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Psychophysical evaluation of contrast sensitivity using Gabor patches in tobacco addiction
Journal of Clinical Neuroscience xxx (2018) xxx–xxx
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Clinical study
Psychophysical evaluation of contrast sensitivity using Gabor patches in tobacco addiction Thiago Monteiro Paiva Fernandes a, Steven M. Silverstein b, Natalia Leandro de Almeida a,⇑, Natanael Antonio dos Santos a a b
Federal University of Paraiba, Joao Pessoa, Brazil Rutgers University Behavioral Health Care, Piscataway, NJ, USA
a r t i c l e
i n f o
Article history: Received 19 April 2018 Accepted 13 August 2018 Available online xxxx Keywords: Psychophysics Cigarette smoking Smoking Visual perception
a b s t r a c t This study, an extension of Fernandes et al. (2017), provided consistent contrast sensitivity function (CSF) measurements in a large sample. CSF was assessed for luminance stimuli in different 48 chronic smokers and 50 healthy nonsmokers. Stimuli for the CSF were Gabor patches with spatial frequencies of .2, 2.5, 5.0, 10.0, and 20.0 cycles per degree (cpd). The use of Gabor patches minimizes uncertainty in spatial position and detection of frequencies. The Gabor patches consisted of vertical gratings that were multiplied by a two-dimensional spatial Gaussian envelope. All of the groups were matched for gender and level of education. All of the participants were free from any neurological disorder, cardiovascular disease, and identifiable ocular disease, and they had normal or corrected-to-normal visual acuity. No abnormalities were detected on the fundoscopic examination or optical coherence tomographic examination. The smoker group had a lower CSF compared with healthy nonsmokers at all spatial frequencies. These results indicate that cigarette smoking or chronic exposure to its constituent compounds affects early-stage visual discrimination, suggesting the existence of deficits in early visual spatial processing in smokers. Ó 2018 Elsevier Ltd. All rights reserved.
1. Introduction Addictive behaviors comprise diverse conditions that are classified by the urge to use or be exposed to an addictive agent [1]. Repeated exposure to these agents may induce long-lasting cortical changes that result in tolerance, craving, or withdrawal [2,3]. Chronic cigarette smoking is one such addictive behavior and a public health priority worldwide. Data from the World Health Organization indicate that cigarettes will kill more than 5 million people by 2030 [4,5]. Tobacco smoke consists of several compounds that are harmful to individuals through either chronic use or toxic smoke inhalation [1,6]. The effects of smoking on cognition have been investigated using neuroimaging [7–9] and electrophysiology [10–12]. Numerous compounds that are contained in cigarette smoke may cause abnormalities in cortical wiring that can cause cognitive decline and dementia [13,14]. Cigarette smoking has been linked to brain atrophy through cortical thinning, with the involvement of such areas as the medial and lateral frontal cortex and a decrease in ⇑ Corresponding author.
activity of the occipital cortex [15,16]. Several studies have investigated the effects of cigarette smoking on cognitive function, but few have evaluated the effects of cigarette smoking on earlystage visual processing [17,18]. This field of study still has gaps in the literature with regard to the ways in which smoking affects the perception of form. As an embryonic extension of the brain, the retina may be one of the most studied regions of the central nervous system because of its easily accessible anatomical position [19,20]. The retina allows noninvasive investigations of visual processing. Several types of measurements have been developed to characterize visual processing, such as visual acuity and the contrast sensitivity function (CSF) [21]. The perception of form is one of the first stages of cognition and one of the first analyses that is performed by the retina-geniculate-striate system [22,23]. Our visual system is able to integrate local features to form a rich perception of spatial and temporal patterns, despite the fact that visual information is discretely sampled by the retina-geniculate-striate system [24]. The assumption that underlies the CSF is that the human visual system decomposes complex stimuli into elemental stimuli that are characterized by low spatial frequencies (i.e., the detection of large objects and the blurring of images), medium spatial frequencies
E-mail address: [email protected] (N.L.d. Almeida). https://doi.org/10.1016/j.jocn.2018.08.034 0967-5868/Ó 2018 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Fernandes TMP et al. Psychophysical evaluation of contrast sensitivity using Gabor patches in tobacco addiction. J Clin Neurosci (2018), https://doi.org/10.1016/j.jocn.2018.08.034
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(i.e., the first impression of an image), and high spatial frequencies (i.e., the detection of fine details of an image) [21,22]. The retinageniculate-striate pathway processes stimuli in the environment, and these stimuli may provide a description of the way in which the central nervous system can be impaired. Kunchulia et al. [18] performed one of the first studies that investigated visual processing in smokers. They investigated spatiotemporal processing in healthy subjects and smokers. The study was divided into two parts. In the first part, the authors investigated visual backward masking in smokers, deprived smokers, and healthy subjects. The results did not indicate significant differences, with the exception of a trend toward a decline in backward masking in deprived smokers. In the second part of the study, the authors divided data from the same tasks according to the age of the participants (i.e., younger and older adults). The results indicated that older adults exhibited a reduction in masking. The authors generally observed small effects of nicotine on spatiotemporal processing. One of the limitations of the study that was mentioned by the authors was the duration of cigarette deprivation (two hours), which can be too short to investigate the short- vs. long-term effects of smoking. In addition, the authors focused mainly on temporal aspects of visual processing, and their design did not allow for a strong test of spatial processing. This study is an extension of Fernandes et al. [19], who proposed to investigate spatial processing in smokers and nonsmokers, with a longer duration of cigarette deprivation. The authors compared groups of smokers, deprived smokers, and nonsmokers using a psychophysical task that assessed visual sensitivity. They observed a reduction of performance in the smoker group as whole. Fernandes et al. [19], however, used stimuli that emphasized spatial frequencies with linear sine-wave gratings in s a small sample. One may argue that linear sine-wave gratings may not provide a complete description of any complex waveform [61]. That is, on the one hand, the processing of spatial frequencies are based on the conventional dimensions of visual receptive fields. On the other hand, the processing of Gabor patches are based on the cells’ ‘‘performing” a Fourier analysis of a narrow range of any visual field rather than only a small part[26]. The local filtering of stimuli can encompass the stimulus at the receptive field level. Among the psychophysical methods of local assessment, Gabor patches have been widely used. Gabor patches (in the Gaussian envelope) allow pure sine and cosine waves to provide a complete and accurate description of any complex waveform [25]. To investigate the psychophysical mechanisms that underlie the perception of form in smokers, we evaluated visual sensitivity using constructed stimuli from Gabor patches [27,28]. Gabor patches closely match the receptive field properties of neurons [29,30] and are quite robust and reliable in terms of understanding the mechanisms of early-stage visual processing. In addition, the use of Gabor patches minimizes uncertainty in spatial position and spatial frequency detection. The present study also investigated whether visual processing is associated with clinical and cognitive variables. We hypothesized the existence of a reduction of the CSF and lower performance on cognitive tests. Our hypothesis was that chronic cigarette use affects the retinal-geniculate-striate system through the inhalation of toxic smoke or the absorption of toxic particles that are contained in cigarette smoke. The main purpose of our study was to use a rigorous and reliable psychophysical method to investigate the possible effects of cigarette smoking on the detection and discrimination of spatial stimuli using Gabor patches. The CSF and Gabor patches can be used as noninvasive tools to detect early-stage visual impairments and may help promote public policies to improve the quality of life of chronic smokers.
