On the numbers of neurons in fields CA1 and CA3 of the hippocampus of Sprague-Dawley and Wistar rats

Human hippocampal CA3 uses specific functional connectivity rules for efficient associative memory

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

Computational modeling of fear and stress responses: validation using consolidated fear and stress protocols

Dysfunction in fear and stress responses is intrinsically linked to various neurological diseases, including anxiety disorders, depression, and Post-Traumatic Stress Disorder. Previous studies using in vivo models with Immediate-Extinction Deficit (IED) and Stress Enhanced Fear Learning (SEFL) protocols have provided valuable insights into these mechanisms and aided the development of new therapeutic approaches. However, assessing these dysfunctions in animal subjects using IED and SEFL protocols can cause significant pain and suffering. To advance the understanding of fear and stress, this study presents a biologically and behaviorally plausible computational architecture that integrates several subregions of key brain structures, such as the amygdala, hippocampus, and medial prefrontal cortex. Additionally, the model incorporates stress hormone curves and employs spiking neural networks with conductance-based integrate-and-fire neurons. The proposed approach was validated using the well-established Contextual Fear Conditioning paradigm and subsequently tested with IED and SEFL protocols. The results confirmed that higher intensity aversive stimuli result in more robust and persistent fear memories, making extinction more challenging. They also underscore the importance of the timing of extinction and the significant influence of stress. To our knowledge, this is the first instance of computational modeling being applied to IED and SEFL protocols. This study validates our computational model's complexity and biological realism in analyzing responses to fear and stress through fear conditioning, IED, and SEFL protocols. Rather than providing new biological insights, the primary contribution of this work lies in its methodological innovation, demonstrating that complex, biologically plausible neural architectures can effectively replicate established findings in fear and stress research. By simulating protocols typically conducted in vivo-often involving significant pain and suffering-in an insilico environment, our model offers a promising tool for studying fear-related mechanisms. These findings support the potential of computational models to reduce the reliance on animal testing while setting the stage for new therapeutic approaches.

Structure, biophysics, and circuit function of a "giant" cortical presynaptic terminal

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

Structure and function of the hippocampal CA3 module

The hippocampal formation is crucial for learning and memory, with submodule CA3 thought to be the substrate of pattern completion. However, the underlying synaptic and computational mechanisms of this network are not well understood. Here, we perform circuit reconstruction of a CA3 module using three dimensional (3D) electron microscopy data and combine this with functional connectivity recordings and computational simulations to determine possible CA3 network mechanisms. Direct measurements of connectivity schemes with both physiological measurements and structural 3D EM revealed a high connectivity rate, multi-fold higher than previously assumed. Mathematical modelling indicated that such CA3 networks can robustly generate pattern completion and replay memory sequences. In conclusion, our data demonstrate that the connectivity scheme of the hippocampal submodule is well suited for efficient memory storage and retrieval.

Hippocampal spatial representations exhibit a hyperbolic geometry that expands with experience

Daily experience suggests that we perceive distances near us linearly. However, the actual geometry of spatial representation in the brain is unknown. Here we report that neurons in the CA1 region of rat hippocampus that mediate spatial perception represent space according to a non-linear hyperbolic geometry. This geometry uses an exponential scale and yields greater positional information than a linear scale. We found that the size of the representation matches the optimal predictions for the number of CA1 neurons. The representations also dynamically expanded proportional to the logarithm of time that the animal spent exploring the environment, in correspondence with the maximal mutual information that can be received. The dynamic changes tracked even small variations due to changes in the running speed of the animal. These results demonstrate how neural circuits achieve efficient representations using dynamic hyperbolic geometry.

The brainstem connectome database

Connectivity data of the nervous system and subdivisions, such as the brainstem, cerebral cortex and subcortical nuclei, are necessary to understand connectional structures, predict effects of connectional disorders and simulate network dynamics. For that purpose, a database was built and analyzed which comprises all known directed and weighted connections within the rat brainstem. A longterm metastudy of original research publications describing tract tracing results form the foundation of the brainstem connectome (BC) database which can be analyzed directly in the framework neuroVIISAS. The BC database can be accessed directly by connectivity tables, a web-based tool and the framework. Analysis of global and local network properties, a motif analysis, and a community analysis of the brainstem connectome provides insight into its network organization. For example, we found that BC is a scale-free network with a small-world connectivity. The Louvain modularity and weighted stochastic block matching resulted in partially matching of functions and connectivity. BC modeling was performed to demonstrate signal propagation through the somatosensory pathway which is affected in Multiple sclerosis.

Measurement(s)	brainstem
Technology Type(s)	tract tracing metastudy
Factor Type(s)	brain region
Sample Characteristic - Organism	Rattus rattus
Sample Characteristic - Environment	Experimental setup
Sample Characteristic - Location	Germany

How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex-dentate gyrus-CA3 network

Pattern separation is a fundamental brain computation that converts small differences in input patterns into large differences in output patterns. Several synaptic mechanisms of pattern separation have been proposed, including code expansion, inhibition and plasticity; however, which of these mechanisms play a role in the entorhinal cortex (EC)-dentate gyrus (DG)-CA3 circuit, a classical pattern separation circuit, remains unclear. Here we show that a biologically realistic, full-scale EC-DG-CA3 circuit model, including granule cells (GCs) and parvalbumin-positive inhibitory interneurons (PV+-INs) in the DG, is an efficient pattern separator. Both external gamma-modulated inhibition and internal lateral inhibition mediated by PV+-INs substantially contributed to pattern separation. Both local connectivity and fast signaling at GC-PV+-IN synapses were important for maximum effectiveness. Similarly, mossy fiber synapses with conditional detonator properties contributed to pattern separation. By contrast, perforant path synapses with Hebbian synaptic plasticity and direct EC-CA3 connection shifted the network towards pattern completion. Our results demonstrate that the specific properties of cells and synapses optimize higher-order computations in biological networks and might be useful to improve the deep learning capabilities of technical networks.

Cognitive Reserve in Model Systems for Mechanistic Discovery: The Importance of Longitudinal Studies

The goal of this review article is to provide a resource for longitudinal studies, using animal models, directed at understanding and modifying the relationship between cognition and brain structure and function throughout life. We propose that forthcoming longitudinal studies will build upon a wealth of knowledge gleaned from prior cross-sectional designs to identify early predictors of variability in cognitive function during aging, and characterize fundamental neurobiological mechanisms that underlie the vulnerability to, and the trajectory of, cognitive decline. Finally, we present examples of biological measures that may differentiate mechanisms of the cognitive reserve at the molecular, cellular, and network level.

