Physiology & Behavior 149 (2015) 324–330
Contents lists available at ScienceDirect
Physiology & Behavior journal homepage: www.elsevier.com/locate/phb
Spatial learning in men undergoing alcohol detoxification Mauro Ceccanti a, Derek Hamilton b, Giovanna Coriale a, Valentina Carito c, Luigi Aloe c, George Chaldakov d, Marina Romeo a, Marco Ceccanti d, Angela Iannitelli e, Marco Fiore c,⁎ a
Center for Alcohol Abuse (Centro Riferimento Alcologico Regione Lazio-CRARL), Department of Clinical Medicine, Sapienza University of Rome, Italy University of New Mexico, Albuquerque, NM, USA Institute of Cell Biology and Neurobiology, National Research Council (IBCN-CNR), Rome, Italy d Division of Cell Biology, Medical University, BG-9002 Varna, Bulgaria e Department of Health Sciences, University of L'Aquila, Italy b c
H I G H L I G H T S • Ethanol addiction affects cognitive capabilities. • Spatial learning responses in alcoholic men • The virtual Morris maze as a useful tool for addiction investigation in humans
a r t i c l e
i n f o
Article history: Received 24 February 2015 Received in revised form 11 June 2015 Accepted 24 June 2015 Available online 5 July 2015 Keywords: Virtual Morris maze Ethanol detoxification
a b s t r a c t Alcohol dependence is a major public health problem worldwide. Brain and behavioral disruptions including changes in cognitive abilities are common features of alcohol addiction. Thus, the present study was aimed to investigate spatial learning and memory in 29 alcoholic men undergoing alcohol detoxification by using a virtual Morris maze task. As age-matched controls we recruited 29 men among occasional drinkers without history of alcohol dependence and/or alcohol related diseases and with a negative blood alcohol level at the time of testing. We found that the responses to the virtual Morris maze are impaired in men undergoing alcohol detoxification. Notably they showed increased latencies in the first movement during the trials, increased latencies in retrieving the hidden platform and increased latencies in reaching the visible platform. These findings were associated with reduced swimming time in the target quadrant of the pool where the platform had been during the 4 hidden platform trials of the learning phase compared to controls. Such increasing latency responses may suggest motor control, attentional and motivational deficits due to alcohol detoxification. © 2015 Elsevier Inc. All rights reserved.
1. Introduction Chronic alcohol consumption is known to induce brain damage associated with cognitive impairments in animal models and humans [11, 27,43,54]. Substantial animal data exist demonstrating that chronic alcohol exposure leads to hippocampal neurodegeneration via the disruption of brain cell proliferation, survival and maturation [26]. Early human studies reported visuospatial and visuoperceptual deficits in detoxified alcoholics by using different tests such as the Rey–Osterrieth complex figure [5,52] and the WAIS Block Design [28]. However very limited data are available concerning spatial cognition changes in alcoholics.
⁎ Corresponding author at: Istituto di Biologia Cellulare e Neurobiologia, Consiglio Nazionale delle Ricerche (CNR), via del Fosso di Fiorano 64, 00143 Roma, Italy. E-mail addresses: marco.fi[email protected], http://www.marcofiore.net (M. Fiore).
http://dx.doi.org/10.1016/j.physbeh.2015.06.034 0031-9384/© 2015 Elsevier Inc. All rights reserved.
Spatial cognition is a basic brain function with the goal to understand space by identifying and using important object-to-self and object-toobject spatial relations and concerns the acquisition, organization and revision of knowledge about spatial environments [38]. In the mammalian brain the parietal neocortex, the parahippocampal cortex and the hippocampus synergistically play a key role in the fine tuning of spatial memory regulation [2,24]. Heavy alcohol consumption has been associated with changes across several domains of cognition [34,36], with executive functioning and memory domains being the most vulnerable to disruptions by alcohol [35,37]. Binge drinking in young adults (approximately 21 years) is considered to be associated with deficits in cognitive functions linked to the dorsolateral prefrontal cortex, as well as modifications in memory functions, associated with the temporal lobe [41]. Adolescents examined after a period of three weeks of abstinence revealed a lower verbal learning and poorer visual reproduction [9]. In 3-week abstinent adult alcoholics, impairments were observed on word recall [42]. In long-
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
term abstinent alcoholics, changes in spatial processing persisted beyond the end of alcohol use, whereas other domains of cognitive function recovered with prolonged abstinence [16]. Moreover, it has also been shown in emerging adults with elevated risk for alcohol abuse disorders, but who do not yet reach diagnostic criteria, that verbal learning is affected by the neurotoxic effects of binge drinking, whereas spatial learning seems to be spared between alcohol intoxication bouts [49]. Another study on the cognitive effects of ethanol in young adults at varied levels of alcohol usage revealed that even at a subsyndromal level, young adults make risky decisions mimicking those observed in individuals with ethanol associated diseases [25]. It has been also shown that acute alcohol drinking impairs executive-type cognitive functions and that binge drinking may be associated with disrupted cognitive function in working memory and pattern recognition tasks [55]. The available human literature on the neurocognitive consequences of alcohol abuse has not fully investigated visuospatial memory, despite the large number of animal studies demonstrating alcohol-related hippocampal abnormalities on the Morris maze task [7,30,44]. Indeed, virtual versions of the Morris maze task have been developed and used to assess spatial memory in humans [4,6,14,50], but with limited data available examining the impact of alcohol on performance. In a previous study, children with Fetal Alcohol Syndrome demonstrated impaired spatial performance on the virtual Morris maze, as measured by decreased time spent searching in the correct quadrant during the probe trial, despite similar motor control, attention and motivation [23]. In an early study by using different methods recently detoxified alcoholics displayed impairment in visuospatial scanning, construction, and utilizing and manipulating information from visual images [5]. Thus, the objective of the present study was to examine the effects of alcohol detoxification on memory function in men with alcohol dependence relative to controls with no history of alcohol abuse or alcohol related disorders by using a virtual analogue of the Morris maze task to measure spatial memory [22,23].
2. Materials and methods 2.1. Participants Participants' description is reported in Table 1. The study included 115 alcoholic men. However, following the exclusion criteria described below the testing included only 29 alcoholic men subjected to detoxification. The alcoholic subjects were recruited in the “Centro di Riferimento Alcologico della Regione Lazio” of Policlinico Umberto I, Sapienza University Hospital, in Rome, Italy. A trained psychologist conducted diagnostic clinical interviews by using the Structured Clinical Interview for Diagnostic and Statistical Manual (DSM-IV) Non-Patient Edition (SCID-I/NP) [19]. All recruited alcoholics met the DSM-IV criteria for alcohol dependence. The alcoholics also underwent two semi-structured interviews to assess lifetime alcohol consumption. The Life Drinking History — L.D.H. [47] and Time Line Follow Back — T.L.F.B. [51] were used to assess alcohol consumption from the first year of regular drinking and specific amounts of alcohol consumed over the past six months respectively. As controls we recruited among moderate drinkers 45 men without history of alcohol dependence and/or alcohol related diseases and with a negative blood alcohol level at the time of the experimentation. According to the indications of the drinking levels of the National Institute on Alcohol Abuse and Alcoholism (NIAAA web site) we considered moderate drinkers people drinking up to 2 drinks per day (in Italy 1 drink = 12 g of alcohol). Exclusion criteria for all participants included history of head injury, loss of consciousness, history of organic mental disorder, present assumption of psychoactive drugs (as cocaine, opioids, amphetamine, other recreational drugs, anxiolytics, euphoriants, antipsychotics, barbiturates, benzodiazepines, antidepressants, hallucinogens — data based on urine toxicology), seizure disorder or central nervous system diseases and no sign of hypertension at the time of
325
Table 1 Description of male patients undergoing alcohol detoxification and relative controls. Data are expressed as mean ± SEM or as percentage. Male Alcoholics Subject Blood alcohol level Age Educational level — 1 low, 4 top SES — 1 low, 4 top Years of risk consumption Alcohol preference (%) Wine Beer Spirit Other CAD (in days) Previous use of psychoactive substances (%) Smoking (daily number of cigarettes)
Controls Subject Blood alcohol level Age Educational level — 1 low, 4 top SES — 1 low, 4 top Years of risk consumption Alcohol preference (%) Wine Beer Spirit Other CAD (in days) Previous use of psychoactive substances (%) Smoking (daily number of cigarettes)
n = 29 0 43.0 ± 1.98 (ns) 2.41 ± 0.15 (ns) 2.12 ± 0.23 (ns) 21.7 ± 2.11 44.24% 23.70% 31.38% 0.88% 9.2 ± 1.65 62.06% 21.8 ± 2.39 (p b 0.01 vs controls in the t-test)
n = 29 0 41.7 ± 2.21 2.3 ± 0.15 2.03 ± 0.45 nm 56.90% 34.48% 8.62% 0.00% nm 34.48% 8.91 ± 2.34
nm: not measurable; ns: not significant between groups. CAD = cumulative abstinence duration; SES = socio-economic status. According to NIAAA for men alcohol risk consumption begins with more than 4 drinks on any single day and more than 14 drinks per week. 1 drink = 12 g of alcohol in Italy.
