ABSTRACT The ability to learn novel items depends on brain functions that store information about items classified by their associated meanings and outcomes1,2,3,4, but the underlying neural

circuit mechanisms of this process remain poorly understood. Here we show that deep layers of the lateral entorhinal cortex (LEC) contain two groups of ‘item–outcome neurons’: one

developing activity for rewarded items during learning, and another for punished items. As mice learned an olfactory item–outcome association, we found that the neuronal population of LEC

layers 5/6 (LECL5/6) formed an internal map of pre-learned and novel items, classified into dichotomic rewarded versus punished groups. Neurons in the medial prefrontal cortex (mPFC), which

individual items were held completely separate, disrupting both learning and retrieval of associations. These results suggest that LECL5/6 neurons and mPFC neurons co-dependently encode item

memory as a map of associated outcome rules. Access through your institution Buy or subscribe This is a preview of subscription content, access via your institution ACCESS OPTIONS Access

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support SIMILAR CONTENT BEING VIEWED BY OTHERS DOPAMINE FACILITATES ASSOCIATIVE MEMORY ENCODING IN THE ENTORHINAL CORTEX Article 22 September 2021 HIPPOCAMPAL AND ORBITOFRONTAL NEURONS

CONTRIBUTE TO COMPLEMENTARY ASPECTS OF ASSOCIATIVE STRUCTURE Article Open access 20 June 2024 FAST UPDATING FEEDBACK FROM PIRIFORM CORTEX TO THE OLFACTORY BULB RELAYS MULTIMODAL IDENTITY AND

REWARD CONTINGENCY SIGNALS DURING RULE-REVERSAL Article Open access 22 January 2025 DATA AVAILABILITY The neurophysiological data generated in this study are available on request. CODE

AVAILABILITY The neurophysiological data and analytical codes are available on request and will be deposited with a subsequent protocol paper. REFERENCES * Suzuki, W. A. Associative learning

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and network correlates of two interneuron types in prefrontal cortex. _Nature_ 20, 363–366 (2013). Article  ADS  Google Scholar  Download references ACKNOWLEDGEMENTS We thank M. Witter and

A. Treves, and members in the Igarashi laboratory for providing valuable comments on this work. The work was supported by the US National Institutes of Health (NIH) R01 grants (R01MH121736,

R01AG063864, R01AG066806 and R01AG086441) and a BrightFocus Foundation Research grant (A2019380S) to K.M.I. H.J. was supported by the University of California, Irvine Medical Scientist

Training Program (MSTP; T32GM008620) and the NIH F31 grant (F31AG069500). J.Y.L. was supported by the NIH F31 grant (F31AG074650). AUTHOR INFORMATION Author notes * These authors contributed

equally: Heechul Jun, Jason Y. Lee AUTHORS AND AFFILIATIONS * Department of Anatomy and Neurobiology, School of Medicine, University of California Irvine, Irvine, CA, USA Heechul Jun, Jason

Y. Lee, Nicholas R. Bleza, Ayana Ichii, Jordan D. Donohue & Kei M. Igarashi * Department of Biomedical Engineering, Samueli School of Engineering, University of California Irvine,

Irvine, CA, USA Kei M. Igarashi * Center for Neural Circuit Mapping, School of Medicine, University of California Irvine, Irvine, CA, USA Kei M. Igarashi * Center for the Neurobiology of

Learning and Memory, University of California Irvine, Irvine, CA, USA Kei M. Igarashi * Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine,

CA, USA Kei M. Igarashi Authors * Heechul Jun View author publications You can also search for this author inPubMed Google Scholar * Jason Y. Lee View author publications You can also search

for this author inPubMed Google Scholar * Nicholas R. Bleza View author publications You can also search for this author inPubMed Google Scholar * Ayana Ichii View author publications You

can also search for this author inPubMed Google Scholar * Jordan D. Donohue View author publications You can also search for this author inPubMed Google Scholar * Kei M. Igarashi View author

publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS H.J., J.Y.L. and K.M.I. conceived the project and designed the experiments. H.J., J.Y.L., N.R.B., A.I.

and J.D.D. performed the experiments. H.J., J.Y.L. and K.M.I. performed the analyses. H.J., J.Y.L. and K.M.I. wrote the paper with input from all authors. CORRESPONDING AUTHOR