Feasibility and resolution limits of opto-magnetic imaging of neural network activity in brain slices using color centers in diamond

We suggest a novel approach for wide-field imaging of the neural network dynamics of brain slices that uses highly sensitivity magnetometry based on nitrogen-vacancy (NV) centers in diamond. In-vitro recordings in brain slices is a proven method for the characterization of electrical neural activity and has strongly contributed to our understanding of the mechanisms that govern neural information processing. However, this traditional approach only acquires signals from a few positions, which severely limits its ability to characterize the dynamics of the underlying neural networks. We suggest to extend its scope using NV magnetometry-based imaging of the neural magnetic fields across the slice. Employing comprehensive computational simulations and theoretical analyses, we determine the spatiotemporal characteristics of the neural fields and the required key performance parameters of an NV magnetometry-based imaging setup. We investigate how the technical parameters determine the achievable spatial resolution for an optimal 2D reconstruction of neural currents from the measured field distributions. Finally, we compare the imaging of neural slice activity with that of a single planar pyramidal cell. Our results suggest that imaging of slice activity will be possible with the upcoming generation of NV magnetic field sensors, while single-shot imaging of planar cell activity remains challenging.

Bio-inspired benchmark generator for extracellular multi-unit recordings

The analysis of multi-unit extracellular recordings of brain activity has led to the development of numerous tools, ranging from signal processing algorithms to electronic devices and applications. Currently, the evaluation and optimisation of these tools are hampered by the lack of ground-truth databases of neural signals. These databases must be parameterisable, easy to generate and bio-inspired, i.e. containing features encountered in real electrophysiological recording sessions. Towards that end, this article introduces an original computational approach to create fully annotated and parameterised benchmark datasets, generated from the summation of three components: neural signals from compartmental models and recorded extracellular spikes, non-stationary slow oscillations, and a variety of different types of artefacts. We present three application examples. (1) We reproduced in-vivo extracellular hippocampal multi-unit recordings from either tetrode or polytrode designs. (2) We simulated recordings in two different experimental conditions: anaesthetised and awake subjects. (3) Last, we also conducted a series of simulations to study the impact of different level of artefacts on extracellular recordings and their influence in the frequency domain. Beyond the results presented here, such a benchmark dataset generator has many applications such as calibration, evaluation and development of both hardware and software architectures.

Microelectrode array analysis of hippocampal network dynamics following theta-burst stimulation via current source density reconstruction by Gaussian interpolation

BACKGROUND

Multielectrode arrays (MEAs) have been used to understand electrophysiological network dynamics by recording real-time activity in groups of cells. The extent to which the collection of such data enables hypothesis testing on the level of circuits and networks depends largely on the sophistication of the analyses applied.

NEW METHOD

We studied the systemic temporal variations of endogenous signaling within an organotypic hippocampal network following theta-burst stimulation (TBS) to the Schaffer collateral-commissural pathways. The recovered current source density (CSD) information from the raw grid of extracellular potentials by using a Gaussian interpolation method increases spatial resolution and avoids border artifacts by numerical differentials.

RESULTS

We compared total sink and source currents in DG, CA3, and CA1; calculated accumulated correlation coefficients to compare pre- with post-stimulation CSD dynamics in each region; and reconstructed functional connectivity maps for regional cross-correlations with respect to temporal CSD variations. The functional connectivity maps for potential correlations pre- and post-TBS were compared to investigate the neural network as a whole, revealing differences post-TBS.

COMPARISON WITH EXISTING METHOD(S)

Previous MEA work on plasticity in hippocampal evoked potentials has focused on synchronicity across the hippocampus within isolated subregions. Such analyses ignore the complex relationships among diverse components of the hippocampal circuitry, thus failing to capture network-level behaviors integral to understanding hippocampal function.

CONCLUSIONS

The proposed method of recovering current source density to examine whole-hippocampal function is sensitive to experimental manipulation and is worth further examination in the context of network-level analyses of neural signaling.

Comparison of unbiased estimation of neuronal number in the rat hippocampus with different staining methods

BACKGROUND

NeuN and Nissl staining (toluidine blue, cresyl violet staining) are routinely used methods in unbiased stereological estimation of the total number of hippocampal neurons.

NEW METHOD

In the present study, we stained serial frozen coronal sections from 5 normal adult male Sprague-Dawley rat brains with different methods, measured the deformation of hippocampal area in brain sections and estimated the total number of hippocampal neurons using the optical fractionator.

RESULTS

The deformation in x, y-axis was not obviously different with different staining protocols, but shrinkage in z-axis was significant after staining (p < 0.001). NeuN staining produced significant higher estimate number than cresyl violet staining by 24% (p = 0.002), however, NeuN and Cresyl Violet staining showed a high degree of correlation in quantification of total neuronal numbers and both methods are suitable for unbiased stereological estimation.

COMPARISON WITH EXISTING METHOD (S)

NeuN is more reliable but if time is limited or the number of animals used in experiments is high, cresyl violet staining may be a feasible method.

CONCLUSIONS

Compared with previous estimates of the neurons number in rat hippocampus, our present data is reliable and the stereological analysis based on our system is a cost-effective unbiased method for estimation of neuron number.

Oxygen and seizure dynamics: I. Experiments

We utilized a novel ratiometric nanoquantum dot fluorescence resonance energy transfer (NQD-FRET) optical sensor to quantitatively measure oxygen dynamics from single cell microdomains during hypoxic episodes as well as during 4-aminopyridine (4-AP)-induced spontaneous seizure-like events in rat hippocampal slices. Coupling oxygen sensing with electrical recordings, we found the greatest reduction in the O2 concentration ([O2]) in the densely packed cell body stratum (st.) pyramidale layer of the CA1 and differential layer-specific O2 dynamics between the st. pyramidale and st. oriens layers. These hypoxic decrements occurred up to several seconds before seizure onset could be electrically measured extracellularly. Without 4-AP, we quantified a narrow range of [O2], similar to the endogenous hypoxia found before epileptiform activity, which permits a quiescent network to enter into a seizure-like state. We demonstrated layer-specific patterns of O2 utilization accompanying layer-specific neuronal interplay in seizure. None of the oxygen overshoot artifacts seen with polarographic measurement techniques were observed. We therefore conclude that endogenously generated hypoxia may be more than just a consequence of increased cellular excitability but an influential and critical factor for orchestrating network dynamics associated with epileptiform activity.

