Reversible online control of habitual behavior by
optogenetic perturbation of medial prefrontal cortex
Kyle S. Smitha,1, Arti Virkuda, Karl Deisserothb, and Ann M. Graybiela,1
aMcGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;
andbDepartment of Bioengineering, Stanford University School of Medicine, Stanford, CA 94305
Contributed by Ann M. Graybiel, September 18, 2012 (sent for review August 20, 2012)
Habits tend to form slowly but, once formed, can have great
stability. We probed these temporal characteristics of habitual
behaviors by intervening optogenetically in forebrain habit cir-
cuits as rats performed well-ingrained habitual runs in a T-maze.
We trained rats to perform a maze habit, confirmed the habitual
behavior by devaluation tests, and then, during the maze runs
(ca. 3 s), we disrupted population activity in a small region in the
medial prefrontal cortex, the infralimbic cortex. In accordance with
evidence that this region is necessary for the expression of habits,
we found that this cortical disruption blocked habitual behavior.
Notably, however, this blockade of habitual performance occurred
on line, within an average of three trials (ca. 9 s of inhibition), and
as soon as during the first trial (<3 s). During subsequent weeks of
training, the rats acquired a new behavioral pattern. When we
again imposed the same cortical perturbation, the rats regained
the suppressed maze-running that typified the original habit, and,
simultaneously, the more recently acquired habit was blocked.
These online changes occurred within an average of two trials
(ca. 6 s of infralimbic inhibition). Measured changes in generalized
performance ability and motivation to consume reward were un-
affected. This immediate toggling between breaking old habits
and returning to them demonstrates that even semiautomatic
behaviors are under cortical control and that this control occurs
online, second by second. These temporal characteristics define a
framework for uncovering cellular transitions between fixed and flex-
ible behaviors, and corresponding disturbances in pathologies.
that a durable representation of the movement repertoire be
acquired. Much evidence suggests that this process involves
a gradual transition from flexible and goal-directed behavior to
a more fixed, habitual behavioral strategy (1–7). How these
properties of habits map onto neural circuitry has been the focus
of classic lesion and chemical inactivation studies, which have
identified regions of the striatum as essential for the expression
of habits (2–4). In addition, such studies have established that
a region in the medial prefrontal cortex also must be intact for
habits to be expressed (7–9). This medial prefrontal region [called
infralimbic (IL) cortex in rodents] is linked to emotion-related
limbic circuitry and projects to sites that promote behavioral
flexibility at the expense of habits (e.g., prelimbic cortex and
medial striatum) (3, 4, 7, 10). Based on this anatomy, the IL
cortex is thought to be at an executive level in the control of
habits and behavioral strategies (1, 8, 9, 11).
This sketch of the circuitry for habits and skilled habit-like
behaviors opens key questions about how habitual behaviors are
controlled on a moment-by-moment basis. The slow emergence
of habits favors a gradual biasing of these behaviors toward au-
tomaticity, but the stability of habits favors their being performed
without moment-to-moment biasing or executive cortical con-
trol. We tested these dynamics of habit control by the prefrontal
IL region by targeting precisely timed optogenetic inhibition to
the IL cortex with light to drive virally introduced halorhodopsin
(eNpHR3.0) (12). This tool allowed us to examine not only the
abits are among the most stable and powerful behaviors that
we have. Forming such strongly ingrained behaviors requires
online contribution of cortical activity to the control of habitual
behavior, but also, because of its unique repeatability, to track
the effects of such brief, seconds-long manipulations over weeks
of subsequent performance. To our surprise, we found that de-
spite the automaticity of habitual behavior, it is subject to online
control by the prefrontal cortex.
Overtrained T-Maze Running Is Habitual. We used a navigational T-
maze task (Fig. 1A) similar to one developed to examine neural
activity in the striatum during habit formation (13–15). We
tracked the learning curves of multiple sets of rat subjects (n =
10). In daily sessions of ca. 40 trials, the rats were required to
initiate maze runs in response to a warning cue, run down the
maze, and turn right or left, depending on an auditory instruction
cue, to receive one of two rewards (chocolate milk or sucrose
solution). For each rat, each reward type was assigned to one end
arm, and entry into an incorrect arm resulted in no reward. Rats
were trained to a criterion of statistically significant performance
accuracy (72.5% correct; criterion training stage 5; Fig. 1B) and
then were overtrained for 10 or more additional sessions. Peak
performance accuracy was high at ∼90% correct (Fig. 1B).
