Neuroscience - US ad feature
http://www.newscientist.com/channel/opinion/careers/dn12881-neuroscience--us-ad-feature.html
It has to be the biggest neural networking opportunity of the year, when the collective brains of the
world's largest neuroscientific organization, the Society for Neuroscience, gather for its annual meeting.
This year, the San Diego sunshine is likely to attract a high head count of cerebral researchers, who will
spend four-and-a-half days discussing the latest results and ideas from every conceivable corner of
neuroscience. Expect disciplines from philosophy to psychology, IT to immunology and medicine to
molecular genetics to be explored - and a blend of everything from the quirky to the profound.
With the society's 38,000 members presenting several thousand research papers, it goes without
saying that you won't catch everything. If you're new to neurons or know them well and are seeking a
new career direction but are too busy to sample what everyone else is up to, or simply can't make it to
southern California, help is at hand.
The society's president, David Van Essen of the University of Washington, St Louis, has selected some
highlights of the conference that will be featured in a series of special lectures. Some of these represent
advances that have only recently become possible through a range of new techniques and technologies
- Van Essen points out how techniques such as neuroinformatics, neuroanatomy and neural
computation have allowed progress that would have been inconceivable a decade ago. Other lectures
reveal new methods and frameworks for dealing with the vast quantities of neuroscientific data that
these techniques have been generating, and show how the ‘decade of the brain' may have been more
the decade of data collection, with the real breakthroughs and payoffs still to come.
We have spoken to some of these featured speakers to find out what they think is hot and happening
right now. Here's a selection of some of neuroscience's most inspiring ideas.
To learn more about the Society for Neuroscience and find details of its annual meeting, visit www.sfn.
org
Plasticity
Mriganka Sur
"Plasticity is one of the most exciting topics in neuroscience today," says Mriganka Sur. It might not
seem an obvious choice of theme for someone with an impressive list of research papers on vision
under his belt, but Sur believes that studying plasticity will be fundamental to understanding how the
brain works, how it develops, how we learn and remember, and even how we see.
Sur says that new tools and approaches are transforming the study of plasticity. To understand the
rules and mechanisms of plasticity depends on understanding all the elements of the brain: synapses,
neurons, circuits and modules. New ways to alter molecular or cellular elements of the intact brain and
examining their function in the cortex and in behaving animals are going to transform the field.
Sur's laboratory uses high-resolution technologies such as two-photon imaging of cellular function or of
synapse and cell structure in vivo, combined with molecular, genetic and cellular markers. One surprise
discovery from the team's two-photon imaging work is how astrocytes - glial cells that are often thought
of as just support structures in the brain - seem to be important in neuronal plasticity.
Flexible interdisciplinary researchers with a broad education will find success in this field. "Biology,
physics, chemistry, computer science, electrical engineering, even materials science, would be an
asset," says Sur.
Mriganka Sur heads the Department of Brain and Cognitive Sciences at the Massachusetts Institute of
Technology
Connectomics
Sebastian Seung
Sebastian Seung studies neural networks using mathematical models and computer algorithms.
Modeling a single neuron provides enough of a research challenge, but Seung is going a step further.
One of the limitations in understanding how real brains work, he says, is the scarcity of information
about how neurons are connected in the brain. An emerging field called ‘connectomics' or
computational neuroanatomy sets out to address this.
New techniques, such as serial block-face scanning electron microscopy, are generating
unprecedented amounts of data about the three-dimensional structure of brain circuitry at the
nanometer scale.
The computer will be an indispensable tool for analyzing and handling such data, and Seung's lab has
begun to develop algorithms, using some novel machine-learning techniques, to take raw images and
generate data about structure and connectivity. That's no mean feat, given that each tissue sample may
contain 10,000 neurons and 10 million synapses - all of which need identifying and classifying. His
group is also generating intriguing testable hypotheses about how synaptic plasticity and
neuromodulators might be acting to create some of the anatomical and behavioral changes seen
experimentally.
As the field matures, it will aid the study of neural development, the process by which the brain wires
itself up. "It could help us discover ‘connectopathies' - neuropathologies of connectivity that are
associated with mental disorders," says Seung.
The first classes in connectomics are being offered jointly at MIT and Harvard this fall. Seung, for one,
hopes that it will inspire a new crop of computer scientists to begin working on the image analysis
problems of connectomics. "There are definitely good opportunities for those with strong training in
machine learning, who are excited by the idea of using artificial intelligence to create tools for
neuroscientists," he says.
