Wolf, Fred

[["dc.contributor.author","Wolf, Fred"],["dc.contributor.author","Pawelzik, Klaus"],["dc.contributor.author","Geisel, Theo"],["dc.contributor.author","Kim, Douglas S."],["dc.contributor.author","Bonhoeffer, Tobias"],["dc.contributor.editor","Gielen, S."],["dc.contributor.editor","Kappen, B."],["dc.date.accessioned","2017-09-07T11:46:18Z"],["dc.date.available","2017-09-07T11:46:18Z"],["dc.date.issued","2012"],["dc.description.abstract","We propose a mathematical description for the spatial organization of orientation preference in the visual cortex. In this approach the spatial pattern of orientation preference is predicted from position and chirality of its singularities (i.e. ”pinwheels”). The theory is derived from a few phenomenological principles characterizing the qualitative structure of orientation maps under the requirement of mathematical simplicity. A comparison with optically recorded images of cortical maps suggests that orientation preference can be predicted over a much larger spatial range than previously estimated on the basis of correlation measurements."],["dc.identifier.doi","10.1007/978-1-4471-2063-6_30"],["dc.identifier.gro","3151879"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8711"],["dc.language.iso","en"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.publisher","Springer"],["dc.publisher.place","London"],["dc.relation.isbn","978-3-540-19839-0"],["dc.relation.ispartof","ICANN ’93"],["dc.title","Map Structure from Pinwheel Position"],["dc.type","book_chapter"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","63"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of Computational Neuroscience"],["dc.bibliographiccitation.lastpage","75"],["dc.bibliographiccitation.volume","39"],["dc.contributor.author","Öz, Pinar"],["dc.contributor.author","Huang, Min"],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2017-09-07T11:46:14Z"],["dc.date.available","2017-09-07T11:46:14Z"],["dc.date.issued","2015"],["dc.description.abstract","Somatic action potentials (AP) of cortical pyramidal neurons have characteristically high onset-rapidness. The onset of the AP waveform is an indirect measure for the ability of a neuron to respond to temporally fast-changing stimuli. Theoretical studies on the pyramidal neuron response usually involves a canonical Hodgkin-Huxley (HH) type ion channel gating model, which assumes statistically independent gating of each individual channel. However, cooperative activity of ion channels are observed for various cell types, meaning that the activity (e.g. opening) of one channel triggers the activity (e.g. opening) of a certain fraction of its neighbors and hence, these groups of channels behave as a unit. In this study, we describe a multi-compartmental conductance-based model with cooperatively gating voltage-gated Na channels in the axon initial segment. Our model successfully reproduced the somatic sharp AP onsets of cortical pyramidal neurons. The onset latencies from the initiation site to the soma and the conduction velocities were also in agreement with the previous experimental studies."],["dc.identifier.doi","10.1007/s10827-015-0561-9"],["dc.identifier.gro","3151864"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8694"],["dc.language.iso","en"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","0929-5313"],["dc.title","Action potential initiation in a multi-compartmental model with cooperatively gating Na channels in the axon initial segment"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","194"],["dc.bibliographiccitation.journal","Journal of Neuroscience Methods"],["dc.bibliographiccitation.lastpage","203"],["dc.bibliographiccitation.volume","257"],["dc.contributor.author","Samhaber, Robert"],["dc.contributor.author","Schottdorf, Manuel"],["dc.contributor.author","El Hady, Ahmed"],["dc.contributor.author","Broeking, Kai"],["dc.contributor.author","Daus, Andreas"],["dc.contributor.author","Thielemann, Christiane"],["dc.contributor.author","Stühmer, Walter"],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2018-11-07T10:19:24Z"],["dc.date.available","2018-11-07T10:19:24Z"],["dc.date.issued","2016"],["dc.description.abstract","Background: Multi-electrode arrays (MEAs) allow non-invasive multi-unit recording in-vitro from cultured neuronal networks. For sufficient neuronal growth and adhesion on such MEAs, substrate preparation is required. Plating of dissociated neurons on a uniformly prepared MEA's surface results in the formation of spatially extended random networks with substantial inter-sample variability. Such cultures are not optimally suited to study