Cognitive impairment

  • Cognitive Changes

What was the objective of this article?

The topic of cognitive impairment among people with MS is laced with confusion, uncertainty, and fear.  Studies demonstrating immense differences (40 to 65%) in the percentages of individuals with MS who will likely encounter changes in their cognitive functions only add to readers’ bewilderment.  Keeping in mind that the following article is rather old (2007), readers who slog their way through this challenging article will find that it helps to place the issue of cognitive impairment in perspective.


How did the authors study this issue?

The authors of this article approach cognitive impairment from the point of view of researchers trying to figure out how to identify, define, and measure cognitive impairment.  These are some of the questions they raise:  


  • How does cognitive impairment show up among individuals with MS?

Individuals with MS may find that different functions such as processing speed and verbal memory change.  


People with MS do not usually experience overall uniform cognitive decline. Tests for changes in information-processing speed and memory seem to be best indicators at this time.


  • How do investigators test for cognitive changes?

The authors argue that, instead of extensive and time-consuming batteries of tests, single tests such as the Paced Auditory Serial Addition Test (PASAT) and the Symbol Digit Modalities Test (SDMT) do a better job of assessing cognitive changes over time.  


Tests of phonemic (e.g., words beginning with a specified letter) and semantic (e.g., objects such as animals or fruits) fluency can be particularly useful in assessing these changes.


  • What happens to the brain that causes these changes?

This is one of the central barriers to understanding cognitive changes better.  If tests such as those described above sometimes detect changes in cognition even in individuals in the early stages of MS, then it is possible that brain tissue that appears completely normal in magnetic resonance imaging (MRI) is undergoing some type of change.  


Among individuals who have developed lesions that are visible in MRI testing, the position, number, and size of lesions may well influence different changes.  Just as lesions tend to dictate other symptoms of MS, each individual’s array of lesions may cause different responses to MS.  


More research and continuing improvements in imaging technology will help us to understand physical changes in the brain better.  


  • Does the brain compensate for these physical changes?

It appears to try to compensate.  Studies of blood flow in the brain seem to indicate that it attempts to re-route processing activity to other areas of the brain.  Again, more research and improved imaging technologies will help us to understand this process better.  

What are the challenges for healthcare providers trying to monitor cognitive changes in individuals with MS?

In addition to the limitations of our understanding of the brain and in the available imaging technologies mentioned above, the manner in which we assess the progress of the disease and even cognitive changes makes uniform testing difficult.  


As we know, MS progresses differently with different symptoms among individuals.  What, then, defines:


  • The stages of MS, or even what do we consider to be “early” MS?
  • The “cut-off” points for marking changes in cognition, especially if these changes affect a wide variety of changes in the speed and manner in which we process information?
  • The correlation between physical changes in the brain and processing and memory?


As with so many aspects of MS, support for further research into the way our brain functions with MS will help us to better understand this important issue.  

SHARE: facebook twitter linkedin google+ forward

Original Article

Cognitive impairment in multiple sclerosis

Stefanie Hoffmann, Marc Tittgemeyer adn D. Yves von Cramon

Current Opinion in Neurology

Purpose of review

For a long time, cognitive impairment in multiple sclerosis patients has been considered less important than, for instance, physical disability. This is no longer true because of the crucial role that cognitive deficits play in the good day-to-day adjustment of patients. This review highlights recent progress made in this area. A special focus lies on studies investigating the neural correlates of cognitive impairment in multiple sclerosis patients as detectable by conventional, quantitative and functional magnetic resonance imaging.


Recent findings

Measures of information-processing speed appear to be the most robust and sensitive markers of cognitive impairment in multiple sclerosis patients. Recent studies demonstrate that single, predominantly speed-related cognitive tests may be superior to extensive and time-consuming test batteries in screening overall cognitive decline. Quantitative magnetic-resonance-imaging findings suggest the extent of subtle tissue damage in normal-appearing white and grey matter to correlate best with the severity of cognitive impairment in multiple sclerosis patients.



From neuropsychological test data, and findings from magnetic resonance imaging and functional magnetic resonance imaging it is evident that cognitive impairment in multiple sclerosis is not just the result of tissue destruction, but rather a balance between tissue destruction, tissue repair, and adaptive functional reorganization.




