Abnormalities of language networks in temporal lobe epilepsy

www.elsevier.com/locate/ynimg NeuroImage 36 (2007) 209 – 221

Abnormalities of language networks in temporal lobe epilepsy H.W. Robert Powell, a Geoff J.M. Parker, b Daniel C. Alexander, c Mark R. Symms, a Philip A. Boulby, a Claudia A.M. Wheeler-Kingshott, d Gareth J. Barker, e Matthias J. Koepp, a and John S. Duncan a,⁎ a

Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK Imaging Science and Biomedical Engineering, University of Manchester, Oxford Road, Manchester, UK c Department of Computer Science, University College London, Gower Street, London, UK d NMR Research Unit, Institute of Neurology, University College London, London, UK e King’s College London, Institute of Psychiatry, Department of Clinical Neuroscience, Centre for Neuroimaging Sciences, London, UK b

Received 30 October 2006; revised 24 January 2007; accepted 10 February 2007 Available online 28 February 2007 Functional magnetic resonance imaging (fMRI) in patients with temporal lobe epilepsy (TLE) has demonstrated reorganisation of language functions with greater involvement of the non-dominant hemisphere. The structural brain connections supporting this atypical language dominance have not previously been identified. We performed fMRI of language functions and imaging of white matter connections using MR tractography in 14 patients with unilateral TLE and hippocampal sclerosis and 10 controls. Verb generation and reading comprehension paradigms were used to define functional regions which were used to generate starting regions for tractography. Controls and right TLE patients had a left-lateralised pattern of both language-related activations and the associated structural connections. Left TLE patients showed more symmetrical language activations, along with reduced left hemisphere and increased right hemisphere structural connections. Subjects with more lateralised functional activation had also more highly lateralised connecting pathways. We provide evidence for structural reorganisation of white matter tracts that reflects the altered functional language lateralisation in left TLE patients. The combination of fMRI and tractography offers a promising tool for studying the reorganisation of language functions in many neurological conditions and may prove useful in predicting language deficits following temporal lobe surgery. © 2007 Elsevier Inc. All rights reserved.

Introduction The relationship between brain structure and function is fundamental to understanding both cognitive neuroscience and clinical neurology. There is good reason to expect a strong correspondence between regional brain function and the underlying neuronal architecture; however, studying this relationship is complicated by the intricacy of the brain’s connections, and the lack of techniques for exploring connectivity in vivo. Recent ⁎ Corresponding author. Fax: +44 207 8373941. E-mail address: [email protected] (J.S. Duncan). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2007.02.028

advances in neuroimaging now allow such relationships to be studied non-invasively, with functional magnetic resonance (fMRI) providing the location of functional regions and diffusion-weighted imaging allowing exploration of the anatomical connectivity of these regions. Temporal lobe epilepsy (TLE) due to hippocampal sclerosis (HS) is a common cause of medically refractory seizures but has a good outcome following anterior temporal lobe resection (ATLR). TLE may be associated with disrupted lateralisation and localisation of language. fMRI studies have demonstrated a higher incidence of atypical language dominance in preoperative left TLE patients (Adcock et al., 2003; Thivard et al., 2005), suggesting that dominant hemisphere lesions can lead to functional reorganisation of language to contralateral cortical regions. The recruitment of right hemisphere regions not activated in control subjects was involved in maintaining reading skills in patients following left ATLR (Noppeney et al., 2005). Verbal fluency fMRI tasks show relative shifts in activation to the right hemisphere in patients with left temporal lobe seizures (Adcock et al., 2003; Lehericy et al., 2000; Voets et al., 2006; Woermann et al., 2003), probably due to epileptic activity affecting normal left hemisphere language organisation (Janszky et al., 2003). Greater right hemisphere reorganisation has been demonstrated for receptive, temporal lobe language functions than for productive, frontal lobe language functions (Thivard et al., 2005). Language function may also be affected by subtle abnormalities remote from the hippocampus. Evidence from a number of imaging modalities including quantitative MRI and MR volumetry (Moran et al., 2001; Sisodiya et al., 1997), MR-spectroscopy (Stefan et al., 2001), voxel based morphometry (Keller et al., 2002) and positron emission tomography (Hammers et al., 2001) suggests the existence of more widespread abnormalities in TLE associated with HS than demonstrated by conventional MRI. The strong connectivity between the inferior frontal and medial temporal lobe (MTL) may make frontal lobe functions particularly sensitive to MTL pathology (Powell et al., 2004), while electrophysiological

210

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

disruption of extratemporal regions may lead to cognitive impairments, in particular on tests of executive function (Hermann and Seidenberg, 1995). Knowing whether any structural changes existed within the white matter pathways involved in language function in TLE patients would be clinically useful as well as providing important insights into the mechanisms underlying functional plasticity within cerebral networks. Diffusion tensor imaging (DTI) is an MRI technique that evaluates brain structure by measurement of water molecules’ threedimensional diffusion through tissue. The diffusion tensor and other models of diffusion allow the directionality of the motion (anisotropy) and the principal orientation(s) of diffusion for each voxel in the brain to be calculated (Pierpaoli et al., 1996; Pierpaoli and Basser, 1996). These provide the basis for MR tractography, a technique that non-invasively investigates the trajectories of cerebral white matter tracts (Conturo et al., 1999; Mori et al., 1999). In this study we used a combination of fMRI and tractography to demonstrate the structure of the white matter tracts connecting functionally defined language regions in patients with TLE and unilateral HS and hypothesised that the language connections in left TLE patients would reflect the pattern of functional activation, with reduced ipsilateral and increased contralateral connections. We also looked for correlations between structure and function, and hypothesised that those subjects with more lateralised language function would have more lateralised structural connections. Materials and methods Subjects We studied 14 patients (median age 35.5; range 25–47 years; 7 female; 13 right-handed) with medically refractory TLE undergoing pre-surgical evaluation at the National Hospital for Neurology and Neurosurgery (NHNN), London, UK. Structural MRI at 1.5 T showed unilateral left HS in 7 patients and right HS in 7 on qualitative and quantitative criteria (Woermann et al., 1998). VideoEEG had confirmed seizures arising from the ipsilateral medial temporal lobe in all 14. Post-operative histology confirmed HS in all cases. All patients were on antiepileptic medication and all were fluent English speakers. Patients’ details are given in Table 1. As previously reported (Powell et al., 2006), we also studied 10 righthanded native English-speaking healthy volunteers (median age 29.5; range 23–50 years; 6 female) with no history of neurological or psychiatric disease. Handedness was determined using the Edinburgh Hand Preference Inventory. Language dominance was assessed using fMRI. The study was approved by the NHNN and the Institute of Neurology Joint Research Ethics Committee and informed written consent was obtained from all subjects. MR data acquisition MRI studies were performed on a 1.5 T General Electric Signa Horizon scanner. Standard imaging gradients with a maximum strength of 22 mTm− 1 and slew rate 120 Tm− 1 s− 1 were used. All data were acquired using a standard quadrature birdcage head coil for both RF transmission and reception. Functional MRI For the language tasks, gradient-echo echo-planar T2*weighted images were acquired, providing blood oxygenation

