www.sciencemag.org/content/348/6234/560/suppl/DC1

Supplementary Materials for

Selective information routing by ventral hippocampal CA1 projection neurons

S. Ciocchi,* J. Passecker, H. Malagon-Vina, N. Mikus, T. Klausberger*

*Corresponding author. E-mail: stephane.ciocchi@meduniwien.ac.at (S.C.); thomas.klausberger@meduniwien.ac.at (T.K.)

Published 1 May 2015, Science 348, 560 (2015)

DOI: 10.1126/science.aaa3245

This PDF file includes:

Materials and Methods Figs. S1 to S14 Table S1 References (31–38)

Materials and Methods

Experimental animals

Behavioural data were obtained from four Long Evans male rats (330 - 420 g, 2½ to 4 months at

the time of surgery, Charles River Laboratories); data from five additional rats were discarded

because of misplaced virus injection, tetrodes or optic fibres. Animals were housed individually

in Plexiglas cages (42 x 27 x 30 cm) and maintained under a 12 h light/12 h dark cycle with ad

libitum access to food and water. Behavioural experiments occurred in the light phase and rats

were food deprived to reach 85 % of the preoperative weight. All experimental procedures were

performed in accordance with regulations of the Austrian ministry of Science and the Medical

University of Vienna.

Surgeries: virus injection and microdrive implantation

Stereotaxic coordinates (31) used for the surgeries are found in the following table:

Procedure Targeted brain area Antero-posterior Medio-lateral Dorso-ventralOptic fiber implantation mPFC 3 0.5 -2.6Optic fiber implantation Acb 1.8 0.8 -6Optic fiber implantation Amy -2.6 4.2 -7Tetrodes implantation dCA1 -3.4 2.5 -1.5Tetrodes implantation vCA1 -4.8 4.5 -6.5

Virus injection (1st track) vCA1 -4.8 4.5 from -8.2 to -7.4Virus injection (2nd track) vCA1 -5.2 5.4 from -8.0 to -6.8

Coordinates given in millimeters and referenced to bregma

Rats were anaesthetised with isofluorane (induction 5%, maintenance 2%) in O2. Rats were fixed

in a stereotaxic frame and body temperature was stabilised with a heating pad. Local and

systemic analgesics (xylocain® 2%, metacam® 2mg/ml, 0.5 ml/kg) were applied. Iodine

solution and eye-protective cream were provided to disinfect the surgery site and protect the

corneas. Every two hours a Ringer's solution (10 ml/kg) was administered subcutaneously to

avoid dehydration. The surgery site was exposed and cleaned with saline solution. Six stainless

steel screws were anchored into the skull with two of them placed above the cerebellum to serve

as grounds and references for the electrophysiological recordings. Craniotomies were performed

in the right hemisphere above dCA1 and vCA1, mPFC, Acb and the Amy. The dura mater was

removed and a saline solution was applied to the brain surface to avoid oedemas. The

recombinant AAV2/1.syn.ChR2(H134R).EYFP (Addgene 26973P) was produced by the Penn

Vector Core at a titer of 5,9 x 1013 genome copies/ml. The virus solution was loaded into a pulled

borosilicate glass capillary and pressure-injected into the vCA1 with a Picospritzer III® (Parker

Hannifin Corporation). About 600-800 nl of virus solution was injected over 10 min along two

tracks. Rats were then implanted above dCA1 and vCA1 with a custom-made microdrive (Miba

Machine Shop, IST Austria) containing 15 independently moveable tetrodes made of four

twisted tungsten microwires (12.7 µm inner diameter, California Fine Wire Company). The

tetrode tips were gold-plated to impedances of 100 - 600 kΩ. 3 plastic tubes were integrated into

the microdrive to enable the placement of optic fibers (200 µm core diameter, 0.37 NA, Thorlabs

GmbH) in mPFC, Acb and Amy. Paraffin wax was then applied around the tetrode guide

cannulae, the remaining lower part of the microdrive was cemented (Refobacin® Bone Cement)

and the surgery site sutured. Animals were given post-operative analgesia (Dipidolor 60 mg

diluted per 500 ml drinking water) and at least 7 days of recovery time.

In vivo electrophysiology and optical stimulations

Tetrodes were progressively lowered to the vCA1 and dCA1 pyramidal layers over a period of

about 3 weeks by using SWR and theta oscillations as electrophysiological hallmarks. For each

recording day, tetrodes were moved to sample new units.

The extracellular electrical signals from the tetrodes were pre-amplified with a headstage (HS-

132A, 2 x 32 channels, Axona Ltd) to reduce cable artefacts. The output signals were amplified

1000X via a 64-channel amplifier and continuously digitised at 24 kHz at 16 bit resolution using

a 64-channel analogue-to-digital converter computer card (Axona Ltd). The signals were down-

sampled offline at 20 kHz. Single-units were extracted offline by detecting signal amplitudes 5

SD above the root mean square of the digitally filtered signal (0.8 - 5 kHz) over 0.2 ms sliding

windows. 32 data points (1.6 ms) were sampled for each single-unit. A principal component

analysis was implemented to extract the first three components of spike waveforms of each

tetrode wire (32).

Spike waveforms from individual neurons were detected using the KlustaKwik automatic

clustering software (http://klustakwik.sourceforge.net/). Individual single-units were isolated

manually by verifying the waveform shape, the modulation of waveform amplitude across

tetrode channels, the temporal autocorrelation (to assess the refractory period of a single-unit)

and crosscorrelation (to assess a common refractory period across single-units) using the

Klusters software (33). The stability of single-units was confirmed by examining spike features

over time.

To locally detect SWRs in vCA1, the local field potential signals were band-pass filtered (150 -

250 Hz) and a reference channel without SWR was subtracted from all channels to remove

common-mode noise (such as chewing artefacts). The detection threshold for SWR (the tetrode

with largest SWR power in vCA1 was selected) was set as 4 - 6 SD above the room mean square

amplitude of the filtered signal (32). SWR detection was achieved during rest/sleeping periods

immediately following behavioural experiments. The quality of SWR detection was confirmed

by visual inspection in the NeuroScope software (33).