Over the past two decades, cognitive impairment in multiple sclerosis has received increasing interest from neuroscientists. Although for a long time underestimated by clinicians, it is now accepted as a decisive feature especially in grasping the early stage of the disease. Its high impact on working and social abilities is now evident more than ever [1,2]. The basic constituents of cognitive dysfunction in multiple sclerosis are still under debate, its frequency and pattern varying considerably between and within patients. This is due primarily to the heterogeneity of the disease in its extent, its location and the dynamics of its pathomorphological processes. Secondly, considerable discrepancies are due to incomparable study designs [3*]. Recently, there has been a major attempt to address the nature of cognitive impairment by focusing on better-operationalized disease stages.


Another focus of current investigations attempts to explore and understand the cerebral correlates of cognitive impairment in multiple sclerosis. Hence, a great number of studies have applied conventional and quantitative magnetic resonance imaging (MRI) techniques to correlate the profile and degree of cognitive impairment with various MRI-detectable abnormalities [4* ,5]. Structural MRI findings have recently been extended by functional MRI studies scrutinizing the brain’s ability for adaptive functional reorganization in the presence of widespread tissue damage [6].


Assessment of cognitive impairment

Cognitive impairment occurs in 43–65% of patients with an established form of multiple sclerosis ([7]; another study [8] even reports 30–70%). It typically consists of differently intermingled domain-specific deficits rather than of a uniform overall cognitive decline. Deficient cognitive performance is predominantly apparent from tests measuring attention and information-processing speed, working memory, verbal and visuospatial memory, and executive functions [9].


Deficits on tests primarily measuring informationprocessing speed and working memory have been considered the most robust neuropsychological findings across various disease stages, and even in the very early phase of multiple sclerosis [10–18]. Using a computerized modification of the Paced Auditory Serial Addition Test (PASAT), a majority of multiple sclerosis patients revealed a speed/accuracy trade-off in information processing, with speed much more impaired than accuracy [19*]. Verbal and visuospatial memory or executive functions appear to provide less robust measures to monitor overall cognitive impairment in multiple sclerosis patients.


This has prompted studies about the question whether a single test, such as the PASAT, or rather a test battery covering a wide range of cognitive functions, provides better results in estimating the severity of cognitive impairment and in measuring changes over time. Recent research [20–23] identified single tests to be better suited to screening overall cognitive impairment than extensive and time-consuming test batteries. High rates of sensitivity could be proved for the Symbol Digit Modalities Test (SDMT) [20–22] and for the PASAT [23–26] (for a further discussion of scoring methods see [27,28]), the latter being included in the Multiple Sclerosis Functional Composite (MSFC). Noteworthy in this context, phonemic and semantic fluency are among the most sensitive neuropsychological measures as indicated by a recent meta-analysis [29]. It is very important to realize that the most sensitive tests are, in a way, ‘dirty tests’ as they assess a compound of various cognitive functions. It is true that they predominantly measure processing speed but in addition they address aspects of working memory and executive functions. Although the lack of specificity could be criticized for scientific reasons, the complexity of these tests appears to account for their high diagnostic usefulness. In a clinical setting, such dirty tests serve physicians as valuable tools to segregate patients with and without cognitive impairment. This does not preclude neuropsychologists from wishing for more elaborate testing to obtain, for instance, well defined starting points for individualized disease management.


Magnetic-resonance-imaging parameters related to cognitive impairment

Magnetic resonance imaging provides further means in a multiparametric approach to monitor a patient’s cognitive status, as it is highly susceptible to both structural and functional brain changes. In multiple sclerosis, MRI has been applied primarily to identify in vivo the extent and the severity of the pathological process underlying cognitive dysfunction. The assessment of the correlation between cognitive impairment and the severity of tissue abnormalities might provide new hypotheses about the underpinnings of the causal mechanisms.


As multiple sclerosis has been for a long time considered exclusively a focal inflammatory disorder, many studies have focused on the relationship between cognitive parameters and the extent of damage as detected with conventional, contrast-enhanced MRI. Three different approaches have been applied to examine this relationship: focusing on (i) the overall relationship, (ii) the relationship between lesion location and specific cognitive changes, and (iii) the relationship between MRI parameters and cognitive changes occurring within the progression of follow-up studies.


