Neurology India
menu-bar5 Open access journal indexed with Index Medicus
  Users online: 2699  
 Home | Login 
About Editorial board Articlesmenu-bullet NSI Publicationsmenu-bullet Search Instructions Online Submission Subscribe Videos Etcetera Contact
  Navigate Here 
 Resource Links
  »  Similar in PUBMED
 »  Search Pubmed for
 »  Search in Google Scholar for
 »Related articles
  »  Article in PDF (1,118 KB)
  »  Citation Manager
  »  Access Statistics
  »  Reader Comments
  »  Email Alert *
  »  Add to My List *
* Registration required (free)  

  In this Article
 »  Abstract
 » Introduction
 »  Materials and Me...
 » Results
 » Discussion
 » Conclusion
 »  References
 »  Article Figures
 »  Article Tables

 Article Access Statistics
    PDF Downloaded42    
    Comments [Add]    
    Cited by others 1    

Recommend this journal


Table of Contents    
Year : 2016  |  Volume : 64  |  Issue : 6  |  Page : 1233-1242

Effects of white matter microstructure lesions on language and memory function in magnetic resonance imaging-negative temporal lobe epilepsy determined by diffusion tensor imaging

1 Neurology Division One, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
2 Radiology Imaging Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China

Date of Web Publication11-Nov-2016

Correspondence Address:
Dr. Huiqin Xu
Neurology Division One, The First Affiliated Hospital of Wenzhou Medical University, No. 2 Fuxue Lane, Wenzhou City, Zhejiang Province - 325000
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0028-3886.193839

Rights and Permissions

 » Abstract 

Objectives: This study was conducted to investigate the associations between white matter lesions and language and memory dysfunctions in patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy.
Materials and Methods: This study included 26 patients with temporal lobe epilepsy, who did not have significant findings on conventional MRI scanning, and 17 healthy subjects as control. Diffusion tensor imaging data was obtained with a 3Tesla (T) MRI scanner. Neuropsychological scores of language and memory functions were measured. One-way analysis of variance was used to analyze abnormal fractional anisotropy and mean diffusivity values. Correlations were performed to evaluate the relationship between fractional anisotropy/mean diffusivity of each fiber tract and neuropsychological measures. Regression analysis was performed to determine the contribution of each fiber tract to cognitive performance.
Results: Our data showed significantly decreased neuropsychological scores in the left and right temporal lobe epilepsy groups compared with control; it however, failed to show a statistical difference between the two groups. For the left temporal lobe epilepsy group, the mean diffusivity of the left parahippocampal and cingulate cortex, right arcuate fasciculus, and left fornix were significantly higher than control. Fractional anisotropy of the right fornix and mean diffusivity of the left uncinate fasciculus were significantly related to confrontational naming scores. There were significant correlations between the fractional anisotropy of the left fornix and verbal delayed memory scores and between the fractional anisotropy of the left fornix and nonverbal delayed memory scores. The mean diffusivity of left fractional anisotropy and the fractional anisotropy of the left uncinate fasciculus were significantly related to confrontational naming and verbal fluency scores, and seizure frequency was significantly related to nonverbal delayed memory scores.
Conclusions: Language and memory function impairment was correlated with white matter structural integrity.

Keywords: Diffusion tensor imaging; fractional anisotropy; fiber tracking; magnetic resonance imaging; mean diffusivity; temporal lobe epilepsy

How to cite this article:
Narenmandula B, Zhou X, Li Y, Tu D, Bao Y, Zheng R, Xu H. Effects of white matter microstructure lesions on language and memory function in magnetic resonance imaging-negative temporal lobe epilepsy determined by diffusion tensor imaging. Neurol India 2016;64:1233-42

How to cite this URL:
Narenmandula B, Zhou X, Li Y, Tu D, Bao Y, Zheng R, Xu H. Effects of white matter microstructure lesions on language and memory function in magnetic resonance imaging-negative temporal lobe epilepsy determined by diffusion tensor imaging. Neurol India [serial online] 2016 [cited 2021 Jun 17];64:1233-42. Available from:

 » Introduction Top

Temporal lobe epilepsy (TLE) is the most common symptomatic epilepsy, accounting for 70 to 80% of refractory epilepsy. Patients with TLE often possess cognitive impairment of memory, language function, learning ability, intelligence quotient, executive function, etc.

