Classical eyeblink conditioning: Clinical models and applications

Classical Eyeblink Conditioning: Clinical Models and Applications

JOSEPH E. STEINMETZ, Jo ANNE TRACY AND JOHN T. GREEN

Department of Psychology Indiana University Bloomington, IN

Abstract--In this paper, we argue that the main reason that classical eyeblink conditioning has proven so useful when applied to clinical situations, is that a great deal of information is known about the behavioral and neural correlates of this form of associative learning. Presented here is a summary of three lines of research that have used classical eyeblink conditioning to study three different clinical conditions; autism, fetal alcohol syndrome, and obsessive-compulsive disorder. While seemingly very different clinical conditions, classical eyeblink conditioning has proven very useful for advancing our understanding of these clinical pathologies and the neural conditions that may underlie them.

Introduct ion

FOR ALMOST 40 YEARS, classical eyeblink conditioning has been a favorite paradigm for studying behavioral correlates of simple associative learning in non-human mammals. In this paradigm, a conditioned stimulus (the CS) is presented before an unconditioned stimulus (the US) on a number of discrete trials. Typically, tones, lights or tactile stimuli, which do not elicit overt movements before training, are used as CSs, while air puffs and eye shocks, which elicit well-defined eye blinks (the unconditioned response, UR) when presented, are used as USs. After a number of paired CS-US presentations, an eye blink conditioned response (CR) that is very similar to that caused by US presentation is elicited by the presentation of the CS. Subsequent repeated CS-alone presentations result in CR extinction, or loss of the CS-elicited eye blink. Thanks in large part to the effort of a number of researchers, much is known about this type of Pavlovian conditioning (e.g., Brandon, Betts, & Wagner, 1994; Gormezano & Kehoe, 1981; Gormezano, Kehoe, & Marshall, 1983; Gormezano, Schneiderman, Deaux, & Fuentes, 1962). For example, optimal training conditions have been determined and the effects of varying key parameters such as interstimulus interval length, intertrial interval timing, CS and US intensity effects, response timing, and transfer-of-training phenomena have been widely researched and delineated (e.g., Gormezano, Kehoe, & Marshall, 1983; Grevert & Moore, 1970; Kehoe & Napier, 1991).

Perhaps the most attractive feature of using classical eyeblink conditioning as a model for simple associative learning is that it has proven extremely useful for studies designed to explore the neural correlates of learning and memory. Arguably, we know more about how the brain encodes classical eyeblink conditioning than any other behavioral paradigm or

Address correspondence to: Joseph E. Steinmetz, Ph.D., Department of Psychology, Indiana University, 1101 E.

10 th Street, Bloomington, IN 47405. Phone: (812) 855-3991 Fax: (812) 855-4691. e-mail: steinmet@ indiana.edu

Integrative Physiological and Behavioral Science, July-August 2001, Vol. 36, No. 3,220-238.

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procedure that is available. Studies have revealed that the basic neuronal plasticity responsible for generating the conditioned eyeblink response occurs in specific regions of the cerebellum (see Steinmetz, 2000 for review). Other brain regions, such as the brain stem, hippocampus, and neostriatum, modulate activity generated in the cerebellum to provide the variations in responding that occur when parameters are manipulated or when variations of the basic excitatory conditioning process are undertaken (e.g., latent inhibition, blocking, conditioned inhibition, etc)(e.g., Solomon & Moore, 1975).

Why has classical eyeblink conditioning proven so useful for the analysis of the neural correlates of associative learning? Most likely, the answer to this question lies in the nature of the behavioral procedure. First, in this type of Pavlovian conditioning, the experimenter controls when the conditioning stimuli are presented and thus knows precisely when stimulus events occur. And, with knowledge of when the CS and US will be presented, the experimenter knows when the CR should occur. In this manner, stimulus-related activation of the brain can be separated from response-related activation. Second, it is relatively easy to separate learning effects from performance effects that result from manipulations of the brain, such as those induced by brain lesions: Both the conditioned and unconditioned responses can be measured independently on US- and CS-alone trials. Manipulations that affect both types of responses are likely to be performance, not learning, effects. Third, because the researcher and not the organism controls when trials are presented, the time period during which behavior and neural activation has to be studied is greatly reduced. This discrete, relatively short sampling period proved especially advantageous before high- speed, high-storage-capacity computers were available to collect behavioral and neural data. Lastly, and perhaps most importantly, because of the very large number of behavioral studies that have been conducted with this paradigm, we know precisely the behavioral result we should get when variables are systematically manipulated. This has made it somewhat easier to make predictions concerning changes in neural activation that are produced by or that underlie the behavioral change.

Recently, there has been a renewed interest in using classical eyeblink conditioning to study human behavior and cognitive processing (see Woodrnff-Pak & Steinmetz, 2000a, for several recent book chapters on human eyeblink conditioning). We use the word "renewed" here because prior to 1960, most classical eyeblink conditioning research that was conducted used humans as subjects (see Appendix A in Woodruff-Pak & Steinmetz, 2000a, for a bibliography of human eyelid conditioning studies). The human studies were abandoned in favor of the animal model for several reasons that included difficulties in response measurement and definition, difficulties in separating "cognitive" features of the procedure from "behavioral" features, and difficulties with a relative dependency of the results on instructions that were given to the subjects.

Why is there a renewed interest in studying eyeblink conditioning in humans? There may be several answers to this question. First, once thought to be a weakness, the simplic- ity of the procedure is now viewed as one of its strengths. Unlike more complicated cognitive tasks, eyeblink conditioning is relatively straightforward and well-defined and instead of inferring process from an indirect measurement thought to reflect cognitive processing, behavior is directly assessed. Second, some investigators have realized that the paradigm provides a powerful tool for studying the effects of factors such as arousal, awareness and emotions on learning and memory (e.g., Clark & Squire, 1998, 2000). Third, studies that have compared eyeblink conditioning in humans versus other mammalian species have demonstrated a close correspondence in conditioning thus suggesting that the basic neural mechanisms that underlie eyeblink conditioning are conserved across

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species. Fourth, and perhaps most important, because we now know a lot about how the mammalian brain encodes this kind of associative learning, there is a growing interest in using this paradigm to investigate human brain function and related clinical issues. This last point is the focus of this paper.

Presented here are data and discussion concerning three clinical applications of classical eyeblink conditioning; its use in studying autism, fetal alcohol syndrome, and obsessive- compulsive disorder. As revealed below, the uses of classical eyeblink conditioning to study these seemingly unrelated clinical conditions were motivated by different reasons. Nonetheless, the results are clear: We have advanced our understanding of specific features of the three disorders by using this behavioral paradigm.

Using Classical Eycblink Conditioning to Study Autism

What is Autism?

Autism is a relatively well-known developmental disorder that is characterized by se- vere impairments in communication and social relating, often accompanied by ritualistic and repetitive patterns of behavior (American Psychiatric Association, 1994). A growing body of literature that began to appear in the 1980s raised the possibility that the cerebellum and related brainstem areas may be pathological in at least a subset of persons with autism. Specifically, histoanatomical and brain imaging studies have shown hypoplasia of the posterior cerebellar vermis and hemispheres and an age-related variation of cell number present in the deep cerebellar nuclei (e.g., Bauman, 1991; Bauman & Kemper, 1985; Courchesne, 1987, 1991). More recent data have also shown critical period-dependent medullary pathologies that could impact cerebellar development and function (e.g., Rodier, Bryson & Welch, 1997). These data together suggested that cerebellum function may be abnormal in persons with autism.