2. Materials and methods 2.1. Participants In the present study, 50 nonsmokers (mean age = 35.4 years; SD = 8.20 years; 23 males) and 48 smokers (mean age = 35.8 years; SD = 7.64 years; 29 males) who were staff or students at the Federal University of Paraiba were recruited through newspaper advertisements. The participants were 25–45 years old. They were excluded if they met any of the following exclusion criteria: <20 or >45 years old, current history of neurological disorder, cardiovascular disease, history of head trauma, history of contact with such substances as solvents, current or previous drug abuse, and current use of medications that may affect visual processing and cognition. Individuals who met the criteria for alcohol use disorder according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) [31]. Female participants who used oral contraceptives were only tested outside their menstrual period to minimize possible confounds associated with hormonal differences [33]. They were free of ocular diseases and had been examined by an ophthalmologist during the last 12 months. The subjects were required to have good ocular health, with no abnormalities on fundoscopic examination or optical coherence tomographic examination. All of the observers were screened for color blindness using Ishihara’s [25] test for color deficiency and had normal or corrected-to-normal (20/20) vision as determined by a Snellen chart. Both groups were matched for gender, age, and level of education. The subjects participated in the study on a voluntary basis. The participants in the healthy control group did not meet the criteria for specific Axis I or Axis II disorders according to the Structured Clinical Interview for the DSM (SCID) [31]. All of the smokers met the criteria for tobacco use disorder according to the DSM-5, currently smoked >20 cigarettes/day, and had a score >7 on the Fagerström Test for Nicotine Dependence (FTND) [34]. Smokers were allowed to smoke until the beginning of the experiment. Nonsmokers met the criteria for never-smokers (currently smoked <15 cigarettes per lifetime) [35]. The time since the last cigarette was assessed by self-report to equate withdrawal across smokers. To assess subjective craving for a cigarette, the smokers provided self-reports and completed psychometric measures, such as the Program to Aid Smokers (PAS) comfort scale [36] and the brief version of the Questionnaire of Smoking Urges (QSU-B) [37].
2.2. Stimuli and apparatus Stimuli for the CSF were Gabor patches with spatial frequencies of .2, 2.5, 5.0, 10.0, and 20.0 cycles per degree (cpd). Each subject was seated at a fixed viewing distance of 200 cm from the computer monitor to ensure that the retinal eccentricities were the same as for the Metropsiss standard. The Gabor patches were composed of vertical gratings in the cosine phase multiplied by a twodimensional spatial Gaussian envelope (for further details about the procedure and stimuli, see [27,38,39]). The Gabor patches were presented on the CRT monitor and subtended a visual angle of 4.2°.
2.3. Neuropsychological tests Flanker Task [40]. This task was used to evaluate attentional control and inhibition. Stimuli (letters, such as ZXYQ) were centrally presented and flanked by peripheral stimuli. We used reaction time as a measure of cognitive ability. A faster reaction time indicated better performance.
Please cite this article in press as: Fernandes TMP et al. Psychophysical evaluation of contrast sensitivity using Gabor patches in tobacco addiction. J Clin Neurosci (2018), https://doi.org/10.1016/j.jocn.2018.08.034
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Trail making test (TMT) [41]: This test was used to observe cognitive operations such as visual search, psychomotor speed, cognitive flexibility and sustained attention. A maximum time limit of 300 s was adopted. The measure used was the scoring errors for the whole test. The lower the number of errors, the better the participant’s performance. We used the B part of the test. Stroop color-word interference [42]: This test was used to measure executive function such as attention, cognitive flexibility, inhibition and information processing speed. A series of colour words was presented to the participant and their task was to name the colour of each word presented. We used four colours (red, blue, yellow and green) in several combinations randomly displayed on a computer screen. The measure was a number of elements properly named. The smaller the number of errors in the incongruence of the stimuli, the better the performance. 2.4. Procedure The procedures were performed in two stages. In the first stage, the participants were referred to our laboratory where we conducted the neuropsychological tasks. A specialist performed the tests. This procedure was performed in a quiet, comfortable, and reserved room; the approximate time was 45 min for each participant. In a second meeting, the participants performed the contrast sensitivity measurements. Each session of the second stage lasted from 30 min to 1 h, according to the participant. Regarding all of these procedures, the participants were encouraged to take breaks at their discretion to avoid fatigue. The two-alternative forced-choice method was used. The subjects’ task was to identify, using a remote control response box, whether the Gabor patches was presented on the left or right side of the monitor. The sinusoidal gratings are variations of luminance in a Cartesian plane. Only the contrast and spatial position are affected. Thus, the participants saw the stimuli, then were also instructed to respond whether they could not identify the stimuli. Metropsis uses a psychometric function that describes thresholds without interference from visual cues. The subjects were instructed to maintain fixation on a small black fixation cross in the center of the display monitor. The order of the spatial frequencies that were tested was randomized within a session. Higher contrast sensitivity values indicated that the participant presented higher sensitivity to the spatial frequency that was evaluated in the test (for procedural details, see [31,32]). To avoid fatigue, the participants were encouraged to take breaks at their discretion every time they completed a reversal for any spatial frequency.
