Publications (54)391.88 Total impact
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Article: Structural neurobiology: missing link to a mechanistic understanding of neural computation.
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ABSTRACT: High-resolution, comprehensive structural information is often the final arbiter between competing mechanistic models of biological processes, and can serve as inspiration for new hypotheses. In molecular biology, definitive structural data at atomic resolution are available for many macromolecules; however, information about the structure of the brain is much less complete, both in scope and resolution. Several technical developments over the past decade, such as serial block-face electron microscopy and trans-synaptic viral tracing, have made the structural biology of neural circuits conceivable: we may be able to obtain the structural information needed to reconstruct the network of cellular connections for large parts of, or even an entire, mouse brain within a decade or so. Given that the brain's algorithms are ultimately encoded by this network, knowing where all of these connections are should, at the very least, provide the data needed to distinguish between models of neural computation.Nature Reviews Neuroscience 02/2012; 13(5):351-8. · 26.48 Impact Factor -
Article: 3D segmentation of SBFSEM images of neuropil by a graphical model over supervoxel boundaries.
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ABSTRACT: The segmentation of large volume images of neuropil acquired by serial sectioning electron microscopy is an important step toward the 3D reconstruction of neural circuits. The only cue provided by the data at hand is boundaries between otherwise indistinguishable objects. This indistinguishability, combined with the boundaries becoming very thin or faint in places, makes the large body of work on region-based segmentation methods inapplicable. On the other hand, boundary-based methods that exploit purely local evidence do not reach the extremely high accuracy required by the application domain that cannot tolerate the global topological errors arising from false local decisions. As a consequence, we propose a supervoxel merging method that arrives at its decisions in a non-local fashion, by posing and approximately solving a joint combinatorial optimization problem over all faces between supervoxels. The use of supervoxels allows the extraction of expressive geometric features. These are used by the higher-order potentials in a graphical model that assimilate knowledge about the geometry of neural surfaces by automated training on a gold standard. The scope of this improvement is demonstrated on the benchmark dataset E1088 (Helmstaedter et al., 2011) of 7.5billionvoxels from the inner plexiform layer of rabbit retina. We provide C++ source code for annotation, geometry extraction, training and inference.Medical image analysis 12/2011; 16(4):796-805. · 3.09 Impact Factor -
Article: Large-scale automated histology in the pursuit of connectomes.
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ABSTRACT: How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.Journal of Neuroscience 11/2011; 31(45):16125-38. · 7.11 Impact Factor -
Article: Wiring specificity in the direction-selectivity circuit of the retina.
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ABSTRACT: The proper connectivity between neurons is essential for the implementation of the algorithms used in neural computations, such as the detection of directed motion by the retina. The analysis of neuronal connectivity is possible with electron microscopy, but technological limitations have impeded the acquisition of high-resolution data on a large enough scale. Here we show, using serial block-face electron microscopy and two-photon calcium imaging, that the dendrites of mouse starburst amacrine cells make highly specific synapses with direction-selective ganglion cells depending on the ganglion cell's preferred direction. Our findings indicate that a structural (wiring) asymmetry contributes to the computation of direction selectivity. The nature of this asymmetry supports some models of direction selectivity and rules out others. It also puts constraints on the developmental mechanisms behind the formation of synaptic connections. Our study demonstrates how otherwise intractable neurobiological questions can be addressed by combining functional imaging with the analysis of neuronal connectivity using large-scale electron microscopy.Nature 03/2011; 471(7337):183-8. · 36.28 Impact Factor -
Article: Two-photon calcium imaging of evoked activity from L5 somatosensory neurons in vivo.
