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Background: Low dopamine D receptor availability in the nucleus accumbens shell is associated with highly impulsive 2/3 behavior in rats as measured by premature responses in a cued attentional task. However, it is unclear whether dopamine D receptor availability in the nucleus accumbens is equally linked to intolerance for delayed rewards, a related form of 2/3 impulsivity. Methods: We investigated the relationship between D receptor availability in the nucleus accumbens and impulsivity in 2/3 a delay-discounting task where animals must choose between immediate, small-magnitude rewards and delayed, larger- magnitude rewards. Corticostriatal D receptor availability was measured in rats stratified for high and low impulsivity using 2/3 18 3 in vivo [ F]fallypride positron emission tomography and ex vivo [ H]raclopride autoradiography. Resting-state functional connectivity in limbic corticostriatal networks was also assessed using fMRI. Results: Delay-discounting task impulsivity was inversely related to D receptor availability in the nucleus accumbens core 2/3 but not the dorsal striatum, with higher D binding in the nucleus accumbens shell of high-impulsive rats compared with 2/3 low-impulsive rats. D receptor availability was associated with stronger connectivity between the cingulate cortex and 2/3 hippocampus of high- vs low-impulsive rats. Conclusions: We conclude that delay-discounting task impulsivity is associated with low D receptor binding in the nucleus 2/3 accumbens core. Thus, two related forms of waiting impulsivity—premature responding and delay intolerance in a delay-of- reward task—implicate an involvement of D receptor availability in the nucleus accumbens shell and core, respectively. This 2/3 dissociation may be causal or consequential to enhanced functional connectivity of limbic brain circuitry and hold relevance for attention-deficit/hyperactivity disorder, drug addiction, and other psychiatric disorders. Keywords: delay discounting, dopamine D receptor, impulsivity, nucleus accumbens, resting-state fMRI, functional 2/3 connectivity Received: January 11, 2018; Revised: March 8, 2018; Accepted: March 14, 2018 © The Author(s) 2018. Published by Oxford University Press on behalf of CINP. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, 705 provided the original work is properly cited. For commercial re-use, please contact firstname.lastname@example.org Downloaded from https://academic.oup.com/ijnp/article-abstract/21/7/705/4938500 by Ed 'DeepDyve' Gillespie user on 03 July 2018 706 | International Journal of Neuropsychopharmacology, 2018 Significance Statement Understanding the neurobiology underlying choice impulsivity, a psychiatric symptom with cross-diagnostic significance, is key to identifying novel therapies for treating impulsivity. Using the delay discounting task, we selected rats with extreme high- and low-impulsive phenotypes to investigate whether differences in dopamine D receptor binding and functional limbic networks 2/3 are associated with trait-like impulsivity. We report a novel inverse correlation between D receptor availability in the ventral 2/3 striatum and impulsive behavior, specifically, lower D receptor binding within the nucleus accumbens core in high- vs low- 2/3 impulsive rats. Strong connectivity within the limbic network in high- vs low-impulsive rats suggests that differences in striatal D receptor availability may underlie naturally occurring impulsivity and be either causal or consequential to limbic network 2/3 connectivity modulation. critical for impulsive choice and consistent with its well-known Introduction role in the attribution of reward value and reward-related behav- Impulsivity is a complex, multifaceted behavioral construct, iors (London et al., 2000; Schoenbaum et al., 2009; Rudebeck and characterized by the tendency to act prematurely and without Murray, 2014). foresight (Dalley et al., 2011). It can be observed behaviorally In the current study, we investigated whether trait-like as impaired response inhibition (“stopping” impulsivity) or the impulsivity in the DDT is associated with differences in D 2/3 inability to wait or tolerate delayed rewards (“waiting” impulsiv- receptor binding and corticolimbic functional network modula- ity). Recent progress in the neuroscientific approach to impul- tion. We hypothesized that naturally occurring impulsivity on sivity has enabled a dissection of these two major components this task may be associated with low D receptor availability in 2/3 of behavioral function according to their underlying neural sub- the ventral striatum, which may impact dopaminergic neuro- strates (Dalley et al., 2011 Dalle ; y and Robbins, 2017), indicating transmission and functional connectivity within limbic corti- that overlapping but distinct corticostriatal substrates underlie costriatal circuitry. stopping and waiting subtypes of impulsivity. Understanding the contribution of inter-individual differ - Materials and Methods ences or trait variables to treatment outcome for patients with impulsivity disorders represents a major challenge to the ef- Subjects and Experimental Design fective treatment of these patients (Dalley et al., 2011 Ho ) wever, investigation into the etiology of natural variation in impulsive Subjects were 96 male Lister-hooded rats (Charles River) weigh- ing 250 to 300 g at the start of the experiment and maintained at choice behavior is limited. Impulsive choice can be defined as the preferential choice of risky or immediate rewards. In add- 85% to 95% of their free-feeding weight. Water was available ad libitum. Animals were group-housed, 4 per cage, and kept under ition to “reward discounting,” “probability discounting” can be assessed when the dimension of waiting is replaced with that 12-hour-light/-dark cycle (white light on/red light off from 6:00 am to 6:00 pm). Behavioral experiments were conducted during of reinforcer uncertainty. Both forms of discounting behavior contribute to performance on more complex behavioral tasks in the day, that is, during the inactive phase of the rats. All experi- mental procedures were authorized by the Local Animal Care and a laboratory setting, such as the Iowa Gambling Task (Bechara, 2003) and the delay discounting task (DDT), where a subject’s Use Committee in accordance with local animal care guidelines, Association for Assessment and Accreditation of Laboratory preference for immediate, small rewards vs larger but delayed rewards is assessed. Animal Care regulations and the USDA Animal Welfare Act and took place in an Association for Assessment and Accreditation Deficits in a specific type of impulsive anticipatory respond- ing, often referred to as motor impulsivity or premature of Laboratory Animal Care-certified facility. Experiments are reported in accordance with the Animal Research: Reporting of responding, have been extensively characterized through nu- merous neurochemical and neuroanatomical manipulations. In Vivo Experiments Guidelines (Kilkenny et al., 2012) We stratified rats according to their behavioral perform- Dopamine D receptor availability in the ventral striatum, for 2/3 example, is predictive of impulsivity on a visual attentional ance on the DDT, selecting those exhibiting extreme high- and low-impulsivity phenotypes, as designated by a number of be- task (Dalley et al., 2007Besson et ; al., 2013; Caprioli et al., 2015; Robertson et al., 2015; Dalley and Robbins, 2017). havioral measures. Additionally, we screened these rats for vari- ations in baseline locomotor activity to assess the validity and Imaging studies in normal healthy volunteers as well as patient populations support the link between low striatal D selectivity of the behavior. The selected rats were then assessed 2/3 for in vivo D receptor availability using [18F]fallypride posi- receptor availability, subsequent