Nature Knows and Psionic Success

Credit: CC0 Public Domain In a significant advance, UC San Francisco Weill Institute for Neurosciences researchers working towards a brain-controlled prosthetic limb have shown that machine learning techniques helped an individual with paralysis learn to control a computer cursor using their brain activity without requiring extensive daily retraining, which has been a requirement of all past brain-computer interface (BCI) efforts.

“The BCI field has made great progress in recent years, but because existing systems have had to be reset and recalibrated each day, they haven’t been able to tap into the brain ‘s natural learning processes. It’s like asking someone to learn to ride a bike over and over again from scratch,” said study senior author Karunesh Ganguly, MD, Ph.D., an associate professor in the UCSF Department of Neurology. “Adapting an artificial learning system to work smoothly with the brain’s sophisticated long-term learning schemas is something that’s never been shown before in a person with paralysis.”

The achievement of “plug and play” performance demonstrates the value of so-called ECoG electrode arrays for BCI applicartions. An ECoG array comprises a pad of electrodes about the size of a post-it note that is surgically placed on the surface of the brain. They allow long-term, stable recordings of neural activity and have been approved for seizure monitoring in epilepsy patients. In contrast, past BCI efforts have used “pin-cushion” style arrays of sharp electrodes that penetrate the brain tissue for more sensitive recordings but tend to shift or lose signal over time. In this case, the authors obtained investigational device approval for long-term chronic implantation of ECoG arrays in paralyzed subjects to test their safety and efficacy as long-term, stable BCI implants.

In their new paper, published September 7, 2020 in Nature Biotechnology , Ganguly’s team documents the use of an ECoG electrode array in an individual with paralysis of all four limbs (tetraplegia). The participant is also enrolled in a clinical trial designed to test the use of ECoG arrays to allow paralyzed patients to control a prosthetic arm and hand, but in the new paper, the participant used the implant to control a computer cursor on a screen.

The researchers developed a BCI algorithm that uses machine learning to match brain activity recorded by the ECoG electrodes to the user’s desired cursor movements. Initially, the researchers followed the standard practice of resetting the algorithm each day. The participant would begin by imagining specific neck and wrist movements while watching the cursor move across the screen. Gradually the computer algorithm would update itself to match the cursor’s movements to the brain activity this generated, effective passing control of the cursor over to the user. However, starting this process over every day put a severe limit on the level of control that could be achieved. It could take hours to master control of the device, and some days the participant had to give up altogether.

The researchers then switched to allow the algorithm to continue updating to match the participant’s brain activity without resetting it each day. They found that the continued interplay between brain signals and the machine learning-enhanced algorithm resulted in continuous improvements in performance over many days. Initially there was a little lost ground to make up each day, but soon the participant was able to immediately achieve top level performance.

“We found that we could further improve learning by making sure that the algorithm wasn’t updating faster than the brain could follow—a rate of about once every 10 seconds,” said Ganguly, a practicing neurologist with UCSF Health and the San Francisco Veterans Administration Medical Center’s Neurology & Rehabilitation Service. “We see this as trying to build a partnership between two learning systems—brain and computer—that ultimately lets the artificial interface become an extension of the user, like their own hand or arm.”

Over time, the participant’s brain was able to amplify patterns of neural activity it could use to most effectively drive the artificial interface via the ECoG array, while eliminating less effective signals—a pruning process much like how the brain is thought to learn any complex task, the researcher say. They observed that the participant’s brain activity seemed to develop an ingrained and consistent mental “model” for controlling the BCI interface, something that had never occurred with daily resetting and recalibration. When the interface was reset after several weeks of continuous learning, the participant rapidly re-established the same patterns of neural activity for controlling the device—effectively retraining the algorithm to its former state.

“Once the user has established an enduring memory of the solution for controlling the interface, there’s no need for resetting,” Ganguly said. “The brain just rapidly convergences back to the same solution.”

Eventually, once expertise was established, the researchers showed they could turn off the algorithm’s need to update itself altogether, and the participant could simply begin using the interface each day without any need for retraining or recalibration. Performance did not decline over 44 days in the absence of retraining, and the participant could even go days without practicing and see little decline in performance. The establishment of stable expertise in one form of BCI control (moving the cursor) also allowed researchers to begin “stacking” additional learned skills—such as “clicking” a virtual button—without loss of performance.

Such immediate “plug and play” BCI performance has long been a goal in the field, but has been out of reach because the “pincushion-style” electrodes used by most researchers tend to move over time, changing the signals seen by each electrode. Also, because these electrodes penetrate brain tissue, the immune system tends to reject them, gradually impairing their signal. ECoG arrays are less sensitive than these traditional implants, but their long-term stability appears to compensate for this shortcoming. The stability of ECoG recordings may be even more important for long-term control of more complex robotic systems such as artificial limbs, a key goal of the next phase of Ganguly’s research.

