Neural correlates of alerting and orienting impairment in multiple sclerosis patients

Manuel Vázquez-Marrufo, Alejandro Galvao-Carmona, Javier J González-Rosa, Antonio R Hidalgo-Muñoz, Mónica Borges, Juan Luis Ruiz-Peña, Guillermo Izquierdo, Manuel Vázquez-Marrufo, Alejandro Galvao-Carmona, Javier J González-Rosa, Antonio R Hidalgo-Muñoz, Mónica Borges, Juan Luis Ruiz-Peña, Guillermo Izquierdo

Abstract

Background: A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test.

Results: After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (p<0.05). ANOVAs showed for the patient group a significant latency delay for P1 and N1 components (p<0.05) and a decrease of P3 amplitude for congruent and incongruent stimuli (p<0.01). With regard to correlation analysis, PASAT-3s and SDMT showed significant correlations with behavioral measures of the Attention Network Test (p<0.01) and an ERP parameter (CNV amplitude).

Conclusions: Behavioral data are highly correlated with the neuropsychological scores and show that the alerting and orienting mechanisms in the patient group were impaired. Reduced amplitude for the Contingent Negative Variation in the patient group suggests that this component could be a physiological marker related to the alerting and orienting impairment in relapsing-remitting multiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention impairment, which could help in the assessment and treatment of relapsing-remitting multiple sclerosis patients.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1. Experimental procedure.
Figure 1. Experimental procedure.
The possible combinations for sets of cues and targets were six: No cue congruent (NC-C), No cue incongruent (NC-I), Central cue congruent (CC-C), Central cue incongruent (CC-I), Spatial cue congruent (SC-C) and Spatial cue incongruent (SC-I).
Figure 2. 58 scalp electrodes recorded and…
Figure 2. 58 scalp electrodes recorded and sets of electrodes analyzed for each ERP (CNV, P1, N1 and P3) studied.
Figure 3. Contingent Negative Variation modulations at…
Figure 3. Contingent Negative Variation modulations at Cz electrode and topographic maps.
Figure 4. P3 component modulations at Pz…
Figure 4. P3 component modulations at Pz electrode and topographic maps.
Figure 5. Correlation analyses.
Figure 5. Correlation analyses.
Neuropsychological score (PASAT-3s) and mean reaction time (upper panel); Accuracy in the Attention Network Test and SDMT score (middle panel), and CNV amplitude and SDMT score (lower panel).

