Biology subjects

Jonas, P.

Publications and source records attributed to Jonas, P..

16 recordsLinked to original sources

bioRxiv2026

Cellular Determinants of CA1 Pyramidal Cell Recruitment during Sharp-Wave Ripples

Hippocampal ripples, accompanied by highly synchronous neuronal firing, are critical for immediate offline memory consolidation, learning, and planning. However, the cellular mechanisms that determine which individual neurons are recruited to participate in action potential (AP) firing during ripples remain unclear. We investigated the membrane potential (Vm) dynamics of CA1 pyramidal cells during ripples using whole-cell recordings in awake, head-fixed mice. We found that ripple participation was strongly associated with concurrent membrane-potential depolarization on an event-to-event basis, whereas between-cell differences in overall participation propensity were jointly explained by ripple-associated depolarization and intrinsic excitability. Applying this framework across CA1 cell populations revealed that differences in recruitment between superficial and deep pyramidal cells were primarily driven by ripple-associated depolarization, counteracted by excitability. Differences between place and non-place cells were similarly driven by ripple-associated depolarization, though this effect acted in the same direction as excitability. Finally, we identified the post-ripple LFP rebound as a prominent marker of ripple diversity linked to post-ripple membrane-potential hyperpolarization at the single-neuron level. Together, these findings provide a mechanistic understanding of how CA1 pyramidal cells are selectively recruited during hippocampal ripples.

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bioRxiv2026

Hippocampal CA3 forms a two-layer network of molecularly distinct cell types in mice and humans

Associational memory is critically dependent on the CA3 recurrent circuit, at the centre of the hippocampal system. While diversity amongst CA3 pyramidal neurons (PNs) has been long reported, the principles organising cell type identity and their consequences for circuit function remain unclear. Here, we demonstrate that deep-superficial is the primary axis of heterogeneity in CA3. PNs segregate into two molecularly distinct subtypes, superficial St18-, and deep St18+ neurons, with distinct anatomical, molecular, and functional properties. Using an St18-Cre mouse line, we reveal that these subtypes have divergent wiring patterns. Superficial neurons form the canonical broad autoassociative network across hemispheres and project to CA1, while deep St18+ PNs form a strikingly distinct, CA3-restricted, and predominantly unilateral projection -- a previously unrecognised circuit module embedded within the hippocampal associative network. This anatomical and molecular organisation is conserved across mammals, including mice, pigs, and humans, where patch-clamp recording in human tissue demonstrates conserved functional hallmarks of each PN subtype. Together, these findings fundamentally revise the hippocampal CA3 circuit map, revealing it as two highly distinct circuit elements and providing the molecular tools to dissect the contribution of each layer to hippocampal computation and cognition.

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bioRxiv2025

Cerebral Organoids Uncover Mechanisms of Neural Activity Changes in Epileptogenesis

Neurological disorders often originate from progressive brain network dysfunctions that start years before symptoms appear. How these changes emerge in the developing human brain remains elusive due to a lack of tractable model systems. Here, we show a cerebral organoid model of Tuberous Sclerosis Complex (TSC) that recapitulates hallmarks of epileptogenesis in vitro. We compare extracellular recordings of TSC organoids with intraoperative electrocorticography from TSC patients to reveal striking functional similarities, including high-frequency oscillations - an electrical biomarker for epileptogenic tissue. In TSC, a human-specific interneuron sub-type derived from the caudal ganglionic eminence drives network hyper-synchronization through increased spontaneous firing and altered excitability. Inhibiting overproliferation of its progenitors via long-term epidermal growth factor receptor inhibition prevented the onset of this pathological phenotype at functional and morphological levels. Our work shows that organoids allow mechanistic analysis of emerging neural network phenotypes, enabling anti-epileptogenic drug testing in a human brain development model.

