- Merging MEG and fMRI using representational similarity analysis
- Engineered Hemodynamic Probes for Detection of Mild Traumatic Brain Injury
- Spatiotemporal Chemical Imaging of Neurotransmitters in the Living Brain using Near Infrared Fluorescent Nanoparticle Sensors
- Super-resolution optical microscope for imaging neural connections
- Fluorescent nanodiamonds: a new class of optical probes for neuroscience
- Inhibiting and Facilitating Nerve transmission through Ion-Selective Membranes
- Multifunctional Platform for Electrophysiological Characterization of Cortical Circuits
- Ultramicrotomy Cutting Mechanics to Achieve High-Resolution Organ Mapping
- Combining functional near-infrared spectroscopy with transcranial magnetic stimulation
- A systems biology approach to study the transcriptional response to neural activity
- An optimized platform for real-time fMRI neurofeedback
- Developing online assessment tool for measuring collective intelligence in ethnically heterogeneous groups
- Mapping anatomical connectivity of functionally defined regions in the human brain
- Optoelectronic devices for electrophysiological characterization and optogenetic stimulation of motor circuits in mouse spinal cord
- Novel Viral Tools for Anatomy and Physiology
- Systematic Classification of Neural Cell Types via Ultratargeted Trascriptomics
- Novel devices for optical neural control and electrical recording
- Implantable devices for drug infusion and electrophysiological recording
- Automated classification of animal behaviors
- Nanowires: Development of polymer-based electrodes for chronic neural recordings in vivo and in vitro
- Alternate Indicators in MRI: Design and synthesis of a new membrane-permeable MRI sensor for functional imaging of neuronal calcium
- Use of virally encoded genes to optically record and manipulate neural activity in the songbird brain
- Application of Optical Control of Neural Activity to Analysis of the Neural Substrates Causally Mediating Cognition
- Ultra-Low-Power Electronics for Chronic Wireless Brain-Machine Interfaces
- Carbon nanotubes
- Rigid sheaths for flexible nanowires
- Optical control of signaling molecules
- Analyzing MRI data
- Detecting patterns in MRI
- Precise detection of brain cells
PIs: Aude Oliva (CSAIL) & Dimitrios Pantazis (McGovern Institute)
An important goal for human neuroimaging is to combine different modalities with complementary strengths and limitations. fMRI can localize brain activity at high spatial resolution but its temporal resolution is limited by the slow hemodynamic response. MEG offers millisecond temporal resolution, the time scale at which neurons communicate, but lacks the spatial precision of MRI. The two methods have recently been combined though a method known as Representational Similarity Analysis (RSA), providing a dynamic view of brain activity at a level of detail not previously achievable. The goal of this project is to further improve the RSA method, and build an open-source toolbox that will facilitate its adoption by the neuroimaging community.
PIs: Lee Goldstein (Boston University) & Alan Jasanoff (McGovern Institute)
With increasing recognition of the cost and consequences of mild traumatic brain injury (mTBI), there is an urgent need for better methods to detect brain dysfunction associated with this condition. This project will use a rodent model of mTBI that was developed at BU to test new MRI-based approaches to measuring the effect of blast injury.
Spatiotemporal Chemical Imaging of Neurotransmitters in the Living Brain using Near Infrared Fluorescent Nanoparticle Sensors
PIs: Michael Strano (Chem Eng.) & Ed Boyden (McGovern Institute)
Single wall carbon nanutubes (SWCNTs) can form complexes with oligonucleotides or other polymers that often fluoresce strongly in the near infrared. By screening many different polymer sequences it is possible to develop reagents that show altered fluorescence in response to a chosen analyte. This project will explore the potential of SCWNTs as sensors for dopamine and other neurotransmitters in the living brain.
PIs: Peter So (Mechanical Engineering) & Ed Boyden (McGovern Institute)
In recent years, super-resolution (SR) optical methods have been developed that can resolve microscopic images below the diffraction limit of light. This high level of resolution is potentially useful for mapping neural connections, but the feasibility of such studies has been limited by the slow speed of most SR methods. This project will combine several technologies in a single instrument that will be capable of SR imaging at much higher speeds than previously possible. We envisage using this instrument for large-scale connectomic studies, but it will also have many other potential applications in biomedical research.
