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In JoVE (1)
Other Publications (10)
- The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
- The Journal of Physiology
- Journal of Computational Neuroscience
- Nature Neuroscience
- The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
- The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
- Proceedings of the National Academy of Sciences of the United States of America
- The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
- Nature Neuroscience
- Hippocampus
Articles by Kamran Diba in JoVE
Large-scale Recording of Neurons by Movable Silicon Probes in Behaving Rodents
Marie Vandecasteele1,2, S. M.1, Sébastien Royer1,3, Mariano Belluscio1, Antal Berényi1, Kamran Diba1,4, Shigeyoshi Fujisawa1, Andres Grosmark1, Dun Mao1, Kenji Mizuseki1, Jagdish Patel1, Eran Stark1, David Sullivan1, Brendon Watson1, György Buzsáki1
1Center for Molecular and Behavioral Neuroscience, University of New Jersey, 2Center for Interdisciplinary Research in Biology, Collège de France, 3Janelia Farm Research Campus, Howards Hughes Medical Institute, 4Deptartment of Psychology, University of Wisconsin at Milwaukee
We describe methods for large-scale recording of multiple single units and local field potential in behaving rodents with silicon probes. Drive fabrication, probe attachment to the drive and probe implantation processes are illustrated in sufficient details for easy replication.
Other articles by Kamran Diba on PubMed
Intrinsic Noise in Cultured Hippocampal Neurons: Experiment and Modeling
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience. Oct, 2004 | Pubmed ID: 15509761
Ion channels open and close stochastically. The fluctuation of these channels represents an intrinsic source of noise that affects the input-output properties of the neuron. We combined whole-cell measurements with biophysical modeling to characterize the intrinsic stochastic and electrical properties of single neurons as observed at the soma. We measured current and voltage noise in 18 d postembryonic cultured neurons from the rat hippocampus, at various subthreshold and near-threshold holding potentials in the presence of synaptic blockers. The observed current noise increased with depolarization, as ion channels were activated, and its spectrum demonstrated generalized 1/f behavior. Exposure to TTX removed a significant contribution from Na+ channels to the noise spectrum, particularly at depolarized potentials, and the resulting spectrum was now dominated by a single Lorentzian (1/f2) component. By replacing the intracellular K+ with Cs+, we demonstrated that a major portion of the observed noise was attributable to K+ channels. We compared the measured power spectral densities to a 1-D cable model of channel fluctuations based on Markov kinetics. We found that a somatic compartment, in combination with a single equivalent cylinder, described the effective geometry from the viewpoint of the soma. Four distinct channel populations were distributed in the membrane and modeled as Lorentzian current noise sources. Using the NEURON simulation program, we summed up the contributions from the spatially distributed current noise sources and calculated the total voltage and current noise. Our quantitative model reproduces important voltage- and frequency-dependent features of the data, accounting for the 1/f behavior, as well as the effects of various blockers.
Subthreshold Voltage Noise of Rat Neocortical Pyramidal Neurones
The Journal of Physiology. Apr, 2005 | Pubmed ID: 15695244
Neurones are noisy elements. Noise arises from both intrinsic and extrinsic sources, and manifests itself as fluctuations in the membrane potential. These fluctuations limit the accuracy of a neurone's output but have also been suggested to play a computational role. We present a detailed study of the amplitude and spectrum of voltage noise recorded at the soma of layer IV-V pyramidal neurones in slices taken from rat neocortex. The dependence of the noise on holding potential, synaptic activity and Na+ conductance is systematically analysed. We demonstrate that voltage noise increases non-linearly as the cell depolarizes (from a standard deviation (s.d.) of 0.19 mV at -75 mV to an s.d. of 0.54 mV at -55 mV). The increase in voltage noise is accompanied by an increase in the cell impedance, due to voltage dependence of Na+ conductance. The impedance increase accounts for the majority (70%) of the voltage noise increase. The increase in voltage noise and impedance is restricted to the low-frequency range (0.2-2 Hz). At the high frequency range (5-100 Hz) the voltage noise is dominated by synaptic activity. In our slice preparation, synaptic noise has little effect on the cell impedance. A minimal model reproduces qualitatively these data. Our results imply that ion channel noise contributes significantly to membrane voltage fluctuations at the subthreshold voltage range, and that Na+ conductance plays a key role in determining the amplitude of this noise by acting as a voltage-dependent amplifier of low-frequency transients.
