Klaus Obermayer

Klaus Obermayer
Technische Universität Berlin | TUB · Department of Software Engineering and Theoretical Computer Science

About

500
Publications
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Publications

Publications (500)
Article
Full-text available
We apply the framework of nonlinear optimal control to a biophysically realistic neural mass model, which consists of two mutually coupled populations of deterministic excitatory and inhibitory neurons. External control signals are realized by time-dependent inputs to both populations. Optimality is defined by two alternative cost functions that tr...
Preprint
Full-text available
It is common practice to reuse models initially trained on different data to increase downstream task performance. Especially in the computer vision domain, ImageNet-pretrained weights have been successfully used for various tasks. In this work, we investigate the impact of transfer learning for segmentation problems, being pixel-wise classificatio...
Preprint
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In transfer learning, only the last part of the networks - the so-called head - is often fine-tuned. Representation similarity analysis shows that the most significant change still occurs in the head even if all weights are updatable. However, recent results from few-shot learning have shown that representation change in the early layers, which are...
Preprint
Full-text available
We provide a new algorithm for solving Risk Sensitive Partially Observable Markov Decisions Processes, when the risk is modeled by a utility function, and both the state space and the space of observations is finite. This algorithm is based on an observation that the change of measure and the subsequent introduction of the information space that is...
Article
Full-text available
Sleep manifests itself by the spontaneous emergence of characteristic oscillatory rhythms, which often time-lock and are implicated in memory formation. Here, we analyze a neural mass model of the thalamocortical loop in which the cortical node can generate slow oscillations (approximately 1 Hz) while its thalamic component can generate fast sleep...
Article
Full-text available
Gamma rhythms play a major role in many different processes in the brain, such as attention, working memory, and sensory processing. While typically considered detrimental, counterintuitively noise can sometimes have beneficial effects on communication and information transfer. Recently, Meng and Riecke showed that synchronization of interacting ne...
Article
Full-text available
During slow-wave sleep, the brain is in a self-organized regime in which slow oscillations (SOs) between up- and down-states travel across the cortex. While an isolated piece of cortex can produce SOs, the brain-wide propagation of these oscillations are thought to be mediated by the long-range axonal connections. We address the mechanism of how SO...
Article
Full-text available
Real-time load information in public transport is of high importance for both passengers and service providers. Neural algorithms have shown a high performance on various object counting tasks and play a continually growing methodological role in developing automated passenger counting systems. However, the publication of public-space video footage...
Preprint
Full-text available
Gamma rhythms play a major role in many different processes in the brain, such as attention, working memory and sensory processing. While typically considered detrimental, counterintuitively noise can sometimes have beneficial effects on communication and information transfer. Recently, Meng and Riecke showed that synchronization of interacting net...
Conference Paper
In this article, we give an interactive introduction to model-agnostic meta-learning (MAML), a well-establish method in the area of meta-learning. Meta-learning is a research field that attempts to equip conventional machine learning architectures with the power to gain meta-knowledge about a range of tasks to solve problems like the one above on a...
Article
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neurolib is a computational framework for whole-brain modeling written in Python. It provides a set of neural mass models that represent the average activity of a brain region on a mesoscopic scale. In a whole-brain network model, brain regions are connected with each other based on biologically informed structural connectivity, i.e., the connectom...
Preprint
Full-text available
Background: Oscillatory rhythms during sleep such as slow oscillations (SO) and spindles, and most importantly their coupling, are thought to underlie processes of memory consolidation. External slow oscillatory transcranial direct current stimulation (so-tDCS) with a frequency of 0.75 Hz has been shown to improve this coupling and memory consolida...
Preprint
Full-text available
Certain neurophysiological characteristics of sleep, in particular slow oscillations (SO), sleep spindles, and their temporal coupling, have been well characterized and associated with human memory formation. Delta waves, which are somewhat higher in frequency and lower in amplitude compared to SO, have only recently been found to play a critical r...
Preprint
Full-text available
Sleep manifests itself by the spontaneous emergence of characteristic oscillatory rhythms, which often time-lock and are implicated in the memory formation. Here, we analyze a neural mass model of the thalamo-cortical loop of which the cortical node can generate slow oscillations (approx. 1 Hz) while its thalamic component can generate sleep spindl...
Presentation
While the prediction of fixation locations on static scenes is an active research area, neither the sequencing of saccades nor dynamic stimuli have received much attention in computational modeling. Here we present a new framework for the simulation of human exploration behavior in dynamic real-world scenes. Saccades are modeled as a sequential dec...
Article
We apply the framework of optimal nonlinear control to steer the dynamics of a whole-brain network of FitzHugh-Nagumo oscillators. Its nodes correspond to the cortical areas of an atlas-based segmentation of the human cerebral cortex, and the internode coupling strengths are derived from diffusion tensor imaging data of the connectome of the human...