dopaminergic dysfunction, and 2/3 elevated levels of self-report and laboratory-assessed impulsiv- tron emission tomography (PET) where we focused on cortical as well as dorsal and ventral striatal regions of interest. Ex vivo ity measures (Lee et al., 2009; Buckholtz et al., 2010Ghahr ; emani et al., 2012; Ballard et al., 2015). The ventral striatum, including autoradiography with [3H]raclopride was used to further lo- calize differences in striatal D receptor availability. Although the nucleus accumbens (NAcb), forms part of the limbic sys- 2/3 tem and the orbitofrontal network; changes within these net- the striatum is an important neural focus of impulsive behavior, it operates within a complex network comprising not only the works may underlie naturally occurring differences in impulsive behavior. Rat lesion studies suggest that the neuroanatomical basal ganglia themselves but also “top-down” influences from limbic structures and the neocortex, including the prefrontal substrates underlying impulsive choice behavior involve key nodes of these networks, including the NAcb (Cardinal et al., cortex, and “bottom-up” modulation from monoamine systems including, but not limited to, the dopaminergic system (Dalley 2001), basolateral amygdala (Winstanley et al., 2004), and hippo- campus (Cheung and Cardinal, 2005). Within the prefrontal and Robbins, 2017). The high- and low-impulsive rats were therefore further assessed by fMRI. cortex, the orbitofrontal cortex (OFC) appears to be specifically Downloaded from https://academic.oup.com/ijnp/article-abstract/21/7/705/4938500 by Ed 'DeepDyve' Gillespie user on 03 July 2018 Barlow et al. | 707 magazine within 10 seconds to trigger the presentation of both Locomotor Activity levers and lever lights. A failure to respond on either lever within Since impulsivity could be primarily or secondarily affected by 10 seconds (an omission) resulted in the retraction of both levers differences in motor activity, locomotor activity was assessed with all lights extinguished and an inter-trial interval initiated using 8 Tru Scan arena chambers each equipped with 2 photo- before the next trial. Responding on one of the levers within 10 beam sensor rings, allowing the detection of activity in 3 orthog- seconds resulted in the retraction of both levers with all lights onal planes (Coulbourn Instruments) as previously described extinguished. Reward delivery was preceded by the illumination (Isherwood et al., 2017). Testing duration was 30 minutes and of the magazine light either immediately or after the chosen took place between 1:00 pm and 4:00 pm. Mean distance travelled delay. The length of the inter-trial interval depended the choice (cm) over 30 minutes was automatically recorded using Tru Scan of the immediate or delayed lever and followed reward delivery 2 software provided by Coulbourn Instruments. to ensure each trial was exactly 72 seconds in duration. Delay Discounting Impulsivity Screening Testing was carried out as previously reported (Isherwood et al., For stratification rats were ranked, from high to low impulsive, 2017) using 32 operant chambers (Med Associates) enclosed in according to their performance on the DDT based on 3 task a sound-attenuating box fitted with a fan for ventilation and parameters: the indifference point (the time point at which ani- masking of external noise. Each chamber was equipped with 2 mals’ choice of the delayed lever is 50%), the steepness of the retractable levers located either side of a centrally located food discounting curve (k), and the area under the curve (AUC). The magazine, into which rodent food pellets (Sandown Scientific) upper and lower 15th centiles of the ranked rats were termed were delivered. A stimulus light was located above each lever, high impulsive (n = 11) and low impulsive (n = 10), respectively and an infrared beam positioned across the food magazine (Table 1). The remaining rats were termed mid impulsive (n = 54). detected reward collection. The testing apparatus was con- Animals with extreme high and low trait-like impulsivity trolled by Med Associates Software. underwent PET imaging and whole-brain resting-state fMRI Subjects were initially habituated to the test apparatus and were used for subsequent ex vivo receptor autoradiography before commencing lever-press training under a fixed-ratio studies. The mid impulsive rats were excluded from any further schedule of reinforcement. During these sessions, both levers experiments. were extended and the lever lights were illuminated; a press on either lever resulted in the delivery of a reward pellet. Rats PET Data Acquisition and PET Data Evaluation were required to reach a criterion of 60 lever presses within a 60-minute period (30 presses on each lever). After this initial All PET scans were performed using the Inveon multi-modality training phase, rats were then exposed to a simplified version of small animal PET/CT scanner (Siemens Healthcare GmbH) with the DDT. Animals were trained to nose-poke in the food maga- an axial field of view of 12.7 cm and a spatial resolution in the zine to trigger the illumination of a lever light and the presen- reconstructed images of 1.4 mm (full width at half maximum) tation of the lever. A response on the lever within 10 seconds (Beltzer et al., 2016). The order of scanning was strictly balanced (limited hold) resulted in the lever light being extinguished and across days. All data acquisition was carried out under isoflu- retraction of the lever, the illumination of the food magazine, rane anaesthesia (3% for induction and 1.5% for maintenance). and the delivery of a single reward pellet. The levers were pre- For [ F]fallypride scans, the animals were placed feet first prone sented pseudo-randomly throughout the session. Rats were in the central field of view on rat brain beds (Medres). The body required to reach a criterion of 60 completed trials within a temperature of the animals was maintained at 37°C throughout 60-minute period. the course of the study using a heating blanket and monitored Each training session consisted of 6 blocks of 10 trials, with by a rectal temperature probe. Respiration was monitored by each trial lasting exactly 72 seconds. Each block of trials began an air-filled pillow positioned under the abdomen of the rats. with 4 forced-choice trials, where only one lever was presented The breathing frequency was maintained at 75 to 80 cycles/ in a pseudorandom order. Six free-choice trials were then min by adjustment of the anesthesia. [ F]fallypride, prepared introduced throughout the task; responding on the right lever using a modified method of a previously described radiosynthe- resulted in the immediate delivery of a single reward pellet. sis (Mukherjee et al., 1995), was then administered as a bolus Responses on the left lever resulted in the delayed delivery of (0.5 mL) i.v. via the tail vein with a specific activity of 20.37± 3.27 3 reward pellets, with increasing delay across blocks of 0, 2, 4, 8, MBq. There were no differences of radioactive-related param- 16, and 32 seconds. As in the pretraining protocol, each trial was eters (injected amounts, specific activity) between the 2 experi- initiated by the illumination of the house and magazine light. mental groups. Sixty-minute PET scans were acquired with an Rats were required to make a nose-poke response in the food energy window of 511 keV and a coincidence window of 3.432 Table 1. Mean, Median, and Interquartile Ranges of the Behavioral Measures Used to Assess Impulsivity on the DDT in High- (n = 11), Mid- (n = 54) and Low-Impulsivity (n = 10) Rats AUC k IP Mean Median IQ range Mean Median IQ range Mean Median IQ range HI 162 186 48 3.421 2.096 0.533 0.347 0.404 0.139 MI 872 661 852 0.517 0.375 0.696 5.284 2.466 5.751 LI 2659 2652 807 0.014 0.011 0.021 29.31 29.31 4.620 AUC, area under the curve; DDT, delay discounting task; HI, high-impulsivity; IP, indifference point; IQ, interquartile; k, steepness of the discounting curve; LI, low- impulsivity; MI, mid-impulsivity. Downloaded from https://academic.oup.com/ijnp/article-abstract/21/7/705/4938500 by Ed 'DeepDyve' Gillespie user on 03 July 2018 708 | International Journal of Neuropsychopharmacology, 2018 ns. PET acquisitions were reconstructed using a filtered back (Müller et al., 2013) and was performed using the Tensor Imaging projection algorithm and the following histogramming: 6 × 10 and Fiber Tracking software package (Müller et al., 2007). seconds, 3 × 20 seconds, 10 × 60 seconds, 10 × 120 seconds, and Preprocessing included (1) spatial upsampling to an isogrid, (2) 7 × 240 seconds (in total 36 frames). An image zoom of 1 and a motion correction, (3) normalization, (4) temporal demeaning 256 × 256 matrix were used yielding in a pixel size of 0.039 cm. and linear detrending, (5) temporal bandpass filtering, and (6) An anatomical CT scan was used for attenuation correction. spatial smoothing. Furthermore, all PET scans were corrected for decay and dead Spatial upsampling from 200 × 200 × 750 μm into a time, and normalization was applied. 