Regarding the overall relationship, correlations between cognitive test performance and several MRI measures such as lesion load or ventricular size have been reported [30–33]. When the amount of shared variance is examined between psychological test scores, lesion burden on conventional MRI, and clinical measures of physical disability, the shared variance between test scores and burden of disease was found to be an order of magnitude higher than that between scores and clinical measures of physical disability [34]. Thus, reasonable correlations are generally found between the extent of disease seen on MRI and cognitive function.


To enhance specificity, a considerable number of studies focus on identifying the relationship between the location of multiple sclerosis lesions and cognitive dysfunction. These studies fall into two general classes of examination: effects of ‘disconnection’ and effects of regionally circumscribed lesion load. Since focal lesions are quite common and often extensive in the cerebral white matter, disconnection syndromes would be expected to be common. In fact, reports of typical disconnection syndromes, such as conduction aphasia, for instance, have been quite uncommon. However, there are numerous correlations reported between the location of multiple sclerosis lesions and cognitive impairment [35–38]. Many of these studies suffer from conflicting results, which can partially be explained by the heterogeneous pathological substrate of multiple sclerosis lesions but mainly by the fact that there is no preferred region where lesions aggregate, besides, for instance, the periventricular white matter. Noteworthy, however, certain cortical areas, such as the cingulate gyrus, insula, and temporobasal cortices, seem to be more affected than others [39 ]. Possibly as a result of this, other regional analyses that rely on MRI assessment of internal or external atrophy or cortical thickness seem to account for more variance in cognitive performance of multiple sclerosis patients than lesion burden does [33,40]. However, there is still an ongoing debate on methodological issues involved in such MRI evaluation of atrophied and lesioned brains [41–43]. Beyond methodological concerns, particularly for multiple sclerosis, the significance of results is limited due to the lack of pathological specificity of contrast-enhanced MRI, the heterogeneous pathological substrate and its inability to detect magnetic-resonance-related diffuse changes in normalappearing brain tissue.


In follow-up studies conflicting results have been reported, with both an increase and a lack of change in cognitive impairment in relation to MRI parameters being seen. A major difference in these studies may be due to the period of follow-up and differences in patient selection, but a general limitation of conventional MRI derivations is the wide intra- and inter-patient variability and heterogeneity of MRI patterns of multiple sclerosis activity and evolution [44].


At present, two important trends can be observed in studying the structural substrates of cognitive dysfunction. First of all, there is mounting evidence of substantial grey-matter involvement [39* ,45–49]. Although it remains to be clarified whether cortical tissue damage is due to a primary degenerative disease process [50] or whether it reflects a consequence of widespread brain inflammation and microglial activation, or both (for a discussion see [51]), its contribution to cognitive impairment has been highlighted by several studies [33,52–56].


Secondly, the application of quantitative magnetic-resonance techniques, such as magnetization transfer imaging, diffusion tensor imaging and (single-) proton magneticresonance spectroscopy (1 H-MRS), has been shown to at least partially overcome the lack of pathological speci- ficity of conventional MRI [4*]. Such data have the potential to provide robust estimates of irreversible tissue damage in lesions as well as in normal-appearing brain tissue [57]. The evidence that normal-appearing white matter is far from normal remains central for understanding the mechanisms of tissue damage of multiple sclerosis. It has clearly been shown that the extent and severity of normal-appearing brain tissue alteration is more strikingly associated to cognitive impairment than the extent of focal pathology [58–63].


Based on the argument that measures of micro- and macroscopic tissue damage alone are not able to fully explain the pathological mechanisms underlying cognitive impairment in multiple sclerosis, recent functional MRI studies highlight the significance of adaptive functional reorganization for cognitive functioning, especially in early multiple sclerosis [6,64–73,74* ]. Using mainly tasks of information-processing speed and working memory, several studies demonstrated altered patterns of hemodynamic responses with patients activating different or additional brain regions as well as showing altered functional connectivity compared to controls. Since most multiple sclerosis patients had normal or only slightly impaired cognitive performance, it has been suggested that the observed changes in cerebral activation patterns are likely to have a compensatory role to limit the impact of tissue damage on patients’ cognitive abilities [75]. In particular, the study of Ranjeva et al. [76 ] emphasized that it is most likely that both structural and functional parameters contribute to the pathology of cognitive dysfunction in multiple sclerosis. Using a multiregression model, the authors demonstrated that parameters measuring the extent and location of tissue damage, cortical reorganization and the disturbance in brain connectivity are conjointly able to explain 90% of the variance in PASAT performance. Despite some reservations about the methodology underlying these parameters, this approach could be most helpful to provide deeper insights into the pathology of cognitive impairment in multiple sclerosis in the future.


