Posts tagged brain mapping
Articles and news from the latest research reports.
High-Resolution Mapping Technique Uncovers Underlying Circuit Architecture of the Brain
The power of the brain lies in its trillions of intercellular connections, called synapses, which together form complex neural “networks.” While neuroscientists have long sought to map these complex connections to see how they influence specific brain functions, traditional techniques have yet to provide the desired resolution. Now, by using an innovative brain-tracing technique, scientists at the Gladstone Institutes and the Salk Institute have found a way to untangle these networks. Their findings offer new insight into how specific brain regions connect to each other, while also revealing clues as to what may happen, neuron by neuron, when these connections are disrupted.
In the latest issue of Neuron, a team led by Gladstone Investigator Anatol Kreitzer, PhD, and Salk Investigator Edward Callaway, PhD, combined mouse models with a sophisticated tracing technique—known as the monosynaptic rabies virus system—to assemble brain-wide maps of neurons that connect with the basal ganglia, a region of the brain that is involved in movement and decision-making. Developing a better understanding of this region is important as it could inform research into disorders causing basal ganglia dysfunction, including Parkinson’s disease and Huntington’s disease.
“Taming and harnessing the rabies virus—as pioneered by Dr. Callaway—is ingenious in the exquisite precision that it offers compared with previous methods, which were messier with a much lower resolution,” explained Dr. Kreitzer, who is also an associate professor of neurology and physiology at the University of California, San Francisco, with which Gladstone is affiliated. “In this paper, we took the approach one step further by activating the tracer genetically, which ensures that it is only turned on in specific neurons in the basal ganglia. This is a huge leap forward technologically, as we can be sure that we’re following only the networks that connect to particular kinds of cells in the basal ganglia.”
At Gladstone, Dr. Kreitzer focuses his research on the role of the basal ganglia in Parkinson’s and other neurological disorders. Last year, he and his team published research that revealed clues to the relationship between two types of neurons found in the region—and how they guide both movement and decision-making. These two types, called direct-pathway medium spiny neurons (dMSNs) and indirect-pathway medium spiny neurons (iMSNs), act as opposing forces. dMSNs initiate movement, like the gas pedal, and iMSNs inhibit movement, like the brake. The latest research from the Kreitzer lab further found that these two types are also involved in behavior, specifically decision-making, and that a dysfunction of dMSNs or iMSNs is associated with addictive or depressive behaviors, respectively. These findings were important because they provided a link between the physical neuronal degeneration seen in movement disorders, such as Parkinson’s, and some of the disease’s behavioral aspects. But this study still left many questions unanswered.
“For example, while that study and others like it revealed the roles of dMSNs and iMSNs in movement and behavior, we knew very little about how other brain regions influenced the function of these two neuron types,” said Salk Institute Postdoctoral Fellow Nicholas Wall, PhD, the paper’s first author. “The monosynaptic rabies virus system helps us address that question.”
The system, originally developed in 2007 and refined by Wall and Callaway for targeting specific cell types in 2010, uses a modified version of the rabies virus to “infect” a brain region, which in turn targets neurons that are connected to it. When the system was applied in genetic mouse models, the team could see specifically how sensory, motor, and reward structures in the brain connected to MSNs in the basal ganglia. And what they found was surprising.
“We noticed that some regions showed a preference for transmitting to dMSNs versus iMSNs, and vice versa,” said Dr. Kreitzer. “For example, neurons residing in the brain’s motor cortex tended to favor iMSNs, while neurons in the sensory and limbic systems preferred dMSNs. This fine-scale organization, which would have been virtually impossible to observe using traditional techniques, allows us to predict the distinct roles of these two neuronal types.”
“These initial results should be treated as a resource not only for decoding how this network guides the vast array of very distinct brain functions, but also how dysfunctions in different parts of this network can lead to different neurological conditions,” said Dr. Callaway. “If we can use the rabies virus system to pinpoint distinct network disruptions in distinct types of disease, we could significantly improve our understanding of these diseases’ underlying molecular mechanisms—and get even closer to developing solutions for them.”
Past Brain Activation Revealed in Scans
Weizmann Institute scientists discover that spontaneously emerging brain activity patterns preserve traces of previous cognitive activity
What if experts could dig into the brain, like archaeologists, and uncover the history of past experiences? This ability might reveal what makes each of us a unique individual, and it could enable the objective diagnosis of a wide range of neuropsychological diseases. New research at the Weizmann Institute hints that such a scenario is within the realm of possibility: It shows that spontaneous waves of neuronal activity in the brain bear the imprints of earlier events for at least 24 hours after the experience has taken place.
The new research stems from earlier findings in the lab of Prof. Rafi Malach of the Institute’s Neurobiology Department and others that the brain never rests, even when its owner is resting. When a person is resting with closed eyes – that is, no visual stimulus is entering the brain – the normal bursts of nerve cell activity associated with incoming information are replaced by ultra-slow patterns of neuronal activity. Such spontaneous or “resting” waves travel in a highly organized and reproducible manner through the brain’s outer layer – the cortex – and the patterns they create are complex, yet periodic and symmetrical.
