www.sciencemag.org/cgi/content/full/313/5790/1093/DC1

Supporting Online Material for

Learning Induces LTP in the Hippocampus Jonathan R. Whitlock, Arnold J. Heynen, Marshall G. Shuler, Mark F. Bear*

*To whom correspondence should be addressed. E-mail: mbear@mit.edu

Published 25 August 2006, Science 313, 1093 (2006).

DOI: 10.1126/science.1128134

This PDF file includes

Materials and Methods Figs. S1 to S8 References

MATERIALS AND METHODSAnimal housing and behavioral proceduresAdult male Long Evans rats (weight 250-350 g) were used in all experiments. Animalswere housed in pairs and kept on a 12-hour light/dark cycle in animal care facilities atleast 6 days prior to behavioral assessment, with access to food and water ad libidum.

IA training experimentsOn the day of training animals were moved into a sound-attenuated, dimly lit room withthe IA training apparatus. The apparatus is a two-chambered Perspex box consisting of alighted safe side and a dark shock side separated by a trap door. During training, ratswere placed in the safe side of the box facing a corner opposite the door. After 10 s thetrap door opened, allowing animals to enter the dark side at will. Four seconds after theanimals entered the dark side, the door closed behind them and they received a 2-s, 1.5mA scrambled foot-shock via electrified steel rods in the floor of the box. The animalswere given 15 s recovery time in the dark compartment before being returned to theirhome cages. At specific time points after training, the animals were either killed with anoverdose of pentobarbitol for biochemical assays, or were tested for avoidance retention(behavioral assay). Retention was assessed by placing either trained or walk-throughcohorts (cagemates that did not receive a foot-shock upon entering the dark compartment)back in the lighted side of the box and measuring latencies for the animals to re-enter thedark compartment. Reentry was counted when all 4 of the animals’ paws were back inthe dark side of the IA apparatus. The foot-shock was not readministered duringretention assays, and measurements were terminated at a ceiling retention interval of 540s. In the biochemical experiments, animals in the “shock-only” condition were placed inthe shock-side of the IA apparatus, given a 2-s, 1.5 mA foot shock and were removedimmediately thereafter. For the in vivo recording experiments, “shock only” conditioningwas administered in a separate clear Perspex box with an electrified floor grating similarto the IA apparatus. Animals given pretraining injections (of saline or CPP, 10 mg/kg)were injected 1 hour prior to training. Statistical significance for avoidance retention wasdetermined using a repeated measures ANOVA, with the criterion for significance set atP < 0.05.

Membrane and synaptoneurosome biochemical preparationsHippocampal and cerebellar tissue samples were obtained at specific time-points after IAtraining or control conditions. Dissections were performed using ice-cold dissectionbuffer (212.7 mM sucrose/2.6 mM KCl/1.23 mM NaH2PO4/26 mM NaHCO3/ 10 mMdextrose/1.0 mM MgCl2/0.5 mM CaCl2/0.02 mM CNQX/0.1 mM D,L-APV/andsaturated with 95% O2/5% CO2).

Membrane preparation: upon dissection, tissue samples were sonicated in 2 mLresuspension buffer (10 mM Na H2PO4 (pH 7.0)/ 100 mM NaCl/10 mM SodiumPyrophosphate/5 mM EDTA/5 mM EGTA/1 µM okadaic acid/1 µM microcystin/10U/mL aprotinin/50 mM NaF/1 mM Sodium Orthovanadate) and spun for 5 min at13,000g. Resultant pellets were re-suspended in 1 mL of fresh re-suspension buffer,sonicated, and spun for 5 min at 13,000g. Pellets were then re-suspended in 200 µL 1%SDS, boiled for 10 min, and stored at –80°C.

Synaptoneurosome preparation: upon dissection, tissue samples were homogenizedin ice-cold homogenization buffer (10 mM Hepes/1.0 mM EDTA/2.0 mM EGTA/0.5mM DTT/0.1 mM PMSF/10 mg/liter leupeptin/100 nM microcystin). Tissue washomogenized in a glass/glass tissue homogenizer, and homogenates were passed throughtwo 100-µm-pore nylon mesh filters, then through a 5-µm-pore filter. Filteredhomogenates were centrifuged at 3600g for 10 min at 4°C. Resultant pellets were re-suspended in 200 µL boiling 1% SDS, boiled for 10 min, and stored at –80°C.Homogenates were also kept for each hippocampal sample, which consisted ofunprocessed homogenate boiled in 10% SDS for 10 min and stored at –80°C. Aspreviously described (S1, S2), synaptoneurosomes enrich for synaptic elements whichresemble native synaptic profiles and this preparation has been shown to be reliable indetecting AMPAR redistribution following LTP induction in the hippocampus in vivo(S3).

