Kamran Diba

Forward and reverse hippocampal place-cell sequences during ripples.

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 CA1 pyramidal cells form functionally distinct sublayers

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.

Relationships between Hippocampal Sharp Waves, Ripples, and Fast Gamma Oscillation: Influence of Dentate and Entorhinal Cortical Activity

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.

Subthreshold voltage noise of rat neocortical pyramidal neurones

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 neurones 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.

Activity Dynamics and Behavioral Correlates of CA3 and CA1 Hippocampal Pyramidal Neurons

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.

Hippocampal network dynamics constrain the time lag between pyramidal cells across modified environments

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.

Temporal delays among place cells determine the frequency of population theta oscillations in the hippocampus

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.

Intrinsic Noise in Cultured Hippocampal Neurons: Experiment and Modeling

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/fbehavior. 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.

Single-Trial Phase Precession in the Hippocampus

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°, the most frequent single-trial phase range was only ∼180°. 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.

Prefrontal Activity Links Nonoverlapping Events in Memory

The medial prefrontal cortex (mPFC) plays an important role in memory. By maintaining a working memory buffer, neurons in prelimbic (PL) mPFC may selectively contribute to learning associations between stimuli that are separated in time, as in trace fear conditioning (TFC). Until now, evidence for this bridging role was largely descriptive. Here we used optogenetics to silence neurons in the PL mPFC of rats during learning in TFC. Memory formation was prevented when mPFC was silenced specifically during the interval separating the cue and shock. Our results provide support for a working memory function for these cells and indicate that associating two noncontiguous stimuli requires bridging activity in PL mPFC.