Abstract

Dopaminergic modulation of the dorsolateral prefrontal cortex (DLPFC) plays an important role in cognitive functions, including working memory. At optimal concentrations, dopamine (DA) enhances pyramidal cell (PC) firing to increase task-related activity. However, spatial and temporal “tuning” of the persistent firing that underlies this mnemonic activity requires inhibitory control from γ-aminobutyric acidergic (GABAergic) interneurons. How DA modulates the inhibitory control provided by different types of interneurons in the primate cortex is not known. We studied the effects of DA and DA receptor–specific agonists and antagonists on GABAergic inhibition and interneuron excitability in slices from primate DLPFC. Using whole-cell voltage-clamp recordings from layer 2/3 pyramidal neurons, we examined the effects of DA on spontaneous (action potential dependent) and miniature (action potential independent) inhibitory postsynaptic currents. We found that DA can increase inhibition via a presynaptic, action potential–dependent mechanism. In current-clamp recordings from physiologically and morphologically identified interneurons, we investigated the pharmacology and cell type specificity of this effect. DA increased the excitability of fast-spiking (FS), nonadapting interneurons via activation of D1- but not D2-type receptors. In contrast, DA had no effect on interneurons with adapting firing patterns. Thus, DA and D1 receptor activation affect local recurrent circuits by selectively modulating FS interneurons that control the firing of PCs through perisomatic innervation.

Introduction

The dorsolateral prefrontal cortex (DLPFC) of primates is involved in the planning and execution of complex behaviors that require working memory (Goldman-Rakic 1995). The active maintenance of information during working memory is believed to result from synaptic activity in local recurrent excitatory circuits (Goldman-Rakic 1995; Wang 2001); and in the DLPFC, intralaminar connections between clusters of layers 2/3 pyramidal cells (PCs) may represent the anatomical correlate of functional cell assemblies (Levitt and others 1993; Kritzer and Goldman-Rakic 1995; Pucak and others 1996; Melchitzky and others 1998). On the other hand, γ-aminobutyric acidergic (GABAergic) interneurons appear equally important for the control of recurrent excitation because inhibition serves both a spatial role (determining which pyramidal neurons are active) and a temporal role (determining when they are active) during different phases of working memory tasks (Constantinidis and others 2002).

Dopamine (DA) modulates both working memory performance and the task-related neuronal activity within the DLPFC (Sawaguchi and Goldman-Rakic 1994; Müller and others 1998; Winterer and Weinberger 2004), following an inverted U-shape dose/response curve (Sawaguchi and others 1988, 1990; Williams and Goldman-Rakic 1995; Murphy and others 1996). Thus, DA can have both facilitatory and suppressive effects on cortical neurons, and it has been speculated that the concentration-dependent effects of DA in vivo result at least in part from indirect effects on interneurons (Muly and others 1998). Dopaminergic axons innervate both pyramidal neurons and GABAergic interneurons (Verney and others 1990; Williams and Goldman-Rakic 1993; Sesack and others 1995, 1998), and both classes of cells express multiple subtypes of DA receptors (Bergson and others 1995; Mrzljak and others 1996; Khan and others 1998; Lidow and others 1998; Muly and others 1998), providing a means for differential DA modulation of cortical neurons. In the monkey DLPFC, dopaminergic axons make contacts with GABAergic neurons that express the calcium-binding protein parvalbumin and an as of yet unidentified group of interneurons but not with cells that contain the calcium-binding protein calretinin (Sesack and others 1995, 1998). We have shown that expression of these calcium-binding proteins differentiates cells with distinct electrophysiological properties (Zaitsev and others 2005). Recent studies in nonprimate species indicate that DA modulates GABAergic inhibition in a cell type– and receptor-specific way: DA appears to act preferentially on the class of fast-spiking (FS) interneurons to increase their excitability via D1 receptors (Zhou and Hablitz 1999; Gorelova and others 2002; Gao and Goldman-Rakic 2003). However, a detailed investigation of the effects of DA on the membrane properties of interneurons with adapting firing patterns is still missing. Similarly, evoked and spontaneous inhibitory postsynaptic currents (sIPSCs) recorded in PCs are enhanced by D1 receptor stimulation (Seamans and others 2001; Trantham-Davidson and others 2004, but see Gao and others 2003). In contrast, stimulation of D2-type receptors can reduce inhibitory postsynaptic currents (IPSCs) in pyramidal neurons, with varying effects on interneurons (Seamans and others 2001; Gorelova and others 2002; Wang and others 2002; Trantham-Davidson and others 2004; Tseng and O'Donnell 2004).

How DA modulates GABAergic inhibition in the primate cortex, however, is unknown. The organization of the frontal cortex and its dopaminergic innervation are remarkably different between rats and primates, including humans (Björklund and Lindvall 1984; van Eden and others 1987; Berger and others 1991; Preuss 1995; Lewis and Sesack 1997; Williams and Goldman-Rakic 1998). Moreover, important differences exist between primate and nonprimate species in the characteristics and relative proportions of interneuron subtypes (Somogyi and Cowey 1984; Kawaguchi 1993, 1995; Conde and others 1994; Gabbott and Bacon 1996; Zaitsev and others 2005; Krimer and others 2005; Yánez and others 2005).

In order to test the effects of DA on GABAergic transmission and membrane properties of interneurons in the primate prefrontal cortex (PFC), we performed whole-cell recordings in slices of monkey DLPFC. DA increased the frequency of sIPSCs (action potential dependent) but not miniature inhibitory postsynaptic currents (mIPSCs) (action potential independent) in layer 2/3 pyramidal neurons, suggesting a presynaptic, action potential–dependent mechanism. In current-clamp recordings from non-PCs, we investigated the pharmacology and cell type specificity underlying this effect. DA increased the excitability of FS nonadapting interneurons via activation of D1- but not D2-type receptors, while having no effect on interneurons that showed adapting firing patterns.

Methods

All procedures were carried out in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by the University of Pittsburgh Institutional Animal Care and Use Committee.

Surgery and Brain Slice Preparation

Prefrontal cortical slices were obtained from 15 young adult (3.5–6 kg, 4–5 years old) male long-tailed macaque monkeys (Macaca fascicularis). Tissue from these animals was also used in other electrophysiological studies (González-Burgos and others 2004, 2005; Krimer and others 2005). Following injections of ketamine hydrochloride (25 mg/kg), dexamethasone phosphate (0.5 mg/kg), and atropine sulfate (0.05 mg/kg), an endotracheal tube was inserted, and the animal was placed in a stereotaxic frame. Anesthesia was maintained with 1% halothane in 28% O2/air. A craniotomy was performed over the dorsal PFC, and a small block of tissue containing both medial and lateral banks of the principal sulcus (area 46) as well as part of area 9 (Walker 1940) was carefully excised. The tissue block was placed in a solution consisting of (in mM) 230 sucrose, 1.9 KCl, 1.2 Na2HPO4, 33 NaHCO3, 6 MgCl2, 0.5 CaCl2, 10 glucose, and 2 kynurenic acid; oxygenated with 95% O2 and 5% CO2. The animal was treated postoperatively with analgesics and antibiotics as previously described (Pucak and others 1996). All animals recovered quickly with no overt behavioral deficits. In most cases, the animals underwent the same procedure 2–4 weeks later to obtain tissue from the opposite hemisphere. During the second procedure, after the craniotomy, the animal was given an overdose of pentobarbital (30 mg/kg) and was perfused transcardially with ice-cold–modified artificial cerebrospinal fluid. A tissue block containing the portions of areas 9 and 46 nonhomotopic to the first biopsy was quickly excised. No consistent differences were observed between tissues obtained on either day. Subsequent treatment of the tissue was the same for both days. Coronal slices (350 μm) were cut in ice-cold high-sucrose ACSF on a vibratome (Leica, VT1000S, Nussloch, Germany). Slices were kept in a holding chamber at room temperature for at least 2 h (and up to 20 h) submerged in an incubation ACSF solution consisting of (in mM) 125 NaCl, 2 KCl, 1.25 Na2HPO4, 10 glucose, 25 NaHCO3, 6.0 MgCl2, and 1.0 CaCl2. Finally, for recordings, slices were transferred to a submerged chamber and superfused with oxygenated ACSF (in mM): 126 NaCl, 2.5 KCl, 1.2 Na2HPO4, 25 NaHCO3, 2.0 CaCl2, 1.0 MgCl2, and 10 glucose at 32–33 °C. All recordings were done in the continuous presence of 75 μM sodium metabisulfite to prevent oxidation of DA.