We applied a reward-devaluation protocol as a quantitative
test for habit formation after this extensive training (16). We
devalued one of the two maze rewards in home-cage sessions and
then tested in the maze experiments for habitual running to the
end arm baited with the now-devalued reward, relative to runs to
the normally valued reward in the other end arm. To induce
devaluation, we paired one reward with a nauseogenic dose of
lithium chloride in home-cage sessions (17, 18). In home-cage
tests, we confirmed that this method produced an aversion to the
devalued reward (Fig. 1C). After devaluation, the rats were
placed in the maze to run the task again, but the end arms were
not baited. This procedure allowed us to determine whether the
animals would still run when instructed to the side with the now-
devalued reward, suggesting that this running was habit-driven.
The behavior of the control rats (n = 4) established that
overtrained T-maze running was normally habitual. In the probe
test after reward devaluation, these rats continued running to the
devalued goal when so instructed, just as they had in the session
before devaluation (Fig. 1D). Their runs to the nondevalued goal
were unchanged and accurate as well (Fig. 1D). This insensitivity
to reward devaluation confirmed that the training procedures
produced ingrained, habitual maze runs.
To test for the effects of IL cortical activity on this habitual
behavior, we used the strategy of perturbing the IL cortex during
the unrewarded probe session. We applied the intervention ex-
clusively during the performance of the runs to ensure that it was
Author contributions: K.S.S. and A.M.G. designed research; K.S.S. and A.V. performed
research; K.D. contributed new reagents/analytic tools; K.S.S. and A.M.G. analyzed data;
and K.S.S., K.D., and A.M.G. wrote the paper.
The authors declare no conflict of interest.
1To whom correspondence may be addressed. E-mail: email@example.com or graybiel@mit.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
| November 13, 2012
| vol. 109
| no. 46www.pnas.org/cgi/doi/10.1073/pnas.1216264109
online. We did not include either the prerun periods, the periods
during reward delivery, or intertrial intervals. In the experi-
mental rats (n = 6), an AAV-5 viral vector encoding eNpHR3.0
fused to EYFP, and targeted preferentially to glutamatergic
pyramidal neurons through the calcium/calmodulin-dependent
protein kinase IIα promoter (AAV5-CaMKIIα-eNpHR3.0-
EYFP) (12), was injected bilaterally into the IL cortex 1–3 mo
before behavioral training (Fig. 2A). Anterograde viral labeling
was later observed in the medial striatum but not in the senso-
rimotor striatum, confirming a lack of a direct corticostriatal
projection from the IL cortex to the dorsolateral region of the
striatum known to also be essential for habit expression (Fig. 2B)
(3, 10). Two of the control rats were given laser exposure fol-
lowing injections of control virus lacking halorhodopsin (AAV5-
CaMKIIα-EYFP). The other two were injected with hal-
orhodopsin-containing virus, but the laser was inactive.
Optical Stimulation of Halorhodopsin-Expressing IL Neurons Inhibits
Spike Activity. IL manipulation was accomplished by delivery of
593.5-nm-wavelength laser light through optical fibers implanted
bilaterally so as to extend to the dorsal edge of the targeted IL
cortex (Fig. 2A). Partial inhibition of IL activity was verified in
two behaving rats fitted with a head stage carrying tetrodes and
optical fibers by applying equivalent illumination parameters to
those that would be used in the maze task (Fig. 2 C–G). Neu-
ronal spike activity was suppressed by 56% on average during
illumination in 11 units, and the suppression was consistent over
40+ trials. This protocol resulted in a more temperate, as well as
temporally specific, suppression of spike activity than the full
blockade of activity produced, presumably, by lesions or drug
infusions. In six units, we observed increased firing rates during
light delivery, and these units were often recorded on the same
tetrode as others showing inhibition (Fig. 2F). Thus, the opto-
genetic inhibition targeted to pyramidal cells influenced local
microcircuitry (19, 20), yielding a time-locked disruption of
population spike activity (inhibition:excitation ratio, 1.8:1).
IL Perturbation Blocks Habits Online. We began by disrupting the IL
cortex online while the rats performed the postdevaluation probe
test (Fig. 3). Light-on occurred immediately after gate-opening,
and light-off occurred immediately after goal-reaching (ca. 3 s of
light per trial; <2 min total per day). This within-run treatment
produced a dramatic effect: the rats acted as though they had not
acquired the habit of running to the devalued goal. As shown in
Fig. 3D, the rats with IL perturbation sharply reduced their runs
to the end arm that would have had the devalued reward—runs
characteristically made by the overtrained control rats (Fig. 3E).
Instead, during the intervention, the rats had a propensity to run
to the nondevalued end arm (Fig. 4 A and B). Such avoidance
behavior was seldom observed in the control group (Fig. 4B).