level dependent (BOLD) contrast. Each volume comprised 17 contiguous 4.6 mm axial slices, with a 22 cm field of view and 96 × 96 acquisition matrix, reconstructed as a 128 × 128 matrix giving an in-plane voxel size of 1.7 mm × 1.7 mm. TE was 40 ms and TR was 4.5 s. The field of view was positioned to maximise coverage of the frontal and temporal lobes. A single volume EPI was acquired with similar parameters and equal sensitivity to geometric distortions but a longer TR (Boulby et al., 2004). This allowed whole-brain coverage and was used as an anatomical reference and to aid spatial normalisation. Each subject performed a verb generation and a reading comprehension task. Both tasks used a blocked experimental design with 30 s task blocks alternating with 30 s of rest over 5 1/2 min. During the verb generation task concrete, nouns were visually presented every 3 s in blocks of 10 nouns. Subjects were instructed to covertly generate verbs from the nouns during the task block and to silently repeat the nouns during the rest block. This paradigms were used to identify anterior language regions in the inferior and middle frontal gyri (Liegeois et al., 2004; Woermann et al., 2003). During the reading comprehension activation condition, subjects silently read 9-word sentences covering a range of different syntactic structures and semantic content. No explicit task was required during scanning in order to avoid inducing additional executive processes. In the baseline condition, subjects attentively viewed 9-word sentences after all the letters were transformed into false fonts. This baseline controlled for visual input but not lexical, semantic or syntactic content. The paradigm therefore maximised our chances of seeing reading-related activation at any level of the reading system. Blocks of six sentences were interleaved with blocks of six false font sentences. Sentences and false fonts were presented one word at a time at a fixed rate (word duration 500 ms, sentence duration 5000 ms; block length: 30 s). This serial presentation mode was used to control for visual input, eye movements and to equate the subjects’ reading pace. This paradigm was designed to identify posterior language regions in the superior and middle temporal gyri (Gaillard, 2004; Noppeney et al., 2005). The data were analysed with statistical parametric mapping (using SPM2 software from the Wellcome Department of Imaging Neuroscience, London; http://www.fil.ion.ucl.ac.uk/spm). Scans from each subject were realigned using the first as a reference, spatially normalised (Friston et al., 1995) into standard space (using the whole brain EPI) (Talairach and Tournoux, 1988), resampled to 3 × 3 × 3 mm3 voxels and spatially smoothed with a Gaussian kernel of 10 mm FWHM. The time-series in each voxel was highpass filtered with a cutoff of 1/128 Hz. A two-level random effects analysis was employed. At the first level, condition-specific effects for each subject were estimated according to the general linear model (Friston et al., 1995). Regressors of interest were formed for each task by creating boxcar functions of task against rest. Parameter estimates for these regressors were then calculated for each voxel. Two contrast images were produced for each subject, corresponding to the main effects of verb generation and reading comprehension against the control conditions. All these images were used for the second-level analysis. At the second level of the random effects analysis, each subject’s contrast image was entered into a one-sample T-test to examine the main effect of verb generation and reading comprehension within each group. For each task, we derived lateralisation

Table 1 Clinical and demographic details for all patients Fluency

Right HV (cm3)

Left HV (cm3)

Hippocampal volume ratio (%)

AEDs (mg/day)

Language dominance

7

33

2.729

1.351

50

Left

93

19

34

3.3

1.88

57

86

88

13

21

2.83

2.02

71

Left TLE

88

111

13

28

2.359

1.789

76

TPR 150 LTG 200 VPA 800 CBZ 800 LVT 2000 PMD 500 CBZ 1200 CLB 10 TPR 175 LVT 4000 OXC 1050 TPR 200

Left HS

Left TLE

76

81

4

25

3.077

1.417

46

Left

CPS 5

Left HS

Left TLE

67

76

6

14

2.235

1.896

85

Left HS, left fusiform gyrus ganglioglioma Right HS

Left TLE

70

94

10

24

2.8

2.385

85

13

SPS 12 CPS 8 SGTC 1 CPS 1

LVT 3000 LTG 600 LVT 2000 VPA 2000 CBZ 1000 CLB 10

Right TLE

73

86

7

21

1.038

2.769

37

Left

Right

14

CPS 4

Right HS

Right TLE

95

104

22

36

2.606

3.034

86

44/M

Right

10

CPS 4

Right HS

Right TLE

117

118

22

51

2.775

3.047

91

11

46/F

Right

8

CPS 5

Right HS

Right TLE

88

84

10

20

1.756

2.695

65

12

32/F

Right

19

CPS 2

Right HS

Right TLE

87

110

15

26

2.299

2.562

90

13

29/M

Right

9

Right HS

Right TLE

93

114

20

27

2.273

2.978

76

14

41/F

Right

14

CPS 30 SGTC 4 CPS 4

LVT 500 PHT 300 CBZ 800 LVT 750 PHT 400 CLB 10 CBZ 800 LVT 1000 TPR 600 PMD 1000 OXC 2400 CBZ 1600 LVT 1000 VPA 2400

Right HS

Right TLE

90

88

13

20

1.628

2.302

71

TGB 15

Age/ gender

Handedness

Epilepsy onset (years)

Seizure types and frequency (per month)

MRI and pathological diagnosis

Clinical and EEG

VIQ

PIQ

1

25/F

Right

17

Left HS

Left TLE

82

80

2

37/M

Left

1

CPS 8 SGTC 0.5 SPS 12 CPS 4

Left HS

Left TLE

94

3

33/M

Right

1

SPS 4 CPS 4

Left HS

Left TLE

4

32/F

Right

22

Left HS

5

28/M

Right

3

SPS 30 CPS 5 SGTC 0.25 CPS 1

6

34/M

Right

21

7

37/F

Right

1

8

47/M

Right

9

44/F

10

Naming

Left

Left

Left

Left Left

Left

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

#

Left Left

Left Left Left

M = male; F = female; SPS = simple partial seizure; CPS = complex partial seizure; SGTC = secondary generalised tonic–clonic seizure; HS = hippocampal sclerosis; EEG = electroencephalogram; TLE = temporal lobe epilepsy; VIQ = verbal intelligence quotient; PIQ = performance intelligence quotient; HV = hippocampal volume; AED = antiepileptic drug; TPR = topiramate; LTG = lamotrigine; VPA = sodium valproate; CBZ = carbamazepine; LVT = levetiracetam; PMD = primidone; CLB = clobazam; OXC = oxcarbazepine; GBP = gabapentin; PHT = phenytoin; TGB = tiagabine. Hippocampal volume ratio is the ratio of ipsilateral (sclerotic) to contralateral hippocampus. 211