Methodological issues

At present, there is increasing awareness of several serious methodological constraints hampering research of cognitive impairment in multiple sclerosis. Studies substantially differ with respect to methods and materials which might lead to a wide margin of error in understanding the profile of cognitive impairment in multiple sclerosis. Among the most important issues which ought to be discussed is the temporal definition of multiple sclerosis disease stages, and particularly in regard to its ‘early’ stage. Investigating cognitive impairment in this disease stage has received increased interest, especially in the context of justifying early disease-modifying therapy. In our view, Achiron et al. [77*] are right to criticize previous studies for the variance in defining the term early, ranging from several weeks up to several years after disease onset. They suggested that future investigations should adopt the clinical definition of the early phase of multiple sclerosis as either (i) immediately at the onset of new neurological symptoms of predominantly white-matter involvement suggestive of multiple sclerosis, or (ii) within the time until the occurrence of a second neurological event. These criteria are consistent with the definition of clinically isolated syndromes (CIS).


Additionally, there is no general agreement in defining reliable cut-off points for cognitive impairment. Mostly, deficits are defined in terms of statistically significant differences in the test performance of patients and controls. This procedure does not consider the high overlap in the performance of both groups and thus might lead to an overestimation of cognitive impairment in multiple sclerosis. Distinguishing between cognitively preserved and impaired multiple sclerosis patients is more appropriate: however, it remains for future studies to exactly and uniformly define cut-off points with respect to the magnitude of standard deviation and the number of failed neuropsychological tests.


Further limitations concern follow-up studies. Among others, considerable practice effects are well known for the majority of neuropsychological tests [3 ]. The best way to adequately interpret these effects is to compare the patient sample with a carefully matched control group at each follow-up evaluation.


Finally, studies differ considerably in statistical procedures. The link between cognitive functions and structural magnetic-resonance parameters is analysed by either a correlation or a regression analysis. Whereas in some studies individual neuropsychological test measures are separately correlated with structural parameters, other studies define summarized cognitive scores. We suggest that the application of multiple regression modelling techniques based on summarized cognitive and structural scores are more appropriate, as they require a more profound theoretical justification in defining explanatory and dependent variables and hence may lead to more precise and reliable findings.



There is increasing interest in understanding the nature of cognitive impairment in multiple sclerosis. Studies still address the frequency and pattern of cognitive deficits with special regard to early multiple sclerosis. Information-processing speed appears to be most consistently impaired irrespective of specific clinical features. Thus, so-called dirty, mainly speed-related, cognitive tests, such as the SDMT or PASAT, appear to be most appropriate to screen overall cognitive impairment and to determine which patients need full neuropsychological assessment by further testing. A considerable amount of actual research, however, investigates the glio-neuronal substrate of cognitive impairment in multiple sclerosis. The burden of brain MRI-visible lesions does not fully account for the degree of multiple sclerosis-related cognitive impairment. Modern quantitative MRI studies suggest that damage in normal-appearing brain tissue significantly contributes to cognitive impairment. Irrespective of the underlying mechanisms, the functional relevance of grey-matter involvement has been emphasized recently. Functional MRI investigations at least partially extend our understanding about the link between structural magnetic-resonance parameters and the severity of cognitive impairment. The observed changes in brain activation in multiple sclerosis patients are assumed to be compensatory to limit the impact of tissue damage on cognitive functioning. Hence, cognitive impairment in multiple sclerosis seems to be not just the result of tissue destruction, but also rather a balance between tissue destruction, tissue repair and adaptive functional reorganisation. Future studies could adopt this assumption by applying combinations of structural and functional MRI measures for investigating cognitive impairment in multiple sclerosis. They should further agree on statistical procedures, reliable cut-off points for cognitive impairment and an exact definition of disease stages.


We thank Schering Germany for their financial support of our work in the domain of cognitive impairment in early multiple sclerosis.


References and recommended reading

Papers of particular interest, published within the annual period of review, have been highlighted as:

* of special interest

** of outstanding interest Additional references related to this topic can also be found in the Current World Literature section in this issue (p. 362).

