Altered phase and nonphase EEG activity expose impaired maintenance of a spatial‑object attentional focus in multiple sclerosis patients

1 Vol.:(0123456789) Scientific Reports | (2020) 10:20721 | https://doi.org/10.1038/s41598-020-77690-y www.nature.com/scientificreports Altered phase and nonphase EEG activity expose impaired maintenance of a spatial‑object attentional focus in multiple sclerosis patients M. Vazquez‑Marrufo1*, E. Sarrias‑Arrabal1, R. Martin‑Clemente2, A. Galvao‑Carmona3, G. Navarro4 & G. Izquierdo5 Some of the anatomical and functional basis of cognitive impairment in multiple sclerosis (MS) currently remains unknown. In particular, there is scarce knowledge about modulations in induced EEG (nonphase activity) for diverse frequency bands related to attentional deficits in this pathology. The present study analyzes phase and nonphase alpha and gamma modulations in 26 remitting‑ relapsing multiple sclerosis patients during their participation in the attention network test compared with twenty‑six healthy controls (HCs) matched in sociodemographic variables. Behavioral results showed that the MS group exhibited general slowing, suggesting impairment in alerting and orienting networks, as has been previously described in other studies. Time–frequency analysis of EEG revealed that the gamma band was related to the spatial translation of the attentional focus, and the alpha band seemed to be related to the expectancy mechanisms and cognitive processing of the target. Moreover, phase and nonphase modulations differed in their psychophysiological roles and were affected differently in the MS and HC groups. In summary, nonphase modulations can unveil hidden cognitive mechanisms for phase analysis and complete our knowledge of the neural basis of cognitive impairment in multiple sclerosis pathology. Multiple sclerosis (MS) is a chronic degenerative neurological disease of unknown etiology that causes mainly neurological damage including demyelination and inflammation of the central nervous system (CNS)1. The onset of MS occurs over a wide age range (mainly between 20 and 40years), and MS predominantly affects women. Approximately 40–70% of patients with the disease show diverse cognitive deficits1–3. Therefore, different neuropsychological profiles can be found during clinical assessments. Attention, processing speed and memory are the cognitive domains most frequently affected4–7. To understand the neural basis of these cognitive alterations in MS, different cognitive paradigms and techniques have been used8–10. One of the cognitive paradigms that has often been used to evaluate attention is the “Attention Network Test” (ANT). The ANT was developed to assess three attentional networks (alerting, orienting and executive systems) and has been performed with different versions and for diverse pathologies11–14. Although the ANT was developed in 200115, it did not begin to be applied in patients with multiple sclerosis until 201016. These authors found an alteration in patients’ alerting network with respect to healthy controls (HCs). The authors suggested that the deficit could be due to lower response readiness or a reduced ability of patients to maintain alertness after presentation of the cue. Other authors have confirmed the alteration in the alerting network in patients with multiple sclerosis even in early stages of the disease17. Moreover, a study18 found deficits in the alerting and orienting networks in patients based not only on behavioral responses but also on specific psychophysiological variables (e.g., changes in the amplitude of the contingent negative variation). OPEN 1Lab B508 (Psychophysiology Unit), Experimental Psychology Department, Faculty of Psychology, University of Seville, Seville, Spain. 2Signal Processing and Communications Department, Higher Technical School of Engineering, University of Seville, Seville, Spain. 3Department of Psychology, Universidad Loyola Andalucía, Seville, Spain. 4Multiple Sclerosis Unit, Hospital Universitario Virgen Macarena, Seville, Spain. 5Multiple Sclerosis Unit, Hospital Vithas, Seville, Spain. *email: [email protected] 2 Vol:.