Early studies have shown that the degree of left hippocampal sclerosis is related to semantic memory decline.[1] It is also reported that there is severe recent-memory impairment following bilateral temporal lobectomy. These studies suggest that hippocampal structures are related to memory function in patients with TLE.[2] With the development of neuroimaging, it has been observed that widespread bilateral cortical lesions outside the hippocampus are involved in cognitive function. The abnormality of widespread areas may be due to the secondary changes induced by frequent seizures that originate from the temporal lobe.[3] Some researchers believe that these multi-regional cortical abnormalities effect memory and language impairment.[4],[5] Therefore, white matter structures that connects the cortical and subcortical areas remain in focus as the main areas producing these disorders. It has been reported that local white matter lesions alone influence memory and language functions in patients with TLE.[6],[7] In addition, some studies point out that the age of onset and the duration of TLE also affect patients' memory and language functions.[1],[8],[9] Studies have also shown that an early intervention prevents cognitive function from undergoing further damage in these patients.[1]

For several TLE patients, the conventional magnetic resonance imaging (MRI) fails to display significant hippocampal sclerosis or any other diseases, and this type of epilepsy is called “MRI-negative TLE.”[10],[11] The conditions of these patients are often more serious than that seen in refractory epilepsy. However, due to unobvious neuroimaging changes, an early therapeutic intervention in these patients is often neglected. Some studies suggest that patients with TLE but without mesial temporal sclerosis show diffusion tensor imaging (DTI) abnormalities of the white matter. In contrast, other evidences suggest that, in TLE without mesial temporal sclerosis, DTI abnormalities are not as extensive and severe as in TLE with mesial temporal sclerosis.[12],[13] In the presence of MRI-negative TLE, it is important to understand the relationship between the anatomic lesion and the existing cognitive impairment for assessment and for instituting an early intervention.

Diffusion MRI is a new neuroimaging technique that can demonstrate ultrastructural tissue changes that cannot be displayed by the conventional MRI, by measuring the relative motility of water within a voxel called “mean diffusivity (MD),” and its directionality called “fractional anisotropy (FA).”[14] A higher MD reflects the expansion of extracellular space of fiber whereas a lower FA reflects factors such as demyelination and axonal injury of fibers, which are important for understanding the presence of a neurological disease. DTI tractography is an extension of DTI that provides an in vivo method for quantifying and visualizing the integrity of white matter tracts. It offers a unique tool for investigating the relationship between the compromise of specific white matter tracts and the associated cognitive impairment existing in the patient.[14],[15]

Recently, few researchers have been exploring the relationship between white matter fiber lesions and cognitive performance by fiber tracking. These studies have shown that the structural integrity of white matter fibers is related to language and memory functions, and some of the white matter lesions alone affect language and memory performance. For memory function, studies have shown that increased MD of the left uncinate fasciculus (UF), left parahippocampal and cingulate gyri (PHC), and left inferior frontal occipital fasciculus (IFOF) are related to verbal memory, and that increased MD of bilateral arcuate fasciculus (AF) and decreased FA of the right AF are also related to verbal memory. With respect to language, increased MD and decreased FA of the AF and UF are related to naming performance. Furthermore, regression analyses reveal that fiber tract integrity of AF, UF, and IFOF independently predicts naming scores after controlling the hippocampal volume.[16] Studies have shown that lesions of the fornix (FORX) are related to immediate memory.[1] The purpose of our study is to assess the relationship between language and memory functional impairment and the integrity of white matter structures in patients with MRI-negative TLE.

 » Materials and Methods Top


In this study, 26 patients with TLE and 17 healthy controls were investigated. The inclusion criteria of the patients with TLE were: (i) A definitive diagnosis of TLE established in the epilepsy outpatient clinic of the neurology department of our hospital from February 2005 to October 2012; (ii) video electroencephalogram (VEEG) (Nicolet One EEG system, VIASYS Healthcare Inc., Madison, WI, USA), clearly revealing unilateral temporal epileptiform discharges; (iii) no seizures in 24 hours prior to image acquisition; (iv) appropriate level of education to complete neuropsychological testing; and (v) right-handedness of the patient. The exclusion criteria of the study were: (i) Abnormalities of the hippocampus or hippocampal atrophy seen on high-resolution MRI; (ii) the patient unable to cooperate or complete the experimental task; and, (iii) coexisting mental or other nervous system disorders. Demographic and clinical data were obtained through interviews with the patients and their relatives. The diagnosis and lateralization of seizure foci were established by a comprehensive evaluation, including a detailed seizure history, neurological examination, VEEG, neuroimaging, and neuropsychology. TLE mainly manifests as generalized and complex partial seizures, and neurological examination usually has normal results. The attack often starts with an aura such as a feeling of gaseous abdominal distension and/or mood disorders. In addition, other mental or central nervous symptoms are also common. When the aura terminates, gazing or automatic movements of the mouth or digestive tract occur, which are accompanied by progressive consciousness disorders. Secondary generalized convulsions may also occur. However, the left TLE is generally not easy to distinguish from the right TLE based on the clinical symptoms. The differentiation of the two is mainly based on EEG findings. The control group consisted of 17 right-handed healthy volunteers with matched age, gender, and education level. This study was approved by the Ethics Committee of Wenzhou Medical University, and the informed consent forms were signed by all the subjects.

TLE patients were divided into the left TLE group (n = 13) and right TLE group (n = 13), according to the findings evident on intermittent VEEG.

Neuropsychological evaluation

China-revised Wechsler Memory Scale [17] was used to evaluate immediate memory (IM), verbal delayed memory (VDM), and nonverbal delayed memory (NVDM). The first project of the fourth part in the Chinese translated version of Western Aphasia Battery (WAB)[18] was used to evaluate confrontational naming (CN), whereas the second project of the fourth part of WAB was used to evaluate verbal fluency (VF).