Whole-Cell Patch Clamp Recordings

Whole-cell recordings were obtained from neurons in layers 2 and 3 identified using infrared-differential interference contrast optics (Axioskop, Zeiss, Germany) and videomicroscopy (Dage MTI, Michigan City, IN). Putative interneurons were targeted based on their smaller soma size and the apparent absence of an apical dendrite. In most neurons, the nonpyramidal morphology was confirmed following histological recovery (see below). For current-clamp recordings, electrodes (4–7 MΩ open tip resistance) were filled with a solution containing (in mM) 120 K-methylsulfate, 10 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), 0.5 ethyleneglycol-bis(2-aminoethylether)-N,N,N′,N′-tetraacetic acid (EGTA), 10 KCl, 10 NaCl, 4 adenosine triphosphate-Mg, 0.3 guanosine triphosphate-Na, 14 phosphocreatine, and 0.5% biocytin. For voltage-clamp recordings, KCl was omitted, and KMeSO4 was substituted with CsCl (130) and Tetraethylamonium (TEA) (10) to block potassium currents.

Data Collection and Analysis

Recordings were obtained with an Axoclamp-2A or Axopatch 1C amplifier (Axon Instruments, Foster City, CA). Membrane potential was not corrected for changes in junction potential after break-in. Signals were low-pass filtered at 3 kHz and digitized at 10 kHz during voltage-clamp and 20 kHz for current-clamp recordings. Data were stored on a personal computer for off-line analysis. Data acquisition and analysis were performed using software (D.A. Henze) written in LabView (National Instruments, Austin, TX). Series of hyperpolarizing and depolarizing current steps (500 ms duration; 5–20 pA increments; 3–5 sweeps each at 0.2 Hz) were delivered from resting membrane potential to evoke both subthreshold responses and spike firing. Intrinsic membrane properties and the evoked firing pattern were used to distinguish subtypes of GABAergic interneurons. In order to determine changes in neuronal excitability following pharmacological manipulations, a small range of depolarizing current steps (as above) below and above the threshold for spike initiation was chosen based on the initial current–voltage plot. This series of pulses was then repeated approximately every 4–5 min for the duration of the experiment. The rheobase current and the voltage threshold at which the first action potential was generated were analyzed. Comparisons of changes in the number of evoked spikes and the duration of the first interspike interval (ISI) were made at a current level that reliably produced repetitive firing under control conditions. The action potential threshold was defined as the initial point of rapid voltage deflection, and the amplitude of the action potential and the fast postspike afterhyperpolarization (AHP) were measured from threshold to the positive and negative peak, respectively. Half-width of the action potential was the duration of the action potential at half-amplitude. Membrane time constant was determined by fitting a single exponential to the response to long (500 ms) hyperpolarizing current steps (−10 to −30 pA). The time-dependent voltage sag that occurred in some neurons in response to hyperpolarizing current pulses is expressed as a percentage and was calculated as 100 × (Vmax − Vend)/Vmax, where Vmax is the peak voltage deflection and Vend the voltage at the end of the current pulse. Drug-induced changes in input resistance (defined as the “passive” membrane properties in the linear portion of the current–voltage plot) were measured from the average (n > 30) of the voltage responses to small hyperpolarizing current pulses (−10 to −30 pA, 150 ms duration) that preceded individual sweeps.

After collection of baseline data, DA or specific DA receptor agonists were bath applied for 2–3 min. We used the agonists (±)-6-chloro-PB hydrobromide (SKF 81297; Sigma, St. Louis, MO) or (±)-1-Phenyl-2,3,4,5-tetrahydro-(1H)-3-benzazepine-7,8-diol hydrochloride (SKF 38393, Research Biochemicals, Natick, MA) to stimulate receptors of the D1/D5 class and (±)-Quinpirole dihydrochloride (Sigma) or PD 168077 (Tocris Cookson, Ellisville, MO) to activate D2-like receptors or D4-type receptors, respectively. When the effects of DA antagonists were examined, the D1 antagonist R-[+]-7-chloro-8-hydroxy-3-methyl-1-phenyl-2,3,4,5-tetrahydro-1H-3-benzazepine (SCH23390) or the D2 antagonist (±)-sulpiride (both Sigma) were bath applied at least 10 min before application of DA and continued to be present throughout the remainder of the experiment. Some experiments were conducted in the presence of 10 μM 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX, to block alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors), 100 μM (±)2-amino-5-phosphonopentanoic acid (APV, to block N-methyl-D-aspartic acid (NMDA) receptors) and 10 μM (-)-bicuculline methiodide (to block GABAA receptors), as indicated. In voltage-clamp experiments, we examined sIPSCs. The membrane potential was held at −85 to −90 mV, and GABA-mediated events were pharmacologically isolated by adding 10 μM CNQX and 100 μM APV to the bath. Action potential–independent mIPSCs were recorded under the same conditions but in the presence of 1 μM tetrodotoxin (TTX; Sigma) to block sodium channels. The frequency and amplitude of events were measured using MiniAnalysis (Synaptosoft, Decatur, GA). Events were detected when they crossed a threshold set at three times the root mean square (RMS) baseline noise. The detected events were confirmed as synaptic events by eye. For IPSCs, we compared the total number of events from 8 min of continuous recordings each before and ∼2 min after DA application.

For statistical comparisons, electrophysiological parameters were measured at multiple time points before, during, and after drug application and averaged for each experimental condition. The time periods used to assess the effects of DA and its agonists on the membrane excitability of interneurons (Figs 4 and 5 and Table 2) are indicated in Figure 5. Only one neuron experiencing drug treatment was used from each brain slice. However, in a few instances, different agonists were applied successively to one cell to test its differential response to various drugs. Usually, either a D1 or a D2 receptor agonist was followed by application of DA. In these cases, only the response to the first drug was used for statistical analysis. Comparisons were performed using analysis of variance and 2-tailed, paired t-tests as indicated (differences of alpha ≤ 0.05 were considered significant). For multiple post hoc comparisons, the alpha-level was Bonferroni adjusted. All data are presented as means ± standard error of the mean.

Histology

Following recording, slices were fixed in 4% paraformaldehyde in 0.1 M phosphate buffered saline (PBS). Slices were resectioned at 70 μm on a freezing microtome and collected in PBS. Biocytin-filled neurons were visualized by standard Ni-enhanced 3,3′-diaminobenzidine histochemistry, using the Vectastain Elite ABC kit (Vector Laboratories, Burlingame, CA). Individual cells were reconstructed using Neurolucida software (Microbrightfield, Williston, VT).

