David A. Leopold - US grants
Affiliations: | National Institute of Mental Health, Bethesda, MD, United States |
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The funding information displayed below comes from the NIH Research Portfolio Online Reporting Tools and the NSF Award Database.The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
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High-probability grants
According to our matching algorithm, David A. Leopold is the likely recipient of the following grants.Years | Recipients | Code | Title / Keywords | Matching score |
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2004 — 2018 | Leopold, David A | Z01Activity Code Description: Undocumented code - click on the grant title for more information. ZIAActivity Code Description: Undocumented code - click on the grant title for more information. |
Neurophysiology of Visual Perception @ National Institute of Mental Health We live in a world that is dominated by vision more than any other sense. Interpreting the structure of the world, for example constructing its third dimension (which must be inferred based on 2-D retinal projections), is an active and poorly understood task of the brain. For example, negotiating the 3-D world entails more than simply assigning distances to objects. Depth analysis involves interpreting shadows, gradients, relative motion, occlusion, and stereoscopic disparity, to understand objects, their spatial relationships, and our own relationship to them. Such analysis is important for all animals that need to ask: Which object is in front and what is behind? What is the shape of an object that is about to be manipulated? Where should a hand or hoof next be placed? The starting point is always a dynamic flat image, or at best a pair. Our 3-D impression of the world is a product of the brain. This principle is perhaps most strikingly demonstrated by visual illusions in which the same sensory stimulus can be interpreted by the brain in multiple different ways. In some cases, the brain can even decide to completely suppress the perception of a visual image.[unreadable] [unreadable] This description of vision as "active and interpretive" does not fit neatly with the experimental toolbox of the sensory physiologist, who is primarily concerned with stimuli and the responses they elicit. What should one make of stimuli that do not have a unique perceptual solution? It is interesting that such stimuli, which are inherently ambiguous, or sometimes inherently conflicting, often have a property of bistability. Bistable patterns, when viewed continuously, produce an alternating sequence of perceptual changes. As in the case of the famous faces vs. vase illusion, the two competing perceptual solutions alternate in the mind's eye, and unsurprisingly this alternation is most often in depth. For the physiologist, such spontaneous perceptual reversals pose a fascinating question: where in the brain do neural responses correspond to the structural components of a stimulus, and where do they instead correspond to a perceptual interpretation?[unreadable] [unreadable] In the past year, we have made good progress toward our goal of understanding the neural mechanisms that underlie a fundamental aspect of visual perception: namely, what makes a stimulus visible? We have approached this problem by performing neurophysiological and imaging experiments in monkeys who were trained to report to us, by making manual responses, when a stimulus was perceived as being visible, and when it subjectively disappeared. To achieve this, we exploited a visual illusion we developed several years ago to induce the prolonged disappearance of a bright, central stimulus upon the presentation of surrounding field of moving stimuli in the periphery. We asked, [unreadable] can be induced to abruptly disappear when a surrounding pattern is flashed to the periphery. We asked, when a high contrast image on the retina, which is normally visible and salient, is perceptually suppressed, does this image continue to activate neurons the primary visual cortex? We focused on this question since it is very important for interpreting a broad range of studies that have found it surprisingly difficult to converge on an answer.[unreadable] [unreadable] Recently, we have published our findings on this topic, which examine the basis of a previously identified discrepancy in the literature. Briefly, human fMRI studies have found that perceptual suppression was associated with a profound decrease in the BOLD (blood oxygenation level-dependent) response in the primary visual cortex, while electrophysiological studies in monkeys found that neurons in the same area did not show any percept-related changes. To examine possible reasons for this discrepancy, we combined microelectrode recordings and fMRI experiments in monkeys trained to report their perception. Using a paradigm we developed called generalized flash suppression (GFS), we found that in the very same monkey subjects, the two techniques (fMRI and single-unit recordings) yielded very different results. Surprisingly, we found that by monitoring the fMRI signal of a monkey's primary visual cortex, it is possible to determine whether a stimulus is visible or invisible, while it is impossible to do so by measuring the responses of individual neurons in the same area. In a control condition, the functional changes in the single unit and fMRI data were in perfect agreement. Thus the story has wider implications: while the neural and fMRI signals were in good agreement in one set of stimulus conditions, they diverged entirely in a different set of conditions. It is interesting that it is precisely during the condition of perceptual suppression (when the stimulus was physically present but invisible) that this uncoupling between the physiological signals took place.