Publications

M.H. Hennig (2022), The sloppy relationship between neural circuit structure and function. Journal of Physiology. Early view.

J. Jude, M.G. Perich, L.E. Miller, M.H. Hennig (2022). Capturing cross-session neural population variability through self-supervised identification of consistent neuron ensembles. NeurIPS Workshop: Symmetry and Geometry in Neural Representations.

I. Pisokas, M.H. Hennig (2022). Can the Insect Path Integration Memory be a Bump Attractor? bioRxiv, 2022.04.05.487126.

J. Jude, M.G. Perich, L.E. Miller, M.H. Hennig (2022). Robust alignment of cross-session recordings of neural population activity by behaviour via unsupervised domain adaptation. ICML 2022.

S.P. Currie, J. Ammer, B. Premchand, Y. Wu, C. Eleftheriou, A.A. Faisal, M.H. Hennig, I. Duguid (2022). Movement-specific signaling is differentially distributed across motor cortex layer 5 projection neuron classes. Cell Reports 39 (6), 110801.

D. Pamplona, G. Hilgen, M.H. Hennig, B. Cessac, E. Sernagor, P. Kornprobst (2022). Large visual neuron assemblies receptive fields estimation using a super-resolution approach. Journal of Neurophysiology, 127 (5), 1334-1347.

C.L. Hurwitz, A. Srivastava, K. Xu, J. Jude, M.G. Perich, L.E. Miller, M.H. Hennig (2021). Targeted Neural Dynamical Modeling. Advances in Neural Information Processing Systems 34.

C. Scholl, M.E. Rule, M.H. Hennig (2021). The Information Theory of Developmental Pruning: Optimizing Global Network Architecture Using Local Synaptic Rules. PLoS Biology, 17 (10), e1009458.

C. Hurwitz, N. Kudryashova, A. Onken, M.H. Hennig (2021). Building population models for large-scale neural recordings: opportunities and pitfalls. Current Opinion in Neurobiology, 70, 64-73.

A.P. Buccino, C.L. Hurwitz, J. Magland, S. Garcia, S.H. Siegle, R. Hurwitz, M.H. Hennig (2020). SpikeInterface, a unified framework for spike sorting. BioRxiv, p.796599. Code.

M.E. Rule, M. Sorbaro, M.H. Hennig (2020). Optimal encoding in stochastic latent-variable Models. Entropy, 22(7), 714.

M.E. Rule, D. Schnoerr, M.H. Hennig, G. Sanguinetti (2019). Neural Field Models for Latent State Inference: Application to Large-Scale Neuronal Recordings. PLoS Computational Biology, 15 (11), e1007442..

E. Rajaram, C. Kaltenbach, M. Fischl, L. Mrowka, O. Alexandrova, B. Grothe, M.H. Hennig, and C. Kopp-Scheinpflug (2019). Slow NMDA-mediated excitation accelerates offset-response latencies generated via a post-inhibitory rebound mechanism. ENeuro, 6(3).

C.L. Hurwitz, K. Xu, A. Srivastava, A.P. Buccino, M.H. Hennig (2019). Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference. Advances in Neural Information Processing Systems, 4724-4736.

M.H. Hennig, C. Hurwitz, M. Sorbaro (2019). Scaling Spike Detection and Sorting for Next Generation Electrophysiology. In: Chiappalone M., Pasquale V., Frega M. (eds) In Vitro Neuronal Networks. Advances in Neurobiology, vol 22. Springer, Cham.

M. Sorbaro, H.M. Herrmann, M.H. Hennig (2019). Statistical models of neural activity, criticality, and Zipf’s law. In: Tomen N., Herrmann J., Ernst U. (eds) The Functional Role of Critical Dynamics in Neural Systems. Springer Series on Bio- and Neurosystems, vol 11. Springer, Cham.

J. Jouty, G. Hilgen, E. Sernagor, M.H. Hennig (2018). Non-parametric physiological classification of retinal ganglion cells in the mouse retina. Frontiers in Cellular Neuroscience, 12, 481.

