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. 2022 May 12;33(5):1913–1924. doi: 10.1093/cercor/bhac182

The medial orbitofrontal cortex governs reward-related circuits in an age-dependent manner

Maxine K Loh 1,2,✉, J Amiel Rosenkranz 3,4
PMCID: PMC9977359  PMID: 35551358

Abstract

Nucleus accumbens (NAc) neurons integrate excitatory inputs from cortical and limbic structures, contributing to critical cognitive functions, including decision-making. As these afferents mature from adolescence through adulthood, incoming signals to the NAc may summate differently between age groups. Decision-making evaluates both reward and risk before action selection, suggesting an interplay between reward- and risk-related circuits. Medial orbitofrontal cortex (MO)-NAc circuits permit risk assessment behaviors and likely underlie risk information incorporation. As adolescents make reward-centric choices regardless of risk, we hypothesized the impact of MO activity alters reward-related NAc circuits in an age-dependent manner. To test this hypothesis, we used single-unit electrophysiology to measure MO train stimulation’s effect on reward-related pathways, specifically the basolateral amygdala (BLA)-NAc circuit, in adult and adolescent rats. MO train stimulation altered the strength but not the timing of BLA–NAc interactions in a frequency-dependent manner. In adults, MO train stimulation produced a frequency-dependent, bidirectional effect on BLA-evoked NAc AP probability. Contrastingly, MO train stimulation uniformly attenuated BLA-NAc interactions in adolescents. While the mature MO can govern reward-related circuits in an activity-dependent manner, perhaps to adapt to positive or negative decision-making outcomes, the adolescent MO may be less able to bidirectionally impact reward-related pathways resulting in biased decision-making.

Keywords: Basolateral amygdala, Adults, Adolescents, Nucleus accumbens, Electrophysiology

Introduction

Survival is dependent on appropriate decision-making, the process of identifying the rewards and risks of every available option, weighing their perceived worth, and selecting the optimal choice. The nucleus accumbens (NAc) supports reward directed actions and integrates multiple excitatory inputs (O’Donnell and Grace 1995; Finch 1996; Groenewegen et al. 1999; McGinty and Grace 2009a; Asher and Lodge 2012), which are ultimately communicated to downstream motor regions (Mogenson et al. 1980). As efferents from cortical and limbic structures carry context-, risk-, and reward-related information, interplay between their incoming signals at the NAc likely contributes to action selection during decision-making.

NAc neuron activity reflects risky behaviors (Matthews et al. 2004; Knutson et al. 2008; Rao et al. 2008; Samanez-Larkin et al. 2010) and is regulated by cortical activity in a top-down manner (Wang et al. 2019). Risk information is likely incorporated through medial orbitofrontal cortex (MO) projections to the NAc. The MO contributes to behavior guided by reward probability (Stopper et al. 2014; Dalton et al. 2016; Jenni et al. 2021) and sends dense, descending inputs into the NAc (Hoover and Vertes 2011). Additionally, disrupting MO-NAc pathways decrease specific risk assessment behaviors and induce suboptimal decision-making, suggesting MO-NAc efferents aid the incorporation of risk information and use previous outcome history to inform future decisions (Jenni et al. 2022; Loh et al. 2022).

Decision-making circuitry likely includes the interaction of risk- and reward-related pathways to reflect the integration of risk and reward information. Excitatory projections from the basolateral amygdala (BLA) to the NAc have been shown to interact with medial prefrontal cortex (mPFC)-NAc inputs (McGinty and Grace 2008, 2009b) and are crucial for reward-learning. BLA-NAc circuits permit the learning of reward-predictive cues and generate reward-seeking behavior (Cador et al. 1989; Everitt et al. 1991; Di Ciano and Everitt 2004). The excitation of NAc neurons by BLA inputs facilitates reward-seeking behavior, and disruption of this pathway impairs reward-directed behaviors (Ambroggi et al. 2008).

Limbic circuits develop earlier than cortical areas (Galvan et al. 2006), which are thought to underlie reward-biased decision-making during adolescence. These findings suggest NAc neurons encode cues to influence reward-seeking behavior and synaptic activity from BLA may be differently affected by cortical activity during adolescence relative to adulthood. The physiological interaction of BLA and MO afferents in NAc neurons may be a critical mechanism that supports action selection in risk-based decision-making. This can be measured in vivo through the effect of repeated MO activation on NAc neuronal responses to BLA stimulation. Here, we examined BLA-evoked NAc firing and tested the effects of MO train-stimulation on BLA-evoked NAc firing in both adolescents and adults.