Research of the Health Sciences Center of Federal University da Paraiba (CAAE: 60944816.3.0000.5188). Written informed consent was obtained from all of the participants. All of the experiments were performed in accordance with relevant guidelines and regulations. 3. Results 3.1. Sample characteristics The sample characteristics of both groups are summarized in Table 1. The groups did not differ with regard to age, level of education or the ratio of males to females. There were no differences between PAS and QSU-B scores before and after the experiment in the smokers group. 3.2. Contrast sensitivity function The results of the psychophysical measurements for contrast sensitivity are shown in Fig. 1. The repeated-measures analysis of variance indicated significant effects of spatial frequency (F4,340 = 1026.49, p < .001, g2 = .924) and group (F1,97 = 83.55, p < .001, g2 = .501) and a significant frequency group interaction (F4,340 = 66.86, p < .001, g2 = .440). The post hoc t-tests indicated a significant reduction of contrast sensitivity in smokers compared with nonsmokers (p < .001). Heavy smokers were less sensitive than healthy controls to spatial frequencies of .2 cpd (t96 = 9.852, p < .001, Cohen’s d = 5.33), 2.5 cpd (t96 = 14.730, p < .001, Cohen’s d = 7.95), 5.0 cpd (t96 = 10.991, p < .001, Cohen’s d = 3.21), 10.0 cpd (t96 = 6.827, p < .001, Cohen’s d = 2.06), and 20.0 cpd (t96 = 8.392, p < .001, Cohen’s d = 4.05). 3.3. Cognitive measures and visual performance Linear regression analyses were conducted to determine the effect of neuropsychological tests on visual performance. Separate correlation analyses for each group showed no significant predictors for visual processing were found in relation to other cognitive tests (Flanker, Stroop and Trail-Making). Regarding smokers’
Table 1 Sample characteristics of nonsmokers and smokers (N = 98). Variable
2.5. Statistical analysis
Gender Male Female Age Age, years (SD) Level of education, years (SD) Cigarette use Age at first use Years of use FTND score PAS Comfort Scale Before experiment After experiment QSU-B Before experiment After experiment Flanker task (seconds) Stroop (incongruent), seconds Trail-making Test-B
The statistical analyses were conducted using SPSS (Statistical Package for the Social Sciences) software, version 23. The distributions for each group were compared using the KolmogorovSmirnov test. Both groups presented a normal distribution; therefore, parametric statistical tests were used to analyze the data. For the CSF, each spatial frequency is considered individually as a dependent variable. However, to avoid the inflation of type 1 errors, values of p < .008 were considered statistically significant. Cohen’s d was used to assess effect sizes [43]. Linear regression analyses were performed to evaluate the relationships between clinical measures, cognitive performance, and contrast sensitivity between groups. The data are expressed as means and standard deviations (SDs). 2.6. Ethics statement The present study followed the ethical principles of the Declaration of Helsinki and was approved by the Committee of Ethics in
a b
Nonsmokers
Smokers
(n = 50)
(n = 48)
p
26 24
29 19
.445a .431a
35.4 (8.20) 13.7 (1.8)
35.8 (7.64) 10.2 (2.1)
.891b .344b
– – –
17 ± 1.2 16 ± 3.9 7 ± 1.4
– –
17.33 ± 1.8 17.44 ± .3
– –
23.55 ± 2.9 25.98 ± 2.1
2.15 (1.5) 1.26 (.05) 41.51 (12.01)
2.68 (2.3) 1.06 (.02) 50.31 (18.44)
.840#,b .794b .613b
v2 test. Student’s t-test.
Please cite this article in press as: Fernandes TMP et al. Psychophysical evaluation of contrast sensitivity using Gabor patches in tobacco addiction. J Clin Neurosci (2018), https://doi.org/10.1016/j.jocn.2018.08.034
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Fig 1. Contrast sensitivity curves as a function of spatial frequency (cpd) in nonsmokers and smokers. Each data point represents the mean sensitivity (reciprocal of contrast threshold), and error bars represent the standard deviation (SD) of mean sensitivity based on 1000 bootstrapping resamples. Data represents the measurements for Gabor patches.
groups, there were no statistically significant differences for the low [F = 1.684, p = .170, adjusted R2 = .052; b = .116, t = .481, p = 633], medium [F = 1.643, p = .180, adjusted R2 = .049; b = .244, t = 1.008, p = .319] and high [F = 1.184, p = .331, adjusted R2 = .014; b = .207, t = .840, p = .405] spatial frequencies.