M. Deistler, M. Sorbaro, M.E. Rule, M.H. Hennig (2018). Local learning rules to attenuate forgetting in neural networks. arXiv:1807.05097.

S.J. Lucas, C.B. Michel, V. Marra, J.L. Smalley, M.H. Hennig, B.P. Graham, I.D. Forsythe (2018). Glucose and lactate as metabolic constraints on presynaptic transmission at an excitatory synapse. Journal of Physiology, 596, 1699-1721. preprint.

G. Hilgen, M. Sorbaro, S. Pirmoradian, J.-O. Muthmann, I. Kepiro, S. Ullo, C. Juarez Ramirez, A. Puente Encinas, A. Maccione, L. Berdondini, V. Murino, D. Sona, F. Cella Zanacchi, E. Sernagor, M.H. Hennig (2017). Unsupervised spike sorting for large scale, high density multielectrode arrays. Cell Reports 18, 2521–2532. bioRxiv doi: http://dx.doi.org/10.1101/048645. Code.

G. Hilgen, S. Pirmoradian, D. Pamplona, P. Kornprobst, B. Cessac, M.H. Hennig, E. Sernagor (2016). Pan-retinal characterisation of Light Responses from Ganglion Cells in the Developing Mouse Retina. Scientific Reports 7, Article number: 42330. bioRxiv doi: http://dx.doi.org/10.1101/050393.

P.J. Tully, H. Linden, M.H. Hennig, A. Lansner (2016) Spike-Based Bayesian-Hebbian Learning of Temporal Sequences. PLoS Comput Biol 12(5): e1004954.

N. Pilati, D.M. Linley, H. Selvaskandan, O. Uchitel, M.H. Hennig, C. Kopp-Scheinpflug, I.D. Forsythe (2016). Acoustic trauma slows AMPAR-mediated EPSCs in the auditory brainstem, reducing GluA4 subunit expression as a mechanism to rescue binaural function. J Physiol. 594, 3683-3703.

J.-O. Muthmann, H. Amin, E. Sernagor, A. Maccione, D. Panas, L. Berdondini, U.S. Bhalla, M.H. Hennig MH (2015). Spike detection for large neural populations using high density multielectrode arrays. Front. Neuroinform. 9:28. doi: 10.3389/fninf.2015.00028. Original code and examples. New version!.

Y. Sweeney, J. Hellgren Kotaleski, M.H. Hennig (2015). A diffusive homeostatic signal maintains neural heterogeneity and responsiveness in cortical networks. PLoS Comput Biol 11(7): e1004389. doi:10.1371/journal.pcbi.1004389. biorxiv preprint. Simulation code and examples.

D. Panas, H. Amin, A. Maccione, O. Muthmann, M. van Rossum, L. Berdondini, M.H. Hennig (2015). Sloppiness in spontaneously active neuronal networks. J Neurosci, 35(22): 8480-8492. Pre-print. Code and data.

P.J. Tully, M.H. Hennig and A. Lansner (2014). Synaptic and nonsynaptic plasticity approximating probabilistic inference. Frontiers in Synaptic Neuroscience.

M.H. Hennig (2014). Retinal Waves, Models of. In: Jaeger D., Jung R. (Ed.) Encyclopedia of Computational Neuroscience: SpringerReference. Springer-Verlag Berlin Heidelberg.

M.H. Hennig (2014). Ionotropic Receptors Dynamics, Conductance Models. In: Jaeger D., Jung R. (Ed.) Encyclopedia of Computational Neuroscience: SpringerReference. Springer-Verlag Berlin Heidelberg.

A. Maccione, M.H. Hennig, M. Gandolfo, O. Muthmann, J. van Copenhagen, S.J. Eglen, L. Berdondini and E. Sernagor (2014). Following the Ontogeny of Retinal Waves: Pan-Retinal Recordings of Population Dynamics in the Neonatal Mouse. Journal of Physiology, 592, 1545-1563.