Correspondence to Kei M. Igarashi. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature_ thanks Thomas McHugh and

the other, anonymous, reviewer(s) for their contribution to the peer review of this work. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to

jurisdictional claims in published maps and institutional affiliations. EXTENDED DATA FIGURES AND TABLES EXTENDED DATA FIG. 1 HISTOLOGICAL VALIDATION OF IMPLANTED SITES. (A) Recording

positions in LEC of _Rbp4_-_Cre_ mice for opt-tagging experiment (Figs. 1 and 4). Positions were marked with electrolytic lesioning. D, dorsal, V, ventral, M, medial, L, lateral. (B) Optic

fiber positions in LEC of _Rbp4_-_Cre_ mice injected with AAV-flex-Jaws-GFP into LEC for inhibition experiments (Fig. 3). Arrowhead, estimated tip of optic fibers. (C) Optic fiber positions

in LEC of _Rbp4_-_Cre_ mice injected with retroAAV-flex-Jaws-GFP into mPFC for inhibition of mPFC-projecting LEC cells (Extended Data Fig. 14). (D) Optic fiber positions in LEC of WT mice

injected with AAV-hSyn-Jaws-GFP into mPFC for inhibition of mPFC terminals in the LEC (Fig. 4 and Extended Data Fig. 17). (E) Recording positions in mPFC of WT mice (Fig. 2). Positions were

marked with electrolytic lesioning. (F) Optic fiber positions in mPFC of WT mice injected with AAV-hSyn-Jaws-GFP into mPFC for inhibition experiments (Fig. 4). *Mice used for recording

LECL5/6 cells + mPFC terminal inhibition; **Mice used for recording mPFC cells + LECL5/6 inhibition. EXTENDED DATA FIG. 2 VERIFICATION OF OPTTAGGING PROCEDURE. (A) Spike raster plots of a

typical opttagged neuron which is seen to follow 1, 2, 5, and 10 Hz pulse trains (5 ms pulse, 10 pulses per train). (B) “Opto-PSTH” of 6 example opttagged neurons. Neurons i-v) feature

optically evoked spikes with low latency and jitter (Bottom right) An excluded opttagged cell (vi), with a long latency of 9.1 ms, suggesting a synaptically tagged cell. (C) Latencies of all

opttagged neurons plotted against the jitter of first spike after stimulation. Opttagged neurons had a wide variety of latencies (2-8.5 ms), making it difficult to delineate real opttagged

cells and potential synaptically tagged cells. (D) PCA trajectories, Euclidian distances, and SI plot of LECL5/6 population as in Fig. 1i, excluding opttagged cells with latency greater than

8.5 ms (n = 213 cells). (E) PCA trajectories, Euclidian distances, and SI plot of LECL5/6 population as in Fig. 1i, excluding opttagged cells with latency greater than 5 ms (n = 153 cells).

These results show a similar Odor-A and -a representation, and similar Odor-B and -b representation at T5. Thus, although the total population analysis may include some synaptically

opttagged neurons, it is likely that our conclusion is not affected by their marginal numbers. EXTENDED DATA FIG. 3 CUE-OUTCOME PROFILE OF LECL5/6 NEURONS ALONG THE DORSOVENTRAL AXIS.

Recorded positions along dorsoventral axis of LEC. Distances were calculated from rhinal sulcus border to approximate location of amygdalopiriform transition area and normalized from 0

(dorsal) to 1 (ventral). The result demonstrated that while Aa cells were observed along the D-V axis, Bb cells were found only in the ventral part of the LEC. EXTENDED DATA FIG. 4 SPIKE

PROPERTIES OF LECL5/6 CELLS DURING CORRECT ASSOCIATIVE LEARNING. (A-D) Spike properties of LECL5/6 cells. LECL5/6 cells were recorded in a session with Odor-A and Odor-B (AB-only session).

After ~20 trials in AB session, associative learning (ABab) session was tested (T1-T5). (A) Spike firing of 228 LECL5/6 cells. Mean spike activity was averaged in 50 ms bins and shown in

z-score compared with −1 – 0 s before odor onset. In this panel, cells were sorted using a cluster analysis of firing property in T5. (B) Mean firing rate of 228 LECL5/6 cells shown in

z-score. (C) Percent responsive cells for each cue combination. Neurons with significant firing during 0.5-3.0 s after odor onset (odor + delay period) were counted (Wilcoxon signed-rank

