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Tabas A.,Bournemouth University | Siebert A.,University of Zurich | Supek S.,University of Zagreb | Pressnitzer D.,Ecole Normale Superieure de Paris | And 3 more authors.
PLoS ONE | Year: 2016

Communication sounds are typically asymmetric in time and human listeners are highly sensitive to this short-term temporal asymmetry. Nevertheless, causal neurophysiological correlates of auditory perceptual asymmetry remain largely elusive to our current analyses and models. Auditory modelling and animal electrophysiological recordings suggest that perceptual asymmetry results from the presence of multiple time scales of temporal integration, central to the auditory periphery. To test this hypothesis we recorded auditory evoked fields (AEF) elicited by asymmetric sounds in humans. We found a strong correlation between perceived tonal salience of ramped and damped sinusoids and the AEFs, as quantified by the amplitude of the N100m dynamics. The N100m amplitude increased with stimulus half-life time, showing a maximum difference between the ramped and damped stimulus for a modulation half-life time of 4 ms which is greatly reduced at 0.5 ms and 32 ms. This behaviour of the N100m closely parallels psychophysical data in a manner that: i) longer half-life times are associated with a stronger tonal percept, and ii) perceptual differences between damped and ramped are maximal at 4 ms half-life time. Interestingly, differences in evoked fields were significantly stronger in the right hemisphere, indicating some degree of hemispheric specialisation. Furthermore, the N100m magnitude was successfully explained by a pitch perception model using multiple scales of temporal integration of auditory nerve activity patterns. This striking correlation between AEFs, perception, and model predictions suggests that the physiological mechanisms involved in the processing of pitch evoked by temporal asymmetric sounds are reflected in the N100m. © 2016 Tabas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Source


Fischer V.,University of Heidelberg | Both M.,University of Heidelberg | Draguhn A.,University of Heidelberg | Draguhn A.,Bernstein Center for Computational Neuroscience Heidelberg Mannheim | And 2 more authors.
Journal of Neurochemistry | Year: 2014

The cholinergic system is critically involved in the modulation of cognitive functions, including learning and memory. Acetylcholine acts through muscarinic (mAChRs) and nicotinic receptors (nAChRs), which are both abundantly expressed in the hippocampus. Previous evidence indicates that choline, the precursor and degradation product of Acetylcholine, can itself activate nAChRs and thereby affects intrinsic and synaptic neuronal functions. Here, we asked whether the cellular actions of choline directly affect hippocampal network activity. Using mouse hippocampal slices we found that choline efficiently suppresses spontaneously occurring sharp wave-ripple complexes (SPW-R) and can induce gamma oscillations. In addition, choline reduces synaptic transmission between hippocampal subfields CA3 and CA1. Surprisingly, these effects are mediated by activation of both mAChRs and α7-containing nAChRs. Most nicotinic effects became only apparent after local, fast application of choline, indicating rapid desensitization kinetics of nAChRs. Effects were still present following block of choline uptake and are, therefore, likely because of direct actions of choline at the respective receptors. Together, choline turns out to be a potent regulator of patterned network activity within the hippocampus. These actions may be of importance for understanding state transitions in normal and pathologically altered neuronal networks. © 2014 International Society for Neurochemistry. Source


Gerchen M.F.,University of Mannheim | Gerchen M.F.,Bernstein Center for Computational Neuroscience Heidelberg Mannheim | Bernal-Casas D.,University of Mannheim | Bernal-Casas D.,Bernstein Center for Computational Neuroscience Heidelberg Mannheim | And 2 more authors.
Human Brain Mapping | Year: 2014

While fMRI activation studies contrasting task conditions regularly assess the whole brain, this is usually not true for studies analyzing task-dependent brain connectivity changes by psychophysiological interactions (PPI). Here we combine standard PPI (sPPI) and generalized PPI (gPPI) with a priori brain parcellation by spatially constrained normalized cut spectral clustering (NCUT) to analyze task-dependent connectivity changes in a whole brain manner, and compare the results to multiseed conventional PPI analyses over all activation peaks in an episodic memory recall task. We show that, depending on the chosen parcellation frame, the whole-brain PPI approach is able to detect a large amount of the information that is detected by the conventional approach. Over and above, whole-brain PPI allows identification of several additional task-modulated connections, particularly from seed regions without significant activation differences between conditions. © 2014 Wiley Periodicals, Inc. Source


Thome C.,University of Heidelberg | Thome C.,Bernstein Center for Computational Neuroscience Heidelberg Mannheim | Kelly T.,University of Bonn | Yanez A.,University of Heidelberg | And 9 more authors.
Neuron | Year: 2014

Neuronal processing is classically conceptualized asdendritic input, somatic integration, and axonal output. The axon initial segment, the proposed site of action potential generation, usually emanates directly from the soma. However, we found that axons of hippocampal pyramidal cells frequently derive from a basal dendrite rather than from the soma. This morphology is particularly enriched in central CA1, the principal hippocampal output area. Multiphoton glutamate uncaging revealed that input onto the axon-carrying dendrites (AcDs) was more efficient in eliciting action potential output than input onto regular basal dendrites. First, synaptic input onto AcDs generates action potentials with lower activation thresholds compared with regular dendrites. Second, AcDs are intrinsically more excitable, generating dendritic spikes with higher probability and greater strength. Thus, axon-carrying dendrites constitute a privileged channel for excitatory synaptic input in a subset of cortical pyramidal cells. © 2014 Elsevier Inc. Source


Pods J.,The Interdisciplinary Center | Pods J.,Bernstein Center for Computational Neuroscience Heidelberg Mannheim | Schonke J.,The Interdisciplinary Center | Schonke J.,Bernstein Center for Computational Neuroscience Heidelberg Mannheim | And 2 more authors.
Biophysical Journal | Year: 2013

In neurophysiology, extracellular signals - as measured by local field potentials (LFP) or electroencephalography - are of great significance. Their exact biophysical basis is, however, still not fully understood. We present a three-dimensional model exploiting the cylinder symmetry of a single axon in extracellular fluid based on the Poisson-Nernst-Planck equations of electrodiffusion. The propagation of an action potential along the axonal membrane is investigated by means of numerical simulations. Special attention is paid to the Debye layer, the region with strong concentration gradients close to the membrane, which is explicitly resolved by the computational mesh. We focus on the evolution of the extracellular electric potential. A characteristic up-down-up LFP waveform in the far-field is found. Close to the membrane, the potential shows a more intricate shape. A comparison with the widely used line source approximation reveals similarities and demonstrates the strong influence of membrane currents. However, the electrodiffusion model shows another signal component stemming directly from the intracellular electric field, called the action potential echo. Depending on the neuronal configuration, this might have a significant effect on the LFP. In these situations, electrodiffusion models should be used for quantitative comparisons with experimental data. © 2013 Biophysical Society. Source

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