212

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

indices for each subject’s mean fMRI activation (LI = L − R), over spherical regions of interest (10 mm radius) centred on each group’s peak frontal and temporal activations. A very low SPM threshold was employed (P < 0.5 uncorrected) in order to include the contributions of all voxels within the regions of interest. In addition, we performed a one-way ANOVA to identify brain regions demonstrating greater or less activation in patients compared with controls. Maps of the main effect of each task across all subjects (controls and patients combined) were generated, thresholded at P < 0.001 (uncorrected) and transformed into each individual’s native space. This uncorrected threshold was adopted on the basis of a strong a priori hypothesis as to the areas of expected activation. These reverse-normalised group maps were then used to define volumes of interest (VOIs) for initiating probabilistic fibre tracking. A total of four VOIs were defined for each subject, one each in the left and right inferior frontal gyri (IFG) and left and right superior temporal gyri (STG), by drawing over selected areas of fMRI activation (see results for details) on consecutive brain slices, using MRIcro (http://www.psychology.nottingham.ac. uk). Each VOI was of identical volume, comprising 125 voxels. Diffusion tensor imaging The DTI acquisition sequence was a single-shot spin-echo echo planar imaging (EPI) sequence, cardiac gated (triggering occurring every QRS complex) (Wheeler-Kingshott et al., 2002), with TE = 95 ms. The acquisition matrix (96 × 96, 128 × 128 reconstructed), field of view (22 cm × 22 cm) and in-plane resolution on reconstruction (1.7 mm × 1.7 mm) were identical to the fMRI data. Acquisitions of 60 contiguous 2.3 mm-thickness axial slices were obtained, covering the whole brain, with diffusion sensitising gradients applied in each of 54 non-colinear directions (maximum b value of 1148 s mm− 2 (δ = 34 ms, Δ= 40 ms, using full gradient strength of 22 mTm− 1)) along with 6 non-diffusionweighted (b = 0) scans. The DTI acquisition time for a total of 3600 images was approximately 25 min (depending on the heart rate). The diffusion tensor eigenvalues λ1, λ2, λ3 and eigenvectors ε1, ε2, ε3 were calculated, and fractional anisotropy (FA) maps were generated (Pierpaoli et al., 1996; Pierpaoli and Basser, 1996). We used the method of Parker and Alexander (Parker et al., 2003; Parker and Alexander, 2003) to reduce fibre orientation ambiguities in voxels containing fibre crossings. Voxels in which the single tensor fitted the data poorly were identified using the spherical–harmonic voxel-classification algorithm of Alexander et al. (2002). In these voxels a mixture of two Gaussian probability densities was fitted and the principal diffusion directions of the two diffusion tensors provided estimates of the orientations of the crossing fibres (Tuch et al., 2002). In all other voxels a single tensor model was fitted. We used the Probabilistic Index of Connectivity (PICo) algorithm extended to cope with crossing fibres (Parker et al., 2003; Parker and Alexander, 2003) to track from the functionally defined VOIs. This algorithm adapts the commonly used streamline approach to exploit the uncertainty due to noise in one or more fibre orientations defined for each voxel. This uncertainty is defined using probability density functions (PDFs) constructed using simulations of the effect of realistic data noise on fibre directions obtained from the mixture model (Parker and Alexander, 2003). The streamline process is repeated using Monte

Carlo methods to generate maps of connection probability or confidence of connection from the chosen start regions. Each output connectivity map was spatially normalised using SPM and binary masks at a threshold connection probability of 0.05 were constructed. Previously we demonstrated that increasing the probability threshold had no effect on the lateralisation of tract volume and no effect on mean FA apart from at very low thresholds (Powell et al., 2006). The chosen threshold strikes a balance between losing non-specific low probability connections while retaining the main body of the pathways. The binary masks were averaged across each group, to produce variability (or commonality) maps indicating the degree of spatial variability and overlap of the identified connections (Parker et al., 2005). A voxel commonality value C of 1.0 indicates that each individual had a connection identified in this voxel while C of 0.0 indicates that none of them did (Parker et al., 2005). Normalised tract volumes were calculated for the left and right tracts of every subject (Toosy et al., 2004) and paired t-tests were used to compare these within groups. Unpaired t-tests were used to compare the patient and control groups. Two repeated measures ANOVAs were used to test for interactions between group and hemisphere, one comparing controls and the left TLE group and the other comparing left and right TLE groups. To calculate the mean FA of the connected volume in native space for the left and right tracts, the binary masks defined above were multiplied with that subject’s whole brain FA image. The mean FA value is the mean intensity value of the voxels within the resulting masked region. We used a paired t-test to compare left and right-sided mean FA within each group. Unpaired t-tests were used to compare the patient and control groups and repeated measures ANOVAs were used to test for interactions between group and hemisphere as described above. Correlations between structure and function We tested for correlations between the lateralisation of fMRI activation and of the lateralisation of the derived connections. For the fMRI we defined 10 mm radius spheres based on the coordinates of the peak magnitude of activation in the left frontal and bilateral temporal lobe, along with a homotopic volume in the right frontal lobe, and calculated left minus right activation for each subject. For the tractography we calculated lateralisation indices LI to assess lateralisation of mean FA between hemispheres; LI ¼ ðMean FAleft  Mean FAright Þ=ðMean FAleft þ Mean FAright Þ We calculated the Spearman correlation coefficient to test for correlations between the two values. We also tested for correlations between the LI of the tracts and the duration of epilepsy. Regression analysis Finally, patients’ fMRI contrast images were entered into a SPM2 simple regression model with the mean FA of the left-sided tracts as a covariate. This allowed us to look at a voxel level for regions showing correlation between fMRI activation and the mean FA of the connections of language-related areas (Powell et al., 2006). This was done for both left and right TLE groups and the resulting SPM maps were thresholded at P < 0.001.

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

Results Demographic data There were no significant differences between left and right TLE groups in epilepsy duration (left TLE median (range) 25 years (8–36), right TLE 30 years (13–36)), naming score (left TLE mean (SD) 10.3 (5.2), right TLE 15.6 (6)) or fluency score (left TLE mean 25.6 (6.9), right TLE 28.7 (11.3)). Mean verbal IQ was lower in the left TLE patients (mean (SD) 80.4 (9.9)) than the right TLE (91.9 (13.2)), although this difference was not statistically significant. There were, as expected, significant differences in

213

hippocampal volumes between the two groups with left TLE patients having smaller left hippocampi (left TLE mean (SD) 1.82 cm3 (0.35), right TLE 2.77 cm3 (0.28)), and right TLE patients having smaller right hippocampi (left TLE 2.76 cm3 (0.37), right TLE 2.05 cm3 (0.61). fMRI results Verb generation was associated with activation in the left IFG in all three groups, with suprathreshold activation in the right IFG in the left TLE group only (Figs. 1A, C and E, Table 2). Reading comprehension was associated with activation in bilateral STG,