test, p < 0.05). (D) Percent responsive cells in periods of 0.5-1.0 s (odor), 2-3 s (delay) and 3-4 s (choice) after odor onset. Neurons with significant firing (p < 0.05) during each

period were counted (two-sided signed-rank test). (E) Trajectories of neural firing of LECL5/6 cell population as in Fig. 1i, but presented throughout timepoints T1 – T5. (F) Euclidian

distance between odor trial types. (G) Mean Euclidian distance during 0.5-3.0 s after odor onset (odor + delay period). Ninety-fifth percentile distance obtained from shuffled data denotes

significant distance (red line). (H) The change of Similarity Index (SI) during associative learning was compared using the bootstrapping method (see Methods). PCA was performed from a

resampled neuronal population, and this procedure was repeated 1000 times to make 1000 bootstraps. SI was calculated for each bootstrap, then SIs in T2–T5 were subtracted by that in T1, to

test if there was a significant distribution above or below zero. SI for Odors A-a increased at T3-5 (p = 0.005, 0.012, 0.0005 respectively, bootstrapping test), as well as SI for Odors B-b

at T3-5 (p = 0.0023, 0.0021, 0.003 respectively), confirming increasing similarity of representations between Odor-A and -a, and between B-b during leaning. *p < 0.05, **p < 0.01, ***p

 < 0.001, two-sided bootstrapping test. Data are presented as mean values +/- SEM. EXTENDED DATA FIG. 5 SELECTIVITY PROFILE OF MPFC AND LECL5/6 SINGLE NEURONS DURING LEARNING. (A)

Examples of neurons based on their selectivity profile between T1 vs T5 period. Type 1: Static cells with same selectivity to an odor cue; Type 2: Static cells without selectivity to any

cue; Type 3: Plastic cells with selectivity in T1 to an odor cue but no selectivity in T5; Type 4: Plastic cells with no selectivity in T1 but gained selectivity to an odor cue in T5; Type

5: Plastic cells with selectivity to an odor cue in T1 but gained distinct selectivity in T5. Significant selectivity (p < 0.05) was assessed using spike response during 0.5 – 3 s after

cue onset, compared to 1 s pre-cue period (two-sided rank sum test). Data are presented as mean values +/- SEM. (B) (Top) Percentage of static (54%) or plastic (46%) mPFC cells. Static cells

were further subdivided into type1 (4%) and type 2 (50%). Plastic cells were further subdivided into type 3 (18%), type 4 (14%), and type 5 (14%). (Bottom) Percentage of static (50%) or

plastic (50%) LEC5/6 cells. Static cells were further subdivided into type1 (4%) and type 2 (46%). Plastic cells were further subdivided into type 3 (19%), type 4 (13%), and type 5 (18%).

EXTENDED DATA FIG. 6 ADDITIONAL PRINCIPAL COMPONENT ANALYSES FOR LECL5/6 CELL RECORDINGS. (a) Error-exclusion analysis. Trajectories of neural firing of LECL5/6 cell population using only

correct (hit) trials for Odors-A and -a and correct rejection (CR) trials for Odors-B and -b. The pattern of A-a vs. B-b dichotomic classification was again observed when the incorrect

trials were removed from the PC analysis, excluding the possibility that the representations in Fig. 1i emerged from the increasing rate of correct trials. (b) Movement analysis.

Trajectories of neural firing of LECL5/6 cell population using only lick (hit) trials for Odors-A and -a, and error lick (false alarm, FA) trials for Odors-B and -b. Although all of them are

trials in which mice made lick responses, the A-a vs. B-b dichotomic classification similar to Fig. 1i was observed, suggesting that LECL5/6 cells do not simply represent lick-related motor

information. EXTENDED DATA FIG. 7 EFFECT OF INDIVIDUAL AA AND BB CELLS ON POPULATION ACTIVITY. PCA trajectories, Euclidian distances, and SI plot of LECL5/6 population, excluding individual

Aa and Bb cells (n = 137 cells). The result showed unstable grouping between Odor-A and Odor-a (shown by unstable SIA-b in the SI plot), and no development of grouping between Odor-B and

Odor-b (shown by low SIB-b throughout the session). This result suggests that Aa cells and Bb cells contribute to the generation of outcome rule representation. EXTENDED DATA FIG. 8

