Biology subjects

Matthias H Hennig

Publications and source records attributed to Matthias H Hennig.

3 recordsLinked to original sources

bioRxiv2016

Pan-retinal characterisation of Light Responses from Ganglion Cells in the Developing Mouse Retina

We have investigated the ontogeny of light-driven responses in mouse retinal ganglion cells (RGCs). Using a large-scale, high-density multielectrode array, we recorded from hundreds to thousands of RGCs simultaneously at pan-retinal level, including dorsal and ventral locations. Responses to different contrasts not only revealed a complex developmental profile for ON, OFF and ON-OFF RGC types, but also unveiled differences between dorsal and ventral RGCs. At eye-opening, dorsal RGCs of all types were more responsive to light, perhaps indicating an environmental priority to nest viewing for pre-weaning pups. The developmental profile of ON and OFF RGCs exhibited antagonistic behavior, with the strongest ON responses shortly after eye-opening, followed by an increase in the strength of OFF responses later on. Further, we found that with maturation receptive field (RF) center sizes decrease, responses to light get stronger, and centers become more circular while seeing differences in all of them between RGC types. These findings show that retinal functionality is not spatially homogeneous, likely reflecting ecological requirements that favour the early development of dorsal retina, and reflecting different roles in vision in the mature animal.

Neuroscience↗

bioRxiv2016

Unsupervised spike sorting for large scale, high density multielectrode arrays

A new method for automated spike sorting for recordings with high density, large scale multielectrode arrays is presented. Exploiting the dense sampling of single neurons by multiple electrodes, we obtain an efficient, low-dimensional representation of detected spikes consisting of estimated spatial spike locations and dominant spike shape features, which enables fast and reliable clustering into single units. Millions of events can be sorted in minutes, and the method is parallelized and scales better than quadratically with the number of detected spikes. We demonstrate this method using recordings with a 4,096 channel array, and present validation based on anatomical imaging, optogenetic stimulation and model-based quality control. A comparison with semi-automated, shape-based spike sorting exposes significant limitations of conventional methods. Our analysis shows that it is feasible to reliably isolate the activity of hundreds to thousands of neurons in a single recording, and that dense, multi-channel probes substantially aid reliable spike sorting.

Neuroscience↗

bioRxiv2014

A diffusive homeostatic signal maintains neural heterogeneity and responsiveness in cortical networks

Gaseous neurotransmitters such as nitric oxide (NO) provide a unique and often overlooked mechanism for neurons to communicate through diffusion within a network, independent of synaptic connectivity. NO provides homeostatic control of intrinsic excitability. Here we conduct a theoretical investigation of the distinguishing roles of NO-mediated diffusive homeostasis in comparison with canonical non-diffusive homeostasis in cortical networks. We find that both forms of homeostasis provide a robust mechanism for maintaining stable activity following perturbations. However, the resulting networks differ, with diffusive homeostasis maintaining substantial heterogeneity in activity levels of individual neurons, a feature disrupted in networks with non-diffusive homeostasis. This results in networks capable of representing input heterogeneity, and linearly responding over a broader range of inputs than those undergoing non-diffusive homeostasis. We further show that these properties are preserved when homeostatic and Hebbian plasticity are combined. These results suggest a mechanism for dynamically maintaining neural heterogeneity, and expose computational advantages of non-local homeostatic processes.\n\nAuthor SummaryNeural firing rates must be maintained within a stable range in the face of ongoing fluctuations in synaptic connectivity. Existing cortical network models achieve this through various homeostatic mechanisms which constrain the excitability of individual neurons according to their recent activity. Here, we propose a new mechanism, diffusive homeostasis, in which neural excitability is modulated by nitric oxide, a gas which can flow freely across cell membranes. Information about a neurons firing rate can be carried by nitric oxide, meaning that an individual neurons excitability is affected by neighboring neurons firing rates as well as its own. We find that this allows a neuron to deviate from the target population activity, as its neighbors will counteract this deviation, thus maintaining stable average activity. This form of neural heterogeneity is more flexible than assigning different target firing rates to individual neurons.

Neuroscience↗