Abstract
Turning on cue or stopping at a red light requires the detection of such cues to select action
sequences, or suppress action, in accordance with cue -associated action rules. Cortico-striatal
projections are an essential part of the brain’s attention-motor interface. Here, we used glutamate-
sensing microelectrode arrays to measure glutamate transients in the dorsomedial striat um
(DMS) of male and female rats walking a treadmill and executing cued turns and stops. Prelimbic-
DMS projections were chemogenetically inhibited to determine their behavioral necessity and the
cortico-striatal origin of cue -evoked glutamate transients. Furthermore , we investigated rats
exhibiting preferably goal-directed (goal trackers, GTs) versus cue-driven attention (sign trackers,
STs), to determine the impact of such cognitive-motivational biases on cortico-striatal control. GTs
executed more cued turns, and initiated such turns more slowly, than STs. During turns, but not
missed turns or cued stops, cue -evoked glutamate concentrations were higher in GTs than in
STs. In conjunction with turn cue-evoked glutamate spike levels, the presence of a single spike
rendered GTs to be almost twice as likely to turn than STs. In contrast, multiple glutamate spikes
predicted STs to be robustly more likely to turn than GTs. In GTs, i nhibition of prelimbic -DMS
projections attenuated turn rates and turn cue-evoked glutamate peaks and increased the number
of spikes. These findings suggest that turn cue-evoked glutamate release dynamics in GTs are
tightly controlled by cortico -striatal neuronal activity. In contrast, in STs, glutamate release from
DMS glutamatergic terminals is regulated by other striatal circuitry, preferably mediating cued
suppression of action and reward tracking.
Significance Statement
Adaptive behavior involves the selection of behaviorally significant cues and the capacity of
selected cues to control behavioral action. Neuronal projections from cortex to striatum are
essential for such an integration of attentional with motor functions. Here we demonstrated that
glutamate release from cortico -striatal projections primarily influences cue d turns but not cued
suppression of actions (cued stops). Cortico-striatal control of cued turning was especially
powerful in rats which, as a psychological trait, preferably depl oy goal -directed attention.
Together, our findings demonstrate the role of cortico -striatal input in cued action selection, and
they emphasize the experimental and biopsychological significance of investigating the brain’s
attentional-motor interface in the context of broader cognitive-motivational styles.
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Key words:
cortex; striatum; glutamate; cued movement control; acetylcholine; attention; substance use
disorder; Parkinson’s Disease.
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Introduction
Cue-triggered selection of action, or suppression of action, are essential components of adaptive
behavior. Fronto-striatal projections “import” information about attended cues into the striatum to
prioritize cue -linked action , and to facilitate modification of action selection in response to
changing action outcomes (Balleine and O'Doherty, 2010; van Schouwenburg et al., 2012;
Chatham et al., 2014; Hart et al., 2018a; Hart et al., 2018b) . Deficient or biased cortico -striatal
cue import has been postulated to cause neuro -psychiatric symptoms ranging from complex
movement control deficits in Parkinson’s Disease (PD) to compulsive addictive drug use (Volkow
et al., 2006; Bohnen et al., 2009; Ersche et al., 2011; Marshall and Ostlund, 2018; Rasooli et al.,
2021; Sarter et al., 2021).
The cortical control of striatal action selection has been extensively supported by studies
investigating the effects of manipulation of the excitability of fronto-striatal neurons in non-human
animals (for review see Sharpe et al., 2019), and fronto-cortical functional connectivity in humans
(Postuma and Dagher, 2006; Shepherd, 2013; Devignes et al., 2022) . The present experiments
were designed to directly determine the fronto -striatal representation of action-initiating and
action-suppressing movement cues. Focusing on the prelimbic projections to DMS (Mailly et al.,
2013), that previously were demonstrated to be necessary for learning goal-directed actions (Hart
et al., 2018b; Choi et al., 2023), we measured real-time cue-locked glutamate release in the DMS,
using amperometry and glutamate-sensing electrodes, and inhibited prelimbic -DMS projections
to attribute such release to activity in this pathway.
Glutamate transients were recorded in rats performing visual and auditory cue-triggered turns and
stops while walking a treadmill that was stopped and restarted in reverse or same direction,
respectively. The development of this task, the Cued-Triggered Turning Task (CTTT; Avila et al.,
2020), was inspired by evidence showing that PD fallers exhibited deficient turns (Stack and
Ashburn, 2008; Cheng et al., 2014). In PD patients, the propensity for falls has been attributed to
loss of cholinergic neurons innervating cortical areas and the resulting failure to select and
evaluate movement cues (Bohnen et al., 2009; Yarnall et al., 2011; Rochester et al., 2012;
Bohnen et al., 2019; Kim et al., 2019; Sarter et al., 2021) . Supporting the validity of the CTTT, in
terms of revealing clinically relevant, attentional -motor deficiencies, rats modeling PD falls
(Kucinski et al., 2013; Sarter et al., 2014; Kucinski et al., 2015) were demonstrated to exhibit
deficits in cued turning, but not cued stopping (Avila et al., 2020).
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Performing well-practiced, visually or auditorily cued turns and cued stops requires sustaining
attention to cue sources the continued selection of cue s as signified by cue-triggered behavior
(termed cue detection; Posner et al., 1980) , monitoring the state of the treadmill and action
outcome, and maintaining cue modality-linked rules in working memory. Cortico-striatal control of
action selection was expected to reflect the capacity for such voluntary, or top -down, attentional
control.
To reveal the impact of variations in such capacity, here we investigated rats which exhibit, as a
trait, opponent attentional biases . These rats are selected from outbred population s using a
Pavlovian Conditioned Approach (PCA) test. Goal-trackers (GTs) preferably orient to a Pavlovian
reward cue, that is , they learn its predictive significance, but they do not approach and contact
such a cue. In contrast, sign -trackers (STs) approach and contact such a cue, which has been
interpreted as a ssigning incentive salience to a Pavlovian cue and attributed to cue-evoked
mesolimbic dopamine signaling (Flagel et al., 2011; Flagel and Robinson, 2017; Iglesias et al.,
2023). The relatively greater vulnerability of STs for addictive drug taking and relapse in the
presence of Pavlovian drug cues has been extensively documented (e.g., Saunders and
Robinson, 2010; Yager and Robinson, 2010; Yager and Robinson, 2013).
Goal- and sign-tracking index the presence of broader, opponent cognitive -motivational styles
that are dominated by a bias toward deploying top -down (or goal -directed) and bottom-up (or
stimulus-driven) processing of action cues, respectively (for review see Sarter and Phillips, 2018;
for evidence of the presence of these traits in humans see Schad et al., 2020; Colaizzi et al.,
2023). As such biases of GTs and STs were previously shown to be mediated in part via
contrasting cholinergic capacities for the detection of cues (Paolone et al., 2013; Koshy Cherian
et al., 2017; Pitchers et al., 2017a; Pitchers et al., 2017b), we hypothesized that the cortico-striatal
processing of movement cues contributes to the expression of these biases. The present results
indicate that cued turning depends on cortico-striatal glutamate signaling in GTs . In contrast,
glutamate signaling in STs preferably mediates cued stops and is independent of cortico -striatal
neuronal activity.
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Materials and methods
Subjects
378 Sprague Dawley rats (215 females; 250-500 g; obtained from Inotiv, West Lafayette, IN, and
Taconic, Rensselaer, NY) were individually housed on a 12-hour light/dark cycle (lights on at 7:00
AM) at ~21ºC with ad libitum access to food (Laboratory Rodent Diet 5001, LabDiet) and water.
The experiments detailed below used four separate cohorts of rats (each consisted of 52 rats, 26
females and composed of rats obtained from both Taconic and Inotiv). The four cohorts were
obtained and formed across 19 months , reflecting the experimental demands of amperometric
recordings. All experimental procedures were approved by the University Committee on the Use
and Care of Animals (UCUCA) at the University of Michigan and carried out in laboratories
accredited by the A ssociation for Assessment and Accreditation of Laboratory Animal Care
(AAALAC). Animals acclimated to housing quarters for two days before the onset of experimental
procedures.
Behavioral phenotyping
Apparatus. Prior to the onset of PCA testing, r ats were handled daily for 3 days and given ~7
banana-flavored sucrose pellets (45 mg; BioServ). Rats were tested in conditioning chambers
(20.5 x 24.1 cm floor area, 20.2 cm high; MED Associates Inc.). Each chamber contained a food
magazine port located 2.5 cm above the floor in the center of the intelligence panel, a red house
light located on the wall opposite the food magazine port (on throughout training sessions), and
a retractable lever (Med Associates) located 2.5 cm to the left or right of the food rec eptacle and
6 cm above the floor. This retractable lever was illuminated when extended with a white LED light
placed inside the lever house. For a lever press to be recorded, a force of ∼15 g was needed.
The pellet dispenser (Med Associates) delivered one 45 mg banana-flavored sucrose pellet (Bio-
Serv) into the food magazine port at a time. A head entry was recorded each time a rat broke the
infrared photobeam located inside the food magazine port. Each conditioning chamber was
placed in a sound -reducing enclosure and a ventilating fan generated background noise. Data
collection was controlled by Med-PC IV Behavioral Control Software Suite.
PCA testing and primary measures. One day prior to the onset of PCA testing, rats were placed
into the test chamber with the red house light illuminated and the lever retracted. 25 food pellets
were delivered in accordance with a variable schedule (VI-30; 0-60 s) to foster the reliable retrieval
of pellets from the food magazine port. During PCA testing, trials began by illuminating and
extending the lever (CS) for 8 s. Immediately following the retraction of the lever, a single banana
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pellet was delivered into the magazine port (US). A variable intertrial interval (ITI; 90±60 s) started
immediately after the retraction of the lever. An individual PCA training session consisted of 25
trials and lasted 35-40 min. The following 5 measures were extracted from individual trials and
collapsed over individual PCA sessions: (1) number of lever deflections (contacts); (2) latency to
first lever deflection; (3) number of head entries into the food magazine port (referred to as food
cup entries) du ring the presentation of the CS ; (4) latency to the first magazine port entry after
CS presentation; (5) number of magazine port entries during the ITI. Data from animals included
in the final analysis reflected sessions during which rats consumed all food pellets.