CHARACTERISTICS OF _RBP4_+ LECL5/6 CELLS. (A) Electrophysiological features for classifying putative principal neurons. Peak to valley time of spike waveform was used to distinguish putative

interneurons from principal neurons in _Rbp4_+ LECL5/6 cells. (Left) Dashed line (230µs) represents cut off for wide spike (WS) excitatory neurons (n = 176; 77%) to narrow spike (NS)

interneurons (n = 52; 23%) classification (Bartho et al., 2004). (Right) Independent trajectories of neural firing of LECL5/6 WS neurons and NS neurons both demonstrated the grouping of

Odors-A and -a and grouping of Odors-B and -b. (B) LECL5/6 labeling with excitatory cell marker. (Left) AAV-flex-tdTomato (red) and AAV-flex-CaMKIIa-GFP (green) were injected into LEC5/6 of

_Rbp4_-_Cre_ mice. (Middle) Coronal sections of LEC layer 5/6. CaMKIIa (green) GFP signal reveals excitatory neurons. TdTomato (red) signal reveals _Rbp4_+ LECL5/6 cells. Bottom panel

demonstrates magnified windows from top panel. Yellow arrow points to example LECL5/6 excitatory cell expressing both CaMKIIa GFP and tdTomato. White arrow points to example LECL5/6

non-excitatory cell expressing only tdTomato. (Right) Percentage of double-positive neurons among tdTomato+ neurons (80.08 ± 2.75 % from 8 sections obtained from n = 2 mice). Data are

presented as mean values +/- SEM. EXTENDED DATA FIG. 9 SPIKE PROPERTIES OF LECL5/6 CELLS DURING SPONTANEOUS ERROR SESSIONS. (A) Behavioral performance of LEC _Rbp4_-_Cre_ recording mice in

correct sessions (Fig. 1) and error sessions where mice spontaneously could not reach >80% performance criteria. Data are presented as mean values +/- SEM. (A1) Top, learning curves

during correct and error sessions. Familiar cue performance (A/B) in blue, novel cue performance (a/b) in red. Bottom, percent correct trials in T5 for correct vs. error sessions (p = 

8.8e-8, two-way ANOVA; A/B correct vs. a/b error, *p = 3.8e-9 or less, post-hoc Tukey test; n = 8 mice). (A2) (Left) Percentage of correct trials plotted in each odor trial type. (Right)

Performance of mice in the last 10 trials (p = 4.8e-28, two-way ANOVA; ***p = 6e-8 between Odor-a correct vs. odor-a error, post-hoc Tukey test; n = 8 mice). (B-E) Same as in Extended Data

Fig. 4a–d, but for error sessions (n = 72 cells). (F) Proportion of Aa cells (left) and Bb cells (right) in correct vs. error sessions. Both response types were missing in error sessions.

(G) Same as in in Extended Data Fig. 4e–g, but for error sessions. SI plot shows that SIA-a did not increase to positive, indicating Odor-a was not classified together with Odor-A. (H)

Bootstrapping analysis. (Top) Same plot as in Extended Data Fig. 4h, but for error sessions. LECL5/6 cells did not develop similar representations between Odors-A and -a, and between Odors-B

and -b observed in correct sessions. (Bottom) Direct comparison between correct and error sessions confirmed the disappearance of similar representations between Odors-A and -a at T3-T5 of

error sessions (p = 0.27, 0.14, 0.13 respectively). The comparison also indicates more similar representations between Odors-a and -b throughout error sessions T1-T5 (p = 0.043, 0.013,

0.0056, 0.026, 0.0054 respectively). *p < 0.05, **p < 0.01, ***p < 0.001, two-sided bootstrapping test. Data are presented as mean values +/- SEM. EXTENDED DATA FIG. 10 SPIKE

PROPERTIES OF MPFC CELLS DURING CORRECT ASSOCIATIVE LEARNING SESSIONS. (A) Spike firing of 779 mPFC cells. Mean spike activity was averaged in 50 ms bins and shown in z-score compared with