Fig. 1. fMRI results: Main effects of the two language paradigms for each group. Significant regions (threshold P < 0.001 unless stated otherwise) are superimposed onto the normalised mean EPI image from all 10 subjects. The left of the brain is displayed on the left of the image. (A) Controls, verb generation, left inferior frontal gyrus activation. (B) Controls, reading comprehension, bilateral superior temporal gyrus activation, adjacent to the superior temporal sulcus. (C) Left TLE, verb generation, left inferior frontal gyrus activation, along with smaller activation in the right inferior frontal gyrus. (D) Left TLE, reading comprehension, left superior temporal gyrus activation*. (E) Right TLE, verb generation, left inferior frontal gyrus activation. (F) Right TLE, reading comprehension, bilateral superior temporal gyrus activation, adjacent to the superior temporal sulcus. (G) Main effects of the three groups combined, verb generation. The regions of activation shown in the coronal slices were used to define VOIs for initiating fibre tracking. (H) Main effects of the three groups combined, reading comprehension. The regions of activation shown in the coronal slices were used to define VOIs for initiating fibre tracking. (I) Lateralisation indices (LIs) (± SE) for each group for frontal lobe activation. An LI of 1 would indicate a fully left lateralised pattern of activation while an LI of − 1 would indicate a fully right lateralised pattern of activation. The LIs for verb generation were significantly more left lateralised in controls and right TLE patients than left TLE patients (P = 0.001). (J) LIs for each group for temporal lobe activation. No significant differences were seen between groups. * figure threshold P < 0.01.

214

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

Table 2 Activation peaks for fMRI effects of interest Group

Contrast

MNI coordinates

Z score

Region

Controls

Verb generation

−44 2 24 −40 20 0 −44 −56 12 −52 −26 − 6 48 − 26 − 4 −40 10 12 38 6 18 −62 −46 − 2 −42 14 22 − 46 28 − 2 −52 −52 6 −56 −30 − 12 54−28 − 12 −44 10 20 −50 −34 − 6 52 − 26 − 6 50 22 40 42 12 38 46 − 8 14 −50 −2 12 −44 −52 22 −42 2 36

5.56 * 5.52 * 4.99 * 4.63 3.53 4.60 3.18 2.78 ** 5.09 * 5.04 * 4.90 4.04 3.60 7.47 * 5.18 * 5.41 * 3.76 4.03 3.77 3.81 3.87 3.47

Left inferior frontal gyrus Left inferior frontal gyrus Left posterior superior temporal gyrus Left superior temporal gyrus Right superior temporal gyrus Left inferior frontal gyrus Right inferior frontal gyrus Left superior temporal gyrus Left inferior frontal gyrus Left inferior frontal gyrus Left superior temporal gyrus Left superior temporal gyrus Right superior temporal gyrus Left inferior frontal gyrus Left superior temporal gyrus Right superior temporal gyrus Right superior frontal gyrus Right middle frontal gyrus Right middle frontal gyrus Left inferior frontal gyrus Left supramarginal gyrus Left middle frontal gyrus

Reading comprehension

Left TLE

Verb generation

Right TLE

Reading comprehension Verb generation Reading comprehension

All subjects

Verb generation Reading comprehension

Group comparisons

Left TLE > controls Right TLE > controls Right TLE > left TLE Regression: verb generation Regression: reading Regression: verb generation

Left TLE Right TLE

Activation peaks for all fMRI effects of interest. For each effect, the Montreal Neurological Institute (MNI) coordinate, Z score and anatomical location are given. Z scores not marked as * or ** are significant at a threshold of P < 0.001 (uncorrected). * P < 0.05 corrected for multiple comparisons. ** Sub-threshold activation only.

adjacent to the superior temporal sulci, in both controls and right TLE patients (Figs. 1B and F, Table 2) but left TLE patients showed only an area of subthreshold activation in the posterior left temporal lobe (Fig. 1D). Frontal lobe LIs for verb generation were significantly more left lateralised in controls and right TLE patients than left TLE patients (F = 9.530, P= 0.001) (Fig. 1I). There was no significant difference in temporal lobe LIs between the three groups for reading comprehension (F = 1.092, P= 0.35) (Fig. 1J). Four VOIs were defined for initiating fibre tracking based on the areas of peak activation for all subjects combined (Figs. 1G–H). One was placed in the left IFG and corresponded to the peak IFG activation seen for verb generation. As no significant activation was seen in this region on the right for all subjects combined, a homotopic VOI of identical size was manually defined using MRIcro. Two further VOIs corresponded to the areas of bilateral STG activation seen during the reading comprehension task. On direct comparison between groups, no brain regions demonstrated significantly greater activation for verb generation in either left or right TLE groups compared with controls. Left TLE patients demonstrated greater activation in a single area in the right superior frontal gyrus, and right TLE patients demonstrated greater activation in the right middle frontal gyrus (Table 2); however, both of these were distant from the defined start regions of interest. There were no significant differences between left and right TLE patients. For reading, no brain regions demonstrated either greater or less activation in patients compared with controls and there were no significant differences between left and right TLE groups. Right TLE patients demonstrated greater activation than left TLE patients in the right middle frontal gyrus (Table 2), posterior to the defined start region of interest.

Tractography results IFG connections The group variability maps for the volumes of connection from the frontal lobe VOIs are shown in Fig. 2. As reported previously in the control group (Powell et al., 2006), greater connections (particularly fronto-temporal connections via the superior longitudinal fasciculus (SLF)) were seen in the left hemisphere than the right. Both connection volumes (left 48.5 cm3, right 41 cm3; P < 0.05) and mean FA (left 0.317, right 0.308; P < 0.05) were greater on the left than the right. For the left TLE group, visual assessment of the pattern of connections demonstrated consistent bilateral connections extending posteriorly from the IFG with greater temporal lobe and supramarginal gyrus connections on the right than on the left. Paired T-tests revealed both greater volume of connections (left 36.1 cm3, right 44.9 cm3; P= 0.018) and mean FA (left 0.301, right 0.316; P= 0.05) on the right than the left. For the right TLE group, the pattern of connections is similar to controls, with greater fronto-temporal connections via the SLF on the left than the right. Mean FA was greater on the left than the right (left 0.307, right 0.295; P= 0.032) but there was no significant difference in the volume of connections (left 46.6 cm3, right 40.4 cm3; P= 0.15). STG connections Fig. 3 shows the group variability maps for the volumes of connection from the temporal lobe VOIs. For the controls, greater connections were seen in the left hemisphere than the right, in particular along the SLF. Both connection volumes (left 44.8 cm3, right 32.3 cm3; P < 0.001) and mean FA (left 0.313, right 0.303; P= 0.05) were greater on the left than the right.