Number and regional distribution of GAD65 mRNA-expressing interneurons in the rat hippocampal formation

In rodent models for neuropsychiatric disorders reduced number of hippocampal interneurons have been reported, but the total number of GABAergic neurons in the normal rat hippocampus is yet unknown. We used in situ hybridization method to label the 65 isoform of glutamic acid decarboxylase (GAD65) and counted the number of GAD65 mRNA-expressing neurons along the entire septo-temporal axis of the hippocampus. We found that 2/3 of the interneurons were in Ammon's horn (61,590) and 1/3 in the dentate gyrus (28,000). We observed the following numbers in Ammon's horn: CA3 area 33,400, CA2 area 4,190, CA1 area 24,000 and in the dentate gyrus: 6,000 in the molecular and 9,000 in the granule cell layers and 13,000 in the hilus. GAD65 mRNA-expressing neurons were significantly more numerous in dorsal than in ventral hippocampus. The ratio between interneurons and principal cells was lowest in the granule cell layer (0.9%) and highest in hilus (21%). In Ammon's horn this ratio was constant being 13% in CA3 and 8% in CA1-2 areas. In the entire hippocampal formation, the interneuron/principal cell ratio was 6%, with a significant difference between Ammon's horn (9.5%) and the dentate gyrus (2.8%) including the hilus. Such low ratios could suggest that even a limited loss of GABAergic neurons in the hippocampus may have a considerable functional impact.

Determining the true polarity and amplitude of synaptic currents underlying gamma oscillations of local field potentials

Fluctuations in successive waves of oscillatory local field potentials (LFPs) reflect the ongoing processing of neuron populations. However, their amplitude, polarity and synaptic origin are uncertain due to the blending of electric fields produced by multiple converging inputs, and the lack of a baseline in standard AC-coupled recordings. Consequently, the estimation of underlying currents by laminar analysis yields spurious sequences of inward and outward currents. We devised a combined analytical/experimental approach that is suitable to study laminated structures. The approach was essayed on an experimental oscillatory LFP as the Schaffer-CA1 gamma input in anesthetized rats, and it was verified by parallel processing of model LFPs obtained through a realistic CA1 aggregate of compartmental units. This approach requires laminar LFP recordings and the isolation of the oscillatory input from other converging pathways, which was achieved through an independent component analysis. It also allows the spatial and temporal components of pathway-specific LFPs to be separated. While reconstructed Schaffer-specific LFPs still show spurious inward/outward current sequences, these were clearly stratified into distinct subcellular domains. These spatial bands guided the localized delivery of neurotransmitter blockers in experiments. As expected, only Glutamate but not GABA blockers abolished Schaffer LFPs when applied to the active but not passive subcellular domains of pyramidal cells. The known chemical nature of the oscillatory LFP allowed an empirical offset of the temporal component of Schaffer LFPs, such that following reconstruction they yield only sinks or sources at the appropriate sites. In terms of number and polarity, some waves increased and others decreased proportional to the concomitant inputs in native multisynaptic LFPs. Interestingly, the processing also retrieved the initiation time for each wave, which can be used to discriminate afferent from postsynaptic cells in standard spike-phase correlations. The applicability of this approach to other pathways and structures is discussed.

Synaptic gating at axonal branches, and sharp-wave ripples with replay: a simulation study

Mechanisms of place cell replay occurring during sharp-wave ripples (SPW-Rs) remain obscure due to the fact that ripples in vitro depend on non-synaptic mechanisms, presumably via axo-axonal gap junctions between pyramidal cells. We suggest a model of in vivo SPW-Rs in which synaptic excitatory post-synaptic potentials (EPSPs) control the axonal spiking of cells in SPW-Rs: ripple activity remains hidden in the network of axonal collaterals (connected by gap junctions) due to conduction failures, unless there is a sufficient dendritic EPSP. The EPSP brings the axonal branching point to threshold, and action potentials from the collateral start to propagate to the soma and to the distal axon. The model coherently explains multiple experimental data on SPW-Rs, both in vitro and in vivo. The mechanism of synaptic gating leads to the following implication: a sequence of pyramidal cells can be replayed at ripple frequency by the superposition of subthreshold dendritic EPSPs and ripple activity in the axonal plexus. Replay is demonstrated in both forward and reverse directions. We discuss several testable predictions. In general, the mechanism of synaptic gating suggests that pyramidal cells under certain conditions can act like a transistor.

A quantitative magnetic resonance histology atlas of postnatal rat brain development with regional estimates of growth and variability

There has been growing interest in the role of postnatal brain development in the etiology of several neurologic diseases. The rat has long been recognized as a powerful model system for studying neuropathology and the safety of pharmacologic treatments. However, the complex spatiotemporal changes that occur during rat neurodevelopment remain to be elucidated. This work establishes the first magnetic resonance histology (MRH) atlas of the developing rat brain, with an emphasis on quantitation. The atlas comprises five specimens at each of nine time points, imaged with eight distinct MR contrasts and segmented into 26 developmentally defined brain regions. The atlas was used to establish a timeline of morphometric changes and variability throughout neurodevelopment and represents a quantitative database of rat neurodevelopment for characterizing rat models of human neurologic disease.

The spiking component of oscillatory extracellular potentials in the rat hippocampus

When monitoring neural activity using intracranial electrical recordings, researchers typically consider the signals to have two primary components: fast action potentials (APs) from neurons near the electrode, and the slower local field potential (LFP), thought to be dominated by postsynaptic currents integrated over a larger volume of tissue. In general, a decrease in signal power with increasing frequency is observed for most brain rhythms. The 100-200 Hz oscillations in the rat hippocampus, including "fast gamma" or "epsilon" oscillations and sharp wave-ripples (SPW-Rs), are one exception, showing an increase in power with frequency within this band. We have used detailed biophysical modeling to investigate the composition of extracellular potentials during fast oscillations in rat CA1. We find that postsynaptic currents exhibit a decreasing ability to generate large-amplitude oscillatory signals at high frequencies, whereas phase-modulated spiking shows the opposite trend. Our estimates indicate that APs and postsynaptic currents contribute similar proportions of the power contained in 140-200 Hz ripples, and the two combined generate a signal that closely resembles in vivo SPW-Rs. Much of the AP-generated signal originates from neurons further than 100 μm from the recording site, consistent with ripples appearing similarly strong regardless of whether or not they contain recognizable APs. Additionally, substantial power can be generated in the 90-150 Hz epsilon band by the APs of rhythmically firing pyramidal neurons. Thus, high-frequency LFPs may generally contain signatures of local cell assembly activation.