4. Discussion The main purpose of the present study was to evaluate disturbances of the visual system in smokers and nonsmokers by measuring the CSF using Gabor patches and to investigate possible relationships between early visual processing and cognitive measures. We hypothesized that smokers would exhibit lower contrast sensitivity compared with nonsmokers. Our results corroborated this hypothesis, providing evidence that chronic cigarette use may be associated with impairments in visual processing. To our knowledge, this is the first study that utilized Gabor patches to detect spatial stimuli in smokers. Although the magnitude and specificity of impairments in the magnocellular (M), parvocellular (P), and koniocellular (K) pathways rely exclusively on photopic, mesopic, or scotopic luminance conditions [44–46], several studies that used the CSF erroneously concluded that impairments that are found at certain spatial frequencies are associated with these pathways. The literature indicates that the use of such these explanations serve as a theoretical basis for the operation of visual processing [22]. The M, P, and K pathways are responsible for transmitting specific visual information from the retina to the visual cortex, and it is necessary to understand the specific roles of each of these pathways separately [38,44]. However, the present discussion focuses on aspects that are related to photopic luminance or processing of the P and K pathways, such as cones and rods. Considering the neuronal selectivity of the human visual system, the M pathway presents high responsiveness to stimuli with low spatial frequencies, whereas the P pathway responds more to medium and high spatial frequencies [23,47,48]. Under conditions that affect the central nervous system, such as smoking, both pathways may exhibit dysfunction because of an imbalance of neurotransmitters [16–18]. For example, dopaminergic hypofunction that is caused by an imbalance of cortical upregulation may increase functional antagonism between the center and periphery of the receptive field of bipolar cells. The reverse may also be true, in which dopamine hyperfunc-
tion may decrease receptive fields of bipolar cells. Under lightadapted conditions, D1 dopamine receptors are able to either decrease or increase the size of the receptive field. Thus, dopamine hyper- of hypofunction may involve changes that are related to spatial vision. Thus, abnormalities in these pathways may cause direct losses of the perception of stimuli at specific spatial or temporal frequencies [49,50]. The physiological mechanisms that are involved in visual processing deserve attention. The ability to detect and interpret details of a visual scene is determined by the ability of the visual system to distinguish contrast patterns [51]. Contrast can also be understood as the physical property of the visual stimulus (i.e., the magnitude of luminance variation in the stimulus related to the total luminance of adjacent areas) [52,53]. Changes in the luminance of the environment can create contrast patterns that describe most of the visual information to the observer [54,55]. The CSF is a basic reflection of input to V1, reflecting optics and receptive field structure [55]. The CSF provides the threshold between the visible and invisible [56]. In the present study, we measured the CSF under equivalent experimental conditions. A greater CSF curve is associated with better discrimination. We observed lower contrast sensitivity in smokers at all spatial frequencies (Fig. 1). Studies indicate that cigarette smoking affects retinal properties through nicotinic acetylcholine receptors [57,58] that are also expressed in the thalamus, basal ganglia, cerebral cortex, hippocampus, cerebellum, and occipital cortex. Chronic cigarette use reduces the overall activation of the visual system [58]. The present study did not intend to assess causal relationships. Nonetheless, our findings provide new insights that may aid future studies with larger samples. We are unable to provide a physiological explanation for the present results, mainly regarding M, P and K pathways, but tobacco use disorder may play a role in visual sensitivity deficits through the actions of its toxic pharmacological constituents and an imbalance of neurotransmitters [13,59]. Neurotransmission is present in the retina, the impairment of which may begin in cones or rods (e.g., bipolar, amacrine, or ganglion cells) and negatively impact the visual processing of spatial stimuli. The present results confirm and extend findings that showed impairments in visual processing in smokers. Our results confirm our previous study [59]. The present study utilized Gabor patches to closely observe the relationship between early-stage visual processing and tobacco use disorder. Gabor patches may generally allow a more accurate description of spatial processing. Considering the homogeneity of our sample, the results suggest that the observed differences can be attributable to the independent variable, namely, smoking. However, it is possible that another variable, one associated with a predisposition to smoking, could be driving the results. Future studies that examine the extent to which smoking vs. characteristics of people who smoke are related to visual processing differences are needed. In addition, the issue of visual processing and smoking needs to be investigated with a wider range of behavioral, electrophysiological, and imaging techniques, to more fully establish the effects of smoking on visual function, and these effects over time. The use of the CSF as a potential noninvasive method of visual processing assessment may have direct application in clinical practice. The CSF could allow the early detection of visual deficits, and detecting such changes early may be beneficial for the studied population. In conclusion, the present psychophysical findings indicate that heavy long-term smokers have lower contrast sensitivity and poorer color discrimination abilities than their non-smoking peers. These data have implications for extending our understanding of the detrimental effects of smoking. In addition, they suggest that research into visual processing impairments (e.g., reduced contrast
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sensitivity) in clinical populations, such as schizophrenia, that are associated with both increased smoking [59,60] and impaired visual processing [61] needs to control for smoking rate or to independently examine smokers vs. non-smokers with the disorder in question. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Contributors TMP conceived and designed the experiments, participated in its coordination, and helped draft the manuscript. SMS helped draft the manuscript, and helped interpret the data. NLA performed the statistical analysis and interpreted the data. NA conceived and designed the experiments, helped draft the manuscript, and helped interpret the data. Role of the funding source The National Council for Scientific and Technological Development (CNPq), Brazil (309778/2014-0), supported this study. Acknowledgements We appreciate the participants who gave their time for this research. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.jocn.2018.08.034. References [1] Chanon VW, Sours CR, Boettiger CA. Attentional bias toward cigarette cues in active smokers. Psychopharmacology 2010;212:309–20. https://doi.org/ 10.1007/s00213-010-1953-1. [2] Waters AJ, Shiffman S, Sayette MA, Paty JA, Gwaltney CJ, Balabanis MH. Attentional Bias Predicts Outcome in Smoking Cessation. Health Psychol Off J Div Health Psychol Am Psychol Assoc. 2003;22:378–87. https://doi.org/ 10.1037/0278-6133.22.4.378. [3] Besson M, Granon S, Mameli-Engvall M, Cloëz-Tayarani I, Maubourguet N, Cormier A, et al. Long-term effects of chronic nicotine exposure on brain nicotinic receptors. Proc Natl Acad Sci 2007;104:8155–60. https://doi.org/ 10.1073/pnas.0702698104. [4] WHO. WHO REPORT ON THE GLOBAL TOBACCO EPIDEMIC, 2013 [Internet]. 2013. Available: http://apps.who.int/iris/bitstream/10665/85380/1/ 9789241505871_eng.pdf [5] WHO WH. WHO report on the global tobacco epidemic, 2015: Raising taxes on tobacco [Internet]. 201Available: http://escholarship.org/uc/item/1fh1f32m [6] Durazzo TC, Meyerhoff DJ, Nixon SJ. Chronic Cigarette Smoking: Implications for Neurocognition and Brain Neurobiology. Int J Environ Res Public Health 2010;7:3760–91. https://doi.org/10.3390/ijerph7103760. [7] D’Souza MS, Markou A. Neuronal Mechanisms Underlying Development of Nicotine Dependence: Implications for Novel Smoking-Cessation Treatments. Addict Sci Clin Pract. 2011;6:4–16. [8] Karama S, Ducharme S, Corley J, Chouinard-Decorte F, Starr JM, Wardlaw JM, et al. Cigarette smoking and thinning of the brain’s cortex. Mol Psychiatry 2015;20:778–85. https://doi.org/10.1038/mp.2014.187. [9] Xu J, Mendrek A, Cohen MS, Monterosso J, Simon S, Jarvik M, et al. Effect of Cigarette Smoking on Prefrontal Cortical Function in Nondeprived Smokers Performing the Stroop Task. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol. 2007;32:1421–8. https://doi.org/10.1038/sj. npp.1301272. [10] Zhou S, Xiao D, Peng P, Wang S-K, Liu Z, Qin H-Y, et al. Effect of smoking on resting-state functional connectivity in smokers: An fMRI study. Respirol Carlton Vic. 2017. https://doi.org/10.1111/resp.13048.