References

    1. Chiaravalloti ND, DeLuca J (2008) Cognitive impairment in multiple sclerosis. Lancet Neurol 7(12): 1139–1151.
    1. Paul RH, Beatty WW, Schneider R, Blanco C, Hames K (1998) Impairments of attention in individuals with multiple sclerosis. Mult Scler 4(5): 433–439.
    1. Prakash RS, Snook EM, Lewis JM, Motl RW, Kramer AF (2008) Cognitive impairments in relapsing-remitting multiple sclerosis: a meta-analysis. Mult Scler 14(9): 1250–1261.
    1. Benedict RH, Zivadinov R (2011) Risk factors for and management of cognitive dysfunction in multiple sclerosis. Nat Rev Neurol 7(6): 332–342.
    1. Tur C, Penny S, Khaleeli Z, Altmann DR, Cipolotti L, et al. (2011) Grey matter damage and overall cognitive impairment in primary progressive multiple sclerosis. Mult Scler 17(11): 1324–1332.
    1. Filippi M, Riccitelli G, Mattioli F, Capra R, Stampatori C, et al. (2012) Multiple sclerosis: effects of cognitive rehabilitation on structural and functional MR Imaging measures—An explorative study. Radiology 262(3): 932–940.
    1. Rossi F, Giorgio A, Battaglini M, Stromillo ML, Portaccion E, et al. (2012) Relevance of brain lesion location to cognition in relapsing multiple sclerosis. PLoS One 7(11): e44826.
    1. Leocani L, González-Rosa JJ, Comi G (2010) Neurophysiological correlates of cognitive disturbances in multiple sclerosis. Neurol Sci 31(2): S249–S253.
    1. González-Rosa JJ, Vázquez-Marrufo M, Vaquero E, Duque P, Borges M, et al. (2011) Cluster analysis of behavioural and event-related potentials during a contingent negative variation paradigm in remitting-relapsing and benign forms of multiple sclerosis. BMC Neurol 11: 64.
    1. Lori S, Portaccio E, Zipoli V, Giannini M, Scarpelli S, et al. (2011) Cognitive impairment and event-related potentials in paediatric multiple sclerosis: 2-year study. Neurol Sci 32(6): 1043–1046.
    1. Whelan R, Lonergan R, Kiiski H, Nolan H, Kinsella K, et al. (2010) A high-density ERP study reveals latency, amplitude, and topographical differences in multiple sclerosis patients versus controls. Clin Neurophysiol 121(9): 1420–1426.
    1. Magnano I, Aiello I, Piras MR (2006) Cognitive impairment and neuropshysiological correlates in MS. J Neurol Sci 245(1–2): 117–122.
    1. Fan J, McCandliss BD, Sommer T, Raz A, Posner MI (2002) Testing the efficiency and independence of attentional networks. J Cogn Neurosci 14(3): 340–347.
    1. Fan J, McCandliss BD, Fossella J, FLombaum JI, Posner MI (2005) The activation of attentional networks. Neuroimage 26(2): 471–479.
    1. Fernández-Duque D, Posner MI (1997) Relating the mechanisms of orienting and alerting. Neuropsychologia 35(4): 477–486.
    1. Callejas A, Lupiàñez J, Funes MJ, Tudela P (2005) Modulations among the alerting, orienting and executive control networks. Exp Brain Res 167(1): 27–37.
    1. McConnell MM, Shore DI (2011) Mixing measures: testing an assumption of the Attention Network Test. Atten Percept Psychophys 73(4): 1096–1107.
    1. Neuhaus AH, Urbanek C, Opgen-Rhein C, Hahn E, Ta TM, et al. (2010) Event-related potentials associated with Attention Network Test. Int J Psychophisiol 76(2): 72–79.
    1. Kratz O, Studer P, Malcherek S, Erbe K, Moll GH, et al. (2011) Attentional processes in children with ADHD: an event-related potential study using the attention network test. Int J Psychophysiol 81(2): 82–90.
    1. Missonnier P, Herrmann FR, Richiardi J, Rodríguez C, Deiber MP, et al. (2013) Attention-related potentials allow for a highly accurate discrimination of mild cognitive impairment subtypes. Neurodegener Dis 12(2): 59–70.
    1. Gómez CM, Marco J, Grau C (2003) Preparatory visuo-motor cortical network of the contingent negative variation estimated by current density. Neuroimage 20(1): 216–224.
    1. Tecce JJ (1972) Contingent negative variation (CNV) and psychological processes in man. Psychol Bull 77(2): 73–108.
    1. Rohrbaugh JW, Gaillard AWK (1983) Sensory and motor aspects of the contingent negative variation. In: Gaillard AWK, Ritter W, editors. Tutorials in Event Related Potential Research: Endogenous Components. Amsterdam: North-Holland. pp. 269–310.
    1. Omisade A, Fisk JD, Klein RM, Schmidt M, Darvesh S, et al. (2012) Information processing and magnetic resonance imaging indices of brain pathology in multiple sclerosis. Int J MS care 14: 84–91.