55 × 55 × 55 μm isogrid (matrix, 256× 256 × 256) was performed [ F]fallypride data were analyzed using the simplified refer - by means of a nonparametric k-nearest neighbor regression ence tissue model (Maier et al., 2014) provided by the Siemens approach using the average voxel intensity of the k-nearest Inveon Research Workplace (version 220.127.116.11) to yield a binding neighbor voxels weighted by the inverse of their distance. potential. For the determination of binding potential, we used Upsampling minimizes partial volume effects in mice (Müller the NAcb, prefrontal cortex, putamen, dorsolateral striatum, and et al., 2013). All volumes were motion-corrected using a rigid motor cortex as target ROI and the cerebellum as the reference body transformation in all directions (6 degrees of freedom) with region. This cerebellum reference region was applied to the res- respect to the first volume to correct for physical motion con- liced dynamic [ F]fallypride image set to generate a cerebellum founding factors such as respiratory and cardiovascular motion time-activity curve. Regions of interest (ROI) were determined as well as potential muscular relaxation of the anesthetized using an MRI-based template that was transferred to the PET-CT rat body over time. An iterative landmark-based deformation data set after alignment of MRI and PET brain images. approach was used to normalize all EPI volumes into a standard stereotaxic rat brain (Müller et al., 2013). The functional image time series were demeaned and detrended to correct for possible Resting-State fMRI Data Acquisition scanner drifts and were then bandpass filtered using a 6th-order The high-impulsivity and low-impulsivity subgroups under - Butterworth bandpass filter design with cut-off frequencies in went whole-brain resting-state fMRI. Data acquisition was car - the range of 0.01< f < 0.08 Hz. Spatial filtering was applied to the ried out under isoflurane anesthesia (3% for induction and 1.5% EPI series by using a 333-μm, 3-dimensional, full-width at half for maintenance). The animals were placed in a stereotaxic head maximum Gaussian blur filter, which equals about twice the in- support (Bruker BioSpin) to immobilize the head. Body tempera- plane resolution (200× 200 μm ) as a common choice according ture was maintained by an integrated water-based heating at to the matched filter design. Finally, the first 30 of the 300 vol- 37°C and monitored by a rectal temperature probe. Respiration umes were discarded owing to the transient filter response to was monitored by an air-filled pillow positioned under the ab- correct for possible scanner oscillations at the beginning of the domen of the rats. The breathing frequency was maintained at fMRI protocol as well as to allow the rats to adapt to the experi- 75 to 80 cycles/min by adjusting anesthesia. The rats rapidly mental condition (e.g., noisy environment, muscular relaxation). recovered after the termination of anesthesia at the end of the MRI procedure. Imaging was done on a 9.4T Biospec scanner fMRI Data Analysis (Bruker BioSpin) and acquired with a Bruker linear transmit volume coil and a parallel receive surface array designed for Spherical a priori defined seed regions (r = 278 μm) were chosen rat’s head MRI. First, 3 orthogonal Turbo RARE -w T eighted based on the anatomical structures belonging to the 5 networks images were acquired to enable the slice positioning for the of interest to generate the whole-brain correlation maps: (1) a fMRI data sets (repetition time [TR] 2000 ms, effective echo time seed in the limbic cortex; (2) a seed in the retrosplenial cortex; [TE] 20.7 ms, 15 slices, 1 mm). Subsequently, resting-state data- (3) a seed in the OFC, and 2 seeds each (4) in the bilateral som- sets were acquired using single-shot gradient-echo Echo Planar atosensory cortex and (5) in the cerebellar cortex were used to Imaging (EPI) sequence with TR 2000 ms, TE 20.7 ms. Twelve axial generate the whole-brain correlation maps for the (1) limbic slices of 1 mm and a gap of 0.25 mm were recorded with a field- network, (2) default mode network, (3) orbitofrontal network of-view of 30 × 30 mm and matrix size of 128 × 128, resulting in (Sforazzini et al., 2014), (4) somatosensory networks (Jonckers voxel dimensions of 0.23 × 0.23 × 1 mm . The used bandwidth was et al., 2011), and (5) cerebellar network, respectively (Sforazzini 400 kHz (3125 Hz/voxel). Each of the resting-state fMRI data sets et al., 2014). The seed regions used to define the networks are comprised 300 repetitions, resulting in a scanning time of 10 common choices, since the seeds are located in major nodes of minutes for each resting-state fMRI dataset. the corresponding functional networks (Smith et al., 2009 Lair ; d et al., 2011). The extracted arithmetically averaged time-courses of each seed region were correlated with the time series of all Preprocessing of Functional Imaging Data other voxels across the whole brain, yielding a corresponding To transfer analysis procedures proven valuable in human Pearson’s product moment correlation coefficient (r-value) for resting-state fMRI, similar volume-to-voxel size relations as in each voxel. Finally, the individual animal’s correlation maps humans were used for the rat scans. The required voxel reso- were Fisher’s r- to z-transformed to normally distributed z(r) lution and brain grid coverage resulted in a plane (sagittal,- cor scores that were used for statistical analysis. onal) brain grid of approximately 50 voxels and an axial grid The two-sided parametric Student’s t test for unequal vari- of approximately 20 voxels to comparatively match brain grid ances was used to test for voxel-wise differences between coverage of standard human resting-state fMRI. Before func- low- and high-impulsivity rats for both networks. Possible cor - tional imaging data analysis, to ensure sufficient image quality, relations between functional connectivity measures and impul- all volumes of the EPI images were visually inspected by an sivity were studied using a data-driven approach by means of experienced neuroimaging expert for proper registration. None Spearman rank-order correlation (Gorges et al., 2016). The z(r) of the functional datasets had to be excluded before the ana- scores corresponding to the limbic and orbitofrontal networks lysis because of artifacts. The functional data analysis followed were correlated with the DDT–AUC score for each voxel across a standardized procedure with adaptation for rodent analysis the whole brain for each network. The resulting P values for Downloaded from https://academic.oup.com/ijnp/article-abstract/21/7/705/4938500 by Ed 'DeepDyve' Gillespie user on 03 July 2018 Barlow et al. | 709 (1) group