1995 — 1996 |
Blair, Hugh T |
F31Activity Code Description: To provide predoctoral individuals with supervised research training in specified health and health-related areas leading toward the research degree (e.g., Ph.D.). |
Neural Computation in the Rat Head-Direction System |
0.906 |
2006 — 2015 |
Blair, Hugh T Knierim, James J |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Crcns: Path Integration by the Grid Cell Network @ University of California Los Angeles
DESCRIPTION (provided by applicant): For as long as it has been possible to measure electrical activity in the nervous system, it has been known that the brain produces oscillatory rhythms. Some rhythms are generated during sleep, others during waking; certain patterns of oscillatory brain activity occur in all healthy people, while other patterns only occur in disease states such as epilepsy, clinical depression, or schizophrenia. Many different brain rhythms have been identified and characterized, and yet almost nothing is known about their function. We know that the brain oscillates, but we do not know why. Over the past few years, discoveries have been made that provide tantalizing new clues for answering this question, by suggesting that neural oscillations are very much like threads that the brain weaves together to create the fabric of memory and perception. In rats, one particular kind of oscillation referred to as theta rhythm is very predominant in the hippocampus and entorhinal cortex, brain areas that play a critical role in learning and memory. It is becoming increasingly clear that theta oscillations (in the frequency band of 4-12 Hz) are building blocks from which the hippocampus and entorhinal cortex can construct memory representations. The studies proposed here will combine neurophysiological recording experiments with computational modeling studies to investigate how the rat brain uses theta oscillations to form memories of familiar locations in space. Neurons called place cells and grid cells become active whenever a rat visits certain familiar locations, and these neurons are strongly synchronized by theta oscillations. Proposed computational modeling studies will investigate how place cells and grid cells use theta oscillations to encode spatial memories, and will seek to decipher the structure of the biological neural networks that perform this task. Proposed neurophysiology studies will attempt to show for the first time that neural oscillators in subcortical regions store memory representations using a phase code, and will examine how the cerebral cortex interacts with subcortical oscillators to read out these memory representations. Pharmacological inactivation studies will be conducted to demonstrate how memory processing breaks down when neural oscillators are disrupted, which may help to explain the causes of memory impairment in humans who suffer from amnesic syndrome in conjunction with disorders like Alzheimer's disease, schizophrenia, depression, anxiety disorders, and post-traumatic stress. By elucidating how memories are formed from theta oscillations in spatial memory circuits, the research proposed here will provide groundbreaking new insights into the fundamental role that neural oscillations play in normal memory processes. This work may in the future make it possible to diagnose and treat brain diseases and mental disorders that currently are not well understood, but which may prove to have roots in dysfunction of the neural oscillators that provide the basic building blocks for memory and perception.
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0.936 |
2006 |
Blair, Hugh T |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Lateralization of Emotional Memory Circuits in Amygdala @ University of California Los Angeles
[unreadable] DESCRIPTION (provided by applicant): "Fear" is an emotion that can be aroused by a predictive stimulus that warns of impending danger, such as the growl of a predator or the sight of an angry face. But most of the stimuli we encounter in our environment are non-threatening, so how do we discriminate stimuli that predict danger from those that do not? Learning to recognize danger depends upon the amygdala, a cluster of nuclei in the brain's temporal lobe. When the amygdala is damaged, people and animals are impaired at recognizing stimuli that predict danger. Conversely, overactivation of the amygdala can lead to excessive fear of non-threatening stimuli and may contribute to disorders such as phobias, chronic anxiety, depression, and post-traumatic stress. A better understanding of the amygdala's role in fear learning may thus provide the key to improving diagnosis and treatment for mental disorders characterized by symptoms of fear and anxiety. The experiments proposed here will pursue a novel approach to studying the amygdala's role in fear learning by using a new procedure that allows fear memories to be stored by one hemisphere of the amygdala and