Brain Research Findings

Using functional connectivity MRI brain scanning, scientists at Washington University and the University of Chieti, have discovered an alteration in the brain's spontaneous background activity after it has learned a new task.

"Recent studies have shown that in the absence of any overt behaviour, and even during sleep or anaesthesia, the brain's spontaneous activity is not random, but organized in patterns of correlated activity that occur in anatomically and functionally connected regions," says senior author Dr. Maurizio Corbetta.

"The reasons behind the spontaneous activity patterns remain mysterious, but we have now shown that learning causes small changes in those patterns, and that these changes are behaviourally important," he added. _More at medindia

The researchers may have stumbled upon a crude neurological correlate of "automaticity", an adaptation of the brain to training, that allows conscious learning to become unconscious knowledge.

Using diffusion tensor imaging, UK researchers have demonstrated changes in white matter brain connectivity after subjects learned to juggle.

Johansen-Berg and colleagues scanned the brains of 48 volunteers who undertook to learn and practise juggling. None of the volunteers could juggle when they started their training which comprised one weekly training session and 30 minutes of daily practice for 6 weeks.

...At the end of the training period, the volunteers reached varying levels of juggling skill, but all those who trained and practised showed changes in white matter, suggesting it wasn't skill attainment that mattered but the time spent training and practising. _MNT

These findings should be studied by anyone connected with the education of children, adolescents, and adults.

Using mice and cell cultures, Stanford University researchers discovered an important mechanism for the formation of new synapses in the brain -- particularly in developing brains.

Stanford University researchers examined the interaction between neurons and brain cells called astrocytes. Previous studies showed that a protein that astrocytes secrete, thrombospondin, is critical to the formation of the brain's circuitry. In the study, researchers found that thrombospondin binds to a receptor, called alpha2delta-1, on the outer membrane of neurons. In a study in mice, they showed that the neurons that lacked alpha2delta-1 could not form synapses in response to the presence of thrombospondin.

Alpha2delta-1 is the receptor for gabapentin. That has been known, although scientists did not understand how gabapentin worked. But the new research revealed that when gabapentin was given to mice, it prevented thrombospondin from binding to the receptor, thus stopping the synapse formation.

While gabapentin, which is sold under the trade name Neurontin, does not dissolve pre-existing synapses, it prevents the formation of new ones. That's why the medication may be dangerous if given to pregnant women or young children, the authors said. The majority of the brain's synapses are formed in utero and early childhood. _LAT

Potentially an extremely important finding for neurologists and all those who care for pregnant women and fetuses.

Perhaps researchers can study the effects of drugs and other chemicals on the developing brain using microfluidic chips, "labs on a chip", being developed by labs around the world: ...Johns Hopkins University, where a lab on chip has been designed to mimic the chemical complexities of the brain; _newelectronics

Computer simulations are simply not up to the chemical and other complexities of the brain -- at any stage of development. It is likely that dynamic models in silicon, however, will eventually approach -- or exceed -- the reliability of animal models for brain research.

Complexity: When Computer Models Simply Will Not Do

Biological systems are too complex to be well-modeled by computers, currently. Medical personnel are on the front lines, saving lives. Society requires a far higher level of certainty of results from medical research than can be achieved by today's computer models.

Most biological models make use of lab animals such as mice or rats. But increasingly, acellular models are used. A fascinating type of biochip that allows placing various cellular components on a silicon dioxide surface--connecting them by microfluidic channels--promises to provide increasingly ingenious acellular models for biomedical research.

Now, in a major breakthrough, a group of researchers at the Weizmann Institute of Science in Israel, led by Roy Bar-Ziv, in collaboration with Margherita Morpurgo from the University of Padova in Italy, have designed a molecule affectionately called the “daisy” that is able to bind genes onto chips in miniature patterned arrays.

Bar-Ziv and co-workers have been able to use the daisy to pattern tiny regions of double-stranded DNA onto silicon dioxide surfaces. Indeed, these immobilized genes are able to conduct their business on patterned silicon substrates without the need for living cells. These biochips can act as protein microtraps, selectively trapping specific proteins from crude cell extracts with high spatial resolution. Moreover, the gene sequences immobilized on the biochips can be used for the on-chip production of proteins by transcription/translation processes such as those occurring within cells.

Bar-Ziv and his colleagues have also demonstrated the integration of these systems with microfluidics. Integration with flow systems is of interest for the fabrication of miniature assembly lines on chips, wherein proteins can be synthesized on the chips and transported to their final destinations through microfluidic channels.

In a remarkable demonstration of the utility of the daisy approach, the researchers have patterned two different genes as alternating stripes on a biochip. The protein synthesized on one stripe diffuses to the second stripe where it regulates the synthesis of a second protein. More complex artificial gene circuits can be envisioned by extending this protocol, and thus the biochips may be able to carry out complex cascaded information-processing functions, mimicking those in living organisms.

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While computer modeling may be sufficient for political organisations such as the IPCC and Greenpeace to predict an apocalyptic future for the earth, for down-to-earth bio-researchers who absolutely must provide reliable results, computers are simply not good enough. But bio-engineers, bio-physicists, and molecular biologists working with nanotechnologists are growing increasingly clever in designing useful models that do not use lab animals.

It will be many years before biomedical research no longer needs to sacrifice large numbers of lab animals for the saving of human life. But it is encouraging to see the creation of "artificial cells" on silicon, and it is fascinating to contemplate the possibilities they offer.