To antidromically identify individual vCA1 projection neurons (from 4 weeks on following virus

injection), a DPSS laser (IkeCool Corporation) generating blue light (473 nm) was sequentially

connected to implanted optic fibres through a ferrule-sleeve system (Senko Ltd) with 30 - 70

mW output power delivered to the brain tissue. A screening protocol of different light

illuminations was used at the end of the behavioural experiments to optimise the identification of

individual projection neurons. This protocol included a combination of light durations of 1 or 5

ms with light intensities of 10, 20, 50 and 100% of laser output power. 50 or 100 repetitions of

each stimulation was done at 5Hz. The ability of vCA1 projection neurons to follow high

frequency stimulation was tested using 20 and 50 Hz light stimulations repeated 50x.

The pharmacological experiment was performed under urethane (1.25 g/kg body weight)

anaesthesia with additional doses of a ketamine/xylazine mixture (17 and 7 mg/ml, respectively;

0.02 - 0.1 ml). NBQX 1mM and D-AP5 2mM (Tocris Bioscience) saline solution was pressure-

injected into vCA1 of a 5 weeks virus-injected rat; in an additional experiment the drugs (NBQX

5mM and D-AP5 10mM) were injected both into the vCA1 and into the frontal cortex to block

synaptic activity also in the prefrontal cortex and nucleus accumbens. Single-unit activity was

recorded in vCA1 with simultaneous optical stimulation of the target areas using protocols

described above. Signals were recorded with 4 tetrodes and transmitted to a RA16AC headstage

(Tucker‐Davis Technologies) and to a 16-bit analogue-to-digital converter (Cambridge

Electronic Design). Single-units were isolated as described above.

Behaviour

A goal-directed navigation task, spatial exploration and an anxiety task were used in the present

study. The goal-directed navigation task and the spatial exploration required a preliminary

training procedure of about 2 - 3 weeks. One week following surgery, food deprivation started

and rats were trained in parallel on both tasks. The goal-directed navigation task was based on

consecutive learning of allocentric and egocentric rules (34). In the allocentric task, rats learnt to

find rewards at the same position at the end of one of the rewarded arms based on spatial

landmarks in the experimental room. In the egocentric rule, rats learnt to find rewards by turning

in the same direction from each of the start arms and therefore ending at opposing rewarded

arms. Rats were first habituated to the maze and to continuously run trials for sucrose pellets (3 x

20 mg, TestDiet) on a plus maze with two opposing starting and rewarded arms meeting at 90o

angles. Sucrose pellets were delivered by sensor-activated dispensers (Campden Instruments

Ltd) at the extremity of each rewarded arm. The size of the arms was 80 cm x 11 cm and the

"reward zone" corresponded to the 30 cm ahead of the dispensers. The plus maze was 55 cm

high and wooden-made. Both rewarded arms were baited during maze habituation but only one

arm during rule learning. Training to allocentric and egocentric rules started once rats

continuously performed 40 - 60 trials during the habituation phase. Rats were manually placed at

a starting arm and freely ran to one of the potentially rewarded arm. The path to the opposite

starting arm was prevented by a ceramic pot. Rats were placed in the ceramic pot between each

trial for about 5 seconds before restarting a new trial. Rats were pseudo-randomly assigned to a

starting arm before each trial: if rats reached a non-rewarded arm, the next trial restarted on the

same start arm again, otherwise, in successful trials, the consecutive trial was randomly assigned.

Rule learning was set to at least 13 correct trials out of the last 15 trials. About 4 - 8 training days

were required for rats to learn 3 - 4 rules within a single training session. The maze was cleaned

with a odourless solution every 8 trials to avoid odour-guided navigation. At least one

behavioural switch (allocentric to egocentric or egocentric to allocentric rule learning) was

presented on each experimental day. For the spatial navigational task, rats learned to forage for

chocolate flakes (Kellogg’s) randomly thrown in a 180 x 180 cm open field surrounded by 30 cm

high walls. 3 - 4 training sessions were required to reach 30 - 40 minutes of continuous open

field exploration. The light intensity in the experimental room during rule switching task and

spatial navigational task was 1 lux. Once learnt, the goal-directed navigation task and the spatial

exploration were performed in conjunction with an anxiety task, based on the exploration of a

wooden elevated-plus-maze. The elevated-plus-maze consisted of two closed and two open arms.

The dimensions of the arms were 9 x 50 cm, the walls in the closed arms were 40 cm high and

the elevated-plus-maze was elevated 70 cm above the floor. Rats were placed on the elevated-

plus-maze facing the open arm distal to the experimenter. The elevated-plus-maze sessions lasted

5 - 8 min and were done at 200 lux of room light intensity (35). To control for the specificity of

neuronal firing in the elevated-plus-maze, arms were interchanged during a consecutive elevated-

plus-maze exploration.

The three tasks were performed in the same room. The room configuration was made different

for all three tasks by changing the landmarks and the configuration of the walls surrounding the

mazes. The presentation of the three tasks was counterbalanced for order from one day to

another. The number of recording days per rat was low (3 - 6 sessions) to keep anxiety levels

high in the elevated-plus-maze task. The rats' position was monitored using an array of LEDs of

three different colours detected at 25 frames per second by an overhead video camera (Sony).

Histology

To confirm the position of the recording sites, lesions were made at the tip of the tetrodes using a

30 µA unipolar current for 10 s (Stimulus Isolator, World Precision Instruments). Rats were then

deeply anesthetised with urethane and perfused with saline followed by 20 min. fixation with 4%

paraformaldehyde, 15% (v/v) saturated picric acid and 0.05% glutaraldehyde in 0.1 M phosphate

buffer. Serial coronal sections were cut at 70 µm with a vibratome (Leica). Sections containing a

lesion were Nissl-stained. To detect the expression of ChR2, we incubated sections of interest in

serum containing mouse anti-ChR2 monoclonal antibody (1/100, mfd Diagnostics) in 0.1M Tris-

buffered saline containing 1% normal horse serum and 0.1% Triton X-100. Sections were next

incubated with a Cy5 anti-mouse fluorescent secondary antibody (1/250, Jackson

Immunoresearch Laboratories). Immunohistochemical analysis was performed on an

epifluorescence microscope (Olympus BX61).