comparison and (2) correlation analysis were consid- are detailed in Table 1. One-Way ANOVA revealed a significant ered as statistically significant at P < .05 and corrected for mul- difference between the 3 impulsivity groups with regards to the tiple comparisons using the false discovery rate (FDR) approach AUC (F(2,72) = 66.48, P < .001), k (F(2,72) = 28.11, P < .001), and the IP (Genovese et al., 2002) at a 5% level. Further cluster-wise correc- (F(2,72) = 24.49, P < .001). Posthoc analysis using Fisher’s LSD test tion for multiple comparisons was performed by a parametric is detailed in Table 2. Analysis of locomotor activity in a novel correlation-based clustering procedure that discarded isolated environment revealed no significant difference in baseline loco- clusters not exceeding the minimum size of 343 voxels in the motor activity between high- and low-impulsive rats (t(20) = 1.68, isogrid, that is, ≤0.057 mm . P > .05) (Table 3). Ex Vivo Receptor Autoradiography Low D Receptor Availability Is Associated with 2/3 Increased DDT Impulsivity Subjects were killed by overdose of pentobarbital and cer - vical dislocation. Brains were rapidly removed and placed on Although no significant differences between high- and low- a steel dissection plate, cooled on dry ice, with the dorsal sur - impulsive rats were observed in D receptor availability in 2/3 face uppermost before being frozen at −80°C. Brains were sec- the prefrontal cortex (F(1,19) = 0.03,P > .05), dorsal striatum tioned in the coronal plane using a Jung CM300 cryostat (Leica). (F(1,19) = 0.23, P > .05), or NAcb (F(1,19) = 0.89, P > .05; Figure 2), a For autoradiography, consecutive 20-μm slices throughout the significant correlation was observed between the binding poten- striatum were mounted on Superfrost Plus microscope slides tial of [ F]fallypride in the left NAcb and both the AUC ( = r −0.78, (Fisher Scientific). Sections were stored at −80°C before being P < .01) and IP (r = −0.79, P < .01) (Figure 2). No such association thawed at room temperature for processing. was observed in low-impulsive rats. [ H]Raclopride (2812 GBq/mmol) was purchased from PerkinElmer. Haloperidol was purchased from Sigma-Aldrich. Low D Receptor Availability Is Localized to the Core Duplicate, consecutive slides were prewashed for 15 minutes at Subregion of the NAcb room temperature in 120 mM of Tris-HCl (pH 7.4). Slides were incubated in a buffer containing 10 nM of the radioligand for Analysis of D receptor binding using [H]raclopride auto- 1 hour. For nonspecific binding, additional 10 µM of cold ligand radiography revealed a lower D receptor availability in the was added to the incubation buffer. Following incubation, slides left NAcb core region of high-impulsive rats vs low-impulsive were washed twice in fresh 4°C buffer for 2 minutes and then rats (F(1,19) = 6.69, P < .05) accompanied by relative higher rinsed in distilled-deionized water. Slides were air-dried for at D receptor availability in both the left and right NAcb shell 2/3 least 2 hours before being fixed in 4% PFA. These were subse- (F(1,19) = 6.13, P < .05; Figure 3). No significant differences in D quently apposed with tritium microscale standards (Amersham binding were observed in either the dorsomedial or dorsolateral Biosciences) to a tritium-sensitive phosphor-imaging plate striatum. Additionally, a dimensional relationship between DDT (Fujifilm). The plates were scanned using a FLA-5000 Bio- impulsivity and D receptor availability in the left NAcb shell 2/3 Imaging Analyzer (Fujifilm) to digitize autoradiographs at 16-bit was observed, specifically in low-impulsive rats where low im- grey scale for image analysis. ROI analysis was conducted using pulsivity, as measured by the AUC, was associated with high D 2/3 ImageJ (Abramoff M, 2004). receptor availability ( = r −0.63, P < .01; Figure 3). Statistical Analysis Increased Functional Brain Connectivity Is Associated with High Impulsive Behavior Behavioral and PET imaging data were analyzed using Statistica 12 (Dell Statistica) and GraphPad Prism 6 (GraphPad Software). The correlation between D receptor availability in the left NAcb 2/3 Locomotor activity data were expressed as the distance travelled and high trait-like impulsivity suggested a potential modulation over the test period of 30 minutes. Data were analyzed using of functional connectivity in limbic brain circuitry. To quantify a nonpaired, two-tailed Student’s t test. Repeated-measures limbic functional connectivity, we measured BOLD coherence ANOVA with a between-subjects factor was used to compare [F] for the limbic network using a seed region in the cingulate cor - 3H fallypride and [ ]raclopride binding in high- and low-impulsiv- tex and demonstrated a consistent functional brain connectivity ity groups. Where significant main effects were found, posthoc analysis using Fisher’s least significant difference (LSD) test was performed. When the assumption of homogeneity of variance could not be met, a Games–Howell test was used. Statistical sig- nificance was set at α = 0.05. Analysis of the functional imaging data is detailed above. All data are given as mean ± SEM. Results Behavioral Screening Rats that completed training on the DDT (average >85% choice of the large-reward lever at a 0-second delay over last 6 days; n = 75) were segregated into 3 groups according to their per - formance. Figure 1 shows the discounting curves for high- and low-impulsive rats in relation to the rest of the cohort (mid- impulsive rats). Descriptive statistics of the 3 behavioral meas- Figure 1. Delay discounting curves for high- (n = 11), mid- (n = 54), and low- ures in high- (n= 11), mid- (n = 54), and low-impulsive (n = 10) rats impulsive (n = 10) rats. Data presented as mean ± SEM. Downloaded from https://academic.oup.com/ijnp/article-abstract/21/7/705/4938500 by Ed 'DeepDyve' Gillespie user on 03 July 2018 710 | International Journal of Neuropsychopharmacology, 2018 Table 2. Summary of Posthoc Fisher’s LSD Test, Assessing Differences in AUC, k, and IP between High- (n= 11), Mid- (n = 54), and Low-Impulsivity (n = 10) Rats AUC k IP HI MI LI HI MI LI HI MI LI HI <0.001 <0.001 <0.001 <0.001 <0.01 <0.001 MI <0.001 <0.001 <0.001 NS <0.01 <0.001 LI <0.001 <0.001 <0.001 NS <0.001 <0.001 AUC, area under the curve; HI, high-impulsivity; IP, indifference point; IQ, interquartile; k, steepness of the discounting curve; LI, low-impulsiv- ity; LSD, least significant difference; MI, mid-impulsivity. Table 3. Different Measures of Spontaneous Activity Do Not Differ between Rats Selected for High- and Low-Impulsive Phenotype Behavior Measured Low-Impulsive Rats High-Impulsive Rats Statistics Average distance moved (cm) 5207 ± 142 4876 ± 209 ns Average rearing frequency (total number) 135 ± 6 123 ± 7 ns Rearing time (average) (s) 372 ± 24 335 ± 27 ns Comparison of activity-dependent parameters between the high- and low-impulsivity subgroups of rats was assessed using a two-tailed unpaired Student’s t test. Statistical significance for all tests was set to P < .05; ns, lack of statistical significance, i.e., P > .05. Data are given as mean ± SEM. Figure 2. [ F]fallypride binding potential (BP) in the left and right hemispheres of the (A) prefrontal cortex, (B) dorsal striatum, and (C) nucleus accumbens (NAcb) of high- (n = 11) and low-impulsive (n = 10) rats. Data presented as mean± SEM. Correlations between area under the curve (AUC) and indifference point (IP) scores in the left and right hemispheres of high- (D–E) and low-impulsive (E) rats in the NAcb. map of the limbic system for both low- and high-impulsivity connectivity networks revealed similar BOLD synchronization in rats (Figure 4A) in agreement with other groups (Müller et al., high- and low-impulsive rats (Figure 4C) as indicated by voxel- 2007). Comparison across the whole brain between low- and wise group comparison (P > .05). By contrast, correlation