A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology.

Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal is to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software (version 1.0) is released as open source to enable broad community reuse and encourage novel applications.

A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology.

Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal was to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software is released as open source to enable broad community reuse and encourage novel applications.

The pelvic organs receive no parasympathetic innervation.

The pelvic organs (bladder, rectum, and sex organs) have been represented for a century as receiving autonomic innervation from two pathways - lumbar sympathetic and sacral parasympathetic - by way of a shared relay, the pelvic ganglion, conceived as an assemblage of sympathetic and parasympathetic neurons. Using single-cell RNA sequencing, we find that the mouse pelvic ganglion is made of four classes of neurons, distinct from both sympathetic and parasympathetic ones, albeit with a kinship to the former, but not the latter, through a complex genetic signature. We also show that spinal lumbar preganglionic neurons synapse in the pelvic ganglion onto equal numbers of noradrenergic and cholinergic cells, both of which therefore serve as sympathetic relays. Thus, the pelvic viscera receive no innervation from parasympathetic or typical sympathetic neurons, but instead from a divergent tail end of the sympathetic chains, in charge of its idiosyncratic functions.

Cadherin-13 Maintains Retinotectal Synapses via Transneuronal Interactions.

Maintaining precise synaptic contacts between neuronal partners is critical to ensure the proper functioning of the mammalian central nervous system (CNS). Diverse cell recognition molecules, such as classic cadherins (Cdhs), are part of the molecular machinery mediating synaptic choices during development and synaptic maintenance. Yet, the principles governing neuron-neuron wiring across diverse CNS neuron types remain largely unknown. The retinotectal synapses, connections from the retinal ganglion cells (RGCs) to the superior collicular (SC) neurons, offer an ideal experimental system to reveal molecular logic underlying synaptic choices and formation. This is due to the retina's unidirectional and laminar-restricted projections to the SC and the large databases of presynaptic RGC subtypes and postsynaptic SC neuronal types. Here, we focused on determining the role of Type II Cdhs in wiring the retinotectal synapses. We surveyed Cdhs expression patterns at neuronal resolution and revealed that Cdh13 is enriched in the wide-field neurons in the superficial SC (sSC). In either the Cdh13 null mutant or selective adult deletion within the wide-field neurons, there is a significant reduction of spine densities in the distal dendrites of these neurons in both sexes. Additionally, Cdh13 removal from presynaptic RGCs reduced dendritic spines in the postsynaptic wide-field neurons. Cdh13-expressing RGCs use differential mechanisms than αRGCs and On-Off Direction-Selective Ganglion Cells (ooDSGCs) to form specific retinotectal synapses. The results revealed a selective transneuronal interaction mediated by Cdh13 to maintain proper retinotectal synapses in vivo.

Identifying neuron types and circuit mechanisms in the auditory midbrain.

The inferior colliculus (IC) is a critical computational hub in the central auditory pathway. From its position in the midbrain, the IC receives nearly all the ascending output from the lower auditory brainstem and provides the main source of auditory information to the thalamocortical system. In addition to being a crossroads for auditory circuits, the IC is rich with local circuits and contains more than five times as many neurons as the nuclei of the lower auditory brainstem combined. These results hint at the enormous computational power of the IC, and indeed, systems-level studies have identified numerous important transformations in sound coding that occur in the IC. However, despite decades of effort, the cellular mechanisms underlying IC computations and how these computations change following hearing loss have remained largely impenetrable. In this review, we argue that this challenge persists due to the surprisingly difficult problem of identifying the neuron types and circuit motifs that comprise the IC. After summarizing the extensive evidence pointing to a diversity of neuron types in the IC, we highlight the successes of recent efforts to parse this complexity using molecular markers to define neuron types. We conclude by arguing that the discovery of molecularly identifiable neuron types ushers in a new era for IC research marked by molecularly targeted recordings and manipulations. We propose that the ability to reproducibly investigate IC circuits at the neuronal level will lead to rapid advances in understanding the fundamental mechanisms driving IC computations and how these mechanisms shift following hearing loss.