Results

DA Modulation of IPSCs

To study the effects of DA on GABAergic inhibition in layers 2–3 of monkey DLPFC in voltage-clamp experiments, we recorded pharmacologically isolated IPSCs from PCs. Spontaneously occurring IPSCs (sIPSCs) represent both action potential–dependent and –independent release of GABA. In contrast, mIPSCs are recorded in the presence of TTX (1 μM) to eliminate the contribution of action potential–mediated release events. Thus, a differential effect of DA on sIPSCs and mIPSCs would indicate either a selective effect on intrinsic interneuron excitability or a modification of GABA release, respectively. Whole-cell recording pipettes contained CsCl and TEA (see Methods), and all IPSCs were recorded at holding potentials of −85 to −90 mV as inward currents. These currents were completely blocked by the addition of 20 μM bicuculline at the end of the experiment, indicating they were mediated by GABAA receptors (data not shown). Bath application of DA (1 or 10 μM) resulted in an increase in the frequency of sIPSCs in 8 of 9 PCs tested (control 9.3 ± 2.0 Hz, DA 12.4 ± 2.5 Hz; P < 0.05, df = 8; Fig. 1A,B2). In most cells, the frequency of the sIPSCs gradually increased over 5 min following DA application and remained at an elevated level for the duration of the recording (Fig. 1B1). Only in a few cells in which the recordings were continued for >30 min was a partial washout of about 50% of the effect observed. The increased frequency of sIPSCs was not accompanied by changes in the relative amplitude distribution of inhibitory synaptic events (Fig. 1C). DA had no effect on mean sIPSC amplitude (Fig. 1D; control 42.8 ± 4.8 pA, DA 41.5 ± 4.7 pA) or decay time kinetics (control 6.8 ± 0.7 ms, DA 6.9 ± 0.8 ms). The increase in the frequency of sIPSCs was mimicked by a D1 agonist (SKF 81297; 10 μM) in 3 out of 3 cells tested (control 6.3 ± 1.6, DA 9.7 ± 2.1 Hz, P < 0.05; data not shown).

Figure 1.

DA increases the frequency of sIPSCs in DLPFC pyramidal neurons. (A) Voltage-clamp recordings of pharmacologically isolated sIPSCs from prefrontal layer 2/3 PCs under baseline conditions (left column) and after application of 10 μM DA. (B) In 8 out of 9 neurons, DA application resulted in a robust and long-lasting increase in the frequency of sIPSCs (B1). (B2) Comparison of the average frequency of events from all cells during 8 min of continuous recording before (period “1” in Fig. B1) and after DA application (period “2” in Fig. B1). (C) Histogram of the amplitude distribution of the events before (black bars) and after (gray bars) DA application, respectively. Inset: Same data replotted as cumulative frequency distribution to show that DA (gray line) did not significantly change the relative number of events of a given amplitude. (D) DA (gray line) also did not affect kinetics or amplitude of the average sIPSC (averaged from all events as shown in B).

Figure 1.

DA increases the frequency of sIPSCs in DLPFC pyramidal neurons. (A) Voltage-clamp recordings of pharmacologically isolated sIPSCs from prefrontal layer 2/3 PCs under baseline conditions (left column) and after application of 10 μM DA. (B) In 8 out of 9 neurons, DA application resulted in a robust and long-lasting increase in the frequency of sIPSCs (B1). (B2) Comparison of the average frequency of events from all cells during 8 min of continuous recording before (period “1” in Fig. B1) and after DA application (period “2” in Fig. B1). (C) Histogram of the amplitude distribution of the events before (black bars) and after (gray bars) DA application, respectively. Inset: Same data replotted as cumulative frequency distribution to show that DA (gray line) did not significantly change the relative number of events of a given amplitude. (D) DA (gray line) also did not affect kinetics or amplitude of the average sIPSC (averaged from all events as shown in B).

In contrast, 10 μM DA had no significant effect on mIPSCs (n = 7). Neither frequency (control 7.0 ± 1.7, DA 8.2 ± 1.5 Hz) nor average amplitude (control 19.5 ± 2.9 pA, DA 19.6 ± 3.3 pA) or decay time (control 7.0 ± 0.7 ms, DA 6.7 ± 0.4 ms) was altered significantly by DA application (Fig. 2).

Figure 2.

DA does not affect the frequency of mIPSCs in DLPFC pyramidal neurons. (A) Action potential–independent mIPSCs were recorded in the presence of 20 μM CNQX, 100 μM APV, and 1 μM TTX in voltage clamp from PCs. Representative traces showing that bath application of DA did not change frequency or amplitude of mIPSCs. (B) Histogram of the amplitude distribution of mIPSCs recorded from 7 neurons before (black bars) and after (gray bars) DA application during 8 min of continuous recording for each condition. Inset: Same data replotted as cumulative frequency distribution to show that DA (gray line) did not change the relative number of events of a given amplitude. (C) Comparison of the average frequency of events from all cells during 8 min of continuous recording under control conditions and after DA application. (D) As was the case with action potential–dependent sIPSCs, DA (gray line) did not affect the kinetics or averaged amplitude of mIPSCs.

Figure 2.

DA does not affect the frequency of mIPSCs in DLPFC pyramidal neurons. (A) Action potential–independent mIPSCs were recorded in the presence of 20 μM CNQX, 100 μM APV, and 1 μM TTX in voltage clamp from PCs. Representative traces showing that bath application of DA did not change frequency or amplitude of mIPSCs. (B) Histogram of the amplitude distribution of mIPSCs recorded from 7 neurons before (black bars) and after (gray bars) DA application during 8 min of continuous recording for each condition. Inset: Same data replotted as cumulative frequency distribution to show that DA (gray line) did not change the relative number of events of a given amplitude. (C) Comparison of the average frequency of events from all cells during 8 min of continuous recording under control conditions and after DA application. (D) As was the case with action potential–dependent sIPSCs, DA (gray line) did not affect the kinetics or averaged amplitude of mIPSCs.

Taken together, these data suggest that DA receptor activation increases interneuron excitability and spontaneous spike firing via a D1 receptor mechanism without altering action potential–independent release of GABA.

DA Modulation of Interneuron Excitability

To assess the mechanisms underlying the DA modulation of inhibition in the primate DLPFC, we obtained current-clamp recordings from a total of 84 nonpyramidal neurons in layers 2 and 3 from areas 46 and 9. Based on electrophysiological characteristics, we divided interneurons into 2 main cell types and then examined the effects of DA or receptor-specific activation on membrane excitability.

Properties of Primate DLPFC Interneurons

Based on the data from this study and a larger sample of neurons not tested for the effects of DA (Krimer and others 2005), we categorized nonpyramidal neurons into 2 distinct groups according to their firing patterns, which was operationalized as the degree of spike-frequency adaptation during repetitive firing. The degree of spike adaptation was calculated for an intermediate level of intracellular current injection (for most neurons ∼60 pA above the current that induced the first spike) by dividing the last ISI through the first ISI (Fig. 3C). Based on this measure, neurons were grouped either as adapting non-PCs (ANP; adaptation ratios > 1.3) or as nonadapting FS cells (adaptation ratios < 1.25) for the further analysis of the effects of DA or its receptor-specific agonists on cell excitability (see below). Adapting and FS cells differed in a variety of basic electrophysiological characteristics that were also distinct from the properties of morphologically identified small PCs (n = 34) in layers 2 and 3 (Table 1).

Figure 3.

Electrophysiological and morphological characteristics of primate DLPFC neurons. (A) Computer reconstructions of biocytin-filled neurons that displayed morphological features of aspiny non-PCs and a pyramidal neuron (far right). Examples of cells with FS firing characteristics included arbor (or basket) cells, which could be further distinguished by the lateral extent of their axonal arbors into local, medium, or wide arbor cells (3 cells on the right) and 2 chandelier cells (not shown). Examples of cells with adapting firing patterns included neurogliaform cells (top center) or types of cells with predominantly vertically oriented axonal arbors, including double bouquet cells. In the reconstructed neurons, the somata and dendrites are drawn in red and the axonal arborizations in blue. The example of a wide arbor cell is taken from Krimer and others (2005), used with permission. (B) Examples of membrane responses and firing patterns for the 2 main classes of interneurons in response to somatic current injections (see Results and Table 1 for details). FS and ANP showed different degrees of frequency adaptation during repetitive firing. (C) For the analysis of DA effects, cells were divided into 2 groups based on their adaptation rate in spike firing (calculated as the ratio between the last ISI divided by the first ISI). The histogram shows the distribution of adaptation ratios in our sample of 85 non-PCs used in this study. We designated all cells with ratios smaller than 1.25 as FS cells and cells with larger ratios as adapting interneurons, respectively.

