Biology subjects

Freund, T. F.

Publications and source records attributed to Freund, T. F..

7 recordsLinked to original sources

bioRxiv2026

Hippocampo-septal inhibitory feedback controls the medial septal circuit as a function of brain state, pyramidal cell activity and movement speed.

Encoding novel experiences and retrieving stored information rely on the hippocampal theta rhythm in several mammalian species. Coordination of putative pacemakers in the medial septum (MS) by the GABAergic hippocampo-septal (HS) feedback is hypothesized to be essential for theta genesis. In order to reveal how the HS-feedback controls the MS circuit, and through it hippocampal oscillations in general, we set out to uncover the behavior-related activity of HS neurons as well as how different components of the MS network are regulated by the HS-feedback. Utilizing computational modelling and in vivo optogenetic manipulation of the HS pathway, we show that the HS feedback is not required for theta generation, which is primarily governed by intra-MS connections. HS blockade did not alter the phase coupling of MS neurons to hippocampal theta rhythm nor the synchrony between rhythmic MS neurons but augmented ongoing theta and coupled mid-gamma oscillations in the hippocampus. By contrast, correlated activity between non-rhythmic MS neurons was sensitive to HS blockade. Moreover, the HS feedback scaled with hippocampal activity and running speed. In turn, modulation of MS neurons by running and ripples was diminished by the transient suppression of HS terminals. These findings suggest that the HS feedback exerts inhibitory control of the MS depending upon hippocampal output and movement speed.

neuroscience↗

bioRxiv2026

How to train your neuron: Developing a detailed, up-to-date, multipurpose model of hippocampal CA1 pyramidal cells

Anatomically and biophysically detailed models of neurons have been widely used to study information processing in these cells. Most studies focused on understanding specific phenomena, while more general models that aim to capture various cellular processes simultaneously remain rare even though such models are required to predict neuronal behavior under more complex, natural conditions. In this study, we aimed to develop a detailed, data-driven, general-purpose biophysical model of hippocampal CA1 pyramidal neurons. We leveraged extensive morphological, biophysical and physiological data available for this cell type, and established a systematic workflow for model construction and validation that relies on our recently developed software tools. The model is based on a high-quality morphological reconstruction and includes a diverse curated set of ion channel models. After incorporating the available constraints on the distribution of ion channels, the remaining free parameters were optimized using the Neuroptimus tool to fit a variety of electrophysiological features extracted from somatic whole-cell recordings. Validation using HippoUnit confirmed the models ability to replicate key electrophysiological features, including somatic voltage responses to current input, the attenuation of synaptic potentials and backpropagating action potentials, and nonlinear synaptic integration in oblique dendrites. Our model also included active dendritic spines, modeled either explicitly or by merging their biophysical mechanisms into those of the parent dendrite. We found that many aspects of neuronal behavior were unaffected by the level of detail in modeling spines, but modeling nonlinear synaptic integration accurately required the explicit modeling of spines. Our data-driven model of CA1 pyramidal cells matching diverse experimental constraints is a general tool for the investigation of the activity and plasticity of these cells and can also be a reliable component of detailed models of the hippocampal network. Our systematic approach to building and validating general-purpose models should apply to other cell types as well. Author SummaryThe brain processes information through the activity of billions of individual neurons. To understand how these cells work, scientists build detailed computer models that reproduce their electrical behavior. These models make it possible to explore situations that are difficult or impossible to test experimentally. However, many existing neuron models were designed to explain only a few specific phenomena, which limits their usefulness in more complex settings. In this study, we developed a comprehensive computer model of a hippocampal CA1 pyramidal neuron, a cell type that plays a central role in learning and memory. We built the model using extensive experimental data and applied automated methods to ensure that it reproduces a broad range of observed neuronal behaviors. We also examined how small structures called dendritic spines--tiny protrusions where most synaptic communication occurs--affect how neurons combine incoming signals. We found that even simplified models without individual spines can capture many aspects of neuronal activity, but understanding more complex forms of signal integration requires modeling spines explicitly. Our work also supports the development of more realistic simulations of brain circuits.

neuroscience↗

bioRxiv2023

Absolute number of three populations of interneurons and GABAergic synapses in the human hippocampus