ana- high-impulsive rats (unpaired t < −2.5; P < .05, FDR corrected for lysis indicated significant positive correlations between regional multiple comparisons) indicated significantly stronger BOLD orbitofrontal functional network connectivity and the DDT-AUC synchronization within the limbic network, that is, higher func- impulsivity score (r > 0.5; P < .05, FDR corrected). As shown in tional connectivity, in high- vs low-impulsive rats. Particularly Figure 4D, bilateral functional connectivity of the hippocampal marked effects were observed bilaterally for the hippocampal formation was also significantly correlated with the DDT-AUC formation, indicating significant functional coupling with the score, that is, the greater the functional coupling between the cingulate cortex in high-impulsive rats. Less-marked effects hippocampal formation and the OFC, the higher the DDT impul- were seen in the striatum, with stronger functional connectiv- sivity. In summary, higher DDT-AUC scores were correlated with ity with the cingulate cortex in high-impulsive rats (Figure 4A). regional functional connectivity in limbic and orbitofrontal net- We then assessed functional connectivity in the orbitofron- works, confirming that these are associated with this measure. tal network, because DDT impulsivity is associated with dopa- However, only high-impulsive rats showed significantly enhanced minergic signaling in the OFC (Zeeb et al., 2010); the functional connectivity in limbic but not in orbitofrontal networks. Downloaded from https://academic.oup.com/ijnp/article-abstract/21/7/705/4938500 by Ed 'DeepDyve' Gillespie user on 03 July 2018 Barlow et al. | 711 Figure 3. [ H]raclopride binding (nCi/mg tissue) in the left and right hemispheres of the (A) nucleus accumbens (NAcb) shell, (B) NAcb core, and (C) dorsal striatum (DMS, dorsomedial striatum; DLS, dorsolateral striatum) of high- (n = 11) and lo w-impulsive (n = 10) rats. Data presented as mean± SEM. (D) Correlations between area under the curve (AUC) in the left and right hemispheres the NAcb shell of low-impulsivity rats. *P < .05. Figure 4. Intrinsic functional connectivity maps in low- (left column) and high-impulsive rats (right column) and its correlations with impulsivity. (A, C) Blood oxygen- ation level–dependent (BOLD) synchronization illustrated as connectivity heat maps showing voxel-wise Fisher’s r-to-z transformed Pearson’s correlation coefficients (thresholded for |z(r)| ≥ 0.4) for which the fMRI BOLD signal was correlated with the signal in the limbic network (Cg, cingulate gyrus, A) and the orbitofrontal network (orbitofrontal cortex [OFC], C). Color coded z(r)-values indicate the strength of correlation for each voxel with respect to the seed region as a measure of functional connectivity. (B) Statistical group comparison (cool colors; corrected P < .05 for multiple comparisons in voxel-wise Student’s t tests) for the limbic network indicated significantly enhanced functional connectivity in high-impulsive rats (n = 11) compared with low-impulsive (n = 10) rats. These patterns of strong functional connect- ivity presented as an enlarged limbic network as illustrated by the delineations (black solid lines, A) corresponding to the limbic functional connectivity network in the low-impulsivity rats (B, left). (C) The orbitofrontal network demonstrated similar functional connectivity maps for low- (left) and high-impulsive rats (right); statistical analysis (voxel-wise Student’s t tests) revealed no significant differences between groups. (D) Significantly positive correlations (hot colors; corrected P < .05; voxel-wise Spearman rank order correlations) were demonstrated for orbitofrontal network connectivity with the impulsive choice score (area under the curve [AUC]) represented as orthogonal pair of slices in all rats. Clusters indicating statistically significant group effects or significant correlations with the impulsive choice score (AUC) were corrected at a 5% false discovery rate (FDR)-level with further cluster-wise correction (minimum size 0.057 mm ). All results are shown in stereotaxic space (55 μm iso- grid) overlaid on the averaged study-specific Echo Planar Imaging (EPI) template (n = 20). CPu, caudate and putamen; HF, hippocampal formation, R, right. Downloaded from https://academic.oup.com/ijnp/article-abstract/21/7/705/4938500 by Ed 'DeepDyve' Gillespie user on 03 July 2018 712 | International Journal of Neuropsychopharmacology, 2018 Treatment response to stimulants is associated with increased Discussion dopamine transmission in the ventral striatum (Volkow et al., Our findings support our hypothesis that low D receptor avail- 2/3 2012; Caprioli et al., 2015), indicating that the efficacy of ADHD ability and functional connectivity modulations within limbic medication may depend, in part, on restoring D receptor sign- 2/3 corticostriatal circuitry are associated with increased preference aling of impulsive individuals. Substance abusers and obese for immediate small-magnitude rewards (i.e., delay aversion). individuals with and without binge eating disorder also have We thus extend earlier reports of low D receptor availability in 2/3 decreased D receptor availability in the striatum, which can 2/3 the ventral striatum and specifically the NAcb shell in a related manifest as a tendency for natural rewards to lose their value form of waiting impulsivity (Dalley et al., 2007Besson et ; al., (Volkow et al., 2008) as well as enhanced impulsivity (Dawe and 2010). Our findings indicate that increased delay aversion in the Loxton, 2004; Nederkoorn et al., 2006; Galanti et al., 2007). Such DDT is inversely associated with low D receptor availability 2/3 impairments can present as discounting deficits, where imme- in the NAcb core. Thus, different forms of waiting impulsivity diate smaller rewards hold greater salience than larger future involving an inability to suppress premature responding when gains due to an impaired reinforcement system (Wang et al., rewards are delayed or when rewards are subjectively devalued 2004; Volkow et al., 2008) resulting in a tendency towards impul- receptor availability but in over time both associate with low D 2/3 sive responding (Robbins et al., 2012). In accordance with this different subregions of the NAcb. hypothesis, a recent imaging study in patients with substance Rats selected for extreme low and high impulsivity on the use disorder found a negative correlation between striatal D 2/3 5-choice serial reaction time task exhibit differential D re- receptor availability with preference for smaller, more imme- 2/3 ceptor availabilities in the ventral striatum, as measured using diate rewards over larger, delayed alternatives (Ballard et al., [ F]fallypride-PET (Dalley et al., 2007). In this study, a signifi- 2015). Interestingly, a computational modeling approach aiming cant inverse correlation between D receptor availability in 2/3 to determine the functional role of ventral striatal dopamine the ventral but not dorsal striatum and premature responses (a D -receptor in the expression of previously acquired behaviors measure of impulsivity) was observed. High-impulsive animals predicted this finding and suggests that dopamine D -receptor on this task maintained significantly higher rates of cocaine manipulation in the ventral striatum selectively modulates self-administration than low-impulsive rats (Dalley et al., 2007) motivated behavior for distal vs proximal outcomes. Specifically, and subsequently developed compulsive cocaine self-admin- the model quantitatively accounts the steepness of discounting istration (Belin et al., 2008). Similarly, high- and low-impulsive on a DDT as a function of D-dependent tonic dopamine firing in rats selected on the DDT demonstrated that impulsive choice the ventral striatum (Smith et al., 2005). predicts resistance to extinction and a propensity to relapse to