Figure 3.

Electrophysiological and morphological characteristics of primate DLPFC neurons. (A) Computer reconstructions of biocytin-filled neurons that displayed morphological features of aspiny non-PCs and a pyramidal neuron (far right). Examples of cells with FS firing characteristics included arbor (or basket) cells, which could be further distinguished by the lateral extent of their axonal arbors into local, medium, or wide arbor cells (3 cells on the right) and 2 chandelier cells (not shown). Examples of cells with adapting firing patterns included neurogliaform cells (top center) or types of cells with predominantly vertically oriented axonal arbors, including double bouquet cells. In the reconstructed neurons, the somata and dendrites are drawn in red and the axonal arborizations in blue. The example of a wide arbor cell is taken from Krimer and others (2005), used with permission. (B) Examples of membrane responses and firing patterns for the 2 main classes of interneurons in response to somatic current injections (see Results and Table 1 for details). FS and ANP showed different degrees of frequency adaptation during repetitive firing. (C) For the analysis of DA effects, cells were divided into 2 groups based on their adaptation rate in spike firing (calculated as the ratio between the last ISI divided by the first ISI). The histogram shows the distribution of adaptation ratios in our sample of 85 non-PCs used in this study. We designated all cells with ratios smaller than 1.25 as FS cells and cells with larger ratios as adapting interneurons, respectively.

Table 1

Electrophysiological properties of 3 classes of neurons in layers 2/3 of monkey PFC (means ± standard error)

 FS cells, n = 56 ANP cells, n = 28 PCs, n = 34 Statistical differences* 
Resting membrane potential (mV) −68.7 (±0.65) −68.0(±0.8) −71.1 (±0.92) — 
Input resistance (MΩ) 191.9 (±17.1) 281.7 (±31.1) 111.2 (±8.7) ANP > FS > PC 
Membrane time constant τ (ms) 10.7 (±1.0) 21.7 (±2.1) 22.8 (±2.9) PC, ANP > FS 
Rheobase current (pA) 139.5 (±13.8) 54.4 (±7.5) 109.5 (±17.0) PC, FS > ANP 
Action potential threshold (mV) −40.0 (±0.9) −43.5 (±0.9) −44.5 (±0.9) PC, ANP > FS 
Action potential amplitude 48.9 (±1.1) 60.2 (±2.2) 73.2 (±1.4) PC > ANP > FS 
Action potential half-width (ms) 0.48 (±0.03) 0.82 (±0.05) 1.05 (±0.04) PC > ANP > FS 
10–90% rise-time of action potential (ms) 0.31 (±0.01) 0.42 (±0.02) 0.48 (±0.02) PC > ANP > FS 
90–10% fall-time of action potential (ms) 0.36 (±0.03) 0.69 (±0.05) 0.93 (±0.05) PC > ANP > FS 
Amplitude AHP (mV) 23.8 (±0.7) 16.1 (±0.9) 11.6 (±0.9) FS > ANP > PC 
AHP time-to-peak (mV) 1.45 (±0.14) 3.53 (±0.76) 3.96 (±1.41) — 
Percentage “sag” 1.56 (±0.16) 2.45 (±0.52) 2.15 (±0.21) — 
 FS cells, n = 56 ANP cells, n = 28 PCs, n = 34 Statistical differences* 
Resting membrane potential (mV) −68.7 (±0.65) −68.0(±0.8) −71.1 (±0.92) — 
Input resistance (MΩ) 191.9 (±17.1) 281.7 (±31.1) 111.2 (±8.7) ANP > FS > PC 
Membrane time constant τ (ms) 10.7 (±1.0) 21.7 (±2.1) 22.8 (±2.9) PC, ANP > FS 
Rheobase current (pA) 139.5 (±13.8) 54.4 (±7.5) 109.5 (±17.0) PC, FS > ANP 
Action potential threshold (mV) −40.0 (±0.9) −43.5 (±0.9) −44.5 (±0.9) PC, ANP > FS 
Action potential amplitude 48.9 (±1.1) 60.2 (±2.2) 73.2 (±1.4) PC > ANP > FS 
Action potential half-width (ms) 0.48 (±0.03) 0.82 (±0.05) 1.05 (±0.04) PC > ANP > FS 
10–90% rise-time of action potential (ms) 0.31 (±0.01) 0.42 (±0.02) 0.48 (±0.02) PC > ANP > FS 
90–10% fall-time of action potential (ms) 0.36 (±0.03) 0.69 (±0.05) 0.93 (±0.05) PC > ANP > FS 
Amplitude AHP (mV) 23.8 (±0.7) 16.1 (±0.9) 11.6 (±0.9) FS > ANP > PC 
AHP time-to-peak (mV) 1.45 (±0.14) 3.53 (±0.76) 3.96 (±1.41) — 
Percentage “sag” 1.56 (±0.16) 2.45 (±0.52) 2.15 (±0.21) — 

Note: *Significant differences indicated by the use of a Scheffé test for multiple comparisons after analysis of variance (P < 0.05).

FS cells (n = 56) were able to sustain high steady-state firing frequencies (up to 300 Hz) with no or little spike-frequency adaptation. FS cells generated spikes of short duration, which were followed by fast, monophasic AHPs of large amplitude (Fig. 3B). FS neurons often displayed strong outward rectification and subthreshold oscillations in the voltage range just negative to threshold (cf., Fig. 3B). Morphologically identified biocytin-filled FS neurons included different types of arbor or “basket” cells and chandelier cells (Fig. 3A).

The patterns of axonal arborizations of arbor cells were similar to those previously described in a Golgi analysis of layer 2/3 nonpyramidal neurons of the primate DLPFC (Lund and Lewis 1993). They included cells with local or narrow axonal arbors, medium arbor cells, and wide arbor cells (cf., Krimer and others 2005; Zaitsev and others 2005). Furthermore, we have recently shown that cells with these physiological and morphological characteristics contain the calcium-binding protein parvalbumin (Zaitsev and others 2005) and thus share important features with parvalbumin and/or calbindin-immunopositive FS cells of the rodent frontal cortex (Kawaguchi and Kubota 1993, 1997; Cauli and others 1997).

Adapting cells (n = 28) on average showed lower steady-state firing frequencies than FS cells and typically had action potentials of intermediate duration (Table 1), often followed by complex AHPs and sometimes depolarizing afterpotentials. None of the cells in this study that were tested for the effects of DA showed the typical low-threshold spiking behavior from hyperpolarized membrane potentials that is often described for adapting cells in rodents (Kawaguchi 1993; Gorelova and others 2002; Goldberg and others 2004). Because the firing patterns of individual adapting interneurons were often indistinguishable from that of PCs in the same layer (Fig. 3 and Table 1), only morphologically identified cells were considered for analysis of DA effects. Biocytin-filled adapting neurons consisted of neurogliaform cells and cells with bitufted dendritic arbors and vertically arranged axonal arbors, which included double bouquet cells (cf., Lund and Lewis 1993; Fig. 3A).