Like hieroglyphics, it seemed that these patterns might have some meaning, and research student Tal Harmelech, under the guidance of Malach and Dr. Son Preminger, set out to uncover their significance. Their idea was that the patterns of resting brain waves may constitute “archives” for earlier experiences. As we add new experiences, the activation of our brain’s networks lead to long-term changes in the links between brain cells, a facility referred to as plasticity. As our experiences become embedded in these connections, they create “expectations” that come into play before we perform any type of mental task, enabling us to anticipate the result. The researchers hypothesized that information about earlier experiences would thus be incorporated into the links between networks of nerve cells in the cortex, and these would show up in the brain’s spontaneously emerging wave patterns.
In the experiment, the researchers had volunteers undertake a training exercise that would strongly activate a well-defined network of nerve cells in the frontal lobes. While undergoing scans of their brain activity in the Institute’s functional magnetic resonance imaging (fMRI) scanner, the subjects were asked to imagine a situation in which they had to make rapid decisions. The subjects received auditory feedback in real time, based on the information obtained directly from their frontal lobe, which indicated the level of neuronal activity in the trained network. This “neurofeedback” strategy proved highly successful in activating the frontal network – a part of the brain that is notoriously difficult to activate under controlled conditions.
To test whether the connections created in the brain during this exercise would leave their traces in the patterns formed by the resting brain waves, the researchers performed fMRI scans on the resting subjects before the exercise, immediately afterward, and 24 hours later. Their findings, which appeared in the Journal of Neuroscience, showed that the activation of the specific areas in the cortex did indeed remodel the resting brain wave patterns. Surprisingly, the new patterns not only remained the next day, they were significantly strengthened. These observations fit in with the classic learning principles proposed by Donald Hebb in the mid-20th century, in which the co-activation of two linked nerve cells leads to long term strengthening of their link, while activity that is not coordinated weakens this link. The fMRI images of the resting brain waves showed that brain areas that were activated together during the training sessions exhibited an increase in their functional link a day after the training, while those areas that were deactivated by the training showed a weakened functional connectivity.
This research suggests a number of future possibilities for exploring the brain. For example, spontaneously emerging brain patterns could be used as a “mapping tool” for unearthing cognitive events from an individual’s recent past. Or, on a wider scale, each person’s unique spontaneously emerging activity patterns might eventually reveal a sort of personal profile – highlighting each individual’s abilities, shortcomings, biases, learning skills, etc. “Today, we are discovering more and more of the common principles of brain activity, but we have not been able to account for the differences between individuals,” says Malach. “In the future, spontaneous brain patterns could be the key to obtaining unbiased individual profiles.” Such profiles could be especially useful in diagnosing or learning the brain pathologies associated with a wide array of cognitive disabilities.
Scientists discover previously unknown requirement for brain development
Scientists at the Salk Institute for Biological Studies have demonstrated that sensory regions in the brain develop in a fundamentally different way than previously thought, a finding that may yield new insights into visual and neural disorders.
In a paper published June 7, 2013, in Science, Salk researcher Dennis O’Leary and his colleagues have shown that genes alone do not determine how the cerebral cortex grows into separate functional areas. Instead, they show that input from the thalamus, the main switching station in the brain for sensory information, is crucially required.
O’Leary has done pioneering studies in “arealization,” the way in which the neo-cortex, the major region of cerebral cortex, develops specific areas dedicated to particular functions. In a landmark paper published in Science in 2000, he showed that two regulatory genes were critically responsible for the general pattern of the neo-cortex, and has since shown distinct roles for other genes in this process. In this new set of mouse experiments, his laboratory focused on the visual system, and discovered a new, unexpected twist to the story.
"In order to function properly, it is essential that cortical areas are mapped out correctly, and it is this architecture that was thought to be genetically pre-programmed," says O’Leary, holder of the Vincent J. Coates Chair in Molecular Neurobiology at Salk. "To our surprise, we discovered thalamic input plays an essential role far earlier in brain development."
Vision is relayed from the outside world into processing areas within the brain. The relay starts when light hits the retina, a thin strip of cells at the back of the eye that detects color and light levels and encodes the information as electrical and chemical signals. Through retinal ganglion cells, those signals are then sent into the Lateral Geniculate Nucleus (LGN), a structure in thalamus.
In the next important step in the relay, the LGN routes the signals into the primary visual area (V1) in the neo-cortex, a multi-layered structure that is divided into functionally and anatomically distinct areas. V1 begins the process of extracting visual information, which is further carried out by “higher order” visual areas in the neo-cortex that are vitally important to visual perception. Like parts in a machine, the functions of these areas are both individual and integrated. Damage in one tiny area can lead to strange visual disorders in which a person may be able to see a moving ball, and yet not perceive it is in motion.
Current dogma holds that this basic architecture is entirely genetically determined, with environmental input only playing a role later in development. One of the most famous examples of this idea is the Nobel Prize-winning work of visual neuroscientists David Hubel and Torsten Wiesel, which showed that there is a “critical period” of sensitivity in vision. Their finding was commonly interpreted as a warning that without exposure to basic visual stimuli early in life, even an individual with a healthy brain will be unable to see correctly.
Later discoveries in neural plasticity more optimistically suggested that early deprivation can be overcome, and the brain can even sprout new neurons in specific areas. Nevertheless, this still reinforced the idea that environmental influences might modify neural architecture, but only genetics could establish how cortical areas would be laid out.