1 Rao SM, Leo GJ, Ellington L, et al. Cognitive dysfunction in multiple sclerosis. II. Impact on employment and social functioning. Neurology 1991; 41:692–696.

2 Benedict RH, Wahlig E, Bakshi R, et al. Predicting quality of life in multiple sclerosis: accounting for physical disability, fatigue, cognition, mood disorder, personality, and behavior change. J Neurol Sci 2005; 231:29–34.

3 * Jonsson A, Andresen J, Storr L, et al. Cognitive impairment in newly diagnosed multiple sclerosis patients: a 4-year follow-up study. J Neurol Sci 2006; 245:77–85. This prototype paper presents data from a 4-year follow-up study of cognitive impairment in newly diagnosed multiple sclerosis with a yearly re-examination. It discusses important methodological limitations such as the problem of practice effects when administering cognitive tests repeatedly.

4 * Rovaris M, Comi G, Filippi M. MRI markers of destructive pathology in multiple sclerosis-related cognitive dysfunction. J Neurol Sci 2006; 245: 111–116. This is a comprehensive review on the neuronal markers of multiple sclerosisrelated cognitive impairment bringing together data from conventional MRI studies, brain-atrophy assessment and quantitative MRI studies. It gives an excellent survey of new quantitative MRI techniques and underlines their importance for the pathogenesis of cognitive deficits in multiple sclerosis.

5 Tekok-Kilic A, Benedict RH, Zivadinov R. Update on the relationships between neuropsychological dysfunction and structural MRI in multiple sclerosis. Expert Rev Neurother 2006; 6:323–331.

6 Mainero C, Pantano P, Caramia F, Pozzilli C. Brain reorganization during attention and memory tasks in multiple sclerosis: insights from functional MRI studies. J Neurol Sci 2006; 245:93–98.

7 Rao SM, Leo GJ, Bernardin L, Unverzagt F. Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction. Neurology 1991; 41:685– 691.

8 Amato MP, Ponziani G, Siracusa G, Sorbi S. Cognitive dysfunction in earlyonset multiple sclerosis: a reappraisal after 10 years. Arch Neurol 2001; 58:1602–1606.

9 Zakzanis KK. Distinct neurocognitive profiles in multiple sclerosis subtypes. Arch Clin Neuropsychol 2000; 15:115–136.

10 Pelosi L, Geesken JM, Holly M, et al. Working memory impairment in early multiple sclerosis. Evidence from an event-related potential study of patients with clinically isolated myelopathy. Brain 1997; 120:2039–2058.

11 DeSonneville LMJ, Boringa JB, Reuling IEW, et al. Information processing characteristics in subtypes of multiple sclerosis. Neuropsychologia 2002; 40:1751–1765.

12 Landro NI, Celius EG, Sletvold H. Depressive symptoms account for deficient information processing speed but not for impaired working memory in early phase multiple sclerosis (MS). J Neurol Sci 2004; 217:211–216.

13 Olivares T, Nieto A, Sanchez MP, et al. Pattern of neuropsychological impairment in the early phase of relapsing-remitting multiple sclerosis. Mult Scler 2005; 11:191–197.

14 McCarthy M, Beaumont JG, Thompson R, Peacock S. Modality-specific aspects of sustained and divided attentional performance in multiple sclerosis. Arch Clin Neuropsychol 2005; 20:705–718.

15 Parmenter BA, Shucard JL, Benedict RH, Shucard DW. Working memory deficits in multiple sclerosis: comparison between the n-back task and the Paced Auditory Serial Addition Test. J Int Neuropsychol Soc 2006; 12:677– 687.

16 Nocentini U, Pasqualetti P, Bonavita S, et al. Cognitive dysfunction in patients with relapsing-remitting multiple sclerosis. Mult Scler 2006; 12:77–87.

17 Schulz D, Kopp B, Kunkel A, Faiss JH. Cognition in the early stage of multiple sclerosis. J Neurol 2006; 253:1002–1010.

18 Feuillet L, Reuter F, Audoin B, Malikova I. Early cognitive impairment in patients with clinically isolated syndrome suggestive of multiple sclerosis. Mult Scler 2007; 13:124–127.