Methods and materials

Subjects

Adult (post-natal day (PND) 70-90) and adolescent (PND 30-40) male Sprague Dawley rats (Envigo, Indianapolis, IN) were group-housed and provided ad libitum access to food and water. PND 28-42 defines rat adolescence based on growth spurt timing, emergence from nest habitat, sexual organ development, and peak social behavior/exploration that is homologous to human behavior (Clermont and Perey 1957; Kennedy and Mitra 1963; Döhler and Wuttke 1975; Galef 1981; Spear 2000). Thus, the PND 30-40 range encapsulates the early to mid-adolescence. All subjects were habituated to the animal facility for one week before experimentation. The colony was maintained on a twelve-hour reverse light cycle, with lights off at 8:00 A.M. Recordings occurred after 9:00 A.M., during the lights off phase. All experiments were conducted under the National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by Rosalind Franklin University of Medicine and Science’s Institutional Animal Care and Use Committee.

Electrophysiology

Naïve subjects were anesthetized with urethane (1.5 g/kg, intraperitoneal injection) and placed on a stereotaxic device (Kopf Instruments, Tujunga, CA). Subject body temperature was monitored through a rectal thermometer and maintained between 36–37°C via a heating pad with a temperature controller (Model TC-1000, CWE Inc, Ardmore, PA). Coordinates used for adult electrophysiology were drawn from a flat skull utilizing the intersection of Bregma and the sagittal suture (MO: A/P + 4.25 mm, M/L + 0.4 mm, D/V −4.2 mm; NAc: A/P + 1.55 mm, M/L + 1.6 mm, D/V −6.0—8.0 mm; BLA: A/P −2.8 mm, M/L + 4.75 mm, D/V −8.6 mm). Coordinates were adjusted for adolescent rats based on the rostral-caudal distance between Bregma and Lambda sutures. Burr holes overlying the MO, NAc, and BLA were drilled into the skull, and the underlying dura was removed. Concentric bipolar stimulation electrodes (MicroProbes, Gaithersburg, MD) were lowered into the MO and BLA then left to stabilize for a minimum of 45 minutes before recording (Fig. 1). Single-barrel electrodes were constructed from glass pipettes (World Precision Instruments, Sarasota, FL) and pulled using a vertical microelectrode puller (PE-2; Narishige, Tokyo, Japan), and broken under a microscope to produce a ~2 μm diameter tip. The electrode was filled with 2% Pontamine Sky Blue in 2 M NaCl and then slowly lowered into the NAc via a hydraulic microdrive (Fig. 1; Model MO-10, Narishige, East Meadow, NY).

Fig. 1.

Fig. 1

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Schematic of stimulation and recording sites. Stimulation electrodes (black) were placed in the medial orbitofrontal cortex (MO) and basolateral amygdala (BLA). MO and BLA regions project into the nucleus accumbens (NAc), where BLA-evoked action potentials were recorded via glass electrode (gray).

Signals were routed to a head-stage connected to a preamplifier and then filtered by an amplifier (Model 1800; A-M Systems, Sequim WA) at 300 Hz (low cut-off frequency) and 5 kHz (high cut-off frequency) and delivered simultaneously to an oscilloscope (Model 2532 BK Precision, Yorba Linda, CA) and an audio monitor (Model AM8 Grass Instruments, West Warwick, RI). Amplified outputs were digitized through an interface (5–10 kHz; Model ITC-18, HEKA, Bellmore, NY) and fed to a personal computer (Mac Pro/2.8 Apple, Cupertino, CA), monitored using recording software (Axograph X, Sydney, Australia), and stored on a hard disk for off-line analysis.

BLA-evoked NAc neuron identification

A cell-searching procedure (McGinty and Grace 2009b, 2009a) was used to identify NAc neurons receiving BLA input. Single stimulation pulses were delivered to the BLA (0.25 ms, 0.6 mA, 0.2 Hz) while slowly advancing the recording electrode through the NAc. Neurons in the NAc were only recorded if they displayed an excitatory response to BLA stimulation and its action potentials (APs) met a > 3:1 signal-to-noise criteria. Excited NAc neurons were identified by the presence of biphasic APs in response to BLA stimulation. Because ~95% of NAc are medium spiny neurons (MSNs) (Meredith and Totterdell 1999), MSNs were likely the vast majority of our recorded neurons. NAc neurons with steady, spontaneous spiking (Wilson et al. 1990) or highly excitable NAc neurons that responded with three or more APs in response to a single BLA stimulation pulse (Mallet 2005) were considered as likely interneurons and were not included in the analysis.

Baseline recordings of BLA-evoked NAc neurons

We measured the NAc neuronal evoked probability from increasing BLA stimulations intensity (0.1–0.9 mA, 0.25 ms, 0.2 Hz). For each tested stimulation intensity, the BLA was stimulation for at least 30 trials. Response probability was calculated by the number of evoked APs divided by the number of stimulation trials. Neurons were incorporated in the analysis if their mean evoked AP latency for BLA inputs was <25 ms at all tested stimulation intensities. The responses to threshold current intensity, the stimulation intensity that evokes between a 40 and 60% response probability, served as a baseline to MO stimulation treatments.

