Computational Neuroscience

Prof. Dr. Andreas Herz

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+49 89 2180 74801

Prof. Dr. Andreas Herz

Room D01.052

Andreas Herz at the Bernstein Center for Computational Neuroscience

Prof. Herz at the GSN

Full CV of Prof. Dr. Andreas Herz (PDF, 56 KB)

Neural dynamics and coding

The brain is one of the most complex biological systems. Understanding its fascinating dynamics and information processing strategies is a major challenge. Our group's focus on nonlinear dynamics, stochastic processes, information theory, and collective phenomena offers a broad spectrum of concepts and techniques for collaborating with experimental laboratories and investigating how the brain solves difficult computational problems. Using various model systems—from the acoustic communication of grasshoppers to the spatial navigation of rodents—we explore questions such as: How do sensory systems integrate information across different time scales to accomplish complex pattern recognition tasks?

How are external signals analyzed in real time, despite the constant influx of new sensory information? How do neural systems cope with the dilemma between “isolation and interaction” that is inherent in any distributed signal processing? We have also developed novel experimental approaches, for example to find the most relevant stimuli for a particular neuron or to decipher its intrinsic processing steps. The results of these investigations can be used to expand our fundamental understanding of “computing” and create new paradigms that transcend the limitations of traditional approaches. This dual role of theoretical neuroscience has led to significant advances in brain research and opens up new connections to theoretical physics, psychology, computer science, and various technical applications.

Current research interests

• Neural basis of spatial navigation
• Interaction of cellular rhythms and large-scale oscillations
• Collective behavior of neural systems
• Mathematical theory of attractor networks

In the past, I have also worked extensively in applied mathematics, statistical physics, game theory, theoretical immunology, and olfactory learning.

Scientific approach

We use methods from dynamic systems theory and probability theory to analyze and model electrophysiological data from various local and international partners and compare them with theoretical predictions.

Publications:

Selected publications:

Csordas DÉ, Fischer C, Nagele J, Stemmler MB, Herz AVM
Spike afterpotentials shape the in vivo burst activity of principal cells in medial entorhinal cortex.
J Neurosci 40, 4512-4524 (2020)

Stemmler MB, Mathis A, Herz AVM
Connecting multiple spatial scales to decode the population activity of grid cells.
Sci Adv 1: e1500816. DOI: 10.1126/science.1500816 (2015)

Herz AVM, Gollisch T, Machens CK, Jaeger D
Modeling single-neuron dynamics and computations: a balance of detail and abstraction.
Science, 314, 80-85 (2006)

Machens CK, Schütze H, Franz A, Kolesnikova O, Stemmler MB, Ronacher B, Herz AVM
Single auditory neurons rapidly discriminate conspecific communication signals.
Nature Neuroscience, 6, 341-342 (2003)

Herz AVM, Bonhoeffer S, Anderson RM, May RM, Nowak MA
Viral dynamics in vivo: Limitations on estimates of intracellular delay and virus decay.
Proc Natl Acad Sci, USA 93, 7247-7251 (1996)

Herz AVM, Hopfield JJ
Earthquake cycles and neural reverberations: Collective oscillations in systems with pulse-coupled threshold elements. Physical Review Letters 75, 1222-1225 (1995)

Full list can be found here:

Media:

Questions & Answers (Current Biology 2018)

"Das Denken ist hartes Brot, verehrte Maschine (PDF, Frankfurter Allgemeine Zeitung 2019) (PDF, 423 KB)

Das Gehirn verstehen - 10 Jahre Bernstein Zentrum München

Computational Neuroscience

Das Bernstein Netzwerk

Alumni: