Nicotinic Acetylcholine Receptors in RatForebrain That Bind 18F-Nifene: Relating

PET Imaging, Autoradiography, andBehavior

KASIA M. BIESZCZAD,1,2 RITU KANT,3 CRISTIAN C. CONSTANTINESCU,3 SURESH K. PANDEY,3

HIDEKI D. KAWAI,1,4 RAJU METHERATE,1,2,5* NORMAN M. WEINBERGER,1,2,5 AND

JOGESHWAR MUKHERJEE3

1Department of Neurobiology & Behavior, University of California, Irvine, California2Center for the Neurobiology of Learning and Memory, University of California, Irvine, California

3Preclinical Imaging Center and Department of Psychiatry & Human Behavior, University of California, Irvine,California

4Faculty of Engineering, Department of Bioinformatics, Soka University, Hachiouji, Tokyo5Center for Hearing Research, University of California, Irvine, California

KEY WORDS nicotine; learning; memory; auditory; thalamocortical; prefrontal

ABSTRACT Nicotinic acetylcholine receptors (nAChRs) in the brain are importantfor cognitive function; however, their specific role in relevant brain regions remainsunclear. In this study, we used the novel compound 18F-nifene to examine the distribu-tion of nAChRs in the rat forebrain, and for individual animals related the results tobehavioral performance on an auditory-cognitive task. We first show negligible bindingof 18F-nifene in mice lacking the b2 nAChR subunit, consistent with previous findingsthat 18F-nifene binds to a4b2* nAChRs. We then examined the distribution of18F-nifene in rat using three methods: in vivo PET, ex vivo PET and autoradiography.Generally, 18F-nifene labeled forebrain regions known to contain nAChRs, and thethree methods produced similar relative binding among regions. Importantly,18F-nifene also labeled some white matter (myelinated axon) tracts, most prominentlyin the temporal subcortical region that contains the auditory thalamocortical pathway.Finally, we related 18F-nifene binding in several forebrain regions to each animal’sperformance on an auditory-cued, active avoidance task. The strongest correlationswith performance after 14 days training were found for 18F-nifene binding in the tem-poral subcortical white matter, subiculum, and medial frontal cortex (correlation coeffi-cients, r > 0.8); there was no correlation with binding in the auditory thalamus orauditory cortex. These findings suggest that individual performance is linked tonicotinic functions in specific brain regions, and further support a role for nAChRs insensory-cognitive function. Synapse 66:418–434, 2012. VVC 2011 Wiley Periodicals, Inc.

INTRODUCTION

Nicotinic regulation of neural processing is impor-tant for sensory-cognitive function, as demonstrated inphysiological and behavioral studies (Hasselmo andSarter, 2011; Levin et al., 2006; Perry et al., 2000). Nic-otine and other agonists enhance performance on cog-nitive tests, and conversely, the loss of forebrainnAChRs is associated with cognitive decline. Althoughstudies indicate that nicotinic function is important forcognition, the relationships among nAChR functions,neural systems and behavior are not well understood.

One approach to understanding this relationship isto relate nicotinic function in specific neural circuits

to behavior. For example, nicotine-induced enhance-ment of auditory cortex function correlates well withauditory-cued behavior in rats, i.e., good performers

K.M.B., R.K., and C.C.C. contributed equally to this work.Contract grant sponsor: NIH; Contract grant numbers: R01AG029479,

R01DC02938, R01DC010013, DC009163, RO3DC08204, R01DA12929,P30DC08369.

*Correspondence to: Raju Metherate, Department of Neurobiology andBehavior, University of California, Irvine, 2205 McGaugh Hall, Irvine, CA92697, USA. E-mail: raju.metherate@uci.edu

Received 7 October 2011; Accepted 14 December 2011

DOI 10.1002/syn.21530

Published online 28 December 2011 in Wiley Online Library (wileyonlinelibrary.com).

VVC 2011 WILEY PERIODICALS, INC.

SYNAPSE 66:418–434 (2012)

on an active avoidance task exhibit stronger nicotineeffects (Liang et al., 2008). Similarly, good performanceon a cortex-dependent task is associated with a higherdensity of nAChRs in hippocampus and neocortex inrabbits (Li et al., 2008). Intriguingly, naturally-occur-ring mutations that enhance nAChR function arelinked to enhanced cognitive performance in humans(Espeseth et al., 2010). Although it may seem surpris-ing that normal variation in cognitive function mayresult from variation in a single neurotransmitterreceptor, the success of this approach may reflect theimportance of nAChRs for cognition. To examine thisissue further, in the present study we assessed thefeasibility of relating behavior to nAChR function asdetermined non-invasively with PET imaging.

In PET studies, radioligands are used to imagenAChRs (reviewed by Horti et al., 2010), with the recentintroduction of 18F-nifene proving effective for imaginga4b2* nAChRs (asterisk indicates presence of addi-tional subunits) with significantly shorter scan timesthan existing radioligands (e.g., 40–60 min vs. severalhours) (Easwaramoorthy et al., 2007; Hillmer et al.,2011; Kant et al., 2011; Pichika et al., 2006). Resultsacross binding studies are largely consistent with thedistribution of a4b2* nAChRs in earlier studies. A nota-ble exception is a PET study demonstrating strong, pu-tative a4b2* nAChR binding in the human temporalsubcortical white matter, an unexpected finding sinceneurotransmitter receptors are not thought to functionin myelinated axon pathways (Ding et al., 2004). How-ever, a subsequent physiological study showed thatnAChRs regulate axon excitability for myelinated axonsin the mouse auditory thalamocortical pathway (Kawaiet al., 2007). Thus, nicotinic regulation of thalamocorti-cal axons can enhance sensory-evoked corticalresponses, which in turn could enhance cognitive proc-essing of sensory stimuli (Metherate, 2011).

