Motor-maps, navigation and implicit space representation in the hippocampus.

Multiple sensory-motor maps located in the brainstem and the cortex are involved in spatial orientation. Guiding movements of eyes, head, neck and arms they provide an approximately linear relation between target distance and motor response. This involves especially the superior colliculus in the brainstem and the parietal cortex. There, the natural frame of reference follows from the retinal representation of the environment. A model of navigation is presented that is based on the modulation of activity in those sensory-motor maps. The actual mechanism chosen was gain-field modulation, a process of multimodal integration that has been demonstrated in the parietal cortex and superior colliculus, and was implemented as attraction to visual cues (colour). Dependent on the metric of the sensory-motor map, the relative attraction to these cues implemented as gain field modulation and their position define a fixed point attractor on the plane for locomotive behaviour. The actual implementation used Kohonen-networks in a variant of reinforcement learning that are well suited to generate such topographically organized sensory-motor maps with roughly linear visuo-motor response characteristics. In the following, it was investigated how such an implicit coding of target positions by gain-field parameters might be represented in the hippocampus formation and under what conditions a direction-invariant space representation can arise from such retinotopic representations of multiple cues. Information about the orientation in the plane--as could be provided by head direction cells--appeared to be necessary for unambiguous space representation in our model in agreement with physiological experiments. With this information, Gauss-shaped "place-cells" could be generated, however, the representation of the spatial environment was repetitive and clustered and single cells were always tuned to the gain-field parameters as well.

Quantifying the species-specificity in genomic signatures, synonymous codon choice, amino acid usage and G+C content.

Each prokaryote has a unique genomic signature as evidenced by a set of species-specific frequencies of short oligonucleotides. With respect to genomic signatures a bacterial genome is homogenous and the variation within a genome is smaller than the variations between genomes of different species. This study quantifies the species-specificity of genomic signatures in the complete genomes of 57 prokaryotes. The species-specificity in the genomic signature was related to the quantification of other sequence biases, such as G+C content, synonymous codon choice and amino acid usage. The results confirm that the genomic signature is genome-wide with high species-specificity in both coding and non-coding regions. In coding regions the species-specific bias in synonymous codon choice was comparable to the genomic signature, while the bias in amino acid usage only captured about 50% of the species-specific bias in the genomic signature. A correlation between the species-specificity in synonymous codon choice and amino acid usage was identified, in which proteins with species-specific amino acid usage were also coded with species-specific synonymous codon choice. However, we demonstrated that the G+C content captures only approximately 40% of the species-specificity in the genomic signature, and is insufficient to explain the species specificity in the non-coding regions. Thus, the species-specific bias in non-coding regions remains largely unknown. Further, we compared the genomic signature in relation to phylogenetic distance. This was performed in order to illustrate the feasibility of a hierarchical classification scheme in future applications of the described classification methodology in screening for horizontal gene transfer and biodiversity studies.

Traveling-wave pattern generator controls movement and organization of sensory feedback in a spinal cord model.

A traveling wave in a two-dimensional spinal cord model constitutes a stable pattern generator for quadruped gaits. In the context of the somatotopic organization of the spinal cord, this pattern generator is sufficient to generate stable locomotive limb trajectories. The elastic properties of muscles alone, providing linear negative feedback, are sufficient to stabilize stance and locomotion in the presence of perturbative forces. We further show that such a pattern generator is capable of organizing sensory processing in the spinal cord. A single-layer perceptron was trained to associate the sensory feedback from the limb (coding force, length, and change of length for each muscle) with the two-dimensional activity profile of the traveling wave. This resulted in a well-defined spatial organization of the connections within the spinal network along a rostrocaudal axis. The spinal network driven by peripheral afferents alone supported autonomous locomotion in the positive feedback mode, whereas in the negative feedback mode stance was stabilized in response to perturbations. Systematic variation of a parameter representing the effect of gamma-motor neurons on muscle spindle activity in our model led to a corresponding shift of limb position during stance and locomotion, resulting in a systematic displacement alteration of foot positions.

Emergence of coherent traveling waves controlling quadruped gaits in a two-dimensional spinal cord model.

The concerted and self-organizing behavior of spinal cord segments in generating locomotor patterns is modulated by afferent sensory information and controlled by descending pathways from the brainstem, cerebellum, or cortex. The purpose of this study was to define a minimal set of parameters that could control a similar self-organizing behavior in a two-dimensional neural network. When we implemented synaptic depression and active membrane repolarization as two properties of the neurons, the two-dimensional neural network generated traveling waves. Their wavelength and angle of propagation could be independently controlled by two parameters that modulated excitatory premotor neurons and inhibitory commissural neurons. It is further demonstrated that the selection of wave parameters corresponds to the selection of quadruped gaits.

Protein names and how to find them.

A prerequisite for all higher level information extraction tasks is the identification of unknown names in text. Today, when large corpora can consist of billions of words, it is of utmost importance to develop accurate techniques for the automatic detection, extraction and categorization of named entities in these corpora. Although named entity recognition might be regarded a solved problem in some domains, it still poses a significant challenge in others. In this work we focus on one of the more difficult tasks, the identification of protein names in text. This task presents several interesting difficulties because of the named entities variant structural characteristics, their sometimes unclear status as names, the lack of common standards and fixed nomenclatures, and the specifics of the texts in the molecular biology domain in which they appear. We describe how we approached these and other difficulties in the implementation of Yapex, a system for the automatic identification of protein names in text. We also evaluate Yapex under four different notions of correctness and compare its performance to that of another publicly available system for protein name recognition.