19 * Lengenfelder J, Bryant D, Diamond BJ, et al. Processing speed interacts with working memory efficiency in multiple sclerosis. Arch Clin Neuropsychol 2006; 21:229–238. An elegant paper that demonstrates the usefulness of experimental modification of cognitive tests in order to increase its specificity with respect to singular cognitive functions. It indicates that information processing speed rather than working memory seems to be the primary deficit in the majority of multiple sclerosis patients.

20 Deloire MS, Bonnet MC, Salort E, et al. How to detect cognitive dysfunction at early stages of multiple sclerosis? Mult Scler 2006; 12:445–452.

21 Sepulcre J, Vanotti S, Hernandez R, et al. Cognitive impairment in patients with multiple sclerosis using the Brief Repeatable Battery-Neuropsychology test. Mult Scler 2006; 12:187–195.

22 Parmenter BA, Weinstock-Guttman B, Garg N, et al. Screening for cognitive impairment in multiple sclerosis using the Symbol Digit Modalities Test. Mult Scler 2007; 13:52–57.

23 Rosti E, Hamalainen P, Koivisto K, Hokkanen L. The PASAT performance among patients with multiple sclerosis: analyses of responding patterns using different scoring methods. Mult Scler 2006; 12:586–593.

24 Fisk JD, Archibald CJ. Limitations of the Paced Auditory Serial Addition Test as a measure of working memory in patients with multiple sclerosis. J Int Neuropsychol Soc 2001; 7:363–372.

25 Solari A, Radice D, Manneschi L, et al. The multiple sclerosis functional composite: different practice effects in the three test components. J Neurol Sci 2005; 228:71–74.

26 Williams J, O’Rourke K, Hutchinson M, Tubridy N. The Face-Symbol Test and the Symbol-Digit Test are not reliable surrogates for the Paced Auditory Serial Addition Test in multiple sclerosis. Mult Scler 2006; 12:599–604.

27 Coo H, Hopman WM, Edgar CM, et al. The Paced Auditory Serial Addition Test: to what extent is it performed as instructed, and is it associated with disease course? Mult Scler 2005; 11:85–89.

28 Balzano J, Chiaravalloti N, Lengenfelder J, et al. Does the scoring of late responses affect the outcome of the paced auditory serial addition task (PASAT)? Arch Clin Neuropsychol 2006; 21:819–825.

29 Henry JD, Beatty WW. Verbal fluency deficits in multiple sclerosis. Neuropsychologia 2006; 44:1166–1174.

30 Rovaris M, Filippi M, Falautano M, et al. Relation between MR abnormalities and patterns of cognitive impairment in multiple sclerosis. Neurology 1998; 50:1601–1608.

31 Nocentini U, Rossini PM, Carlesimo GA, et al. Patterns of cognitive impairment in secondary progressive stable phase of multiple sclerosis: correlations with MRI findings. Eur Neurol 2001; 45:11–18.

32 Benedict RH, Weinstock-Guttman B, Fishman I, et al. Prediction of neuropsychological impairment in multiple sclerosis: comparison of conventional magnetic resonance imaging measures of atrophy and lesion burden. Arch Neurol 2004; 61:226–230.

33 Benedict RH, Bruce JM, Dwyer MG, et al. Neocortical atrophy, third ventricular width, and cognitive dysfunction in multiple sclerosis. Arch Neurol 2006; 63:1301–1306.

34 Miller DH, Grossman RI, Reingold SC, McFarland HF. The role of magnetic resonance techniques in understanding and managing multiple sclerosis. Brain 1998; 121:3–24.

35 Anzola GP, Bevilacqua L, Cappa SF, et al. Neuropsychological assessment in patients with relapsing-remitting multiple sclerosis and mild functional impairment: correlation with magnetic resonance imaging. J Neurol Neurosurg Psychiatry 1990; 53:142–145.

36 Miki Y, Grossman RI, Udupa JK, et al. Isolated U-fiber involvement in MS: preliminary observations. Neurology 1998; 50:1301–1306.

37 Comi G, Rovaris M, Falautano M, et al. A multiparametric MRI study of frontal lobe dementia in multiple sclerosis. J Neurol Sci 1999; 171:135–144.

38 Sperling RA, Guttmann CR, Hohol MJ, et al. Regional magnetic resonance imaging lesion burden and cognitive function in multiple sclerosis: a longitudinal study. Arch Neurol 2001; 58:115–121.