Phenotype classification . The propensity for rats to approach the lever CS versus the food
magazine port during the CS period was expressed by a PCA index score. Briefly, the PCA index
score consisted of averaging three measures of the conditioned approach on the 4th and 5th day
of testing (e.g., Robinson and Flagel, 2009; Meyer et al., 2012; Yager et al., 2015; Pitchers et al.,
2017a; Pitchers et al., 2017b) : (1) the probability of contacting either the lever CS or food
magazine port during the CS period (P(lever) − P(food port)); (2) the response bias for contacting
the lever CS or the food magazine port during the CS period: (# lever CS contacts − # food
magazine port contacts)/(# lever CS contacts + # food magazine port contacts); and (3) the
latency to contact the lever CS or the food magazine port during the CS period: (food magazine
port contact latency − lever CS contact latency)/8. Averaging these thre e measures yields PCA
index scores ranging from −1.0 to +1.0, where +1.0 indicates an animal made a sign-tracking CR
on every trial and −1.0 a goal-tracking CR on every trial. Further, rats with an averaged PCA index
score ranging from −1.0 to −0.5 were classified as GTs, and rats with a PCA index score between
+0.5 and +1.0 as STs.
Cue-triggered turning task (CTTT)
Apparatus. The 32.51 cm wide by 153.67 cm long treadmill was constructed by modifying a 2200
Series Flat Belt End Drive Dorner conveyor (Dorner, WI). The conveyor belt surface material was
polypropylene, friction -resistant, and easily cleaned with ethanol or soap. T he convey or was
paired with a Dorner Variable Speed Controller (Dorner, WI), with speeds ranging from 0 cm/s to
32 cm/s or 19.2 m/min. The Variable Speed Controller included a reversing controller, allowing
the belt to rotate clockwise, "forward," or counterclockwise, "reverse." An in-house-made Faraday
cage was placed on top of this conveyer, 145.10 cm long, 32.51 cm wide, and 38.1 cm tall. The
wooden frame of the Faraday cage was enclosed by a woven copper mesh and grounded to block
out static electric fields. Plexiglass inserts were placed inside the Faraday cage to prevent rodents
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from chewing on the mesh. Copper reward ports were installed on either end of the treadmill to
allow delivery of 45 mg banana pellets. Experimenters raised two wooden panels on the cage to
place rodents on the treadmill. The 28V DC, 100 mA stimulus light was approximately 2.54 cm in
diameter with a flat lens and mounted on both sides lengthwise on the Faraday cage
(MedAssociates, Inc., St. Albans, VT). The auditory cue was a Mallory -SonAlert audible device.
This 28V DC, 18 mA device was mounted on the cente r of the Faraday cage and was
approximately 4.3 cm long by 4.3 cm wide by 3.6 cm tall. This device emitted a continuous tone
at 68 dBA sound pressure level, which is within the acceptable range for chronic presentations,
to neither elicit a fearful response nor induce hearing loss (Turner et al., 2005; Castelhano-Carlos
and Baumans, 2009) . These devices were controlled by a MedAssociate interface and a relay
module to run our custom program. Performance sessions were videotaped with four web
cameras (Logitech C920x HD Pro Webcam, Full HD 1080p/30fps) and relayed to an Intel Xeon
workstation (Dell, Round Rock, TX) via USB cords and processed with OBS Studio (Open
Broadcaster Software, free and open-source software).
Training regimen. Rats were trained to walk on a treadmill until the onset of one of two cues
(tone or sound, presented for 2 s), indicating that following a treadmill stop , 1 s after cue onset,
and a 5-s pause, the treadmill restarted in the reverse or same direction, respectively (Avila et al.,
2020). Rats learn to respond to turn cues by turning around, and to the stop cue by stopping and
not turning. Cued turns and cued stops were rewarded by manually delivering a banana-flavored
sucrose pellet (45 mg; Bio-Serv) into the reward port 2-3 s following the treadmill stop.
Rats first underwent a treadmill acclimation regimen using a procedure adapted from Arnold and
Salvatore (2014). First, rats were handled for 20 min for two days. On the second day, rats were
placed in the Faraday cage for 15 min with the belt paused. All sessions were conducted under
dim red lighting to minimize stressors and increase the discriminability of the light cue. For a week,
rats were placed into the Faraday cage for 3 min with the belt paused and then trained to walk on
the treadmill at speeds up to 9.6 cm/s or approximately 6 m/min. The experimenter manually set
the initial rate and direction of the tre admill, with the initial direction counterbalanced within and
across subjects. During this training, rats were reoriented by gentle prodding if they began to walk
in the opposite direction of the belt. After each session, rats were immediately returned to their
home cage and housing room. Between sessions and subjects, the Plexiglass walls of the
Faraday cage and the treadmill belt were wiped down with 70% ethanol and soap.
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The initial treadmill speed was set at 3.2 cm/s for the first two days and gradually increased by
1.6 cm/s every 2 min. Each session lasted 20 min, so the final walking speed reached 8 cm/s. On
the third and fourth days, the initial rate was set at 6.2 cm/s, increasing by 1.6 cm/s every 5 min
until the maximum speed of 9.6 cm/s was reached. On the fifth and sixth day, rats walked at 8.0
cm/s for 10 min and 9.6 cm/s for the last 10 min. Finally, on the seventh day of this training
regimen, rats walked at 9.6 cm/s for 20 min. In the next training phase, rats were placed on the
treadmill and presented with turn and stop cues. The modality of the turn and stop cues was
counterbalanced across animals.
Contrary to the acclimation training phase, during which experimenters manually controlled the
treadmill, this phase was controlled entirely by custom scripts using Med -PC software and
interface (MedAssociates). Rats walked at a speed of 9.6 cm/s and cues were presented for 2 s.
Maximally two successive presentations of a cue of the same modality were allowed. The intertrial
interval (ITI) was 60±30 s. The total number of trials per daily session was 18, with a maximum
duration of a test session of 20 min. Rats underwent cue training for approximately two to three
weeks. Then, upon reaching the performance criterion, defined as 70% correct responses to
either cue for two consecutive days, rats were tested and videotaped for four additional days.
Data from th ese four sessions were used to determine potential phenotype and sex -based
differences in baseline performance. Thereafter, rats underwent surgery for chronic
microelectrode array implantation.
CTTT performance measures. Performance measures were cued turns, missed turns, cued
stops, and false turns, and extracted from offline scoring of session videos. For a successful turn
to be scored, the animal must have initiated a turn, defined by a rotation of the longitudinal
orientation of the body of at least 90°, before the treadmill restart, that is, within 8 s of the cue
onset. A stop was defined as a cessation of forward movement. For stops occurring before the
treadmill stopped, rats would typically stop while positioned at the backend of the treadmill so that
following a stop, the treadmill would transport them to the front of the treadmill (within the
remaining 1-3 s until the treadmill stopped), without the rat contacting the front end of the test
chamber. Following the treadmill stop and during the 5 -s pause, a false turn was scored if the
animal (falsely) turned. The time of initiation and completion of cued turns, relative to the onset of
the cue, were extracted from session videos. For the analysis of baseline CTTT performance, and
because rats generated a variable number of cued turns during the 4 sessions used for this
analysis, individual turn onset and completion times were averaged across the test sessions.
Additional performance measures were extracted from training and testing sessions to explore
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relationships between cued turning and stopping performance, phenotype and, subsequently,
glutamatergic transients (detailed in Results).
Amperometric recordings of glutamate currents
Electrode preparation and calibration. Extracellular glutamate concentrations were measured
by oxidizing glutamate on an electrode surface featuring immobilized glutamate oxidase (GO) ,
and by oxidizing the resulting peroxide levels using fixed-potential amperometry. Based on
calibration curve s generated in vitro , the resulting currents were expressed as micromolar
glutamate concentrations at the recording site (Rutherford et al., 2007; Hascup et al., 2008; Parikh
et al., 2008; Parikh et al., 2010a; Parikh et al., 2014; Clay and Monbouquette, 2018; Bermingham
et al., 2022) . The configuration consisted of a ceramic backbone probe ( Quanteon LLC,
Nicholasville, KY, USA ) housing four recording sites , each 15×333 μm, crafted from platinum -
iridium (Pt/Ir). These recording sites were grouped into two pairs, separat ed by 30 μm between
each member of a pair and a 100 μm vertical spacing between the pairs, so that the two pairs of
electrodes were linearly arranged along the shank of the probe. Microelectrode arrays were
modified for in vivo recordings in behaving rats by soldering four enamel-coated magnet wires (30
ga) to the terminals on the electrode panel and the other end to gold-pin connectors. Reference
electrodes we re constructed by soldering Ag/AgCl reference electrodes prepared from 0.008”
silver wire (A -M Systems, Carlsberg, WA) to gold -pin connectors. The pins were then inserted
into a 9-pin ABS plug (GS09PLG-220, Grinder Scientific) and adhered to the microelectrode with
epoxy. Custom 9-pin ABS plugs were also printed with a STUDIO G2 3D printer (BigRep, Berlin,
Germany). The top pair of electrodes, termed active sites, were coated with recombinant L-GO
(US Biological Life Sciences) solution (1 U in 1 μL DiH2O), cross-linked with a BSA and
glutaraldehyde mixture, by manually applying microdroplets using a 1 -μl Hamilton syringe . The
lower pair of electrodes , termed sentinels, were coated with only the BSA and glutaraldehyde
mixture, to record currents unrelated to glutamate concentrations. After a minimum 24 -hr
incubation period to ensure optimal adherence of the enzyme layer, an exclusion layer composed
of meta-(1,3)-phenylenediamine (mPD) was electroplated onto each recording site's surface by
5-min application of 0.85 V versus an Ag/AgCl reference electrode (Bioanalytical Systems). This
exclusion layer prevents sensing electroactive interferents such as ascorbic acid (AA) and
catecholamines (e.g., Mitchell, 2004). After another 24-hr incubation period for the electrode sites
to dry, recording sites were calibrated to determine the sensitivity for glutamate, selectivity for
glutamate versus interferents, stability, and limit of detection of glutamate. Calibrations we re
conducted using a FAST-16 electrochemical system (Quanteon). A constant voltage of 0.7 V was
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applied versus an Ag/AgCl reference electrode, and the system was placed in a heated 40 m L
bath of 0.05 M PBS. Following a 30 -minute baseline recording, a solution containing 20 mM
ascorbic acid (AA, interferent), 20 mM glutamate (analyte), and 2 mM dopamine was introduced
to the bath. These additions generated the following concentrations: 250 μM AA, 20, 40, and 80
μM glutamate, and 2 μM dopamine. Changes in amperometric current at individual electrode sites
were measured after each solution to calculate t he slope (sensitivity), the limit of detection,
selectivity for AA and dopamine, and linearity ( R2). Glutamate sensors were required , at a
minimum, to have a sensitivity of >5 pA/μ M glutamate, a limit of detection 50:1, and a linear response to increasing glutamate concentrations
(20-80 μ M glutamate) of R >0.95. The characteristics of the electrodes used in the present
experiments exceeded these minimum requirements (Table 1).