“We’ve always been mindful of the need to design technology that doesn’t end up in a drawer, so to speak, but which will actually improve the day-to-day lives of paralyzed […]

Read more at medicalxpress.com

In a significant advance, UC San Francisco Weill Institute for Neurosciences researchers working towards a brain-controlled prosthetic limb have shown that machine learning techniques helped an individual with paralysis learn to control a computer cursor using their brain activity without requiring extensive daily retraining, which has been a requirement of all past brain-computer interface (BCI) efforts. The BCI field has made great progress in recent years, but because existing systems have had to be reset and recalibrated each day, they haven’t been able to tap into the brain’s natural learning processes. It’s like asking someone to learn to ride a bike over and over again from scratch. Adapting an artificial learning system to work smoothly with the brain’s sophisticated long-term learning schemas is something that’s never been shown before in a person with paralysis.” Karunesh Ganguly, MD, PhD, Study Senior Author, Associate Professor, UCSF Department of Neurology The achievement of “plug and play” performance demonstrates the value of so-called ECoG electrode arrays for BCI applicartions. An ECoG array comprises a pad of electrodes about the size of a post-it note that is surgically placed on the surface of the brain. They allow long-term, stable recordings of neural activity and have been approved for seizure monitoring in epilepsy patients. In contrast, past BCI efforts have used “pin-cushion” style arrays of sharp electrodes that penetrate the brain tissue for more sensitive recordings but tend to shift or lose signal over time. In this case, the authors obtained investigational device approval for long-term chronic implantation of ECoG arrays in paralyzed subjects to test their safety and efficacy as long-term, stable BCI implants.

In their new paper, published September 7, 2020 in Nature Biotechnology , Ganguly’s team documents the use of an ECoG electrode array in an individual with paralysis of all four limbs (tetraplegia). The participant is also enrolled in a clinical trial designed to test the use of ECoG arrays to allow paralyzed patients to control a prosthetic arm and hand, but in the new paper, the participant used the implant to control a computer cursor on a screen.

The researchers developed a BCI algorithm that uses machine learning to match brain activity recorded by the ECoG electrodes to the user’s desired cursor movements. Initially, the researchers followed the standard practice of resetting the algorithm each day. The participant would begin by imagining specific neck and wrist movements while watching the cursor move across the screen. Gradually the computer algorithm would update itself to match the cursor’s movements to the brain activity this generated, effective passing control of the cursor over to the user. However, starting this process over every day put a severe limit on the level of control that could be achieved. It could take hours to master control of the device, and some days the participant had to give up altogether.

The researchers then switched to allow the algorithm to continue updating to match the participant’s brain activity without resetting it each day. They found that the continued interplay between brain signals and the machine learning-enhanced algorithm resulted in continuous improvements in performance over many days. Initially there was a little lost ground to make up each day, but soon the participant was able to immediately achieve top level performance.

“We found that we could further improve learning by making sure that the algorithm wasn’t updating faster than the brain could follow — a rate of about once every 10 seconds,” said Ganguly, a practicing neurologist with UCSF Health and the San Francisco Veterans Administration Medical Center’s Neurology & Rehabilitation Service. “We see this as trying to build a partnership between two learning systems — brain and computer — that ultimately lets the artificial interface become an extension of the user, like their own hand or arm.”

Over time, the participant’s brain was able to amplify patterns of neural activity it could use to most effectively drive the artificial interface via the ECoG array, while eliminating less effective signals — a pruning process much like how the brain is thought to learn any complex task, the researcher say. They observed that the participant’s brain activity seemed to develop an ingrained and consistent mental “model” for controlling the BCI interface, something that had never occurred with daily resetting and recalibration. When the interface was reset after several weeks of continuous learning, the participant rapidly re-established the same patterns of neural activity for controlling the device — effectively retraining the algorithm to its former state.

“Once the user has established an enduring memory of the solution for controlling the interface, there’s no need for resetting,” Ganguly said. “The brain just rapidly convergences back to the same solution.”

Eventually, once expertise was established, the researchers showed they could turn off the algorithm’s need to update itself altogether, and the participant could simply begin using the interface each day without any need for retraining or recalibration. Performance did not decline over 44 days in the absence of retraining, and the participant could even go days without practicing and see little decline in performance. The establishment of stable expertise in one form of BCI control (moving the cursor) also allowed researchers to begin “stacking” additional learned skills — such as “clicking” a virtual button — without loss of performance.

Such immediate “plug and play” BCI performance has long been a goal in the field, but has been out of reach because the “pincushion-style” electrodes used by most researchers tend to move over time, changing the signals seen by each electrode. Also, because these electrodes penetrate brain tissue, the immune system tends to reject them, gradually impairing their signal. ECoG arrays are less sensitive than these traditional implants, but their long-term stability appears to compensate for this shortcoming. The stability of ECoG recordings may be even more important for long-term control of more complex robotic systems such as artificial limbs, a key goal of the next phase of Ganguly’s research.