[unreadable] [unreadable] Subsequent findings (manuscripts in preparation) studied the role of the visual thalamus in perceptual suppression. Single-unit studies showed that neurons the pulvinar nucleus, a large secondary thalamic nucleus heavily connected with the cortex, are closely associated with stimulus visibility. Unlike the primary visual cortex, neurons in this area showed strong changes in activity when the monkey reported that the stimulus had become invisible. In contrast, neurons in the neighboring lateral geniculate nucleus, whose main role is to pass visual information to the cortex respond only based on the sensory stimulus, and not what is perceived. Thus it appears that information about the perceptual state contributes to the pulvinar's responses to a stimulus. Additional studies are presently investigating the effects of inactivating this structure, whose responses may have less to do with "sensory analysis" and more to do with the organization of stimulus-based attention and actions.[unreadable] [unreadable] Finally, several studies, including our most recent one, indicates that there is a widespread modulation of local field potential (LFP) in the primary visual cortex during perceptual suppression. Using a technique called current source density analysis, we have found that the synaptic currents giving rise to this signal appear to be located not in V1, where the LFP modulations have been measured. Instead they appear to be originating elsewhere in the brain. These findings raise questions about how to think about the site of visual perception, particularly in light of the different tools used to study it. They also underscore the importance of studying and understanding the relationship between the neural responses in the brain and the corresponding fMRI responses, which are sometimes in clear disagreement. |
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2007 — 2018 | Leopold, David A | Z01Activity Code Description: Undocumented code - click on the grant title for more information. ZICActivity Code Description: Undocumented code - click on the grant title for more information. |
Neurophysiology Imaging Facility Core: Functional and Structural Mri @ National Institute of Mental Health At the NIH, the Neurophysiology Imaging Facility is a core facility dedicated to the MRI scanning of nonhuman primates. The NIF, which was founded in 2004, offers services to a wide range of investigators in each of the three sponsoring institutes (NIMH, NINDS, and NEI). These services assist in the research effort of many investigators in the thriving NIH nonhuman primate community. Anatomical scans allow for the identification and verification of brain structures in vivo. Scientists needing to localize a neural circuit of interest or investigating the distribution of a new drug in the brain are able to quickly and easily scan their animals in the facility. Functional scans (fMRI), conducted in animals performing a host of behavioral tasks, allow for the assessment of brain activity, thus providing a bridge to the wealth of human fMRI studies. Both structural and functional imaging in the NIF exploit the latest cutting-edge MRI imaging technology, allowing users to combine imaging with other invasive techniques, such as microelectrode recordings, pharmacological inactivation, or anatomical tract tracing. The facility develops, designs, builds, and maintains radio frequency (RF) coils for a range of imaging needs. Testing animals inside a strong magnetic field has required the development of a wide array of MRI-compatible equipment, including animal chairs, restraint devices, reward delivery apparatus, eye position tracking cameras, and manual response keys. Users are set up with RF coils and these other devices, allowing them to initiate their studies with minimal development on their part. Structural scans: Using the standard setup, the facility staff assists with scans that aid in MRI-targeting of electrophysiological sites, identification of microelectrode positions, evaluation of experimental precision, and, importantly, the direct comparison of electrical recording sites with foci of fMRI responses in the context of a cognitive task. We are further able to combine these techniques with (1) reversible inactivation of electrical neural activity using pharmacological agents, (2) the identification of anatomical pathways using transported, MRI-visible chemicals such as manganese chloride, and (3) electrical microstimulation, where small local currents activate neurons that project to regions that can be detected using the fMRI signal. Surgical targeting is another relies upon particularly high-quality, distortion-free 3-D images of the brain. We have recently implemented algorithms that measure and compensate for small geometric distortions in