Why Use Eyeblink Conditioning to Study Autism?

Since the early 1980s, another body of research has demonstrated that the cerebellum (cortical hemispheres and deep nuclei) are critically involved in classical eyeblink conditioning (see Steinmetz, 2000 for review as well as Woodruff-Pak & Steinmetz, 2000b, for several chapters on the involvement of the cerebellum in eyeblink conditioning). For example, cerebellar lesions placed in rabbits or rats before training prevented acquisition of eyeblink CRs (e.g., Sears & Steinmetz, 1990) while lesions placed after training totally abolished previously learned CRs (e.g., McCormick & Thompson, 1984). Similarly, humans with cerebellar damage were unable to learn the eyeblink CR (Daum, Schugens, Ackermann, Lutzenberger, Dichgans, & Birbaumer, 1993). Recording data also support the idea that the cerebellum is involved in eyeblink conditioning. Changes in neuronal spiking patterns can be seen in the cerebellar cortex and the deep cerebellar nuclei as CS- US associations take place and CRs are formed. This activity completely predicts the behavioral response and is thought to be responsible for driving brain stem motor neurons responsible for CR execution (e.g., Berthier & Moore, 1986, 1990; Gould & Steinmetz, 1996; Katz & Steinmetz, 1997).

Lonnie Sears, a graduate student at Indiana University in the late 1980s and early 1990s, made a very simple, but important, prediction that became the focus of his doctoral thesis. He predicted that given the prevalence of cerebellar pathology in persons with autism and

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given the critical dependency of classical eyeblink conditioning on cerebellar function, we would see a disruption of eyebtink conditioning if we attempted to train subjects in this procedure. He designed an experiment to test this rather straightforward prediction, an experiment that revealed that he was at least partially correct (Sears, Finn, & Steinmetz, 1994; Sears & Steinmetz, 2000).

Classical Eyeblink Conditioning in Persons with Autism

For this study, we recruited 11 persons with autism who ranged in age from seven to twenty-two. The subjects were not medicated, had no other known medical conditions (including fragile-X syndrome), and had IQs appropriate for their age. Eleven control subjects, matched on age, gender and 1Q, were also recruited and used in the experiment. The autistic and control subjects were given classical eyeblink conditioning training on two separate sessions. CS-alone extinction training was given during the second halt of the second session. The CS was a 400 msec, 1 kHz, 70 dB tone that co-terminated with a 50 msec, 5 psi air puff directed toward the cornea of the eye. Eyeblinks were measured as corneoretinal potentials and CRs were defined as those eyeblinks that occurred 80-350 msec after CS presentation. A variety of measures were recorded and calculated including percent CRs, CR amplitude, onset latency of the CR, latency to the peak of the CR, and UR amplitude (measured on US-alone trials that were presented throughout training).

Initially, we were somewhat surprised by the results we obtained: The autistic group actually showed a facilitation of learning relative to the control subjects (see Figure 1); we expected that they would perform more poorly given their likely cerebellar damage. We did note that extinction appeared to occur more rapidly in the autistic group but that after initial decrements in responding, the rates of extinction were similar in the two groups, The amplitudes of the URs recorded in the two groups were nearly identical suggesting no facilitation (or deficits, for that matter) in response performance for the autistic group. Analysis of response timing characteristics, however, revealed a systematic deficit in the autistic subjects--the onset latencies and peak latencies of the CRs were shifted forward in time (i.e., they occurred earlier than in control subjects). The persons with autism began their eyeblink CRs early and showed maximum eye closure well before the presentation of the air puff US. Thus, unlike the pattern of CR execution seen in control subjects, where maximum eye closure occurs at the same time the air puff is presented, the CRs of the persons with autism were significantly mistimed. Furthermore, there was a definite age- related trend in the autistic data: Facilitated conditioning and mistimed responses were more prevalent in younger subjects than in the older subjects.

Why do Persons with Autism Show Aberrant Classical Eyeblink Conditioning?

We have hypothesized that the facilitated learning and mistimed CRs seen in the persons with autism were due at least in part to cerebellar pathologies that may have been present in these individuals. Cerebellar cortex inhibits those regions of the deep cerebellar nuclei to which it projects. Assuming that persons with autism have a somewhat normal number of neurons in the deep nuclei, but a reduced number of neurons in the cerebellar cortex, it is likely that the nucleus is in a state of relative hyperexcitation due to a lack of inhibition from the Purkinje cells in the cerebellar cortex, Because plasticity underlying eyeblink conditioning occurs in the deep nuclei, we reasoned that it is possible that the facilitation of learning is due to the existence of this above-normal level of excitation in


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Blocks of Training FIG. 1. Acquisition of classically conditioned eyeblink responses in persons with autism (open squares) and

age- and gender-matched control subjects (filled squares). Shown here are 18 blocks of training (10 trials per block). Blocks 1-10 were delivered in Session 1 while Blocks 11-18 were delivered in Session 2. On Blocks 1, 11, and 12, no paired trials were delivered, but rather these blocks contained only US-alone presentations. Note the facilitated rate of learning seen in the autistic group, Adapted from Sears, Finn, & Steinmetz, 1994.

the nuclei. Likewise, it appears that CR timing is at least in part dependent on cerebellar cortical activation (Perrett, Ruiz & Mauk, 1993). Deficits in CR timing may therefore be caused by the reduced number of cerebellar cortical neurons present in conjunction with the relatively more excitable deep cerebellar nuclei. Alternatively, or perhaps in addition, it is possible that the aberrant pattern of conditioning seen in the autistic group is due to general hyperexcitability of other brain stem areas (including auditory structures) or pathologies in other brain areas known to modulate conditioning (e.g., the hippocampus and neostriatum). These ideas are testable through behavioral experiments designed to manipu- late stimulus parameters and temporal features of eyeblink conditioning.

The eyeblink conditioning data from autistics described here illustrate one way in which eyeblink conditioning has been effectively used to study a clinical problem. The predictions made in this study were based on solid existing knowledge of the behavior under study as well as a relatively thorough knowledge of the neural substrates of that behavior. Because a great deal of information was known about the behavioral paradigm and the basic neurology that underlies the learning and memory of this simple form of associative learning, rather precise hypotheses could be advanced concerning conditioning in this population and the functional integrity of the brain circuits known to be involved in eyeblink conditioning (i.e., the brain stem and cerebellum). Future studies will explore further these brain-behavior correlates in hopes of shedding additional light on the disorder.


Using Classical Eyeblink Conditioning to Study Fetal Alcohol Syndrome

What is Fetal Alcohol Syndrome?

Prenatal alcohol exposure can produce any or all of a number of both physiological and behavioral effects in children, the combination of which is known as fetal alcohol syndrome (FAS). Physiological effects produced by prenatal alcohol exposure include central nervous system damage, growth deficits, and facial abnormalities (see Roebuck, Mattson, & Riley, 1998, for a review). Behavioral effects include decreased IQ, hyperactivity and attentional deficits, impairments in learning and memory, and disruptions in motor development and motor skills (see Mattson & Riley, 1998; Streissguth & O'Malley, 2000, for reviews).