Analysis and Statistics

Optogenetic identification of vCA1 projection neurons.

To identify individual vCA1 projection neurons by antidromic spiking, we used a combination of

criteria including low spike jitter (< 0.3 ms), early latency (< 22 ms for mPFC stimulation, < 17

ms for Acb shell stimulation, < 13 ms for the Amy stimulation ) and high fidelity (> 50% of light

responsive sweeps) of light-induced spikes. Spike-collisions and the ability of vCA1 neurons to

follow 50 and/or 20 Hz photostimulation were also tested. Collision tests were classified into

three categories: neurons with a spike collision occurring in a sequence of at least 5 consecutive

antidromic spikes (binomial test, p < 0.05), neurons with a spike collision occurring without a

sequence of 5 consecutive antidromic spikes and neurons without a testable spike collision

(absence of spontaneous spikes or collisions occurring during the refractory period of a

spontaneous spike before antidromic activation (< 2 ms)). The efficacy of collisions was

dependent of the photostimulation intervals between spontaneous and antidromic spikes as

described previously (3). vCA1 neurons fulfilling at least 3 of these criteria were classified as

projection neurons to a defined target. The spike waveform similarity between antidromic spikes

and spontaneous spikes of individual vCA1 projection neurons was calculated by correlational

analysis on the averaged spike waveforms. The channel of the tetrode with the largest voltage

amplitude was used.

Analysis of place cells.

To compute firing rate maps, the arena of exploration was divided into 300 x 400 pixels. In each

pixel, the number of spikes was divided by the rat´s occupancy: the firing rate maps were

smoothed by convolving them in two dimensions with a Gaussian low-pass filter. To calculate

the stability score of place fields during the exploration of the open field, the rat´s trajectory was

divided into a first and a second half, and firing maps were computed for the 2 trajectories. A

pixel-to-pixel comparison was made by correlational analysis to assess the similarity and

therefore the stability of place fields over time. Correlation values close to 1 indicate stable place

fields whereas values closer to -1 indicate spatially anti-correlated place fields. Cells with a place

field stability score > 0.37 were considered as stable place cells. The 0.37 threshold was chosen

because it corresponded to the intersection of the bimodally distributed dCA1 place field stability

scores. The area of a place field was computed by calculating the percentage of pixels with a

firing rate value > 20% of the neuronal peak firing rate (13). The spatial tuning was calculated by

subtracting the mean firing rate from the peak firing rate of the firing rate map of each neuron.

Analysis of anxiety cells.

Elevated-plus-maze scores of firing rates of individual cells were calculated as previously

reported (4):

Elevated − plus − maze �iring rate score =A − BA + B

,where

A = 0.25 ∗ (|FL − FU| + |FL − FD| + |FR − FU| + |FR− FD|) and

B = 0.5 ∗ (|FL − FR| + |FU − FD|)

FL, FR, FU, and FD are the difference from mean firing rate (in percent) in left, right, up and

down arms, respectively. A corresponds to the mean difference in normalised firing rate between

arms of different types, while B corresponds to the mean difference in normalised firing rate for

arms of the same type. Scores with values close to 1 indicate that the firing rates are very similar

within arms of the same type (small B value) but different across arms of different types (high A

value). Negative scores indicate that the firing rates are inconsistent within arms of the same type

but very similar across arms of different types. A score of zero corresponds to a neuron with the

same firing rate in each arm of the maze. Neurons with an elevated-plus-maze score > 0.37 were

considered as anxiety responsive. Only neurons with more than 50 spikes could be classified as

anxiety cells. To quantify anxiety behaviour, we calculated offline the percentage of time spent

and the number of entries in each of the four arms based on the rat leaving or re-entering the

central part of the elevated-plus-maze. An entry was counted when the rat´s trajectory was longer

than 0.5 s in a specific arm.

Analysis of goal-directed cells.

To identify neurons excited or inhibited in the reward zone, we compared the averaged firing rate

histograms before (-2 s to 0 s, 10 bins) to after (0 s to 4 s, 20 bins) the entry into the reward zone

with the Mann–Whitney rank sum test. The trials were divided in two blocks to assess the

maintenance of reward-modulated firing. Neurons with p-values < 0.1 in each block of trials

were classified as reward modulated neurons. All reward-modulated neurons had different

activities when comparing the firing rates before and after the entry into the reward zone across

all trials (p < 0.05, Wilcoxon signed-rank test). To identify neurons that significantly changed

firing over trials, we used the change-point analysis developed by Gallistel et al., 2004 (36).

Change-point analysis enabled the identification of trials displaying a significant change in firing

relative to the preceding trials. The population z-scored firing rate histograms were computed

separately for reward zone-excited or -inhibited neurons by averaging the z-scored firing rate

histograms of individual reward zone-modulated neurons. To directly compare the time-course

of reward zone-modulated neurons in the different trial conditions of the rule switching task

(allocentric vs. egocentric; reward zone 1 vs. reward zone 2; trajectory 1 vs. trajectory 2 vs.

trajectory 3 vs. trajectory 4; rewarded vs. non-rewarded), we averaged the individual z-scored

firing rate histograms of reward zone-excited neurons with the individual and absolute z-scored

firing rate histograms of reward zone-inhibited neurons. A change-point analysis was done at the

population level to determine the earliest time point of firing rate changes during approach of the

reward zone. A state-space model developed by Smith et al., 2004 (37) was used to analyse the

behavioural learning curves of rats during the rule switching task. This model enabled the

calculation of probabilistic learning curves with confidence intervals out of binary behavioural

outcomes (correct vs. incorrect trials). The probability of correct outcome was set at 0.5.

Recruitment of cells during SWR.