Image acquisition

MRI was performed on a General Electric 3.0 T EXCITE HD scanner (General Electric, Waukesha, WI, USA) with an eight-channel phased array head coil. To exclude obvious lesions and hippocampal atrophy, image acquisition included a conventional three-plane localizer, as well as sagittal T1 fast spin echo (FSE), axial T2FSE, axial T1 fluid-attenuated inversion recovery (FLAIR), axial T2FLAIR, and coronal T2FLAIR hippocampal phase sequences. DTI data were acquired using a single-shot spin-echo, echo planar image (SE-EPI) sequence. The diffusion sensitizing gradients were applied simultaneously along 30 non-collinear directions (b = 1000 s/mm 2); an acquisition without diffusion weighing (b = 0) was also obtained. Moreover, 37 contiguous slices were acquired with a 3-mm slice thickness without any gap. Other acquisition parameters were repetition time (TR) =10000 ms, echo-time (TE) =75.7 ms, number of excitations (NEX) =2, a 128 × 128 matrix, and a 24 × 24 cm field of view (FOV).

Data processing

DTI datasets were transferred to a personal computer running Windows and processed using DTIstudio analysis software (H. Jiang and S. Mori, Johns Hopkins University and Kennedy Krieger institute, or[14] Images were first realigned using the automated image registration (AIR) program,[19] in order to remove any potential, small bulk motions that occurred during the scans. After tensor diagonalization, 3 eigenvalues and eigenvectors were obtained and FA maps were calculated. The eigenvector associated with the largest eigenvalue was used as an indicator for fiber orientation. In the DTI color maps, red, green, and blue colors were assigned to right–left, anterior–posterior, and superior-inferior orientations, respectively.[15]

Fiber tracking and calculations

For three-dimensional (3D) tract reconstruction, the fibers were assigned by continuous tracking or FACT method,[20],[21] in which PHC, IFOF, and AF were used with a fractional anisotropy threshold of 0.2 and a principal eigenvector turning angle threshold of 40°, whereas FORX and UF were used with a fractional anisotropy threshold of 0.2 and a principal eigenvector turning angle threshold of 60°. Fiber tracking was performed by the DTIstudio software [Figure 1]. A multi-region of interest (ROI) approach was used to reconstruct tracts of interest which exploited existing anatomical knowledge of tract trajectories. A description of the tracking protocol is provided in our previous papers.[15],[22] Then, the mean FA and MD value were measured on these target fiber bundles.
Figure 1: Axial and sagittal views of the five fiber tracts in a healthy subject. Each fiber bundle was tracked, overlaid on the corresponding apparent diffusion coefficient maps, and finally colored. These procedures were completed on the DTIStudio software. (a) Left parahippocampal cingulum (PHC); (b) Left inferior fronto-occipital fasciculus (IFOF); (c) Left arcuate fasciculus (AF); (d) Left fornix (FORX); (e) Left uncinate fasciculus (UF). Color-coding was included to assist in the identification of the fibers and did not provide information regarding fiber orientation

Click here to view

Statistical analyses

One-way analysis of variance (ANOVA) was performed to examine group differences in FA, MD, and each neuropsychological measure. The relationships between age and education-adjusted test scores and FA/MD of each fiber tract were evaluated using Spearman rho correlations. Regression analyses were then performed to determine the contributions of each fiber tract and TLE pathogenic factors (including age at initial onset, disease duration, seizure frequency, and the number of antiepileptic drugs [AEDs] with cognitive adverse effects) to cognitive performances in patients with TLE, after controlling the factors of age of the patient and their level of education.

 » Results Top

Basic statistics

To test if significant differences exist between the groups, and if pathogenic factors have adverse effects, the age, educational level, and gender composition of the participants were compared. The age and educational level of all groups are compared with one-way ANOVA, and sex ratios of the three groups were analyzed by using Fisher's exact probability test [Table 1].
Table 1: Age and educational levels of all groups (means±SD), compared by one-way analysis of variance and sex ratio of the three groups, analyzed by Fisher's exact probability test

Click here to view

More detailed clinical information of the patients with TLE is shown in [Table 2]. The mean age at initial onset was 19.2 ± 7.8 (range 5–42) years; the mean disease duration was 12.6 ± 9.4 (range 1–43) years; and, the mean seizure frequency was 3.1 ± 2.1 (range 1–10) per month.
Table 2: Clinical information of the patients