Physiological effects appear to depend on when during pregnancy alcohol exposure occurs (Guerri, 1998). Exposure during the first trimester is associated with facial dysmorphology and alterations in proliferation of neuronal precursor cells. Exposure during the second trimester is associated with abnormalities in the proliferation, generation, and migration of neurons in several brain areas, particularly neocortex and hippocampus. Exposure during the third trimester is associated with a number of abnormalities, including proliferation, generation, and migration of cerebellar Purkinje and granule cells, and behavioral dysfunctions. In particular, cells that are relatively vulnerable to hypoxia, such as hippocampal pyramidal cells and cerebellar Purkinje cells, also appear to be particularly vulnerable to the teratogenic effects of alcohol (Guerri, 1998; Hannigan, 1996).

Behavioral deficits are many and varied after prenatal exposure to alcohol. Streissguth and colleagues have studied the development of children of mothers who consumed alcohol during pregnancy (Streissguth, Bookstein, & Barr, 1996). Deficits in habituation and arousal were apparent immediately after birth. At four years of age, a three-fold relative risk of an IQ below 85 was found in children prenatally exposed to alcohol. Problems with arithmetic performance emerged at seven years of age and were still apparent at 14 years. In addition, deficits in attention were found in older children. Streissguth and colleagues concluded that the most prominent effects of prenatal alcohol exposure were in behaviors related to central nervous system function, rather than growth or facial abnormalities (Streissguth, Bookstein, & Barr, 1996).

An Animal Model of Fetal Alcohol Syndrome

Animal models of a clinical syndrome allow experimental manipulation of putative causal factors in order to determine which factors lead to which outcomes. In the case of FAS, development of a model system in the rat over the past twenty years has led to definitive evidence that the two most important causal factors in producing brain damage in FAS are the level of blood alcohol concentration produced and the period of brain development in which alcohol exposure occurs. High blood alcohol concentrations in the third trimester of pregnancy appear to produce the most widespread brain damage. This has been demonstrated through use of a rat model of FAS, which allows precise control of the blood alcohol concentration produced as well as the timing of exposure. It is important to note that blood alcohol concentration, rather than alcohol dose, and stage of brain development, rather than chronological age, are used in comparing data generated in the rat model to human FAS (Goodlett & Johnson, 1999). This allows equating of species differences in pharmokinetic profiles and in the rate at which various brain areas undergo


maturation. For example, cerebellar development occurs in humans during the third trimester of pregnancy but largely in the first two weeks after birth in rats.

Studies using the rat model of FAS have found that both the hippocampus and the cerebellum are profoundly impacted by alcohol during brain development. We will con- centrate on the cerebellum here, due to its role as the critical neural substrate across procedures in classical eyeblink conditioning (see above). Over the past decade, cell counting studies have revealed that cerebellar Purkinje cells are severely reduced when blood alcohol concentrations above 200 mg/dl are produced in rat pups (Bonthius and West, 1990, 1991; Hamre and West, 1993). Although Purkinje cells are differentiating during the neonatal period in the rat, they are generated prenatally, and some studies have reported Purkinje cell loss after prenatal exposure to alcohol. However, a direct comparison of prenatal and postnatal alcohol exposure demonstrated that only postnatal exposure produced profound Purkinje cell loss (Marcussen, Goodlett, Mahoney, & West, 1994). Spe- cifically, alcohol exposure on gestational days 13-18 (rats are typically born on gestational day 22) via oral intubation of dams produced no deficits in Purkinje cell number. In contrast, alcohol exposure on postnatal days 4-9 replicated previous studies in showing a reduction in Purkinje cells. Thus, it appears that Purkinje cells are particularly susceptible to the effects of alcohol during differentiation, rather than during neurogenesis.

Recent studies have made use of an unbiased stereological approach to assess Purkinje cell numbers. This technique avoids sampling bias by using systematic random sampling of the entire structure of interest. The first study to use unbiased stereology to examine cerebellar cell loss following alcohol-exposure in neonatal rats replicated the treatment procedure of Bonthius and West ( 1991) to examine long-term effects of alcohol exposure on total numbers of Purkinje and granule cells in neonatal rats (Napper & West, 1995a). However, in contrast to Bonthius and West (1991), there were also reductions in both cell populations with very low (34 mg/dl) blood alcohol concentrations. It is important to note that this study examined only the floccular-parafloccular region of the cerebellum, rather than the entire cerebellum. Thus, the difference in results may have been due to either the use of a more sensitive cell counting technique, which allowed an estimation of total cell population, or the results may only apply to the floccular-parafloccular region of the cerebellum.

Other studies using unbiased stereological cell counting of the entire cerebellum have provided evidence that Purkinje cells are lost when high blood alcohol concentrations are produced (Goodlett & Eilers, 1997; Goodlett, Pearlman, Lundahl, & Pearlman, 1997; Goodlett, Pearlman, & Lundahl, 1998; Pauli, Wilce, & Bedi, 1995). The period of greatest vulnerability of Purkinje cells to alcohol-induced death appears to be around postnatal days 4-5 in the rat (Goodlett & Eilers, 1997). Both alcohol exposure via artificial rearing (Goodlett & Eilers, 1997) and alcohol exposure via intragastric intubation (Goodlett et al., 1997) produce comparable results. With increasing blood alcohol concentrations, there is greater Purkinje cell loss (Goodlett, Pearlman, & Lundahl, 1998). Additionally, the inferior olive, which sends afferent fibers to Purkinje cells, also sustains cell loss after neonatal alcohol exposure (Napper & West, 1995b). The loss of inferior olive cells appears to make an impact on cellular activity in Purkinje cells. A decrease in spontaneous complex spikes (which are generated by inferior olive input) has been observed in Purkinje cells following neonatal alcohol exposure (Backman, West, Mahoney, & Palmer, 1998).

Neonatal alcohol exposure in rats has a fairly dramatic impact on behavioral tasks believed to engage the cerebellum. Two motor learning tasks have been the most heavily studied. In the parallel rod task, two horizontal rods are set a few centimeters apart and the

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rat is required to traverse them. After several successful traversals, the width between the rods is increased, until the rat can no longer make a successful traversal. Rats exposed to alcohol as neonates are impaired on this task (Goodlett & Lundahl, 1996; Meyer, Kotch, & Riley, 1990; Thomas, Wasserman, West, & Goodlett, 1996). There is a significant correlation between the maximum width that can be successfully traversed and the number of Purkinje cells present (Thomas, Goodlett, & West, 1998). The second motor learning task is the rotating rod task. In the rotating rod task, the rat is placed on a stationary rod, which is then set in motion. Several different rotation speeds are tested and the time that the rat remains on the rod is recorded. The rotating rod task is also impaired by neonatal exposure to alcohol (Goodlett, Thomas, & West, 1991).

The problem with the parallel bar and rotating rod tasks is that the precise neural substrates of these tasks are unknown. It is assumed that they require an intact cerebellum for successful performance and therefore that Purkinje cells are necessary. Exactly which areas of cerebellum are engaged and exactly how Purkinje cells are utilized is not known. In contrast, the precise areas of the cerebellum engaged in classical eyeblink conditioning are known in detail. Thus, we reasoned that use of the classical eyeblink conditioning procedure would be ideal for exploring the functionality of the cerebellum in rats exposed to ethanol.