(1234567890) Scientific Reports | (2020) 10:20721 | https://doi.org/10.1038/s41598-020-77690-y www.nature.com/scientificreports/ One way to improve our knowledge of the neural basis of cognitive impairment in MS pathology is to analyze the frequency domain of the EEG signal. In its origins, the EEG signal was largely studied using fast Fourier transformation (FFT), but this approach has the disadvantage of renouncing the high EEG time resolution19,20. Time–frequency EEG methods such as temporal spectral evolution (TSE) can overcome this limit21. TSE shows EEG time–frequency information that includes both phase (evoked) and nonphase (induced) activity related to stimulus presentation (for a detailed description of the TSE method22,23). Through TSE and other time–frequency techniques, numerous studies have related frequency bands of EEG to specific cognitive mechanisms. In the case of the alpha band, originally, it was identified as an indicator of a neural area at rest24. However, some authors have argued that it may not exclusively reflect an idling status but can also play an active role in inhibitory control and timing of sensory processing25. Along this line, some authors have suggested that an increase in alpha activity in regions irrelevant to the task may reflect inhibition processes26. Specifically, for attentional visual processing, some studies have observed higher alpha activity in those regions of the occipital cortex where unattended locations are retinotopically represented27–29. For decades, it has been suggested that there are two types of alpha bands, namely, low alpha (8–10.5Hz) and upper alpha (10.5–13Hz) bands, with different psychophysiological meanings30. Low alpha bands may be related to a general attention, while upper alpha bands are proposed to be linked to more specific processes such as semantic processing31,32. In fact, the topographical distribution of low alpha bands is usually larger and less specific than that of upper alpha bands, which tends to be more localized in scalp regions33,34. Another neurophysiological correlate that has been linked to cognitive functioning is the gamma band35,36. The functional roles assigned to this band are more than the visual grouping, as has been reviewed by some authors37. In particular, this neural activity has been related to arousal or attention in humans38–40. One of the reasons that this band is suitable for attentional mechanisms is its fine temporal tuning for neuronal firing (10–30ms time precision)41. Some studies have described the specific involvement of the gamma band in visual attentional tasks41,42. In the study by Gruber etal.41, the authors displayed colored rectangles in the left or right half of the screen, and a cue indicated to the subjects in which visual hemifield they had to shift their attention to detect target stimuli. These authors found an increase in the gamma activity (35–51Hz) when the attended stimuli were rotating. In the study by Fries etal.42, neurons from cortical area V4 in macaque monkeys exhibited an increase in the gamma band (35–90Hz) when the experimental subjects were attending to relevant stimuli and ignoring distracters. With regard to these spectral bands and their relation to cognitive impairment in MS, some studies have described a higher decrement of the alpha band in MS patients reflecting a recruitment of more cognitive resources to perform the task43. A more recent study44 showed that the alpha band is related to attentional mechanisms and processing speed; a smaller decrease in the resting-state alpha band in specific experimental conditions was associated with a poorer behavioral performance. With regard to the gamma band, a few studies have described alterations in this band in MS patients related to diverse phenomena, such as alterations in cognitive processing in a visual attention task45, a neurophysiological correlate of compensatory mechanisms or cortical excitatory states representative of some phases during the MS course45, or gray matter dysfunction, possibly mediated by GABAergic changes46. Finally, there is scarce knowledge about the meaning of the spectral modulations observed during the execution of the ANT47–49. Authors have described a decrease in the alpha band after the warning signal (alerting effect) and an increase in the gamma content at 200ms after target onset related to the orienting network47. However, this study did not consider if the