Slow Noise in the Period of a Biological Oscillator Underlies Gradual Trends and Abrupt Transitions in Phasic Relationships in Hybrid Neural Networks

In order to study the ability of coupled neural oscillators to synchronize in the presence of intrinsic as opposed to synaptic noise, we constructed hybrid circuits consisting of one biological and one computational model neuron with reciprocal synaptic inhibition using the dynamic clamp. Uncoupled, both neurons fired periodic trains of action potentials. Most coupled circuits exhibited qualitative changes between one-to-one phase-locking with fairly constant phasic relationships and phase slipping with a constant progression in the phasic relationships across cycles. The phase resetting curve (PRC) and intrinsic periods were measured for both neurons, and used to construct a map of the firing intervals for both the coupled and externally forced (PRC measurement) conditions. For the coupled network, a stable fixed point of the map predicted phase locking, and its absence produced phase slipping. Repetitive application of the map was used to calibrate different noise models to simultaneously fit the noise level in the measurement of the PRC and the dynamics of the hybrid circuit experiments. Only a noise model that added history-dependent variability to the intrinsic period could fit both data sets with the same parameter values, as well as capture bifurcations in the fixed points of the map that cause switching between slipping and locking. We conclude that the biological neurons in our study have slowly-fluctuating stochastic dynamics that confer history dependence on the period. Theoretical results to date on the behavior of ensembles of noisy biological oscillators may require re-evaluation to account for transitions induced by slow noise dynamics.

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Staying focused: Cortico-thalamic pathway filters relevant sensory cues from perceptual input

On the one hand, the nervous has limited computational capability – but at the same time, the sensory environment contains an immense amount of information. In this demanding situation, the brain somehow manages to selectively focus attention on relevant stimuli. Recently, scientists at Technische Universität München, Munich and Ruhr University Bochum, Bochum investigated thalamic tactile sensory relay by employing optogenetics (the use of light to control neurons which have been genetically sensitized to light) to control specific cortical input to the thalamus. They show that the deepest cortical layer (known as layer six, or simply L6) plays a key role in controlling thalamic signal transformation (specifically, by controlling adaptive responses of thalamic neurons) and thalamic gating of dynamic sensory input patterns by changing the firing mode.

Dr. Rebecca A. Mease and Dr. Alexander Groh discussed the paper they and Prof. Patrik Krieger published in Proceedings of the National Academy of Sciences. In this study they investigated how the brain actively controls and gates information reaching higher stages of cortical processing by using optogenetics to turn on specific cortical input to the thalamus and measure how this impacts the processing of sensory signals in the thalamus.

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Illuminating neuron activity in 3-D

Researchers at MIT and the University of Vienna have created an imaging system that reveals neural activity throughout the brains of living animals. This technique, the first that can generate 3-D movies of entire brains at the millisecond timescale, could help scientists discover how neuronal networks process sensory information and generate behavior.

The team used the new system to simultaneously image the activity of every neuron in the worm Caenorhabditis elegans, as well as the entire brain of a zebrafish larva, offering a more complete picture of nervous system activity than has been previously possible.

“Looking at the activity of just one neuron in the brain doesn’t tell you how that information is being computed; for that, you need to know what upstream neurons are doing. And to understand what the activity of a given neuron means, you have to be able to see what downstream neurons are doing,” says Ed Boyden, an associate professor of biological engineering and brain and cognitive sciences at MIT and one of the leaders of the research team. “In short, if you want to understand how information is being integrated from sensation all the way to action, you have to see the entire brain.”

The new approach, described May 18 in Nature Methods, could also help neuroscientists learn more about the biological basis of brain disorders. “We don’t really know, for any brain disorder, the exact set of cells involved,” Boyden says. “The ability to survey activity throughout a nervous system may help pinpoint the cells or networks that are involved with a brain disorder, leading to new ideas for therapies.”