Click here to view

All patients were regularly taking AEDs, including valproate, carbamazepine, topiramate, lamotrigine, levetiracetam, and oxcarbazepine. Previous studies have shown that some AEDs, such as topiramate,[23] valproate,[24] and carbamazepine,[25],[26] have adverse effects on cognitive function, whereas lamotrigine,[27] levetiracetam,[28],[29] and oxcarbazepine [30] have minimal or even no cognitive adverse effects. The use of concurrent medications appears to increase the likelihood of cognitive adverse effects with AEDs such as valproate,[31] carbamazepine,[32] and topiramte.[33],[34] [Table 3] shows the constituent ratio of AEDs with cognitive adverse effects in the left TLE group and the right TLE group analyzed by chi-square test, suggesting that cognitive adverse effects between the two groups of AEDs were not significantly different in the distribution (P = 0.158).
Table 3: Constituent ratio of antiepileptic drugs with cognitive adverse effects in the left temporal lobe epilepsy group and the right temporal lobe epilepsy group (%) analyzed by chi-square test

Click here to view

These results suggest that no statistically significant difference existed among the three groups regarding age, educational level, and gender distribution, and that there was no difference in the type of AEDs being administered as well as the cognitive adverse effects between the left and right TLE groups.

Neuropsychological scores were decreased and mean diffusivity was increased in left and right temporal lobe epilepsy groups

To examine group differences in FA, MD, and each neuropsychological measure, one-way analysis of variance (ANOVA) test was performed. Data analysis showed significantly decreased neuropsychological scores in the left TLE and right TLE groups compared with the control group (P < 0.05), however, it failed to show statistical difference between the neuropsychological scores of the left TLE and the right TLE groups (P > 0.05) [Table 4]. For the left TLE group, the MD of the left PHC, right AF, and left FORX were all significantly higher than that of the control group [Table 5]. However, no differences were observed for patients between right TLE and left TLE in cognitive performances and FA/MD. These data suggest that neuropsychological scores were decreased and MD was increased in both the left TLE and right TLE groups compared with the control group.
Table 4: The neuropsychological test scores of language and memory function for the left temporal lobe epilepsy group, right temporal lobe epilepsy group, and the control group. Data are expressed as means±SD

Click here to view
Table 5: The fiber fractional anisotropy (FA) and mean diffusivity (MD) values for the left TLE group, right TLE group and the control group. Data are expressed as means±SD

Click here to view

Fractional anisotropy/mean diffusivity of some fibers significantly correlated with the neuropsychological scores

To evaluate the relationships between age and education-adjusted test scores and FA/MD of each fiber tract, Spearman rho correlations were used. Regarding the language functions, by controlling the factor of the level of education and age, MD of the left FORX [Figure 2]a, FA of the right FORX [Figure 2]b and FA of the left UF [Figure 2]c were significantly related to the VF scores. In addition, FA of the right FORX [Figure 2]d and FA of the left UF [Figure 2]e were significantly related to CN scores. FA of the left FORX was strongly related to the IM scores [Figure 2]f, and there may be a correlation between the MD of the right AF and the IM score. Regarding the memory functions, there was a significant correlation between the FA of the left FORX and the NVDM score [Figure 2]g, and between the FA of left FORX and the VDM score [Figure 2]h. In addition, a positive correlation between the FA of fibers and neuropsychological scores, and a negative correlation between FA or MD of other fibers and neuropsychological scores were found [Figure 2]a-h. However, no significant correlation between other FA or MD of other fibers and neuropsychological scores was observed. Therefore, these data suggested that FA/MD of some fibers significantly correlated the neuropsychological scores.
Figure 2: Scatter plots displaying the relationship between neuropsychological test performance and fractional anisotropy (FA) or mean diffusivity (MD) of selected fiber tracts in patients with MRI-negative temporal lobe epilepsy. (a) Scatter plot showing that MD of fibers and neuropsychological performance are negatively correlated. (b-h) Scatter plots showing that FA of fibers and neuropsychological performance are positively correlated. Only results with statistical significance (P < 0.05) are shown in the scatter plots. Horizontal axis represents FA/MD of fibers. Corresponding fiber tracts include the fornix (FORX) and uncinate fasciculus (UF). Vertical axis represents the neuropsychological scores. Corresponding neuropsychological indices include confrontational naming (CN), verbal fluency (VF), verbal delayed memory (VDM), nonverbal delayed memory (NVDM), and immediate memory (IM). r, correlation coefficient.

Click here to view

Left arcuate fasciculus and left uncinate fasciculus independently affected language-related scale scores whereas seizure frequency affected nonverbal delayed memory scores

To determine the contribution of each fiber tract and the pathogenic factors responsible for TLE, to the cognitive performance in patients with TLE, a regression analysis was performed. After controlling the level of education, the MD of the left AF, and the FA of the left UF, were significantly related to the CN scores. The MD of the left AF and the FA of left UF were able to account for 44% of the variance in CN scores. In addition, the MD of left AF and the FA of left UF were significantly associated with the VF scores. The MD of the left AF and the FA of the left UF were able to account for 52% of the variance in the VF scores. After controlling for the level of education, the seizure frequency and the NVDM scores significantly correlated. The MD of left AF and the FA of left UF were able to account for 35% of the variance in the NVDM scores. No other variables were found to be significant contributors to the prediction of the neuropsychological scores. These data indicated that the left AF and left UF independently affected the language-related scale scores, whereas seizure frequency affected the NVDM scores.

