fMRI-driven neurofeedback has been used in various contexts, but never applied to the treatment of anxiety.
Yale University researchers used fMRI to display the activity of the orbitofrontal cortex, a brain region just above the eyes, to subjects in real time. Through a process of trial and error, the subjects learned to control their brain activity. This neurofeedback led to changes in brain connectivity and increased control over anxiety. The changes were still present several days after the exercise.
SimSensei software, developed by Stefan Scherer and colleagues at the University of Southern California, combines computer vision algorithms and the psychological model of depression. An on-screen psychologist asks you a series of questions and watches how you physically respond. Using Kinect, the computer vision algorithms build up a very detailed model of your face and body, including your “smile level,” horizontal gaze and vertical gaze, how wide open your eyes are, and whether you are leaning toward or away from the camera. From these markers, SimSensei can determine whether you’re exhibiting signs that indicate depression — gaze aversion, smiling less, and fidgeting.
Researchers from the Stanford University School of Medicine used brain scans to look for a link between math-learning abilities and brain structure or function, and compared neural and cognitive predictors of childrens’ responses to tutoring.
The analysis of the children’s structural brain scans showed that larger gray matter volume in three brain structures predicted greater ability to benefit from math tutoring. The predictions were generated with a machine learning algorithm.
The researchers’ next steps will include comparing brain structure and wiring in children with and without math learning disabilities, analyzing how the wiring of the brain changes in response to tutoring, and examining whether lower-performing children’s brains can be exercised to help them learn math.
Finding the point at which babies’ reactions change from being purely reflexive to reflecting more intention is leading researches to focus on the first glimmers of conscious thought in infants as young as 5 months old.
Ideally, the infant studies would enable scientists to trace a trajectory of how consciousness generates. “You can start to use this method very early to basically try to check whether there is normal or abnormal development,” says Sid Kouider, a researcher at the École Normale Supérieure in Paris. “We know that autistic children can have trouble being aware of faces, and you could imagine this kind of method to diagnose early on whether someone is reacting in a normal way to objects or faces.”
Kurzweil predicts that computers will be able to have a deep understanding of human emotion by 2029. He wants to see search evolve to understand even more complex language that will involve “emotional intelligence, being funny, getting the joke, being sexy, being loving, understanding human emotion.”
Pass-thoughts are thoughts that a headset records through brainwaves. The computer learns what your individual brainwaves are like and then identifies you. Traditionally, these brainwaves, called electroencephalograms (EEGs), are collected through expensive and sometimes invasive devices, so the pass-thought growth has been severely stunted.
Berkeley’s John Chuang and his team conducted a series of experiments to determine whether a single, less expensive, non-invasive EEG channel provided high enough signal quality for accurate authentication. For authentication, the computer needs to be able to accurately and consistently distinguish your brainwave patterns from someone else’s.
By selecting customized tasks for each user and then customizing each user’s authentication thresholds, the team was able to reduce error rates to below 1%, comparable to the accuracy of more invasive multi-channel EEG signals.
Sample sizes in neurological research are often too small to draw general conclusions.
Marcus Munafo, from the University of Bristol, and his colleagues analyzed hundreds of neuroscience studies to determine their “statistical power”. If the researchers’ figures are accurate—and if the 12-month period they looked at is representative of neuroscience research in general—then the implications are alarming. Bluntly, much of the published neuroscientific research is likely to be reporting effects, correlations and “facts” that are simply not real. At the same time, real phenomena are going unnoticed.
Understanding the brain is the most important opportunity of our lifetime. It’s afflictions and treatments can no longer be based on hypothesis, trial and error. Let’s not miss it.
A group of scientists at the University of Michigan have succeeded in using functional magnetic resonance imaging to tease apart the brain’s consistent response to physical pain from its very similar response to emotional pain. The result is a moving picture of physical pain that allowed the researchers to predict with remarkable accuracy whether the individual whose brain they were watching was experiencing intense physical pain, the sensation of a warm spot on his arm, or the sting of social rejection.
The study – known as the Developing Human Connectome Project – hopes to look at more than 1,500 babies, studying many aspects of their neurological development.
By examining the brains of babies while they are still growing in the womb, as well as those born prematurely and at full term, the scientists will try to define baselines of normal development and investigate how these may be affected by problems around birth.
Central to this project are advanced MRI scanning techniques, which the scientists say are able to pick up on details of the growing brain that have been difficult to capture until now.
Thank you, President Obama.
Today at the White House, President Obama unveiled the “BRAIN” Initiative—a bold new research effort to revolutionize our understanding of the human mind and uncover new ways to treat, prevent, and cure brain disorders like Alzheimer’s, schizophrenia, autism, epilepsy, and traumatic brain injury.
The Initiative promises to accelerate the invention of new technologies that will help researchers produce real-time pictures of complex neural circuits and visualize the rapid-fire interactions of cells that occur at the speed of thought.
The BRAIN Initiative is launching with approximately $100 million in funding for research supported by the National Institutes of Health (NIH), the Defense Advanced Research Projects Agency (DARPA), and the National Science Foundation (NSF) in the President’s Fiscal Year 2014 budget.