Effect of DA Application on Interneuron Excitability

Bath application of either 10 or 50 μM DA for 2–3 min led to a cell type–specific increase in the membrane excitability of DLPFC interneurons. In FS cells (n = 14; 10 and 50 μM pooled), DA application resulted in a significant depolarization from the resting membrane potential (baseline −69.5 ± 0.9 mV, DA −65.8 ± 1.1 mV; df = 13, P < 0.01). In contrast, changes in the resting membrane potential of ANP neurons in response to bath application of DA were less consistent, and in 10 neurons tested, the small depolarization was not significant (baseline −68.1 ± 1.1 mV, DA −66.7 ± 0.9 mV; df = 9, t = −2.225, P = 0.57).

The change in membrane potential was compensated with DC injection to bring the membrane potential back to baseline values before other measures of excitability were obtained. To measure changes in intrinsic excitability, we measured the response to somatic current injections. For statistical analysis, a current intensity was chosen that consistently evoked repetitive spiking under baseline conditions (see Methods). Figure 4 presents data for groups of FS and ANP cells that received 10 or 50 μM DA, respectively. In FS cells (10 μM DA, n = 11; 50 μM DA, n = 10), but not in adapting cells (10 μM DA, n = 12; 50 μM DA, n = 8), DA resulted in a large increase of action potentials evoked by a 500-ms depolarizing current step (Figs 4A1,B and 5) without affecting input resistance measured at rest (Figs 4C,H and 5). This change was accompanied by a significant shift in the threshold of the first action potential toward hyperpolarized potentials (Figs 4D–H and 5), and a reduction in the rheobase current injected is required to evoke this first spike (Fig. 4E). The reduction in rheobase current and the threshold of action potential initiation is likely to reflect activation of active conductances at depolarized potentials (Fig. 4H). Furthermore, at current levels that induced repetitive firing, the interval between the first and the second action potential was significantly shortened (Fig. 4F), and also the latency of the first spike was often reduced (Fig. 4G). On the other hand, in adapting cells, none of these measures of excitability were significantly altered by application of DA (Fig. 4A2,B–F).

Figure 4.

DA increases the membrane excitability of DLPFC interneurons in a cell type–specific fashion. (A) Bath application of DA leads to a large increase of action potentials evoked by a 500-ms depolarizing current step in FS cells (A1) but not in adapting interneurons (A2). (BF) Measures of intrinsic excitability in FS and ANP cells for 2 different concentrations of DA. In FS cells (10 μM DA, n = 11; 50 μM DA, n = 10), but not in adapting cells (10 μM DA, n = 12; 50 μM DA, n = 8), DA resulted in a significant increase of action potentials (B). In FS cells, the increase in spike firing was accompanied by a hyperpolarizing shift in the voltage threshold of the first action potential (D), a reduction in the rheobase current required to initiate spike firing (E), and a shortening of the first ISI (F). Measurements for baseline and drug condition were averaged across the time periods indicated in Figure 5 and compared using paired t-tests. Significant differences compared with baseline condition are indicated as * for P < 0.05 and ** for P < 0.01. (G) Sample traces from a FS neuron for control (gray) and DA conditions illustrating the reduction in spike threshold and latency of the first spike, as well as the shortening of the ISIs. (H) DA modulation of subthreshold electrotonic potentials. An effect of DA on Rin only becomes apparent at potentials close to spike threshold. The increased membrane response at depolarized potentials is reflected in the reduction of the rheobase current and the reduction in the action potential threshold (arrows).

Figure 4.

DA increases the membrane excitability of DLPFC interneurons in a cell type–specific fashion. (A) Bath application of DA leads to a large increase of action potentials evoked by a 500-ms depolarizing current step in FS cells (A1) but not in adapting interneurons (A2). (BF) Measures of intrinsic excitability in FS and ANP cells for 2 different concentrations of DA. In FS cells (10 μM DA, n = 11; 50 μM DA, n = 10), but not in adapting cells (10 μM DA, n = 12; 50 μM DA, n = 8), DA resulted in a significant increase of action potentials (B). In FS cells, the increase in spike firing was accompanied by a hyperpolarizing shift in the voltage threshold of the first action potential (D), a reduction in the rheobase current required to initiate spike firing (E), and a shortening of the first ISI (F). Measurements for baseline and drug condition were averaged across the time periods indicated in Figure 5 and compared using paired t-tests. Significant differences compared with baseline condition are indicated as * for P < 0.05 and ** for P < 0.01. (G) Sample traces from a FS neuron for control (gray) and DA conditions illustrating the reduction in spike threshold and latency of the first spike, as well as the shortening of the ISIs. (H) DA modulation of subthreshold electrotonic potentials. An effect of DA on Rin only becomes apparent at potentials close to spike threshold. The increased membrane response at depolarized potentials is reflected in the reduction of the rheobase current and the reduction in the action potential threshold (arrows).

Although in general the effects of DA were detectable within a few minutes after the drug was washed into the chamber, the maximal response was often only seen after about 20 min. This slow developing and very long–lasting modulation of membrane excitability by DA is illustrated in Figure 5 for the increase in the number of spikes and the reduction in the action potential threshold. Figure 5C also demonstrates that these changes were independent of changes in input resistance.

Figure 5.

The increase in membrane excitability in FS cells is long lasting. (AC) The same data as shown in Figure 4 for the 10 and 50 μM DA conditions in FS cells shown as a function of time (N = 11 and 10 for 10 and 50 μM DA, respectively, but the number of cells at individual time points varies). Both the increase in evoked spike firing (A) and the shift in action potential threshold (B) developed rapidly within minutes of the drug reaching the chamber. However, the maximal effect of DA on these measures was often only seen after 20–30 min and almost never washed out. In contrast, measures of input resistance (C) showed comparatively little change over time.

Figure 5.

The increase in membrane excitability in FS cells is long lasting. (AC) The same data as shown in Figure 4 for the 10 and 50 μM DA conditions in FS cells shown as a function of time (N = 11 and 10 for 10 and 50 μM DA, respectively, but the number of cells at individual time points varies). Both the increase in evoked spike firing (A) and the shift in action potential threshold (B) developed rapidly within minutes of the drug reaching the chamber. However, the maximal effect of DA on these measures was often only seen after 20–30 min and almost never washed out. In contrast, measures of input resistance (C) showed comparatively little change over time.

Because it is possible that the change in excitability was due to DA effects upon synaptic inputs, DA applications were repeated in a separate group of FS neurons (n = 4) in the presence of glutamatergic and GABAergic antagonists (10 μM CNQX, 100 μM APV, 10 μM bicuculline) to block synaptic inputs. With synaptic inputs blocked, DA still exerted the same effect on excitability in FS cells (number of spikes control 12.7 ± 2.3, number of spikes DA 19.8 ± 3.4, P < 0.05; spike threshold baseline −41.2 ± 1.6, spike threshold DA −44.7 ± 2.1, P < 0.05; data not shown), demonstrating that the increased excitability was due to intrinsic mechanisms and did not depend on altered synaptic drive.

Pharmacology of the Dopaminergic Modulation of DLPFC Interneurons

In order to determine the DA receptor subtypes involved in modulating the excitability of DLPFC interneurons, receptor-specific agonists were applied in the same manner as DA. The actions of DA upon excitability in FS neurons were mimicked by the D1 agonists SKF 81297 (n = 6) and SKF 38393 (n = 6) (both 10 μM; Fig. 6A and Table 2). As with DA, application of the agonists resulted in a reduction of the action potential threshold that was accompanied by a large increase in the number of evoked spikes. In contrast, D1 receptor activation had no effect on adapting interneurons (n = 8; Table 2).