-------------------------------------
Insert Table 1 about here
-------------------------------------
Chronic implantation of microelectrode arrays (MEAs). Upon having reached stable, criterion-
level performance CTTT (≥70% cued turns and stops for two consecutive days), microelectrode
arrays were chronically implanted into the DMS. Rats were anesthetized using isoflurane gas (5%
induction and 1 –3% maintenance) and mounted on a stereotaxic frame on a heating pad to
maintain a 37°C body temperature. Ophthalmic ointment lubricated eyes. A craniotomy and
durotomy using a bent 27 -gauge needle for dura removal were performed above the right DMS
(AP: +0.50 mm; ML: −2.20 mm from bregma). Three stainless steel screws were threaded into
the cranium. The MEA was then lowered 4.5 mm dorsoventrally from the dura into the striatum.
At the same time, an Ag/AgCl reference electrode was implanted at a remote site in the
contralateral hemisphere. The microelectrode assembly was anchored with methyl methacrylate
dental cement, and exposed regions of the skull were filled with a translucent, medium -viscosity
silicone adhesive to minimize leakage of the dental cement onto the brain. Animals rested over a
48-hour recovery period before moving to the next phase of the experiment. Amperometric
recordings were collected by connecting the head stages to a FAST -16 potentiostat/data
electrochemical system (Quanteon) via a shielded cable and low -impedance commutator. The
hydrogen peroxide by-product of GO catalyzation was electrochemically oxidized by applying 0.7
V versus the Ag/AgCl reference electrode and digitized at a sampling rate of 5 Hz. Behavioral
sessions began following a 50 -minute baseline recording period. Consistent with prior evidence
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showing that implanted MEAs maintain stable sensitivity and reliability for at least seven days
after implantation, electrochemical recordings were completed within seven days of MEA
implantation (Rutherford et al., 2007).
Amperometry data processing and analysis of glutamate peaks. Electrochemical recording
data were processed using a custom MATLAB (MathWorks) script. The background current
recorded on sentinel sites was subtracted from the current recorded on the active sites,
normalized by the response to dopamine, and then converted to glutamate concentration based
on calibration curves. Trial-associated glutamate concentrations were determined over 13-s bins,
involving the following task-related periods: 3 s prior to the onset of turn and stop cue presentation,
throughout cue presentation (2 s), and until the treadmill stopped (1 s after cue offset), during the
subsequent 5 s pause when the reward was delivered and retrieved , and for 2 s following the
restart of the treadmill belt. The concentration of glutamate currents recorded over 2.5 s prior to
cue onset (approximately 10 data points), served as a baseline for analyzing glutamate levels for
each trial. Changes from the se baselines were used for statistical analyses (e.g., Parikh et al.,
2007a) and, therefore, glutamate concentrations shown in graphs depict sentinel -corrected,
normalized and baseline-corrected levels. Although minimal drift of baseline glutamate levels was
seen across trials and sessions, such baseline -based correction reduced the impact of potential
minute-based variations in glutamate concentrations.
The analysis of glutamate concentrations focused on the maximum peak concentrations and,
secondarily, the timing of the first peak relative to cue onset and reward delivery, and the number
of peaks within 1.5 s of these events. Prior studies on the effects of depolarization of s ynaptic
terminals, blocking such depolarization, or of pharmacological manipulations of the excitability of
terminals, confirmed that peak concentrations of extracellular glutamate indicate the extent of
terminal depolarization (Hascup et al., 2008; Parikh et al., 2008; Parikh et al., 2010b; Mattinson
et al., 2011; Quintero et al., 2011; Parikh et al., 2014) . The PeakDet function in MATLAB
(MathWorks) was utilized to identify peaks, requiring setting threshold and minimum differences.
To be identified as a peak, glutamate concentrations needed to be 3 standard deviations (SD)
above the average baseline current (recorded over 2.5 s before cue presentation). In addition, for
a value to be identified as a peak, the preceding and subsequent values needed to be at least 1
SD (derived from baseline data) below the peak value. These parameters were adopted from
peak analyses in neurophysiological studies (e.g., Ghosh et al., 2022) and ensure d a robust
separation of peaks from potentially noisy recordings of relatively small currents.
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For each response category (cued turns, misses, cued stops, false turns), glutamate traces were
included into the final analyses if; a) if the electrode met the in vitro calibration criteria, b) traces
were devoid of major electrostatic interferences (such as resulting from the headstage contacting
the reward port); c) task compliance was apparent (animals walking continuously counter the
direction of the treadmill and pr omptly reversing direction upon cue or treadmill onset) ; d) the
accuracy of the electro de placement was confirmed, determined following the completion of
experiments. The data from a rat that developed seizures after the 2nd day of recordings were
completely excluded from the final analyses. As a result, 1 -27 (range) traces per rats and
response categories were included in the final analyses.
The maximum peak concentration (µM), time to peak (s), and number of peaks were extracted
from each trace used for the final analyses. Peak amplitude was defined as the highest glutamate
concentration reached within 1 s from the onset of a cue or from reward delivery. The time to peak
was defined as the time from cue onset or reward delivery to the first peak. During missed turns,
peaks were not identified in a small fraction of trials (<2% in both phenotypes), yielding missed
data for this measure. The number of peaks were counted across a 1.5 -s period from cue onset
or reward delivery.
Verification of MEA placements in the DMS. Microelectrode arrays (MEAs) were chronically
implanted into the DMS to record extracellular glutamate levels while performing the CTTT.
Following the completion of experiments, administration of a lethal dose of sodium pentobarbital
(270 mg/kg, i.p.) was followed by transcardial perfusion of saline, followed by 4%
paraformaldehyde in 0.15 m sodium-phosphate solution, pH 7.4. Extracted brains were postfixed
in 4% paraformaldehyde for 24 hrs, then submerged in 30% sucrose solution until they sank.
Using a freezing microtome (CM 2000R; Leica), 35 -μm thick brain slices were sectioned and
stored in cryoprotectant until further histologic processing. Sections were mounted and processed
with a Cresyl Violet Nissl stain to confirm MEAs placement. A Leica DM400B digital microscope
was used to photomicrograph the sections at 1.25X and 5X magnification at three A-P levels (0.2
mm, 0.5 mm, and 1.0 mm).
Intracranial infusions of a Cre-dependent DREADD and a retrograde Cre-vector
We utilized a pathway-specific dual-vector chemogenetic strategy (e.g., Sherafat et al., 2020) to
selectively inhibit the activity of fronto -cortical projections to the DMS. Intracranial infusions of a
Cre-dependent Designer Receptor Activated Only by Designer Drug (DREADD) and a retrograde
were carried out following PCA screening and prior to CTTT acquisition training. In a subset of
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rats, a second surgery, carried out following the acquisition of the CTTT, was conducted to implant
electrochemical recording electrodes into the DMS. The viral vectors containing the Cre -
dependent plasmid pAAV -hSyn-DIO-hM4D(Gi)-mCherry (AddGene #44362 -AAV8; titer of
2.1x1013 GC/mL), Cre-dependent control plasmid pAAV-hSyn-DIO-mCherry (AddGene #50459-
AAV8; titer of 2.2x1013 GC/mL), or the retrograde ly transported Cre-expressing plasmid pENN-
rAAV-hSyn-HI-eGFP-Cre-WPRE-SV40 #105540-AAVrg; titer of 1.9x1013 GC /mL) were infused
into the lower layers of the prelimbic cortex (for the anatomical organization of fronto -striatal
projections see, e.g., Mailly et al., 2013) and the DMS, respectively.
Craniotomies and durotomies were carefully performed above four sites of the DMS using a bent
27-gauge needle for dura removal to minimize the impact on the subsequent implantation of
recording electrodes and electrochemical recordings. One μL of pENN-rAAV-hSyn-HI-eGFP-Cre-
WPRE-SV40 vector was infused (bolus) into the DMS at two sites per hemisphere (AP: +0.2/1.2;
ML: ±2.5/2.2; DV: -4.5 mm from dura) to retrogradely transfect afferent projections. In addition,
one μL of AAV -hSyn-DIO-hM4D(Gi)-mCherry or AAV -hSyn-DIO-mCherry (control vector ) was
infused (bolus) into the prelimbic cortex (AP: +3.2; ML: ±0.7; DV: -3.5 mm from dura) to allow for
the selective inhibition of cortico-striatal projections. The injector was left in place for 8 min to
minimize diffusion into the injector tract. Rodents recovered for one week before treadmill and
CTTT training.
Clozapine N-oxide (CNO). CNO was obtained from Tocris Bioscience (Bristol, United Kingdom)
and dissolved 10 mg/ml in 6% DMSO in 0.9% NaCl solution. CNO (5.0 mg/ml/kg; i.p.) or vehicle
was administered i.p. 50 min before the onset of CTTT testing . In rats also equipped for
electrochemical recording of dorsomedial GLU levels, CNO was given just prior to the onset of
the pre -task GLU baseline (above). Rats were given v ehicle and CNO on alternate days.
Regarding potential off-target effects of clozapine (Gomez et al., 2017) , we and others have
previously consistently failed to detect effects of this dose of CNO in rats expressing the control
vector, including in rats performing the CTTT, complex movement control tasks, or an operant
sustained attention task (Jendryka et al., 2019; Avila et al., 2020; Kucinski et al., 2022) . Given
effective dose ranges of clozapine in rodents performing complex behavioral tasks (Martinez and
Sarter, 2008), and given the proposed conversion rate of CNO to clozapine, an approximately 50-
100-fold higher dose of clozapine would be required to produce significant effects (see also
Mahler and Aston-Jones, 2018; Lawson et al., 2023).
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Visualization and quantification of GFP/mCherry -expressing neurons. We amplified the
mCherry fluorescent reporter signal of the inhibitory hM4Di DREADD vector to enhance the
evaluation of the transfection efficacy and distribution of neurons expressing mCherry and eGFP,
the latter indicating the expression of the retrograde Cre-expressing vector in frontal cortex. The
eGFP fluorescent label did not necessitate signal enhancement. Sections underwent six washes
for 5 min each in 0.1 m PBS, pH 7.3, and then were immersed in 0.1% Triton X -100 diluted in
PBS for 15 min. After three 5-min PBS rinses, sections incubated for 60 min at room temperature
(RT) in the blocking solution, 1% normal donkey serum (NDS) and 1% Triton X-100 made in PBS.
Sections were incubated overnight in the primary antibod y (rabbit anti -mCherry, ab167453,
Abcam; 1:500; diluted in blocking solution to prevent non -specific binding). The next day , and
following three 5 -min PBS rinses, sections were incubated for 90 min at RT in the secondary
antibody (donkey anti -rabbit conjugated to Alexa 594, PIA32754, Invitrogen, 1:500). Following
three 5 min -rinses with PBS and sections were mounted, air dried, and cover -slipped with
Vectashield Antifade Mounting Medium (H-1000; Vector Laboratories).
A Zeiss LM 700 confocal microscope, equipped for sequential multi -track acquisition with 488 -
and 561nm excitation lines, along with specific filter sets for Alexa 488 (Zeiss filter set 38 HE) and
Alexa 594 (Zeiss filter set 54 HE), was employed for visual izing and capturing images of
fluorescent neurons. Images were taken at magnifications of 10 x to confirm placement s of
infusions in the DMS, 20x and 40x at five anterior-posterior levels (frontal cortex: 3.0 mm and 3.24
mm, striatum: 1.2 mm, 0.5 mm, and 0. 2 mm) for verification and documentation of single and
double-labeled cells in cortex and striatum.
We employed a modification of a prior, semi -quantitative estimation of transfection efficacy and
space (Avila et al., 2020) . Briefly, GFP labeling that was centered in the striatal target region of
prelimbic projections (Mailly et al., 2013) was assigned the highest transfection score (5), whereas
labeling that extended into more lateral and ventral regions and only partially covered the target
region were assigned lower scores. Likewise, mCherry labeling that exclusively covered the entire
prelimbic cortex was assigned the highest score. Partial expression of mCherry in this region, or
labeling that extended dorsally or ventrally beyond the prelimbic cortex , were assigned lower
transfection efficacy scores. Furthermore, single-and double-labeled neurons were counted in the
prelimbic region, and the proportion of double -labeled neurons was computed for each rat.
Counting frames were superimposed on each sub region using the ImageJ multipoint tool. Cells
were counted on two sections per brain, yielding four counts per brain and subregion. Averaged
counts obtained from each brain and subregion were used for further analyses. To produce
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images of neurons expressing mCherry and GFP, and control for potential “bleed-through” (e.g.,
North, 2006) ,we used the split view feature within Zen Black software ( ZEN 2.31 SP1 Black
Edition; Zeiss) for examination of individual channels with multi -track images. T ile
scanning/stitching techniques were implemented at both 10 x (3 × 2 tiles, covering an area of
3455.94 by 2370.64 μm) and 20 x magnifications (4 × 3 tiles, covering an area of 1407.88 by
1135.31 μm).
Experimental design and statistical analyses
Behavioral data. Chi-square tests were used to determine the effects of sex and the commercial
source of rats (vendor) on the distribution of PCA screening scores. Baseline CTTT performance
was analyzed using conventional repeated measures ANOVAs; associated graphs depict
individual values, means, and 95% Confidence Intervals (CI). Conventional ANOVAs were
computed using SPSS for Windows (version 28.0; SPSS) and GraphPad Prism (version 10.1.2).
Glutamate concentrations and effects of CNO . Extracellular glutamate concentrations were
sentinel-corrected, normalized to dopamine, and pre -cue baseline corrected (see above for
details). From these data, peak concentrations and peak timing information were extracted (see
above for the definition of the three measures and of peaks). Given the complexity of the
experimental design (variable number of rats per phenotype, turn and stop trials, and of cue -
evoked glutamatergic transients), here we first determined potential phenotype -specific
differences in glutamate peaks across trial types and response categories, followed, in cases, by
post hoc analyses of event -related glutamate levels within individual phenotypes. Linear -mixed
effects models (LMMs) with restricted maximum likelihood estimation were employed by SPSS
for Windows (version 28.0; SPSS). A key reason for using LMMs concerned the definition of
sample size (number of an imals versus the number of individual traces collected from each
animal). Moreover, sample sizes may vary across repeated or otherwise dependent measures
(e.g., Schielzeth et al., 2020; Yu et al., 2022). Data from repeated sessions were used to compute
the repeated fixed effect, and phenotype was used to determine between-subjects fixed effects,
with a subject identifier random intercept. Separate LMMs were computed for the analysis of
glutamate levels during four response categories (cued turns, missed turns, cued stops, reward
delivery); the three measures analyzed per response categories ( maximum peak levels, time to
first peak, and number of peaks ; defined above ) were treated as dependent measures. The
covariance structures with the lowest Akaike’s information criterion were selected for each model
(Verbeke and Molenberghs, 2009) . Main effects of phenotype derived from the analysis of the
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three measures were followed up using Bonferroni's method for pairwise comparison of the
means. When LMMs reported significant interactions, repeated measures ANOVAs were used to
compare data from repeated sessions, with Huynh –Feldt-corrected F values and corrected
degrees of freedom applied in case of violation of the sphericity assumption. Data graphs showing
glutamate concentrations depict individual values, estimated marginal means (EMMs), and 95%
CI.
Contingency table analyses. Glutamate trace characteristics were extracted from 548
recordings of turn cue trials, 364 of which yielded a turn (GTs: 206, STs: 158) and 184 a miss
(GTs: 112, STs: 72). Contingent on threshold maximum peak concentrations, and the presence
of a single o r multiple cue -evoked glutamate peaks, the proportions of turns and misses were
compared using contingency table analyses ( P values were computed using Fisher’s exact test;
GraphPad Prism). Furthermore, the relative probability for turns in GTs, as well as the reciprocal
value, were derived from these analyses (Koopman asymptotic score; Koopman, 1984; Motulsky,
2018).
Effects of CNO on CTTT performance . The effects of CNO or its vehicle on cued turns and
stops, in rats expressing the inhibitory DREADD or the empty control vector, were analyzed using
repeated measures ANOVA (general linear model) on the effects of phenotype and treatment
day. For clarity, effects on the two be havioral measures were analyzed separately, at
alpha=0.05/2. Tukey's Honest Significant Difference test was used to compare, post hoc , the
effects of the 1st and 2nd administration of CNO with the effects of the 1st and 2nd administration of
vehicle (GraphPad Prism).
P values and effect sizes. Exact P values were reported (Greenwald et al., 1996; Sarter and
Fritschy, 2008; Michel et al., 2020) . For key findings, e ffect sizes were computed using
generalized eta squared (ηp2) (effect sizes of 0.02 typically are classified as small, 0.13 as
medium, and 0.26 as large; e.g., Bakeman, 2005), derived from Bonferroni pairwise comparisons
of estimated marginal means (Greenwald et al., 1996).
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Results
Phenotype screening and distribution by sex and vendor
PCA screening generated five behavioral measures indicating the speed and frequency of
contacting the lever (Pavlovian CS) versus the speed and frequency of head entries into the food
port. These measures were collapsed into the PCA score, indicating the degree of sign -tracking
and goal-tracking, respectively, of individual rats over 5 PCA test sessions . Prior analyses have
consistently shown that all rats orient toward the CS , that is, all rats learn the predictive
significance of the CS, but only some – the STs – approach and contact the CS (Fig. 1a, top right
photo), while GTs do not contact the CS but approach and enter the food port (Fig., 1a, bottom
right photo; e.g., Robinson and Flagel, 2009; Meyer et al., 2012; Pitchers et al., 2017a).
--------------------------------------
Insert Figure 1 about here
--------------------------------------
PCA scores from the last two sessions were averaged and used to classify rats as STs and GTs.
PCA screening of N=378 (215 females) rats yielded 113 GTs (30%), 155 rats with intermediate
scores (INs; 41%; not shown), and 110 STs (29%). Figure 1a shows the distribution of PCA scores
across the five test sessions of the rats used for CTTT training and amperometric recordings (79
rats GTs, 13 females; 22 STs, 13 females; data from rats with intermediate P CA scores are not
shown).
As PCA screening was conducted in four separate cohorts of rats, separated by 2-19 months, we
first determined that PCA scores did not differ across these cohorts (no main effects of cohort on
response bias (respbias), probability difference (probdiff), latency, or PCA index; all F0.16). Chi-square tests were used to determine if sex or the commercial source of the rats
(vendor) influenced the distribution of phenotypes. Consistent with prior reports (Pitchers et al.,
2015), the distribution of PCA scores did not differ by sex (X2(2, N=378)=01.63, P=0.44; Fig. 1b).
However, the distribution of PCA scores from rats obtained from the two vendors differed
significantly (X2(2, N=378)=36.62, P<0.001; Fig. 1c). Relatively more r ats obtained from Inotiv
displayed lever -directed behaviors, while rats supplied by Taconic relatively more frequently
exhibited goal cup-directed behaviors. A follow-up analysis rejected the possibility that vendor -
specific PCA score distribution differed by sex (Inotiv: X2(2, N=133)=1.30, P=0.52; Taconic: X2(2,
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N=245)=1.41, P=0.50. GTs and STs of both sexes and from either vendor were combined for use
in subsequent experiments.
Cue-triggered turning task (CTTT) acquisition and criterion performance
Upon reaching criterion performance in the CTTT ( see task illustration in Fig. 2a-c), defined as
>70% cued turns and cued stops for two consecutive days/sessions, and prior to the intracranial
implantation of microelectrode arrays, the relative number of cued turns and stops were recorded
from an additional 4 test sessions to determine baseline CTTT performance of GTs and STs.
---------------------------------------------
Insert Figures 2 and 3 about here
---------------------------------------------
The number of training sessions required by GTs (n=29, 13 females) and STs (n=22, 12 females)
to reach CTTT criterion performance, defined as 70% correct responses to either cue for two
consecutive sessions, did not differ significantly (F(1,47)=0.01, P=0.94; Fig. 3a). Likewise, males
and female rats acquired this task at comparable rates (main effect of sex: F(1,47)=0.81, P=0.37;
phenotype x sex: F(1,47)= 0.27, P=0.61).
