Transitions between stochastic and oscillatory active sensing in pulse-type electric fish

Rather than wait passively for signals to be detected by their sensors, animals actively move in order to gather information from their environment. Furthermore, when sensing is performed by means of rhythmic movements, reafferent sensory streams are also rhythmic, which is advantageous for sensory processing. Here, we report on and characterize an hitherto unknown behavioural state of pulse-type weakly electric fish during which electrosensory acquisition becomes rhythmic and is coupled to low-frequency movement. The oscillatory nature of this sensory sampling strategy is in stark contrast to that exhibited during other behavioural states, which we show to be well-modelled by jump-diffusion stochastic processes.

To characterize the oscillatory dynamics of these rhythmic behavioural states, we identify and extract them from long-term observations of freely-moving fish. To achieve this, we apply a wavelet transform to the inter-pulse interval time series and use the resulting spectra as input for t-distributed Stochastic Neighbor Embedding. This creates a 2D clustered representation of the data from which we successfully classify different sensory acquisition strategies. This approach reveals that rhythmic sampling in fact occurs over a range of frequencies between 0.5 and 1 Hz.