Wolf, Fred

[["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.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.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","1113"],["dc.bibliographiccitation.issue","6007"],["dc.bibliographiccitation.journal","Science"],["dc.bibliographiccitation.lastpage","1116"],["dc.bibliographiccitation.volume","330"],["dc.contributor.author","Kaschube, Matthias"],["dc.contributor.author","Schnabel, Michael"],["dc.contributor.author","Löwel, Siegrid"],["dc.contributor.author","Coppola, David M."],["dc.contributor.author","White, Leonard E."],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2017-09-07T11:46:14Z"],["dc.date.available","2017-09-07T11:46:14Z"],["dc.date.issued","2010"],["dc.description.abstract","The brain’s visual cortex processes information concerning form, pattern, and motion within functional maps that reflect the layout of neuronal circuits. We analyzed functional maps of orientation preference in the ferret, tree shrew, and galago—three species separated since the basal radiation of placental mammals more than 65 million years ago—and found a common organizing principle. A symmetry-based class of models for the self-organization of cortical networks predicts all essential features of the layout of these neuronal circuits, but only if suppressive long-range interactions dominate development. We show mathematically that orientation-selective long-range connectivity can mediate the required interactions. Our results suggest that self-organization has canalized the evolution of the neuronal circuitry underlying orientation preference maps into a single common design."],["dc.identifier.doi","10.1126/science.1194869"],["dc.identifier.gro","3151861"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8691"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0036-8075"],["dc.title","Universality in the Evolution of Orientation Columns in the Visual Cortex"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Kaschube, Matthias"],["dc.contributor.author","Wolf, F."],["dc.contributor.author","Geisel, Theo"],["dc.contributor.author","Löwel, Siegrid"],["dc.date.accessioned","2017-11-22T08:54:13Z"],["dc.date.available","2017-11-22T08:54:13Z"],["dc.date.issued","1999"],["dc.format.extent","480"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/10174"],["dc.language.iso","en"],["dc.notes.status","new -primates"],["dc.publisher","Thieme"],["dc.publisher.place","Stuttgart"],["dc.relation.ispartof","Proceedings of the 27th Göttingen Neurobiology Conference"],["dc.title","Quantifying the Variability of Patterns of Orientation Columns in Cat’s Area 17: Correlation-Lengths and Wavelengths"],["dc.type","book_chapter"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e1002466"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","PLoS Computational Biology"],["dc.bibliographiccitation.volume","8"],["dc.contributor.author","Reichl, Lars"],["dc.contributor.author","Heide, Dominik"],["dc.contributor.author","Löwel, Siegrid"],["dc.contributor.author","Crowley, Justin C."],["dc.contributor.author","Kaschube, Matthias"],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2017-09-07T11:46:12Z"],["dc.date.available","2017-09-07T11:46:12Z"],["dc.date.issued","2012"],["dc.description.abstract","In the primary visual cortex of primates and carnivores, functional architecture can be characterized by maps of various stimulus features such as orientation preference (OP), ocular dominance (OD), and spatial frequency. It is a long-standing question in theoretical neuroscience whether the observed maps should be interpreted as optima of a specific energy functional that summarizes the design principles of cortical functional architecture. A rigorous evaluation of this optimization hypothesis is particularly demanded by recent evidence that the functional architecture of orientation columns precisely follows species invariant quantitative laws. Because it would be desirable to infer the form of such an optimization principle from the biological data, the optimization approach to explain cortical functional architecture raises the following questions: i) What are the genuine ground states of candidate energy functionals and how can they be calculated with precision and rigor? ii) How do differences in candidate optimization principles impact on the predicted map structure and conversely what can be learned about a hypothetical underlying optimization principle from observations on map structure? iii) Is there a way to analyze the coordinated organization of cortical maps predicted by optimization principles in general? To answer these questions we developed a general dynamical systems approach to the combined optimization of visual cortical maps of OP and another scalar feature such as OD or spatial frequency preference. From basic symmetry assumptions we obtain