In their new study, however, O’Leary and the paper’s co-first authors, Shen-Ju Chou and Zoila Babot, post-doctoral researchers in O’Leary’s laboratory, show that genetics only provides a broad field in the neo-cortex for visual areas.
When they created mouse mutants that disconnected the link between thalamus and cortex but only after early cortical development was complete, they found that the primary and higher order visual areas failed to differentiate from one another as they should.
"Our new understanding is that genes only create a rough lay-out of cortical areas," explains O’Leary. "There must be thalamic input to develop the fine differentiation necessary for proper sensory processing."
Essentially, if the brain were a house, genes would determine which areas were bedrooms. Thalamic input provides the details, distinguishing what will be the master bedroom, a child’s bedroom, a guest bedroom and so on. “The size and location of areas within the overall cortex does not change, but without thalamic input from the LGN, the critical differentiation process that creates primary and higher order visual areas does not happen,” says O’Leary.
Given that most sensory modalities—sight, hearing, touch—route through thalamus to cortex, this experiment may suggest why, when someone lacks a sensory modality from birth, that individual has a harder time processing restored sensory input than someone who lost the sense later in life. But in addition, as O’Leary says, “More subtle changes in thalamic input in humans would also likely result in changes to the neo-cortex that could well have a substantial impact on the ability to process vision, or other senses, and lead to abnormal behavior.”
O’Leary says his lab plans to continue to explore the links between how cortical areas in the brain are established and various developmental disorders, such as autism.
(Image: Nucleus Medical Art, Inc.)
"BigBrain" Study Provides Most Detailed 3-D Map of the Brain Yet
A landmark three-dimensional digital reconstruction of a complete human brain, called the BigBrain, shows the brain anatomy in microscopic detail at a spatial resolution of 20 micrometers—smaller than the size of one fine strand of hair.
The reconstruction, published in the 21 June issue of the journal Science, exceeds the resolution of all existing reference brains presently in the public domain, and will be made freely available to the broader scientific community.
The fine-grained anatomical resolution of the BigBrain will allow scientists who use it to gain insights into the neurobiological basis of cognition, language, emotions and other processes, according to the study. The anatomical tool yielded by the researchers will serve as an atlas for neurosurgery and provide a framework for research in many directions, including enhanced understanding of brain diseases, such as Alzheimer’s disease.
"It is a common basis for scientific discussions because everybody can work with this brain model," said Science co-author Karl Zilles, senior professor of the Jülich Aachen Research Alliance.
The new reference brain, which is part of the European Human Brain Project, “redefines traditional maps from the beginning of the 20th century,” explained lead author Katrin Amunts from the Research Centre Jülich. Amunts serves as director of the Cecile and Oskar Vogt Institute for Brain Research at the Heinrich Heine University Düsseldorf in Germany.
"The authors pushed the limits of current technology," said Science Senior Editor Peter Stern. Existing reference brains do not probe further than the macroscopic, or visible, components of the brain. The BigBrain provides a resolution much finer than the typical 1 millimeter resolution from MRI studies. "The spatial resolution the researchers achieved exceeds that of presently available reference brains by a factor of 50," said Stern.
"Of course, we would love to have spatial resolution going down to 1 micrometer," said Amunts in a 19 June press teleconference. However, "there are simply no computers at this moment which would be capable to process such data, to visualize this or to analyze it."
To create the detailed brain atlas, Amunts and colleagues took advantage of new advances in computing capacities and image analysis. Using a special tool called a microtome, they carefully cut the paraffin-covered brain of a 65-year-old female into 20 micrometer-thick sections.
The project was “a tour-de-force to assemble images of over 7400 individual histological sections, each with its own distortions, rips and tears, into a coherent 3-D volume,” said Science co-author Alan Evans, a professor at the Montreal Neurological Institute at McGill University in Montreal, Canada.
The sections were mounted on slides, stained to detect cell structures and finally digitized with a high-resolution flatbed scanner so researchers could reconstruct the high-resolution 3-D brain model. It took approximately 1000 hours to collect the data.
The researchers’ future plans for using the map include extracting measurements of cortical thickness to gain insights into aging and neurodegenerative disorders. Eventually, Amunts and colleagues hope to build a brain model at the resolution of 1 micron to capture details of single cell morphology. Detailed brain maps can aid researchers who are exploring the full set of neural connections and real-time brain activity, as scientists discussed recently in a Capitol Hill briefing sponsored by AAAS.
The creation of such a detailed brain map, offering a gateway to unprecedented insights into the brain’s anatomy and organization, was long in the works. “It was a dream for almost 20 years,” Amunts said. “The dream came true because of an interdisciplinary and intercontinental collaboration spanning from Europe to Canada and from neuroanatomy to supercomputing .”
Though not directly related to the BRAIN Initiative announced by President Barack Obama earlier this year, the work by Amunts and colleagues supports the Initiative’s goal of giving scientists the best possible tools with which to obtain a dynamic picture of the brain.
Validating maps of the brain’s resting state
Kick back and shut your eyes. Now stop thinking.
You have just put your brain into what neuroscientists call its resting state. What the brain is doing when an individual is not focused on the outside world has become the focus of considerable research in recent years. One of the potential benefits of these studies could be definitive diagnoses of mental health disorders ranging from bipolar to post-traumatic stress disorders.