 » Discussion Top

The decreased neuropsychological scores of both the left and right TLE patients demonstrate impairment of their cognitive functions. However, there was no statistical difference between the neuropsychological scores of the left and the right TLE groups. This result is consistent with the result obtained in the study by McDonald et al., which demonstrated that cognitive impairments of the left MRI-negative TLE patients and that of the right MRI-negative TLE patients do not show any statistically significant difference.[35]

Our results also suggest that there are local white matter lesions in MRI-negative patients with TLE. We observed an increased MD for the left PHC, the left FORX, and the right AF in left TLE patients. The increased MD value suggests an increase in the extracellular space of nerve fibers, which indirectly reflects on the existence of lesions.[36],[37] For the left TLE patients, left FORX and left PHC are located in ipsilateral epileptogenic medial temporal lobe regions, and are vulnerable to attacks. Concha et al., found that patients with TLE and hippocampal sclerosis have decreased FA values for the ipsilateral hippocampal sclerosis region with increased MD values, as well as decreased FA value, in MRI-negative TLE patients.[38] Right AF lesions indicate damage to the left TLE regions of the temporal lobe in contralateral outer epileptic foci, suggesting the presence of a broad range of lesions. However, our study did not show the microstructure of white matter lesions for right TLE patients. This concurs with some previous reports.[39]

The results of the correlation analysis suggest that there was a correlation between the number of fibers and cognitive performance. For language function, we found that the left UF was related to CN and VF, and that increased MD of the left UF was associated with the decline of CN. These results were similar to the results of McDonald et al.,[35] and Hayashi et al.[40] Our study showed that there was an association between the left UF and VF naming function because the UF fibers are connected to the medial temporal lobe and the medial frontal lobe. Although no change in the left UF was found, the correlation change in the MD of the left UF with language function was consistent with the studies of McDonald et al.,[35] and Shinoura et al.,[41] in which they found that the changes in the MD value of the left UF were associated with the changes in language function; they speculated that the structural integrity of the left UF would affect language features.

Our study also indicated that bilateral FORX involvement affects language function. Decreased FA of the right FORX is related with the decline of CN and VF, whereas FA of the left FORX is related to VF. Most literature suggests that FORX is involved in memory-related cognitive activity, but does not participate in language information processing.[35],[42] Therefore, we propose that the FORNX of both the sides may be responsible for language as a compensatory mechanism due to the preexisting impaired neural network responsible for language function. However, this needs further investigation.

Of note, our study has not found correlation of AF and IFOF with language function. DTI studies have shown that the left AF and CN function are closely related, and that the integrity of the right AF is also involved in language function. In addition to AF, the left IFOF plays an important role in language function. IFOF takes part in the subcortical pathways of the semantic system.[35]

Regarding memory function, the left FORX shows a strong association with the function of immediate memory, and it is also related to the VDM and NVDM. This result in our study was consistent with the results of Kern et al.,[43] even though McDonald et al., showed that the impairment of FORX plays a minor role in memory activity in TLE.[35]

Our results revealed that the integrity of the left FORX (especially in left TLE) was damaged, and that compromise of the left FORX correlated with decreased memory function. These results may have been obtained due to the fact that the FORX may serve as the main neural pathway that takes part in the process of converting immediate memory into long-term memory.[16] However, our results have not shown that UF and PHC correlated with memory function. UF, the main nerve fiber that connects the inferior frontal and the anterior temporal lobe, plays a key role in episodic and semantic memory activity. McDonald et al., noted that an increased MD of the left UF was associated with semantic memory activity. In addition, PHC connects the medial temporal region and the posterior cingulate cortex, and is a major component of the Papaz Circuit. McDonald et al., reported that an increased MD of the left PHC has a strong correlation with the semantic memory decline in TLE patients.[35]

Regarding the DTI index, we observed that language and memory functions might strongly correlate with changes in the FA instead of changes in the MD [Figure 2]a-h. The result suggested that the change in FA might be more sensitive than the change in MD in influencing predictive and cognitive functions. We, therefore, propose that the change in FA reflects the pathological features of nerve axons, whereas the change in MD reflects the expanded extracellular space of the fiber. In addition, we noted a positive correlation between the FA of fibers and the neuropsychological scores, and a negative correlation between the MD of fibers and the neuropsychological scores. This suggests that verbal memory function declines as fiber bundle axonal lesions and extracellular spaces increase.[44]

The use of concurrent medications, including some AEDs such as valproate,[31],[32] carbamazepine,[32] and topiramate,[33],[34] appears to increase the possibility of cognitive adverse effects. In addition to AEDs, the age of onset, duration, and the frequency of seizures may also influence language and memory functions.[8],[15] It has been reported that education [45] and age [46] influence the cognitive function, and that the degree of hippocampal atrophy is the main factor influencing these functions.[38] Therefore, in our statistical analyses, we have made efforts to control these two factors and to exclude patients with hippocampus atrophy.

