Abstract
Feature-selective firing allows networks to produce representations of the external and internal environments. Despite its importance, the mechanisms generating neuronal feature selectivity are incompletely understood. In many cortical microcircuits the integration of two functionally distinct inputs occurs nonlinearly through generation of active dendritic signals that drive burst firing and robust plasticity. To examine the role of this processing in feature selectivity, we recorded CA1 pyramidal neuron membrane potential and local field potential in mice running on a linear treadmill. We found that dendritic plateau potentials were produced by an interaction between properly timed input from entorhinal cortex and hippocampal CA3. These conjunctive signals positively modulated the firing of previously established place fields and rapidly induced new place field formation to produce feature selectivity in CA1 that is a function of both entorhinal cortex and CA3 input. Such selectivity could allow mixed network level representations that support context-dependent spatial maps.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Introducing the Dendrify framework for incorporating dendrites to spiking neural networks
Nature Communications Open Access 10 January 2023
-
An astrocytic signaling loop for frequency-dependent control of dendritic integration and spatial learning
Nature Communications Open Access 24 December 2022
-
Entorhinal cortex directs learning-related changes in CA1 representations
Nature Open Access 02 November 2022
Access options
Subscribe to this journal
Receive 12 print issues and online access
$189.00 per year
only $15.75 per issue
Rent or buy this article
Get just this article for as long as you need it
$39.95
Prices may be subject to local taxes which are calculated during checkout








References
Shepherd, G.M. The Synaptic Organization of the Brain 5th edn. (Oxford Univ. Press, New York, 2004).
Steward, O. & Scoville, S.A. Cells of origin of entorhinal cortical afferents to the hippocampus and fascia dentata of the rat. J. Comp. Neurol. 169, 347–370 (1976).
Megías, M., Emri, Z., Freund, T.F. & Gulyas, A.I. Total number and distribution of inhibitory and excitatory synapses on hippocampal CA1 pyramidal cells. Neuroscience 102, 527–540 (2001).
Cauller, L.J., Clancy, B. & Connors, B.W. Backward cortical projections to primary somatosensory cortex in rats extend long horizontal axons in layer I. J. Comp. Neurol. 390, 297–310 (1998).
Petreanu, L., Mao, T., Sternson, S.M. & Svoboda, K. The subcellular organization of neocortical excitatory connections. Nature 457, 1142–1145 (2009).
Xu, N.L. et al. Nonlinear dendritic integration of sensory and motor input produces an object localization signal. Nature 492, 247–251 (2012).
Harnett, M.T. et al. Potassium channels control the interaction between active dendritic compartments in layer 5 cortical pyramidal neurons. Neuron 79, 516–529 (2013).
Larkum, M.E., Zhu, J.J. & Sakmann, B. A new cellular mechanism for coupling inputs arriving at different cortical layers. Nature 398, 338–341 (1999).
Larkum, M. A cellular mechanism for cortical associations: an organizing principle for the cerebral cortex. Trends Neurosci. 36, 141–151 (2013).
Takahashi, H. & Magee, J.C. Pathway interactions and synaptic plasticity in the dendritic tuft regions of CA1 pyramidal neurons. Neuron 62, 102–111 (2009).
Tsay, D., Dudman, J.T. & Siegelbaum, S.A. HCN1 channels constrain synaptically evoked Ca2+ spikes in distal dendrites of CA1 pyramidal neurons. Neuron 56, 1076–1089 (2007).
Jarsky, T., Roxin, A., Kath, W.L. & Spruston, N. Conditional dendritic spike propagation following distal synaptic activation in hippocampal CA1 pyramidal neurons. Nat. Neurosci. 8, 1667–1676 (2005).
Kamondi, A., Acsády, L. & Buzsáki, G. Dendritic spikes are enhanced by cooperative network activity in the intact hippocampus. J. Neurosci. 18, 3919–3928 (1998).
Sjöström, P.J. & Häusser, M. A cooperative switch determines the sign of synaptic plasticity in distal dendrites of neocortical pyramidal neurons. Neuron 51, 227–238 (2006).
Salinas, E. & Sejnowski, T.J. Gain modulation in the central nervous system: where behavior, neurophysiology and computation meet. Neuroscientist 7, 430–440 (2001).
Pouget, A., Deneve, S. & Duhamel, J.-R. A computational perspective on the neural basis of multisensory spatial representations. Nat. Rev. Neurosci. 3, 741–747 (2002).