Spike Propagation in Dendrites with Stochastic Ion Channels
Journal of Computational Neuroscience. Feb, 2006 | Pubmed ID: 16649068
We investigate the effects of the stochastic nature of ion channels on the faithfulness, precision and reproducibility of electrical signal transmission in weakly active, dendritic membrane under in vitro conditions. The properties of forward and backpropagating action potentials (BPAPs) in the dendritic tree of pyramidal cells are the subject of intense empirical work and theoretical speculation (Larkum et al., 1999; Zhu, 2000; Larkum et al., 2001; Larkum and Zhu, 2002; Schaefer et al., 2003; Williams, 2004; Waters et al., 2005). We numerically simulate the effects of stochastic ion channels on the forward and backward propagation of dendritic spikes in Monte-Carlo simulations on a reconstructed layer 5 pyramidal neuron. We report that in most instances there is little variation in timing or amplitude for a single BPAP, while variable backpropagation can occur for trains of action potentials. Additionally, we find that the generation and forward propagation of dendritic Ca(2+) spikes are susceptible to channel variability. This indicates limitations on computations that depend on the precise timing of Ca(2+) spikes.
Forward and Reverse Hippocampal Place-cell Sequences During Ripples
Nature Neuroscience. Oct, 2007 | Pubmed ID: 17828259
We report that temporal spike sequences from hippocampal place neurons of rats on an elevated track recurred in reverse order at the end of a run, but in forward order in anticipation of the run, coinciding with sharp waves. Vector distances between the place fields were reflected in the temporal structure of these sequences. This bidirectional re-enactment of temporal sequences may contribute to the establishment of higher-order associations in episodic memory.
Hippocampal Network Dynamics Constrain the Time Lag Between Pyramidal Cells Across Modified Environments
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience. Dec, 2008 | Pubmed ID: 19074018
The hippocampus provides a spatial map of the environment. Changes in the environment alter the firing patterns of hippocampal neurons, but are presumably constrained by elements of the network dynamics. We compared the neural activity in CA1 and CA3 regions of the hippocampus in rats running for water reward on a linear track, before and after the track length was shortened. A fraction of cells lost their place fields and new sets of cells with fields emerged, indicating distinct representation of the two tracks. Cells active in both environments shifted their place fields in a location-dependent manner, most notably at the beginning and the end of the track. Furthermore, peak firing rates and place-field sizes decreased, whereas place-field overlap and coactivity increased. Power in the theta-frequency band of the local field potentials also decreased in both CA1 and CA3, along with the coherence between the two structures. In contrast, the theta-scale (0-150 ms) time lags between cell pairs, representing distances on the tracks, were conserved, and the activity of the inhibitory neuron population was maintained across environments. We interpret these observations as reflecting the freedoms and constraints of the hippocampal network dynamics. The freedoms permit the necessary flexibility for the network to distinctly represent unique patterns, whereas the dynamics constrain the speed at which activity propagates between the cell assemblies representing the patterns.
Single-trial Phase Precession in the Hippocampus
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience. Oct, 2009 | Pubmed ID: 19846711
During the crossing of the place field of a pyramidal cell in the rat hippocampus, the firing phase of the cell decreases with respect to the local theta rhythm. This phase precession is usually studied on the basis of data in which many place field traversals are pooled together. Here we study properties of phase precession in single trials. We found that single-trial and pooled-trial phase precession were different with respect to phase-position correlation, phase-time correlation, and phase range. Whereas pooled-trial phase precession may span 360 degrees , the most frequent single-trial phase range was only approximately 180 degrees. In pooled trials, the correlation between phase and position (r = -0.58) was stronger than the correlation between phase and time (r = -0.27), whereas in single trials these correlations (r = -0.61 for both) were not significantly different. Next, we demonstrated that phase precession exhibited a large trial-to-trial variability. Overall, only a small fraction of the trial-to-trial variability in measures of phase precession (e.g., slope or offset) could be explained by other single-trial properties (such as running speed or firing rate), whereas the larger part of the variability remains to be explained. Finally, we found that surrogate single trials, created by randomly drawing spikes from the pooled data, are not equivalent to experimental single trials: pooling over trials therefore changes basic measures of phase precession. These findings indicate that single trials may be better suited for encoding temporally structured events than is suggested by the pooled data.
