Neurol Sci (2015) 36:391–395 DOI 10.1007/s10072-014-1962-7
ORIGINAL ARTICLE
Lack of habituation of evoked visual potentials in analytic information processing style: evidence in healthy subjects Marzia Buonfiglio • M. Toscano • F. Puledda • G. Avanzini • L. Di Clemente • F. Di Sabato • V. Di Piero
Received: 23 April 2014 / Accepted: 19 September 2014 / Published online: 27 September 2014 Springer-Verlag Italia 2014
Abstract Habituation is considered one of the most basic mechanisms of learning. Habituation deficit to several sensory stimulations has been defined as a trait of migraine brain and also observed in other disorders. On the other hand, analytic information processing style is characterized by the habit of continually evaluating stimuli and it has been associated with migraine. We investigated a possible correlation between lack of habituation of evoked visual potentials and analytic cognitive style in healthy subjects. According to Sternberg–Wagner self-assessment inventory, 15 healthy volunteers (HV) with high analytic score and 15 HV with high global score were recruited. Both groups underwent visual evoked potentials recordings after psychological evaluation. We observed significant lack of habituation in analytical individuals compared to global group. In conclusion, a reduced habituation of visual evoked potentials has been observed in analytic subjects. Our results suggest that further research should be
M. Buonfiglio (&) F. Di Sabato Department of Clinical Medicine, ‘‘Sapienza’’ University of Rome, Policlinico Umberto I, Viale del Policlinico 155, 00161 Rome, Italy e-mail: [email protected] M. Toscano Department of Psychology, ‘‘Sapienza’’ University of Rome, Rome, Italy F. Puledda L. Di Clemente V. Di Piero Department of Neurology and Psychiatry, ‘‘Sapienza’’ University of Rome, Rome, Italy G. Avanzini Department of Neurophysiology, IRCCS Foundation Neurological Institute ‘‘Carlo Besta’’, Milan, Italy
undertaken regarding the relationship between analytic cognitive style and lack of habituation in both physiological and pathophysiological conditions. Keywords Lack of habituation Evoked visual potentials Analytic information processing style Sternberg–Wagner self-assessment inventory Healthy subjects
Introduction Habituation of neural evoked activity is an ubiquitous phenomenon, a processing modality of sensorial stimuli primarily defined by a ‘‘response decrement as a result of repeated stimulations’’ [1]. It is a compensatory mechanism for lactate accumulation in cerebral cortex, thus protecting a normally functioning brain from sensory overload [2, 3]. At a neurophysiological level, a lack of habituation means that the decrease in response after repetitive sensorial stimulations is reduced or absent [4]. Over the years the parametric properties of this phenomenon were revised [5]. Habituation deficit to several sensory stimulations has been highlighted in migraine [3, 6, 7]. It has been defined as a characteristic of the migraine brain, and shows a familial trait [8]. Noteworthy, habituation deficit fluctuates in relation to migraine cycle, being most pronounced interictally and normalizing during attack [3]. Moreover, lack of habituation was also observed with various stimulus modalities in other disorders [9–13]. The cause of this abnormality is still matter of debate [14] and it was hypothesized that it leads to high brain activation and energy demand [3]. Habituation mechanism is considered extremely useful for studying the mechanism of learning processes [3].
123
392
It has been suggested that impaired visual habituation may disrupt sustained attention via inability to modulate the repeated intrusion of irrelevant stimuli and it may explain clinical symptoms associated with adult attention deficit disorders [15]. However, an habituation variability can also be expected in healthy subjects, depending on a series of parametric properties or characteristics and on a rich collection of cellular mechanisms that are differentially recruited in different parts of the nervous system and by different stimulus paradigms [16]. Analytic information processing style is a specific cognitive behavior characterized by high activation of attention and continuous evaluation of stimuli [17–19]. It is an habitual and favorite way of perceiving incoming information and can be present from childhood [17, 18, 20]. A correlation between this cognitive style and migraine has been earlier observed [18]. Moreover, the neurophysiological correlates of cognitive styles have been previously highlighted by eventrelated potentials (ERP) [21, 22]. However, to our knowledge, no previous works have explored a possible link between the habituation response and analytic information processing style, which is the aim of the present study. We investigated this issue on a sample of 30 healthy subjects.
Materials and methods Subjects From a consecutive series of healthy volunteers taken from the personnel working in our department, we selected 15 healthy subjects aged 20–60 scoring higher in analytic cognitive style, that were attributed to group AN (Analytical) according to Sternberg test instructions [17] and 15 subjects that scored higher in global cognitive style, defined as group GL (Global). AN group was composed of 12 females and 3 males, while GL group of eight females and seven males. Mean age of AN group was 40.3 ± 8.9 while mean age of GL group was 44.1 ± 11.7. The volunteers had no first degree relatives suffering from recurrent headache or any other neurologic, psychiatric or chronic disorders. Subjects were not affected by any disease and had not taken drugs on a regular basis for at least 3 months before the recording took place. Physical examination was normal. Written informed consent was obtained from all participants in the study. The study was approved by the ethics committee of Policlinico Umberto I, Sapienza University of Rome.
123
Neurol Sci (2015) 36:391–395
Psychological evaluation The instruments used to gather psychological data for the study consisted in: – –
A clinical psychological diagnostic interview, divided into three sessions for each subject. Participation in three tests: • • •
Sternberg–Wagner self-assessment inventory [17] Test series called AMOS [20] Brain Dominance Questionnaire [18].
Two sessions were held with each participant. In the first session the subject was tested, and in the second session an interview was held to determine whether the test results coincided with the subject’s self-evaluation. A total of five 1-h sessions were held with each participant in the study. Sternberg–Wagner self-assessment inventory, also known as thinking style inventory (TSI), is a reliable measurement for assessing the thinking style proposed in Sternberg’s theory and shows good external validity [17]. Score values are assigned to categories (from very low to very high) according to different ranges, which are distinct for male and female subjects. According to Sternberg test’s instructions, individuals that scored in the higher categories (i.e., range score, 5–7) of global or analytical questionnaires, were categorized, respectively, as global and analytical [17]. AMOS test [20] and Brain Dominance questionnaire [18], which focused on the distinction between global and analytic style, were utilized to confirm our obtained results. VEP recordings All subjects underwent a visual evoked potentials (VEP) recording session. This took place in a quiet room with dimmed light. Subjects were seated 1 m in front of a television monitor (mean luminance 250 candela/m2, color temperature 9,500 K). Stimuli were presented as a checkerboard pattern of white and black squares (contrast 80 %) subtending 1, 8 min of arc and reversed at a rate of 3.1/s. With one eye patched, subjects were instructed to fix a red dot in the middle of the screen. Electrodes were placed in the midline over the occipital region 2.5 cm above the inion (Oz: active electrode) and over the frontal region (Fz: reference). The ground electrode was placed on the forearm. An uninterrupted delivery of 250 stimuli was recorded. Five sequential blocks of 50 responses were extracted offline and sequentially averaged for a total duration of 1.5 min, obtaining five average values for the entire stimulation. All subjects were recorded using an STIM 2 Neuroscan System
Neurol Sci (2015) 36:391–395 Table 1 Latencies (ms), first block amplitudes (lV) and habituation as percentage and slope of VEPs (mean ± standard deviation)
393
AN N1 latency
81.07 ± 3.53
78.87 ± 6.4
AN vs. GL, p = 0.54
P1 latency
113.07 ± 6.13
112.33 ± 6.37
AN vs. GL, p = 0.7
N2 latency
150.93 ± 7.0
156.53 ± 13.93
AN vs. GL, p = 0.3
9.91 ± 3.27
AN vs. GL, p = 0.27
N1–P1 amplitude (I block)
8.63 ± 3.92 19.67 ± 31.5
212.66 ± 23.53
N1–P1 slope
0.27 ± 0.36
20.23 ± 0.35
P1–N2 amplitude (I block)
10.1 ± 4.99
12.4 ± 4.59
N1–P1 habituation (%)
P1–N2 habituation (%) Values in bold are statistically significant results (p \ 0.05)
GL
P1–N2 slope
with Brain Vision amplifiers. Analysis was performed after artifact rejection; all traces were inspected manually by the same operator and all frames containing a deflection exceeding 100 lV or in which the potential was not detected, were discarded. Only subjects with more than 90 % of valid traces were considered for the analysis. VEP components were identified according to their latencies: N1 was defined as the most negative peak between 60 and 90 ms; P1 as the most positive peak following N1 between 80 and 120 ms; and N2 as the most negative peak following P1 at between 125 and 150 ms. Statistical analysis For epidemiological purposes, a Chi-square test was used to determine whether there were significant differences regarding gender distribution in the two groups. Mean latencies of each VEP component (N1, P1, N2) were calculated. We measured the peak-to-peak amplitude of both the N1–P1 and the P1–N2 complex. Block amplitudes were then normalized as percentages of the first block. Habituation was defined both as the change in amplitude of N1–P1 and P1–N2 recorded during the five blocks (expressed as the amplitude change in percentage between the 1st and the 5th block of averages) as well as the slope of the linear regression for the five blocks. Results are expressed as mean ± standard deviation. We used the Shapiro–Wilk test for assessing normal distribution of the variables. Since most variables did not meet the normality criterium, we used Mann–Whitney test to estimate the intergroup differences (latencies, amplitudes and habituation values between group AN and group GL). All results were considered significant at p \ 0.05. Statistical calculations were carried out using STATISTICA (version 7, StatSoft, OK, USA).