Boyden’s team developed the brain-mapping method with researchers in the lab of Alipasha Vaziri of the University of Vienna and the Research Institute of Molecular Pathology in Vienna. The paper’s lead authors are Young-Gyu Yoon, a graduate student at MIT, and Robert Prevedel, a postdoc at the University of Vienna.

High-speed 3-D imaging

Neurons encode information — sensory data, motor plans, emotional states, and thoughts — using electrical impulses called action potentials, which provoke calcium ions to stream into each cell as it fires. By engineering fluorescent proteins to glow when they bind calcium, scientists can visualize this electrical firing of neurons. However, until now there has been no way to image this neural activity over a large volume, in three dimensions, and at high speed.

Scanning the brain with a laser beam can produce 3-D images of neural activity, but it takes a long time to capture an image because each point must be scanned individually. The MIT team wanted to achieve similar 3-D imaging but accelerate the process so they could see neuronal firing, which takes only milliseconds, as it occurs.

The new method is based on a widely used technology known as light-field imaging, which creates 3-D images by measuring the angles of incoming rays of light. Ramesh Raskar, an associate professor of media arts and sciences at MIT and an author of this paper, has worked extensively on developing this type of 3-D imaging. Microscopes that perform light-field imaging have been developed previously by multiple groups. In the new paper, the MIT and Austrian researchers optimized the light-field microscope, and applied it, for the first time, to imaging neural activity.

With this kind of microscope, the light emitted by the sample being imaged is sent through an array of lenses that refracts the light in different directions. Each point of the sample generates about 400 different points of light, which can then be recombined using a computer algorithm to recreate the 3-D structure.

“If you have one light-emitting molecule in your sample, rather than just refocusing it into a single point on the camera the way regular microscopes do, these tiny lenses will project its light onto many points. From that, you can infer the three-dimensional position of where the molecule was,” says Boyden, who is a member of MIT’s Media Lab and McGovern Institute for Brain Research.

Prevedel built the microscope, and Yoon devised the computational strategies that reconstruct the 3-D images.

Aravinthan Samuel, a professor of physics at Harvard University, says this approach seems to be an “extremely promising” way to speed up 3-D imaging of living, moving animals, and to correlate their neuronal activity with their behavior. “What’s very impressive about it is that it is such an elegantly simple implementation,” says Samuel, who was not part of the research team. “I could imagine many labs adopting this.”

Neurons in action

The researchers used this technique to image neural activity in the worm C. elegans, the only organism for which the entire neural wiring diagram is known. This 1-millimeter worm has 302 neurons, each of which the researchers imaged as the worm performed natural behaviors, such as crawling. They also observed the neuronal response to sensory stimuli, such as smells.

The downside to light field microscopy, Boyden says, is that the resolution is not as good as that of techniques that slowly scan a sample. The current resolution is high enough to see activity of individual neurons, but the researchers are now working on improving it so the microscope could also be used to image parts of neurons, such as the long dendrites that branch out from neurons’ main bodies. They also hope to speed up the computing process, which currently takes a few minutes to analyze one second of imaging data.

The researchers also plan to combine this technique with optogenetics, which enables neuronal firing to be controlled by shining light on cells engineered to express light-sensitive proteins. By stimulating a neuron with light and observing the results elsewhere in the brain, scientists could determine which neurons are participating in particular tasks.

The brain: key to a better computer

Your brain is incredibly well-suited to handling whatever comes along, plus it’s tough and operates on little energy. Those attributes — dealing with real-world situations, resiliency and energy efficiency — are precisely what might be possible with neuro-inspired computing.

“Today’s computers are wonderful at bookkeeping and solving scientific problems often described by partial differential equations, but they’re horrible at just using common sense, seeing new patterns, dealing with ambiguity and making smart decisions,” said John Wagner, cognitive sciences manager at Sandia National Laboratories.

In contrast, the brain is “proof that you can have a formidable computer that never stops learning, operates on the power of a 20-watt light bulb and can last a hundred years,” he said.