The human hippocampus, essential for learning and memory, is implicated in numerous neurological and psychiatric disorders, each linked to specific neuronal subpopulations. Advancing our understanding of hippocampal function requires computational models grounded in precise quantitative neuronal data. While extensive data exist on the neuronal composition and synaptic architecture of the rodent hippocampus, analogous quantitative data for the human hippocampus remain very limited. Given the critical role of local GABAergic interneurons in modulating hippocampal functions, we employed unbiased stereological techniques to estimate the density and total number of three major GABAergic cell types in the human hippocampus: parvalbumin (PV)-expressing, somatostatin (SOM)-positive, and calretinin (CR)-positive interneurons. Our findings reveal an estimated 49,400 PV-positive, 141,500 SOM-positive, and 250,600 CR-positive interneurons per hippocampal hemisphere. Notably, the higher proportion of CR-positive, primarily interneuron-selective, cells in humans, compared to rodents, may enhance local interneuron regulation. Additionally, using 3-dimensional electron microscopy, we estimated approximately 25 billion GABAergic synapses per hippocampal hemisphere, with PV-positive boutons comprising around 3.5 billion synapses, or 14% of the total GABAergic synapses. These findings contribute crucial quantitative insights for modeling human hippocampal circuits and understanding its complex regulatory dynamics.

neuroscience↗

bioRxiv2023

Synaptic and dendritic architecture of two types of hippocampal somatostatin interneurons

GABAergic inhibitory neurons fundamentally shape the activity and plasticity of cortical circuits. A major subset of these neurons contains somatostatin (SOM); these cells play crucial roles in neuroplasticity, learning and memory in many brain areas including the hippocampus, and are implicated in several neuropsychiatric diseases and neurodegenerative disorders. Two main types of SOM-containing cells in area CA1 of the hippocampus are oriens-lacunosum-moleculare (OLM) cells and hippocampo-septal (HS) cells. These cell types show many similarities in their soma-dendritic architecture, but they have different axonal targets, display different activity patterns in vivo and are thought to have distinct network functions. However, a complete understanding of the functional roles of these interneurons requires a precise description of their intrinsic computational properties and their synaptic interactions. In the current study we generated, analyzed and make available several key datasets that enable a quantitative comparison of various anatomical and physiological properties of OLM and HS cells in mouse. The dataset includes detailed scanning electron microscopy-based 3-dimensional reconstructions of OLM and HS cells along with their excitatory and inhibitory synaptic inputs. Combining this core dataset with other anatomical data, patch-clamp electrophysiology and compartmental modeling, we examined the precise morphological structure, inputs, outputs, and basic physiological properties of these cells. Our results highlight key differences between OLM and HS cells, particularly regarding the density and distribution of their synaptic inputs and mitochondria. For instance, we estimated that an OLM cell receives about 8400, whereas an HS cell about 15600 synaptic inputs, about 16% of which are GABAergic. Our data and models provide insight into the possible basis of the different functionality of OLM and HS cell types and supply essential information for more detailed functional models of these neurons and the hippocampal network.

neuroscience↗

bioRxiv2021

Huygens synchronization of medial septal pacemaker neurons generates hippocampal theta oscillation

Episodic learning and memory retrieval are critically dependent on a hippocampal 4-12 Hz oscillatory clock signal, the theta oscillation. This clock is largely externally paced, by a network of GABAergic neurons in the medial septum (MS). Theoretical studies suggested a range of hypotheses how this network may achieve theta synchrony; however, experimental evidence is still lacking. By recording multiple single MS neurons and hippocampal local field potential oscillations simultaneously, with both acute and chronically implanted silicon probes, we show that MS pacemaker units oscillate at individual frequencies within the theta range in rodents. Synchronization of MS neuron frequencies, accompanied by an elevation of firing rates, was found to parallel hippocampal theta formation in multiple rodent model systems. This suggests a general mechanism for theta synchronization, akin to the synchronization of weakly coupled pendulum clocks observed by Huygens in the 17th century. We optogenetically identified the MS pacemaker units as parvalbumin-expressing GABAergic neurons, while the previously enigmatic MS glutamatergic neurons were mostly theta-activated non-rhythmic cells. Our data were consistent with a network model of partially connected single-compartment inhibitory pacemaker neurons, in which synchronization and de-synchronization in the frequency domain upon waxing and waning tonic excitatory drive was sufficient to toggle MS network output between theta and non-theta states. These results provide experimental and theoretical support to a frequency-synchronization mechanism for pacing hippocampal theta, which may serve as an inspirational prototype for the countless examples of synchronization processes in the central nervous system from Nematoda to Anthropoda to Chordate and Vertebrate phyla.