Classical Eyeblink Conditioning in Rats"

Although the rabbit has been used most extensively for nonhuman eyeblink conditioning studies, use of the rat (Biel & Wickens, 1941; Hughes & Schlosberg, 1938) actually predates that of the rabbit (Gormezano, Schneiderman, Deaux, & Fuentes, 1962). Rats were used initially because they had already been studied extensively in laboratory tasks. However, early studies of eyeblink conditioning using restrained rats had difficulty in delivering USs and measuring eye blinks. Subsequent researchers favored conditioning of the nictitating membrane response in rabbits, rather than the eyeblink response in rats. The nictitating membrane response in the rabbit had the advantages of being both easier to measure and a more discrete response. In addition, the rabbit is significantly more tolerant of restraint and rarely emits spontaneous blinks. Thus, with the exception of a study by Hall (1973) and a brief report by Lovick and Zbrozyna (1975), there were no further studies of eyeblink conditioning in rats in the literature until the late 1980s. Beginning at that time and continuing to the present, there has been a growing interest in eyeblink conditioning in rats.

A procedure introduced by Skelton (1988) has become the standard for most laborato- ries investigating eyeblink conditioning in rats (although a few studies still use restrained rats, e.g., Schmajuk & Christiansen, 1990). Skelton was able to condition freely moving rats by cementing a headstage to the skull which carried leads from the eye muscles for delivering a periorbital shock US and recording an EMG response. The rat is plugged into a commutator, which carries the leads out to equipment used to deliver stimuli and record responses. With this procedure, robust eyeblink conditioning was obtained using a 280-ms delay procedure, with a criterion of 9 CRs in 10 consecutive trials met in an average of 139 trials. More recently, studies have also demonstrated trace conditioning in freely moving rats (Beylin & Shors, 1998; Weiss et al., 1999), with a 250-ms trace period appearing to be optimal for robust learning (Weiss et al., 1999).

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extinction training for rats given either alcohol or sham intubations early in development then tested as adults (see text for details). Note the relatively poor learning seen in the alcohol-exposed rats relative to the two control groups. Adapted from Green et al., 2000.

Combining the Rat Model of FAS with Eyeblink Conditioning

Two studies have examined the effects of early exposure to alcohol on subsequent acquisition of eyeblink conditioning. In the first study, two separate groups of artificially- reared rats received infusions through a surgically implanted gastric tube of either 5.25 g/ kg/day of alcohol in milk formula (which produced an average peak blood alcohol concentration of 331 mg/dl) or calorically-matched milk formula without alcohol on postnatal days 4-9 (Stanton & Goodlett, 1998). A third group was reared normally. On postnatal days 23 and 24, these rats received three sessions of 100 paired trials each (with approximately five hours between sessions) of eyeblink conditioning in a 280-ms delay procedure using a tone CS and a periorbital shock US. Results showed that rats exposed to alcohol were significantly impaired in learning compared to the two control groups. In contrast, there was no difference between groups in startle respones (i.e., responses within 80-ms of tone onset) to the tone CS, suggesting that differences in acquisition were not due to an inability to perceive the tone in the alcohol-exposed group.

We conducted a follow-up study to examine the long-term consequences of early exposure to alcohol on eyeblink conditioning (Green, Rogers, Goodlett, & Steinmetz, 2000). In


this study, we used an intragastric intubation procedure to infuse 5.25 g/kg/day of alcohol (which produced an average peak blood alcohol concentration of 363 mg/dl) in milk formula or milk formula alone on postnatal days 4-9 in two separate groups of rats. Again, a third group of rats was untreated, and all rats were reared by the dam, rather than artificially. Beginning at approximately 5-6 months old, rats were trained in either the 350-ms delay procedure or received unpaired stimuli. A tone again served as CS and a periorbital shock as US and rats received either 100 trials (90 paired and the CS presented alone on every tenth trial) per day (paired group) or 100 CS-alone and 90 US-alone trials per day (unpaired group). Following 10 days of training, all rats underwent four days of extinction in which they received 100 CS-alone trials per day. The results indicated that the deficits in acquisition of eyeblink conditioning produced by neonatal alcohol exposure persist into adulthood (see Figure 2). Furthermore, these deficits are associative in nature, as we found no differences between unpaired groups. There was some suggestion of abnormal timing of CRs in the alcohol-exposed group. In particular, the onset-to-peak latency of CRs was significantly shorter in the alcohol-exposed group.

Given the evidence that eyeblink conditioning requires the cerebellum and that cerebellar Purkinje and granule cells are lost after early exposure to alcohol, we hypothesized that the deficits in acquisition of eyeblink conditioning in rats exposed to alcohol as neonates were caused by cerebellar (and possibly brainstem) damage. We chose the interpositus nucleus as the first area to examine for abnormalities. Purkinje cells normally inhibit the deep nuclei. Several models of eyeblink conditioning suggest that regulation of interpositus activity by Purkinje cells is an important part of the neural substrate of acquisition of eyeblink conditioning (e.g., Buonomano & Mauk, 1994). Since the interpositus nucleus appears to be where the CS-US association in eyeblink conditioning occurs and Purkinje cells may play a more modulatory role, we decided that examining interpositus nucleus activity during eyeblink conditioning in alcohol-exposed rats is an important first step towards determining exactly how the functionality of the cerebellum is compromised by early exposure to alcohol.

Rats were treated as in our previous study with the addition of stereotaxic implantation in each rat of a pair of etched, stainless steel microelectrodes in the area of the interpositus nucleus ipsilateral to the eye that received the periorbital shock US. Subsequently, rats underwent paired or unpaired training. Preliminary analyses of the behavioral data col- lected thus far replicate the results of our previous study, with alcohol-exposed rats showing an impairment in acquisition of eyeblink conditioning (Green, Johnson, Goodlett, & Steinmetz, 2000). In addition, preliminary analyses of the neural data suggest that interpositus nucleus activity during eyeblink conditioning in alcohol-exposed rats is different than control rats. We are currently examining to what extent this differential pattern of neural activity correlates with the differential rate of acquisition. Future studies in alcohol- exposed rats will examine neural activity during eyeblink conditioning in other areas required for eyeblink conditioning, including Purkinje cells, the inferior olive, and pontine nuclei. We are also engaged in unbiased stereological cell counting of deep nuclear cells in adult rats from our initial study in order to determine whether these cells are lost after neonatal alcohol exposure and whether the number of remaining deep nuclear cells is related to the ability to learn eyeblink conditioning.

In summary, classical eyeblink conditioning has already proven to be quite useful for studying the effects of early ethanol exposure on behavioral and neural function. Similar to our application of the paradigm to study autism, the selection of the eyeblink conditioning procedure for these studies was based on the rather extensive data base that is available


concerning how the brain encodes this simple form of associative learning. Early exposure of rats to binge levels of alcohol produces a lasting effect on the structure and organization of those areas of the cerebellum known to be involved in generating and maintaining conditioned eyeblink responses. We believe that further studies of the anatomy and physiology of the cerebellum, in conjunction with classical eyeblink conditioning, will significantly advance our understanding of the effects of early ethanol exposure on behavioral and neural function, in general. This approach would seem to be a very good model for fetal alcohol syndrome, a devastating clinical disorder that annually affects thousands of human infants.

Using Classical Eyeblink Conditioning to Study Obsessive-Compulsive Disorder

What is Obsessive-Compulsive Disorder ( OCD) ?