the relationship between defined structure and dynamics in neuronal networks. To overcome these shortcomings, neurons can be cultured with pre-defined topology by spatially structured surface modification. Spatially structuring a MEA surface accurately and reproducibly with the equipment of a typical cell-culture laboratory is challenging. New method: In this paper, we present a novel approach utilizing micro-contact printing (mu CP) combined with a custom-made device to accurately position patterns on MEAs with high precision. We call this technique AP-mu CP (accurate positioning micro-contact printing). Comparison with existing methods: Other approaches presented in the literature using mu CP for patterning either relied on facilities or techniques not readily available in a standard cell culture laboratory, or they did not specify means of precise pattern positioning. Conclusion: Here we present a relatively simple device for reproducible and precise patterning in a standard cell-culture laboratory setting. The patterned neuronal islands on MEAs provide a basis for high throughput electrophysiology to study the dynamics of single neurons and neuronal networks. (C) 2015 Elsevier B.V. All rights reserved."],["dc.identifier.doi","10.1016/j.jneumeth.2015.09.022"],["dc.identifier.isi","000366224100020"],["dc.identifier.pmid","26432934"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/41649"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","1872-678X"],["dc.relation.issn","0165-0270"],["dc.title","Growing neuronal islands on multi-electrode arrays using an accurate positioning-mu CP device"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1335"],["dc.bibliographiccitation.journal","Neurocomputing"],["dc.bibliographiccitation.lastpage","1339"],["dc.bibliographiccitation.volume","38-40"],["dc.contributor.author","Kaschube, Matthias"],["dc.contributor.author","Wolf, Fred"],["dc.contributor.author","Geisel, Theo"],["dc.contributor.author","Löwel, Siegrid"],["dc.date.accessioned","2017-09-07T11:46:12Z"],["dc.date.available","2017-09-07T11:46:12Z"],["dc.date.issued","2001"],["dc.description.abstract","Our visual system preferentially groups contour segments that not only have the same orientation but are colinear as well. Long-range horizontal connections are thought to play an important role in context-dependent modifications of neuronal responses. Since the topology of these connections shows a close relation to the perceptual grouping criterion of colinearity, we tested whether the statistical properties of real world images are biased towards colinear contours. By wavelet analysis we detected contours in images of natural environments and calculated their spatial correlations. In urban as well as in natural environments, the correlations between colinear contour segments were larger than the correlations for parallel contour segments. These observations indicate that colinear contour segments dominate real world images and thus might bias the functional and structural development of our visual system."],["dc.identifier.doi","10.1016/s0925-2312(01)00493-3"],["dc.identifier.gro","3151855"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8684"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.issn","0925-2312"],["dc.subject","Image analysis; Natural scenes; Wavelets; Visual cortex"],["dc.title","The prevalence of colinear contours in the real world"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","015108"],["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Chaos: An Interdisciplinary Journal of Nonlinear Science"],["dc.bibliographiccitation.lastpage","16"],["dc.bibliographiccitation.volume","16"],["dc.contributor.author","Timme, Marc"],["dc.contributor.author","Geisel, Theo"],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2017-09-07T11:46:16Z"],["dc.date.available","2017-09-07T11:46:16Z"],["dc.date.issued","2006"],["dc.description.abstract","We analyze the dynamics of networks of spiking neural oscillators. First, we present an exact linear stability theory of the synchronous state for networks of arbitrary connectivity. For general neuron rise functions, stability is determined by multiple operators, for which standard analysis is not suitable. We describe a general nonstandard solution to the multioperator problem. Subsequently, we derive a class of neuronal rise functions for which all stability operators become degenerate and standard eigenvalue analysis becomes a suitable tool. Interestingly, this class is found to consist of networks of leaky integrate-and-fire neurons. For random networks of inhibitory integrate-and-fire