The present study was conceived as a first steptowards relating nicotinic function in specific brainregions to behavior. We first determined the distribu-tion of 18F-nifene using in vivo PET, ex vivo PET, andautoradiography in rats, wild-type mice, and mice lack-ing b2 nAChRs, and then correlated nAChR levels inselected brain regions with behavioral performance fora subgroup of rats. Regions of interest selected for corre-lation of 18F-nifene binding with behavior were selectedeither for relevance to auditory processing or for knowndensity of nAChRs. The results show that auditory-cog-nitive performance is correlated positively with 18F-nifene binding in a subset of brain areas including fron-tal cortex, subiculum, and, exclusively among auditoryregions, the temporal subcortical white matter.

MATERIALS AND METHODS

All animal procedures were performed in accord-ance with NIH guidelines and approved by the Uni-

versity of California, Irvine IACUC. Rats used forPET studies were first characterized behaviorally,then scanned and the data analyzed with the experi-menter blind to behavioral results. For experimentsin mice, subjects were either wild type or transgenicmice lacking the b2 nAChR subunit (Picciotto et al.,1995).

General imaging methods

All chemicals and solvents were purchased fromAldrich Chemical and Fisher Scientific. Deionizedwater was acquired using a Millipore Milli-Q WaterPurification System. Gilson high performance liquidchromatography (HPLC) was used for the semipre-parative reverse-phase column chromatography. Fluo-rine-18 fluoride was produced via MC-17 Scanditronixcyclotron using oxygen-18 enriched water. Radioactiv-ity was counted using a Capintec dose calibratorwhile low level counting was done using a well-coun-ter. An Inveon preclinical dedicated PET (SiemensMedical Solutions, Knoxville, TN) with a transaxialFWHM of 1.46 mm, and axial FWHM of 1.15 mm(Bao et al., 2009; Constantinescu and Mukherjee,2009) was used for the PET studies. Both in vivo andex vivo PET images of rat brains were obtained andanalyzed using Acquisition Sinogram Image Process-ing (ASIPRO) and Pixelwise Modeling Software(PMOD) software. For autoradiography, brain sliceswere prepared at 10–40 lm thickness using a Leica1850 cryotome. Labeled sections were exposed tophosphor films (Perkin Elmer Multisensitive, MediumMS) and read using the Cyclone Phosphor ImagingSystem (Packard Instruments). Analysis of autoradio-graphs was done using Optiquant acquisition andanalysis software.

PET experiments

Radiolabeling

Synthesis of 18F-nifene was carried out followingreported procedures (Pichika et al., 2006). The auto-mated radiosynthesis of 18F-nifene was carried out inthe CPCU (chemistry-processing control unit) box. AnAlltech C18 column (10 lm, 250 3 10 mm2) was usedfor reverse-phase HPLC purification and specific ac-tivity of 18F-nifene was approximately 2000 Ci/mmol.

Animal handling

In preparation for scanning, rats and mice werehoused in individual cages in a climate-controlledroom (248C) with a 12:12-h light cycle. Subjects hadfree access to food and water until the day of imaging,and then were fasted in the imaging room, in a darkquiet place, for 20–24 h before experiments. Beforethe scan, animals were placed in an induction cham-ber and anesthetized with isoflurane at 4% concentra-

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tion. Animals were maintained under anesthesiathroughout the scan with 2% isoflurane delivered viaa nose-cone. Body temperature was maintained witha water-circulating heating pad.

In vivo imaging

Rats were injected with 31.5 6 5.3 MBq of 18F-nifene and scanned for 90 min in the Inveon scanner.List-mode data were histogrammed in 45 time frames(10 3 0.5 min, 15 3 1 min, 10 3 2 min, 10 3 5 min).WT and b2-KO mice were injected with 9.63 6 0.85MBq of 18F-nifene and scanned for 30 min, starting30 min post injection. Random events were subtractedbefore reconstruction. The images were reconstructedusing Fourier rebinning and two-dimensional filteredback-projection (2D FBP) method (Hanning filter andcutoff at Nyquist frequency) with an image matrix of128 3 128 3 159, resulting in a pixel size of 0.77 mmand a slice thickness of 0.796 mm. All dynamicimages were corrected for radioactive decay. Attenua-tion correction was performed using a 10-min trans-mission scan with a 57Co point source performed priorto tracer injection. Normalization of detectorresponses was also applied using a cylinder sourceinversion method.

Ex vivo imaging and autoradiography

Immediately following in vivo acquisition, animalswere sacrificed by decapitation. The brain wasexcised, placed in a dish, and frozen on a bed of dryice. The brain was then imaged for 30 min in thePET scanner. The same imaging parameters as for invivo imaging were used. Following ex vivo imagingthe brains were sectioned at 20 lm. Approximately 40sections were laid on glass slides, placed on film andleft overnight. The following day, film was exposedusing a Cyclone Phosphor Imaging System.

Image analysis

Processing of reconstructed images was performedwith PMOD software package (PMOD Technologies).PET images were normalized to the standard spacedescribed by the stereotaxic coordinates of Paxinos &Watson (Paxinos and Watson, 1986) via co-registra-tion to an MRI rat template (Schweinhardt et al.,2003). The size of the template image was 80 3 63 3108 voxels with a voxel size of 2 mm. The templateincludes a scale factor of 10 to roughly match the sizeof the human brain and facilitate analysis with SPMsoftware. Bregma was set as the origin of coordinatessystem. The spatial extent of the template volume(bounding box) was from 280 to 80 mm in X direction(left to right of the midline, through the sagittalplanes), 2120 to 6 mm in the Y direction (ventral todorsal, through the horizontal planes) and from 2156to 60 mm in the Z direction (posterior to anterior,

through the coronal planes). 3D volumes of interest(VOIs) were drawn on the MR template for thalamus(TH), striatum (STR), frontal cortex (FC), subiculum(SUB), temporal subcortical white matter (TSW), andcerebellum (CB). The placing of the VOIs was guidedby examination of the Paxinos & Watson rat atlas(4th edition). The VOI over TH (11.1 mm3) was a pro-late ellipsoid with the center at (x, y, z) 5 (0.0, 260.4,32.0) mm, a long axis of 53 mm in X direction, and ashort axis of 20 mm. VOI on STR consisted of a seriesof elliptical 2D regions placed bilaterally and symmet-rically with respect to the midline on multiple hori-zontal planes with the center of mass at (614, 238,270) mm (right\left STR, 5 mm3). The VOIs on FCconsisted of irregular 2D regions placed on multiplecoronal planes, with the centers of mass at (613.4,242.5, 34) mm (right\left FC, 3.2 mm3), (647, 249,230.9) mm (right\left TSW, 0.1 mm3), (646.9, 252.7,268.5) mm (right\left SUB, 5 mm3). The left andright VOIs on STR, FC, SUB, and TSW were com-bined into single VOIs for each structure. The CBVOI (7.6 mm3) consisted of a prolate ellipsoid cen-tered at (20.5, 246.5, 2106.0) mm with a long axis of3.6 mm and a short axis of 2 mm.

