Publications by authors named "Richard Kempter"

58 Publications

Hebbian plasticity in parallel synaptic pathways: A circuit mechanism for systems memory consolidation.

PLoS Comput Biol 2021 12 7;17(12):e1009681. Epub 2021 Dec 7.

Department of Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

Systems memory consolidation involves the transfer of memories across brain regions and the transformation of memory content. For example, declarative memories that transiently depend on the hippocampal formation are transformed into long-term memory traces in neocortical networks, and procedural memories are transformed within cortico-striatal networks. These consolidation processes are thought to rely on replay and repetition of recently acquired memories, but the cellular and network mechanisms that mediate the changes of memories are poorly understood. Here, we suggest that systems memory consolidation could arise from Hebbian plasticity in networks with parallel synaptic pathways-two ubiquitous features of neural circuits in the brain. We explore this hypothesis in the context of hippocampus-dependent memories. Using computational models and mathematical analyses, we illustrate how memories are transferred across circuits and discuss why their representations could change. The analyses suggest that Hebbian plasticity mediates consolidation by transferring a linear approximation of a previously acquired memory into a parallel pathway. Our modelling results are further in quantitative agreement with lesion studies in rodents. Moreover, a hierarchical iteration of the mechanism yields power-law forgetting-as observed in psychophysical studies in humans. The predicted circuit mechanism thus bridges spatial scales from single cells to cortical areas and time scales from milliseconds to years.
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http://dx.doi.org/10.1371/journal.pcbi.1009681DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8683039PMC
December 2021

A neural code for egocentric spatial maps in the human medial temporal lobe.

Neuron 2021 09 14;109(17):2781-2796.e10. Epub 2021 Jul 14.

Department of Biomedical Engineering, Columbia University, New York, NY, USA.

Spatial navigation and memory rely on neural systems that encode places, distances, and directions in relation to the external world or relative to the navigating organism. Place, grid, and head-direction cells form key units of world-referenced, allocentric cognitive maps, but the neural basis of self-centered, egocentric representations remains poorly understood. Here, we used human single-neuron recordings during virtual spatial navigation tasks to identify neurons providing a neural code for egocentric spatial maps in the human brain. Consistent with previous observations in rodents, these neurons represented egocentric bearings toward reference points positioned throughout the environment. Egocentric bearing cells were abundant in the parahippocampal cortex and supported vectorial representations of egocentric space by also encoding distances toward reference points. Beyond navigation, the observed neurons showed activity increases during spatial and episodic memory recall, suggesting that egocentric bearing cells are not only relevant for navigation but also play a role in human memory.
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http://dx.doi.org/10.1016/j.neuron.2021.06.019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8518022PMC
September 2021

Microcircuits for spatial coding in the medial entorhinal cortex.

Physiol Rev 2022 04 13;102(2):653-688. Epub 2021 Jul 13.

German Center for Neurodegenerative Diseases (DZNE) Berlin, Berlin, Germany.

The hippocampal formation is critically involved in learning and memory and contains a large proportion of neurons encoding aspects of the organism's spatial surroundings. In the medial entorhinal cortex (MEC), this includes grid cells with their distinctive hexagonal firing fields as well as a host of other functionally defined cell types including head direction cells, speed cells, border cells, and object-vector cells. Such spatial coding emerges from the processing of external inputs by local microcircuits. However, it remains unclear exactly how local microcircuits and their dynamics within the MEC contribute to spatial discharge patterns. In this review we focus on recent investigations of intrinsic MEC connectivity, which have started to describe and quantify both excitatory and inhibitory wiring in the superficial layers of the MEC. Although the picture is far from complete, it appears that these layers contain robust recurrent connectivity that could sustain the attractor dynamics posited to underlie grid pattern formation. These findings pave the way to a deeper understanding of the mechanisms underlying spatial navigation and memory.
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http://dx.doi.org/10.1152/physrev.00042.2020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759973PMC
April 2022

Synaptic learning rules for sequence learning.

Elife 2021 04 16;10. Epub 2021 Apr 16.

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

Remembering the temporal order of a sequence of events is a task easily performed by humans in everyday life, but the underlying neuronal mechanisms are unclear. This problem is particularly intriguing as human behavior often proceeds on a time scale of seconds, which is in stark contrast to the much faster millisecond time-scale of neuronal processing in our brains. One long-held hypothesis in sequence learning suggests that a particular temporal fine-structure of neuronal activity - termed 'phase precession' - enables the compression of slow behavioral sequences down to the fast time scale of the induction of synaptic plasticity. Using mathematical analysis and computer simulations, we find that - for short enough synaptic learning windows - phase precession can improve temporal-order learning tremendously and that the asymmetric part of the synaptic learning window is essential for temporal-order learning. To test these predictions, we suggest experiments that selectively alter phase precession or the learning window and evaluate memory of temporal order.
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http://dx.doi.org/10.7554/eLife.67171DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175084PMC
April 2021

Recurrent amplification of grid-cell activity.

Hippocampus 2020 12 6;30(12):1268-1297. Epub 2020 Oct 6.

