Page: Research groups > Systems Neurophysiology (Schwarz)



Head
Prof. Dr. rer. nat. Cornelius Schwarz
Tel. +49 (0)7071 29 80462
Fax +49 (0)7071 29 5724

Lab members
Dr. rer. nat. Alia Benali
 Dr. rer. nat. Dominik Bruggersergejus.butovas(at)uni-tuebingen.dedominikbrugger(at)fastmail.fm
Dr. rer. nat. Sergejus Butovas
Caroline Bergner (MD project)
Andre Maia Chagas (PhD project)
Petya Georgieva (PhD project)
Bettina Joachimsthaler (PhD project)
puzicha.chr(at)gmx.deChristian Waiblinger (PhD project)
Ursula Pascht (Technician)

Former lab members
Dr. rer. nat. Florent Haiss
Dr. rer. nat. Harald Hentschke
Todor Gerdjikov, PhD
Dr. rer. nat. Maik C. Stüttgenmaik.stuettgen(at)rub.de

 

Goals

1) Active Perception
Perception is an active process. Before actively seeking sensory information, the individual forms an internal hypothesis about its sensory environment. Based on this hypothesis, sensor movements, covert and overt shifts of attention, and selection of explorative strategies, amongst others, are employed to optimize the acquisition of sensory stimuli. Passive perception, on the other hand, only occurs if the individual has no chance to anticipate the sensory event and thus fails to prepare its perceptual system and engage in appropriate explorative behavior. Once an individual acquires sensory data in an active manner, it needs to interpret these data according to its internal hypothesis. In other words, active sensory data must be integrated in a top-down fashion by signals holding the internal hypothesis. For instance, the individual needs to calibrate incoming sensory data according to the movement pattern or attentional mechanisms used, it must update its internal hypothesis based on the new insights gained, and appropriately factor in information obtained from other sensory modi.

We study Active Touch as a model system for Active Perception. Rats perform active palpatory vibrissa movements in order to discriminate surface textures and shapes of objects. The great advantage of this model system is that the easily accessible vibrissal movements can be used as the estimate of the individual's internal hypothesis. A further advantage is the relative simplicity of whisker movements (essentially 1D hair movement around a pivot point in the skin) and the large and accessible whisker representations in the somatosensory and motor cortex. Probing these representations with multi-electrode recordings, while rats perform vibrissa movements and/or tactile detection/discrimination tasks, we investigate how motor signals (carrying the internal hypothesis) modulate tactile processing.

Key publications

  • Haiss F, Schwarz C (2005) Spatial segregation of different modes of movement control in the whisker representation of rat primary motor cortex. J Neurosci 25:1579-1587
  • Hentschke H, Haiss F, Schwarz C (2006) Central signals rapidly switch tactile processing in rat barrel cortex during whisker movements. Cerebral Cortex 16:1142-1156
  • Stüttgen MC, Rüter J, Schwarz C (2006) Two psychophysical channels of whisker deflection in rats align with two neuronal classes of primary afferents. J Neurosci 26:7933-7941.
  • Stüttgen MC, Schwarz C (2008) Psychophysical and neurometric detection performance under stimulus uncertainty. Nat Neurosci 11:1091-1099
  • Gerdjikov TV, Bergner CG, Stüttgen MC, Waiblinger C, Schwarz C (2010) Discrimination of vibrotactile stimuli in the rat whisker system - behavior and neurometrics. Neuron 65:530-540

2) Context dependency of cortical microstimulation
It is sought to establish methodological approaches to use CNS-multi-electrode implants for neurological rehabilitation. A microstimulation pulse applied in a CNS structure will generate neuronal activity that is dependent on the context. The context is determined by two sources. A) The spatio-temporal microstimulation pattern itself: it matters if a given pulse is applied in isolation or if it is embedded within a spatio-temporal pulse pattern. B) The functional state of the CNS structure that is to be stimulated: it matters if the structure is engaged in a task or idling (i.e. during sleep) when stimulating it. We aim to employ the Active Touch model system (described above) to determine basic neuronal activity evoked by multi-electrode stimulation in cortical representations of the vibrissal system.

Key publications

  • Butovas S, Schwarz C (2003) Spatiotemporal effects of microstimulation in rat neocortex: a parametric study using multielectrode recordings. J Neurophysiol 90: 3024
  • Butovas S, Hormuzdi SG, Monyer H, Schwarz C (2006) Effects of electrically coupled inhibitory networks on local neuronal responses to intracortical microstimulation. J Neurophysiol 96:1227-1236.
  • Butovas S Schwarz C (2007) Intracortical microstimulation in barrel cortex of awake, head-restraint rats: assessment of detection thresholds. Eur J Neurosci 25:2161-2169


Methods

  1. Operant conditioning of rats and psychophysics
  2. Real-time registration of vibrissa trajectories and precise vibrissal stimulation.
  3. Electrophysiological recording via implanted microelectrode arrays.
  4. Multielectrode Stimulation


Teaching

  1. Lecture Neurophysiology Graduate School of Cognitive and Behavioural Neuroscience (Schwarz, Pedroarena, Antkowiak). Winter term. In English.
  2. Lab Practical Neurophysiology (Schwarz, Pedroarena, Antkowiak, Hentschke). Open for students of the Graduate School of Cognitive and Behavioural Neuroscience, Medicine, Psychology, Sciences. HIH Otfried Müller Str. 27, August, 1 week block. In English.

In vitro Electrophysiology Lab

Head
Christine Pedroarena, MD

Intrinsic and synaptic mechanisms determining cerebellar nuclei neurons spike output
Although all forms of cerebellar dysfunction are characterized by severe impairment in the timing of muscular activation and consequent uncoordinated movements, the cellular underpinnings of the cerebellum control of movement remains unknown. Our research is focused on the neurons of the deep cerebellar nuclei (DCN) which carry almost all cerebellar output signals and are the main target of the cerebellar cortex signals. Despite their central position in the cerebellar system, the internal micro-circuits and cellular mechanisms determining DCN output are still poorly understood. Moreover, in many types of cerebellar diseases, deep cerebellar nuclei neurons are spared and their function is altered only secondarily to the alterations occurring at the cerebellar cortex. Hence, cerebellar nuclei are a natural place for compensatory mechanisms for diseases affecting the cerebellar cortex. The general aim of this research is to understand the cellular mechanism that control DCNs output. Particularly, three areas are currently investigated:

  1. The ionic mechanisms controlling spontaneous end evoked firing of DCNs.
  2. How synaptic and intrinsic mechanisms interact to support transfer of information from the Purkinje cells to the DCNs.
  3. DCN neurons are a heterogeneous population with different neurotransmitter content and projection patterns. We are investigating how connectivity and cellular properties of each DCN type determine its specific output.

Finally we are interested in the potential plasticity of the above mentioned mechanisms.

Methods

  1. in vitro electrophysiology using whole cell patch recordings
  2. brain slices taken from wild type and transgenic animals
  3. immuno-histochemistry and intracellular staining techniques  

 

Key publications



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