To establish whether a neuron was activated during locally detected SWR, we computed z-

scored firing rate histograms for each vCA1 neuron relative to the peak voltage amplitude of

each detected SWR. Histograms ranged from -0.5 s to 0.5s and the spikes of each neuron was

binned by 0.05 s. Neurons with at least one z-score value > 2.2 in the 2 bins surrounding SWR

detection were considered as activated by SWR. Two behavioural sessions were omitted of SWR

analysis due to the absence of a rest/sleeping period.

Locomotor activity and firing rates.

For the correlational analysis of firing rates with locomotor activity, the open field exploration of

each rat was divided in 1 s time segments and firing rates, speeds (first derivative of the position

with respect to time) and accelerations (2nd derivative of the position with respect to time)

values were calculated and correlated for each vCA1 neuron over each time segments.

Bootstrap analysis.

We used bootstrap analysis to determine whether a vCA1 projection type was significantly

enriched or impoverished in task-responsive neurons. For each projection type and its

corresponding number of projections, we randomly assigned a number of task-responsive

neurons from the grand total. This operation was repeated 10000 times which led to a bootstrap

distribution of resampled data and the original dataset was compared to the bootstrapped

distribution. Data points beyond 95% of the confidence interval of the bootstrapped distribution

were considered as significantly enriched or impoverished in task-responsive neurons.

All calculations were made in MATLAB (version 7.9) and statistical analysis was done in the

commercially available software SPSS (version 22.0) and SigmaPlot (version 12.5). All

significant correlational analysis was significant at alpha = 0.05 with both Spearman’s and

Pearson’s methods.

Statistics were performed for each experiment as follows:

Fig. 1 (F). Box plots display the median, the first and third quartiles and the ranges of the

latencies distribution of individual cells.

Fig. 2 (C). (Left) Percentage of dCA1 and vCA1 anxiety neurons were unequally represented.

The null hypothesis, that the percentage of dCA1 and vCA1 anxiety neurons was similar, was

rejected by the Pearson Chi-Square test: χ2 (1, 499) = 14.61, p < 0.001. Thus, there were

significantly more anxiety neurons in vCA1 (n = 43 out of 233, 18.45 %) compared to dCA1 (n

= 19 out of 266, 7.14 %).

Fig. 2 (C). (Right) Percentage of anxiety neurons among vCA1 projection types. Bootstrap

analysis revealed that the percentage of anxiety neurons in the vCA1 → mPFC projection (n = 6

out of 14, 42.86 %, p < 0.05) lay above confidence intervals. Thus, there were significantly more

anxiety neurons in the vCA1 → mPFC projection than chance level. All of the other projection

types lay within confidence intervals (p > 0.05).

Fig. 2 (D). Difference of elevated-plus-maze scores between vCA1 projection neurons with an

axon collateral in mPFC or the Amy (without counting axon collaterals in both targets). Two-

tailed, unpaired t-test revealed a significant difference (p < 0.05) between elevated-plus-maze

scores of vCA1 projection neurons with an axon collateral in mPFC (n = 43, elevated-plus-maze

score = 0.12 ± 0.04 ) and vCA1 projection neurons with an axon collateral in the Amy (n = 12,

elevated-plus-maze score = -0.08 ± 0.06). Values are expressed as mean ± s.e.m..

Fig. 2 (G). (Left) Percentage of dCA1 and vCA1 place cells was different. The null hypothesis

that the percentage of dCA1 and vCA1 place cells was similar was rejected by the Pearson Chi-

Square test: χ2 (1, 499) = 71.85, p < 0.001. Thus, there were significantly less place cells in

vCA1 (n = 33 out of 233, 14.16 %) compared to dCA1 (n = 133 out of 266, 50 %).

Fig. 2 (G). (Right) Percentage of place cells among vCA1 projection types revealed that none of

the projection types lay beyond confidence intervals (Bootstrap analysis, p > 0.05 for all

projection types).

Fig. 3 (C). (Top) Percentage of reward zone-excited neurons among vCA1 projection types.

Bootstrap analysis revealed that the percentage of reward zone-excited neurons in the vCA1 →

mPFC/Acb projection (n = 6 out of 29, 20.67 %, p < 0.05) lay above confidence intervals Thus,

there were significantly more reward zone-excited neurons in the vCA1 → mPFC/Acb projection

than chance level. All of the other projection types lay within confidence intervals (p > 0.05).

Fig. 3 (C). (Bottom) Percentage of reward zone-inhibited neurons among vCA1 projection types.

Bootstrap analysis revealed that the percentage of reward zone-inhibited neurons in the vCA1 →

Acb projection (n = 10 out of 35, 28.57 %, p < 0.05) lay above confidence intervals. Thus, there

were significantly more reward zone-inhibited neurons in the vCA1 → Acb projection compared

to chance level. All of the other projection types lay within confidence intervals (p > 0.05).

Fig. 3 (D). Percentage of reward zone-excited, reward zone-inhibited and non responsive

neurons in vCA1 projections to mPFC/Acb and Acb were differently represented. The null

hypothesis that reward zone responses had similar proportions across or within vCA1 projections

to mPFC/Acb and Acb was rejected by the Pearson Chi-Square test: χ2 (2, 64) = 10.55, p < 0.01.

Thus, there were significantly more reward zone-excited neurons in vCA1 → mPFC/Acb

projections (n = 6 out of 29, 20.67 %) than reward zone-excited neurons in vCA1 → Acb

projections (n = 1 out of 35, 2.86 %), and than reward zone-inhibited neurons within vCA1 →

mPFC/Acb projections (n = 1 out of 29, 3.45 %, post-hoc Bonferroni correction, p < 0.05 for

both comparisons). Also, there were significantly more reward zone-inhibited neurons in

vCA1→ Acb projections (n = 10 out of 35, 28.57 %) than reward zone-inhibited neurons in

vCA1→ mPFC/Acb projections (n = 1 out of 29, 3.45 %), and than reward zone-excited neurons

within vCA1 → Acb projections (n = 1 out of 35, 2.86 %, post -hoc Bonferroni correction, p <

0.05 for both comparisons). The proportions of non-responsive neurons were not significantly

different from the other groups.

