FG Neuronale Informationsverarbeitung

23 Items

Recent Submissions
Neural correlates of cue‐induced changes in decision‐making distinguish subjects with gambling disorder from healthy controls

Genauck, Alexander ; Matthis, Caroline ; Andrejevic, Milan ; Ballon, Lukas ; Chiarello, Francesca ; Duecker, Katharina ; Heinz, Andreas ; Kathmann, Norbert ; Romanczuk‐Seiferth, Nina (2020-08-05)

In addiction, there are few human studies on the neural basis of cue‐induced changes in value‐based decision making (Pavlovian‐to‐instrumental transfer, PIT). It is especially unclear whether neural alterations related to PIT are due to the physiological effects of substance abuse or rather related to learning processes and/or other etiological factors related to addiction. We have thus investi...

Approximate Inference for Time-Varying Interactions and Macroscopic Dynamics of Neural Populations

Donner, Christian ; Obermayer, Klaus ; Shimazaki, Hideaki (2017-01-17)

The models in statistical physics such as an Ising model offer a convenient way to characterize stationary activity of neural populations. Such stationary activity of neurons may be expected for recordings from in vitro slices or anesthetized animals. However, modeling activity of cortical circuitries of awake animals has been more challenging because both spike-rates and interactions can chang...

Maximum likelihood difference scales represent perceptual magnitudes and predict appearance matches

Wiebel, Christiane B. ; Aguilar, Guillermo ; Maertens, Marianne (2017)

One central problem in perception research is to understand how internal experiences are linked to physical variables. Most commonly, this relationship is measured using the method of adjustment, but this has two shortcomings: The perceptual scales that relate physical and perceptual variables are not measured directly, and the method often requires perceptual comparisons between viewing condit...

Comparing sensitivity estimates from MLDS and forced-choice methods in a slant-from-texture experiment

Aguilar, Guillermo ; Wichmann, Felix A. ; Maertens, Marianne (2017)

Maximum likelihood difference scaling (MLDS) is a method for the estimation of perceptual scales based on the judgment of differences in stimulus appearance (Maloney & Yang, 2003). MLDS has recently also been used to estimate near-threshold discrimination performance (Devinck & Knoblauch, 2012). Using MLDS as a psychophysical method for sensitivity estimation is potentially appealing, because M...

Cue‐induced effects on decision‐making distinguish subjects with gambling disorder from healthy controls

Genauck, Alexander ; Andrejevic, Milan ; Brehm, Katharina ; Matthis, Caroline ; Heinz, Andreas ; Weinreich, André ; Kathmann, Norbert ; Romanczuk‐Seiferth, Nina (2019-11-12)

While an increased impact of cues on decision‐making has been associated with substance dependence, it is yet unclear whether this is also a phenotype of non‐substance‐related addictive disorders, such as gambling disorder (GD). To better understand the basic mechanisms of impaired decision‐making in addiction, we investigated whether cue‐induced changes in decision‐making could distinguish GD ...

Coding of low-dimensional variables with spiking neural networks

Koren, Veronika (2020)

Spikes, extremely precise temporal signals, are believed to be the main mean of communication between neurons. However, it is at present unclear how can be the information, contained in spike timing, utilized for encoding of low-dimensional variables. Based on work by Boerlin, Machens and Deneve (Boerlin et al. 2013), we derive a functional model of spiking neural activity that exploits informa...

Robust sound event detection in binaural computational auditory scene analysis

Trowitzsch, Ivo (2020)

Automatic sound event detection and computational auditory scene analysis gain importance through the increasing prevalence of technical systems operating autonomously or in the background, since such operation requires awareness of the system's environment. In realistic scenes, reliable sound event detection, despite the big improvements of the related automatic speech recognition, still pose...

Neurobehavioural patterns of alcohol abuse in adolescence

Matthis, Caroline (2019)

Excessive alcohol consumption has a detrimental effect on public health. Alcohol abuse is a top-ranked disorder of the brain with respect to total costs to economy and is linked to an estimated 3.8 % of global deaths. Often, first experiences with alcohol are made during adolescence, the time of transition between childhood and adulthood. Adolescence marks a period of complex social, biological...

Spike avalanches in vivo suggest a driven, slightly subcritical brain state

Priesemann, Viola ; Wibral, Michael ; Valderrama, Mario ; Pröpper, Robert ; Le Van Quyen, Michel ; Geisel, Theo ; Triesch, Jochen ; Nikolić, Danko ; Munk, Matthias H. J. (2014-06-24)

In self-organized critical (SOC) systems avalanche size distributions follow power-laws. Power-laws have also been observed for neural activity, and so it has been proposed that SOC underlies brain organization as well. Surprisingly, for spiking activity in vivo, evidence for SOC is still lacking. Therefore, we analyzed highly parallel spike recordings from awake rats and monkeys, anesthetized ...

Motor Task-Dependent Dissociated Effects of Transcranial Random Noise Stimulation in a Finger-Tapping Task Versus a Go/No-Go Task on Corticospinal Excitability and Task Performance

Jooss, Andreas ; Haberbosch, Linus ; Köhn, Arvid ; Rönnefarth, Maria ; Bathe-Peters, Rouven ; Kozarzewski, Leonard ; Fleischmann, Robert ; Scholz, Michael ; Schmidt, Sein ; Brandt, Stephan A. (2019-02-27)

Background and Objective: Transcranial random noise stimulation (tRNS) is an emerging non-invasive brain stimulation technique to modulate brain function, with previous studies highlighting its considerable benefits in therapeutic stimulation of the motor system. However, high variability of results and bidirectional task-dependent effects limit more widespread clinical application. Task depend...