Quantitative immunoblottingEqual amounts of membrane, synaptoneurosome, or homogenate, determined with thebicinchonic acid assay (BCA), were resolved on 7.5% polyacrylamide gels, andtransferred to nitrocellulose or PVDF membranes. Membranes were blocked with either1% BSA or 5% non-fat dry milk in TBS-Tween 20 (0.1%) for 1 hour and incubated inprimary antibody (p-Ser831 1:500, p-Ser845 1:500; GluR1 1:1000; GluR2 1:200; NR11:1000, or Actin 1:2000. Blots were then washed 3 x 10 min in TBS-Tween 20 andplaced in HRP-conjugated anti-rabbit secondary antibody (1:3500 for p-Ser831 & Ser845,and GluR1), HRP-conjugated anti-mouse antibody (1:3500 for Actin), or HRP-conjugated anti-goat secondary antibody (1:3500 for NR1, 1:200 for GluR2). Blots werethen washed 3 x 20 min in TBS-Tween 20, then 3 x 10 min in TBS and reacted with ECLor ECL-plus reagents.

ECL-treated blots (used for phospho-specific antibodies) were visualized usingautoradiographic ECL-hyperfilms. Digital images, produced by densitometric scanning ofautoradiographs using Desk Scan II software were quantified using NIH Image 1.62software. Optical densities for bands were determined relative to baseline valuesimmediately above and below the bands in the same lanes. To determine total GluR1amounts, the same nitrocellulose blots were stripped in low pH acid strip buffer (0.2 MGlycine, pH 2.5, 0.05% Tween-20), re-probed for GluR1, and quantified again asdescribed above. Quantification of the immunoblots was carried out with the quantifierblind to the tissue samples loaded (i.e., hippocampal versus cerebellar tissue; control vs.trained tissue) and antibodies used (i.e., phospho Ser831 vs. GluR1). Absorbances forphospho-specific antibodies were normalized to within-lane GluR1 absorbances togenerate a phospho-specific/total GluR1 ratio (i.e., p-Ser831/GluR1 or p-Ser845/GluR1).The p-Ser831/GluR1 or p-Ser845/GluR1 ratios for each trained animal were thennormalized to corresponding values from their cagemate controls. For display purposes,the ratios across trained and control animals were averaged and data were expressed as apercentage of control values. The linear range for phospho-specific antibody signaldetection was determined for each lot of antibody prior to running experimental samples.This was done by loading protein samples at systematically varied concentrations anddetermining the range within which the phospho-specific/GluR1 signal did not change asa function of the amount of protein loaded. All experimental samples were then loaded

within the linear range for antibody signal detection. Statistical significance at each time-point following training was determined using a 2-tailed, paired Student’s t-test.

ECL-plus treated PVDF blots were visualized using a Storm 860 scanner with thePMT set at 800 V. Scanned images were quantified with ImageQuant software. We thenperformed a volumetric analysis with the local median surrounding each band serving asbackground values. Values obtained for GluR1, GluR2 and NR1 were normalized towithin-lane actin signal (as a loading control). Again, protein samples were loaded withinthe range where Glutamate Receptor/Actin ratios did not change as a function of proteinconcentration. For display purposes, Glutamate Receptor/Actin ratios from trainedanimals were normalized to their control counterparts as described above. Statisticalsignificance at each time-point following was determined using a 2-tailed, pairedStudent’s t-test.