Fig. 3 (E). Comparison of absolute difference in firing rate between reward zone and maze for

vCA1 projections with an axon collateral in Acb (n = 79, 1.12 ± 0.23 Hz) compared to vCA1

neurons without Acb projections (n = 20, 0.47 ± 0.19 Hz). Two-tailed, unpaired t-test revealed a

significant difference (p < 0.05). Values are expressed as mean ± s.e.m..

Fig. 4 (A). (Left) Percentage of overall task responsiveness was higher than chance levels in

vCA1 → mPFC/Amy/Acb projections (Bootstrap analysis, p < 0.05). None of the othe r

projection types lay beyond confidence intervals (Bootstrap analysis, p > 0.05 for all the

projection types).

Fig. 4 (A). (Right) Percentage of overall task responsive neurons was higher in the vCA1 →

mPFC/Amy/Acb projections compared to all the remainder of the vCA1 projections pooled

together (Pearson Chi-Square test: χ2 (1, 297) = 4.72, p < 0.05).

Fig. 4 (B). (Left) Comparison of the averaged firing rates of the vCA1 projection types across the

three behavioural tasks. One-way ANOVA test (F(7,16) = 8.53, P < 0.001) revealed a significant

difference among groups (Amy: 2.15 ± 0.34 Hz, Acb: 2.41 ± 0.25 Hz, mPFC: 1.00 ± 0.31 Hz,

mPFC/Acb: 1.62 ± 0.26 Hz, mPFC/Amy: 1.32 ± 0.58 Hz, Acb/Amy: 1.68 ± 0.62 Hz,

mPFC/Amy/Acb: 5.30 ± 1.29 Hz, non identified projection: 5.24 ± 0.17 Hz). Pair wise multiple

comparisons with the Bonferroni t-test revealed significant difference between the vCA1 triple

projections and all the other projection types (P < 0.05), with the exception of the non-identified

projection group (p > 0.05).

Fig. 4 (C). Percentage of SWR-active neurons was higher than chance levels in the vCA1 →

mPFC/Amy/Acb projections (Bootstrap analysis, p < 0.05). None of the other projection types

lay beyond confidence intervals (Bootstrap analysis, p > 0.05 for all the projection types).

Fig. S5. There were no differences in the jitter of antidromic spikes before (0.24 ± 0.03 ms; mean

± s.e.m.) and after drug application (0.20 ± 0.02 ms, n = 4 cells, p > 0.05, two-tailed paired t-

test).

Fig. S8 (A). Comparison of percentage of time and entries in open and closed arms of the

elevated-plus-maze. Two-tailed, paired t-test revealed a significant difference for the percentage

of time spent in open arms vs. closed arms (open arms: 41.42 ± 4.96 %, closed arms: 58.58 ±

4.96 %, n = 16 elevated-plus-maze sessions, p < 0.05) and of entries in open vs. closed arms

(open arms: 44.57 ± 3 .48 %, closed arms: 55.43 ± 3.48 %, n = 16 elevated-plus-maze sessions, p

< 0.05). Values are expressed as mean ± s.e.m..

Fig. S8 (B). Comparison of the firing rate differences between each closed arm and each open

arm of the elevated-plus-maze for all vCA1 neurons. Difference of firing rate from mean firing

on the elevated-plus-maze was calculated for each closed arm (closed arm 1: -0.26 ± 0.09 Hz,

closed arm 2: -0.27 ± 0.08 Hz) and each open arm (open arm 1: 0.31 ± 0.09 Hz, open arm 2: 0.22

± 0.07 Hz) for all 233 vCA1 neurons. Due to non-normally distributed data, the Kruskal–Wallis

one-way ANOVA ranks test was used and revealed significant differences between the different

arm groups (H = 56.84, 3 degrees of freedom, P < 0.001). Pair wise multiple comparisons with

the Tukey test revealed significant differences between closed arm 1 and each of the open arms

(p < 0.05) and between closed arm 2 and each of the open arms (p < 0.05). There were no

significant differences between closed arm 1 and closed arm 2, and between open arm 1 and

open arm 2 (p > 0.05 for both). Values are expressed as mean ± s.e.m..

Fig. S9. (Left) Comparison of place field size between vCA1 (n = 233, 59.23 ± 1.99 %) and

dCA1 (n = 266, 48.83 ± 2.02 %) revealed significantly larger place fields in vCA1 vs. dCA1

(Mann-Whitney Rank Sum Test, p < 0.001). Values are expressed as mean ± s.e.m..

Fig. S9. (Middle) Comparison of the spatial tuning of place fields between vCA1 (n = 233, 4.26

± 0.40 Hz) and dCA1 (n = 266, 7.94 ± 0.42 Hz) revealed significantly lower spatial tuning in

vCA1 vs. dCA1 (Mann-Whitney Rank Sum Test, p < 0.001). Values are expressed as mean ±

s.e.m..

Fig. S9. (Right) Comparison of the spatial stability of place fields between vCA1 (n = 233, 0.11

± 0.02 %) and dCA1 (n = 266, 0.38 ± 0.02 %) revealed significantly less stable place fields in

vCA1 vs. dCA1 (Mann-Whitney Rank Sum Test, p < 0.001). Values are expressed as mean ±

s.e.m..

Fig. S10 (B). (Top left) A two-way repeated measures ANOVA test revealed no significant

difference within the strategy factor (allocentric and egocentric, F(1,754) = 0.88, p > 0.05).

Fig. S10 (B). (Top right) A two-way repeated measures ANOVA test revealed a significant

difference within the reward zone factor (reward zone 1, reward zone 2, (F(1,754) = 4.93, p <

0.05). Yet, none of interaction between reward zone and time led to significant results (post-hoc

Bonferroni test, p > 0.05).

Fig. S10 (B). (Bottom left) A two-way repeated measures ANOVA test revealed no significant

difference within the trajectory factor (trajectory 1, 2, 3 4, F(3,2262) = 0.54, p > 0.05).