recruitment. Another exclusion criterion for all participants was the lack of familiarity in the use of a computer. Blood alcohol levels were measured in all participants by using Alcoscan AL7000. 2.2. Procedure A virtual version of the Morris Water Maze was used [22,23] with minor modifications [18]. It consisted of the display of a square environment containing a circular pool of water (Fig. 1). Four rectangular drawings that were distinguishable by their shape, color, and placement on the walls surrounding the pool, served as navigational cues to support orientation. Each cue was placed on a different wall of the room and stretched from the ceiling to the pool wall. Experimental subjects navigated in the pool from a first-person perspective and moved around by using the ‘up’, ‘left’ and ‘right’ arrow curser keys of the keyboard. Following methods previously described [45] to more closely mimic typical rodent behavior, the ‘back’ arrow key was disabled to not permit participants to back up. If participants needed to turn around, they had to spin 180° around their left or right axis using the right or left arrow key. Participants performed the experiment on a PC with a 17-in. monitor in a room without windows of the Centro Riferimento Alcologico Regione Lazio, Rome, Italy. Participants were told that after completion of a trial, the screen would go blank and then they must hit the enter key on the keyboard to start the next trial. In order to limit the procedure to a maximum of 15 min to not affect participants' concentration and motivational abilities patients and controls were subjected to a total number of 7 experimental trials. Indeed, testing consisted (without any training trial) of four trials (learning phase) where the subjects had to navigate to the hidden platform located in the north-east quadrant (target); if they swam over the area of the pool where the platform was located, a tone sounded, the platform raised out of the water and a
326
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
2.3. Data analyses ANOVAs with alcohol dependence as the independent variable were used to analyze i, the latency to the first movement in all trials; ii, the latency to reach the hidden platform in the learning phase; iii, the latency to reach the visible platform; iv, the total distance moved in all trials; and v, the time spent in % in the quadrants with the hidden platform (probe trial). The latency to the first movement in all trials and the total distance moved in all trials were also analyzed with a 7-level repeated measure outcome. The data of the latency to reach the hidden platform in the learning phase were analyzed also with a 4-level repeated measure outcome while the data of the latency to reach the visible platform were analyzed also with a 2-level repeated measure outcome. Post-hoc comparisons were performed using Tukey's HSD test. Since alcoholic patients resulted to be heavy smokers (Table 1) data were additionally analyzed with the smoking factor as a covariate in the ANOVA analyses. 3. Results Fig. 2 shows the swim paths of both a control and a man undergoing alcohol detoxification in the learning phase (A), in the probe trial (B) and in the visible platform phase (C). As clearly reported in the pictures path navigations resemble those observed in the Morris maze for animal models. Although in the absence of statistical differences in the total distance moved in the learning phase and in the probe trial between controls and alcoholics (see results below) the pictures (A and B) demonstrate evidence of quite different patterns of platform retrieving. 3.1. Latency to the first movement in all trials
Fig. 1. Schematic reproduction of a virtual Morris maze based on [22] with minor modifications. The circular pool (A) is in the center of a room whereas the platform is located in north-east quadrant of the pool (target). Panel B represents a monitor-based first person perspective from the center of the circular pool.
Fig. 3A shows the mean latency to the first movement in all trials. In men undergoing alcohol detoxification latencies were higher in all trials but not in trial number 5 with the absent platform (see posthocs for comparison: F(1,56) = 9.55, p b 0.01 for the effect of alcohol dependence; F(6,336) = 2.80, p = 0.01 for the effect of the repeated measures; F(6,336) = 2.52, p = 0.02 for the interaction alcohol dependence × repeated measures). 3.2. Latency to reach the hidden platform in the learning phase
message saying “congratulations” was displayed. If 120 s elapsed without platform retrieving by participants, the platform was raised out of the pool so that it was visible and a message appeared “Time has expired. Please swim toward the platform”. After the learning phase, participants underwent a single platform-less trial (probe trial). In the probe trial there was no indication for the participants that the probe trial was different from the learning phase until it was completed. These trials allowed examination of where in the pool the participant searched for the platform without receiving feedback. The logic is that the participant by using the spatial cues to locate the platform, would spend the majority of their swimming during the probe trial in the target quadrant of the pool. Upon the conclusion of the probe trial the platform was raised out of the water so that it was visible to the participants. This last phase is referred to as the “visible platform phase” and consisted of two trials. All events and consequences were identical to those of the previous phases. The visible platform phase is aimed to assess possible attentional, motivational, locomotor or perceptive difficulties due to the interaction with a workstation. Data analyzed were i, the latency to the first movement in all trials; ii, the latency to reach the hidden platform in the learning phase; iii, the latency to reach the visible platform; iv, the total distance moved in all trials; and v, the time spent in % in the quadrants with the hidden platform (probe trial).
These data are shown in Figs 3B. ANOVA revealed a main effect of alcohol dependence mostly evident in trials 1 and 2 (see posthocs: F(1,56) = 8.08, p b 0.01 for the effect of alcohol dependence; F(1,228) = 5.07, p = 0.02 for the effect of smoking as a covariate). 3.3. Latency to reach the visible platform As shown in Fig. 3C patients had higher latency over the 2 trials (F(1,56) = 4.01, p b 0.05 for the effect of alcohol dependence; F(1,56) = 6.72, p = 0.012 for the effect of the repeated measures). 3.4. Total distance moved in all trials Statistical analysis did not reveal differences between groups (Fig. 3D) but only an increase for both groups during the probe trial (F(6,336) = 50.35, p b 0.01 for the effect of the repeated measures). 3.5. Time spent in % in the quadrants with the hidden platform (probe trial) Fig. 3E shows the data on the time spent in % in the target quadrant with the hidden platform (probe trial). Patients had lower scores in the north-east quadrant (see post-hocs for comparison), the sector with the hidden platform of the previous trials (F(1,56) = 9.03, p b 0.01 for the effect of alcohol dependence).
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
327
Learning Phase (A) 1
2
3
4
1
2
3
4
trial number
Alcoholic
Control
Probe Trial (B) 5
5
Control
Alcoholic
trial number
Visible Platform Phase (C) 6 7 Control
6 7 Alcoholic
trial number
Fig. 2. The panels show the swim directions of a control and of an alcoholic patient undergoing detoxification in the learning phase (A), in the probe trial (B) and in the visible platform phase (C) of the virtual Morris maze.