Molecular Diversity of Neuron Types in the Salamander Amygdala and Implications for Amygdalar Evolution.

The amygdala is a complex brain structure in the vertebrate telencephalon, essential for regulating social behaviors, emotions, and (social) cognition. In contrast to the vast majority of neuron types described in the many nuclei of the mammalian amygdala, little is known about the neuronal diversity in non-mammals, making reconstruction of its evolution particularly difficult. Here, we characterize glutamatergic neuron types in the amygdala of the urodele amphibian Pleurodeles waltl. Our single-cell RNA sequencing data indicate the existence of at least ten distinct types and subtypes of glutamatergic neurons in the salamander amygdala. These neuron types are molecularly distinct from neurons in the ventral pallium (VP), suggesting that the pallial amygdala and the VP are two separate areas in the telencephalon. In situ hybridization for marker genes indicates that amygdalar glutamatergic neuron types are located in three major subdivisions: the lateral amygdala, the medial amygdala, and a newly defined area demarcated by high expression of the transcription factor Sim1. The gene expression profiles of these neuron types suggest similarities with specific neurons in the sauropsid and mammalian amygdala. In particular, we identify Sim1+ and Sim1+ Otp+ expressing neuron types, potentially homologous to the mammalian nucleus of the lateral olfactory tract (NLOT) and to hypothalamic-derived neurons of the medial amygdala, respectively. Taken together, our results reveal a surprising diversity of glutamatergic neuron types in the amygdala of salamanders, despite the anatomical simplicity of their brain. These results offer new insights on the cellular and anatomical complexity of the amygdala in tetrapod ancestors.

Regional, Layer, and Cell-Type-Specific Connectivity of the Mouse Default Mode Network.

The evolutionarily conserved default mode network (DMN) is a distributed set of brain regions coactivated during resting states that is vulnerable to brain disorders. How disease affects the DMN is unknown, but detailed anatomical descriptions could provide clues. Mice offer an opportunity to investigate structural connectivity of the DMN across spatial scales with cell-type resolution. We co-registered maps from functional magnetic resonance imaging and axonal tracing experiments into the 3D Allen mouse brain reference atlas. We find that the mouse DMN consists of preferentially interconnected cortical regions. As a population, DMN layer 2/3 (L2/3) neurons project almost exclusively to other DMN regions, whereas L5 neurons project in and out of the DMN. In the retrosplenial cortex, a core DMN region, we identify two L5 projection types differentiated by in- or out-DMN targets, laminar position, and gene expression. These results provide a multi-scale description of the anatomical correlates of the mouse DMN.

Identification of Mouse Claustral Neuron Types Based on Their Intrinsic Electrical Properties.

Although its dense connections with other brain areas suggests that the claustrum is involved in higher-order brain functions, little is known about the properties of claustrum neurons. Using whole-cell patch clamp recordings in acute brain slices of mice, we characterized the intrinsic electrical properties of more than 300 claustral neurons and used unsupervised clustering of these properties to define distinct cell types. Differences in intrinsic properties permitted separation of interneurons (INs) from projection neurons (PNs). Five subtypes of PNs could be further identified by differences in their adaptation of action potential (AP) frequency and amplitude, as well as their AP firing variability. Injection of retrogradely transported fluorescent beads revealed that PN subtypes differed in their projection targets: one projected solely to subcortical areas while three out of the remaining four targeted cortical areas. INs expressing parvalbumin (PV), somatostatin (SST), or vasoactive intestinal peptide (VIP) formed a heterogenous group. PV-INs were readily distinguishable from VIP-INs and SST-INs, while the latter two were clustered together. To distinguish IN subtypes, an artificial neural network was trained to distinguish the properties of PV-INs, SST-INs, and VIP-INs, as independently identified through their expression of marker proteins. A user-friendly, machine-learning tool that uses intrinsic electrical properties to distinguish these eight different types of claustral cells was developed to facilitate implementation of our classification scheme. Systematic classification of claustrum neurons lays the foundation for future determinations of claustrum circuit function, which will advance our understanding of the role of the claustrum in brain function.