Table 2

Effects of specific DA receptor agonists and antagonists on electrophysiological properties of FS and adapting interneurons

 Resting membrane potential Number of evoked spikes Action potential threshold (mV) Rheobase current (pA) Input resistance (MΩ) Duration of first ISI (ms) 
FS cells       
    Control −70.5 (±2.0) (n = 5) 14.2 (±1.9) −39.4 (±1.6) 144.5 (±31.6) 231.6 (±49.5) 33.9 (±11.8) 
    10 μM SKF 38393 or SKF 81297 (D1 agonists) (n = 12) −69.5 (±1.8) (n = 5) 20.6 (±3.2)* −43.7 (±1.6)** 121.3 (±24.6)* 243.7 (±54.5) 28.5 (±11.3)** 
    Control −70.0 (±0.0) (n = 3) 14.4 (±2.1) −40.8 (±2.1) 113.9 (±34.1) 224.4 (±60.4) — 
    10 μM quinpirole (D2 agonist) (n = 6) −66.5 (±1.5) (n = 3) 15.0 (±2.8) −41.1 (±2.2) 106.1 (±33.4) 239.2 (±72.7) — 
    Control — 14.3 (±3.9) −42.1 (±1.2) 91.41 (±11.4) 205.5 (±24.5) — 
    1 or 5 μM PD 168077 (D4 agonist) (n = 5) — 14.5 (±4.2) −42.4 (±1.5) 93.5 (±10.5) 201.8 (±22.3) — 
    Control — 18.5 (±1.3) −43.6 (±1.2) 138.4 (±29.5) 214.5 (±59.0) — 
    5 μM SCH23390 (D1 antagonist) (n = 7) — 19.3 (±2.5) −43.7 (±1.3) 134.2 (±28.1) 218.7 (±59.3) — 
    5 μM SCH23390 + 50 μM DA (n = 7) — 19.6 (±2.6) −44.3 (±1.2) 132.1 (±28.0) 222.2 (±59.8) — 
    Control — 13.1 (±3.8) −43.3 (±2.0) 105.4 (±24.1) 193.3 (±40.9) — 
    5 μM sulpiride (D2 antagonist) (n = 5) — 16.1 (±5.0) −44.2 (±1.8)** 105.1 (±26.7) 188.3 (±34.1) — 
    5 μM sulpiride + 10 μM DA (n = 5) — 26.3 (±5.6)** −45.9 (±1.5) 90.9 (±21.6) 189.2 (±29.0) — 
Adapting cells       
    Control −78.0 (±2.0) (n = 3) 6.5 (±1.7) −40.4 (±1.7) 77.9 (±20.2) 273.1 (±20.2) 66.9 (±30.4) 
    10 μM SKF 38393 or SKF 81297 (D1 agonists) (n = 8) −74.5 (±2.0) 7.3 (±1.1) −43.3 (±2.1)* 84.3 (±25.3) 270.0 (±44.6) 41.7 (±15.2) 
 Resting membrane potential Number of evoked spikes Action potential threshold (mV) Rheobase current (pA) Input resistance (MΩ) Duration of first ISI (ms) 
FS cells       
    Control −70.5 (±2.0) (n = 5) 14.2 (±1.9) −39.4 (±1.6) 144.5 (±31.6) 231.6 (±49.5) 33.9 (±11.8) 
    10 μM SKF 38393 or SKF 81297 (D1 agonists) (n = 12) −69.5 (±1.8) (n = 5) 20.6 (±3.2)* −43.7 (±1.6)** 121.3 (±24.6)* 243.7 (±54.5) 28.5 (±11.3)** 
    Control −70.0 (±0.0) (n = 3) 14.4 (±2.1) −40.8 (±2.1) 113.9 (±34.1) 224.4 (±60.4) — 
    10 μM quinpirole (D2 agonist) (n = 6) −66.5 (±1.5) (n = 3) 15.0 (±2.8) −41.1 (±2.2) 106.1 (±33.4) 239.2 (±72.7) — 
    Control — 14.3 (±3.9) −42.1 (±1.2) 91.41 (±11.4) 205.5 (±24.5) — 
    1 or 5 μM PD 168077 (D4 agonist) (n = 5) — 14.5 (±4.2) −42.4 (±1.5) 93.5 (±10.5) 201.8 (±22.3) — 
    Control — 18.5 (±1.3) −43.6 (±1.2) 138.4 (±29.5) 214.5 (±59.0) — 
    5 μM SCH23390 (D1 antagonist) (n = 7) — 19.3 (±2.5) −43.7 (±1.3) 134.2 (±28.1) 218.7 (±59.3) — 
    5 μM SCH23390 + 50 μM DA (n = 7) — 19.6 (±2.6) −44.3 (±1.2) 132.1 (±28.0) 222.2 (±59.8) — 
    Control — 13.1 (±3.8) −43.3 (±2.0) 105.4 (±24.1) 193.3 (±40.9) — 
    5 μM sulpiride (D2 antagonist) (n = 5) — 16.1 (±5.0) −44.2 (±1.8)** 105.1 (±26.7) 188.3 (±34.1) — 
    5 μM sulpiride + 10 μM DA (n = 5) — 26.3 (±5.6)** −45.9 (±1.5) 90.9 (±21.6) 189.2 (±29.0) — 
Adapting cells       
    Control −78.0 (±2.0) (n = 3) 6.5 (±1.7) −40.4 (±1.7) 77.9 (±20.2) 273.1 (±20.2) 66.9 (±30.4) 
    10 μM SKF 38393 or SKF 81297 (D1 agonists) (n = 8) −74.5 (±2.0) 7.3 (±1.1) −43.3 (±2.1)* 84.3 (±25.3) 270.0 (±44.6) 41.7 (±15.2) 

Note: In the case of experiments involving antagonists, the effects of DA were compared with the effects of the antagonist alone. Significant differences compared with control or antagonist baseline condition, respectively, are indicated as * for P < 0.05 and ** for P < 0.01. Note that changes in the resting membrane potential were not obtained for all cells within a given drug condition. The numbers in brackets give the actual number of cells for which values were obtained.

Figure 6.

The increase in membrane excitability in FS is mediated by D1 but not D2 receptors. (A) Application of a D1 receptor agonist (SKF 38393 or SKF 81297 at 10 μM) mimicks the effects of DA on evoked firing. (B) Similarly, when D2-like receptors were blocked by the antagonist sulpiride (5 μM; bath applied for at least 10 min before DA application), thus leaving only D1-type receptors available, subsequent DA application (10 μM) lead to large increases in spike firing. On the other hand, activation of D2-type receptors by specific agonists or DA itself had little effect on intrinsic excitability. (C) Application of the D2 receptor agonist quinpirole has no significant effect on spike firing. (D) Blockade of D1-like receptors by the antagonist SCH23990 (5 μM; bath applied for at least 10 min before DA application) prevents the increase in intrinsic excitability normally seen with bath application of DA (50 μM). The arrows indicate the measured action potential threshold in control or drug conditions. See Results and Table 2 for details.

Figure 6.

The increase in membrane excitability in FS is mediated by D1 but not D2 receptors. (A) Application of a D1 receptor agonist (SKF 38393 or SKF 81297 at 10 μM) mimicks the effects of DA on evoked firing. (B) Similarly, when D2-like receptors were blocked by the antagonist sulpiride (5 μM; bath applied for at least 10 min before DA application), thus leaving only D1-type receptors available, subsequent DA application (10 μM) lead to large increases in spike firing. On the other hand, activation of D2-type receptors by specific agonists or DA itself had little effect on intrinsic excitability. (C) Application of the D2 receptor agonist quinpirole has no significant effect on spike firing. (D) Blockade of D1-like receptors by the antagonist SCH23990 (5 μM; bath applied for at least 10 min before DA application) prevents the increase in intrinsic excitability normally seen with bath application of DA (50 μM). The arrows indicate the measured action potential threshold in control or drug conditions. See Results and Table 2 for details.

Blockade of D1-type receptors by the antagonists SCH23390 further underlined the importance of D1 receptors for the effects of DA in FS cells: When DA was bath applied in the presence of SCH23390 (following 10–15 min pre-application of the antagonist alone), no significant changes in the number of spikes or the action potential threshold were observed (Fig. 6D and Table 2).