39 * Kutzelnigg A, Lassmann H. Cortical demyelination in multiple sclerosis: a substrate for cognitive deficits? J Neurol Sci 2006; 245:123–126. An interesting description of the distribution and pattern of cortical demyelinated plaques. Band-like subpial demyelination may indeed escape the detection by current magnetic resonance technology.

40 Charil A, Dagher A, Lerch JP, et al. Focal cortical atrophy in multiple sclerosis: relation to lesion load and disability. Neuroimage 2007; 34:509–517.

41 Mehta S, Grabowski TJ, Trivedi Y, Damasio H. Evaluation of voxel-based morphometry for focal lesion detection in individuals. Neuroimage 2003; 20:1438–1454.

42 Rorden C, Karnath HO. Using human brain lesions to infer function: a relic from a past era in the fMRI age? Nat Rev Neurosci 2004; 5:813– 819.

43 Stamatakis EA, Tyler LK. Identifying lesions on structural brain images– validation of the method and application to neuropsychological patients. Brain Lang 2005; 94:167–177.

44 Filippi M, Grossman RI. MRI techniques to monitor MS evolution: the present and the future. Neurology 2002; 58:1147–1153.

45 De Stefano N, Matthews PM, Filippi M, et al. Evidence of early cortical atrophy in MS: relevance to white matter changes and disability. Neurology 2003; 60:1157–1162.

46 Davies GR, Ramio-Torrenta L, Hadjiprocopis A, et al. Evidence for grey matter MTR abnormality in minimally disabled patients with early relapsingremitting multiple sclerosis. J Neurol Neurosurg Psychiatry 2004; 75:998– 1002.

47 Kutzelnigg A, Lucchinetti CF, Stadelmann C, et al. Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain 2005; 128:2705– 2712.

48 Oreja-Guevara C, Rovaris M, Iannucci G, et al. Progressive gray matter damage in patients with relapsing-remitting multiple sclerosis: a longitudinal diffusion tensor magnetic resonance imaging study. Arch Neurol 2005; 62:578–584.

49 Rovaris M, Gallo A, Valsasina P, et al. Short-term accrual of gray matter pathology in patients with progressive multiple sclerosis: an in vivo study using diffusion tensor MRI. Neuroimage 2005; 24:1139–1146.

50 Lassmann H. Brain damage when multiple sclerosis is diagnosed clinically. Lancet 2003; 361:1317–1318.

51 Compston A. Making progress on the natural history of multiple sclerosis. Brain 2006; 129:561–563.

52 Amato MP, Bartolozzi ML, Zipoli V, et al. Neocortical volume decrease in relapsing-remitting MS patients with mild cognitive impairment. Neurology 2004; 63:89–93.

53 Morgen K, Sammer G, Courtney SM, et al. Evidence for a direct association between cortical atrophy and cognitive impairment in relapsing-remitting MS. Neuroimage 2005; 30:891–898.

54 Brass SD, Benedict RH, Weinstock-Guttman B, et al. Cognitive impairment is associated with subcortical magnetic resonance imaging grey matter T2 hypointensity in multiple sclerosis. Mult Scler 2006; 12:437–444.

55 Portaccio E, Amato MP, Bartolozzi ML, et al. Neocortical volume decrease in relapsing-remitting multiple sclerosis with mild cognitive impairment. J Neurol Sci 2006; 245:195–199.

56 Sanfilipo MP, Benedict RH, Weinstock-Guttman B, Bakshi R. Gray and white matter brain atrophy and neuropsychological impairment in multiple sclerosis. Neurology 2006; 66:685–692.

57 Filippi M, Dousset V, McFarland HF, et al. Role of magnetic resonance imaging in the diagnosis and monitoring of multiple sclerosis: consensus report of the White Matter Study Group. J Magn Reson Imaging 2002; 15:499–504.

58 Filippi M, Tortorella C, Rovaris M, et al. Changes in the normal appearing brain tissue and cognitive impairment in multiple sclerosis. J Neurol Neurosurg Psychiatry 2000; 68:157–161.

59 Deloire MS, Salort E, Bonnet M, et al. Cognitive impairment as marker of diffuse brain abnormalities in early relapsing remitting multiple sclerosis. J Neurol Neurosurg Psychiatry 2005; 76:519–526.

