Breakthrough nanoparticle halts multiple sclerosis

In a breakthrough for nanotechnology and multiple sclerosis, a biodegradable nanoparticle turns out to be the perfect vehicle to stealthily deliver an antigen that tricks the immune system into stopping its attack on myelin and halt a model of relapsing remitting multiple sclerosis (MS) in mice, according to new Northwestern Medicine research.

The new nanotechnology also can be applied to a variety of immune-mediated diseases including Type 1 diabetes, food allergies and airway allergies such as asthma.

In MS, the immune system attacks the myelin membrane that insulates nerves cells in the brain, spinal cord and optic nerve. When the insulation is destroyed, electrical signals can’t be effectively conducted, resulting in symptoms that range from mild limb numbness to paralysis or blindness. About 80 percent of MS patients are diagnosed with the relapsing remitting form of the disease.

The Northwestern nanotechnology does not suppress the entire immune system as do current therapies for MS, which make patients more susceptible to everyday infections and higher rates of cancer. Rather, when the nanoparticles are attached to myelin antigens and injected into the mice, the immune system is reset to normal. The immune system stops recognizing myelin as an alien invader and halts its attack on it.

"This is a highly significant breakthrough in translational immunotherapy," said Stephen Miller, a corresponding author of the study and the Judy Gugenheim Research Professor of Microbiology-Immunology at Northwestern University Feinberg School of Medicine. "The beauty of this new technology is it can be used in many immune-related diseases. We simply change the antigen that’s delivered."

"The holy grail is to develop a therapy that is specific to the pathological immune response, in this case the body attacking myelin," Miller added. "Our approach resets the immune system so it no longer attacks myelin but leaves the function of the normal immune system intact."

The nanoparticle, made from an easily produced and already FDA-approved substance, was developed by Lonnie Shea, professor of chemical and biological engineering at Northwestern’s McCormick School of Engineering and Applied Science.

"This is a major breakthrough in nanotechnology, showing you can use it to regulate the immune system," said Shea, also a corresponding author. The paper was published Nov. 18 in the journal Nature Biotechnology.

New algorithm greatly improves speed and accuracy of thought-controlled computer cursor

When a paralyzed person imagines moving a limb, cells in the part of the brain that controls movement still activate as if trying to make the immobile limb work again. Despite neurological injury or disease that has severed the pathway between brain and muscle, the region where the signals originate remains intact and functional.

In recent years, neuroscientists and neuroengineers working in prosthetics have begun to develop brain-implantable sensors that can measure signals from individual neurons, and after passing those signals through a mathematical decode algorithm, can use them to control computer cursors with thoughts. The work is part of a field known as neural prosthetics.

A team of Stanford researchers have now developed an algorithm, known as ReFIT, that vastly improves the speed and accuracy of neural prosthetics that control computer cursors. The results were published November 18 in the journal Nature Neuroscience in a paper by Krishna Shenoy, a professor of electrical engineering, bioengineering and neurobiology at Stanford, and a team led by research associate Dr. Vikash Gilja and bioengineering doctoral candidate Paul Nuyujukian.

In side-by-side demonstrations with rhesus monkeys, cursors controlled by the ReFIT algorithm doubled the performance of existing systems and approached performance of the real arm. Better yet, more than four years after implantation, the new system is still going strong, while previous systems have seen a steady decline in performance over time.

"These findings could lead to greatly improved prosthetic system performance and robustness in paralyzed people, which we are actively pursuing as part of the FDA Phase-I BrainGate2 clinical trial here at Stanford," said Shenoy.

Optogenetics illuminates pathways of motivation through brain

Whether you are an apple tree or an antelope, survival depends on using your energy efficiently. In a difficult or dangerous situation, the key question is whether exerting effort — sending out roots in search of nutrients in a drought or running at top speed from a predator — will be worth the energy.

In a paper published online Nov. 18 in Nature, Karl Deisseroth, MD, PhD, a professor of bioengineering and of psychiatry and behavioral sciences at Stanford University, and postdoctoral scholar Melissa Warden, PhD, describe how they have isolated the neurons that carry these split-second decisions to act from the higher brain to the brain stem. In doing so, they have provided insight into the causes of severe brain disorders such as depression.