modulation was in phase or nonphase to the onset of the stimuli47. In the last years, neuroscientists have focused on this difference and found that both domains (evoked and induced) could represent diverse processes in cognition50–52. Considering all these premises, the main goal of the present study was to analyze the modulations in the alpha and gamma bands (and in both evoked and induced modalities) related to attentional impairment in an MS group assessed by the ANT. Our hypothesis was that behavioral data would show a general slowing in the MS group compared to the healthy group that would be corroborated by the neuropsychological assessment. Alpha and gamma modulations related to attentional mechanisms would show alterations in the MS group during the execution of the ANT. An open question in the present study was which components of the alpha and gamma modulations (evoked, induced or both) would be related to attentional impairment. Results Behavioral data. The HCs obtained a significantly shorter reaction time than the MS group [F (1,50) = 26,55; p < 0.001; η2 = 0.438]. In addition, the cue factor revealed differences between cues, with the no cue (NC) condition showing larger reaction times followed by the central cue (CC) condition and finally the spatial cue (SC) condition, which was the fastest [F (2,100) = 287.04; p < 0.001; η2 = 0.930] (Table1and supplementary Table1 for statistical results). Post hoc Bonferroni comparisons confirmed the differences between all cue levels (p < 0.001). After applying the correction of Fernández-Duque and Black53, differences in the NC condition were observed between groups [t = 2.186; p = 0.03], and patients were faster than HCs. This value does not indicate that MS patients were faster than HC subjects in this condition; it shows that MS patients were relatively faster for this condition than in all conditions in the MS group in the same comparison for HCs. With regard to precision, there were no significant differences between groups or other factors because of a similar high percentage of accuracy for all conditions in both experimental groups (Table1). Neuropsychological and depression assessments. In terms of the number of hits on the PASAT-3s and the overall hit rate on the symbol digit modality test (SDMT), the latter showed a value of 2 SD under the cutoff scores defined by Sepulcre54, indicating a moderate attentional impairment in our sample of MS patients 3 Vol.:(0123456789) Scientific Reports | (2020) 10:20721 | https://doi.org/10.1038/s41598-020-77690-y www.nature.com/scientificreports/ (SDMT score = 44 ± 13.82). Last, Beck depression scores (BDI-II) indicated that there were not severe signs of depression in the MS group (BDI-II score = 7.44 ± 6.3). Gamma activity. Expectancy interval. The evoked gamma activity showed no differences in latency after presentation of an SC between both groups (Fig.1).There were no appreciable modulations for the NC and CC conditions to calculate the latency. With regard to the amplitude, the evoked gamma activity showed no differences after presentation of any type of cue (NC, CC or SC) or between both groups (Fig.1 and Table2). With regard to the induced activity, peak latency analysis of the SC conditions showed no differences between groups (Table2).In the case of the amplitude analysis, the cue factor was statistically significant (F(2,100) = 53.89, p < 0.001, ƞ2: 0.666). However, a post hoc comparison showed no significant differences between the levels of this Table 1. ANT behavioral results. *The p value refers to the ‘‘Group’’ factor before correction for general slowing had been applied (see text for details). **The P value refers to the “Group” factor after correction for general slowing had been applied. Abbreviations: MS: multiple sclerosis; HC: healthy controls. SD: standard deviation, RT: reaction time, NC: no cue; CC: central cue; SC: spatial cue. Reaction time (mean ± SD) Accuracy (mean ± SD) Conditions Correction not applied P value* Correction applied P-value** MS HCMS HC MS HC NC 638 ± 81 531 ± 71 < 0.001 1.05 ± 0.02 1.06 ± 0.01 0.03 92.90 ± 11.21 96.51 ± 2.49 CC 614 ± 85 505 ± 74 < 0.001 1.01 ± 0.02 1.00 ± 0.01 0.72 94.07 ± 9.73 96 ± 3.86 SC 568 ± 78 462 ± 63 < 0.001 0.93 ± 0.02 0.92 ± 0.02 0.12 95.35 ± 5.26 96.78 ± 2.43 Mean 607 ± 80 500 ± 69 < 0.001 –––94.11 ± 8.52 96.42 ± 2.39 Figure1. (a) Evoked and induced waves for the gamma band (30–45Hz) in the expectancy and target response intervals. (b) 2-D head maps for the peak and valley latencies of evoked and induced activity. Abbreviations: MS: multiple sclerosis; HC: healthy controls; CC: central cue; SC: spatial cue; EXP: expectancy interval; ms: milliseconds. 