Suh, J., Rivest, A.J., Nakashiba, T., Tominaga, T. & Tonegawa, S. Entorhinal cortex layer III input to the hippocampus is crucial for temporal association memory. Science 334, 1415–1420 (2011).
Witter, M.P. et al. Cortico-hippocampal communication by way of parallel parahippocampal-subicular pathways. Hippocampus 10, 398–410 (2000).
Epsztein, J., Brecht, M. & Lee, A.K. Intracellular determinants of hippocampal CA1 place and silent cell activity in a novel environment. Neuron 70, 109–120 (2011).
Harvey, C.D., Collman, F., Dombeck, D.A. & Tank, D.W. Intracellular dynamics of hippocampal place cells during virtual navigation. Nature 461, 941–946 (2009).
Grienberger, C., Chen, X. & Konnerth, A. NMDA receptor-dependent multidendrite Ca2+ spikes required for hippocampal burst firing in vivo. Neuron 81, 1274–1281 (2014).
Wood, E.R., Dudchenko, P.A., Robitsek, R.J. & Eichenbaum, H. Hippocampal neurons encode information about different types of memory episodes occurring in the same location. Neuron 27, 623–633 (2000).
Markus, E.J. et al. Interactions between location and task affect the spatial and directional firing of hippocampal neurons. J. Neurosci. 15, 7079–7094 (1995).
Frank, L.M., Brown, E.N. & Wilson, M. Trajectory encoding in the hippocampus and entorhinal cortex. Neuron 27, 169–178 (2000).
Leutgeb, S. et al. Independent codes for spatial and episodic memory in hippocampal ensembles. Science 309, 619–623 (2005).
Royer, S. et al. Control of timing, rate and bursts of hippocampal place cells by dendritic and somatic inhibition. Nat. Neurosci. 15, 769–775 (2012).
Brankacˇk, J., Stewart, M. & Fox, S.E. Current source density analysis of the hippocampal theta rhythm: associated sustained potentials and candidate synaptic generators. Brain Res. 615, 310–327 (1993).
Mizuseki, K., Sirota, A., Pastalkova, E. & Buzsáki, G. Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop. Neuron 64, 267–280 (2009).
Thomson, A.M. Facilitation, augmentation and potentiation at central synapses. Trends Neurosci. 23, 305–312 (2000).
Xu, W. et al. Distinct neuronal coding schemes in memory revealed by selective erasure of fast synchronous synaptic transmission. Neuron 73, 990–1001 (2012).
Anderson, J.S., Lampl, I., Gillespie, D.C. & Ferster, D. The contribution of noise to contrast invariance of orientation tuning in cat visual cortex. Science 290, 1968–1972 (2000).
Kuhn, A., Aertsen, A. & Rotter, S. Neuronal integration of synaptic input in the fluctuation driven regime. J. Neurosci. 24, 2345–2356 (2004).
Buzsáki, G., Horvath, Z., Urioste, R., Hetke, J. & Wise, K. High frequency network oscillation in the hippocampus. Science 256, 1025–1027 (1992).
O'Neill, J., Senior, T. & Csicsvari, J. Place-selective firing of CA1 pyramidal cells during sharp wave/ripple network patterns in exploratory behavior. Neuron 49, 143–155 (2006).
Buzsáki, G., Leung, L.W. & Vanderwolf, C.H. Cellular bases of hippocampal EEG in the behaving rat. Brain Res. 6, 139–171 (1983).
Sullivan, D. et al. Relationships between hippocampal sharp waves, ripples, and fast gamma oscillation: influence of dentate and entorhinal cortical activity. J. Neurosci. 31, 8605–8616 (2011).
O'Keefe, J. & Burgess, N. Dual phase and rate coding in hippocampal place cells: theoretical significance and relationship to entorhinal grid cells. Hippocampus 15, 853–866 (2005).
Rolls, E.T. Entorhinal cortex grid cells can map to hippocampal place cells by competitive learning. Network 17, 447–465 (2006).
McHugh, T.J., Blum, K.I., Tsien, J.Z., Tonegawa, S. & Wilson, M.A. Impaired hippocampal representation of space in CA1-specific NMDAR1 knock out mice. Cell 87, 1339–1349 (1996).
Kentros, C. et al. Abolition of long-term stability of new hippocampal place cell maps by NMDA receptor blockade. Science 280, 2121–2126 (1998).
Mehta, M.R., Quirk, M.C. & Wilson, M.A. Experience-dependent asymmetric shape of hippocampal receptive fields. Neuron 25, 707–715 (2000).
