Abstract
To support cognitive function, the CA3 region of the hippocampus performs computations involving attractor dynamics. Understanding how cellular and ensemble activities of CA3 neurons enable computation is critical for elucidating the neural correlates of cognition. Here we show that CA3 comprises not only classically described pyramid cells with thorny excrescences, but also includes previously unidentified ‘athorny’ pyramid cells that lack mossy-fiber input. Moreover, the two neuron types have distinct morphological and physiological phenotypes and are differentially modulated by acetylcholine. To understand the contribution of these athorny pyramid neurons to circuit function, we measured cell-type-specific firing patterns during sharp-wave synchronization events in vivo and recapitulated these dynamics with an attractor network model comprising two principal cell types. Our data and simulations reveal a key role for athorny cell bursting in the initiation of sharp waves: transient network attractor states that signify the execution of pattern completion computations vital to cognitive function.
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Acknowledgements
We thank B. Shields for assistance with histology; D. Jin and R. Pearcy for assistance with morphological reconstructions; D. Otstot for animal breeding and genotyping; and L. Frank, J. Fitzgerald, J. Magee, and members of the Spruston lab for comments on the manuscript. This work was made possible by funding from the Howard Hughes Medical Institute.
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D.L.H. conceived the project and designed the experiments in consultation with N.S. D.L.H. acquired and analyzed the in vitro electrophysiology data. D.L.H. acquired the in vivo electrophysiology data. D.L.H. and D.L. analyzed the in vivo electrophysiology data. B.S. and S.R. performed network simulations in consultation with D.L.H. and N.S. D.L.H. and N.S. wrote the manuscript with input from all co-authors.
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Supplementary Figure 1 Countermodulation of CA3 pyramidal neurons in rat hippocampus.
a-c) Three examples of athorny pyramidal neurons identified from rat hippocampal slices (n = 5 cells). Left, low magnification bright-field image of CA3 region where recoded neuron is stained with biocytin and indicated by green arrow. Middle panel, 2-photon image (max intensity projection) taken at 60X magnification where no thorny excrescences can be observed on any of the three example cells. Right panel, firing pattern elicited by somatic current injection, illustrating the intrinsically bursting firing pattern. d) Representative traces from a rat CA3 pyramidal cell under control conditions (no drugs) where a regular spiking firing pattern is observed close to rheobase, and the subsequent shift in intrinsic properties to burst-firing in the presence of the cholinergic agonist carbachol. e) Representative traces from a CA3 pyramidal cell of a rat under control conditions where a burst-firing pattern is observed close to rheobase and the shift in intrinsic properties to regular spiking in the presence of the cholinergic agonist carbachol. f) Left, summary data of individual data points for the input-output relationship of 8 regular spiking cells recorded under control conditions, and for 5 cells recorded in the presence of carbachol. Right, mean and SEM for control and carbachol conditions (rheobase current p = 0.2; output frequency p = 0.03, two-sided paired t-test) g) Left, summary data of individual data points for the input-output relationship of 9 bursting cells recorded under control conditions, and for 5 cells recorded in the presence of carbachol. Right, mean and SEM for control and carbachol conditions (rheobase current p = 0.49; output frequency p = 0.04, two-sided paired t-test).
Supplementary Figure 2 Thorny and athorny neurons can be labeled by Golgi staining.
a) Schematic of hippocampal region isolated for Golgi staining. b) Low magnification bright-field image of Golgi stained hippocampus (opaque, black) and co-staining with cresyl violet to indicate the locations of cell bodies (n = 3 animals). c) Representative example of a thorny pyramidal cell which were abundant in each brain tested, where thorny excrescences adorn the proximal apical dendrite indicated by red arrows (n = 5 cells). d) Representative example of an athorny cell which were reliably identified in each brain tested, where no complex multi-headed spines are apparent along the main apical dendritic shaft although simple spines are present, indicating that the imaged cell is unlikely to be an inhibitory interneuron (n = 10 cells identified).
Supplementary Figure 3 Athorny neurons are negative for the GABAergic marker VGAT.
a, b) Representative low-magnification images of virally labeled deep-layer excitatory cells that are negative for the inhibitory marker vesicular GABA transporter (VGAT) (4 animals tested with similar results) c) High-resolution confocal images (63X, 1.4 NA) of the proximal apical dendritic region of the three neurons indicated in (a), lacking prominent thorny excrescences (n = 3 cells).
Supplementary Figure 4 Athorny neurons are positive for glutamatergic markers VGLUT1 & VGLUT2.
a) Low-magnification images of the CA3 region where pyramidal neurons are sparsely labeled with GFP (n = 3 animals). b) High-magnification images of individual athorny CA3 neurons from the corresponding section shown above (n = 3 cells). c) Single optical sections through the soma of the cells shown above in (b) where the GFP positive somatic region is also positive for the glutamatergic markers VGLUT1 and VGLUT2 (n = 3 cells).