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ABSTRACT: Multiphoton imaging (MPI) is widely used for recording activity simultaneously from many neurons in superficial cortical layers in vivo. We combined regenerative amplification multiphoton microscopy (RAMM) with genetically encoded calcium indicators to extend MPI of neuronal population activity into layer 5 (L5) of adult mouse somatosensory cortex. We found that this approach could be used to record and quantify spontaneous and sensory-evoked activity in populations of L5 neuronal somata located as much as 800 μm below the pia. In addition, we found that RAMM could be used to simultaneously image activity from large (80) populations of apical dendrites and follow these dendrites down to their somata of origin.Nature Neuroscience 01/2011; 14(8):1089-93. · 15.53 Impact Factor -
Article: Second-harmonic generation imaging of membrane potential with retinal analogues.
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ABSTRACT: Second-harmonic generation (SHG) by membrane-incorporated probes is a nonlinear optical signal that is voltage-sensitive and the basis of a sensitive method for imaging membrane potential. The voltage dependence of SHG by four different probes, three retinoids (all-trans retinal), and two new retinal analogs, 3-methyl-7-(4'-dimethylamino-phenyl)-2,4,6-heptatrienal (AR-3) and 3,7-dimethyl-9-(4'-dimethylamino-phenyl)-2,4,6,8-nonatetraenal (AR-4), and a styryl dye (FM4-64), were compared in HEK-293 cells. Results were analyzed by fitting data with an expression based on an electrooptic mechanism for SHG, which depends on the complex-valued first- and second-order nonlinear electric susceptibilities (χ² and χ³) of the probe. This gave values for the voltage sensitivity at the cell's resting potential, the voltage where the SHG is minimal, and the amplitude of the signal at that voltage for each of the four compounds. These measures show that χ² and χ³ are complex numbers for all compounds except all-trans retinal, consistent with the proximities of excitation and/or emission wavelengths to molecular resonances. Estimates of probe orientation and location in the membrane electric field show that, for the far-from-resonance case, the shot noise-limited signal/noise ratio depends on the location of the probe in the membrane, and on χ³ but not on χ².Biophysical Journal 01/2011; 100(1):232-42. · 3.65 Impact Factor -
Article: High-accuracy neurite reconstruction for high-throughput neuroanatomy.
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ABSTRACT: Neuroanatomic analysis depends on the reconstruction of complete cell shapes. High-throughput reconstruction of neural circuits, or connectomics, using volume electron microscopy requires dense staining of all cells, which leads even experts to make annotation errors. Currently, reconstruction speed rather than acquisition speed limits the determination of neural wiring diagrams. We developed a method for fast and reliable reconstruction of densely labeled data sets. Our approach, based on manually skeletonizing each neurite redundantly (multiple times) with a visualization-annotation software tool called KNOSSOS, is ∼50-fold faster than volume labeling. Errors are detected and eliminated by a redundant-skeleton consensus procedure (RESCOP), which uses a statistical model of how true neurite connectivity is transformed into annotation decisions. RESCOP also estimates the reliability of consensus skeletons. Focused reannotation of difficult locations promises a rather steep increase of reliability as a function of the average skeleton redundancy and thus the nearly error-free analysis of large neuroanatomical datasets.Nature Neuroscience 01/2011; 14(8):1081-8. · 15.53 Impact Factor -
Article: High speed optical coherence microscopy with autofocus adjustment and a miniaturized endoscopic imaging probe.
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ABSTRACT: Optical coherence microscopy (OCM) is a promising technique for high resolution cellular imaging in human tissues. An OCM system for high-speed en face cellular resolution imaging was developed at 1060 nm wavelength at frame rates up to 5 Hz with resolutions of < 4 microm axial and < 2 microm transverse. The system utilized a novel polarization compensation method to combat wavelength dependent source polarization and achieve broadband electro-optic phase modulation compatible with ultrahigh axial resolution. In addition, the system incorporated an auto-focusing feature that enables precise, near real-time alignment of the confocal and coherence gates in tissue, allowing user-friendly optimization of image quality during the imaging procedure. Ex vivo cellular images of human esophagus, colon, and cervix as well as in vivo results from human skin are presented. Finally, the system design is demonstrated with a miniaturized piezoelectric fiber-scanning probe which can be adapted for laparoscopic and endoscopic imaging applications.Optics Express 03/2010; 18(5):4222-39. · 3.59 Impact Factor -
Conference Proceeding: Boundary Learning by Optimization with Topological Constraints.
The Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2010, San Francisco, CA, USA, 13-18 June 2010; 01/2010 -
Article: Maximin affinity learning of image segmentation
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ABSTRACT: Images can be segmented by first using a classifier to predict an affinity graph that reflects the degree to which image pixels must be grouped together and then partitioning the graph to yield a segmentation. Machine learning has been applied to the affinity classifier to produce affinity graphs that are good in the sense of minimizing edge misclassification rates. However, this error measure is only indirectly related to the quality of segmentations produced by ultimately partitioning the affinity graph. We present the first machine learning algorithm for training a classifier to produce affinity graphs that are good in the sense of producing segmentations that directly minimize the Rand index, a well known segmentation performance measure. The Rand index measures segmentation performance by quantifying the classification of the connectivity of image pixel pairs after segmentation. By using the simple graph partitioning algorithm of finding the connected components of the thresholded affinity graph, we are able to train an affinity classifier to directly minimize the Rand index of segmentations resulting from the graph partitioning. Our learning algorithm corresponds to the learning of maximin affinities between image pixel pairs, which are predictive of the pixel-pair connectivity.11/2009; -
Article: Visually evoked activity in cortical cells imaged in freely moving animals.
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ABSTRACT: We describe a miniaturized head-mounted multiphoton microscope and its use for recording Ca(2+) transients from the somata of layer 2/3 neurons in the visual cortex of awake, freely moving rats. Images contained up to 20 neurons and were stable enough to record continuously for >5 min per trial and 20 trials per imaging session, even as the animal was running at velocities of up to 0.6 m/s. Neuronal Ca(2+) transients were readily detected, and responses to various static visual stimuli were observed during free movement on a running track. Neuronal activity was sparse and increased when the animal swept its gaze across a visual stimulus. Neurons showing preferential activation by specific stimuli were observed in freely moving animals. These results demonstrate that the multiphoton fiberscope is suitable for functional imaging in awake and freely moving animals.Proceedings of the National Academy of Sciences 11/2009; 106(46):19557-62. · 9.68 Impact Factor -
Article: Convolutional networks can learn to generate affinity graphs for image segmentation.
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ABSTRACT: Many image segmentation algorithms first generate an affinity graph and then partition it. We present a machine learning approach to computing an affinity graph using a convolutional network (CN) trained using ground truth provided by human experts. The CN affinity graph can be paired with any standard partitioning algorithm and improves segmentation accuracy significantly compared to standard hand-designed affinity functions. We apply our algorithm to the challenging 3D segmentation problem of reconstructing neuronal processes from volumetric electron microscopy (EM) and show that we are able to learn a good affinity graph directly from the raw EM images. Further, we show that our affinity graph improves the segmentation accuracy of both simple and sophisticated graph partitioning algorithms. In contrast to previous work, we do not rely on prior knowledge in the form of hand-designed image features or image preprocessing. Thus, we expect our algorithm to generalize effectively to arbitrary image types.Neural Computation 11/2009; 22(2):511-38. · 1.88 Impact Factor -
Article: 3D structural imaging of the brain with photons and electrons.
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ABSTRACT: Recent technological developments have renewed the interest in large-scale neural circuit reconstruction. To resolve the structure of entire circuits, thousands of neurons must be reconstructed and their synapses identified. Reconstruction techniques at the light microscopic level are capable of following sparsely labeled neurites over long distances, but fail with densely labeled neuropil. Electron microscopy provides the resolution required to resolve densely stained neuropil, but is challenged when data for volumes large enough to contain complete circuits need to be collected. Both photon-based and electron-based imaging methods will ultimately need highly automated data analysis, because the manual tracing of most networks of interest would require hundreds to tens of thousands of years in human labor.Current opinion in neurobiology 05/2009; 18(6):633-41. · 7.21 Impact Factor -
Article: Single-spike detection in vitro and in vivo with a genetic Ca2+ sensor.
