Active dendrites enrich the repertoire of single-neuron computations. Whereas a lot is known about the function of dendrites in vitro, information about their in vivo properties is limited. A new study1 uses advanced imaging to study hippocampal CA1 pyramidal neuron dendrites in head-fixed, awake animals.

Hippocampal CA3 pyramidal neurons (PNs) form the largest autoassociative network in the mammalian brain. Whether CA3-CA3 recurrent connectivity is genetically preconfigured or environmentally shaped during ongoing memory storage is currently unknown. To address this question, we performed multicellular patch-clamp-based circuit mapping of up to eight CA3 PNs in the mouse hippocampus at multiple postnatal time points (P7-8, P18-25, and P45-50). Here, we show that the hippocampal CA3 network undergoes a developmental transformation from local, dense, and random connectivity to a distributed, sparse, and structured configuration. Thus, sparse and structured connectivity may emerge via experience-dependent mechanisms. In parallel, the strength of single synapses is downregulated; single synaptic events are sufficient to trigger postsynaptic spiking early in development, whereas spatial summation of several inputs is required at later time points. Biologically inspired models of memory storage by Hebbian synaptic plasticity and retrieval via pattern completion suggest that developmental changes improve specific aspects of memory storage and retrieval. Our results imply a developmental transformation of the neuronal code and the memory functions in the hippocampal CA3 network.

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. ### Competing Interest Statement J.A.K. is co-founder of A:Head bio AG and is an inventor on several patents relating to cerebral organoids. Austrian Academy of Sciences, https://ror.org/03anc3s24 FWF Austrian Science Fund, https://ror.org/013tf3c58, F7804-B FWF Austrian Science Fund, P35680 FWF Austrian Science Fund, P35369 Federal Ministry of Education, Science and Research, https://ror.org/03gng8t46 The Gilbert Family Foundation, 923017 Valencian Council for Education, Culture, University and Employment, CIPROM/2023/053 Instituto de Investigación Sanitaria La Fe Dutch Research Council, 09150172210057 Australian Research Council, FT230100138 Horizon 2023 Framework Programme (Marie Skłodowska-Curie), 101155338

The hippocampus, critical for learning and memory, is dogmatically described as a trisynaptic circuit where dentate gyrus granule cells (GCs), CA3 pyramidal neurons (PNs), and CA1 PNs are serially connected. However, CA3 also forms an autoassociative network, and its PNs have diverse morphologies, intrinsic properties, and GC input levels. How PN subtypes compose this recurrent network is unknown. To determine the synaptic arrangement of identified CA3 PNs, we combine multicellular patch-clamp recording and post hoc morphological analysis in mouse hippocampal slices. PNs can be divided into distinct "superficial" and "deep" subclasses, the latter including previously reported "athorny" cells. Subclasses have distinct input-output transformations and asymmetric connectivity, which is more abundant from superficial to deep PNs, splitting CA3 locally into two parallel recurrent networks. Coincident spontaneous inhibition occurs frequently within but not between subclasses, implying subclass-specific inhibitory innervation. Our results suggest two separately controlled sublayers for parallel information processing in hippocampal CA3.

Our brain has remarkable computational power, generating sophisticated behaviors, storing memories over an individual’s lifetime, and producing higher cognitive functions. However, little of our neuroscience knowledge covers the human brain. Is this organ truly unique, or is it a scaled version of the extensively studied rodent brain? Combining multicellular patch-clamp recording with expansion-based superresolution microscopy and full-scale modeling, we determined the cellular and microcircuit properties of the human hippocampal CA3 region, a fundamental circuit for memory storage. In contrast to neocortical networks, human hippocampal CA3 displayed sparse connectivity, providing a circuit architecture that maximizes associational power. Human synapses showed unique reliability, high precision, and long integration times, exhibiting both species- and circuit-specific properties. Together with expanded neuronal numbers, these circuit characteristics greatly enhanced the memory storage capacity of CA3. Our results reveal distinct microcircuit properties of the human hippocampus and begin to unravel the inner workings of our most complex organ.