1.98 % ± 50.84 0.07 ± 0.57
AN vs. GL, p < 0.001 AN vs. GL, p < 0.001 AN vs. GL, p = 0.29
-8.43 % ± 26.6
AN vs. GL, p = 0.5
-0.29 ± 0.57
AN vs. GL, p = 0.1
the GL subjects; the Chi-square test, however, did not show significant difference between the two groups (p = 0.12; df = 1). Main values of VEP recordings for both groups and statistics are summarized in Table 1. We did not observe a difference between N1, P1 and N2 mean latencies between the two groups. Amplitudes of the first block of responses for the N1–P1 component showed a lower value in the AN group (8.63 ± 3.92 vs. 9.91 ± 3.27, p = 0.27); this was confirmed for the P1–N2 value of first block amplitudes (AN group vs. GL group: 10.1 ± 4.99 vs. 12.4 ± 4.59, p = 0.29). However, these differences were not statistically significant. We instead found a significantly reduced N1–P1 habituation in group AN (19.67 % ± 31.5) with respect to group GL (-12.66 ± 23.53) as seen by measuring intergroup differences in habituation using the Mann–Whitney test (p = 0.0002) (Fig. 1). The slope of the linear regression for the N1–P1 was also significantly higher in AN group (0.27 ± 0.36) respect to GL group (-0.23 ± 0.35, p = 0.0009) (Fig. 2). Regarding the P1–N2 component, we could only demonstrate a trend of significance for a reduced habituation in
Results The two analyzed groups (AN and GL) were matched for age. Regarding gender, there was a prevalence of males in
Fig. 1 N1–P1 habituation after VEP stimulation for the two groups, expressed in successive blocks percentage amplitudes relative to the first block (values ± standard errors)
123
394
Fig. 2 Slope of the linear trend of the N1–P1 component (values ± standard errors)
Analytical group vs. Global group (AN group 1.98 % ± 50.84 vs. GL group -8.43 % ± 26.6; p = 0.5). This was confirmed for the slope values (AN group 0.07 ± 0.57 vs. GL group -0.29 ± 0.57; p = 0.1) (Table 1).
Discussion and conclusion In this study, habituation measured by VEPs was assessed separately in individuals characterized by analytic and global cognitive styles. We observed a significant difference regarding the habituation degree for the N1–P1 component of VEPs, as well as a trend of significance for the P1–N2 component, in analytical individuals with respect to global subjects, showing in the first a reduced habituation compared to the latter. Nowadays, it is widely accepted that habituation is a feature of healthy brain, although this phenomenon has been shown to be more or less pronounced in different individuals; it has been hypothesized that deficient habituation may represent an endophenotypic marker of presymptomatic migraine [7, 8]. In the present study, we observed lack of habituation in analytical healthy subjects devoid of positive family history of migraine or other types of diseases in which deficit of habituation has been highlighted. It might thus be possible to hypothesize a direct link between this neurophysiological phenomenon and cognitive and behavioral aspects that influence the way of analyzing reality, which is intrinsic to each individual. As Sternberg emphasized [17], analytic cognitive style is not a personality trait or a psychological disorder [17, 18], representing simply a specific manner of information processing, characterized by the habit of continually evaluating and processing stimuli and dealing with details. Considering this description, it is possible to correlate this
123
Neurol Sci (2015) 36:391–395
cognitive modality of information processing on what we hypothesize to be its neurophysiological correlate: the habituation mechanism. Habituation is in fact one of the most basic mechanisms of learning [5]. The nervous system is constantly evaluating incoming stimuli and filtering out the ones that are not important for the organism’s survival. At a neurophysiological level, this mechanism produces an habituation of cortical responses [8]. It has thus been suggested that habituation may be a protective mechanism economizing energy balance in a normally functioning brain [23]. Based on our findings, it could be hypothesized that continuous analytical behavior may share common neurophysiological basis with lack of habituation. Both could in fact imply high brain activation [3, 19]. The studies that have previously investigated correlates of evoked potentials with cognitive styles, seem to be in line with this hypothesis. In particular, Goode and colleagues have found higher slow negative wave following the P300 response in field-independent subjects, which use a more analytical approach; this could suggest deeper processing of information in these individuals [21, 24]. Furthermore, by analyzing the responses of event-related potentials, Meng et al. [22] have highlighted differences regarding the way in which field-dependent (global) and field-independent (analytic) subjects process information. They found that a higher amplitude of N270 in the latter could represent greater recruitment of neuronal resources used to resolve a conflict through the attentional biasing of perceptual processes. Earlier studies have demonstrated increased cortical activation in analytical individuals compared to the global ones, stressing that the former are generally more ‘‘aroused’’ than the latter [25]. In migraineurs, it has been hypothesized that a reduced preactivation level of sensory cortices and consequent ‘‘hyperresponsivity’’ may be the main culprit for deficit of habituation [26]. Our result of a lower amplitude of the first block of averaging in analytic group (Table 1), even if not significant, seems to be in line with such a hypothesis, suggesting that the mechanism underlying a deficient habituation might be present also in healthy analytic individuals. Analytic cognitive style, considering its behavioral characteristics (continually evaluating and processing stimuli) [18], may thus share common neurophysiological basis with cortical ‘‘hyperresponsivity’’ [26]. Whether or not the two factors are in causal relationship cannot be stated on the basis of our results and it could be matter for further studies. Furthermore, given that the origin of cognitive styles is unclear, another question arises as to whether these are actually inbuilt, genetically determined, or if they develop in response to early experiences [19] or to attachment styles [27]. In any case, as it has been demonstrated,
Neurol Sci (2015) 36:391–395
cognitive style can be modified and taught [17, 20]. It would thus be interesting to investigate if a modification of analytic mode of information processing could affect the associated reduced habituation, therefore reverting this neurophysiological behavior. Limits of this study were the small sample size and the non-homogeneous distribution of gender in the two groups, specifically regarding a male prevalence among global subjects. In conclusion, a reduced habituation of VEPs has been observed, for the first time, in analytic healthy subjects. Our results suggest that further research should be undertaken from a neurological and psychological point of view, regarding the relationship between the analytic cognitive style and lack of habituation, both in physiological and pathophysiological conditions. Acknowledgments The authors would like to thank Giovanna Castelli, Raffaella Policastro and Luca Pierotti for their technical assistance to the manuscript. The authors are enormously grateful to Dr. Rita Levi Montalcini for her invaluable encouragement during the preparation of the manuscript. Conflict of interest
None.