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bioRxiv2024

Cell-specific wiring routes information flow through hippocampal CA3

The hippocampus is dogmatically described as a trisynaptic circuit. Dentate gyrus granule cells, CA3 pyramidal neurons (PNs), and CA1 PNs are serially connected, forming a circuit that critically enables memory storage in the brain. However, fundamental aspects of hippocampal function go beyond this simplistic trisynaptic definition. CA3 PNs connect not only to CA1, but also establish the largest autoassociative network in the brain. In addition, CA3 PNs are not uniform, differing in their morphology, intrinsic properties, and even the extent of granule cell input. Understanding how these different subtypes of CA3 PNs are embedded in the hippocampal network is essential for our quest to understand learning and memory. Here, we performed simultaneous multi-cellular patch-clamp recordings from up to eight CA3 PNs in acute mouse hippocampal slices, testing 3114 possible connections between identified cells. Combined with post-hoc morphological analysis, this allowed full characterization of neuronal heterogeneity in functioning microcircuits. We demonstrate that CA3 PNs can be divided into distinct deep and superficial subclasses, with altered input-output balance. While both subtypes formed recurrent connectivity within classes, connectivity between subtypes was surprisingly asymmetric. Recurrent connectivity was abundant from superficial to deep, but almost absent from deep to superficial PNs, thereby splitting CA3 into parallel recurrent networks which will allow more complex information processing. Finally, we observed innervation of PN subclasses by distinct interneurons, a potential mechanism to gate information flow through CA3 sublayers. Together, our data present a major revision to the classical trisynaptic view of the hippocampus, bringing us closer to understanding its complex action in information storage.

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bioRxiv2024

Human hippocampal CA3 uses specific functional connectivity rules for efficient associative memory

The human brain has remarkable computational power. It generates sophisticated behavioral sequences, stores engrams over an individuals lifetime, and produces higher cognitive functions up to the level of consciousness. However, so little of our neuroscience knowledge covers the human brain, and it remains unknown whether this organ is truly unique, or is a scaled version of the extensively studied rodent brain. To address this fundamental question, we determined the cellular, synaptic, and connectivity rules of the hippocampal CA3 recurrent circuit using multicellular patch clamp-recording. This circuit is the largest autoassociative network in the brain, and plays a key role in memory and higher-order computations such as pattern separation and pattern completion. We demonstrate that human hippocampal CA3 employs sparse connectivity, in stark contrast to neocortical recurrent networks. Connectivity sparsifies from rodents to humans, providing a circuit architecture that maximizes associational power. Unitary synaptic events at human CA3-CA3 synapses showed both distinct species-specific and circuit-dependent properties, with high reliability, unique amplitude precision, and long integration times. We also identify differential scaling rules between hippocampal pathways from rodents to humans, with a moderate increase in the convergence of CA3 inputs per cell, but a marked increase in human mossy fiber innervation. Anatomically guided full-scale modeling suggests that the human brains sparse connectivity, expanded neuronal number, and reliable synaptic signaling combine to enhance the associative memory storage capacity of CA3. Together, our results reveal unique rules of connectivity and synaptic signaling in the human hippocampus, demonstrating the absolute necessity of human brain research and beginning to unravel the remarkable performance of our autoassociative memory circuits.

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bioRxiv2023

Presynaptic cAMP-PKA-mediated potentiation induces reconfiguration of synaptic vesicle pools and channel-vesicle coupling at hippocampal mossy fiber boutons

It is widely believed that information storage in neuronal circuits involves nanoscopic structural changes at synapses, resulting in the formation of synaptic engrams. However, direct evidence for this hypothesis is lacking. To test this conjecture, we combined chemical potentiation, functional analysis by paired pre-postsynaptic recordings, and structural analysis by electron microscopy (EM) and freeze-fracture replica labeling (FRL) at the hippocampal mossy fiber synapse, a key synapse in the trisynaptic circuit of the hippocampus. Biophysical analysis of synaptic transmission revealed that forskolin-induced chemical potentiation increased the readily releasable vesicle pool size (RRP) and vesicular release probability (Pr) by 146% and 49%, respectively. Structural analysis of mossy fiber synapses by EM and FRL demonstrated an increase in the number of vesicles close to the plasma membrane and the number of clusters of the priming protein Munc13-1, indicating an increase in the number of both docked and primed vesicles. Furthermore, FRL analysis revealed a significant reduction of the nearest neighbor distance (NND) between Munc13-1 and CaV2.1 Ca2+ channels, suggesting reconfiguration of the channel-vesicle coupling nanotopography. Our results indicate that presynaptic plasticity is associated with structural reorganization of active zones (AZs). We propose that changes in potential nanoscopic organization at synaptic vesicle release sites may be correlates of learning and memory at a plastic central synapse.