After having reached performance criterion, GTs scored significantly more cued turns than STs
across four subsequent test sessions (main effect of phenotype:
F(1,47)=5.03, P=0.003, ηp2=0.097; GTs: 0.80 (mean) cued turns/trials; STs: 0.73; note that while
Figs. 3b and c show response ratios, ANOVAs were conducted with arcsine -transformed values
because ratio data violated homoscedasticity ). A main effect of day (or session; F(3,141)=
4.96, P=0.003, ηp2=0.096) reflected that rats generated more cued turns during the third when
compared with the first of the four sessions used for the determination of CTTT baseline
performance (Fig. 3b; day 1: 0.71 (mean) cued turns/trials; day 3: 0.83). Sex did not affect turning
rates (F(1,47)=0.01, P=0.95) and interactions between phenotype, sex and day remained
insignificant (all F0.15). Cued stops did not differ by phenotype, day or sex (all main
effects and interactions: all F0.052; Fig. 3c).
Relative to the time of cue onset, GTs initiated and completed cued turns significantly later than
STs (main effects of phenotype; initiation: F(1,51)= 8.84, P=0.005, ηp2=0.16; completion: F(1,51)=
9.40, p=0.004, ηp2=0.17; Fig. 3d; effects of sex and interactions between the effects of sex and
phenotype: all F0.32). Reflecting the parallel effects of phenotype on initiation and
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completion time, the time needed to complete turns did not differ between the phenotypes (main
effects of phenotype, sex, and interactions: all F0.07); GTs: 2.69±0.15 s (M, SEM);
STs: 2.33±0.17 s; not shown).
Taken together, GTs and STs acquired the CTTT within a similar number of training sessions,
GTs scored more cued turns than STs, and GTs initiated and completed cued turns at significantly
later times relative to cue onset. Subsequent experiments recorded mediodorsal striatal
glutamatergic transients during cued turns and stops, missed turns and false turns, and tested
the role of fronto -striatal glutamatergic projections in generating performance -associated
glutamatergic transients. Because of the absence of significant effects of sex and interactions
involving sex in the analysis of baseline CTTT performance, subsequent statistical analyses,
using linear mixed effect models to account for effects of animals and variable numbers of
transients recorded from each animal, did not further involve sex as a statistical variable.
Furthermore, cue modality did not impact turn or stop rates and thus , likewise, was not included
as a factor in the final analyses.
Turn and stop cue-locked, phenotype-specific dorsomedial glutamate dynamics
Rats were screened for the classification of the phenotypes, underwent CTTT training until they
performed at criterion level, followed by implantation of an MEA into the DMS and subsequent
recordings of glutamate currents during CTTT performance. Figure 4 illustrates the four recording
sites fabricated onto a ceramic backbone (Fig. 4a) and the preparation of pairs of recording sites
for the measurement of glutamate concentrations and potential electroactive interferents (Figs
4b,c). Following calibration of the electrodes in vitro (Table 1; a representative example is shown
in Fig. 4d), MEA s were permanently implanted into the DMS (Fig. 4e). Examples of currents,
recorded via GO -sensitive electrodes (Fig. 4f) and sentinels (Fig. 4g), serve to illustrate the
resulting, subtracted current (Fig. 4h) . Using sentinel - and pre -cue baseline -corrected traces,
glutamate concentration peaks (Fig. 4i) were identified using a MATLAB tool (data points that
were >3 SD above baseline levels and >1 SD above adjacent data points (see Methods). Peaks
of extracellular glutamate at the active electrode surface may reflect the orchestrated yet
asynchronous depolarization of glutamatergic terminals , over several hundreds of milliseconds
and within fractions of micrometers from the electrode surface , and likely sufficient to stimulate
synaptic and extra-synaptic, relatively low-affinity GLU receptors (Hascup et al., 2008; Parikh et
al., 2008; Parikh et al., 2010b; Mattinson et al., 2011; Quintero et al., 2011; Parikh et al., 2014) ,
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(e.g., Clements et al., 1992; Rusakov and Kullmann, 1998; Budisantoso et al., 2013; Matthews et
al., 2022; Mendonca et al., 2022).
-------------------------------------
Insert Figure 4 about here
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Figure 5a shows representative glutamate currents obtained from a GT and a ST during a cued
turn (peaks are symbolized as circles; horizontal bars indicate the timing of the actual turn ). The
recording from the GT indicated a peak for the first data point after cue onset, followed by a
maximum peak. In contrast, in the ST, only the third data point after cue onset was the first peak,
and also the maximum peak, locked to the turn cue, and it was followed by 2 more peaks within
1 s following that first peak. The maximum, turn cue-locked peak concentration was higher in the
GT than the ST. Reward delivery elicited two additional peaks in the ST, but none in the GT.
-------------------------------------
Insert Figure 5 about here
-------------------------------------
LMMs were used to analyze phenotype-dependent maximum peak glutamate concentrations
within 1 s of the onset of turn and stop cues and of reward delivery, time to first peak , and the
number of peaks occurring within 1.5 s of cue onset or reward delivery. Maximum glutamate peak
concentrations recorded during cued turns were significantly higher in GTs than in STs
(phenotype: F(1,28.85)= 8.85, P=0.006, ηp2=0.23; Fig. 5b). In contrast, maximum peak
amplitudes locked to other task events all were significantly higher in STs (missed turns:
F(1,193)= 55.20, P<0.001, ηp2=0.22, Fig. 5c; cued stops: F(1,27.67)= 33.32, P<0.001, ηp2= 0.55,
Fig. 5d; reward delivery (during cued turn trial): F(1,19.28)= 28.88, P<0.001, ηp2= 0.40, Fig. 5e;
errors in response to stop cues were extremely rare and thus not analyzed ). In addition, in GTs,
turn cue -locked increases in glutamate concentrations rose faster (time to first peak:
phenotype: F(1,19.38)= 7.10, P=0.02, η p2=0.27, GTs: 0.69 s; STs: 0.76 s) and peaked less
frequently (number of peaks: F(1,27.81)= 13.80, P<0.001, ηp2=0.33, GTs: 1.28 peaks; STs: 1.59)
than in STs (not shown). Significant phenotype-specific effects on time-to-peak and the number
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of peaks locked to other task events were less consistent (missed turns: faster peak times in GTs
(F(1,193)=5.43, P=0.02) but similar peak numbers; cued stops: similar peak times but more peaks
in GTs (F(1,29.21)= 18.24, P<0.001); reward delivery: similar peak times and numbers; not
shown).
Glutamate trace characteristics predicting cued turns
Glutamate trace characteristics were extracted from 548 recordings of turn cue trials, 364 of which
yielded a turn (GTs: 206, STs: 158) and 184 a miss (GTs: 112, STs: 72) , to determine whether
such characteristics, individually or in combination, disproportionally predicted more cued-
triggered turns in GTs or STs. Contingency tables were used to compare phenotype and outcome-
specific proportions and to compute the probability for turns in GTs relative to STs.
-------------------------------------
Insert Figure 6 about here
-------------------------------------
Turn cue -evoked glutamate peak concentrations greater than 2.8 µM were followed by
disproportionally more turns in GTs than STs ( 2.8-8 µM: P=0.045-2.8 µM) to 1.40 (>8 µM) times as
likely as STs to turn (Fig. 6; concentrations >10 µM yielded contingency table cell counts of n<10
and thus were not included).
Furthermore, if one single glutamate peak occurred following the onset of turn cues, GTs were
1.43 times as likely as STs to turn (P<0.0001). In addition, if only one single glutamate peak
followed the turn cue, increasing amplitudes of these peaks predicted significantly higher relative
probabilities for turns in GTs, plateauing at >4 µM where GTs were 1.73 times as likely as STs to
turn (Fig. 6, top curve; note that all data points of this curve reflect highly significant phenotype -
dependent differences in the proportion of turns and misses).
In contrast to the significantly higher odds for turns in GTs following a single cue-evoked glutamate
peak, following 2 and 3 glutamate peaks (no more than 3 peaks were observed), GTs were only
0.74 times as likely as GTs to turn (or STs were 1.35 times as likely as GTs to turn; P4 µM, GTs
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were as likely as STs to turn (both P>0.85; Fig. 6, bottom curve).
Irrespective of whether a single or multiple glutamate peaks were evoked by the turn cue,
increasing maximum glutamate concentrations increased the relative probabilities of GTs to turn.
This observation was substantiated by the finding that the slopes of the linear regressions of both
curves (top and lower in Fig. 6) were different from zero (both P4 µM, GTs were 1.002
times more likely (or nearly exactly twice as likely) as STs to turn if the number of cue -evoked
glutamate peaks was limited to one.
Together, these analyses of glutamate trace characteristics indicated that, individually, increasing
maximum peak glutamate concentrations and the presence of a single, cue -evoked glutamate
peak strongly increased the relative probability of GTs to execute a cued turn. Moreover, the
combination of these two properties yielded significantly even higher relative turn probabilities in
GTs (Fig. 6). In contrast, the presence of multiple glutamate peaks , GTs were significantly less
likely than STs to turn although, when combined with high (<4 µM) maximum peak concentrations,
turn proportions of the two phenotypes no longer differed significantly. These findings suggest
fundamentally different turn cue-evoked glutamate release dynamics in GTs versus STs, perhaps
involving separate afferent circuitry influencing the excitability of cortico -striatal glutamatergic
terminals. Therefore , we predicted that inhibition of the cortico -striatal neurons affects turning
rates and cued turn -evoked glutamate peaks primarily in GTs, consistent with prior evidence
indicating their relative reliance on top-down, cortico-fugal systems to execute cued responses.
Inhibition of fronto -striatal projection disrupts cued turning and turn cue -evoked GLU in
GTs, but not STs
As described above, in GTs, cued turning was mediated via tightly orchestrated single glutamate
release events that were closely locked to the turn cue, comparable with cue -evoked cholinergic
transients in cortex (Parikh et al., 2007b; Gritton et al., 2016; Howe et al., 2017) and therefore
hypothesized to reflect cortico-striatal activation. In contrast, in STs, more slowly rising, multiple
glutamate release events , as well as the presence of relatively larger reward delivery -locked
glutamate release, may have reflected the impact of intra-striatal circuitry and ascending ,
including dopaminergic, inputs on the excitability of glutamatergic terminals of cortico-striatal
projections (e.g., Tritsch and Sabatini, 2012; Agnoli et al., 2013; Dautan et al., 2020; Moss et al.,
2021). We tested th e hypothesis that turn cue -locked glutamate peaks in GTs reflect cortico -
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striatal activation by using a dual vector approach to express an inhibitory DREADD in fronto -
striatal projection neurons.
