The nicotinic cholinergic system function in the human brain

Neuropharmacology xxx (2014) 1e13

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Invited review

The nicotinic cholinergic system function in the human brain Frauke Nees* Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany

a r t i c l e i n f o

a b s t r a c t

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Research on the nicotinic cholinergic system function in the brain was previously mainly derived from animal studies, yet, research in humans is growing. Up to date, findings allow significant advances on the understanding of nicotinic cholinergic effects on human cognition, emotion and behavior using a range of functional brain imaging approaches such as pharmacological functional magnetic resonance imaging or positron emission tomography. Studies provided insights across various mechanistic psychological domains using different tasks as well as at rest in both healthy individuals and patient populations, with so far partly mixed results reporting both enhancements and decrements of neural activity related to the nicotinic cholinergic system. Moreover, studies on the relation between brain structure and the nicotinic cholinergic system add important information in this context. The present review summarizes the current status of human brain imaging studies and presents the findings within a theoretical and clinical perspective as they may be useful not only for an advancement of the understanding of basic nicotinic cholinergic-related mechanisms, but also for the development and integration of psychological and pharmacological treatment approaches. Patterns of functional neuroanatomy and neural circuitry across various cognitive and emotional domains may be used as neuropsychological markers of mental disorders such as addiction, Alzheimer's disease, Parkinson disease or schizophrenia, where nicotinic cholinergic system changes are characteristic. This article is part of a Special Issue entitled ‘Nicotinic Acetylcholine Receptor’. © 2014 Elsevier Ltd. All rights reserved.

Keywords: Brain imaging Nicotine Acetylcholine Gene Cognition Emotion

1. Introduction Investigations of the nicotinic cholinergic system function in the brain has mainly been emerged from animal studies so far, but research on its effects on brain activity in humans is growing (e.g. see Heishman et al., 2010 for meta-analysis). The nicotinic acetylcholine (nACh) receptors are some of the most abundant in the brain, with the highest affinity for nicotine, the chemical in tobacco smoke (Benowitz, 1996). Specifically the b2*-nACh receptors mediate the effects of nicotine in the brain, most commonly expressed by the striatal reward pathways (Picciotto et al., 1998). Repeated or chronic exposure to nicotine results in an upregulation as well as in increase in availability and in the number of nACh receptors (e.g. Flores et al., 1992; Schwartz and Kellar, 1983; Cosgrove et al., 2009) containing b2 subunit proteins (Marks et al., 2011). The nACh receptor structure is composed of five subunits, a2g a9 and bg-b4 (Paterson and Nordberg, 2000). Beside the b2*-nACh receptors, other major neuronal subunits are

* Tel.: þ49 621 1703 6306; fax: þ49 621 1703 6305. E-mail address: [email protected].

heteromeric a3 and homomeric a7 subtypes, with co-expressions of various combinations of a2, a3, a5, a6, and b2 and b4 subunits (Paterson and Nordberg, 2000). Research to uncover the effects of the nicotinic cholinergic system function in the human brain was done not only using a range of brain imaging methods, pharmacological and genetic approaches, but also various tasks and different study populations. Nicotine has been shown to improve cognitive functions such as attention, working memory and response inhibition as well as reward and emotion in both animals and humans (Rezvani and Levin, 2001; Stein et al., 1998). These effects may result from nACh receptor changes in cerebral gray or white matter and in multiple brain areas including the amygdala, the hippocampus, the striatum, the cerebellum and the prefrontal cortex (PFC) following nicotine exposure. Nicotine use was shown to have a significant impact on white matter, with some studies demonstrating increase in white matter integrity during initial nicotine use and reduction in chronic use, possibly due to activation of nicotinic receptors in thinly myelinated white matter tracts (e.g., Kochunov et al., 2007; Mandl et al., 2008; Paul et al., 2008; Hudkins et al., 2010; Liao et al., 2011). Moreover, using single photon emission computed

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Please cite this article in press as: Nees, F., The nicotinic cholinergic system function in the human brain, Neuropharmacology (2014), http:// dx.doi.org/10.1016/j.neuropharm.2014.10.021

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tomography (SPECT) with [123I]5-IA, that binds b2-nACh receptors at the interface between the a4 and b2 subunits, studies found significantly higher availability of b2*-nACh receptors in the cerebellum, striatum and throughout the cortex in recently abstinent compared to non-smokers (Staley et al., 2006). Interestingly, in abstinent smokers, this higher availability was normalized to the levels of non-smokers only after 6e12 weeks (Cosgrove et al., 2009). The duration of smoking history may therefore also be an important factor in nACh receptor effects in the human brain. This is corroborated by Musso et al., 2007 that found a similar effect on brain function, specifically on the PFC activity, in adolescents and young adults already following some years of nicotine abuse. Moreover, b2*-nACh receptors availability may also significantly depend on gender aspects. Differences in availability in the cerebellum, striatum and cortex between smokers and non-smokers were observed in men, while availability in female smokers and non-smokers did not significantly differ in any brain region. In smoking women, however, significant positive correlations of progesterone levels and craving for cigarettes, nicotine withdrawal and depressive symptoms were found (Cosgrove et al., 2012). Moreover, beside some environmental influence, smoking is influenced by genetic factors, with variable heritability ranging from 40% to 75% (Sullivan and Kendler, 1999; Vink et al., 2005; Maes and Neale, 2009; Nugent et al., 2014). With respect to the nicotinic cholinergic system, genomwide approaches reported on a significant association of the 15q nACh receptor a5-a3-b4 gene cluster with persistent smoking, and on the a4b2 nACh receptor as key regulator of nicotine addiction (Saccone et al., 2007; Bierut et al., 2008; Thorgeirsson et al., 2008). Furthermore, an impact of this gene cluster on brain activation has also been reported. A recent study by Hong et al. (2010) showed that the a5 subunit gene (CHRNA5) rs16969968 or aspartic acid (Asp) 398 asparagine (Asn) polymorphism, where the Asn risk allele (A allele) produced a reduction of a4b2a5 receptor function (Bierut et al., 2008) and may enhance nicotine dependence susceptibility through regulation of dopamine-mediated reward signaling (Bierut et al., 2008) or ameliorate cognitive impairments (Winterer et al., 2010), was significantly associated with resting state functional connectivity in the dorsal anterior cingulate (dACC) e ventral striatal circuit, that was also found being related to nicotine addiction (Hong et al., 2009). Moreover, another polymorphism related to the nicotinic cholinergic system function, the CHRNA4 polymorphism rs1044396, has been associated with various phenotypes such as nicotine addiction and smoking status (Chu et al., 2011; Feng et al., 2004) including differences in brain activation during task performance, for example in tasks assessing attentional processes (Espeseth et al., 2007; Winterer et al., 2007). These findings gain further importance, since many of the mental disorders that contribute substantially to smoking risk or show high rates of comorbid smoking are highly genetic (e.g. Purcell et al., 2009), with potentially shared genetic influence. Abnormalities in the nicotinic cholinergic system are also implicated in several mental disorders other than addiction such as Parkinson disease (PD), Alzheimer's disease (AD) or schizophrenia. For example, nACh receptor binding in cortical and subcortical brain areas was shown to be reduced in neurodegenerative disorders such as PD, AD or dementia (e.g. Court et al., 2000; Graham et al., 2002). Comorbidities of tobacco (ab)use and other disorders were also often observed (50e80% smoking rate, Regier et al., 1990; Lasser et al., 2000) and pharmacological agents to ameliorate clinical symptoms were targeted by substances that act on various nACh subtypes not only in nicotine addiction, but also in other disorders (e.g. Aarsland et al., 2003). The evaluation of the neurobiological mechanisms underlying the impact of nicotine on brain structure and function, and related