Fig. S10 (B). (Bottom right) A two-way repeated measures ANOVA test revealed no significant

difference within the reward outcome factor (rewarded and non rewarded, F(1,754) = 3.08, p >

0.05).

Fig. S13. (Left) Percentage of task responsive neurons was higher than chance levels in vCA1 →

mPFC/Amy/Acb and vCA1 → mPFC/Acb projections (Bootstrap analysis, p < 0.05). (Right)

Percentage of task responsive neurons was higher than chance levels in double and triple vCA1

projections (Bootstrap analysis, p < 0.05). None of the other projection types lay beyond

confidence intervals (Bootstrap analysis, p > 0.05 for all the projection types).

Fig. S1. Location of the recording sites in vCA1 and dCA1 and endpoints of the optic fibres during photostimulation in mPFC, Acb and Amy.

- 4.6 mm - 4.8 mm - 5.2 mm

- 4.4 mm- 3.8 mm- 3.1 mm

- 2.6 mm1.8 mm3 mm

Recording site Optical stimulation site

1 mm

mPFC Acb Amy

dCA1 dCA1 dCA1

vCA1 and dCA1 vCA1 vCA1

Fig. S2. For each projection type three neurons with light-induced spikes from multisynaptic pathways are shown (green rectangles), which have a longer latency and larger jitter compared to light-induced antidromic spikes (red rectangles).

-50 -40-30-20-10 0 10 20 30 40 50

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Optic fibre targeting the Amy:three different vCA1 cells

Optic fibre targeting the Acb :three different vCA1 cells

Optic fibre targeting the mPFC:three different vCA1 cells

Latency (ms) Latency (ms) Latency (ms)

= light-induced antidromic spikes= light-induced spikes from mutli-synaptic pathways

Fig. S3. For each projection type five neurons with increasing antidromic activation latencies are shown. Note that the jitter of the antidromically evoked spikes does not increase with longer latencies. Activation latencies reflect axonal geometries, paths and conduction time, and might be different for individual vCA1 pyramidal cells (22).

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Latency (ms)

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Latency (ms)

Latency: 4 ms

Latency: 9 ms

Latency: 12 ms

Latency: 7 ms

Latency: 11 ms

Latency: 7 ms

Latency: 9 ms Latency: 11 ms

Latency: 13 ms

Latency: 15 ms Latency: 17 ms

Latency: 15 ms

Latency: 8 ms

Latency: 13 ms

Latency: 11 ms

Five different vCA1 Amyproj. neurons

Five different vCA1 Acbproj. neurons

Five different vCA1 mPFCproj. neurons

Fig. S4. (A) For each projection type the spikes of a neuron induced with different laser powers are shown. Note that the latencies increased with lower laser power. (B) For the majority of projecting neurons, such a shift in spike latencies with different laser powers were observed which is consistent with a previous report on optogenetically induced spikes (38).

-50 -40-30-20-10 0 10 20 30 40 500

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Latency (ms) Latency (ms)

Estimated power: 15 mWLatency: 8.0 ms

Late

ncy

chan

gew

ithpo

wer

chan

ge(%

neur

ons)

0

50

100

vCA1 Amy projections vCA1 Acb projections vCA1 mPFC projections

-50-40-30-20-10 0 10 20 30 40 500

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50

Latency (ms)

Estimated power: 3 mWLatency: 10.8 ms

vCA1 mPFCproj. neuron

vCA1 Acbproj. neuron

vCA1 Amyproj. neuron

-50 -40-30-20-10 0 10 20 30 40 50

Tria

ls

0

10

20

30

40

50Estimated power: 30 mWLatency: 4.3 ms

Estimated power: 20 mWLatency: 8.2 ms

Estimated power: 7 mWLatency: 8.8 ms

Estimated power: 30 mWLatency: 7.4 ms

Estimated power: 20 mWLatency: 11.6 ms

Estimated power: 7 mWLatency: 12.9 ms

Estimated power: 30 mWLatency: 10.5 ms

0

50

100

0

50

100

17/21 64/79 39/52

A

B

= light-induced antidromic spikes

Fig. S5. Spontaneous and light-induced spiking of four vCA1 neurons before and after infusion of synaptic transmission blockers in vCA1 and the frontal cortex of an anesthetised rat. In the presence of NBQX and APV, spontaneous spiking and light-induced orthodromic spikes (B, green box) are abolished, while light-induced antidromic spiking (A; red box) remains stable. There are no differences in the jitter of antidromic spikes before (0.24 ± 0.03 ms; mean ± s.e.m.) and after drug application (0.20 ± 0.02 ms, n = 4 cells, p > 0.05, two-tailed paired t-test).

light period, same laser power before and after NBQX+APV

NBQX+ APV

-100 -50 0 50 1000

25

50

-100 -50 0 50 1000

25

50

NBQX+ APV

-100 -50 0 50 1000

25

50

Latency (ms)

-100 -50 0 50 1000

25

50

Latency (ms)

A

B

= light-induced antidromic spikes

= light-induced orthodromic spikes

NBQX+ APV

-100 -50 0 50 1000

25

50

-100 -50 0 50 1000

25

50

Latency (ms)Latency (ms)

NBQX+ APV

-100 -50 0 50 1000

25

50

-100 -50 0 50 1000

25

50

Tria

lsTr

ials

Tria

lsTr

ials

Fig. S6. (A) Spike waveform comparison between spontaneous and light-induced activity in an optogenetically identified vCA1 projection neuron. Scale bars: 400 µs, 50 µV. (B) Correlation values of spontaneous and light-induced spike waveforms of all vCA1 projection neurons.

Waveform similarity (r)0.90 0.95 1.00

Cou

nt

0

10

20

30

r = 0.994

LightSpont.