References 1. Harris J (1943) Habituatory response decrement in the intact organism. Psichol Bull 40:385–422 2. Schoenen J (1996) Deficient habituation of evoked cortical potentials in migraine: a link between brain biology, behavior and trigeminovascular activation? Biomed Pharmacother 50(2):71–78 3. Coppola G, Pierelli F, Schoenen J (2009) Habituation and migraine. Neurobiol Learn Mem 92(2):249–259 4. Coppola G, Schoenen J (2012) Measures of cortical excitability. In: Borsook D, May A, Goadsby PJ, Hargreaves R (eds) The migraine brain: imaging structure and function. Oxford University Press, New York 5. Coppola G, Di Lorenzo C, Schoenen J, Pierelli F (2013) Habituation and sensitization in primary headaches. J Headache Pain 14:65. doi:10.1186/1129-2377-14-65 6. Siniatchkin M, Kropp P, Gerber WB (2003) What kind of habituation is impaired in migraine patients? Cephalalgia 23(7):511–518 7. Di Clemente L, Coppola G, Magis D et al (2007) Interictal habituation deficit of the nociceptive blink reflex: an endophenotypic marker for presymptomatic migraine? Brain 130(Pt 3):765–770 8. Siniatchkin M, Kropp P, Gerber WD (2001) Contingent negative variation in subjects at risk for migraine without aura. Pain 94(2):159–167
395 9. Walpurger V, Hebing-Lennartz G, Denecke H, Pietrowsky R (2003) Habituation deficit in auditory event-related potentials in tinnitus complainers. Hear Res 181:57–64 10. Meincke U, Light GA, Geyer MA et al (2004) Sensitization and habituation of the acoustic startle reflex in patients with schizophrenia. Psychiatry Res 126:51–61 11. De Tommaso M, Federici A, Santostasi R et al (2011) Laserevoked potentials habituation in fibromyalgia. J Pain 12(1):16–24 12. Schestatsky P, Kumru H, Valls-Sole J et al (2007) Neurophysiologic study of central pain in patients with Parkinson disease. Neurology 4:2162–2169 13. Brazzo D, Di Lorenzo G, Bill P et al (2011) Abnormal visual habituation in pediatric photosensitive epilepsy. Clin Neurophysiol 122(1):16–20 14. Valeriani M, Le Pera D (2007) Abnormal brain excitability in migraine: a debated subject. In: Clarke LB (ed) Migraine disorders research trends. Nova Science Publishers, New York, pp 35–60 15. Massa J, O’ Desky IH (2012) Impaired visual habituation in adults with ADHD. J Atten Disord 16(7):553–561 16. Rankin CH, Abrams T et al (2009) Habituation revisited : an updated and revised description of the behavioral characteristics of habituation. Neurobiol Learn Mem 92(2):135–138 17. Sternberg RJ (1997) Thinking styles. Cambridge University Press, Cambridge 18. Di Sabato F, Buonfiglio M, Mandillo S (2013) Analytic information processing style in migraineurs. Neurol Sci 34:1145–1150. doi:10. 1007/s10072-012-1193-8 19. Riding RJ, Glass A et al (1997) Cognitive style and individual differences in EEG alpha during information processing. Educ Psychol 17:219–234 20. De Beni R, Moe˘ A, Cornoldi C (2003) AMOS. Abilita` e motivazione allo studio: Prove di valutazione e orientamento. Erikson, Trento 21. Goode PE, Goddard P, Pascual-Leone J (2002) Event-related potentials index cognitive style differences during a serial- order recall task. Int J Psychol 43(2002):123–140 22. Xiangong Meng, Wei Mao, Wei Sun et al (2012) Event related potentials with different cognitive styles: field dependence and field independence. Exp Brain Res 2016:231–240 23. Schoenen J (1994) Pathogenesis of migraine: the biobehavioural and hypoxia theories reconciled. Acta Neurol Belg 94(2):79–86 24. Witkin HA, Moore CA, Goodenough DR (1977) Field dependent and field independent cognitive styles and their educational implications. Rev Educ Res 47(1):1–64 25. Glass A, Riding RJ (1999) EEG differences and cognitive style. Biol Psychol 51(1):23–41 26. Coppola G, Pierelli F, Schoenen J (2007) Is the cerebral cortex hyperexcitable or hyperresponsive in migraine? Cephalalgia 27:1429–1439 27. Vermigli P, Toni A (2004) Attachment and field dependence: individual difference in information processing. Eur Psychol 9(1):43–45
123
ORIGINAL ARTICLE
Lack of habituation of evoked visual potentials in analytic information processing style: evidence in healthy subjects Marzia Buonfiglio • M. Toscano • F. Puledda • G. Avanzini • L. Di Clemente • F. Di Sabato • V. Di Piero
Received: 23 April 2014 / Accepted: 19 September 2014 / Published online: 27 September 2014 Springer-Verlag Italia 2014
Abstract Habituation is considered one of the most basic mechanisms of learning. Habituation deficit to several sensory stimulations has been defined as a trait of migraine brain and also observed in other disorders. On the other hand, analytic information processing style is characterized by the habit of continually evaluating stimuli and it has been associated with migraine. We investigated a possible correlation between lack of habituation of evoked visual potentials and analytic cognitive style in healthy subjects. According to Sternberg–Wagner self-assessment inventory, 15 healthy volunteers (HV) with high analytic score and 15 HV with high global score were recruited. Both groups underwent visual evoked potentials recordings after psychological evaluation. We observed significant lack of habituation in analytical individuals compared to global group. In conclusion, a reduced habituation of visual evoked potentials has been observed in analytic subjects. Our results suggest that further research should be