Activation of D2- and D3-like receptors by (±)-Quinpirole dihydrochloride (n = 6) on the other hand did not alter measures of membrane excitability in FS cells (Fig. 6C and Table 2). Because anatomical studies have suggested that interneurons in the primate DLPFC preferentially express receptors of the D4 subtype (Mrzljak and others 1996), we also tested the effects of the D4 receptor–specific agonist N-(methyl)-4-(2-cyanophenyl)piperazinyl-3-methybenzamide maleate (PD 168077) on membrane properties of FS interneurons (n = 5). As summarized in Table 2, PD 168077 similarly had no effect on membrane excitability. Finally, blockade of D2-like receptors by the antagonist sulpiride (n = 5) did not prevent the increase in excitability in FS cells observed following subsequent coapplication of DA, thus further implicating D1 receptors in the DA-mediated increase in excitability (Fig. 6B and Table 2). However, in our small sample, the actions of DA in the presence of sulpiride only partly mimicked the effects of the full agonist (i.e., DA alone) or of D1 receptor stimulation via a selective agonist (see above). Although DA in the presence of sulpiride strongly increased the number of evoked spikes, it did not significantly change the action potential threshold or the current required to evoke the first spike. Rather, sulpiride by itself already significantly lowered the threshold of the initial action potential (Table 2). One possible explanation for this effect could be activation of D1 receptors by a background level of DA in the slice. Taken together, these data show that the effects of DA on membrane excitability in FS interneurons require activation of D1-type receptors.

Discussion

Our data show that activation of DA D1-type receptors results in a marked increase in the excitability of FS interneurons in DLPFC, producing an increase in GABAergic inhibition, without altering action potential–independent release of GABA. The apparent network-specific regulation of the DLPFC by DA has implications for our understanding of both normal information processing in this brain region and of the pathological changes that may underlie diseases such as schizophrenia and drug addiction.

Mechanisms and Pharmacology of the Dopaminergic Modulation of Inhibition

GABAergic interneurons in both rat and monkey PFC have been shown to possess D1- and/or D2-type receptors (Vincent and others 1995; Mrzljak and others 1996; Vysokanov and others 1998; Khan and others 1998; LeMoine and Gaspar 1998; Muly and others 1998; Wedzony and others 2000; Paspalas and Goldman-Rakic 2005). Our data show that activation of DA D1-type receptors alone can account for the increase in FS neuron excitability and the increased frequency of GABAergic events in PCs. In the rat, most studies that measured sIPSCs or membrane excitability of FS interneurons found similar DA and D1 receptor–mediated increases (Zhou and Hablitz 1999; Seamans and others 2001; Gorelova and others 2002). However, the effects of DA on GABAergic synaptic transmission in the PFC are complex, and both a reduction (Law-Tho and others 1994; Gonzalez-Islas and Hablitz 2001; Seamans and others 2001; Wang and others 2002; Gao and others 2003; Trantham-Davidson and others 2004) and an increase (Penit-Soria and others 1987; Zhou and Hablitz 1999; Gulledge and Jaffe 2001; Seamans and others 2001; Gao and others 2003; Trantham-Davidson and others 2004) in either the amplitude of evoked inhibitory synaptic events or the frequency of sIPSCs have been described. Thus, it appears that DA can differentially modulate spontaneous and evoked inhibitory synaptic events, despite that both depend on action potential–mediated release of GABA and hence should share common presynaptic release mechanisms (Seamans and Yang 2004). Our data from mIPSCs in TTX (Fig. 2) argue against DA-induced changes in the probability of release at GABAergic terminals.

One explanation for the observed differences is that the IPSCs evoked by extracellular stimulation reflect GABA release from selected fibers, whereas sIPSCs reflect multiple divergent inputs. Indirect evidence for this stems from recordings of unitary connections between PCs and different types of interneurons that show a cell type–specific modulation of IPSPs by DA (Gao and others 2003). However, the results from this latter study suggested a presynaptic D1 receptor–mediated “reduction” in IPSP amplitude at FS-PC connections, which appears to be in contrast to the increase in FS neuron membrane excitability that we report here and that also was seen by the same authors in the ferret (Gao and Goldman-Rakic 2003). Finally, recent data suggest that the effects of DA on evoked IPSCs may be time and concentration dependent, with high DA concentrations preferentially activating D2 receptors to (transiently) reduce IPSC amplitude and low doses of DA preferentially activating D1 receptors to produce a prolonged increase of IPSC amplitude (Seamans and others 2001; Trantham-Davidson and others 2004; but see Gao and others 2003).

Dopaminergic Modulation of Membrane Excitability in FS Interneurons

In cortical and striatal cells, DA modulates a variety of currents, including Na+ and Ca++ currents that govern spike initiation and repetitive firing (for reviews, see Nicola and others 2000; Seamans and Yang 2004). We observed a consistent depolarization of FS interneurons by DA and a D1 receptor–mediated increase in repetitive firing that was accompanied by a reduction in action potential threshold and shortening of ISIs (Fig. 4 and Table 2). In the rat, D1 receptor activation can change the excitability of both PCs and FS interneurons by reducing several K+ currents (Yang and Seamans 1996; Gorelova and others 2002; Dong and White 2003). In FS interneurons, activation of D1-type receptors suppresses a Cs-sensitive inward rectifying K+ current and a resting leak K+ current leading to membrane depolarization (Gorelova and others 2002). While we did see a strong and consistent depolarization in 14 cells tested with DA (10 and 50 μM pooled), the effects of D1 receptor activation by selective agonists were not as pronounced. Although each individual cell depolarized, this trend failed to reach statistical significance in our small sample of 5 neurons tested (out of 12).

Results from experiments in rats furthermore show that both in PCs and interneurons, suppression of a slowly inactivating outward K+ current (ID) leads to an increase in repetitive firing and reduction of the spike threshold in response to depolarizing inputs (Yang and Seamans 1996; Gorelova and others 2002; Dong and White 2003; Kröner and others 2005). The study by Gorelova and others (2002) examined the effects of DA on membrane depolarization (caused by the inward rectifying K+ current and the resting leak K+ current) in both FS cells and adapting interneurons; however, the effects of DA on spike firing and the modulation of the ID current were subsequently only assessed in FS cells. Here, we replicate the absence of a membrane depolarization in adapting interneurons (Gorelova and others 2002) and also show that neither DA nor D1 receptor agonists affect evoked firing in these cells. This suggests that in adapting interneurons, ID or other currents that regulate adaptation are not a target of DA actions.

The long-lasting modulation of intrinsic excitability seen in FS interneurons (Fig. 5) is in agreement with previous reported effects of D1 activation on synaptic transmission and evoked firing, both in vivo and in vitro (Trantham-Davidson and others 2004; Lavin and others 2005; Kröner and others 2005). The functional significance of these prolonged effects is not readily apparent, but Seamans and Yang (2004) have argued that DA provides only limited information but rather provides a processing tone and regulates the gain within the PFC network. Furthermore, in the behaving animal, in vivo mechanisms are likely to exist that can curtail the prolonged effects of D1 receptor activation, such as a DA concentration–dependent antagonism via D2 receptors (Trantham-Davidson and others 2004; Seamans and Yang 2004).