−1 – 0 s before odor onset. In this panel, cells were sorted using a cluster analysis of firing property in T5. (B) Mean firing rate of 779 mPFC cells shown in z-score. (C) Percent

responsive cells in correct T5 (top) and error T5 (bottom). Neurons with significant firing (p < 0.05) during 0.5-3.0 s after odor onset (odor + delay period) were counted (two-sided

signed-rank test). (D) Percent responsive cells in periods of 0.5-1.0 s (odor), 2-3 s (delay) and 3-4 s (choice) after odor onset. Neurons with significant firing (p < 0.05) during each

period were counted (two-sided signed-rank test). (E) Trajectories of neural firing of mPFC cell population as shown in Fig. 2h, but for timepoints T1 – T5. (F) Euclidian distance between

odor trial types. (G) Mean Euclidian distance during 0.5-3.0 s after odor onset (odor + delay period) for timepoints T1 – T5 of correct sessions. Ninety-fifth percentile distance obtained

from shuffled data denotes significant distance (red line). (H) Bootstrapping analysis for Fig. 2j. SI for Odors A-a and B-b showed significant increases in T5 compared to T1 (p = 0.0039 and

p = 1.7e-8, respectively, bootstrapping test), while SI for Odors A-B and a-b showed significant decreases (p = 3.1e-5 and p = 0.029, respectively), confirming increasing similarity between

odors of the same outcome, and decreasing similarity between odors of the different outcome. *p < 0.05, **p < 0.01, ***p < 0.001, two-sided test, n = 1000 bootstraps each. Data are

presented as mean values +/- SEM. EXTENDED DATA FIG. 11 EARLY EMERGENCE OF GROUPING OF ODOR-A AND ODOR-A REWARDED CUES. (A) Trajectories of neural firing of LECL5/6 cell population as in

Fig. 1i, but presented throughout timepoints T1a (first five trials of T1) and T1b (second five trials of T1). (B) Trajectories of neural firing of mPFC cell population as above. EXTENDED

DATA FIG. 12 ADDITIONAL PRINCIPAL COMPONENT ANALYSES FOR MPFC CELL RECORDINGS. (A) Error-exclusion analysis. Trajectories of neural firing of mPFC cell population using only correct (hit)

trials for Odors-A and -a, and correct rejection (CR) trials for Odors-B and -b. The pattern of A-a vs. B-b dichotomic classification was again observed when the incorrect trials were

removed from the PC analysis, excluding the possibility that the representations in Fig. 2h emerged from the increasing rate of correct trials. (B) Movement analysis. Trajectories of neural

firing of mPFC cell population using only lick (hit) trials for Odors-A and -a and error lick (false alarm, FA) trials for Odors-B and -b. Although all of them are trials in which mice made

lick responses, the A-a vs. B-b dichotomic classification similar to Fig. 2h was observed, suggesting that mPFC cells do not simply represent lick-related motor information. EXTENDED DATA

FIG. 13 SPIKE PROPERTIES OF MPFC CELLS DURING SPONTANEOUS ERROR SESSIONS. (A) Behavioral performance of mPFC recording mice in correct sessions (Fig. 2) and error sessions where mice

spontaneously could not reach >80% performance criteria. Data are presented as mean values +/- SEM. (A1) Behavioral performance of mPFC recording mice in correct vs. error sessions. Top,

learning curves during correct and error sessions. Familiar cue performance (A/B) in blue, novel cue performance (a/b) in red. Bottom, percentage of correct trials in T5 for correct vs.

error sessions (p = 2.4e-7, ANOVA; p = 1.9e-8 or less, post-hoc Tukey test; n = 6 mice). (A2) mPFC recording mice data plotted for percent correct trials in each odor trial type as a

function of trial number for each odor type. (Right) Performance of mice in the last 10 trials (p = 1.99e-11, ANOVA; ***p = 6e-8 between Odor-a correct vs. odor-a error, post-hoc Tukey test;

n = 6 mice). (B-E) Same as in Extended Data Fig. 10a–d, but for error sessions (n = 116 cells). (F) Proportion of mPFC Aa cells (left) and Bb cells (right) in correct vs. error sessions.

Aa: p = 1.8e-7, Bb: p = 2.2e-13, two-sided binomial test. (G) Same as in Extended Data Fig. 10e–g, but for error sessions. (H) Bootstrapping analysis. (Top) Same plot as in Extended Data