Surgery and electrode placementAnimals were deeply anaesthetized with Nembutal (65 mg/kg), placed in a stereotaxicframe and anaesthesia was maintained with inhaled isofluorane. A trephine hole 3 mm indiameter was made in the skull overlying the dorsal hippocampus, with the center of thehole 3.6 mm posterior to Bregma and 2.5 mm lateral to the midline. A single-row, 8-electrode recording array ~1.75 mm in width was implanted 3.6 mm posterior to Bregmawith the medial-most electrode 1.1 mm lateral of the midline. A monopolar stimulatingelectrode was implanted immediately posterior and lateral to the recording array. Bothstimulating and recording electrodes consisted of stainless steel wire insulated withTeflon; recording electrodes were 50µm in diameter, and the stimulating electrode was75µm in diameter. The final position (depth) of the stimulating and recording electrodeswas at a site eliciting a maximal field potential (fEPSP) slope across all recordingelectrodes in CA1. Craniotomy holes were then filled with a small amount of dentalcement and the electrode assembly was secured firmly to screws previously inserted inthe skull. Surgical wounds were sutured, and antiseptic ointment was applied to preventinfection. Animals were provided softened, wet food during postoperative recovery.Evoked fEPSPs were amplified (x1000) and filtered at 1-3 kHz, digitized at 4 kHz andstored on a PC using Plexon Recorder software. fEPSP slope was determined with anautomated algorithm on digitized raw data in MATLAB.

Electrophysiological recordings during behavioral manipulationsOne week following surgery, animals were handled and habituated to a recording box(14” x 14” x 16” black Perspex) for a minimum of 2 days. For LTP saturationexperiments, habituation was extended by at least 1 additional day, and animals were pre-exposed to the light side of the IA training apparatus. On the subsequent day, input-output curves were obtained and baseline responses were recorded for at least 1 hour.fEPSPs were evoked once every 30 s using stimuli of 0.2 ms duration. fEPSPs (4 Khzsampling frequency) were entered into MATLAB for automated analysis. The algorithmin MATLAB determines the fEPSP slope value by finding the maximum value of thederivative of the signal within the first 5 ms following the stimulus artifact (care wastaken to avoid contamination of this measurement by the fiber volley when present). Theaccuracy of the algorithm was verified by concomitant real-time slope measurementsusing Experimenter's Workbench (DataWave Technologies). All baseline recordingswere carried out with a stimulation intensity that elicited a group average of ~50%

maximal fEPSP slope across the multiple recording electrodes. For LTP saturationexperiments, we also determined the maximal stimulation intensity of HFS to induce LTPwithout causing ictal after-discharges (20-70% maximal, individually determined foreach animal) on this day. On the day of behavioral conditioning, baseline responses wererecorded for at least 1 hour, animals underwent behavioral conditioning (e.g. IA training),and baseline-intensity recordings resumed ~15 minutes following conditioning for 3-4hours. Care was taken to ensure that the animals remained awake and at rest for theduration of the recordings. Electrophysiological data recorded after behavioralconditioning were normalized to the baseline period and for presentation purposes, slopemeasurements were averaged into 5 min time bins for each individual electrode and themean (± SEM) plotted for each group. For LTP saturation experiments, HFS consisted ofa 1-s train of pulses (200µs) delivered at 100 Hz. 5 trains of HFS (delivered 30 s apart)were delivered at 30-minute intervals until the electrodes showed no further fEPSP slopeenhancements. Statview (version 5.0.1) software was used for all statistical analyses.

ReferencesS1. E. M. Quinlan, D. H. Olstein, M. F. Bear, Proc Natl Acad Sci U S A 96, 12876

(1999).S2. E. B. Hollingsworth et al., J Neurosci 5, 2240 (1985).S3. A. J. Heynen, E. M. Quinlan, D. C. Bae, M. F. Bear, Neuron 28, 527 (2000).

Figure LegendsFig. S1. Single-trial inhibitory avoidance training results in a long-lasting, NMDAR-dependent contextual aversion. (A) Latency (in seconds) for IA trained animals (blackcircles) and walk-through controls (white circles) to re-enter the shock compartment ofthe apparatus; latencies were measured with separate groups of animals up to 24 hourspost-conditioning. Error bars indicate SEM in this and all subsequent figures. At all post-training time-points (0 to 24 hours), trained animals waited significantly longer thanwalk-through cohorts to re-enter the dark side (repeated measures ANOVA, F(1,36)=149.5, P < 0.0001). (B) Pre-training injection of a competitive NMDAR-antagonist, (RS)-3-(2-carboxypiperazin-4-yl)-propyl-1-phosphonic acid (CPP; 10 mg/kg, i.p.; n = 8, greybars), significantly reduced avoidance retention compared to saline-injected controls(black bars, n = 11) both 30 minutes and 24 hours after training (repeated measuresANOVA, F(1,10)= 39.37 P < 0.0001). The latencies for the two groups to enter the darkside during acquisition of the task did not differ (unpaired Student’s t test, P > 0.05).