4 Vol:.(1234567890) Scientific Reports | (2020) 10:20721 | https://doi.org/10.1038/s41598-020-77690-y www.nature.com/scientificreports/ main factor. Nevertheless, a post hoc comparison for the following interaction “cue × anterior–posterior location and medial–lateral location” showed that the SC was higher in amplitude than theNC and CC conditions for all derivations (p < 0.001 in all cases) (Fig.1 and and supplementary Table2 for amplitude values). Group factor also showed a significant result (F(1,50) = 4.51, p < 0.038, ƞ2: 0.136) that was caused by a higher amplitude of the gamma modulation in the MS group than in the HC group (Fig.1 and Table2). No significant differences were found for the group factor in terms of its interaction with location factors. Target interval. In contrast to the almost nonexistent response for the cue, the evoked gamma activity for target stimuli was mainly observed for the NC and CC conditions. The latency variable was not different between cue conditions; however, the amplitude exhibited a statistically significant result for the cue factor (F(2,100) = 6.42, p = 0.002, ƞ2: 0.204) (Fig.1 and Table2). In a post hoc analysis, no differences were found between the levels of this main factor; however, a post hoc comparison for the interaction “cue × anterior–posterior × lateral-medial” factors revealed that all derivations exhibited a lower amplitude for the SC than for the NC or CC conditions. No significant differences were found between the NC and CC conditions (Fig.1). Neither group nor an interaction of this factor with location factors resulted in a statistically significant difference. With regard to the induced activity, latency did not show differences for cue or group factors. For the amplitude variable, ANOVA showed that the “cue × anterior–posterior × lateral-medial” interaction was statistically significant (F(24,1200) = 1.80, p < 0.009, ƞ2: 0.068). Post hoc comparisons showed that all derivations were higher in amplitude for the NC and CC conditions than for the SC condition (p < 0.001 in all cases). Group factor also showed a statistically significant result (F(1,50) = 6.24, p = 0.015, ƞ2: 0.177), with MS patients exhibiting a higher amplitude than the healthy group (Fig.1 and Table2). No significant differences were found for the group factor in its interaction with other location factors. Low (8–10.5 Hz) and upper (10.5–13 Hz) alpha bands. Expectancy interval. In the evoked activity latency analysis, no significant differences between groups were present either in the low or upper alpha bands (Fig.2, 3). For the amplitude variable, HCs showed larger values than patients in both the low alpha [F (1,50) = 7.1205; p = 0.010; η2 = 0.237] and upper alpha bands [F (1,50) = 4.4794; p = 0.039; η2 = 0.164] (Figs.2, 3) (Tables3, 4 for amplitude and latency values). Despite the differences in the amplitude in both bands, there were no differences in their topographical distributions between groups (interactions for group and location factors). Regarding induced activity, the latency in which the maximum amplitude was reached was different for each cue condition (Figs.2, 3). This difference for the cue factor was observed both in the low alpha [F (1.50) = 0.77980; p < 0.001; η2 = 0.714] and upper alpha bands [F (1.50) = 6.3649; p = 0.014; η2 = 0.773]. A post-hoc Bonferroni comparison showed that the SC condition reached the maximum amplitude later than the CC condition (in both the low and upper alpha bands, p < 0.001) (Tables3, 4 for latency values). Despite the larger amplitude observed in the control group (Figs.2, 3), no statistically significant differences for group factor were observed throughout the expectancy interval divided into two time intervals (0–350ms and 350–700ms) or in its interaction with other location factors (Tables3, 4 for mean amplitude values). Table 2. Evoked and induced values for the gamma