Song, S., Miller, K.D. & Abbott, L.F. Competitive Hebbian learning through spike-timing-dependent synaptic plasticity. Nat. Neurosci. 3, 919–926 (2000).
McClelland, J.L., McNaughton, B.L. & O'Reilly, R.C. Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory. Psychol. Rev. 102, 419–457 (1995).
Hill, A.J. First occurrence of hippocampal spatial firing in a new environment. Exp. Neurol. 62, 282–297 (1978).
Frank, L.M. Hippocampal plasticity across multiple days of exposure to novel environments. J. Neurosci. 24, 7681–7689 (2004).
Monaco, J.D., Rao, G., Roth, E.D. & Knierim, J.J. Attentive scanning behavior drives one-trial potentiation of hippocampal place fields. Nat. Neurosci. 17, 725–731 (2014).
Palmer, L., Murayama, M. & Larkum, M. Inhibitory regulation of dendritic activity in vivo. Front. Neural Circuits 6, 26 (2012).
Jiang, X., Wang, G., Lee, A.J., Stornetta, R.L. & Zhu, J.J. The organization of two new cortical interneuronal circuits. Nat. Neurosci. 16, 210–218 (2013).
Lovett-Barron, M. et al. Dendritic inhibition in the hippocampus supports fear learning. Science 343, 857–863 (2014).
Gambino, F. et al. Sensory-evoked LTP driven by dendritic plateau potentials in vivo. Nature 515, 116–119 (2014).
Acknowledgements
We thank S. Royer, M. Karlsson, J. Osborne, J. Chen and S. Sawtelle for assistance in designing the experimental setup; J. Cohen and A. Lee for technical assistance; W.L. Sun for fiber etching; B. Shields and M. Copeland for histology; M. Lengyel, E. Pastalkova, Y. Wang and B. Lustig for discussions; and M. Mehta, J. Dudman, A. Lee and N. Spruston for comments on the manuscript. This work was supported by Howard Hughes Medical Institute and in part by RIKEN, Wako-shi Japan and the Howard Hughes Medical Institute to the Massachusetts Institute of Technology (S.T.).
Author information
Authors and Affiliations
Contributions
K.C.B. and J.C.M. designed experiments; K.C.B. and C.G. performed in vivo recordings; S.P.V. and A.D.M. performed in vitro recordings; J.J.M. designed and built light probes; J.S. and S.T. designed and produced pOxr1 Cre mice; J.C.M., K.C.B. and C.G. analyzed data. J.C.M. and K.C.B. wrote the manuscript with input from all authors.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Integrated supplementary information
Supplementary Figure 1 CA1 pyramidal neuron firing categories.
From top, Vm (black) and LFP (green) traces for sequential laps as a function of time, trial-by-trial AP spatial firing rate, mean AP spatial firing rate, mean ramp depolarization, mean theta envelope as a function of position from neurons categorized as a, silent cells, b, non-place cells and c, place-cells.
Supplementary Figure 2 Place field firing and theta phase procession.
a, Top. AP rate for single trials as a function of distance for a representative cell (neuron#1 from 1d). Bottom. Average AP rate as a function of distance for all trials. b, Representative intracellular Vm as a function of time for consecutive trials for cell shown in a. c, (from top) ramp potential for lap#20 of neuron#1 (red); intracellular theta (thetain, blue), envelope of thetain (envel., black); the mean ramp trace versus position for all laps (red), amplitude calculation shown; the mean envelope trace versus position (black) with Δtheta calculation shown. d, Top, Hilbert transform of extracellular theta as a function of time (grey). Colored dots represent phase of APs (black) and intracellular theta peaks (blue, thetain). Bottom traces are extracellular theta (green), intracellular theta (blue), and intracellular Vm (black) as a function of time. Data are from lap 20 for cell shown in a. e, Theta phase of all APs (black) and intracellular theta peaks (blue) for lap 20 as a function of time. f, Extracellular theta phase of intracellular theta peaks (left) and APs (right) for all trials as a function of position. Individuals are shown in grey and boxcar smoothed data are shown in colored (5 points). g, Extracellular theta phase of intracellular theta peaks (blue) and APs (black) as a function of position for all trials binned in 10 cm bins for cell shown in a. Grey dotted line is a Gaussian fit to the place field and plus symbols represent first and last 10 cm of the field (10 cm bins). h, Extracellular theta phase of intracellular theta peaks (thetain, blue) and APs (black) as a function of position for all place cells (N = 14). Data are shown as mean±SEM for the first and last 10 cm and these points were used to test for significance; p = 0.2e−4 for thetain and p = 0.1e−5 for APs paired two-way t-test.