Although brain-inspired computing is in its infancy, Sandia has included it in a long-term research project whose goal is future computer systems. Neuro-inspired computing seeks to develop algorithms that would run on computers that function more like a brain than a conventional computer.

“We’re evaluating what the benefits would be of a system like this and considering what types of devices and architectures would be needed to enable it,” said microsystems researcher Murat Okandan.

Sandia’s facilities and past research make the laboratories a natural for this work: its Microsystems & Engineering Science Applications (MESA) complex, a fabrication facility that can build massively interconnected computational elements; its computer architecture group and its long history of designing and building supercomputers; strong cognitive neurosciences research, with expertise in such areas as brain-inspired algorithms; and its decades of work on nationally important problems, Wagner said.

New technology often is spurred by a particular need. Early conventional computing grew from the need for neutron diffusion simulations and weather prediction. Today, big data problems and remote autonomous and semiautonomous systems need far more computational power and better energy efficiency.

Neuro-inspired computers would be ideal for robots, remote sensors

Neuro-inspired computers would be ideal for operating such systems as unmanned aerial vehicles, robots and remote sensors, and solving big data problems, such as those the cyber world faces and analyzing transactions whizzing around the world, “looking at what’s going where and for what reason,” Okandan said.

Such computers would be able to detect patterns and anomalies, sensing what fits and what doesn’t. Perhaps the computer wouldn’t find the entire answer, but could wade through enormous amounts of data to point a human analyst in the right direction, Okandan said.

“If you do conventional computing, you are doing exact computations and exact computations only. If you’re looking at neurocomputation, you are looking at history, or memories in your sort of innate way of looking at them, then making predictions on what’s going to happen next,” he said. “That’s a very different realm.”

Modern computers are largely calculating machines with a central processing unit and memory that stores both a program and data. They take a command from the program and data from the memory to execute the command, one step at a time, no matter how fast they run. Parallel and multicore computers can do more than one thing at a time but still use the same basic approach and remain very far removed from the way the brain routinely handles multiple problems concurrently.

The architecture of neuro-inspired computers would be fundamentally different, uniting processing and storage in a network architecture “so the pieces that are processing the data are the same pieces that are storing the data, and the data will be processed with all nodes functioning concurrently,” Wagner said. “It won’t be a serial step-by-step process; it’ll be this network processing everything all at the same time. So it will be very efficient and very quick.”

Unlike today’s computers, neuro-inspired computers would inherently use the critical notion of time. “The things that you represent are not just static shots, but they are preceded by something and there’s usually something that comes after them,” creating episodic memory that links what happens when. This requires massive interconnectivity and a unique way of encoding information in the activity of the system itself, Okandan said.

More neurosciences research opens more possibilities for brain-inspired computing

Each neuron in a neural structure can have connections coming in from about 10,000 neurons, which in turn can connect to 10,000 other neurons in a dynamic way. Conventional computer transistors, on the other hand, connect on average to four other transistors in a static pattern.

Computer design has drawn from neuroscience before, but an explosion in neuroscience research in recent years opens more possibilities. While it’s far from a complete picture, Okandan said what’s known offers “more guidance in terms of how neural systems might be representing data and processing information” and clues about replicating those tasks in a different structure to address problems impossible to solve on today’s systems.

Brain-inspired computing isn’t the same as artificial intelligence, although a broad definition of artificial intelligence could encompass it.

“Where I think brain-inspired computing can start differentiating itself is where it really truly tries to take inspiration from biosystems, which have evolved over generations to be incredibly good at what they do and very robust against a component failure. They are very energy efficient and very good at dealing with real-world situations. Our current computers are very energy inefficient, they are very failure-prone due to components failing and they can’t make sense of complex data sets,” Okandan said.

Computers today do required computations without any sense of what the data is — it’s just a representation chosen by a programmer.

“Whereas if you think about neuro-inspired computing systems, the structure itself will have an internal representation of the datastream that it’s receiving and previous history that it’s seen, so ideally it will be able to make predictions on what the future states of that datastream should be, and have a sense for what the information represents.” Okandan said.