not the other. A recent study by the investigator has shown that when rats are trained to fear a noise by pairing it with electric shock delivered to one eyelid, learning to fear the noise depends upon the amygdala contralateral but not ipsilateral from the shocked eyelid. This discovery reveals that the amygdala's fear circuitry is functionally lateralized, so that fear memories about stimuli that predict threats to one side of the body can be represented mainly within the amygdala of the opposite brain hemisphere. An integrated program of behavioral, electrophysiological, and immunostaining experiments will exploit this lateralization to investigate the functional architecture of the amygdala's fear circuitry. First, anatomical pathways that convey information about aversive stimuli to the amygdala will be identified. Second, studies will test the hypothesis that fear memories are stored in the amygdala by synaptic changes triggered by convergence of sensory information about neutral and aversive stimuli. Third, studies will determine whether the left and right hemispheres of the amygdala exert opponent control over lateralized defensive behaviors. Findings from these experiments will help to resolve critical questions about the amygdala's role in learning, memory, and emotions, and thereby pave the way for improving future diagnosis and treatment of anxiety disorders. [unreadable] [unreadable] [unreadable]
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0.936 |
2007 — 2008 |
Blair, Hugh T |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Hemispheric Lateralization of Emotional Memory Circuits in the Amygdala @ University of California Los Angeles
[unreadable] DESCRIPTION (provided by applicant): "Fear" is an emotion that can be aroused by a predictive stimulus that warns of impending danger, such as the growl of a predator or the sight of an angry face. But most of the stimuli we encounter in our environment are non-threatening, so how do we discriminate stimuli that predict danger from those that do not? Learning to recognize danger depends upon the amygdala, a cluster of nuclei in the brain's temporal lobe. When the amygdala is damaged, people and animals are impaired at recognizing stimuli that predict danger. Conversely, overactivation of the amygdala can lead to excessive fear of non-threatening stimuli and may contribute to disorders such as phobias, chronic anxiety, depression, and post-traumatic stress. A better understanding of the amygdala's role in fear learning may thus provide the key to improving diagnosis and treatment for mental disorders characterized by symptoms of fear and anxiety. The experiments proposed here will pursue a novel approach to studying the amygdala's role in fear learning by using a new procedure that allows fear memories to be stored by one hemisphere of the amygdala and not the other. A recent study by the investigator has shown that when rats are trained to fear a noise by pairing it with electric shock delivered to one eyelid, learning to fear the noise depends upon the amygdala contralateral but not ipsilateral from the shocked eyelid. This discovery reveals that the amygdala's fear circuitry is functionally lateralized, so that fear memories about stimuli that predict threats to one side of the body can be represented mainly within the amygdala of the opposite brain hemisphere. An integrated program of behavioral, electrophysiological, and immunostaining experiments will exploit this lateralization to investigate the functional architecture of the amygdala's fear circuitry. First, anatomical pathways that convey information about aversive stimuli to the amygdala will be identified. Second, studies will test the hypothesis that fear memories are stored in the amygdala by synaptic changes triggered by convergence of sensory information about neutral and aversive stimuli. Third, studies will determine whether the left and right hemispheres of the amygdala exert opponent control over lateralized defensive behaviors. Findings from these experiments will help to resolve critical questions about the amygdala's role in learning, memory, and emotions, and thereby pave the way for improving future diagnosis and treatment of anxiety disorders. [unreadable] [unreadable] [unreadable]
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0.936 |
2011 — 2015 |
Blair, Hugh T Knierim, James J Zhang, Kechen (co-PI) [⬀] |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Crcns: Path Intergration by the Grid Cell Network @ University of California Los Angeles