Fig. 10h, but for error sessions. During the error sessions, mPFC cells did not develop similar representations between Odors-A and -a (T2-T5: p = 0.24, 0.39, 0.36, 0.36, respectively) and

between Odors-B and -b (T2-T5: p = 0.36, 0.034, 0.089, 0.43, respectively) observed in correct sessions. (Bottom) Direct comparison between correct and error sessions confirmed the

disappearance of similar representations between Odors-A and -a (T3-T5: p = 0.006, 0.0005, 6.3e-8, respectively), and similar representations between Odors-B and -b (T5, p = 0.0002). The

comparison also indicates more similar representations between Odors-A and -B (T1-T5: p = 3e-6, 1.8e-6, 6.2e-8. 4e-7, 1.2e-7, respectively), and between Odors-a and -b throughout the error

sessions (T1-T5: p = 7e-6, 1e-16, 3e-15, 1e-16, 1e-16, respectively). *p < 0.05, **p < 0.01, ***p < 0.001, bootstrapping test, n = 1000 bootstraps each. Data are presented as mean

values +/- SEM. EXTENDED DATA FIG. 14 BEHAVIORAL PERFORMANCE IN LECL5/6 INHIBITION EXPERIMENTS. (A) Behavioral performance of LEC _Rbp4_-_Cre_ mice in Fig. 3a,b, but plotted for each odor

trial type. Learning curves during control (left) and LECL5/6 inhibition (middle) sessions. (Right) Performance of mice in the last 10 trials (p = 3.8e-13, two-way ANOVA; p = 6e-8 between

Odor-a in control vs. Odor-a inhibition sessions, post-hoc Tukey test; n = 10 mice). Data are presented as mean values +/- SEM. (B-D) mPFC-projecting LECL5/6 cell inhibition experiments.

Data are presented as mean values +/- SEM. (C) (Left) Learning curves during control and inhibition sessions. (Middle) Percent correct trials in T5 for control vs. inhibition sessions (p = 

3.4e-6, two-way ANOVA; A/B control vs. a/b inhibition, p = 3.8e-9; a/b correct vs. a/b error, p = 7.2e-9; A/B error vs. a/b error, p = 3.9e-9, post-hoc Tukey test; n = 10 mice). (Right)

Proportion of correct sessions between control and inhibition conditions (p = 0.0064, two-sided binomial test; n = 30 control and 30 inhibition sessions). (D) Percent correct trials in each

odor trial type as a function of trial number for each odor type. (Right) Performance of mice in the last 10 trials (p = 1.5e-16, two-way ANOVA; p = 6e-8 for Odor-a in correct sessions vs.

odor-a in error sessions, post-hoc Tukey test; n = 10 mice). EXTENDED DATA FIG. 15 MODULATION OF NEURONAL ACTIVITY WITH JAWS INHIBITION. (A) (Top) Recording of mPFC cells during inhibition.

Jaws were expressed in mPFC cells using synapsin promoter driven AAVs. (Middle) Correlation between change in firing rate and pre-stimulation firing rate divided into principal neurons and

interneurons based on their spike waveform peak-to-trough width threshold of 230 μs. Each dot represents a single cell. Cells were classified as inhibited, unaffected, or disinhibited using

two-sided rank sum test (p < 0.05 threshold) between pre-stimulation firing rate and firing rate during inhibition. (Bottom) Percentage of inhibited (21.9%), unaffected (60.3%), or

disinhibited (17.8%) mPFC cells during inhibition. (B) (Top) Opt-tag recording of LECL5/6 cells during inhibition. ChR2 and Jaws were expressed in LECL5/6 of _Rbp4_-_Cre_ mice. (Middle)

Correlation between change in firing rate and pre-stimulation firing rate. Each dot represents a single cell. Cells were classified as inhibited, unaffected, or disinhibited using two-sided

rank sum test (p < 0.05 threshold) between pre-stimulation firing rate and firing rate during inhibition. (Bottom) Percentage of inhibited (12.5%), unaffected (75%), or disinhibited

(12.5%) LEC5/6 cells during inhibition. EXTENDED DATA FIG. 16 DETAILED ANALYSES FROM RECORDING OF MPFC CELLS WITH LECL5/6 INHIBITION. (A-B) Behavioral performance only from n = 4 mice used

in mPFC cell recording with simultaneous inhibition of LECL5/6 cells. (B1) (Top) Learning curves during control and inhibition sessions. (Bottom left) Percentage of correct trials in T5 for

control vs. inhibition sessions (p = 7.5e-9, two-way ANOVA; p = 5.6e-9 or less, post-hoc Tukey test; n = 4 mice). (Bottom right) Proportion of correct sessions between control and inhibition

conditions (p = 1.6e-10, two-sided binomial test; n = 24 control and 24 inhibition sessions). Data are presented as mean values +/- SEM. (B2) Percent correct trials in each odor trial type

as a function of trial number for each odor type. (Right) Performance of mice in the last 10 trials (p = 2.8e-18, two-way ANOVA; p = 6e-6 between Odor-a in correct sessions vs. Odor-a in