A B

Fig. S7. Measures of antidromic spike responses across individual vCA1 projection neurons targeting Amy, Acb or mPFC. (A) Percentage of vCA1 → Amy projection neurons with spike collision, low spike jitter, early spike latency, high spike fidelity and with the ability to follow high frequency stimulations. (B) Same quantification as in (A) for vCA1 projection neurons targeting Acb. (C) Same quantification as in (A) for vCA1 projection neurons targeting mPFC. Projection neurons without spontaneous activity during stimulation or with collisions occurring during the refractory period of a spontaneous spike before antidromic activation (< 2 ms) are defined as not testable collisions. Absolute numbers per category are indicated.

Perc

enta

ge

0

25

50

75

100

Not testable collision

Spike collision (w/o a sequenceof 5 consecutive antidromic spikes)

Spike collision (in a sequenceof at least 5 consecutiveantidromic spikes)

11

4

6

Spikes follow 50 or 20 Hzphotostimulations

Spikes do not follow 50 or 20 hzphotostimulations

Jitter < 0.3 ms Spike fidelity > 50%

Spike fidelity < 50%

Photostimulationnot tested

12

9

21

8

8

5

Amy < 13 ms, Acb < 17 ms,mPFC < 22 ms

21

A vCA1 to Amy projections B vCA1 to Acb projections C vCA1 to mPFC projections

Collis

ion

Jitte

rLa

tenc

yFi

delity HFS

Perc

enta

ge

0

25

50

75

100

38

27

14

44

35

79

47

15

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79

Collis

ion

Jitte

rLa

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yFi

delity HFS

Perc

enta

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10032

11

9

31

21

5231

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52

Collis

ion

Jitte

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yFi

delity HFS

Spike collision: Spike jitter: Spike latency: Spike fidelity: High frequency stimulation(HFS):

Fig. S8. Specificity of anxiety-related firing in the vCA1. (A) (Left) Trajectory of a rat during elevated-plus-maze exploration and (right) percentage of time spent and entries in the open and closed arms of the elevated-plus-maze for all anxiety sessions (n = 16). Error bars indicate mean ± s.e.m. (B) (Left) Firing rate map of an individual vCA1 neuron with higher discharge in each of the open arms compared to the closed arms. (Right) Averaged firing rates

Perc

enta

ge

0

20

40

60

80**

Open armsClosed arms

Time Entries

Closed arm

Open arm

Rat's trajectory ΔFi

ring

rate

(di ff

.fro

mm

ean,

Hz)

-0.50

-0.25

0.00

0.25

0.50

Closedarms

n = 233

**

Openarms

(open arm 1)

-8 -4 0 4 8

(ope

nar

m2)

-5

0

5

(closed arms)

-15 -10 -5 0 5 10

(ope

nar

ms)

-10

-5

0

5r2 = 0.33p < 0.001

r2 = 0.27p < 0.001

Δ Firing rate(closed arm 1)

-15 -10 -5 0 5 10

ΔFi

ring

rate

(clo

sed

arm

2)

-10

-5

0

5 r2 = 0.21p < 0.001

Min

Firingrate

Max25 cm

25 cm

BA

C Correlational analysis within standard EPM

D Correlational analysis across standard and altered EPM

Δ Firing rate(standard maze)

-12 -8 -4 0 4

Firin

gra

te(a

ltere

dm

aze)

-15-10

-505 r2 = 0.24

p < 0.001

(standard maze)

-8 -4 0 4 8

Firin

gra

te(a

ltere

dm

aze)

-15

0

15

30 r2 = 0.27p < 0.001

open - openclosed - closed

EPM score(standard maze)

-0.5 0.0 0.5 1.0

EPM

scor

e(a

ltere

dm

aze)

-0.5

0.0

0.5

1.0 r2 = 0.19p < 0.001

ΔFi

ring

rate

ΔFi

ring

rate

Δ Firing rate Δ Firing rateΔ Δ

Δ Firing rate

Cel

ls(%

)

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50

**

33/23315/266

*

17/1343/70/80/24/295/144/350/4

Cel

ls(%

)

0

25

50

dCA1 vCA110/2334/266

Amy Acb mPFC mPFCAcb

mPFCAmy

AcbAmy

mPFCAmyAcb

non ident.projection

7/1340/70/80/21/291/141/350/4

Cells firing in open arms

Cells firing in closed arms

F

E

Mean EPM score ofEPM-responsive neurons

0.3 0.6 0.9

0

50

100

r2 = 0.28p < 0.05

Ope

nar

ms

-clo

sed

arm

s(%

time)

(difference from mean) of the entire vCA1 neuronal population in each arm of the elevated-plus-maze. A higher firing is observed in open arms. Error bars indicate mean ± s.e.m. (C) Correlational analysis of firing rates for all vCA1 units (n = 233) between (left) open arms, (middle) closed arms and (right) across open and closed arms. Firing rates are positively correlated within the closed and open arms, but negatively correlated across arms of different types. (D) Correlational analysis of (left) elevated-plus-maze scores, and of firing rates across (middle) closed arms and (right) open arms in the standard and altered elevated-plus-maze (n = 58 units). Elevated-plus-maze scores and firing rates are positively correlated across mazes. (E) Most of the neurons with significant elevated-plus-maze-score increase their firing when the animals are on the open arms. The histogram from Fig. 2C is here split into neurons firing more on the open or closed arms. (F) Elevated-plus-maze-scores (averaged for each behavioural session) correlate with behavioural anxiety levels measured as time spent in open or closed arms (n = 16 elevated-plus-maze sessions). Note that no differences in linear speed or acceleration (data not shown) are observed between open and closed arms (speed open arms: 22.1 ± 1.0 m/s, speed closed arms: 21.9 ± 1.3 m/s, acceleration open arms: 1.2 ± 1.4 m/s2 acceleration closed arms: -1.2 ± 1.4 m/s2, n = 16 sessions, p > 0.05, data are mean ± s.e.m.. * P < 0.05, ** P < 0.01 significance levels.

Fig. S9. Measures of place cells across the longitudinal axis of the hippocampus. (Left) Quantification of place field size, (middle) spatial tuning and (right) spatial stability in dCA1 (n = 266) and vCA1 (n = 233) neurons. vCA1 neurons have larger place fields, lower spatial tuning and stability compared to dCA1 neurons. Box plots indicate median, quartiles (boxes) and range (whiskers). *** P < 0.001 significance levels.