“We’ve always been mindful of the need to design technology that doesn’t end up in a drawer, so to speak, but which will […]

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Scientists are getting better at using machines to decode electrical signals coming from the brain, but a new “plug-and-play” device represents a significant step forward Machines that attach to the brain and decode its activity promise to open up all kinds of medical possibilities, potentially allowing for improved screening of Alzheimer’s or the monitoring of internal organs . One of their more promising applications involves allowing sufferers of paralysis to regain control of prosthetic devices and limbs via their brain signals, something a team from the University of California, San Francisco (UCSF) has now demonstrated with a first-of-a-kind plug-and-play device.

These types of machines are known as brain-computer interfaces (BCIs), and there are quite a few under development that have shown some promising capabilities over the past few years. In their various forms, these devices can be implanted in the brain and, powered by advanced algorithms, turn its electrical signals into control inputs for all kinds of devices, from prosthetic limbs , to complete exoskeletons and even drones .

The new technology developed at UCSF could mark a significant step forward in this field of research, with the team focusing on the software that translates brain activity into action. This machine learning algorithm was trained to track a paralyzed user’s imagined movements of the neck or wrist, as they watched a computer cursor make its way across a screen.

To begin with, this algorithm had to be reset each day, with the software gradually learning to match the user’s desired motions with the actual movement of the cursor on screen, eventually enabling them to control it. But this could take hours of experimentation each day, so the scientists began to explore other options.

Some tweaks to the algorithm enabled it to continue learning about the user’s brain activity and desired movements, without resetting and starting from scratch each day. The team found that this approach enabled the algorithm to better itself each day on an ongoing basis, and eventually meant that the user was able to plug in and begin using it to great effect right away. Steve Babuljak Senior author Karunesh Ganguly in the lab during previous research “We found that we could further improve learning by making sure that the algorithm wasn’t updating faster than the brain could follow – a rate of about once every 10 seconds,” says Karunesh Ganguly, a practicing neurologist with UCSF Health. “We see this as trying to build a partnership between two learning systems – brain and computer – that ultimately lets the artificial interface become an extension of the user, like their own hand or arm.”

The BCI used in these experiments is known as an ECoG array, which is a pad of electrodes around the size of a Post-it note that is surgically implanted on the surface of the brain. The researchers obtained special approval to implant it in paralyzed patients on a long-term basis for the purpose of their experiments, and found that over time, the users’ brains were optimizing their activity to control the BCI, without the need for daily recalibration.

“Once the user has established an enduring memory of the solution for controlling the interface, there’s no need for resetting,” says study senior author Karunesh Ganguly. “The brain just rapidly convergences back to the same solution.”

With enough work, the researchers found they could actually switch off the algorithm’s auto-updating feature and the user could simply plug in and start using it each day. Even without any daily calibration, the performance did not decline over a 44-day period of use, with the user also able go several days without using it and only experience a small decline in performance.

“The BCI field has made great progress in recent years, but because existing systems have had to be reset and recalibrated each day, they haven’t been able to tap into the brain’s natural learning processes. It’s like asking someone to learn to ride a bike over and over again from scratch,” says Ganguly. “Adapting an artificial learning system to work smoothly with the brain’s sophisticated long-term learning schemas is something that’s never been shown before in a paralyzed person.”

The research was published in the journal Nature Biotechnology .

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( Natural News ) Prenatal exposure to organophosphate pesticides, a kind of pesticide considered toxic to humans, has been linked to impaired cognition and significant changes in the brain .

In a major breakthrough, scientists from the University of California, Berkeley (UCB) and Stanford University found that teenagers exposed in utero to organophosphate pesticides demonstrated altered brain activities during tasks that required executive control.

Sharon Sagiv, an assistant professor of disease and environmental health at UCB and the study’s lead author, said that their findings offer insight into the impact of organophosphate pesticides on the brain.

Sagiv and her colleagues are also the first to use advanced brain imaging techniques to demonstrate that exposure in utero to the said toxic chemicals can change brain activities.

Their findings appeared online in the journal Proceedings of the National Academy of Sciences of the United States of America (PNAS). Prenatal pesticide exposure changes the brain

Despite breakthroughs in brain science, the potential impact of pesticides on neurodevelopment is still unclear. To this end, Sagiv and her colleagues used functional near-infrared imaging (fNIRS) to monitor blood circulation in the brains of 95 teenagers born and raised in California’s Salinas Valley.

The use of organophosphate pesticides in Salinas Valley, one of California’s major valleys and most productive agricultural regions, is common practice. This renders the cohort a relevant group to examine for the potential effects of organophosphate pesticide exposure on the brain.

The participants had also been part of an earlier phase of the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) study. This is a longitudinal birth cohort study assessing the possible effects of pesticide exposure and other environmental factors on children’s health and neurodevelopment.

UCB scientists initiated the CHAMACOS study more than 20 years ago. The findings of their earlier research had linked prenatal organophosphate exposure to attention problems and a low intelligence quotient in children.

For this recent second phase, Sagiv and her colleagues used fNIRS to measure cerebral changes as the participants engaged in various tasks that required executive function, attention, social cognition and language comprehension.