Non-homogeneous stereological properties of the rat hippocampus from high-resolution 3D serial reconstruction of thin histological sections

Integrating hippocampal anatomy from neuronal dendrites to whole system may help elucidate its relation to function. Toward this aim, we digitally traced the cytoarchitectonic boundaries of the dentate gyrus (DG) and areas CA3/CA1 throughout their entire longitudinal extent from high-resolution images of thin cryostatic sections of adult rat brain. The 3D computational reconstruction identified all isotropic 16 μm voxels with appropriate subregions and layers (http://krasnow1.gmu.edu/cn3/hippocampus3d). Overall, DG, CA3, and CA1 occupied comparable volumes (15.3, 12.2, and 18.8 mm(3), respectively), but displayed substantial rostrocaudal volumetric gradients: CA1 made up more than half of the posterior hippocampus, whereas CA3 and DG were more prominent in the anterior regions. The CA3/CA1 ratio increased from ∼0.4 to ∼1 septo-temporally because of a specific change in stratum radiatum volume. Next we virtually embedded 1.8 million neuronal morphologies stochastically resampled from 244 digital reconstructions, emulating the dense packing of granular and pyramidal layers, and appropriately orienting the principal dendritic axes relative to local curvature. The resulting neuropil occupancy reproduced recent electron microscopy data measured in a restricted location. Extension of this analysis across each layer and subregion over the whole hippocampus revealed highly non-homogeneous dendritic density. In CA1, dendritic occupancy was >60% higher temporally than septally (0.46 vs. 0.28, s.e.m. ∼0.05). CA3 values varied both across subfields (from 0.35 in CA3b/CA3c to 0.50 in CA3a) and layers (0.48, 0.34, and 0.27 in oriens, radiatum, and lacunosum-moleculare, respectively). Dendritic occupancy was substantially lower in DG, especially in the supra-pyramidal blade (0.18). The computed probability of dendrodendritic collision significantly correlated with expression of the membrane repulsion signal Down syndrome cell adhesion molecule (DSCAM). These heterogeneous stereological properties reflect and complement the non-uniform molecular composition, circuit connectivity, and computational function of the hippocampus across its transverse, longitudinal, and laminar organization.

Parallel readout of pathway-specific inputs to laminated brain structures

Local field potentials (LFPs) capture the electrical activity produced by principal cells during integration of converging synaptic inputs from multiple neuronal populations. However, since synaptic currents mix in the extracellular volume, LFPs have complex spatiotemporal structure, making them hard to exploit. Here we propose a biophysical framework to identify and separate LFP-generators. First we use a computational multineuronal model that scales up single cell electrogenesis driven by several synaptic inputs to realistic aggregate LFPs. This approach relies on the fixed but distinct locations of synaptic inputs from different presynaptic populations targeting a laminated brain structure. Thus the LFPs are contributed by several pathway-specific LFP-generators, whose electrical activity is defined by the spatial distribution of synaptic terminals and the time course of synaptic currents initiated in target cells by the corresponding presynaptic population. Then we explore the efficacy of independent component analysis to blindly separate converging sources and reconstruct pathway-specific LFP-generators. This approach can optimally locate synaptic inputs with subcellular accuracy while the reconstructed time course of pathway-specific LFP-generators is reliable in the millisecond scale. We also describe few cases where the non-linear intracellular interaction of strongly overlapping LFP-generators may lead to a significant cross-contamination and the appearance of derivative generators. We show that the approach reliably disentangle ongoing LFPs in the hippocampus into contribution of several LFP-generators. We were able to readout in parallel the pathway-specific presynaptic activity of projection cells in the entorhinal cortex and pyramidal cells in the ipsilateral and contralateral CA3. Thus we provide formal mathematical and experimental support for parallel readout of the activity of converging presynaptic populations in working neuronal circuits from common LFPs.

Disambiguating the similar: the dentate gyrus and pattern separation

The human hippocampus supports the formation of episodic memory without confusing new memories with old ones. To accomplish this, the brain must disambiguate memories (i.e., accentuate the differences between experiences). There is convergent evidence linking pattern separation to the dentate gyrus. Damage to the dentate gyrus reduces an organism's ability to differentiate between similar objects. The dentate gyrus has tenfold more principle cells than its cortical input, allowing for a divergence in information flow. Dentate gyrus granule neurons also show a very different pattern of representing the environment than "classic" place cells in CA1 and CA3, or grid cells in the entorhinal cortex. More recently immediate early genes have been used to "timestamp" activity of individual cells throughout the dentate gyrus. These data indicate that the dentate gyrus robustly differentiates similar situations. The degree of differentiation is non-linear, with even small changes in input inducing a near maximal response in the dentate. Furthermore this differentiation occurs throughout the dentate gyrus longitudinal (dorsal-ventral) axis. Conversely, the data point to a divergence in information processing between the dentate gyrus suprapyramidal and infrapyramidal blades possibly related to differences in organization within these regions. The accumulated evidence from different approaches converges to support a role for the dentate gyrus in pattern separation. There are however inconsistencies that may require incorporation of neurogenesis and hippocampal microcircuits into the currents models. They also suggest different roles for the dentate gyrus suprapyramidal and infrapyramidal blades, and the responsiveness of CA3 to dentate input.

Three-dimensional localization of neurons in cortical tetrode recordings

The recording radius and spatial selectivity of an extracellular probe are important for interpreting neurophysiological recordings but are rarely measured. Moreover, an analysis of the recording biophysics of multisite probes (e.g., tetrodes) can provide for source characterization and localization of spiking single units, but this capability has remained largely unexploited. Here we address both issues quantitatively. Advancing a tetrode (≈40-μm contact separation, tetrahedral geometry) in 5- to 10-μm steps, we repeatedly recorded extracellular action potentials (EAPs) of single neurons in the visual cortex. Using measured spatial variation of EAPs, the tetrodes' measured geometry, and a volume conductor model of the cortical tissue, we solved the inverse problem of estimating the location and the size of the equivalent dipole model of the spike generator associated with each neuron. Half of the 61 visual neurons were localized within a radius of ≈100 μm and 95% within ≈130 μm around the tetrode tip (i.e., a large fraction was much further than previously thought). Because of the combined angular sensitivity of the tetrode's leads, location uncertainty was less than one-half the cell's distance. We quantified the spatial dependence of the probability of cell isolation, the isolated fraction, and the dependence of the recording radius on probe size and equivalent dipole size. We also reconstructed the spatial configuration of sets of simultaneously recorded neurons to demonstrate the potential use of 3D dipole localization for functional anatomy. Finally, we found that the dipole moment vector, surprisingly, tended to point toward the probe, leading to the interpretation that the equivalent dipole represents a "local lobe" of the dendritic arbor.

