Axon morphology and intrinsic cellular properties determine repetitive transcranial magnetic stimulation threshold for plasticity.

Introduction: Repetitive transcranial magnetic stimulation (rTMS) is a widely used therapeutic tool in neurology and psychiatry, but its cellular and molecular mechanisms are not fully understood. Standardizing stimulus parameters, specifically electric field strength, is crucial in experimental and clinical settings. It enables meaningful comparisons across studies and facilitates the translation of findings into clinical practice. However, the impact of biophysical properties inherent to the stimulated neurons and networks on the outcome of rTMS protocols remains not well understood. Consequently, achieving standardization of biological effects across different brain regions and subjects poses a significant challenge. Methods: This study compared the effects of 10 Hz repetitive magnetic stimulation (rMS) in entorhino-hippocampal tissue cultures from mice and rats, providing insights into the impact of the same stimulation protocol on similar neuronal networks under standardized conditions. Results: We observed the previously described plastic changes in excitatory and inhibitory synaptic strength of CA1 pyramidal neurons in both mouse and rat tissue cultures, but a higher stimulation intensity was required for the induction of rMS-induced synaptic plasticity in rat tissue cultures. Through systematic comparison of neuronal structural and functional properties and computational modeling, we found that morphological parameters of CA1 pyramidal neurons alone are insufficient to explain the observed differences between the groups. Although morphologies of mouse and rat CA1 neurons showed no significant differences, simulations confirmed that axon morphologies significantly influence individual cell activation thresholds. Notably, differences in intrinsic cellular properties were sufficient to account for the 10% higher intensity required for the induction of synaptic plasticity in the rat tissue cultures. Conclusion: These findings demonstrate the critical importance of axon morphology and intrinsic cellular properties in predicting the plasticity effects of rTMS, carrying valuable implications for the development of computer models aimed at predicting and standardizing the biological effects of rTMS.

A voltage-based Event-Timing-Dependent Plasticity rule accounts for LTP subthreshold and suprathreshold for dendritic spikes in CA1 pyramidal neurons.

Long-term potentiation (LTP) is a synaptic mechanism involved in learning and memory. Experiments have shown that dendritic sodium spikes (Na-dSpikes) are required for LTP in the distal apical dendrites of CA1 pyramidal cells. On the other hand, LTP in perisomatic dendrites can be induced by synaptic input patterns that can be both subthreshold and suprathreshold for Na-dSpikes. It is unclear whether these results can be explained by one unifying plasticity mechanism. Here, we show in biophysically and morphologically realistic compartmental models of the CA1 pyramidal cell that these forms of LTP can be fully accounted for by a simple plasticity rule. We call it the voltage-based Event-Timing-Dependent Plasticity (ETDP) rule. The presynaptic event is the presynaptic spike or release of glutamate. The postsynaptic event is the local depolarization that exceeds a certain plasticity threshold. Our model reproduced the experimentally observed LTP in a variety of protocols, including local pharmacological inhibition of dendritic spikes by tetrodotoxin (TTX). In summary, we have provided a validation of the voltage-based ETDP, suggesting that this simple plasticity rule can be used to model even complex spatiotemporal patterns of long-term synaptic plasticity in neuronal dendrites.

Robust and consistent measures of pattern separation based on information theory and demonstrated in the dentate gyrus.

Pattern separation is a valuable computational function performed by neuronal circuits, such as the dentate gyrus, where dissimilarity between inputs is increased, reducing noise and increasing the storage capacity of downstream networks. Pattern separation is studied from both in vivo experimental and computational perspectives and, a number of different measures (such as orthogonalisation, decorrelation, or spike train distance) have been applied to quantify the process of pattern separation. However, these are known to give conclusions that can differ qualitatively depending on the choice of measure and the parameters used to calculate it. We here demonstrate that arbitrarily increasing sparsity, a noticeable feature of dentate granule cell firing and one that is believed to be key to pattern separation, typically leads to improved classical measures for pattern separation even, inappropriately, up to the point where almost all information about the inputs is lost. Standard measures therefore both cannot differentiate between pattern separation and pattern destruction, and give results that may depend on arbitrary parameter choices. We propose that techniques from information theory, in particular mutual information, transfer entropy, and redundancy, should be applied to penalise the potential for lost information (often due to increased sparsity) that is neglected by existing measures. We compare five commonly-used measures of pattern separation with three novel techniques based on information theory, showing that the latter can be applied in a principled way and provide a robust and reliable measure for comparing the pattern separation performance of different neurons and networks. We demonstrate our new measures on detailed compartmental models of individual dentate granule cells and a dentate microcircuit, and show how structural changes associated with epilepsy affect pattern separation performance. We also demonstrate how our measures of pattern separation can predict pattern completion accuracy. Overall, our measures solve a widely acknowledged problem in assessing the pattern separation of neural circuits such as the dentate gyrus, as well as the cerebellum and mushroom body. Finally we provide a publicly available toolbox allowing for easy analysis of pattern separation in spike train ensembles.