MO Stimulation on BLA-evoked NAc firing

As orbitofrontal cortex (OFC) neurons fire at various frequencies in response to sensory information and during reward-related behaviors (Ramus and Eichenbaum 2000; Burton et al. 2014; Lopatina et al. 2016), we tested the impact of MO train subthreshold stimulation at different physiologically relevant frequencies on threshold BLA-evoked NAc firing. mPFC afferents to NAc are glutamatergic (Brenhouse et al. 2008) and can induce AP firing in NAc neurons (McGinty and Grace 2009b). Therefore, MO pulses were delivered at stimulation intensities subthreshold to NAc AP generation to avoid activating potentially confounding MO-evoked NAc AP responses (0.1–0.3 mA, 0.1 ms), but high enough to observe a small amplitude evoked field potentials indicative of afferent activation. At least 30 trials at each train frequency were tested, and AP probabilities (AP/stimulation trials expressed as %) were calculated for each train frequency. As some NAc cells are bistable neurons that can shift into the up or down state (O’Donnell and Grace 1995), BLA-evoked NAc threshold intensity was monitored between stimulation protocols and adjusted to ensure the BLA stimulation was delivered at a threshold current intensity.

MO stimulation included the delivery of 10-pulses at 5, 10, 20, 40, or 60 Hz (0.3 mA, 0.1 ms) with the last pulse of the 10-pulse train following BLA stimulation by 1 ms to synchronize the incoming inputs into the NAc neuron. MO neurons projecting to the NAc have an antidromic AP latency of 12 ± 1 ms in adults and 11 ± 2 ms in adolescents (Loh and Rosenkranz 2021). BLA-NAc projections have similar antidromic AP latencies of 12.1 ± 0.9 ms (McGinty and Grace 2009b). The order of tested train stimulation frequencies were counterbalanced between BLA-evoked NAc neurons within subjects and between subjects.

Histology

The recording electrode’s final position was marked by an iontophoretic ejection of Pontamine (−30uA, 30-minutes). Subjects were euthanized and their brains fixed in 4% paraformaldehyde overnight. The following day, brains were transferred to 0.1 M phosphate buffered saline and sliced on a Leica VT1000 S vibratome (Leica Biosystems, Buffalo Grove, IL). Sections containing Pontamine or stimulation electrode track marks were mounted onto slides for subsequent Nissl staining. The location of the recording and stimulation electrodes were determined via rat brain atlas (Paxinos and Watson 2007). Neuron locations and stimulation sites were reconstructed from the location of the dye deposit and residual track markings respectively (Fig. 2).

Fig. 2.

Fig. 2

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Location reconstruction of BLA-responsive NAc neurons and BLA and MO stimulation sites from adolescent and adult recordings. Pontamine dye was injected at the last recorded active NAc neuron, and tissue slices were stained with Cresyl-violet. Residual markings from stimulation probes were visualized from Nissl stain. The locations of recorded neurons and stimulation sites were verified based on the post-recording histological reconstruction (adolescent, PND 30–40, open circle; adult, PND 70–90, closed square).

Data analysis and statistics

We analyzed our results and constructed plots using PRISM 7.0 statistical software (GraphPad, La Jolla, CA), with data and figure bars expressed as the group mean ± standard error of the mean (SEM). Statistical significance was set at P < 0.05 to determine differences between experimental conditions. AP probability, latency, and jitter (the period between earliest and latest evoked response) were measured. Comparisons between adult and adolescent BLA-evoked NAc AP latency and jitter were assessed via unpaired t-tests. Comparisons between baseline BLA-evoked NAc firing to BLA-evoked NAc firing post-MO stimulation at various frequencies and changes to BLA-evoked NAc firing between age-groups were analyzed using a two-way repeated measures (RM) analysis of variance (ANOVA) with Holm–Sidak’s multiple comparisons post hoc if appropriate. To assess differences in shifts in BLA-evoked NAc firing within age groups, a one-way RM ANOVA was utilized and followed with Tukey’s multiple comparisons post hoc if appropriate. In many cases, complete inhibition of BLA-evoked NAc firing by MO train stimulation was observed, and therefore, NAc AP latency and jitter could not be quantified. Thus, shifts or baseline to post-MO stimulation measurements of AP latency and jitter were analyzed using a one-way ANOVA or two-way ANOVA, respectively.

Results

Properties of BLA-evoked NAc firing

NAc neurons responsive to BLA stimulation were identified, indicated by orthodromic responses following the BLA stimulation artifact (Fig. 3A). BLA-responsive NAc neurons were similarly excitable between age groups, sharing comparable evoked AP probabilities across BLA stimulation intensities (Fig. 3B; no significant main effect of age: F(1, 26) = 0.0909, P > 0.05, two-way ANOVA). In adults, BLA-evoked NAc average AP latency was 15.1 ± 0.7 ms in response to BLA threshold stimulation (Fig. 3C), which is consistent with previous studies measuring BLA-NAc monosynaptic, orthodromic transmission (McGinty and Grace 2009b). In adolescents, BLA-evoked NAc average AP latency was 15 ± 1 ms in response to BLA threshold stimulation, which was not significantly different from adult responses (Fig. 3C; P > 0.05, unpaired t-test). At threshold stimulation, BLA-evoked NAc AP jitter was also comparable between age groups (Fig. 3D; adults: 3.0 ± 0.3 ms, adolescents: 3.3 ± 0.4 ms, P > 0.05, unpaired t-test).