60 Rovaris M, Iannucci G, Falautano M, et al. Cognitive dysfunction in patients with mildly disabling relapsing-remitting multiple sclerosis: an exploratory study with diffusion tensor MR imaging. J Neurol Sci 2002; 195:103– 109.

61 Foong J, Rozewicz L, Davie CA, et al. Correlates of executive function in multiple sclerosis: the use of magnetic resonance spectroscopy as an index of focal pathology. J Neuropsychiatry Clin Neurosci 1999; 11:45– 50.

62 Mathiesen HK, Jonsson A, Tscherning T, et al. Correlation of global N-acetyl aspartate with cognitive impairment in multiple sclerosis. Arch Neurol 2006; 63:533–536.

63 Sorensen PS, Jonsson A, Mathiesen HK, et al. The relationship between MRI and PET changes and cognitive disturbances in MS. J Neurol Sci 2006; 245:99–102.

64 Audoin B, Au Duong MV, Ranjeva JP, et al. Magnetic resonance study of the influence of tissue damage and cortical reorganization on PASAT performance at the earliest stage of multiple sclerosis. Hum Brain Mapp 2005; 24:216–228.

65 Au Doung MV, Boulanouar K, Audoin B, et al. Modulation of effective connectivity inside the working memory network in patients at the earliest stage of multiple sclerosis. Neuroimage 2005; 24:533–538.

66 Buckle GJ. Functional magnetic resonance imaging and multiple sclerosis: the evidence for neuronal plasticity. J Neuroimaging 2005; 15:82S– 93S.

67 Chiaravalloti N, Hillary F, Ricker J, et al. Cerebral activation patterns during working memory performance in multiple sclerosis using FMRI. J Clin Exp Neuropsychol 2005; 27:33–54.

68 Pantano P, Mainero C, Caramia F. Functional brain reorganization in multiple sclerosis: evidence from fMRI studies. J Neuroimaging 2006; 16:104– 114.

69 Audoin B, Au Duong MV, Malikova I, et al. Functional magnetic resonance imaging and cognition at the very early stage of MS. J Neurol Sci 2006; 245:87–91.

70 Rachbauer D, Kronbichler M, Ropele S, et al. Differences in cerebral activation patterns in idiopathic inflammatory demyelination using the paced visual serial addition task: an fMRI study. J Neurol Sci 2006; 244:11–16.

71 Bobholz JA, Rao SM, Lobeck L, et al. fMRI study of episodic memory in relapsing-remitting MS: correlation with T2 lesion volume. Neurology 2006; 67:1640–1645.

72 Forn C, Barros-Loscertales A, Escudero J, et al. Cortical reorganization during PASAT task in MS patients with preserved working memory functions. Neuroimage 2006; 31:686–691.

73 Sweet LH, Rao SM, Primeau M, et al. Functional magnetic resonance imaging response to increased verbal working memory demands among patients with multiple sclerosis. Hum Brain Mapp 2006; 27:28–36.

74 * Cader S, Cifelli A, Abu-Omar Y, et al. Reduced brain functional reserve and altered functional connectivity in patients with multiple sclerosis. Brain 2006; 129:527–537. The paper includes an interesting reflection on the question as to whether altered functional interactions between brain regions normally recruited provide an alternative adaptive mechanism with multiple sclerosis pathology.

75 Rocca MA, Filippi M. Toward a better understanding of cerebral plasticity in multiple sclerosis. J Neurol Sci 2006; 244:1–2.

76 * Ranjeva JP, Audoin B, Au Duong MV, et al. Structural and functional surrogates of cognitive impairment at the very early stage of multiple sclerosis. J Neurol Sci 2006; 245:161–167. An innovative study using a multiregression model to demonstrate the importance of both morphological and functional MRI parameters for explaining cognitive performance in multiple sclerosis.

77 * Achiron A, Barak Y. Cognitive changes in early MS: a call for a common framework. J Neurol Sci 2006; 245:47–51. An important paper calling for a consensus with respect to the temporal criteria of early multiple sclerosis, the definition of cognitive impairment and the application of neuropsychological tools. It provides an excellent survey of studies investigating cognitive impairment in early multiple sclerosis.

Full Article

Subscribe to Our Newsletter

Receive all the latest MS News directly to your inbox!