Plac

efie

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ze(%

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)

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vCA1dCA1 Spat

ialt

unin

g(Δ

Hz)

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10

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vCA1 dCA1

Spat

ials

tabi

lity

(r)

-0.5

0.0

0.5

1.0

vCA1dCA1

*** *** ***

Fig. S10. Goal-directed navigation task, behavioural performance and general goal-directed activity in vCA1 projection neurons. (A) (Left) Experimental design of the goal-directed navigation with changing rules. (Right) Behavioural learning curve of a rat during strategy switching predicted by a state–space model (37). Rule change was not signalled to the rat. (B) Normalised population firing rate histograms of reward zone-modulated neurons subdivided into (top left) allocentric and egocentric trials, (top right) reward zone 1 and reward zone 2 trials, (bottom left) trajectory 1, 2, 3 or 4 trials and (bottom right) rewarded and non-rewarded trials. No change is observed in any of the conditions suggesting that goal-directed firing is a general phenomenon for a subset of vCA1 projection neurons. Data are mean ± s.e.m.

Start

Start

RewardReward

Start

Start

Allocentric("go to west")

Egocentric("turn right")

Reward >< <Trials

0 20 40 60Prob

abili

tyof

aco

rrec

ttria

l

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0.5

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Switch

mean performance95th confidenceinterval

incorrect trial

correct trial

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Firin

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Time (s)

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traj. 3traj. 2traj. 4

Time (s)

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non-rewarded

reward zone 1reward zone 2

-2 -1 0 1 2 3 4

-1012

-2 -1 0 1 2 3 4

-1012

B

Firin

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te(Z

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reno

rm.)

Firin

gra

te(Z

-sco

reno

rm.)

Firin

gra

te(Z

-sco

reno

rm.)

<

Fig. S11. Correlational analysis of firing rates versus locomotor activity in vCA1. (Left) Low correlation values of firing rates (n = 233 units) with the speed or (right) the acceleration of the rats.

Firing rate vs.acceleration correlation (r)

-1.0 -0.5 0.0 0.5 1.0

Cou

nt0

50100150200250

Firing rate vs.speed correlation (r)

-1.0 -0.5 0.0 0.5 1.0

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050

100150200250

Fig. S12. The number of vCA1 projection neurons and the percentages of anxiety-related, place and reward zone-responsive cells are shown for each of the four recorded rats individually. Projections significantly enriched in tasks responsive neurons are marked with an arrow. Note that the observed differences in task responsiveness are not due to a strong sampling bias originating from a single animal. Note that the percentages of anxiety-related, place and reward zone-responsive cells were not different (data not shown) when comparing the cells with faster antidromic activation latencies (0-50th percentile) to all cells (chi-square tests, p > 0.05).

Anxi

ety

cells

(%)

0

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30

40

50

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ece

lls(%

)

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Rew

ard-

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ulat

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)

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mPFCAmy

mPFCAmyAcb

AcbAmy

Num

ber o

f pro

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ions

0

10

20

30

40

rat 1 rat 2 rat 3 rat 4

Fig. S13. Higher overall behavioural responsiveness of vCA1 triple projections compared to chance level and (right) to the other vCA1 projection types pooled together. Numbers indicate the ratio of task-responsive neurons in each group. This is the same plot as in Fig. 4A but here each neuron counts only as 1 irrespective if it responds to one, two or all three tasks. Note the stepwise increase in task-responsiveness along with increase in target numbers. * P < 0.05 significance level.

Task

resp

.(%

)

0

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40

60

80

100

Amy Acb mPFC mPFCAcb

mPFCAmy

mPFCAmyAcb

non ident.projection

AcbAmy

*

58/1346/75/81/218/296/1416/351/4

*

58/1346/724/3923/53

**

Tripleproj.

non ident.projection

Singleproj.

Doubleproj.

Fig. S14. Percentages of anxiety-related, place, reward zone-excited or reward zone-inhibited neurons for each projection type. Bootstrap analysis indicates that reward zone-inhibited cells are significantly enriched in neurons projecting to Acb, while anxiety-related cells are significantly enriched in neurons projecting to mPFC (p < 0.05). This analysis for single projections across different tasks reaches similar conclusion as the analysis of different projections for a single task shown in Figs. 2 and 3.

Task

resp

.cel

ls(%

)

0

20

40

60

Amy(n = 4)

Acb(n = 35)

mPFC(n = 14)

mPFCAcb

(n = 29)

mPFCAmy(n = 2)

mPFCAmyAcb

(n = 7)

non ident.projection

(n = 134)

AcbAmy(n = 8)

**

0 1 0 1 5 4 1 10 6 1 1 1 5 3 6 1 0 1 0 0 0 0 1 3 3 3 1 1 24 20 11 22

Anxiety cells Place cells Reward zone-excited cells

Reward zone-inhibited cells

Table S1. The overlap of task-responsive cells is listed for each projection type. Note the low number of cells responding to more than one task. In particular, out of the 11 vCA1-> Acb reward zone-modulated neurons, only 3/11 are also responsive in the other two tasks. Similarly, out of the 6 vCA1-> mPFC anxiety neurons, only 1/6 is also responsive in the other two tasks. Out of the 7 vCA1-> mPFC/Acb reward zone-modulated neurons, only 1/7 is also responsive in the other two tasks.

Amy(n = 4)

Acb(n = 35)

mPFC(n = 14)

mPFCAcb

(n = 29)

mPFCAmy(n = 2)

mPFCAmyAcb(n = 7)

non ident.projection

(n = 134)

AcbAmy(n = 8)

Anxiety/place

Anxiety/goal

Place/goal

Anxiety/place/goal

Ove

rlap

of ta

skre

spon

sive

cells

0 1 1 1 0 0 0 3

1 2 1 1 0 0 1 2

0 2 2 1 0 0 1 10

0 1 0 1 0 0 0 0

Projection type

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