DESCRIPTION (provided by applicant): For as long as it has been possible to measure electrical activity in the nervous system, it has been known that the brain produces oscillatory rhythms. Some rhythms are generated during sleep, others during waking; certain patterns of oscillatory brain activity occur in all healthy people, while other patterns only occur in disease states such as epilepsy, clinical depression, or schizophrenia. Many different brain rhythms have been identified and characterized, and yet almost nothing is known about their function. We know that the brain oscillates, but we do not know why. Over the past few years, discoveries have been made that provide tantalizing new clues for answering this question, by suggesting that neural oscillations are very much like threads that the brain weaves together to create the fabric of memory and perception. In rats, one particular kind of oscillation referred to as theta rhythm is very predominant in the hippocampus and entorhinal cortex, brain areas that play a critical role in learning and memory. It is becoming increasingly clear that theta oscillations (in the frequency band of 4-12 Hz) are building blocks from which the hippocampus and entorhinal cortex can construct memory representations. The studies proposed here will combine neurophysiological recording experiments with computational modeling studies to investigate how the rat brain uses theta oscillations to form memories of familiar locations in space. Neurons called place cells and grid cells become active whenever a rat visits certain familiar locations, and these neurons are strongly synchronized by theta oscillations. Proposed computational modeling studies will investigate how place cells and grid cells use theta oscillations to encode spatial memories, and will seek to decipher the structure of the biological neural networks that perform this task. Proposed neurophysiology studies will attempt to show for the first time that neural oscillators in subcortical regions store memory representations using a phase code, and will examine how the cerebral cortex interacts with subcortical oscillators to read out these memory representations. Pharmacological inactivation studies will be conducted to demonstrate how memory processing breaks down when neural oscillators are disrupted, which may help to explain the causes of memory impairment in humans who suffer from amnesic syndrome in conjunction with disorders like Alzheimer's disease, schizophrenia, depression, anxiety disorders, and post-traumatic stress. By elucidating how memories are formed from theta oscillations in spatial memory circuits, the research proposed here will provide groundbreaking new insights into the fundamental role that neural oscillations play in normal memory processes. This work may in the future make it possible to diagnose and treat brain diseases and mental disorders that currently are not well understood, but which may prove to have roots in dysfunction of the neural oscillators that provide the basic building blocks for memory and perception.
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0.936 |
2017 — 2019 |
Blair, Hugh Golshani, Peyman [⬀] Masmanidis, Sotiris Cong, Jason (co-PI) [⬀] Silva, Alcino (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Neuronex Technology Hub: Miniaturized Open Source Devices For Calcium Imaging, Electrophysiology, and Real-Time Control of Neural Activity @ University of California-Los Angeles
To understand how the brain processes information, creates and retrieves memories, and makes decisions it is necessary to record the activity of thousands of brain cells simultaneously. New small and light-weight microscopes have been developed that can be carried on the heads of laboratory mice and rats. These microscopes take advantage of new probes that sense calcium levels and flash bright when a brain cell becomes active. The Neuronex Neurotechnology Hub has built new miniature microscopes that not only sense light but can also directly record the electrical activity of the large numbers of cells deep in the brain. This combination of electrical and optical recordings gives scientists the new ability to read out how large groups of brain cells and brain regions work together as the brain senses, learns, plans and executes actions. The Neuronex Neurotechnology Hub will also create new computer systems that can analyze these activity patterns extremely quickly (within small fractions of a second). This rapid feedback system will allow investigators to rapidly probe how the activity of specific groups of brain cells is linked to each behavior. Finally, the Hub will build and test a new miniature microscope called a "light field miniature microscope". This version of the microscope will allow investigators to make 3-D movies of brain activity, greatly improving their view of the large network of brain cells. All these technologies will be openly shared with neuroscience community through a website (miniscope.org), such that each laboratory can build each of these devices themselves at very low cost. The Hub will hold workshops to teach scientists how to build and use the various devices. Finally the hub will reach out to the broader community by holding classes for K-12 and college students, and demonstrating how these devices can give us a view of brain function.