They also utilized data from the California Pesticide Use Reporting program to estimate the proximity of the participants’ homes to pesticide-treated sites.

Upon assessing these data, they found that participants with higher prenatal organophosphate pesticide exposure in utero had less blood flow in their prefrontal cortex than their peers during tasks that required cognitive flexibility . This refers to the ability to switch between thinking about two different concepts or to think about multiple concepts at once.

However, the same participants demonstrated greater blood flow to their parietal and temporal lobes than their peers when engaged in tasks that tested memory retrieval, or the process of remembering information stored in long-term memory.

Brenda Eskenazi, a professor of public health at UCB and a member of the research team, said that fNIRS and neuroimaging afforded them insight into the potential impact of prenatal organophosphate pesticide exposure on the brain . Similar patterns in other brain conditions

However, their findings offered no clear explanation as to how organophosphate pesticide exposure led to reduced blood flow in some regions, but greater blood flow in others during different cognitive tasks.

That being said, the patterns are not unique to organophosphate pesticide exposure. Similar patterns are apparent in other conditions that affect the brain, including Type 1 diabetes , Parkinson’s disease and Alzheimer’s disease , according to Allan Reiss, the study’s co-author and a professor of behavioral sciences at Stanford University .

Reiss also speculated that the increase in blood flow could mean that the brain is utilizing more neural resources to address deficiencies in certain areas as a result of long-term or prenatal organophosphate pesticide exposure.

Therefore, further studies might help shed light on the mechanisms behind the effects of organophosphate pesticide exposure on neurodevelopment. (Related: DDT pesticide exposure during pregnancy now scientifically linked to autism .)

Sagiv and her colleagues plan to repeat the brain imaging experiments on a larger cohort to determine if the patterns hold.

Read more articles about the harmful effects of pesticide exposure at Pesticides.news .

Sources include:

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SANTA MONICA, Calif., Sept. 3, 2020 /PRNewswire/ — Problems with failing memory are common for many individuals as they grow older, and is particularly characteristic of patients with Alzheimer’s disease. Research shows that aging-related cognitive decline may be affected by Omega-3 levels and the health of cell membranes. Certain nutritional supplements developed to target Omega-3 and plasmalogen levels have shown promise in supporting brain health among older adults.

Plasmalogens are unique lipid molecules that are necessary for optimal neurological health and performance. Plasmalogen levels decrease with age as the body is no longer able to make enough to keep up with demand; this phenomenon appears to be amplified in degenerative diseases such as Alzheimer’s. While it is not possible to replenish plasmalogens through diet alone, supplementation involving Omega-3 and DHA may help boost plasmalogen levels.

ProdromeSciences has developed a 100% vegan and all-natural Omega-3 nutritional supplement oil, ProdromeNeuro. ProdromeNeuro is specifically designed to elevate Omega-3 plasmalogens, support cellular function, and help restore, maintain, and optimize neural membranes. The first human trial of this supplement successfully demonstrated increased Omega-3 plasmalogen levels in all six subjects at 24-hours post-consumption ( p <0.001). On average, these participants yielded 24-hour plasmalogen levels at 180% of baseline. No adverse reactions were observed.

The Regenesis Project, a clinical research program led by expert neurologist Dr. Sheldon Jordan, is investigating the ProdromeNeuro oil supplement among participants with age-related cognitive decline. It is hoped that the consumption of this product over the course of 4 months will yield improved plasmalogen levels and optimized memory function.

Study enrollment is already over 50% complete. To learn more about this study and how to enroll, visit www.neurologysantamonica.com .

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Turmeric’s benefits have been known for thousands of years, but thanks to Instagram and Pinterest (we see you, golden milk), the spice is enjoying a massive surge in popularity. “Turmeric is getting a lot of attention lately,” says nutritionist and registered dietician Karen Ansel , R.D.N., C.D.N., author of Healing Superfoods for Anti-Aging . “But this root has been used in Chinese and Ayurvedic medicine for thousands of years to fight inflammation and improve digestive health.”

Grown throughout India and other parts of Asia, turmeric is a major ingredient in curry powder. It’s mainly found in spice- or supplement-form, and as a spice it’s commonly used to brighten up curries, stir fries, soups, and even smoothies. $8.40

“Any time you have brightly colored foods, you know there are plant compounds in there doing something great,” says Dawn Jackson Blatner, R.D.N., a dietitian and author of The Superfood Swap . “And turmeric is a bright golden—there’s nothing like it.”

Curcumin, one of turmeric’s primary ingredients, is thought to help fight inflammation, says Jackson Blatner. “All diseases basically start with inflammation, from gingivitis in your mouth to heart disease, so the idea of having a teaspoon a day of turmeric may be a good thing.” How much turmeric should you take each day?

When you’re looking for the correct dosage to take in supplement form, there’s no quick answer to this question, especially since more studies are needed; it also depends on what you’re trying to treat, and what your health practitioner recommends. Many of the studies cited below used a dosage of 500 mg , once or twice a day. What are the side effects of taking turmeric?