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bioRxiv2022

A two-pool mechanism of vesicle release in medial habenula terminals underlies GABAB receptor-mediated potentiation

GABAB receptor (GBR) activation inhibits neurotransmitter release in axon terminals in the brain, except in medial habenula (MHb) terminals, which show robust potentiation. However, mechanisms underlying this enigmatic potentiation remain elusive. Here, we report that GBR activation induces a transition from tonic to phasic release accompanied by a 4-fold increase in readily releasable pool (RRP) size in MHb terminals, mirrored by a similar increase in the docked vesicle number at the presynaptic active zone (AZ). The tonic and phasic release vesicles have distinct coupling distances. We identified two vesicle-associated molecules, synaptoporin and CAPS2, selectively involved in tonic and phasic release, respectively. Synaptoporin mediates augmentation of tonic release and CAPS2 stabilizes readily releasable vesicles during phasic release. A newly developed "Flash and Freeze-fracture" method revealed selective recruitment of CAPS2 to the AZ during phasic release. Thus, we propose a novel two-pool mechanism underlying the GBR-mediated potentiation of release from MHb terminals.

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bioRxiv2022

Validation of a stereological method for estimating particle size and density from 2D projections with high accuracy

AO_SCPLOWBSTRACTC_SCPLOWStereological methods for estimating the 3D particle size and density from 2D projections are essential to many research fields. These methods are, however, prone to errors arising from undetected particle profiles due to sectioning and limited resolution, known as lost caps. A potential solution by Keiding et al. (1972) accounts for lost caps by quantifying the smallest detectable profiles in terms of their limiting section angle ({phi}). However, this simple solution has not been widely adopted nor validated. Rather, model-independent design-based stereological methods, which do not explicitly account for lost caps, have come to the fore. Here, we provide the first experimental validation of the Keiding model by quantifying {phi} of synaptic vesicles using electron-tomography 3D reconstructions. This analysis reveals a Gaussian distribution for {phi} rather than a single value. Nevertheless, curve fits of the Keiding model to the 2D diameter distribution accurately estimate the mean {phi} and 3D diameter distribution. While systematic testing using Monte Carlo simulations revealed an upper limit to determining {phi}, our analysis shows that mean {phi} can be used to estimate the 3D particle density from the 2D density under a wide range of conditions, and this method is potentially more accurate than minimum-size-based lost-cap corrections and disector methods. We applied the Keiding model to estimate the size and density of somata, nuclei and vesicles in rodent cerebella, where high packing density can be problematic for design-based methods.

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bioRxiv2022

Uncovering brain tissue architecture across scales with super-resolution light microscopy

Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanoscopic synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS leverages fixation-compatible extracellular labeling and advanced optical readout, in particular stimulated-emission depletion and expansion microscopy, to comprehensively delineate cellular structures. It enables 3D-reconstructing single synapses and mapping synaptic connectivity by identification and tailored analysis of putative synaptic cleft regions. Applying CATS to the hippocampal mossy fiber circuitry, we demonstrate its power to reveal the systems molecularly informed ultrastructure across spatial scales and assess local connectivity by reconstructing and quantifying the synaptic input and output structure of identified neurons.

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bioRxiv2022

Saturated reconstruction of living brain tissue

Complex wiring between neurons underlies the information-processing network enabling all brain functions, including cognition and memory. For understanding how the network is structured, processes information, and changes over time, comprehensive visualization of the architecture of living brain tissue with its cellular and molecular components would open up major opportunities. However, electron microscopy (EM) provides nanometre-scale resolution required for full in-silico reconstruction1-5, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches6-12 facilitating nanoscale visualization, but comprehensive 3D-reconstruction of living brain tissue has been hindered by tissue photo-burden, photobleaching, insufficient 3D-resolution, and inadequate signal-to-noise ratio (SNR). Here we demonstrate saturated reconstruction of living brain tissue. We developed an integrated imaging and analysis technology, adapting stimulated emission depletion (STED) microscopy6,13 in extracellularly labelled tissue14 for high SNR and near-isotropic resolution. Centrally, a two-stage deep-learning approach leveraged previously obtained information on sample structure to drastically reduce photo-burden and enable automated volumetric reconstruction down to single synapse level. Live reconstruction provides unbiased analysis of tissue architecture across time in relation to functional activity and targeted activation, and contextual understanding of molecular labelling. This adoptable technology will facilitate novel insights into the dynamic functional architecture of living brain tissue.