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ABSTRACT: Measurement of population activity with single-action-potential, single-neuron resolution is pivotal for understanding information representation and processing in the brain and how the brain's responses are altered by experience. Genetically encoded indicators of neuronal activity allow long-term, cell type-specific expression. Fluorescent Ca2+ indicator proteins (FCIPs), a main class of reporters of neural activity, initially suffered, in particular, from an inability to report single action potentials in vivo. Although suboptimal Ca2+-binding dynamics and Ca2+-induced fluorescence changes in FCIPs are important factors, low levels of expression also seem to play a role. Here we report that delivering D3cpv, an improved fluorescent resonance energy transfer-based FCIP, using a recombinant adeno-associated virus results in expression sufficient to detect the Ca2+ transients that accompany single action potentials. In upper-layer cortical neurons, we were able to detect transients associated with single action potentials firing at rates of <1 Hz, with high reliability, from in vivo recordings in living mice.Nature Methods 09/2008; 5(9):797-804. · 19.28 Impact Factor -
Article: Spatiotemporally graded NMDA spike/plateau potentials in basal dendrites of neocortical pyramidal neurons.
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ABSTRACT: Glutamatergic inputs clustered over approximately 20-40 microm can elicit local N-methyl-D-aspartate (NMDA) spike/plateau potentials in terminal dendrites of cortical pyramidal neurons, inspiring the notion that a single terminal dendrite can function as a decision-making computational subunit. A typical terminal basal dendrite is approximately 100-200 microm long: could it function as multiple decision-making subunits? We test this by sequential focal stimulation of multiple sites along terminal basal dendrites of layer 5 pyramidal neurons in rat somatosensory cortical brain slices, using iontophoresis or uncaging of brief glutamate pulses. There was an approximately sevenfold spatial gradient in average spike/plateau amplitude measured at the soma, from approximately 3 mV for distal inputs to approximately 23 mV for proximal inputs. Spike/plateaus were NMDA receptor (NMDAR) conductance-dominated at all locations. Large Ca(2+) transients accompanied spike/plateaus over a approximately 10- to 40-microm zone around the input site; smaller Ca(2+) transients extended approximately uniformly to the dendritic tip. Spike/plateau duration grew with increasing glutamate and depolarization; high Ca(2+) zone size grew with spike/plateau duration. The minimum high Ca(2+) zone half-width (just above NMDA spike threshold) increased from distal (approximately 10 microm) to proximal locations (approximately 25 microm), as did the NMDA spike glutamate threshold. Depolarization reduced glutamate thresholds. Simulations exploring multi-site interactions based on this demonstrate that if appropriately timed and localized inputs occur in vivo, a single basal dendrite could correspond to a cascade of multiple co-operating dynamic decision-making subunits able to retain information for hundreds of milliseconds, with increasing influence on neural output from distal to proximal. Dendritic NMDA spike/plateaus are thus well-suited to support graded persistent firing.Journal of Neurophysiology 06/2008; 99(5):2584-601. · 3.32 Impact Factor -
Article: Imaging in vivo: watching the brain in action.
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ABSTRACT: The appeal of in vivo cellular imaging to any neuroscientist is not hard to understand: it is almost impossible to isolate individual neurons while keeping them and their complex interactions with surrounding tissue intact. These interactions lead to the complex network dynamics that underlie neural computation which, in turn, forms the basis of cognition, perception and consciousness. In vivo imaging allows the study of both form and function in reasonably intact preparations, often with subcellular spatial resolution, a time resolution of milliseconds and a purview of months. Recently, the limits of what can be achieved in vivo have been pushed into terrain that was previously only accessible in vitro, due to advances in both physical-imaging technology and the design of molecular contrast agents.Nature Reviews Neuroscience 04/2008; 9(3):195-205. · 26.48 Impact Factor -
Article: Targeted patch-clamp recordings and single-cell electroporation of unlabeled neurons in vivo.