neurons, we then develop an analytical approach, based on the theory of random matrices, to precisely determine the eigenvalue distributions of the stability operators. This yields the asymptotic relaxation time for perturbations to the synchronous state which provides the characteristic time scale on which neurons can coordinate their activity in such networks. For networks with finite in-degree, i.e., finite number of presynaptic inputs per neuron, we find a speed limit to coordinating spiking activity. Even with arbitrarily strong interaction strengths neurons cannot synchronize faster than at a certain maximal speed determined by the typical in-degree.The individual units of many physical systems, from the planets of our solar system to the atoms in a solid, typically interact continuously in time and without significant delay. Thus at every instant of time such a unit is influenced by the current state of its interaction partners. Moreover, particles of many-body systems are often considered to have very simple lattice topology (as in a crystal) or no prescribed topology at all (as in an ideal gas). Many important biological systems are drastically different: their units are interacting by sending and receiving pulses at discrete instances of time. Furthermore, biological systems often exhibit significant delays in the couplings and very complicated topologies of their interaction networks. Examples of such systems include neurons, which interact by stereotyped electrical pulses called action potentials or spikes; crickets, which chirp to communicate acoustically; populations of fireflies that interact by short light pulses. The combination of pulse-coupling, delays, and complicated network topology formally makes the dynamical system to be investigated a high dimensional, heterogeneous nonlinear hybrid system with delays. Here we present an exact analysis of aspects of the dynamics of such networks in the case of simple one-dimensional nonlinear interacting units. These systems are simple models for the collective dynamics of recurrent networks of spiking neurons. After briefly presenting stability results for the synchronous state, we show how to use the theory of random matrices to analytically predict the eigenvalue distribution of stability matrices and thus derive the speed of synchronization in terms of dynamical and network parameters. We find that networks of neural oscillators typically exhibit speed limits and cannot synchronize faster than a certain bound defined by the network topology."],["dc.identifier.doi","10.1063/1.2150775"],["dc.identifier.gro","3151890"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8722"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","1054-1500"],["dc.title","Speed of synchronization in complex networks of neural oscillators: Analytic results based on Random Matrix Theory"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","821"],["dc.contributor.author","Timme, Marc"],["dc.contributor.author","Geisel, Theo"],["dc.contributor.author","Wolf, F."],["dc.date.accessioned","2017-11-21T15:34:02Z"],["dc.date.available","2017-11-21T15:34:02Z"],["dc.date.issued","2001"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/10167"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.eventend","2001-11-15"],["dc.relation.eventlocation","San Diego"],["dc.relation.eventstart","2001-11-10"],["dc.relation.ispartof","Society for Neuroscience Abstracts"],["dc.title","Synchronization and Desynchronization in Neural Networks with General Connectivity"],["dc.type","conference_abstract"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","367"],["dc.bibliographiccitation.journal","Neurocomputing"],["dc.bibliographiccitation.lastpage","374"],["dc.bibliographiccitation.volume","26-27"],["dc.contributor.author","Ernst, Udo"],["dc.contributor.author","Pawelzik, Klaus"],["dc.contributor.author","Wolf, Fred"],["dc.contributor.author","Geisel, Theo"],["dc.date.accessioned","2017-09-07T11:46:13Z"],["dc.date.available","2017-09-07T11:46:13Z"],["dc.date.issued","1999"],["dc.description.abstract","In many experiments it has been found that stimuli outside the classical receptive-field of orientation-selective cells in the visual cortex can strongly modulate the response properties of these cells. Typically, stimuli with orientation contrasts lead to enhancement, whereas iso-orientation stimuli lead to suppression of the neuronal activity, but these phenomena in general depend in a complicate manner on various parameters like stimulus configuration, contrast, and geometry. In this contribution, we develop a simple theory for such