Generation of Sustained Field Potentials by Gradients of Polarization Within Single Neurons: A Macroscopic Model of Spreading Depression

Spreading depression (SD) is a pathological wave of depolarization of the neural tissue producing a negative macroscopic field potential ( Vo), used as a marker for diagnostic purposes. The cellular basis of SD and neuronal mechanisms of generation of Vo at the microscopic level are poorly understood. Using a CA1 mathematical model and experimental verification, we examined how transmembrane currents in single cells scale up in the extracellular space shaping Vo. The model includes an array of 17,000 realistically modeled neurons (responsible for generating transmembrane currents) dynamically coupled to a virtual aggregate/extracellular space (responsible for Vo). The SD wave in different tissue bands is simulated by imposing membrane shunts in the corresponding dendritic elements as suggested by experimentally assessed drop in membrane resistance. We show that strong isopotential depolarization of wide domains (as in the main SD phase) produce broad central cancellation of axial and transmembrane currents in single cells. When depolarization is restricted to narrow dendritic domains (as in the late SD phase), the internal cancellation shrinks and the transmembrane current increases. This explains why in the laminated CA1 the Vo is smaller in the main phase of SD, when both dendritic layers are seized, than in the SD tail restricted to an apical band. Moreover, scattering of the neuronal somatas (as in cortical regions) further decreases the aggregate Vo due to the volume averaging. Although mechanistically the Vo associated to SD is similar to customary transient fields, its changes maybe related to spatial factors in single cells rather than cell number or depolarization strength.

Disentanglement of local field potential sources by independent component analysis

The spontaneous activity of working neurons yields synaptic currents that mix up in the volume conductor. This activity is picked up by intracerebral recording electrodes as local field potentials (LFPs), but their separation into original informative sources is an unresolved problem. Assuming that synaptic currents have stationary placing we implemented independent component model for blind source separation of LFPs in the hippocampal CA1 region. After suppressing contaminating sources from adjacent regions we obtained three main local LFP generators. The specificity of the information contained in isolated generators is much higher than in raw potentials as revealed by stronger phase-spike correlation with local putative interneurons. The spatial distribution of the population synaptic input corresponding to each isolated generator was disclosed by current-source density analysis of spatial weights. The found generators match with axonal terminal fields from subtypes of local interneurons and associational fibers from nearby subfields. The found distributions of synaptic currents were employed in a computational model to reconstruct spontaneous LFPs. The phase-spike correlations of simulated units and LFPs show laminar dependency that reflects the nature and magnitude of the synaptic currents in the targeted pyramidal cells. We propose that each isolated generator captures the synaptic activity driven by a different neuron subpopulation. This offers experimentally justified model of local circuits creating extracellular potential, which involves distinct neuron subtypes.

Evidence of multistability in a realistic computer simulation of hippocampus subfield CA1

The manner in which hippocampus processes neural signals is thought to be central to the memory encoding process. A theoretically oriented literature has suggested that this is carried out via "attractors" or distinctive spatio-temporal patterns of activity. However, these ideas have not been thoroughly investigated using computational models featuring both realistic single-cell physiology and detailed cell-to-cell connectivity. Here we present a 452 cell simulation based on Traub et al.'s pyramidal cell [Traub RD, Jefferys JG, Miles R, Whittington MA, Toth K. A branching dendritic model of a rodent CA3 pyramidal neurone. J Physiol (Lond) 1994;481:79-95] and interneuron [Traub RD, Miles R, Pyramidal cell-to-inhibitory cell spike transduction explicable by active dendritic conductances in inhibitory cell. J Comput Neurosci 1995;2:291-8] models, incorporating patterns of synaptic connectivity based on an extensive review of the neuroanatomic literature. When stimulated with a one second physiologically realistic input, our simulated tissue shows the ability to hold activity on-line for several seconds; furthermore, its spiking activity, as measured by frequency and interspike interval (ISI) distributions, resembles that of in vivo hippocampus. An interesting emergent property of the system is its tendency to transition from stable state to stable state, a behavior consistent with recent experimental findings [Sasaki T, Matsuki N, Ikegaya Y. Metastability of active CA3 networks. J Neurosci 2007;27:517-28]. Inspection of spike trains and simulated blockade of K(AHP) channels suggest that this is mediated by spike frequency adaptation. This finding, in conjunction with studies showing that apamin, a K(AHP) channel blocker, enhances the memory consolidation process in laboratory animals, suggests the formation of stable attractor states is central to the process by which memories are encoded. Ways that this methodology could shed light on the etiology of mental illness, such as schizophrenia, are discussed.

Capacity-enhancing synaptic learning rules in a medial temporal lobe online learning model

Medial temporal lobe structures are responsible for recording the continuous stream of autobiographical memories that define our unique personal history. Remarkably, these areas can construct durable memories from brief exposures to the constantly changing activity patterns arriving from antecedent cortical areas. Using a computer model of the hippocampal Schaffer collateral pathway that incorporates evidence for dendritic spikes in CA1 pyramidal neurons, we searched for biologically-plausible long-term potentiation (LTP) and homeostatic depression (HD) rules that maximize "online" learning capacity. We found memory utilization is most efficient when (1) very few synapses are modified to store each pattern, (2) LTP, the learning operation, is dendrite-specific and gated by distinct pre- and postsynaptic thresholds, (3) HD, the forgetting operation, co-occurs with LTP and targets least-recently potentiated synapses, and (4) both LTP and HD are all-or-none, leading de facto to binary-valued synaptic weights. In networks containing up to 40 million synapses, the learning scheme led to order-of-magnitude capacity increases compared to conventional plasticity rules.