neuroscience↗

bioRxiv2020

Systematic comparison and automated validation of detailed models of hippocampal neurons

Anatomically and biophysically detailed data-driven neuronal models have become widely used tools for understanding and predicting the behavior and function of neurons. Due to the increasing availability of experimental data from anatomical and electrophysiological measurements as well as the growing number of computational and software tools that enable accurate neuronal modeling, there are now a large number of different models of many cell types available in the literature. These models were usually built to capture a few important or interesting properties of the given neuron type, and it is often unknown how they would behave outside their original context. In addition, there is currently no simple way of quantitatively comparing different models regarding how closely they match specific experimental observations. This limits the evaluation, re-use and further development of the existing models. Further, the development of new models could also be significantly facilitated by the ability to rapidly test the behavior of model candidates against the relevant collection of experimental data. We address these problems for the representative case of the CA1 pyramidal cell of the rat hippocampus by developing an open-source Python test suite, which makes it possible to automatically and systematically test multiple properties of models by making quantitative comparisons between the models and electrophysiological data. The tests cover various aspects of somatic behavior, and signal propagation and integration in apical dendrites. To demonstrate the utility of our approach, we applied our tests to compare the behavior of several different hippocampal CA1 pyramidal cell models from the ModelDB database against electrophysiological data available in the literature, and concluded that each of these models provides a good match to experimental results in some domains but not in others. We also show how we employed the test suite to aid the development of models within the European Human Brain Project (HBP), and describe the integration of the tests into the validation framework developed in the HBP, with the aim of facilitating more reproducible and transparent model building in the neuroscience community. Author summary Anatomically and biophysically detailed neuronal models are useful tools in neuroscience because they allow the prediction of the behavior and the function of the studied cell type under circumstances that are hard to investigate experimentally. However, most detailed biophysical models have been built to capture a few selected properties of the real neuron, and it is often unknown how they would behave under different circumstances, or whether they can be used to successfully answer different scientific questions. To help the modeling community develop better neural models, and make the process of model building more reproducible and transparent, we developed a test suite that enables the comparison of the behavior of models of neurons in the rat hippocampus and their evaluation against experimental data. Applying our tests to several models available in the literature, we show that each model is able to capture some of the important properties of the real neuron but fails to match experimental data in other domains. We also use the test suite in the model development workflow of the European Human Brain Project to aid the construction of better models of hippocampal neurons and networks.

neuroscience↗

bioRxiv2017

Synaptic co-transmission of acetylcholine and GABA regulates hippocampal states

The basal forebrain cholinergic system is widely assumed to control cortical functions via non-synaptic transmission of a single neurotransmitter, acetylcholine. Yet, using immune-electron tomographic, molecular anatomical, optogenetic and physiological techniques, we find that mouse hippocampal cholinergic terminals invariably establish synapses and their vesicles dock at synapses only. We demonstrate that these synapses do not co-release but co-transmit GABA and acetylcholine via different vesicles, whose release is triggered by distinct calcium channels. This co-transmission evokes fast composite postsynaptic potentials, which are mutually cross-regulated by presynaptic auto-receptors and display different short-term plasticity. The GABAergic component alone effectively suppresses hippocampal sharp wave-ripples and epileptiform activity. The synaptic nature of the forebrain cholinergic system with differentially regulated, fast, GABAergic and cholinergic co-transmission suggests a hitherto unrecognized level of synaptic control over cortical states. This novel model of hippocampal cholinergic neurotransmission could form the basis for alternative pharmacotherapies after cholinergic deinnervation seen in neurodegenerative disorders.\n\nSupplementary materials are attached after the main text.

neuroscience↗