A biologically inspired repair mechanism for neuronal reconstructions with a focus on human dendrites.

Investigating and modelling the functionality of human neurons remains challenging due to the technical limitations, resulting in scarce and incomplete 3D anatomical reconstructions. Here we used a morphological modelling approach based on optimal wiring to repair the parts of a dendritic morphology that were lost due to incomplete tissue samples. In Drosophila, where dendritic regrowth has been studied experimentally using laser ablation, we found that modelling the regrowth reproduced a bimodal distribution between regeneration of cut branches and invasion by neighbouring branches. Interestingly, our repair model followed growth rules similar to those for the generation of a new dendritic tree. To generalise the repair algorithm from Drosophila to mammalian neurons, we artificially sectioned reconstructed dendrites from mouse and human hippocampal pyramidal cell morphologies, and showed that the regrown dendrites were morphologically similar to the original ones. Furthermore, we were able to restore their electrophysiological functionality, as evidenced by the recovery of their firing behaviour. Importantly, we show that such repairs also apply to other neuron types including hippocampal granule cells and cerebellar Purkinje cells. We then extrapolated the repair to incomplete human CA1 pyramidal neurons, where the anatomical boundaries of the particular brain areas innervated by the neurons in question were known. Interestingly, the repair of incomplete human dendrites helped to simulate the recently observed increased synaptic thresholds for dendritic NMDA spikes in human versus mouse dendrites. To make the repair tool available to the neuroscience community, we have developed an intuitive and simple graphical user interface (GUI), which is available in the TREES toolbox (www.treestoolbox.org).

Axon morphology and intrinsic cellular properties determine repetitive transcranial magnetic stimulation threshold for plasticity.

Repetitive transcranial magnetic stimulation (rTMS) is a widely used therapeutic tool in neurology and psychiatry, but its cellular and molecular mechanisms are not fully understood. Standardizing stimulus parameters, specifically electric field strength and direction, is crucial in experimental and clinical settings. It enables meaningful comparisons across studies and facilitating the translation of findings into clinical practice. However, the impact of biophysical properties inherent to the stimulated neurons and networks on the outcome of rTMS protocols remains not well understood. Consequently, achieving standardization of biological effects across different brain regions and subjects poses a significant challenge. This study compared the effects of 10 Hz repetitive magnetic stimulation (rMS) in entorhino-hippocampal tissue cultures from mice and rats, providing insights into the impact of the same stimulation protocol on similar neuronal networks under standardized conditions. We observed the previously described plastic changes in excitatory and inhibitory synaptic strength of CA1 pyramidal neurons in both mouse and rat tissue cultures, but a higher stimulation intensity was required for the induction of rMS-induced synaptic plasticity in rat tissue cultures. Through systematic comparison of neuronal structural and functional properties and computational modeling, we found that morphological parameters of CA1 pyramidal neurons alone are insufficient to explain the observed differences between the groups. However, axon morphologies of individual cells played a significant role in determining activation thresholds. Notably, differences in intrinsic cellular properties were sufficient to account for the 10 % higher intensity required for the induction of synaptic plasticity in the rat tissue cultures. These findings demonstrate the critical importance of axon morphology and intrinsic cellular properties in predicting the plasticity effects of rTMS, carrying valuable implications for the development of computer models aimed at predicting and standardizing the biological effects of rTMS.

Skewed distribution of spines is independent of presynaptic transmitter release and synaptic plasticity, and emerges early during adult neurogenesis.