The dynamic PET images were first summed andthe sum image was resliced using the Fusion toolboxof PMOD to match the size of the template. All sumimages were subjected to an initial spatial transfor-mation consisting of a scale factor (zoom) of 10 and arotation of 1808 around the z axis so that the orienta-tion of the brain to roughly match the orientation ofthe MR brain template. Through subsequent rigidtransformations (translations and rotations) appliedto each sum image the brain was co-registered tomatch the template and therefore the Paxinos atlas.The resulting transformation matrix for each subjectwas subsequently applied to all the images in thedynamic series. Time activity curves (TACs) wereextracted for each VOI from the dynamic PET data.

The ex vivo images were also rescaled to match thetemplate. However, due to the resulting decompres-sion following the excision of the brain from the skullit was not possible to co-register the images to thetemplate using a simple rigid transformation. How-ever, the ex vivo PET images were manually co-regis-tered to each other and unique VOIs were drawn onTH, STR, FC, SUB, TSW, and CB. The same regionswere also identified and drawn on the autoradio-graphic images, along with auditory cortex (AC) andauditory thalamus (medial geniculate, MG) identifiedfrom unstained tissue sections.

Mouse in vivo PET images also were co-registeredto an MRI brain template (Ma et al., 2005) of size 1923 96 3 256 voxels with a voxel size of 2 mm, whichwas preliminarily scaled by a factor of 20. VOIs repre-senting TH and CB were manually drawn on the MRtemplate and copied to PET images.

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Kinetic analysis of rat in vivo PET studies was per-formed using kinetic analysis toolbox in PMOD. Dis-tribution volume ratio (DVR) in each selected brainregion was calculated for using Logan non-invasivemethod (LNI) (Logan et al., 1996). Binding potential(BPND) was calculated as ‘‘DVR-1.’’ Cerebellum wasused as a reference region since it is known not to beenriched with a4b2* nAChRs. LNI method requiresprior estimation of the blood-tissue tracer transferrate in the cerebellum, k’2, which was computed indi-rectly from fitting the simplified reference tissuemodel (SRTM) (Lammertsma and Hume, 1996) to theTH curve using a Marquandt optimization algorithmwith 200 iterations. The estimated k’2 for each subjectwas then fixed and used subsequently for Logan anal-ysis of all other brain regions. The cutoff of Loganplot was determined based on a preset error of 10%between the fit and the data.

In ex vivo analysis and autoradiography, 18F-nifenebinding was quantified as ratios between activity inthe target region and that in the cerebellum.

Behavior experiments

Animals

Adult, male Sprague–Dawley rats (300–350 g,Charles River Laboratories; Wilmington, MA) werehoused in individual cages in a temperature con-trolled (228C) vivarium and maintained on a 12/12 hlight/dark cycle (lights on at 7:00 a.m.) with ad libi-tum access to food and water. Animals were handledfor 2–3 days before an adaptation session of 30 minfree exploration in a shuttle box training apparatus.

Training apparatus and tone generation

Training was conducted in a shuttle box (modifiedfrom H10-11R-SC Coulbourn Instruments, Allentown,PA) contained within a sound-attenuating enclosure(H10-24A, Coulbourn). The shuttle box consisted ofan alley-way contained by clear acrylic walls (51.0cm long, 10.5 cm wide, and 8.0 cm high) illuminatedby two house lights (H11-01R, Coulbourn), and a cen-trally-located overhead speaker for presentation oftones (H12-01R, Coulbourn). The floor was an electri-fied grid that could deliver 8-pole scrambled footshock (60 Hz, 0.7 mA; H13-15, Coulbourn) to eitherhalf of the shuttle box. Acoustic stimuli were 8.0kHz tones (65 dB SPL, rise/fall time 5 ms, calibratedfor animal head height throughout the alley), pre-sented at the rate of 2.5 Hz (310 ms on alternatingwith 90 ms of silence) for 10 s, generated by Tucker-Davis Technologies (TDT) System 3 (RP2.1 Real-Time Processor) and RPvdsEx software. Tone andshock presentation, and behavioral responses werecontrolled and recorded with Coulbourn GraphicState software.

Training protocol

Prior to training with tones, animals were shapedto escape shock (e.g., Liang et al, 2008). The goal ofshaping was to promote running to the opposite sideof the shuttlebox to minimize receipt of shock, whichwas escaped upon crossing the midline. The shockwas administered only when animals faced the oppo-site side. These shock-only trials were given on aver-age at intervals of 60 6 20 s. Shaping trials werepresented until the animal learned to orient to theopposite side of the shuttle box, cross the midlinewhen shocked and re-orient to face the other side inpreparation for the next trial (maximum crossinglatency, <60 s).