Different coding strategy of sound information between GABAergic and glutamatergic neurons in the auditory midbrain.

KEY POINTS: In the central nucleus of the inferior colliculus (ICC), which acts as the hub of the auditory pathways, how the sound is coded by distinct cell types is largely unknown. Large GABAergic cells are tuned broadly to pure tones and respond more strongly to frequency-modulated sweeps than small GABAergic and glutamatergic (GLU) cells. Neurons, especially GLU cells, which share sharpness of tuning and sweep sensitivity, were spatially clustered inside the ICC. The difference in responsiveness between cell types was partially explained by the morphology of dendritic trees and the spatial distributions of excitatory and inhibitory inputs. The results suggest that each ICC cell type has a particular sound-encoding strategy, which is partially determined by the morphological characteristics and location of cells, and contributes information coding in higher centres in different ways. ABSTRACT: The rules governing the encoding of sound information in the higher auditory centres are largely unknown. In the central nucleus of the inferior colliculus (ICC), which acts as the hub of the auditory pathways, the presence of functional maps other than tonotopicity has been suggested but not established, due to significant heterogeneity in the response properties of single microdomains. Since each ICC cell type has distinct neuronal circuitry, each cell type might encode sound information differently. Here, juxtacellular recording from rat ICC of both sexes revealed that large GABAergic (LG), small GABAergic (SG) and glutamatergic (GLU) cells encode sound information differently. LG cells are broadly tuned and respond more strongly to frequency-modulated sweeps than SG and GLU cells. At a population level, responsiveness to sweeps is location dependent: the responsiveness to sweeps is shared in local clusters of GLU cells, whereas that to directional selectivity of sweeps is shared in local clusters of LG cells. The difference in responsiveness between cell types was partially explained by the morphology of dendritic trees and the spatial distributions of excitatory and inhibitory inputs. LG neurons had a dense local axonal plexus with projection fibres to multiple distant targets, whereas GLU projection neurons mainly aimed at a single, distant target and had less dense local collaterals. These results suggest that each ICC cell type has a particular sound-encoding strategy, which is partially determined by the morphological characteristics and location of the cell, and the different cell types contribute information coding in higher centres in different ways.

A comprehensive knowledge base of synaptic electrophysiology in the rodent hippocampal formation.

The cellular and synaptic architecture of the rodent hippocampus has been described in thousands of peer-reviewed publications. However, no human- or machine-readable public catalog of synaptic electrophysiology data exists for this or any other neural system. Harnessing state-of-the-art information technology, we have developed a cloud-based toolset for identifying empirical evidence from the scientific literature pertaining to synaptic electrophysiology, for extracting the experimental data of interest, and for linking each entry to relevant text or figure excerpts. Mining more than 1,200 published journal articles, we have identified eight different signal modalities quantified by 90 different methods to measure synaptic amplitude, kinetics, and plasticity in hippocampal neurons. We have designed a data structure that both reflects the differences and maintains the existing relations among experimental modalities. Moreover, we mapped every annotated experiment to identified potential connections, that is, specific pairs of presynaptic and postsynaptic neuron types. To this aim, we leveraged Hippocampome.org, an open-access knowledge base of morphologically, electrophysiologically, and molecularly characterized neuron types in the rodent hippocampal formation. Specifically, we have implemented a computational pipeline to systematically translate neuron type properties into formal queries in order to find all compatible potential connections. With this system, we have collected nearly 40,000 synaptic data entities covering 88% of the 3,120 potential connections in Hippocampome.org. Correcting membrane potentials with respect to liquid junction potentials significantly reduced the difference between theoretical and experimental reversal potentials, thereby enabling the accurate conversion of all synaptic amplitudes to conductance. This data set allows for large-scale hypothesis testing of the general rules governing synaptic signals. To illustrate these applications, we confirmed several expected correlations between synaptic measurements and their covariates while suggesting previously unreported ones. We release all data open-source at Hippocampome.org in order to further research across disciplines.