non-classical receptive-field phenomena. We explain the basic mechanisms by a fixed-point analysis. Within this analysis, center-surround experiments can be described by trajectories in parameter space. This allows for a systematic variation of the coupling and stimulation constants. We show that the strength or sign of the enhancement or suppression should not only vary with the experimental paradigm but also with the position of the cell within the cortex. Our results suggest that non-classical receptive-field phenomena are mediated through orientation-specific lateral excitatory interactions."],["dc.identifier.doi","10.1016/s0925-2312(99)00026-0"],["dc.identifier.gro","3151865"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8695"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.issn","0925-2312"],["dc.subject","Receptive fields; Visual cortex; Orientation contrast sensitivity; Fixed-point analysis; Center-surround phenomena"],["dc.title","Theory of non-classical receptive field phenomena in the visual cortex"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","e2114549118"],["dc.bibliographiccitation.issue","51"],["dc.bibliographiccitation.journal","Proceedings of the National Academy of Sciences"],["dc.bibliographiccitation.volume","118"],["dc.contributor.author","Merino, Ricardo Martins"],["dc.contributor.author","Leon-Pinzon, Carolina"],["dc.contributor.author","Stühmer, Walter"],["dc.contributor.author","Möck, Martin"],["dc.contributor.author","Staiger, Jochen F."],["dc.contributor.author","Wolf, Fred"],["dc.contributor.author","Neef, Andreas"],["dc.date.accessioned","2022-02-01T10:31:17Z"],["dc.date.available","2022-02-01T10:31:17Z"],["dc.date.issued","2021"],["dc.description.abstract","Fast oscillations in cortical circuits critically depend on GABAergic interneurons. Which interneuron types and populations can drive different cortical rhythms, however, remains unresolved and may depend on brain state. Here, we measured the sensitivity of different GABAergic interneurons in prefrontal cortex under conditions mimicking distinct brain states. While fast-spiking neurons always exhibited a wide bandwidth of around 400 Hz, the response properties of spike-frequency adapting interneurons switched with the background input\\’s statistics. Slowly fluctuating background activity, as typical for sleep or quiet wakefulness, dramatically boosted the neurons\\’ sensitivity to gamma and ripple frequencies. We developed a time-resolved dynamic gain analysis and revealed rapid sensitivity modulations that enable neurons to periodically boost gamma oscillations and ripples during specific phases of ongoing low-frequency oscillations. This mechanism predicts these prefrontal interneurons to be exquisitely sensitive to high-frequency ripples, especially during brain states characterized by slow rhythms, and to contribute substantially to theta-gamma cross-frequency coupling."],["dc.description.abstract","Fast oscillations in cortical circuits critically depend on GABAergic interneurons. Which interneuron types and populations can drive different cortical rhythms, however, remains unresolved and may depend on brain state. Here, we measured the sensitivity of different GABAergic interneurons in prefrontal cortex under conditions mimicking distinct brain states. While fast-spiking neurons always exhibited a wide bandwidth of around 400 Hz, the response properties of spike-frequency adapting interneurons switched with the background input’s statistics. Slowly fluctuating background activity, as typical for sleep or quiet wakefulness, dramatically boosted the neurons’ sensitivity to gamma and ripple frequencies. We developed a time-resolved dynamic gain analysis and revealed rapid sensitivity modulations that enable neurons to periodically boost gamma oscillations and ripples during specific phases of ongoing low-frequency oscillations. This mechanism predicts these prefrontal interneurons to be exquisitely sensitive to high-frequency ripples, especially during brain states characterized by slow rhythms, and to contribute substantially to theta-gamma cross-frequency coupling."],["dc.identifier.doi","10.1073/pnas.2114549118"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/98819"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-517"],["dc.relation.eissn","1091-6490"],["dc.relation.issn","0027-8424"],["dc.rights.uri","https://www.pnas.org/site/aboutpnas/licenses.xhtml"],["dc.title","Theta activity paradoxically boosts gamma and ripple frequency sensitivity in prefrontal interneurons"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","12933"],["dc.bibliographiccitation.issue","47"],["dc.bibliographiccitation.journal","The