4. Discussion This is the first study to demonstrate that the behavioral responses in a virtual Morris maze test may be affected in men undergoing alcohol detoxification. The Morris maze is a well established tool for examining the disrupting effects of alcohol on spatial learning and memory abilities in rodents [13,17] and the virtual Morris maze is commonly used in humans to investigate changes in spatial memory. For example marijuana smokers had some impairments in the virtual Morris maze that resulted to be associated with parahippocampal hypoactivation, indicative of differences in neuronal resources utilized during memory retrieval [48]. The virtual Morris maze is also commonly used in humans to investigate changes due to diseases of the central nervous system involving mostly the hippocampal formation. Spatial navigation in this task is impaired in patients after the first episode of schizophrenia [15] and in patients affected by major depression [12] and by vestibular disorders [8], with hippocampal damage [3,20] or following traumatic brain injury [46]. As for ethanol related diseases children with Fetal Alcohol Syndrome are impaired at place learning but not in cuednavigation [23]. In the present study we found substantial differences in the virtual Morris maze response of men undergoing alcohol detoxification. Indeed, patients undergoing alcohol detoxification are characterized by the highest latencies in the first movement of the trials (Fig. 3A). This finding was particularly evident during the learning phase (Fig. 3B) and during the visible platform phase (Fig. 3C). Surprisingly, total virtual locomotion (Fig. 3D) was not statistically affected by alcohol detoxification as shown by the data on the total distance moved in all trials. In the probe trial marked differences between men undergoing ethanol detoxification and their age-matched controls were revealed in the time spent in the target quadrant but without any alteration in the latency to the first movement (trial number 5 of Fig. 3A). Indeed, during the
no-platform probe trial, patients undergoing ethanol detoxification spent significantly less time in swimming in the target quadrant of the pool (north-east) where the platform had been during the 4 hidden platform trials of the learning phase compared to controls indicative of some alterations in spatial cognition. As for the latency to the first movement in all trials participants undergoing ethanol detoxification showed a habituation profile (Fig. 3A) from trial number 1 to trial number 5 leading to similar values to those of controls in trial number 5 (the probe trial). However, the confusion generated by the absence of the platform in the probe trial elicited again an increase in the latencies during the visible platform phase. Such increasing latency responses are suggestive of motor control, attentional and motivational deficits due to alcohol detoxification rather than a marked spatial cognition disruption as alternative explanations for the impaired place learning of the probe trial. Indeed trial number 1 (Fig. 3A and B) of the learning phase is presumably a naïve performance, and therefore learning has not yet occurred. Trial 2 is the first opportunity to examine a learning effect, and the effect appears to be modest and transient (i.e., all participants are performing at the same level by trial 3). Moreover, the effect is only seen in latency to reach the platform and not in distance. Time measures could be biased by differences in motor speed and response, rather than clearly capturing cognitive ability. Arguably, the measure of distance is less biased by differences in motor control (a probable confounding factor to the study group design). Given this constellation of evidence, the effect at trial 2 is likely driven by differences in cognitive–motor circuits, and not in learning and memory function per se. This is further supported by the evidence from the visible platform trials. Panels A and B in Fig. 2 indicating platform retrieval strategies of a control subject and an alcoholic seem to emphasize the resemblance and reliability of the virtual Morris maze for humans with the Morris maze commonly used for laboratory rodents. However these pictures may represent several search strategies also in the absence of statistical
328
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
Latency to the First Movement in all Trials
Latency to Reach the Hidden Platform in the Learning Phase 70
6
Time in sec
Time in sec
12
*
*
*
* 35
A
B
0
0 1
2
3
4
5
6
7
1
2
trial number
Latency to Reach the Visible Platform 4
Arbitrary units
Time in sec
4
Total Distance Moved in All Trials
20
10
0
3
trial number
2
D
C 0 6
1
7
2
3
trial number Controls
4 5 trial number
6
7
Alcoholics
Time spent in % in the Quadrant with the Hidden Platform (Probe Trial)
percentage
North-East (target)
60
* 30
0
Controls
Alcoholics
E
Fig. 3. The figure shows the latency to the first movement in all trials (panel A), the latency to reach the hidden platform in the learning phase (panel B), the latency to reach the visible platform (panel C) and the total distance moved in all trials (panel D) in patients undergoing alcohol detoxification and respective controls. The panel E shows the time spent in percentage in the target quadrant with the hidden platform (probe trial—trial number 5). The vertical lines in the figure indicate pooled standard error means (SEM) derived from appropriate error mean square in the ANOVA. Asterisks indicate significant differences between groups (*p b 0.05).
difference in locomotory parameters in the learning phase and in the probe trial between controls and alcoholics. The alcoholic participants would move at a set distance from the wall until they hit the platform. No spatial learning was needed to locate the platform. This search strategy could explore the implication that alcoholics might choose a simpler but less effective strategy rather than be impaired on spatial learning. The observed patterns of behavioral responses in the virtual Morris maze in men undergoing ethanol detoxification are somehow comparable to the behavioral dissociations observed in animal models with brain damage [21,40] and/or in animals exposed to alcohol [31,39]. The virtual Morris maze responses in these subjects might be generated by psychological processes comparable to those involved in the original Morris maze for rodents (see, e.g. [32]), involving and requiring hippocampal, cortical and other brain areas' circuitries [18,29]. Indeed, Morris maze response impairments in animal models resulted to be associated
with other sets of neural circuitry, including the caudate–putamen and striatal areas [10,13,33]. Accordingly, it could be possible that the ethanol detoxification-related impairments in the virtual Morris maze described here may trigger selected modifications in brain biochemistry, physiology, and neuronal morphology [1,31,53]. Concerning the whole set of human nerve circuitry involved in spatial learning relatively little is known. However, based on the concept that the neural substrate of spatial learning is similar in rodents and humans, changes in brain areas, either individually or in combination, may have had a role in the ethanol-related motor/motivational/spatial learning impairments described here. Previous studies revealed changes in virtual spatial learning in patients with traumatic brain injury, indicating that some aspect of human spatial learning could be linked to a wide nonspecific brain damage [45,46]. Thus, given the multidirectional effects of alcohol in different brain areas possibly involved in human spatial learning,
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
firmly concluding that specific alterations within limbic circuitries are responsible for impaired place learning in men undergoing ethanol detoxification is not possible. Further studies are needed to elucidate this aspect of the present data. Moreover, it should be noted that other potentially confounding factors might have influenced the present findings such as the exclusion of women in the study design, or the previous use by patients and also by controls of psychoactive substances, as well as the fact that many subjects were heavy smokers, which was also represented among controls. Another possible limitation of a human study like this based on preliminary interviews is the reliability of the interviews per se although under our experimental conditions all subjects (patients and controls) had a negative blood alcohol level at the time of testing. In conclusion as ethanol detoxification and ethanol withdrawal are crucial points of the recovery process from alcohol dependence the present study represents a further step in the attempt to unravel the behavioral processes involved in such events. Therefore, this study may attract and, hopefully, generate a significant interest from those working on human addiction. References [1] K. Abernathy, L.J. Chandler, J.J. Woodward, Alcohol and the prefrontal cortex, Int. Rev. Neurobiol. 91 (2010) 289–320. [2] E.M. Aminoff, K. Kveraga, M. Bar, The role of the parahippocampal cortex in cognition, Trends Cogn. Sci. 17 (2013) 379–390. [3] R.S. Astur, L.B. Taylor, A.N. Mamelak, L. Philpott, R.J. Sutherland, Humans with hippocampus damage display severe spatial memory impairments in a virtual Morris water task, Behav. Brain Res. 132 (2002) 77–84. [4] R.S. Astur, J. Tropp, S. Sava, R.T. Constable, E.J. Markus, Sex differences and correlations in a virtual Morris water task, a virtual radial arm maze, and mental rotation, Behav. Brain Res. 151 (2004) 103–115. [5] W.W. Beatty, K.A. Hames, C.R. Blanco, S.J. Nixon, L.J. Tivis, Visuospatial perception, construction and memory in alcoholism, J. Stud. Alcohol 57 (1996) 136–143. [6] M. Boccia, F. Nemmi, C. Guariglia, Neuropsychology of environmental navigation in humans: review and meta-analysis of FMRI studies in healthy participants, Neuropsychol. Rev. 24 (2014) 236–251, http://dx.doi.org/10.1007/s11065-0149247-8. [7] M. Boulouard, V. Lelong, M. Daoust, M. Naassila, Chronic ethanol consumption induces tolerance to the spatial memory impairing effects of acute ethanol administration in rats, Behav. Brain Res. 136 (2002) 239–246. [8] T. Brandt, F. Schautzer, D.A. Hamilton, R. Bruning, H.J. Markowitsch, R. Kalla, C. Darlington, P. Smith, M. Strupp, Vestibular loss causes hippocampal atrophy and impaired spatial memory in humans, Brain J. Neurol. 128 (2005) 2732–2741. [9] S.A. Brown, S.F. Tapert, E. Granholm, D.C. Delis, Neurocognitive functioning of adolescents: effects of protracted alcohol use, Alcohol. Clin. Exp. Res. 24 (2000) 164–171. [10] T. Bueters, M. von Euler, O. Bendel, G. von Euler, Degeneration of newly formed CA1 neurons following global ischemia in the rat, Exp. Neurol. 209 (2008) 114–124. [11] G. Coriale, E. Bilotta, L. Leone, F. Cosimi, R. Porrari, F. De Rosa, M. Ceccanti, Avoidance coping strategies, alexithymia and alcohol abuse: a mediation analysis, Addict. Behav. 37 (2012) 1224–1229. [12] B.R. Cornwell, G. Salvadore, V. Colon-Rosario, D.R. Latov, T. Holroyd, F.W. Carver, R. Coppola, H.K. Manji, C.A. Zarate Jr., C. Grillon, Abnormal hippocampal functioning and impaired spatial navigation in depressed individuals: evidence from wholehead magnetoencephalography, Am. J. Psychiatry 167 (2010) 836–844. [13] R. D'Hooge, P.P. De Deyn, Applications of the Morris water maze in the study of learning and memory, Brain Res. Brain Res. Rev. 36 (2001) 60–90. [14] I. Driscoll, D.A. Hamilton, R.A. Yeo, W.M. Brooks, R.J. Sutherland, Virtual navigation in humans: the impact of age, sex, and hormones on place learning, Horm. Behav. 47 (2005) 326–335. [15] I. Fajnerova, M. Rodriguez, D. Levcik, L. Konradova, P. Mikolas, C. Brom, A. Stuchlik, K. Vlcek, J. Horacek, A virtual reality task based on animal research — spatial learning and memory in patients after the first episode of schizophrenia, Front. Behav. Neurosci. 8 (2014) 157. [16] G. Fein, J. Torres, L.J. Price, V. Di Sclafani, Cognitive performance in long-term abstinent alcoholic individuals, Alcohol. Clin. Exp. Res. 30 (2006) 1538–1544. [17] M. Fiore, F. Angelucci, E. Alleva, I. Branchi, L. Probert, L. Aloe, Learning performances, brain NGF distribution and NPY levels in transgenic mice expressing TNF-alpha, Behav. Brain Res. 112 (2000) 165–175. [18] M. Fiore, J. Korf, A. Antonelli, L. Talamini, L. Aloe, Long-lasting effects of prenatal MAM treatment on water maze performance in rats: associations with altered brain development and neurotrophin levels, Neurotoxicol. Teratol. 24 (2002) 179–191. [19] M.S. First, R.L. Spitzer, M. Gibbon, J.B.W. Williams, Structured Clinical Interview for DSM-IV Axis I Disorders (Clinical Version), American Psychiatric Press, Washington, DC, USA, 1997. [20] N.J. Goodrich-Hunsaker, S.A. Livingstone, R.W. Skelton, R.O. Hopkins, Spatial deficits in a virtual water maze in amnesic participants with hippocampal damage, Hippocampus 20 (2010) 481–491.