Sebastian Seung is a Howard Hughes Medical Institute investigator at MIT's Department of Brain and
Cognitive Sciences
Neuroinformatics
Mark Ellisman
Mark Ellisman believes that neuroscience is set to benefit from two convergent revolutions. The first is
that new technologies are allowing us to observe the nervous system at every level, from single
molecules to the level of behavior. The second revolution is that advances in information technology
have enabled us to handle the vast amounts of data these technologies generate.
Decreased information storage costs and increasing bandwidth for communications between different
locations are bringing scientists, with their wealth of data, together in a large virtual community. Ellisman
highlights the Biomedical Informatics Research Network (BIRN), which links research centers in the US,
UK and Canada, as an example of how researchers are tackling the challenges of data sharing.
Part of the solution is standardizing terminology across disciplines and species. Another major issue is
creating standardized spatial frameworks for the data so that results from different studies can be
compared and combined more easily. BIRN has already had some success in combining and mining
structural MRI data from many different Alzheimer's studies, revealing that there may be subtle changes
in hippocampal shape early in the disease process.
Data aggregation has also highlighted the varying amounts of data on different aspects of brain
function. For example, says Ellisman, there's a wealth of data about the genome and RNAs, "but almost
nothing about the organization of supramolecular complexes, such as the constellation of proteins in
synapses, and how these vary in the brain".
For such community efforts to succeed, there may need to be a complete shift in how scientists' careers
are run. "Scientists of the future should be facilitated and rewarded for working in larger teams," says
Ellisman. "Faculty are currently judged by their individual contributions, but cooperative work needs to
be better rewarded."
Mark Ellisman directs the BIRN project's coordinating center as well as the University of California San
Diego's National Center for Microscopy and Imaging Research and Center for Research in Biological
Systems
Social neuroscience
Mike Gazzaniga
Mike Gazzaniga has made many pioneering discoveries about how different regions of the cortex
construct our beliefs and sense of self, and is widely regarded as founder of the field of cognitive
neuroscience. More recently he has been delving into some of the trickiest aspects of human nature,
researching such topics as criminality and morality.
The brain is a decision-making device, he says. But while neuroscience knows an awful lot about
perceptual decisions, such as whether we're looking at a square or a triangle, when was the last time
you thought about a triangle or made a decision about one? Then contrast this with the last time you
thought about social issues. "My guess is that the latter set of issues consumes you and every other
human," says Gazzaniga. "Neuroscience allows you a window into the basic biology of human nature."
It is a field that is coming of age with the help of some smart imaging techniques, including recording
event-related potentials, and the rapidly improving spatial and temporal resolution of functional MRI,
magnetoencephalography and near-infrared optical imaging. These are yielding new views of how
brains work in an environment full of other brains - and not just simple shapes, colors and sounds.
"We are moving on to consider the essence of human existence, social behavior and the like - such
questions as ‘Are we moral because we learn social rules or because our moral responses are built into
the brain?'," says Gazzaniga. "Brain imaging will help answer that classic issue."
With his multidisciplinary approach to research, Gazzaniga has no fixed ideas about the sorts of courses
or background experience that could lead a researcher into this field. He says that every scientist
should follow their own mental wanderings and temperament. Usually, he says, "things click, and if they
don't, try investment banking!"
Mike Gazzaniga is director of the Sage Center for the Study of Mind at the University of California, Santa
Barbara
Neocortical theory
Jeff Hawkins
Neuroscientists old and young will tell you that they got interested in the subject in order to understand
how the brain works, says inventor, neuroscientist and author Jeff Hawkins. "This quest for a theory is
not just today's hot topic but a perennial hot topic," he says. "Fortunately, we are starting to make
substantial progress and I predict interest in neocortical theory will grow explosively over the coming
years."
A brain theory is an exciting prospect on many levels - it could help us cure disease, develop better
ways to learn, understand human nature and human conflict, and build machines that work on the same
principles. Such a theory is long overdue, given the mountains of brain data that exist. So what makes
Hawkins optimistic now?
The brain, he says, records everything we experience and helps us predict intelligently - the question is
how the neocortex stores information and learns.
This is not a trivial problem to solve, but it may become more manageable. For one thing, until recently
mathematicians and engineers interested in machine learning did not interact much with neuroscientists.
"Our understanding of how the brain works has suffered," says Hawkins. But that is changing rapidly.