Understanding memory through hippocampal remapping

Memory interference is a common cause of forgetting. Interference is a byproduct of the need to balance the formation of well-differentiated representations against the ability to retrieve memories from cues that are not identical to the original experience. How the brain accomplishes this has remained elusive. Here we review how insights can be gained from studies of an apparently unrelated phenomenon in the rodent brain--remapping in hippocampal place cells. Remapping refers to the formation of distinct representations in populations of place cells after minor changes in inputs to the hippocampus. Remapping might reflect processes involved generally in decorrelation of overlapping signals. These processes might be crucial for storing large numbers of similar experiences with only minimal interference.

A neural network model of hippocampal-striatal-prefrontal interactions in contextual conditioning

The hippocampus is thought to be critical for encoding contextually bound memories and setting the context for ongoing behavior. However, the mechanisms by which the hippocampal-cortical system controls behavior are poorly understood. We propose a computational model in which the hippocampus exerts contextual control over motivated behavior by gating prefrontal cortex inputs to the nucleus accumbens. The model integrates the episodic memory functions of the hippocampus, the prefrontal role in representing the motivational stimuli and cognitive control, and the role of striatal regions in conditioned learning within a single theoretical framework. Simulation results are consistent with the hypothesis that hippocampal-prefrontal interactions may act as the neural substrate that allows contextual cues to override conditioned responses at the level of the nucleus accumbens. Prefrontal and hippocampal input overrides the predominant CS-US association if the context is inconsistent, and promotes flexible selection of previously learned associations and behaviors. Simulated transection of the fornix, effectively eliminating hippocampal and prefrontal influence over the nucleus accumbens, abolishes normal contextual modulation of behavior. The model is consistent with a wide range of empirical data.

Design-based estimation of neuronal number and individual neuronal volume in the rat hippocampus

Tools recently developed in stereology were employed for unbiased estimation of the neuronal number and volume in three major subdivisions of rat hippocampus (dentate granular, CA1 and CA3 pyramidal layers). The optical fractionator is used extensively in quantitative studies of the hippocampus; however, the classical optical fractionator design may be affected by tissue deformation in the z-axis of the section. In this study, we applied an improved optical fractionator design to estimate total number of neurons on 100 microm thick vibratome sections that had been deformed, in the z-dimension, during histological processing. For estimating cell number, it is necessary to randomize only the location of section planes. But, in the local stereological methods, like cell volume estimation, the orientation of sections must also be randomized. We present a detailed application of a method for making vertical sections from the hippocampus. The volume of hippocampal neurons was estimated using the rotator principle on 40 microm thick plastic vertical uniform random sections and corrected for tissue shrinkage. Application of the proposed new design should result in more accurate estimates of neuron number and neuronal volumes in tissue sections affected by homogenous non-uniform shrinkage.

The effect of neuronal population size on the development of epileptiform discharges in the low calcium model of epilepsy

The CA1 region of the rat hippocampal slice generates spontaneous electrographic seizures (field bursts) when exposed to ACSF containing < or = 0.2 mM calcium. It has been proposed that, particularly during the early part of a field burst, synchronised activity in small independent aggregates of neurons results in low amplitude irregular population spikes and subsequent fusion of aggregates generates high amplitude, regular discharging spikes. In the present experiments, we have tested the hypothesis that progression from aggregate formation to aggregate fusion requires a critical mass of participating neurons. We found that isolated CA1 segments >2 mm are still able to generate high amplitude, regular discharging population spikes, but when segment length is reduced to 1-2 mm, only 29% generate spikes with these characteristics; in the remainder, the field burst shows a DC shift+/-low amplitude irregular population spikes. No field bursts were seen in segments < 0.7 mm or in 50% of those 0.7-1 mm in length (in the remaining 50%, only the DC component of the field burst was present). Exposing 1-2 mm segments to hypo-osmolar perfusate induced a return of high amplitude rhythmic discharging population spikes in the field burst. We interpret these observations by indicating that progression from aggregate formation to aggregate fusion requires a critical neuronal mass and can be enhanced by reducing osmolarity of the perfusate.

Estradiol's effects on learning and neuronal morphology vary with route of administration

Estrogen's effects on performance and neuronal morphology are variable, and the reasons for this variability are not yet understood. In this study, the authors compared the effects of 2 delivery routes of 17 beta-estradiol on spatial learning and dendritic spine densities in young ovariectomized rats; estradiol was administered by implanted capsules or by daily oral gavage. Estradiol treatment via capsules improved performance in the radial-arm water maze and increased spine densities on dendrites of CA1 pyramidal neurons in the hippocampal formation. In contrast, daily oral administration of estradiol did not affect either measure. These data demonstrate that estradiol delivery is a critical variable in animal studies and that clinical studies comparing the effects of different estradiol treatment routes on cognition are warranted.

Intersection of microwire electrodes with proximal CA1 stratum-pyramidale neurons at insertion for multiunit recordings predicted by a 3-D computer model

It is of broad interest in the context of neuronal multiunit extracellular recordings to understand electrode-tissue interactions in order to maximize the number of recordable units and to minimize experimental artifacts due to mechanical tissue alteration. Toward this goal, a computer model of microwire electrode insertion in hippocampus CA1 area was developed, firstly to provide estimates of the number of electrode-neuron intersections affecting recordable (local) neurons and, secondly, to determine optimal insertion/electrode parameters that minimize the number of intersections. The model predicts that in hippocampus CA1 area, using an electrode 50 microm in diameter, only 10% of the recordable neurons (those within 50 microm of the electrode), would remain collision free. Moreover, the model also predicts that inhibitory neurons are less prone to be intersected by the electrode, resulting in a 2 to threefold higher percentage of collision-free interneurons than expected from the relative densities of pyramidal cells and interneurons. Furthermore, the model confirms, in agreement with experimental observations, that electrode tilting with respect to the main neuronal axis increases the number of intact neurons (fourfold for a 50-microm electrode at 45 degrees when compared to 0 degrees , i.e., an insertion normal to the cell body layer).

