The COVID-19 pandemic is leading a Purdue University innovator to make changes as she works to provide new options for people with Parkinson's disease. Jessica Huber, a professor of Speech, Language, and Hearing Sciences and associate dean for research in Purdue's College of Health and Human Sciences, leads Purdue's Motor Speech Lab. Huber and her team are now doing virtual studies to evaluate speech disorders related to Parkinson's using artificial intelligence technology platforms. Huber and her team have been working to develop telepractice tools for the assessment and treatment of speech impairments like Parkinson's disease. They received a National Institutes of Health small business innovation and research grant to develop a telehealth platform to facilitate the provision of speech treatment with the SpeechVive device, which has received attention at the Annual Convention of the American Speech-Language-Hearing Association.
Drinking cocoa can increase your mental agility thanks to the presence of flavanols – chemicals that are abundant in cocoa beans. UK and US researchers found healthy adults performed better on difficult cognitive tasks if the participants had consumed a cocoa drink containing high levels of flavanols. After drinking flavanol-rich cocoa, participants produced a faster and greater increase in blood oxygenation in the frontal cortex – a brain region that plays a key role in cognition and decision-making – that helped them complete these tasks. Flavanols are antioxidants and are abundant in tea, red wine, blueberries, apples, pears, cherries, and peanuts, as well as in the seeds of the cacao tree – cocoa beans. By enriching supermarket cocoa with flavanols, food producers could help us increase the brain-boosting plant nutrient in our diet.
A simple eye exam combined with powerful artificial intelligence (AI) machine learning technology could provide early detection of Parkinson's disease, according to research being presented at the annual meeting of the Radiological Society of North America (RSNA). Parkinson's disease is a progressive disorder of the central nervous system that affects millions of people worldwide. Diagnosis is typically based on symptoms like tremors, muscle stiffness and impaired balance--an approach that has significant limitations. "The issue with that method is that patients usually develop symptoms only after prolonged progression with significant injury to dopamine brain neurons," said study lead author Maximillian Diaz, a biomedical engineering Ph.D. student at the University of Florida in Gainesville, Florida. "This means that we are diagnosing patients late in the disease process." Disease progression is characterized by nerve cell decay that thins the walls of the retina, the layer of tissue that lines the back of the eyeball.
People crave company when socially isolated -- such as amid lockdown -- in almost exactly the same way that a hungry individual longs for food, a study has concluded. US experts found that after ten hours of seclusion, people not only want company but also exhibit increased brain responses to pictures of social interactions. Social interactions are rewarding, the team said -- and related images (like smiling faces or people chatting) also engages the brain's dopamine-based reward system. The findings build on past work that found mice exhibited increased responses in the midbrain dopamine system when being social after a period of isolation. While this had suggested that the midbrain may play a role in feelings of social isolation, it had been unclear exactly whether the same would apply in humans.
Summary: When convolutional neural networks are trained under experimental conditions, they are decided by the brightness and color of a visual image in similar ways to the human visual system. A convolutional neural network is a type of artificial neural network in which the neurons are organized into receptive fields in a very similar way to neurons in the visual cortex of a biological brain. Today, convolutional neural networks (CNNs) are found in a variety of autonomous systems (for example, face detection and recognition, autonomous vehicles, etc.). This type of network is highly effective in many artificial vision tasks, such as in image segmentation and classification, along with many other applications. Convolutional networks were inspired by the behaviour of the human visual system, particularly its basic structure formed by the concatenation of compound modules comprising a linear operation followed by a non-linear operation.
We are living through one of the greatest of scientific endeavours – the attempt to understand the most complex object in the universe, the brain. Scientists are accumulating vast amounts of data about structure and function in a huge array of brains, from the tiniest to our own. Tens of thousands of researchers are devoting massive amounts of time and energy to thinking about what brains do, and astonishing new technology is enabling us to both describe and manipulate that activity. We can now make a mouse remember something about a smell it has never encountered, turn a bad mouse memory into a good one, and even use a surge of electricity to change how people perceive faces. We are drawing up increasingly detailed and complex functional maps of the brain, human and otherwise. In some species, we can change the brain's very structure at will, altering the animal's behaviour as a result. Some of the most profound consequences of our growing mastery can be seen in our ability to enable a paralysed person to control a robotic arm with the power of their mind.
A new machine-learning algorithm can successfully determine which specific behaviors--like walking and breathing--belong to which specific brain signal, and it has the potential to help the military maintain a more ready force. At any given time, people perform a myriad of tasks. All of the brain and behavioral signals associated with these tasks mix together to form a complicated web. Until now, this web has been difficult to untangle and translate. But researchers funded by the U.S. Army developed a machine-learning algorithm that can model and decode these signals, according to a Nov. 12 press release.
Bris tol My ers Squibb is turn ing to one of the star up starts in the ma chine learn ing world to go back to the draw ing board and come up with the dis ease mod els need ed to find drugs that can work against two of the tough est tar gets in the neu ro world. Daphne Koller's well-fund ed in sitro is get ting $70 mil lion in cash and near-term mile stones to use their ma chine learn ing plat form to cre ate in duced pluripo tent stem cell-de rived dis ease mod els for ALS and fron totem po ral de men tia. Then they'll use those in sights to start build ing new drugs for those two ail ments; a com plex, ground-up ap proach that has al ready won a close al liance with Gilead. Suc cess would trig ger up to $2 bil lion in mile stones, run ning a gamut of re search and com mer cial goals. "We be lieve that ma chine learn ing and da ta gen er at ed by nov el ex per i men tal plat forms of fer the op por tu ni ty to re think how we dis cov er and de sign nov el med i cines," said Richard Har g reaves, the chief of the neu ro group at Bris tol My ers, who made the leap from Cel gene.