M. Buonfiglio (&) F. Di Sabato Department of Clinical Medicine, ‘‘Sapienza’’ University of Rome, Policlinico Umberto I, Viale del Policlinico 155, 00161 Rome, Italy e-mail: [email protected] M. Toscano Department of Psychology, ‘‘Sapienza’’ University of Rome, Rome, Italy F. Puledda L. Di Clemente V. Di Piero Department of Neurology and Psychiatry, ‘‘Sapienza’’ University of Rome, Rome, Italy G. Avanzini Department of Neurophysiology, IRCCS Foundation Neurological Institute ‘‘Carlo Besta’’, Milan, Italy
undertaken regarding the relationship between analytic cognitive style and lack of habituation in both physiological and pathophysiological conditions. Keywords Lack of habituation Evoked visual potentials Analytic information processing style Sternberg–Wagner self-assessment inventory Healthy subjects
Introduction Habituation of neural evoked activity is an ubiquitous phenomenon, a processing modality of sensorial stimuli primarily defined by a ‘‘response decrement as a result of repeated stimulations’’ [1]. It is a compensatory mechanism for lactate accumulation in cerebral cortex, thus protecting a normally functioning brain from sensory overload [2, 3]. At a neurophysiological level, a lack of habituation means that the decrease in response after repetitive sensorial stimulations is reduced or absent [4]. Over the years the parametric properties of this phenomenon were revised [5]. Habituation deficit to several sensory stimulations has been highlighted in migraine [3, 6, 7]. It has been defined as a characteristic of the migraine brain, and shows a familial trait [8]. Noteworthy, habituation deficit fluctuates in relation to migraine cycle, being most pronounced interictally and normalizing during attack [3]. Moreover, lack of habituation was also observed with various stimulus modalities in other disorders [9–13]. The cause of this abnormality is still matter of debate [14] and it was hypothesized that it leads to high brain activation and energy demand [3]. Habituation mechanism is considered extremely useful for studying the mechanism of learning processes [3].
123
392
It has been suggested that impaired visual habituation may disrupt sustained attention via inability to modulate the repeated intrusion of irrelevant stimuli and it may explain clinical symptoms associated with adult attention deficit disorders [15]. However, an habituation variability can also be expected in healthy subjects, depending on a series of parametric properties or characteristics and on a rich collection of cellular mechanisms that are differentially recruited in different parts of the nervous system and by different stimulus paradigms [16]. Analytic information processing style is a specific cognitive behavior characterized by high activation of attention and continuous evaluation of stimuli [17–19]. It is an habitual and favorite way of perceiving incoming information and can be present from childhood [17, 18, 20]. A correlation between this cognitive style and migraine has been earlier observed [18]. Moreover, the neurophysiological correlates of cognitive styles have been previously highlighted by eventrelated potentials (ERP) [21, 22]. However, to our knowledge, no previous works have explored a possible link between the habituation response and analytic information processing style, which is the aim of the present study. We investigated this issue on a sample of 30 healthy subjects.
Materials and methods Subjects From a consecutive series of healthy volunteers taken from the personnel working in our department, we selected 15 healthy subjects aged 20–60 scoring higher in analytic cognitive style, that were attributed to group AN (Analytical) according to Sternberg test instructions [17] and 15 subjects that scored higher in global cognitive style, defined as group GL (Global). AN group was composed of 12 females and 3 males, while GL group of eight females and seven males. Mean age of AN group was 40.3 ± 8.9 while mean age of GL group was 44.1 ± 11.7. The volunteers had no first degree relatives suffering from recurrent headache or any other neurologic, psychiatric or chronic disorders. Subjects were not affected by any disease and had not taken drugs on a regular basis for at least 3 months before the recording took place. Physical examination was normal. Written informed consent was obtained from all participants in the study. The study was approved by the ethics committee of Policlinico Umberto I, Sapienza University of Rome.
