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","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","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"]]

[["dc.bibliographiccitation.artnumber","e1002438"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","PLoS Computational Biology"],["dc.bibliographiccitation.volume","8"],["dc.contributor.author","Battaglia, Demian"],["dc.contributor.author","Witt, Annette"],["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","2012"],["dc.description.abstract","Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we advance here that dynamic interactions between brain rhythms provide as well the basis for the self-organized control of this “communication-through-coherence”, making thus possible a fast “on-demand” reconfiguration of global information routing modalities."],["dc.identifier.doi","10.1371/journal.pcbi.1002438"],["dc.identifier.gro","3151853"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/7868"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8682"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","1553-7358"],["dc.rights","CC BY 2.5"],["dc.rights.uri","https://creativecommons.org/licenses/by/2.5"],["dc.title","Dynamic Effective Connectivity of Inter-Areal Brain Circuits"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","75"],["dc.bibliographiccitation.journal","European Journal of Neuroscience"],["dc.contributor.author","Wolf, Fred"],["dc.contributor.author","Geisel, Theo"],["dc.date.accessioned","2017-11-22T09:58:30Z"],["dc.date.available","2017-11-22T09:58:30Z"],["dc.date.issued","2000"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/10184"],["dc.language.iso","en"],["dc.notes.status","new -primates"],["dc.title","Are pinwheels essential?"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3251"],["dc.bibliographiccitation.issue","12"],["dc.bibliographiccitation.journal","European Journal of Neuroscience"],["dc.bibliographiccitation.lastpage","3266"],["dc.bibliographiccitation.volume","18"],["dc.contributor.author","Kaschube, Matthias"],["dc.contributor.author","Wolf, Fred"],["dc.contributor.author","Puhlmann, Mathias"],["dc.contributor.author","Rathjen, Stefan"],["dc.contributor.author","Schmidt, Karl-Friedrich"],["dc.contributor.author","Geisel, Theo"],["dc.contributor.author","Löwel, Siegrid"],["dc.date.accessioned","2017-09-07T11:45:37Z"],["dc.date.available","2017-09-07T11:45:37Z"],["dc.date.issued","2003"],["dc.description.abstract","We present a comprehensive analysis of the intrinsic variability of the periodicity of ocular dominance columns in cat primary visual cortex (area 17) and its relationship to genetic background and visual experience. We characterized the intra-areal and interindividual variability of column spacing in a large set (n = 49) of ocular dominance patterns adapting a recently developed technique for the two-dimensional analysis of orientation column patterns. Patterns were obtained from three different cat colonies (termed F, M and D), the cats having either normal visual experience or experimentally induced strabismus. Two-dimensional maps of local column spacing were calculated for every pattern. In individual cortices, local column spacings varied by > 50% with the majority of column spacings ranging between 0.6 and 1.5 mm in different animals. In animals from colonies F and M (n = 29), the mean column spacing ranged between 1.03 and 1.27 mm and exhibited no significant differences, either between the two breeds or between strabismic and normal animals. The mean spacing was moderately clustered in the left and right brain hemisphere of individual animals but not in littermates. In animals from colony D (n = 2), average column spacing ranged between 0.73 and 0.95 mm, and was thus significantly different from the distribution of spacings in animals from breeds F and M, suggesting an influence of genetic factors on the layout of ocular dominance columns. Local column spacing exhibited a considerable systematic intra-areal variation, with largest spacings along the representation of the horizontal meridian and smallest spacings along the peripheral representation of the vertical meridian. The total variability of ocular dominance column spacing comprised 24% systematic intra-areal variation, 18% interindividual differences of mean column spacing and 58% nonsystematic intra-areal variability."],["dc.identifier.doi","10.1111/j.1460-9568.2003.02979.x"],["dc.identifier.gro","3151826"],["dc.identifier.pmid","14686899"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8656"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0953-816X"],["dc.title","The pattern of ocular dominance columns in cat primary visual cortex: intra- and interindividual variability of column spacing and its dependence on genetic background"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","97"],["dc.bibliographiccitation.lastpage","101"],["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","Eeckman, Frank H."],["dc.date.accessioned","2017-09-07T11:45:41Z"],["dc.date.available","2017-09-07T11:45:41Z"],["dc.date.issued","2011"],["dc.description.abstract","We propose a mathematical description for the spatial organization of orientation preference in the visual cortex. The theory is derived from the principle of optimal smoothness and predicts the spatial pattern of orientation preference from position and chirality of its singularities (i.e. “pinwheels”). The model exhibits long range order in the sense that, given the configuration of singularities, the specification of orientation preference at a single location fixes the entire map. A comparison with optically recorded images of cortical maps suggests that orientation preference can indeed be predicted over a much larger spatial range than previously estimated on the basis of correlation measurements."],["dc.identifier.doi","10.1007/978-1-4615-2714-5_16"],["dc.identifier.gro","3151843"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8670"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.publisher","Springer"],["dc.publisher.place","Boston, MA"],["dc.relation.isbn","978-1-4613-6169-5"],["dc.relation.ispartof","Computation in Neurons and Neural Systems"],["dc.title","Optimal Smoothness of Orientation Preference Maps"],["dc.type","book_chapter"],["dc.type.internalPublication","no"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]