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

High-level cognitive abilities such as navigation and spatial memory are thought to rely on the activity of grid cells in the medial entorhinal cortex (MEC), which encode the animal's position in space with periodic triangular patterns. Yet the neural mechanisms that underlie grid-cell activity are still unknown. Recent in vitro and in vivo experiments indicate that grid cells are embedded in highly structured recurrent networks. But how could recurrent connectivity become structured during development? And what is the functional role of these connections? With mathematical modeling and simulations, we show that recurrent circuits in the MEC could emerge under the supervision of weakly grid-tuned feedforward inputs. We demonstrate that a learned excitatory connectivity could amplify grid patterns when the feedforward sensory inputs are available and sustain attractor states when the sensory cues are lost. Finally, we propose a Fourier-based measure to quantify the spatial periodicity of grid patterns: the grid-tuning index.
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http://dx.doi.org/10.1002/hipo.23254DOI Listing
December 2020

Generation of Sharp Wave-Ripple Events by Disinhibition.

J Neurosci 2020 10 10;40(41):7811-7836. Epub 2020 Sep 10.

Department of Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, 10115, Germany

Sharp wave-ripple complexes (SWRs) are hippocampal network phenomena involved in memory consolidation. To date, the mechanisms underlying their occurrence remain obscure. Here, we show how the interactions between pyramidal cells, parvalbumin-positive (PV) basket cells, and an unidentified class of anti-SWR interneurons can contribute to the initiation and termination of SWRs. Using a biophysically constrained model of a network of spiking neurons and a rate-model approximation, we demonstrate that SWRs emerge as a result of the competition between two interneuron populations and the resulting disinhibition of pyramidal cells. Our models explain how the activation of pyramidal cells or PV cells can trigger SWRs, as shown , and suggests that PV cell-mediated short-term synaptic depression influences the experimentally reported dynamics of SWR events. Furthermore, we predict that the silencing of anti-SWR interneurons can trigger SWRs. These results broaden our understanding of the microcircuits supporting the generation of memory-related network dynamics. The hippocampus is a part of the mammalian brain that is crucial for episodic memories. During periods of sleep and inactive waking, the extracellular activity of the hippocampus is dominated by sharp wave-ripple events (SWRs), which have been shown to be important for memory consolidation. The mechanisms regulating the emergence of these events are still unclear. We developed a computational model to study the emergence of SWRs and to explain the roles of different cell types in regulating them. The model accounts for several previously unexplained features of SWRs and thus advances the understanding of memory-related dynamics.
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http://dx.doi.org/10.1523/JNEUROSCI.2174-19.2020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7548694PMC
October 2020

Propofol Modulates Early Memory Consolidation in Humans.

eNeuro 2020 May/Jun;7(3). Epub 2020 Jun 19.

Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin D-13353, Germany

Maintenance of memory across time is crucial for adaptive behavior. Current theories posit that the underlying consolidation process depends on stabilization of synapses and reorganization of interactions between hippocampus and neocortex. However, the temporal properties of hippocampal-neocortical network reconfiguration during consolidation are still a matter of debate. Translational research on this issue is challenged by the paucity of techniques to transiently interfere with memory in the healthy human brain. Here, we report a neuro-pharmacological approach with the GABAergic anesthetic propofol and a memory task sensitive to hippocampal dysfunction. Patients undergoing minor surgery learned word lists before injection of an anesthetic dose of propofol. Results show that administration of the drug shortly after learning (∼13 min) impairs recall after awakening but spares recognition. By contrast, later administration (∼105 min) has no effect. These findings suggest significant changes in memory networks very early after learning that are decisive for later recall. Propofol general anesthesia provides an experimental tool to modulate the first steps of hippocampus-mediated memory consolidation in humans.
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http://dx.doi.org/10.1523/ENEURO.0537-19.2020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7307630PMC
June 2021

Spikelets in pyramidal neurons: generating mechanisms, distinguishing properties, and functional implications.

Rev Neurosci 2019 12;31(1):101-119

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, D-10115 Berlin, Germany.

Spikelets are small spike-like depolarizations that are found in somatic recordings of many neuron types. Spikelets have been assigned important functions, ranging from neuronal synchronization to the regulation of synaptic plasticity, which are specific to the particular mechanism of spikelet generation. As spikelets reflect spiking activity in neuronal compartments that are electrotonically distinct from the soma, four modes of spikelet generation can be envisaged: (1) dendritic spikes or (2) axonal action potentials occurring in a single cell as well as action potentials transmitted via (3) gap junctions or (4) ephaptic coupling in pairs of neurons. In one of the best studied neuron type, cortical pyramidal neurons, the origins and functions of spikelets are still unresolved; all four potential mechanisms have been proposed, but the experimental evidence remains ambiguous. Here we attempt to reconcile the scattered experimental findings in a coherent theoretical framework. We review in detail the various mechanisms that can give rise to spikelets. For each mechanism, we present the biophysical underpinnings as well as the resulting properties of spikelets and compare these predictions to experimental data from pyramidal neurons. We also discuss the functional implications of each mechanism. On the example of pyramidal neurons, we illustrate that several independent spikelet-generating mechanisms fulfilling vastly different functions might be operating in a single cell.
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http://dx.doi.org/10.1515/revneuro-2019-0044DOI Listing
December 2019

Auditory brainstem response wave III is correlated with extracellular field potentials from nucleus laminaris of the barn owl.