A team of psychologists and imaging scientists at Vanderbilt has collaborated on a study that provides important corroboration of the validity of recent research examining the relationship of functional magnetic resonance imaging or fMRI maps of the brain’s resting state networks with it’s underlying anatomical and neurological structure. The study is published in the June 19 issue of the journal Neuron.
“Previous studies have suggested that resting state connectivity shown in brain scans is anchored by anatomical connectivity,” said co-senior author Anna Roe, professor of psychology at Vanderbilt. “But our study has confirmed this relationship at the single neuron level for the first time.”
For the last decade, neuroscientists have been using the non-invasive brain-mapping technique fMRI to examine activity patterns in human and animal brains in the resting state in order to figure out how different parts of the brain are connected and to identify the changes that occur in neurological and psychiatric diseases. For example, there are indications that Alzheimer’s may be associated with decreased connectivity; depression with increased connectivity; epilepsy with disruptions in connectivity and Parkinson’s with alterations in connectivity.
The new findings from Vanderbilt are important because fMRI doesn’t measure brain activity directly. It does so by measuring changes in blood-oxygen levels in different areas. The technique relies on the observation that when activity in an area of the brain increases, blood-oxygen levels in that region rise, which modulates the MRI signal. Neuroscientists have taken this a step further by assuming that different areas in the brain are connected if they show synchronized variations while the brain is in a resting state.
“This is an important validation,” said co-senior author John Gore, director of the Institute of Imaging Science at Vanderbilt and Hertha Ramsey Cress University Professor of Radiology and Radiological Sciences and Biomedical Engineering. “There has always been a sense of unease that we might be interpreting something incorrectly but this gives us confidence that resting state variations can be interpreted in a meaningful way and encourages us to continue the research we have been doing for a number of years. Resting state fMRI provides a uniquely powerful, non-invasive technology to look at the circuits in the human brain.”
To examine the relationship between fMRI scans, patterns of neuronal activity and anatomical structure of the brain, the researchers examined the region of the parietal lobe of squirrel monkeys devoted to monitoring touch sensations. Specifically, they looked at an area linked to the hand that consists of a series of adjacent areas each devoted to a different finger.
Using one of the strongest MRI machines available, with a field strength three to six times that of typical clinical scanners, the researchers produced brain scans that resolved millimeter-scale networks for the first time.
To compare these patterns to the actual electrical activity in the brains, the researchers inserted electrodes capable of recording the firing patterns of individual neurons. In addition, they used optical techniques to trace the anatomical connections between the neurons throughout the region.
“With all three techniques, we found the same pattern of connectivity. Connections coming from other areas in the brain tend to link to individual digits while connections that originate within the area tend to link to multiple digits,” said Roe. “Our results demonstrate that fMRI images of the resting state brain accurately reflect the brain’s anatomical and functional connectivity down to an extremely fine scale.”
Freiburg Researchers Use Signals from Natural Movements to Identify Brain Regions
Whether we run to catch a bus or reach for a pen: Activities that involve the use of muscles are related to very specific areas in the brain. Traditionally, their exact location has only been determined through electrical stimulation or unnatural, experimental tasks. A team of scientists in Freiburg has now succeeded for the first time in mapping the brain’s surface using measurements of everyday movements.
Attributing abilities to specific brain regions and identifying pathological areas is especially important in the treatment of epilepsy patients, as severe cases require removal of neural tissue. Until now, such “mapping” involved stimulating individual regions of the brain’s surface with electric currents and observing the reaction or sensation. Alternatively, patients were asked to perform the same movements again and again until the physicians isolated the corresponding patterns in brain activity. However, these methods required for the patient to cooperate and to provide detailed answers to the physicians’ questions. This is a prerequisite that small children or patients with impaired mental abilities can hardly meet, and hence there is a need for other strategies.
Scientists from the group of Dr. Tonio Ball at the Cluster of Excellence “BrainLinks-BrainTools” and the Bernstein Center Freiburg report in the current issue of NeuroImage that the brain’s natural activity during everyday movements can also be used to reliably identify the regions responsible for arm and leg movements.
The researchers examined data from epilepsy patients who had electrodes implanted under their skull prior to surgery. Using video recordings, the team captured the spontaneous movements of their patients, searching for concurrent signals of a certain frequency in the data gathered on the surface of the brain. They succeeded in creating a map of the brain’s surface for arm and leg movements that is as accurate as those created through established experimental methods.
A big hope for the team of researchers is also to gain new insights into the control of movements in the brain, as their method allows them to explore all manner of behaviors and is no longer limited to experimental conditions. Last but not least, the scientists explain that this new method of analyzing signals from the brain will contribute to the development of brain-machine interfaces that are suitable for daily use.
Physicist’s tool has potential for brain mapping
A new tool being developed by UT Arlington assistant professor of physics could help scientists map and track the interactions between neurons inside different areas of the brain.
The journal Optics Letters recently published a paper by Samarendra Mohanty on the development of a fiber-optic, two-photon, optogenetic stimulator and its use on human cells in a laboratory. The tiny tool builds on Mohanty’s previous discovery that near-infrared light can be used to stimulate a light-sensitive protein introduced into living cells and neurons in the brain. This new method could show how different parts of the brain react when a linked area is stimulated.