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ABSTRACT: Here we describe an approach for making targeted patch-clamp recordings from single neurons in vivo, visualized by two-photon microscopy. A patch electrode is used to perfuse the extracellular space surrounding the neuron of interest with a fluorescent dye, thus enabling the neuron to be visualized as a negative image ('shadow') and identified on the basis of its somatodendritic structure. The same electrode is then placed on the neuron under visual control to allow formation of a gigaseal ('shadowpatching'). We demonstrate the reliability and versatility of shadowpatching by performing whole-cell recordings from visually identified neurons in the neocortex and cerebellum of rat and mouse. We also show that the method can be used for targeted in vivo single-cell electroporation of plasmid DNA into identified cell types, leading to stable transgene expression. This approach facilitates the recording, labeling and genetic manipulation of single neurons in the intact native mammalian brain without the need to pre-label neuronal populations.Nature Methods 02/2008; 5(1):61-7. · 19.28 Impact Factor -
Article: Contour-propagation algorithms for semi-automated reconstruction of neural processes.
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ABSTRACT: A new technique, "serial block face scanning electron microscopy" (SBFSEM), allows for automatic sectioning and imaging of biological tissue with a scanning electron microscope. Image stacks generated with this technology have a resolution sufficient to distinguish different cellular compartments, including synaptic structures, which should make it possible to obtain detailed anatomical knowledge of complete neuronal circuits. Such an image stack contains several thousands of images and is recorded with a minimal voxel size of 10-20 nm in the x- and y-direction and 30 nm in z-direction. Consequently, a tissue block of 1 mm(3)(the approximate volume of the Calliphora vicina brain) will produce several hundred terabytes of data. Therefore, highly automated 3D reconstruction algorithms are needed. As a first step in this direction we have developed semi-automated segmentation algorithms for a precise contour tracing of cell membranes. These algorithms were embedded into an easy-to-operate user interface, which allows direct 3D observation of the extracted objects during the segmentation of image stacks. Compared to purely manual tracing, processing time is greatly accelerated.Journal of Neuroscience Methods 02/2008; 167(2):349-57. · 1.98 Impact Factor -
Conference Proceeding: Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification.
Pattern Recognition, 30th DAGM Symposium, Munich, Germany, June 10-13, 2008, Proceedings; 01/2008 -
Article: Properties of coherence-gated wavefront sensing.
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ABSTRACT: Coherence-gated wavefront sensing (CGWS) allows the determination of wavefront aberrations in strongly scattering tissue and their correction by adaptive optics. This allows, e.g., the restoration of the diffraction limit in light microscopy. Here, we develop a model, based on ray tracing of ballistic light scattered from a set of discrete scatterers, to characterize CGWS performance as it depends on coherence length, scatterer density, coherence-gate position, and polarization. The model is evaluated by using Monte Carlo simulation and verified against experimental measurements. We show, in particular, that all aberrations needed for adaptive wavefront restoration are correctly sensed if circularly polarized light is used.Journal of the Optical Society of America A 12/2007; 24(11):3517-29. · 1.56 Impact Factor
Top co-authors
Top Journals
Institutions
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2002–2012
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Max-Planck-Institut für Medizinische Forschung
- Abteilung Biomedizinische Optik
Heidelberg, Baden-Wuerttemberg, Germany -
Max-Planck-Gesellschaft
München, Bavaria, Germany
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2011
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Janelia Farm Research Campus
Ashburn, VA, USA
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2009
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Massachusetts Institute of Technology
- Department of Brain and Cognitive Sciences
Cambridge, MA, USA
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2008
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Cardiff University
- School of Biosciences
Cardiff, WLS, United Kingdom -
Max-Planck-Institut für biologische Kybernetik
Tübingen, Baden-Wuerttemberg, Germany
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2006
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Universität Zürich
- The KEY Institute for Brain-Mind Research
Zürich, ZH, Switzerland
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1996
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Columbia University
New York City, NY, USA
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