Prenatal protracted irradiation at very low dose rate induces severe neuronal loss in rat hippocampus and cerebellum

Prenatal irradiation is known to damage the developing brain. However, little is known about the consequences of very low dose rate prenatal protracted irradiation over several days on neuron numbers in the offspring brain, and on volumes of the corresponding brain regions. Pregnant Wistar rats were exposed either to a protracted gamma irradiation from embryonic day (E) 13 to E16 (0.7 mGy/min; total cumulative dose approximately 3 Gy) or were sham-irradiated. Thirty months old male and female offspring were then analyzed for alterations in hippocampal and cerebellar morphology. Using design-based stereology and the analysis of sets of sections systematically and randomly sampled to span the entire brain region of interest, a statistically significant decrease in numbers of hippocampal pyramidal and granule cells as well as of cerebellar Purkinje and granule cells (approximately 50%) was found in male and female irradiated offspring. The volumes of these brain regions were comparably altered. The analysis of only a "representative" section per animal yielded mostly non-significant trends. Evaluation of neuron densities showed no differences between prenatally irradiated and sham-irradiated offspring. Most importantly, very low dose rate prenatal protracted gamma irradiation did not result in the same morphologic alterations in the offspring brain as previously observed after prenatal single irradiation such as derangement of the laminar structure of pyramidal cells within the hippocampus or malformation of cerebellar lobules.

Effects of stimulus frequency and age on bidirectional synaptic plasticity in the dentate gyrus of freely moving rats

We investigated the frequency-dependent transition from homosynaptic long-term depression (LTD) to long-term potentiation (LTP) at the lateral perforant pathway/dentate gyrus synapse in adult (90 days of age) and immature (15 days of age) awake, freely moving rats. Dentate-evoked field potentials were recorded and analyzed using the population spike amplitude and the field EPSP slope measures following sustained stimulation (900 pulses) of the lateral perforant pathway at various frequencies (1, 3, 7, 30, 50, or 200 Hz). Our results indicate that both the strength and the direction (LTP or LTD) of synaptic plasticity vary as a function of activation frequency: sustained low-frequency stimulation ranging from 1 to 7 Hz results in depression of activated synapses, whereas high-frequency stimulation (30-200 Hz) produces potentiation. In addition, a significant (P < 0.01) ontogenetic shift in the frequency of transition from LTD to LTP was observed; the transition frequency in immature animals was significantly lower than that obtained in adult animals. These observations agree strongly with the prediction of the Bienenstock-Cooper-Munro theory of synapse modification, indicating perhaps a neurophysiological basis for this theoretical model of learning in the dentate gyrus of awake behaving rats.

Exercise increases the vulnerability of rat hippocampal neurons to kainate lesion

Available evidence suggests that regular, moderate-intensity exercise has beneficial effects on neural health, perhaps including neuroprotection. To evaluate this idea further, we compared the severity of kainate-induced neuronal loss in exercised versus sedentary female rats. Stereological estimations of neuron number revealed that rats in the exercise condition exhibited significantly greater neuron loss in hippocampal region CA2/3, suggesting that high levels of physical activity may increase neuronal vulnerability to excitotoxicity.

Development of spatial firing in the hippocampus of young rats

The hippocampal formation participates in learning and memory, particularly that of a spatial nature. In adult rats, individual CA1 pyramidal neurons only fire when the animal visits specific locations in an environment, the "place field" of the neuron. Other structures (postsubiculum, thalamus, cingulum) contain neurons that code for the animal's instantaneous head direction. Previous work has shown that the rat hippocampal formation undergoes anatomical and neurophysiological maturation during the first 2 months of life and that rats <40 days of age are impaired in spatial navigation tasks. Here we show that the locational firing of CA1 pyramidal neurons is both less specific and less stable in animals aged <50 days. However, preliminary results indicate that head directional firing recorded around day 30 is essentially identical to that seen in adult animals. Therefore, the development of reliable, spatially specific place cell activity parallels the developmental time course of spatial navigational ability, but head directional firing appears before full maturation of the hippocampus.

Hippocampal and neocortical contributions to memory: advances in the complementary learning systems framework

The complementary learning systems framework provides a simple set of principles, derived from converging biological, psychological and computational constraints, for understanding the differential contributions of the neocortex and hippocampus to learning and memory. The central principles are that the neocortex has a low learning rate and uses overlapping distributed representations to extract the general statistical structure of the environment, whereas the hippocampus learns rapidly using separated representations to encode the details of specific events while minimizing interference. In recent years, we have instantiated these principles in working computational models, and have used these models to address human and animal learning and memory findings, across a wide range of domains and paradigms. Here, we review a few representative applications of our models, focusing on two domains: recognition memory and animal learning in the fear-conditioning paradigm. In both domains, the models have generated novel predictions that have been tested and confirmed.

Structural inhomogeneities differentially modulate action currents and population spikes initiated in the axon or dendrites

Action potentials (APs) in CA1 pyramidal cells propagate in different directions along the somatodendritic axis depending on the activation mode (synaptic or axonal). We studied how the geometrical inhomogeneities along the apical shaft, soma, and initial axon modulate the transmembrane current (I(m)) flow underlying APs, using model and experimental techniques. The computations obtained at the subcellular level during forward- and backpropagation were extrapolated to macroscopic level (field potentials) and compared with the basic in vivo features of the ortho- and antidromic population spike (PS) that reflects the sum total of all elementary currents from synchronously firing cells. The matching of theoretical and experimental results supports the following conclusions. Because the charge carried by axonal APs is almost entirely drained into dendrites, the soma invasion is preceded by little capacitive currents (I(cap)), the ionic currents (I(ion)) dominating I(m) and the depolarizing phase. The subsequent invasion of the tapering apical shaft is preceded, however, by significant I(cap), while I(ion) decayed gradually. A similar pattern occurred during backpropagation of spikes synaptically initiated in the axon. On the contrary, when the AP was apically initiated, the dendritic I(ion) was boosted by the apical flare, it was preceded by weak I(cap) and spread forwardly at a slower velocity. Soma invasion is reliable once the AP reached the main apical shaft but less so distal to the primary bifurcation, where it may be upheld by concurrent synaptic activity. The decreasing internal resistance of the apical shaft guided most axial current into the soma, causing its fast charging. There, I(ion) began later in the depolarizing phase of the AP and the reduced driving force made it smaller. This, in addition to a poor temporal overlapping of somatodendritic inward currents within individual cells, built a smaller extracellular sink, i.e., a smaller PS. In both experiment and model, the antidromic (axon-initiated) PS in the soma layer is approximately 30% larger than an orthodromic (apical shaft-initiated) PS contributed by the same number of firing cells. We conclude that the dominance of capacitive or ionic current components on I(m) is a distinguishing feature of forward and backward APs that is predictable from the geometric inhomogeneities between conducting subregions. Correspondingly, experimental and model APs have a faster rising slope during ortho than antidromic activation. The moderate flare of the apical shaft makes forward AP conduction quite safe. This alternative trigger zone enables two different processing modes for apical inputs.

