Philipp Rudiger PhD

Philipp Rudiger


Research Interests

My primary research interest is the manner by which the neocortex can construct a useful model of the world from the noisy chaos it is constantly bombarded with by the sensory pathways. Using computational models I hope to replicate the complex interaction of feedforward, recurrent lateral and feedback connections in the primary visual cortex to achieve a better understanding of how the brain selects salient objects from their background or from other distracting stimuli and how this can facilitate how our brain learns about the world.

Publications:
2014
  Relationship between natural image statistics and lateral connectivity in the primary visual cortex
Rudiger, P, Stevens, J-L, Talluri, B & Bednar, JA 2014, 'Relationship between natural image statistics and lateral connectivity in the primary visual cortex' Computational and Systems Neuroscience (Cosyne) 2014, Salt Lake City, United States, 27/02/14 - 2/03/14, pp. 148-149.
The distribution of orientation-selective cells in the primary visual cortex has been found to reflect the first-order statistics of visual inputs, i.e. which orientations are most common during a critical period [1]. Similarly, some properties of the lateral connections between these cells have been found to reflect the second-order statistics of images, i.e. the coocurrence statistics of oriented edge elements, but the results have differed by species. Specifically, horizontal connections have been found to be elongated along the axis of preferred orientation in tree shrew [2] and owl monkey [3], but not in macaque [4]. It is unclear whether these results indicate genuine species differences, or perhaps differences in the visual environments in which these animals were raised. Here we analyse the effect of input statistics on lateral excitatory connectivity in a developmental model of primary visual cortex, by relating differences in co-occurence statistics of distinct image datasets, analysed using methods presented in [5], to corresponding differences in the emergent long-range lateral structure. The goal is to propose a testable series of mechanisms linking visual inputs, to cortical structure, and then to predicted behavioral results on tests of surround modulation. The model, based on earlier variations of a self-organizing map model, develops robust yet adaptive orientation maps [6], long-range lateral connectivity, and a wide range of contextual modulatory effects in a spatially calibrated circuit of macaque V1 [7]. By training the model using images with previously characterized second-order statistics, we demonstrate that the co-occurence of oriented edges is encoded within the horizontal connectivity of our model. On that basis we predict patterns of lateral connectivity for animas reared in different environments, which can be tested by in future experiments.
[1] Shigeru Tanaka, Jerome Ribot, Kazuyuki Imamura, and Toshiki Tani. Orientation-restricted continuous visual exposure induces marked reorganization of orientation maps in early life. NeuroImage, 30(2):462?77, April 2006.
[2] W H Bosking, Y Zhang, B Schofield, and D Fitzpatrick. Orientation selectivity and the arrangement of horizontal connections in tree shrew striate cortex. The Journal of Neuroscience, 17(6):2112?27, March 1997.
[3] L C Sincich and G G Blasdel. Oriented axon projections in primary visual cortex of the monkey. The Journal of Neuroscience, 21(12):4416?26, June 2001.
[4] Alessandra Angelucci, Jonathan B Levitt, Emma J S Walton, Jean-Michel Hupe, Jean Bullier, and Jennifer S Lund. Circuits for local and global signal integration in primary visual cortex. The Journal of Neuroscience, 22(19):8633?46, October 2002.
[5] Laurent Perrinet and James A. Bednar. Edge co-occurrences are sufficient to categorize natural versus animal images. Submitted.
[6] Jean-luc R Stevens, Judith S Law, Jan Antolik, and James A Bednar. Mechanisms for stable, robust,and adaptive development of orientation maps in the primary visual cortex. Journal of Neuroscience,33(40):15747?15766, 2013.
[7] Philipp Rudiger and James A. Bednar. Unifying anatomical, psychophysical and developmental circuit models of primary visual cortex. In Society for Neuroscience, page Program No. 639.11/EE10, 2013.
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Rudiger, Philipp, Stevens, Jean-Luc, Talluri, Bharath & Bednar, James A..
Number of pages: 1
Publication Date: 2014
Publication Information
Category: Poster
Original Language: English
  Relating the diversity of interneuronal subtypes to their functional roles in development, homeostasis and sensory processing
Rudiger, P & Bednar, J 2014, 'Relating the diversity of interneuronal subtypes to their functional roles in development, homeostasis and sensory processing' 44th Society for Neuroscience Annual Meeting, Washington, DC, United States, 15/11/14 - 19/11/14, .
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Rudiger, Philipp & Bednar, James.
Publication Date: 2014
Publication Information
Category: Poster
Original Language: English
2013
  Developing orientation maps using realistic patterns of lateral connectivity
Rudiger, P, Law, J, Antolik, J & Bednar, J 2013, 'Developing orientation maps using realistic patterns of lateral connectivity' 22nd Annual Computational Neuroscience Meeting: CNS 2013, Paris, France, 13/07/13 - 18/07/13, .
While developmental models have been very successful in replicating the main features of experimentally observed topographic maps in the primary visual cortex (V1), they have relied on several unrealistic assumptions. These models are typically variants of the self-organizing
map model [1], and almost universally assume “Mexicanhat” lateral connectivity in V1, with short-range excitatory and longer-range inhibitory connections. Experimental data is in direct conflict with this assumption, with anatomical tracing studies showing that neurons making long-range connections are excitatory [2,3]. A variety of
electrophysiological and psychophysical studies also suggest both excitatory and inhibitory effects at long ranges, depending on experimental conditions. The current consensus is that the actual pattern of connectivity consists of long-range excitation leading to di-synaptic inhibition via local inhibitory interneurons [2-4]. The
resulting aggregate circuit has an overall inhibitory effect when the excitatory drive to local inhibitory synapses is large enough. In principle, the behavior of this circuit at high input contrasts may therefore mimic the Mexican-hat profile of these earlier model, while potentially exhibiting more realistic contrast dependent behavior.