He estimates a project dedicated to brain-inspired computing will develop early examples of a new architecture in the first several years, but said higher levels of complexity could take decades, even with the many efforts around the world working toward the same goal.

“The ultimate question is, ‘What are the physical things in the biological system that let you think and act, what’s the core essence of intelligence and thought?’ That might take just a bit longer,” he said.

With imprecise chips to the artificial brain

Which circuits and chips are suitable for building artificial brains using the least possible amount of power? This is the question that Junior Professor Dr. Elisabetta Chicca from the Center of Excellence Cognitive Interaction Technology (CITEC) has been investigating in collaboration with colleagues from Italy and Switzerland. A surprising finding: Constructions that use not only digital but also analog compact and imprecise circuits are more suitable for building artificial nervous systems, rather than arrangements with only digital or precise but power-demanding analog electronic circuits. The study will be published in the scientific journal ‘Proceedings of the IEEE’. A preview was published online on Thursday, 1 March 2014.

Elisabetta Chicca is the head of the research group ‘Neuromorphic Behaving Systems’. One of the aims of her work is to make robots and other technical systems as autonomous and capable of learning as possible. The artificial brains that she and her team are developing are modelled on the biological nervous systems of humans and animals. ‘Environmental stimuli are processed in the biological nervous systems of humans and animals in a totally different way to modern computers’, says Chicca. ‘Biological nervous systems organise themselves; they adapt and learn. In doing so, they require a relatively small amount of energy in comparison with computers and allow for complex skills such as decision-making, the recognition of associations and of patterns.’

The neuroinformatics researcher is trying to utilise biological principles to build artificial nervous systems. Dr. Chicca and her colleagues have been investigating which type of circuits can simulate synapses electronically. Synapses serve as the ‘bridges’ that transmit signals between nerve cells. Stimuli are communicated through them and they can also save information. Furthermore, the research team have analysed which type of circuit can imitate the so-called plasticity of the biological nerves. Plasticity describes the ability of nerve cells, synapses and cerebral areas to adapt their characteristics according to use. In the brains of athletes, for example, certain cerebral areas are more strongly connected than in non-athletes.

The four researchers also offer solutions for the control of artificial nervous systems. They present software on the basis of which programmes can be written that can control the circuits and chips of an ‘electronic brain’.

Hope for paraplegic patients

People with severe injuries to their spinal cord currently have no prospect of recovery and remain confined to their wheelchairs. Now, all that could change with a new treatment that stimulates the spinal cord using electric impulses. The hope is that the technique will help paraplegic patients learn to walk again. From June 3 – 5, Fraunhofer researchers will be at the Sensor + Test measurement fair in Nürnberg to showcase the implantable microelectrode sensors they have developed in the course of pre-clinical development work (Hall 12, Booth 12-537).

Thomas T. was just 25 years old when a severe motorcycle accident changed his life in an instant. Doctors diagnosed him with paraplegia following an injury to his spinal cord in the lumbar region. The young man has been confined to a wheelchair ever since. The diagnosis of paraplegia came as a shock, and it was only in the course of a month-long period of rehabilitation that Thomas T. was able to come to terms with his condition. Patients like him currently have no prospect of recovery, as there is still no effective course of treatment available for improving motor function among the severely disabled.

Now a consortium of European research institutions and companies want to get affected patients quite literally back on their feet. In the EU’s NEUWalk project, which has been awarded funding of some nine million euros, researchers are working on a new method of treatment designed to restore motor function in patients who have suffered severe injuries to their spinal cord. The technique relies on electrically stimulating the nerve pathways in the spinal cord. “In the injured area, the nerve cells have been damaged to such an extent that they no longer receive usable information from the brain, so the stimulation needs to be delivered beneath that,” explains Dr. Peter Detemple, head of department at the Fraunhofer Institute for Chemical Technology’s Mainz branch (IMM) and NEUWalk project coordinator. To do this, Detemple and his team are developing flexible, wafer-thin microelectrodes that are implanted within the spinal canal on the spinal cord. These multichannel electrode arrays stimulate the nerve pathways with electric impulses that are generated by the accompanying by microprocessor-controlled neurostimulator. “The various electrodes of the array are located around the nerve roots responsible for locomotion. By delivering a series of pulses, we can trigger those nerve roots in the correct order to provoke motion sequences of movements and support the motor function,” says Detemple.