GABA B 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 on MHb terminals induces an activity-dependent transition from a facilitating, tonic to a depressing, phasic neurotransmitter release mode. This transition is accompanied by a 4.1-fold increase in readily releasable vesicle pool (RRP) size and a 3.5-fold increase of docked synaptic vesicles (SVs) at the presynaptic active zone (AZ). Strikingly, the depressing phasic release exhibits looser coupling distance than the tonic release. Furthermore, the tonic and phasic release are selectively affected by deletion of synaptoporin (SPO) and Ca 2+ -dependent activator protein for secretion 2 (CAPS2), respectively. SPO modulates augmentation, the short-term plasticity associated with tonic release, and CAPS2 retains the increased RRP for initial responses in phasic response trains. The cytosolic protein CAPS2 showed a SV-associated distribution similar to the vesicular transmembrane protein SPO, and they were colocalized in the same terminals. We developed the “Flash and Freeze-fracture” method, and revealed the release of SPO-associated vesicles in both tonic and phasic modes and activity-dependent recruitment of CAPS2 to the AZ during phasic release, which lasted several minutes. Overall, these results indicate that GBR activation translocates CAPS2 to the AZ along with the fusion of CAPS2-associated SVs, contributing to persistency of the RRP increase. Thus, we identified structural and molecular mechanisms underlying tonic and phasic neurotransmitter release and their transition by GBR activation in MHb terminals.

The coupling between Ca2+ channels and release sensors is a key factor defining the signaling properties of a synapse. However, the coupling nanotopography at many synapses remains unknown, and it is unclear how it changes during development. To address these questions, we examined coupling at the cerebellar inhibitory basket cell (BC)-Purkinje cell (PC) synapse. Biophysical analysis of transmission by paired recording and intracellular pipette perfusion revealed that the effects of exogenous Ca2+ chelators decreased during development, despite constant reliance of release on P/Q-type Ca2+ channels. Structural analysis by freeze -fracture replica labeling (FRL) and transmission electron microscopy (EM) indicated that presynaptic P/Q-type Ca2+ channels formed nanoclusters throughout development, whereas docked vesicles were only clustered at later developmental stages. Modeling suggested a developmental transformation from a more random to a more clustered coupling nanotopography. Thus, presynaptic signaling developmentally approaches a point-topoint configuration, optimizing speed, reliability, and energy efficiency of synaptic transmission.

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 rodent 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 and vesicular release probability 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 distance 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. 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.

The hippocampal mossy fiber synapse, formed between axons of dentate gyrus granule cells and dendrites of CA3 pyramidal neurons, is a key synapse in the trisynaptic circuitry of the hippocampus. Because of its comparatively large size, this synapse is accessible to direct presynaptic recording, allowing a rigorous investigation of the biophysical mechanisms of synaptic transmission and plasticity. Furthermore, because of its placement in the very center of the hippocampal memory circuit, this synapse seems to be critically involved in several higher network functions, such as learning, memory, pattern separation, and pattern completion. Recent work based on new technologies in both nanoanatomy and nanophysiology, including presynaptic patch-clamp recording, paired recording, super-resolution light microscopy, and freeze-fracture and “flash-and-freeze” electron microscopy, has provided new insights into the structure, biophysics, and network function of this intriguing synapse. This brings us one step closer to answering a fundamental question in neuroscience: how basic synaptic properties shape higher network computations.

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 nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.

Stereological 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 developed by Keiding, Jensen, and Ranek in 1972, which we refer to as the Keiding model, accounts for lost caps by quantifying the smallest detectable profile in terms of its limiting 'cap angle' (ϕ), a size-independent measure of a particle's distance from the section surface. However, this simple solution has not been widely adopted nor tested. 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 comparing the size and density of particles estimated from 2D projections with direct measurement from 3D EM reconstructions of the same tissue. We applied the Keiding model to estimate the size and density of somata, nuclei and vesicles in the cerebellum of mice and rats, where high packing density can be problematic for design-based methods. Our analysis reveals a Gaussian distribution for ϕ rather than a single value. Nevertheless, curve fits of the Keiding model to the 2D diameter distribution accurately estimate the mean ϕ and 3D diameter distribution. While systematic testing using simulations revealed an upper limit to determining ϕ, our analysis shows that estimated ϕ can be used to determine 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. Our results show the Keiding model provides an efficient means of accurately estimating the size and density of particles from 2D projections even under conditions of a high density.

Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure–function relationships of the brain’s complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture 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 reconstruction1–6, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches7–15 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) microscopy7,16 in extracellularly labelled tissue17 for high SNR and 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 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.

GABA B 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.

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) and sending it back to its deeper layers. Here, we show that excitatory neurons in layer 6b of the mouse EC project to all sub-regions comprising the HF and receive input from the CA1, thalamus and claustrum. Furthermore, their output is characterized by unique slow-decaying excitatory postsynaptic currents capable of driving plateau-like potentials in their postsynaptic targets. Optogenetic inhibition of the EC-6b pathway 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 evidence of a functional role for cortical layer 6b neurons in the adult brain.

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.

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 system’s molecularly informed ultrastructure across spatial scales and assess local connectivity by reconstructing and quantifying the synaptic input and output structure of identified neurons.

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 neurotropic RVdG(envA)-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 mouse 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.

The synaptic connection from medial habenula (MHb) to interpeduncular nucleus (IPN) is critical for emotion-related behaviors and uniquely expresses R-type Ca2+ channels (Cav2.3) and auxiliary GABAB receptor (GBR) subunits, the K+-channel tetramerization domain-containing proteins (KCTDs). Activation of GBRs facilitates or inhibits transmitter release from MHb terminals depending on the IPN subnucleus, but the role of KCTDs is unknown. We therefore examined the localization and function of Cav2.3, GBRs, and KCTDs in this pathway in mice. We show in heterologous cells that KCTD8 and KCTD12b directly bind to Cav2.3 and that KCTD8 potentiates Cav2.3 currents in the absence of GBRs. In the rostral IPN, KCTD8, KCTD12b, and Cav2.3 co-localize at the presynaptic active zone. Genetic deletion indicated a bidirectional modulation of Cav2.3-mediated release by these KCTDs with a compensatory increase of KCTD8 in the active zone in KCTD12b-deficient mice. The interaction of Cav2.3 with KCTDs therefore scales synaptic strength independent of GBR activation.

BACKGROUND:To understand information coding in single neurons, it is necessary to analyze subthreshold synaptic events, action potentials (APs), and their interrelation in different behavioral states. However, detecting excitatory postsynaptic potentials (EPSPs) or currents (EPSCs) in behaving animals remains challenging, because of unfavorable signal-to-noise ratio, high frequency, fluctuating amplitude, and variable time course of synaptic events.NEW METHOD:We developed a method for synaptic event detection, termed MOD (Machine-learning Optimal-filtering Detection-procedure), which combines concepts of supervised machine learning and optimal Wiener filtering. Experts were asked to manually score short epochs of data. The algorithm was trained to obtain the optimal filter coefficients of a Wiener filter and the optimal detection threshold. Scored and unscored data were then processed with the optimal filter, and events were detected as peaks above threshold.RESULTS:We challenged MOD with EPSP traces in vivo in mice during spatial navigation and EPSC traces in vitro in slices under conditions of enhanced transmitter release. The area under the curve (AUC) of the receiver operating characteristics (ROC) curve was, on average, 0.894 for in vivo and 0.969 for in vitro data sets, indicating high detection accuracy and efficiency.COMPARISON WITH EXISTING METHODS:When benchmarked using a (1 - AUC)-1 metric, MOD outperformed previous methods (template-fit, deconvolution, and Bayesian methods) by an average factor of 3.13 for in vivo data sets, but showed comparable (template-fit, deconvolution) or higher (Bayesian) computational efficacy.CONCLUSIONS:MOD may become an important new tool for large-scale, real-time analysis of synaptic activity.