The devaluation sensitivity induced by IL perturbation was
evident almost immediately (Fig. 4C). It took on average of three
light trials for rats to begin avoiding the devalued goal when
instructed there. In one animal, the avoidance was present dur-
ing the first trial. This onset of habit blockade corresponded to
an average within-run illumination time of ca. 7–9 s, with the
most immediate effect within 3 s in the single rat. The online IL
intervention did not have a generalized effect on the perfor-
mance ability of the rats, however, because they ran accurately
and seemingly automatically with IL illumination when they were
instructed to run to the nondevalued reward side (Fig. 3D).
These experiments suggested that IL cortical activity was re-
quired online, during the actual maze runs, in order for the ex-
pression of running behavior as a habit.
Replacement Habit Forms with Postdevaluation Training. We next
analyzed the behavior of the rats when they again received re-
ward for correct performance in subsequent days of maze
training (Figs. 4 and 5). In accordance with classic findings (3, 17,
18, 21), all of the rats, including the control animals, avoided the
devalued end arm after being reexposed to the reward that had
been devalued (Figs. 4 A and B and 5 A and B), and they almost
never consumed it (Fig. 5C). Thus, the control rats required
actual contact with the devalued reward on the maze to trigger
a loss of habitual behavior that rats with a disrupted IL cortex
already exhibited in the unrewarded probe session.
Under IL perturbation, when the rats avoided the now-
devalued goal, they almost never stopped the task. Instead, they
continued to run to the nondevalued end arm (Figs. 4B and 5B).
These “wrong-way runs” increased in frequency over days, de-
spite the fact that the rats had not been instructed to go to that
end arm and did not ever receive reward for these runs. The rats
showed no overt anticipatory behavior such as licking or signs of
distress at the lack of reward. In control rats, the high frequency
of wrong-way runs lasted for as long as we tested (>3 wk).
Moreover, these runs also appeared immune to the modest loss
of in-maze aversion to the devalued outcome that appeared to
occur during this time, as indicated by a small recovery of in-
maze drinking of the devalued reward when the rats did run to it
(Fig. 5C). This pattern of behavior suggested that the rats de-
veloped a new habit in these postdevaluation days, namely of
always running to the nondevalued end arm.
IL Perturbation Blocks Replacement Habit and Returns Original
Behavior. The nearly immediate loss of habitual behavior dur-
ing online perturbation of IL activity suggested that switching off
IL cortex might be like flipping an off-switch for habitual be-
havior, consistent with prior work (8, 9).
To evaluate this possibility further, we extended the laser
experiments after the original probe test, gradually increasing the
time for up to a month. The IL cortex was first disrupted during
one to two rewarded sessions immediately after the initial probe
test intervention [postprobe stage (PP)1 (first laser-on days after
probe); Figs. 4 and 5]. This intervention produced no detectable
Instructed to devalued goal
Instructed to non-devalued goal
Home-cage intake of
devalued reward (ml)
for task training. (B) Performance across training stages for control rats. (C)
Home-cage reward drinking before (Pre) and after (Post) devaluation. (D)
Performance during the last session before devaluation (Left) and then
during probe test after (Right), for control rats (solid, cued to devalued goal;
dashed, cued to nondevalued goal). NS, not significantly different. *P < 0.05.
Data are presented as means ± SEM throughout.
T-maze training and habitual behavior of control rats. (A) Protocol
Smith et al.PNAS
| November 13, 2012
| vol. 109
| no. 46
effect on behavior; both groups of rats equally avoided the
devalued end arm on most trials. Nor did further IL perturbation
introduced at up to 6 d after the initial procedure change the
behavior of the rats (n = 2), which remained stable for up to 14 d
[stages PP2–PP5 (laser-off days); Figs. 4–6]. This result suggested
that once the habitual behavior had been blocked, and the IL-
disrupted rats were outcome-guided in behavior like the control
rats, further IL disruption failed to affect maze runs.
We obtained sharply different results when we extended the
time before imposing the further perturbation (Figs. 4–6). When
we again disrupted the IL cortex online 2–3 wk after the initial
disruption, on days 13 (n = 4), 15 (n = 1), or 21 (n = 1) (stage
PP6), the effect was immediate and surprising: the rats now
readily ran to the devalued side when so instructed (Figs. 4A and
5A). They displayed the original behavior that they had had
before any IL manipulation and did so within fewer than two
laser trials on average (and on the first trial for three of the rats)
(Fig. 4D). Moreover, they drank the devalued reward every time
they ran to it (Fig. 5C). Simultaneously, the rats nearly stopped
performing wrong-way runs (Fig. 4B). Thus, their behavior be-
came similar for runs to the devalued and nondevalued sides
(Fig. 5 A–D).