Acta Acust United Acust 2018 Sep-Oct;104(5):874-877

Department of Biology, University of Maryland, College Park MD 20742, USA.

The auditory brainstem response (ABR) is generated in the auditory brainstem by local current sources, which also give rise to extracellular field potentials (EFPs). The origins of both the ABR and the EFP are not well understood. We have recently found that EFPs, especially their dipole behavior, may be dominated by the branching patterns and the activity of axonal terminal zones [1]. To test the hypothesis that axons also shape the ABR, we used the well-described barn owl early auditory system. We recorded the ABR and a series of EFPs between the brain surface and nucleus laminaris (NL) in response to binaural clicks. The ABR and the EFP within and around NL are correlated. Together, our data suggest that axonal dipoles within the barn owl nucleus laminaris contribute to the ABR wave III.
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http://dx.doi.org/10.3813/AAA.919236DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6455957PMC
April 2019

Dynamics of synaptic extracellular field potentials in the nucleus laminaris of the barn owl.

J Neurophysiol 2019 03 21;121(3):1034-1047. Epub 2018 Dec 21.

Bernstein Center for Computational Neuroscience , Berlin , Germany.

Synaptic currents are frequently assumed to make a major contribution to the extracellular field potential (EFP). However, in any neuronal population, the explicit separation of synaptic sources from other contributions such as postsynaptic spikes remains a challenge. Here we take advantage of the simple organization of the barn owl nucleus laminaris (NL) in the auditory brain stem to isolate synaptic currents through the iontophoretic application of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-receptor antagonist 1,2,3,4-tetrahydro-6-nitro-2,3-dioxo-benzo[ f]quinoxaline-7-sulfonamide (NBQX). Responses to auditory stimulation show that the temporal dynamics of the evoked synaptic contributions to the EFP are consistent with synaptic short-term depression (STD). The estimated time constants of an STD model fitted to the data are similar to the fast time constants reported from in vitro experiments in the chick. Overall, the putative synaptic EFPs in the barn owl NL are significant but small (<1% change of the variance by NBQX). This result supports the hypothesis that the EFP in NL is generated mainly by axonal spikes, in contrast to most other neuronal systems. NEW & NOTEWORTHY Synaptic currents are assumed to make a major contribution to the extracellular field potential in the brain, but it is hard to directly isolate these synaptic components. Here we take advantage of the simple organization of the barn owl nucleus laminaris in the auditory brain stem to isolate synaptic currents through the iontophoretic application of a synaptic blocker. We show that the responses are consistent with a simple model of short-term synaptic depression.
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http://dx.doi.org/10.1152/jn.00648.2017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6520630PMC
March 2019

Interneuronal gap junctions increase synchrony and robustness of hippocampal ripple oscillations.

Eur J Neurosci 2018 12;48(12):3446-3465

Department of Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

Sharp wave-ripples (SWRs) are important for memory consolidation. Their signature in the hippocampal extracellular field potential can be decomposed into a ≈100 ms long sharp wave superimposed by ≈200 Hz ripple oscillations. How ripple oscillations are generated is currently not well understood. A promising model for the genesis of ripple oscillations is based on recurrent interneuronal networks (INT-INT). According to this hypothesis, the INT-INT network in CA1 receives a burst of excitation from CA3 that generates the sharp wave, and recurrent inhibition leads to an ultrafast synchronization of the CA1 network causing the ripple oscillations; fast-spiking parvalbumin-positive basket cells (PV  BCs) may constitute the ripple-generating interneuronal network. PV  BCs are also coupled by gap junctions (GJs) but the function of GJs for ripple oscillations has not been quantified. Using simulations of CA1 hippocampal networks of PV  BCs, we show that GJs promote synchrony beyond a level that could be obtained by only inhibition. GJs also increase the neuronal firing rate of the interneuronal ensemble, while they affect the ripple frequency only mildly. The promoting effect of GJs on ripple oscillations depends on fast GJ transmission ( 0.5 ms), which requires proximal GJ coupling ( 100 μm from soma), but is robust to variability in the delay and the amplitude of GJ coupling.
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http://dx.doi.org/10.1111/ejn.14267DOI Listing
December 2018

Extracellular waveforms reveal an axonal origin of spikelets in pyramidal neurons.

J Neurophysiol 2018 10 27;120(4):1484-1495. Epub 2018 Jun 27.

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin , Germany.