Also, while the neocortex makes up 60 percent of the volume of a human brain and contains about 30
billion cells, it uses similar operating principles across all the senses. "What is new is recognizing that
the mid- and large-scale structure of the neocortex, in particular its hierarchical connectivity,
significantly constrains how it must store knowledge about the world," says Hawkins.
Jeff Hawkins is the inventor of the Palm Pilot and director of the Redwood Center for Theoretical
Neuroscience at the University of California, Berkeley
Neural circuits
Karel Svoboda
Karel Svoboda has quite literally been creating windows into the mind - or at least the mouse brain. He
places small glass slides in the skull and has developed a remarkable combination of fluorescent labels,
the latest of which are produced by the genetically engineered mice themselves.
Using innovative microscope technologies, he has found a way to locate and study the same synapse in
the brain, day after day, sometimes for more than a month, with relatively little disturbance to an
animal's brain or behavior. While it is well known that synapses and the brain's wiring change in
response to experiences, Svoboda can actually watch it happening, right down to details about the ion
channels involved. Combining these optical techniques with electrophysiology, he hopes to understand
the nature of synaptic change and how such changes contribute to large-scale rewiring of the brain's
circuitry with experience.
"My view is that an understanding of the circuit diagram of the brain is necessary - although not
sufficient - to understand the brain," says Svoboda. "The wiring diagram of C. elegans, constructed in
Sydney Brenner's lab 20 years ago, is the scaffold on which every C. elegans neurobiology experiment
is designed. We don't have anything comparable in any other organism."
Not yet. But a confluence of new tools and a sense of zeitgeist are attracting many good researchers
into the field, which is not just labels and microscopes but genetics, too. For example, the cloning of a
light-sensitive ion channel has allowed researchers to stimulate specific genetically defined neurons with
light, so controlling their activity and providing another tool with which to map and test connections.
So what's the best way to get involved in this exciting field? Clearly it's another area attracting
researchers from many different disciplines. Data analysis techniques are becoming increasingly
important when dealing with the vast amounts of information generated by new, high-throughput tools in
anatomy and physiology. And Svoboda believes that nimbleness with quantitative methods through
courses in applied math, computer science and physics will be increasingly important.
Karel Svoboda is a group leader at the Howard Hughes Medical Institute Janelia Farm Research
Campus, Virginia
Next
http://www.newscientist.com/channel/opinion/careers/dn12881-neuroscience--us-ad-feature.html
It has to be the biggest neural networking opportunity of the year, when the collective brains of the
world's largest neuroscientific organization, the Society for Neuroscience, gather for its annual meeting.
This year, the San Diego sunshine is likely to attract a high head count of cerebral researchers, who will
spend four-and-a-half days discussing the latest results and ideas from every conceivable corner of
neuroscience. Expect disciplines from philosophy to psychology, IT to immunology and medicine to
molecular genetics to be explored - and a blend of everything from the quirky to the profound.
With the society's 38,000 members presenting several thousand research papers, it goes without
saying that you won't catch everything. If you're new to neurons or know them well and are seeking a
new career direction but are too busy to sample what everyone else is up to, or simply can't make it to
southern California, help is at hand.
The society's president, David Van Essen of the University of Washington, St Louis, has selected some
highlights of the conference that will be featured in a series of special lectures. Some of these represent
advances that have only recently become possible through a range of new techniques and technologies
- Van Essen points out how techniques such as neuroinformatics, neuroanatomy and neural
computation have allowed progress that would have been inconceivable a decade ago. Other lectures
reveal new methods and frameworks for dealing with the vast quantities of neuroscientific data that
these techniques have been generating, and show how the ‘decade of the brain' may have been more
the decade of data collection, with the real breakthroughs and payoffs still to come.
We have spoken to some of these featured speakers to find out what they think is hot and happening
right now. Here's a selection of some of neuroscience's most inspiring ideas.
To learn more about the Society for Neuroscience and find details of its annual meeting, visit www.sfn.
org
Plasticity
Mriganka Sur
"Plasticity is one of the most exciting topics in neuroscience today," says Mriganka Sur. It might not
seem an obvious choice of theme for someone with an impressive list of research papers on vision
under his belt, but Sur believes that studying plasticity will be fundamental to understanding how the
brain works, how it develops, how we learn and remember, and even how we see.
Sur says that new tools and approaches are transforming the study of plasticity. To understand the
rules and mechanisms of plasticity depends on understanding all the elements of the brain: synapses,
neurons, circuits and modules. New ways to alter molecular or cellular elements of the intact brain and
examining their function in the cortex and in behaving animals are going to transform the field.