This change in behavior was abrupt. These rats, on the day
before the late IL perturbation, ran to the devalued reward when
so cued 6 times on average and drank it 2.17 times on average
(∼0.7 mL), at most twice consecutively (Figs. 4D and 6 A and B).
Despite having sampled the devalued reward on this prior day, as
well as on days before that (average = 1.88 drinks/day), these rats
did not return to their original habitual behavior of running to
the devalued reward when cued to do so (Figs. 4D and 6 A and
B). By contrast, on the following day with IL illumination, the
rats ran to the devalued reward and drank it earlier in the ses-
sion, quickly reached an equivalent number as on the prior day,
surpassed it by the fifth such trial on average, and then kept
going: they ran there and drank 14.5 times on average (∼4.4 mL),
often in long repeated sequences of consecutive runs and drinks
(Fig. 6B). Simultaneously, this late IL perturbation blocked the
new wrong-way running habit that had developed. Both effects
occurred within seconds, and within few trials, as had the original
habit blockade. Control rats rarely ran to the devalued reward on
the equivalent test trials (mean runs and drinks, 1.25 times) and,
instead, continued to mainly avoid the devalued reward (Figs. 4–
6, black lines).
This apparent return of the original habitual behavior after the
late IL disruption remained during subsequent laser-off days
(stages PP7–PP8, up to 4 test days; Figs. 4 and 5). When we then
administered another laser session (stage PP9), this treatment
fully returned the original habitual behavior, which remained for
as long as we tested (up to 20 d after the third silencing, stage
PP10) (Figs. 4 and 5). Over the same length of time, control rats
continued to avoid the devalued goal and to not consume it
(Figs. 4 and 5).
Day-by-day analysis of the running patterns suggested that
a tipping point for return of the original learned behavior oc-
curred between 6 and 13 d after the initial probe test, following
which the effect of IL perturbation changed from blocking the
initial habit to seemingly promoting it (Fig. 6C). This reversal of
the effect of IL perturbation corresponded to the time when the
new wrong-way runs had been repeated over a number of ses-
sions. The coordinate effects on the original and new behavior of
Time (s)Time (s)
-3 secLight+3 sec-3 secLight+3 sec
P = 0.05
Firing rate (Hz)
First 10 trials
Last 10 trials
1 mm1 mm
activity. (A) Photomicrograph of optical fiber track
(black, activated microglia stain) and virally infected
neuropil (brown, EYFP stain for eNpHR3.0-EYFP).
Images show areas of weak (Upper) and dense
(Lower) expression. (B) Photomicrograph of virally
infected IL axons and terminals in the medial, but
not lateral, striatum (black, EYFP stain). The high-
magnification image shows dense terminal field.
(C) Arrangement of tetrodes and optical fibers in IL
cortex. (D) Photomicrographs of virally infected
neurons in IL cortex and track of optical fiber im-
plant (Left) and tetrode (Right). cc, corpus callosum.
(E) Raster and histogram plots of spike activity for
an IL unit (50-ms bins), recorded ±3 s around light
delivery (yellow) during each of 40 trials. (F) Op-
posite modulation by light of the activity of two IL
units recorded simultaneously with the same tet-
rode. One is inhibited during light delivery (with
single spike rebound at light offset), whereas the
other shows excitation (with momentary inhibition
at light offset). (G) Average per-session spike ac-
tivity of inhibited units (n = 11, from 2 rats) 3 s
before light onset, during light delivery, and 3 s
after light offset. (H) Average spiking during first 10
illumination trials (blue) and last 10 trials (red).#P <
0.01;+P < 0.001.
Optogenetic modulation of IL neuronal
| www.pnas.org/cgi/doi/10.1073/pnas.1216264109Smith et al.
the rats suggested that IL perturbation might have turned
off both the initial habit and the new habit and that blockade
of the second habit might, thus, have uncovered the original
IL Perturbation Does Not Affect Generalized Motivation to Consume
the Devalued Reward or Taste-Aversion Memory. We tested the al-
ternative possibility that the IL manipulation was changing a gen-
eralized motivation to drink or the associated taste-aversion
memory irrespective of maze habits by examining home-cage
drinking of the devalued reward on test days following the late IL
perturbation (around stage PP9). The cages were in the maze
room to provide context similarity (Fig. 5E). On sequential test
days, light was delivered or not delivered while the reward was
freely available to the rats in their cages (n = 6). This IL manipu-
lation had no effect on drinking of the devalued reward (Fig. 5E,
“Late”), which was also similar to home-cage drinking assessed at
and again found no effect (Fig. 5E, “Early”). This lack of effect
sharply contrasted to the major effect of IL intervention on
drinking after correct performance in the maze experiment
proper, both at the first IL intervention and at the late inter-
ventions (Figs. 5C and 6B). Thus, if IL perturbation was affecting
appetitive motivation, it was doing so only in the maze.