Preprint
Full-text available
Visually exploring the world around us is not a passive process. Instead, we actively explore the world and acquire visual information over time. Here, we present a new model for simulating human eye-movement behavior in dynamic real-world scenes. We model this active scene exploration as a sequential decision making process. We adapt the popular d...
Article
Full-text available
Brain–computer interface (BCI) has developed rapidly over the past two decades, mainly due to advancements in machine learning. Subjects must learn to modulate their brain activities to ensure a successful BCI. Feedback training is a practical approach to this learning process; however, the commonly used classifier-dependent approaches have inheren...
Article
Full-text available
The coordinated dynamic interactions of large-scale brain circuits and networks have been associated with cognitive functions and behavior. Recent advances in network neuroscience have suggested that the anatomical organization of such networks puts fundamental constraints on the dynamical landscape of brain activity, i.e., the different states, or...
Article
Full-text available
[This corrects the article DOI: 10.1371/journal.pcbi.1007822.].
Preprint
Full-text available
The coordinated, dynamical interactions of large-scale networks give rise to cognitive function. Recent advances in network neuroscience have suggested that the anatomical organization of such networks puts a fundamental constraint on the dynamical landscape of the brain. Consequently, changes in large-scale brain activity have been hypothesized to...
Preprint
Full-text available
neurolib is a computational framework for whole-brain modeling written in Python. It provides a set of neural mass models that represent the average activity of a brain region on a mesoscopic scale. In a whole-brain network model, brain regions are connected with each other based on biologically informed structural connectivity, i.e. the connectome...
Preprint
Full-text available
We apply the framework of optimal nonlinear control to steer the dynamics of a whole-brain network of FitzHugh-Nagumo oscillators. Its nodes correspond to the cortical areas of an atlas-based segmentation of the human cerebral cortex, and the inter-node coupling strengths are derived from Diffusion Tensor Imaging data of the connectome of the human...
Preprint
Full-text available
During slow-wave sleep, the brain is in a self-organized regime in which slow oscillations (SOs) between up- and down-states propagate across the cortex. We address the mechanism of how SOs emerge and can recruit large parts of the brain using a whole-brain model based on empirical connectivity data. Individual brain areas generate SOs that are ind...
Article
Full-text available
In visual areas of primates, neurons activate in parallel while the animal is engaged in a behavioral task. In this study, we examine the structure of the population code while the animal performs delayed match-to-sample tasks on complex natural images. The macaque monkeys visualized two consecutive stimuli that were either the same or different, w...
Article
Full-text available
Electrical stimulation of neural systems is a key tool for understanding neural dynamics and ultimately for developing clinical treatments. Many applications of electrical stimulation affect large populations of neurons. However, computational models of large networks of spiking neurons are inherently hard to simulate and analyze. We evaluate a red...
Preprint
Full-text available
Primary visual cortex (V1) is absolutely necessary for normal visual processing, but whether V1 encodes upcoming behavioral decisions based on visual information is an unresolved issue, with conflicting evidence. Further, no study so far has been able to predict choice from time-resolved spiking activity in V1. Here, we hypothesized that the choice...
Article
Identification and localization of sounds are both integral parts of computational auditory scene analysis. Although each can be solved separately, the goal of forming coherent auditory objects and achieving a comprehensive spatial scene understanding suggests pursuing a joint solution of the two problems. This article presents an approach that rob...
Poster
Full-text available
We study a mean-field neural mass model of spiking adaptive exponential integrate-and-fire (AdEx) neurons and are interested in the effects of electric fields on the population activity. Our primary research question is: How do time-varying electric field inputs affect endogenous population dynamics of a cortical E-I network?
Article
Full-text available
We propose a new model of the read-out of spike trains that exploits the multivariate structure of responses of neural ensembles. Assuming the point of view of a read-out neuron that receives synaptic inputs from a population of projecting neurons, synaptic inputs are weighted with a heterogeneous set of weights. We propose that synaptic weights re...
Preprint
Full-text available
We propose a new algorithm that uses an auxiliary Neural Network to calculate the transport distance between two data distributions and export an optimal transport map. In the sequel we use the aforementioned map to train Generative Networks. Unlike WGANs, where the Euclidean distance is implicitly used, this new method allows to use any transporta...
Preprint
Full-text available
Electrical stimulation of neural populations is a key tool for understanding neural dynamics and developing treatments. To investigate the effects of external stimulation on a basic cortical motif, we analyse the dynamical properties of an efficient mean-field neural mass model of excitatory and inhibitory adaptive exponential integrate-and-fire (A...
