Prof. Dr. Dr. h.c. mult. Wolf Singer
The working hypothesis of the Singer Lab was that the processing mechanisms in the cerebral cortex utilize the high-dimensional dynamics that arise in recurrent networks whose nodes have the properties of damped harmonic oscillators.
Years ago, researchers discovered that feature-specific neurons in the visual cortex synchronize their responses when these features belong to the same visual object. This mechanism is discussed as a possible solution to the “binding problem” and for the formation of Hebbian assemblies.
This synchronization is often accompanied by oscillations in the gamma frequency range, raising the question of whether the observed oscillations have functional meaning or are merely an epiphenomenon of complex interactions in recurrent networks.
This question is difficult to answer in neurophysiological experiments because it is almost impossible to manipulate the oscillations in a targeted manner without also changing other variables of the system dynamics. Therefore, researchers at the Singer Lab at ESI conducted simulation experiments that allowed them to control the oscillations in a targeted manner. To do this, they programmed a simulation of a recurrent network and configured the nodes as damped harmonic oscillators.
By varying the damping factor, they were able to configure the nodes to function either as conventional integrators (leaky integrators) or as damped oscillators. To quantify the performance of the networks, the scientists trained them to recognize handwritten letters and spoken words.
It was found that the networks performed significantly better at recognition when the nodes were enabled to oscillate. The learning speed and resilience of the networks to disturbances increased dramatically compared to non-oscillating networks. The implementation of additional properties of the cerebral cortex (heterogeneous oscillation frequencies, varying conduction speeds of the recurrent connections, and modularity of the connection architecture) led to further increases in the performance of the networks without increasing the number of parameters to be specified. In addition, the oscillating networks reproduced a variety of structural and functional features of the cerebral cortex.
This suggested that the information processing processes based on oscillations are also realized in the cerebral cortex and that the oscillations should not be considered an epiphenomenon.
Much of the current work at the Singer Lab at ESI aimed to understand the computational operations that make oscillating recurrent networks so unusually efficient.
The researchers investigated this question with extensive simulation experiments. They focused on three objectives:
Prof. Dr. Martin Vinck
The Vinck Lab’s research focused on three approaches: circuits, collectives, and learning. The lab’s work was supported by the ERC and BMF.
Circuits: The researchers investigated how different types of excitatory and inhibitory neurons regulate brain plasticity and how they contribute to flexible information processing.
Collectives: The lab investigated how collectives of neurons encode information through spatiotemporal activity patterns and, in particular, what role spike sequences and bursts play in this process. In addition, the researchers were interested in the relationship between spontaneous neural activity (e.g., during dreaming) and neural activity triggered by sensory perceptions (hearing, seeing, etc.).
Learning: The scientists investigated how the brain learns based on predictions about the immediate future, how the brain recognizes objects based on their properties, and what role recurrent networks play in this process. To answer these questions, the researchers used a wide range of methods and approaches, such as machine learning, to model predictable relationships between sensory input across space and time. The lab developed algorithms to enable unsupervised clustering in multidimensional neural data and new methods for evaluating electrophysiological data. In their work, the researchers applied information theory and neural network theory. The scientists collected the data for the models using electrophysiological recordings across all cortical layers and from several brain sections simultaneously. Using optogenetic methods, they identified subtypes of cells, such as interneurons with specific projection patterns.
Prof. Dr. David Poeppel
The overall goal of the research program was to develop a theoretically motivated, computationally explicit, and biologically realistic perspective on auditory cognition (including music), speech perception, and language comprehension. The work proceeded on three fronts:
(i) basic physiological properties of human cortex (non-invasive studies of neural encoding);
(ii) hearing and speech perception (psychophysical and neurobiological approaches); and
(iii) neurobiological foundations of language.
These three areas of inquiry are closely related, although not all of the work was necessarily of an interdisciplinary nature. The lab used all available cognitive neuroscience tools. The main methods employed included electrophysiological recordings using magnetoencephalography (MEG), electroencephalography (EEG), and electrocorticography (ECoG), as well as imaging studies using structural and functional magnetic resonance imaging (MRI).
Prof. Dr. Pascal Fries
Networks of neurons typically engage in rhythmic, synchronized activity. Neuronal synchronization likely affects neuronal processing. If so, evolution has probably selected functional synchronization and mechanisms for its adaptive modulation. The Lab studied neuronal synchronization’s mechanisms, its consequences and its cognitive functions.
Prof. Dr. Ilka Diester
The Lab investigated the interaction between brain areas involved in tactile perception (somatosensory input), cognitive processing, and movement generation (motor output) in order to understand basic principles of the brain and ultimately to advance the design of neural prostheses. The Group addressed these research goals with behavioral tests and electrophysiological and optogenetic tools in the mammalian brain.
Dr. Michael C. Schmid
Work in the Schmid lab was centered on investigating the fundamental brain principles that lead to visual perception. The researchers were particularly interested in understanding how visibility arises from the communication of neurons in different brain areas, how processes that occur during attention might support it and how it is affected after neural injury. Their aim was to describe these functions with a specific focus on the thalamus, one of the brain’s major relay systems. To delineate the dynamics by which thalamus and cortex interact with each other they combined parallel electrophysiological recording methods in the mammalian brain with complementary techniques ranging from psychophysics and fMRI to pharmacology and optogenetics.