The first auditory-cued avoidance training sessionbegan immediately after escape training and con-sisted of 30 trials per daily session (inter-trialintervals, 60 6 20 s). Each trial consisted of tone pre-sentation that signaled forthcoming shock (toneonset-to-shock interval, 10 s). An avoidance responsewas defined as a midline crossing during the 10 stone-shock interval, before the presentation of shock.Escape responses were crossings made after the 10 stone-shock interval, during shock presentation. Tonepresentation ceased at the moment of midline cross-ing. Crossings during the silent inter-trial intervalshad no effect. Performance was measured as the per-centage of avoidance responses during a session, i.e.,(number of trials with avoidance responses/number oftrials) 3 100%. Initial avoidance training was for 14consecutive days. To confirm performance beforeimaging, short blocks of training were resumed inanimals selected for imaging for a total of 21 trainingsessions over 2–3 months. Training was continuedbeyond 14 days for two reasons. First, it assured theconsistency of ‘‘good’’ or ‘‘poor’’ avoidance behaviorprior to imaging and second, it was used to determinewhether all animals were equally capable of learning,if only to some low level of performance, and wouldexhibit the expected learning effect of memory consol-idation (i.e., an increase in performance after a reten-tion period without continued training). Consolidationwas calculated as the change in each animal’sperformance after 2 weeks without training betweensessions 14 and 15, i.e.: (percent avoidance duringsession 15 – percent avoidance during session 14).

RESULTS

We present the results in three sections. In Section1, we demonstrate the selectivity of 18F-nifene usingwild-type (WT) and transgenic (b2 knockout, b2-KO)mice, show its distribution in rat forebrain usingthree methods—in vivo PET, ex vivo PET and autora-diography—and compare 18F-nifene binding obtainedusing the three methods. The cerebellum (CB)exhibited minimal binding and served as a reference.

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Subsequent experiments were done only in the ratdue to superior spatial resolution for imaging, andwell-characterized behavior (see below). In Section 2we describe the performance of 12 rats trained on anauditory-cognitive task, i.e., auditory-cued activeavoidance. Performance on this task is impaired bylesions of auditory cortex (Delay and Rudolph, 1994;Duvel et al., 2001; Ohl et al., 1999), and enhanced bysystemic administration of nicotine (Erickson, 1971;Sansone et al., 1991, 1994a,b; Yilmaz et al., 1997).Finally, in Section 3 we present 18F-nifene bindingdata for six rats—the three best-performing and threeworst-performing animals from the cohort—to corre-late performance with binding in selected brainregions. Seven regions were selected for their rele-vance to auditory processing (auditory cortex, AC; au-ditory thalamus/medial geniculate, MG; and theintervening temporal subcortical white matter, TSW)and for known high levels of nAChRs (frontal cortex,FC; striatum, STR; subiculum, SUB; and overall thal-amus, TH).

Section 1. Imaging 18F-nifene: In vivo PET, exvivo PET, and autoradiography

PET imaging of anesthetized WT and b2-KO micewas carried out using 18F-nifene. Figures 1A–1Cincludes coronal sections of mouse MR template (Fig.1A) through TH and cortical regions. Binding of 18F-nifene in the TH of the WT was observed (Fig. 1B)while the b2-KO mouse had minimal binding (Fig.1C). Measured TH-to-CB ratios of 18F-nifene in WTwas 1.3 while that in the b2-KO was 0.92. In autora-diography, WT horizontal slices (Fig. 1D) exhibited18F-nifene binding in several brain regions consistentwith our findings in rats (see below and Easwara-moorthy et al., 2007). These regions included TH,STR, FC, SUB, and CB. In contrast, b2-KO mice (Fig.1E) showed little binding. Average TH-to-CB ratio inautoradiography tissue was 6.4 in WT and 2.1 in b2-KO mice. Using adjacent brain slices from the samemouse brains, dopamine D2/D3 receptors wereimaged in STR in both WT and b2-KO (Figs. 1F and1G) using 18F-fallypride. 18F-Fallypride imaging ofWT and b2-KO mice revealed similar binding in STR(STR/CB 5 13.7 for WT, 14.0 for b2-KO). In both indi-vidual examples and group data (Fig. 1H, n 5 2), WTmice exhibited the binding profile for 18F-nifene ofTH > SUB � STR � FC > HP � CB and for 18F-fall-ypride of STR > TH > FC > HP � CB, whereas b2-KO mice revealed 18F-fallypride binding consistentwith the WT, but had little 18F-nifene binding. 18F-Nifene binding in WT mice was greater than in b2-KO mice in all regions (paired one-tailed t-test, df 2,n 5 2, P < 0.01). Binding of 18F-fallypride in STR ofWT mice was not different from that in STR of b2-KOmice (P 5 0.45).

We then examined localization of 18F-nifene in ratusing co-registered PET images and the rat brainMRI template (Fig. 2, top row). Figure 2 (middle row)shows horizontal PET sections with 18F-nifene bind-ing measured in regions corresponding to those onthe MRI template. The fused images (Fig. 2, bottom)confirm good co-registration of major landmarks suchas FC, TH, and CB, consistent with our previouswork using an MRI template (Constantinescu et al.,2011).

Representative time-activity curves of 18F-nifeneare shown in Figure 3. Curves were generated forTH, STR, FC, SUB, TSW, and CB. TH exhibited thehighest binding followed by other brain regions con-sistent with previous findings in rat and monkey(Kant et al., 2011; Pichika et al., 2006). Note that thetime-activity curve of TSW was suggestive of signifi-cant receptor-mediated binding, similar to that of FCand SUB. Average binding potentials (BPND) variedbetween 1.97 for TH and 0.66 for STR and followedthe order TH > SUB > FC > TSW > STR (see Table I).

Following the 90-min in vivo PET scan, the brain ofeach rat was immediately excised and ex vivo PETimages were acquired. Distribution of 18F-nifene wasconsistent across animals and brain regions. Figure4A shows an example of an ex vivo PET image withmaximum binding in TH, followed by FC, STR andTSW, with little binding in CB. After the ex vivo PETscan, horizontal brain sections (20 lm) were cut forautoradiography. Brain sections (Fig. 4B) showed 18F-nifene relative binding consistent with that seen inPET images. For quantitative measurements, photo-scans of tissue sections were used to identify brainregions (Fig. 4C). Note, in Figure 4B, bilateral bind-ing of 18F-nifene in the TSW between TH and tempo-ral cortex (additional details below). The order of 18F-nifene binding among the various regions largely fol-lowed that measured in PET scans (TH > SUB > FC> TSW > STR > CB).