Our study indicates that the MD of left AF and FA of left UF independently impact CN and VF after controlling for the education levels. This result concurs with that of McDonalds et al., who also noted that left AF and left UF had an independent contribution to language function.[35] Similar result have also been reported by Shinoura et al.[41]

The left AF connects the perisylvian frontal, parietal, and temporal cortex in the left cerebral hemisphere, and has an important role in regulating the naming function. The left UF connects the mesial temporal structures and the mesial frontal region, and has some impact on language function.[47] The study found that the frequency of seizures affects VDM. Regression analysis showed that language and memory performance are the overall combined effects of multiple factors.[35]

Except for the correlation between the left FORX lesions and verbal memory function, our results have not shown fiber bundle disease, which may be associated with language and memory performance deficiencies. However, most results of the correlation analysis are consistent with the previous findings of other studies on TLE. These findings further confirm that the integrity of white matter in TLE patients correlated with the performance of language and memory. It is also important to note that the correlation between DTI index changes in white matter fiber tracts and the performance of language and memory may also exist in patients with TLE associated with hippocampal atrophy.

However, there are some limitations in the study. First, the technique of fiber tracking may differ in different studies. DTIstudio software is often used to draw multiple regions of interests (ROIs) to determine fiber bundles. In some cases, attention should be paid to the positional change of the head position while selecting the ROI (especially when selecting the first ROI). At the regions of fiber bifurcation, excess fiber bundles have to be removed. We find that the form of each fiber is of significant difference to the individuals. Deleting the excessive fibers may introduce some artificial errors.[48] Second, the decreased FA and increased MD are often interpreted as white matter degeneration. In fact, decreased FA can have multiple interpretations, including an axonal packaging density decrease, the existinece of demyelination, or the presence of cross-bundle fibers. However, histological confirmation is still needed.[48] Third, it is not known if similar results would be obtained in the presence of other disease groups. In our next study, we will add further disease groups to test whether these DTI anomalies are characteristic of the temporal lobe epilepsy disease group only or may also occur in other diseases. Fourth, the small sample size was also a main factor influencing the results. In future studies, we will increase the sample size to further verify the results.

 » Conclusion Top

In conclusion, we correlated the ultrastructural alterations in the local white matter tracts in patients with MRI-negative temporal lobe epilepsy (using DTI technology) with the presence of cognitive impairments in these patients (assessed by a number of neuropsychological assessment tests). Correlation and regression analysis have also shown that there was a correlation between language and memory functional impairments with the white matter structural integrity. The study suggested that although language and memory functions of patients with MRI-negative temporal lobe epilepsy are influenced by multiple factors, an important facts that emerged was that some white matter fibers can affect language function independently. The study also showed that DTI is a sensitive neuroradiological technique for identifying lesions that may not be visible on the conventional MRI screening.


This work was supported by grants for Zhejiang Provincial Health Department funded projects (2010KYA133).