Turmeric doesn’t seem to cause serious side effects, though at higher doses it may cause mild stomach distress (nausea, diarrhea, stomach upset). It’s a good idea to check with a health practitioner who’s familiar with natural treatments, however, because turmeric can interfere with certain medications.

So, could taking turmeric or curcumin supplements help boost your health? There’s a lot of misinformation out there, so we looked at the science to bring you 10 ways that turmeric and curcumin could possibly improve your health. 1. Turmeric might help your memory.

Research done in Asian populations back in 2006 found that people who ate more curry scored higher on cognitive function tests (tests that measure memory, attention span, etc.) than those who didn’t eat as much of the spice. The scientists chalked up this benefit to turmeric, which is a major part of the Asian diet.

Recent findings have also pointed to brain-related benefits: For example, a 2018 study of people aged 51 to 84 found that those who took a 90 milligram curcumin supplement twice a day for 18 months saw a boost in memory compared to those who took a placebo. The study was small, but the researchers theorize that curcumin’s anti-inflammatory effects might protect the brain from memory-related diseases. More research will be needed to confirm these findings. 2. Turmeric may help ward off heart disease.

Curcumin’s antioxidants and anti-inflammatory compounds may help protect against certain heart conditions, including diabetic cardiomyopathy (heart muscle disease), arrhythmia (irregular heartbeat) and more, according to a 2017 review in the journal Pharmacological Research . 3. Turmeric might have an impact on certain cancers.

A 2015 review published in the journal Molecules concluded that curcumin might have the potential to fight off certain cancers. But it’s important to take these claims with a grain of salt: So far, most of this research has been conducted in in vitro studies. Still, the authors of the review also note that curcumin has been shown to prevent or slow down the activity of certain tumor cells, including those of skin cancers , digestive cancers, and more. Certainly, more studies would be needed to determine the impact of tumeric on cancer. 4. Turmeric may ease osteoarthritis pain.

Osteoarthritis is the most common cause of disability in the United States, affecting an estimated 30.8 million Americans, according to the Arthritis Foundation . A 2016 research review found that taking curcumin for 4 weeks could help relieve osteoarthritis pain among people who already have the condition—an effect that’s comparable to taking NSAIDs or glucosamine. 5. Turmeric may help with hay fever.

If you’re miserable in certain seasons with the sniffling, hacking, itchy, runny nose, and congestion of hay fever , curcumin could help because of its antioxidant and inflammatory powers. In a 2008 review of animal studies on the effectiveness of curcumin on allergy symptoms, it was found to inhibit the release of histimines, resulting in a marked reduction of symptoms. 6. Turmeric could help with depression symptoms.

In people with major depressive disorder who were already taking an antidepressant, curcumin was found to help ease symptoms. It was a small study , of short duration (only six weeks), and there have been reports online that overstated the findings. But in the study, there seemed to be no ill effects of taking curcumin in conjunction with Prozac, the antidepressant in the study, and perhaps some benefits. 7. Turmeric may have an impact on cholesterol.

This one is iffy, but there is some evidence that curcumin could help keep a certain type of bad cholesterol in line. A 2017 review of seven studies looked at the effects of turmeric and curcumin on blood lipid levels, and found that they may offer some improvement in people with cardiovascular disease risks. The review authors pointed out, however, that it’s premature to use the substances in a clinical setting because it’s hard to know what the correct dosage would be, and that more studies are needed. 8. Turmeric could be good for the liver.

A study review showed that a higher-dose of curcumin supplements could have a positive effect on non-alcoholic fatty liver disease (NAFLD), a condition in which there’s a build-up of fat in the liver that’s not caused by drinking too much alcohol. It’s one of the most common causes of liver disease in the U.S., according to the […]

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The optimum time of day to exercise is ultimately one that suits your individual lifestyle, sleeping habits and preferences. After all, squeezing in a workout at 7pm because you couldn’t resist a lie-in is always going to be a better option than skipping it altogether.

With that said, there are a whole host of benefits associated with swerving the snooze button and getting your workout done first thing. With advice from personal trainer James Starks, co-founder of Starks Fitness , we present 14 compelling reasons to hit the gym before 9am: 16 reasons to workout in the morning

The first couple of hours in the morning sets the tone for the rest of your day. Here are 14 morning workout benefits that might just convince you to set your alarm extra-early tomorrow morning: 1. Fewer distractions

When you first wake up, you’re totally unplugged from the world and haven’t yet turned your attention to your daily to-do list. For an hour or two hours, freedom from work and social commitments means you can focus more intently on your workout. Plus, when you exercise in the morning, you’re less likely to be interrupted by phone calls, texts or emails. 2. Reduced appetite

It may sound counter-intuitive, but a morning workout helps to banish food cravings. A study by Brigham Young University found that 45 minutes of moderate-to-vigorous exercise in the morning actually reduces a person’s emotional response to pictures of food. Not only were participants less tempted by the food, but they didn’t eat more food to make up for the extra calories they burned while exercising. 3. Increased overall activity