Temporal Delays Among Place Cells Determine the Frequency of Population Theta Oscillations in the Hippocampus
Proceedings of the National Academy of Sciences of the United States of America. Apr, 2010 | Pubmed ID: 20375279
Driven either by external landmarks or by internal dynamics, hippocampal neurons form sequences of cell assemblies. The coordinated firing of these active cells is organized by the prominent "theta" oscillations in the local field potential (LFP): place cells discharge at progressively earlier theta phases as the rat crosses the respective place field ("phase precession"). The faster oscillation frequency of active neurons and the slower theta LFP, underlying phase precession, creates a paradox. How can faster oscillating neurons comprise a slower population oscillation, as reflected by the LFP? We built a mathematical model that allowed us to calculate the population activity analytically from experimentally derived parameters of the single neuron oscillation frequency, firing field size (duration), and the relationship between within-theta delays of place cell pairs and their distance representations ("compression"). The appropriate combination of these parameters generated a constant frequency population rhythm along the septo-temporal axis of the hippocampus, while allowing individual neurons to vary their oscillation frequency and field size. Our results suggest that the faster-than-theta oscillations of pyramidal cells are inherent and that phase precession is a result of the coordinated activity of temporally shifted cell assemblies, relative to the population activity, reflected by the LFP.
Relationships Between Hippocampal Sharp Waves, Ripples, and Fast Gamma Oscillation: Influence of Dentate and Entorhinal Cortical Activity
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience. Jun, 2011 | Pubmed ID: 21653864
Hippocampal sharp waves (SPWs) and associated fast ("ripple") oscillations (SPW-Rs) in the CA1 region are among the most synchronous physiological patterns in the mammalian brain. Using two-dimensional arrays of electrodes for recording local field potentials and unit discharges in freely moving rats, we studied the emergence of ripple oscillations (140-220 Hz) and compared their origin and cellular-synaptic mechanisms with fast gamma oscillations (90-140 Hz). We show that (1) hippocampal SPW-Rs and fast gamma oscillations are quantitatively distinct patterns but involve the same networks and share similar mechanisms; (2) both the frequency and magnitude of fast oscillations are positively correlated with the magnitude of SPWs; (3) during both ripples and fast gamma oscillations the frequency of network oscillation is higher in CA1 than in CA3; and (4) the emergence of CA3 population bursts, a prerequisite for SPW-Rs, is biased by activity patterns in the dentate gyrus and entorhinal cortex, with the highest probability of ripples associated with an "optimum" level of dentate gamma power. We hypothesize that each hippocampal subnetwork possesses distinct resonant properties, tuned by the magnitude of the excitatory drive.
Hippocampal CA1 Pyramidal Cells Form Functionally Distinct Sublayers
Nature Neuroscience. Sep, 2011 | Pubmed ID: 21822270
Hippocampal CA1 pyramidal neurons have frequently been regarded as a homogeneous cell population in biophysical, pharmacological and modeling studies. We found robust differences between pyramidal neurons residing in the deep and superficial CA1 sublayers in rats. Compared with their superficial peers, deep pyramidal cells fired at higher rates, burst more frequently, were more likely to have place fields and were more strongly modulated by slow oscillations of sleep. Both deep and superficial pyramidal cells fired preferentially at the trough of theta oscillations during maze exploration, whereas deep pyramidal cells shifted their preferred phase of firing to the peak of theta during rapid eye movement (REM) sleep. Furthermore, although the majority of REM theta phase-shifting cells fired at the ascending phase of gamma oscillations during waking, nonshifting cells preferred the trough. Thus, CA1 pyramidal cells in adjacent sublayers can address their targets jointly or differentially, depending on brain states.
Activity Dynamics and Behavioral Correlates of CA3 and CA1 Hippocampal Pyramidal Neurons
Hippocampus. Feb, 2012 | Pubmed ID: 22367959
The CA3 and CA1 pyramidal neurons are the major principal cell types of the hippocampus proper. The strongly recurrent collateral system of CA3 cells and the largely parallel-organized CA1 neurons suggest that these regions perform distinct computations. However, a comprehensive comparison between CA1 and CA3 pyramidal cells in terms of firing properties, network dynamics, and behavioral correlations is sparse in the intact animal. We performed large-scale recordings in the dorsal hippocampus of rats to quantify the similarities and differences between CA1 (n > 3,600) and CA3 (n > 2,200) pyramidal cells during sleep and exploration in multiple environments. CA1 and CA3 neurons differed significantly in firing rates, spike burst propensity, spike entrainment by the theta rhythm, and other aspects of spiking dynamics in a brain state-dependent manner. A smaller proportion of CA3 than CA1 cells displayed prominent place fields, but place fields of CA3 neurons were more compact, more stable, and carried more spatial information per spike than those of CA1 pyramidal cells. Several other features of the two cell types were specific to the testing environment. CA3 neurons showed less pronounced phase precession and a weaker position versus spike-phase relationship than CA1 cells. Our findings suggest that these distinct activity dynamics of CA1 and CA3 pyramidal cells support their distinct computational roles. © 2012 Wiley Periodicals, Inc.
