New tools to answer timeless questions

After finishing his PhD in molecular biophysics, Alan Jasanoff decided to veer away from that field and try looking into some of the biggest questions in neuroscience: How do we perceive things? What happens in our brains when we make decisions?

After a few months, however, he realized that he didn’t have the tools he wanted to use — so he decided to start making his own.

Jasanoff, who recently earned tenure in MIT’s Department of Biological Engineering, now specializes in developing novel brain-imaging agents that can reveal information more detailed than other human brain-imaging techniques such as fMRI and PET, and more comprehensive than traditional neuroscience measurements such as microscopy and electrode recordings. With the new tools, he is also beginning to explore some of the fundamental questions that first drew him into neuroscience.

Neuroscientists commonly use fMRI, which measures blood flow in the brain, as a proxy for neural activity. In the past several years, Jasanoff has developed sensors that can be used with fMRI to image brain activity more directly, by measuring levels of neurotransmitters (the chemicals that carry messages between neurons) and calcium, which enters neurons when they fire.

Using those sensors, Jasanoff has started exploring how positive reinforcement influences behavior and decision making in animals. His work could also be applicable to fields outside of neuroscience, because intracellular signaling molecules such as calcium “are really ubiquitous — not just in neuronal signaling but signaling throughout the body, during development, immune-cell activity and so on,” says Jasanoff, who is an associate member of MIT’s McGovern Institute for Brain Research and an associate professor of biological engineering, nuclear science and engineering, and brain and cognitive sciences.

As a teenager, Jasanoff had a strong interest in science and two role models for a career in academia — his parents, both social scientists. Jasanoff spent his childhood first in Cambridge, Mass., where his father taught at Harvard University, then Ithaca, N.Y., where both parents were professors at Cornell University. His parents, Jay and Sheila Sen Jasanoff, have since returned to Harvard. “My sister Maya is also a professor at Harvard, so I’m the black sheep,” Jasanoff jokes.

While a senior in high school, Jasanoff got his start in science with a part-time job washing test tubes in a lab at Cornell. “That wasn’t a very technically sophisticated job, but I occasionally would hit up the local grad students and postdocs for slightly more scientific insight into what was going on,” he says.

As an undergraduate at Harvard, Jasanoff studied biochemical sciences and had a strong interest in structural biology, using the techniques of X-ray crystallography and nuclear magnetic resonance (NMR) to study molecules far too small to examine with the naked eye. “I like molecules,” he says, adding, “My mother always says it’s an outgrowth of my fascination with LEGO.”

He stayed at Harvard to get his PhD in biophysics, then went to MIT’s Whitehead Institute to begin independent research as a Whitehead Fellow. With a growing interest in some of the “timeless questions” of neuroscience, he began working on molecular-level neuroimaging — trading the relative predictability of structural biology for the complexity of a field “famous among many for its unanswerable questions,” he says.

Direct measurements

Functional MRI, or fMRI, currently one of the best ways to try to address those questions, provides an indirect view of what’s happening inside the brain, and can only reveal average activity in large regions. Meanwhile, traditional neuroscience techniques such as optical imaging provide a precise record of activity at the cellular level but cannot be done non-invasively over large areas of the brain.

Jasanoff wanted to find a way to have the best of both worlds — imaging large brain regions non-invasively, but with cellular precision.

He spent several years as a postdoc trying to achieve that in flies, until he realized that to be successful, he would have to develop his own molecular tools. “I tried one after another failed or weak experiments,” he recalls. “I sort of hoped there were off-the-shelf chemicals and reagents that could be useful for this, and that was probably foolhardy.”

Since joining the MIT faculty in 2004, Jasanoff has developed sensors that can be used with fMRI to monitor the neurotransmitters dopamine and serotonin, as well as calcium and other signaling molecules. The sensors, which currently can only be used in animals, include a section that binds to the target molecule, as well as a magnetic component that allows them to become visible with MRI.

Dopamine holds great interest for neuroscientists because of its role in reward, addiction and neurodegenerative disorders such as Parkinson’s disease. Jasanoff’s lab is now focusing on the role of rewards, or positive reinforcement of behavior, in decision making.