Far from completely wearing you out, working out in the morning can inspire you to move more throughout the day. In the same study , participants showed an increase in total physical activity on the days they worked out in the morning. ‘Once you’ve passed the hurdle of getting to the gym, it will leave you in a better state of mind and more likely make you take the stairs rather than the lift,’ says Stark. 4. Increased fat-burning

Exercising on an empty stomach – sometimes referred to as ‘fasted cardio’ – isn’t for everyone, but if weight loss is your goal, it might just help you supercharge your fat-burning potential. In a study of 10 men, published in the British Journal of Nutrition , working out before breakfast was shown to burn up to 20 per cent more fat compared to working out in the afternoon or evening. 5. Improved decision making

Working out in the morning also gives your brain a boost. A morning bout of moderate-intensity exercise improves cognitive performance – like decision-making, attention and visual learning – across the day, according to a study published in the British Journal of Sports Medicine . When participants added brief walking breaks over the course of an eight-hour day, they also saw a boost in short-term memory – even as little as three minutes every half an hour. 6. Fire up the brain

A morning workout may be a better match for your circadian rhythm, which involves the timed release of hormones such as cortisol. While it’s commonly known as the ‘stress hormone’, since it’s part of your body’s natural response to threats of harm or danger, cortisol’s role is to make you feel awake and alert. Typically, levels of the hormone increase in the morning – naturally peaking at around 8am – and dip in the evening. 7. Energy boost

Regular exercise is known to boost energy and reduce feelings of fatigue. In a study published in the journal Psychotherapy and Psychosomatics , researchers found that inactive people with persistent fatigue increased their perceived energy levels by 20 per cent and decreased fatigue by as much as 65 per cent by participating in regular exercise. By getting your workout in early, you’ll benefit from more energy throughout the day. 8. Mood boost

When you exercise, your body releases an array mood-boosting brain chemicals – including dopamine, norepinephrine, serotonin and endorphins – which promotes a sense of wellbeing. Working out also balances your body’s level of stress hormones, such as adrenaline and cortisol. ‘Getting the body moving is a well-known way of boosting endorphins – the body’s feel-good hormones – ensuring that you are set up for a productive day,’ says Stark. ‘Coming out of the gym will leave you feeling in a more positive mood and ready to take on the day.’ 9. Better food choices

Regular exercise can even change your food preferences and give you an appetite for fruits and vegetables. Analysis by Indiana University found that people who exercised for at least 30 minutes, five times or more a week ate the most fruit and vegetables, while those who exercised the least also ate the least. ‘Having already made the decision to get to the gym, you’re more likely to make the correct choices when it comes to food,’ says Stark. 10. Build muscle faster

Testosterone plays an important role in building and maintaining muscle mass and helping your body recover after a workout. It increases neurotransmitters, which encourage tissue growth; interacts with nuclear receptors in DNA, stimulating protein synthesis; and increases levels of growth hormone, which is essential for repairing muscles. Your testosterone levels are highest upon waking, so a morning workout will help you reap the benefits. 11. Better sleep

Where an evening workout is likely to rev you up before bed, boosting your heart rate and core temperature, a morning workout can help you get a better night’s kip. A study by Appalachian State University, adults who exercised at 7am fell asleep faster and slept better than those who hit the gym in the afternoon or evening. Who could turn down the opportunity for deeper, longer, higher-quality sleep? 12. Reduced diabetes risk

Hitting the gym first thing may help ward off type 2 diabetes by helping to regulate blood sugar levels. In a study by KU Leuven University, participants who exercised […]

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Summary: Neuroimaging study reveals how human brain complexity and cognitive flexibility develops during early infancy.

Source: University of North Carolina Health Care

Cognitive flexibility refers to the ability to readily switch between mental processes in response to external stimuli and different task demands. For example, when our brains are processing one task, an external stimulus is present, requiring us to switch our mental processes to attend to this external stimulus. This ability of switching from one to another mental task is the cognitive flexibility. Such flexibility can predict reading ability, academic success, resilience to stress, creativity, and lower risk of various neurological and psychiatric disorders. To shed light on the development of this critical cognitive process during early infancy, researchers at the UNC Biomedical Research Imaging Center (BRIC) at the UNC School of Medicine conducted a brain imaging study in infants to examine the emergence of neural flexibility, which refers to the frequency with which a brain region changes its role (or allegiance to one functional network to another). Neural flexibility is thought to underlie cognitive flexibility.

Publishing their work in the Proceedings of the National Academy of Sciences (PNAS), the researchers show that brain regions with high neural flexibility appear consistent with the core brain regions that support cognitive flexibility processing in adults, whereas brain regions governing basic brain functions, such as motor skills, exhibit lower neural flexibility in adults, demonstrating the emergence of functionally flexible brains during early infancy.