PIs: Dirk Englund (Electrical Engineering & Computer Science) & Ed Boyden (McGovern Institute)
Nitrogen vacancy (NV) centers in diamond have unusual quantum properties that make them well suited as probes for many biological phenomena. This project will explore the applications of N-V nanodiamonds in neuroscience, in particular as optical reporters of neural activity.
PIs: Jongyoon Han (Electrical Engineering & Computer Science) & Emilio Bizzi (McGovern Institute)
Many neurological disorders involve unwanted neural activity, and a method for selectively blocking the propagation of activity could have many potential clinical applications. This project will explore the use of ion-selective membranes to modulate the spread of action potentials in peripheral nerves through local alterations in the ionic environment.
PIs: Polina Anikeeva (Materials Science & Engineering) & Guoping Feng (McGovern Institute)
This project will build on previous work from Dr Anikeeva’s lab, to develop a combined optical-electrophysiological probe that can be used for optogenetic stimulation and recording of brain circuits, along with local delivery of drugs, viruses or other reagents. These approaches will be applied to studying mouse models of autism and other neurpsychiatric disorders.
PIs: Martin Culpepper (Mechanical Engineering) & Ed Boyden (McGovern Institute)
Serial electron microscopic images can be used to reconstruct the fine anatomical structure of neural circuits, and when combined with appropriate labeling methods can also provide high resolution molecular imaging. The goal of this project is to apply engineering insights to the design of a high-throughput system for cutting ultra-thin sections of brain tissue.
PIs: Rebecca Saxe (McGovern Institute); Blaise Frederick (McLean Hospital and Harvard Medical School)
Transcranial magnetic stimulation (TMS) is used both clinically and as a research tool for manipulating human brain activity. How TMS affects brain activity is not fully understood, and this project will explore the question by combining TMS with functional near-infrared spectroscopy (fNIRS) a method that allows measurements of human brain activity through the skull, based on changes in blood oxygenation.
PIs: Yingxi Lin (McGovern Institute); Thomas Nieland & Nir Hacohen (Broad Institute)
Neural activity is known to cause rapid changes in transcription, and such changes are important mediators of neural plasticity. The goal of this project is to study these changes on a genome-wide scale, using recently developed tools from systems biology to identify, and ultimately to manipulate, specific functional gene networks that are regulated by neural activity.
PIs: Satrajit Ghosh & John Gabrieli (McGovern Institute); Eden Evins (MGH)
Advances in real-time fMRI have enabled the use of fMRI-based signals as a source of neurofeedback. In a typical protocol, subjects in the scanner receive feedback on the activity of a specific brain region, which can guide them toward greater volitional control of their own brain state. This approach has been explored in many studies, and shows promise as a treatment method for a range of disorders, from chronic pain to substance abuse to attention deficit disorder. Progress has been limited, however, by the lack of efficient platforms for implementing such feedback protocols, making it difficult to explore different methods in a systematic way. This project will develop a standardized platform for implementing fMRI-based feedback, enabling faster testing of key parameters and sharing of protocols across different sites and scanners.
Developing online assessment tool for measuring collective intelligence in ethnically heterogeneous groups
PIs: Rebecca Saxe (McGovern Institute); Thomas Malone (MIT Sloan School)
Many programs have been established that aim to reduce tensions between different ethnic groups by promoting inter-group dialog and understanding. The Saxe lab has been working with one such program in an effort to understand inter-group relationships from a cognitive neuroscience perspective. However, there are few reliable methods for measuring the effectiveness of these interventions. One potentially quantifiable measure, which has been studied by Malone and colleagues, is ‘collective intelligence’, the ability to solve problems as a group. Collective intelligence is independent of the intelligence of individual group members but is correlated with measures of how well group members communicate with each other. This project will support the development of a culturally neutral online tool for evaluating collective intelligence in multi-cultural groups. This will be used to measure collective intelligence in culturally homogeneous or heterogeneous groups, and to determine whether programs that promote inter-cultural dialog are effective at raising group intelligence.