329
[21] M.L. Gordan, B. Jungwirth, F. Ohl, K. Kellermann, E.F. Kochs, M. Blobner, Evaluation of neurobehavioral deficits following different severities of cerebral ischemia in rats: a comparison between the modified hole board test and the Morris water maze test, Behav. Brain Res. 235 (2012) 7–20. [22] D.A. Hamilton, T.E. Johnson, E.S. Redhead, S.P. Verney, Control of rodent and human spatial navigation by room and apparatus cues, Behav. Process. 81 (2009) 154–169. [23] D.A. Hamilton, P. Kodituwakku, R.J. Sutherland, D.D. Savage, Children with Fetal Alcohol Syndrome are impaired at place learning but not cued-navigation in a virtual Morris water task, Behav. Brain Res. 143 (2003) 85–94. [24] T. Hartley, N. Burgess, Complementary memory systems: competition, cooperation and compensation, Trends Neurosci. 28 (2005) 169–170. [25] A.M. Harvanko, B.L. Odlaug, L.R. Schreiber, J.E. Grant, Cognitive task performance and frequency of alcohol usage in young adults, Journal of Addiction Medicine 6 (2012) 106–111. [26] J. He, K. Nixon, A.K. Shetty, F.T. Crews, Chronic alcohol exposure reduces hippocampal neurogenesis and dendritic growth of newborn neurons, The European Journal of Neuroscience 21 (2005) 2711–2720. [27] A.J. Heinz, A. Beck, A. Meyer-Lindenberg, P. Sterzer, A. Heinz, Cognitive and neurobiological mechanisms of alcohol-related aggression, Nat. Rev. Neurosci. 12 (2011) 400–413. [28] J.H. Kramer, E. Kaplan, M.J. Blusewicz, K.A. Preston, Visual hierarchical analysis of Block Design configural errors, J. Clin. Exp. Neuropsychol. 13 (1991) 455–465. [29] E.A. Maguire, N. Burgess, J. O'Keefe, Human spatial navigation: cognitive maps, sexual dimorphism, and neural substrates, Curr. Opin. Neurobiol. 9 (1999) 171–177. [30] B.J. Markwiese, S.K. Acheson, E.D. Levin, W.A. Wilson, H.S. Swartzwelder, Differential effects of ethanol on memory in adolescent and adult rats, Alcohol. Clin. Exp. Res. 22 (1998) 416–421. [31] D.B. Matthews, J.R. Silvers, The use of acute ethanol administration as a tool to investigate multiple memory systems, Neurobiol. Learn. Mem. 82 (2004) 299–308. [32] R.G. Morris, P. Garrud, J.N. Rawlins, J. O'Keefe, Place navigation impaired in rats with hippocampal lesions, Nature 297 (1982) 681–683. [33] H.W. Nam, R.C. Bruner, D.S. Choi, Adenosine signaling in striatal circuits and alcohol use disorders, Mol. Cell 36 (2013) 195–202. [34] M. Oscar-Berman, Learning and memory deficits in detoxified alcoholics, NIDA Res. Monogr. 101 (1990) 136–155. [35] M. Oscar-Berman, R.J. Ellis, Cognitive deficits related to memory impairments in alcoholism, Recent developments in alcoholism: an official publication of the American Medical Society on Alcoholism, the Research Society on Alcoholism, and the National Council on Alcoholism 5 (1987) 59–80. [36] M. Oscar-Berman, K. Marinkovic, Alcoholism and the brain: an overview, Alcohol Research & Health: The Journal of the National Institute on Alcohol Abuse and Alcoholism 27 (2003) 125–133. [37] M. Oscar-Berman, K. Marinkovic, Alcohol: effects on neurobehavioral functions and the brain, Neuropsychol. Rev. 17 (2007) 239–257. [38] A. Pasqualotto, M.J. Proulx, The role of visual experience for the neural basis of spatial cognition, Neurosci. Biobehav. Rev. 36 (2012) 1179–1187. [39] P. Rajendran, L.P. Spear, The effects of ethanol on spatial and nonspatial memory in adolescent and adult rats studied using an appetitive paradigm, Ann. N. Y. Acad. Sci. 1021 (2004) 441–444. [40] N.J. Rich, J.W. Van Landingham, S. Figueiroa, R. Seth, R.S. Corniola, C.W. Levenson, Chronic caloric restriction reduces tissue damage and improves spatial memory in a rat model of traumatic brain injury, J. Neurosci. Res. 88 (2010) 2933–2939. [41] J.C. Scaife, T. Duka, Behavioural measures of frontal lobe function in a population of young social drinkers with binge drinking pattern, Pharmacol. Biochem. Behav. 93 (2009) 354–362. [42] M.A. Schottenbauer, D. Hommer, H. Weingartner, Memory deficits among alcoholics: performance on a selective reminding task, Neuropsychology, Development, and Cognition Section B, Aging, Neuropsychology and Cognition 14 (2007) 505–516. [43] T. Schulte, B.G. Oberlin, D.A. Kareken, K. Marinkovic, E.M. Muller-Oehring, D.J. Meyerhoff, S. Tapert, How acute and chronic alcohol consumption affects brain networks: insights from multimodal neuroimaging, Alcohol. Clin. Exp. Res. 36 (2012) 2017–2027. [44] R. Sircar, D. Sircar, Adolescent rats exposed to repeated ethanol treatment show lingering behavioral impairments, Alcohol. Clin. Exp. Res. 29 (2005) 1402–1410. [45] R.W. Skelton, C.M. Bukach, H.E. Laurance, K.G. Thomas, J.W. Jacobs, Humans with traumatic brain injuries show place-learning deficits in computer-generated virtual space, J. Clin. Exp. Neuropsychol. 22 (2000) 157–175. [46] R.W. Skelton, S.P. Ross, L. Nerad, S.A. Livingstone, Human spatial navigation deficits after traumatic brain injury shown in the arena maze, a virtual Morris water maze, Brain Injury: [BI] 20 (2006) 189–203. [47] H.A. Skinner, W.J. Sheu, Reliability of alcohol use indices. The Lifetime Drinking History and the MAST, J. Stud. Alcohol 43 (1982) 1157–1170. [48] J.T. Sneider, J.E. Cohen-Gilbert, D.J. Crowley, M.D. Paul, M.M. Silveri, Differential effects of binge drinking on learning and memory in emerging adults, Journal of Addiction Research & Therapy (Suppl 7) (2013). [49] Sneider JT, Gruber SA, Rogowska J, Silveri MM, Yurgelun-Todd DA (2013b) A preliminary study of functional brain activation among marijuana users during performance of a virtual water maze task. Journal of Addiction 2013a:461029. [50] J.T. Sneider, S. Sava, J. Rogowska, D.A. Yurgelun-Todd, A preliminary study of sex differences in brain activation during a spatial navigation task in healthy adults, Percept. Mot. Skills 113 (2011) 461–480. [51] L.C. Sobell, M. Sobell, Timeline Follow-Back: A Technique for Assessing Self-reported Alcohol Consumption, Humama Press, Totowa, NJ, USA, 1992.
330
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
[52] E.V. Sullivan, D.H. Mathalon, C.N. Ha, R.B. Zipursky, A. Pfefferbaum, The contribution of constructional accuracy and organizational strategy to nonverbal recall in schizophrenia and chronic alcoholism, Biol. Psychiatry 32 (1992) 312–333. [53] B. Tabakoff, P.L. Hoffman, The neurobiology of alcohol consumption and alcoholism: an integrative history, Pharmacol. Biochem. Behav. 113 (2013) 20–37.
[54] J.R. Trudell, R.O. Messing, J. Mayfield, R.A. Harris, Alcohol dependence: molecular and behavioral evidence, Trends Pharmacol. Sci. (2014). [55] R. Weissenborn, T. Duka, Acute alcohol effects on cognitive function in social drinkers: their relationship to drinking habits, Psychopharmacology 165 (2003) 306–312.