Dysfunction of midbrain dopaminergic systems have been cocaine seeking (Broos et al., 2012). implicated in several forms of impulsive behavior in rodents, es- A plethora of human imaging studies indicate reduced pecially within the NAcb (Dalley et al., 2007 Besson et ; al., 2010; striatal availability of D -like dopamine receptors in patients Dalley and Robbins, 2017). NAcb core lesions shift behavior to- with stimulant-use disorder and other addiction pathologies, ward the choice of small, immediate food rewards, although which might already partially exist before drug exposure and damage to 2 of its afferents, the anterior cingulate cortex and may predispose for addictive behaviors (for review see, Ashok medial prefrontal cortex, is without effect (Cardinal et al., 2001; et al., 2017). Since self-report impulsivity is negatively correlated Pothuizen et al., 2005; Basar et al., 2010) and there is evidence with D availability in the ventral striatum and globus pallidus the NAcb core is also important for modulating probability dis- 2/3 (Buckholtz et al., 2010Car ; avaggio et al., 2016) and high trait-like counting (Basar et al., 2010). The NAcb is part of a larger net- impulsivity is a predisposing factor for substance abuse (Robbins work encompassing the amygdala and prefrontal cortex. As et al., 2012), these studies highlight a potential overlap of D -like such, lesions on the basolateral amygdala and OFC exert quali- dopamine receptors with both impulsivity and substance abuse tatively similar effects on impulsive choice as those on the NAcb vulnerability. As per the original observation, we observed a sig- core (Mobini et al., 2002; Winstanley et al., 2004Rude ; beck et al., nificant inverse correlation between D receptor availability 2006). However, the opposite preference for a larger delayed re- 2/3 and choice impulsivity in the ventral, but not dorsal striatum by ward has also been reported with regard to OFC lesions, poten- [ F]fallypride PET imaging, specifically in high-impulsive rats. tially owing to variations in task procedure, such as inclusion of This suggests a common neurobiological substrate underlying a conditioned reinforcer during the delay interval (Winstanley both impulsive choice as assessed on the DDT and motor impul- et al., 2004; Zeeb et al., 2010). The importance of the OFC in regu- sivity as assessed on the 5-choice serial reaction time task. Ex lating impulsive choice has been established through observa- vivo receptor autoradiography analysis demonstrated that high- tions of enhanced dopamine release during the choice phase impulsive rats exhibited significantly lower D receptor binding of DDT and by molecular changes, induced by impulsive be- within the NAcb core vs low-impulsive rats associated with a havior itself within the OFC (Zeeb et al., 2010). An association concurrent higher D receptor binding in the NAcb shell sub- between changes in the activation of limbic frontostriatal net- region, significant in the left hemisphere only. Taken together, works with age-dependent reductions in impulsive choice have these data point to a dysfunction of striatal dopaminergic neuro- previously been reported in a human temporal discounting task transmission, in line with a recent report demonstrating altered (Christakou et al., 2011), suggesting that altered activation coup- dopamine release in the NAcb core of high- vs low-impulsive ling between areas such as the anterior cingulate cortex, OFC, rats selected on the DDT (Moschak and Carelli, 2017). striatum, and amygdala may underlie naturally occurring im- Recent clinical studies link alterations in striatal D re- pulsive choice behavior. 2/3 ceptor availability and subsequent dopaminergic dysfunction Our resting-state functional connectivity data are consistent with attention deficit hyperactivity disorder (ADHD), a condi- with previous findings in humans (Davis et al., 2013; Gorges tion characterized by both motor (Lipszyc and Schachar, 2010) et al., 2015, 2016) and rodents (Power et al., 2012; Zhan et al., and choice impulsivity (Patros et al., 2016). PET studies in adult 2014), demonstrating that abnormal functional integration of medication-naive ADHD patients found reduced D receptor specific disease-related networks is associated with different 2/3 behavioral phenotypes. Specifically, rats selected for extreme availability in the NAcb and caudate (Volkow et al., 2009). Downloaded from https://academic.oup.com/ijnp/article-abstract/21/7/705/4938500 by Ed 'DeepDyve' Gillespie user on 03 July 2018 Barlow et al. | 713 impulsivity phenotypes exhibited a pattern of increased func- waiting impulsivity is key to identifying novel treatment strate- tional connectivity within the major limbic system nodes. These gies for treating impulsivity as a specific psychiatric symptom findings were strengthened by abnormally increased region-to- with cross-diagnostic significance (Dalley and Robbins, 2017). region connectivity within the limbic network of high-impulsiv- ity rats, similar to that shown in patients with ADHD, especially Funding hyperactive-impulsive subtypes (Sanefuji et al., 2017). Orbitofrontal network connectivity did not differ between This work was supported in full by Boehringer Ingelheim high- and low-impulsive rats, although it correlated with choice Pharma GmbH & Co. KG, Div. Research Germany, Birkendorf impulsivity as measured by numerous behavioral scores. Within Strasse 65, 88397, Biberach an der Riss, Germany. this network, low NAcb core D receptor availability may re- 2/3 sult in an imbalanced dopaminergic-mediated functional coup- Acknowledgments ling that may underlie naturally occurring choice impulsivity. Imaging studies in ADHD report increased connectivity between We thank Andrea Vögtle, Thomas Kaulisch, Peter Schorn, and the NAcb core and prefrontal cortex associated with increased David Kind for excellent technical support and Detlef Stiller and choice impulsivity (Costa Dias et al., 2013), as well as atypical Janet Nicholson for helpful scientific discussion. Editorial support activation of the NAcb and OFC when performing the DDT and formatting assistance for this manuscript were provided by (Plichta et al., 2009). In line with this, methamphetamine users Michelle Marvel, BA, and Heather Shawcross, PhD, of Fishawack exhibit low striatal D receptor availability and poor inhibitory Communications Ltd, funded by Boehringer Ingelheim. 2/3 control and choice impulsivity. Thus, impaired activation and connectivity in frontostriatal networks may underlie aberrant Statement of Interest reward-driven behavior in methamphetamine users (Kohno et al., 2014; London et al., 2015). Since reduced striatal D re- R.L.B., A.W., H.G.N., and A.P. are employees of Boehringer 2/3 ceptor availability has been shown in ADHD and methampheta- Ingelheim Pharma GmbH & Co. K.G. M.G., J.K., and J.W.D. declare mine users (Volkow et al., 2009; Kohno et al., 2014), alterations no conflicts of interest. in OFC activation and orbitofrontal network connectivity may be secondary and consequential to altered striatal dopaminergic References neurotransmission. In Parkinson’s disease, ongoing dopamin- ergic cell degeneration is associated with increased functional Abramoff MD, Magalhães PJ, Ram SJ (2004) Image processing connectivity early in the disease (Gorges et al., 2015). Therefore, with ImageJ. Biophotonics Int 11:36–42. any imbalance in the dopaminergic system associated with ab- Ashok AH, Mizuno Y, Volkow ND, Howes OD (2017) Association normal functional coupling could potentially result in altered of stimulant use with dopaminergic alterations in users of behavioral performance, specifically neurobiological changes cocaine, amphetamine, or methamphetamine: a systematic in the limbic system including the NAcb. A caveat is that func- review and meta-analysis. JAMA Psychiatry 74:511–519. tional connectivity results can be only indirectly