Spikelets are small spike-like membrane depolarizations measured at the soma whose origin in pyramidal neurons is still unresolved. We investigated the mechanism of spikelet generation using detailed models of pyramidal neurons. We simulated extracellular waveforms associated with action potentials and spikelets and compared these with experimental data obtained by Chorev and Brecht ( J Neurophysiol 108: 1584-1593, 2012) from hippocampal pyramidal neurons in vivo. We considered spikelets originating in the axon of a single cell as well as spikelets generated in two cells coupled with gap junctions. We found that in both cases the experimental data can be explained by an axonal origin of spikelets: in the single-cell case, action potentials are generated in the axon but fail to activate the soma. Such spikelets can be evoked by dendritic input. Alternatively, spikelets resulting from axoaxonal gap junction coupling with a large (greater than several hundred μm) distance between the somata of the coupled cells are also consistent with the data. Our results demonstrate that a cell firing a somatic spikelet generates a detectable extracellular potential that is different from the action potential-correlated extracellular waveform generated by the same cell and recorded at the same location. This, together with the absence of a refractory period between action potentials and spikelets, implies that spikelets and action potentials generated in one cell may easily get misclassified in extracellular recordings as two different cells, albeit they both constitute the output of a single pyramidal neuron. NEW & NOTEWORTHY We addressed the origin of spikelets, using compartmental models of pyramidal neurons. Comparing our simulation results with published extracellular spikelet recordings revealed an axonal origin of spikelets. Our results imply that action potential- and spikelet-associated extracellular waveforms may easily get misclassified as two different cells, albeit they both constitute the output of a single pyramidal cell.
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http://dx.doi.org/10.1152/jn.00463.2017DOI Listing
October 2018

Hippocampal Ripple Oscillations and Inhibition-First Network Models: Frequency Dynamics and Response to GABA Modulators.

J Neurosci 2018 03 16;38(12):3124-3146. Epub 2018 Feb 16.

Humboldt-Universität zu Berlin, Department of Biology, Institute for Theoretical Biology, 10115 Berlin, Germany,

Hippocampal ripples are involved in memory consolidation, but the mechanisms underlying their generation remain unclear. Models relying on interneuron networks in the CA1 region disagree on the predominant source of excitation to interneurons: either "direct," via the Schaffer collaterals that provide feedforward input from CA3 to CA1, or "indirect," via the local pyramidal cells in CA1, which are embedded in a recurrent excitatory-inhibitory network. Here, we used physiologically constrained computational models of basket-cell networks to investigate how they respond to different conditions of transient, noisy excitation. We found that direct excitation of interneurons could evoke ripples (140-220 Hz) that exhibited intraripple frequency accommodation and were frequency-insensitive to GABA modulators, as previously shown in experiments. In addition, the indirect excitation of the basket-cell network enabled the expression of intraripple frequency accommodation in the fast-gamma range (90-140 Hz), as In our model, intraripple frequency accommodation results from a hysteresis phenomenon in which the frequency responds differentially to the rising and descending phases of the transient excitation. Such a phenomenon predicts a maximum oscillation frequency occurring several milliseconds before the peak of excitation. We confirmed this prediction for ripples in brain slices from male mice. These results suggest that ripple and fast-gamma episodes are produced by the same interneuron network that is recruited via different excitatory input pathways, which could be supported by the previously reported intralaminar connectivity bias between basket cells and functionally distinct subpopulations of pyramidal cells in CA1. Together, our findings unify competing inhibition-first models of rhythm generation in the hippocampus. The hippocampus is a part of the brain of humans and other mammals that is critical for the acquisition and consolidation of memories. During deep sleep and resting periods, the hippocampus generates high-frequency (∼200 Hz) oscillations called ripples, which are important for memory consolidation. The mechanisms underlying ripple generation are not well understood. A prominent hypothesis holds that the ripples are generated by local recurrent networks of inhibitory neurons. Using computational models and experiments in brain slices from rodents, we show that the dynamics of interneuron networks clarify several previously unexplained characteristics of ripple oscillations, which advances our understanding of hippocampus-dependent memory consolidation.
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http://dx.doi.org/10.1523/JNEUROSCI.0188-17.2018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6596071PMC
March 2018

Contribution of action potentials to the extracellular field potential in the nucleus laminaris of barn owl.

J Neurophysiol 2018 04 20;119(4):1422-1436. Epub 2017 Dec 20.

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

Extracellular field potentials (EFP) are widely used to evaluate in vivo neural activity, but identification of multiple sources and their relative contributions is often ambiguous, making the interpretation of the EFP difficult. We have therefore analyzed a model EFP from a simple brainstem circuit with separable pre- and postsynaptic components to determine whether we could isolate its sources. Our previous papers had shown that the barn owl neurophonic largely originates with spikes from input axons and synapses that terminate on the neurons in the nucleus laminaris (NL) (Kuokkanen PT, Wagner H, Ashida G, Carr CE, Kempter R. J Neurophysiol 104: 2274-2290, 2010; Kuokkanen PT, Ashida G, Carr CE, Wagner H, Kempter R. J Neurophysiol 110: 117-130, 2013; McColgan T, Liu J, Kuokkanen PT, Carr CE, Wagner H, Kempter R. eLife 6: e26106, 2017). To determine how much the postsynaptic NL neurons contributed to the neurophonic, we recorded EFP responses in NL in vivo. Power spectral analyses showed that a small spectral component of the evoked response, between 200 and 700 Hz, could be attributed to the NL neurons' spikes, while nucleus magnocellularis (NM) spikes dominate the EFP at frequencies ≳1 kHz. Thus, spikes of NL neurons and NM axons contribute to the EFP in NL in distinct frequency bands. We conclude that if the spectral components of source types are different and if their activities can be selectively modulated, the identification of EFP sources is possible. NEW & NOTEWORTHY Extracellular field potentials (EFPs) generate clinically important signals, but their sources are incompletely understood. As a model, we have analyzed the auditory neurophonic in the barn owl's nucleus laminaris. There the EFP originates predominantly from spiking in the afferent axons, with spectral power ≳1 kHz, while postsynaptic laminaris neurons contribute little. In conclusion, the identification of EFP sources is possible if they have different spectral components and if their activities can be modulated selectively.
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http://dx.doi.org/10.1152/jn.00175.2017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5966727PMC
April 2018

A single-cell spiking model for the origin of grid-cell patterns.