Contents lists available at ScienceDirect
Physiology & Behavior journal homepage: www.elsevier.com/locate/phb
Spatial learning in men undergoing alcohol detoxification Mauro Ceccanti a, Derek Hamilton b, Giovanna Coriale a, Valentina Carito c, Luigi Aloe c, George Chaldakov d, Marina Romeo a, Marco Ceccanti d, Angela Iannitelli e, Marco Fiore c,⁎ a
Center for Alcohol Abuse (Centro Riferimento Alcologico Regione Lazio-CRARL), Department of Clinical Medicine, Sapienza University of Rome, Italy University of New Mexico, Albuquerque, NM, USA Institute of Cell Biology and Neurobiology, National Research Council (IBCN-CNR), Rome, Italy d Division of Cell Biology, Medical University, BG-9002 Varna, Bulgaria e Department of Health Sciences, University of L'Aquila, Italy b c
H I G H L I G H T S • Ethanol addiction affects cognitive capabilities. • Spatial learning responses in alcoholic men • The virtual Morris maze as a useful tool for addiction investigation in humans
a r t i c l e
i n f o
Article history: Received 24 February 2015 Received in revised form 11 June 2015 Accepted 24 June 2015 Available online 5 July 2015 Keywords: Virtual Morris maze Ethanol detoxification
a b s t r a c t Alcohol dependence is a major public health problem worldwide. Brain and behavioral disruptions including changes in cognitive abilities are common features of alcohol addiction. Thus, the present study was aimed to investigate spatial learning and memory in 29 alcoholic men undergoing alcohol detoxification by using a virtual Morris maze task. As age-matched controls we recruited 29 men among occasional drinkers without history of alcohol dependence and/or alcohol related diseases and with a negative blood alcohol level at the time of testing. We found that the responses to the virtual Morris maze are impaired in men undergoing alcohol detoxification. Notably they showed increased latencies in the first movement during the trials, increased latencies in retrieving the hidden platform and increased latencies in reaching the visible platform. These findings were associated with reduced swimming time in the target quadrant of the pool where the platform had been during the 4 hidden platform trials of the learning phase compared to controls. Such increasing latency responses may suggest motor control, attentional and motivational deficits due to alcohol detoxification. © 2015 Elsevier Inc. All rights reserved.
1. Introduction Chronic alcohol consumption is known to induce brain damage associated with cognitive impairments in animal models and humans [11, 27,43,54]. Substantial animal data exist demonstrating that chronic alcohol exposure leads to hippocampal neurodegeneration via the disruption of brain cell proliferation, survival and maturation [26]. Early human studies reported visuospatial and visuoperceptual deficits in detoxified alcoholics by using different tests such as the Rey–Osterrieth complex figure [5,52] and the WAIS Block Design [28]. However very limited data are available concerning spatial cognition changes in alcoholics.
⁎ Corresponding author at: Istituto di Biologia Cellulare e Neurobiologia, Consiglio Nazionale delle Ricerche (CNR), via del Fosso di Fiorano 64, 00143 Roma, Italy. E-mail addresses: marco.fi[email protected], http://www.marcofiore.net (M. Fiore).
http://dx.doi.org/10.1016/j.physbeh.2015.06.034 0031-9384/© 2015 Elsevier Inc. All rights reserved.
Spatial cognition is a basic brain function with the goal to understand space by identifying and using important object-to-self and object-toobject spatial relations and concerns the acquisition, organization and revision of knowledge about spatial environments [38]. In the mammalian brain the parietal neocortex, the parahippocampal cortex and the hippocampus synergistically play a key role in the fine tuning of spatial memory regulation [2,24]. Heavy alcohol consumption has been associated with changes across several domains of cognition [34,36], with executive functioning and memory domains being the most vulnerable to disruptions by alcohol [35,37]. Binge drinking in young adults (approximately 21 years) is considered to be associated with deficits in cognitive functions linked to the dorsolateral prefrontal cortex, as well as modifications in memory functions, associated with the temporal lobe [41]. Adolescents examined after a period of three weeks of abstinence revealed a lower verbal learning and poorer visual reproduction [9]. In 3-week abstinent adult alcoholics, impairments were observed on word recall [42]. In long-
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
term abstinent alcoholics, changes in spatial processing persisted beyond the end of alcohol use, whereas other domains of cognitive function recovered with prolonged abstinence [16]. Moreover, it has also been shown in emerging adults with elevated risk for alcohol abuse disorders, but who do not yet reach diagnostic criteria, that verbal learning is affected by the neurotoxic effects of binge drinking, whereas spatial learning seems to be spared between alcohol intoxication bouts [49]. Another study on the cognitive effects of ethanol in young adults at varied levels of alcohol usage revealed that even at a subsyndromal level, young adults make risky decisions mimicking those observed in individuals with ethanol associated diseases [25]. It has been also shown that acute alcohol drinking impairs executive-type cognitive functions and that binge drinking may be associated with disrupted cognitive function in working memory and pattern recognition tasks [55]. The available human literature on the neurocognitive consequences of alcohol abuse has not fully investigated visuospatial memory, despite the large number of animal studies demonstrating alcohol-related hippocampal abnormalities on the Morris maze task [7,30,44]. Indeed, virtual versions of the Morris maze task have been developed and used to assess spatial memory in humans [4,6,14,50], but with limited data available examining the impact of alcohol on performance. In a previous study, children with Fetal Alcohol Syndrome demonstrated impaired spatial performance on the virtual Morris maze, as measured by decreased time spent searching in the correct quadrant during the probe trial, despite similar motor control, attention and motivation [23]. In an early study by using different methods recently detoxified alcoholics displayed impairment in visuospatial scanning, construction, and utilizing and manipulating information from visual images [5]. Thus, the objective of the present study was to examine the effects of alcohol detoxification on memory function in men with alcohol dependence relative to controls with no history of alcohol abuse or alcohol related disorders by using a virtual analogue of the Morris maze task to measure spatial memory [22,23].
2. Materials and methods 2.1. Participants Participants' description is reported in Table 1. The study included 115 alcoholic men. However, following the exclusion criteria described below the testing included only 29 alcoholic men subjected to detoxification. The alcoholic subjects were recruited in the “Centro di Riferimento Alcologico della Regione Lazio” of Policlinico Umberto I, Sapienza University Hospital, in Rome, Italy. A trained psychologist conducted diagnostic clinical interviews by using the Structured Clinical Interview for Diagnostic and Statistical Manual (DSM-IV) Non-Patient Edition (SCID-I/NP) [19]. All recruited alcoholics met the DSM-IV criteria for alcohol dependence. The alcoholics also underwent two semi-structured interviews to assess lifetime alcohol consumption. The Life Drinking History — L.D.H. [47] and Time Line Follow Back — T.L.F.B. [51] were used to assess alcohol consumption from the first year of regular drinking and specific amounts of alcohol consumed over the past six months respectively. As controls we recruited among moderate drinkers 45 men without history of alcohol dependence and/or alcohol related diseases and with a negative blood alcohol level at the time of the experimentation. According to the indications of the drinking levels of the National Institute on Alcohol Abuse and Alcoholism (NIAAA web site) we considered moderate drinkers people drinking up to 2 drinks per day (in Italy 1 drink = 12 g of alcohol). Exclusion criteria for all participants included history of head injury, loss of consciousness, history of organic mental disorder, present assumption of psychoactive drugs (as cocaine, opioids, amphetamine, other recreational drugs, anxiolytics, euphoriants, antipsychotics, barbiturates, benzodiazepines, antidepressants, hallucinogens — data based on urine toxicology), seizure disorder or central nervous system diseases and no sign of hypertension at the time of
325
Table 1 Description of male patients undergoing alcohol detoxification and relative controls. Data are expressed as mean ± SEM or as percentage. Male Alcoholics Subject Blood alcohol level Age Educational level — 1 low, 4 top SES — 1 low, 4 top Years of risk consumption Alcohol preference (%) Wine Beer Spirit Other CAD (in days) Previous use of psychoactive substances (%) Smoking (daily number of cigarettes)
Controls Subject Blood alcohol level Age Educational level — 1 low, 4 top SES — 1 low, 4 top Years of risk consumption Alcohol preference (%) Wine Beer Spirit Other CAD (in days) Previous use of psychoactive substances (%) Smoking (daily number of cigarettes)
n = 29 0 43.0 ± 1.98 (ns) 2.41 ± 0.15 (ns) 2.12 ± 0.23 (ns) 21.7 ± 2.11 44.24% 23.70% 31.38% 0.88% 9.2 ± 1.65 62.06% 21.8 ± 2.39 (p b 0.01 vs controls in the t-test)
n = 29 0 41.7 ± 2.21 2.3 ± 0.15 2.03 ± 0.45 nm 56.90% 34.48% 8.62% 0.00% nm 34.48% 8.91 ± 2.34
nm: not measurable; ns: not significant between groups. CAD = cumulative abstinence duration; SES = socio-economic status. According to NIAAA for men alcohol risk consumption begins with more than 4 drinks on any single day and more than 14 drinks per week. 1 drink = 12 g of alcohol in Italy.