Supplementary Figure 5 Gallery of cells reconstructed from mouse hippocampus.
a) Five reconstructed thorny cells that exhibited a regular spiking intrinsic phenotype. b) Eleven reconstructed athorny cells that exhibited a bursting phenotype.
Supplementary Figure 6 Summary of physiological properties of CA3 pyramidal cells.
a) Representative firing patterns from a regular spiking and a bursting cell where the boxed region indicates an isolated single spike utilized for feature extraction. b) Overlaid individual traces (grey) and average (black, regular spiking (n = 20 cells); red, bursting (n = 14 cells)) of action potential waveforms that are peak aligned. Inset, onset alighted trace averages with bounded SEM error clouds, indicating a more prominent fast after-hyperpolarization potential (fAHP) for regular spiking cells, and a more pronounced after-depolarizing potential (ADP) for bursting cells. c) Phase plot of spike waveform averages for regular spiking (black) and bursting neurons (red) indicating a difference in the rising phase of the action potential waveform between the two cell-types. Inset, upper right (boxed region) illustrates the difference in action potential threshold between the two cell-types. d) Population histograms across all recordings for each feature.
Supplementary Figure 7 ChR2-assisted circuit mapping of mossy-fiber inputs to CA3 pyramidal cell types.
a) Expression pattern of Rbp4cre mice crossed to the Ai9 reporter line illustrating dense expression in the dentate gyrus, specifically in mature granule cells. b) Validation that optical activation drives spiking in dentate granule cells when crossed with the Ai32 line (ChR2-YFP). c) Schematic of experimental design for ChR2-assisted circuit mapping of mossy fiber inputs to CA3 pyramidal cell-types. d) Two representative examples of superficial-layer (close to stratum lucidum, green band) that exhibited regular spiking phenotypes (n = 2 cells). e) Two representative examples of deep-layer (close to stratum oriens) that exhibited bursting phenotypes (n = 2 cells). f) Expression pattern of Pomc1cre mice crossed to the Ai9 reporter line illustrating sparse expression in the dentate gyrus, specifically in immature granule cells (n = 10 animals). g) Representative traces from a regular spiking cell (top) and bursting cell (bottom) illustrating synaptic responses only observed in regular spiking cells when elicited by optical activation of mossy fibers in Pomccre mice. For a total of 11 bursting neurons recorded, none exhibited synaptic responses, while 4 of 9 regular spiking cells displayed typical mossy-fiber synaptic responses.
Supplementary Figure 8 Simultaneous recordings of sharp-wave and ripple oscillations in CA1 and CA3 regions.
a) Recording of sharp-wave and ripple events in the CA1 region of the hippocampus. Schematic (left) depicts the position of the recording electrode as it is moved across lamina. Representative events filtered in either the 4–20 Hz sharp-wave band (violet) or the 150–250 Hz ripple band (grey). Note the presence of ripple oscillations in the pyramidal layer, and the reversal of sharp-wave polarity across the pyramidal layer in CA1. b) Concurrently recorded sharp-wave and ripple oscillations in the CA3 region from the same experiment. Note both sharp-wave and ripple oscillations can be detected in the CA3 pyramidal layer. c) Summary data for all sharp-waves recorded in the CA3 region. Left, distribution and cumulative percentage of sharp-wave inter-event intervals. Inset; representative example trace of a sharp wave cluster. Middle, distribution and cumulative percentage of sharp-wave event amplitudes. Inset, representative individual sharp-wave event where amplitude measurement is indicated by orange arrow. Right, distribution and cumulative percentage of sharp-wave event durations. Inset, representative individual sharp-wave event where duration measurement is indicated by red arrow.
Supplementary Figure 9 Spike sorting and unit isolation for extracellular recordings in vivo.
a) Left and middle, spike waveform properties used for sorting individual extracellular units plotted relative to each other, and the spike autocorrelation function for a recording in which only a single extracellular unit was present. Note the prominent gap around zero-time, indicating clear unit isolation. b) Top, spike waveform properties and spike autocorrelation function (bottom) for a recording in which 2 extracellular units could be clearly identified. Separate units are color coded (magenta, green). Note Y axis difference in bottom panels. c) Spike waveform properties and spike autocorrelation function for a recording in which 3 extracellular units could be clearly identified. Separate units are color coded (magenta, green, orange). Note Y axis difference in bottom panels. Across all recording session we found an average of 1.3 units per recording.