PLoS Comput Biol 2017 Oct 2;13(10):e1005782. Epub 2017 Oct 2.

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity.
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http://dx.doi.org/10.1371/journal.pcbi.1005782DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5638623PMC
October 2017

Dipolar extracellular potentials generated by axonal projections.

Elife 2017 09 5;6. Epub 2017 Sep 5.

Department for Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

Extracellular field potentials (EFPs) are an important source of information in neuroscience, but their physiological basis is in many cases still a matter of debate. Axonal sources are typically discounted in modeling and data analysis because their contributions are assumed to be negligible. Here, we established experimentally and theoretically that contributions of axons to EFPs can be significant. Modeling action potentials propagating along axons, we showed that EFPs were prominent in the presence of terminal zones where axons branch and terminate in close succession, as found in many brain regions. Our models predicted a dipolar far field and a polarity reversal at the center of the terminal zone. We confirmed these predictions using EFPs from the barn owl auditory brainstem where we recorded in nucleus laminaris using a multielectrode array. These results demonstrate that axonal terminal zones can produce EFPs with considerable amplitude and spatial reach.
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http://dx.doi.org/10.7554/eLife.26106DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5617635PMC
September 2017

Refractoriness Accounts for Variable Spike Burst Responses in Somatosensory Cortex.

eNeuro 2017 Jul-Aug;4(4). Epub 2017 Aug 23.

Unité de Neurosciences Information et Complexité, Centre National de la Recherche Scientifique, Gif-sur-Yvette 91198, France.

Neurons in the primary somatosensory cortex (S1) respond to peripheral stimulation with synchronized bursts of spikes, which lock to the macroscopic 600-Hz EEG waves. The mechanism of burst generation and synchronization in S1 is not yet understood. Using models of single-neuron responses fitted to unit recordings from macaque monkeys, we show that these synchronized bursts are the consequence of correlated synaptic inputs combined with a refractory mechanism. In the presence of noise these models reproduce also the observed trial-to-trial response variability, where individual bursts represent one of many stereotypical temporal spike patterns. When additional slower and global excitability fluctuations are introduced the single-neuron spike patterns are correlated with the population activity, as demonstrated in experimental data. The underlying biophysical mechanism of S1 responses involves thalamic inputs arriving through depressing synapses to cortical neurons in a high-conductance state. Our findings show that a simple feedforward processing of peripheral inputs could give rise to neuronal responses with nontrivial temporal and population statistics. We conclude that neural systems could use refractoriness to encode variable cortical states into stereotypical short-term spike patterns amenable to processing at neuronal time scales (tens of milliseconds).
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http://dx.doi.org/10.1523/ENEURO.0173-17.2017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5566798PMC
September 2018

Excitatory Microcircuits within Superficial Layers of the Medial Entorhinal Cortex.

Cell Rep 2017 05;19(6):1110-1116

Neuroscience Research Center, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany; Berlin Institute of Health, 10117 Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, 10115 Berlin, Germany; Cluster of Excellence NeuroCure, 10117 Berlin, Germany; Center for Neurodegenerative Diseases Berlin, 10117 Berlin, Germany. Electronic address:

The distinctive firing pattern of grid cells in the medial entorhinal cortex (MEC) supports its role in the representation of space. It is widely believed that the hexagonal firing field of grid cells emerges from neural dynamics that depend on the local microcircuitry. However, local networks within the MEC are still not sufficiently characterized. Here, applying up to eight simultaneous whole-cell recordings in acute brain slices, we demonstrate the existence of unitary excitatory connections between principal neurons in the superficial layers of the MEC. In particular, we find prevalent feed-forward excitation from pyramidal neurons in layer III and layer II onto stellate cells in layer II, which might contribute to the generation or the inheritance of grid cell patterns.
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http://dx.doi.org/10.1016/j.celrep.2017.04.041DOI Listing
May 2017

Phase precession: a neural code underlying episodic memory?

Curr Opin Neurobiol 2017 04 6;43:130-138. Epub 2017 Apr 6.