We present a rate-based model of simple-cell development that robustly self-organizes into biologically realistic orientation maps on the basis of this experimentally determined connectivity. The model is built using the Topographica simulator [5], and consists of a number of sheets of units representing the retinal photoreceptors, RGC/LGN
cells, and individual populations of excitatory and inhibitory V1 neurons. The receptive field weights, initialized randomly within a Gaussian envelope, are adjusted through Hebbian learning with divisive normalization in response to activity driven by 20,000 consecutive input
patterns (either natural images or artificial patterns). We show that development of realistic maps is robust, primarily due to homeostaticmechanisms in V1 and divisive contrast-gain control in the RGC/LGNlayer.

The model demonstrates that the experimentally established connectivity framework can lead to orderly map development and can replicate many of the contextual and contrast dependent effects observed in adult V1. This work looks at how Mexican-hat connectivity arises from the overall network interactions at high contrast and how
it adjusts at lower contrasts. Further, it demonstrates clearly how patchy long-range connectivity between isoorientation domains emerges, and the role it plays in modulating V1 activity. In doing so, the model provides a clear link between topographic map formation, the development of the underlying connectivity, and the perceptual consequences of this circuitry, including contrast-dependent
size-tuning shifts and the early stages of more complex effects like pop-out and contour completion.

In future, this work will help us to complete our understanding of the V1 circuit by adding feedback mechanisms or selectively modulating specific connections to model the effects of different neuromodulators. Additionally, the results may be used to provide realistic connectivity patterns for large scale spiking models, which often struggle to adequately constrain their connectivity. Overall, this model demonstrates for the first time that it is possible to robustly develop biologically plausible orientation maps on the basis of realistic connectivity, accounting for various surround modulation effects and providing a solid basis for future models of V1.

References

[1] Von der Malsburg, C.: Self-organization of orientation sensitive cells in the striate cortex. Kybernetik 1973, 14(2): 85–100

[2] Gilbert, D., & Wiesel, T.: Columnar specificity of intrinsic horizontal and corticocortical connections in cat visual cortex. The Journal of Neuroscience 1989, 9(7): 2432–2442.