Preprint
Full-text available
In visual areas of primates, neurons activate in parallel while the animal is engaged in a behavioral task. In this study, we examine the structure of the population code while the animal performs delayed match to sample task on complex natural images. The macaque monkeys visualized two consecutive stimuli that were either the same or different, wh...
Preprint
Full-text available
We propose a novel method of the read-out of spike trains that exploits the structure of responses of neural ensembles. Assuming the point of view of a read-out neuron that receives synaptic inputs from a population of projecting neurons, synaptic inputs are weighted with a heterogeneous set of weights. We propose that synaptic weights reflect the...
Article
Full-text available
By using the fact that the space of all probability measures with finite support can be completed in two different fashions, one generating the Arens-Eells space and another generating the Kantorovich-Wasserstein (Wasserstein-1) space, and by exploiting the duality relationship between the Arens-Eells space with the space of Lipschitz functions, we...
Article
Full-text available
Transcranial brain stimulation and evidence of ephaptic coupling have sparked strong interests in understanding the effects of weak electric fields on the dynamics of neuronal populations. While their influence on the subthreshold membrane voltage can be biophysically well explained using spatially extended neuron models, mechanistic analyses of ne...
Data
Subthreshold response properties of ball-and-stick neurons and fitted two-compartment neurons. A: amplitude of subthreshold somatic impedances for inputs at the soma and dendrite, respectively, as a function of input frequency (cf. Fig 1C). B: amplitude of subthreshold somatic voltage responses to a sinusoidal electric field with amplitude E1 = 1 V...
Data
Spike rate responses of two-compartment neurons. A: spike rate as a function of somatic (green) and dendritic (blue) mean input, respectively, for σs/Cs=0.1V/s and σd/Cd=0.05V/s (cf. Fig 1H). B: amplitude of spike rate responses to sinusoidal modulations of the mean input at the soma (green) or at the dendrite (blue) as a function of modulation fre...
Preprint
Identification and localization of sounds are both integral parts of computational auditory scene analysis. Although each can be solved separately, the goal of forming coherent auditory objects and achieving a comprehensive spatial scene understanding suggests pursuing a joint solution of the two problems. This work presents an approach that robust...
Preprint
Computational auditory scene analysis is gaining interest in the last years. Trailing behind the more mature field of speech recognition, it is particularly general sound event detection, that is attracting increasing attention. Crucial for training and testing reasonable models is having available enough suitable data -- until recently, general so...
Preprint
Classifying objects in images is a major task in many modern computer vision applications. Due to the complex­ity of detecting, describing and finally recognizing items with differing sizes and orientations, this task still remains a highly challenging problem. During the last decades, Con­volutional Neural Networks (CNNs) have proven to yield top­...
Preprint
This paper is in a publication limbo at the moment. In the last review, we were crtisized for lack of examples and proper connection to other results. If someone finds something usable/relatable in the method that the paper describes, we are open to any form of collaboration. The core novelty/observetion in this paper is that the change of measure...
Preprint
Full-text available
Transcranial brain stimulation and evidence of ephaptic coupling have sparked strong interests in understanding the effects of weak electric fields on the dynamics of neuronal populations. While their influence on the subthreshold membrane voltage can be biophysically well explained using spatially extended neuron models, mechanistic analyses of ne...
Article
Full-text available
The rise of transcranial current stimulation (tCS) techniques have sparked an increasing interest in the effects of weak extracellular electric fields on neural activity. These fields modulate ongoing neural activity through polarization of the neuronal membrane. While the somatic polarization has been investigated experimentally, the frequency-dep...
Data
Increasing the neuron membrane surface reduces the sensitivity to DC fields. Polarization of passive cells due to a positive 1 V/m field plotted as the function of the distance from the soma. For clarity basal dendrites are plotted with negative distance. The polarization is plotted for original cell (green) and for a cell with an increased membran...
Data
In a passive cable with a right bending angle, the length of the bent branch mainly affects the field sensitivity at its extremity, without inducing a resonance. The subplots represent the field sensitivity (in V / (V/λ)) at both cable ends: (top,red star) the unbent branch and (bottom, violet circle) the bent one, as function of the field frequenc...
Data
In a passive cable with an acute bending angle, the membrane time constant τ determines the resonance frequency. The subplots represent the field sensitivity (in V / (V/λ)) at both cable ends: (top,red star) the unbent branch and (bottom, violet circle) the bent one, as function of the field frequency (x axis). The field sensitivity are displayed f...
Data
In an active pyramidal cell model, the field sensitivity presents a strong resonance around 10-20Hz at the apical dendrite but not at the soma or the basal dendrite. Frequency-dependent sensitivity of the cell to AC field measured at different locations at the basal (A) or apical (B) dendrites. Colors code the distance to the soma of the considered...