Sur's laboratory uses high-resolution technologies such as two-photon imaging of cellular function or of
synapse and cell structure in vivo, combined with molecular, genetic and cellular markers. One surprise
discovery from the team's two-photon imaging work is how astrocytes - glial cells that are often thought
of as just support structures in the brain - seem to be important in neuronal plasticity.
Flexible interdisciplinary researchers with a broad education will find success in this field. "Biology,
physics, chemistry, computer science, electrical engineering, even materials science, would be an
asset," says Sur.
Mriganka Sur heads the Department of Brain and Cognitive Sciences at the Massachusetts Institute of
Technology
Connectomics
Sebastian Seung
Sebastian Seung studies neural networks using mathematical models and computer algorithms.
Modeling a single neuron provides enough of a research challenge, but Seung is going a step further.
One of the limitations in understanding how real brains work, he says, is the scarcity of information
about how neurons are connected in the brain. An emerging field called ‘connectomics' or
computational neuroanatomy sets out to address this.
New techniques, such as serial block-face scanning electron microscopy, are generating
unprecedented amounts of data about the three-dimensional structure of brain circuitry at the
nanometer scale.
The computer will be an indispensable tool for analyzing and handling such data, and Seung's lab has
begun to develop algorithms, using some novel machine-learning techniques, to take raw images and
generate data about structure and connectivity. That's no mean feat, given that each tissue sample may
contain 10,000 neurons and 10 million synapses - all of which need identifying and classifying. His
group is also generating intriguing testable hypotheses about how synaptic plasticity and
neuromodulators might be acting to create some of the anatomical and behavioral changes seen
experimentally.
As the field matures, it will aid the study of neural development, the process by which the brain wires
itself up. "It could help us discover ‘connectopathies' - neuropathologies of connectivity that are
associated with mental disorders," says Seung.
The first classes in connectomics are being offered jointly at MIT and Harvard this fall. Seung, for one,
hopes that it will inspire a new crop of computer scientists to begin working on the image analysis
problems of connectomics. "There are definitely good opportunities for those with strong training in
machine learning, who are excited by the idea of using artificial intelligence to create tools for
neuroscientists," he says.
Sebastian Seung is a Howard Hughes Medical Institute investigator at MIT's Department of Brain and
Cognitive Sciences
Neuroinformatics
Mark Ellisman
Mark Ellisman believes that neuroscience is set to benefit from two convergent revolutions. The first is
that new technologies are allowing us to observe the nervous system at every level, from single
molecules to the level of behavior. The second revolution is that advances in information technology
have enabled us to handle the vast amounts of data these technologies generate.
Decreased information storage costs and increasing bandwidth for communications between different
locations are bringing scientists, with their wealth of data, together in a large virtual community. Ellisman
highlights the Biomedical Informatics Research Network (BIRN), which links research centers in the US,
UK and Canada, as an example of how researchers are tackling the challenges of data sharing.
Part of the solution is standardizing terminology across disciplines and species. Another major issue is
creating standardized spatial frameworks for the data so that results from different studies can be
compared and combined more easily. BIRN has already had some success in combining and mining
structural MRI data from many different Alzheimer's studies, revealing that there may be subtle changes
in hippocampal shape early in the disease process.
Data aggregation has also highlighted the varying amounts of data on different aspects of brain
function. For example, says Ellisman, there's a wealth of data about the genome and RNAs, "but almost
nothing about the organization of supramolecular complexes, such as the constellation of proteins in
synapses, and how these vary in the brain".
For such community efforts to succeed, there may need to be a complete shift in how scientists' careers
are run. "Scientists of the future should be facilitated and rewarded for working in larger teams," says
Ellisman. "Faculty are currently judged by their individual contributions, but cooperative work needs to
be better rewarded."
Mark Ellisman directs the BIRN project's coordinating center as well as the University of California San
Diego's National Center for Microscopy and Imaging Research and Center for Research in Biological
Systems
Social neuroscience
Mike Gazzaniga
Mike Gazzaniga has made many pioneering discoveries about how different regions of the cortex
construct our beliefs and sense of self, and is widely regarded as founder of the field of cognitive
neuroscience. More recently he has been delving into some of the trickiest aspects of human nature,
researching such topics as criminality and morality.