cognition and behavior is therefore of high clinical importance. Results from studies on the actions of nACh receptor functions using neuroimaging techniques involving positron emission tomography (PET), SPECT, and structural and functional magnetic resonance imaging (fMRI) may lead to an improvement in the development of therapeutics and associated psychological treatment approaches for smoking and AD, PD or schizophrenia (Jasinska et al., 2013). 2. Overview on brain structure and function A number of human neuroimaging studies have investigated the effects of cigarette smoking or acute nicotine administration on brain activity in smokers versus non-smoking individuals. Although applications range from intravenous nicotine administration to nicotine patches or nasal administration using nicotine sprays, the majority of affected brain areas are consistent across these different pharmacological approaches, although mixed activationedeactivation patterns were reported. For example, Stein et al. (1998) showed an increased brain activation in various cortical and subcortical regions such as the cingulate cortex, the PFC (including dorsolateral, medial and orbital areas), the insula, the nucleus accumbens, the thalamus, the amygdala and partly temporal and occipital areas in non-deprived smokers following intravenous nicotine administration. Studies using cigarettes or nasal nicotine spray corroborated these early findings for the thalamus and the occipital cortex, but additionally found an increase in the regional cerebral blood flow (rCBF) in the cerebellum, and highlighted variably decreased rCBF in the cingulate cortex, the nucleus accumbens, amygdala and temporal cortex as well as in the hippocampus (Domino et al., 2000; Zubieta et al., 2005). Moreover, a very recent study (Picard et al., 2013) that used 2-[18F]F-A-85380 PET and a volume-of-interest-based analysis demonstrated the highest distribution of the heteromeric a4b2 nACh receptors in non-smoking healthy individuals throughout the insular cortex and the ACC, a neural network that was previously discussed as default mode or salience network fundamental to cognitive functions, specifically attention (see Fig. 1, left). The nicotinic cholinergic system may therefore also be a significant modulator for these mechanisms, which further highlights its important role in various mental disorders, where alterations in cognition and attention were often observed. Furthermore, another recent study (Brody et al., 2013) reported a prominent role of the brainstem and the cerebellum in smoking reduction and cessation. Decreases in specific binding volume of distribution for these brain regions were significantly correlated with a reduction in cigarette use per day. These studies may provide a promising and useful basis for the treatment of smokers. Moreover, in the context of successful smoking cessation, but also with respect to the development and maintenance of nicotine addiction, craving, i.e. the urge to consume the drug nicotine, have previously been identified as an important factor. Studies already provided evidence for an association of nicotine and craving in brain areas involving the thalamus (Rose et al., 2003; Due et al., 2002) and the striatum (Berlanga et al., 2003) which were shown to have a high density of nACh receptors and were additionally involved in mechanisms of emotion and reward (see McClernon and Gilbert, 2004 for review). In addition, an interesting association between craving and brain regions related to motor functions including the premotor cortex, the primary motor cortex and the supplementary motor area, additionally depending on the input of the cerebellum, were also highlighted (Smolka et al., 2006). The urge to resist to craving during the presentation of cigarette cues was related to reduced activation of the motor cortex in smokers (Brody et al., 2007). Together with findings of a significant

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Fig. 1. Left: Average nicotinic receptor density in five control networks (fronto-parietal, dorsal attention, default mode, sensorimotor, visual) and the cingulo-insular network, A) Intrinsic connectivity networks for attentional/topedown control including the fronto-parietal, the dorsal attention and the cingulo-insular network, B) Averaged mean receptor density signal across all voxels of each of the five control networks and the cingulo-insular networks. Lines on the left side show the cortical voxels only (solid line) and the complete network including thalamus (dashed line) e significantly higher nAChR density in the cingulo-insular network than any other network was found for both cases. (slightly modified from Picard et al., 2013); Middle: Prefrontal and insula structural alterations in smokers compared to non-smokers, A) Lower white matter integrity in the left prefrontal cortex in € m Test of Nicotine Dependence, Dijkstra and Tromp, 2002) compared to controls with high smokers with high sensitivity of nicotine dependence (measured with the Fagerstro sensitivity of nicotine dependence (marked in red; green represents a white matter skeleton of the right hemisphere MNI brain), B) Higher gray matter density in the left insula in smokers compared to controls, independent of the sensitivity of nicotine dependence, C) Lower gray matter density in the left prefrontal area in smokers who reported high cigarette exposure (represented by pack-years) compared to high pack-years control individuals (slightly modified from Zhang et al., 2011); Right: White matter integrity between striatum and the prefrontal cortex in patients with schizophrenia and the role of smoking, A) Significant main effect of schizophrenia in the left anterior thalamic radiation/anterior limb of the internal capsula (whole brain analysis), B) Significant main effect of smoking in the left anterior thalamic radiation/anterior limb of the internal capsula (whole brain analysis). Arrows represent overlapping fibers of A and B., C) Significant main effect of schizophrenia in the left uncinate fasciculus/inferior fronto-occipital fasciculus, D) Significant main effect of schizophrenia in the right uncinate fasciculus/inferior fronto-occipital fasciculus, E) Significant main effect of smoking for the left frontal area (slightly modified from Zhang et al., 2010). Left: Error bars represent ±standard error of the mean across individuals; CI ¼ cingulo-insular network, FP ¼ fronto-parietal network, DAT ¼ dorsal attention network, DM ¼ default mode network, SM ¼ sensorimotor network, VIS ¼ visual network. Right: blue: white matter skeleton; red: clusters significant for schizophrenia; green: clusters significant for smoking.