band (30–45Hz). MS: multiple sclerosis; HC: healthy controls; SD: standard deviation; NC: no cue; CC: central cue; SC: spatial cue. Latency (mean ± SD) Expectancy interval Target interval Conditions MS HC Conditions MS HC Evoked activity Evoked activity NC ––NC 199 ± 55 220 ± 53 CC ––CC 209 ± 46 186 ± 58 SC ––SC 201 ± 50 208 ± 58 Induced activity Induced activity NC ––NC 212 ± 82 214 ± 76 CC ––CC 212 ± 67 208 ± 72 SC 222 ± 29 210 ± 37 SC 224 ± 80 222 ± 63 Amplitude (mean ± SD) Expectancy interval Target interval Evoked activity Evoked activity NC − 0.11 ± 0.03 − 0.01 ± 0.04 NC 0.06 ± 0.10 0.06 ± 0.11 CC − 0.01 ± 0.05 − 0.02 ± 0.06 CC 0.06 ± 0.13 0.09 ± 0.08 SC 0.06 ± 0.08 − 0.01 ± 0.06 SC 0.01 ± 0.07 0.03 ± 0.07 Induced activity Induced activity NC 0.01 ± 0.28 0.01 ± 0.27 NC 0.45 ± 0.30 0.29 ± 0.36 CC 0.01 ± 0.20 − 0.03 ± 0.24 CC 0.50 ± 0.30 0.24 ± 0.40 SC 0.40 ± 0.27 0.24 ± 0.22 SC 0.16 ± 0.19 0.07 ± 0.21 5 Vol.:(0123456789) Scientific Reports | (2020) 10:20721 | https://doi.org/10.1038/s41598-020-77690-y www.nature.com/scientificreports/ Target interval. Evoked latency showed no significant differences between the two groups in the low alpha and upper alpha subbands (Figs.2, 3). HCs showed a larger amplitude than MS patients in both the low alpha [F (1.50) = 8.4645; p = 0.005; η2 = 0.242] and upper alpha bands [F (1.50) = 4.5503; p = 0.037; η2 = 0.125] (Figs.2, 3 and Tables3, 4 for amplitude and latency values). There were no differences in topographical distribution between groups. In the induced latency analysis, the interaction of group and cue factors was significant in both the low and upper alpha bands [F (2.204) = 81.212; p < 0.001; η2 = 0.599] [F (2.204) = 87.305; p < 0.001; η2 = 0.644] (Figs.2, 3).A post-hoc Bonferroni comparison showed that MS patients in the NC and CC conditions reached the maximum amplitude later than controls in both alpha subbands (p < 0.001). However, in the SC condition, there were no differences between groups in the latency in the low alpha or upper alpha bands (Figs.2, 3). With regard to the amplitude variable for induced modulation, no differences in topographical distribution were found for the group factor or its interaction with other location factors in either low alpha or upper alpha bands or in any time interval analyzed (0–350ms and 350–700ms) (Figs.2, 3 and Tables3, 4 for mean amplitude and latency values). Phase analysis for induced and evoked activity. After phase analyses were made for the evoked and induced activities in the frequency bands (low and upper alpha and gamma bands) and for both groups, it was possible to conclude that the potential contribution of the evoked activity over induced activity could be discarded in all bands, as has been described in previous studies52,55. Figure4 shows that the phase values of induced activity for HCs in the lower and upper alpha subbands and gamma band for the target stimuli following a central cue showed random values that were not concentrated in the phase value of the evoked activity. Similar results were observed in other cue conditions and for the MS group (see Figs.1–7 in supplementary material). Discussion The behavioral results suggested an attentional impairment in the MS group. A general slowing was observed (approximately 100ms) for MS patients in all cue conditions. Moreover, the delay in reaction times was not caused by a speed-accuracy tradeoff between experimental conditions for the patient group compared with the Figure2. (a) Evoked and induced waves for the low alpha band (8–10.5Hz) in the expectancy and target response intervals. (b) 2-D head maps for the peak and valley latencies of evoked and induced activity. Abbreviations: MS: multiple sclerosis; HC: healthy controls; NC: no cue; CC: Central cue; SC: spatial cue; ms: milliseconds. 6 Vol:.