Differences in the Organization of the Prefrontal Network in Primates and Rodents

Taken together, our results indicate that at the single-cell level, the effects of DA in primates and nonprimate species are remarkably similar. This correspondence may be surprising given the number of species differences in the organization of the prefrontal cortical network between rodents and primates. Whereas dorsolateral prefrontal cortical areas in macaque monkeys and humans share multiple characteristics with regard to cytoarchitecture, hodology (Petrides and Pandya 1999), and DA innervation (Lewis and Sesack 1997), the organization of the frontal cortex and its dopaminergic innervation are vastly different in rats versus primates (Björklund and Lindvall 1984; van Eden and others 1987; Berger and others 1991; Preuss 1995; Lewis and Sesack 1997; Williams and Goldman-Rakic 1998). Chief among these differences is the laminar distribution of DA fibers and DA receptors, which in monkey and human PFC are abundant in both deep and superficial layers, but in the PFC of rats are abundant only in layers 5 and 6 (Berger and others 1991; Preuss 1995; Lewis and Sesack 1997). In the monkey PFC, superficial layers contain the majority of neurons that provide output to and receive input from other neocortical regions (Selemon and Goldman-Rakic 1988; Lewis and others 2002), and delay period activity during working memory tasks is most prominent in layers 2/3 (Friedman and Goldman-Rakic 1994). Moreover, differences exist between primate and nonprimate species in the characteristics of interneuron subtypes with regard to the firing properties of cells (Kawaguchi 1993, 1995; Zaitsev and others 2005; Krimer and others 2005; present study), the morphological characteristics of classes of interneurons (Somogyi and Cowey 1984; Yánez and others 2005), and the relative number and distribution of subpopulations defined by calcium-binding proteins (Conde and others 1994; Gabbott and Bacon 1996; Gabbott and others 1997; Kawaguchi and Kubota 1997). Thus, although in both primates and rodents DA increases inhibition through activation of FS cells, the qualitative effect of DA on intracortical communication will strongly depend on the properties and connections of the network that is being modulated.

Implications for Cortical Processing and Working Memory

During delayed response tasks, putative GABAergic interneurons show task-related activity similar to that of nearby PCs, whereas interneurons and PCs within different columns exhibit cross-directional tuning (Wilson and others 1994; Rao and others 1999; Constantinidis and Goldman-Rakic 2002). This spatially tuned delay period activity is disrupted by local application of a GABA receptor antagonist (Rao and others 2000). DA, via D1 receptor activation, enhances working memory–related network activity by increasing delay- and response-related firing relative to background activity (Sawaguchi and others 1988, 1990). Our data demonstrate that D1 receptor activation increases the excitability of FS interneurons and GABAergic conductances, which may thus sharpen the spatial “cognitive” tuning of PCs and focus activity on task-relevant items (Goldman-Rakic, 1995; Rao and others 1999).

Although the persistent mnemonic-related activity in the primate PFC has consistently been shown to be modulated by D1 receptor activation (Sawaguchi and others 1988, 1990; Sawaguchi and Goldman-Rakic 1994; Williams and Goldman-Rakic 1995; Müller and others 1998; Wang and others 2004), a recent study also demonstrated a specific role for D2 receptors in modulating the motor-related neural activity of a typical working memory task (Wang and others 2004), thus integrating previous conflicting results in monkeys and humans (Luciana and others 1992; Arnsten and others 1995; but see Mehta and others 2005).

GABAergic neurons in rat and primate PFC possess receptors of the D2 family (Mrzljak and others 1996; Vysokanov and others 1998; Khan and others 1998; LeMoine and Gaspar 1998; Wedzony and others 2000), but their contribution to the behavioral output is still unclear. Our present data and previous studies in the rat (Gorelova and others 2002) have failed to demonstrate a role of D2-like receptors in modulating somatic excitability (but see Tseng and O'Donnell 2004). And although D2 agonists can increase the release of GABA in the PFC (Grobin and Deutch 1998), electrophysiological investigations into the effects of D2-type receptor activation suggest that GABAergic synaptic transmission is reduced due to presynaptic mechanisms or postsynaptic receptor down-regulation (Wang and others 2002; Trantham-Davidson and others 2004).

The absence of a D2 effect in our preparation is unlikely to reflect a developmentally immature dopaminergic system. The tissue used in our studies was obtained from animals 4–5 years of age. In primates, the catecholaminergic innervation reaches adult levels between 2–5 years of age (Rosenberg and Lewis 1995; Lambe and others 2000). Similarly, the adult distribution of both D1- and D2-type dopaminergic receptors in most cortical areas is achieved prenatally, soon after all cortical neurons assume their final positions (Lidow 1995). The density of all monoaminergic receptors is highest at about 2 months postnatally and then gradually declines to adult densities by puberty at about 3 years of age (Lidow and Rakic 1992).

Axons of GABAergic interneurons target distinct subcellular domains on principal neurons and therefore appear to have specialized roles in regulating pyramidal neuron activity. Layer 2/3 interneurons with adapting firing patterns express the calcium-binding proteins calbindin or calretinin (Zaitsev and others 2005). These groups include double bouquet and neurogliaform cells that target distal dendrites of PCs (Somogyi and Cowey 1984; Tamas and others 2003; Zaitsev and others 2005; Krimer and others 2005; Yánez and others 2005), and they are believed to regulate the vertical integration of synaptic inputs along the dendritic tree of PCs. Our data and previous findings in rat and ferret PFC (Gorelova and others 2002; Gao and Goldman-Rakic 2003) show that DA does not affect the membrane properties of interneurons with adapting firing patterns, and previous anatomical data showing an absence of DA innervation to calretinin-positive cells also make them an unlikely target for DA modulation (Sesack and others 1995; but see Gao and others 2003).

FS interneurons on the other hand express the calcium-binding protein parvalbumin (Zaitsev and others 2005) and include chandelier or basket-type cells (Fig. 3), whose synapses target the axon initial segment (in the case of chandelier cells) or the soma and proximal dendrites of PCs (Somogyi and others 1983; Tamas and others 2000; Szabadics and others 2006). This perisomatic innervation is suited to provide tight control over the output of PCs (Szabadics and others 2006) and is thought to regulate synchronous and oscillatory activity of large populations of PCs (Cobb and others 1995; Tamas and others 2000).

DA modulates the excitatory synaptic inputs onto FS cells to improve detection of bursts of excitatory postsynaptic potentials above background synaptic activity (González-Burgos and others 2005). The excitatory effects of DA on the membrane properties of FS cells reported here could serve to overcome the strongly depressing effects of repetitive activation on their synaptic inputs (González-Burgos and others 2004, 2005), enabling them to fire throughout periods of sustained synaptic activity and to maintain a balance between excitation and inhibition during heightened activity. On the other hand, higher than normal concentrations of DA—as they may occur in the PFC during stressful events or as a result of pharmacological manipulations—could shift the balance in the network by disproportionally activating inhibitory interneurons. This may account for the “inhibitory” actions of D1 receptor activation on PC firing in vivo (Williams and Goldman-Rakic 1995; Murphy and others 1996; Zahrt and others 1997).

Finally, alterations in the dopaminergic regulation of GABA neurons have clinical relevance for the pathophysiology of schizophrenia, where both the synthesis and reuptake of GABA are reduced in a subset of PFC interneurons, and the subpopulation of parvalbumin-expressing neurons is particularly vulnerable (Lewis and others 2005). Both a general reduction in the DA innervation (Akil and others 1999) and a miswiring of DA afferents onto interneurons (Benes and others 1997) could affect regulation of inhibition during cortical processing. Thus, a breakdown of spatial or temporal PC tuning due to changes in DA and/or GABA transmission might underlie deficits in working memory (Spencer and others 2003) and other cognitive deficits in schizophrenia (Winterer and Weinberger 2004; Lewis and others 2005).

The authors wish to thank Olga Krimer and Ingelore Kröner for excellent histological processing and reconstructions of neurons and Dr Guillermo Gonzalez-Burgos for continuous cooperation. Support was provided by National Institutes of Health grants MH51234, MH45156, and K08 MH63561-01 and a National Alliance for Research on Schizophrenia and Depression (NARSAD) Independent Investigator Award (GB). Conflict of Interest: None declared.

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