Supplementary Figure 3 Plateau potential detection and characterization.
a, Representative intracellular Vm as a function of time. Dotted lines indicate plateau threshold (−35 mV) and baseline Vm (−60 mV). Right trace is expanded (black bar). b, Intracellular Vm from cell in a with spikes removed and smoothed (smoothed Vm) as a function of time. The smoothed Vm trace was used for automatic detection of plateau potentials. Arrows indicate detected plateau events. Right trace is expanded (black bar). c, Frequency distribution of smoothed Vm for all laps of cell in a (red). Distribution fit by double gaussian function (black), with separate peaks labeled. Expanded plot (inset) shows prominent tail diverges from fit near −35 mV for this cell with a high plateau probability (9.2/100 AP). d, Frequency distribution of smoothed Vm for all laps of cell shown in Fig 6a-f (red). Distribution fit by double gaussian function (black), with separate peaks labeled. Expanded plot (inset) shows no prominent tail for this cell with a low plateau probability (0.7/100AP). e, Vm distribution for all cells showing plateaus (N = 9) separated into trials containing plateaus (black) and those without plateaus (red) demonstrating non-gaussian tail component is due to the occurrence of plateau potentials. Arrow indicates location of baseline Vm. Inset in e shows distribution over a smaller Vm range. f, left, Experimental setup for in-vitro data in f-k. Dual (soma and dendrite) recording of a CA1 neuron. Bipolar stimtrodes were placed in SLM and SR, approximately 100 µm from the recording site (not shown). Right, Representative somatic Vm (black), dendritic Vm (blue) and smoothed Vm (red) in response to electrical stimulation (artifacts removed during analysis). g, FWHM for the last spike in the AP burst recorded at the dendrite with classification for plateaus as described in methods, example shown at top. h, i, Distribution (h) or cumulative distribution (i) of peak smoothed Vm for plateau (red) and non-plateau (black) AP bursts. Plateaus were identified from dendritic voltage. k, Vm distribution for all cells with (red) and without (black) plateaus (N = 7)
Supplementary Figure 4 Plateaus are positively correlated with firing rate, ramp amplitude and Δtheta.
a, b, Representative intracellular Vm traces (a) and spatial firing rates (b) for 4 laps from a representative cell. e, f, Subthreshold Vm low-pass filtered to produce ramp traces (e) and band-pass filtered to produce intracellular theta traces (thetain, grey, f) and envelope (blue, f) from 4 laps shown in a. g, h, i, Plateau probability as a function of peak firing rate (g), ramp amplitude (h), and Δtheta (i) for all place cells (N=22).
Supplementary Figure 5 MK801 decreases plateau probability and duration.
a, b, c, d Average AP rate (a), plateau probability (b), plateau duration (c), and plateau probability*duration (d) for control cells (black, open symbols, N=17) and MK801 containing cells (red, open symbols, N=13 for probability, N=10 for duration). Filled symbols are population averages shown as mean+SEM. Plateau probabilities and durations were calculated for all cells over the entire duration of the recording over both running and non-running periods using a threshold of -30mV. Only recordings of 15 minutes or longer were included in the analysis to ensure complete dialysis of cell with 1-2 mM MK801. The control cells included here were all stable recordings of greater than 15 minutes in length that were recorded within 9 months of the MK801 cells. Asterisks indicate p=0.0016 for probability and p=0.009 for normalized duration, Mann-Whitney U test.
Supplementary Figure 6 Manipulation of AP phase using LFP current injections.
Schematic of manipulation to examine the effect of CA1 spike phase on plateau probability. Briefly, the extracellular LFP was filtered, phase shifted and injected into the cell as a current. The current was phase shifted sufficiently to cause spikes to occur near the peak, (short delay, red, center) or trough (long delay, blue, right) of extracellular theta. b, c Online LFP processing to produce current injections that result in spiking at the peak of extracellular theta (red, b) or the trough of extracellular theta (blue, c). d, e, Representative intracellular Vm traces (d) and smoothed intracellular Vm (e) without current injections (black), with injected current with short delay (red, peak), or with injected current with long delay (blue, trough).