the images that might hamper surgical precision. The facility also offers a frameless stereotaxy protocol to assist the surgeon with implantation. This method permits a visualization of the high-resolution scan during surgery, with a real-time depiction of the surgical instruments relative to the scanned brain structures. We have used this approach routinely to aid in the accurate implantation of electrode bundles and chronic cannulae, targeted ablations, and the placement of recording chambers. Functional MRI scans: The most unique aspect of the facility is the capacity to conduct fMRI simultaneous with other measurements and perturbations. The Intramural Research Program at the NIH is one of the very few sites around the world in which monkeys can routinely participate in both fMRI and electrophysiological studies. The fMRI studies go beyond mapping functional specialization in the brain. Experiments within the facility typically combine fMRI with other, invasive procedures, such as microelectrode recordings or pharmacological inactivation. In the last year, neuroscience have combined fMRI with cortical ablation, pharmacological inactivation, electrocorticogram recordings, electrical microstimulation, and recordings from chronic microwire arrays. The fMRI experiments produce large data files that must be processed to evaluate the functional activity patterns across the brain. The facility provides storage of these data, as well as help in the initial processing steps. Ex-vivo MRI scans for diffusion MRI: The core facility also carries out some diffusion weighted (DTI) scanning of, both in vivo and ex vivo. Recently, Dr. Ye in the facility has led an investigation exploring the possibilities of DTI, and the associated tractography methods. To do this, multiple macaque and marmoset brains were scanned ex vivo, each for up to 72 hours continuously. This approach allowed for sufficient signal to noise and angular resolution that might foreshadow in vivo human data acquisition in the future. These very high quality brain samples were analyzed in multiple ways, with one publication nearing publication Thomas et al, (2014), and a second one nearing submission. These studies aim to clarify the promise and inherent limits of diffusion tractography in the human brain , now and in the near future. |
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2007 — 2018 | Leopold, David A | Z01Activity Code Description: Undocumented code - click on the grant title for more information. ZIAActivity Code Description: Undocumented code - click on the grant title for more information. |
The Neural Basis of Functional Mri Responses @ National Institute of Mental Health In the last year, my laboratory has published three papers related to the neural basis of the spontaneous fMRI signal (Leopold and Maier, NeuroImage, 2012; Hutchison et al. NeuroImage, 2013; Scholvinck et al, NeuroImage, 2013). The gist of these papers is that the spontaneous fMRI correlations that are commonly used to evaluate the connectional structure of the human brain are well-behaved and link to electrophysiogical signals, but their origins remain mysterious. We also have made experimental headway on this topic with two recent studies. In Spaak et al, (Current Biology, 2012), we show that resting state electrophysiological processes exhibit a layer-specific coupling, including over time scales relevant for fMRI. Likewise, in a collaborative study (Fukushima et al, Neuron, 2012), we demonstrate that the spatial patterns of spontaneous activity observed in the auditory cortex during rest closely resemble those found during normal acoustic stimulation. These findings are present evidence of a link between spontaneous electrophysiological correlations and fMRI resting state correlations. In a new project, we have begun to investigate whether correlated spontaneous fMRI fluctuations may have their origins not only in the direct connections between two areas, but also in the shared innervation of areas based on input from the basal forebrain. While it is clear that anatomical connections will constrain patterns of activity correlations, their existence does not explain why slow fluctuations in spontaneous activity emerges in the first place. One possibility is that the far-reaching modulatory cholinergic and GABAergic inputs emanating from the several basal forebrain structures drives periods of high and low cortical excitability in concert, which would result in a pattern of functional correlations commonly measured in human fMRI. Our planned first steps to test this hypothesis involves combining inactivation of several basal forebrain structures with fMRI measurements during rest, and later during natural viewing. The null hypothesis of this experiment is clear: inactivation of these projection neurons should have no effect on the pattern of correlated fluctuations over the cortical surface. In another project, we asked to what extent responses observed in high-level visual cortex using fMRI would resemble neural responses observed in the same piece of cortex using microelectrode recordings. We approached this project using natural viewing of social videos, recording both fMRI and electrophysiological responses while monkeys repeatedly watched a number of five-minute video clips. Using this method, we measured a consistent time