Models of sensory representations and episodic memory Computational Neuroscience

Description

During the processing of sensory information, a higher order representation is generated. For an example, consider the hierarchical processing in the visual system (Felleman & Van Essen, 1991). The higher-level visual areas directly project to medial temporal lobe (MTL) structures, which are well-known to be crucial for episodic memory (Squire & Zola, 1998). We have previously suggested that episodic memory stores only the gist of scenes and their temporal evolution by means of sequences of sensory representations (Cheng, 2013). Furthermore, there is evidence for coordinated replay of neuronal sequences in the MTL and the visual cortex (Ji & Wilson, 2007). Thus, there is an interaction between episodic memory in the MTL and sensory representations in neocortex. A growing body of studies indicates that the MTL may not only be crucial for memory but also play a critical role in high-level perception (Lech & Suchan, 2013). Patients with MTL lesions have been shown to be impaired in certain visual discrimination tasks (Lee et al., 2005).

Using computational modeling approaches we investigate the nature of the sensory representations and how they can be tuned with episodic memory. Our models demonstrate that the impairment of MTL patients in discrimination tasks may be due to the limited availability of episodic memory for improving the sensory representations that are required for visual discrimination. We use algorithmic models, deep learning, and network models. We regularly have Bachelor or Master projects to offer along those lines. Usually knowledge of Python or Matlab is required.

References

Cheng, S. (2013). The CRISP theory of hippocampal function in episodic memory. Frontiers in Neural Circuits, 7(May), 88. https://doi.org/10.3389/fncir.2013.00088

Felleman, D. J., & Van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex (New York, N.Y.: 1991), 1(1), 1–47.

Ji, D., & Wilson, M. A. (2007). Coordinated memory replay in the visual cortex and hippocampus during sleep. Nature Neuroscience, 10(1), 100–107. https://doi.org/10.1038/nn1825

Lech, R. K., & Suchan, B. (2013). The medial temporal lobe: Memory and beyond. Behavioural Brain Research, 254, 45–49. https://doi.org/10.1016/j.bbr.2013.06.009

Lee, A. C. H., Fischer, T. J., Murray, E. A., Saksida, L. M., Epstein, R. A., Kapur, N., … Graham, K. S. (2005). Perceptual deficits in amnesia: challenging the medial temporal lobe “mnemonic” view. Neuropsychologia, 43(1), 1–11. https://doi.org/10.1016/j.neuropsychologia.2004.07.017

Squire, L. R., & Zola, S. M. (1998). Episodic memory, semantic memory, and amnesia. Hippocampus, 8(3), 205–211. https://doi.org/10.1002/(SICI)1098-1063(1998)8:3<205::AID-HIPO3>3.0.CO;2-I

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

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