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Philippstr. 13, 10115 Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, Philippstr. 13, 10115 Berlin, Germany. Electronic address:

In the hippocampal formation, the sequential activation of place-specific cells represents a conceptual model for the spatio-temporal events that assemble episodic memories. The imprinting of behavioral sequences in hippocampal networks might be achieved via spike-timing-dependent plasticity and phase precession of the spiking activity of neurons. It is unclear, however, whether phase precession plays an active role by enabling sequence learning via synaptic plasticity or whether phase precession passively reflects retrieval dynamics. Here we examine these possibilities in the context of potential mechanisms generating phase precession. Knowledge of these mechanisms would allow to selectively alter phase precession and test its role in episodic memory. We finally review the few successful approaches to degrade phase precession and the resulting impact on behavior.
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http://dx.doi.org/10.1016/j.conb.2017.02.006DOI Listing
April 2017

Memory replay in balanced recurrent networks.

PLoS Comput Biol 2017 01 30;13(1):e1005359. Epub 2017 Jan 30.

Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

Complex patterns of neural activity appear during up-states in the neocortex and sharp waves in the hippocampus, including sequences that resemble those during prior behavioral experience. The mechanisms underlying this replay are not well understood. How can small synaptic footprints engraved by experience control large-scale network activity during memory retrieval and consolidation? We hypothesize that sparse and weak synaptic connectivity between Hebbian assemblies are boosted by pre-existing recurrent connectivity within them. To investigate this idea, we connect sequences of assemblies in randomly connected spiking neuronal networks with a balance of excitation and inhibition. Simulations and analytical calculations show that recurrent connections within assemblies allow for a fast amplification of signals that indeed reduces the required number of inter-assembly connections. Replay can be evoked by small sensory-like cues or emerge spontaneously by activity fluctuations. Global-potentially neuromodulatory-alterations of neuronal excitability can switch between network states that favor retrieval and consolidation.
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http://dx.doi.org/10.1371/journal.pcbi.1005359DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5305273PMC
January 2017

Spikelets in Pyramidal Neurons: Action Potentials Initiated in the Axon Initial Segment That Do Not Activate the Soma.

PLoS Comput Biol 2017 01 9;13(1):e1005237. Epub 2017 Jan 9.

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

Spikelets are small spike-like depolarizations that can be measured in somatic intracellular recordings. Their origin in pyramidal neurons remains controversial. To explain spikelet generation, we propose a novel single-cell mechanism: somato-dendritic input generates action potentials at the axon initial segment that may fail to activate the soma and manifest as somatic spikelets. Using mathematical analysis and numerical simulations of compartmental neuron models, we identified four key factors controlling spikelet generation: (1) difference in firing threshold, (2) impedance mismatch, and (3) electrotonic separation between the soma and the axon initial segment, as well as (4) input amplitude. Because spikelets involve forward propagation of action potentials along the axon while they avoid full depolarization of the somato-dendritic compartments, we conjecture that this mode of operation saves energy and regulates dendritic plasticity while still allowing for a read-out of results of neuronal computations.
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http://dx.doi.org/10.1371/journal.pcbi.1005237DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5221759PMC
January 2017

Early Cortical Changes in Gamma Oscillations in Alzheimer's Disease.

Front Syst Neurosci 2016 26;10:83. Epub 2016 Oct 26.

Neuroscience Research Center, Charité UniversityBerlin, Germany; DZNE - German Center for Neurodegenerative DiseasesBerlin, Germany; Berlin Institute of HealthBerlin, Germany.

The entorhinal cortices in the temporal lobe of the brain are key structures relaying memory related information between the neocortex and the hippocampus. The medial entorhinal cortex (MEC) routes spatial information, whereas the lateral entorhinal cortex (LEC) routes predominantly olfactory information to the hippocampus. Gamma oscillations are known to coordinate information transfer between brain regions by precisely timing population activity of neuronal ensembles. Here, we studied the organization of gamma oscillations in the MEC and LEC of the transgenic (tg) amyloid precursor protein (APP)-presenilin 1 (PS1) mouse model of Alzheimer's Disease (AD) at 4-5 months of age. gamma oscillations using the kainate model peaked between 30-50 Hz and therefore we analyzed the oscillatory properties in the 20-60 Hz range. Our results indicate that the LEC shows clear alterations in frequency and power of gamma oscillations at an early stage of AD as compared to the MEC. The gamma-frequency oscillation slows down in the LEC and also the gamma power in dorsal LEC is decreased as early as 4-5 months in the tg APP-PS1 mice. The results of this study suggest that the timing of olfactory inputs from LEC to the hippocampus might be affected at an early stage of AD, resulting in a possible erroneous integration of the information carried by the two input pathways to the hippocampal subfields.
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http://dx.doi.org/10.3389/fnsys.2016.00083DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5080538PMC
October 2016

Cell Type-Specific Differences in Spike Timing and Spike Shape in the Rat Parasubiculum and Superficial Medial Entorhinal Cortex.

Cell Rep 2016 07 14;16(4):1005-1015. Epub 2016 Jul 14.