Fig. 3.

Fig. 3

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Characterizing BLA-evoked NAc firing. (A) BLA-responsive NAc neurons were identified by visualizing NAc action potentials evoked from BLA stimulation. BLA stimulation was delivered at increasing current intensities (shown: 0.3, 0.5, and 0.7 mA) for 30 sweeps at 0.2 Hz. This protocol was used to calculate the evoked response probability (%) from each stimulation intensity and the threshold current, the stimulation intensity required to evoke a ~ 50% AP probability (scale bars, 0.1 mV/10 ms). (B) At equivalent intensities, BLA-evoked NAc AP probability was similar between adolescents and adults. (C) At threshold intensity, BLA-evoked NAc average AP latency was not significantly different between adults and adolescents. (D) At threshold intensity, BLA-evoked NAc AP jitter was not significantly different between adults (adults n = 19; adolescents n = 10).

MO stimulation governs the strength of BLA-NAc interactions in adults

We measured the effects of MO train stimulation, delivered between 5 and 60 Hz, on BLA-evoked NAc firing in adults (Fig. 4A). MO train stimulation altered BLA-evoked NAc probability and produced opposing effects dependent on the train frequency (Fig. 4B; main effect of MO train stimulation: F(1, 18) = 3.732, P = 0.07; main effect of MO train frequency: F(4, 72) = 14.45, P < 0.000001; MO train stimulation × MO train frequency interaction: F(4, 72) = 17.39, P < 0.000001, two-way RM ANOVA). MO train stimulation delivered at 5 and 10 Hz facilitated BLA-evoked NAc AP probability (Fig. 4B and Table 1; 5 Hz: P < 0.05; 10 Hz: P < 0.01, Holm–Sidak’s multiple comparisons test), whereas MO trains delivered at 20, 40, and 60 Hz diminished BLA-evoked NAc AP probability (Fig. 4C and Table 1; 20 Hz: P < 0.05; 40 Hz: P = 0.000005; 60 Hz: P < 0.000005, Holm–Sidak’s multiple comparisons test). Train stimulation did not influence BLA-evoked NAc AP timing or jitter (Fig. 4C and D; average AP latency: no significant main effect of MO train stimulation: F(1, 148) = 0.0515, P > 0.05; no significant main effect of MO train frequency: F(4, 148) = 0.59, P > 0.05; AP jitter: no significant main effect of MO train stimulation: F(1, 136) = 0.7634, P > 0.05; no significant main effect of MO train frequency: F(4, 136) = 0.6836, P > 0.05, two-way ANOVA).

Fig. 4.

Fig. 4

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MO train stimulation bidirectionally governs BLA-evoked NAc AP probability in adults. (A) Stimulation protocols were used to identify the effects of MO 10-pulse train stimulation on BLA-evoked NAc firing. Superimposed traces from ten stimulation trials from each MO train stimulation protocol. 10-pulses were delivered to the MO (white triangle) at 5, 10, 20, 40, and 60 Hz at subthreshold intensity before BLA (gray triangle) threshold stimulation (scale bar, 10 ms/0.1 mV). (B) MO train stimulation had a frequency-dependent effect on BLA-evoked NAc AP probability. At 5 and 10 Hz, MO train stimulation facilitated BLA-evoked NAc AP probability. MO train stimulation delivered between 20 and 60 Hz diminished BLA-evoked AP probability (n = 19). (C and D) MO train stimulation did not alter mean BLA-evoked NAc AP latency or AP jitter (AP latency: 5 and 10 Hz n = 19, 20 Hz n = 17, 40, and 60 Hz n = 12; AP jitter: 5 Hz n = 18, 10 Hz n = 19, 20 Hz n = 16, 40, and 60 Hz n = 10). (E) Shifts to BLA-evoked NAc probability at different frequencies were significantly different from one another (n = 19). (F and G) MO train frequency-driven shifts to BLA-evoked NAc latency and jitter were not significantly different from each other (AP latency: 5 and 10 Hz n = 19, 20 Hz n = 17, 40, and 60 Hz n = 12; AP jitter: 5 Hz n = 18, 10 Hz n = 19, 20 Hz n = 16, 40, and 60 Hz n = 10). Baseline to post-MO stimulation comparisons: *P < 0.05, **P < 0.01, ****P ≤ 0.000005. Effects of MO 10-pulse stimulation frequency comparisons: ***P < 0.005–5 Hz; #P < 0.05, ##P < 0.01, ###P < 0.005–10 Hz; &P < 0.05–20 Hz.

