Hippocampome.org is a comprehensive knowledge base of neuron types in the rodent hippocampal formation (dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex). Although the hippocampal literature is remarkably information-rich, neuron properties are often reported with incompletely defined and notoriously inconsistent terminology, creating a formidable challenge for data integration. Our extensive literature mining and data reconciliation identified 122 neuron types based on neurotransmitter, axonal and dendritic patterns, synaptic specificity, electrophysiology, and molecular biomarkers. All ∼3700 annotated properties are individually supported by specific evidence (∼14,000 pieces) in peer-reviewed publications. Systematic analysis of this unprecedented amount of machine-readable information reveals novel correlations among neuron types and properties, the potential connectivity of the full hippocampal circuitry, and outstanding knowledge gaps. User-friendly browsing and online querying of Hippocampome.org may aid design and interpretation of both experiments and simulations. This powerful, simple, and extensible neuron classification endeavor is unique in its detail, utility, and completeness.DOI: http://dx.doi.org/10.7554/eLife.09960.001

Komendantov, Alexander O., Olena G. Komendantova, Steven W. Johnson, and Carmen C. Canavier. A modeling study suggests complementary roles for GABA A and NMDA receptors and the SK channel in regulating the firing pattern in midbrain dopamine neurons.

Komendantov AO, Ascoli GA. Dendritic excitability and neuronal morphology as determinants of synaptic efficacy. J Neurophysiol 101: 1847-1866, 2009. First published January 28, 2009 doi:10.1152/jn.01235.2007. The ability to trigger neuronal spiking activity is one of the most important functional characteristics of synaptic inputs and can be quantified as a measure of synaptic efficacy (SE). Using model neurons with both highly simplified and real morphological structures (from a single cylindrical dendrite to a hippocampal granule cell, CA1 pyramidal cell, spinal motoneuron, and retinal ganglion neurons) we found that SE of excitatory inputs decreases with the distance from the soma and active nonlinear properties of the dendrites can counterbalance this global effect of attenuation. This phenomenon is frequency dependent, with a more prominent gain in SE observed at lower levels of background inputoutput neuronal activity. In contrast, there are no significant differences in SE between passive and active dendrites under higher frequencies of background activity. The influence of the nonuniform distribution of active properties on SE is also more prominent at lower background frequencies. In models with real morphologies, the effect of active dendritic conductances becomes more dramatic and inverts the SE relationship between distal and proximal locations. In active dendrites, distal synapses have higher efficacy than that of proximal ones because of arising dendritic spiking in thin branches with high-input resistance. Lower levels of dendritic excitability can make SE independent of the distance from the soma. Although increasing dendritic excitability may boost SE of distal synapses in real neurons, it may actually reduce overall SE. The results are robust with respect to morphological variation and biophysical properties of the model neurons. The model of CA1 pyramidal cell with realistic distributions of dendritic conductances demonstrated important roles of hyperpolarization-activated (h-) current and A-type K ϩ current in controlling the efficacy of single synaptic inputs and overall SE differently in basal and apical dendrites. I N T R O D U C T I O NDendrites play a central role in neuronal information processing. Electrical signals from other neurons are transmitted onto dendrites via synaptic inputs, which are located throughout the dendritic tree. The most important functional characteristic of synaptic inputs is their ability to influence neuronal spiking activity. At a strong excitatory synapse, a single action potential (AP) in the presynaptic cell might trigger an AP in the postsynaptic neuron, whereas at a weak excitatory synapse only a subthreshold excitatory postsynaptic potential (EPSP) would be initiated under the same stimulating conditions. In real neuronal networks an individual neuron receives many synaptic inputs from numerous other neurons. Under the appropriate circumstance of background activity, even an individual weak synaptic input can be the determining factor for AP initiation...

Systematically organizing the anatomical, molecular, and physiological properties of cortical neurons is important for understanding their computational functions. Hippocampome.org defines 122 neuron types in the rodent hippocampal formation based on their somatic, axonal, and dendritic locations, putative excitatory/inhibitory outputs, molecular marker expression, and biophysical properties. We augmented the electrophysiological data of this knowledge base by collecting, quantifying, and analyzing the firing responses to depolarizing current injections for every hippocampal neuron type from published experiments. We designed and implemented objective protocols to classify firing patterns based on 5 transients (delay, adapting spiking, rapidly adapting spiking, transient stuttering, and transient slow-wave bursting) and 4 steady states (non-adapting spiking, persistent stuttering, persistent slow-wave bursting, and silence). This automated approach revealed 9 unique (plus one spurious) families of firing pattern phenotypes while distinguishing potential new neuronal subtypes. Novel statistical associations emerged between firing responses and other electrophysiological properties, morphological features, and molecular marker expression. The firing pattern parameters, experimental conditions, spike times, references to the original empirical evidences, and analysis scripts are released open-source through Hippocampome.org for all neuron types, greatly enhancing the existing search and browse capabilities. This information, collated online in human- and machine-accessible form, will help design and interpret both experiments and model simulations.