-------------------------------------
Insert Figure 7 about here
-------------------------------------
Following PCA screening, GTs (n=12, 6 females) and STs (n=10, 4 females) underwent surgery
to infuse an inhibitory DREADD vector into the prelimbic cortex and a Cre -expressing,
retrogradely transported plasmid into the DMS (see Fig. 7 for a timeline and a schematic
illustration of the dual vector strategy used to inhibit cortico-striatal projections). An additional
group of GTs (n= 5, 2 females) and STs (n= 2, 2 females) received infusions of a mCherry
expressing control vector into the prelimbic cortex, in addition to the Cre-expressing plasmid into
the striatum, to allow for the assessment of potential off-target effects of CNO. Following this
surgery, all rats were trained to CTTT performance criterion. Thereafter, the effects of CNO or
vehicle on CTTT performance were assessed in n=14 rats (9 GTs, 3 females, 5 STs, 4 females ;
Fig. 7c). The remainder of the rats (8 GTs, 4 females, 7 STs, 2 females) underwent a second
surgery to implant glutama te recording electrodes into the DMS (Fig. 7d), followed by the
assessment of the effects of CNO on performance and glutamate transients (Fig. 7d).
CNO disrupts cued turns in GTs. On the first of 4 days of testing of the effects of CNO or vehicle,
and when the vehicle for CNO was administered, the number of turns/turn cue trials and the
number of stops/stop cue trials did not differ significantly between animals without (Fig. 7c) and
with (Fig. 7d) implanted MEAs (both t0.53, at alpha=0.05/2). Thus, for the initial
analysis of the effects of CNO on CTTT performance, data from both subgroups were collapsed.
The effects of CNO/vehicle in GTs and STs on cued turns and cued stops were analyzed
individually, using ANOVA of the effects of phenotype and day (repeated measures ANOVA, with
alpha=0.05/2).
In rats expressing the inhibitory DREADD, administration of CNO reduced the relative number of
cued turns in GTs but not STs (main effect of phenotype: F(1,20)=9.45, P=0.006; main effect of
day: F(3,60)=17.27, P<0.0001; phenotype x day: F(3,60)=16.30, P<0.0001; see Fig. 7e for
multiple comparisons). As reflected by the size of the effect of CNO in GTs (ηp2=0.72), the number
of cued turns in GTs were approximately halved by the administrated of CNO. In contrast, CNO
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did not affect the relative number of cued stops (main effect of day: F(3,60)=0.18, P=0.89; day x
treatment: F(3, 60)=0.26, P=0.86; main effect of phenotype: F(1,20)=5.14, P=0.04, n.s. at
alpha=0.05/2, reflecting a trend for relatively more cued stops in GTs; Fig. 7f). In rats expressing
the empty control vector, CNO affected neither the relative number of cued turns (all F0.17) nor cued stops ((all F0.43; not shown).
CNO attenuates turn cue-locked glutamate peaks in GTs. Guided by the results illustrated in
Figs. 5 and 6 and using identical peak definitions and extraction methods, the analyses of the
effects of CNO on glutamate transients focused on cue -evoked maximum peak concentrations
and the number of peaks. Linear mixed-effects models were used to analyze the effects of CNO
or vehicle on glutamate transients recorded from GTs and STs expressing the inhibitory hM4Di
DREADD or the empty control construct. Glutamate peaks from cued turns, missed turns, cued
stops, and false turns were analyzed (Fig. 7g-j).
Administration of CNO significantly reduced turn cue -locked maximum peak glutamate
concentrations in GTs, but not STs (phenotype x treatment: (F(1,200.79)=18.42, P<0.001; main
effect of treatment: F(1,200.79)=44.76, P<0.001; phenotype: F(1,9.50)=0.73, P=0.41, reflecting
the efficacy of CNO in GTs, yielding statistically similar glutamate concentrations in both
phenotypes: GTs: 8.61±0.69 µM, STs: 7.77±0.70 µM ). Multiple comparisons (shown in Fig. 7g)
indicated that CNO significantly suppressed turn cue -locked maximum peaks in GTs (η p2=0.21),
but not STs, and that following the administration of vehicle, GTs again (see Fig. 5b) exhibited
higher maximum peak levels than STs. CNO reduced maximum peaks in GTs to statistically
similar levels seen in STs irrespective of treatment (Fig. 7g).
As seen before, the number of glutamate peaks seen during cued turns was significantly higher
in STs than in GTs (main effect of phenotype: F(1,11.72)=8.10, P=0.02; GTs: 1.74±0.15 peaks
(M, SEM); STs: 2.38±0.17). CNO administration increased the number of peaks only in GTs, as
was indicated by a significant interaction between the effects of treatment and phenotype and
multiple comparisons (F(1,73)=3.83, P=0.04, ηp2=0.05; GTs/SAL:1.51±0.16 peaks; GTs/CNO:
1.96±0.18; STs/SAL: 2.32±0.18; GTs/CNO: 2.44±0.19; not shown).
Residual turns following CNO in GTs. CNO robustly reduced cued turn rates in GTs (Fig. 7e).
Furthermore, we observed CNO-attenuated maximum glutamate peaks (Fig. 7g) during (residual)
cued turns, raising the question whether these residual turns differed behaviorally from those
seen in vehicle -treated GTs. Thus, we compared residual cued turns following CNO with turns
executed following vehicle administration and, guided by the turn initiation time data shown in Fig.
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3d (baseline performance), focused on this parameter. Based on data from individual trials (Fig.
7h), administration of CNO significantly increased the time GTs took to initiate turns when
compared with STs (LMM; phenotype x treatment: F(1,173.72)=9.70, P=0.002, ηp2=0.05; see Fig.
7h for multiple comparisons). As before (Fig. 3d), GTs took more time to initiate the turn (main
effects of phenotype: F(1,14.02)=9.69, P =0.01, ηp2=0.41; treatment: F(1,173.72)=30.34,
P<0.001, ηp2=0.15).
To gain further insight into the effects of CNO, a second analysis of this data was based on the
average turn initiation times of individual rats following the two treatments (Fig. 7i). Main effects
of phenotype (F(1,13)=7.34, P=0.02, ηp2=0.36) and treatment (F(1,13)=39.82, P<0.001, ηp2=0.75)
reflected that GTs generally took more time to initiate turns than STs, and that CNO generally
increased the time from cue onset to the initiation of turns. Furthermore, following the
administration of CNO, turn initiation times became significantly slower in GTs relative to STs, as
was supported by a significant interaction between the two factors ( F(1,13)=7.15,
p=0.02, ηp2=0.36) and multiple comparisons (Fig. 7i). It is noteworthy that turn initiation times of
all GTs robustly slowed following CNO, by an average of 1.56 s (STs: 0.62 s).
Effects of CNO on glutamate peaks during misses , cued stops and reward delivery. In
contrast to turn-cue evoked maximum glutamate peaks in trials followed by turns, CNO had no
effects on peak glutamate levels in GTs when the cue was not followed by a turn. In STs, however,
CNO significantly reduced maximum peak levels in such trials (phenotype x
treatment: (F(1,133.99)=3.88, P=0.04; Fig. 7j).
There were no effects of CNO on stop cue-locked glutamate peaks (main effects of injection and
interaction: all P>0.37). However, and mirroring a similar finding described above (Fig. 5d) ,
maximum peak glutamate levels were generally higher in STs (main effect of
phenotype: F(1,9.57)=5.42, P=0.04; GTs: 4.79±0.73; STs: 7.33±0.8; Fig. 7k). Neither CNO nor
phenotype affected glutamate maximum peaks in trials in which the stop cue was followed by
false turns (main effects and interaction: all F0.23; Fig. 7 l). As before (Fig. 5e),
glutamate concentrations locked to reward delivery were higher in STs than in GTs (main effects
of phenotype: F(1,10.45)=22.38, P <0.001, ηp2=0.68). CNO administration to both phenotypes
resulted in an extremely small decrease of glutamate peak concentrations (main effect of
treatment: F(1,412.73)=4.83, P=0.03, ηp2=0.01; interaction: F(1,412.729)=1.35, P=0.25).
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Importantly, in control rats expressing the empty construct in cortico -striatal projection neurons,
administration of CNO had no effect on any parameter of cue -locked glutamate peaks (main
effects of treatment and interactions: all F0.33).
-------------------------------------
Insert Figure 8 about here
-------------------------------------
DREADD expression in prelimbic cortex predicts CNO efficacy . The efficacy of the
expression of eGFP in the DMS and of mCherry in the prelimbic cortex was quantified using
categories (illustrated in Fig. 8a -f). Furthermore, we computed the proportion of neurons in the
prelimbic cortex in which both fluorochrome reporters were colocalized (Fig. 8h,i). As the area of
eGFP expression in neuronal soma in the DMS may only partially correspond to the synaptic
space of prelimbic projections, it was not unexpected that DMS eGFP transfection efficacy scores
did not correlate significantly with the efficacy of CNO to reduce cued turns (GTs:
R2=0.01, P=0.84; STs: R2=0.32, P=0.09). in contrast, in GTs, but not STs, the expression efficacy
of mCherry in the prelimbic cortex, that is, of the inhibitory DREADD construct, was significantly
correlated with the efficacy of CNO to attenuate cued turns (GTs: R 2=0.48, P=0.02; STs:
R2=0.06, P=0.51; Fig. 8g). Likewise, in GTs, but not STs, the proportion of neurons expressing
both the reporter for the inhibitory DREADD and the retrogradely transported Cre -expressing
construct was positively correlated with CNO -induced reduction of cued turns (G Ts:
R2=0.77, P=0.0004; STs: R 2=0.06, P=0.51; Fig. 8j). Thus, the degree of CNO -induced inhibition
of prelimbic cortex-DMS projections predicted cued turning efficacy in GTs only.