association between craving and the cerebellum in smokers (Cosgrove et al., 2009), an interesting link between the nACh receptor function and the preparation and goal-directed action for cigarette use may be assumed, which may critically be tied to craving for a cigarette during abstinence. This might furthermore be underlined by the prominent role of nACh target receptors in subcortical and cortical areas important to drug reward and reward-relevant processes, partly due to nACh projections on the dopaminergic efflux in the ventral tegmental area (Clarke and Pert, 1985; Weiner et al., 1990) and the subsequent dopamine effect on nACh interneurons in the striatum (Berlanga et al., 2003), and suggests an important role of nACh and dopamine system interaction for striatal reward coordinations (Zhou et al., 2003). Interestingly, in the context of smoking abstinence, another study reported a possible role of the b2*-nACh receptor in pain sensitivity during tobacco smoking withdrawal (Cosgrove et al., 2010). Following a period of 7e13 days of smoking abstinence, Cosgrove et al. (2010) found a significant correlation between percent change in pain sensitivity from the first to the second session of a cold pressor task and b2*-nACh receptor availability in the cerebellum, ACC, thalamus, parietal, temporal and occipital cortices as well as the striatum. b2*-nACh receptor availability in these brain areas may thus serve as protecting factor in individuals who are more likely to relapse when they are confronted with painful stimuli during acute abstinence.

Besides nicotine addiction, similar changes in neural responses to cholinergic probes were also found for cocaine addiction. Alterations in brain regions important in the regulation of learning and memory of drug cues and craving involving the insula, the hippocampus and the amygdala as well as the dorsolateral PFC, ventral tegmentum, posterior cingulate and orbitofrontal cortex (OFC) were highlighted in cocaine-addicted patients compared to healthy controls (Adinoff et al., 2010). Moreover, human imaging studies addressed the effects of nACh receptor function on brain activity also in patient populations other than addiction such as patients with mood disorders or schizophrenia. For example, Thomsen et al. (2011) documented a dysfunction of the a7 nAChR-dependent signaling in the hippocampus and perirhinal cortex in patients with bipolar disorder compared to healthy control individuals. Although dysfunction of a7 nAChR-dependent signaling in the hippocampus was previously also reported for schizophrenia (Freedman et al., 1995), it could not be replicated in the study by Thomsen et al. (2011), which is in accordance with so far mixed results in this context (e.g. Breese et al., 2000; Mathew et al., 2007). Lastly, growing evidence has also been made in investigating the impact of the nicotinic cholinergic system in neurodegenerative disorders including PD, AD, and mild cognitive impairment (MCI). Degeneration of the basal forebrain cholinergic system appeared already early in PD prior to dementia symptoms (Hilker et al., 2005; Shimada et al., 2009). Specifically the nucleus basalis of Meynert

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(nbM) in the basal forebrain supplies the majority of the cholinergic input to the cerebral cortex and projects to thalamic nuclei (Perry et al., 1999). A study in PD that additionally addressed the role of depressive and cognitive symptoms in this disorder found a reduction of a4b2-nACh receptor binding in the cingulate cortex and frontoparietaleoccipital cortical regions, especially in those PD patients with mild depression (Meyer et al., 2009). The a4b2-nACh receptor may therefore represent a target therapeutic effector system to regulate non-motor symptoms in PD. Moreover, a reduction in a4b2-nACh receptor binding in the pons, cerebellum and midbrain was found in patients with MCI (Meyer et al., 2009). And, in MCI patients compared to healthy controls, an increase in the frontal and visual association cortex and the hippocampus due to cholinergic modulation were observed (e.g. Montine et al., 2010). These patients also exhibited an association of a significant decline of cortical nACh receptor activity in temporal brain regions with neuropsychological function (Haense et al., 2012). Structural brain imaging. Few human neuroimaging studies have investigated the effects of the nicotinic cholinergic system on structural brain measures. For example, researchers found lower gray matter densities in the bilateral PFC, ACC, OFC, occipital, temporal lobe, cerebellum and thalamus as well as smaller gray matter and left dACC volume in smokers compared to non-smoking individuals (Brody et al., 2004; Gallinat et al., 2006). Interestingly, gray matter densities in the PFC, OFC, ACC, temporal and cerebellar cortices were additionally negatively correlated with the magnitude of lifetime smoking exposure (Brody et al., 2004; Gallinat et al., 2006), and, cortical thickness of the OFC with both daily and lifetime smoking exposure (Kühn et al., 2010). Studies using diffusion tensor imaging (DTI) and fractional anisotropy (FA) reported an association of the degree of smoking dependence and prefrontal FA as well as increased gray matter density in the left insular cortex in smoking individuals (Zhang et al., 2011; see Fig. 1, middle). And, Tregellas et al. (2007) reported larger gray matter volumes in the lateral PFC and in superior temporal cortices in smoking compared to non-smoking schizophrenia patients. Furthermore, smoking has been linked to FA not only of gray, but also of cerebral white matter (e.g., Kochunov et al., 2007). Studies provided contradictory findings with both increased and decreased FA in smokers. While chronic and heavy smokers compared to non-smokers exhibited reduced FA values (Swan and Lessov-Schlaggar, 2007; Hudkins et al., 2010; Kim et al., 2010; Cullen et al., 2012; Gons et al., 2011; Liao et al., 2011; Zhang et al., 2010, 2011), for example in the corpus callosum (Lin et al., 2012; Umene-Nakano et al., 2014), which was additionally related to the amount of nicotine use indicated by the number of cigarettes per day (Umene-Nakano et al., 2014), smoking adolescents compared to non-smoking adolescents showed increased FA, for example in the anterior cortical white matter and in regions of the internal capsule with auditory thalamocortical and corticofugal fibers (Jacobsen et al., 2007; Paul et al., 2008; Hudkins et al., 2010; Liao et al., 2011). Moreover, in smoking compared to non-smoking adolescents, a significant positive association between FA of the posterior limb of the left inferior capsule and the response time during auditory attention was observed (Jacobsen et al., 2007). In addition, acute nicotine exposure using nicotine versus placebo patch in smokers resulted in significantly increased FA values in the genu of the corpus callosum in those smokers with low previous smoking and may thus depend on recent nicotine intake (Kochunov et al., 2013). These white matter changes furthermore explained 22% of the variance in performance during sustained attention, which was however limited to those smokers also suffering from schizophrenia (Kochunov et al., 2013). Thus, the previously mentioned importance of common and distinct effects of nACh receptor function on brain mechanisms across several disorders was also picked up by structural neuroimaging studies. In