“This is one of the areas of neuroscience where I think we can make a difference relatively soon, just because we’ve got the tools for it,” Jasanoff says. “We’re also hard at work on sensors for a range of other molecular targets; our vision is to have a whole set of these probes available for ‘dissecting’ multiple aspects of neural function in living, intact brains.”

Your brain on ‘shrooms: fMRI elucidates neural correlates of psilocybin psychedelic state

Psychedelic substances have long been used for healing, ceremonial, or mind-altering subjective experiences due to compounds that, when ingested or inhaled, generate hallucinations, perceptual distortions, or altered states of awareness. Of these, the psychedelic substance psilocybin, the prodrug (a precursor of a drug that must in vivo chemical conversion by metabolic processes before becoming an active pharmacological agent) of psilocin (4-hydroxy-dimethyltryptamine) and the key hallucinogen found in so-called magic mushrooms, is widely used not only in healing ceremonies, but, more recently, in psychotherapy as well – but little has been known about its specific activity in the brain.

Recently, however, scientists in the Neuropsychopharmacology Unit at Imperial College London used complementary blood-oxygen level dependent (BOLD) functional MRI, or fMRI, in conjunction with a technique for imaging the transition from normal waking consciousness to the psychedelic state. The study found decreased blood flow and BOLD in the thalamus, anterior and posterior cingulate cortex, and medial prefrontal cortex. The researchers concluded that the surprising results strongly suggest that the subjective effects of psychedelic drugs are caused by decreased activity and connectivity in the brain’s key connector hubs, enabling a state of unconstrained cognition.

Lead researcher Dr. Robin L. Carhart-Harris, working in the Neuropsychopharmacology Unit created by Prof. David J. Nutt, recounts the team’s main challenges in establishing an fMRI methodology that would be specific enough to highly correlate neurophysiological activity with the neuronal presence or absence of psilocybin. “There were a number of considerations,” Carhart-Harris tells Medical Xpress. “In terms of experimental design, we had to determine the precise dose and delivery protocol that would be appropriate for obtaining clear fMRI results. “For example,” he explains, “we had to consider temporal dynamics: If the drug was administered orally, the protracted period of time between ingestion, metabolism, and crossing of the blood-brain barrier would fall outside of the short scanning window needed to capture induced brain activity.” They therefore had to rely on intravenous administration.

“Another issue,” Carhart-Harris adds, “was methodological – specifically, isolating any placebo effect derived from changes not due to the injection itself, such as anticipatory anxiety.” The team also had to measure physiological parameters, including breathing and heart rate, in order to use these signals as weighting factors, correlate with baseline levels and remove them as a possible explanation of any observed brain changes.

To address these challenges, Carhart-Harris points to the pilot work the team performed in order to determine the optimal dose. “The original dose was too low in our mock scanner environment, in which subjects were asked to rate regular subjective or perceptual experiences< he recalls. “However, that simply wouldn’t work in a scanning environment, since their very response would interfere with fMRI measurement.”

Regarding next steps in their research, Carhart-Harris sees obtaining a grant to study psilocybin as a treatment for depression – scheduled to begin at the end of 2012 – as key. “Psilocybin decreases brain activity in regions such as the medial prefrontal cortex,” he explains, “that are overactive in depression.” The team may also perform the same investigations with alternative psychedelic compounds, such as MDMA (3,4-methylenedioxymethamphetamine) – a synthetic, psychoactive drug, commonly known as Ecstasy, that is chemically similar to the stimulant methamphetamine.

Carhart-Harris is also interested in the effects of psilocybin on memory. “When subjects are in the scanner,” he illustrates, “and are shown personal memory cues, then asked to close their eyes and remember the emotions at the time of the original event, the recalled emotions are more vivid – indicating elevated brain activation – when under the effects of psilocybin.” Moreover, Carhart-Harris notes that when administered psilocybin when undergoingpsychotherapy, there is an increased incidence of sudden personal insights. He speculates that this suggests that psilocybin-induced visual changes indicate that the visual pathways are more sensitive to signals from the hippocampus, which is involved in memory, when under psilocybin.