The in-cage test showed that both the control and IL-manipu-
lated rats drank more at the late time than they did right after
devaluation, with control rats reaching 33% (ca. 10 mL) of pre-
with the consistently low levels of drinking in the maze during the
same time period: in the maze, the rats still rejected drinking over
half of the times that they ran to it (Figs. 5C and 6A). Thus, even
though the incentive value of the reward at home was partly re-
covering over time, it had remained weak in the maze normally.
These disconnects between in-cage and in-maze drinking accord
with the strong context-dependency of habits.
Our findings demonstrate that well-ingrained habits can be
controlled online by optogenetic manipulation of a specific site
in the prefrontal cortex, the IL cortex. Strikingly, this control was
effective even when exerted only during performance of the
behavior. Moreover, although optogenetic inhibition of the IL
cortex could block expression of an ingrained habit, further IL
inhibition could return this habitual behavior if enough time had
elapsed to allow the formation of a new habitual behavior. These
effects occurred within seconds of online performance time.
These findings carry implications for the temporal dynamics
and online scope of behavioral control exerted by the neocortex
over habitual behavior. First, despite the seemingly automatic
behavior typified by habits, their behavioral automaticity requires
ongoing permissive or supervisory activity in the medial pre-
frontal cortex. Second, this prefrontal control appears to favor
new habits if there is a competition between old and new habits;
IL perturbation can block an old habit abruptly but can also
abruptly bring back an old habitual behavior by blocking the
newer one. Third, online manipulation of the medial prefron-
tal cortex affects the expression of habitual behavior almost
immediately (within a performance cycle or two, totaling only
Instructed to devalued goal
Instructed to non-devalued goal
Home-cage intake of
devalued reward (ml)
Instructed to non-
nation protocol. (B) Equivalent performance across training for hal-
orhodopsin-treated (red) and control (dashed gray) rats before devaluation
and silencing. (C) Home-cage drinking pre- and postdevaluation for IL-hal-
orhodopsin (IL-halo) rats. (D) Performance during last session before de-
valuation (Left) and probe test after (Right), for rats with IL-halo (solid, cued
to devalued goal; dashed, cued to nondevalued goal). (E) Performance
during the probe session for control and IL-halo rat groups. Interaction of
goal value and rat group on probe: P = 0.001; main comparisons shown: *P <
0.05;#P < 0.01,+P < 0.001. NS, not significantly different.
Optogenetic perturbation of IL cortex blocks habits. (A) IL-illumi-
Percent trials instructed
to devalued goal
Wrong way run
Run and drink
Running to devlaued
goal and drinking
“Wrong Way” running
to non-devalued goal
Trial cued to devalued goal Trial cued to devalued goal
Control group Control group
IL-halo groupIL-halo group
replacement habit. (A) Percentage of trials in which rats instructed to run to
the devalued goal went there correctly and also drank the reward (IL-halo
group, red; control group, black; see Fig. 5 for runs and drinks separately).
Shown are five sessions leading up to reward devaluation, the unrewarded
probe session (only correct runs shown), and the postdevaluation stages [PP1
initial light-on session(s) or first postprobe session for controls; PP2–PP5 and
PP7–PP8: sessions without light; PP6: light-on session or equivalent for con-
trol; PP9: light-on session(s); PP10: final session(s) without light]. *P < 0.05;
#P < 0.01,+P < 0.001 between groups within stage; differences lacking sym-
bols indicate not significantly different. (B) Percentage of wrong-way runs to
nondevalued goal. (C) Trial-by-trial plot for the IL-halo group and control
group, in which rats ran the wrong way during probe session (i.e., habit
blockade). For each trial, wrong-way run was scored “1,” and correct run was
scored “0,” and then scores were averaged (e.g., “0.5”: half of rats ran the
wrong way and half ran correctly; “1”: all rats ran the wrong way). (D) Trial
plot for IL-halo and control groups, in which rats ran to the devalued reward
when instructed and drank it, during stage PP6 (i.e., habit reinstatement).
IL perturbation reinstates original habit and simultaneously breaks
Smith et al.PNAS
| November 13, 2012
| vol. 109
| no. 46
seconds of disrupted neuronal activity) when exerted only during
performance, not during pretask anticipation and planning or
during postperformance reinforcement or consolidation times.