For this study, the authors used magnetic resonance imaging to examine brain activity up to seven times in 52 typically developing infants under the age of two during natural sleep. The researchers, led by Weili Lin, PhD, director of BRIC, the Dixie Lee Boney Soo Distinguished Professor of Neurological Medicine, and Vice Chair of Basic Research in the UNC Department of Radiology, found that neural flexibility increased with age across the whole brain, and specifically in brain regions that control movement, potentially enabling infants to learn new motor skills. Neural flexibility also increased with age in brain regions involved in higher-level cognitive processes, such as attention, memory, and response inhibition, indicating continuing development of these functional networks as babies become toddlers.

The age-related increase in neural flexibility was highest in brain regions already implicated in cognitive flexibility in adults, suggesting that cognitive flexibility may start to develop during the first two years of life.

“Neural flexibility in these brain regions may reflect early developmental processes that support the later emergence of cognitive flexibility,” Lin said. “What we’ve imaged, in essence, is the brain’s flexibility setting the stage for later maturity of higher cognitive brain functions.”

Additional analysis of brain regions with especially high neural flexibility revealed the presence of relatively weak and unstable connections from these regions to other parts of the brain, potentially showing how these regions can rapidly switch their allegiances between different functional networks. By contrast, neural flexibility in brain regions involved in visual functions remained relatively low throughout the first two years of life, suggesting that these regions had already matured. This image is of MRI data, showing neural flexibility over time. Image is credited to Biomedical Research Imaging Center at UNC-Chapel Hill. Lower levels of neural flexibility (i.e., greater established brain maturity) of visual brain regions at three and 18 months of age were associated with better performance on cognitive and behavioral assessments at the age of five or six years.

These findings provide insights into the development of higher-level brain functions, and could be used to predict cognitive outcomes later in life. The developed approach of assessing neural flexibility non-invasively could also provide a new means to assess subjects with neurodevelopmental disorders.

First author of this study is BRIC postdoctoral researcher Weiyan Yin, PhD. Other authors aside from Yin and Lin include Sheng-Che Hung, MD, clinical instructor of radiology; Han Zhang, PhD, assistant professor of radiology; Li Wang, PhD, research assistant professor of radiology; Dinggang Shen, PhD, Director of the UNC BRIC Image Analysis Core and professor of radiology, Hongtu Zhu, PhD, Peter Mucha, PhD, professor of mathematics and applied physical sciences; and Jessica Cohen, PhD, assistant professor of psychology and neuroscience, all at UNC-Chapel Hill. All but Mucha are members of BRIC.

Funding: The National Institutes of Health funded this work.

About this neurodevelopment research article

Source:
University of North Carolina Health Care
Contacts:
Mark Derewicz – University of North Carolina Health Care
Image Source:
The image is credited to Biomedical Research Imaging Center at UNC-Chapel Hill.

Original Research: Open access
“The emergence of a functionally flexible brain during early infancy” by Weili Lin et al. PNAS .

Abstract

The emergence of a functionally flexible brain during early infancy

Adult brains are functionally flexible, a unique characteristic that is thought to contribute to cognitive flexibility. While tools to assess cognitive flexibility during early infancy are lacking, we aimed to assess the spatiotemporal developmental features of “neural flexibility” during the first 2 y of life. Fifty-two typically developing children 0 to 2 y old were longitudinally imaged up to seven times during natural sleep using resting-state functional MRI. Using a sliding window approach, MR-derived neural flexibility, a quantitative measure of the frequency at which brain regions change their allegiance from one functional module to another during a given time period, was used to evaluate the temporal emergence of neural flexibility during early infancy. Results showed that neural flexibility of whole brain, motor, and high-order brain functional networks/regions increased significantly with age, while visual regions exhibited a temporally stable pattern, suggesting spatially and temporally nonuniform developmental features of neural flexibility. Additionally, the neural flexibility of the primary visual network at 3 mo of age was significantly and negatively associated with cognitive ability evaluated at 5/6 y of age. The “flexible club,” comprising brain regions with neural flexibility significantly higher than whole-brain neural flexibility, were consistent with brain regions known to govern cognitive flexibility in adults and exhibited unique characteristics when compared to the functional hub and diverse club regions. Thus, MR-derived […]

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This image is of MRI data, showing neural flexibility over time. Credit: Biomedical Research Imaging Center at UNC-Chapel Hill. Cognitive flexibility refers to the ability to readily switch between mental processes in response to external stimuli and different task demands. For example, when our brains are processing one task, an external stimulus is present, requiring us to switch our mental processes to attend to this external stimulus. This ability of switching from one to another mental task is the cognitive flexibility. Such flexibility can predict reading ability, academic success, resilience to stress, creativity, and lower risk of various neurological and psychiatric disorders. To shed light on the development of this critical cognitive process during early infancy, researchers at the UNC Biomedical Research Imaging Center (BRIC) at the UNC School of Medicine conducted a brain imaging study in infants to examine the emergence of neural flexibility, which refers to the frequency with which a brain region changes its role (or allegiance to one functional network to another). Neural flexibility is thought to underlie cognitive flexibility.