addition, Zhang et al. (2010) showed a reduction of the FA of the white matter fibers connecting the PFC with the thalamus and the striatum in nicotine-addicted patients and patients with schizophrenia (see Fig. 1, right). These changes in white matter function based on cholinergic stimulation of nicotinic receptors may be partly driven by promyelinating effects via glycogen synthase kinase-3 inhibition (Bartzokis, 2012; De Sarno et al., 2006; Wang et al., 2011). Finally, along a genetic-imaging approach, three SNPs (rs16969968, rs1051730, rs2869546) in the CHRNA3 and CHRNA5 receptor genes were significantly associated with nicotine dependence, but neither with tobacco initiation nor regular smoking (Maes et al., 2011). Last, Markett et al. (2013) demonstrated a reduced gray matter volume in the right putamen in homozygous T allele carriers of the CHRNA4 rs1044396 polymorphism. Interestingly, this gray matter reduction was additionally found in homozygous C allele carriers of a dopaminergic polymorphism, the DRD2 rs6277, again supporting the importance of an interaction of the nicotinic cholinergic system and the dopaminergic system on brain structure and function, which was also highlighted above. Resting state brain imaging. Several neuroimaging studies have investigated the impact of nicotine and tobacco on large-scale brain networks that can be detected at rest, without any explicit task performances, reflecting the underlying structural and functional architecture of the human brain (Greicius et al., 2009; Smith et al., 2009; van den Heuvel et al., 2009). Resting state brain responses has been conceptualized as an antagonism between a task-positive network that is kind of extrospective and a task-negative network that is rather introspective (Brody et al., 2009). In contrast to its supposed enhancement of the so-called task-positive networks and thus improvements of cognitive performances, nicotine was shown to have suppressing effects on the task-negative networks. The default mode network (DMN) is comprised by the medial PFC, posterior cingulate cortex, medial temporal and inferiorelateral parietal cortex and showed spontaneous brain activity fluctuations at rest that has been shown to deactivate during effortful tasks (Raichle et al., 2001). Nicotinic imaging studies in smokers versus non-smokers revealed a reduction of those DMN brain regions at rest, especially of the posterior cingulate cortex (Tanabe et al., 2011), and therefore corroborated findings of a reduction in default mode regions (Hahn et al., 2007, 2009; Ettinger et al., 2009; Tanabe et al., 2011). Furthermore, activity in brain regions of the DMN were involved in the prediction of behavioral changes following nicotine exposure, which may suggest that individuals who have difficulties in sustaining attention might be those who specifically benefit from nicotine (Giessing et al., 2007). Interestingly, Hong et al. (2009) addressed another important aspect in this context, namely the duration of nicotine exposure, and its subsequent effects on resting-state functional connectivity. Following acute nicotine administration, smokers exhibited enhanced connectivity between subdivisions of the cingulate cortex and parietal and frontal cortical regions, which might be interpreted as a statelike effect, while a chronic nicotine effect, determined by the severity of nicotine dependence, was mediated by a negative association of the dACCeventral striatal circuit (Moran et al., 2012). Furthermore, Cole et al. (2010) investigated the effects of nicotine replacement not only on the DMN, but also its interaction with the executive control network (ECN) involved in attention demanding cognitive tasks and deactivated during rest. Cole et al. (2010) found that cognitive withdrawal symptoms following nicotine replacement were associated with a negative interaction of DMN and ECN. This is also consistent with previous studies on nicotine-induced DMN deactivation during a selective attention task (Hahn et al., 2007). Moreover, Tanabe et al. (2011) found reduced activity in the DMN following acute nicotine exposure in non-smoking

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individuals, along with increased activity in extra-striate brain regions comprising the visual attention network. Reduced resting state strength was not only observed for the DMN following nicotine administration in abstinent smokers, but also for interactions

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between the DMN including parahippocampus, posterior cingulate and ventro- and dorsomedial PFC and the insula as well as for amygdalaeinsula circuits (Sutherland et al., 2013; see Fig. 2). Both insulaeamygdala and insulaeDMN connectivities at rest may

Fig. 2. Amygdala and insula functional circuits following administration of varenicline and nicotine in abstinent cigarette smokers, A) Increased resting-state functional connectivity strength in a posterior cingulate cortex-medial prefrontal cortex circuit following nicotine administration in abstinent smokers (S, green: center coordinate obtained from an insulacentric analysis), B) Decreased resting-state functional connectivity strength in amygdalaecentric and insula-centric circuits (1), with a left (L.) amygdala seed (S, green), in the precentral gyrus (2), parietal regions (3), and the posterior insula (4) following nicotine administration in abstinent smokers., C) Decreased resting-state functional connectivity strength in insula and posterior cingulate cortex/precuneus (1), with a left insula seed (S, green: center coordinate obtained from an insula-centric analysis), in the ventromedial prefrontal cortex (2), the dorsomedial prefrontal cortex (3), and the midcingulate cortex (4) following nicotine administration in abstinent smokers. (slightly modified from Sutherland et al., 2013). rsFC ¼ resting-state functional connectivity; PCC ¼ posterior cingulate cortex; mPFC ¼ medial prefrontal cortex; Plac. ¼ placebo; Pre- ¼ prepill.