Dendritic spines are crucial for excitatory synaptic transmission as the size of a spine head correlates with the strength of its synapse. The distribution of spine head sizes follows a lognormal-like distribution with more small spines than large ones. We analysed the impact of synaptic activity and plasticity on the spine size distribution in adult-born hippocampal granule cells from rats with induced homo- and heterosynaptic long-term plasticity in vivo and CA1 pyramidal cells from Munc13-1/Munc13-2 knockout mice with completely blocked synaptic transmission. Neither the induction of extrinsic synaptic plasticity nor the blockage of presynaptic activity degrades the lognormal-like distribution but changes its mean, variance and skewness. The skewed distribution develops early in the life of the neuron. Our findings and their computational modelling support the idea that intrinsic synaptic plasticity is sufficient for the generation, while a combination of intrinsic and extrinsic synaptic plasticity maintains lognormal-like distribution of spines.

Biological complexity facilitates tuning of the neuronal parameter space.

The electrical and computational properties of neurons in our brains are determined by a rich repertoire of membrane-spanning ion channels and elaborate dendritic trees. However, the precise reason for this inherent complexity remains unknown, given that simpler models with fewer ion channels are also able to functionally reproduce the behaviour of some neurons. Here, we stochastically varied the ion channel densities of a biophysically detailed dentate gyrus granule cell model to produce a large population of putative granule cells, comparing those with all 15 original ion channels to their reduced but functional counterparts containing only 5 ion channels. Strikingly, valid parameter combinations in the full models were dramatically more frequent at ~6% vs. ~1% in the simpler model. The full models were also more stable in the face of perturbations to channel expression levels. Scaling up the numbers of ion channels artificially in the reduced models recovered these advantages confirming the key contribution of the actual number of ion channel types. We conclude that the diversity of ion channels gives a neuron greater flexibility and robustness to achieve a target excitability.

Layer-specific changes of KCC2 and NKCC1 in the mouse dentate gyrus after entorhinal denervation.

The cation-chloride cotransporters KCC2 and NKCC1 regulate the intracellular Cl- concentration and cell volume of neurons and/or glia. The Cl- extruder KCC2 is expressed at higher levels than the Cl- transporter NKCC1 in mature compared to immature neurons, accounting for the developmental shift from high to low Cl- concentration and from depolarizing to hyperpolarizing currents through GABA-A receptors. Previous studies have shown that KCC2 expression is downregulated following central nervous system injury, returning neurons to a more excitable state, which can be pathological or adaptive. Here, we show that deafferentation of the dendritic segments of granule cells in the outer (oml) and middle (mml) molecular layer of the dentate gyrus via entorhinal denervation in vivo leads to cell-type- and layer-specific changes in the expression of KCC2 and NKCC1. Microarray analysis validated by reverse transcription-quantitative polymerase chain reaction revealed a significant decrease in Kcc2 mRNA in the granule cell layer 7 days post-lesion. In contrast, Nkcc1 mRNA was upregulated in the oml/mml at this time point. Immunostaining revealed a selective reduction in KCC2 protein expression in the denervated dendrites of granule cells and an increase in NKCC1 expression in reactive astrocytes in the oml/mml. The NKCC1 upregulation is likely related to the increased activity of astrocytes and/or microglia in the deafferented region, while the transient KCC2 downregulation in granule cells may be associated with denervation-induced spine loss, potentially also serving a homeostatic role via boosting GABAergic depolarization. Furthermore, the delayed KCC2 recovery might be involved in the subsequent compensatory spinogenesis.

The Amyloid Precursor Protein Regulates Synaptic Transmission at Medial Perforant Path Synapses.

The perforant path provides the primary cortical excitatory input to the hippocampus. Because of its important role in information processing and coding, entorhinal projections to the dentate gyrus have been studied in considerable detail. Nevertheless, synaptic transmission between individual connected pairs of entorhinal stellate cells and dentate granule cells remains to be characterized. Here, we have used mouse organotypic entorhino-hippocampal tissue cultures of either sex, in which the entorhinal cortex (EC) to dentate granule cell (GC; EC-GC) projection is present, and EC-GC pairs can be studied using whole-cell patch-clamp recordings. By using cultures of wild-type mice, the properties of EC-GC synapses formed by afferents from the lateral and medial entorhinal cortex were compared, and differences in short-term plasticity were identified. As the perforant path is severely affected in Alzheimer's disease, we used tissue cultures of amyloid precursor protein (APP)-deficient mice to examine the role of APP at this synapse. APP deficiency altered excitatory neurotransmission at medial perforant path synapses, which was accompanied by transcriptomic and ultrastructural changes. Moreover, presynaptic but not postsynaptic APP deletion through the local injection of Cre-expressing adeno-associated viruses in conditional APPflox/flox tissue cultures increased the neurotransmission efficacy at perforant path synapses. In summary, these data suggest a physiological role for presynaptic APP at medial perforant path synapses that may be adversely affected under altered APP processing conditions.SIGNIFICANCE STATEMENT The hippocampus receives input from the entorhinal cortex via the perforant path. These projections to hippocampal dentate granule cells are of utmost importance for learning and memory formation. Although there is detailed knowledge about perforant path projections, the functional synaptic properties at the level of individual connected pairs of neurons are not well understood. In this study, we investigated the role of APP in mediating functional properties and transmission rules in individually connected neurons using paired whole-cell patch-clamp recordings and genetic tools in organotypic tissue cultures. Our results show that presynaptic APP expression limits excitatory neurotransmission via the perforant path, which could be compromised in pathologic conditions such as Alzheimer's disease.

Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair.

Due to its complex and multifaceted nature, developing effective treatments for epilepsy is still a major challenge. To deal with this complexity we introduce the concept of degeneracy to the field of epilepsy research: the ability of disparate elements to cause an analogous function or malfunction. Here, we review examples of epilepsy-related degeneracy at multiple levels of brain organisation, ranging from the cellular to the network and systems level. Based on these insights, we outline new multiscale and population modelling approaches to disentangle the complex web of interactions underlying epilepsy and to design personalised multitarget therapies.

Structural plasticity of the axon initial segment in rat hippocampal granule cells following high frequency stimulation and LTP induction.

The axon initial segment (AIS) is the site of action potential initiation and important for the integration of synaptic input. Length and localization of the AIS are dynamic, modulated by afferent activity and contribute to the homeostatic control of neuronal excitability. Synaptopodin is a plasticity-related protein expressed by the majority of telencephalic neurons. It is required for the formation of cisternal organelles within the AIS and an excellent marker to identify these enigmatic organelles at the light microscopic level. Here we applied 2 h of high frequency stimulation of the medial perforant path in rats in vivo to induce a strong long-term potentiation of dentate gyrus granule cells. Immunolabeling for ßIV-spectrin and synaptopodin were performed to study structural changes of the AIS and its cisternal organelles. Three-dimensional analysis of the AIS revealed a shortening of the AIS and a corresponding reduction of the number of synaptopodin clusters. These data demonstrate a rapid structural plasticity of the AIS and its cisternal organelles to strong stimulation, indicating a homeostatic response of the entire AIS compartment.

Increased Network Inhibition in the Dentate Gyrus of Adult Neuroligin-4 Knock-Out Mice.

Loss-of-function mutations in neuroligin-4 (Nlgn4), a member of the neuroligin family of postsynaptic adhesion proteins, cause autism spectrum disorder in humans. Nlgn4 knockout (KO) in mice leads to social behavior deficits and complex alterations of synaptic inhibition or excitation, depending on the brain region. In the present work, we comprehensively analyzed synaptic function and plasticity at the cellular and network levels in hippocampal dentate gyrus of Nlgn4 KO mice. Compared with wild-type littermates, adult Nlgn4 KO mice exhibited increased paired-pulse inhibition of dentate granule cell population spikes, but no impairments in excitatory synaptic transmission or short-term and long-term plasticity in vivo In vitro patch-clamp recordings in neonatal organotypic entorhino-hippocampal slice cultures from Nlgn4 KO and wild-type littermates revealed no significant differences in excitatory or inhibitory synaptic transmission, homeostatic synaptic plasticity, and passive electrotonic properties in dentate granule cells, suggesting that the increased inhibition in vivo is the result of altered network activity in the adult Nlgn4 KO. A comparison with prior studies on Nlgn 1-3 knock-out mice reveals that each of the four neuroligins exerts a characteristic effect on both intrinsic cellular and network activity in the dentate gyrus in vivo.

Modelling the contributions to hyperexcitability in a mouse model of Alzheimer's disease.

