Projects of the RTG 1589 "Sensory Computation in Neural Systems" (2009-2019)

The Research Training Group (RTG) "Sensory Computation in Neural Systems" was established in 2010 and generously funded by the German Research Foundation (DFG). Projects in the RTG 1589 aimed to combine techniques and concepts from machine learning, computational neuroscience, and systems neurobiology to address sensory computation specifically. Experimentalists and theoreticians joined forces and educated young scientists: (1) to work on interdisciplinary projects investigating the neural computations underlying perception, (2) to address the processes underlying perception on different scales and different levels of abstraction, and (3) to develop new theories of computation, hand-in-hand with wellcontrolled experiments, to test functional hypotheses. Through this research training group, our graduates gained competence in a broad range of computational techniques; encompassing neurons, networks, and systems, and are able to judge the implications, as well as limits, given the data at hand.
The scientific program focused on sensory processing and perception. Since perception is task dependent (“perception serves a purpose”), sensory processing is connected to cognitive functions (decision making, memory function, planning, and motor control) and is linked to performance measures. Hence, perception is related to almost all experiments involving behaving animals or human subjects. Moreover, our students exploited new ideas from the fields of dynamical systems and machine learning to develop novel theoretical concepts to link the distinct levels of abstraction together. Over the past ten years, significant advances have been made by students of the RTG 1589 in developing computational models, experimental tests and theories with the goal of bridging the distinct levels of abstraction.

Over 70 PhD projects were completed with an excellent publication record:

On modelling data from visual psychophysics: A Bayesian graphical model approach		Nonlinear encoding and decoding of signals for noisy neurons
Decoding multiple sclerosis and related disease parameters using structural brain fMRI and multivariate analysis algorithms		Stochastic properties of brain network models
Learning on relational data – Prototype-based classification of attributed graphs		Effects of ionic concentration dynamics on neuronal activity
From behavioural plasticity to neuronal computation: An investigation of associative learning in honeybee brain		Bayesian inference of inhomogeneous point process models: Methodologica advances and modelling of neuronal spiking data
Classification of single trial EEG in non-stationary envionrments		Neurobehavioural patterns of alcohol abuse in adolescense
Spike statistics and coding properties of phase models – from ion channels to neural coding		Gaze effects in value-based choice
Neural representations of conditional task rules		The effects of corrupted feedback on visual perception
Temperature dependence of auditory computations in insect nervous systems		Maintaining & manipulating somatosensory working memory representations
Optimal population coding of dynamic stimuli		Neurochemical and neuroanatomical principles of neural connectivity and function in cortical structures
Goal-directed behaviour and the usability of Friston’s free-energy principle		Cellular mechanisms of working memory
Cortical Information processing under non-stationary network state conditions		Mechanisms of inhibition-based ripple oscillations in the hippocampal formation
Computational modeling of reversal learning in alcohol use disorder		Neural basis of somatosensory target detection
Reward-dependent perceptual learning		On modelling data from visual psychophysics: A Bayesian graphical model approach
The brain as Data Source – Model – Inspiration		Decoding multiple sclerosis and related disease parameters using structural brain fMRI and multivariate analysis algorithms
Decision processes in bilinguale language perception		Learning on relational data – Prototype-based classification of attributed graphs
Computational tools for model analysis		From behavioural plasticity to neuronal computation: An investigation of associative learning in honeybee brain
Neurodynamics in complex networks		Classification of single trial EEG in non-stationary envionrments
The computational role of cortical feedback in the domain of lightness perception		Spike statistics and coding properties of phase models – from ion channels to neural coding
Signal processing and signal gating in stochastic neurons with short-term plasticity		Neural representations of conditional task rules
The neural code of visual working memory		Temperature dependence of auditory computations in insect nervous systems
Neuronal morphology and its influence on computational properties		Optimal population coding of dynamic stimuli
Effects of inhibition on dendritic signal propagation		Goal-directed behaviour and the usability of Friston’s free-energy principle
Information integration in the human brain		On modelling data from visual psychophysics: A Bayesian graphical model approach
Dynamic gesture recognition		Decoding multiple sclerosis and related disease parameters using structural brain fMRI and multivariate analysis algorithms
Modelling and connectivity for nonstationary neural data		Learning on relational data – Prototype-based classification of attributed graphs
Correlations and coding in primary visual cortex		From behavioural plasticity to neuronal computation: An investigation of associative learning in honeybee brain
Modeling the spatiotemporal neuronal dynamics of conscious tactile information processing		Classification of single trial EEG in non-stationary envionrments
Task-dependent sensorimotor integration and behaviour recognition		Spike statistics and coding properties of phase models – from ion channels to neural coding
Olfactory computation in insect nervous systems		Neural representations of conditional task rules
Sensory undetermination and the interplay between sensory features studied in the domains of lightness and depth perception		Temperature dependence of auditory computations in insect nervous systems
Models of somesthesis		Optimal population coding of dynamic stimuli
Detecting single-cell stimulation in recurrent networks of integrate-and-fire neurons		Goal-directed behaviour and the usability of Friston’s free-energy principle
Decision-making and its modulation by cues in addictive disorders		Cortical Information processing under non-stationary network state conditions
Interneuronal gap junctions with short delays increase neuronal synchrony of ripple oscillations		Computational modeling of reversal learning in alcohol use disorder
Coding of low-dimensional variables with spiking neural networks		Reward-dependent perceptual learning
Computational modelling of glutamate-induced calcium signal generation and propagation in astrocytes		The brain as Data Source – Model – Inspiration
How brain rhythms guide memory and decisions		Decision processes in bilinguale language perception