Table 1.

MO train stimulation alterations of BLA-evoked NAc AP probability in adult subjects.

Adults
MO train frequency (Hz) Baseline: BLA-NAc AP probability (%) Post-MO train: BLA-NAc AP probability (%) Δ in BLA-NAc AP probability (%)
5 50.3 ± 1.5 63.4 ± 5.9* 13.1 ± 6.0
10 46.7 ± 1.6 61.7 ± 4.4** 15.0 ± 4.9
20 48.0 ± 1.8 36.0 ± 6.2* −12.0 ± 6.0#
40 49.4 ± 1.4 23.5 ± 6.1**** −25.9 ± 6.2###,***
60 48.3 ± 1.6 21.0 ± 6.3**** −27.3 ± 6.0&,##,***
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Post-MO Train to Baseline: *0.05, **p<0.01, ****p<0.001, Holm-Sidak's multiple comparisons test. Δ in BLA-NAc AP Probability: ***p<0.005 to 5 Hz; #p<0.05, ##p<0.01, ###p<0.005 to 10 Hz; &p<0.05 to 20 Hz, Tukey's multiple comparisons test.

Shifts to BLA-evoked NAc AP probability by different MO train frequencies were significantly different from one another (Fig. 4E; F(1.917, 34.5) = 17.39, P < 0.0001, one-way RM ANOVA). Specific significant differences in BLA-evoked NAc AP probability shifts were found between 5 and 40 Hz, 5 and 60 Hz, 10 and 20 Hz, 10 and 40 Hz, 10 and 60 Hz, as well as 20 and 60 Hz MO train frequencies (Fig. 4E and Table 1; 5 vs. 10 Hz, P > 0.05; 5 vs. 20 Hz, P = 0.06; 5 vs. 40 Hz, P = 0.0009; 5 vs. 60 Hz, P = 0.0009; 10 vs. 20 Hz, P < 0.05; 10 vs. 40 Hz, P = 0.001; 10 vs. 60 Hz, P = 0.0013; 20 vs. 40 Hz, P = 0.06; 20 vs. 60 Hz, P < 0.05; 40 vs. 60 Hz, P > 0.05, Tukey’s multiple comparisons test). However, shifts to BLA-evoked NAc average AP latency and jitter by different MO train frequencies were not significantly different from one another (Fig. 4F; F(4, 74) = 1.725, P > 0.05; Fig. 4G; F(4, 68) = 1.117, P > 0.05; one-way ANOVA).

MO train stimulation uniformly diminishes BLA-evoked NAc firing in adolescents

In adolescents, MO train stimulation altered BLA-evoked NAc AP probability (Fig. 5A; main effect of MO stimulation: F(1, 9) = 11.96, P < 0.01; main effect of frequency: F(4, 36) = 6.993, P < 0.0005; MO train stimulation × train frequency interaction: F(4, 36) = 2.994, P < 0.05, two-way RM ANOVA). MO trains delivered between 10-60 Hz significantly reduced BLA-evoked NAc AP probability (Fig. 5A and Table 2; 5 Hz: P > 0.05; 10 Hz: P < 0.005; 20 Hz: P = 0.000007; 40 Hz: P = 0.000025; 60 Hz: P < 0.005, post hoc Holm–Sidak’s multiple comparisons test). MO train stimulation in adolescents did not have an effect on BLA-evoked NAc AP timing, as average AP latency and jitter were unaltered by cortical stimulation (Fig. 5B-C; average AP latency: no significant main effect of MO train stimulation: F(1, 62) = 0.2685, P > 0.05; no significant main effect of MO train frequency: F(4, 62) = 0.7206, P > 0.05; AP jitter: no significant main effect of MO train stimulation: F(1, 66) = 1.171, P > 0.05; no significant main effect of MO train frequency: F(4, 66) = 0.3207, P > 0.05, two-way ANOVA).

Fig. 5.

Fig. 5

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Adolescent MO stimulation reduces BLA-evoked NAc AP probability in a frequency-dependent manner. (A) MO train stimulation reduces BLA-evoked NAc AP probability when delivered at 10, 20, 40, and 60 Hz (n = 10). (B and C) MO train stimulation does not alter mean BLA-evoked NAc AP latency or AP jitter (5 Hz n = 10, 10 Hz n = 9, 20 Hz n = 5, 40, and 60 Hz n = 7). (D-F) in adolescents, shifts to BLA-evoked NAc AP probability, average latency, and jitter at different frequencies were not significantly different from one another in adolescents (AP % n = 10; AP latency/jitter: 5 Hz n = 10, 10 Hz n = 9, 20 Hz n = 5, 40, and 60 Hz n = 7). Baseline to post-MO stimulation comparisons: ***P < 0.005, ****P < 0.00005.

Table 2.

MO train stimulation alterations of BLA-evoked NAc AP probability in adolescent subjects.