Data
The distribution of the resting membrane potential does not qualitatively affects the field sensitivity profile of the active cell at the apical dendrites. (A) Distribution of the membrane potential at rest, i.e. in absence of electrical fields, in the fully active Hay et al. model. (B) Field sensitivity of the fully active model in case of non-uni...
Data
A passive pyramidal neuron exhibits a frequency resonance in its field sensitivity at the proximal dendrites. (Left) Frequency-dependent sensitivity of the passive cell, i.e. without any active ion channels, due to AC field parallel to the somato-dendritic axis. The locations where these sensitivities are measured are displayed on the cell (right)....
Data
In a passive cable with an obtuse bending angle, the length of the bent branch has little effects on the field sensitivity at both extremities. The subplots represent the field sensitivity (in V / (V/λ)) at both cable ends: (top,red star) the unbent branch and (bottom, violet circle) the bent one, as function of the field frequency (x axis). The fi...
Data
The type of QA channel, with conductance distributed increasingly from the soma, affects more strongly the field sensitivity at apical dendrites than at the soma and basal dendrites. The neuron model includes a leak current and a single QA channel, whose conductance distribution increases linearly with distance from the soma. The shades of grey in...
Data
The effects of the channel type on the field sensitivity are transposable to other pyramidal cell morphologies. We consider a neuron model which includes solely a leak conductance and a single uniformly distributed quasi-active channel (QA). We use the reconstructed morphology corresponding to cell 3 in the Hay et al. [16] paper. The plots display...
Data
In a passive cable with an acute bending angle, the relative length of the bent branch, D, determines the presence of a resonance and the membrane time constant, τ, the resonance frequency. We consider the sensitivity to AC fields of a cable with acute bending angle (Θ = π/4) measured at the bent extremity. From left to right, the plots represent t...
Data
Decreasing the membrane time constant reduces the field sensitivity frequency-dependence of bent cable. Distribution of the sensitivity (top) and phase (bottom) along the bent cable for different field frequencies (0.5, 10, 50, 100, 200, 500 and 1000Hz). Cable parameters are τ = 5(ms), L = 1(λ), Θ = π/4 (rad) and D = 0.4(λ). (TIF)
Data
The presence of several basal dendrites parallel to apical dendrites increases the field sensitivity at the apical dendrites and can induce a resonance at the soma. (A) Schematic representation of the simplified neuron model at use. The model consists in a main branch of length H, parallel to the extracellular field. Several branches of length D ar...
Data
The presence of a shunt at the soma induces an asymmetric field sensitivity, the apical dendrites being more sensitive than the soma and basal dendrites. (A) Schematic representation of the simplified neuron model at use. The model consists in a passive cable with a local shunt (green square), i.e. an additional local conductance. The shunt is loca...
Data
The type of QA channel, with conductance distributed decreasingly from the soma, affects the field sensitivity at the soma, apical and basal dendrites. The neuron model includes a leak current and a single QA channel, whose conductance distribution decreases linearly with distance from the soma. The shades of grey in the cell plot represent this di...
Data
The transfer impedances between the apical dendrite and the soma are symmetric and are not affected by DC fields. The impedances are displayed in the absence of field (solid lines) and in the presence of a positive DC field of 1 V/m (dashed lines). The impedances are computed through the injection of a low amplitude sinusoidal current at one locati...
Data
The effects of the channel type on the field sensitivity are transposable to other pyramidal cell morphologies. We consider a neuron model which includes solely a leak conductance and a single uniformly distributed quasi-active channel (QA). We use the reconstructed morphology corresponding to cell 2 in the Hay et al. [16] paper. The plots display...
Data
The field sensitivity of a pyramidal cell is less frequency-dependent in an high-conductance state. We consider the field sensitivity of a neuron model in different conductance states. The low-conductance state corresponds to the model with the same leak conductance as the original Hay et al. [16] model. In the high- (blue lines) and higher-conduct...
Article
Abnormalities across different domains of neuropsychological functioning may constitute a risk factor for heavy drinking during adolescence and for developing alcohol use disorders later in life. However, the exact nature of such multi‐domain risk profiles is unclear, and it is further unclear whether these risk profiles differ between genders. We...
Article
Full-text available
The rise of transcranial current stimulation (tCS) techniques have sparked an increasing interest in the effects of weak extracellular electric fields on neural activity. These fields modulate ongoing neural activity through polarization of the neuronal membrane. While the somatic polarization has been investigated experimentally, the frequency-dep...
Conference Paper
Full-text available
Using an extracellular medium with high potassium/low magnesium concentration with the addition of 4-AP we induced epileptiform activity in combined hippocampus/entorhinal cortex slices of the rat brain [1]. In this in vitro model of temporal lobe epilepsy, we observed the repeating sequences of interictal discharge (IID) regimes and seizure-like e...