The technology would be useful in the BRAIN mapping initiative recently championed by President Barack Obama, Mohanty said. BRAIN stands for Brain Research Through Advancing Innovative Neurotechnologies and will include $100 million in government investments in research.
“Scientists have spent a lot of time looking at the physical connections between different regions of the brain. But that information is not sufficient unless we examine how those connections function,” Mohanty said. “That’s where two-photon optogenetics comes into play. This is a tool not only to control the neuronal activity but to understand how the brain works.”
The two-photon optogenetic stimulation described in the Optics Letter paper involves introducing the gene for ChR2, a protein that responds to light, into a sample of excitable cells. A fiber-optic infrared beam of light can then be used to precisely excite the neurons in a tissue circuit.
In the brain, researchers would then observe responses in the excited area as well as other parts of the neural circuit. In living subjects, scientists would also observe the behavioral outcome, Mohanty said.
Optogenetic stimulation avoids damage to living tissue by using light to stimulate neurons instead of electric pulses used in past research. Mohanty’s method of using low-energy near-infrared light also enables more precision and a deeper focus than the blue or green light beams often used in optogenetic stimulation, the paper said.
Using fiber optics to deliver the two-photon optogenetic beam is another advance. Previous methods required bulky microscopes or complex scanning beams. Mohanty’s group is collaborating with UT Arlington Department of Psychology assistant professor Linda Perrotti to apply this technology in living animals.
“Dr. Mohanty’s innovations continue to be recognized because of the great potential they hold,” said Pamela Jansma, dean of the UT Arlington College of Science. “Hopefully, his work will one day provide researchers in other fields the tools they need to examine how the human body works and why normal processes sometimes fail.”
(Image: Shutterstock)
Neuroscientists put heads together at national brainstorming session
This week over 150 neuroscientists were invited to meet in Arlington, Virginia to discuss the finer points of President Obama’s recently announced BRAIN Initative. Rather than discuss funding particulars, each participant was given the chance to broadly declare what they thought needed to be done in neuroscience. At least 75 of the participants initially responded to a request for a short white paper outlining the major obstacles currently impeding neuroscience research. A live webcast of some of the key talks was available, although many of the smaller workshops were held in private. Fortunately, updates regarding the content discussed at these workshops was posted live to twitter under the handle @openconnectome. This precipitated lively discussion, primarily under the hashtags #nsfBRAINmtg or #braini, and provided a way for a larger audience to be involved.
The working title of this inaugural NSF meeting was Physical and Mathematical Principles of Brain Structure and Function. In actuality, there was little discussion of all that, and for good reason—no such principles have been shown to exist. Even more concerning, only a few principles have ever even been proposed. Simplistic scaling laws dealing with connectivity, particularly within sensory systems or the cortex, have been suggested in the past. Generally they seek to account for only one or two structural parameters at a time, like for example, axon diameter and branching order. Typically, the chosen parameters are only considered in the context of optimizing a single physical variable, like for example, electrotonic function. While these efforts are a start, they usually do not garner much attention from the larger neuroscience community.
The early days of neuroscience were marked with the assertion of many principles and laws. They served well to focus ideas, but over time, they lost much of their original perceived generality. For example, concepts like one transmitter type per neuron, and no new neurons in adult brains later proved to have significant exceptions. The early breakthrough days in neuroscience have now given way to a grant system that stifles imagination, and by its competitiveness, encourages fraud. Many of the speakers at the BRAIN Initiative meeting have called for new tools and theories, but in most cases, they have offered only little has been offered. Instead of expanding the range acceptable pursuits, their vision appears to have imploded inward with calls for increased rigor, statistical power, diversity of animal models, experimental falsifiability, and most of all, data, on an increasingly limited range of ideas.
A lot of talk was given to the resolution at which connectivity, and activity maps should be detailed. Similar points were made for the need to develop electrode arrays of higher density and durability to more accurately record function. The ample discussion of an ideal animal model was punctuated by the notable advances made this year in whole brain recordings from Zebrafish, and also from large scale connectivity mapping now possible in small mammals with the new CLARITY transparent brain techniques. The general lack of agreement and clear path forward as to which organisms among many are ideal here was noted by representatives from several funding bodies who spoke at the meeting. Highlighting points made earlier in a talk by George Whitesides, they stressed the need to come to forward with a concrete plan that is comprehensible not only to the funding organizations, but the larger public as well.
Many discussions focused on brain mechanisms, like for example, how many neurons might contribute to a particular function. One participate, David Kleinfeld, called for a study of how many neurons are involved in communication at different scales. He also stressed the importance of looking at basic systems involving feedback, such as the brain stem and spinal cord, and their dynamic interaction with muscle. Michael Stryker observed that the goal should not be recording from the most neurons, and storing the most data, but rather finding the right neurons.
While it was not explicitly stated, a lot of the talk begged the conclusion that the answers to the questions we have will not be answered with animal studies. Knowing what a neuron does is itself an ill-posed question. In worms and flies, where the inputs and outputs of single neurons can be mapped to static sensory and motor functions in the real world, we might know what that neuron does. However in larger, human brains, we can ask an even better question—what does the neuron feel like? In most cases that answer will likely be, nothing.