Adolescents
MO train frequency (Hz) Baseline: BLA-NAc AP probability (%) Post-MO train: BLA-NAc AP probability (%) Δ in BLA-NAc AP probability (%)
5 53.6 ± 1.9 46.8 ± 7.1 −7.9 ± 5.7
10 50.8 ± 1.8 33.7 ± 4.7*** −18.6 ± 5.1
20 48.7 ± 2.6 20.4 ± 8.6**** −21.7 ± 9.3
40 49.7 ± 2.5 23.8 ± 7.1**** −22.8 ± 9.2
60 51.0 ± 1.5 32.8 ± 6.0*** −19.7 ± 6.5
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Post-MO train to baseline:

* * * P < 0.005,

* * * * P < 0.00005, Holm–Sidak’s multiple comparisons test.

In adolescents, shifts to BLA-evoked NAc AP probability, average latency, and jitter by different MO train frequencies were not significantly different from one another (Fig. 5D; F(2.411, 21.7) = 1.376, P > 0.05, one-way RM ANOVA; Fig. 5E; F (4, 31) = 0.8885, P > 0.05; Fig. 5F; F (4, 33) = 0.943, P > 0.05, one-way ANOVA).

MO stimulation produces pattern- and age-dependent effects on BLA-evoked NAc firing

MO train stimulation elicited frequency-dependent effects on BLA-evoked NAc firing across ages (Fig. 6A; no significant main effect of age: F(1, 27) = 2.503, P > 0.05, main effect of MO train frequency: F(4, 108) = 10.4, P < 0.000001; age × MO train frequency interaction: F(4, 108) = 4.832, P < 0.005, two-way RM ANOVA). BLA-evoked NAc AP probability sensitivity to MO 10 Hz trains were significantly different between adolescents and adults (Fig. 6A; 5 Hz: P = 0.12; 10 Hz: P < 0.005; 20 Hz: P > 0.05; 40 Hz: P > 0.05; 60 Hz: P > 0.05, post hoc Holm–Sidak’s multiple comparisons test). In regards to the effects of MO train stimulation on BLA-evoked NAc AP timing, shifts in AP latency and jitter by MO train stimulation did not differ between age groups (Fig. 6B; Changes to AP Latency: no significant main effect of age: P > 0.05, F(1,107) = 1.857, no significant main effect of MO train frequency: P > 0.05, F(4, 107) = 1.714; Fig. 6C; Changes to AP Jitter: no significant main effect of age: P > 0.05, F(1, 101) = 0.8946, no significant main effect of MO train frequency: P > 0.05, F(4, 101) = 1.979, two-way ANOVA).

Fig. 6.

Fig. 6

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Effects of MO train stimulation on BLA-evoked NAc AP strength is age-dependent. (A) MO train stimulation delivered at 10 Hz produces opposing effects on BLA-evoked NAc AP probability between adults and adolescents. During MO 10 Hz stimulation, BLA-evoked NAc AP probability is facilitated in adults but diminished in adolescents (adults n = 19; adolescents n = 10). (B and C) changes to BLA-evoked NAc average AP latency and AP jitter did not report any age-dependent differences by MO train stimulation (changes to AP LatencyAdults: 5 Hz n = 18, 10 Hz n = 19, 20 Hz n = 16, 40 and 60 Hz n = 10; changes to AP LatencyAdolescents: 5 Hz n = 10, 10 Hz n = 9, 20 Hz n = 5, 40 and 60 Hz n = 7; changes to AP JitterAdults: 5 and 10 Hz n = 19, 20 Hz n = 17, 40, and 60 Hz n = 12, changes to AP JitterAdolescents: 5 Hz n = 10, 10 Hz n = 9, 20 Hz n = 5, 40, and 60 Hz n = 7). Age differences: ***P < 0.005.

Discussion

The integration of MO and BLA synaptic inputs into NAc cells may be a critical mechanism by which the MO governs decision-making through its influence over reward-related circuits. In the present study, MO activation exerted train frequency- and age-dependent effects on BLA-NAc interactions. In adults, MO train stimulation did not alter the timing of BLA-evoked NAc firing but facilitated AP probability at 5 and 10 Hz and diminished AP probability at 20, 40, and 60 Hz. Interestingly, MO-evoked effects on BLA-NAc interactions differed between adolescents and adults; MO train stimulation uniformly diminished BLA-evoked NAc AP probability when delivered between 10 and 60 Hz.