Neuronal hyperexcitability is a pathological characteristic of Alzheimer's disease (AD). Three main mechanisms have been proposed to explain it: (i) dendritic degeneration leading to increased input resistance, (ii) ion channel changes leading to enhanced intrinsic excitability, and (iii) synaptic changes leading to excitation-inhibition (E/I) imbalance. However, the relative contribution of these mechanisms is not fully understood. Therefore, we performed biophysically realistic multi-compartmental modelling of neuronal excitability in reconstructed CA1 pyramidal neurons from wild-type and APP/PS1 mice, a well-established animal model of AD. We show that, for synaptic activation, the excitability-promoting effects of dendritic degeneration are cancelled out by decreased excitation due to synaptic loss. We find an interesting balance between excitability regulation and an enhanced degeneration in the basal dendrites of APP/PS1 cells, potentially leading to increased excitation by the apical but decreased excitation by the basal Schaffer collateral pathway. Furthermore, our simulations reveal three pathomechanistic scenarios that can account for the experimentally observed increase in firing and bursting of CA1 pyramidal neurons in APP/PS1 mice: scenario 1: enhanced E/I ratio; scenario 2: alteration of intrinsic ion channels (IAHP down-regulated; INap , INa and ICaT up-regulated) in addition to enhanced E/I ratio; and scenario 3: increased excitatory burst input. Our work supports the hypothesis that pathological network and ion channel changes are major contributors to neuronal hyperexcitability in AD. Overall, our results are in line with the concept of multi-causality according to which multiple different disruptions are separately sufficient but no single particular disruption is necessary for neuronal hyperexcitability. KEY POINTS: This work presents simulations of synaptically driven responses in pyramidal cells (PCs) with Alzheimer's disease (AD)-related dendritic degeneration. Dendritic degeneration alone alters PC responses to layer-specific input but additional pathomechanistic scenarios are required to explain neuronal hyperexcitability in AD as follows. Possible scenario 1: AD-related increased excitatory input together with decreased inhibitory input (E/I imbalance) can lead to hyperexcitability in PCs. Possible scenario 2: changes in E/I balance combined with altered ion channel properties can account for hyperexcitability in AD. Possible scenario 3: burst hyperactivity of the surrounding network can explain hyperexcitability of PCs during AD.

The Current Status and Work of Three Rs Centres and Platforms in Europe.

The adoption of Directive 2010/63/EU on the protection of animals used for scientific purposes has given a major push to the formation of Three Rs initiatives in the form of centres and platforms. These centres and platforms are dedicated to the so-called Three Rs, which are the Replacement, Reduction and Refinement of animal use in experiments. ATLA's 50th Anniversary year has seen the publication of two articles on European Three Rs centres and platforms. The first of these was about the progressive rise in their numbers and about their founding history; this second part focuses on their current status and activities. This article takes a closer look at their financial and organisational structures, describes their Three Rs focus and core activities (dissemination, education, implementation, scientific quality/translatability, ethics), and presents their areas of responsibility and projects in detail. This overview of the work and diverse structures of the Three Rs centres and platforms is not only intended to bring them closer to the reader, but also to provide role models and show examples of how such Three Rs centres and platforms could be made sustainable. The Three Rs centres and platforms are very important focal points and play an immense role as facilitators of Directive 2010/63/EU 'on the ground' in their respective countries. They are also invaluable for the wide dissemination of information and for promoting the implementation of the Three Rs in general.

Dosing Transcranial Magnetic Stimulation of the Primary Motor and Dorsolateral Prefrontal Cortices With Multi-Scale Modeling.

Transcranial magnetic stimulation (TMS) can depolarize cortical neurons through the intact skin and skull. The characteristics of the induced electric field (E-field) have a major impact on specific outcomes of TMS. Using multi-scale computational modeling, we explored whether the stimulation parameters derived from the primary motor cortex (M1) induce comparable macroscopic E-field strengths and subcellular/cellular responses in the dorsolateral prefrontal cortex (DLPFC). To this aim, we calculated the TMS-induced E-field in 16 anatomically realistic head models and simulated the changes in membrane voltage and intracellular calcium levels of morphologically and biophysically realistic human pyramidal cells in the M1 and DLPFC. We found that the conventional intensity selection methods (i.e., motor threshold and fixed intensities) produce variable macroscopic E-fields. Consequently, it was challenging to produce comparable subcellular/cellular responses across cortical regions with distinct folding characteristics. Prospectively, personalized stimulation intensity selection could standardize the E-fields and the subcellular/cellular responses to repetitive TMS across cortical regions and individuals. The suggested computational approach points to the shortcomings of the conventional intensity selection methods used in clinical settings. We propose that multi-scale modeling has the potential to overcome some of these limitations and broaden our understanding of the neuronal mechanisms for TMS.