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The role of gap junctions between midbrain dopamine (DA) neurons in mechanisms of firing pattern generation and synchronization has not been well characterized experimentally. We modified a multi-compartment model of DA neuron by adding a spike-generating mechanism and electrically coupling the dendrites of two such neurons through gap junctions. The burst-generating mechanism in the model neuron results from the interaction of a N-methyl-D-aspartate (NMDA)-induced current and the sodium pump. The firing patterns exhibited by the two model neurons included low frequency (2-7 Hz) spiking, high-frequency (13-20 Hz) spiking, irregular spiking, regular bursting, irregular bursting, and leader/follower bursting, depending on the parameter values used for the permeability for NMDA-induced current and the conductance for electrical coupling. All of these firing patterns have been observed in physiological neurons, but a systematic dependence of the firing pattern on the covariation of these two parameters has not been established experimentally. Our simulations indicate that electrical coupling facilitates NMDA-induced burst firing via two mechanisms. The first can be observed in a pair of identical cells. At low frequencies (low NMDA), as coupling strength was increased, only a transition from asynchronous to synchronous single-spike firing was observed. At high frequencies (high NMDA), increasing the strength of the electrical coupling in an identical pair resulted in a transition from high-frequency single-spike firing to burst firing, and further increases led to synchronous high-frequency spiking. Weak electrical coupling destabilizes the synchronous solution of the fast spiking subsystems, and in the presence of a slowly varying sodium concentration, the desynchronized spiking solution leads to bursts that are approximately in phase with spikes that are not in phase. Thus this transitional mechanism depends critically on action potential dynamics. The second mechanism for the induction of burst firing requires a heterogeneous pair that is, respectively, too depolarized and too hyperpolarized to burst. The net effect of the coupling is to bias at least one cell into an endogenously burst firing regime. In this case, action potential dynamics are not critical to the transitional mechanism. If electrical coupling is indeed more prominent in vivo due to basal level of modulation of gap junctions in vivo, these results may indicate why NMDA-induced burst firing is easier to observe in vivo as compared in vitro.

Magnocellular neuroendocrine cells (MNCs) of the hypothalamus synthesize the neurohormones vasopressin and oxytocin, which are released into the blood and exert a wide spectrum of actions, including the regulation of cardiovascular and reproductive functions. Vasopressin-and oxytocinsecreting neurons have similar morphological structure and electrophysiological characteristics. A realistic multicompartmental model of a MNC with a bipolar branching structure was developed and calibrated based on morphological and in vitro electrophysiological data in order to explore the roles of ion currents and intracellular calcium dynamics in the intrinsic electrical MNC properties. The model was used to determine the likely distributions of ion conductances in morphologically distinct parts of the MNCs: soma, primary dendrites and secondary dendrites. While reproducing the general electrophysiological features of MNCs, the model demonstrates that the differential spatial distributions of ion channels influence the functional expression of MNC properties, and reveals the potential importance of dendritic conductances in these properties.

Widely spread naming inconsistencies in neuroscience pose a vexing obstacle to effective communication within and across areas of expertise. This problem is particularly acute when identifying neuron types and their properties. Hippocampome.org is a web-accessible neuroinformatics resource that organizes existing data about essential properties of all known neuron types in the rodent hippocampal formation. Hippocampome.org links evidence supporting the assignment of a property to a type with direct pointers to quotes and figures. Mining this knowledge from peer-reviewed reports reveals the troubling extent of terminological ambiguity and undefined terms. Examples span simple cases of using multiple synonyms and acronyms for the same molecular biomarkers (or other property) to more complex cases of neuronal naming. New publications often use different terms without mapping them to previous terms. As a result, neurons of the same type are assigned disparate names, while neurons of different types are bestowed the same name. Furthermore, non-unique properties are frequently used as names, and several neuron types are not named at all. In order to alleviate this nomenclature confusion regarding hippocampal neuron types and properties, we introduce a new functionality of Hippocampome.org: a fully searchable, curated catalog of human and machine-readable definitions, each linked to the corresponding neuron and property terms. Furthermore, we extend our robust approach to providing each neuron type with an informative name and unique identifier by mapping all encountered synonyms and homonyms.