Single-cell transcriptomic evidence for dense intracortical neuropeptide networks.

Seeking new insights into the homeostasis, modulation and plasticity of cortical synaptic networks, we have analyzed results from a single-cell RNA-seq study of 22,439 mouse neocortical neurons. Our analysis exposes transcriptomic evidence for dozens of molecularly distinct neuropeptidergic modulatory networks that directly interconnect all cortical neurons. This evidence begins with a discovery that transcripts of one or more neuropeptide precursor (NPP) and one or more neuropeptide-selective G-protein-coupled receptor (NP-GPCR) genes are highly abundant in all, or very nearly all, cortical neurons. Individual neurons express diverse subsets of NP signaling genes from palettes encoding 18 NPPs and 29 NP-GPCRs. These 47 genes comprise 37 cognate NPP/NP-GPCR pairs, implying the likelihood of local neuropeptide signaling. Here, we use neuron-type-specific patterns of NP gene expression to offer specific, testable predictions regarding 37 peptidergic neuromodulatory networks that may play prominent roles in cortical homeostasis and plasticity.

A novel class of inferior colliculus principal neurons labeled in vasoactive intestinal peptide-Cre mice.

Located in the midbrain, the inferior colliculus (IC) is the hub of the central auditory system. Although the IC plays important roles in speech processing, sound localization, and other auditory computations, the organization of the IC microcircuitry remains largely unknown. Using a multifaceted approach in mice, we have identified vasoactive intestinal peptide (VIP) neurons as a novel class of IC principal neurons. VIP neurons are glutamatergic stellate cells with sustained firing patterns. Their extensive axons project to long-range targets including the auditory thalamus, auditory brainstem, superior colliculus, and periaqueductal gray. Using optogenetic circuit mapping, we found that VIP neurons integrate input from the contralateral IC and the dorsal cochlear nucleus. The dorsal cochlear nucleus also drove feedforward inhibition to VIP neurons, indicating that inhibitory circuits within the IC shape the temporal integration of ascending inputs. Thus, VIP neurons are well-positioned to influence auditory computations in a number of brain regions.

Electrophysiological properties of neurons and synapses in the lateral habenular complex (LHb).

Animal including human behavior is highly sophisticated. Besides reflective actions it is largely based on the desire for magnificent internal feelings, which are provided by the reward system. Its counterpart an "anti-reward" system is mainly composed of the lateral habenular complex (LHb) and its extensive interconnections with the monoaminergic cell groups in the mid- and hindbrain. The present review focuses on the neuronal composition and the internal signaling in the LHb. Morphologically six distinct types of neurons (spherical, fusiform-1, fusiform-2, polymorphic, vertical, neurogliaform) can be identified. In contrast, setting aside neurogliaform cells, only three broad categories (silent, tonic firing, bursting) can be identified using electrophysiological criteria. Functionally, LHb neurons express HCN channels and therefore in an "indifferent" situation LHb appears to be tonically active. When the situation takes a turn for the better habenular cells become inhibited, releasing dopaminergic VTA neurons from continuous damping. In contrast, when the situation takes a turn for the worse, LHb neurons are stimulated, completely shutting down the activity of dopaminergic cells in the VTA.

Molecular fingerprinting of principal neurons in the rodent hippocampus: A neuroinformatics approach.