Supplementary Figure 7 Optical delivery and light intensity measurements.
a, Left, Composite image of the photodetector taken in brightfield (grayscale image) and fluorescence (red image, 561 nm excitation, 630/75 emission), showing the region of 645-nm emitting quantum dots at the end of a pipette tip; Center, Diagram for 594 nm laser light delivery via an optical fiber to a LFP/fiber electrode (black), and detection of laser light via induced quantum dot fluorescence from the photodetector pipette (magenta) recorded by a fiber-coupled spectrometer (not shown), this geometry was used for both in vivo measurements and intensity calibration in saline; Right panel: Representative LFP/fiber electrode with 8.5 μm diameter etched fiber, recessed 200 μm from the pipette tip. b, Laser intensity measurements taken at 50 μm steps in the vertical direction and 100 μm in the saggital plane represented as a heatmap with 50 μm pixels. Pixel values between lateral data points were linearly interpolated and superimposed on a DAPI stained saggitally sliced 150 μm thick section, intensity scale is for 1 mW power out of the LFP/fiber electrode with fiber tip recessed 90 μm from pipette tip. c, Representative LFP recording (blue) from an EC3xAi35D to show the effect of light (594 laser pulses, yellow lines) on the LFP in Arch expressing mice. In Arch positive mice there was a reproducible DC offset in the LFP induced by light that did not occur in mice not expressing Arch. d, Representative LFP (blue) and intracellular Vm (black) traces from a C57/B6 mouse during light pulses (yellow) to demonstrate a lack of effect of the light in mice not expressing Arch.
Supplementary Figure 8 Light stimulation of Arch in EC3 axons in CA1 in hippocampal slices reduces evoked perforant path EPSPs.
a, Example 2-photon Z-stack of a CA1 neuron patched at the soma with Alexa Fluor 488 dye in a hippocampal slice from a mouse expressing Arch-EGFP in EC3 axons. b, Example voltage trace from a CA1 soma during theta burst electrical stimulation of perforant path axons in the presence and absence of whole-field red light (590/55nm) stimulation to activate Arch expressed in EC3 axons. c, Summary of experiments of the type shown in (b). The average EPSP area is expressed as mean ± SEM (N = 8, p = 0.015, Mann Whitney U-test paired).
Supplementary Figure 9 Effects of light on intracellular Vm in an EC3xAi35D mouse.
a, b, Representative intracellular Vm (a), and smoothed intracellular Vm (b) as a function of position for consecutive trials with (yellow) and without (black) light pulses from a representative cell in an EC3xAi35D mouse. The light pulses are shown in grey and the blue dotted lines indicate the relative location/time of the light pulses. Control trials for this cell had 12 plateaus and 476 APs while light trials had 1 plateau and 285 APs. Plateau probability was 2.5/100APs for control and 0.4/100APs for light trials. Average durations were 91 ms (control) and 50 ms (light) and total durations were 228 (control) vs 20 (light) ms/100APs. c-e Peak firing rate (c), Δtheta (d) and ramp amplitude for all cells (N = 8) for control (grey) and light (yellow) periods. Individuals are shown colored and averages are in black as mean+SEM.
Supplementary Figure 10 Place fields induced by spontaneous plateau potentials.
a, AP firing rate as a function of position for single laps for all cells in which a place field formed after a spontaneous plateau potential. The lap containing the plateau is indicated with an arrow b, Representative intracellular Vm as a function of time from laps with spontaneous plateaus.
Supplementary Figure 11 Place fields formed following plateau-inducing current injections.
a, b, c, AP firing rate as a function of position for single laps for all cells in which a place field was induced using current injection at position 1 (a), position 2 (b) and position 3 (c). The laps containing the current injections are marked with an arrow. b, d-f, Place field (e), AP (f) and plateau (d) properties for naturally occurring place cells (C, N = 21) or place cells induced using plateau current injections (I, N = 14). d, Plateau theta modulation (left) and theta phase preference (right). e, Intracellular Vm ramp (left), Δtheta, (middle) and phase precession (right). f, Left to right, AP peak rate, AP theta phase preference, and AP theta phase precession. Data are shown as mean+SEM (d-f). p-values from left to right are 0.068, 0.079, 0.46, 0.001, 0.09, 0.22, 0.28, 0.067; unpaired two-tail t-tests.
Supplementary Figure 12 Rin does not change following place field induction.
a, Representative current waveforms and resulting Vm deflections for times b, before and c, after the place field induction. Average voltage deflections from entire sequence used for Rin calculation are shown at right. d, plot of Rin versus time for entire recording. Values calculated from traces in b and c are indicated. e, population data for all neurons with induced fields (N = 14).