recruitment. Another exclusion criterion for all participants was the lack of familiarity in the use of a computer. Blood alcohol levels were measured in all participants by using Alcoscan AL7000. 2.2. Procedure A virtual version of the Morris Water Maze was used [22,23] with minor modifications [18]. It consisted of the display of a square environment containing a circular pool of water (Fig. 1). Four rectangular drawings that were distinguishable by their shape, color, and placement on the walls surrounding the pool, served as navigational cues to support orientation. Each cue was placed on a different wall of the room and stretched from the ceiling to the pool wall. Experimental subjects navigated in the pool from a first-person perspective and moved around by using the ‘up’, ‘left’ and ‘right’ arrow curser keys of the keyboard. Following methods previously described [45] to more closely mimic typical rodent behavior, the ‘back’ arrow key was disabled to not permit participants to back up. If participants needed to turn around, they had to spin 180° around their left or right axis using the right or left arrow key. Participants performed the experiment on a PC with a 17-in. monitor in a room without windows of the Centro Riferimento Alcologico Regione Lazio, Rome, Italy. Participants were told that after completion of a trial, the screen would go blank and then they must hit the enter key on the keyboard to start the next trial. In order to limit the procedure to a maximum of 15 min to not affect participants' concentration and motivational abilities patients and controls were subjected to a total number of 7 experimental trials. Indeed, testing consisted (without any training trial) of four trials (learning phase) where the subjects had to navigate to the hidden platform located in the north-east quadrant (target); if they swam over the area of the pool where the platform was located, a tone sounded, the platform raised out of the water and a
326
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
2.3. Data analyses ANOVAs with alcohol dependence as the independent variable were used to analyze i, the latency to the first movement in all trials; ii, the latency to reach the hidden platform in the learning phase; iii, the latency to reach the visible platform; iv, the total distance moved in all trials; and v, the time spent in % in the quadrants with the hidden platform (probe trial). The latency to the first movement in all trials and the total distance moved in all trials were also analyzed with a 7-level repeated measure outcome. The data of the latency to reach the hidden platform in the learning phase were analyzed also with a 4-level repeated measure outcome while the data of the latency to reach the visible platform were analyzed also with a 2-level repeated measure outcome. Post-hoc comparisons were performed using Tukey's HSD test. Since alcoholic patients resulted to be heavy smokers (Table 1) data were additionally analyzed with the smoking factor as a covariate in the ANOVA analyses. 3. Results Fig. 2 shows the swim paths of both a control and a man undergoing alcohol detoxification in the learning phase (A), in the probe trial (B) and in the visible platform phase (C). As clearly reported in the pictures path navigations resemble those observed in the Morris maze for animal models. Although in the absence of statistical differences in the total distance moved in the learning phase and in the probe trial between controls and alcoholics (see results below) the pictures (A and B) demonstrate evidence of quite different patterns of platform retrieving. 3.1. Latency to the first movement in all trials
Fig. 1. Schematic reproduction of a virtual Morris maze based on [22] with minor modifications. The circular pool (A) is in the center of a room whereas the platform is located in north-east quadrant of the pool (target). Panel B represents a monitor-based first person perspective from the center of the circular pool.
Fig. 3A shows the mean latency to the first movement in all trials. In men undergoing alcohol detoxification latencies were higher in all trials but not in trial number 5 with the absent platform (see posthocs for comparison: F(1,56) = 9.55, p b 0.01 for the effect of alcohol dependence; F(6,336) = 2.80, p = 0.01 for the effect of the repeated measures; F(6,336) = 2.52, p = 0.02 for the interaction alcohol dependence × repeated measures). 3.2. Latency to reach the hidden platform in the learning phase
message saying “congratulations” was displayed. If 120 s elapsed without platform retrieving by participants, the platform was raised out of the pool so that it was visible and a message appeared “Time has expired. Please swim toward the platform”. After the learning phase, participants underwent a single platform-less trial (probe trial). In the probe trial there was no indication for the participants that the probe trial was different from the learning phase until it was completed. These trials allowed examination of where in the pool the participant searched for the platform without receiving feedback. The logic is that the participant by using the spatial cues to locate the platform, would spend the majority of their swimming during the probe trial in the target quadrant of the pool. Upon the conclusion of the probe trial the platform was raised out of the water so that it was visible to the participants. This last phase is referred to as the “visible platform phase” and consisted of two trials. All events and consequences were identical to those of the previous phases. The visible platform phase is aimed to assess possible attentional, motivational, locomotor or perceptive difficulties due to the interaction with a workstation. Data analyzed were i, the latency to the first movement in all trials; ii, the latency to reach the hidden platform in the learning phase; iii, the latency to reach the visible platform; iv, the total distance moved in all trials; and v, the time spent in % in the quadrants with the hidden platform (probe trial).
These data are shown in Figs 3B. ANOVA revealed a main effect of alcohol dependence mostly evident in trials 1 and 2 (see posthocs: F(1,56) = 8.08, p b 0.01 for the effect of alcohol dependence; F(1,228) = 5.07, p = 0.02 for the effect of smoking as a covariate). 3.3. Latency to reach the visible platform As shown in Fig. 3C patients had higher latency over the 2 trials (F(1,56) = 4.01, p b 0.05 for the effect of alcohol dependence; F(1,56) = 6.72, p = 0.012 for the effect of the repeated measures). 3.4. Total distance moved in all trials Statistical analysis did not reveal differences between groups (Fig. 3D) but only an increase for both groups during the probe trial (F(6,336) = 50.35, p b 0.01 for the effect of the repeated measures). 3.5. Time spent in % in the quadrants with the hidden platform (probe trial) Fig. 3E shows the data on the time spent in % in the target quadrant with the hidden platform (probe trial). Patients had lower scores in the north-east quadrant (see post-hocs for comparison), the sector with the hidden platform of the previous trials (F(1,56) = 9.03, p b 0.01 for the effect of alcohol dependence).
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
327
Learning Phase (A) 1
2
3
4
1
2
3
4
trial number
Alcoholic
Control
Probe Trial (B) 5
5
Control
Alcoholic
trial number
Visible Platform Phase (C) 6 7 Control
6 7 Alcoholic
trial number
Fig. 2. The panels show the swim directions of a control and of an alcoholic patient undergoing detoxification in the learning phase (A), in the probe trial (B) and in the visible platform phase (C) of the virtual Morris maze.
4. Discussion This is the first study to demonstrate that the behavioral responses in a virtual Morris maze test may be affected in men undergoing alcohol detoxification. The Morris maze is a well established tool for examining the disrupting effects of alcohol on spatial learning and memory abilities in rodents [13,17] and the virtual Morris maze is commonly used in humans to investigate changes in spatial memory. For example marijuana smokers had some impairments in the virtual Morris maze that resulted to be associated with parahippocampal hypoactivation, indicative of differences in neuronal resources utilized during memory retrieval [48]. The virtual Morris maze is also commonly used in humans to investigate changes due to diseases of the central nervous system involving mostly the hippocampal formation. Spatial navigation in this task is impaired in patients after the first episode of schizophrenia [15] and in patients affected by major depression [12] and by vestibular disorders [8], with hippocampal damage [3,20] or following traumatic brain injury [46]. As for ethanol related diseases children with Fetal Alcohol Syndrome are impaired at place learning but not in cuednavigation [23]. In the present study we found substantial differences in the virtual Morris maze response of men undergoing alcohol detoxification. Indeed, patients undergoing alcohol detoxification are characterized by the highest latencies in the first movement of the trials (Fig. 3A). This finding was particularly evident during the learning phase (Fig. 3B) and during the visible platform phase (Fig. 3C). Surprisingly, total virtual locomotion (Fig. 3D) was not statistically affected by alcohol detoxification as shown by the data on the total distance moved in all trials. In the probe trial marked differences between men undergoing ethanol detoxification and their age-matched controls were revealed in the time spent in the target quadrant but without any alteration in the latency to the first movement (trial number 5 of Fig. 3A). Indeed, during the
no-platform probe trial, patients undergoing ethanol detoxification spent significantly less time in swimming in the target quadrant of the pool (north-east) where the platform had been during the 4 hidden platform trials of the learning phase compared to controls indicative of some alterations in spatial cognition. As for the latency to the first movement in all trials participants undergoing ethanol detoxification showed a habituation profile (Fig. 3A) from trial number 1 to trial number 5 leading to similar values to those of controls in trial number 5 (the probe trial). However, the confusion generated by the absence of the platform in the probe trial elicited again an increase in the latencies during the visible platform phase. Such increasing latency responses are suggestive of motor control, attentional and motivational deficits due to alcohol detoxification rather than a marked spatial cognition disruption as alternative explanations for the impaired place learning of the probe trial. Indeed trial number 1 (Fig. 3A and B) of the learning phase is presumably a naïve performance, and therefore learning has not yet occurred. Trial 2 is the first opportunity to examine a learning effect, and the effect appears to be modest and transient (i.e., all participants are performing at the same level by trial 3). Moreover, the effect is only seen in latency to reach the platform and not in distance. Time measures could be biased by differences in motor speed and response, rather than clearly capturing cognitive ability. Arguably, the measure of distance is less biased by differences in motor control (a probable confounding factor to the study group design). Given this constellation of evidence, the effect at trial 2 is likely driven by differences in cognitive–motor circuits, and not in learning and memory function per se. This is further supported by the evidence from the visible platform trials. Panels A and B in Fig. 2 indicating platform retrieval strategies of a control subject and an alcoholic seem to emphasize the resemblance and reliability of the virtual Morris maze for humans with the Morris maze commonly used for laboratory rodents. However these pictures may represent several search strategies also in the absence of statistical
328
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
Latency to the First Movement in all Trials
Latency to Reach the Hidden Platform in the Learning Phase 70
6
Time in sec
Time in sec
12
*
*
*
* 35
A
B
0
0 1
2
3
4
5
6
7
1
2
trial number
Latency to Reach the Visible Platform 4
Arbitrary units
Time in sec
4
Total Distance Moved in All Trials
20
10
0
3
trial number
2
D
C 0 6
1
7
2
3
trial number Controls
4 5 trial number
6
7
Alcoholics
Time spent in % in the Quadrant with the Hidden Platform (Probe Trial)
percentage
North-East (target)
60
* 30
0
Controls
Alcoholics
E
Fig. 3. The figure shows the latency to the first movement in all trials (panel A), the latency to reach the hidden platform in the learning phase (panel B), the latency to reach the visible platform (panel C) and the total distance moved in all trials (panel D) in patients undergoing alcohol detoxification and respective controls. The panel E shows the time spent in percentage in the target quadrant with the hidden platform (probe trial—trial number 5). The vertical lines in the figure indicate pooled standard error means (SEM) derived from appropriate error mean square in the ANOVA. Asterisks indicate significant differences between groups (*p b 0.05).
