Research team discovers: brain does not process sensory information sufficiently

The reason why some people are worse at learning than others has been revealed by a research team from Berlin, Bochum, and Leipzig, operating within the framework of the Germany-wide network “Bernstein Focus State Dependencies of Learning”. They have discovered that the main problem is not that learning processes are inefficient per se, but that the brain insufficiently processes the information to be learned. The scientists trained the subjects’ sense of touch to be more sensitive. In subjects who responded well to the training, the EEG revealed characteristic changes in brain activity, more specifically in the alpha waves. These alpha waves show, among other things, how effectively the brain exploits the sensory information needed for learning. “An exciting question now is to what extent the alpha activity can be deliberately influenced with biofeedback”, says PD Dr. Hubert Dinse from the Neural Plasticity Lab of the Ruhr-Universität Bochum. “This could have enormous implications for therapy after brain injury or, quite generally, for the understanding of learning processes.” The research team from the Ruhr-Universität, the Humboldt Universität zu Berlin, Charité – Universitätsmedizin Berlin and the Max Planck Institute (MPI) for Human Cognitive and Brain Sciences reported their findings in the Journal of Neuroscience.

Learning without attention: passive training of the sense of touch

How well we learn depends on genetic aspects, the individual brain anatomy, and, not least, on attention. “In recent years we have established a procedure with which we trigger learning processes in people that do not require attention”, says Hubert Dinse. The researchers were, therefore, able to exclude attention as a factor. They repeatedly stimulated the participants’ sense of touch for 30 minutes by electrically stimulating the skin of the hand. Before and after this passive training, they tested the so-called “two-point discrimination threshold”, a measure of the sensitivity of touch. For this, they applied gentle pressure to the hand with two needles and determined the smallest distance between the needles at which the patient still perceived them as separate stimuli. On average, the passive training improved the discrimination threshold by twelve percent—but not in all of the 26 participants. Using EEG, the team studied why some people learned better than others.

Imaging the brain state using EEG: the alpha waves are decisive

The cooperation partners from Berlin and Leipzig, PD Dr. Petra Ritter, Dr. Frank Freyer, and Dr. Robert Becker recorded the subjects’ spontaneous EEG before and during passive training. They then identified the components of the brain activity related to improvement in the discrimination test. The alpha activity was decisive, i.e., the brain activity was in the frequency range 8 to 12 hertz. The higher the alpha activity before the passive training, the better the people learned. In addition, the more the alpha activity decreased during passive training, the more easily they learned. These effects occurred in the somatosensory cortex, that is, where the sense of touch is located in the brain.

Researchers seek new methods for therapy

“How the alpha rhythm manages to affect learning is something we investigate with computer models”, says PD Dr. Petra Ritter, Head of the Working Group “Brain Modes” at the MPI Leipzig and the Berlin Charité. “Only when we understand the complex information processing in the brain, can we intervene specifically in the processes to help disorders”, adds Petra Ritter. New therapies are the aim of the cooperation network, which Ritter coordinates, the international “Virtual Brain” project, which her team collaborates on, and the “Neural Plasticity Lab”, chaired by Hubert Dinse at the RUB.

Learning is dependent on access to sensory information

A high level of alpha activity counts as a marker of the readiness of the brain to exploit new incoming information. Conversely, a strong decrease of alpha activity during sensory stimulation counts as an indicator that the brain processes stimuli particularly efficiently. The results, therefore, suggest that perception-based learning is highly dependent on how accessible the sensory information is. The alpha activity, as a marker of constantly changing brain states, modulates this accessibility.

Brain imaging research shows how unconscious processing improves decision-making

When faced with a difficult decision, it is often suggested to “sleep on it” or take a break from thinking about the decision in order to gain clarity.

But new brain imaging research from Carnegie Mellon University, published in the journal “Social Cognitive and Affective Neuroscience,” finds that the brain regions responsible for making decisions continue to be active even when the conscious brain is distracted with a different task. The research provides some of the first evidence showing how the brain unconsciously processes decision information in ways that lead to improved decision-making.