Quantitative analysis of 18F-nifene binding usingthe three imaging methods is shown in Table I. Foreach method, CB was used as a reference region. Theex vivo measures (PET and autoradiography) aredirect ratios while the in vivo measure is a BPND

derived from distribution volume ratios (DVR-1)obtained from the analysis of dynamic PET data. Therank order of 18F-nifene binding across brain regionsfor the three methods followed a similar profile. Iden-tification of regions of interest, particularly smallbrain regions such as the SUB and TSW, were moreaccurate in the higher-resolution autoradiographs (cf.Figs. 2 and 4). While both in vivo and ex vivo meas-urements were aided by MRI template fused images,fusion of the excised brain was more challenging dueto small changes in gross structure (e.g., caused bycompression of the excised brain), affecting quantita-tion of smaller brain regions.

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Fig. 1. 18F-Nifene and 18F-fallypride binding in WT and b2-KOmouse brains. A: Coronal slice from MR template of the mouse brain.B and C: PET images showing strong 18F-nifene binding in WTmouse (B) with little binding in b2-KO mouse (C). Color scale (left)reflects in vivo PET 18F-nifene binding. D–G: Mouse autoradiographyhorizontal slices showing 18F-nifene binding in TH and other brainregions of WT (D), whereas b2-KO (E) showed little binding. In thesame brain, as a control, 18F-fallypride binds to dopamine D2/D3

receptors similarly in WT (F) and b2-KO (G). H: Group data of 18F-nifene and 18F-fallypride binding in WT and b2-KO mouse brains (n5 2 each, multiple sections per animal); relative 18F-nifene binding inTH > SUB � STR � FC > CB � Hippocampus (HP), with little bind-ing in b2-KO. 18F-Fallypride binding was similar in WT and b2-KO.DLU/mm2, digital light units per unit area (measured in autoradio-graphic sections, D–G). [Color figure can be viewed in the onlineissue, which is available at wileyonlinelibrary.com.]

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Figure 5 shows the correlation between autoradiog-raphy and ex vivo PET (Fig. 5A) or in vivo PET (Fig.5B), after averaging data across animals (n 5 6; bind-ing in CB used to normalize values across animals).For these measures of average binding, the correla-tions between methods were high (Fig. 5A, r2 50.972, P 5 0.002; Fig. 5B, r2 5 0.935, P 5 0.007).However, binding in specific brain regions of individ-ual animals did not always correlate well among mea-surement methods, likely due to methodological limi-tations, e.g., imaging in small brain regions using ei-ther PET method (Fig. 5C, example of correlationbetween autoradiography and in vivo PET measuresfor TSW binding, r2 5 0.448, P 5 0.146; values forother pairwise comparisons with autoradiography

ranged from r2 5 0.027 for in vivo PET SUB to r2 50.953 for ex vivo PET TH). Thus, while averagingacross animals yields good agreement among meth-ods, only the highest resolution method, autoradiogra-phy, was used for comparison of 18F-nifene bindingamong individual animals (below).

Given the apparent 18F-nifene binding in TSW (Fig.4), we also compared binding in several prominentwhite matter tracts: corpus callosum, fimbria, TSWand cerebellar white matter (Fig. 6A). For the exam-ple (Fig. 6B) and group (Fig. 6E) autoradiograph datain Figure 6, binding was highest in TSW, followed byfimbria, corpus callosum (CC) and cerebellar whitematter (CBW; note, however, that spillover into thefimbria from the adjacent TH and STR probably

Fig. 2. PET imaging of 18F-nifene in rat brain. Representativehorizontal sections of a rat brain MR template (upper panel), invivo PET imaging of 18F-nifene (middle panel), and fused images(lower panel); coordinates with respect to bregma (left to right):23.6, 24.4, 25.4, and 26.0 mm. PET images were integrated over5–30 min interval, and the intensity was scaled relative to the

whole image volume (upper threshold set to 75%). VOI placementson FC, STR, SUB, TSW, and CB are shown on each panel, withlabels on MR template. VOIs for TSW and STR were placed on thehorizontal slices of the MR template. All other VOIs were placed onthe axial slices. [Color figure can be viewed in the online issue,which is available at wileyonlinelibrary.com.]

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results in an overestimation of activity). For both au-toradiography and ex vivo PET results, 18F-nifenebinding differed among white matter regions (Fig. 6E,ANOVAs, P < 0.01; post-hoc Tukey-Kramer pair-wisecomparisons indicated TSW differed from all otherregions for autoradiography, and that all regions dif-fered from each other for ex vivo PET). Nonspecificbinding was determined by autoradiography after dis-placement from nAChRs by 300 micromolar nicotine(Figs. 6C and 6D). 18F-Nifene binding in CC, fimbriaand TSW was reduced following nicotine displace-ment (Fig. 6E, one-tailed t-test, n 5 2–3, P 5 0.0001,0.0010, 0.0.0039, respectively) while binding in CBWwas not reduced (P 5 0.1378). These data indicatesignificant 18F-nifene binding in white matter, notablyTSW.

Section 2. Auditory behavior

A group of 12 male rats underwent behavioraltraining for 14 days (30 trials per day). Each wasplaced in a shuttle box where a tone signaled animpending shock (beginning 10 s after tone onset).Crossing the midline terminated the tone (if the ani-mal crossed <10 s after tone onset) or concurrenttone and shock (if the animal crossed >10 s after toneonset). With training, over half the animals (7/12)learned to avoid the shock by crossing to the othercompartment in time. The remaining animals (5/12)on most trials did not cross in time, and escaped theshock by crossing only after shock onset. Performancefor the 12 animals is shown in Figure 7 (inset). Meanavoidance performance across the 14-day block oftraining provided a criterion to designate an individ-ual subject’s learning as ‘‘good’’ (above the groupmean) or ‘‘poor’’ (below the mean). Of the 12 trainedanimals, six that represented extreme levels of good(n 5 3) and poor (n 5 3) learning were selected forsubsequent imaging; their performance is shown inFigure 7.

Fig. 3. Representative time-activity curves from an in vivo 18F-nifene PET scan are shown for TH, STR, FC, SUB, TSW, and CB.

