Of Minnesota , Mathew Rynes , Vijay Rajendran , Gregoryw Johnson , Suhasa Kodandaramaiah , Judith Dominguez , Zahras Navabi , Leila Ghanbari , Samantha Linn , Majid Mohajerani , Mojtaba Nazari , Michael Laroque , Daniel Surinach , Biophotonics Congress , University Of Lethbridge , National Institutes Of Health , Xlife Sciences On , University Of Minnesota College Science , College Of Science , Brain Initiative , University Of Minnesota Medical School , Minnesota Informatics Institute , University Of Minnesota Department Biomedical Engineering , National Institute For Neurological Disorders ,

A statistical solution to processing very large datasets efficiently with memory limit

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IMAGE: Estimating the variance of the number of clusters and the sample size for which it is maximum can give us an estimate of the total number of clusters for the.
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Credit: Ryo Maezono from JAIST.
Ishikawa, Japan - Any high-performance computing should be able to handle a vast amount of data in a short amount of time an important aspect on which entire fields (data science, Big Data) are based. Usually, the first step to managing a large amount of data is to either classify it based on well-defined attributes or as is typical in machine learning cluster them into groups such that data points in the same group are more similar to one another than to those in another group. However, for an extremely large dataset, which can have trillions of sample points, it is tedious to even group data points into a single cluster without huge memory requirements. ....

Ryo Maezono , Keishu Utimula , University Of Tokyo , National Institute For Materials Science , Japan Advanced Institute Of Science , Big Data , Professor Ryo Maezono , Japan Advanced Institute , Advanced Theory , Information Science , National Institute , Materials Science , Chemistry Physics Materials Sciences , Mathematics Statistics , Technology Engineering Computer Science , பல்கலைக்கழகம் ஆஃப் டோக்கியோ , தேசிய நிறுவனம் க்கு பொருட்கள் அறிவியல் , பெரியது தகவல்கள் , தகவல் அறிவியல் , தேசிய நிறுவனம் , பொருட்கள் அறிவியல் , வேதியியல் இயற்பியல் பொருட்கள் அறிவியல் , கணிதம் புள்ளிவிவரங்கள் , தொழில்நுட்பம் பொறியியல் கணினி அறிவியல் ,

BrainGate: First human use of high-bandwidth wireless brain-computer interface

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IMAGE: A participant in the BrainGate clinical trial uses wireless transmitters that replace the cables normally used to transmit signals from sensors inside the brain.
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Credit: Braingate.ord
PROVIDENCE, R.I. [Brown University and Providence Veterans Affairs Medical Center] Brain-computer interfaces (BCIs) are an emerging assistive technology, enabling people with paralysis to type on computer screens or manipulate robotic prostheses just by thinking about moving their own bodies. For years, investigational BCIs used in clinical trials have required cables to connect the sensing array in the brain to computers that decode the signals and use them to drive external devices. ....

Brown School , United States , Pamela Garlick , Thomas Hosman , Betsy Reeves , Jessica Kelemen , John Ciancibello , Marco Vilela , Leigh Hochberg , David Brandman , Paymon Rezaii , Krishna Shenoy , Brian Franco , Blackrock Microsystems , Emad Eskandar , Sharlene Flesher , John Simeral , Arto Nurmikko , David Rosler , Jaimie Henderson , Wu Tsai Neurosciences Institute At Stanford , Brown School Of Engineering , Development Center , Brown Carney Institute For Brain Science , Va Rehabilitation Research , Mgh Deane Institute ,

New method uses device cameras to measure pulse, breathing rate and could help telehealth

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Telehealth has become a critical way for doctors to still provide health care while minimizing in-person contact during COVID-19. But with phone or Zoom appointments, it s harder for doctors to get important vital signs from a patient, such as their pulse or respiration rate, in real time.
A University of Washington-led team has developed a method that uses the camera on a person s smartphone or computer to take their pulse and respiration signal from a real-time video of their face. The researchers presented this state-of-the-art system in December at the Neural Information Processing Systems conference.
Now the team is proposing a better system to measure these physiological signals. This system is less likely to be tripped up by different cameras, lighting conditions or facial features, such as skin color. The researchers will present these findings April 8 at the ACM Conference on Health, Interference, and Learning. ....

Xuhai Xu , Shwetak Patel , Xin Liu , Josh Fromm , Ziheng Jiang , Daniel Mcduff At Microsoft Research , University Of Washington , Information School , Conference On Health , Melinda Gates Foundation , Allen School , Neural Information Processing Systems , Computer Science , Daniel Mcduff , Microsoft Research , Health Care Systems Services , Technology Engineering Computer Science , Multimedia Networking Interface Design , Software Engineering , Robotry Artificial Intelligence , க்ஷின் லியூ , ஜோஷ் ஃப்ராம் , டேனியல் மக்டஃப் இல் மைக்ரோசாஃப்ட் ஆராய்ச்சி , பல்கலைக்கழகம் ஆஃப் வாஷிங்டன் , தகவல் பள்ளி , மாநாடு ஆன் ஆரோக்கியம் ,

Researchers realize synthetic gauge fields in single optomechanical resonator

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IMAGE: (a-b) Multimode interaction in a single optomechanical resonator creates an extensible synthetic gauge field; (c-e) Responses of optical photons and phonons in the cavity under different synthetic magnetic field intensities..
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Credit: CHEN Yuan et al.
The research team led by Prof. GUO Guangcan and Dr. DONG Chunhua from the University of Science and Technology of China realized synthetic gauge fields in a single optomechanical resonator by controlling geometric phase with the multimode interaction in the micro-resonator.
By engineering a Hamiltonian, uncharged particles or bosonic excitations can acquire a path-dependent phase which realizes a synthetic magnetic field. Such synthetic gauge field can improve the precision of quantum many-body simulation and control over bosons. ....

University Of Science , Technology Of China , Physics Review , Chemistry Physics Materials Sciences , Atomic Molecular Particle Physics , Technology Engineering Computer Science , Research Development , Atomic Physics , Particle Physics , பல்கலைக்கழகம் ஆஃப் அறிவியல் , தொழில்நுட்பம் ஆஃப் சீனா , இயற்பியல் விமர்சனம் , வேதியியல் இயற்பியல் பொருட்கள் அறிவியல் , அணு மூலக்கூறு துகள் இயற்பியல் , தொழில்நுட்பம் பொறியியல் கணினி அறிவியல் , ஆராய்ச்சி வளர்ச்சி , அணு இயற்பியல் , துகள் இயற்பியல் ,