assessed from Ballard ME, Mandelkern MA, Monterosso JR, Hsu E, Robertson CL, the limited signal-to-noise ratio of the BOLD signal acquired at a Ishibashi K, Dean AC, London ED (2015) Low dopamine D2/ given spatial resolution (Power et al., 2012). D3 receptor availability is associated with steep discounting Resting-state fMRI is an indirect measure for functional con- of delayed rewards in methamphetamine dependence. Int J nectivity constrained by the limited signal-to-noise ratio and Neuropsychopharmacol 18:pyu119. limited spatial resolution (Gorges et al., 2017 The ) seed-based Basar K, Sesia T, Groenewegen H, Steinbusch HW, Visser- approach measures connectivity with respect to the reference Vandewalle V, Temel Y (2010) Nucleus accumbens and impul- voxel and, hence, does not characterize the full functional sivity. Prog Neurobiol 92:533–557. connectome, which presents a limitation of the current study. Bechara A (2003) Risky business: emotion, decision-making, and Future studies might utilize connectome-based approaches that addiction. J Gambl Stud 19:23–51. model the NAcb together with relevant regions of the limbic Belin D, Mar AC, Dalley JW, Robbins TW, Everitt BJ (2008) High system as nodes. In addition, we cannot exclude the possibility impulsivity predicts the switch to compulsive cocaine-tak- that general anesthesia influenced resting-state functional con- ing. Science 320:1352–1355. nectivity presenting a potential limitation of our study. A -fur Beltzer A, Kaulisch T, Bluhmki T, Schoenberger T, Stierstorfer B, ther caveat is that of [F]fallypride lacks selectivity for o D ver Stiller D (2016) Evaluation of quantitative imaging biomark- D receptors(Mukherjee et al., 2002). Further studies with more ers in the DSS colitis model. Mol Imaging Biol 18:697–704. selective PET tracers are thus needed to resolve the relative in- Besson M, Belin D, McNamara R, Theobald DE, Castel A, Beckett volvement of D and D receptors in choice impulsivity. VL, Crittenden BM, Newman AH, Everitt BJ, Robbins TW, 2 3 In summary, we report a significant correlation between low Dalley JW (2010) Dissociable control of impulsivity in rats by D receptor availability in the ventral striatum and increased dopamine d2/3 receptors in the core and shell subregions 2/3 DDT impulsivity, specifically, lower D receptor binding within of the nucleus accumbens. Neuropsychopharmacology 2/3 the NAcb core of high- vs low-impulsive rats. The strong con- 35:560–569. nectivity within the limbic network in high- vs low-impulsive Besson M, Pelloux Y, Dilleen R, Theobald DE, Lyon A, Belin- rats supports the hypothesis that differences in D receptor Rauscent A, Robbins TW, Dalley JW, Everitt BJ, Belin D (2013) 2/3 binding within the NAcb may underlie naturally occurring Cocaine modulation of frontostriatal expression of zif268, variation in waiting impulsivity and be either causal or conse- D2, and 5-HT2C receptors in high and low impulsive rats. quential to modulations of limbic network connectivity. An im- Neuropsychopharmacology 38:1963–1973. portant question for future research is whether interventions Broos N, Diergaarde L, Schoffelmeer AN, Pattij T, De Vries TJ that increase striatal D receptor availability can normalize (2012) Trait impulsive choice predicts resistance to extinction 2/3 high impulsivity and attenuate associated limbic hyper-connec- and propensity to relapse to cocaine seeking: a bidirectional tivity. Understanding the neurobiological processes underlying investigation. Neuropsychopharmacology 37:1377–1386. Downloaded from https://academic.oup.com/ijnp/article-abstract/21/7/705/4938500 by Ed 'DeepDyve' Gillespie user on 03 July 2018 714 | International Journal of Neuropsychopharmacology, 2018 Buckholtz JW, Treadway MT, Cowan RL, Woodward ND, Li R, functional connectivity in parkinson’s disease. Brain Imaging Ansari MS, Baldwin RM, Schwartzman AN, Shelby ES, Smith Behav 10:79–91. CE, Kessler RM, Zald DH (2010) Dopaminergic network differ - Gorges M, Roselli F, Müller HP, Ludolph AC, Rasche V, Kassubek J ences in human impulsivity. Science 329:532. (2017) Functional connectivity mapping in the animal model: Caprioli D, Jupp B, Hong YT, Sawiak SJ, Ferrari V, Wharton L, principles and applications of resting-state fmri. Front Neurol Williamson DJ, McNabb C, Berry D, Aigbirhio FI, Robbins TW, 8:200. Fryer TD, Dalley JW (2015) Dissociable rate-dependent effects Isherwood SN, Robbins TW, Nicholson JR, Dalley JW, Pekcec A of oral methylphenidate on impulsivity and D2/3 receptor (2017) Selective and interactive effects of d2receptor antag- availability in the striatum. J Neurosci 35:3747–3755. onism and positive allosteric mglur4 modulation on waiting Caravaggio F, Fervaha G, Chung JK, Gerretsen P, Nakajima impulsivity. Neuropharmacology 123:249–260. S, Plitman E, Iwata Y, Wilson A, Graff-Guerrero A (2016) Jonckers E, Van Audekerke J, De Visscher G, Van der Linden A, Exploring personality traits related to dopamine D2/3 Verhoye M (2011) Functional connectivity fmri of the rodent receptor availability in striatal subregions of humans. Eur brain: comparison of functional connectivity networks in rat Neuropsychopharmacol 26:644–652. and mouse. Plos One 6:e18876. Cardinal RN, Pennicott DR, Sugathapala CL, Robbins TW, Everitt Kilkenny C, Browne WJ, Cuthill IC, Emerson M, Altman DG (2012) BJ (2001) Impulsive choice induced in rats by lesions of the Improving bioscience research reporting: the ARRIVE guide- nucleus accumbens core. Science 292:2499–2501. lines for reporting animal research. Osteoarthritis Cartilage Cheung TH, Cardinal RN (2005) Hippocampal lesions facili- 20:256–260. tate instrumental learning with delayed reinforcement but Kohno M, Morales AM, Ghahremani DG, Hellemann G, London induce impulsive choice in rats. BMC Neurosci 6:36. ED (2014) Risky decision making, prefrontal cortex, and mes- Christakou A, Brammer M, Rubia K (2011) Maturation of lim- ocorticolimbic functional connectivity in methamphetamine bic corticostriatal activation and connectivity associated dependence. JAMA Psychiatry 71:812–820. with developmental changes in temporal discounting. Laird AR, Fox PM, Eickhoff SB, Turner JA, Ray KL, McKay DR, Glahn Neuroimage 54:1344–1354. DC, Beckmann CF, Smith SM, Fox PT (2011) Behavioral inter - Costa Dias TG, Wilson VB, Bathula DR, Iyer SP, Mills KL, Thurlow pretations of intrinsic connectivity networks. J Cogn Neurosci BL, Stevens CA, Musser ED, Carpenter SD, Grayson DS, Mitchell 23:4022–4037. SH, Nigg JT, Fair DA (2013) Reward circuit connectivity relates Lee B, London ED, Poldrack RA, Farahi J, Nacca A, Monterosso JR, to delay discounting in children with attention-deficit/hyper - Mumford JA, Bokarius AV, Dahlbom M, Mukherjee J, Bilder activity disorder. Eur Neuropsychopharmacol 23:33–45. RM, Brody AL, Mandelkern MA (2009) Striatal dopamine Dalley JW, Everitt BJ, Robbins TW (2011) Impulsivity, compulsiv- d2/d3 receptor availability is reduced in methampheta- ity, and top-down cognitive control. Neuron 69:680–694. mine dependence and is linked to impulsivity. J Neurosci Dalley JW, Fryer TD, Brichard L, Robinson ES, Theobald DE, Lääne 29:14734–14740. K, Peña Y, Murphy ER, Shah Y, Probst K, Abakumova I, Aigbirhio Lipszyc J, Schachar R (2010) Inhibitory control and psychopath- FI, Richards HK, Hong Y, Baron JC, Everitt BJ, Robbins TW (2007) ology: a meta-analysis of studies using the stop signal task. J Nucleus accumbens D2/3 receptors predict trait impulsivity Int Neuropsychol Soc 16:1064–1076. and cocaine reinforcement. Science 315:1267–1270. London ED, Ernst M, Grant S, Bonson K, Weinstein A (2000) Dalley JW, Robbins TW (2017) Fractionating impulsivity: neuro- Orbitofrontal cortex and human drug abuse: functional psychiatric implications. Nat Rev Neurosci 18:158–171. imaging. Cereb Cortex 10:334–342. Davis FC, Knodt AR, Sporns O, Lahey BB, Zald DH, Brigidi BD, London ED, Kohno M, Morales AM, Ballard ME (2015) Chronic