TABLE I. Comparison of 18F-nifene binding in rat forebrain regionsusing three imaging methodsa

Brain region In vivo PETb Ex vivo PETc Autoradiographyd

TH 1.97 6 0.66 4.84 6 1.18 5.68 6 1.00SUB 1.21 6 1.06 2.38 6 0.29 2.58 6 0.38FC 1.11 6 0.33 2.34 6 0.38 1.94 6 0.27TSW 0.80 6 0.34 1.76 6 0.11 1.80 6 0.12STR 0.66 6 0.33 1.93 6 0.19 1.48 6 0.06

aMean (6SD) binding in six animals.bBPND values calculated from in vivo PET studies using CB as reference.cRatios of brain regions versus CB in summed ex vivo PET scans.dRatios for brain regions versus CB in autoradiographic sections.

Fig. 4. 18F-Nifene binding from horizontal ex vivo PET and au-toradiography images in same rat brain. A: Ex vivo PET image of arat sacrificed 60 min after initial scan and the brain excised; maxi-mum binding is in TH, lesser binding in FC, STR, and TSW, and lit-tle binding in CB. B: Autoradiograph of brain slice (40 lm) at level

corresponding to the auditory forebrain shows prominent binding inTSW bilaterally. C: Photoscan of same tissue section as B. [Colorfigure can be viewed in the online issue, which is available atwileyonlinelibrary.com.]

425FOREBRAIN NACHRS AND RELATION TO BEHAVIOR

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The three good and three poor learners exhibitedavoidance performance above 90% or below 10%,respectively, in at least one of the first five trainingsessions. Across avoidance training sessions, therewas a significant difference in performance betweengroups: [F(20, 84) 5 2.91, P < 0.0003]. All animalswere tested 2 weeks after the end of training to con-firm lasting effects (Fig. 7, Consolidation), and oncemore after a variable interval (depending on avail-ability of the scanner), immediately prior to imaging(Fig. 7, Pre-Scan). The good learners showed anincrease in avoidance performance after the 2-weekconsolidation period of 11.1 6 6.2%, which mighthave been greater but for a ceiling effect. Of particu-lar interest, the poor learners also exhibited anincrease in avoidance of 34.4 6 18.5%. Thus, theywere capable of learning the task, albeit not as wellas the good performers, and their mechanisms formemory consolidation were functional.

The difference in group performance (good vs. poorlearners) was not due to a difference in ability to

cross the midline to the safe side of the shuttlebox,since the ability to escape shock did not differbetween groups: shock levels were not different(Mann-Whitney U 5 8.0, P 5 0.40), the number ofshock escape shaping trials was not different (median6 inter-quartile range): good (8 6 3) versus poor (106 15), Mann-Whitney U 5 8.5, P 5 0.50, and the la-tency to escape shock was not different (median 6inter-quartile range): good (15.5 s 6 15.8) versus poor(28.3 s 6 34.9); Mann-Whitney U 5 13.0, P 5 0.40.Therefore, differences in avoidance performanceappear to reflect differences in learning ability in thistask, rather than differences in ability to perform theavoidance response.

Section 3. Correlation of 18F-nifene bindingwith behavior

The six best and worst learners were placed in thePET scanner and imaged for 18F-nifene bindingusing in vivo PET, ex vivo PET, and autoradiogra-phy. The imaging data is presented above (Section1), but because of the high spatial resolution andreliability of autoradiography, only it was correlatedwith behavior. The extent of 18F-nifene binding wasmeasured in the five regions described above (e.g.,Fig. 4), plus AC and MG as identified from photo-scans of autoradiography sections (e.g., Fig. 4C).Thus, the seven brain regions chosen for analysisinclude three from the auditory forebrain (AC, MG,and TSW), and four regions characterized by signifi-cant 18F-nifene binding (TH, FC, SUB, and STR).For each region, 18F-nifene binding was correlatedwith performance on the auditory-cued behavioraltask. Performance was characterized using multiplemeasures including learning rate, eventual level ofperformance after 14 days training, and subsequentperformance at the 2-week retention test (Table II).Significant correlations between the performance and18F-nifene binding are indicated in Table II (regres-sion coefficient, r, values, * P < 0.05, or ** P <0.01). Two notable brain regions are FC and TSW;for each of these regions, 18F-nifene binding corre-lates with all, or nearly all, behavioral measures.Figure 8 depicts representative scatter plots relating18F-nifene binding in each of the regions to learningrate (column 1 in Table II).

To demonstrate how 18F-nifene binding determinedafter training relates to the development of behaviorover the period of training, Figure 9 shows the corre-lation of binding in each brain region with the levelof avoidance performance on each day of training(gray shading in Fig. 9 indicates significant correla-tion). Of the seven brain regions, only TH shows sig-nificant correlations for each of the first 2 days oftraining, but the correlation decreases thereafter overthe 2 weeks. Conversely, TSW, SUB, and FC show

Fig. 5. Correlation of 18F-nifene autoradiography to ex vivo PET(A) and in vivo PET (B) measures. Each data point represents an av-erage of six animals, with CB in each animal used as a reference tonormalize binding across animals. C: Correlation of binding estimatesfrom autoradiography versus in vivo PET for TSW in six animals.

426 K.M. BIESZCZAD ET AL.

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significant correlations only on the third day or later,with FC reaching criterion only on the last day. Otherbrain regions, notably AC and MG in the auditoryforebrain, never showed significant correlation of 18F-nifene binding with performance.

The contrast in Figure 9 between TH (higher corre-lation early in training) and FC, SUB, and TSW(higher correlation later in training), suggests thepossibility that nAChRs in different brain regionscontribute to behavior during different phases oflearning. An analysis suggesting differential involve-ment of brain regions over the course of training isshown in Figure 10: pairs of regions that correlatesimilarly with behavior throughout training showpositive regressions – for example, TSW and SUBshow similarly poor correlations between 18F-nifenebinding and performance on days 1–2, and increas-ingly better correlations over the next 12 days –whereas the opposite trend (negative-slope regression)is seen when correlating TH with other regions. Thenegative regressions suggest a systematic transition

from brain networks involving TH to those involvingother regions (TSW, FC, and SUB).