[3] Hirsch, J. A, & Gilbert, C. D.: Synaptic physiology of horizontal connections in the cat’s visual cortex. The Journal of Neuroscience 1991, 11(6): 1800–9

[4] Weliky, M., Kandler, K., Fitzpatrick, D., & Katz, L. C. : Patterns of excitation and inhibition evoked by horizontal connections in visual cortex share a common relationship to orientation columns. Neuron 1995, 15(3): 541–52

[5] The Topographica Neural Map Simulator. [http://www.topographica.org]
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Rudiger, Philipp, Law, Judith, Antolik, Jan & Bednar, James.
Publication Date: 2013
Publication Information
Category: Poster
Original Language: English
  Unifying anatomical, psychophysical, and developmental circuit models of primary visual cortex
Rudiger, P & Bednar, JA 2013, 'Unifying anatomical, psychophysical, and developmental circuit models of primary visual cortex' Society for Neuroscience Annual Meeting 2013, San Diego, United States, 9/11/13 - 13/11/13, .
Different cortical connectivity patterns have been used to explain the development and function of the primary visual cortex across varying time scales and stimulus protocols. Modellers looking at the long-term development of the cortex have generally assumed Mexican-Hat lateral interactions. Similarly, psychophysical studies of surround modulation have primarily focused on long-range inhibition, leading to the term "surround suppression". Yet the actual anatomical substrate for long-range interaction appears to mediated by excitatory connections [1]. Electrophysiologists have long known that V1 neuron responses differ markedly depending on contrast and distance of the stimuli [1] and some modeling work has suggested differences in the excitatory and inhibitory populations as the cause. Here we propose a model that explains how each of these sources of evidence is compatible with a single underlying circuit, which effectively reduces to Mexican-Hat connectivity for high-contrast inputs. The model is based on two anatomically and functionally distinct inhibitory populations: the wide-arbor perisomatically targeting and Parvalbumin-immunoreactive (Pv-ir) basket cells with weakly tuned, low-latency suppression [2,3], and the smaller, high-latency and strongly tuned somatostatin-expressing (Som-ir) inhibitory interneurons, which could provide long-range orientation-specific inhibition through polysynaptic circuits [4]. This anatomically grounded V1 circuit and the resulting model is the first to demonstrate how the observed connectivity patterns can emerge, and analyzes their role in mediating surround facilitation and suppression. Through manipulation of individual neural populations, as in recent experiments by Nienborg et al. [5], we predict that the PV-ir and Som-ir populations are intricately involved in mediating the contrast response and surround modulatory effects exhibited by neurons in V1 across species.
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Rudiger, Philipp & Bednar, James A..
Publication Date: 2013
Publication Information
Category: Poster
Original Language: English
2012
  A spatio-temporally calibrated model of feature map development and neuronal activity in primate V1
Rudiger, P, Stevens, J-L & Bednar, J 2012, 'A spatio-temporally calibrated model of feature map development and neuronal activity in primate V1' Society for Neuroscience Annual Meeting 2012, New Orleans, 13/10/12 - 17/10/12, .
Detailed spiking models of the primary visual cortex (V1) in mammals use experimentally derived patterns of connectivity from adult animals, failing to explain how this connectivity develops or how it relates to function. In contrast, developmental models explore how connectivity arises as receptive fields and feature maps organize [1]. A unifying model would retain the parsimony of the developmental approach, while still accounting for the spatial and temporal characteristics of experimentally recorded activity.
Here we present the Spatio-Temporally CALibrated (S-TCAL) rate-based model of feature map development and cortical activity at parafoveal eccentricity of 4-5° in macaque. This model is a variant on GCAL [2] with spatially calibrated connectivity and temporal activity profiles in the lateral geniculate nucleus (LGN) and V1. The aim is to determine whether dynamics of V1 activity can be explained with a rate based model, using connectivity organised through visual experience without simulating spiking potentials.

[1] Geofrrey J. Goodhill. Contributions of Theoretical Modeling to the Understanding of Neural Map Development. Neuron Review 56:301-310, 2007.
[2] James A. Bednar. Building a mechanistic model of the development and function of the primary visual cortex. Journal of Physiology (Paris), 2012. In press.
General Information
Organisations: Institute for Adaptive and Neural Computation .
Authors: Rudiger, Philipp, Stevens, Jean-Luc & Bednar, James.
Publication Date: 2012
Publication Information
Category: Poster
Original Language: English

Projects:
Modelling the effects of attentional feedback signals on response properties, contextual integration, and learning in the primary visual cortex (PhD)