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Clinical study
Psychophysical evaluation of contrast sensitivity using Gabor patches in tobacco addiction Thiago Monteiro Paiva Fernandes a, Steven M. Silverstein b, Natalia Leandro de Almeida a,⇑, Natanael Antonio dos Santos a a b
Federal University of Paraiba, Joao Pessoa, Brazil Rutgers University Behavioral Health Care, Piscataway, NJ, USA
a r t i c l e
i n f o
Article history: Received 19 April 2018 Accepted 13 August 2018 Available online xxxx Keywords: Psychophysics Cigarette smoking Smoking Visual perception
a b s t r a c t This study, an extension of Fernandes et al. (2017), provided consistent contrast sensitivity function (CSF) measurements in a large sample. CSF was assessed for luminance stimuli in different 48 chronic smokers and 50 healthy nonsmokers. Stimuli for the CSF were Gabor patches with spatial frequencies of .2, 2.5, 5.0, 10.0, and 20.0 cycles per degree (cpd). The use of Gabor patches minimizes uncertainty in spatial position and detection of frequencies. The Gabor patches consisted of vertical gratings that were multiplied by a two-dimensional spatial Gaussian envelope. All of the groups were matched for gender and level of education. All of the participants were free from any neurological disorder, cardiovascular disease, and identifiable ocular disease, and they had normal or corrected-to-normal visual acuity. No abnormalities were detected on the fundoscopic examination or optical coherence tomographic examination. The smoker group had a lower CSF compared with healthy nonsmokers at all spatial frequencies. These results indicate that cigarette smoking or chronic exposure to its constituent compounds affects early-stage visual discrimination, suggesting the existence of deficits in early visual spatial processing in smokers. Ó 2018 Elsevier Ltd. All rights reserved.
1. Introduction Addictive behaviors comprise diverse conditions that are classified by the urge to use or be exposed to an addictive agent [1]. Repeated exposure to these agents may induce long-lasting cortical changes that result in tolerance, craving, or withdrawal [2,3]. Chronic cigarette smoking is one such addictive behavior and a public health priority worldwide. Data from the World Health Organization indicate that cigarettes will kill more than 5 million people by 2030 [4,5]. Tobacco smoke consists of several compounds that are harmful to individuals through either chronic use or toxic smoke inhalation [1,6]. The effects of smoking on cognition have been investigated using neuroimaging [7–9] and electrophysiology [10–12]. Numerous compounds that are contained in cigarette smoke may cause abnormalities in cortical wiring that can cause cognitive decline and dementia [13,14]. Cigarette smoking has been linked to brain atrophy through cortical thinning, with the involvement of such areas as the medial and lateral frontal cortex and a decrease in ⇑ Corresponding author.
activity of the occipital cortex [15,16]. Several studies have investigated the effects of cigarette smoking on cognitive function, but few have evaluated the effects of cigarette smoking on earlystage visual processing [17,18]. This field of study still has gaps in the literature with regard to the ways in which smoking affects the perception of form. As an embryonic extension of the brain, the retina may be one of the most studied regions of the central nervous system because of its easily accessible anatomical position [19,20]. The retina allows noninvasive investigations of visual processing. Several types of measurements have been developed to characterize visual processing, such as visual acuity and the contrast sensitivity function (CSF) [21]. The perception of form is one of the first stages of cognition and one of the first analyses that is performed by the retina-geniculate-striate system [22,23]. Our visual system is able to integrate local features to form a rich perception of spatial and temporal patterns, despite the fact that visual information is discretely sampled by the retina-geniculate-striate system [24]. The assumption that underlies the CSF is that the human visual system decomposes complex stimuli into elemental stimuli that are characterized by low spatial frequencies (i.e., the detection of large objects and the blurring of images), medium spatial frequencies
E-mail address: [email protected] (N.L.d. Almeida). https://doi.org/10.1016/j.jocn.2018.08.034 0967-5868/Ó 2018 Elsevier Ltd. All rights reserved.
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(i.e., the first impression of an image), and high spatial frequencies (i.e., the detection of fine details of an image) [21,22]. The retinageniculate-striate pathway processes stimuli in the environment, and these stimuli may provide a description of the way in which the central nervous system can be impaired. Kunchulia et al. [18] performed one of the first studies that investigated visual processing in smokers. They investigated spatiotemporal processing in healthy subjects and smokers. The study was divided into two parts. In the first part, the authors investigated visual backward masking in smokers, deprived smokers, and healthy subjects. The results did not indicate significant differences, with the exception of a trend toward a decline in backward masking in deprived smokers. In the second part of the study, the authors divided data from the same tasks according to the age of the participants (i.e., younger and older adults). The results indicated that older adults exhibited a reduction in masking. The authors generally observed small effects of nicotine on spatiotemporal processing. One of the limitations of the study that was mentioned by the authors was the duration of cigarette deprivation (two hours), which can be too short to investigate the short- vs. long-term effects of smoking. In addition, the authors focused mainly on temporal aspects of visual processing, and their design did not allow for a strong test of spatial processing. This study is an extension of Fernandes et al. [19], who proposed to investigate spatial processing in smokers and nonsmokers, with a longer duration of cigarette deprivation. The authors compared groups of smokers, deprived smokers, and nonsmokers using a psychophysical task that assessed visual sensitivity. They observed a reduction of performance in the smoker group as whole. Fernandes et al. [19], however, used stimuli that emphasized spatial frequencies with linear sine-wave gratings in s a small sample. One may argue that linear sine-wave gratings may not provide a complete description of any complex waveform [61]. That is, on the one hand, the processing of spatial frequencies are based on the conventional dimensions of visual receptive fields. On the other hand, the processing of Gabor patches are based on the cells’ ‘‘performing” a Fourier analysis of a narrow range of any visual field rather than only a small part[26]. The local filtering of stimuli can encompass the stimulus at the receptive field level. Among the psychophysical methods of local assessment, Gabor patches have been widely used. Gabor patches (in the Gaussian envelope) allow pure sine and cosine waves to provide a complete and accurate description of any complex waveform [25]. To investigate the psychophysical mechanisms that underlie the perception of form in smokers, we evaluated visual sensitivity using constructed stimuli from Gabor patches [27,28]. Gabor patches closely match the receptive field properties of neurons [29,30] and are quite robust and reliable in terms of understanding the mechanisms of early-stage visual processing. In addition, the use of Gabor patches minimizes uncertainty in spatial position and spatial frequency detection. The present study also investigated whether visual processing is associated with clinical and cognitive variables. We hypothesized the existence of a reduction of the CSF and lower performance on cognitive tests. Our hypothesis was that chronic cigarette use affects the retinal-geniculate-striate system through the inhalation of toxic smoke or the absorption of toxic particles that are contained in cigarette smoke. The main purpose of our study was to use a rigorous and reliable psychophysical method to investigate the possible effects of cigarette smoking on the detection and discrimination of spatial stimuli using Gabor patches. The CSF and Gabor patches can be used as noninvasive tools to detect early-stage visual impairments and may help promote public policies to improve the quality of life of chronic smokers.