course evoked for each movie in the microelectrode spiking data and the hemodynamic fMRI data. Given that each voxel in the fMRI signal contains hundreds of thousands of neurons, these results raise the question: to what extent does the activity time course of the fMRI signal in a voxel reflect the time course of spiking within that voxel? As a first step, we have assessed the correlation between adjacent neurons within our microwire array. Neurons were separated by no more than 400 microns, and were thus part of the same cortical column. We found that, even though individual cells are very reliably driven by multiple repetitions of the same movie, nearby cells are remarkably uncorrelated in their responses. Our planned extension of this work is to examine whether some aspect of collective neural activity, such as the mean activity of all neurons in a voxel, or the activity of special, identified neurons, most closely reflects the hemodynamic time course. The hope is that this approach can not only allow us to understand about the coding principles in this part of the brain, but also about how this coding is reflected in the fMRI signal. Finally, we have begun another experiment in which we measure single unit activity from implanted, MR-compatible electrodes, in monkeys that are undergoing fMRI. As described above, adjacent neurons show very different time courses during natural viewing. The same is true during spontaneous activity. Thus one planned experiment is to determine whether two neurons showing different time courses are functionally linked with different fMRI networks in the brain. Thus using spiking fluctuations of two different neurons to reveal two different networks may elucidate the relative contributions of different brain networks to the local neural machinery in a confined cortical area. |
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2007 — 2012 | Leopold, David | Z01Activity Code Description: Undocumented code - click on the grant title for more information. ZIAActivity Code Description: Undocumented code - click on the grant title for more information. |
Visual Adaptation and Neuronal Selectivity @ National Institute of Mental Health Flexible visual recognition, such as that required for social perception, is a notoriously difficult problem for the brain to solve. Ultimately, visual recognition is based on the decoding of the retinal imaging. However, the retinal image cast by a given person's face is never the same twice, and the brain therefore needs to categorize very different images as corresponding to the same person. For example, each time a friend or relative is seen, they are illuminated differently, are seen from a different angle, and are wearing different clothes. Moreover, the internal features of the face will have a different, as the expression-producing muscles give rise to an infinite number of different poses. Nonetheless, the recognition of a familiar individual is immediate and effortless. We are interested in how the brain accomplishes this task, and how social information such as emotional or attentional state, can be extracted based on facial features. Central to understanding the remarkable flexibility in face recognition is plasticity and learning. To this end, we are presently using two approaches to understand how complex stimuli are learned, encoded and stored in high-level visual cortex. In one approach, we are using implanted microwire bundle electrodes to longitudinally track neural responses to faces and other objects during periods of focused learning. We previously demonstrated that in the absence of learning pressures, neurons in the macaque inferotemporal cortex exhibited near-complete stability in their responses over periods exceeding two weeks. This finding raised the question whether learning new stimuli would give rise to changes in neural tuning when monkeys learned new faces, either as individuals, categories, or artificial races. We are presently investigating this issue, with initial results suggesting that training can significantly affect the tuning of inferotemporal neurons. This was shown most clearly using a paradigm the monkey learned positive or negative reward values for a large number of face and non-face stimuli, after which the responses of the learned stimuli differed markedly and the difference lasted for the remaining week of recording. A second paradigm examines the effect of visual priming, or previous exposure, on fMRI responses to stimuli throughout the brain. In priming, previously viewed stimuli generate faster responses than those seen for the first time. As a first step toward investigating the neurobiological basis of priming the macaque prefrontal and temporal cortices, we have recently implemented a novel event-related design in awake monkeys. These findings demonstrate that fMRI responses to previously viewed stimuli are significantly lower in several patches of cortex. We are presently investigating the relationship between these cortical sites and areas known to show selective responses for social stimuli such as faces and bodies. Both longitudinal single-cell recordings and event-related fMRI recordings during priming tap into the cortical plasticity in the brain that characterizes adult learning of social stimuli. Deficits in social learning are characteristic of a number of psychiatric disorders, whose origins are thought to be developmental. However, since cortical learning of social stimuli remains malleable in the adult, gaining a deeper understanding of the cortical changes involved is an important step toward developing interventions to help individuals that have specific difficulty with visual social cognition. |