Supplementary Figure 13 APs alone do not induce place fields.
a, Representative intracellular Vm as a function of time for laps (numbers at left) before, during and after current injections that induce APs but no plateaus. Current injections were 100 Hz, 2 ms pulses for at least 300 ms. b, AP firing rate for single laps as a function of distance for representative cell from a. Arrow indicated where currents were injected c, Top, intracellular Vm (black), and extracellular theta (green) from lap 10 as indicated by red box on expanded time base to show plateau characteristics. Red line is smoothed trace. Bottom, the trace from top shown on an expanded time base to show AP characteristics. d, Mean intracellular ramp amplitude (top) and Δtheta (bottom) as a function of time for cell in a. e, Average intracellular ramp (top) and theta (bottom) as a function of time across laps within the time window indicated by the grey or black bar in d to show the average ramp and theta for laps before and after current injections (N = 6).
Supplementary Figure 14 Integration of Poisson input trains simulation.
a, Model EPSPs for a single excitatory input train with a 3x increase in amplitude (black) or rate (grey) within the field with no change in IPSP rate or amplitude (red). Forcing function for amplitude or rate (green). b, model Vm as a function of time for 300 inputs (150 excitatory, 150 inhibitory) for a single lap and corresponding residual. c, residual probability distribution outside the field (blue), in field with an increase in rate (grey), or amplitude (black). d, mean Vm (top) and variance (bottom) for a change in rate (grey) or amplitude (black). e, Variance as a function of trial out of field (blue), in field with a change in rate (grey), or amplitude (black). f, variance as a function of mean for a change in rate (grey) or amplitude (black). Lines are fits by y=mpx+b, where p for each condition is shown. g, variance as a function of mean for an extreme change in both excitation rate (6X) and inhibition rate (4×). Lines are fits by y = mpx+b, where p is shown. Bottom, equations governing the linear integration of Poisson EPSP and IPSP input trains32.
Supplementary Figure 15 Schematic of hypothesized impact of nonlinear input processing on feature-specific firing.
a, Generalized cortical microcircuit. 1) Pyramidal type principal neuron, 2) separate feed forward inhibitory elements, 3) dendrite targeting feedback inhibitory element, 4) disinhibitory elements with modulatory input. b, No feature specific firing for a given context occurs when the neuron receives many hundreds of weak excitatory inputs each with their own feature selectivity when this input is countered by nonselective inhibitory inputs. c, To induce feature specific firing a plateau is initiated by matched EC3 and CA3 input plus some dis-inhibition and the excitatory input associated with the plateau potentiates. d, feature specific firing is expressed and maintained in a given context when the potentiated inputs depolarize the neuron at the feature position. Evoked plateaus maintain potentiation and stabilize firing field. e, i) CA1 microcircuit involving pyramidal neuron #10 receives input from EC3 but only weak or phase delayed input from CA3 leading to ii) linear (no plateau initiated) dendritic integration between input streams that iii) does not induce synaptic/dendritic plasticity leaving the input with a low efficacy and iv) a low frequency single spiking output. v) If a place field is generated in this neuron it is weak and unstable leading to vi) the unique context-dependent population activity map using both rate and phase coding. f, scheme for processing in hypothetical context #2. i) CA1 microcircuit involving pyramidal neuron #10 receives input from EC3 with strong or phase advanced input from CA3 leading to ii) nonlinear (plateau initiated) dendritic integration between input streams that iii) induces strong synaptic/dendritic plasticity leaving the input with a high efficacy and iv) a high frequency burst firing output. v) The place field generated in this neuron is strong and stable leading to vi) the unique context-dependent population activity map using both rate (shown) and phase coding. Same neurons and spatial alignment as in context #1. EC3 and CA3 input are labeled with hypothetical informational content that could produce episode specific memories.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–15 (PDF 3122 kb)
Rights and permissions
About this article
Cite this article
Bittner, K., Grienberger, C., Vaidya, S. et al. Conjunctive input processing drives feature selectivity in hippocampal CA1 neurons. Nat Neurosci 18, 1133–1142 (2015). https://doi.org/10.1038/nn.4062
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/nn.4062
This article is cited by
-
Introducing the Dendrify framework for incorporating dendrites to spiking neural networks
Nature Communications (2023)
-
The role of inhibitory circuits in hippocampal memory processing
Nature Reviews Neuroscience (2022)
-
Hippocampal place codes are gated by behavioral engagement
Nature Neuroscience (2022)
-
Local circuit amplification of spatial selectivity in the hippocampus
Nature (2022)
-
A direct excitatory projection from entorhinal layer 6b neurons to the hippocampus contributes to spatial coding and memory
Nature Communications (2022)