In addition to depression, Carhart-Harris observes, there are other research and applications that might benefit from the team’s findings. “Those suffering from cluster headaches,” he notes, “report excruciating pain that is difficult to treat, sometimes describing it as worse than the pain childbirth. During such headaches, they show an increase in hypothalamic activity to date has only been ameliorated by deep brain stimulation. However,” he concludes, “when administered psilocybin, they display a decrease in hypothalamic activity and a corresponding suspension of cluster headaches.”

More information: Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin, Published online before print January 23, 2012, doi: 10.1073/pnas.1119598109, PNAS February 7, 2012 vol. 109 no. 6 2138-2143.

Usually I avoid reblogging such memes, but I think we can all relate…

Women report more intense pain than men in virtually every disease category, according to Stanford University School of Medicine investigators who mined a huge collection of electronic medical records to establish the broad gender difference to a high level of statistical significance.

Read the whole article HERE

approachingsignificance:

The patient uploaded his x-ray to Facebook in the ambulance between hospitals.

A suburban Chicago man accidentally shot a 3.25in (8.25cm) nail into his skull but is recovering after doctors successfully removed it from the centre of his brain.

Dante Autullo, 34, was in his workshop when a nail gun recoiled near his head.

But he had no idea the nail had entered his brain until the next day, when he began feeling nauseous.

Doctors told Mr Autullo that the nail came within millimetres of the area used for motor function.

Autism Redefined: New Diagnostic Criteria More Restrictive

The proposed changes to the diagnostic definition would be published in the fifth edition of the American Psychiatric Association’s (APA) “Diagnostic and Statistical Manual of Mental Disorders (DSM-5).”

“Given the potential implications of these findings for service eligibility, our findings offer important information for consideration by the task force finalizing DSM-5 diagnostic criteria,” said Yale Child Study Center (CSC) director Fred Volkmar, M.D., who conducted the study with CSC colleagues Brian Reichow and James McPartland.

Volkmar and his team found that in a group of individuals without intellectual disabilities who were evaluated during the 1994 DSM-IV field trial, it was estimated that approximately half might not qualify for a diagnosis of autism under the proposed new definition.

Volkmar stressed that these preliminary findings relate only to the most cognitively able and may have less impact on diagnosis of more cognitively disabled people. “Use of such labels, particularly in the United States, can have important implications for service,” he said. “Major changes in diagnosis also pose issues for comparing results across research studies.”

(http://www.sciencedaily.com/releases/2012/01/120120184525.htm)

Neural network gets an idea of number without counting

AN ARTIFICIAL brain has taught itself to estimate the number of objects in an image without actually counting them, emulating abilities displayed by some animals including lions and fish, as well as humans.

Because the model was not preprogrammed with numerical capabilities, the feat suggests that this skill emerges due to general learning processes rather than number-specific mechanisms. “It answers the question of how numerosity emerges without teaching anything about numbers in the first place,” says Marco Zorzi at the University of Padua in Italy, who led the work.

The finding may also help us to understand dyscalculia - where people find it nearly impossible to acquire basic number and arithmetic skills - and enhance robotics and computer vision.

The skill in question is known as approximate number sense. A simple test of ANS involves looking at two groups of dots on a page and intuitively knowing which has more dots, even though you have not counted them. Fish use ANS to pick the larger, and therefore safer, shoal to swim in.

To investigate ANS, Zorzi and colleague Ivilin Stoianov used a computerised neural network that responds to images and generates new “fantasy” ones based on rules that it deduces from the original images. The software models a retina-like layer of neurons that fire in response to the raw pixels, plus two deeper layers that do more sophisticated processing based on signals from layers above.

The pair fed the network 51,800 images, each containing up to 32 rectangles of varying sizes. In response to each image, the program strengthened or weakened connections between neurons so that its image generation model was refined by the pattern it had just “seen”. Zorzi likens it to “learning how to visualise what it has just experienced”.