These results support the findings of classic work on the habit
system suggesting that in rodents, the IL cortex is necessary for
habit expression (7–9) and point to the startling extent and po-
tency of control exerted by this small cortical region. Our
experiments also generated the unanticipated finding that IL
perturbation can have the opposite effect when applied later to
the same animals, when they had acquired a new habit: it can
result in the expression of the apparently same habitual behavior
that earlier IL perturbation originally blocked. Runs to the
nondevalued goal, and home-cage drinking, were unaffected by
the intervention, ruling out generalized effects on performance
ability, motivation to drink, or devaluation memory.
One interpretation of these findings is that after devaluation,
the original habit lost access to behavior, but its representa-
tion was maintained in the brain, and the late IL perturbation
unmasked it. This conclusion is in good accordance with evi-
dence, dating from the time of Pavlov (22), that when a habit is
broken, it is not forgotten; rather, a new one replaces it. By this
view, the IL cortex might serve, in part, as an online executive
controller that favors newly acquired habits over old strategies
(8, 11). Certainly, the IL cortex did not appear to act as a sim-
ple bidirectional on/off switch for habitual behavior: when we
performed the second manipulation before the 1- to 2-wk period
after which the new habit was well developed, the perturbation
did not reinstate the original habit (nor did it block the emerg-
ing new behavior). We take this result to suggest that the rein-
statement was locked to the blockade of the second habit. The
view that the IL cortex supervises newly established habits over
old strategies, even habits, is consistent with evidence that the IL
cortex helps maintain current response tendencies when they
compete with prior ones (7, 11, 23).
An alternative view is that the late perturbation could have
returned the rats to a state of value-driven behavior. There is
usually a close coupling of reward-proximal stimuli and actions
to current value (7, 21, 24, 25); the fact that the rats drank the
devalued reward after this late manipulation of IL suggests that
the reward might no longer have been aversive. However, this
interpretation must face three issues. First, in-maze drinking was
consistently low throughout testing in control rats and was low in
the IL-halorhodopsin rats up to the putative “reinstatement.”
Even when these rats ran to the devalued reward, they drank
it <50% of the time; they had the opportunity to drink more on
the maze but did not. Thus, the devalued reward was consis-
tently aversive on the maze up to the point of IL-perturbation.
However, then, during the late IL intervention, pursuit of this
devalued reward jumped far above this level. Second, the IL-
halorhodopsin rats had experience with the devalued reward in
sessions before IL perturbation on the few trials they drank it,
and yet this experience failed to evoke a return of the original
-5-1 PP1PP10 PP6
Home-cage intake of
devalued reward (ml)
Early Late Late
to nondevalued goal (B). *P < 0.05;#P < 0.01;+P < 0.001; differences lacking symbols indicate not significantly different. (C and D) Percentage of drinking of
devalued reward (C) and nondevalued reward (D) when the trial was run correctly. The inverse is runs to the devalued goal without drinking. (E) Home-cage
drinking of devalued reward for IL-halo group in two light-on and light-off sessions after devaluation (“Early” test, conducted around PP1–PP2), and in light-on
+P < 0.05 compared with intake just after devaluation (“Post”). (Right) Home-cage drinking of devalued reward for control group (around PP9).
PP6, and IL-halo rats the day before PP6 and on PP6. (B) Habit reinstatement on PP6 in IL-halo rats (red), compared with the prior day (green) and to control
rats on PP6 (black). Measures of running and drinking devalued goal: first trial of occurrence in the session (if ≥ one occurrence), number of repeats (two
consecutive), percentage occurring in a repeat, and resulting intake volume. *P < 0.05 IL-halo rats on PP6 compared with the prior day (green) or control rats
on PP6 (black). (C) Effects over postprobe days in 5-d blocks on performance during trials instructed to the devalued goal (solid, correct runs; dashed, wrong-
way runs). Dots show individual data points for correct runs during light sessions, color-coded by order of light delivery after the initial probe session (e.g.,
black, second time overall that the rat received IL light).
Timeline of late IL perturbation effects. (A) Behavior when cued to devalued goal for each rat (top to bottom) and each trial, showing control rats on
| www.pnas.org/cgi/doi/10.1073/pnas.1216264109Smith et al.
behavior. Only during the IL intervention, and only in the later
period of testing (PP6), did rats continue to pursue the devalued
goal beyond a few samples. Third, the return of pursuing the
devalued goal was nearly immediate, as soon as the very first
laser trial, suggesting that the runs were based on a stored value
rather than rats changing their performance within the session
after contact with the devalued reward.