Our findings build on other recent results that point to maturation of the MO-NAc circuit. Functionally, MO-NAc projections contribute to specific age-dependent risk assessment behaviors and optimize decision-making during probabilistic discounting tasks (Jenni et al. 2022; Loh et al. 2022). Together, the behavioral evidence positions MO-NAc as a key circuit for incorporating risk information to inform future reward-based decisions as means to optimize outcomes. Additionally, OFC neurons in unanaesthetized rats have baseline firing rates 3–5 Hz, which shift in response to reward-predictive cues, rewards, and choice selection during decision-making tasks (Roesch et al. 2006; Roitman and Roitman 2010; Burton et al. 2014). MO neuronal firing rates increase 2–4-fold during reward presentation, where greater shifts reflect rewards of larger magnitude and shorter delays (Burton et al. 2014). Thus, the bidirectional effects of MO when activated at different frequencies on reward-related circuits may be a mechanism for flexible decision-making during adulthood.

MO-mediated BLA-NAc facilitation

NAc facilitation can be due to many factors, including glutamatergic and dopaminergic mechanisms; N-Methyl-D-aspartic acid (NMDA) channels contribute to excitatory transmission (Valiullina et al. 2016), and local dopamine (DA) release augments excitatory inputs into NAc neurons (Brady and O’Donnell 2004; Goto and Grace 2005; Ambroggi et al. 2008). Though NAc DA release by MO stimulation has not been reported, train stimulation of the mPFC governs phasic NAc DA release in a frequency- and duration-dependent manner (Jackson et al. 2001; Hill et al. 2018).

Previous studies report mPFC 60-pulse stimulation increases NAc DA release but is optimal when delivered at 10–20 Hz (Hill et al. 2018). Contrasting studies have reported that mPFC low-frequency stimulation (e.g. 10 Hz) reduces NAc DA release (Jackson et al. 2001). However, mPFC stimulation duration is also an important factor. NAc DA release by 1-s mPFC train stimulation is greater in response to high-frequency stimulation than to low-frequency stimulation (e.g. 60 vs. 10 Hz). Whereas a 20s mPFC train evokes a more robust NAc DA response to low-frequency stimulation than high-frequency stimulation (Hill et al. 2018). A maximal release of NAc DA by mPFC 10-Hz trains provides an intriguing parallel to the noted age differences on BLA-evoked NAc facilitation by MO 10 Hz trains in our results, although across very different time scales (100-ms train compared to 20–60s).

MO activation of the NAc-ventral pallidum (VP)-ventral tegmental area (VTA) pathway is one mechanism for NAc DA release; excitation of GABAergic NAc projections inhibits VP GABAergic neurons that synapse onto dopaminergic VTA neurons, resulting in the disinhibition of dopaminergic VTA neurons and increased NAc DA release (Zahm and Heimer 1990; Michael et al. 1996; Floresco et al. 2003). PFC neurons provide immense excitatory, glutamatergic drive to NAc (Fuller et al. 1987; Sesack et al. 1989; Brenhouse et al. 2008); thus, stimulation of cortical areas, including the MO, may increase DA at specific train frequencies. MO-driven NAc DA release as a mechanism for strengthened BLA-NAc pathways in adults but weakened BLA-NAc in adolescents complements previous adolescent studies. MO-NAc fiber density increases from adolescence to adulthood (Loh et al. 2022), so low-frequency MO train stimulation may produce greater impact on DA release in adults than in adolescents.

MO-mediated BLA-NAc depression

The overall inhibitory effect of higher MO train stimulation frequencies on BLA-evoked NAc firing may be attributed to the NAc GABAergic microcircuit. The GABAergic microcircuit is an internal regulatory pathway composed of MSN axon collaterals and interneurons that participate in feed-forward inhibition of striatal activity, reducing evoked responses from incoming inputs (Pennartz and Kitai 1991; Koós and Tepper 1999; Wilson 2007; Gruber et al. 2009). GABAergic parvalbumin-positive (PV) fast-spiking interneurons (FSI) fire at high frequencies without adaptation (Kawaguchi 1993; Beatty et al. 2015), are innervated by cortical projections, and synapse with nearby NAc MSNs (Bennett and Bolam 1994; Ramanathan et al. 2002; Taverna et al. 2007). Electrophysiology studies confirm that PFC stimulation activates feed-forward inhibition in the NAc and limits excitation of MSNs through FSI activation (O’Donnell and Grace 1995; Mallet 2005; Gruber et al. 2009; Wright et al. 2017). Thus, MO stimulation’s depression of evoked-NAc firing may be mediated by PV FSI activation.

Depression of BLA-NAc activity by MO stimulation may also be a product of the PFC-driven slow inhibitory GABA component that follows NAc glutamatergic excitation (Chang and Kitai 1986). PFC stimulation evokes a prolonged hyperpolarization in the NAc after EPSCs (O’Donnell and Grace 1995). Signals that converge onto NAc neurons gate the evoked response, but the excitation or inhibition of NAc neurons is dependent on the order of cortical and BLA activation. While mPFC inputs into the NAc are enhanced by preceding limbic activation, mPFC inputs are dampened by BLA-evoked NAc EPSCs (Goto and O’Donnell 2002). The depression of BLA-evoked NAc firing by MO train stimulation observed here could be due to a similar attenuation of limbic-evoked EPSCs.