Infants demonstrate ANS without being taught, so the network was not preprogrammed with the concept of “amount”. But when Zorzi and Stoianov looked at the network’s behaviour, they discovered a subset of neurons in the deepest layer that fired more often as the number of objects in the image decreased. This suggested that the network had learned to estimate the number of objects in each image as part of its rules for generating images. This behaviour was independent of the total surface area of the objects, emphasising that the neurons were detecting number.

What’s more, these firing patterns followed the trend shown by neurons inside the parietal cortex of monkeys. This region is involved in knowledge of numbers, suggesting that the model might reflect how real brains work.

To see if these patterns could give rise to ANS, the pair created a second program and fed it the firing patterns of the number-detecting neurons in the first program. They also fed it information on whether the number of objects associated with each firing pattern was bigger or smaller than a reference number. Trained in this way, the model could estimate whether a fresh image contained more or fewer than a given number of objects (Nature Neuroscience, DOI: 10.1038/nn.2996).

Brian Butterworth, who studies mathematical cognition at University College London, says the work breaks new ground. “It gives an explanation for how we estimate number when we can’t count.”

(Content provided by New Scientist)

How the Brain Cell Works: A Dive Into Its Inner Network

University of Miami (UM) biology professor Akira Chiba is leading a multidisciplinary team to develop the first systematic survey of protein interactions within brain cells. The team is aiming to reconstruct genome-wide in situ protein-protein interaction networks (isPIN) within the neurons of a multicellular organism. Preliminary data were presented at the American Society for Cell Biology annual meeting, December 3 through 7, 2011, in Denver, Colorado.

“This work brings us closer to understanding the mechanics of molecules that keep us functioning,” says Chiba, principal investigator of this project. “Knowing how our cells work will improve medicine. Most importantly, we will gain a better understanding of what life is at the molecular level.”

Neurons are the cells that are mainly responsible for signaling in the brain. Like all other cells, each neuron produces millions of individual proteins that associate with one another and form a complex communication network. Until recently, observing these protein-protein interactions had not been possible due to technical difficulties. Individual proteins are small and typically less than 10 nm (nanometer) in diameter. Yet, this nano-scale distance was considered to be off-limits even with super-resolution microscopy.

Now, Chiba and his collaborators have developed a novel methodology to examine interaction of individual proteins in the fruit fly — the model organism of choice for this project. The researchers are creating genetically engineered insects that are capable of expressing over 500 fluorescently-tagged assorted proteins, two at a time. The fluorescent tags make it possible to visualize the exact spot where a given pair of proteins associates with each other.

The team utilizes a custom- built 3D FLIM (fluorescent lifetime imaging microscopy) system to quantify this association event within the cells of a live animal. FLIM shows the location and time of such protein interaction, providing the data that allow creation of a point-by-point map of protein-protein interactions.

The pilot phase of this multidisciplinary project is being funded by the National Institutes of Health. It employs advanced genetics, molecular imaging technology and high-performance computation, among other fields. “Collaborating fluorescent chemistry, laser optics and artificial intelligence, my team is working in the ‘jungle’ of the molecules of life within the living cells,” Chiba says. “This is a new kind of ecology played out at the scale of nanometers — creating a sense of deja vu 80 years after the birth of modern ecology.”

At present, the researchers still need to extrapolate from data obtained in test tubes. In the future, they will begin to visualize directly how the individual proteins interact with one another in their ‘native environment,’ which are the cells in our body.

Even unconsciously, sound helps us see

Imagine you are playing ping-pong with a friend. Your friend makes a serve. Information about where and when the ball hit the table is provided by both vision and hearing. Scientists have believed that each of the senses produces an estimate relevant for the task (in this example, about the location or time of the ball’s impact) and then these votes get combined subconsciously according to rules that take into account which sense is more reliable. And this is how the senses interact in how we perceive the world. However, our findings show that the senses of hearing and vision can also interact at a more basic level, before they each even produce an estimate,” says Ladan Shams, a UCLA professor of psychology, and the senior author of a new study appearing in the December issue of Psychological Science, a journal published by the Association for Psychological Science. “If we think of the perceptual system as a democracy where each sense is like a person casting a vote and all votes are counted (albeit with different weights) to reach a decision, what our study shows is that the voters talk to one another and influence one another even before each casts a vote.

(read more)