Fig. S2. IA training results in an enhancement of fEPSPs in area CA1 of thehippocampus in vivo. (A) Single animal example (same as in Fig. 2 without averagingdata into 5 min bins) of raw fEPSP slope measures obtained from 2 electrodes prior toand following IA training. One electrode showed an average fEPSP enhancement ~15%above baseline (red circles), while the average fEPSP slope measures from the secondelectrode remained within ±7% of baseline (blue circles). (B) Within-animaldemonstration that fEPSP enhancements >10% above baseline are specific to IA training.First pair of color plots represent fEPSP slope measurements obtained from one animalfollowing the walk-through condition (top) and, on a subsequent day, following IAtraining (bottom). Bottom pair of color plots present data from a second animal who firstunderwent the shock-only condition (top) and, on a subsequent day, received IA training(bottom). None of the recording electrodes from either animal showed, on average, >10%enhancement of fEPSPs following the control conditions, whereas 3 electrodes showed>10% enhancement following IA training. (C-F) Color plots representing fEPSP slopemeasures obtained from all animals in the study, including those subjected to a secondbehavioral condition (white tick-marks indicate individual animals in each group).Whereas 16 of 71 recording electrodes showed average fEPSP slope measures >10%above baseline following IA training, no electrodes showed such an enhancementfollowing any of the control behavioral conditions (totaling 174 electrodes). Of the 10trained animals (T1-T10), 4 had undergone prior control behavioral conditioning; T4 &T5

were used as walk-through controls (W1 & W2), and T7 & T10 were used earlier as shock-only animals (S5 & S2). Walk-through animals W5 & W7 were used previously as shock-only controls (S3 and S7). Shock-only animals S1, S6 & S8 were used previously as walk-through animals (W3, W6 & W9). (G-I) Cumulative probability distributions of fEPSPslope for IA trained (red circles, n = 71 electrodes), walk-through (white circles, n = 65electrodes), shock-only (light grey, n = 54 electrodes), and naïve animals (blue, n = 55electrodes) demonstrate that fEPSP slope measures were enhanced following IA trainingrelative to control conditions (K-S test, P < 0.05) at 30 minutes, 60 minutes, and 120minutes post-conditioning. Note that these findings (and their statistical significance) arecomparable to those animals participating in only a single behavioral condition (shown inFig. 2).

Fig. S3. Learning-related enhancements are obscured in group fEPSP averages, but arerevealed by analyses of the distribution of responses (data obtained from same animals asin Fig. S2). (A-D) Effect of experience on means ± SEM of all electrodes in all animalsnormalized to baseline. Since IA training affected a sub-population of electrodes, thegroup average for fEPSP slope remained within 5% of baseline following IA training (A),whereas average fEPSP slope measures declined over time in the walk-through, shock-only and “naïve” conditions (B-D). (E-H) Effect of experience on the fraction ofelectrodes with responses greater- or less-than 1 standard deviation (SD) of the baselinedistribution. Approximately 16% of channels show responses > 1 SD during baseline.However, after training 28.1% of 71 electrodes had fEPSP slope values > 1 SD of thebaseline distribution (E, filled circles), whereas fEPSP slope in control electrodes did notincrease. The percentage of channels >1 SD below baseline (open symbols) increasedover time in all groups, most likely in a state-dependent manner (see Fig. S4). (I-L)Within-animal variance in responses across electrodes. Plotted are the mean (±SEM)across-electrode standard deviations, normalized to the baseline values. Variability infEPSP slope measures across electrodes increased to more than 200% of the baselinemean following IA training (I), whereas variance remained within ~50% of the baselinemean for controls (J-L).

Fig. S4: All behavioral conditions showed time-dependent decreases in fEPSP slope thatcorrelated significantly with increases in the theta/delta ratio (TDR) in the spontaneousEEG. (A) A single animal demonstrating that decreases in fEPSP slope (black dots;average fEPSP slope from 6 recording electrodes) are attended by concurrent increases inthe TDR (continuous raw TDR measures shown in grey). Arrows indicate epochs whereaverage fEPSP slope decreases as TDR increases. (B) Group average data for the Walk-through condition (n = 9 animals) exemplifies the time-dependent, inverse relationshipobserved between mean fEPSP values and TDR measures (dots represent 30 minute-binaverages for both fEPSP slope and TDR expressed as % baseline; dashed lines indicatelines of best fit for this and subsequent correlations). (C) A statistically significantinverse correlation is observed between mean fEPSP slope and the mean TDR across allbehavioral groups (same animals as in S2; correlation Z-test, R = 0.572 , P < 0.005); eachdot represents a30 min average for EPSP slope and TDR. (D) Data from the IA trainedgroup (grey circles, n = 10 animals) vs. controls (black circles, n = 9 walk, 8 shock, 6naive) did not differ with respect to TDR (1-Way ANOVA, F(3,25) = 0.022, P > 0.85),but did differ in fEPSP slope measures (1-Way ANOVA, F(3,25) = 5.46, P < 0.03).Importantly, the relationship between fEPSP slope and TDR did not differ between IAtrained vs. control groups (ANCOVA, FP slope x TDR, F(3,25) = 0.032, P > 0.85).