DISCUSSION

We examined the distribution of 18F-nifene in behav-iorally-characterized rats, in order to relate the avail-ability of nAChRs in forebrain sub-regions to behav-ioral performance. Three imaging methods—in vivoPET, ex vivo PET and autoradiography—producedsimilar measures of relative binding of 18F-nifeneamong brain regions, and the overall distribution wasconsistent with that of a4b2* nAChRs, as was the lackof binding in b2-KO mice. An important finding wasthat 18F-nifene labeled some white matter pathways,notably the TSW containing the auditory thalamocorti-cal pathway. Finally, a comparison of 18F-nifene bind-ing with auditory-cued behavior produced four regionswith significant correlations: TSW, FC, SUB, and TH.Binding in other areas, notably AC and MG in the au-ditory forebrain, did not correlate with behavior.

Fig. 6. 18F-Nifene binding in forebrain white matter. A: Photo-scan of a 40 lm tissue section showing regions of interest: corpuscallosum (CC, 1), fimbria (2), TSW (3), and CB white matter (CBW,4). B: Same section as (A), showing 18F-nifene autoradiography. Cand D: 18F-nifene binding in the absence (C) and presence (D) of

300 micromolar nicotine to reveal nonspecific binding. E: Mean 18F-nifene binding in white matter for ex vivo PET and autoradiogra-phy (n 5 4), and nonspecific (NS) binding (n 5 2–3). [Color figurecan be viewed in the online issue, which is available at wileyonlinelibrary.com.]

427FOREBRAIN NACHRS AND RELATION TO BEHAVIOR

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18F-nifene binding in rat forebrain

The distribution of 18F-nifene in the present studyis consistent with previous results suggesting that18F-nifene binds to a4b2* nAChRs (Easwaramoorthyet al., 2007; Kant et al., 2011; Pichika et al., 2006).Lack of binding in the b2-KO mouse further supportsthis conclusion. All three methods of quantifying 18F-nifene binding—in vivo PET, ex vivo PET and autora-diography—show the same order of relative bindingamong brain subregions, supporting the utility ofeach method. However, in individual animals,between-method comparison of measurements forsome brain regions did not produce strong correla-tions. This may reflect methodological limits, espe-cially for regions with low levels of 18F-nifene binding,and is less of an issue for regions with higher levels;in TH, for example, repeated PET measurements inthe same animal vary only � 3% (Kant et al., 2011).Thus, while the finding of similar relative bindingamong brain regions is likely due to averaging acrossanimals, only the highest resolution method—autora-diography—was used for correlating binding withbehavior in individual animals.

A notable finding is that of 18F-nifene in the whitematter pathway between the dorsal thalamus andtemporal cortex, i.e., the TSW. A similar conclusionwas reached in a PET study of a4b2* nAChRs in

humans (Ding et al., 2004). In that study, as in thepresent one, weaker binding was observed in otherwhite matter pathways, such as corpus callosum.Ding et al. (2004) note that binding in white matteris not necessarily functional, but may, for example,reflect axonal transport of nAChRs. However, recentwork suggests that activation of nAChRs in the audi-tory thalamocortical pathway enhances the excitabil-ity of myelinated thalamocortical axons (Kawai et al.,2007). Moreover, microinjection of nAChR antagonistinto the pathway reduced the amplitude of sound-evoked responses in auditory cortex, suggesting thatendogenously released ACh acts at nAChRs in thepathway to enhance cortical responsiveness. Thus,ACh release upon increased arousal and attentioncould enhance sound-evoked responses in A1. Con-versely, studies of chronic nicotine exposure in smok-ers or their offspring have revealed deficits in audi-tory function and TSW structure (Fried et al., 2003;Jacobsen et al., 2007a,b; McCartney et al., 1994).These effects, both positive and negative, may involvenAChRs situated along TSW pathways.

18F-nifene and behavior: Relevance of nAChRsfor cognitive function

Significant correlations were found between behav-ioral performance and 18F-nifene binding in TSW, FC,

Fig. 7. Behavioral performance in an auditory-cued, active avoidance task over 14 days oftraining, followed by a retention test after 2 weeks, and a final test after variable delay beforePET session. Performance is shown as mean (6SEM) percentage of avoided shocks for the best-(n 5 3) and worst- (n 5 3) performing animals; inset shows data for all 12 animals tested, sepa-rately for those that learned (n 5 7) or did not (n 5 5; see text for learning criterion).

428 K.M. BIESZCZAD ET AL.

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TH and SUB. Each of these sites may contribute toperformance in the behavioral task. Given the audi-tory nature of the task, TSW binding may indicatethat activation of nAChRs in the auditory thalamo-cortical pathway could increase thalamocortical relayof acoustic information and produce stronger corticalresponses, which could underlie better performance.Such a mechanism is consistent with our previousfinding that animals with better performance (usingthe same task as in the present study) exhibit stron-ger nicotinic enhancement of tone-evoked corticalresponses (Liang et al., 2008). It is important to note,however, that the TSW includes not only thalamocort-ical axons but also corticothalamic projections. More-over, it is not clear exactly where nAChRs are situ-ated and what they regulate; while changes in axonexcitability might be expected to involve nodes ofRanvier, the dense TSW binding in some animalsseems to imply binding that extends beyond justnodes. Non-neuronal binding sites, for example onastrocytes, may also regulate neuronal function(Grybko et al., 2010; Hernandez-Morales and Garcia-Colunga, 2009). Regardless of the locus of action,behaviorally-induced regulation of TSW might con-tribute to lasting changes, such as those observed inwhite matter pathways following behavioral training(Carreiras et al., 2009; Scholz et al., 2009). Finally, itis important to note that the involvement of TSWin the present study could not have been observedwith standard electrophysiological or metabolicapproaches, underscoring the novelty and utility of18F-nifene imaging.