(1234567890) Scientific Reports | (2020) 10:20721 | https://doi.org/10.1038/s41598-020-77690-y www.nature.com/scientificreports/ HC group. In addition, the neuropsychological assessment revealed an attentional impairment that was not caused by severe signs of depression (low scores on the BDI). A delay in the reaction time for attentional tasks in MS patients has been described in previous studies18,56–58. With regard to the neural networks, the slower reaction times in the NC and CC conditions suggest that alerting mechanisms (phasic or tonic) could be impaired, as has been suggested by other studies16–18. Moreover, a longer reaction time in the SC condition also indicates that the orienting mechanism could also be affected, as previously described18. However, it seems unreasonable that such a common delay in all cue conditions (100ms) could be due to multiple and diverse impairments such as the phasic and tonic alerting or orientation mechanisms. It is not possible with the current results to discard that a common mechanism operating in all conditions could be the reason for the general slowing in the MS sample. A relevant result to better understand the attention impairment in the MS group comes from the data after the correction of Fernandez-Duque and Black53. A statistical t test group comparison in all cue conditions (e.g., NC MS vs NC HC) showed that the NC condition was responded to faster in the internal comparisons for MS patients than the same comparison in the HC group. This result suggests that MS patients try to be more ready for uncued targets that are more demanding in terms of response time. This approach could be a strategic compensation from MS patients to reduce the average reaction time for all the experimental conditions. However, a more intricate interpretation is suggested from neurophysiological measures, which will be described in the following paragraphs. Regarding the induced activity, the gamma band seems to be related to the translation of the attentional focus towards the cued visual spatial locations. The only condition in the expectancy interval that showed an increase in the gamma amplitude was the SC condition during which subjects were required to move their attentional focus to specific spatial regions indicated by cues (100% valid). On the other hand, during the NC or CC conditions, the attentional focus is maintained around a fixation point; therefore, no increase in the gamma activity is observed. In the case of the induced gamma response for target stimuli, the NC and CC conditions need an orienting response provoked by the onset of the stimuli and consequently a shifting of the attention focus towards it. This shift is translated as an increase in the amplitude of the gamma activity as it occurred in the SC condition for the Figure3. (a) Evoked and induced waves for the upper alpha band (10.5–13Hz) in the expectancy and target response intervals. (b) 2-D head maps for the peak and valley latencies of evoked and induced activity. Abbreviations: MS: multiple sclerosis; HC: healthy controls; NC: no cue; CC: central cue; SC: spatial cue; ms: milliseconds. 7 Vol.:(0123456789) Scientific Reports | (2020) 10:20721 | https://doi.org/10.1038/s41598-020-77690-y www.nature.com/scientificreports/ Table 3. Evoked and induced values for low alpha (8–10.5Hz) and upper alpha bands (10.5–13Hz) in the expectancy interval. MS: multiple sclerosis; HC: healthy controls; SD: standard deviation. NC: no cue; CC: central cue; SC: spatial cue. Latency (mean ± SD) Low alpha (8–10.5Hz) Upper alpha (10.5–13Hz) Conditions MS HC Conditions MS HC Evoked activity Evoked activity CC 173 ± 67 176 ± 45 CC 192 ± 78 164 ± 56 SC 183 ± 65 157 ± 42 SC 173 ± 70 187 ± 62 Induced activity Induced activity CC 403 ± 96 362 ± 158 CC 370 ± 80 441 ± 90 SC 542 ± 77 556 ± 68 SC 556 ± 60 519 ± 75 Amplitude (mean ± SD) Low alpha (8–10.5Hz) Upper alpha (10.5–13Hz) Evoked activity (0–350ms) Evoked activity (0–350ms) NC 0.004 ± 0.14 0.023 ± 0.12 NC 0.001 ± 0.09 0.015 ± 0.08 CC 0.155 ± 0.22 0.259 ± 0.23 CC 0.093 ± 0.14 0.160 ± 0.17 SC 0.181 ± 0.22 0.277 ± 0.23 SC 0.131 ± 0.16 0.181 ± 0.17 Induced activity (0–350ms) Induced activity (0–350ms) NC 0.103 ± 0.21 0.061 ± 0.23 NC 0.057 ± 0.15 0.084 ± 0.22 CC − 0.098 ± 0.24 − 0.145 ± 0.20 CC − 0.077 ± 0.17 − 0.110 ± 0.19 SC − 0.101 ± 0.19 − 0.129 ± 0.22 SC − 0.087 ± 0.14 − 0.101 ± 0.20 Induced activity (350–700ms) Induced activity (350–700ms) NC 0.053 ± 0.23 0.034 ± 0.22 NC 0.029 ± 0.16 0.067 ± 0.24 CC − 0.190 ± 0.34 − 0.248 ± 0.36 CC − 0.121 ± 0.28 − 0.168 ± 0.26 SC − 0.260 ± 0.48 − 0.277 ± 0.43 SC − 0.204 ± 0.38 − 0.207 ± 0.31 Table 4. Evoked and induced values for low alpha (8–10.5Hz) and upper alpha bands (10.5–13Hz) in the target interval. MS: multiple sclerosis; HC: healthy controls; SD: standard deviation. NC: no cue; CC: central cue; SC: spatial cue. Latency (mean ± SD) Low alpha (8–10.5Hz) Upper alpha (10.5–13Hz) Conditions MS HC Conditions MS HC Evoked activity Evoked activity NC 170 ± 55 167 ± 48 NC 172 ± 49 174 ± 66 CC 158 ± 57 172 ± 49 CC 167 ± 71 170 ± 63 SC 154 ± 52 158 ± 38 SC 155 ± 38 156 ± 44 Induced activity Induced activity NC 540 ± 81 404 ± 78 NC 487 ± 82 414 ± 76 CC 473 ± 72 195 ± 73 CC 466 ± 67 206 ± 72 SC 191 ± 80 178 ± 55 SC 183 ± 80 180 ± 63 Amplitude (mean ± SD) Low alpha (8–10.5Hz) Upper alpha (10.5–13Hz) Evoked activity (0–350ms) Evoked activity (0–350ms) NC 0.070 ± 0.36 0.353 ± 0.35 NC 0.141 ± 0.09 0.216 ± 0.08 CC 0.277 ± 0.31 0.410 ± 0.32 CC 0.134 ± 0.15 0.235 ± 0.17 SC 0.376 ± 0.34 0.476 ± 0.33 SC 0.218 ± 0.16 0.329 ± 0.17 Induced activity (0–350ms) Induced activity (0–350ms) NC − 0.183 ± 0.35 − 0.148 ± 0.26 NC − 0.106 ± 0.15 − 0.129 ± 0.22 CC − 0.106 ± 0.29 − 0.257 ± 0.33 CC − 0.071 ± 0.17 − 0.220 ± 0.19 SC − 0.177 ± 0.25 − 0.261 ± 0.23 SC − 0.128 ± 0.14 − 0.207 ± 0.20 Induced activity (350–700ms) Induced activity (350–700ms) NC − 0.360 ± 0.67 − 0.262 ± 0.56 NC − 0.270 ± 0.16 − 0.205 ± 0.24 CC − 0.300 ± 0.54 − 0.215 ± 0.57 CC − 0.203 ± 0.27 − 0.150 ± 0.26 SC − 0.208 ± 0.36 − 0.056 ± 0.54 SC − 0.099 ± 0.38 0.037 ± 0.31 8 Vol:.(1234567890) Scientific Reports | (2020) 10:20721 | https://doi.org/10.1038/s41598-020-77690-y www.nature.com/scientificreports/ Figure4. Plotting of phase values in the lower and upper alpha and gamma bands for evoked and induced activities and in the target response interval following the presentation of a central cue and for each healthy control subject (26 subjects). Evoked activity is represented by red, yellow and green dots, and induced activity is displayed with green, blue and red crosses for lower alpha (8–10.5Hz), upper alpha (10.5–13Hz) and gamma (30–45Hz) bands, respectively. 9 Vol.:(0123456789) Scientific Reports | (2020) 10:20721 | https://doi.org/10.1038/s41598-020-77690-y www.nature.com/scientificreports/ cue onset. In the case of the target preceded by the SC condition, a small increase in the gamma response could represent a lower need to readjust the attentional focus precisely over the central arrow to avoid competition from distractor stimuli. These results are in accordance with those of a previous study that showed that the orientation mechanism modulates gamma activity (without a specific definition of evoked or induced activity) in the first 200ms after the onset of the target47. Gamma band activity has been associated with an attentional mechanism involved in optimal performance in cognitive tasks37, 39. With regard to the group variable, a first consideration is that the peak latencies of the evoked or induced gamma activities were not different between both groups. It is well known that MS pathology usually implies delays in the timing of cognitive processes caused by the demyelination process59–61. However, there have been diverse studies that have not found latency delays in behavioral or EEG parameters in MS patients during the execution of cognitive tasks20,62. At the same time, the amplitude for induced gamma activity was higher for MS subjects than for the HC group. It is counterintuitive that the MS group exhibited a higher amplitude than and a similar latency to the HC group. However, if the functional meaning of the induced gamma modulation represents the translation of the attentional focus in the visual field, a possible interpretation is that the ability of the patients to adequately keep this focus in an appropriate location (e.g., on the fixation point) is impaired, and constant reorienting processes are needed with a consequent increase in the gamma amplitude. In this case, the gamma band reflects a compensatory mechanism rather than an impaired one. A corollary of this interpretation is that MS patients probably need to increase their engagement of alerting and orienting mechanisms to improve their reaction in each trial to relocate their attentional focus as fast as possible. The maintenance of this strategy to compensate for the deficit is probably the cause of cognitive fatigue observed in some cases among MS patients during sustained attention tasks63,64. Finally, it is necessary to comment about the difference between