Nancy Kanwisher (McGovern Institute); Larry Wald & Bruce Fischl (MGH)
fMRI has enabled researchers to identify many human brain regions with distinct functions. To understand how these regions work, it is important to know how they are connected to other parts of the brain. A MRI-based method known as diffusion tractography has been used to trace anatomical connections within the human brain, but standard methods are insufficient for detailed tracing of functionally defined regions. This project will take advantage of the recently developed ‘Connectom’ scanner at MGH, which allows diffusion imaging with much higher angular resolution than previously possible. The collaborators will use fMRI-based functional localizers to define areas of interest in individual human subjects, and then these same areas will be subjected to tractography analysis based on diffusion MRI scans performed with the connectom machine.
Optoelectronic devices for electrophysiological characterization and optogenetic stimulation of motor circuits in mouse spinal cord
Emilio Bizzi (McGovern Institute); Polina Anikeeva (MIT Dept. of Materials Science & Engineering)
Optogenetics, a method for controlling brain activity with light, has emerged as a powerful tool for neuroscience research. However with the ability to control neural circuits comes the demand for simultaneous electrophysiological recording. The goal of this project is to develop an optoelectronic array for the rodent spinal cord that can support simultaneous multi-channel recordings and light-based control of neural activity. The project will use advanced fabrication methods to create flexible probes that combine microelectrodes and light waveguides. Applying this approach to the mouse spinal cord will enable new studies of spinal motor circuits and may eventually form the basis for new types of prosthetics for spinal cord injury.
PI: Sebastian Seung
Co-PIs: Ed Boyden, Ki Goosens, Ann Graybiel, Yingxi Lin
Other personnel: Ian Wickersham
Understanding neural circuitry would be greatly advanced by the abilities to trace the inputs to neurons in vivo and to record from or manipulate the activity of these identified synaptic partners. The natural ability of rabies virus to spread retrogradely from an infected neuron to its presynaptic partners has previously been exploited to engineer deletion-mutant “lyssaviral” vectors that infect and express transgenes only in cells that are monosynaptically connected to neurons of interest. (These vectors are nonhazardous because they are missing a gene essential for cell-to-cell spread and therefore cannot cause disease.) The current project will build on this previous work, combining lyssaviral vectors with cell-type specific expression systems to map the connections of defined subsets of neurons, and to permit recordings from identified classes of projection neurons.
Co-PI: Erez Liberman-Aiden (Harvard University and Broad Institute)
Co-PI: Ed Boyden (McGovern Institute)
It is unknown how many different cell types exist within the brain. Traditional molecular methods such as immunostaining and in situ hybridization have revealed a great diversity of neural cell types, but these methods are laborious and provide incomplete descriptions of the brain’s molecular complexity. Advances in genomic technology have enabled new approaches to ‘transcriptomics’ – sensitive methods for measuring the abundance of different RNAs in individual cells. But these methods remain technically challenging and do not lend themselves to scaling up to study large populations of cells. The collaborators propose to address this challenge by testing a novel technological approach. Using a high-technology combination of barcoded deep sequencing and sophisticated statistical analysis, they hope to discover transcriptional ‘fingerprints’ of different cell types. If successful, this method would be valuable not only to neuroscientists but also to researchers in other fields such as developmental biology and cancer research, where heterogeneity at the level of single cells is also important.