The maze behavior we analyzed here constituted a complex
habit, with components related to the two different rewards, only
one of which was devalued. Our findings suggest, as a favored
interpretation, that the return of the original behavior of running
to the devalued goal was a readjustment of a component of the
larger behavioral repertoire learned by the rats and may have
influenced the coupling of the components and subcomponents
of running and drinking as well.
This evidence, collectively, places the temporal control of habit
expression in a paradoxical context: despite the apparent auto-
matic performance of habits, classically considered as outcome-
capacity to reverse the semiautomatic behavioral expression. Our
findings further raise the possibility that scripts for alternate ha-
bitual behaviors are somehow stored when not expressed and that
they can be unmasked if IL activity is disturbed, suggesting co-
how this coordination is accomplished or whether it is accom-
plished exclusively online. Still, our anatomical evidence from
sites confirmed that this region did not have detectable direct
connections with the sensorimotor striatum but, rather, with
regions (10) that should give the IL cortex direct access to circuits
involved in flexibility and reinforcement as well as addiction (e.g.,
via projections to prelimbic neocortex and to the medial and
ventral striatum) (3, 4, 6, 7, 15, 23, 25, 26), and also to habit-pro-
moting circuits through the central amygdala (27). Each could be
important for the IL habit-toggling function.
These observations raise the question of whether the IL cortex,
or its human brain homolog, could similarly control addictions
or states in which behavioral flexibility and behavioral fixity are
out of balance, as seen in major neurologic and neuropsychiatric
disorders (5, 6, 23, 26, 28–30). Evoking fast, robust, and enduring
behavioral change by targeting the IL cortex or its homolog
could be of substantial value in treating disease states in a range
of clinical settings, in addition to serving as a powerful approach
to studying the real-time making and breaking of normal ha-
Materials and Methods
Rats were trained on a T-maze task requiring them to respond to auditory
instruction cues by turning into maze end arms to receive reward (∼0.3 mL
chocolate milk or sucrose, each paired with a distinct cue). Training pro-
ceeded over daily sessions through task acquisition (72.5% accuracy) and
through 10+ additional overtraining sessions. For reward devaluation, rats
received three pairings of free home-cage intake with lithium chloride in-
jection and were later returned to the task for an unrewarded probe session
and rewarded sessions. Task events were controlled by computer software
(MED-PC; Med Associates). Behavior was monitored by in-maze photobeams
and an overhead video camera. For optogenetic manipulation, injections
of AAV5-eNpHR3.0-CaMKIIα-EYFP or AAV5-CaMKIIα-EYFP were made bi-
laterally into the IL cortex, and bilateral dual-ferrule optical fibers were
implanted to terminate at the dorsal aspect of the IL cortex. To perturb
neurons during maze runs, yellow light (2.5–5 mW) was delivered from the
warning cue to goal arrival (ca. 3 s). In tests to analyze spiking dynamics,
neuronal activity was recorded from 12 to 24 tetrodes while light was de-
livered (3-s-on/10-s-off pulses). Immunostaining and Nissl-staining proce-
dures were used to label tetrode tracks, fiber optic cannulae tracks, and YFP-
positive neurons. ANOVA and neuronal spike distribution statistics were
used to assess behavioral and neuronal activity changes, with significance set
at P < 0.05. Also see SI Materials and Methods.
ACKNOWLEDGMENTS. We thank Christine Keller-McGandy, Alex McWhin-
nie, Dr. Daniel J. Gibson, Henry F. Hall, Dr. Dan Hu, Dr. Yasuo Kubota, and
Dordaneh Sugano for their technical help. This work was supported by Na-
tional Institutes of Health (NIH) Grants R01 MH060379 (to A.M.G.) and F32
MH085454 (to K.S.S.); by the Stanley H. and Sheila G. Sydney Fund (A.M.G.);
funding from Mr. R. Pourian and Julia Madadi (A.M.G.); and grants from the
NIH, Defense Advanced Research Projects Agency, and the Gatsby Founda-
tion (to K.D.).
1. Daw ND, Niv Y, Dayan P (2005) Actions, policies, values, and the basal ganglia. Recent
Breakthroughs in Basal Ganglia Research, ed Bezard E (Nova Science Publishers,
Hauppauge, NY), pp 91–106.
2. Packard MG (2009) Exhumed from thought: Basal ganglia and response learning in
the plus-maze. Behav Brain Res 199(1):24–31.