There was no correlation of performance with bind-ing in other auditory forebrain regions, i.e., MG andAC. This lack of correlation does not necessarilymean that nAChRs in these structures are not impor-tant for performance, but potentially that nAChRscontribute multiple functions, some of which may notbe related to performance on this task.

The measured region in the FC corresponds closelyto the medial prefrontal cortex (mPFC) (cf. VOI inFig. 2) (Paxinos and Watson, 1986), which has beenimplicated in executive control of processing in audi-tory and other sensory cortices (Hasselmo andSarter, 2011; Romanski et al., 1999), and which hasreciprocal connections with basal forebrain andbrainstem cholinergic nuclei (Uylings et al., 2003). Inparticular, mPFC is thought to regulate sensory cor-tex by way of nucleus basalis cholinergic neurons(Hasselmo and Sarter, 2011; Parikh et al., 2007).Moreover, nAChRs are known to regulate multiplethalamocortical and intrinsic circuits within themPFC (Lambe et al., 2003; Poorthuis et al., 2009),thereby contributing to its attention-related functions(Hahn et al., 2003). It is likely that some of thesecircuits contribute to the behavioral outcomesobserved in the present study.

TABLE

II.Correlation

(rvalue)

betweenbeh

avioralperform

ance

and18F-nifen

ebindingin

ratforebrain

regionsa

Rate

ofavoidance

learn

ing

Lev

elof

avoidance

perform

ance

Mea

navoidance

latency

Fastestavoidance

latency

Brain

region

Lea

rningslop

e(%

Avoidance/Session

)(sess.

1–4)

First

Trial#

ofthreeconsecu

tive

‘‘Avoided

’’sh

ocks

Asymptote

(sess.

12–14)

Con

solidation

(sess.

15)

Reten

tion

(sess.

15–18)

Asymptote

(sess.

12–14)

Reten

tion

(sess.

15–18)

Asymptote

(sess.

12–14)

Reten

tion

(sess.

15–18)

AC

0.45

0.29

0.41

0.16

0.23

0.16

0.08

0.33

0.23

MG

0.42

0.21

0.33

0.15

0.07

0.29

0.12

0.10

0.11

TH

0.07

20.66

0.69

0.36

0.40

0.22

0.38

0.40

0.40

STR

0.42

0.64

20.53

20.70

20.69

0.71

0.70

0.60

0.66

FC

0.92**

20.84*

0.82*

0.87**

0.89**

20.85*

20.91*

20.76*

0.89**

SUB

0.46

20.81**

0.88**

0.53

0.59

0.42

20.61

0.53

20.63

TSW

0.74*

20.89*

0.92**

0.79*

0.84*

20.71

20.83*

20.79*

20.82*

aData

from

sixanim

als.

*P<

0.05;

**P<

0.01.

429FOREBRAIN NACHRS AND RELATION TO BEHAVIOR

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Fig. 8. Relation between 18F-nifene binding in seven forebrain subregions and of initiallearning rate for the three best- and three worst-performing animals. Autoradiographic bindingwas determined after all testing was completed, and was correlated with initial rate of learning(Table II, column 1), as an example of the analyses presented in Table II. Regression coefficient,R; *P < 0.05, or **P < 0.01.

430 K.M. BIESZCZAD ET AL.

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Fig. 9. Correlation of behavioral performance on each day of training with 18F-nifene bind-ing in forebrain subregions determined after all testing was completed. Data are for the threebest- and three worst-performing animals (see top left for example, TSW binding versus per-formance on training days 1 and 14; autoradiography ratio is binding relative to CB in thesame animal). For each forebrain region, regression coefficients are plotted for each day; dashedline indicates threshold for significance (P 5 0.05).

431FOREBRAIN NACHRS AND RELATION TO BEHAVIOR

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Two other regions, TH and SUB, also were impli-cated in nicotinic regulation of behavior. The implica-tion of SUB is consistent with its role in nicotinicregulation of information flow through the hippocam-pal-entorhinal complex, a critical locus for cognitivefunction (O’Mara, 2005; Perry et al., 2002; Tu et al.,2009). SUB also is an interface with PFC and brainreward centers such as nucleus accumbens (Cooperet al., 2006). Alone of all measured brain regions, THbinding correlated well with performance on the firsttwo days of training, but the correlation declined overthe remaining period of training even as it increasedfor other regions (TSW, FC, and SUB). This resultsuggests that nicotinic regulation of TH is most im-portant early in training, and that there is a system-atic progression, as training continues, to nicotinicregulation in other brain regions. This progressionresembles a similar transition over time of memory-related substrates from hippocampus to cerebral cor-tex in other tasks (Bontempi et al., 1999). The currentfindings support a transition from TH to TSW, FC,

and SUB for improved levels of performance over thecourse of training, and also regional specificity of nic-otinic regulation in these latter areas to supportlearning-related behaviors like the rate of acquisitionand successful memory retention.

These results support the use of 18F-nifene forrelating nAChRs to behavior, and potentially fortracking the dynamics of brain networks duringlearning acquisition and memory consolidation. Theuse of PET, in particular, raises the possibility ofassessing nAChR availability repeatedly across train-ing, for example, to examine whether better perform-ance is the result of, or results from, increasednAChR availability. Our findings support the feasibil-ity of before-and-after PET imaging, especially inlarger brain regions and larger brains. Notably, giventhe advantages of 18F-nifene over radioligands cur-rently used for human PET studies (i.e., significantlyshorter scan times), future investigations could exam-ine this important issue in humans. Overall, our find-ings suggest that individual performance is linked to

Fig. 10. Potential cooperativity among brain regions during learning. Regression data inFigure 9 were correlated among pairs of brain regions, with significant correlations shownhere. Negative correlations suggest a systematic transition from brain networks involving nico-tinic regulation of TH to those involving TSW, FC, and SUB.

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nicotinic functions in specific brain regions, and fur-ther support a role for nAChRs in sensory-cognitivefunction.

ACKNOWLEDGMENTS

The authors thank Robert Coleman, Dr. Min-LiangPan and Jemmy Chen for technical assistance, andDr. Marina Picciotto for providing breeding stock forb2 knock-out mice.

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