The brain is a decision-making device, he says. But while neuroscience knows an awful lot about
perceptual decisions, such as whether we're looking at a square or a triangle, when was the last time
you thought about a triangle or made a decision about one? Then contrast this with the last time you
thought about social issues. "My guess is that the latter set of issues consumes you and every other
human," says Gazzaniga. "Neuroscience allows you a window into the basic biology of human nature."
It is a field that is coming of age with the help of some smart imaging techniques, including recording
event-related potentials, and the rapidly improving spatial and temporal resolution of functional MRI,
magnetoencephalography and near-infrared optical imaging. These are yielding new views of how
brains work in an environment full of other brains - and not just simple shapes, colors and sounds.
"We are moving on to consider the essence of human existence, social behavior and the like - such
questions as ‘Are we moral because we learn social rules or because our moral responses are built into
the brain?'," says Gazzaniga. "Brain imaging will help answer that classic issue."
With his multidisciplinary approach to research, Gazzaniga has no fixed ideas about the sorts of courses
or background experience that could lead a researcher into this field. He says that every scientist
should follow their own mental wanderings and temperament. Usually, he says, "things click, and if they
don't, try investment banking!"
Mike Gazzaniga is director of the Sage Center for the Study of Mind at the University of California, Santa
Barbara
Neocortical theory
Jeff Hawkins
Neuroscientists old and young will tell you that they got interested in the subject in order to understand
how the brain works, says inventor, neuroscientist and author Jeff Hawkins. "This quest for a theory is
not just today's hot topic but a perennial hot topic," he says. "Fortunately, we are starting to make
substantial progress and I predict interest in neocortical theory will grow explosively over the coming
years."
A brain theory is an exciting prospect on many levels - it could help us cure disease, develop better
ways to learn, understand human nature and human conflict, and build machines that work on the same
principles. Such a theory is long overdue, given the mountains of brain data that exist. So what makes
Hawkins optimistic now?
The brain, he says, records everything we experience and helps us predict intelligently - the question is
how the neocortex stores information and learns.
This is not a trivial problem to solve, but it may become more manageable. For one thing, until recently
mathematicians and engineers interested in machine learning did not interact much with neuroscientists.
"Our understanding of how the brain works has suffered," says Hawkins. But that is changing rapidly.
Also, while the neocortex makes up 60 percent of the volume of a human brain and contains about 30
billion cells, it uses similar operating principles across all the senses. "What is new is recognizing that
the mid- and large-scale structure of the neocortex, in particular its hierarchical connectivity,
significantly constrains how it must store knowledge about the world," says Hawkins.
Jeff Hawkins is the inventor of the Palm Pilot and director of the Redwood Center for Theoretical
Neuroscience at the University of California, Berkeley
Neural circuits
Karel Svoboda
Karel Svoboda has quite literally been creating windows into the mind - or at least the mouse brain. He
places small glass slides in the skull and has developed a remarkable combination of fluorescent labels,
the latest of which are produced by the genetically engineered mice themselves.
Using innovative microscope technologies, he has found a way to locate and study the same synapse in
the brain, day after day, sometimes for more than a month, with relatively little disturbance to an
animal's brain or behavior. While it is well known that synapses and the brain's wiring change in
response to experiences, Svoboda can actually watch it happening, right down to details about the ion
channels involved. Combining these optical techniques with electrophysiology, he hopes to understand
the nature of synaptic change and how such changes contribute to large-scale rewiring of the brain's
circuitry with experience.
"My view is that an understanding of the circuit diagram of the brain is necessary - although not
sufficient - to understand the brain," says Svoboda. "The wiring diagram of C. elegans, constructed in
Sydney Brenner's lab 20 years ago, is the scaffold on which every C. elegans neurobiology experiment
is designed. We don't have anything comparable in any other organism."
Not yet. But a confluence of new tools and a sense of zeitgeist are attracting many good researchers
into the field, which is not just labels and microscopes but genetics, too. For example, the cloning of a
light-sensitive ion channel has allowed researchers to stimulate specific genetically defined neurons with
light, so controlling their activity and providing another tool with which to map and test connections.
So what's the best way to get involved in this exciting field? Clearly it's another area attracting
researchers from many different disciplines. Data analysis techniques are becoming increasingly
important when dealing with the vast amounts of information generated by new, high-throughput tools in
anatomy and physiology. And Svoboda believes that nimbleness with quantitative methods through
courses in applied math, computer science and physics will be increasingly important.
Karel Svoboda is a group leader at the Howard Hughes Medical Institute Janelia Farm Research
Campus, Virginia
Next
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