Obsessive-compulsive disorder (OCD) is an anxiety disorder, as identified by the Diag- nostic and Statistical Manual of Mental Disorders (DSM-IV). It is characterized by intru- sive, unwanted, and uncontrollable thoughts and images that the individual recognizes as irrational and self-generated (the obsessive feature), and by uncontrollable urges to engage in repetitive irrational behaviors or mental acts aimed at avoiding or reducing the anxiety elicited by the obsessions (the compulsive feature). For a person to be diagnosed with OCD, the obsessions and compulsions must disrupt the person's daily functioning and be experienced as distressing, excessive, and unreasonable (American Psychiatric Associa- tion, 1994). With a lifetime prevalence of 2-3% in the United States, it is common enough to incur significant social, economic, and personal costs. Persons suffering from OCD can spend so many hours a day engaged in compulsive behaviors, virtually every free moment, that there is little time in their lives for anything else.

Anxiety disorders in general have been theorized to be learned responses, acquired and maintained by a combination of classical (Pavlovian) and operant conditioning (Mowrer, 1960). Accordingly, acquisition of OCD may be the product of a classical conditioning process whereby a neutral stimulus (the CS) becomes associated with a stress or anxiety- inducing event (the US). The individual "learns" that the CS predicts the US and soon the CS itself elicits the anxiety response even in the absence of the US. This initial acquisition of the anxious response is a classically conditioned association, albeit a dysfunctional and maladaptive association. The anxious state brought on by the presence of the CS usually persists until some strategy is found to relieve it. Relief typically takes the form of a superstitious or ritualistic behavior or mental activity, which, when enacted repeatedly, reduces anxiety. For example, the sight of a doorknob may become associated with obsessive thoughts about germs, infection and disease. The anxiety generated by these obsessions is so great that the individual may come to irrationally fear for his or her life, or the lives of loved ones. The resulting anxiety may be relieved by engaging in some behavior, such as hand washing, which is repeated to the point of compulsion. This relief from anxiety serves to negatively reinforce the compulsive behavior. These rituals can occur every time a trigger stimulus (CS) is present.

One of the most successful behavioral treatments for OCD is exposure and response prevention (ERP) (Foa & Kozak, 1985). The success of ERP depends upon a subject's ability to withhold compulsive responses to a trigger stimulus. Ideally, after repeatedly withholding responses, the individual faces the irrational nature of their obsession and


anxiety gradually decreases, along with the compulsive behaviors. ERP significantly reduces OCD symptoms (60% or more reduction) in 75% of the patients who complete the program (Craske & Barlow, 1993; Stanley & Turner, 1995).

The success rate of ERP, which is essentially an extinction paradigm, supports the theory that OCD arises originally from a learning process, though it gives no insights as to why some people form such persistent and maladaptive associations and others do not. Presumably, everyone, at some point, experiences some level of anxiety and stress like the kind that precipitates OCD. Yet, few ever develop OCD symptoms. Suggestions that OCD arises from unusual experiences have not been supported (DiNardo & Barlow, 1990; Ost, 1987). If the anxiety associated with OCD is a learned response, OCD itself may be the result of differential learning capabilities. More specifically, the neural and behavioral processes associated with classical conditioning, and possibly associative learning in general, are somehow different for the population prone to anxiety disorders. If this is true, we reasoned that people who are likely to develop OCD should demonstrate a general devi- ance from the normal population in learning other classically conditioned responses.

Why use Classical Eyeblink Conditioning to Study OCD?

As mentioned above, the very fact that ERP is a successful treatment for OCD, and that extinction paradigms generally are often the therapies of choice for anxiety disorders as a category, suggests that this learning model is a valid theoretical direction that may lead to a clearer understanding of the etiology of anxiety based pathologies. Since the time of Watson (1924), however, surprisingly few empirical studies of learning-based theories of human anxiety can be found in the literature.

Given what we now know about the learning, cognition, and neural processing involved, we reasoned that the eyeblink conditioning paradigm would provide an excellent platform for testing specific predictions derived from clinical theories of anxiety disorders in general, and OCD in particular. As a test of associative learning, the conditioned eyebl ink response is a direct measure of motor learning. It does not require operationalization, nor is it generally affected by mood or intention. Thus, it is relatively free of confounding variables. We hypothesized that if the clinical theories are correct, persons suffering from anxiety disorders should acquire the conditioned eyeblink response more rapidly and/or extinguish more slowly than normal control subjects. The two experiments summarized here tested the hypothesis that college students who scored high on OCD inventories should show facilitated learning during eyeblink conditioning as compared to normal controls (see Tracy, Ghose, Stecher, McFall, & Steinmetz, 1999, for the original report of these studies).

Classical Eyeblink Conditioning in OCD-like Subjects

Participants in both studies were college undergraduates from introductory psychology classes who were pre-screened on the Maudsley Obsessional-Compulsive Inventory (MOCI; (Hodgson & Rachman, 1977), a self-report measure of OCD behaviors. Our nonclinical OCD sample was drawn from students scoring in the top 4% on this measure; our control group was drawn randomly (matching for sex) from students scoring in the bottom 75% of the MOCI. Previous research has shown that non-clinical participants who admit to high rates of obsessions and compulsions are similar to clinically diagnosed OCD patients (Frost, Sher, & Green, 1986; Rachman & deSilva, 1978).


Control OCD

Exp. 1

0.1s

Exp. 2

CS US CS US FIG. 3. Behavioral responses recorded during Experiments 1 and 2 for control (left-side) and OCD (fight-

side) subjects undergoing 10 blocks of classical eyeblink conditioning (see text for details). Each trace represents the averaged behavioral responses recorded on each block for all subjects in each group. Experiments 1 and 2 differed only in the background task required of the subjects during training. The first vertical line represents onset of the tone CS while the second vertical line represents the onset of the air puff US. Note the differences in response topography present during Experiment 2 when the control and OCD subjects are compared. Adapted from Tracy et al., 1999.

Both studies used a standard delay paradigm (500 ms tone CS, 100 ms air puff US, 400 ms ISI), consisting of 10 blocks of 10 paired acquisition trials followed by three additional blocks of 10 tone-alone extinction trials. The inter-trial interval varied from 10 to 20 s, with a mean of 15 s. The subjects engaged in a background task concurrent with undergoing the conditioning procedure. The only difference between Studies 1 and 2 was the nature of this background task--in Study 1, it was an active visual search task; in Study 2, it was a passive picture viewing task. Both tasks involved attending to images on a computer screen and making a keyboard response to each image; however, the visual search task was more arousing, requiring vigilance and involving the risk of errors, whereas the picture viewing task was neither demanding nor arousing.

Analyses of eyeblink conditioning data from Study 1 uncovered no between-group differences. The groups did not differ significantly in percentage of participants reaching the conditioning criterion, number of trials to criterion, percentage of conditioned responses, mean latency to the peak of the CR, mean amplitude of the peak response, or mean amplitude of the UR. In contrast, analyses of data From Study 2 revealed clear between-group differences: The OCD group acquired the conditioned eyeblink response significantly more rapidly than the control group did. The OCD group also showed a significantly greater decrease in UR amplitudes over blocks than the control group. Figure


3 displays the eyeblink amplitude and timing curves for each group, averaged for each block of conditioning trials, for each study. The curves for the OCD group in Study 2 clearly differ from the curves in the other three panels. In Study 2 only, the OCD group showed evidence of conditioning within the first five trials of the very first block, and showed a corresponding drop in UR amplitude starting with the same early trials. Thus, the results from Study 2 support the learning-theory model of OCD, which predicts that people with OCD should acquire classically conditioned responses more rapidly than normals. There was no support for the hypothesis that persons with OCD might extinguish more slowly than nornlals.