Bernstein Center for Computational Neuroscience, Humboldt Universität zu Berlin, Philippstr. 13, Haus 6, 10115 Berlin, Germany. Electronic address:

The medial entorhinal cortex (MEC) and the adjacent parasubiculum are known for their elaborate spatial discharges (grid cells, border cells, etc.) and the precessing of spikes relative to the local field potential. We know little, however, about how spatio-temporal firing patterns map onto cell types. We find that cell type is a major determinant of spatio-temporal discharge properties. Parasubicular neurons and MEC layer 2 (L2) pyramids have shorter spikes, discharge spikes in bursts, and are theta-modulated (rhythmic, locking, skipping), but spikes phase-precess only weakly. MEC L2 stellates and layer 3 (L3) neurons have longer spikes, do not discharge in bursts, and are weakly theta-modulated (non-rhythmic, weakly locking, rarely skipping), but spikes steeply phase-precess. The similarities between MEC L3 neurons and MEC L2 stellates on one hand and parasubicular neurons and MEC L2 pyramids on the other hand suggest two distinct streams of temporal coding in the parahippocampal cortex.
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http://dx.doi.org/10.1016/j.celrep.2016.06.057DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967475PMC
July 2016

The Role of Conduction Delay in Creating Sensitivity to Interaural Time Differences.

Adv Exp Med Biol 2016 ;894:189-196

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

Axons from the nucleus magnocellularis (NM) and their targets in nucleus laminaris (NL) form the circuit responsible for encoding interaural time difference (ITD). In barn owls, NL receives bilateral inputs from NM, such that axons from the ipsilateral NM enter NL dorsally, while contralateral axons enter from the ventral side. These afferents act as delay lines to create maps of ITD in NL. Since delay-line inputs are characterized by a precise latency to auditory stimulation, but the postsynaptic coincidence detectors respond to ongoing phase difference, we asked whether the latencies of a local group of axons were identical, or varied by multiples of the inverse of the frequency they respond to, i.e., to multiples of 2π phase. Intracellular recordings from NM axons were used to measure delay-line latencies in NL. Systematic shifts in conduction delay within NL accounted for the maps of ITD, but recorded latencies of individual inputs at nearby locations could vary by 2π or 4π. Therefore microsecond precision is achieved through sensitivity to phase delays, rather than absolute latencies. We propose that the auditory system "coarsely" matches ipsilateral and contralateral latencies using physical delay lines, so that inputs arrive at NL at about the same time, and then "finely" matches latency modulo 2π to achieve microsecond ITD precision.
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http://dx.doi.org/10.1007/978-3-319-25474-6_20DOI Listing
September 2016

Cell-Type Specific Phase Precession in Layer II of the Medial Entorhinal Cortex.

J Neurosci 2016 Feb;36(7):2283-8

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany, Bernstein Center for Computational Neuroscience Berlin, 10115 Berlin, Germany, and.

The identity of phase-precessing cells in the entorhinal cortex is unknown. Here, we used a classifier derived from cell-attached recordings to separate putative pyramidal cells and putative stellate cells recorded extracellularly in layer II of the medial entorhinal cortex in rats. Using a novel method to identify single runs as temporal periods of elevated spiking activity, we find that both cell types show phase precession but putative stellate cells show steeper slopes of phase precession and larger phase ranges. As the two classes of cells have different projection patterns, phase precession is differentially passed on to different subregions of the hippocampal formation.

Significance Statement: It is a great challenge for neuroscience to reveal the cellular basis of cognitive functions. One such function is the ability to learn and recollect temporal sequences of events. The representation of sequences in the brain is thought to require temporally structured activity of nerve cells. How different types of neurons generate temporally structured activity is currently unknown. In the present study, we use a computational classification procedure to separate different cell types and find that a subpopulation of cells, so-called stellate neurons, exhibits clear temporal coding. Contrary to the stellate cells, pyramidal cells show weaker temporal coding. This discovery sheds light on the cellular basis of temporal coding in the brain.
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http://dx.doi.org/10.1523/JNEUROSCI.2986-15.2016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602039PMC
February 2016

Maps of interaural delay in the owl's nucleus laminaris.

J Neurophysiol 2015 Sep 29;114(3):1862-73. Epub 2015 Jul 29.

Institute for Biology II, RWTH Aachen, Aachen, Germany; and.

Axons from the nucleus magnocellularis form a presynaptic map of interaural time differences (ITDs) in the nucleus laminaris (NL). These inputs generate a field potential that varies systematically with recording position and can be used to measure the map of ITDs. In the barn owl, the representation of best ITD shifts with mediolateral position in NL, so as to form continuous, smoothly overlapping maps of ITD with iso-ITD contours that are not parallel to the NL border. Frontal space (0°) is, however, represented throughout and thus overrepresented with respect to the periphery. Measurements of presynaptic conduction delay, combined with a model of delay line conduction velocity, reveal that conduction delays can account for the mediolateral shifts in the map of ITD.
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http://dx.doi.org/10.1152/jn.00644.2015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575979PMC
September 2015

Inheritance of Hippocampal Place Fields Through Hebbian Learning: Effects of Theta Modulation and Phase Precession on Structure Formation.

Neural Comput 2015 Aug 16;27(8):1624-72. Epub 2015 Jun 16.