2. Materials and methods 2.1. Participants In the present study, 50 nonsmokers (mean age = 35.4 years; SD = 8.20 years; 23 males) and 48 smokers (mean age = 35.8 years; SD = 7.64 years; 29 males) who were staff or students at the Federal University of Paraiba were recruited through newspaper advertisements. The participants were 25–45 years old. They were excluded if they met any of the following exclusion criteria: <20 or >45 years old, current history of neurological disorder, cardiovascular disease, history of head trauma, history of contact with such substances as solvents, current or previous drug abuse, and current use of medications that may affect visual processing and cognition. Individuals who met the criteria for alcohol use disorder according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) [31]. Female participants who used oral contraceptives were only tested outside their menstrual period to minimize possible confounds associated with hormonal differences [33]. They were free of ocular diseases and had been examined by an ophthalmologist during the last 12 months. The subjects were required to have good ocular health, with no abnormalities on fundoscopic examination or optical coherence tomographic examination. All of the observers were screened for color blindness using Ishihara’s [25] test for color deficiency and had normal or corrected-to-normal (20/20) vision as determined by a Snellen chart. Both groups were matched for gender, age, and level of education. The subjects participated in the study on a voluntary basis. The participants in the healthy control group did not meet the criteria for specific Axis I or Axis II disorders according to the Structured Clinical Interview for the DSM (SCID) [31]. All of the smokers met the criteria for tobacco use disorder according to the DSM-5, currently smoked >20 cigarettes/day, and had a score >7 on the Fagerström Test for Nicotine Dependence (FTND) [34]. Smokers were allowed to smoke until the beginning of the experiment. Nonsmokers met the criteria for never-smokers (currently smoked <15 cigarettes per lifetime) [35]. The time since the last cigarette was assessed by self-report to equate withdrawal across smokers. To assess subjective craving for a cigarette, the smokers provided self-reports and completed psychometric measures, such as the Program to Aid Smokers (PAS) comfort scale [36] and the brief version of the Questionnaire of Smoking Urges (QSU-B) [37].
2.2. Stimuli and apparatus Stimuli for the CSF were Gabor patches with spatial frequencies of .2, 2.5, 5.0, 10.0, and 20.0 cycles per degree (cpd). Each subject was seated at a fixed viewing distance of 200 cm from the computer monitor to ensure that the retinal eccentricities were the same as for the Metropsiss standard. The Gabor patches were composed of vertical gratings in the cosine phase multiplied by a twodimensional spatial Gaussian envelope (for further details about the procedure and stimuli, see [27,38,39]). The Gabor patches were presented on the CRT monitor and subtended a visual angle of 4.2°.
2.3. Neuropsychological tests Flanker Task [40]. This task was used to evaluate attentional control and inhibition. Stimuli (letters, such as ZXYQ) were centrally presented and flanked by peripheral stimuli. We used reaction time as a measure of cognitive ability. A faster reaction time indicated better performance.
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Trail making test (TMT) [41]: This test was used to observe cognitive operations such as visual search, psychomotor speed, cognitive flexibility and sustained attention. A maximum time limit of 300 s was adopted. The measure used was the scoring errors for the whole test. The lower the number of errors, the better the participant’s performance. We used the B part of the test. Stroop color-word interference [42]: This test was used to measure executive function such as attention, cognitive flexibility, inhibition and information processing speed. A series of colour words was presented to the participant and their task was to name the colour of each word presented. We used four colours (red, blue, yellow and green) in several combinations randomly displayed on a computer screen. The measure was a number of elements properly named. The smaller the number of errors in the incongruence of the stimuli, the better the performance. 2.4. Procedure The procedures were performed in two stages. In the first stage, the participants were referred to our laboratory where we conducted the neuropsychological tasks. A specialist performed the tests. This procedure was performed in a quiet, comfortable, and reserved room; the approximate time was 45 min for each participant. In a second meeting, the participants performed the contrast sensitivity measurements. Each session of the second stage lasted from 30 min to 1 h, according to the participant. Regarding all of these procedures, the participants were encouraged to take breaks at their discretion to avoid fatigue. The two-alternative forced-choice method was used. The subjects’ task was to identify, using a remote control response box, whether the Gabor patches was presented on the left or right side of the monitor. The sinusoidal gratings are variations of luminance in a Cartesian plane. Only the contrast and spatial position are affected. Thus, the participants saw the stimuli, then were also instructed to respond whether they could not identify the stimuli. Metropsis uses a psychometric function that describes thresholds without interference from visual cues. The subjects were instructed to maintain fixation on a small black fixation cross in the center of the display monitor. The order of the spatial frequencies that were tested was randomized within a session. Higher contrast sensitivity values indicated that the participant presented higher sensitivity to the spatial frequency that was evaluated in the test (for procedural details, see [31,32]). To avoid fatigue, the participants were encouraged to take breaks at their discretion every time they completed a reversal for any spatial frequency.