If however, in a given human brain, a single neuron critically poised within that brain’s structural hierarchy can be stimulated to observable effect, some measure of its function has been gained. That effect might be a simple itch or twitch. Less plausibly perhaps it could be seeing a picture of a face undergo a change, sensing fear, or even imagining your grandmother. If that turns out not to be possible for most single neurons, we already know that we can find some minimal group of neurons where stimulation has uniquely perceivable effects.
While understanding the brain on different scales is important, the most rewarding endeavors likely exist where functionality can be correlated across those scales. Behavior at the scale of the organism within a given environment is readily observable. At the next scale down, the behavior of neurons witnessed by its spikes and structural alterations, is only observable now in part. Below the scale of the neuron, the mitochondria and other organelles move with a purpose and relation to activity of the neuron that has only been imagined, but is experimentally addressable.
Several speakers also mentioned the idea of a neural code. Spikes are a convenient metric for assessing brain activity, and we should seek to correlate their occurrence with behaviors on various scales mentioned above. They are a universal and non-local currency, among others in the brain, that inflates rapidly with stimulation and arousal. Unfortunately, the most logical conclusion for us must be that there is no code for spikes. Anyone attempting to observe and record a code for one neuron would probably find that it has, in short order, become unrecognizable, particularly in the context of the next. There are however constraints on spikes, and on neurons, and while considerable mention of the word was made at the meeting none were detailed in depth.
To formulate constraints on a system, at a level we don’t understand, we might look at constraints on other systems that we have some knowledge about. Neurons are neither wholly like ants, nor tress, but share some aspects of both. Similarly brains are neither like ant colonies, or forests, but shares some features in common. The most obvious constraint that comes to mind, and applies to these systems at every level, is energy. A subtle refinement of that is the concept of entropy generation. One key idea is that entropy generation at different scales, while proceeding according to as yet determined laws, need not necessarily maximize entropy at each point in time, but rather along paths through time.
A voice heard throughout the conference was that of Bill Bialek who diffusely observed that attempts to apply the laws of statistical mechanics to aspects of brain functions are not very productive because the brain is not at an equilibrium state. That would have been a good sentence to begin the conference perhaps rather than end it. Hopefully, the next NSF meeting will be a little more transparent to the public than the first. A more thorough webcast, with uploading to a media channel would be desirable to many who like to participate, as would a path for two-way communication on the issues. Mention should also be made of the efforts of a few neuroscientists peripheral to the BRAIN Initiative that have been maintaining important blog discussions, and metablog publication lists to track the progress made over last few months. This morning, NIH announced a new website has just been set up to provide additional public feedback.
(Source: medicalxpress.com)
Australian scientists map mouse brains in greatest detail yet
Hopes for a cure for many brain diseases may rest on the humble mouse, now that scientists can map the rodents’ brains more thoroughly than ever before.
Researchers at The University of Queensland’s Centre for Advanced Imaging (CAI) and Curtin University have created the most detailed atlas of the mouse brain, a development that is helping in the fight against brain disease.
This new tool will allow researchers to map what parts of the brain are affected in mouse models of brain disease – such as brain cancer, Parkinson’s disease and Alzheimers disease, which affect nearly 1 in 6 of the world’s population.
Lead author, Dr Jeremy Ullmann said that the new brain atlas provided a fundamental tool for the neuroscience community.
“The mouse is now the most widely used animal model for neuroscience research and magnetic resonance imaging (MRI) is fundamental to investigating changes in the brain,” Dr Ullman said.
“Our atlas is already much in demand internationally because it allows researchers to use MRI to automatically map brain structures.”
The atlas was created in the laboratory of Professor David Reutens, CAI Director.
“In making these world-first maps, we had the advantage of using the most powerful MRI scanners in the Southern Hemisphere, backed up by leaders in digital image analysis, resulting in remarkably clear images of the brain,” Professor Reutens said.
The project’s lead neuroanatomist, Professor Charles Watson from Curtin University, believes that the study will open the door to accurate analysis of gene targeting in the mouse brain.
“The invention of gene targeting in the mouse has made this species the centrepiece of studies on models of human brain disease. MRI allows researchers to follow changes in the brain over time in the same animals,” Professor Watson said.
The atlas was recently described in an article published in the journal NeuroImage.
Mapping The Brain Onto The Mind
BRAIN initiative aims to improve tools for studying neurons to answer questions about human thought and behavior
The images appearing on the computer screen were almost too detailed and fast-moving to take in, Misha B. Ahrens remembers. He and colleague Philipp J. Keller were recording the activity of about 80,000 neurons in a live zebrafish brain, the first time something on this scale had been done. Cross-sectional pictures of the young fish’s head flew by, dotted with splotches of light.
The Howard Hughes Medical Institute (HHMI) neuroscientists were using a zebrafish larva with a fluorescent protein inserted in its neurons, and the protein was lighting up every time the cells fired. Their custom-built microscope imaged and recorded the resulting lightning storm in the fish’s brain in real time.
Ahrens commemorated the milestone experiment—which took place nearly seven months ago in a lab at the institute’s Janelia Farm Research Campus outside Washington, D.C.—by filming it with his iPhone. “It was mind-blowing to see the entire brain flash past our eyes,” he remembers.