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therefore contribute to symptoms of subjective withdrawal. So far, genetic-imaging approaches showed a key impact of the a3 rs578776 polymorphism on resting state functional connectivity, more precisely the dACCethalamus circuit and an association of this interaction with smoking (Hong et al., 2010). Moreover, an interaction of the a5 gene variant Asp398Asn with the dACCeventral striatum/extended amygdala circuit was observed, in that risk allele carriers of this gene variant showed reduced connectivity (Hong et al., 2010). These findings on the effects of a3 and a5 gene variants on the resting state network and its association with the strength of both smoking status and nicotine addiction may highlight a differential mediation of state and trait aspects by the nACh receptor function. Lastly, the strength of the resting state brain circuit was also reduced in patients with various mental disorders who show high rates of smoking. For example, a negative association of smoking severity and resting state connectivity between the striatum, dACC and additionally the insula was found in smoking patients with schizophrenia, with an additive effect of smoking and schizophrenia diagnosis on insulaedACC connectivity reductions (Moran et al., 2012). In addition, a study in non-smoking patients with schizophrenia also reported a DMN reduction following the administration of the a7 nicotinic receptor agonist 3(2,4-Dimethoxybenzylidene)-anabaseine (Tregellas et al., 2011). Therefore, the nicotinic cholinergic system may modulate both global and local, intero- and exteroceptive aspects of information processing, and partly across mental disorders. Together, the nicotinic cholinergic system does not only exert effects on brain activity per se, without any task performance, but is also critical in modulating brain activation during task execution and thus for specific mechanistic domains. Cholinergic inputs from the basal forebrain are crucial for attention and memory function through connectivity to frontal or basolateral limbic brain areas. Findings in this context will be summarized in the next section of this review. 3. Affected domains Nicotine is known to enhance various cognitive functions including specifically attention and memory, but also response inhibition, emotion, cue reactivity and reward processing (see Heishman et al., 2010 for meta-analysis). 3.1. Attention Human neuroimaging research revealed a modulation of various attentional processes, especially selective attention, by the cholinergic agonist nicotine (see Heishman et al., 2010 for review). During a rapid visual information processing task, smokers showed alterations not only on a behavioral level exhibiting an increased number of hits following nicotine exposure compared to a placebo condition, but, on a neural level, also increased activation in the thalamus, parietal cortex and caudate nucleus (Lawrence et al., 2002). Interestingly though, although brain activation was increased in the smokers, their activation in the caudate nucleus and parietal cortex was still significantly lower compared to the activation in these brain regions in healthy non-smoking individuals following nicotine administration (Lawrence et al., 2002). Moreover, using a visual oddball task, Warbrick et al. (2012) recently reported an increased activation in the superior parietal and lateral occipital cortices and the precuneus following nicotine administration in smokers. Another recent study by Ricciardi et al. (2013) showed that cholinergic enhancement resulted in improved behavioral performance during a selective attention task, that was associated with reduced functional connectivity between taskrelated regions including the parietal, occipital and prefrontal

cortices, and ventral visual processing areas. The authors conclude that this decreased connectivity strength in task-relevant regions and regions related to stimulus processing, along with behavioral improvements may speak for an increased neural efficiency due to cholinergic augmentation. Interestingly, the improvement of attention during a rapid visual information processing task following nicotine exposure in smokers accompanied by an activation of cortical areas including the middle and inferior frontal cortices, anterior insula, thalamus, cerebellum, parietal and occipital cortex and the caudate (Lawrence et al., 2002), was also shown in patients with schizophrenia who smoke (Jacobsen et al., 2004). However, using the same task, another study found that patients with schizophrenia compared to healthy controls showed reduced task-related activation in these brain regions following both placebo and nicotine administration (Hong et al., 2011). These controversial findings may suggest either a dose-specific effect in that the dose of nicotine was not high enough to overcome attention-related neural deficits or that nicotine can not normalize attention deficits in these patients (Hong et al., 2011). Furthermore, acute nicotine did not only modulate brain areas associated with direct attentional processes, but also brain region that are involved in associated intentional and motor preparation including the left inferior parietal lobule, the left postcentral gyrus and the suprmarginal gyrus (Rose et al., 2010). Interestingly, in the study of Lawrence et al. (2002), not only an increased activation in various brain regions was found, but also a decrease in brain activity in the amygdala, anterior and posterior cingulate, medial frontal cortex, parahippocampus and mid-insula was observed. In comparison to non-smoking individuals, smokers exhibited reduced task-induced activation in the parietal cortex and caudate following placebo administration, but increased activation in the thalamus, parietal cortex and caudatus following nicotine exposure (Lawrence et al., 2002). The parietal cortex is a region that was also found to be increased in other studies that investigated nonsmoking individuals following nicotine exposure who underwent a visuospatial selective attention task, the cued target detection task (e.g. Giessing et al., 2006; Thiel et al., 2005). Moreover, using this task, other significantly activated brain areas during reorienting of attention, assessed by contrasting invalid-cued trials with valid-cued trials, comprised the superior and middle temporal as well as middle frontal cortex, whose activity was also increased following nicotine administration, and in some cases additionally associated with speeded reaction times (e.g. Giessing et al., 2006; Thiel et al., 2005). In addition, in mildly deprived smokers, nicotine exposure resulted in reduced activation in the parietal cortex, anterior and posterior cingulate cortices and the middle frontal cortex during a cued selective attention task (Hahn et al., 2007, 2009). Further studies demonstrated the effects of nicotinic blockade on brain activity during attention using antinicotinic drugs such as mecamylamine, a non-competitive nicotinic receptor antagonist with specific effects at a4b2 nicotinic receptors (Newhouse et al., 1992, 1993, 1994). For example, Thienel et al. (2009) used the attention network task that addresses sub-attentive components of orienting, alerting and executive control, and found a reduced activation in the thalamus, posterior cingulate, superior occipital and parahippocampal gyrus in the orienting condition in healthy non-smoking individuals that was accompanied by increased reaction times across all three sub-components. For executive functioning, reduced activity following mecamylamine compared to placebo was observed in the superior parietal area, the precuneus and gyrus rectus (Thienel et al., 2009). Imaging-genetic studies revealed a significant association of the CHRNA4 receptor polymorphism rs1044396 on brain activation during a cued attention task (e.g. Winterer et al., 2007). On trials,