Publishing their work in the Proceedings of the National Academy of Sciences (PNAS) , the researchers show that brain regions with high neural flexibility appear consistent with the core brain regions that support cognitive flexibility processing in adults, whereas brain regions governing basic brain functions, such as motor skills, exhibit lower neural flexibility in adults, demonstrating the emergence of functionally flexible brains during early infancy.

For this study, the authors used magnetic resonance imaging to examine brain activity up to seven times in 52 typically developing infants under the age of two during natural sleep. The researchers, led by Weili Lin, Ph.D., director of BRIC, the Dixie Lee Boney Soo Distinguished Professor of Neurological Medicine, and Vice Chair of Basic Research in the UNC Department of Radiology, found that neural flexibility increased with age across the whole brain, and specifically in brain regions that control movement, potentially enabling infants to learn new motor skills. Neural flexibility also increased with age in brain regions involved in higher-level cognitive processes, such as attention, memory, and response inhibition, indicating continuing development of these functional networks as babies become toddlers.

The age-related increase in neural flexibility was highest in brain regions already implicated in cognitive flexibility in adults, suggesting that cognitive flexibility may start to develop during the first two years of life.

“Neural flexibility in these brain regions may reflect early developmental processes that support the later emergence of cognitive flexibility,” Lin said. “What we’ve imaged, in essence, is the brain’s flexibility setting the stage for later maturity of higher cognitive brain functions.”

Additional analysis of brain regions with especially high neural flexibility revealed the presence of relatively weak and unstable connections from these regions to other parts of the brain, potentially showing how these regions can rapidly switch their allegiances between different functional networks. By contrast, neural flexibility in brain regions involved in visual functions remained relatively low throughout the first two years of life, suggesting that these regions had already matured.

Lower levels of neural flexibility (i.e., greater established brain maturity) of visual brain regions at three and 18 months of age were associated with better performance on cognitive and behavioral assessments at the age of five or six years.

These findings provide insights into the development of higher-level brain functions, and could be used to predict cognitive outcomes later in life. The developed approach of assessing neural flexibility non-invasively could also provide a new means to assess subjects with neurodevelopmental disorders.

Provided by University of North Carolina Health Care

Read more at medicalxpress.com

North Carolina : To shed light on the development of cognitive flexibility during early infancy, researchers conducted a brain imaging study in infants to examine the emergence of neural flexibility, which refers to the frequency with which a brain region changes its role (or allegiance to one functional network to another).

Cognitive flexibility refers to the ability to readily switch between mental processes in response to external stimuli and different task demands. For example, when our brains are processing one task, an external stimulus is present, requiring us to switch our mental processes to attend to this external stimulus. This ability to switch from one to another mental task is cognitive flexibility. Such flexibility can predict reading ability, academic success, resilience to stress, creativity, and lower risk of various neurological and psychiatric disorders. Neural flexibility is thought to underlie cognitive flexibility.

Publishing their work in the Proceedings of the National Academy of Sciences (PNAS), the researchers show that brain regions with high neural flexibility appear consistent with the core brain regions that support cognitive flexibility processing in adults, whereas brain regions governing basic brain functions, such as motor skills, exhibit lower neural flexibility in adults, demonstrating the emergence of functionally flexible brains during early infancy.

For this study, the authors used magnetic resonance imaging to examine brain activity up to seven times in 52 typically developing infants under the age of two during natural sleep.

The research, led by Weili Lin, PhD, director of BRIC, the Dixie Lee Boney Soo Distinguished Professor of Neurological Medicine, and Vice-Chair of Basic Research in the UNC Department of Radiology, found that neural flexibility increased with age across the whole brain, and specifically in brain regions that control movement, potentially enabling infants to learn new motor skills.

Neural flexibility also increased with age in brain regions involved in higher-level cognitive processes, such as attention, memory, and response inhibition, indicating continuing development of these functional networks as babies become toddlers.

The age-related increase in neural flexibility was highest in brain regions already implicated in cognitive flexibility in adults, suggesting that cognitive flexibility may start to develop during the first two years of life.

“Neural flexibility in these brain regions may reflect early developmental processes that support the later emergence of cognitive flexibility,” Lin said. “What we`ve imaged, in essence, is the brain`s flexibility setting the stage for later maturity of higher cognitive brain functions.”

Additional analysis of brain regions with especially high neural flexibility revealed the presence of relatively weak and unstable connections from these regions to other parts of the brain, potentially showing how these regions can rapidly switch their allegiances between different functional networks. By contrast, neural flexibility in brain regions involved in visual functions remained relatively low throughout the first two years of life, suggesting that these regions had already matured.

Lower levels of neural flexibility (ie, greater established brain maturity) of visual brain regions at three and 18 months of age were associated with better performance on cognitive and behavioural assessments at the age of five or six years.

These findings provide insights into the development of higher-level brain functions and could be used to predict cognitive outcomes later in life. The developed approach of assessing neural flexibility non-invasively could also provide a new means to assess subjects with neurodevelopmental disorders.

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