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bioRxiv2022

Entorhinal layer 6b subplate neurons govern spatial learning and memory

The mammalian hippocampal formation (HF) plays a key role in several higher brain functions, such as spatial coding, learning and memory. Its simple circuit architecture is often viewed as a "trisynaptic loop", processing input originating from the superficial layers of the entorhinal cortex (EC) in a linear fashion, and sending it back to its deeper layers. Here, we show that contrary to this canonical view, excitatory neurons in the deepest layer of the mouse EC, exhibiting the unique morphology and molecular profile of layer 6b cortical subplate neurons (SPNs), project to all sub-regions comprising the HF, with a preference towards CA3 pyramidal neurons, and receive input from the CA1, thalamus and claustrum. Furthermore, their output is characterized by unique slow-decaying excitatory post-synaptic currents (EPSCs), capable of driving plateau-like potentials in their target cells. Optogenetic inhibition of the EC-6b pathway markedly affects spatial coding in CA1 pyramidal neurons, while cell ablation impairs not only acquisition of new spatial memories, but also degradation of previously acquired ones. Our results provide the first evidence of a functional role for the cortical layer 6b neurons in the adult brain and elucidate a critical novel element determining cortico-hippocampal activity patterns.

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bioRxiv2021

An extended toolkit for production and use of RVdG-CVS-N2c rabies viral vectors uncovers hidden hippocampal connections

To understand the function of neuronal circuits it is crucial to disentangle the connectivity patterns within the network. However, most tools currently used to explore connectivity have low-throughput, low-selectivity, or limited accessibility. Here, we report the development of an improved packaging system for the production of the highly neurotrophic RVdGenvA-CVS-N2c rabies viral vectors, yielding titers orders of magnitude higher with no background contamination, at a fraction of the production time, while preserving the efficiency of transsynaptic labeling. Along with the production pipeline, we developed suites of "starter" AAV and bicistronic RVdG-CVS-N2c vectors, enabling retrograde labeling from a wide range of neuronal populations, tailored for diverse experimental requirements. We demonstrate the power and flexibility of the new system by uncovering hidden local and distal inhibitory connections in the hippocampal formation and by imaging the functional properties of a cortical microcircuit across weeks. Our novel production pipeline provides a convenient approach to generate new rabies vectors, while our toolkit flexibly and efficiently expands the current capacity to label, manipulate and image the neuronal activity of interconnected neuronal circuits in vitro and in vivo.

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bioRxiv2020

Transsynaptic modulation of presynaptic short-term plasticity induction in hippocampal mossy fiber synapses

The hippocampal mossy fiber synapse is a key synapse of the trisynaptic circuit of the hippocampus. Post-tetanic potentiation (PTP) is the most powerful form of plasticity at this synaptic connection. It is widely believed that mossy fiber PTP is an entirely presynaptic phenomenon, implying that PTP induction is input-specific, and requires neither activity of multiple inputs nor stimulation of postsynaptic neurons for induction. Thus, mossy fiber PTP appears to lack cooperativity and associativity that characterize other forms of plasticity. To directly test these predictions, we made paired recordings between single mossy fiber terminals and postsynaptic CA3 pyramidal neurons in rat brain slices. By stimulating parallel but non-overlapping mossy fiber bouton (MFB) inputs converging onto single CA3 neurons, we confirmed that PTP was inputspecific and non-cooperative. Unexpectedly, mossy fiber PTP showed anti-associative induction properties. Mossy fiber excitatory postsynaptic currents (EPSCs) showed only minimal PTP after combined pre- and postsynaptic high-frequency stimulation (HFS) with intact postsynaptic Ca2+ signaling (0.1 mM EGTA), but marked PTP in the absence of postsynaptic spiking and after suppression of postsynaptic Ca2+ signaling (10 mM EGTA). PTP was rescued by blocking Ca2+ entry via voltage-gated R-type and to a smaller extent L-type Ca2+channels. PTP was also recovered by extracellular application of group II metabotropic glutamate receptor (mGluR) antagonists and vacuolar-type (v-type) H+-ATPase inhibitors, suggesting the involvement of retrograde vesicular glutamate signaling. Transsynaptic regulation of PTP induction may increase the computational power of mossy fiber synapses, and implement a break on hippocampal mossy fiber detonation.