Discussion
The present experiments were designed to assess the role of cortico-striatal glutamate signaling
for cued movement and movement suppression. Furthermore, by investigating rats selected for
the expression of opponent cognitive -motivational biases, GTs and STs, cue-locked cortico-
striatal glutamate was hypothesized to contribute to cued movements predominantly in GTs. The
impact of individual differences on our findings can be illustrated by contrasting the actual results
with hypothetical findings obtained had experiments been conducted in non-selected rats. 1) Turn
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cue-evoked glutamate concentrations reached higher levels in GTs compared with STs. In
contrast, glutamate concentrations during missed turns, stops, and locked to reward delivery ,
reached significantly higher levels in STs. In the absence of phenotype as a factor, cue -evoked
glutamate concentrations merely would have been found to be higher during turns when
compared with missed turns and stops, but not reward delivery. 2) Turn cue-evoked glutamate
peak concentrations, in conjunction with single spikes, nearly doubled the likelihood for a turn in
GTs relative to STs . In contrast, in conjunction with multiple glutamate spikes , relatively low
glutamate peak concentrations predicted that STs were robustly more likely to turn. In the
absence of phenotype as a factor , some animals would have been found to turn when peak
glutamate concentrations were relatively low but multiple peaks were pres ent, and some when
the concentrations of single spikes reached the same relatively low peak concentrations (Fig. 6,
left half of the upper and lower functions). Consequently, the number of glutamate spikes would
have been concluded to have no impact on turn probability. 3) In GTs, but not STs, i nhibition of
cortico-striatal neurons reduced cued turn rates and turn cue-evoked glutamate peak
concentrations, and it increased the number of glutamate peaks. In the absence of phenotype as
a factor, the effects of CNO would have been found to be extremely variable, and the collective
Results
would not have provided an interpretational framework for such a finding. 4) In GTs, but
not STs, the efficacy of CNO to attenuate cued turns was significantly correlated with transcription
efficacy scores for the inhibitory DREADD , and with the relative number of prelimbic-DMS
neurons expressing the inhibitory DREADD. In the absence of phenotype as a factor, no such
relationships would have been found (both R 2<0.17), limiting the attribution of limited behavioral
and glutamatergic effects of DREADD activation to prelimbic cortex -DMS projections. The se
contrasts between actual and hypothetical results indicate the essential role of the phenotypes
for the discussion of the present evidence.
Goal- and sign-tracking index the presence of larger, opponent cognitive-motivational biases (for
review see Sarter and Phillips, 2018) . Collectively, th e evidence supports the notion that STs
preferably assign motivational significance to reward cues, with the result that they perceive such
cues as rewarding and worth approaching and working for. This bias by STs is illustrated by their
propensity to approach and contact Pavlovian food or drug cues (e.g., Robinson and Flagel,
2009), and by the relatively greater efficacy of cocaine cues to instigate drug taking (e.g.,
Saunders and Robinson, 2011; Yager and Robinson, 2013) . In contrast, GTs are biased toward
an analysis of the behavioral utility of a reward or drug cues. While, in GTs, such cues likewise
evoke an enhanced motivational state and the expectation of reward, GTs tend to not approach
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and contact such cues. Such a top-down bias indexed by goal-tracking can be revealed not only
by the absence of non -instrumental behavior toward reward cues. In contrast to STs, GTs were
able to utilize complex occasion setters predicting the availability of cocaine (Saunders et al.,
2014; Pitchers et al., 2017b) . Research in human s has confirmed the presence of such broad
opponent cognitive -motivational styles indexed by sign - and goal -tracking, particularly the
propensity of STs to attend to cues preferably as a function of cue salience and prediction of
reward (Schad et al., 2020; Duckworth et al., 2022; Colaizzi et al., 2023).
The present findings indicate that turn cue processing in the striatum of GTs is closely controlled
by cortico-striatal activity, and that GTs utilize cues evoking a complex movement more reliably
than STs. These findings co mplement prior evidence from experiments assessing the selection
of cues for extended processing and behavioral control. GTs out -performed STs in tasks taxing
the detection of cues, in part by deploying goal -directed attentional mechanisms to detect cues
and maintain stable task performance (e.g., Paolone et al., 2013; Kucinski et al., 2018; Phillips
and Sarter, 2020; Kucinski et al., 2022) . The present results are consistent with a relatively less
efficacious cue detection process in STs that may be mediated via deficient cortical cholinergic
mechanisms (Paolone et al., 2013; Koshy Cherian et al., 2017; Pitchers et al., 2017a; Kucinski et
al., 2022; Carmon et al., 2023). Consequently, subcortical mechanisms predominately contribute
to behavioral control in STs (see also Flagel et al., 2011; Campus et al., 2019; Schad et al., 2020;
Iglesias et al., 2023).
In GTs, inhibition of prelimbic-DMS projections attenuated cued turns and associated glutamate
concentrations. In contrast, suppression of movement, as seen during cued stops, and associated
glutamate release dynamics , remained unaffected by CNO and, therefore, may not depend on
cortico-striatal processing of movement cues (see also Vandaele et al., 2019; Cruz et al., 2022) .
In GTs, turn cue-evoked glutamate concentrations as well as the presence of single peaks may
be speculated to be secondary to the cue detection -mediating generation of single cholinergic
transients in prelimbic cortex and resulting high-frequency oscillations (Gritton et al., 2016; Howe
et al., 2017). In the DSM, single high-amplitude glutamate transients from cortical afferents may
recruit multiple populations of interneurons and striatal output neurons, thereby forming, for a
precise period of time, fronto-striatal cell assemblies to force cue-associated action selection (see
also Hart et al., 2018a; Hart et al., 2018b; Oberto et al., 2022).
Cortico-striatal, glutamatergic terminals are also recruited, directly and indirectly via striatal
interneurons, by striatal dopaminergic afferents, thereby supporting bidirectional glutamatergic -
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dopaminergic interactions and allowing reward expectation and action outcome to influence the
glutamatergic representation of movement cues (Bamford et al., 2004; Agnoli et al., 2013; Kosillo
et al., 2016; Cai and Ford, 2018; Moss et al., 2021; Choi et al., 2023; Holly et al., 2024) . Such
striatal control of cortico-striatal terminals , primarily via cholinergic and dopaminergic
heteroreceptors (for review see Lovinger et al., 2022) , may preferentially yield suppression of
action in STs. This view is consistent with several findings and considerations. 1) G lutamate
concentrations in STs were relatively higher during stops, irrespective of the validity of stops (false
stops or stop cue-evoked stops). 2) The presence of multiple glutamate peaks in STs (a second
or third peak occurred on average 1.58±0.39 s and 1.83±0.25 s (M, SD), respectively, following
cue onset), may reflect relatively slow, reverberating interactions between striatal interneurons,
dopamine signaling, and cortico-striatal glutamate release (e.g., Dorst et al., 2020; Frost Nylen et
al., 2021). 3) Inhibition of the prelimbic-DSM pathway impacted neither turn cue-locked glutamate
release in STs nor cued stops or stop cue -locked glutamate release in either phenotype. 4)
Reward delivery-locked glutamate concentrations were higher in STs than GTs. Thus, in STs, the
relatively lasting glutamatergic signal of the turn cue may be speculated to primarily signal the
dopaminergically-mediated expectation of reward, and also the heightened perceptual value of a
reward predicting cue, that is, its incentive salience (see also Pitchers et al., 2017a; Saunders et
al., 2018; Iglesias et al., 2023; Bernklau et al., 2024).
Given that CNO did not attenuate turn cue-evoked glutamate concentrations in STs, the neuronal
source for striatal information about the sensory properties of the cue remains unclear. Other
striatal afferent systems, originating from midbrain cholinergic and glutamatergic regions (Dautan
et al., 2014; Assous et al., 2019; Dautan et al., 2020), or thalamus (Diaz-Hernandez et al., 2018),
may serve as alternative sources to “import” post-perceptual cue information into striatal circuitry
to support well-practiced, habitual cued action in STs and action suppression in both phenotypes.
The present results contribute to bio-behavioral conceptualizations of individual differences in the
vulnerability for compulsive drug taking (e.g., Volkow et al., 2006; Robbins et al., 2012; Marhe et
al., 2013; Kilts et al., 2014; George and Koob, 2017; Pitchers et al., 2018) . In contrast, the
significance of cognitive -motivational endophenotypic traits such as goal - and sign-tracking for
neurological disorders has yet to be explored (but see Deik et al., 2012; Kucinski et al., 2018) .
Consistent with the view that striatal pathology contributes little to the explanation of individual,
clinical severity of PD (Johansson et al., 2024), our findings predict a greater vulnerability of PD
patients who preferentially utilize cortico -striatal mechanisms to process cues - that is, GTs - for
cholinergic loss-associated cued movement control and falls (Sarter et al., 2014; Sarter et al.,
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2021). In contrast, STs generally may be less efficient in executing cued movements, particularly
in situations featuring complex and competing movement cues (e.g., Beaulne-Seguin and Nantel,
2016). As we demonstrated here, the investigation of the impact of endophenotypic indices that
predict individual differences in fundamental brain function may be necessary to reveal potently
predictive neuronal and cognitive markers of psychiatric and neurological disease vulnerability.
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Figure Legends
Figure 1
a Distribution of PCA scores, from a total of N=378 rats (215 females) used for the analysis of
CTTT performance and associated glutamatergic transients. Final phenotypic classification was
based on averages from the 4th and 5th test session (rats with intermediate PCA scores, INs, are
not shown). The photos on the right depict lever (CS) contact, indicative of sign-tracking behavior
(top) versus CS -triggered food port entry, signifying goal -tracking behavior (bottom). The
distribution of PCA scores was unaf fected by sex ( b) but differed among rats obtained from the
two vendors (c). Relatively more rats from Inotiv were classified as STs while rats from Taconic
tended to emerge relatively more often as GTs. The distribution of vendor -specific PCA scores
was not affected by sex.
Figure 2
Illustration of the CTTT, trial timeline, and of a cued turn. a shows a lateral view of 1.5 -m long
CTTT, with Faraday shielding comprised of copper wire mesh surrounding the motor and wooden
frame of the Plexiglas -lined enclosure (both grounded), 2 mounted cue lights on both ends, 1
mounted audible device centered (not visible here), and a copper reward port installed on either
end of the treadmill. Web cameras were placed on each side of the treadmill for off-line analysis
of the rat’s performance. b Trial events and timeline. The CTTT required rats to walk on a treadmill
(walking speed: 9.6 cm/s). Presentation of a turn or stop cue (tone or light for 2 s), indicated that
the treadmill stopped 1 s later, and restarted after a 5-s pause, in the reverse or same direction,
respectively, Successful turns and stops without turns, respectively, were rewarded by delivering
a 45 mg banana pellet, on average 3.6 s following cue offset (see green square in b). c shows
photographs of a cued turn, initiated within the first second of cue onset (see lines connecting the
individual photos to the task timeline in b). Successive presentation of cues was separated by a
variable intertrial interval (ITI) of 60±45 s during which the rat continued walking the treadmill.