PI: Clif Fonstad (MIT Dept of Electrical Engineering and Computer Science)
Co-PI: Ed Boyden (MIT Media Lab, McGovern Institute)
Ed Boyden in the MIT Media Lab and Clif Fonstad in the department of Electrical Engineering and Computer Science will collaborate to develop new devices for optical control of neural activity. Boyden, an associate member of the McGovern Institute, has been a pioneer in the development of optogenetics, a technology in which light-sensitive ion channels are expressed in target neurons, allowing their activity to be controlled by light. The approach has great promise for research and clinical applications, but to take full advantage of this potential, better methods are needed for delivering bright light to target neurons within the brain. Fonstad, an expert on optoelectronics, plans to work with Boyden to build miniature implantable devices that can deliver light to precise locations deep within the brain and record electrical activity at the same target locations. If successful, this approach could open the door to a new generation of therapies based on light activation of specific brain circuits.
PI: Michael Cima (MIT Dept of Materials Science and Engineering)
Co-PI: Ann Graybiel (McGovern Institute)
Ann Graybiel of the McGovern Institute and Michael Cima in the MIT department of Materials Science and Engineering are collaborating to make a device that combines a recording electrode with a precise drug infusion system, allowing researchers to record electrical responses to pulses of drugs within the brain. Cima, an expert on the design of medical devices, will work with Graybiel to develop a fluid-handling system that will allow rapid and precise control of drug release from different reservoirs, and that can be implanted chronically into the brain. Graybiel hopes to use the resulting system to characterize different compartments within the striatum, a brain structure that is implicated in reward, motivation and substance abuse. In the longer term, the method should also be applicable to clinical drug delivery, by allowing rapid monitoring of a drug’s effect on the brain.
PI: Tomaso Poggio (McGovern Institute)
Co-PIs: Yingxi Lin, Ed Boyden, Ann Graybiel (McGovern Institute); Tracy Petryshyn (Broad Institute)
Tomaso Poggio of the McGovern Institute and his postdoc Thomas Serre recently developed a computer system that can learn to recognize different actions, using strategies similar to those used by the brain. Their system has many potential applications, but the possibility of recognizing animal behaviors is especially important for neuroscience, for instance as a way to evaluate mouse behavioral mutants or to test the effects of drugs. The new MINT award will support scaling up of the initial prototype to create a working system that will be tested in four different labs at the McGovern Institute and the Broad Institute. The ability to recognize and quantify behaviors automatically would greatly accelerate many aspects of behavioral research and drug discovery for behavioral disorders.
Nanowires: Development of polymer-based electrodes for chronic neural recordings in vivo and in vitro.
PI: Ian Hunter (MIT Dept. of Mechanical Engineering)
Co-PIs: Emilio Bizzi and Martha Constantine-Paton (McGovern Institute)
Other personnel: (Andrew Taberner, Bryan Ruddy, Giovanni Talei-Franzesi, Dept. of Mechanical Engineering; Woong-Jin (Chris) Bae, McGovern Institute)
Conducting polymers have great potential as new materials for electrode construction. Compared to traditional metal or glass electrodes, polymers such as polypyrrole are flexible and highly biocompatible, and they can be made extremely thin. These properties will be especially valuable for the construction of high-density electrode arrays that can be implanted chronically in the brain. We are fabricating polypyrrole nanowires and exploring their use as intracortical recording electrodes. Ultimately we hope to develop a new generation of electrodes that can be stably implanted in the brain for long periods of time, both for research and clinical applications.
We are also working to produce polypyrrole electrode arrays on a tissue culture surface. These arrays will be used to deliver patterned stimulation to neurons in culture, in order to explore synaptic plasticity rules and neural network effects in vitro. Such a system may ultimately form the basis of a new platform for drug discovery, by allowing high-throughput screening of chemicals that modify the properties of neural networks in therapeutically useful ways.
Alternate Indicators in MRI: Design and synthesis of a new membrane-permeable MRI sensor for functional imaging of neuronal calcium
PI: Stephen Lippard (MIT Dept. of Chemistry)
Co-PI: Alan Jasanoff (McGovern Institute)
Other personnel: Xiao-an Zhang (Dept. of Chemistry)
Functional magnetic resonance imaging (fMRI) is a well-established noninvasive neuroimaging method that measures brain activity indirectly through local changes in blood flow and oxygenation. fMRI is limited, however, by the slow time-course and coarse spatial scale of the hemodynamic response, and by confounding factors unrelated to neural activity. It is thus of great interest to develop more direct fMRI methods that combine the cellular specificity of classical neurophysiology techniques with the noninvasiveness and whole-brain coverage of MRI. Such a technique would give us a greatly expanded view of brain function and, potentially, of human brain disorders.