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

For the left TLE group, extensive and consistent connections were seen bilaterally to the superior and middle temporal gyri, extending anteriorly into the temporal lobe. More extensive rightsided connections were seen to the extra-striate visual cortex (Brodmann area 19). Connections to the inferior frontal lobe via the SLF were demonstrated on the left but not on the right. Overall there was no significant difference in either volume of connections (left 41.8 cm3, right 40.2 cm3; P= 0.77) or mean FA (left 0.290, right 0.297; P= 0.48) between left and right hemispheres. For the right TLE group most connections were relatively symmetrical, although greater connections along the SLF were demonstrated on the left. The volume of connections was greater on the left than the right (left 57.4 cm3, right 43.6 cm3; P= 0.006) but

215

there was no significant difference in mean FA (left 0.305, right 0.294; P= 0.12). Comparison with controls Left TLE In comparison with controls, left TLE patients demonstrated less left-sided and greater right-sided connections, most strikingly from the frontal lobe VOIs (Fig. 2). The overall connecting volume of the left frontal tracts was significantly less than controls (P= 0.006) but there was no significant difference in the right frontal connections. There was a trend for the patients’ mean FA to be lower than controls on the left and greater than controls on the right although neither of these differences was significant.

Fig. 2. Group variability maps (at a probability threshold of 0.05) of the connecting paths tracked from the left and right frontal VOIs for each of the 3 groups. Each image shows the maximum intensity of the commonality maps in each plane of view as a brain surface rendering. Radiological convention is applied. The colour scale indicates the degree of overlap among subjects (expressed as commonality value); for example, a value of 1 (pure red) represents 100% subject overlap (i.e. every subject's identified tract contains the voxel in question). Controls and right TLE patients show a similar pattern of connections with greater SLF connections to the temporal lobe on the left (arrowed) than the right. In the left TLE group the opposite pattern is seen with greater temporal lobe connections on the right (dotted arrow).

216

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

Significant two-way interactions between group and hemisphere were demonstrated for both volume of connections (F[1,6] = 7.76, P= 0.032; Fig. 4A) and mean FA (F[1,6] = 14.6, P= 0.009; Fig. 4B) with left TLE patients being lower on the left and greater on the right than controls. The overall connecting volume of the right temporal tracts was significantly greater in patients than controls (P= 0.031) but there was no significant difference in left temporal connections (Fig. 4C). Mean FA was less in patients than controls on the left (P= 0.036) but there was no significant difference on the right (Fig. 4D). Right TLE Right TLE patients demonstrated a similar pattern of results to controls with greater connections in the left hemisphere. No significant differences from controls were observed in either frontal

volumes of connections (Fig. 4A) or mean FA (Fig. 4B). For temporal connections the overall connecting volume of both left (P= 0.002; Fig. 4C) and right (P= 0.033; Fig. 4C) temporal tracts was significantly greater in patients than in controls. No significant differences in mean FA were observed between patients and controls (Fig. 4D). Comparison of Left and Right TLE groups For the frontal lobe connections right TLE patients demonstrated a significantly lower mean FA on the right than left TLE patients (P= 0.042). There were significant two-way interactions between group and hemisphere for both volume of connections (F[1,6] = 16.23, P= 0.007; Fig. 4A) and mean FA (F[1,6] = 21.79, P= 0.003; Fig. 4B) with left TLE patients being lower on the left

Fig. 3. Group variability maps of the connecting paths tracked from the left and right temporal VOIs for each of the 3 groups. Controls and right TLE patients show a similar pattern of connections with more substantial SLF connections to the frontal lobe on the left (arrowed) than the right, and relatively symmetrical occipital lobe connections. In the left TLE group more extensive right-sided connections are seen to the inferior frontal lobe via the inferior fronto-occipital fasciculus and the uncinate fasciculus (dotted arrow), and to the extra-striate visual cortex (thick arrow). Consistent bilateral connections were seen to the superior and middle temporal gyri, extending anteriorly into the temporal lobe, in all three groups.

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

and greater on the right. The overall connecting volume of the left temporal tracts was significantly less in left than right TLE patients (P= 0.018) but there was no significant difference for the right temporal connections (Fig. 4C). No significant differences were observed between the two patient groups in mean FA (Fig. 4D).

217

significantly correlated with mean FA of the left temporal connections (Fig. 6B, Table 2). For the right TLE patients we found a correlation between the mean FA of the left frontal connections and fMRI activity for verb generation in the left middle temporal gyrus (Fig. 6C, Table 2). No correlation was seen for the temporal connections.

Correlations between structure and function Discussion In the left TLE patients, a significant correlation was seen between lateralisation of mean FA of the frontal connections, and functional lateralisation for verb generation in the frontal lobes (Spearman coefficient = 0.857, P= 0.014; Fig. 5A). In the right TLE patients, a significant correlation was seen between lateralisation of mean FA of the temporal connections, and functional lateralisation for reading in the temporal lobes (Spearman coefficient = 0.786, P= 0.036; Fig. 5B). These were characterised by greater structural lateralisation in subjects with greater functional lateralisation. Looking at correlations between duration of epilepsy and tract lateralisation, there was a trend for longer duration of epilepsy to be associated with less lateralised tracts (Spearman coefficient = −0.739; P= 0.05). Regression analysis For the left TLE patients we found a correlation between the mean FA of the left frontal connections and fMRI activity for verb generation in the left IFG (Fig. 6A, Table 2). For reading comprehension activation within the left supramarginal gyrus was

We found evidence for structural reorganisation of white matter tracts underlying altered language lateralisation in patients with unilateral TLE. In patients with left TLE there were reduced left hemisphere language connections compared to both controls and right TLE patients. This was evident both on visual inspection of the pathways delineated, and quantitatively by comparing the volume and mean FA of the tracts. In contrast, in the right hemisphere there were greater connections in left TLE patients than both controls and right TLE patients. This suggests a reduction in structural connections in the pathological left hemisphere and a possible compensatory increase in the unaffected right hemisphere. For the right TLE patients the overall pattern of connectivity was similar to controls with greater fronto-temporal connections in the left hemisphere than the right. Quantitatively the only significant difference from controls was greater mean FA of the left-sided temporal connections. This suggests a degree of reorganisation away from the pathological right hemisphere, although given that the non-language-dominant hemisphere is affected, the

Fig. 4. (A) Comparison of normalised tract volumes (NV) (±SE) between controls, left and right TLE patients for frontal lobe connections. (B) Comparison of mean FA (± SE) between controls, left and right TLE patients for frontal lobe connections. (C) Comparison of NV between controls, left and right TLE patients for temporal lobe connections. (D) Comparison of mean FA between controls, left and right TLE patients for temporal lobe connections. For the frontal lobe connections, significant two-way interactions between group and hemisphere are seen for both NV and FA characterised by left TLE patients having lower values on the left and greater values on the right, compared with both controls and right TLE patients.

