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amir.azizi@rub.de (+49) 234-32-27987

Dr. Amir Hossein Azizi

Computational Neuroscience

Computational Neuroscience

amir.azizi@rub.de

(+49) 234-32-27987

RESEARCH

As a PostDoc researcher, I focus on the learning mechanisms that leads to enhanced replay sequential activity of an exploration and intrinsic factors determining the actual place field sizes in the hippocampus.

 

BACKGROUND

I completed my M.Sc. degree in Physics at the IASBS (Institute for Advanced Studies in Basic Sciences). My thesis research was mainly focused on visual memory representation in the primate visual system. As a PhD student in the Ruhr-university Bochum (RUB), I studied the network structures capable of generating intrinsic sequential activities in the hippocapus, and the robustness of the transformation from grid cells to place cells.

    2023

  • Working memory performance is tied to stimulus complexity
    Pusch, R., Packheiser, J., Azizi, A. H., Sevincik, C. S., Rose, J., Cheng, S., et al.
    Communications Biology, 6(1)
    Working memory performance is tied to stimulus complexity

    • 2019

  • Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia)
    Azizi, A. H., Pusch, R., Koenen, C., Klatt, S., Bröcker, F., Thiele, S., et al.
    Behavioural Brain Research, 356, 423–434
  • A Hippocampus Model for Online One-Shot Storage of Pattern Sequences
    Melchior, J., Bayati, M., Azizi, A., Cheng, S., & Wiskott, L.
    CoRR e-print arXiv:1905.12937

    • 2017

  • From grid cells to place cells with realistic field sizes
    Neher, T., Azizi, A. H., & Cheng, S.
    PLoS ONE, 12(7), e0181618

    • 2014

  • The transformation from grid cells to place cells is robust to noise in the grid pattern
    Azizi, A. H., Schieferstein, N., & Cheng, S.
    Hippocampus, 24(8), 912–919

    • 2013

  • A computational model for preplay in the hippocampus
    Azizi, A. H., Wiskott, L., & Cheng, S.
    Frontiers in Computational Neuroscience, 7, 161

    • 2011

  • Reactivation, Replay, and Preplay: How It Might All Fit Together
    Buhry, L., Azizi, A. H., & Cheng, S.
    Neural Plasticity, 2011, 1–11

Winter Term 2017/2018

SeminarsThe Neural Basis of Vision

Summer Term 2017

LecturesDynamical Systems in Neuroscience

    2019

  • Driving network oscillations in ING and PING models with realistic spiking inputs
    Sowade, J.
    Master’s thesis, Applied Informatics, Univ. of Bochum, Germany

    • 2016

  • Propagation of sequential activity in feedforward neural networks
    Hakobyan, O.
    Master’s thesis, Cognitive Science, Univ. of Bochum, Germany
  • Uncovering the representation of visual categories in neural ensembles
    Klatt, S.
    Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany
  • Modeling the effect of depression on mortality.
    Ogiermann, D.
    Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany

About the INI

The Institut für Neuroinformatik (INI) is a research unit of the Faculty of Computer Science at the Ruhr-Universität Bochum. Its scientific goal is to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory and 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 psychology and neurophysiology as well as machine learning, neural artificial intelligence, computer vision, and robotics.

Contact

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

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210

sekretariat@ini.rub.de
www.ini.rub.de