Life-long stability of neurons: a century of research on neurogenesis, neuronal death and neuron quantification in adult CNS

In this chapter we provide an extensive review of 100 years of research on the stability of neurons in the mammalian brain, with special emphasis on humans. Although Cajal formulated the Neuronal Doctrine, he was wrong in his beliefs that adult neurogenesis did not occur and adult neurons are dying throughout life. These two beliefs became accepted "common knowledge" and have shaped much of neuroscience research and provided much of the basis for clinical treatment of age-related brain diseases. In this review, we consider adult neurogenesis from a historical and evolutionary perspective. It is concluded, that while adult neurogenesis is a factor in the dynamics of the dentate gyrus and olfactory bulb, it is probably not a major factor during the life-span in most brain areas. Likewise, the acceptance of neuronal death as an explanation for normal age-related senility is challenged with evidence collected over the last fifty years. Much of the problem in changing this common belief of dying neurons was the inadequacies of neuronal counting methods. In this review we discuss in detail implications of recent improvements in neuronal quantification. We conclude: First, age-related neuronal atrophy is the major factor in functional deterioration of existing neurons and could be slowed down, or even reversed by various pharmacological interventions. Second, in most cases neuronal degeneration during aging is a pathology that in principle may be avoided. Third, loss of myelin and of the white matter is more frequent and important than the limited neuronal death in normal aging.

Geometry and structural plasticity of synaptic connectivity

Changes in synaptic connectivity patterns through the formation and elimination of dendritic spines may contribute to structural plasticity in the brain. We characterize this contribution quantitatively by estimating the number of different synaptic connectivity patterns attainable without major arbor remodeling. This number depends on the ratio of the synapses on a dendrite to the axons that pass within a spine length of that dendrite. We call this ratio the filling fraction and calculate it from geometrical analysis and anatomical data. The filling fraction is 0.26 in mouse neocortex, 0.22-0.34 in rat hippocampus. In the macaque visual cortex, the filling fraction increases by a factor of 1.6-1.8 from area V1 to areas V2, V4, and 7a. Since the filling fraction is much smaller than 1, spine remodeling can make a large contribution to structural plasticity.

Neonatal novelty exposure modulates hippocampal volumetric asymmetry in the rat

Early life environmental manipulations have been shown to affect hippocampal-dependent learning, hippocampal volume and cerebral lateralization. In this study, we investigated the effects of neonatal stimulation on hippocampal volumetric asymmetry. Long-Evans hooded rats were exposed to a novel non-home environment 3 min daily for the first 3 weeks of life. Histological measures of the left and right hippocampus were made at 8 months of age. We found that neonatal novelty exposure resulted in a long-lasting change in hippocampal volumetric asymmetry. Specifically, this brief and transient early life stimulation increased the right hippocampal volumetric dominance at mid-adulthood.

Conjunctive representations in learning and memory: principles of cortical and hippocampal function

The authors present a theoretical framework for understanding the roles of the hippocampus and neocortex in learning and memory. This framework incorporates a theme found in many theories of hippocampal function: that the hippocampus is responsible for developing conjunctive representations binding together stimulus elements into a unitary representation that can later be recalled from partial input cues. This idea is contradicted by the fact that hippocampally lesioned rats can learn nonlinear discrimination problems that require conjunctive representations. The authors' framework accommodates this finding by establishing a principled division of labor, where the cortex is responsible for slow learning that integrates over multiple experiences to extract generalities whereas the hippocampus performs rapid learning of the arbitrary contents of individual experiences. This framework suggests that tasks involving rapid, incidental conjunctive learning are better tests of hippocampal function. The authors implement this framework in a computational neural network model and show that it can account for a wide range of data in animal learning.

Distribution of thorny excrescences on CA3 pyramidal neurons in the rat hippocampus

Thorny excrescences are the postsynaptic components of synapses between mossy fibers of granule cells and dendrites of CA3 pyramidal neurons in the hippocampal formation. Very little quantitative data on the number and distribution of excrescences in adult rats are available because, first, the vast majority are grouped into clusters and it is not possible to identify single excrescences within these clusters at the light microscope level. Second, clusters are of varying lengths and are distributed over hundreds of micrometers, making ultrastructural analysis prohibitively time-consuming. Here, by using three-dimensional analysis techniques at the light microscope level, we quantified the number, length, and distribution of excrescence clusters on proximal and midfield pyramidal neurons in the rat. Results indicated that proximal neurons had similar numbers of clusters on their apical and basal trees, and that cluster length was also similar. In contrast, midfield neurons had more apical than basal clusters, and apical clusters were longer. For neurons in both regions, basal clusters were located about 50% closer to somata. Overall, proximal neurons had more clusters than did midfield neurons, but the clusters were shorter; thus, proximal and midfield neurons had about the same total cluster length, and presumably the same number of single excrescences. Based on these data and on published ultrastructural measurements of single excrescences, we estimated an average of 41 excrescences/neuron, and suggest that a pyramidal neuron can be contacted by a maximum of 41 mossy fiber boutons, each from a different granule cell.

Intracellular features predicted by extracellular recordings in the hippocampus in vivo

Multichannel tetrode array recording in awake behaving animals provides a powerful method to record the activity of large numbers of neurons. The power of this method could be extended if further information concerning the intracellular state of the neurons could be extracted from the extracellularly recorded signals. Toward this end, we have simultaneously recorded intracellular and extracellular signals from hippocampal CA1 pyramidal cells and interneurons in the anesthetized rat. We found that several intracellular parameters can be deduced from extracellular spike waveforms. The width of the intracellular action potential is defined precisely by distinct points on the extracellular spike. Amplitude changes of the intracellular action potential are reflected by changes in the amplitude of the initial negative phase of the extracellular spike, and these amplitude changes are dependent on the state of the network. In addition, intracellular recordings from dendrites with simultaneous extracellular recordings from the soma indicate that, on average, action potentials are initiated in the perisomatic region and propagate to the dendrites at 1.68 m/s. Finally we determined that a tetrode in hippocampal area CA1 theoretically should be able to record electrical signals from approximately 1, 000 neurons. Of these, 60-100 neurons should generate spikes of sufficient amplitude to be detectable from the noise and to allow for their separation using current spatial clustering methods. This theoretical maximum is in contrast to the approximately six units that are usually detected per tetrode. From this, we conclude that a large percentage of hippocampal CA1 pyramidal cells are silent in any given behavioral condition.