Journal of neuroscience"],["dc.bibliographiccitation.lastpage","12944"],["dc.bibliographiccitation.volume","27"],["dc.contributor.author","Neef, Andreas"],["dc.contributor.author","Khimich, Darina"],["dc.contributor.author","Pirih, Primoz"],["dc.contributor.author","Riedel, Dietmar"],["dc.contributor.author","Wolf, Fred"],["dc.contributor.author","Moser, Tobias"],["dc.date.accessioned","2017-09-07T11:49:23Z"],["dc.date.available","2017-09-07T11:49:23Z"],["dc.date.issued","2007"],["dc.description.abstract","Hearing relies on faithful synaptic transmission at the ribbon synapse of cochlear inner hair cells (IHCs). Postsynaptic recordings from this synapse in prehearing animals had delivered strong indications for synchronized release of several vesicles. The underlying mechanism, however, remains unclear. Here, we used presynaptic membrane capacitance measurements to test whether IHCs release vesicles in a statistically independent or dependent ( coordinated) manner. Exocytic changes of membrane capacitance (Delta C-m) were repeatedly stimulated in IHCs of prehearing and hearing mice by short depolarizations to preferentially recruit the readily releasable pool of synaptic vesicles. A compound Poisson model was devised to describe hair cell exocytosis and to test the analysis. From the trial-to-trial fluctuations of the Delta C-m we were able to estimate the apparent size of the elementary fusion event (C-app) at the hair cell synapse to be 96-223 aF in immature and 55-149 aF in mature IHCs. We also approximated the single vesicle capacitance in IHCs by measurements of synaptic vesicle diameters in electron micrographs. The results (immature, 48 aF; mature, 45 aF) were lower than the respective Capp estimates. This indicates that coordinated exocytosis of synaptic vesicles occurs at both immature and mature hair cell synapses. Approximately 35% of the release events in mature IHCs and similar to 50% in immature IHCs were predicted to involve coordinated fusion, when assuming a geometric distribution of elementary sizes. In summary, our presynaptic measurements indicate coordinated exocytosis but argue for a lesser degree of coordination than suggested by postsynaptic recordings."],["dc.identifier.doi","10.1523/JNEUROSCI.1996-07.2007"],["dc.identifier.gro","3143408"],["dc.identifier.isi","000251157200022"],["dc.identifier.pmid","18032667"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/919"],["dc.notes.intern","WoS Import 2017-03-10"],["dc.notes.status","final"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Soc Neuroscience"],["dc.relation.issn","0270-6474"],["dc.title","Probing the mechanism of exocytosis at the hair cell ribbon synapse"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","7206"],["dc.bibliographiccitation.issue","16"],["dc.bibliographiccitation.journal","Journal of Neuroscience"],["dc.bibliographiccitation.lastpage","7217"],["dc.bibliographiccitation.volume","22"],["dc.contributor.author","Kaschube, M."],["dc.contributor.author","Geisel, Theo"],["dc.contributor.author","Lowel, S."],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2018-11-07T10:10:41Z"],["dc.date.available","2018-11-07T10:10:41Z"],["dc.date.issued","2002"],["dc.description.abstract","The layout of functional cortical maps exhibits a high degree of interindividual variability that may account for individual differences in sensory and cognitive abilities. By quantitatively assessing the interindividual variability of orientation preference columns in the primary visual cortex, we demonstrate that column sizes and shapes as well as a measure of the homogeneity of column sizes across the visual cortex are significantly clustered in genetically related animals and in the two hemispheres of individual brains. Taking the developmental timetable of column formation into account, our data indicate a substantial genetic influence on the developmental specification of visual cortical architecture and suggest ways in which genetic information may influence an individual's visual abilities."],["dc.identifier.isi","000177421000036"],["dc.identifier.pmid","12177215"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/39905"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Soc Neuroscience"],["dc.relation.eissn","1529-2401"],["dc.relation.issn","0270-6474"],["dc.subject","visual cortex; development; orientation columns; cortical maps; area 17; genetic determination"],["dc.title","Genetic influence on quantitative features of neocortical architecture"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]