123
Neurol Sci (2015) 36:391–395
Psychological evaluation The instruments used to gather psychological data for the study consisted in: – –
A clinical psychological diagnostic interview, divided into three sessions for each subject. Participation in three tests: • • •
Sternberg–Wagner self-assessment inventory [17] Test series called AMOS [20] Brain Dominance Questionnaire [18].
Two sessions were held with each participant. In the first session the subject was tested, and in the second session an interview was held to determine whether the test results coincided with the subject’s self-evaluation. A total of five 1-h sessions were held with each participant in the study. Sternberg–Wagner self-assessment inventory, also known as thinking style inventory (TSI), is a reliable measurement for assessing the thinking style proposed in Sternberg’s theory and shows good external validity [17]. Score values are assigned to categories (from very low to very high) according to different ranges, which are distinct for male and female subjects. According to Sternberg test’s instructions, individuals that scored in the higher categories (i.e., range score, 5–7) of global or analytical questionnaires, were categorized, respectively, as global and analytical [17]. AMOS test [20] and Brain Dominance questionnaire [18], which focused on the distinction between global and analytic style, were utilized to confirm our obtained results. VEP recordings All subjects underwent a visual evoked potentials (VEP) recording session. This took place in a quiet room with dimmed light. Subjects were seated 1 m in front of a television monitor (mean luminance 250 candela/m2, color temperature 9,500 K). Stimuli were presented as a checkerboard pattern of white and black squares (contrast 80 %) subtending 1, 8 min of arc and reversed at a rate of 3.1/s. With one eye patched, subjects were instructed to fix a red dot in the middle of the screen. Electrodes were placed in the midline over the occipital region 2.5 cm above the inion (Oz: active electrode) and over the frontal region (Fz: reference). The ground electrode was placed on the forearm. An uninterrupted delivery of 250 stimuli was recorded. Five sequential blocks of 50 responses were extracted offline and sequentially averaged for a total duration of 1.5 min, obtaining five average values for the entire stimulation. All subjects were recorded using an STIM 2 Neuroscan System
Neurol Sci (2015) 36:391–395 Table 1 Latencies (ms), first block amplitudes (lV) and habituation as percentage and slope of VEPs (mean ± standard deviation)
393
AN N1 latency
81.07 ± 3.53
78.87 ± 6.4
AN vs. GL, p = 0.54
P1 latency
113.07 ± 6.13
112.33 ± 6.37
AN vs. GL, p = 0.7
N2 latency
150.93 ± 7.0
156.53 ± 13.93
AN vs. GL, p = 0.3
9.91 ± 3.27
AN vs. GL, p = 0.27
N1–P1 amplitude (I block)
8.63 ± 3.92 19.67 ± 31.5
212.66 ± 23.53
N1–P1 slope
0.27 ± 0.36
20.23 ± 0.35
P1–N2 amplitude (I block)
10.1 ± 4.99
12.4 ± 4.59
N1–P1 habituation (%)
P1–N2 habituation (%) Values in bold are statistically significant results (p \ 0.05)
GL
P1–N2 slope
with Brain Vision amplifiers. Analysis was performed after artifact rejection; all traces were inspected manually by the same operator and all frames containing a deflection exceeding 100 lV or in which the potential was not detected, were discarded. Only subjects with more than 90 % of valid traces were considered for the analysis. VEP components were identified according to their latencies: N1 was defined as the most negative peak between 60 and 90 ms; P1 as the most positive peak following N1 between 80 and 120 ms; and N2 as the most negative peak following P1 at between 125 and 150 ms. Statistical analysis For epidemiological purposes, a Chi-square test was used to determine whether there were significant differences regarding gender distribution in the two groups. Mean latencies of each VEP component (N1, P1, N2) were calculated. We measured the peak-to-peak amplitude of both the N1–P1 and the P1–N2 complex. Block amplitudes were then normalized as percentages of the first block. Habituation was defined both as the change in amplitude of N1–P1 and P1–N2 recorded during the five blocks (expressed as the amplitude change in percentage between the 1st and the 5th block of averages) as well as the slope of the linear regression for the five blocks. Results are expressed as mean ± standard deviation. We used the Shapiro–Wilk test for assessing normal distribution of the variables. Since most variables did not meet the normality criterium, we used Mann–Whitney test to estimate the intergroup differences (latencies, amplitudes and habituation values between group AN and group GL). All results were considered significant at p \ 0.05. Statistical calculations were carried out using STATISTICA (version 7, StatSoft, OK, USA).