    1. Urbanek C, Weinges-Evers N, Bellmann-Strobl J, Bock M, Dörr J, et al. (2010) Attention Network Test reveals alerting network dysfunction in multiple sclerosis. Mult Scler 16(1): 93–99.
    1. Crivelli L, Farez MF, González CD, Fiol M, Amengual A, et al. (2012) Alerting network dysfunction in early multiple sclerosis. J Int Neuropsychol Soc 18(4): 757–763.
    1. Kiiski H, Reilly RB, Lonergan R, Kelly S, ÓBrien M, et al. (2011) Change in PASAT performance correlates with change in P3 ERP amplitude over a 12-month period in multiple sclerosis patients. J Neurol Sci 305(1–2): 45–52.
    1. Kiiski H, Whelan R, Lonergan R, Nolan H, Kinsella K, et al. (2011) Preliminary evidence for correlation between PASAT performance and P3a and P3b amplitudes in progressive multiple sclerosis. Eur J Neurol 18(5): 792–795.
    1. Poser CM, Paty DW, Scheinberg L, McDonald WI, Davis FA, et al. (1983) New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 13(3): 227–231.
    1. Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33(11): 1444–1452.
    1. Gronwall DMA (1977) Paced auditory serial-addition task: a measure of recovery from concussion. Percept Mot Skills 44(2): 367–373.
    1. Tombaugh TN (2006) A comprehensive review of the Paced Auditory Serial Addition Test (PASAT). Arch Clin Neuropsychol 21(1): 53–76.
    1. Smith A (1968) The symbol-digit modalities test: a neuropsychologic test of learning and other cerebral disorders. In: Helmuth J, editor. Learning Disorders. Seattle: Special Child Publications. pp. 83–91.
    1. Smith A (1982) Symbol Digits Modalities Test. Los Angeles: Western Psychological Services.
    1. Sepulcre J, Vanotti S, Hernández R, Sandoval G, Cáceres F, et al. (2006) Cognitive impairment in patients with multiple sclerosis using the Brief Repeatable Battery-Neuropsychology test. Mult Scler 12(2): 187–195.
    1. Beck AT, Steer RA, Ball R, Ranieri W (1996) Comparison of Beck Depression Inventories -IA and –II in psychiatric outpatients. J Pers Assess 67(3): 588–597.
    1. Beck AT, Steer RA, Brown GK (1996) Manual for the Beck Depression Inventory-II. San Antonio: Psychological Corporation.
    1. Duncan CC, Barry RJ, Connolly JF, Fisher C, Michie PT, et al. (2009) Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clin Neurophysiol 120(11): 1883–1908.
    1. Polich J (1986) P300 development from auditory stimuli. Psychophisiology 23(5): 590–597.
    1. Fernández-Duque D, Black SE (2006) Attentional Networks in Normal Aging and Alzheimer's Disease. Neuropychology 20(2): 133–143.
    1. Kail R (1998) Speed of information processing in patients with multiple sclerosis. J Clin Exp Neuropsychol 20(1): 98–106.
    1. De Sonneville LM, Boringa JB, Reuling IE, Lazeron RH, Adér HJ, et al. (2002) Information processing characteristics in subtypes of multiple sclerosis. Neuropychologia 40(11): 1751–1765.
    1. VaezMousavi SM, Barry RJ (1993) Positive and negative shifts of the readiness potential: preparatory effects. Int J Psychophysiol 15(2): 105–113.
    1. Baker KS, Mattingley JB, Chambers CD, Cunnington R (2011) Attention and the readiness for action. Neuropsychologia 49(12): 3303–3313.
    1. Gómez CM, Delinte A, Vaquero E, Cardoso MJ, Vázquez M, et al. Current source density analysis of CNV during temporal gap paradigm. Brain Topogr 13(3): 149–159.
    1. González-Rosa JJ, Vázquez-Marrufo M, Vaquero E, Duque P, Borges M, et al. (2006) Differential cognitive impairment for diverse forms of multiple sclerosis. BMC Neurosci 19: 7–39.
    1. Neuhaus AH, Trempler NR, Hahn E, Luborzewski A, Karl C, et al. (2010) Evidence of specificity of a visual P3 amplitude modulation deficit in schizophrenia. Schizophr Res 124(1–3): 119–126.
    1. Yin X, Zhao L, Xu J, Evans AC, Fan L, et al. (2012) Anatomical substrates of the alerting, orienting and executive control components of attention: focus on the posterior parietal lobe. PLoS One 7(11): e50590.
    1. Arnett PA, Strober LB (2011) Cognitive and neurobehavioral features in multiple sclerosis. Expert Rev Neurother 11(3): 411–424.
    1. Wojtowicz M, Omisade A, Fisk JD (2013) Indices of cognitive dysfunction in relapsing-remitting multiple sclerosis: intra-individual variability, processing speed and attention network efficiency. J Int Neuropsychol Soc 19(5): 551–558.

Source: PubMed

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