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

 » References Top

Bell B, Lin JJ, Seidenberg M, Hermann B. The neurobiology of cognitive disorders in temporal lobe epilepsy. Nat Rev Neurol 2010;7:154-64.  Back to cited text no. 1
Squire LR. Memory and brain systems: 1969–2009. J Neurosci 2009;29:12711-6.  Back to cited text no. 2
Inoue Y, Mihara T. Awareness and responsiveness during partial seizures. Epilepsia 39 Suppl 1998;5:7-10.  Back to cited text no. 3
Hermann B, Seidenberg M, Bell B, Rutecki P, Sheth RD, Wendt G, et al. Extratemporal quantitative MR volumetrics and neuropsychological status in temporal lobe epilepsy. J Int Neuropsychol Soc 2003;9:353-62.  Back to cited text no. 4
Focke NK, Thompson PJ, Duncan JS. Correlation of cognitive functions with voxel-based morphometry in patients with hippocampal sclerosis. Epilepsy Behav 2008;12:472-6.  Back to cited text no. 5
Seidenberg M, Hermann B, Pulsipher D, Morton J, Parrish J, Geary E, et al. Thalamic atrophy and cognition in unilateral temporal lobe epilepsy. J Int Neuropsychol Soc 2008;14:384-93.  Back to cited text no. 6
Geary EK, Seidenberg M, Hermann B. Atrophy of basal ganglia nuclei and negative symptoms in temporal lobe epilepsy. J Neuropsychiatry Clin Neurosci 2009;21:152-9.  Back to cited text no. 7
Baxendale S, Thompson P, Harkness W, Duncan J. Predicting memory decline following epilepsy surgery: A multivariate approach. Epilepsia 2006;47:1887-94.  Back to cited text no. 8
Binder JR, Sabsevitz DS, Swanson SJ, Hammeke TA, Raghavan M, Mueller WM. Use of preoperative functional MRI to predict verbal memory decline after temporal lobe epilepsy surgery. Epilepsia 2008;49:1377-94.  Back to cited text no. 9
Gok B, Jallo G, Hayeri R, Wahl R, Aygun N. The evaluation of FDG-PET imaging for epileptogenic focus localization in patients with MRI positive and MRI negative temporal lobe epilepsy. Neuroradiology 2013;55:541-50.  Back to cited text no. 10
LoPinto-Khoury C, Sperling MR, Skidmore C, Nei M, Evans J, Sharan A, et al. Surgical outcome in PET-positive, MRI-negative patients with temporal lobe epilepsy. Epilepsia 2012;53:342-8.  Back to cited text no. 11
Gross DW, Concha L, Beaulieu C. Extratemporal white matter abnormalities in mesial temporal lobe epilepsy demonstrated with diffusion tensor imaging. Epilepsia 2006;47:1360-3.  Back to cited text no. 12
Thivard L, Lehéricyc S, Krainike A, Adam C, Dormont D, Chiras J, et al. Diffusion tensor imaging in medial temporal lobe epilepsy with hippocampal sclerosis. Neuroimage 2005;28:682-90.  Back to cited text no. 13
Jiang H, van Zijl PC, Kim J, Pearlson GD, Mori S. DtiStudio: Resource program for diffusion tensor computation and fiber bundle tracking. Comput Methods Programs Biomed 2006;81:106-16.  Back to cited text no. 14
Wakana S, Caprihan A, Panzenboeck MM, Fallon JH, Perry M, Gollub RL, et al. Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 2007;36:630-44.  Back to cited text no. 15
Schmahmann JD, Pandya D. Fiber pathways of the brain. USA: Oxford University Press; 2010.  Back to cited text no. 16
Gong YX. Revised Wechsler Memory Scale Manual. Hunan: Mapping Press; 1989.  Back to cited text no. 17
Shewan CM, Kertesz A. Reliability and validity characteristics of the Western Aphasia Battery (WAB). J Speech Hear Disord 1980;45:308-24.  Back to cited text no. 18
Woods RP, Grafton ST, Holmes CJ, Cherry SR, Mazziotta JC. Automated image registration: I. General methods and intrasubject, intramodality validation. J Comput Assist Tomogr 1998;22:139-52.  Back to cited text no. 19
Mori S, Crain BJ, Chacko VP, van Zijl PC. Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol 1999;45:265-9.  Back to cited text no. 20
Xue R, van Zijl PC, Crain BJ, Solaiyappan M, Mori S. In vivo three-dimensional reconstruction of rat brain axonal projections by diffusion tensor imaging. Magn Reson Med 1999;42:1123-7.  Back to cited text no. 21
Wakana S, Jiang H, Nagae-Poetscher LM, van Zijl PC, Mori S. Fiber tract-based atlas of human white matter anatomy. Radiology 2004;230:77-87.  Back to cited text no. 22
Bootsma HP, Aldenkamp AP, Diepman L, Hulsman J, Lambrechts D, Leenen L, et al. The effect of antiepileptic drugs on cognition: Patient perceived cognitive problems of topiramate versus levetiracetam in clinical practice. Epilepsia 2006;2 (47 Suppl):24-7.  Back to cited text no. 23
Ristić AJ, Vojvodić N, Janković S, Sindelić A, Sokić D. The frequency of reversible parkinsonism and cognitive decline associated with valproate treatment: A study of 364 patients with different types of epilepsy. Epilepsia 2006;47:2183-5.  Back to cited text no. 24
Aikiä M, Jutila L, Salmenperä T, Mervaala E, Kälviäinen R. Long-term effects of tiagabine monotherapy on cognition and mood in adult patients with chronic partial epilepsy. Epilepsy Behav 2006;8:750-5.  Back to cited text no. 25
Shehata GA, Bateh Ael-A, Hamed SA, Rageh TA, Elsorogy YB. Neuropsychological effects of antiepileptic drugs (carbamazepine versus valproate) in adult males with epilepsy. Neuropsychiatr Dis Treat 2009;5:527-33.  Back to cited text no. 26