Hariri AR (2013) Impulsivity and the modular organization methamphetamine abuse and corticostriatal deficits revealed of resting-state neural networks. Cereb Cortex 23:1444–1452. by neuroimaging. Brain Res 1628:174–185. Dawe S, Loxton NJ (2004) The role of impulsivity in the devel- Maier FC, Wehrl HF, Schmid AM, Mannheim JG, Wiehr S, Lerdkrai opment of substance use and eating disorders. Neurosci C, Calaminus C, Stahlschmidt A, Ye L, Burnet M, Stiller D, Sabri Biobehav Rev 28:343–351. O, Reischl G, Staufenbiel M, Garaschuk O, Jucker M, Pichler Galanti K, Gluck ME, Geliebter A (2007) Test meal intake in obese BJ (2014) Longitudinal PET-MRI reveals β-amyloid deposition binge eaters in relation to impulsivity and compulsivity. Int J and rcbf dynamics and connects vascular amyloidosis to Eat Disord 40:727–732. quantitative loss of perfusion. Nat Med 20:1485–1492. Genovese CR, Lazar NA, Nichols T (2002) Thresholding of statis- Mobini S, Body S, Ho MY, Bradshaw CM, Szabadi E, Deakin JF, tical maps in functional neuroimaging using the false discov- Anderson IM (2002) Effects of lesions of the orbitofrontal cor - ery rate. Neuroimage 15:870–878. tex on sensitivity to delayed and probabilistic reinforcement. Ghahremani DG, Lee B, Robertson CL, Tabibnia G, Morgan AT, De Psychopharmacology (Berl) 160:290–298. Shetler N, Brown AK, Monterosso JR, Aron AR, Mandelkern MA, Moschak TM, Carelli RM (2017) Impulsive rats exhibit blunted Poldrack RA, London ED (2012) Striatal dopamine D(2)/D(3) dopamine release dynamics during a delay discounting receptors mediate response inhibition and related activ- task independent of cocaine history. eNeuro 4:doi: 10.1523/ ity in frontostriatal neural circuitry in humans. J Neurosci ENEURO.0119-17.2017. 32:7316–7324. Mukherjee J, Yang ZY, Das MK, Brown T (1995) Fluorinated Gorges M, Müller HP, Lulé D, Pinkhardt EH, Ludolph AC, Kassubek benzamide neuroleptics–III. Development of (S)-N-[(1- J, LANDSCAPE Consortium (2015) To rise and to fall: func- allyl-2-pyrrolidinyl)methyl]-5-(3-[18F]fluoropropyl)-2, tional connectivity in cognitively normal and cognitively impaired patients with parkinson’s disease. Neurobiol Aging 3-dimethoxybenzamide as an improved dopamine D-2 receptor tracer. Nucl Med Biol 22:283–296. 36:1727–1735. Gorges M, Müller HP, Lulé D, Pinkhardt EH, Ludolph AC, Kassubek Mukherjee J, Christian BT, Dunigan KA, Shi B, Narayanan TK, J, LANDSCAPE Consortium (2016) The association between Satter M, Mantil J (2002) Brain imaging of 18F-fallypride in alterations of eye movement control and cerebral intrinsic normal volunteers: blood analysis, distribution, test-retest Downloaded from https://academic.oup.com/ijnp/article-abstract/21/7/705/4938500 by Ed 'DeepDyve' Gillespie user on 03 July 2018 Barlow et al. | 715 studies, and preliminary assessment of sensitivity to aging between the mechanism leading to impulsivity and inatten- effects on dopamine D-2/D-3 receptors. Synapse 46:170–188. tion in attention deficit hyperactivity disorder: a resting-state Müller HP, Unrath A, Ludolph AC, Kassubek J (2007) Preservation functional connectivity study. Cortex 86:290–302. of diffusion tensor properties during spatial normalization by Schoenbaum G, Roesch MR, Stalnaker TA, Takahashi YK (2009) use of tensor imaging and fibre tracking on a normal brain A new perspective on the role of the orbitofrontal cortex in database. Phys Med Biol 52:N99–109. adaptive behaviour. Nat Rev Neurosci 10:885–892. Müller HP, Kassubek J, Vernikouskaya I, Ludolph AC, Stiller D, Sforazzini F, Schwarz AJ, Galbusera A, Bifone A, Gozzi A (2014) Rasche V (2013) Diffusion tensor magnetic resonance imaging Distributed BOLD and CBV-weighted resting-state networks of the brain in APP transgenic mice: a cohort study. Plos One in the mouse brain. Neuroimage 87:403–415. 8:e67630. Smith AJ, Becker S, Kapur S (2005) A computational model of Nederkoorn C, Braet C, Van Eijs Y, Tanghe A, Jansen A (2006) Why the functional role of the ventral-striatal D2 receptor in the obese children cannot resist food: the role of impulsivity. Eat expression of previously acquired behaviors. Neural Comput Behav 7:315–322. 17:361–395. Patros CH, Alderson RM, Kasper LJ, Tarle SJ, Lea SE, Hudec KL Smith SM, Fox PT, Miller KL, Glahn DC, Fox PM, Mackay CE, (2016) Choice-impulsivity in children and adolescents with Filippini N, Watkins KE, Toro R, Laird AR, Beckmann CF (2009) attention-deficit/hyperactivity disorder (ADHD): a meta-ana- Correspondence of the brain’s functional architecture during lytic review. Clin Psychol Rev 43:162–174. activation and rest. Proc Natl Acad Sci U S A 106:13040–13045. Plichta MM, Vasic N, Wolf RC, Lesch KP, Brummer D, Jacob C, Volkow ND, Wang GJ, Fowler JS, Telang F (2008) Overlapping neur - Fallgatter AJ, Grön G (2009) Neural hyporesponsiveness and onal circuits in addiction and obesity: evidence of systems hyperresponsiveness during immediate and delayed reward pathology. Philos Trans R Soc Lond B Biol Sci 363:3191–3200. processing in adult attention-deficit/hyperactivity disorder. Volkow ND, Wang GJ, Kollins SH, Wigal TL, Newcorn JH, Telang F, Biol Psychiatry 65:7–14. Fowler JS, Zhu W, Logan J, Ma Y, Pradhan K, Wong C, Swanson Pothuizen HH, Jongen-Rêlo AL, Feldon J, Yee BK (2005) Double JM (2009) Evaluating dopamine reward pathway in ADHD: dissociation of the effects of selective nucleus accumbens clinical implications. Jama 302:1084–1091. core and shell lesions on impulsive-choice behaviour and Volkow ND, Wang GJ, Tomasi D, Kollins SH, Wigal TL, Newcorn salience learning in rats. Eur J Neurosci 22:2605–2616. JH, Telang FW, Fowler JS, Logan J, Wong CT, Swanson JM (2012) Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE (2012) Methylphenidate-elicited dopamine increases in ventral Spurious but systematic correlations in functional connect- striatum are associated with long-term symptom improve- ivity MRI networks arise from subject motion. Neuroimage ment in adults with attention deficit hyperactivity disorder. 59:2142–2154. J Neurosci 32:841–849. Robbins TW, Gillan CM, Smith DG, de Wit S, Ersche KD (2012) Wang GJ, Volkow ND, Thanos PK, Fowler JS (2004) Similarity Neurocognitive endophenotypes of impulsivity and compulsiv- between obesity and drug addiction as assessed by neu- ity: towards dimensional psychiatry. Trends Cogn Sci 16:81–91. rofunctional imaging: a concept review. J Addict Dis Robertson CL, Ishibashi K, Mandelkern MA, Brown AK, 23:39–53. Ghahremani DG, Sabb F, Bilder R, Cannon T, Borg J, London Winstanley CA, Theobald DE, Cardinal RN, Robbins TW (2004) ED (2015) Striatal D1- and D2-type dopamine receptors are Contrasting roles of basolateral amygdala and orbitofrontal linked to motor response inhibition in human subjects. J cortex in impulsive choice. J Neurosci 24:4718–4722. Neurosci 35:5990–5997. Zeeb FD, Floresco SB, Winstanley CA (2010) Contributions of the Rudebeck PH, Murray EA (2014) The orbitofrontal oracle: cortical orbitofrontal cortex to impulsive choice: interactions with mechanisms for the prediction and evaluation of specific basal levels of impulsivity, dopamine signalling, and reward- behavioral outcomes. Neuron 84:1143–1156. related cues. Psychopharmacology (Berl) 211:87–98. Rudebeck PH, Walton ME, Smyth AN, Bannerman DM, Rushworth Zhan Y, Paolicelli RC, Sforazzini F, Weinhard L, Bolasco G, MF (2006) Separate neural pathways process different deci- Pagani F, Vyssotski AL, Bifone A, Gozzi A, Ragozzino D, Gross sion costs. Nat Neurosci 9:1161–1168. CT (2014) Deficient neuron-microglia signaling results in Sanefuji M, Craig M, Parlatini V, Mehta MA, Murphy DG, Catani M, impaired functional brain connectivity and social behavior. Cerliani L, Thiebaut de Schotten M (2017) Double-dissociation Nat Neurosci 17:400–406. 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International Journal of Neuropsychopharmacology – Oxford University Press
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