Neurons are often classified by their morphological and molecular properties. The online knowledge base Hippocampome.org primarily defines neuron types from the rodent hippocampal formation based on their main neurotransmitter (glutamate or GABA) and the spatial distributions of their axons and dendrites. For each neuron type, this open-access resource reports any and all published information regarding the presence or absence of known molecular markers, including calcium-binding proteins, neuropeptides, receptors, channels, transcription factors, and other molecules of biomedical relevance. The resulting chemical profile is relatively sparse: even for the best studied neuron types, the expression or lack thereof of fewer than 70 molecules has been firmly established to date. The mouse genome-wide in situ hybridization mapping of the Allen Brain Atlas provides a wealth of data that, when appropriately analyzed, can substantially augment the molecular marker knowledge in Hippocampome.org. Here we focus on the principal cell layers of dentate gyrus (DG), CA3, CA2, and CA1, which together contain approximately 90% of hippocampal neurons. These four anatomical parcels are densely packed with somata of mostly excitatory projection neurons. Thus, gene expression data for those layers can be justifiably linked to the respective principal neuron types: granule cells in DG and pyramidal cells in CA3, CA2, and CA1. In order to enable consistent interpretation across genes and regions, we screened the whole-genome dataset against known molecular markers of those neuron types. The resulting threshold values allow over 6000 very-high confidence (>99.5%) expressed/not-expressed assignments, expanding the biochemical information content of Hippocampome.org more than five-fold. Many of these newly identified molecular markers are potential pharmacological targets for major neurological and psychiatric conditions. Furthermore, our approach yields reasonable expression/non-expression estimates for every single gene in each of these four neuron types with >90% average confidence, providing a considerably complete genetic characterization of hippocampal principal neurons.

Neurochemical Markers in the Mammalian Brain: Structure, Roles in Synaptic Communication, and Pharmacological Relevance.

BACKGROUND: Knowledge of molecular marker (typically protein or mRNA) expression in neural systems can provide insight to the chemical blueprint of signal processing and transmission, assist in tracking developmental or pathological progressions, and yield key information regarding potential medicinal targets. These markers are particularly relevant in the mammalian brain in the light of its unsurpassed cellular diversity. Accordingly, molecular expression profiling is rapidly becoming a major approach to classify neuron types. Despite a profusion of research, however, the biological functions of molecular markers commonly used to distinguish neuron types remain incompletely understood. Furthermore, most molecular markers of mammalian neuron types are also present in other organs, therefore complicating considerations of their potential pharmacological interactions. OBJECTIVE: Here, we survey 15 prominent neurochemical markers from five categories, namely membrane transporters, calcium-binding proteins, neuropeptides, receptors, and extracellular matrix proteins, explaining their relation and relevance to synaptic communication. METHOD: For each marker, we summarize fundamental structural features, cellular functionality, distributions within and outside the brain, as well as known drug effectors and mechanisms of action. CONCLUSION: This essential primer thus links together the cellular complexity of the brain, the chemical properties of key molecular players in neurotransmission, and possible biomedical opportunities.

Transcriptomic-anatomic analysis of the mouse habenula uncovers a high molecular heterogeneity among neurons in the lateral complex, while gene expression in the medial complex largely obeys subnuclear boundaries.

The mammalian habenula with its medial and lateral complexes has gained much interest in recent years, while knowledge on the detailed biological functions of these nuclei is still scarce. Novel strategies to differentiate and identify habenular cell types are required. Such attempts have largely failed, most likely due to the lack of appropriate molecular markers. One important tool to approach this dilemma is available in form of the Allen Brain Atlas (ABA), which provides detailed expression patterns of many genes in the mouse brain. In the present report, ABA tools in combination with visual inspection of ISH images were used to detect transcripts, which are strongly expressed in medial (MHb) and lateral (LHb) habenular complexes. Against our expectations, most transcripts were differentially distributed throughout the LHb, disregarding boundaries of subnuclear areas. Nine distinct distribution patterns were recognized. Yet, several transcripts could not be attributed to one of these, suggesting a high diversity of neuron types in the LHb. In the MHb, in contrast, many transcripts tended to obey subnuclear boundaries. The differential distribution of others like Adcyap1, Chrna3, or Trp53i11 suggests the presence of a novel subfield adjacent to the region of the MHbVm, which now is termed intermediate field of the ventral MHb. In addition, the localizations of Amigo2, Adcyap1, and a couple of other transcripts suggest a lateral extension of the MHb, which is here, termed HbX area. Apparently, this area is composed of intermingled MHb and LHb neurons and may allow functional interaction between the both habenular complexes.