1.98 % ± 50.84 0.07 ± 0.57
AN vs. GL, p < 0.001 AN vs. GL, p < 0.001 AN vs. GL, p = 0.29
-8.43 % ± 26.6
AN vs. GL, p = 0.5
-0.29 ± 0.57
AN vs. GL, p = 0.1
the GL subjects; the Chi-square test, however, did not show significant difference between the two groups (p = 0.12; df = 1). Main values of VEP recordings for both groups and statistics are summarized in Table 1. We did not observe a difference between N1, P1 and N2 mean latencies between the two groups. Amplitudes of the first block of responses for the N1–P1 component showed a lower value in the AN group (8.63 ± 3.92 vs. 9.91 ± 3.27, p = 0.27); this was confirmed for the P1–N2 value of first block amplitudes (AN group vs. GL group: 10.1 ± 4.99 vs. 12.4 ± 4.59, p = 0.29). However, these differences were not statistically significant. We instead found a significantly reduced N1–P1 habituation in group AN (19.67 % ± 31.5) with respect to group GL (-12.66 ± 23.53) as seen by measuring intergroup differences in habituation using the Mann–Whitney test (p = 0.0002) (Fig. 1). The slope of the linear regression for the N1–P1 was also significantly higher in AN group (0.27 ± 0.36) respect to GL group (-0.23 ± 0.35, p = 0.0009) (Fig. 2). Regarding the P1–N2 component, we could only demonstrate a trend of significance for a reduced habituation in
Results The two analyzed groups (AN and GL) were matched for age. Regarding gender, there was a prevalence of males in
Fig. 1 N1–P1 habituation after VEP stimulation for the two groups, expressed in successive blocks percentage amplitudes relative to the first block (values ± standard errors)
123
394
Fig. 2 Slope of the linear trend of the N1–P1 component (values ± standard errors)
Analytical group vs. Global group (AN group 1.98 % ± 50.84 vs. GL group -8.43 % ± 26.6; p = 0.5). This was confirmed for the slope values (AN group 0.07 ± 0.57 vs. GL group -0.29 ± 0.57; p = 0.1) (Table 1).
Discussion and conclusion In this study, habituation measured by VEPs was assessed separately in individuals characterized by analytic and global cognitive styles. We observed a significant difference regarding the habituation degree for the N1–P1 component of VEPs, as well as a trend of significance for the P1–N2 component, in analytical individuals with respect to global subjects, showing in the first a reduced habituation compared to the latter. Nowadays, it is widely accepted that habituation is a feature of healthy brain, although this phenomenon has been shown to be more or less pronounced in different individuals; it has been hypothesized that deficient habituation may represent an endophenotypic marker of presymptomatic migraine [7, 8]. In the present study, we observed lack of habituation in analytical healthy subjects devoid of positive family history of migraine or other types of diseases in which deficit of habituation has been highlighted. It might thus be possible to hypothesize a direct link between this neurophysiological phenomenon and cognitive and behavioral aspects that influence the way of analyzing reality, which is intrinsic to each individual. As Sternberg emphasized [17], analytic cognitive style is not a personality trait or a psychological disorder [17, 18], representing simply a specific manner of information processing, characterized by the habit of continually evaluating and processing stimuli and dealing with details. Considering this description, it is possible to correlate this
123
Neurol Sci (2015) 36:391–395
cognitive modality of information processing on what we hypothesize to be its neurophysiological correlate: the habituation mechanism. Habituation is in fact one of the most basic mechanisms of learning [5]. The nervous system is constantly evaluating incoming stimuli and filtering out the ones that are not important for the organism’s survival. At a neurophysiological level, this mechanism produces an habituation of cortical responses [8]. It has thus been suggested that habituation may be a protective mechanism economizing energy balance in a normally functioning brain [23]. Based on our findings, it could be hypothesized that continuous analytical behavior may share common neurophysiological basis with lack of habituation. Both could in fact imply high brain activation [3, 19]. The studies that have previously investigated correlates of evoked potentials with cognitive styles, seem to be in line with this hypothesis. In particular, Goode and colleagues have found higher slow negative wave following the P300 response in field-independent subjects, which use a more analytical approach; this could suggest deeper processing of information in these individuals [21, 24]. Furthermore, by analyzing the responses of event-related potentials, Meng et al. [22] have highlighted differences regarding the way in which field-dependent (global) and field-independent (analytic) subjects process information. They found that a higher amplitude of N270 in the latter could represent greater recruitment of neuronal resources used to resolve a conflict through the attentional biasing of perceptual processes. Earlier studies have demonstrated increased cortical activation in analytical individuals compared to the global ones, stressing that the former are generally more ‘‘aroused’’ than the latter [25]. In migraineurs, it has been hypothesized that a reduced preactivation level of sensory cortices and consequent ‘‘hyperresponsivity’’ may be the main culprit for deficit of habituation [26]. Our result of a lower amplitude of the first block of averaging in analytic group (Table 1), even if not significant, seems to be in line with such a hypothesis, suggesting that the mechanism underlying a deficient habituation might be present also in healthy analytic individuals. Analytic cognitive style, considering its behavioral characteristics (continually evaluating and processing stimuli) [18], may thus share common neurophysiological basis with cortical ‘‘hyperresponsivity’’ [26]. Whether or not the two factors are in causal relationship cannot be stated on the basis of our results and it could be matter for further studies. Furthermore, given that the origin of cognitive styles is unclear, another question arises as to whether these are actually inbuilt, genetically determined, or if they develop in response to early experiences [19] or to attachment styles [27]. In any case, as it has been demonstrated,
Neurol Sci (2015) 36:391–395
cognitive style can be modified and taught [17, 20]. It would thus be interesting to investigate if a modification of analytic mode of information processing could affect the associated reduced habituation, therefore reverting this neurophysiological behavior. Limits of this study were the small sample size and the non-homogeneous distribution of gender in the two groups, specifically regarding a male prevalence among global subjects. In conclusion, a reduced habituation of VEPs has been observed, for the first time, in analytic healthy subjects. Our results suggest that further research should be undertaken from a neurological and psychological point of view, regarding the relationship between the analytic cognitive style and lack of habituation, both in physiological and pathophysiological conditions. Acknowledgments The authors would like to thank Giovanna Castelli, Raffaella Policastro and Luca Pierotti for their technical assistance to the manuscript. The authors are enormously grateful to Dr. Rita Levi Montalcini for her invaluable encouragement during the preparation of the manuscript. Conflict of interest
None.