Research of the Health Sciences Center of Federal University da Paraiba (CAAE: 60944816.3.0000.5188). Written informed consent was obtained from all of the participants. All of the experiments were performed in accordance with relevant guidelines and regulations. 3. Results 3.1. Sample characteristics The sample characteristics of both groups are summarized in Table 1. The groups did not differ with regard to age, level of education or the ratio of males to females. There were no differences between PAS and QSU-B scores before and after the experiment in the smokers group. 3.2. Contrast sensitivity function The results of the psychophysical measurements for contrast sensitivity are shown in Fig. 1. The repeated-measures analysis of variance indicated significant effects of spatial frequency (F4,340 = 1026.49, p < .001, g2 = .924) and group (F1,97 = 83.55, p < .001, g2 = .501) and a significant frequency group interaction (F4,340 = 66.86, p < .001, g2 = .440). The post hoc t-tests indicated a significant reduction of contrast sensitivity in smokers compared with nonsmokers (p < .001). Heavy smokers were less sensitive than healthy controls to spatial frequencies of .2 cpd (t96 = 9.852, p < .001, Cohen’s d = 5.33), 2.5 cpd (t96 = 14.730, p < .001, Cohen’s d = 7.95), 5.0 cpd (t96 = 10.991, p < .001, Cohen’s d = 3.21), 10.0 cpd (t96 = 6.827, p < .001, Cohen’s d = 2.06), and 20.0 cpd (t96 = 8.392, p < .001, Cohen’s d = 4.05). 3.3. Cognitive measures and visual performance Linear regression analyses were conducted to determine the effect of neuropsychological tests on visual performance. Separate correlation analyses for each group showed no significant predictors for visual processing were found in relation to other cognitive tests (Flanker, Stroop and Trail-Making). Regarding smokers’
Table 1 Sample characteristics of nonsmokers and smokers (N = 98). Variable
2.5. Statistical analysis
Gender Male Female Age Age, years (SD) Level of education, years (SD) Cigarette use Age at first use Years of use FTND score PAS Comfort Scale Before experiment After experiment QSU-B Before experiment After experiment Flanker task (seconds) Stroop (incongruent), seconds Trail-making Test-B
The statistical analyses were conducted using SPSS (Statistical Package for the Social Sciences) software, version 23. The distributions for each group were compared using the KolmogorovSmirnov test. Both groups presented a normal distribution; therefore, parametric statistical tests were used to analyze the data. For the CSF, each spatial frequency is considered individually as a dependent variable. However, to avoid the inflation of type 1 errors, values of p < .008 were considered statistically significant. Cohen’s d was used to assess effect sizes [43]. Linear regression analyses were performed to evaluate the relationships between clinical measures, cognitive performance, and contrast sensitivity between groups. The data are expressed as means and standard deviations (SDs). 2.6. Ethics statement The present study followed the ethical principles of the Declaration of Helsinki and was approved by the Committee of Ethics in
a b
Nonsmokers
Smokers
(n = 50)
(n = 48)
p
26 24
29 19
.445a .431a
35.4 (8.20) 13.7 (1.8)
35.8 (7.64) 10.2 (2.1)
.891b .344b
– – –
17 ± 1.2 16 ± 3.9 7 ± 1.4
– –
17.33 ± 1.8 17.44 ± .3
– –
23.55 ± 2.9 25.98 ± 2.1
2.15 (1.5) 1.26 (.05) 41.51 (12.01)
2.68 (2.3) 1.06 (.02) 50.31 (18.44)
.840#,b .794b .613b
v2 test. Student’s t-test.
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Fig 1. Contrast sensitivity curves as a function of spatial frequency (cpd) in nonsmokers and smokers. Each data point represents the mean sensitivity (reciprocal of contrast threshold), and error bars represent the standard deviation (SD) of mean sensitivity based on 1000 bootstrapping resamples. Data represents the measurements for Gabor patches.
groups, there were no statistically significant differences for the low [F = 1.684, p = .170, adjusted R2 = .052; b = .116, t = .481, p = 633], medium [F = 1.643, p = .180, adjusted R2 = .049; b = .244, t = 1.008, p = .319] and high [F = 1.184, p = .331, adjusted R2 = .014; b = .207, t = .840, p = .405] spatial frequencies.
4. Discussion The main purpose of the present study was to evaluate disturbances of the visual system in smokers and nonsmokers by measuring the CSF using Gabor patches and to investigate possible relationships between early visual processing and cognitive measures. We hypothesized that smokers would exhibit lower contrast sensitivity compared with nonsmokers. Our results corroborated this hypothesis, providing evidence that chronic cigarette use may be associated with impairments in visual processing. To our knowledge, this is the first study that utilized Gabor patches to detect spatial stimuli in smokers. Although the magnitude and specificity of impairments in the magnocellular (M), parvocellular (P), and koniocellular (K) pathways rely exclusively on photopic, mesopic, or scotopic luminance conditions [44–46], several studies that used the CSF erroneously concluded that impairments that are found at certain spatial frequencies are associated with these pathways. The literature indicates that the use of such these explanations serve as a theoretical basis for the operation of visual processing [22]. The M, P, and K pathways are responsible for transmitting specific visual information from the retina to the visual cortex, and it is necessary to understand the specific roles of each of these pathways separately [38,44]. However, the present discussion focuses on aspects that are related to photopic luminance or processing of the P and K pathways, such as cones and rods. Considering the neuronal selectivity of the human visual system, the M pathway presents high responsiveness to stimuli with low spatial frequencies, whereas the P pathway responds more to medium and high spatial frequencies [23,47,48]. Under conditions that affect the central nervous system, such as smoking, both pathways may exhibit dysfunction because of an imbalance of neurotransmitters [16–18]. For example, dopaminergic hypofunction that is caused by an imbalance of cortical upregulation may increase functional antagonism between the center and periphery of the receptive field of bipolar cells. The reverse may also be true, in which dopamine hyperfunc-