error sessions, post-hoc Tukey test; n = 4 mice). Data are presented as mean values +/- SEM. (C) (Top) Trajectories of neural firing of n = 497 mPFC cell population in no-laser control

sessions. (Middle) Euclidian distance between odor trial types. (Bottom) Mean Euclidian distance during 0.5-3.0 s after odor onset (odor + delay period) for timepoints T1 – T5 of correct

sessions. Ninety-fifth percentile distance obtained from shuffled data denotes significant distance (red line). (Right) Similarity index. (D) Same as (c), but for inhibition sessions (laser

on). (E) Bootstrapping analysis. (Top) In control sessions, SI between Odors A-a and between Odors B-b showed significant increase from T1 to T5 (p = 0.014, p = 2.6e-6, respectively). SI for

Odors A-B and a-b showed significant decrease from T1 to T5 (p = 5.4e-6, p = 0.0027, respectively, bootstrapping test). (Middle) In inhibition sessions, SI for all odor pairs did not show

significant differences from T1 to T5 (Aa: p = 0.15, Bb: p = 0.08, AB: p = 0.45, ab: p = 0.34), confirming the impairment of outcome classification. (Bottom) Direct comparison between

control and inhibition sessions confirmed the disappearance of similar representations between Odors-A and -a (T5: p = 7e-6). The comparison also indicates disappearance of separate

representations between Odors-A and -B and between Odors-a and -b in inhibition sessions (p = 2e-4, 8e-13, respectively). n = 1000 bootstraps; *p < 0.05, **p < 0.01, ***p < 0.001,

bootstrapping test. Data are presented as mean values +/- SEM. EXTENDED DATA FIG. 17 BEHAVIORAL PERFORMANCE FOR MPFC INHIBITIONS. (A) Behavioral performance during mPFC inhibition in Fig.

4a,b, but plotted for each odor trial type. Learning curves during control (left) and mPFC inhibition (middle) sessions. (Right) Performance of mice in the last 10 trials (p = 1e-32, two-way

ANOVA; p = 6e-8 between Odor-A in control sessions vs. Odor-A in inhibition sessions; p = 6e-8 between Odor-a in control sessions vs. Odor-a in inhibition sessions, post-hoc Tukey test; n =

 13 mice). Data are presented as mean values +/- SEM. (B-D) Behavior performance during mPFC terminal inhibition. Data are presented as mean values +/- SEM. (C) (Left) Learning curves during

control and inhibition sessions. (Middle) Percent correct trials in T5 for control vs. inhibition sessions (p = 0.029, two-way ANOVA; p = 0.0088 or less, post-hoc Tukey test; n = 7 mice).

(Right) Proportion of correct sessions between control and inhibition conditions (p = 0.0001, two-way binomial test; n = 31 control and 21 inhibition sessions). (D) Percent correct trials in

each odor trial type as a function of trial number for each odor type. (Right) Performance of mice in the last 10 trials (p = 0.0037, two-way ANOVA; p = 0.0003 between Odor-a in correct

sessions vs. Odor-a in error sessions, post-hoc Tukey test; n = 7 mice). Although not significant, we observed a trend of decrease in the performance for Odor-A during inhibition (p = 0.63,

Odor-A in correct sessions vs. Odor-A in error sessions, post-hoc Tukey test). EXTENDED DATA FIG. 18 DETAILED ANALYSES FROM RECORDING OF LECL5/6 CELLS WITH MPFC TERMINAL INHIBITION. (A)

Opt-tag recording of LECL5/6 cells with simultaneous inhibition of mPFC inputs in LEC. (B) (Top) Trajectories of neural firing of n = 181 LECL5/6 cell population in no-laser control

sessions. (Middle) Euclidian distance between odor trial types. (Bottom) Mean Euclidian distance during 0.5-3.0 s after odor onset (odor + delay period) for timepoints T1 – T5 of correct

sessions. Ninety-fifth percentile distance obtained from shuffled data denotes significant distance (red line). (Right) Similarity index. (C) Same as (b), but for n = 249 LECL5/6 cell

population during mPFC terminal inhibition sessions (laser on). (D) Bootstrapping analysis. (Top) In control sessions, SI between Odors A-a and between Odors B-b showed significant increase

from T1 to T5 (p = 0.012, p = 0.0095, respectively). (Middle) In inhibition sessions, SI for all odor pairs did not show significant differences from T1 to T5 (Aa: p = 0.41, Bb: p = 0.07,