"This research begins to chip away at the mystery of our unconscious brains and decision-making," said J. David Creswell, assistant professor of psychology in CMU’s Dietrich College of Humanities and Social Sciences and director of the Health and Human Performance Laboratory. "It shows that brain regions important for decision-making remain active even while our brains may be simultaneously engaged in unrelated tasks, such as thinking about a math problem. What’s most intriguing about this finding is that participants did not have any awareness that their brains were still working on the decision problem while they were engaged in an unrelated task."

Blood May Hold Clues to Risk of Memory Problems After Menopause

New Mayo Clinic research suggests that blood may hold clues to whether post-menopausal women may be at an increased risk for areas of brain damage that can lead to memory problems and possibly increased risk of stroke. The study shows that blood’s tendency to clot may contribute to areas of brain damage called white matter hyperintensities. The findings are published in the Feb. 13 online issue of Neurology, the medical journal of the American Academy of Neurology.

The study involved 95 women with an average age of 53 who recently went through menopause. The women had magnetic resonance imaging, or MRIs, taken of their brains at the start of the study. They then received a placebo, oral hormone therapy or the hormone skin patch. They had MRIs periodically over the next four years.

During the study, women with higher levels of thrombogenic microvesicles, the platelets more likely to cause blood to clot, were likelier to have higher increases in the amount of white matter hyperintensities (shown as concentrated white areas on an MRI scan), which may lead to memory loss.

"This study suggests that the tendency of the blood to clot may contribute to a cascade of events leading to the development of brain damage in women who have recently gone through menopause," says study author Kejal Kantarci, M.D., of Mayo Clinic. "Preventing the platelets from developing these microvesicles could be a way to stop the progression of white matter hyperintensities in the brain."

All of the women had white matter hyperintensities at the start of the study. The amount increased by an average volume of 63 cubic millimeters at 18 months, 122 cubic millimeters at three years and 155 cubic millimeters at four years.

(Image: Shutterstock)

Long memories in brain activity explain streaks in individual behaviour

Even with a constant task, human performance fluctuates in time-scales from seconds to minutes in a fractal manner. In a recent study a Finnish research group found that the individual variability in the brain dynamics as indexed by the neuronal scaling laws predicted the individual behavioral variability and the conscious detection of very weak sensory stimuli. These data indicate that individual neuronal dynamics underlie the individual variability in human cognition and performance. Results may also have a strong impact in understanding the neuronal mechanism of neuropsychiatric diseases in which behavioral dynamics are abnormal.

Human performance in cognitive tasks varies from moment-to-moment so that the similar behavioral performance is clustered into streaks. The neuronal dynamics underlying this behavioral variability has remained unknown.

Similar scale-free and power-law distributed “avalanche dynamics” is observed in many natural systems such as sand piles, earthquakes, gene regulation, and also brain activity. However, the functional significance of the neuronal scale-free behavior has remained unknown. It is also unclear whether it is just epiphenomena without any further significance. 

"We investigated whether the individual variability in the scaling-laws governing the detection of auditory and visual stimuli presented in the threshold of detection could be predicted by the variability in the neuronal scaling laws", explains Matias Palva, project leader in the Neuroscience Center of the University of Helsinki, Finland.

The researchers used magneto- and electroencephalography to record non-invasively human brain activity during the task performance. They found that both the behavioral and neuronal dynamics were characterized by scale-free dynamics. Individual variability in the neuronal scaling laws predicted the individual scaling laws in behavioral performance.

"These results suggest that the individual behavioral and psychophysical variability in task performance is largely a result of the inherent variability in the individual neuronal dynamics", says project leader Satu Palva.

(Image: Harry Sieplinga, HMS/Getty Images)

Will we ever… simulate the human brain?

A billion dollar project claims it will recreate the most complex organ in the human body in just 10 years. But detractors say it is impossible. Who is right?