Researchers from the consortium have already successfully conducted tests on rats in which the spinal cord had not been completely severed. As well as stimulating the spinal cord, the rats were given a combination of medicine and rehabilitation training. Afterwards the animals were able not only to walk but also to run, climb stairs and surmount obstacles. “We were able to trigger specific movements by delivering certain sequences of pulses to the various electrodes implanted on the spinal cord,” says Detemple. The research scientist and his team believe that the same approach could help people to walk again, too. “We hope that we will be able to transfer the results of our animal testing to people. Of course, people who have suffered injuries to their spinal cord will still be limited when it comes to sport or walking long distances. The first priority is to give them a certain level of independence so that they can move around their apartment and look after themselves, for instance, or walk for short distances without requiring assistance,” says Detemple.

Researchers from the NEUWalk project intend to try out their system on two patients this summer. In this case, the patients are not completely paraplegic, which means there is still some limited communication between the brain and the legs. The scientists are currently working on tailored implants for the intervention. “However, even if both trials are a success, it will still be a few years before the system is ready for the general market. First, the method has to undergo clinical studies and demonstrate its effectiveness among a wider group of patients,” says Detemple.

Electric spinal cord stimulation to offer relief for Parkinson’s disease

Patients with Parkinson’s disease could also benefit from the neural prostheses. The most well-known symptoms of the disease are trembling, extreme muscle tremors and a short, stooped gait that has a profound effect on patients’ mobility. Until now this neurodegenerative disorder has mostly been treated with dopamine agonists – drugs that chemically imitate the effects of dopamine but that often lead to severe side effects when taken over a longer period of time. Once the disease has reached an advanced stage, doctors often turn to deep brain stimulation. This involves a complex operation to implant electrodes in specific parts of the brain so that the nerve cells in the region can be stimulated or suppressed as required. In the NEUWalk project, researchers are working on electric spinal cord simulation – an altogether less dangerous intervention that should however ease the symptoms of Parkinson’s disease just as effectively. “Initial animal testing has yielded some very promising results,” says Detemple.

The researchers from Mainz will be at the Sensor + Test 2014 measurement fair in Nürnberg to showcase their neural prostheses. These include implantable microelectrode sensors controlled by microprocessors as well as rigid multi-channel sensors that can be used to record electrophysiological signals and to stimulate neural structures.

No such thing as a ‘universal’ intelligence test. Cultural differences determine results country by country

Researchers at the University of Granada have shown that a universal test of intelligence quotient (IQ) does not exist. Results in this type of test are determined by cultural differences.

Their objective was to study and explain cultural differences in IQ test performance. To do this, scientists from CIMCYC—the University of Granada’s Brain Mind and Behavior Research Center—conducted a study of 54 individuals aged between 18 and 54 years: 27 were Spanish and the other 27 were Moroccans residing in Spain.

The groups were selected to ensure that clear cultural differences existed between them: they spoke different languages (Spanish versus Arabic), professed different religions (Christians versus Muslims), had different traditions, and came from very different geographical contexts (Europe versus Africa).

Both groups underwent different tests of intellectual capacity: for example, a test of non-verbal intelligence, and various neuropsychological tests that measure functions such as visual memory and executive functions.

The same test measures different cognitive functions

Although the two groups were similar in terms of sex, educational level and socio-economic status, the results showed that in the test of non-verbal intelligence, the Spanish group obtained a higher IQ score than the Moroccan group. Moreover, the neuropsychological skills used in each subtest were clearly dependent on the country of origin of each participant. In other words, the same test can measure different cognitive functions in individuals from different cultures.