BOiS—Berlin Object in Scene Database: Controlled Photographic Images for Visual Search Experiments with Quantified Contextual Priors

Mohr, Johannes ; Seyfarth, Julia ; Lueschow, Andreas ; Weber, Joachim E. ; Wichmann, Felix A. ; Obermayer, Klaus (2016-05-23)

Photographic stimuli are often used for studying human perception. To faithfully represent our natural viewing environment, these stimuli should be free of potential artifacts. If stimulus material for scientific experiments is generated from photographs that were created for a different purpose, such as advertisement or art, the scene layout and focal depth might not be typical for our visual ...

pypet: A Python Toolkit for Data Management of Parameter Explorations

Meyer, Robert ; Obermayer, Klaus (2016-08-25)

pypet (Python parameter exploration toolkit) is a new multi-platform Python toolkit for managing numerical simulations. Sampling the space of model parameters is a key aspect of simulations and numerical experiments. pypet is designed to allow easy and arbitrary sampling of trajectories through a parameter space beyond simple grid searches. pypet collects and stores both simulation parameters a...

Neo: an object model for handling electrophysiology data in multiple formats

Garcia, Samuel ; Guarino, Domenico ; Jaillet, Florent ; Jennings, Todd ; Pröpper, Robert ; Rautenberg, Philipp L. ; Rodgers, Chris C. ; Sobolev, Andrey ; Wachtler, Thomas ; Yger, Pierre ; Davison, Andrew P. (2014-02-20)

Neuroscientists use many different software tools to acquire, analyze and visualize electrophysiological signals. However, incompatible data models and file formats make it difficult to exchange data between these tools. This reduces scientific productivity, renders potentially useful analysis methods inaccessible and impedes collaboration between labs. A common representation of the core data ...

Spyke Viewer: a flexible and extensible platform for electrophysiological data analysis

Pröpper, Robert ; Obermayer, Klaus (2013-11-11)

Spyke Viewer is an open source application designed to help researchers analyze data from electrophysiological recordings or neural simulations. It provides a graphical data browser and supports finding and selecting relevant subsets of the data. Users can interact with the selected data using an integrated Python console or plugins. Spyke Viewer includes plugins for several common visualizatio...

Inferring network properties of cortical neurons with synaptic coupling and parameter dispersion

Roy, Dipanjan ; Jirsa, Viktor (2013-03-26)

Computational models at different space-time scales allow us to understand the fundamental mechanisms that govern neural processes and relate uniquely these processes to neuroscience data. In this work, we propose a novel neurocomputational unit (a mesoscopic model which tell us about the interaction between local cortical nodes in a large scale neural mass model) of bursters that qualitatively...

Safety Aspects, Tolerability and Modeling of Retinofugal Alternating Current Stimulation

Haberbosch, Linus ; Datta, Abhishek ; Thomas, Chris ; Jooß, Andreas ; Köhn, Arvid ; Rönnefarth, Maria ; Scholz, Michael ; Brandt, Stephan A. ; Schmidt, Sein (2019-08-07)

Background While alternating current stimulation (ACS) is gaining relevance as a tool in research and approaching clinical applications, its mechanisms of action remain unclear. A review by Schutter and colleagues argues for a retinal origin of transcranial ACS’ neuromodulatory effects. Interestingly, there is an alternative application form of ACS specifically targeting α-oscillations in the ...

Optimizing the depth and the direction of prospective planning using information values

Sezener, Can Eren ; Dezfouli, Amir ; Keramati, Mehdi (2019-03-12)

Evaluating the future consequences of actions is achievable by simulating a mental search tree into the future. Expanding deep trees, however, is computationally taxing. Therefore, machines and humans use a plan-until-habit scheme that simulates the environment up to a limited depth and then exploits habitual values as proxies for consequences that may arise in the future. Two outstanding quest...

Computational modeling of glutamate-induced calcium signal generation and propagation in astrocytes

Oschmann, Franziska (2018)

Since the 1990s researchers have shown that astrocytes generate calcium oscillations in response to neuronal activity and propagate them as intercellular calcium waves over long distances. Moreover, astrocytes release transmitters in a calcium-dependent manner and by that signal to neurons. These discoveries have made astrocytes and especially calcium signal generation and propagation in astroc...

Investigating the effects of weak extracellular fields on single neurons: a modelling approach

Aspart, Florian (2018)

In the past decades, the rise of transcranial current stimulation (tCS) has sparkled an increasing interest in the effects of weak extracellular electric fields on neural activity. These fields, such as induced during tCS, have been shown to polarize the neuronal membrane and, consequently, to modulate the spiking activity. In this thesis, I follow a modelling approach to investigate how single...

Dorsolateral prefrontal cortex contributes to the impaired behavioral adaptation in alcohol dependence

Beylergil, Sinem Balta ; Beck, Anne ; Deserno, Lorenz ; Lorenz, Robert C. ; Rapp, Michael A. ; Schlagenhauf, Florian ; Heinz, Andreas ; Obermayer, Klaus (2017-04-17)

Substance-dependent individuals often lack the ability to adjust decisions flexibly in response to the changes in reward contingencies. Prediction errors (PEs) are thought to mediate flexible decision-making by updating the reward values associated with available actions. In this study, we explored whether the neurobiological correlates of PEs are altered in alcohol dependence. Behavioral, and ...