Support for the learning model, however, was dependent on the background task. The OCD and normal groups conditioned at the same rate when exposed to the demanding visual search task; both groups performed better under this task than under the picture viewing task. The overall percentage of conditioned responses for both groups was 75%, which is well above the level typically reported in the human eyeblink literature. Under the less demanding picture viewing task, the overall percentage of conditioned responses declined for both groups, but this decline was greater for the normal group than for the OCD group. Previous research has focused on the possibility that background tasks may interfere with the acquisition of conditioned responses (Papka, Ivry, & Woodruff-Pak, 1995); our studies raise the possibility that some tasks actually may facilitate conditioning. The results of this experiment demonstrate that classical eyeblink conditioning is sensitive to differences in clinically identified populations and may prove useful in defining the bases of some psychological disorders.

Why is Classical Eyeblink Conditioning Different in an OCD-like Sample?

Learning models for classical conditioning have modeled the neural processes associated with acquisition of conditioned responses as error-correcting algorithms (Rescorla & Wagner, 1972; Thompson et al., 1989). It is possible that the learning differences observed when the two groups were compared were related to dysfunction in this error correction. According the Rescorla-Wagner model (1972), as learning progresses and responses become more accurate, the error signal decreases. An error signal that fails to subside, or is greater than it should be, would result in faster learning that is not necessarily adaptive. Although the studies discussed here did not address neural mechanisms associated with accelerated learning in OCDs, it has been reported that a component of event-related brain potential measurements, error-related negativity (ERN), is greater in OCD subjects than normal controls (Gehring, Himle, & Nisenson, 2000). ERN signals the occurrence of an error during reaction time tasks. While there is no indication that the ERN signal differences occur during classical conditioning, it is an intriguing question for future studies.

Alternatively, general arousal may be sufficient to explain the differences in learning (OCD is, after all, an anxiety disorder). Experiments using a variety of background tasks, arousing and non-arousing, and physiological measurements are ongoing and continue to address these questions. For purposes of this paper, the OCD data illustrate another clinical use of classical eyeblink conditioning: A number of past theories concerning OCD have predicted that people with OCD are susceptible to aversive conditioning procedures. In the studies described above, we directly tested this prediction using classical eyeblink conditioning. Thus, this is an example of using the behavioral procedure to directly test hypotheses concerning the etiology of a clinical disorder. Our results indicate that at least under some circumstances, there may be some experimental support for the idea that individuals

234 STE1NMETZ, TRACY, AND GREEN

who present with OCD symptoms readily form associations between neutral and negative events.

Conclus ions

Three clinical applications of the classical eyeblink conditioning paradigm were presented here. These three lines of research were undertaken for different reasons, but all illustrate the utility of applying this learning paradigm for the study of brain - behavioral correlates of clinical pathology.

We chose to use eyeblink conditioning to study persons with autism because the neuro- logical literature suggested that at least some autistic persons had brain abnormalities that involved the cerebellum and brain stem. About 20 years of research has established clearly that the cerebellum contains sites where critical neuronal plasticity that underlies eyeblink conditioning occurs. Thus, we reasoned that behavioral deficits associated with these brain stem and cerebellar abnormalities would be found when we classically conditioned persons with autism. This is what we found--relative to age-matched control subjects, persons with autism showed faster learning of eyeblink CRs that were mistimed.

Similarly, we chose to use eyeblink conditioning to develop an animal model of fetal alcohol syndrome because it was firmly established that early exposure of rats pups to binge levels of alcohol produced cerebellar and brain stem abnormalities. We reasoned that the reduction in cerebellar Purkinje cells and effects on areas that project to the cerebellum would significantly impair classical eyeblink conditioning, both in young rats, and when the rats reached adulthood. Again, this is what we have observed. The early exposed rats show significantly fewer CRs and our preliminary recording data from the interpositus nucleus suggest that the presence of fewer CRs is reflected in a recruitment of a fewer number of neurons in this region of the brain where learning-related plasticity is thought to be present.

Finally, we have had success using classical eyeblink conditioning to study behavioral features of OCD. Unlike the first two examples of clinical applications of eyeblink conditioning, this last application was not inspired by existing knowledge of the neural pathologies that underlie OCD. Rather, this line of research was based on behavioral theories that have existed for many years concerning the etiology of this disorder. With these theories in mind, we predicted that persons with OCD would show facilitated eyeblink conditioning because they supposedly had a tendency to readily form associations in aversive conditioning situations. We found that this was true, at least under some background arousal conditions. We plan to continue this line of research by concentrating on interactions between background contextual conditions and the presentation of the conditioning stimuli to determine how these features may interact during conditioning in persons with OCD.

We believe that there will be a continued interest in the clinical use of classical eyeblink conditioning for many years to come, mostly because at this point we know quite a bit about behavioral and neural aspects of this type of associative learning. Indeed, these future studies should provide interesting new data from both basic science and clinical perspectives.

CI.ASSICAL EYEBLINK CONDITIONING 235

Acknowledgements

This paper is based on a presentation made by JES at the 2000 meeting of the Pavlovian Society in Annapolis, Maryland. Research presented in this paper was supported by funds from Indiana University and NIH grants MH51178 and NIAAA AA11945.

References

American Psychiatric Association. (1994). Diagnostic" and statistical manual of mental disorders (4 t~ ed.). Washington, D.C., American Psychiatric Association.

Backman, C., West, J. R., Mahoney. J. C., & Palmer, M. R. (1998). Electrophysiological characterization of cerebellar neurons from adult rats exposed to ethanol during development. Alcoholism: Clinical and Experi- mental Research, 22, 1137-1145.

Bauman, M. L. (1991). Microscopic neuroanatomic abnormalities in autism. Pediatrics (Supplement), 1,791- 796.

Bauman, M.L., & Kemper, T. L. (1985). Histoanatomic observations of the brain in early infantile autism. Neurology, 35,866-874.

Berthier, N. E., & Moore, J. W. (1986). Cerebellar Purkinje cell activity related to the classically conditioned nictitating membrane response. Experimental Brain Research, 63, 341-350.

Berthier, N. E., & Moore, J. W. (1990). Activity of deep cerebellar nuclear cells during classical conditioning of nictitating membrane extension in rabbits. Experimental Brain Research, 83, 44-54.

Beylin, A. V., & Shots, T. J. (1998). Stress enhances excitatory trace eyeblink conditioning and opposes acquisition of inhibitory conditioning. Behavioral Neuroscience, 112, 1327-1338.

Biel, W. C., & Wickens, D. D. (1941). The effects of vitamin BI deficiency on the conditioning of eyelid responses in the rat. Journal of Comparative and Physiological Psychology, 32,329-340.

Bonthius, D. J., & West, J. R. (1990). Alcohol-induced neuronal loss in developing rats: Increased brain damage with binge exposure. Alcoholism: Clinical and s Research, 14, 107-118.

Bonthius, D. J., & West, J. R. (1991). Permanent neuronal deficits in rats exposed to alcohol during the brain growth spurt. Teratology, 44, 147-163.

Brandon, S. E., Betts, S. L., & Wagner, A. R. (1994). Discriminated lateralized eyeblink conditioning in the rabbit: An experimental context for separating specific and general associative influences. Journal of Experimental Psychology: Animal Behavior Processes, 20,292-307.