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where attention had to be redirected, homozygous T-allele carriers showed increased activation in the superior temporal gyrus, implicated in re-orienting, while homozygous C-allele carriers showed increased activation in the middle temporal gyrus, implicated in cognitive control (Giessing et al., 2012). Since the superior temporal gyrus was more strongly connected to the superior temporal sulcus and the middle temporal gyrus with the head of the caudate, these findings may suggest a modulatory effect of the CHRNA4 genotype on the use of specific attentional strategies (see Greenwood et al., 2012 for review). Furthermore, the impact of the rs1044396 polymorphism was also investigated using an attentionrequiring visual oddball task (Winterer et al., 2007). In this study, the authors reported a significant genotype effect targeting the supplementary motor area/anterior cingulate and parietal cortex and a significant gene-dosage effect in the parietal cortex, but in this case in the absence of any behavioral effects. In sum, nicotine may exert attention modulating effects by the induction of activity changes in cortical regions mainly including the parietal, prefrontal and occipital cortex, and both amygdala and hippocampus may also play a significant role (Levin et al., 2002; Newhouse et al., 2004). 3.2. Memory Several recent human studies reported significant effects of nicotine on memory performance indicated by improvement of accuracy in episodic memory, while for example accuracy in working memory was not significantly modulated, although reaction times were found to be significantly improved (see Heishman et al., 2010 for review). Functional brain imaging data exists to a larger extent for working memory and only a few studies have investigated the impact of the nicotinic cholinergic system on episodic memory processes (Bozzali et al., 2006; Kukolja et al., 2009). Similar to the findings from research on attention, nicotine-related pharmacological interventions showed partly differences in brain activation patterns depending on the study population, i.e. whether smokers or non-smoking individuals were investigated (Ernst et al., 2001). For example, during working memory, varenicline, a partial agonist at a4b2* nACh receptors, resulted in an increased activation of the dACC, dorsolateral PFC and medial frontal cortex in heavily dependent smokers (Giessing et al., 2006). Studies in non-smoking individuals using an n-back task that assess working memory performance showed increased activity in fronto-parietal regions, but reduction activation of the posterior cingulate cortex following nicotine exposure (Kumari et al., 2003). These findings are similar with those from studies on attention processes that used the rapid visual information processing task, a task that have several similarities with the n-back task measuring sustained attention and working memory (e.g. Lawrence et al., 2002). Moreover, in another study the administration of varenicline resulted in increased activity in dorsolateral and medial frontal regions for the very difficult 3-back condition (Loughead et al., 2013), a finding that was partly also reported in deprived smokers (Xu et al., 2006). Further increases in brain activation in this n-back condition were observed in the parahippocampal gyrus, the superior and inferior frontal gyrus and the posterior cingulate cortex (Loughead et al., 2013). Lastly, an enhancement of cholinergic transmission by administration of physostigmine, a cholinomimetic drug, resulted in increased activation in ventral visual cortical regions, but in decreased activation in the anterior PFC during working memory (Furey et al., 2000). Moreover, a recent study reported on the neural correlates of the association between nACh receptor stimulations following acute nicotine exposure and modulations during prospective memory (Rusted et al., 2011). Using a simple attention task

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containing prospective memory trials, acute nicotine administration resulted in decreased activation of parietal regions, but had no significant effect on prefrontal/frontal regions that were shown to be significantly activated during task performance in general (Rusted et al., 2011). Another study on the effects of cholinergic enhancement on the encoding of key visual processing features showed increased activation in the dorsal stream during encoding of face location and in the ventral stream during encoding of face identity in individuals following administration of the nACh inhibitor physostigmine, but reduced activation in these brain regions in response to the sensorimotor control images (Handjaras et al., 2013). Neural activity related to the cholinergic system may therefore play an important role in signal detection and early perceptual processing depending on stimulus features. Interestingly, Sutherland et al. (2011) investigated mildly deprived smokers following nicotine exposure and found significant effects on the behavioral performance, but yielded no significant modulation of brain activation. Moreover, studies that have examined the effects of nicotinic blockade, for example with mecamylamine, did neither found significant impairments in working memory nor in recognition memory, but mecamylamine compared to placebo exposure resulted in increased activation in the hippocampus and frontal regions during episodic memory performance (Dumas et al., 2008). In addition, nicotinic blockade also resulted in decreased activation in the occipital cortex during encoding, but in increased activation in the anterior hippocampus, the inferior temporal gyrus and the occipital cortex during memory retrieval (Dumas et al., 2010). Research in humans has also addressed the role of the nicotinic cholinergic system on memory performance in patient populations other than addiction. A study that investigated the effect of nicotine exposure during working memory using a dichotic 2-back task condition in schizophrenia patients showed enhanced activation in the thalamus, the ACC as well as thalamo-cortical functional connectivity in patients compared to control individuals (Jacobsen et al., 2004). Another study investigated AD and MCI patients using a pharmacological intervention via cholinergic stimulation induced by exposure to galantamine, a cholinesterase inhibitor, used also for treatment of memory deficits in AD (Goekoop et al., 2006). In MCI, acute galantamine exposure resulted in increased activation in the left inferior parietal cortex, the posterior cingulate and anterior temporal cortex, while prolonged exposure induced decreased activation in the posterior cingulate and the PFC. These effects were specific to memory retrieval indicated by a stronger modulation of positive, familiar compared to negative, unfamiliar decisions. In contrast, in AD, acute exposure resulted in increased activation in the hippocampus, while prolonged exposure resulted in decreased hippocampal activity. This effect was specific for memory encoding indicated by stronger effects for negative compared to positive decisions (Goekoop et al., 2006). These differential brain response patterns in MCI and AD may suggest a difference in the functional status of the nicotinic cholinergic system, which might be important for processes underlying the development of AD a well as for clinical treatment approaches. Interestingly, in the context of treatment of AD patients, Miettinen et al. (2011) investigated the effect of the acetylcholinesterase inhibitor rivastigmine on brain activation during a face recognition memory task. After both acute and chronic (4 weeks) rivastigmine treatment compared to the placebo condition, increased activation in the PFC was found in AD patients. This PFC activation was significantly associated with the preserved cognitive ability of the patients in that those patients with poorer cognition showed greater PFC activity following chronic treatment. Finally, one study also used genetic imaging approaches to uncover the role of the nicotinic cholinergic system on brain