218

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

Fig. 5. Significant correlations between mean FA lateralisation index (LI = FAleft − FAright / FAleft + FAright) of the pathways identified and functional laterality of fMRI activation in the frontal lobes for verb generation in left TLE patients (A), and in the temporal lobe for reading comprehension in right TLE patients (B).

effect was less marked than in left TLE patients. In summary left TLE had less left-sided and greater right-sided connections than controls and right TLE patients had greater left-sided connections than controls. We also demonstrated correlations between the structural lateralisation of the identified pathways and the left–right difference in functional activation in both left and right TLE patients, with subjects with more highly lateralised language function having a more lateralised pattern of connections. This relationship between brain structure and function was previously demonstrated in controls (Powell et al., 2006). It is interesting that it is maintained in the presence of pathology, demonstrating how structural reorganisation underpins functional plasticity in cerebral networks, and may be important when planning ATLR. Finally we used a regression analysis to identify regions where voxel-level fMRI activity correlated with mean FA. These were located in dominant hemisphere language-related regions in both left and right TLE groups, similar to those seen in controls (Powell et al., 2006). Our findings relate to a relatively small sample of patients and will require confirmation in larger groups. The sample size does not allow us to investigate fully the influence of other potentially important factors, for example age of onset, and duration and severity of epilepsy on our findings. Nevertheless there was a trend for longer duration of epilepsy to be associated with less lateralised tracts, suggesting that early age of onset is associated with greater plasticity. In addition the small sample did not allow us to assess

the effect of handedness on structural lateralisation. One of the left TLE patients was left-handed but clearly left-hemisphere-dominant for language. Excluding this subject from the group analyses had no effect on the differences between groups or on the correlation between structure and function. We did not carry out performance monitoring or behavioural testing outside the scanner to assess the patients’ ability to perform the task adequately. There were, however, no significant differences in neuropsychological measures of naming and fluency, or verbal IQ between left and right TLE patients, and previous use of the reading task found no difference between TLE patients and controls in their ability to perform the task (Noppeney et al., 2005). Nevertheless there was a trend for left TLE patients to have lower verbal IQ and language scores, and we cannot exclude differential performance as a contributory factor to the differences observed in fMRI activation between groups. The pattern of reorganisation reflects the fMRI results. Functional activation for the expressive language task was more left lateralised in controls and right TLE than left TLE patients in whom overall activation was more bilateral. A number of studies have shown that left TLE patients have a more symmetrical, less lateralised pattern of language activation than controls and right TLE patients (Adcock et al., 2003; Janszky et al., 2003; Thivard et al., 2005; Voets et al., 2006). One recent study has demonstrated a higher degree of atypical language dominance, in both frontal and temporal language areas, in patients with left HS compared to patients with left frontal and lateral temporal lesions (Weber et al., 2006), suggesting that the hippocampus itself may play an important role in the establishment of language dominance.

Fig. 6. Regression analysis between fMRI contrasts and tract mean FA. (A) Correlation between fMRI activation for verb generation and mean FA of the left frontal connections, left TLE patients. (B) Correlation between fMRI activation for reading and mean FA of the left temporal connections, left TLE patients. (C) Correlation between fMRI activation for verb generation and mean FA of the left frontal connections, right TLE patients.

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

A few studies have used tractography to look at the white matter pathways underlying language function in control subjects, demonstrating a left lateralised pattern of connections, reflecting the functional dominance of the left hemisphere (Nucifora et al., 2005; Parker et al., 2005; Powell et al., 2006). Our study reports these connections in a patient population and differs from work of other groups in that we use fMRI to define functionally active regions to use as start points for fibre tracking. This has the advantage of reducing the observer bias inherent in manual VOI definition and allows the study of the neuronal networks connecting cortical regions subserving particular functions. A study by Catani et al. used tractography to study left hemispheric perisylvian language networks (Catani et al., 2005). In addition to the direct pathway connecting Broca and Wernicke’s areas, they used a two-VOI approach to demonstrate a second, indirect pathway passing through the inferior parietal cortex. This ran laterally to the direct pathway and was composed of an anterior segment connecting Broca’s area with the inferior parietal lobe and a posterior segment connecting the inferior parietal lobe to Wernicke’s area. The authors argued that the existence of this second pathway helped to explain the diverse clinical spectrum of aphasic disconnection syndromes. Our findings are in keeping with these as we demonstrate a connection to the supramarginal gyrus (Brodmann area 40) in the inferior parietal lobe (Powell et al., 2006), a region implicated in a number of language-related tasks (Hickok and Poeppel, 2000; Wise et al., 2001). The single VOI approach does not allow us to distinguish whether this is a separate and discrete pathway to the other fronto-temporal connections demonstrated. We used a single starting region along with a probabilistic tractography technique. Tracking from single VOIs for each functional localisation in each individual allowed a global assessment of the pattern of connectivity without imposing strong prior user knowledge, and provided a measure of confidence to the connections seen. It may be the case that some pathways which play a role in certain aspects of language processing do not directly connect Broca and Wernicke’s areas (for example the connections between Wernicke’s area and visual and auditory cortex) and therefore would not be seen when the results are constrained by using two VOIs. Two region approaches also have the disadvantage of potential bias due to the a priori assumption that connections between the two sites do actually exist. As a result, clear prominence is given to apparent connections between these sites, thus ignoring other potentially interesting connections. The advantages of using a two region approach, along with streamline tractography techniques, are that they reduce the likelihood of false positive pathways and allow separate pathways to be studied individually or compared between different groups. In order to minimise operator bias and to ensure consistency in our method, we used the group activation peak for defining start regions for fibre tracking, rather than each individual subject’s own activation peak. We realise that this may reduce our sensitivity in identifying subtle differences in connection patterns between individuals but concluded that it was the most robust and reliable method for detecting group level differences between patients and controls. Difficulties in co-registering fMRI and DTI can lead to problems in the use of fMRI to define starting points for tractography. The steps of normalisation to standard space (to obtain the group activation maps) and subsequent reverse normalisation to native space, along with the differences in susceptibility and other artefacts between fMRI and DTI images are potential