Supplementary Figure 10 Features and principal component analysis for extracellular and juxtacellular recordings.
a) Summary statistics of features extracted from sorted extracellular units. b) Same as (a) but for features extracted from juxtacellular units. Note the higher burst index and number of spikes/burst afforded by the high signal-to-noise ratio of juxtacellular recordings. c) Principal component analysis of individual cellular features of extracellular sorted units (n = 203 cells). Eigenvectors related to each feature are superimposed (blue) with no clear segregation across the population. d) Principal component analysis of individual cellular features of juxtacellular units (n = 140 cells). Eigenvectors related to each feature are superimposed in blue. Note a segregation into two groups can now be observed (red dashed oval).
Supplementary Figure 11 Single-cell summaries for juxtacellular recording and labeling in vivo.
For all panels, morphology recovered from the recorded cell is pictured on top. The SW-triggered activity where a single sweep is shown on top (black), middle panel shows the SW-triggered raster where singe-spikes are black ticks and the first spike in a burst is indicated by a red tick and subsequent spikes in the burst are grey. a, and b are two additional examples of PCP4 negative thorny cells which predominantly fired single spikes during the SW (n = 2 cells). C and D are two additional examples of athorny neurons where bursting can be observed prior to the onset of the SW (n = 3 cells). e-h are additional examples of thorny cells across different sub-regions of CA3, indicating consistent behavior during sharp-waves (n = 6 cells). i and j are two examples of CA2 neurons (+ PCP4) which had similar firing phenotypes to thorny CA3 pyramidal cells for comparison (n = 2 cells). k and l are CA1 cells as a further comparison, which only exhibited sparse firing within the SW LFP envelope (n = 2 cells). Note only athorny CA3 neurons exhibit a prominent burst-firing pattern prior to the onset of the sharp-wave.
Supplementary Figure 12 Population analysis of sharp-wave participation.
Quantification of the SW participation index for all single-spikes only (top), or complex spikes (bottom) from cluster-1 (RS, black, n = 117 cells) and cluster-2 (B, red, n = 23 cells) during the ramp and exponential (Exp.) phases of the sharp wave. All data points are shown left and summarized with a box plot left. Whiskers of the box plots indicate maximum and minimum values, square point indicates the mean, horizontal line within the box indicates the median and the box length indicates the standard error. Statistical significance between mean values was determined by a two-sided two-sample t-test.
Supplementary Figure 13 Simulating cell-type-specific intrinsic properties with ADEX neuron models.
a) Representative traces of increasing current injection for adaptive integrate-and-fire models tuned to have different intrinsic properties. Two excitatory cell-types are modeled as regular spiking and bursting neurons. One inhibitory cell-type is modeled as fast spiking. b) Initial firing frequency of cell-types described in (a) for a range of somatic current injections, note the steep gain function of the bursting cells (red) compared to that of the regular spiking cells (black). c) Summary of network configurations where the proportion of excitatory to inhibitory neurons is constant but the ratio of regular spiking to bursting neurons is systematically changed. d) Table summarizing the cell-type specific parameters used for the adaptive integrate and fire neurons. For the inhibitory cells, parameters were varied by a random amount (r) sampled from a uniform distribution over the range [0,1].
Supplementary Figure 14 Synchronization dynamics of an attractor network in silico.
a) Matrix of network raster plots for different network configurations with varying cell-type composition and synaptic weight. Each tile of the matrix depicts 15 s of simulation time (x-axis) for a network of 1000 neurons (y-axis). The transition from the asynchronous regime to the partial synchrony regime is a function of increasing synaptic weight as well as the proportion of bursting cells in the network. b) Tabular summary of network parameters used for the partial synchrony regime. JE = 3 nA/ms, and p = 0.1 are default parameters for the simulation results reported in the figures, if not specified otherwise c) Summary data across all simulations illustrating the increasing synaptic weight on the frequency of synchronization events for networks with different proportions of excitatory cells from (a). d) Summary data across all simulations illustrating how the proportion of bursting cells in the network influences the size (i.e. number of active cells) for each synchronization event as a function of synaptic weight.
Supplementary Figure 15 Quantification and analysis of synchronization events in silico.
a) Phase estimation and first peak detection of synchronization events. Each synchronization event in the 3-s duration simulation is color coded. Vertical solid line represent time at which each SW occurred, and horizontal dashed lines indication the “center-of-mass” of the synchronizing ensemble and its linearized position (i.e. phase) on the ring. b) SW-onset triggered PSTH for regular spiking cells (black) and bursting cells (red). Solid lines represent the firing rate of the sub-set of cells involved in synchronization event (inside bump), while dashed lines show the firing rate of cells not involved in the SW (outside bump). Inset right, network raster (excitatory cells only) illustrating that all synchronization events of regular spiking cells are associated with preceding bursting cell activity (shown overlaid).
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Hunt, D.L., Linaro, D., Si, B. et al. A novel pyramidal cell type promotes sharp-wave synchronization in the hippocampus. Nat Neurosci 21, 985–995 (2018). https://doi.org/10.1038/s41593-018-0172-7
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DOI: https://doi.org/10.1038/s41593-018-0172-7
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