evoked and induced gamma activity. Notably, evoked gamma modulation was mainly present for the target stimuli, and induced activity was linked to both stimuli (cue and target). It could be suggested that evoked activity is only related to the relevant stimuli that require a motor response; in contrast, induced activity does not depend on that feature. Unfortunately, the present experiment does not allow further assessment of this issue, and future studies are necessary to disentangle the precise functional role of both gamma modulations in this respect. With regard to evoked activity that may mainly represent the alpha content of the early ERPs (P1 and N1), there was no difference between groups for the latency parameter. Therefore, it could be suggested that the described slowing in the latency of early ERPsin MS patients18,58,65,66 due to the demyelination was not observed in our data. However, other studies did not find differences in early visual ERP latency between HCs and patients with MS67. On the other hand, with regard to the amplitude parameter, previous studies have found lower amplitudes in the P1 component68 and N1-P2 complex69,70among MS patients. Our results are in agreement with these studies in terms of both the cue and target early evoked responses. This decrement in the amplitude could reflect that a lower number of neurons were synchronized to elicit the evoked response but at the same time preserved their connectivity, which maintained the appropriate latency. Other authors have interpreted similar results as an impaired mechanism of synchrony in the neural generators of the early visual processing in MS group71. With regard to the induced alpha activity, a clear negative trend was observed in the CC and SC conditions in the expectancy interval. It has been suggested that the onset of alpha desynchronization starting at approximately 300ms is a sign that the influence of the alpha band on cortical activity was disappearing and that other taskrelevant processes/bands took place25. This reduction of alpha synchronization observed in our study could also be in accordance with the findings of previous studies in which a decreased alpha band was linked to anticipatory attention (orienting network) with respect to the arrival of the target in a cue paradigm26. In the particular case of alpha modulations during the ANT, a study found a decrease in alpha activity (not distinguished between phase or nonphase) related to the alerting network from 200 to 450ms after the onset of the cue47. These authors indicated that this desynchronization could be related to the abrupt onset of the cue that engages an alerting response. However, in our study, the cue factor results from ANOVA indicated that the CC condition reached its highest value before the SC condition. We suggest that the reason for this difference may be the different information content involved in the two cues. The CC condition provides timing information, while the SC condition adds spatial information to the timing expectancy. The more information is added, the more latency is necessary to reach the maximum desynchronization. Previous studies have demonstrated in the time domain of EEG [contingent negative variation (CNV)] that the more spatial and timing information was given in the cue, the higher the amplitude of the CNV72. However, the CNV trend is maintained until the target stimuli are presented (at least in a one-second SOA), but induced alpha modulation reaches maximum negativity and starts recovering to the baseline level before the target appears. This last modulation seems to be more related to a specific mechanism in a determined time interval than to a sustained preparatory state for incoming stimuli. This difference between the CC and SC conditions observed in both alpha bands (low and upper) could indicate that both general (alerting) and specific (orienting) attentional mechanisms are recruited in the expectancy interval. In particular, some authors have suggested that the decrease in the upper alpha band may be related to anticipatory attention26or maintaining attentional focus73. With regard to the comparison between both experimental groups, no differences were found in the latency or amplitude. 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