219

sources of error when co-registering the two modalities. We tried to limit the effect of small registration errors by defining relatively large VOIs (each consisted of 125 voxels). Spatial smoothing of the fMRI scans leads to blurring of activations across neighbouring voxels, leading to activations which include both grey and white matter. This provided a relatively unbiased choice of white matter voxels for tractography seeding, avoiding the necessity to manually define the white matter voxels expected to subserve a particular grey matter area. We studied a homogenous group of patients, all of whom had HS. One previous tractography study in patients with TLE and unilateral HS, showed bilateral symmetrical abnormalities and FA reduction of the fornix and cingulum, suggesting that HS is associated with bilateral limbic system pathology not revealed on conventional neuroimaging (Concha et al., 2005). Given the direct connections between the hippocampus and these structures, the authors speculated that this may reflect downstream axonal Wallerian degeneration (Werring et al., 2000). A more likely explanation for our findings is that structural reorganisation occurs along with functional plasticity secondary to a pathological process affecting the temporal lobe early in life. In patients with left HS this functional reorganisation could lead to reduced left hemisphere activation and an increased role for the right hemisphere in language function which in turn could affect the neuronal architecture underlying language functions. Alternatively more widespread structural abnormalities may occur following the initial pathological insult that causes HS, which subsequently serve as a structural substrate upon which the abnormal functional activation develops. The effect is similar to that observed in people with early blindness, in whom tractography of the optic radiations has revealed reduced thalamocortical connections compared to normal controls (Shimony et al., 2006), and suggests that the status of the structural components of cerebral networks may be critical in understanding the overall changes in function. We feel that it is unlikely that patients’ lesions will have a direct affect on the tracking results as we have selected a homogenous patient sample with the same pathological lesion of hippocampal sclerosis. In particular, bias as a result of false positive pathways is unlikely to be a major problem in the patient group. If anything we would expect to get more false negatives if tracking gets dispersed in areas of unusually low anisotropy, indicating tract damage. The lateralisation of language function inevitably leads to problems in the identification of the right hemisphere homologues to Broca’s and Wernicke’s areas. Our solution in the frontal lobes was to manually define right hemisphere VOIs of identical size in areas homotopic to the functionally defined regions. The aim was to minimise operator bias, although we recognise the limitations of this approach given that structurally homotopic regions do not necessarily correspond functionally, and the location of functional regions may differ between groups. One recent study has indeed demonstrated that right frontal activation on tasks of verbal fluency was not homologous to that seen in the left frontal lobe and that in a group of patients with left TLE the right frontal activation shifted in location (Voets et al., 2006). By performing direct contrasts of activation between each patient group in turn with controls we demonstrated that there were no significant differences of activation within the chosen VOIs, justifying the use of a single right-sided VOI for all three groups. For the superior temporal gyrus, however, we had areas of fMRI activation from the reading comprehension paradigm in both left

220

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221

and right hemispheres which we used for defining left and rightsided VOIs. Both the quantitative measures used, tract volume and mean FA, reflect the underlying structural organisation of the pathways in question. FA is a measure of intravoxel fibre coherence and has been shown to be reduced in a number of diseases including MS (Rovaris et al., 2005) and epilepsy (Eriksson et al., 2001), reflecting axonal degeneration (Concha et al., 2005) or loss of myelination. The lower values of FA seen in the non-dominant hemisphere of healthy subjects, and in the patients’ pathological hemisphere, are consistent with a reduction in the coherence of axons within the white matter pathways, indicating a reduction in structural organisation relative to the dominant and undamaged hemispheres. Tract volume changes are more difficult to interpret, particularly when using probabilistic tractography. One theory is that tract volume changes are a reflection of the uncertainty of fibre orientation, with increasing uncertainty leading to greater spreading of tracts. If this was the case, however, we would expect to see reduced FA and increased tract volume in the patients. We see the opposite, however, with reduced FA and smaller volumes suggesting that our findings reflect a reduction in real tract volume, due to atrophy. Selective language deficits have been reported following language-dominant ATLR in patients with medically refractory TLE. In one study, nearly 40% of patients demonstrated a significant postoperative decline on a standard neuropsychological naming test (Davies et al., 1998). Our results suggest that tractography, in combination with fMRI, may be able to predict and minimise such post-operative language deficits. Tractography also has broader applications to delineate the structural basis of cerebral connectivity and how it is affected by disease. Acknowledgments This work was supported by the Wellcome Trust (Programme Grant No.067176, HWRP, MRS), the National Society for Epilepsy (MJK, JD) and Action Medical Research (PB).

References Adcock, J.E., Wise, R.G., Oxbury, J.M., Oxbury, S.M., Matthews, P.M., 2003. Quantitative fMRI assessment of the differences in lateralization of language-related brain activation in patients with temporal lobe epilepsy. NeuroImage 18, 423–438. Alexander, D.C., Barker, G.J., Arridge, S.R., 2002. Detection and modeling of non-Gaussian apparent diffusion coefficient profiles in human brain data. Magn. Reson. Med. 48, 331–340. Boulby, P.A., Symms, M., Barker, G.J., 2004. A simple method for matching distortions in functional and structural data. ISMRM 12th Scientific Meeting. Proc. Int. Soc. Magn. Reson., p. 2196. Catani, M., Jones, D.K., Ffytche, D.H., 2005. Perisylvian language networks of the human brain. Ann. Neurol. 57, 8–16. Concha, L., Beaulieu, C., Gross, D.W., 2005. Bilateral limbic diffusion abnormalities in unilateral temporal lobe epilepsy. Ann. Neurol. 57, 188–196. Conturo, T.E., Lori, N.F., Cull, T.S., Akbudak, E., Snyder, A.Z., Shimony, J.S., McKinstry, R.C., Burton, H., Raichle, M.E., 1999. Tracking neuronal fiber pathways in the living human brain. Proc. Natl. Acad. Sci. U. S. A. 96, 10422–10427. Davies, K.G., Bell, B.D., Bush, A.J., Hermann, B.P., Dohan Jr., F.C., Jaap, A.S., 1998. Naming decline after left anterior temporal lobectomy

