Quantifizierung und Analyse dynamischer sensorischer Information: vom Verhalten zur Verarbeitung des sensorischen Flusses im elektrosensorischen System.
Biologie des Verhaltens und der Sinne
Zusammenfassung der Projektergebnisse
Active sensing in its most common form involves the generation of movements. Whether and how these are controlled with respect to their sensory corollaries is mostly unknown. A way in which animals can control or select the sensory information they obtain depends on context-specific modulations of their behavior that change their sensory input. When this done purposively it is considered as an active sensing strategy. This project focused on weakly electric fish as an example for active sensory systems, as they offer several advantages when studying active sensing strategies. Starting at the behavioral level we investigated the sensory consequences of varying active sensing strategies in weakly electric fish. We show that decomposing complex behavior into kinematic units and analyzing reoccurring concatenations of these units is a suitable approach to identify behavioral building blocks. By combining this approach with the ability to computationally reconstruct the electrosensory input we could show that the stereotyped approach behavior of G. petersii results in a novel dynamic distance cue (relative gradient). The physical and behavioral similarities between electrolocation and other active sensory systems suggest that this may be a mechanism shared by (active) sensory systems. To test if dynamic sensory information (i.e., electrosensory flow) is also actively used by fish we turned to a well-established behavioral paradigm where fish aim to remain centered in a shelter, even when this moves. By varying the relative speed between the two shelter walls, we found that weakly electric fish both the Gymnotiform and Mormyrid family station within the shelter by moving closer towards the slower moving side. In addition to the field calculations and measurements that indicated that the nonlinear properties of the electric field should result in parallax-like depth cues, these behavioral data suggest that electric parallax (a cue dependent on relative movements) is actively used by weakly electric fish. This this is the first demonstration showing that context-dependent electromotor behavior can be actively used by weakly electric fish to shape the sensory input. Extending on this data, we finally turned to non-spontaneous behaviors, investigating how electromotor behavior changes with learning. To analyze this we extended the analysis to incorporate an information theoretic analysis of the sensory flow, finding that existing kinematic units are restructured to optimize the information extractable form the environment. In this part of the study we also addressed how neurons in the first central processing stage, the electrosensory lateral line lobe, respond to the objects previously used in the behavioral experiments. Based on single unit recordings we found a surprisingly poor detection range, substantially below the behaviorally documented limits. Future studies extending on these preliminary physiological results are required to address neuronal coding under natural electromotor conditions.
Projektbezogene Publikationen (Auswahl)
- Motor patterns during active electrosensory acquisition, Frontiers in Behav. Neuroscience, 8
Hofmann V, Guerten B, Sanguinetti-Scheck J, Gomez-Senna and Engelmann J
(Siehe online unter https://doi.org/10.3389/fnbeh.2014.00186) - Sensory flow as a basis for a novel distance cue in freely behaving electric fish. J. Neuroscience (2017);37(2):302-312
Hofmann V, Sanguinetti-Scheck J, Gómez-Sena L and Engelmann J
(Siehe online unter https://doi.org/10.1523/JNEUROSCI.1361-16.2016) - Motion parallax in electric sensing. PNAS 2018, 115 (3) 573-577
Pedraja F, Hofmann V, Lucas K.M., Young C, Engelmann J und Lewis J E
(Siehe online unter https://doi.org/10.1073/pnas.1712380115) - Task-Related Sensorimotor Adjustments Increase the Sensory Range in Electrolocation. J Neurosci. 2020;40(5):1097-1109
Pedraja F, Hofmann V, Goulet J, Engelmann J
(Siehe online unter https://doi.org/10.1523/JNEUROSCI.1024-19.2019)