difference in locomotory parameters in the learning phase and in the probe trial between controls and alcoholics. The alcoholic participants would move at a set distance from the wall until they hit the platform. No spatial learning was needed to locate the platform. This search strategy could explore the implication that alcoholics might choose a simpler but less effective strategy rather than be impaired on spatial learning. The observed patterns of behavioral responses in the virtual Morris maze in men undergoing ethanol detoxification are somehow comparable to the behavioral dissociations observed in animal models with brain damage [21,40] and/or in animals exposed to alcohol [31,39]. The virtual Morris maze responses in these subjects might be generated by psychological processes comparable to those involved in the original Morris maze for rodents (see, e.g. [32]), involving and requiring hippocampal, cortical and other brain areas' circuitries [18,29]. Indeed, Morris maze response impairments in animal models resulted to be associated
with other sets of neural circuitry, including the caudate–putamen and striatal areas [10,13,33]. Accordingly, it could be possible that the ethanol detoxification-related impairments in the virtual Morris maze described here may trigger selected modifications in brain biochemistry, physiology, and neuronal morphology [1,31,53]. Concerning the whole set of human nerve circuitry involved in spatial learning relatively little is known. However, based on the concept that the neural substrate of spatial learning is similar in rodents and humans, changes in brain areas, either individually or in combination, may have had a role in the ethanol-related motor/motivational/spatial learning impairments described here. Previous studies revealed changes in virtual spatial learning in patients with traumatic brain injury, indicating that some aspect of human spatial learning could be linked to a wide nonspecific brain damage [45,46]. Thus, given the multidirectional effects of alcohol in different brain areas possibly involved in human spatial learning,
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
firmly concluding that specific alterations within limbic circuitries are responsible for impaired place learning in men undergoing ethanol detoxification is not possible. Further studies are needed to elucidate this aspect of the present data. Moreover, it should be noted that other potentially confounding factors might have influenced the present findings such as the exclusion of women in the study design, or the previous use by patients and also by controls of psychoactive substances, as well as the fact that many subjects were heavy smokers, which was also represented among controls. Another possible limitation of a human study like this based on preliminary interviews is the reliability of the interviews per se although under our experimental conditions all subjects (patients and controls) had a negative blood alcohol level at the time of testing. In conclusion as ethanol detoxification and ethanol withdrawal are crucial points of the recovery process from alcohol dependence the present study represents a further step in the attempt to unravel the behavioral processes involved in such events. Therefore, this study may attract and, hopefully, generate a significant interest from those working on human addiction. References [1] K. Abernathy, L.J. Chandler, J.J. Woodward, Alcohol and the prefrontal cortex, Int. Rev. Neurobiol. 91 (2010) 289–320. [2] E.M. Aminoff, K. Kveraga, M. Bar, The role of the parahippocampal cortex in cognition, Trends Cogn. Sci. 17 (2013) 379–390. [3] R.S. Astur, L.B. Taylor, A.N. Mamelak, L. Philpott, R.J. Sutherland, Humans with hippocampus damage display severe spatial memory impairments in a virtual Morris water task, Behav. Brain Res. 132 (2002) 77–84. [4] R.S. Astur, J. Tropp, S. Sava, R.T. Constable, E.J. Markus, Sex differences and correlations in a virtual Morris water task, a virtual radial arm maze, and mental rotation, Behav. Brain Res. 151 (2004) 103–115. [5] W.W. Beatty, K.A. Hames, C.R. Blanco, S.J. Nixon, L.J. Tivis, Visuospatial perception, construction and memory in alcoholism, J. Stud. Alcohol 57 (1996) 136–143. [6] M. Boccia, F. Nemmi, C. Guariglia, Neuropsychology of environmental navigation in humans: review and meta-analysis of FMRI studies in healthy participants, Neuropsychol. Rev. 24 (2014) 236–251, http://dx.doi.org/10.1007/s11065-0149247-8. [7] M. Boulouard, V. Lelong, M. Daoust, M. Naassila, Chronic ethanol consumption induces tolerance to the spatial memory impairing effects of acute ethanol administration in rats, Behav. Brain Res. 136 (2002) 239–246. [8] T. Brandt, F. Schautzer, D.A. Hamilton, R. Bruning, H.J. Markowitsch, R. Kalla, C. Darlington, P. Smith, M. Strupp, Vestibular loss causes hippocampal atrophy and impaired spatial memory in humans, Brain J. Neurol. 128 (2005) 2732–2741. [9] S.A. Brown, S.F. Tapert, E. Granholm, D.C. Delis, Neurocognitive functioning of adolescents: effects of protracted alcohol use, Alcohol. Clin. Exp. Res. 24 (2000) 164–171. [10] T. Bueters, M. von Euler, O. Bendel, G. von Euler, Degeneration of newly formed CA1 neurons following global ischemia in the rat, Exp. Neurol. 209 (2008) 114–124. [11] G. Coriale, E. Bilotta, L. Leone, F. Cosimi, R. Porrari, F. De Rosa, M. Ceccanti, Avoidance coping strategies, alexithymia and alcohol abuse: a mediation analysis, Addict. Behav. 37 (2012) 1224–1229. [12] B.R. Cornwell, G. Salvadore, V. Colon-Rosario, D.R. Latov, T. Holroyd, F.W. Carver, R. Coppola, H.K. Manji, C.A. Zarate Jr., C. Grillon, Abnormal hippocampal functioning and impaired spatial navigation in depressed individuals: evidence from wholehead magnetoencephalography, Am. J. Psychiatry 167 (2010) 836–844. [13] R. D'Hooge, P.P. De Deyn, Applications of the Morris water maze in the study of learning and memory, Brain Res. Brain Res. Rev. 36 (2001) 60–90. [14] I. Driscoll, D.A. Hamilton, R.A. Yeo, W.M. Brooks, R.J. Sutherland, Virtual navigation in humans: the impact of age, sex, and hormones on place learning, Horm. Behav. 47 (2005) 326–335. [15] I. Fajnerova, M. Rodriguez, D. Levcik, L. Konradova, P. Mikolas, C. Brom, A. Stuchlik, K. Vlcek, J. Horacek, A virtual reality task based on animal research — spatial learning and memory in patients after the first episode of schizophrenia, Front. Behav. Neurosci. 8 (2014) 157. [16] G. Fein, J. Torres, L.J. Price, V. Di Sclafani, Cognitive performance in long-term abstinent alcoholic individuals, Alcohol. Clin. Exp. Res. 30 (2006) 1538–1544. [17] M. Fiore, F. Angelucci, E. Alleva, I. Branchi, L. Probert, L. Aloe, Learning performances, brain NGF distribution and NPY levels in transgenic mice expressing TNF-alpha, Behav. Brain Res. 112 (2000) 165–175. [18] M. Fiore, J. Korf, A. Antonelli, L. Talamini, L. Aloe, Long-lasting effects of prenatal MAM treatment on water maze performance in rats: associations with altered brain development and neurotrophin levels, Neurotoxicol. Teratol. 24 (2002) 179–191. [19] M.S. First, R.L. Spitzer, M. Gibbon, J.B.W. Williams, Structured Clinical Interview for DSM-IV Axis I Disorders (Clinical Version), American Psychiatric Press, Washington, DC, USA, 1997. [20] N.J. Goodrich-Hunsaker, S.A. Livingstone, R.W. Skelton, R.O. Hopkins, Spatial deficits in a virtual water maze in amnesic participants with hippocampal damage, Hippocampus 20 (2010) 481–491.