3. Yin HH, Knowlton BJ (2006) The role of the basal ganglia in habit formation. Nat Rev
4. Balleine BW, O’Doherty JP (2010) Human and rodent homologies in action control:
Corticostriatal determinantsof goal-directed
5. Graybiel AM (2008) Habits, rituals, and the evaluative brain. Annu Rev Neurosci 31:
6. Everitt BJ, Robbins TW (2005) Neural systems of reinforcement for drug addiction:
From actions to habits to compulsion. Nat Neurosci 8(11):1481–1489.
7. Killcross S, Coutureau E (2003) Coordination of actions and habits in the medial
prefrontal cortex of rats. Cereb Cortex 13(4):400–408.
8. Coutureau E, Killcross S (2003) Inactivation of the infralimbic prefrontal cortex re-
instates goal-directed responding in overtrained rats. Behav Brain Res 146(1-2):
9. Hitchcott PK, Quinn JJ, Taylor JR (2007) Bidirectional modulation of goal-directed
actions by prefrontal cortical dopamine. Cereb Cortex 17(12):2820–2827.
10. Hurley KM, Herbert H, Moga MM, Saper CB (1991) Efferent projections of the in-
fralimbic cortex of the rat. J Comp Neurol 308(2):249–276.
11. Rich EL, Shapiro M (2009) Rat prefrontal cortical neurons selectively code strategy
switches. J Neurosci 29(22):7208–7219.
12. Gradinaru V, et al. (2010) Molecular and cellular approaches for diversifying and
extending optogenetics. Cell 141(1):154–165.
13. Jog MS, Kubota Y, Connolly CI, Hillegaart V, Graybiel AM (1999) Building neural
representations of habits. Science 286(5445):1745–1749.
14. Barnes TD, Kubota Y, Hu D, Jin DZ, Graybiel AM (2005) Activity of striatal neurons
reflects dynamic encoding and recoding of procedural memories. Nature 437(7062):
15. Thorn CA, Atallah H, Howe M, Graybiel AM (2010) Differential dynamics of activity
changes in dorsolateral and dorsomedial striatal loops during learning. Neuron 66(5):
and habitualaction. Neuro-
16. Dickinson A (1985) Actions and habits: The development of behavioral autonomy.
Philos Trans R Soc Lond B Biol Sci 308:67–78.
17. Adams CD (1982) Variations in the sensitivity of instrumental responding to reinforcer
devaluation. Q J Exp Psychol B 34:77–98.
18. Holland PC, Straub JJ (1979) Differential effects of two ways of devaluing the un-
conditioned stimulus after Pavlovian appetitive conditioning. J Exp Psychol Anim
Behav Process 5(1):65–78.
19. Anikeeva P, et al. (2012) Optetrode: A multichannel readout for optogenetic control
in freely moving mice. Nat Neurosci 15(1):163–170.
20. Han X, et al. (2009) Millisecond-timescale optical control of neural dynamics in the
nonhuman primate brain. Neuron 62(2):191–198.
21. Holland PC, Wheeler DS (2009) Representation-mediated food aversions. Conditioned
Taste Aversion: Behavioral and Neural Processes, eds Reilly S, Schachtman T (Oxford
Univ Press, Oxford), pp 196–225.
22. Pavlov I (1927) Conditioned Reflexes (Dover Publications, Mineola, NY), 448 pp.
23. Peters J, Kalivas PW, Quirk GJ (2009) Extinction circuits for fear and addiction overlap
in prefrontal cortex. Learn Mem 16(5):279–288.
24. Balleine BW, Garner C, Gonzalez F, Dickinson A (1995) Motivational control of
heterogeneous instrumental chains. J Exp Psychol Anim Behav Process 21:
25. Smith KS, Berridge KC, Aldridge JW (2011) Disentangling pleasure from incentive
salience and learning signals in brain reward circuitry. Proc Natl Acad Sci USA 108(27):
26. Pascoli V, Turiault M, Lüscher C (2012) Reversal of cocaine-evoked synaptic potenti-
ation resets drug-induced adaptive behaviour. Nature 481(7379):71–75.
27. Lingawi NW, Balleine BW (2012) Amygdala central nucleus interacts with dorsolateral
striatum to regulate the acquisition of habits. J Neurosci 32(3):1073–1081.
28. Hyman SE, Malenka RC, Nestler EJ (2006) Neural mechanisms of addiction: The role of
reward-related learning and memory. Annu Rev Neurosci 29:565–598.
29. Gillan CM, et al. (2011) Disruption in the balance between goal-directed behavior and
habit learning in obsessive-compulsive disorder. Am J Psychiatry 168(7):718–726.
30. Leckman JF, Riddle MA (2000) Tourette’s syndrome: When habit-forming systems
form habits of their own? Neuron 28(2):349–354.
Smith et al.PNAS
| November 13, 2012
| vol. 109
| no. 46