We have recently developed a zinc MRI sensor based on water-soluble manganese porphyrin. This agent is the first reported cell membrane-permeable contrast agent for metal ion sensing. The establishment of this chemical platform allows us to design a novel calcium sensor for MRI, based on a mechanism of Ca-dependent ligand gating of a water coordination site on the metalloporphyrin complex. We plan to synthesize this molecule and test its utility as a MRI sensor in the rodent brain.
Use of virally encoded genes to optically record and manipulate neural activity in the songbird brain
PI: Michale Fee (McGovern Institute)
Co-PI: Carlos Lois (Picower Institute for Learning and Memory)
Other Personnel: Tim Gardner (McGovern Institute)
To understand brain function at the level of neural circuits, we wish to visualize the activity of many neurons simultaneously, with high temporal resolution. We are developing a genetic approach to this goal based on a new calcium indicator, GCaMP2, that has recently been developed by Dr Junichi Nakai at RIKEN Brain Science Institute. This indicator, consisting of a circularly permuted GFP fused to calmodulin, has been used to image Ca signaling in transgenic mouse heart. We will use this system for monitoring neural activity in vivo, using viral vectors to deliver the transgene reporter to neurons in the song bird nucleus known as HVC. Our goal is twofold: to examine spatio-temporal patterns of activity in HVC during bird song learning (a model for the acquisition of complex motor skills such as speech), and more generally to demonstrate the utility of GCaMP2 as a genetic indicator of neural activity. If successful, we also plan to combine this approach with the use of channelrhodopsin-2 and/or halorhodopsin, which should allow simultaneous optical recording and manipulation of neural activity in vivo.
Application of Optical Control of Neural Activity to Analysis of the Neural Substrates Causally Mediating Cognition
PI: Ed Boyden (MIT Media Lab)
Co-PI: Robert Desimone (McGovern Institute)
Other Personnel: Xue Han (McGovern Institute)
We have recently shown that the light-activated proteins channelrhodopsin-2 and halorhodopsin can be used to activate and inhibit neurons in response to light of different wavelengths. We are now developing precisely-targetable fiber arrays and in vivo-optimized expression systems to enable the use of this tool in awake, behaving primates. By combining these technologies with behavioral and physiological experiments, we hope to open up new horizons on the analysis of cognition. In the longer term, it may be possible to apply a similar approach to the human nervous system; potential clinical applications include the suppression of epileptic seizures, restoration of visual perception in patients with retinal degeneration, or deep brain stimulation for conditions such as Parkinson's disease.
PI: Rahul Sarpeshkar (MIT Dept. of Electrical Engineering & Computer Science)
Co-PI: Michale Fee (McGovern Institute)
The development of brain-machine interfaces holds great promise as a new therapeutic approach to neurological disease and injury. An implanted prosthetic device could, for example, enable a paralyzed patient to control a computer or mechanical device directly through signals recorded from the brain, without any need for manual controls. Successful implementation of this concept will require local processing of information from implanted electrode arrays followed by transmission (preferably wireless) across the skull. This must be accomplished with minimal power consumption in order to prolong battery life and to avoid excessive dissipation of heat within the cranium. We are developing an ultra-low power neural amplifier along with circuits and algorithms for compression of neural recording data. These systems, which exploit a combination of analog and digital processing, will be tested in the songbird brain, with the aim of establishing a chronic interface for intracranial recording and telemetry.
PI: Jing Kong (MIT Department of Electrical Engineering and Computer Science)
Co-PI: Emilio Bizzi (McGovern Institute)
Bizzi and Kong are exploring the use of carbon nanotubes as an alternated, biocompatible alternative material. To study long-term changes in the brain, researchers need to make chronic recordings of neural activity. But the standard electrodes can damage brain tissue and lose their electrical contacts over time, so there is a need for alternative materials. Bizzi, who researches the control of movement, wants to use long-term recordings initially for basic research but ultimately for prosthetic devices in human patients. Such devices might, for example, allow a paralyzed patient to control a robotic arm or a computer directly from the brain.