Bootsma HP, Vos AM, Hulsman J, Lambrechts D, Leenen L, Majoie M, et al. Lamotrigine in clinical practice: Long-term experience in patients with refractory epilepsy referred to a tertiary epilepsy center. Epilepsy Behav 2008;12:262-8.  Back to cited text no. 27
Levisohn PM, Mintz M, Hunter SJ, Yang H, Jones J. Neurocognitive effects of adjunctive levetiracetam in children with partial-onset seizures: A randomized, double-blind, placebo-controlled, noninferiority trial. Epilepsia 2009;50:2377-89.  Back to cited text no. 28
Huang CW, Pai MC, Tsai JJ. Comparative cognitive effects of levetiracetam and topiramate in intractable epilepsy. Psychiatry Clin Neurosci 2008;62:548-53.  Back to cited text no. 29
Donati F, Gobbi G, Campistol J, Rapatz G, Daehler M, Sturm Y, et al. Effects of oxcarbazepine on cognitive function in children and adolescents with partial seizures. Neurology 2006;67:679-82.  Back to cited text no. 30
Thome-Souza S, Moreira B, Valente KD. Late adverse effects of the coadministration of valproate and lamotrigine. Pediatr Neurol 2012;47:47-50.  Back to cited text no. 31
Eddy CM, Rickards HE, Cavanna AE. The cognitive impact of antiepileptic drugs. Ther Adv Neurol Disord 2011;4:385-407.  Back to cited text no. 32
Brandl U, Kurlemann G, Neubauer B, Rettig K, Schäuble B, Schreiner A. Seizure and cognitive outcomes in children and adolescents with epilepsy treated with topiramate. Neuropediatrics 2010;41:113-20.  Back to cited text no. 33
Mula M, Trimble MR, Thompson P, Sander JW. Topiramate and word-finding difficulties in patients with epilepsy. Neurology 2003;60:1104-7.  Back to cited text no. 34
McDonald CR, Ahmadi ME, Hagler DJ, Tecoma ES, Iragui VJ, Gharapetian L, et al. Diffusion tensor imaging correlates of memory and language impairments in temporal lobe epilepsy. Neurology 2008;71:1869-76.  Back to cited text no. 35
Liacu D, Idy-Peretti I, Ducreux D, Bouilleret V, de Marco G. Diffusion tensor imaging tractography parameters of limbic system bundles in temporal lobe epilepsy patients. J Magn Reson Imaging 2012;36:561-8.  Back to cited text no. 36
Hagler DJ Jr, Ahmadi ME, Kuperman J, Holland D, McDonald CR, Halgren E, et al. Automated white-matter tractography using a probabilistic diffusion tensor atlas: Application to temporal lobe epilepsy. Hum Brain Mapp 2009;30:1535-47.  Back to cited text no. 37
Concha L, Beaulieu C, Collins DL, Gross DW. White-matter diffusion abnormalities in temporal-lobe epilepsy with and without mesial temporal sclerosis. J Neurol Neurosurg Psychiatry 2009;80:312-9.  Back to cited text no. 38
Ahmadi ME, Hagler DJ Jr, McDonald CR, Tecoma ES, Iragui VJ, Dale AM, et al. Side matters: Diffusion tensor imaging tractography in left and right temporal lobe epilepsy. AJNR Am J Neuroradiol 2009;30:1740-7.  Back to cited text no. 39
Hayashi Y, Kinoshita M, Nakada M, Hamada J. Correlation between language function and the left arcuate fasciculus detected by diffusion tensor imaging tractography after brain tumor surgery. J Neurosurg 2012;17:839-43.  Back to cited text no. 40
Shinoura N, Midorikawa A, Onodera T, Tsukada M, Yamada R, Tabei Y, et al. Damage to the left ventral, arcuate fasciculus and superior longitudinal fasciculus-related pathways induces deficits in object naming, phonological language function and writing, respectively. Int J Neurosci 2013;123:494-502.  Back to cited text no. 41
Riley JD, Franklin DL, Choi V, Kim RC, Binder DK, Cramer SC, et al. Altered white matter integrity in temporal lobe epilepsy: Association with cognitive and clinical profiles. Epilepsia 2010;51:536-45.  Back to cited text no. 42
Kern KC, Ekstrom AD, Suthana NA, Giesser BS, Montag M, Arshanapalli A, et al. Fornix damage limits verbal memory functional compensation in multiple sclerosis. Neuroimage 2012;59:2932-40.  Back to cited text no. 43
Liacu D, de Marco G, Ducreux D, Bouilleret V, Masnou P, Idy-Peretti I. Diffusion tensor changes in epileptogenic hippocampus of TLE patients. Neurophysiol Clin 2010;40:151-7.  Back to cited text no. 44
Wilson RS, Hebert LE, Scherr PA, Barnes LL, Mendes de Leon CF, Evans DA. Educational attainment and cognitive decline in old age. Neurology 2009;72:460-5.  Back to cited text no. 45
Singh-Manoux A, Kivimaki M, Glymour MM, Elbaz A, Berr C, Ebmeier KP, et al. Timing of onset of cognitive decline: Results from Whitehall II prospective cohort study. BMJ 2012;344:d7622.  Back to cited text no. 46
Heilman KM. Aphasia and the diagram makers revisited: An update of information processing models. J Clin Neurol 2006;2:149-62.  Back to cited text no. 47
Mukherjee P, Berman JI, Chung SW, Hess CP, Henry RG. Diffusion tensor MR imaging and fiber tractography: Theoretic underpinnings. AJNR Am J Neuroradiol 2008;29:632-41.  Back to cited text no. 48


  [Figure 1], [Figure 2]

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]

This article has been cited by
1 Brain network alteration in patients with temporal lobe epilepsy with cognitive impairment
Hongyu Yang,Chao Zhang,Chang Liu,Tao Yu,Guojun Zhang,Nan Chen,Kuncheng Li
Epilepsy & Behavior. 2018; 81: 41
[Pubmed] | [DOI]


Print this article  Email this article
Online since 20th March '04
Published by Wolters Kluwer - Medknow