M.H. Hennig (2013). Theoretical models of synaptic short term plasticity. Frontiers in Computational Neuroscience, 7, 45.

E. Sernagor and M.H. Hennig (2013). Retinal Waves: Underlying Cellular Mechanisms and Theoretical Considerations. In: Comprehensive Developmental Neuroscience: Cellular Migration and Formation of Neuronal Connections, J. Rubenstein, P. Rakic, eds, San Diego: Academic Press. Preprint

C. Kopp-Scheinpflug, A.J.B. Tozer, S.W. Robinson, B.L. Tempel, M.H. Hennig and I.D. Forsythe (2011). The Sound of Silence: ionic mechanisms encoding sound termination. Neuron, 71, 911-925. Model code (on ModelDB)

M.H. Hennig, J. Grady, J. van Coppenhagen and E. Sernagor (2011). Age-dependent homeostatic plasticity of GABAergic signaling in developing retinal networks. Journal of Neuroscience, 31(34): 12159-12164. Preprint Experimental data

A. Karcz, M.H. Hennig, B.L. Tempel, R. Rübsamen R and C. Kopp-Scheinpflug (2011). Low-voltage activated Kv1.1 subunits are crucial for the processing of sound source location in the lateral superior olive in mice. Journal of Physiology, 589:1143-1157.

E. Sernagor, A. Maccione, M.H. Hennig, M. Gandolfo, S.J. Eglen, L. Berdondini (2010). Changing dynamics of spontaneous waves during retinal development: a novel panretinal perspective achieved with the Active Pixel Sensor (APS) 4,096 electrodes array. 7th Int. Meeting on Substrate-Integrated Microelectrodes. Stuttgart: BIOPRO Baden-Würtemberg GmbH.

M.H. Hennig, C.Adams, D. Willshaw and E. Sernagor (2009). Early-stage waves in the retinal network emerge close to a critical state transition between local and global functional connectivity. Journal of Neuroscience, 29:1077-1086.

Z. Yang, M.H. Hennig, M. Postlethwaite, I.D. Forsythe and B.P. Graham (2009).Wide-band information transmission at the calyx of Held. Neural Computation, 21: 991-1017. Code

M.H. Hennig, M. Postlethwaite, I.D. Forsythe and B.P. Graham (2008). Interactions between multiple sources of short term plasticity during evoked and spontaneous activity at the rat calyx of Held. Journal of Physiology, 13: 3129-3146. Code

M.H. Hennig and F. Wörgötter (2007). Effects of fixational eye movements on retinal ganglion cell responses: a modelling study. Frontiers in Computational Neuroscience, 1:2.

M. Postlethwaite, M.H. Hennig, J.R. Steinert, B.P. Graham and I.D. Forsythe (2007). Acceleration of AMPA receptor kinetics underlies temperature- dependent changes in synaptic strength at the rat calyx of Held. Journal of Physiology, 579:69-84. Code

M.H. Hennig, M. Postlethwaite, I.D. Forsythe and B.P. Graham (2007). A biophysical model of short-term plasticity at the calyx of Held. Neurocomputing, 70:1626-1629.

M.H. Hennig and F. Wörgötter (2004). Eye micro-movements improve stimulus detection beyond the Nyquist limit in the peripheral retina. In Advances in Neural Information Processing Systems 16, MIT Press.

M.H. Hennig, K. Funke and F. Wörgötter (2002). The influence of different retinal subcircuits on the nonlinearity of ganglion cell behavior. Journal of Neuroscience, 22:8726-8738.

M.H. Hennig, N.J. Kerscher, K. Funke and F. Wörgötter (2002). Stochastic resonance in visual cortical neurons: does the eye-tremor actually improve visual acuity? Neurocomputing, 44:115-120.

M.H. Hennig and K. Funke (2001). A biophysically realistic simulation of the vertebrate retina. Neurocomputing, 38:659-665.