AB: p = 0.15, ab: p = 0.23), confirming the impairment of outcome classification. (Bottom) Direct comparison between control and inhibition sessions confirmed the disappearance of similar

representations between Odors-A and -a (p = 0.0014 at T5). *p < 0.05, **p < 0.01, ***p < 0.001, two-sided bootstrapping test, n = 1000 bootstraps each. Data are presented as mean

values +/- SEM. EXTENDED DATA FIG. 19 FAST DEVELOPMENT OF ODOR OUTCOME REPRESENTATION IN MPFC POPULATION. (A) Development of task performance, Similarity Index (SI) between Odors-A and a

(SIA-a) for LECL5/6 cell population, and SI between Odors B and b (SI B-b) for LECL5/6 cell population. Variables are normalized onto a scale from 0 (T1a) to 1 (T5). (B) Development of task

performance, SIA-a for mPFC population and SIB-b for mPFC population as above. EXTENDED DATA FIG. 20 DECODING ANALYSES OF LECL5/6 AND MPFC POPULATION ACTIVITY. (A-B) A support vector machine

(SVM) decoder was trained to discriminate novel Odor-a vs. Odor-b, using neural responses to familiar Odor-A vs. Odor-B in the same timepoint (T) as training data. For each 100 ms time bin,

100 SVMs were trained and their performances averaged to achieve the final % correct value. Decoding performance increases quickly in mPFC between T1-T2 (~90% at Trials 6-10 (T1b)), while

performance only gradually reached ~90% at T3 in LECL5/6, indicating a quicker development of outcome representation in mPFC. T1A = trials 1-5; T1B = trials 6-10. A) Decoder performance for

Correct sessions. (Top row) LECL5/6 population. (Bottom row) mPFC population. Right: Average performance from the 0.5-3 s window of each timepoint. B) As above, but for Error sessions. (C-D)

The decoder was trained to discriminate within outcome categories (Odor-A vs. Odor-a OR Odor-B vs. Odor-b), using half the trials of one timepoint to train and the other half to test.

Although the discriminatory power between Odor-A and Odor-a gradually decreased from T1 to T5, it remained at ~75% at T5. This result suggests that LEC neural activities still have

information distinct enough for the decoder to discriminate between Odor-A and -a at T5. This was also the case for Odor-B vs Odor-b (78% at T5), as well as mPFC (82% at T5 for A vs a, 98%

at T5 for B vs b). (C) Decoder performance for LECL5/6 population during Correct sessions. (D) Decoder performance for mPFC population during Correct sessions. EXTENDED DATA FIG. 21

CHARACTERIZING MONOSYNAPTIC INPUT TO _RBP4_+ LECL5/6 CELLS USING RETROGRADE RABIES TRACING. Monosynaptic retrograde tracing of _Rbp4_+ LECL5/6 neurons. (Left) Cre-depndent glycoprotein and

TVA-GFP virus (green) and G-deleted rabies virus expressing mCherry (red) were injected into the LECL5/6 of _Rbp4_-_Cre_ mice. (Right) Top panel shows coronal sections revealing starter

_Rbp4_+ cells (indicated by white arrows) that are double positive (red and green) near the injection site. The remaining panels demonstrate coronal sections with examples of presynaptically

labelled neurons (red only) from local LEC, posterior piriform cortex, amygdala and hippocampal CA1 of the intermediate-ventral tiers (indicated by white arrows). (BLA = Basolateral

amygdala, BMP = Basomedial posterior amygdala, BLV = Basolateral ventral amygdala, LaVL = Lateral amygdala ventrolateral, LaVM = Lateral amygdala ventromedial and LaDL = Lateral amygdala

dorsolateral). SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Results and Discussion which report and discuss additional results that are not logically connected to the

main text. REPORTING SUMMARY SUPPLEMENTARY TABLES Supplementary Tables 1–5 RIGHTS AND PERMISSIONS Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to

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terms of such publishing agreement and applicable law. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Jun, H., Lee, J.Y., Bleza, N.R. _et al._ Prefrontal and lateral

entorhinal neurons co-dependently learn item–outcome rules. _Nature_ 633, 864–871 (2024). https://doi.org/10.1038/s41586-024-07868-1 Download citation * Received: 02 November 2023 *

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