correlates with pathological status of resected hippocampus. Epilepsia 39, 407–419. Eriksson, S.H., Rugg-Gunn, F.J., Symms, M.R., Barker, G.J., Duncan, J.S., 2001. Diffusion tensor imaging in patients with epilepsy and malformations of cortical development. Brain 124, 617–626. Friston, K.J., Holmes, A.P., Worsley, K.J., Poline, J.B., Frith, C.D., Frackowiak, R.S., 1995. Statistical parametric maps in functional imaging: a general linear approach. Hum. Brain Mapp. 2, 189–210. Gaillard, W.D., 2004. Functional MR imaging of language, memory, and sensorimotor cortex. Neuroimaging Clin. N. Am. 14, 471–485. Hammers, A., Koepp, M.J., Labbe, C., Brooks, D.J., Thom, M., Cunningham, V.J., Duncan, J.S., 2001. Neocortical abnormalities of [11C]-flumazenil PET in mesial temporal lobe epilepsy. Neurology 56, 897–906. Hermann, B., Seidenberg, M., 1995. Executive system dysfunction in temporal lobe epilepsy: effects of nociferous cortex versus hippocampal pathology. J. Clin. Exp. Neuropsychol. 17, 809–819. Hickok, G., Poeppel, D., 2000. Towards a functional neuroanatomy of speech perception. Trends Cogn. Sci. 4, 131–138. Janszky, J., Jokeit, H., Heinemann, D., Schulz, R., Woermann, F.G., Ebner, A., 2003. Epileptic activity influences the speech organization in medial temporal lobe epilepsy. Brain 126, 2043–2051. Keller, S.S., Mackay, C.E., Barrick, T.R., Wieshmann, U.C., Howard, M.A., Roberts, N., 2002. Voxel-based morphometric comparison of hippocampal and extrahippocampal abnormalities in patients with left and right hippocampal atrophy. NeuroImage 16, 23–31. Lehericy, S., Cohen, L., Bazin, B., Samson, S., Giacomini, E., Rougetet, R., Hertz-Pannier, L., Le Bihan, D., Marsault, C., Baulac, M., 2000. Functional MR evaluation of temporal and frontal language dominance compared with the Wada test. Neurology 54, 1625–1633. Liegeois, F., Connelly, A., Cross, J.H., Boyd, S.G., Gadian, D.G., VarghaKhadem, F., Baldeweg, T., 2004. Language reorganization in children with early-onset lesions of the left hemisphere: an fMRI study. Brain 127, 1229–1236. Moran, N.F., Lemieux, L., Kitchen, N.D., Fish, D.R., Shorvon, S.D., 2001. Extrahippocampal temporal lobe atrophy in temporal lobe epilepsy and mesial temporal sclerosis. Brain 124, 167–175. Mori, S., Crain, B.J., Chacko, V.P., van Zijl, P.C., 1999. Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann. Neurol. 45, 265–269. Noppeney, U., Price, C.J., Duncan, J.S., Koepp, M.J., 2005. Reading skills after left anterior temporal lobe resection: an fMRI study. Brain 128, 1377–1385. Nucifora, P.G., Verma, R., Melhem, E.R., Gur, R.E., Gur, R.C., 2005. Leftward asymmetry in relative fiber density of the arcuate fasciculus. NeuroReport 16, 791–794. Parker, G.J., Alexander, D.C., 2003. Probabilistic Monte Carlo based mapping of cerebral connections utilising whole-brain crossing fibre information. Lect. Notes Comput. Sci. 2737, 684–695. Parker, G.J., Haroon, H.A., Wheeler-Kingshott, C.A., 2003. A framework for a streamline-based probabilistic index of connectivity (PICo) using a structural interpretation of MRI diffusion measurements. J. Magn. Reson. Imaging 18, 242–254. Parker, G.J., Luzzi, S., Alexander, D.C., Wheeler-Kingshott, C.A., Ciccarelli, O., Lambon Ralph, M.A., 2005. Lateralization of ventral and dorsal auditory-language pathways in the human brain. NeuroImage 24, 656–666. Pierpaoli, C., Basser, P.J., 1996. Toward a quantitative assessment of diffusion anisotropy. Magn. Reson. Med. 36, 893–906. Pierpaoli, C., Jezzard, P., Basser, P.J., Barnett, A., Di Chiro, G., 1996. Diffusion tensor MR imaging of the human brain. Radiology 201, 637–648. Powell, H.W., Guye, M., Parker, G.J., Symms, M.R., Boulby, P., Koepp, M.J., Barker, G.J., Duncan, J.S., 2004. Noninvasive in vivo demonstration of the connections of the human parahippocampal gyrus. NeuroImage 22, 740–747. Powell, H.W., Parker, G.J., Alexander, D.C., Symms, M.R., Boulby, P.A., Wheeler-Kingshott, C.A., Barker, G.J., Noppeney, U., Koepp, M.J.,

H.W.R. Powell et al. / NeuroImage 36 (2007) 209–221 Duncan, J.S., 2006. Hemispheric asymmetries in language-related pathways: a combined functional MRI and tractography study. NeuroImage 32, 388–399. Rovaris, M., Gass, A., Bammer, R., Hickman, S.J., Ciccarelli, O., Miller, D.H., Filippi, M., 2005. Diffusion MRI in multiple sclerosis. Neurology 65, 1526–1532. Shimony, J.S., Burton, H., Epstein, A.A., McLaren, D.G., Sun, S.W., Snyder, A.Z., 2006. Diffusion tensor imaging reveals white matter reorganization in early blind humans. Cereb. Cortex 16, 1653–1661. Sisodiya, S.M., Moran, N., Free, S.L., Kitchen, N.D., Stevens, J.M., Harkness, W.F., Fish, D.R., Shorvon, S.D., 1997. Correlation of widespread preoperative magnetic resonance imaging changes with unsuccessful surgery for hippocampal sclerosis. Ann. Neurol. 41, 490–496. Stefan, H., Feichtinger, M., Pauli, E., Schafer, I., Eberhardt, K.W., Kasper, B.S., Hopp, P., Buchfelder, M., Huk, J., Paulus, W., 2001. Magnetic resonance spectroscopy and histopathological findings in temporal lobe epilepsy. Epilepsia 42, 41–46. Talairach, J., Tournoux, P., 1988. Co-Planar Stereotaxic Atlas of the Human Brain. Georg Thieme Verlag, Stuttgart. Thivard, L., Hombrouck, J., du Montcel, S.T., Delmaire, C., Cohen, L., Samson, S., Dupont, S., Chiras, J., Baulac, M., Lehericy, S., 2005. Productive and perceptive language reorganization in temporal lobe epilepsy. NeuroImage 24, 841–851. Toosy, A.T., Ciccarelli, O., Parker, G.J., Wheeler-Kingshott, C.A., Miller, D.H., Thompson, A.J., 2004. Characterizing function-structure relationships in the human visual system with functional MRI and diffusion tensor imaging. NeuroImage 21, 1452–1463. Tuch, D.S., Reese, T.G., Wiegell, M.R., Makris, N., Belliveau, J.W., Wedeen, V.J., 2002. High angular resolution diffusion imaging reveals

221

intravoxel white matter fiber heterogeneity. Magn. Reson. Med. 48, 577–582. Voets, N.L., Adcock, J.E., Flitney, D.E., Behrens, T.E., Hart, Y., Stacey, R., Carpenter, K., Matthews, P.M., 2006. Distinct right frontal lobe activation in language processing following left hemisphere injury. Brain 129, 754–766. Weber, B., Wellmer, J., Reuber, M., Mormann, F., Weis, S., Urbach, H., Ruhlmann, J., Elger, C.E., Fernandez, G., 2006. Left hippocampal pathology is associated with atypical language lateralization in patients with focal epilepsy. Brain 129, 346–351. Werring, D.J., Toosy, A.T., Clark, C.A., Parker, G.J., Barker, G.J., Miller, D.H., Thompson, A.J., 2000. Diffusion tensor imaging can detect and quantify corticospinal tract degeneration after stroke. J. Neurol., Neurosurg. Psychiatry 69, 269–272. Wheeler-Kingshott, C.A., Hickman, S.J., Parker, G.J., Ciccarelli, O., Symms, M.R., Miller, D.H., Barker, G.J., 2002. Investigating cervical spinal cord structure using axial diffusion tensor imaging. NeuroImage 16, 93–102. Wise, R.J., Scott, S.K., Blank, S.C., Mummery, C.J., Murphy, K., Warburton, E.A., 2001. Separate neural subsystems within ‘Wernicke’s area’. Brain 124, 83–95. Woermann, F.G., Barker, G.J., Birnie, K.D., Meencke, H.J., Duncan, J.S., 1998. Regional changes in hippocampal T2 relaxation and volume: a quantitative magnetic resonance imaging study of hippocampal sclerosis. J. Neurol., Neurosurg. Psychiatry 65, 656–664. Woermann, F.G., Jokeit, H., Luerding, R., Freitag, H., Schulz, R., Guertler, S., Okujava, M., Wolf, P., Tuxhorn, I., Ebner, A., 2003. Language lateralization by Wada test and fMRI in 100 patients with epilepsy. Neurology 61, 699–701.