tion may decrease receptive fields of bipolar cells. Under lightadapted conditions, D1 dopamine receptors are able to either decrease or increase the size of the receptive field. Thus, dopamine hyper- of hypofunction may involve changes that are related to spatial vision. Thus, abnormalities in these pathways may cause direct losses of the perception of stimuli at specific spatial or temporal frequencies [49,50]. The physiological mechanisms that are involved in visual processing deserve attention. The ability to detect and interpret details of a visual scene is determined by the ability of the visual system to distinguish contrast patterns [51]. Contrast can also be understood as the physical property of the visual stimulus (i.e., the magnitude of luminance variation in the stimulus related to the total luminance of adjacent areas) [52,53]. Changes in the luminance of the environment can create contrast patterns that describe most of the visual information to the observer [54,55]. The CSF is a basic reflection of input to V1, reflecting optics and receptive field structure [55]. The CSF provides the threshold between the visible and invisible [56]. In the present study, we measured the CSF under equivalent experimental conditions. A greater CSF curve is associated with better discrimination. We observed lower contrast sensitivity in smokers at all spatial frequencies (Fig. 1). Studies indicate that cigarette smoking affects retinal properties through nicotinic acetylcholine receptors [57,58] that are also expressed in the thalamus, basal ganglia, cerebral cortex, hippocampus, cerebellum, and occipital cortex. Chronic cigarette use reduces the overall activation of the visual system [58]. The present study did not intend to assess causal relationships. Nonetheless, our findings provide new insights that may aid future studies with larger samples. We are unable to provide a physiological explanation for the present results, mainly regarding M, P and K pathways, but tobacco use disorder may play a role in visual sensitivity deficits through the actions of its toxic pharmacological constituents and an imbalance of neurotransmitters [13,59]. Neurotransmission is present in the retina, the impairment of which may begin in cones or rods (e.g., bipolar, amacrine, or ganglion cells) and negatively impact the visual processing of spatial stimuli. The present results confirm and extend findings that showed impairments in visual processing in smokers. Our results confirm our previous study [59]. The present study utilized Gabor patches to closely observe the relationship between early-stage visual processing and tobacco use disorder. Gabor patches may generally allow a more accurate description of spatial processing. Considering the homogeneity of our sample, the results suggest that the observed differences can be attributable to the independent variable, namely, smoking. However, it is possible that another variable, one associated with a predisposition to smoking, could be driving the results. Future studies that examine the extent to which smoking vs. characteristics of people who smoke are related to visual processing differences are needed. In addition, the issue of visual processing and smoking needs to be investigated with a wider range of behavioral, electrophysiological, and imaging techniques, to more fully establish the effects of smoking on visual function, and these effects over time. The use of the CSF as a potential noninvasive method of visual processing assessment may have direct application in clinical practice. The CSF could allow the early detection of visual deficits, and detecting such changes early may be beneficial for the studied population. In conclusion, the present psychophysical findings indicate that heavy long-term smokers have lower contrast sensitivity and poorer color discrimination abilities than their non-smoking peers. These data have implications for extending our understanding of the detrimental effects of smoking. In addition, they suggest that research into visual processing impairments (e.g., reduced contrast
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sensitivity) in clinical populations, such as schizophrenia, that are associated with both increased smoking [59,60] and impaired visual processing [61] needs to control for smoking rate or to independently examine smokers vs. non-smokers with the disorder in question. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Contributors TMP conceived and designed the experiments, participated in its coordination, and helped draft the manuscript. SMS helped draft the manuscript, and helped interpret the data. NLA performed the statistical analysis and interpreted the data. NA conceived and designed the experiments, helped draft the manuscript, and helped interpret the data. Role of the funding source The National Council for Scientific and Technological Development (CNPq), Brazil (309778/2014-0), supported this study. Acknowledgements We appreciate the participants who gave their time for this research. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.jocn.2018.08.034. References [1] Chanon VW, Sours CR, Boettiger CA. Attentional bias toward cigarette cues in active smokers. Psychopharmacology 2010;212:309–20. https://doi.org/ 10.1007/s00213-010-1953-1. [2] Waters AJ, Shiffman S, Sayette MA, Paty JA, Gwaltney CJ, Balabanis MH. Attentional Bias Predicts Outcome in Smoking Cessation. Health Psychol Off J Div Health Psychol Am Psychol Assoc. 2003;22:378–87. https://doi.org/ 10.1037/0278-6133.22.4.378. [3] Besson M, Granon S, Mameli-Engvall M, Cloëz-Tayarani I, Maubourguet N, Cormier A, et al. Long-term effects of chronic nicotine exposure on brain nicotinic receptors. Proc Natl Acad Sci 2007;104:8155–60. https://doi.org/ 10.1073/pnas.0702698104. [4] WHO. WHO REPORT ON THE GLOBAL TOBACCO EPIDEMIC, 2013 [Internet]. 2013. Available: http://apps.who.int/iris/bitstream/10665/85380/1/ 9789241505871_eng.pdf [5] WHO WH. WHO report on the global tobacco epidemic, 2015: Raising taxes on tobacco [Internet]. 201Available: http://escholarship.org/uc/item/1fh1f32m [6] Durazzo TC, Meyerhoff DJ, Nixon SJ. Chronic Cigarette Smoking: Implications for Neurocognition and Brain Neurobiology. Int J Environ Res Public Health 2010;7:3760–91. https://doi.org/10.3390/ijerph7103760. [7] D’Souza MS, Markou A. Neuronal Mechanisms Underlying Development of Nicotine Dependence: Implications for Novel Smoking-Cessation Treatments. Addict Sci Clin Pract. 2011;6:4–16. [8] Karama S, Ducharme S, Corley J, Chouinard-Decorte F, Starr JM, Wardlaw JM, et al. Cigarette smoking and thinning of the brain’s cortex. Mol Psychiatry 2015;20:778–85. https://doi.org/10.1038/mp.2014.187. [9] Xu J, Mendrek A, Cohen MS, Monterosso J, Simon S, Jarvik M, et al. Effect of Cigarette Smoking on Prefrontal Cortical Function in Nondeprived Smokers Performing the Stroop Task. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol. 2007;32:1421–8. https://doi.org/10.1038/sj. npp.1301272. [10] Zhou S, Xiao D, Peng P, Wang S-K, Liu Z, Qin H-Y, et al. Effect of smoking on resting-state functional connectivity in smokers: An fMRI study. Respirol Carlton Vic. 2017. https://doi.org/10.1111/resp.13048.
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Please cite this article in press as: Fernandes TMP et al. Psychophysical evaluation of contrast sensitivity using Gabor patches in tobacco addiction. J Clin Neurosci (2018), https://doi.org/10.1016/j.jocn.2018.08.034