Implications for adolescent behavior

Age-dependent differences in effects of MO activation on BLA-NAc circuits are a likely result of MO-NAc maturation. Human cortical circuits undergo immense reorganization during adolescence, including synaptic pruning and a decline in dendritic spines, which are met with functional changes (Huttenlocher and Peter 1979; Huttenlocher and Dabholkar 1997; Petanjek et al. 2011). In rats, PFC- and MO-NAc fiber densities increase significantly from adolescence to adulthood (Brenhouse et al. 2008; Loh et al. 2022). MO neurons project onto NAc dopamine D1-receptor-expressing (D1) MSNs and dopamine D2 receptor-expressing (D2) MSNs but preferentially target D1 MSNs (Barrientos et al. 2018). D1 and D2 MSNs exert opposing effects on behavior. Activation of D1 MSNs promotes positive reinforcement and increases the generation of reward–context associations, whereas D2 MSN activation suppresses some reward-seeking behaviors (Lobo et al. 2010). Collectively, these results suggest that the maturation of MO-NAc pathways alters reinforcement and reward-seeking behaviors.

Since NAc DA release augments BLA-evoked NAc firing (Ambroggi et al. 2008), the age-dependent effects may also reflect developing DA systems. In the NAc, adolescent rats display lower estimates of DA synthesis and lower DA turnover rates relative to adults (Teicher et al. 1993; Andersen et al. 1997). The maturation of NAc DA systems is in line with our findings, as MO train stimulation did not augment evoked-NAc firing in adolescent recordings. BLA-NAc interactions facilitate optimal decision-making, and silencing BLA terminals in the NAc reduced risky, large-reward choices when prior outcomes were favorable and increased risky, large-reward choices were disadvantageous (Bercovici et al. 2018). However, adolescent decision-making tends toward risky choices. In our recordings, the adolescent MO strictly diminished BLA-NAc interactions, which may lead to biased adolescent decision-making.

Limitations

We acknowledge several limitations in these experiments. First, the study was performed only in male subjects. Though we prioritized testing age-dependent effects of MO activation on reward-related pathways over testing sex differences, the absence of female subjects limits findings. Additionally, sex differences in MO activation may exist as males and females perform MO-dependent decision-making tasks differently across species (Van den Bos et al. 2012; van den Bos et al. 2013; Stopper et al. 2014; Orsini et al. 2016; Jenni et al. 2017, 2022). Second, it is possible that indirect pathways contribute to the effects of MO activation on BLA-evoked NAc spiking, such as MO-BLA activation; the 10-pulse train stimulation provides enough of a time delay to potentially prime BLA-evoked NAc spiking. While this is a limitation of in vivo intact circuitry, on balance, the nature of the electrophysiology in vivo preparation allows a more naturalistic assessment of functional changes. In addition, electrical stimulation is delivered directly to BLA, which likely overshadows potential effects of MO on BLA activation.

Conclusions

NAc neurons receive multiple afferents that influence the timing and reliability of NAc neuronal firing. The MO’s governance over NAc response probability to BLA inputs may be a critical mechanism by which the MO contributes to the NAc’s coding of reward-related information. In cognitive behaviors that rely on NAc activity, such as decision-making, performance may be optimal when risk-related information from the MO is coordinated with reward-related information driven by incoming BLA inputs. MO activation produced unimodal effects on reward-related circuits in adolescents in contrast to bimodal effects seen in adults, perhaps contributing to biased decision-making during adolescence.

Author contributions

Conceptualization done by MKL & JAR; methodology by MKL & JAR; data curation done by MKL; validation by MKL; analysis performed by MKL; resources provided by JAR; writing done by MKL & JAR; and funding acquisition from JAR.

Acknowledgments

We gratefully acknowledge the help of Dr Nicole C. Ferrara for technical support and edits. We also thank Dr Anthony R. West for his exceptional advisement during the project and miss him dearly.

Contributor Information

Maxine K Loh, Department of Foundational Sciences and Humanities, Cellular and Molecular Pharmacology, Chicago Medical School, Rosalind Franklin University of Medicine and Science, North Chicago, IL 60064, USA; Center for Neurobiology of Stress Resilience and Psychiatric Disorders, Rosalind Franklin University of Medicine and Science, North Chicago, IL 60064, USA.

J Amiel Rosenkranz, Department of Foundational Sciences and Humanities, Cellular and Molecular Pharmacology, Chicago Medical School, Rosalind Franklin University of Medicine and Science, North Chicago, IL 60064, USA; Center for Neurobiology of Stress Resilience and Psychiatric Disorders, Rosalind Franklin University of Medicine and Science, North Chicago, IL 60064, USA.

Funding

National Institutes of Health (MH084970, MH118237 to J.A.R.). The funding agents did not have a role in study design, collection, analysis, interpretation of data, writing of the report, or in the decision to submit this work for publication.

Conflict of interest statement: None declared.

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