Buounomano, D.V., & Mauk, M.D. (1994). Neural network model of the cerebellum: Temporal discrimination and the timing of motor responses. Neural Computation, 6, 38-55.

Clark, R. E., & Squire, L. R. (1998). Classical conditioning and brain systems: The role of awareness. Science, 280, 77-81.

Clark, R. E., & Squire, L. R. (2000). Awareness and the conditioned eyeblink response. In D.S. Woodruff-Pak and J.E. Steinmetz (Eds.), Eyeblink classical conditioning: Volume l: Applications in humans, pp. 229-252, Boston: Kluwer.

Courchesne, E. (1987). A neurophysiological view of autism. In E. Schopler & G. B. Mesibov (Eds.), Neuro- biological issues in atttism, pp. 285 324, New York: Plenum Press.

Courchesne, E. (199l). Neuroanatomic imaging in autism. Pediatrics, 87,781-790. Craske, M. G., & Barlow, D. H. (1993). Panic disorder and agoraphobia. In D. H. Barlow (Ed.), Clinical

Handbook of Psychological Disorders (Vol. 2rid, ). New York: Guilford. Daum, I., Schugens, M. M.. Ackermann, H., Lutzenberger, W., Dichgans, J., & Birbaumer, N. (1993). Classi-

cal conditioning after cerebellar lesions in humans. Behavioral Neuroscience, 107, 748-756. DiNardo, P. A., & Barlow, D. H. (1990). Syndrome and symptom co-occurrence in the anxiety disorders. In J.

D, Maser & C. R. Cloninger (Eds.), Comorbidity of Mood and Anxie O, Disorders, pp. 205-230. Washing- ton, DC: American Psychiatric Press,

Foa, E. B., & Kozak, M. J. (1985). Treatment of anxiety disorders: Implications for psychopathology. In A. H. Tuma & J. D. Maser (Eds.), Anxiety and Anxie~' Disorders, pp. 421-452. Hillsdale, N J: Erlbaum.

Frost. R. O., Sher, K. J., & Green, T. (1986). Psychopathology and personality characteristics of nonclinical compulsive checkers. Behaviour Research and Therapy, 24, 133-143.

Gehring, W. J., Himle, J., & Nisenson. L. G. (2000). Action-monitoring dysfunction in obsessive-compulsive disorder. Psychological Science, 11, 1-6.

Goodlett, C. R., & Eilers. A. T. (1997). Alcohol-induced Purkinje cell loss with a single binge exposure in


neonatal rats: A stereological study of temporal windows of vulnerability. Alcoholism: Clinical and Experi- mental Research, 21,738-744.

Goodlett, C. R., & Johnson, T. B. (1999). Temporal windows of vulnerability to alcohol during the third trimester equivalent: Why "knowing when" matters. In J. H. Hannigan, L. P. Spear, N. E. Spear, & C. R. Goodlett (Eds.), Alcohol and Alcoholism: Effects on Brain and Development, pp. 59-91. Hillsdale, NJ: Lawrence Erlbaum.

Goodlett, C. R., & Lundahl, K. R. (1996). Temporal determinants of neonatal alcohol-induced cerebellar damage and motor performance deficits. Pharmacology, Biochemistry and Behavior, 55, 531-540.

Goodlett, C. R., Pearlman, A. D., & Lundahl, K. R. (1998). Binge neonatal alcohol intubations induce dose- dependent loss of Purkinje cells. Neurotoxicology and Teratology, 20, 285-292.

Goodlett, C. R., Peterson, S. D., Lundahl, K. R., & Pearlman, A. D. (1997). Binge-like alcohol exposure of neonatal rats via intragastric intubation induces both Purkinje cell loss and cortical astrogliosis. Alcoholism: Clinical and Experimental Research, 21, 101 O- 1017.

Goodlett, C. R., Thomas, J. D., & West, J. R. (1991). Long-term deficits in cerebellar growth and rotarod performance of rats following "binge-like" alcohol exposure during the neonatal brain growth spurt. Neurotoxicology and Teratology, 13, 69-74.

Gormezano, I., & Kehoe, E. J. (1981). Classical conditioning and the law of contiguity. In P. Harzem & M. D. Zeiler (Eds.), Predictabili~, Correlation, and Contiguio', pp. 1-45. New York: John Wiley & Sons.

Gormezano, I., Kehoe, E. J., & Marshall, B. S. (1983). Twenty years of clasical conditioning with the rabbit. Progress in Psychobiology and Physiological Psychology, 10, 197-275.

Gormezano, I., Schneiderman, N., Deaux, E., & Fuentes, I. (1962). Nictitating membrane: classical conditioning and extinction in the albino rabbit. Science, 138, 33-34.

Gould, T.J. & Steinmetz, J.E. (1996). Changes in rabbit cerebellar cortical and interpositus nucleus activity during acquisition, extinction and backward classical conditioning. Neurobiology of Learning and Memory, 65, 17-34.

Green, J.T., Johnson, T.B., Goodlett, C.R., & Steinmetz, J.E. (2000). Neonatal alcohol exposure in rats disrupts adult eyeblink conditioning and cerebellar neural activity. Society for Neuroscience Abstracts, 26, 721.

Green, J.T., Rogers, R.F., Goodlett, C.R., & Steinmetz, J.E. (2000). Impairment in eyeblink classical conditioning in adult rats exposed to ethanol as neonates. Alcoholism: Clinical and Experimental Research, 24,438- 447.

Grevert, P., & Moore, J. W. (1970). The effect of unpaired US presentations on conditioning of the rabbit's nictitating membrane response: consolidation or contingency. Psychonomic Science, 20, 177-179.

Guerri, C. (1998). Neuroanatomical and neurophysiological mechanisms involved in central nervous system dysfunction induced by prenatal alcohol exposure. Alcoholism: Clinical and Experimental Research, 22, 304-312.

Hall, R. D. (1973). Methods and designs: Some properties of conditioned and unconditioned eyelid reflexes in the albino rat. Behavior Research Methods and Instrumentation, 5,321-331.

Hamre, K. M., & West, J. R. (1993). The effects of the timing of ethanol exposure during the brain growth spurt on the number of cerebellar purkinje and granule cell nuclear profiles. Alcoholism: Clinical Experi- mental Research, 17, 610-622.

Hannigan, J. H. (1996). What research with animals is telling us about alcohol related neurodevelopmental disorder. Pharmacology, Biochemist~ and Behavior, 55,489-499.

Hodgson, R. J., & Rachman, S. (1977). Obsessive-compulsive complaints. Behaviour Research and Therapy, 15,389-395.

Hughes, B., & Schlosberg, H. (1938). Conditioning in the white rat. IV. The conditioned lid reflex. Journal of Experimental Psychology, 23, 641-650.

Katz, D.B., & Steinmetz, J.E. (1997). Single-unit evidence for eyeblink conditioning in cerebellar cortex is altered, but not eliminated, by interpositus nucleus lesions. Learning & Memory, 4, 88-104.

Kehoe, E. J., & Napier, R. M. (1991). Temporal specificity in cross-modal transfer of the rabbit nictitating membrane responses. Journal of Experimental Psychology, 26-35.

Lovick, T. A., & Zbrozyna, A. W. (1975). Classical conditioning of the corneal reflex in the chronic decer- ebrate rat. Brain Research, 89, 337-340.