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bioRxiv2020

MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo

To understand the mechanisms of information coding in single neurons, it is necessary to analyze subthreshold synaptic events, action potentials (APs), and the interrelation between these two forms of activity in different behavioral states. However, detecting excitatory postsynaptic potentials (EPSPs) or currents (EPSCs) in awake, behaving animals remains challenging, because of unfavorable signal-to-noise ratio, high frequency, fluctuating amplitude, and variable time course of synaptic events. Here, we developed a new method for synaptic event detection, termed MOD (Machine-learning Optimal-filtering Detection-procedure), which combines concepts of supervised machine learning and optimal Wiener filtering. First, experts were asked to manually score short epochs of data. Second, the algorithm was trained to obtain the optimal filter coefficients of a Wiener filter and the optimal detection threshold. Third, scored and unscored data were processed with the optimal filter, and events were detected as peaks above threshold. Finally, the area under the curve (AUC) of the receiver operating characteristics (ROC) curve was used to quantify accuracy and efficiency of detection. Additionally, cross-validation was performed to exclude overfitting of the scored data, a potential concern with machine-learning approaches. We then challenged the new detection method with EPSP traces in vivo in mice during spatial navigation and EPSC traces in vitro in slices under conditions of enhanced transmitter release. When benchmarked using a (1-AUC)-1 metric, MOD outperformed previous methods (template-fit and deconvolution) by a factor of up to 3. Thus, MOD may become an important tool for large-scale analysis of synaptic activity in vivo and in vitro. HighlightsO_LIA new method for detection of synaptic events, termed MOD, is described C_LIO_LIThe method combines the concepts of supervised machine learning and optimal filtering C_LIO_LIThe method is useful for analysis of both in vitro and in vivo data sets C_LIO_LIMOD outperforms previously published methods for synaptic event detection by a factor of up to 3 C_LI

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bioRxiv2020

GABAB receptor auxiliary subunits modulate Cav2.3-mediated release from medial habenula terminals

The connection from medial habenula (MHb) to interpeduncular nucleus is critical for aversion- and addiction-related behaviors. This pathway is unique in selective expression of R-type voltage-gated Ca2+ channels (Cav2.3) in its terminals, and robust potentiation of release via presynaptic GABAB receptors (GBRs). To understand the mechanism underlying this peculiar GBR effect, we examined the presynaptic localization and function of Cav2.3, GBR, and its auxiliary subunits, K+-channel tetramerization domain-containing (KCTD) proteins. We found selective co-expression of KCTD12b and Cav2.3 at the presynaptic active zone. GBR-mediated potentiation remained intact in KCTD12b KO mice but lasted significantly shorter. This impairment was associated with increased release and an insertion of KCTD8 into the active zone. In heterologous cells, we found direct binding of KCTD8 and KCTD12b to Cav2.3, and potentiation of Cav2.3 currents by KCTD8. The unexpected interaction of Cav2.3 with KCTDs therefore provides a means to scale synaptic strength independent of GBR activation.

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bioRxiv2019

Fast signaling and focal connectivity of PV+ interneurons ensure efficient patternseparation by lateral inhibition in a full-scale dentate gyrus network model

Pattern separation is a fundamental brain computation that converts small differences in synaptic input patterns into large differences in action potential (AP) output patterns. Pattern separation plays a key role in the dentate gyrus, enabling the efficient storage and recall of memories in downstream hippocampal CA3 networks. Several mechanisms for pattern separation have been proposed, including expansion of coding space, sparsification of neuronal activity, and simple thresholding mechanisms. Alternatively, a winner-takes-all mechanism, in which the most excited cells inhibit all less-excited cells by lateral inhibition, might be involved. Although such a mechanism is computationally powerful, it remains unclear whether it operates in biological networks. Here, we develop a full-scale network model of the dentate gyrus, comprised of granule cells (GCs) and parvalbumin+ (PV+) inhibitory interneurons, based on experimentally determined biophysical cellular properties and synaptic connectivity rules. Our results demonstrate that a biologically realistic principal neuron-interneuron (PN-IN) network model is a highly efficient pattern separator. Mechanistic dissection in the model revealed that a winner-takes-all mechanism by lateral inhibition plays a crucial role in pattern separation. Furthermore, both fast signaling properties of PV+ interneurons and focal GC-interneuron connectivity are essential for efficient pattern separation. Thus, PV+ interneurons are not only involved in basic microcircuit functions, but also contribute to higher-order computations in neuronal networks, such as pattern separation.

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