a comprehensive phenomenological classification of possible inter-map coupling energies and examine representative examples. We show that each individual coupling energy leads to a different class of OP solutions with different correlations among the maps such that inferences about the optimization principle from map layout appear viable. We systematically assess whether quantitative laws resembling experimental observations can result from the coordinated optimization of orientation columns with other feature maps."],["dc.identifier.doi","10.1371/journal.pcbi.1002466"],["dc.identifier.gro","3151847"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8433"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8676"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","1553-7358"],["dc.relation.orgunit","Fakultät für Physik"],["dc.rights","CC BY 2.5"],["dc.rights.uri","http://creativecommons.org/licenses/by/2.5/"],["dc.title","Coordinated Optimization of Visual Cortical Maps (I) Symmetry-based Analysis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Kaschube, Matthias"],["dc.contributor.author","Wolf, F."],["dc.contributor.author","Geisel, Theo"],["dc.contributor.author","Rathjen, Stefan"],["dc.contributor.author","Löwel, Siegrid"],["dc.date.accessioned","2017-11-21T15:23:16Z"],["dc.date.available","2017-11-21T15:23:16Z"],["dc.date.issued","2001"],["dc.format.extent","546"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/10164"],["dc.language.iso","en"],["dc.notes.status","new -primates"],["dc.publisher","Thieme Verlag"],["dc.relation.ispartof","28th Göttingen Neurobiology Conference, Göttingen"],["dc.title","2-D Analysis of Patterns of Ocular Dominance Columns in Cat Primary Visual Cortex"],["dc.type","book_chapter"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","6080"],["dc.bibliographiccitation.journal","Science"],["dc.bibliographiccitation.volume","336"],["dc.contributor.author","Keil, Wolfgang"],["dc.contributor.author","Kaschube, Matthias"],["dc.contributor.author","Schnabel, Michael"],["dc.contributor.author","Kisvarday, Zoltan F."],["dc.contributor.author","Löwel, Siegrid"],["dc.contributor.author","Coppola, David M."],["dc.contributor.author","White, Leonard E."],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2017-09-07T11:46:13Z"],["dc.date.available","2017-09-07T11:46:13Z"],["dc.date.issued","2012"],["dc.description.abstract","Meng et al. conjecture that pinwheel density scales with body and brain size. Our data, spanning a 40-fold range of body sizes in Laurasiatheria and Euarchonta, do not support this conclusion. The noncolumnar layout in Glires also appears size-insensitive. Thus, body and brain size may be understood as a constraint on the evolution of visual cortical circuitry, but not as a determining factor."],["dc.identifier.doi","10.1126/science.1206416"],["dc.identifier.gro","3151851"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8680"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0036-8075"],["dc.title","Response to Comment on \"Universality in the Evolution of Orientation Columns in the Visual Cortex\""],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","346"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Society of Neuroscience Abstracts"],["dc.bibliographiccitation.volume","32"],["dc.contributor.author","Schnabel, Michael"],["dc.contributor.author","Kaschube, Matthias"],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2017-11-21T14:00:59Z"],["dc.date.available","2017-11-21T14:00:59Z"],["dc.date.issued","2007"],["dc.description.abstract","It has been proposed that the dynamical stability of topological defects in the visual cortex reflects the Euclidean symmetry of the visual world. We analyze defect stability and pattern selection in a generalized Swift-Hohenberg model of visual cortical development symmetric under the Euclidean group E(2). Euclidean symmetry strongly influences the geometry and multistability of model solutions but does not directly impact on defect stability."],["dc.identifier.arxiv","0801.3832v2"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/10153"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.title","Pinwheel stability, pattern selection and the geometry of visual space"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","488"],["dc.bibliographiccitation.journal","European Journal of Neuroscience"],["dc.contributor.author","Kaschube, Matthias"],["dc.contributor.author","Wolf, Fred"],["dc.contributor.author","Geisel, Theo"],["dc.date.accessioned","2017-11-22T10:07:59Z"],["dc.date.available","2017-11-22T10:07:59Z"],["dc.date.issued","2000"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/10187"],["dc.language.iso","en"],["dc.notes.status","new -primates"],["dc.title","Cortical architectures for peripheral and central vision"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]