Marcussen, B. L., Goodlett, C. R., Mahoney, J. C., & West, J. R. (1994). Developing rat Purkinje cells are more vulnerable to alcohol-induced depletion during differentiation than during neurogensis. Alcohol, 11, 147-156.

Mattson, S. N., & Riley, E. P. (1998). A review of the neurobehavioral deficits in children with fetal alcohol


syndrome or prenatal exposure to alcohol. Alcoholism: Clinical and Experimental Research, 22, 279-294. McCormick, D. A., & Thompson, R. F. (1984). Cerebellum essential involvement in the classically condi-

tioned eyelid response. Science, 223,296-299. Meyer, L. S., Kotch, L. E., & Riley, E. P. (1990). Neonatal ethanol exposure: Functional alterations associated

with cerebellar growth retardation. Neurotoxicology and Teratology, f2, 15-22. Mowrer, O. H. (1960). I~arning Theory and Behavior. New York: John Wiley and Sons. Napper, R. M. A., & West, J. R. (1995a). Permanent neuronal cell loss in the cerebellum of rats exposed to

continuous low blood alcohol levels during the brain growth spurt: A stereological investigation. Journal of Comparative Neurology, 362,283-292.

Napper, R. M. A., & West, J. R. (1995b). Permanent neuronal cell loss in the inferior olive of adult rats exposed to alcohol during the brain growth spurt: A stereological investigation. Alcoholism: Clinical and Experimental Research, 19, 1321-1326.

Ost, L. G. (1987). Age of onset in different phobias. Journal of Abnormal Psychology, 96,223-229. Papka, M., Ivry, R. B., & Woodruff-Pak, D. S. (t995). Selective disruption of eyeblink classical conditioning

by concurrent tapping. NeuroReport, 6, 1493-1497. Pauli, J., Wilce, P., & Bedi, K. S. (I 995). Acute exposure to alcohol during early postnatal life causes a deficit

in the total number of cerebellar Purkinje cells in the rat. Journal of Comparative Neurology, 360, 506-512. Perrett, S. P., Ruiz, B. P., & Mauk, M. D. (1993). Cerebellar cortex lesions disrupt learning-dependent timing

of conditioned eyelid responses. Journal of Neuroscience, 13, 1708-17 l 8. Rachman, S., & deSilva, P. (1978). Abnormal and normal obsessions. Behaviour Research and Therapy, 16,

233-248. Rescorla, R. A., & Wagner, A. R. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness

of reinforcement and non-reirfforcement. In A. H. Black & W. F. Prokasy (Eds.), Classical conditioning II: Current research and theory. New York: Appleton-Century-Crofts.

Rodier, P. M., Bryson, S. E., & Welch, J. P. (1997). Minor malformations and physical measurements in autism: Data from Nova Scotia. Teratology, 55, 319-325.

Roebuck, T. M., Mattson, S. N., & Riley, E. P. (1998). A review of the neuroanatomical findings in children with fetal alcohol syndrome or prenatal exposure to alcohol. Alcoholism: Clinical and Experimental Re- search, 22,339-344.

Schmajuk, N. A., & Christiansen, B. A. (1990). Eyeblink conditioning in rats. Physiology & Behavior, 48, 755-758.

Sears, L. L., Finn, P. R.. & Steinmetz, J. E. (1994). Abnormal classical eyeblink conditioning in autism. Journal of Autism and Developmental Disorders, 24,737-751.

Sears, L. L., & Steinmetz, J. E. (1990). Acquisition of classically conditioned-related activity in the hippocampus is affected by lesions of the cerebellar interpositus nucleus. Behavioral Neuroscience, 104,681-692.

Sears, L. L., & Steinmetz, J. E. (2000). Classical eyeblink conditioning in normal and autistic children. In: D.S. Woodruff-Pak & J.E. Steinmetz (Eds), Eyeblink Classical Conditioning, Vol 1: Human Applications, pp. 143-162, Boston: Kluwer.

Skelton, R. W. (1988). Bilateral cerebellar lesions disrupt conditioned eyelid responses in unrestrained rats. Behavioral Neuroscience, 102,586-590.

Solomon, P. R., & Moore, J. W. (1975). Latent inhibition and stimulus generalization of the classically conditioned nictitating membrane response in rabbits (Oryctolagus cuniculus) following dorsal hippocampal ablation. Journal of Comparative and Physiological Psychology, 89, 1192-1203.

Stanley, M. A., & Turner, S. M. (1995). Current status of pharmacological and behavioral treatment of obsessive-compulsive disorder. Behavioral Therapy, 26, 163-186.

Stanton, M. E., & Goodlett, C. R. (1998). Neonatal ethanol exposure impairs eyeblink conditioning in wean- ling rats. Alcoholism: Clinical and Experimental Research. 22, 270-275.

Steinmetz, J. E. (2000). Brain substrates of classical eyeblink conditioning: A highly localized hut also distrib- uted system. Behavioural Brain Research, 110, 13-24.

Streissguth, A. P., Bookstein, F. L., & Barr, H. M. (1996). A dose-response study of the enduring effects of prenatal alcohol exposure: birth to 14 years, tn H.-L. Spohr & H.-C. Steinhausen (Eds.), Alcohol, pregnancy and the developing child, pp. 141-168. Cambridge: Cambridge University Press.

Streissguth, A. P., & O'Malley, K. (2000). Neuropsychiatric implications and long-term consequences of fetal alcohol spectrum disorders. Seminars in Clinical Neuropsychiatry, 5, 177-190.

Thomas, J. D., Goodlett, C. R., & West, J. R. (1998). Alcohol-induced Purkinje cell loss depends on developmental timing of alcohol exposure and correlates with motor performance. Developmental Brain Research, 105, 159-166.

Thomas, J. D., Wasserman, E. A., West, J. R., & Goodlett, C. R. (1996). Behavioral deficits induced by


bingelike exposure to alcohol in neonatal rats: Importance of developmental timing and number of epi- sodes. Developmental Psychobiology, 29, 433-452.

Thompson, R. F., Barnes, C., Carew, T., Cooper, L.. Gallagher, M., Posner, M., Rescorla, R., Schacter, D., Squire, L., & Wagner, A. (1989). Psychobiology of learning and memory, tn R. D. Luce, N. J. Smelser, & D. R. Gerstein (Eds.), Leading edges in social and behavioral science, pp. 21 39. New York: Russell Sage Foundation.

Tracy, J. A., Ghose, S. S., Stetcher, T., McFall, R. M., & Steinmetz, J. E. (1999). Classical conditioning in a nonclinical obsessive-compulsive population. Psychological Science, 10, 9-13.

Watson, J. B. (1924). Psychology from the Standpoint of a Behaviorist. Philadelphia: J. B. Lippincott Com- pany.

Weiss, C., Knuttinen, M.-G., Power, J. M., Patel, R. I., O'Connor, M, S., & Disterhoft, J. F. (1999). Trace eyeblink conditioning in the freely moving rat: Optimizing the conditioning parameters. Behavioral Neuro- science, 5, 1100-1105.

Woodruff-Pak, D. S., & Steinmetz, J. E. (Eds.) (2000a). Eyeblink Classical Conditioning, Volume 1: Human Applications, Boston: Kluwer.

Woodruff-Pak, D. S., & Steinmetz, J. E. (Eds.) (2000b). Eveblink Classical Conditioning, Volume 2: Animal Models, Boston: Kluwer.

Classical eyeblink conditioning: Clinical models and applications

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