References 1. Harris J (1943) Habituatory response decrement in the intact organism. Psichol Bull 40:385–422 2. Schoenen J (1996) Deficient habituation of evoked cortical potentials in migraine: a link between brain biology, behavior and trigeminovascular activation? Biomed Pharmacother 50(2):71–78 3. Coppola G, Pierelli F, Schoenen J (2009) Habituation and migraine. Neurobiol Learn Mem 92(2):249–259 4. Coppola G, Schoenen J (2012) Measures of cortical excitability. In: Borsook D, May A, Goadsby PJ, Hargreaves R (eds) The migraine brain: imaging structure and function. Oxford University Press, New York 5. Coppola G, Di Lorenzo C, Schoenen J, Pierelli F (2013) Habituation and sensitization in primary headaches. J Headache Pain 14:65. doi:10.1186/1129-2377-14-65 6. Siniatchkin M, Kropp P, Gerber WB (2003) What kind of habituation is impaired in migraine patients? Cephalalgia 23(7):511–518 7. Di Clemente L, Coppola G, Magis D et al (2007) Interictal habituation deficit of the nociceptive blink reflex: an endophenotypic marker for presymptomatic migraine? Brain 130(Pt 3):765–770 8. Siniatchkin M, Kropp P, Gerber WD (2001) Contingent negative variation in subjects at risk for migraine without aura. Pain 94(2):159–167
395 9. Walpurger V, Hebing-Lennartz G, Denecke H, Pietrowsky R (2003) Habituation deficit in auditory event-related potentials in tinnitus complainers. Hear Res 181:57–64 10. Meincke U, Light GA, Geyer MA et al (2004) Sensitization and habituation of the acoustic startle reflex in patients with schizophrenia. Psychiatry Res 126:51–61 11. De Tommaso M, Federici A, Santostasi R et al (2011) Laserevoked potentials habituation in fibromyalgia. J Pain 12(1):16–24 12. Schestatsky P, Kumru H, Valls-Sole J et al (2007) Neurophysiologic study of central pain in patients with Parkinson disease. Neurology 4:2162–2169 13. Brazzo D, Di Lorenzo G, Bill P et al (2011) Abnormal visual habituation in pediatric photosensitive epilepsy. Clin Neurophysiol 122(1):16–20 14. Valeriani M, Le Pera D (2007) Abnormal brain excitability in migraine: a debated subject. In: Clarke LB (ed) Migraine disorders research trends. Nova Science Publishers, New York, pp 35–60 15. Massa J, O’ Desky IH (2012) Impaired visual habituation in adults with ADHD. J Atten Disord 16(7):553–561 16. Rankin CH, Abrams T et al (2009) Habituation revisited : an updated and revised description of the behavioral characteristics of habituation. Neurobiol Learn Mem 92(2):135–138 17. Sternberg RJ (1997) Thinking styles. Cambridge University Press, Cambridge 18. Di Sabato F, Buonfiglio M, Mandillo S (2013) Analytic information processing style in migraineurs. Neurol Sci 34:1145–1150. doi:10. 1007/s10072-012-1193-8 19. Riding RJ, Glass A et al (1997) Cognitive style and individual differences in EEG alpha during information processing. Educ Psychol 17:219–234 20. De Beni R, Moe˘ A, Cornoldi C (2003) AMOS. Abilita` e motivazione allo studio: Prove di valutazione e orientamento. Erikson, Trento 21. Goode PE, Goddard P, Pascual-Leone J (2002) Event-related potentials index cognitive style differences during a serial- order recall task. Int J Psychol 43(2002):123–140 22. Xiangong Meng, Wei Mao, Wei Sun et al (2012) Event related potentials with different cognitive styles: field dependence and field independence. Exp Brain Res 2016:231–240 23. Schoenen J (1994) Pathogenesis of migraine: the biobehavioural and hypoxia theories reconciled. Acta Neurol Belg 94(2):79–86 24. Witkin HA, Moore CA, Goodenough DR (1977) Field dependent and field independent cognitive styles and their educational implications. Rev Educ Res 47(1):1–64 25. Glass A, Riding RJ (1999) EEG differences and cognitive style. Biol Psychol 51(1):23–41 26. Coppola G, Pierelli F, Schoenen J (2007) Is the cerebral cortex hyperexcitable or hyperresponsive in migraine? Cephalalgia 27:1429–1439 27. Vermigli P, Toni A (2004) Attachment and field dependence: individual difference in information processing. Eur Psychol 9(1):43–45
123