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany, and Bernstein Center for Computational Neuroscience Berlin, 10115 Berlin, Germany

A place cell is a neuron that fires whenever the animal traverses a particular location of the environment-the place field of the cell. Place cells are found in two regions of the rodent hippocampus: CA3 and CA1. Motivated by the anatomical connectivity between these two regions and by the evidence for synaptic plasticity at these connections, we study how a place field in CA1 can be inherited from an upstream region such as CA3 through a Hebbian learning rule, in particular, through spike-timing-dependent plasticity (STDP). To this end, we model a population of CA3 place cells projecting to a single CA1 cell, and we assume that the CA1 input synapses are plastic according to STDP. With both numerical and analytical methods, we show that in the case of overlapping CA3 input place fields, the STDP learning rule leads to the formation of a place field in CA1. We then investigate the roles of the hippocampal theta modulation and phase precession on the inheritance process. We find that theta modulation favors the inheritance and leads to faster place field formation whereas phase precession changes the drift of CA1 place fields over time.
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http://dx.doi.org/10.1162/NECO_a_00752DOI Listing
August 2015

State-dependencies of learning across brain scales.

Front Comput Neurosci 2015 26;9. Epub 2015 Feb 26.

Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; Department of Biology, Institute for Theoretical Biology (ITB), Humboldt-Universität zu Berlin Berlin, Germany.

Learning is a complex brain function operating on different time scales, from milliseconds to years, which induces enduring changes in brain dynamics. The brain also undergoes continuous "spontaneous" shifts in states, which, amongst others, are characterized by rhythmic activity of various frequencies. Besides the most obvious distinct modes of waking and sleep, wake-associated brain states comprise modulations of vigilance and attention. Recent findings show that certain brain states, particularly during sleep, are essential for learning and memory consolidation. Oscillatory activity plays a crucial role on several spatial scales, for example in plasticity at a synaptic level or in communication across brain areas. However, the underlying mechanisms and computational rules linking brain states and rhythms to learning, though relevant for our understanding of brain function and therapeutic approaches in brain disease, have not yet been elucidated. Here we review known mechanisms of how brain states mediate and modulate learning by their characteristic rhythmic signatures. To understand the critical interplay between brain states, brain rhythms, and learning processes, a wide range of experimental and theoretical work in animal models and human subjects from the single synapse to the large-scale cortical level needs to be integrated. By discussing results from experiments and theoretical approaches, we illuminate new avenues for utilizing neuronal learning mechanisms in developing tools and therapies, e.g., for stroke patients and to devise memory enhancement strategies for the elderly.
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http://dx.doi.org/10.3389/fncom.2015.00001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4341560PMC
March 2015

Correlates of a single cortical action potential in the epidural EEG.

Neuroimage 2015 Apr 30;109:357-67. Epub 2014 Dec 30.

Neurophysics Group, Department of Neurology, Campus Benjamin Franklin, Charité-Universitätsmedizin Berlin, 12200 Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, 10115 Berlin, Germany; Bernstein Focus Neurotechnology Berlin, 10587 Berlin, Germany.

To identify the correlates of a single cortical action potential in surface EEG, we recorded simultaneously epidural EEG and single-unit activity in the primary somatosensory cortex of awake macaque monkeys. By averaging over EEG segments coincident with more than hundred thousand single spikes, we found short-lived (≈ 0.5 ms) triphasic EEG deflections dominated by high-frequency components >800 Hz. The peak-to-peak amplitude of the grand-averaged spike correlate was 80 nV, which matched theoretical predictions, while single-neuron amplitudes ranged from 12 to 966 nV. Combining these estimates with post-stimulus-time histograms of single-unit responses to median-nerve stimulation allowed us to predict the shape of the evoked epidural EEG response and to estimate the number of contributing neurons. These findings establish spiking activity of cortical neurons as a primary building block of high-frequency epidural EEG, which thus can serve as a quantitative macroscopic marker of neuronal spikes.
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http://dx.doi.org/10.1016/j.neuroimage.2014.12.057DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4349634PMC
April 2015

Movement dependence and layer specificity of entorhinal phase precession in two-dimensional environments.

PLoS One 2014 24;9(6):e100638. Epub 2014 Jun 24.

Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany and Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.

As a rat moves, grid cells in its entorhinal cortex (EC) discharge at multiple locations of the external world, and the firing fields of each grid cell span a hexagonal lattice. For movements on linear tracks, spikes tend to occur at successively earlier phases of the theta-band filtered local field potential during the traversal of a firing field - a phenomenon termed phase precession. The complex movement patterns observed in two-dimensional (2D) open-field environments may fundamentally alter phase precession. To study this question at the behaviorally relevant single-run level, we analyzed EC spike patterns as a function of the distance traveled by the rat along each trajectory. This analysis revealed that cells across all EC layers fire spikes that phase-precess; indeed, the rate and extent of phase precession were the same, only the correlation between spike phase and path length was weaker in EC layer III. Both slope and correlation of phase precession were surprisingly similar on linear tracks and in 2D open-field environments despite strong differences in the movement statistics, including running speed. While the phase-precession slope did not correlate with the average running speed, it did depend on specific properties of the animal's path. The longer a curving path through a grid-field in a 2D environment, the shallower was the rate of phase precession, while runs that grazed a grid field tangentially led to a steeper phase-precession slope than runs through the field center. Oscillatory interference models for grid cells do not reproduce the observed phenomena.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0100638PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4069107PMC
March 2015
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