Biomedical subjects
Publications and source records attributed to D Jancke.
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There exist a large number of visual illusions indicating that perception differs from pure representation of physical input. For example, a spot of light can be characterized by its position, but it does not contribute any information about orientation. However, when moved fast enough, a continuous streak along its trajectory is perceived that helps to determine the orientation of the movement path. The question arises whether the processing of the trajectory and its orientation are simultaneously represented in the primary visual cortex. Here I show that decoding neural population activity within a two-dimensional parameter space represents both (1) physical input given by the actual position of the moving spot and (2) orientation. This latter parameter has no physical counterpart in the stimulus but must be actively formed by spatiotemporal integration of the spot's trajectory.
In many cortical areas, simple stimuli or task conditions activate large populations of neurons. We hypothesize that such populations support processes of interaction within parametric representations and integration of multiple sources of input and we propose to study these processes using distributions of population activation (DPAs) as a tool. Such distributions can be viewed as neuronal representations of continuous stimulus or task parameters. They are built from basis functions contributed by each neuron. These functions may be explicitly chosen based on tuning curves or receptive field profiles. Or they may be determined by minimizing the distance between chosen target distributions and the constructed DPAs. In both cases, construction of the DPA is based on a set of reference conditions in which the stimulus or task parameters are sampled experimentally. In a second step, basis functions are kept fixed, and the DPAs are used to explore time dependent processing, interaction and integration of information. For instance, stimuli which simultaneously specify multiple parameter values can be used to study interactions within the parametric representation. We review an experiment, in which the representation of retinal position is probed in this way, revealing fast excitatory interactions among neurons representing similar retinal positions and slower inhibitory interactions among neurons representing dissimilar retinal positions. Similarly, DPAs can be used to analyze different sources of input that are fused within a parametric representation. We review an experiment in which the representation of the direction of goal-directed arm movements in motor and premotor cortex is studied when prior and current information about upcoming movement tasks are integrated.
Neuronal interactions are an intricate part of cortical information processing generating internal representations of the environment beyond simple one-to-one mappings of the input parameter space. Here we examined functional ranges of interaction processes within ensembles of neurons in cat primary visual cortex. Seven "elementary" stimuli consisting of small squares of light were presented at contiguous horizontal positions. The population representation of these stimuli was compared to the representation of "composite" stimuli, consisting of two squares of light at varied separations. Based on receptive field measurements and by application of an Optimal Linear Estimator, the representation of retinal location was constructed as a distribution of population activation (DPA) in visual space. The spatiotemporal pattern of the DPA was investigated by obtaining the activity of each neuron for a sequence of time intervals. We found that the DPA of composite stimuli deviates from the superposition of its components because of distance-dependent (1) early excitation and (2) late inhibition. (3) The shape of the DPA of composite stimuli revealed a distance-dependent repulsion effect. We simulated these findings within the framework of dynamic neural fields. In the model, the feedforward response of neurons is modulated by spatial ranges of excitatory and inhibitory interactions within the population. A single set of model parameters was sufficient to describe the main experimental effects. Combined, our results indicate that the spatiotemporal processing of visual stimuli is characterized by a delicate, mutual interplay between stimulus-dependent and interaction-based strategies contributing to the formation of widespread cortical activation patterns.