Sensory and motor coding in the organization of behavior

A central question in Neuroscience is how information is encoded in the nervous system. While neurons communicate with each other using spikes, i.e. discrete singular events in time, it is unclear whether information is effectively encoded in the average firing rates or the precise timing of single spikes. Similarly, it is not known in what context a population of neurons usees cooperative or independent coding. This thesis tries to elaborate a new view on these issues by proposing a new type of coding which features both, coding in the temporal domain as well as cooperative coding across neurons, the temporal population code. While the assessment of any coding strategy is strongly dependent on its range of applications, the uniformity of cortical anatomy suggests affinities between the coding of information of different modalities in cortical structures. Therefore, this thesis will be focused on applying the proposed coding scheme to real-world situations and in particular incorporating different modalities such as vision, motor and higher order representations. In the first part of this thesis, a new approach towards invariant pattern recognition will be presented, the temporal population code. The key ingredient to the model presented is the coding of information in the temporal domain. Visual stimuli become encoded by a cortical network of laterally coupled integrate-and-fire neurons due to a direct relation between the transduction speed and the distance a signal has to travel between neurons. This representation of a stimulus is positionand rotation invariant while retaining class specificity in order to allow for their classification. The code is robust with respect to synaptic noise and can be generated quickly. Additionally, incorporating orientation and spatial frequency selective neurons allows to represent and reliably classify large stimulus sets of increased complexity. In this context, the temporal population code is successfully applied to the classification of the MNIST database, a benchmark database for pattern recognition systems containing handwritten digits from 250 different writers. Using large synthetically generated stimulus sets, it is shown that the concept of the temporal population code favorably scales to hundreds of stimulus classes. In order to show that this coding strategy generalizes to other modalities, a model of sensori-motor integration is introduced in the second part of this thesis. While the traditional view on the control of behavior considers a sequence of sensory processing, decision making and movement control, recent experimental studies suggest that the motor system is most likely more than only being responsible for motor execution. Building on these ideas it is shown, that the population response of the motor system provides a substrate for the categorization of behavioral situations. The model lends credence to the emerging reconceptualization of behavioral control. In this context, the motor system can be considered as part of a high-level perceptual system which allows for the detection of behaviorally salient situations invariant to their detailed sensory manifestation. After successful application to the direct encoding of information in sensory as well as motor systems, the question arises, what properties of the proposed coding scheme could be of particular interest for higher order representations. In the last part of this thesis, a new model for the formation of place cells as found in rat hippocampus will be presented, which exploits the topology preserving properties of the temporal population code. Due to the relatively broad tuning of these place cells, only a relatively small number is required for accurate position reconstruction. Thus, for a behaving organism exploring an unknown environment, this implies that a relatively sparse exploration strategy suffices to create a complete representation of the new environment. In summary, the new coding scheme considered has proven to be applicable to different modalities while providing interesting invariance properties for the formation of higher level representations of the world.