Florentin Wörgötter

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To extract important information from the environment on a useful timescale, the visual system must be able to adapt rapidly to constantly changing scenes. This requires dynamic control of visual resolution, possibly at the level of the responses of single neurons. Individual cells in the visual cortex respond to light stimuli on particular locations(More)
Plasticity in the brain reaches far beyond a mere changing of synaptic strengths. Recent time-lapse imaging in the living brain reveals ongoing structural plasticity by forming or breaking of synapses, motile spines, and re-routing of axonal branches in the developing and adult brain. Some forms of structural plasticity do not follow Hebbian- or(More)
In this paper, we present our design and experiments on a planar biped robot under the control of a pure sensor-driven controller. This design has some special mechanical features, for example small curved feet allowing rolling action and a properly positioned center of mass, that facilitate fast walking through exploitation of the robot's natural dynamics.(More)
The hippocampus encodes both spatial and nonspatial aspects of a rat's ongoing behavior at the single-cell level. In this study, we examined the encoding of intended destination by hippocampal (CA1) place cells during performance of a serial reversal task on a double Y-maze. On the maze, rats had to make two choices to access one of four possible goal(More)
In this review, we compare methods for temporal sequence learning (TSL) across the disciplines machine-control, classical conditioning, neuronal models for TSL as well as spike-timing-dependent plasticity (STDP). This review introduces the most influential models and focuses on two questions: To what degree are reward-based (e.g., TD learning) and(More)
Spike-timing-dependent plasticity (STDP) is described by long-term potentiation (LTP), when a presynaptic event precedes a postsynaptic event, and by long-term depression (LTD), when the temporal order is reversed. In this article, we present a biophysical model of STDP based on a differential Hebbian learning rule (ISO learning). This rule correlates(More)
1. Visually driven single-unit activity was recorded in the dorsal lateral geniculate nucleus (dLGN) of the anaesthetized cat while inactivating or stimulating the corticofugal feedback from area 17/18 by means of cortical cooling or application of GABA (inactivation), or application of glutamate or quisqualate (Glu, Quis; stimulation) to layer VI. 2.(More)
We investigated how changes in the temporal firing rate of thalamocortical activity affect the spatiotemporal structure of receptive field (RF) subunits in cat primary visual cortex. Spike activity of 67 neurons (48 simple, 19 complex cells) was extracellulary recorded from area 17/18 of anesthetized and paralyzed cats. A total of 107 subfields (on/off)(More)
Unsupervised over-segmentation of an image into regions of perceptually similar pixels, known as superpix-els, is a widely used preprocessing step in segmentation algorithms. Superpixel methods reduce the number of regions that must be considered later by more computation-ally expensive algorithms, with a minimal loss of information. Nevertheless, as some(More)
Recently evidence has accumulated that many neural networks exhibit self-organized criticality. In this state, activity is similar across temporal scales and this is beneficial with respect to information flow. If subcritical, activity can die out, if supercritical epileptiform patterns may occur. Little is known about how developing networks will reach and(More)