For years, Henry Markram has claimed that he can simulate the human brain in a computer within a decade. On 23 January 2013, the European Commission told him to prove it. His ambitious Human Brain Project (HBP) won one of two ceiling-shattering grants from the EC to the tune of a billion euros, ending a two-year contest against several other grandiose projects. Can he now deliver? Is it even possible to build a computer simulation of the most powerful computer in the world – the 1.4-kg (3 lb) cluster of 86 billion neurons that sits inside our skulls?

The very idea has many neuroscientists in an uproar, and the HBP’s substantial budget, awarded at a tumultuous time for research funding, is not helping. The common refrain is that the brain is just too complicated to simulate, and our understanding of it is at too primordial a stage.

Then, there’s Markram’s strategy. Neuroscientists have built computer simulations of neurons since the 1950s, but the vast majority treat these cells as single abstract points. Markram says he wants to build the cells as they are – gloriously detailed branching networks, full of active genes and electrical activity. He wants to simulate them down to their ion channels – the molecular gates that allow neurons to build up a voltage by shuttling charged particles in and out of their membrane borders. He wants to represent the genes that switch on and off inside them. He wants to simulate the 3,000 or so synapses that allow neurons to communicate with their neighbours.

Erin McKiernan, who builds computer models of single neurons, is a fan of this bottom-up approach. “Really understanding what’s happening at a fundamental level and building up – I generally agree with that,” she says. “But I tend to disagree with the time frame. [Markram] said that in 10 years, we could have a fully simulated brain, but I don’t think that’ll happen.”

Even building McKiernan’s single-neuron models is a fiendishly complicated task. “For many neurons, we don’t understand well the complement of ion channels within them, how they work together to produce electrical activity, how they change over development or injury,” she says. “At the next level, we have even less knowledge about how these cells connect, or how they’re constantly reaching out, retracting or changing their strength.” It’s ignorance all the way down.

“For sure, what we have is a tiny, tiny fraction of what we need,” says Markram. Worse still, experimentally mapping out every molecule, cell and connection is completely unfeasible in terms of cost, technical requirements and motivation. But he argues that building a unified model is the only way to unite our knowledge, and to start filling in the gaps in a focused way. By putting it all together, we can use what we know to predict what we don’t, and to refine everything on the fly as new insights come in.

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Why we’re building a €1 billion model of a human brain

We want to reach a unified understanding of the brain and the simulation on a supercomputer is the tool. Today you have neuroscientists working on a genetic, behavioural or cognitive level, and then you have informaticians, chemists and mathematicians. They all have their own understanding of how the brain functions and is structured. How do you get them all around the same table? We think of the project as like a CERN for the brain. The model is our way of bringing everyone, and our understanding, together.

This Is Your Brain On Movies: Neuroscientists Weigh In On The Brain Science of Cinema

In movies, we explore landscapes far removed from our day-to-day lives. Whether experiencing the fantastical adventures of Star Wars or the dramatic throes of The English Patient, movies demand that our brains engage in a complex firing of neurons and cognitive processes. We enter into manipulated worlds where musical scores enhance feeling; where cinematography clues us into details we’d normally gloss over; where, like omniscient beings, we voyeuristically peek into others’ lives and minds; and where we can travel from Marrakech to Mars without ever having left our seat. Movies reflect reality, yet are anything but.

“Movies are highly complex, multidimensional stimuli,” said Uri Hasson, a neuroscientist and psychologist at Princeton University. “Some areas of the brain analyze sound bites, some analyze word context, some the sentence content, music, emotional aspect, color or motion.” Just as many people must come together to work on different elements of a movie’s script, score, visuals or costumes, he explained, so many areas of the brain must also be engaged in processing those disparate elements.

The relatively new field of neurocinematic studies seeks to untangle our neurological experience of film and, in doing so, learn not only the mechanisms behind movie watching but also how movies might teach us more about ourselves.

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