In the light of the results of this study, the authors suggest that the non-verbal tests cannot be considered culture-free and confirm the importance of validating the tests in their cultural context.

In 2014, this study has been ranked in the top 10 of articles downloaded from Archives of Clinical Neuropsychology.

Herpes-loaded stem cells used to kill brain tumors

Harvard Stem Cell Institute (HSCI) scientists at Massachusetts General Hospital have a potential solution for how to more effectively kill tumor cells using cancer-killing viruses. The investigators report that trapping virus-loaded stem cells in a gel and applying them to tumors significantly improved survival in mice with glioblastoma multiforme, the most common brain tumor in human adults and also the most difficult to treat.

The work, led by Khalid Shah, MS, PhD, an HSCI Principal Faculty member, is published in the Journal of the National Cancer Institute. Shah heads the Molecular Neurotherapy and Imaging Laboratory at Massachusetts General Hospital.

Cancer-killing or oncolytic viruses have been used in numerous phase 1 and 2 clinical trials for brain tumors but with limited success. In preclinical studies, oncolytic herpes simplex viruses seemed especially promising, as they naturally infect dividing brain cells. However, the therapy hasn’t translated as well for human patients. The problem previous researchers couldn’t overcome was how to keep the herpes viruses at the tumor site long enough to work.

Shah and his team turned to mesenchymal stem cells (MSCs)—a type of stem cell that gives rise to bone marrow tissue—which have been very attractive drug delivery vehicles because they trigger a minimal immune response and can be utilized to carry oncolytic viruses. Shah and his team loaded the herpes virus into human MSCs and injected the cells into glioblastoma tumors developed in mice. Using multiple imaging markers, it was possible to watch the virus as it passed from the stem cells to the first layer of brain tumor cells and subsequently into all of the tumor cells.

“So, how do you translate this into the clinic?” asked Shah, who also is an Associate Professor at Harvard Medical School.

“We know that 70-75 percent of glioblastoma patients undergo surgery for tumor debulking, and we have previously shown that MSCs encapsulated in biocompatible gels can be used as therapeutic agents in a mouse model that mimics this debulking,” he continued. “So, we loaded MSCs with oncolytic herpes virus and encapsulated these cells in biocompatible gels and applied the gels directly onto the adjacent tissue after debulking. We then compared the efficacy of virus-loaded, encapsulated MSCs versus direct injection of the virus into the cavity of the debulked tumors.”

Using imaging proteins to watch in real time how the virus combated the cancer, Shah’s team noticed that the gel kept the stem cells alive longer, which allowed the virus to replicate and kill any residual cancer cells that were not cut out during the debulking surgery. This translated into a higher survival rate for mice that received the gel-encapsulated stem cells.

“They survived because the virus doesn’t get washed out by the cerebrospinal fluid that fills the cavity,” Shah said. “Previous studies that have injected the virus directly into the resection cavity did not follow the fate of the virus in the cavity. However, our imaging and side-by-side comparison studies showed that the naked virus rarely infects the residual tumor cells. This could give us insight into why the results from clinical trials with oncolytic viruses alone were modest.”

The study also addressed another weakness of cancer-killing viruses, which is that not all brain tumors are susceptible to the therapy. The researchers’ solution was to engineer oncolytic herpes viruses to express an additional tumor-killing agent, called TRAIL. Again, using mouse models of glioblastoma—this time created from brain tumor cells that were resistant to the herpes virus—the therapy led to increased animal survival.

“Our approach can overcome problems associated with current clinical procedures,” Shah said. “The work will have direct implications for designing clinical trials using oncolytic viruses, not only for brain tumors, but for other solid tumors.”

Further preclinical work will be needed to use the herpes-loaded stem cells for breast, lung and skin cancer tumors that metastasize to the brain. Shah predicts the approach will enter clinical trials within the next two to three years.