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2013 — 2018 | Leopold, David A | ZIAActivity Code Description: Undocumented code - click on the grant title for more information. |
Social Processing and Neural Plasticity @ National Institute of Mental Health There are countless mechanisms by which the brain learns, with the fundamental unit of learning expressed at the synapse. In vitro studies can track the changing strength of synapses based on principles of coordinated presynaptic and postsynaptic activity. Many of the principles of neural learning have been a part of the animals central nervous system for hundreds of millions of years. At the level of an individual person or animal, these changes are collectively expressed in such a way that it is useful for ones interaction with the environment. For example, upon meeting and getting to know somebody for the first time, one learns not only their basic facial features, but also how they use their face to express themselves. The brain is able to hold onto, and later use, this information and this is undeniably related to the modification of synaptic strengths, probably in the visual system. However, it is very difficult to even begin to understand how this pattern of learning is expressed across different cortical areas. There may be millions or billions of synapses that are affected during the learning of a face. Where are these changes taking place, and how is it that changing one set of synaptic weights will not severely disrupt other previously learned items? These changes must be back compatible. Sometimes new technologies are needed to shed new light on aspects of brain function. In the laboratory, we have recently developed a chronic recording array of inertialess microwires that were capable of following the activity of single neurons across multiple days. A methods paper on this subject was recently published McMahon et al., J Neurophysiol (2014). With this method, we are able to isolate individual neurons to measure each of their action potentials, either spontaneous or in response to visual stimuli. Because of their small size, and the apparent absence of a gliosis reaction, the electrodes are able to routinely maintain isolation of the same neurons for periods that are much longer than have previously been demonstrated in the visual cortex. This new capacity has enormous implications for the types of experiments one can conduct. For example, with this capacity, it means one is able to examine the responses of single neurons longitudinally, not only over a few hours of a session, but also between sessions, and even across weeks and months. In a recently published study, we measured the responses of multiple neurons within fMRI defined face patches McMahon et al, Proc Natl Acad Sci (2014). We presented a large number of static stimuli in order to establish the selectivity of individual neurons a fingerprint of sorts. Then we went back on subsequent days to the same electrodes (which remained permanently implanted in position) and found that the neurons were still there, and that they maintained a virtually identical fingerprint of stimulus responses. In fact, over time periods of months and even exceeding one year, neurons in the recorded area maintained their precise pattern of stimulus response selectivity. This finding is unexpected because it suggest that neurons in a region of the brain ostensibly dedicated to faces do not exhibit updates or adjustments in their activity with natural experience. To examine face patch plasticity further, we asked whether intensive perceptual training with faces might affect neural responses Jones et al, SFN Abstr (2013). In that study, monkeys were trained to report the identity of a set of morphed human faces as well as a set of morphed macaque faces. We tracked that activity of neurons over a period of longer than three months to determine whether this training would have any effect on the response fingerprint. Training commenced after one month. Throughout this period we presented the same basic stimuli and examined the responses for signs of neural plasticity. We were unable to detect any changes associated with learning. This is striking given that we were recording from one of the fMRI face patches, where we demonstrated that neurons responded vigorously and selective to faces. These findings together present the unexpected result that neurons in a face patch do not change in their responses over time. It is important to point out that this result will almost certainly differ across the brain, as it is clear that some areas within the brain must learn about faces. However, this study does provide a new understanding about what is possible at a neural level: once individual neurons in certain areas of the brain acquire a specific set of stimulus-contingent responses, they are able to retain this precise selectivity for much longer than was previously supposed. |
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