329
[21] M.L. Gordan, B. Jungwirth, F. Ohl, K. Kellermann, E.F. Kochs, M. Blobner, Evaluation of neurobehavioral deficits following different severities of cerebral ischemia in rats: a comparison between the modified hole board test and the Morris water maze test, Behav. Brain Res. 235 (2012) 7–20. [22] D.A. Hamilton, T.E. Johnson, E.S. Redhead, S.P. Verney, Control of rodent and human spatial navigation by room and apparatus cues, Behav. Process. 81 (2009) 154–169. [23] D.A. Hamilton, P. Kodituwakku, R.J. Sutherland, D.D. Savage, Children with Fetal Alcohol Syndrome are impaired at place learning but not cued-navigation in a virtual Morris water task, Behav. Brain Res. 143 (2003) 85–94. [24] T. Hartley, N. Burgess, Complementary memory systems: competition, cooperation and compensation, Trends Neurosci. 28 (2005) 169–170. [25] A.M. Harvanko, B.L. Odlaug, L.R. Schreiber, J.E. Grant, Cognitive task performance and frequency of alcohol usage in young adults, Journal of Addiction Medicine 6 (2012) 106–111. [26] J. He, K. Nixon, A.K. Shetty, F.T. Crews, Chronic alcohol exposure reduces hippocampal neurogenesis and dendritic growth of newborn neurons, The European Journal of Neuroscience 21 (2005) 2711–2720. [27] A.J. Heinz, A. Beck, A. Meyer-Lindenberg, P. Sterzer, A. Heinz, Cognitive and neurobiological mechanisms of alcohol-related aggression, Nat. Rev. Neurosci. 12 (2011) 400–413. [28] J.H. Kramer, E. Kaplan, M.J. Blusewicz, K.A. Preston, Visual hierarchical analysis of Block Design configural errors, J. Clin. Exp. Neuropsychol. 13 (1991) 455–465. [29] E.A. Maguire, N. Burgess, J. O'Keefe, Human spatial navigation: cognitive maps, sexual dimorphism, and neural substrates, Curr. Opin. Neurobiol. 9 (1999) 171–177. [30] B.J. Markwiese, S.K. Acheson, E.D. Levin, W.A. Wilson, H.S. Swartzwelder, Differential effects of ethanol on memory in adolescent and adult rats, Alcohol. Clin. Exp. Res. 22 (1998) 416–421. [31] D.B. Matthews, J.R. Silvers, The use of acute ethanol administration as a tool to investigate multiple memory systems, Neurobiol. Learn. Mem. 82 (2004) 299–308. [32] R.G. Morris, P. Garrud, J.N. Rawlins, J. O'Keefe, Place navigation impaired in rats with hippocampal lesions, Nature 297 (1982) 681–683. [33] H.W. Nam, R.C. Bruner, D.S. Choi, Adenosine signaling in striatal circuits and alcohol use disorders, Mol. Cell 36 (2013) 195–202. [34] M. Oscar-Berman, Learning and memory deficits in detoxified alcoholics, NIDA Res. Monogr. 101 (1990) 136–155. [35] M. Oscar-Berman, R.J. Ellis, Cognitive deficits related to memory impairments in alcoholism, Recent developments in alcoholism: an official publication of the American Medical Society on Alcoholism, the Research Society on Alcoholism, and the National Council on Alcoholism 5 (1987) 59–80. [36] M. Oscar-Berman, K. Marinkovic, Alcoholism and the brain: an overview, Alcohol Research & Health: The Journal of the National Institute on Alcohol Abuse and Alcoholism 27 (2003) 125–133. [37] M. Oscar-Berman, K. Marinkovic, Alcohol: effects on neurobehavioral functions and the brain, Neuropsychol. Rev. 17 (2007) 239–257. [38] A. Pasqualotto, M.J. Proulx, The role of visual experience for the neural basis of spatial cognition, Neurosci. Biobehav. Rev. 36 (2012) 1179–1187. [39] P. Rajendran, L.P. Spear, The effects of ethanol on spatial and nonspatial memory in adolescent and adult rats studied using an appetitive paradigm, Ann. N. Y. Acad. Sci. 1021 (2004) 441–444. [40] N.J. Rich, J.W. Van Landingham, S. Figueiroa, R. Seth, R.S. Corniola, C.W. Levenson, Chronic caloric restriction reduces tissue damage and improves spatial memory in a rat model of traumatic brain injury, J. Neurosci. Res. 88 (2010) 2933–2939. [41] J.C. Scaife, T. Duka, Behavioural measures of frontal lobe function in a population of young social drinkers with binge drinking pattern, Pharmacol. Biochem. Behav. 93 (2009) 354–362. [42] M.A. Schottenbauer, D. Hommer, H. Weingartner, Memory deficits among alcoholics: performance on a selective reminding task, Neuropsychology, Development, and Cognition Section B, Aging, Neuropsychology and Cognition 14 (2007) 505–516. [43] T. Schulte, B.G. Oberlin, D.A. Kareken, K. Marinkovic, E.M. Muller-Oehring, D.J. Meyerhoff, S. Tapert, How acute and chronic alcohol consumption affects brain networks: insights from multimodal neuroimaging, Alcohol. Clin. Exp. Res. 36 (2012) 2017–2027. [44] R. Sircar, D. Sircar, Adolescent rats exposed to repeated ethanol treatment show lingering behavioral impairments, Alcohol. Clin. Exp. Res. 29 (2005) 1402–1410. [45] R.W. Skelton, C.M. Bukach, H.E. Laurance, K.G. Thomas, J.W. Jacobs, Humans with traumatic brain injuries show place-learning deficits in computer-generated virtual space, J. Clin. Exp. Neuropsychol. 22 (2000) 157–175. [46] R.W. Skelton, S.P. Ross, L. Nerad, S.A. Livingstone, Human spatial navigation deficits after traumatic brain injury shown in the arena maze, a virtual Morris water maze, Brain Injury: [BI] 20 (2006) 189–203. [47] H.A. Skinner, W.J. Sheu, Reliability of alcohol use indices. The Lifetime Drinking History and the MAST, J. Stud. Alcohol 43 (1982) 1157–1170. [48] J.T. Sneider, J.E. Cohen-Gilbert, D.J. Crowley, M.D. Paul, M.M. Silveri, Differential effects of binge drinking on learning and memory in emerging adults, Journal of Addiction Research & Therapy (Suppl 7) (2013). [49] Sneider JT, Gruber SA, Rogowska J, Silveri MM, Yurgelun-Todd DA (2013b) A preliminary study of functional brain activation among marijuana users during performance of a virtual water maze task. Journal of Addiction 2013a:461029. [50] J.T. Sneider, S. Sava, J. Rogowska, D.A. Yurgelun-Todd, A preliminary study of sex differences in brain activation during a spatial navigation task in healthy adults, Percept. Mot. Skills 113 (2011) 461–480. [51] L.C. Sobell, M. Sobell, Timeline Follow-Back: A Technique for Assessing Self-reported Alcohol Consumption, Humama Press, Totowa, NJ, USA, 1992.
330
M. Ceccanti et al. / Physiology & Behavior 149 (2015) 324–330
[52] E.V. Sullivan, D.H. Mathalon, C.N. Ha, R.B. Zipursky, A. Pfefferbaum, The contribution of constructional accuracy and organizational strategy to nonverbal recall in schizophrenia and chronic alcoholism, Biol. Psychiatry 32 (1992) 312–333. [53] B. Tabakoff, P.L. Hoffman, The neurobiology of alcohol consumption and alcoholism: an integrative history, Pharmacol. Biochem. Behav. 113 (2013) 20–37.
[54] J.R. Trudell, R.O. Messing, J. Mayfield, R.A. Harris, Alcohol dependence: molecular and behavioral evidence, Trends Pharmacol. Sci. (2014). [55] R. Weissenborn, T. Duka, Acute alcohol effects on cognitive function in social drinkers: their relationship to drinking habits, Psychopharmacology 165 (2003) 306–312.