Keller sat in awe at the computer, repeatedly pulling up and admiring slices of data the high-speed apparatus was collecting. The translucent zebrafish, immobilized in a glass tube filled with gel and nestled among the microscope’s optics, was completely unaware that its neural processing was causing such a stir.
Up until that point, scientists had been able to record simultaneous activity from only about 2 to 3% of the 100,000 neurons in a young zebrafish’s head, Keller says. He and Ahrens managed to capture 80%—a giant leap for fishkind.
On March 18, the duo reported their brain-imaging feat online at Nature Methods. Just 15 days later, President Barack Obama announced a large-scale neuroscience initiative to study the dynamics of brain circuits (C&EN, April 8, page 9).
Unlike the Human Connectome Project—a federal program that strives to uncover a static map of the brain’s circuits—this new initiative aims to uncover those circuits’ activity and interplay. BRAIN (Brain Research through Advancing Innovative Neurotechnologies), as the project is called, will get $100 million in federal support if Obama’s request is granted (see page 25), and it will get a similar amount from private foundations such as HHMI in 2014.
“It was a coincidence,” Keller says of the timing of the proposal. He and Ahrens weren’t involved in developing BRAIN, but their goal—to record all the activity from all the neurons in a simple organism’s brain at once—falls directly in line with the initiative.
Eighty-thousand neurons is a lot. But it’s nothing compared with the 85 billion nerve cells that humans have in their brains, or even the 75 million that mice have. To make the leap to measuring large swaths of the brain circuits of rodents or even humans, BRAIN researchers will need to develop new methods of measuring neuronal activity. They are already working on molecular tags to more accurately indicate nerve cell firing in real time. And scientists are developing miniaturized probes to monitor brain cells without disturbing the organ itself, as well as faster techniques for analyzing the flood of data generated by such a huge number of neurons.
Some imaging methods that monitor multitudes of neurons, like that of Ahrens and Keller, already exist. As do techniques for probing scads of nerve cells with tiny electrodes. BRAIN will likely build on these technologies, experts say. But it will also shoot to build “dream” technologies such as implantable nanomaterials that transmit the activity of individual neurons from inside the head.
At the moment, however, no one knows the exact scope of BRAIN. The National Institutes of Health has already appointed a team of neuroscientists to draw up a blueprint for what should be a multiyear initiative. Other federal agencies involved—the National Science Foundation and the Defense Advanced Research Projects Agency—have yet to announce their strategies.
“Neuroscience is getting to the point where researchers cannot take the next big step to understand neural circuits armed with traditional technology,” says Rafael Yuste, a neuron-imaging expert at Columbia University.
And taking that step, he argues, is vital to understanding human thought. “We have a suspicion that the brain is an emerging system,” Yuste says. In other words, how the brain produces memories or actions involves the interactions of all its neurons, rather than just one or even 1,000. It’s like watching television, Yuste adds. “You need to see all the pixels, or at least most of them, to figure out what’s playing.”
Along with five other scientists, Yuste made the original pitch for a public-private project to map the brain’s dynamics in a 2012 article in Neuron. The group argued that not only could this approach help reveal how the human mind works, but it might also offer some insight into what happens when the brain malfunctions. Knowing how the brain’s circuits are supposed to function, Yuste says, could help pinpoint what’s going wrong in conditions such as schizophrenia, which likely involve faulty circuitry.
BRAIN proponents also say areas outside of science and medicine could profit from the initiative. If successful, they claim, BRAIN could yield economic benefits similar to the Human Genome Project, a program launched in 1990 to sequence all the base pairs in a person’s DNA. “Every dollar we spent to map the human genome has returned $140 to our economy,” President Obama noted when he announced BRAIN.
As was the case for the Human Genome Project, BRAIN has been criticized by many scientists. In an already-tight fiscal climate, some researchers have voiced worries that paying for the initiative will mean losing their own funds. And others have expressed reservations that the project is going after too many neurons to yield interpretable, useful results.
But no one seems to dispute that better tools to record activity from nerve cells is a worthwhile goal. “There’s definitely room to grow in many of the techniques we use to record brain activity,” says Mark J. Schnitzer, a neuroscientist at Stanford University. So far, he says, progress has been made mainly by individual labs doing their own thing. But to get to the next level more rapidly, a coordinated effort like BRAIN—centers and labs of neuroscientists, chemists, and researchers in other disciplines working together—might be the ticket.
Until recently, the number of neurons being recorded simultaneously in experiments was doubling every seven years, according to a 2011 review in Nature Neuroscience. But the Janelia team blew this trend out of the water with its high-speed camera and microscope, which rapidly illuminates and images slices of the brain.
The Janelia experiment worked primarily because zebrafish larvae are transparent to light and can be easily immobilized without negative consequences to their brain activity. But moving to mice, which have more neurons and a light-impenetrable skull, will require some more serious innovation, Keller adds.
Some researchers have designed implantable prisms and fiber-optic probes to direct light into the depths of the mouse brain. But those optical tricks are still limited to measuring a few hundred neurons at once. Plus, the mouse has to be tethered to the fibers or prevented from moving altogether.