In organisms as complex as humans, the neural mechanisms that help answer the question, “Is it worth my effort?” can fail, leading to debilitating mental illnesses. Major depressive disorder, for instance, which affects nearly 20 percent of people at some point in life, is correlated with underperformance in the parts of the brain involved in motivation. But researchers have struggled to work out the exact cause and effect.

“It’s challenging because we do not have a fundamental understanding of the circuitry that controls this sort of behavioral pattern selection. We don’t understand what the brain is doing wrong when these behaviors become dysfunctional, or even what the brain is supposed to be doing when things are working right,” Deisseroth said. “This is the level of the mystery we face in this field.”

Clinicians refer to this slowing down of motivation in depressed patients as “psychomotor retardation.” According to Deisseroth, who is also a practicing psychiatrist, patients may experience this symptom mentally, finding it hard to envision the positive results of an action, or, he said, they may feel physically heavy, like their limbs just do not want to move.

“This is one of the most debilitating aspects of depression, and motivation to take action is something that we can model in animals. That’s the exciting opportunity for us as researchers,” said Deisseroth, who also holds the D.H. Chen Professorship.

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Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject’s learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations.

Linguistics as a Window to Understanding the Brain

Why is it so hard to give good directions?

We’ve all been there – the directions sounded so clear when we were told them. Every step of the journey seemed obvious, we thought we had understood the directions perfectly. And yet here we are miles from anywhere, after dark, in a field arguing about whether we should have gone left or right at the last turn, whether we’re going to have to sleep here now, and exactly whose fault it is.

The truth is we shouldn’t be too hard on ourselves. Psychologically speaking giving good directions is a particularly difficult task.

The reason we find it hard to give good directions is because of the “curse of knowledge”, a psychological quirk whereby, once we have learnt something, we find it hard to appreciate how the world looks to someone who doesn’t know it yet. We don’t just want people to walk a mile in our shoes, we assume they already know the route. Once we know the way to a place we don’t need directions, and descriptions like “its the left about halfway along” or “the one with the little red door” seem to make full and complete sense.

But if you’ve never been to a place before, you need more than a description of a place; you need an exact definition, or a precise formula for finding it. The curse of knowledge is the reason why, when I had to search for a friend’s tent in a field, their advice of “it’s the blue one” seemed perfectly sensible to them and was completely useless for me, as I stood there staring blankly at hundreds of blue tents.

This same quirk is why teaching is so difficult to do well. Once you are familiar with a topic it is very hard to understand what someone who isn’t familiar with it needs to know. The curse of knowledge isn’t a surprising flaw in our mental machinery – really it is just a side effect of our basic alienation from each other. We all have different thoughts and beliefs, and we have no special access to each other’s minds. A lot of the time we can fake understanding by mentally simulating what we’d want in someone else’s position. We have thoughts along the lines of “I’d like it if there was one bagel left in the morning” and therefore conclude “so I won’t eat all the bagels before my wife gets up in the morning”. This shortcut allows us to appear considerate, without doing any deep thought about what other people really know and want.

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Swimming kids are smarter

Children who learn how to swim at a young age are reaching many developmental milestones earlier than the norm.

Researchers from the Griffith Institute for Educational Research surveyed parents of 7000 under-fives from Australia, New Zealand and the US over three years.

A further 180 children aged 3, 4 and 5 years have been involved in intensive testing, making it the world’s most comprehensive study into early-years swimming.

Lead researcher Professor Robyn Jorgensen says the study shows young children who participate in early-years swimming achieve a wide range of skills earlier than the normal population.

“Many of these skills are those that help young children into the transition into formal learning contexts such as pre-school or school.

“The research also found significant differences between the swimming cohort and non-swimmers regardless of socio-economic background.

“While the two higher socio-economic groups performed better than the lower two in testing, the four SES groups all performed better than the normal population.

The researchers also found there were no gender differences between the research cohort and the normal population.

As well as achieving physical milestones faster, children also scored significantly better in visual-motor skills such as cutting paper, colouring in and drawing lines and shapes, and many mathematically-related tasks. Their oral expression was also better as well as in the general areas of literacy and numeracy.

“Many of these skills are highly valuable in other learning environments and will be of considerable benefit for young children as they transition into pre-schools and school.”