This Neurotechnology Hub will develop and share next-generation miniaturized in vivo sensing devices that integrate optical and electrophysiological recording from hundreds or thousands of neurons in behaving animals. These devices will be coupled with energy-efficient computing hardware for real-time signal processing and closed-loop feedback capabilities. The Hub will also create light field miniaturized microscopes that will allow three dimensional optical recordings of network activity in freely behaving animals. Last, the Hub will manufacture and distribute custom made, 3 dimensional silicon microprobes for large scale electrophysiological recordings. Making these devices widely available for neuroscience research and teaching will have significant broader impacts, by accelerating discovery and broadening outreach. The devices and techniques will be distributed widely to a large community of researchers, as previously done with the open-source miniaturized microscope developed by the PIs (the website at miniscope.org already has >2500 registered users and >250 labs using our microscope), as well as with silicon microprobes (>100 devices have been shared with users). Hence, the Hub will have a broad impact upon neuroscience research, facilitating many future advances in our understanding of the neural basis for emotion, cognition, and behavior, with a high potential to catalyze major new discoveries. The PIs will establish an outreach program through partnership with the Minority Access to Research Careers program at UCLA, as well as the UCLA Center for Excellence in Engineering and Diversity (CEED), to involve highly diversified high school and undergraduate students in this research. This NeuroTechnology Hub award is funded by the Division of Emerging Frontiers within the Directorate for Biological Sciences as part of the BRAIN Initiative and NSF's Understanding the Brain activities.
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0.915 |
2021 |
Blair, Hugh T Izquierdo, Alicia [⬀] |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Frontocortical Signaling Signatures in Flexible Reinforcement Learning @ University of California Los Angeles
Various neuropsychiatric conditions lead to failures in generating accurate models of the reward environment or inabilities in using those models to guide flexible behavior, very often manifesting as impaired reversal learning. The anterior cingulate cortex (ACC) and the orbitofrontal cortex (OFC) are frontocortical regions important for flexible reinforcement learning, and have been theorized to work in a hierarchy of parallel processes for reward- based choice. In OFC, there is priority encoding of lower-level attributes like reward-predictive value of sensory cues, the palatability of specific rewards, and the current stimulus-reward mappings relevant to behavior. In ACC, these variables are thought to be multiplexed for higher-level computations of reward prediction error (RPE) and confidence/uncertainty of predictions, which are used to monitor performance and update behavioral strategies when necessary (particularly overall trial strategy following positive feedback, i.e., WinStay). These computations may depend upon propagation of spikes from OFC to ACC. However, it remains poorly understood how flexible reward learning is mediated by interactions between OFC and ACC. Here we will investigate this question using a robust animal model of adaptive learning under uncertainty: stimulus-based probabilistic reversal learning (PRL). In freely behaving rats, we will use a combination of in vivo 1-photon calcium imaging and electrophysiology, chemogenetics, and closed-loop neural control of reward delivery to examine how OFC and ACC regulate PRL. Using new technology that we have recently developed for online decoding of calcium activity we will use a novel strategy of regulating reward delivery based upon neural activity in ACC and OFC to test whether flexible reward learning depends upon accurate neural representations in these frontocortical areas. To date, we have: demonstrated effective DREADDs manipulation in vivo and in transduced cortical slices; designed and tested custom electrode arrays to perform chronic in vivo electrophysiological recordings in these areas simultaneously; and imaged ensemble activity time-locked to behavior, which has proven stable over multiple sessions, ideal to study learning. Leveraging these technical advances and using this capacity as a platform, we propose to identify the precise cortico-cortical mechanisms of encoding variables in flexible reinforcement learning across two Aims. Collectively, these experiments will: 1) shed new light on the signaling signatures of cortical regions and their respective roles in flexible reinforcement learning, 2) accelerate groundbreaking experiments as they would be performed in closed-loop: control of reversal learning in real-time using decoded neural expectation, and 3) these signals would eventually be compared in animal models of psychopathology because of their known failures in reversal learning. These novel and unconventional approaches make the R21 mechanism ideal for the proposed work.
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0.936 |