Fig. S5: The within-animal SD of fEPSP slope measures does not correlate with inherentSD in spontaneous EEG amplitude. Using MATLAB we calculated the average rootmean square (RMS) of spontaneous local EEG amplitude during the 30-s intervalsbetween evoked fEPSPs from both the baseline and post-training epochs. Average RMSvalues from the post-training epoch were normalized to values from the pre-trainingepoch, and data were expressed as a % baseline. We did not find a relationship betweenaverage within-animal SD in the amplitude of the spontaneous EEG and variance infEPSP slope (each dot represents one trained animal, n = 10; Correlation Z-test, R =0.132, P = 0.725).

Fig. S6: Power spectral analysis did not reveal systematic variations in the spontaneousEEG recorded in electrodes showing fEPSP enhancements > 10% above pre-trainingbaseline values versus neighboring electrodes that did not. To determine whether localfield state varied systematically in electrodes enhanced by IA training vs. non-enhancedelectrodes, we performed a power spectral analysis on the spontaneous LFP in the 10-second interval immediately prior to the evoked fEPSP. Power spectral analysis wasperformed in MATLAB, with filter settings for delta (1.5–4.0 Hz), theta (4.5–12.0 Hz),beta (13.0–30.0 Hz), and gamma (30.0–60.0 Hz) frequencies. Mean power for each of thefrequencies was determined for each electrode before and after behavioral conditioning,and post-training values were normalized to pre-training values. There was no effect ofgroup for “enhanced” vs. “non-enhanced” electrodes across the frequencies analyzed (2-Way ANOVA, F(1,47) = 1.4, P = 0.24).

Fig. S7: Changes in core body temperature cause alterations in synaptic transmission thatwere not detected in IA-trained animals. (A) Representative examples of paired-pulseresponses (40 ms ISI) collected from an anaesthetized animal with core temperatures of29˚C and 37˚C (left column), as well as from an IA-trained animal before and afterconditioning (right column). (B) Increasing core body temperature leads to (i) anenhancement of fEPSP slope and (ii) a simultaneous reduction in paired-pulsefacilitation. (Top) Enhancements in fEPSP slope correlate significantly with increases incore body temperature (Correlation Z-test used here and in subsequent correlationanalyses, R = 0.326, P < 0.005). Black dots represent average slope measures of 20fEPSPs recorded at each temperature in 3 animals. fEPSP slope values are expressed as apercent of initial measures taken at resting body temperature. (Bottom) Increases in coretemperature correlated significantly with decreased paired-pulse facilitation (R = 0.272, P< 0.01). (C) We found a significant inverse correlation between fEPSP slope and paired-pulse ratios measured from individual electrodes in 3 animals with core temperaturesranging from 28.3˚C to 39.3˚C (R = 0.502, P < 0.0001). (D) There was no correlationbetween fEPSP slope and paired-pulse ratios in IA trained animals (R = 0.085, P > 0.49),measured ≥ 75 min after training. (Inset) The 70% average increase of within-animalsvariance in these experiments confirms an effect of IA on fEPSPs (cf. Fig. 3I).

Fig S8: Initial fEPSP slope values from the baseline period correlate with the amount ofsubsequent HFS-induced LTP and the amount of fEPSP enhancement observed followingIA training. (A) A significant positive correlation (R = 0.89, P < 0.0001, correlation Z-test) is observed between the initial (pre-conditioning) fEPSP slope and the degree ofLTP attained after HFS. (B) A significant negative correlation is observed between theinitial (preconditioning) fEPSP slope and the subsequent magnitude of IA-related fEPSPenhancements (Correlation Z-test, R = 0.425, P < 0.005).

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