Figure 3
CTTT acquisition and asymptotic performance by GTs (n=29, 13 females) and STs (n=22, 12
females). a The number of training sessions to reach CTTT criterion performance, defined as
70% correct responses to either cue for two consecutive days, neither differed between the
phenotypes nor the sexes. However, baseline performance, based on data from four test sessions
conducted after rats had reached criterion performance, indicated that GTs scored more cued
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turns than STs (main effect of phenotype; GTs: 0.80 (M) cued turns/trials; STs: 0.73). Moreover,
a main effect of day reflected that rats performed more cued turns on day 3 than on day 1 (post
hoc Bonferroni test; b; 1note that b and c show response ratios but ANOVAs were conducted
using arcsine transformed data because ratio data violated homoscedasticity). c The relative
number of cued stops did not differ between the phenotypes. There were no main effects of sex
and no significant interactions between the effects of phenotype, day and sex on either measure.
d Relative to the time of cue onset, GTs initiated and completed cued turns later than STs.
Reflecting the parallel effects of phenotype on initiation and completion times, the act ual time
needed to complete turns did not differ between the phenotypes (not shown; *,**,***: P<0.05, 0.01,
0.001).
Figure 4
Electrochemical measurement scheme, electrode calibration, sentinel correction and glutamate
peak identification. a Schematic illustration of a ceramic backbone with four platinum-iridium (Pt/Ir)
recording sites, organized in two pairs, with each recording site measuring 333 µm long and 15
µm wide. The upper pair was fabricated to measure currents reflecting GLU concentration (red,
also b), while the lower pair served as sentinels for background current recording and subtraction
(yellow, also c). Glutamate oxidase (GO) was immobilized onto the upper ( b), but not lower ( c),
pair of recording sites. After GO coating, a non -conducting polymer, m-(1,3)-phenylenediamine
(mPD), was electroplated onto both sites to prevent the transfer of small electroactive organic
molecules like dopamine to the Pt sites. Application of a 0.7 V constant potential versus a n
Ag/AgCl reference electrode (not shown) served to oxidize hydrogen peroxide at individual
recording sites (e.g., Burmeister et al., 2000; Parikh et al., 2010b), yielding current proportional to
the concentration of GLU at the recording site. d In vitro calibration (representative example; see
Table 1 for calibration data) indicated the sensitivity, linearity of the response to increasing
concentrations of glutamate, and selectivity of GO -coated recording sites (red). Sentinel sites
typically did not respond to glutamate and ascorbic acid (AA) and exhibited a relatively small
response to the addition of dopamine (DA) to the bath. e Electrodes were implanted into the DMS;
the circles in e indicate the location of microelectrode tips in this area (red circles: placements in
rats which were recorded during CTTT performance; purple circles: placements in rats in which
fronto-striatal projections were silenced). f Example of a turn -cue evoked current recorded via
GO-coated recording sites and, g, via sentinels. The subtracted trace is shown in h. i Glutamate
trace (sentinel- and baseline-corrected) exemplifying the identification of peaks (red dots) using
the PeakDet tool in Matlab. As detailed in Methods, peak identification required GLU levels above
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3 SDs of pre -cue baseline levels and 1 SD (of baseline levels) above the preceding and
subsequent data point.
Figure 5
GLU maximum peak concentrations locked to turn and stop cues and reward delivery. a shows
representative recording traces of a GT (blue, squares) and a ST (red, triangles) during a cued
turn. The time of c ue onset, offset, and reward delivery are indicated by arrows, and the actual
timing of the turn by horizontal bars. Identified peaks are symbolized by circles. Note that following
turn cue onset, already the first subsequent data point from the GT was a peak, followed by one
more peak that a lso constituted the maximum peak locked to the turn cue . In contrast, in the
recording from the ST, only the third data point following cue onset was a peak, and it also
constituted the maximum peak. Moreover, the 6th and 7th data point following cue onset were also
peaks in the ST, reflecting the return to baseline GLU levels in between the first and the
subsequent, turn cue -locked peaks. Reward delivery did not elicit a peak in the GT but was
followed by two peaks in the ST. LMM-based analysis of GLU traces collected from N=30 rats (15
females) indicated significantly, and robustly ( ηp2=0.23) higher GLU maximum peaks in GTs
following turn cues and when followed by a turn ( b). In contrast, maximum GLU concentrations
were higher in STs during all other response categories (missed turns, c; cued stops d; errors
following stop cues were extremely rare and thus not analyzed) and following reward delivery
during cued turn trials (e; b-e depict estimated marginal means (EMMs), and 95% CI; main effects
of phenotype: **,***: P<0.01, 0.001).
Figure 6
Relative probabilities for cued turns in GTs given the presence of individual and combined
properties of turn cue -evoked glutamate peaks (based on a total of 548 traces, 364 recorded
during cued turns and 184 during misses, 318 from GTs and 230 from STs). The ordinate depicts
relative probabilities derived from contingency table analyses. A value of 1 would indicate that
GTs were as likely as STs to turn (inserted line), while a value of 2 that GTs were twice as likely
as STs to turn. For each value, the associated significance level derived from contingency table
analyses is indicated by the symbol color (no fill, not significant, n.s.; blue, P<0.05; green, P<0.01;
magenta, P<0.001; red: P<0.0001). Regardless of other glutamate trace properties, increasing
maximum peak concentrations, beginning with 2.8 µM g lutamate, yielded significantly different
proportions of turns and misses in GTs and STs and therefore rising relative probabilities for GTs
to execute a turn (“GLU max peaks ≥x”; the slope of the linear regression of all three curves was
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35
significantly different from zero; see Results). For example, for maximum peak concentrations ≥4
µM, GTs were 1.24 times as likely as STs to turn. The presence of a single turn cue-evoked peak,
regardless of other trace properties, strongly increased the probability for GTs to turn (see
Results). In conjunction with increasing amplitudes of these peaks (“1 peak only ∪ ≥x”), these
probabilities did further increase, reaching, for example, 1.73 for glutamate concentrations ≥4 µM.
In striking contrast, and reg ardless of other trace properties, the presence of 2 or 3 turn cue -
evoked peaks (no more than 3 peaks were observed) significantly lowered the relative probability
for a turn in GTs below 1 or, conversely, indicated that STs were 1.35 times as likely to turn as
GTs (see Results). However, in conjunction with rising max amplitude threshold levels (“2 and 3
peaks ∪ max peaks ≥x”), the relative probabilities of GTs to turn increased, so that, for example,
STs were only 1.17 times as likely as STs to turn at maximum peak concentrations ≥ 6 µM
glutamate, no longer reflecting dissimilar proportions in the two phenotypes. The vertical brackets
on the right symbolize significant differences between the relative probabilities of the three trace
characteristics (H(3)=33.41, P<0.0001; Kruskal–Wallis test; multiple comparisons: *,****, P<0.05,
0.0001).
Figure 7
Timeline of experimental procedures and effects of CNO on CTTT performance. a: Following
initial handling and screening to identify the rat’s phenotype (17 GTs, 7 females; 12 STs, 6
females), rats were infused with either a Cre-dependent inhibitory DREADD or the empty control
vector (both expressing mCherry ; b) into the lower layers of the prelimbic cortex, and a
retrogradely transported, Cre -expressing plasmid into the DMS (expressing eGFP). These rats
continued to undergo CTTT performance training, followed either by ( c) a test of the effects of
vehicle or CNO (the blue syringes symbolizing CNO administration) or by (d) implantation of an
MEA for the measurement of glutamate concentrations into the mediodorsal stratum. Following
recovery from that surgery, the effects of CNO and vehicle on performance and performance -
associated glutamate concentrations were assessed. In GTs, administration of CNO significantly
reduced the relative number of cued turns (e), but not cued stops (f; graphs show individual data,
mean and 95% CI; post hoc multiple comparisons: ***,****: P<0.001, 0.0001, Tukey’s Honest
Significant Difference test). CNO had no effects on cued turns or stops in rats expressing an
empty control vector ( not shown; see Results). In GTs, CNO administration attenuated cue-
locked maximum peak glutamate concentrations during (residual) cued turns ( g) and also
increased the number of peaks (not shown). Residual turns too k significantly more time to be
initiated in GTs than STs, as was indicated by an analysis based on turn initiation times from
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individual trials (h) and individual rats (the lines in i depict averaged individual turn initiation times
following saline (SAL) and CNO). Note that CNO increased initiation times of residual turns in all
GTs. CNO administration did not affect maximum peak glutamate concentrations in GTs during
missed turns (j), cued stops (k), and false turns (l; except for I, graphs depict individual data points,
EMMs, and 95% CI; multiple comparisons: *,**,***: P<0.05, 0.01, 0.001).
Figure 8
Expression of eGFP (green channel), indicating the expression of the retrograde, Cre-expressing
vector, in the DMS (DMS) and, following retrograde transport, in the medial frontal cortex. The
presence of the amplified mCherry fluorescent reporter signal (red channel) in cortex indicated
the expression of the inhibitory hM4Di DREADD vector (see also Fig. 7b). Illustration of
expression efficacy ratings for eGFP in the DMS ( a,b) and of mCherry in the prelimbic cortex
(prelimbic cortex ; c,d), with a top score of 5 indicating complete or near -complete expression
exclusively in the DMS projection field of prelimbic cortex efferent neurons (Mailly et al., 2013)
and prelimbic cortex, respectively. The example of eGFP expression in the DMS in e (cc, corpus
callosum) received a score of 2 (illustrated in a) because the expression field was located in part
lateral to the prelimbic cortex projection field. f depicts an example of mCherry expression in the
prelimbic cortex that was assigned a scores of 4 as it was restricted to the deeper layers in the
prelimbic cortex and extended dorsally into cingulate cortex. In GTs, but not STs, mCherry
expression scores were significantly correlated with the efficacy of CNO to reduce cued turns (g).
h depicts the retrogradely transported eGFP and the expression of mCherry, including the co -
expressing of both fluorochromes, primarily in layer 5 of the prelimbic cortex . The bright
rectangular region in h is enlarged in i and illustrated neurons co-expressing nucleolar eGFP and
cytoplasmic mCherry (white arrows). In GTs, but not STs, the proportion of double -labeled
neurons in prelimbic cortex was significantly correlated with the efficacy of CNO to attenuate cued
turns (j).
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Table 1. Electrode in vitro calibration characteristics
Sensitivity
(Slope) to
Glutamate
Selectivity for
Glutamate over
Ascorbic Acid (AA)
Limit of
Detection of
Glutamate
Linearity of
Response
(R2)
Minimum Criteria >5 pA/μM >50:1
glutamate:AA 0.95
Measured (N=30;
M±SEM): 11.52±0.10 132.08±2.41 0.31±0.01 0.99±0.001
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Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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