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activation patterns during memory performance. Smokers with an A-allele of the a5 subunit-containing nACh receptor polymorphism rs16969968, which is known to reduce nACh receptor function in the hippocampus, showed disruptive working memory performance in an n-back task (Winterer et al., 2010). 3.3. Response inhibition Behavioral studies that have shown that the nicotinic cholinergic system is associated with response inhibition deficits in patients with attention deficit-hyperactivity disorder (ADHD) already pointed to the evidence of nicotinic cholinergic system function effects on cognitive control and response inhibition, which might contribute to impulsivity symptoms in this disorder (Potter et al., 2006). The few recent bran imaging studies on the impact of the nicotinic cholinergic system on response inhibition corroborated these previous behavioral findings. Along with a normalization of response inhibition deficits following acute nicotine administration in both patients with ADHD and non-smoking adolescents, functional brain imaging studies in smoking individuals found that increased activation in the neural response inhibition network including the basal ganglia, the inferior frontal gyrus and the presupplementary motor area was positively associated with smoking behavior and significantly predicted smokers' attempts to quit (Berkman et al., 2011). Moreover, not only for smoking or ADHD, but also for patients with multiple sclerosis (MS), studies have demonstrated an important role of the nicotinic cholinergic system on the neural correlates of response inhibition and cognitive control. Using the Stroop task that measured the inhibition of word reading versus colour naming, administration of rivastigmine, a cholinesterase inhibitor that increases nicotinic signaling, compared to placebo, resulted in increased activation in the inferior frontal gyrus during the conflict condition of the Stroop task and thus in a normalization of brain activation patterns to a level similar to control individuals (Parry et al., 2003; Cader et al., 2009). 3.4. Emotion, reward and cue reactivity Brain imaging studies on the effects of the nicotinic cholinergic system on emotional or reward processing and cue reactivity are scarce. With respect to the treatment of smoking cessation, the use of varenicline that was shown to relieve negative affective signs of nicotine withdrawal, resulted in decreased activation in the amygdala, the dACC/medial frontal cortex, the thalamus and the occipital cortex, along with increased activation in the middle temporal gyrus in abstinent smokers that underwent a face emotion identification task (Loughead et al., 2011). These activation patterns were however only associated with correct response and interestingly also independent of the emotional valence of the stimulus (Loughead et al., 2011). Moreover, acute nicotine exposure in non-smoking individuals resulted in increased activation in the amygdala and other limbic and subcortical areas in response to unpleasant, but not pleasant stimuli (Kobiella et al., 2011). In addition, cholinergic enhancement following administration of physostigmine induced an increased activation in the dorsolateral and medial PFC in response to task-relevant fearful faces (Vuilleumier et al., 2001; Armony and Dolan, 2002; Perlstein et al., 2002) as well as increased activation in the parietal and orbitorfrontal cortices in response to task-irrelevant fearful stimuli (Bentley et al., 2003a). These studies point to the evidence that cholinergic stimulation enhance processing of emotional stimuli (Bentley et al., 2003a), depending on the relevance of these stimuli, and support the importance of nicotinic antagonists also in the treatment of mood disorders such as depression, where for example mecamylamine has already been studied as an augmentation treatment (George et al.,

2008; Lippiello et al., 2008; Lindsley, 2010). Although these findings were derived from studies in different populations, they point to the importance of specificities in biochemical drug effects. While varenicline seems to enhance early perceptual face processing rather than to mediate affective changes, the latter one seems to be true for the nicotinic drug physostigmine. Thus, a rather complex nicotinic modulation pattern on emotional processing at the neuronal systems level may be assumed. In the context of clinical and preclinical research in drug addiction, cue reactivity has been identified as an important mechanism for nicotine seeking and smoking behavior and may confer relapse vulnerability in smokers (e.g. Janes et al., 2010). Nicotinic stimulation by the administration of varenicline resulted in reduced responsivity to smoking-related cues mediated by reduced activation in the ventral striatum and the medial orbitofrontal cortex (Franklin et al., 2011). Moreover, varenicline administration also induced an increased activation in the inferior, middle and upper frontal gyri, the anterior and posterior cingulate, the dorsolateral PFC and the lateral orbitofrontal cortex (Franklin et al., 2011). Therefore, the nicotinic cholinergic system might play a role in a) control over motivational and emotional behavior such as craving for nicotine (Cardinal et al., 2002), indicated by the activation of the ventral striatum in response to smoking cues, b) reward-related decision making and representation of the affective value of rewarding stimuli, indicated by activation in the medial orbitofrontal cortex (Kringelbach, 2005), and c) the re-evaluation and subsequent response selection of rewarding responses indicated by the lateral orbitofrontal cortex (Elliott et al., 2000). Furthermore, genome wide association studies have previously revealed a relationship between the nACh receptor a5 subunit gene (CHRNA5) and addiction. While the single-nucleotide polymorphism rs16969968 was found to be associated with nicotine dependence and dACCestriatal circuit, another polymorphsism of this gene, rs578776, was associated with smoking behavior, along with activity in the dACCethalamus circuit (Hong et al., 2010). A following study found an additional role of rs16969968 in brain activation during smoking cue reactivity, with homozygous G-allele carrying women exhibiting increased activation in bran regions such as the dorsal striatum and hippocampus (Janes et al., 2012), that were also involved in memory and habitual behavior (e.g. van der Meer et al., 2010). Moreover, we have recently observed reduced activation in the right ventral and dorsal ACC during general, non-drug-related reward processing in adolescent carriers of the G/G genotype of the rs578776 polymorphism, that might interestingly at least partly also being related to anxiety sensitivity (Nees et al., 2013). Therefore, via different nACh receptor function expressions in the human brain, the nicotinic cholinergic system seems to be involved in the recall of smoking-related memories and habitual responding to smoking cues as well as the processing of and behavioral adaptation to changing reward outcomes. 4. Discussion and conclusion Although, the majority of studies reported very consistently an increased activation in task-related brain regions during attention, memory, response inhibition and emotional processing as well as reduced activation of the DMN network at rest, human brain imaging studies partly provided also mixed results and rather point to a complex role of the nicotinic cholinergic system on brain activation, with both increased and decreased neural activation patterns across a large set of brain areas involving frontal, temporal, visual, parietal and thalamic as well as limbic cortices. Moreover, structural brain changes, for example in gray and white matter tracts, following acute nicotine exposure and smoking history were