Neuronal Organization of the Brain in the Adult Amphioxus (Branchiostoma lanceolatum): A Study With Acetylated Tubulin Immunohistochemistry.

Amphioxus (Cephalochordata) belongs to the most basal extant chordates, and knowledge of their brain organization appears to be key to deciphering the early stages of evolution of vertebrate brains. Most comprehensive studies of the organization of the central nervous system of adult amphioxus have investigated the spinal cord. Some brain populations have been characterized via neurochemistry and electron microscopy, and the overall cytoarchitecture of the brain was studied by Ekhart et al. (2003; J. Comp. Neurol. 466:319-330) with general staining methods and retrograde transport from the spinal cord. Here, the cytoarchitecture of the brain of adult amphioxus Branchiostoma lanceolatum was reinvestigated by using acetylated tubulin immunohistochemistry, which specifically stains neurons and fibers, in combination with some ancillary methods. This method allowed reproducible staining and mapping of types of neuron, mostly in brain regions caudal to the entrance level of nerve 2, and its comparison with spinal cord populations. The brain populations studied and discussed in detail were the Retzius bipolar cells, lamellate cells, Joseph cells, various types of translumenal cells, somatic motoneurons, Rohde nucleus cells, small ventral multipolar neurons, and Edinger cells. These observations expand our knowledge of the distribution of cell types and provide additional data on the number of cells and the axonal tracts and commissural regions of the adult amphioxus brain. The results of this comprehensive study provide a framework for comparison of complex adult populations with the early brain neuronal populations revealed in developmental studies of the amphioxus.

Neurons from the adult human dentate nucleus: neural networks in the neuron classification.

OBJECTIVES: Topological (central vs. border neuron type) and morphological classification of adult human dentate nucleus neurons according to their quantified histomorphological properties using neural networks on real and virtual neuron samples. RESULTS: In the real sample 53.1% and 14.1% of central and border neurons, respectively, are classified correctly with total of 32.8% of misclassified neurons. The most important result present 62.2% of misclassified neurons in border neurons group which is even greater than number of correctly classified neurons (37.8%) in that group, showing obvious failure of network to classify neurons correctly based on computational parameters used in our study. On the virtual sample 97.3% of misclassified neurons in border neurons group which is much greater than number of correctly classified neurons (2.7%) in that group, again confirms obvious failure of network to classify neurons correctly. Statistical analysis shows that there is no statistically significant difference in between central and border neurons for each measured parameter (p>0.05). Total of 96.74% neurons are morphologically classified correctly by neural networks and each one belongs to one of the four histomorphological types: (a) neurons with small soma and short dendrites, (b) neurons with small soma and long dendrites, (c) neuron with large soma and short dendrites, (d) neurons with large soma and long dendrites. Statistical analysis supports these results (p<0.05). CONCLUSION: Human dentate nucleus neurons can be classified in four neuron types according to their quantitative histomorphological properties. These neuron types consist of two neuron sets, small and large ones with respect to their perykarions with subtypes differing in dendrite length i.e. neurons with short vs. long dendrites. Besides confirmation of neuron classification on small and large ones, already shown in literature, we found two new subtypes i.e. neurons with small soma and long dendrites and with large soma and short dendrites. These neurons are most probably equally distributed throughout the dentate nucleus as no significant difference in their topological distribution is observed.