Stanford’s Schnitzer has overcome the mobility issue with a miniaturized microscope that he and his team designed to fit onto a mouse’s head. Standing three-quarters of an inch tall, the lightweight device, which contains its own light source and camera, gets implanted into the rodent’s brain, enabling researchers to track the freely moving animal’s nerve cell activity.
Early this year, Schnitzer’s group used the setup to follow the dynamics of roughly 1,000 neurons in a mouse’s brain for more than a month (Nat. Neurosci., DOI: 10.1038/nn.3329). The team learned that neurons in one part of the mouse’s brain fired in similar patterns whenever the mouse returned to a familiar spot in its enclosure.
Still, such optical techniques are invasive. “The most elegant experiment would be done from the outside, without mechanical disturbance to the brain,” Columbia’s Yuste says. He’d like to see BRAIN help develop new light sources that can penetrate farther into brain tissue than a few millimeters.
Also on Yuste’s neuron-imaging wish list is a better way to indicate cell firing. As in the Janelia experiment and Schnitzer’s microscope study, the imaging of neuronal activity is typically carried out with calcium indicators. These are molecules that move to the insides of neurons or are proteins engineered to reside there, both designed to fluoresce when they bind to calcium ions.
As a nerve cell fires, its ion channels open, allowing calcium ions to trickle inside and trigger the indicators.
However, “calcium imaging is flawed,” Yuste says. “It’s an indirect method of tracking neuronal firing.” The indicators can’t tell scientists whether a nerve cell fired a little or a lot, he argues. And they don’t track the cells’ electrical activity in real time because calcium diffusion and binding are comparatively slow.
So Yuste and others are working to develop dyes or nanomaterials, called voltage indicators, that bind within a neuron’s membrane and optically signal the cell’s electrical status. Progress is slow-going, however, because a cell’s membrane can hold only so many indicators on its surface and the resulting signal is low.
Another way neuroscientists are more directly measuring nerve cells’ electrical activity is with miniaturized electrodes and nanowires. These probes measure, at submillisecond speeds, the electrical current emitted by a neuron when it fires.
“But anytime you plunge anything into the brain, you have to worry about tissue damage,” says Sotiris Masmanidis, a neurobiologist at the University of California, Los Angeles. “The concern is, how much are you perturbing the system you’re studying?”
To minimize tissue disturbance, Masmanidis and others are lithographically fabricating arrays of microelectrodes that can record nerve cells’ electrical signals from 50 to 100 µm away. So far, the UCLA researcher says, electrode arrays are capable of measuring, at most, 100 to 1,000 neurons at a time.
Determining what types of nerve cells an arrayed microelectrode is measuring, however, is not exactly straightforward, given that it blindly measures any neuron in its vicinity, Masmanidis says. To figure it out, scientists have to take extra steps and monitor the cells’ reaction to drugs or other modulators.
But what good is measuring the dynamics of a slew of nerve cells without having any idea why they’re firing? BRAIN supporters think one way of getting an answer to which environmental cues or perceptions trigger certain neuronal activity patterns is a technique called optogenetics.
Hailed by Nature Methods as the “method of the year” in 2010, optogenetics enables scientists to activate particular nerve cells in the brains of animals with light. The researchers first engineer light-activated proteins into a mouse’s neurons and then trigger the macromolecules via fiber-optic arrays implanted in the rodent’s brain.
Once researchers have measured a firing pattern from an animal’s nerve cells, they can later play it back to see what happens, says Edward S. Boyden, an optogenetics pioneer and neurobiologist at Massachusetts Institute of Technology. “Once we ‘dial’ an activity pattern into the brain,” he says, “if we see that it’s enough to drive some behavior, that could be quite powerful for understanding which parts of the brain drive specific functions.”
Researchers have already been optogenetically stimulating clusters of a few hundred cells in mice, investigating the rodents’ decision-making abilities and aggressive tendencies.
But a brain is more than just electrical activity, says Anne M. Andrews, a psychiatry professor at UCLA. It also uses at least 100 types of neurotransmitters that are involved in triggering neuronal activity at cell junctions, or synapses. “If we want to understand how information is encoded in neuronal signaling, we have to study chemical neurotransmission at the level of synapses,” Andrews says.
And what better way to do that than with nanotechnology? asks Paul S. Weiss, a chemist and nanoscience expert, also at UCLA. After all, the junctions between neurons are just 10 nm wide, he adds.
Andrews and Weiss are hoping BRAIN will support the development of nanoscale sensors to measure the chemical activity at synapses. And they’re already in talks with UCLA’s Masmanidis to functionalize channels on his microelectrodes with molecules that could sense neurotransmitters.
No matter what BRAIN ends up encompassing, one thing is clear: Advances in the numbers of neurons monitored will necessitate improvements in data analysis and storage.
Take, for instance, the experiment done at Janelia. That single session of recording from a zebrafish brain generated 1 terabyte of data. “So you can fit two or three experiments on a computer hard drive,” Ahrens says. “It’s not a bottleneck yet, but when we start creating faster microscopes, computational power might become a problem.”
He and Keller also have just scratched the surface when it comes to analyzing the data they obtained from their initial experiments. As they reported in their Nature Methods paper, the pair found a circuit in the fish’s hindbrain functionally coupled to a specific part of its spinal cord. But determining what that means and what the rest of the brain is doing will require more study and help from computational neuroscientists.