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observed, but results range along both enhanced and reduced FA values. This furthermore points to a complex pattern of nicotinic cholinergic system effects on the human brain and highlights the need to consider additional factors such as cognitive alterations (e.g. intelligence, Cullen et al., 2012) or duration and degree of nicotine exposure as well as age and gender (e.g., Jacobsen et al., 2007; Kochunov et al., 2013). Interestingly, studies so far highlighted the modulation of common neural response patterns across various psychological domains as well as mental and neurodegenerative disorders. This points to the suggestions by the Research Domain Criteria Initiative of the National Institutes of Mental Health (Cuthbert and Insel, 2013; Flor and Meyer-Lindenberg, 2014) on common symptoms and mechanisms across disorders which might be fruitful to investigate also in the context of the nACh receptor function. Mental disorders may not only differ in a number of symptoms and related brain responses, but also across mental disorders and studies, shared key features can be assumed. In addition, there are subgroups with common mechanisms within disorders and comorbidity may change the neural and behavioral correlates related to a specific disorder. A specific need in future studies is therefore a more detailed identification of mechanisms related to the nicotinic cholinergic system that are common and different across mental disorders. The diversity of brain regions influenced by the nicotinic cholinergic system also suggests that this system may act on sub-processes of mechanistic domains, whereby different conditions, for example within attention and working memory processes, may be regulated by different cortical regions. Moreover, findings within the same population (e.g. smokers) also revealed different response patterns depending on specificities of the task and experimental design, the type of drug and the duration or method to stimulate or block the nicotinic system. For example, for the stimulation of the nicotinic cholinergic system via acute nicotine administration methods range from using nicotine patches, sprays or intravenous nicotine exposure (see Bentley et al., 2003b for meta-analysis). Moreover, baseline differences in the cholinergic system function may also play an important role. The investigation of healthy individuals with normal cholinergic function versus patient groups or smoking individuals with a different duration of smoking history and thus a possible basline hyper- or hypocholinergic function, may result in side-effects on nACh system level modulation on brain activation patterns. Lastly, some of the previously reported effects of the nicotinic cholinergic system function on deactivationeactivation patterns related to the DMN at rest versus to task-related brain regions point to a role as significant biomarker in the context of preparing or re-orienting to internal processing versus external input. Together, findings can be discussed in the context of drug development for treatment approaches, also in combination with psychological treatment lines, depending on the observed correlation of brain activity with cognitive and behavioral performances. 5. Outlook A large number of future studies is needed to further uncover the impact of the nicotinic cholinergic system on the human brain. Beside a more stringent use of tasks that assess important cognitive functions, growing evidence from studies on brain activation at rest may provide additional advantages (Greicius, 2008). A lack of research is currently obvious for emotional and reward processing and cue reactivity or learning, where almost no human brain imaging study exists. Therefore, with respect to psychological domains, not only further studies on different mechanisms and functions are needed, but also approaches that enable the dissociation of different sub-processes of a specific domain, for example disentangling encoding, maintenance and retrieval of episodic or

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working memory (Dumas et al., 2010) are necessary and may represent an important new avenue. Moreover, investigations on the limbic circuits following an increase in the nicotinic cholinergic function, specifically on limbic-frontal functional connections, that were for example found to be associated with an increase in attentional processing of emotional stimuli, may also be important. In addition, some evidence exists on the effects of the nicotinic cholinergic system on structural properties of brain regions with measures such as gray and white matter densities, DTI or volumetric imaging. This may shed further light into specific modulation patterns and is useful in disentangling possible baseline difference before performing pharmacological interventions. Future human brain imaging studies should also consider looking at potential neural responders versus non-responders following stimulation or blockade of the nicotinic cholinergic system (Giessing et al., 2007; Honey et al., 2008). Advanced neuroimaging methods such as multivariate and pattern analyses may provide promising tools to identify and classify individuals in this context (Fu et al., 2008). Furthermore, genes for nicotinic receptors have been linked to both normal development and diseases (Todd et al., 2003; Hruska et al., 2009). Additional work along an imaging-genetics approach is needed investigating not only further polymorphisms, but also uncovering the causative role of identified functional polymorphisms on neural network function as well as comparing different populations including clinical samples. The investigation of an interaction between the dopaminergic and nicotinic cholinergic system, also with respect to genotype effects, seems to be a promising line of research, because nACh receptor function was shown to stimulate dopaminergic efflux in the striatum and the DRD2 together with the CHRNA4 genetic variant were shown to be associated with reduced gray matter volume in striatal tissue, which was additionally negatively related to cognitive performance (Esterlis et al., 2013). Finally, the application of longitudinal studies is a promising way not only to elucidate neural changes associated with pharmacological modulation effects, but also for monitoring treatment efficacy and in consequence for the development and elucidation as well as improvement of treatment approaches. A study by Pa et al. (2013) has recently supported this approach. Using a 3-month follow-up procedure the authors highlighted an improvement in goal-directed processing as well as in the interaction of attention and memory processes following increased cholinergic transmission via donepezil administration, indicated by enhanced functional connectivity between the hippocampus and the left fusiform face area in a face and scene memory task. But, further research is needed also in this context. Acknowledgment This study was supported by the IMAGEN project, which receives research funding from the European Community's Sixth Framework Program (LSHM-CT-2007-037286). References Aarsland, D., Hutchinson, M., Larsen, J.P., 2003. Cognitive, psychiatric and motor response to galantamine in Parkinson's disease with dementia. Int. J. Geriatr. Psychiatry 18, 937e941. Adinoff, B., Devous, M.D., Williams, M.J., Best, S.E., Harris, T.S., Minhajuddin, A., Zielinski, T., Cullum, M., 2010. Altered neural cholinergic receptor systems in cocaine-addicted subjects. Neuropsychopharmacology 35, 1485e1499. Armony, J.L., Dolan, R.J., 2002. Modulation of spatial attention by fear-conditioned stimuli: an event-related fMRI study. Neuropsychologia 40, 817e826. Bartzokis, G., 2012. Neuroglialpharmacology: myelination as a shared mechanism of action of psychotropic treatments. Neuropharmacology 62, 2137e2153. Benowitz, N.L., 1996. Pharmacology of nicotine: addiction and therapeutics. Annu. Rev. Pharmacol. Toxicol. 36, 597e613.

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Please cite this article in press as: Nees, F., The nicotinic cholinergic system function in the human brain, Neuropharmacology (2014), http:// dx.doi.org/10.1016/j.neuropharm.2014.10.021