Contributions by metaplasticity to solving the Catastrophic Forgetting Problem.

Catastrophic forgetting (CF) refers to the sudden and severe loss of prior information in learning systems when acquiring new information. CF has been an Achilles heel of standard artificial neural networks (ANNs) when learning multiple tasks sequentially. The brain, by contrast, has solved this problem during evolution. Modellers now use a variety of strategies to overcome CF, many of which have parallels to cellular and circuit functions in the brain. One common strategy, based on metaplasticity phenomena, controls the future rate of change at key connections to help retain previously learned information. However, the metaplasticity properties so far used are only a subset of those existing in neurobiology. We propose that as models become more sophisticated, there could be value in drawing on a richer set of metaplasticity rules, especially when promoting continual learning in agents moving about the environment.

Pareto optimality, economy-effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons.

Neurons encounter unavoidable evolutionary trade-offs between multiple tasks. They must consume as little energy as possible while effectively fulfilling their functions. Cells displaying the best performance for such multi-task trade-offs are said to be Pareto optimal, with their ion channel configurations underpinning their functionality. Ion channel degeneracy, however, implies that multiple ion channel configurations can lead to functionally similar behaviour. Therefore, instead of a single model, neuroscientists often use populations of models with distinct combinations of ionic conductances. This approach is called population (database or ensemble) modelling. It remains unclear, which ion channel parameters in the vast population of functional models are more likely to be found in the brain. Here we argue that Pareto optimality can serve as a guiding principle for addressing this issue by helping to identify the subpopulations of conductance-based models that perform best for the trade-off between economy and functionality. In this way, the high-dimensional parameter space of neuronal models might be reduced to geometrically simple low-dimensional manifolds, potentially explaining experimentally observed ion channel correlations. Conversely, Pareto inference might also help deduce neuronal functions from high-dimensional Patch-seq data. In summary, Pareto optimality is a promising framework for improving population modelling of neurons and their circuits.

A mathematical model of neuroimmune interactions in epileptogenesis for discovering treatment strategies.

The development of epilepsy (epileptogenesis) involves a complex interplay of neuronal and immune processes. Here, we present a first-of-its-kind mathematical model to better understand the relationships among these processes. Our model describes the interaction between neuroinflammation, blood-brain barrier disruption, neuronal loss, circuit remodeling, and seizures. Formulated as a system of nonlinear differential equations, the model reproduces the available data from three animal models. The model successfully describes characteristic features of epileptogenesis such as its paradoxically long timescales (up to decades) despite short and transient injuries or the existence of qualitatively different outcomes for varying injury intensity. In line with the concept of degeneracy, our simulations reveal multiple routes toward epilepsy with neuronal loss as a sufficient but non-necessary component. Finally, we show that our model allows for in silico predictions of therapeutic strategies, revealing injury-specific therapeutic targets and optimal time windows for intervention.

The Rise of Three Rs Centres and Platforms in Europe.

Public awareness and discussion about animal experiments and replacement methods has greatly increased in recent years. The term 'the Three Rs', which stands for the Replacement, Reduction and Refinement of animal experiments, is inseparably linked in this context. A common goal within the Three Rs scientific community is to develop predictive non-animal models and to better integrate all available data from in vitro, in silico and omics technologies into regulatory decision-making processes regarding, for example, the toxicity of chemicals, drugs or food ingredients. In addition, it is a general concern to implement (human) non-animal methods in basic research. Toward these efforts, there has been an ever-increasing number of Three Rs centres and platforms established over recent years - not only to develop novel methods, but also to disseminate knowledge and help to implement the Three Rs principles in policies and education. The adoption of Directive 2010/63/EU on the protection of animals used for scientific purposes gave a strong impetus to the creation of Three Rs initiatives, in the form of centres and platforms. As the first of a series of papers, this article gives an overview of the European Three Rs centres and platforms, and their historical development. The subsequent articles, to be published over the course of ATLA's 50th Anniversary year, will summarise the current focus and tasks as well as the future and the plans of the Three Rs centres and platforms. The Three Rs centres and platforms are very important points of contact and play an immense role in their respective countries as 'on the ground' facilitators of Directive 2010/63/EU. They are also invaluable for the widespread dissemination of information and for promoting implementation of the Three Rs in general.