PI: Robert Langer (MIT Department of Chemical Engineering)
Co-PI: Emilio Bizzi (McGovern Institute)
Bizzi is also exploring another alternative electrode material made from thin flexible strands of conducting polymers, called nanowires. These polymers are expected to produce less damage to brain tissue, but they are difficult to insert into the brain. Langer and Bizzi will explore one potential solution: a biodegradable coating that can provide temporary stiffness but disappears after insertion.
PI: Shuguang Zhang (MIT Center for Biomedical Engineering)
Co-PI: Ed Boyden (McGovern Institute)
Ed Boyden, a member of the MIT media lab and an associate member of McGovern Institute, is a pioneer in the development of optical tools for manipulating electrical activity in neurons. He plans to extend this approach to manipulate intracellular signaling, in collaboration with Shuguang Zhang, director of the MIT Center for Biomedical Engineering and an expert on protein engineering. If successful, this could be a valuable method for determining the function of signaling pathways in vivo and for identifying potential targets for drug development.
Nancy Kanwisher in the McGovern Institute and Polina Golland, Associate Professor, EECS and Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT.
One challenge for neuroscience research is analyzing the very large datasets produced by brain imaging studies. Two new MINT projects will explore different computational approaches, using data from Nancy Kanwisher at McGovern Institute.
In the first, Polina Golland in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) will use Kanwisher's fMRI data to search for brain areas that respond to specific categories of visual objects. Several such areas are known to exist, but the current methods for identifying them only work if they are in the same location in every person. Golland has developed a computational method that avoids this assumption. She and Kanwisher plan to test the method on a large body of brain scanning data to determine whether it can reveal the existence of new brain areas that cannot be found with existing methods. Golland also collaborates with neurosurgeons to analyze imaging data to help surgical planning for brain tumor surgery.
PIs: Navia Systems
Co-PI: Nancy Kanwisher (McGovern Institute)
In a related project, Kanwisher will work with Navia Systems Inc, a startup company founded by former MIT students in the Department of Brain and Cognitive Sciences. Navia uses proprietary computational methods, licensed from MIT, to identify patterns in large complex datasets and assign significance to them Navia to develop algorithms for detect patterns in large, complex data sets, such as neural imaging studies. The algorithms look for clusters that exist within the data without any prior assumptions. For example, does the category 'animal' activate one tight cluster or a million scattered points? How do patterns for bats, birds and cats differ? These algorithms will help reveal how the brain classifies the world, and could enhance the study of brain disorders, for example by identifying relationships between brain activity, genetics and clinical diagnostic categories. It could also be adapted to other fields, such as seismic data to locate oil fields.
PI: Mehmet Fatih Yanik (MIT Department of Electrical Engineering)
Co-PI: Ann Graybiel (McGovern Institute)
Researchers often use a method called laser capture microdissection (LCM) to analyze single cells within a tissue -- for example to identify genetic abnormalities that distinguish tumor cells from their healthy neighbors. The ability to analyze single cells is especially important in the brain, where cells of many different types are closely intermingled. However, because of the brain's dense meshwork of connections, it is often impossible to cleanly remove a single cell without contamination from adjacent cells. To solve this problem, Ann Graybiel of the McGovern Institute will collaborate with Mehmet Fatih Yanik in the MIT department of Electrical Engineering and Computer Science, who developed a laser producing extremely local concentrations of very high energy pulses lasting just a femtosecond (1 millionth of a nanosecond, or 10-15 of a second). Yanik plans to develop a 3-dimensional laser-based cutting method that can dissect a single cell from its neighbors. Graybiel hopes to apply these new methods to her studies on the basal ganglia, brain regions implicated in Parkinson's disease, addictive behaviors and mood disorders.