Direct diffusion-based parcellation of the human thalamus

ORIGINAL ARTICLE

Direct diffusion-based parcellation of the human thalamus

Vinod Kumar • Sarah Mang • Wolfgang Grodd

Received: 29 October 2013 /Accepted: 7 February 2014 / Published online: 22 March 2014

� Springer-Verlag Berlin Heidelberg 2014

Abstract To assess stable anatomical features of the

human thalamus, an unbiased diffusion tensor parcellation

approach was used to segment thalamic substructures with

similar spatial orientation. We determined localization, size

and individual variations of 21 thalamic clusters in a group

of 63 healthy human subjects (32 males/31 females). The

laterality differences accounted for ±6 % and gender dif-

ferences for ±4 % of the thalamic volume. Consecutively,

five stable clusters in the anterior, medial, lateral and

posterior thalamus were selected, which were common to

90 % of all subjects and contained at least 10 voxels. These

clusters could be assigned to the anteroventral nucleus

(AN) group, the mediodorsal (MD) nucleus, the medial

pulvinar (PuM), and the lateral nuclei group. The subcor-

tical and cortical connectivity of these clusters revealed

that: (1) the oblique cranio-caudal-oriented fibers of the

AN cluster mainly connect to limbic structures, (2) the

numerous dorso-frontal-oriented fibers of MD mainly

project to the prefrontal cortex and the medial temporal

lobe, (3) the fibers of the PuM running in parallel with the

x-axis project to medio-occipital and medio-temporal areas

and connect visual areas with the hippocampus and

amygdala and via intrathalamic pathways with medio-

frontal areas, and (4) the oblique caudo-cranial fibers of the

two lateral clusters located anteriorly in the motor and

posteriorly in the sensory thalamus are routing sensory–

motor information from the brain stem via the internal

capsule to pre- and peri-central regions of the cortex.

Keywords Thalamus � Anatomy � Diffusion tensor

imaging � Laterality � Gender � Connectivity

Abbreviations

AC Anterior commissure

Acc Nucleus accumbens

AD Anterodorsal nucleus

AM Anteromedial nucleus

Amy Amygdala

AN Anterior cluster

AV Anteroventral group

BS Brainstem

Cau Caudate nucleus

CoG Center of gravity

DDO Dominant diffusion orientations

Den Dentate nucleus

DTI Diffusion tensor imaging

EPI Echo planar imaging

Hip Hippocampus

LA Lateral-anterior cluster

LD Lateral dorsal group

LP Lateral-posterior cluster

MD Mediodorsal nucleus

MED Medial cluster

MRI Magnetic resonance imaging

Electronic supplementary material The online version of thisarticle (doi:10.1007/s00429-014-0748-2) contains supplementarymaterial, which is available to authorized users.

V. Kumar � W. Grodd (&)

Department of Psychiatry, Psychotherapy and Psychosomatics,

JARA-Translational Brain Medicine, University Hospital,

Rheinisch-Westfalische Technische Hochschule (RWTH)

Aachen University, Pauwelstr. 30, Aachen 52074, Germany

e-mail: [email protected]

V. Kumar

Graduate School of Neural and Behavioral Sciences,

International Max Planck Research School, Tubingen, Germany

S. Mang

Software Development for Integrated Diagnostics and Therapy,

German Cancer Research Center, Heidelberg, Germany

123

Brain Struct Funct (2015) 220:1619–1635

DOI 10.1007/s00429-014-0748-2

http://dx.doi.org/10.1007/s00429-014-0748-2

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Pal Pallidum

PC Posterior commissure

PO Posterior cluster

PuM Medial pulvinar

Put Putamen

Red Red nucleus

SD Standard deviation

T Tesla

TE Echo time

TR Repetition time

VA Ventral anterior

VLa Ventral lateral anterior

VLp Ventral lateral posterior

VM Ventral medial

VP Ventral posterior complex

VPI Ventral posterior inferior nucleus

VPL Ventral posterolateral

VPM Ventral posteromedial

Introduction

The thalamus is one of the most complex structures of the

CNS. Its internal organization and connections are until

today only distinguishable by histology. Although a num-

ber of studies using various magnetic resonance imaging

(MRI) methods like combined T1- and T2-maps at

1.5 Tesla (T) (Deoni et al. 2007), magnetization transfer at

3 T (Gringel et al. 2009), high-resolution T1-maps at 4.7 T

(Lemaire et al. 2010), and susceptibility-weighted imaging

at 7 T (Abosch et al. 2010) were performed, these

approaches did not offer sufficient tissue contrast and thus

cannot be used for an internal differentiation. However, as

each thalamic nucleus possesses a specific pattern of cor-

tical and subcortical connections, a parcellation in vivo can

be achieved using diffusion tensor imaging (DTI). Diffu-

sion tensor imaging detects the directional organization of

brain tissue with the aid of restricted diffusion properties of

water molecules and allows examining connectivity pattern

of thalamic compartments using additional probabilistic

tractography methods (Behrens et al. 2003a). This

approach has successfully been used to identify specific

connections between the thalamus and cortical areas (Jo-

hansen-Berg et al. 2005) and to parcellate the thalamus into

distinct ‘connectivity-defined regions’. However, the cor-

tical areas have to be segmented in correspondence to their

known connectivity with major nuclear groups known from

studies in non-human primates in advance to tractography.

An alternative in vivo approach is to distinguish voxels

within the thalamus solely by their DTI-determined fiber

orientations. Using an automatic DTI clustering algorithm

(Wiegell et al. 2003) determined the center-of-mass

coordinates for the segmented nuclei, registered them to

Talairach space (Talairach et al. 1957), and found a fair

agreement to centers obtained from the stereotactic atlas of

the human thalamus provided by Niemann et al. (2000).

The DTI method in this study uses a similar approach

and is based on prior work of our group (Unrath et al.

2008), where we determined the principal diffusion direc-

tion and classified them according to their three major

orientations to identify thalamic sub-regions. This diffusion

direction-based segmentation allows a simple and fast

parcellation. In general, classification techniques based on

the principal diffusion direction are much less sensitive to

user-defined parameters and do not rely on a manual pre-

segmentation of brain areas in contrast to connectivity-

based DTI methods. Our segmentation approach has

meanwhile been improved by defining a set of 21 reference

directions, geometrically distributed over the unit sphere

(Mang et al. 2012). In evaluating this approach in a group

of subjects, we were able to classify the local, dominant

diffusion orientations for each voxel of the thalamus. The

stability of this segmentation in respect to the number of

gradient-encoding directions was shown using 12, 30 and

126 directions at 1.5 and 3 T. We found that the CoG of the

clusters was stable in location (Kumar et al. 2010) but

showed a considerable individual variability in size

(Kumar et al. 2011). In the present study, we now report on

differences in laterality and gender, on the anatomical

assignment of five major clusters and on their specific

subcortical and cortical connectivity profiles.

Materials and methods

Subjects

Sixty-three healthy right-handed volunteers (32 male and

31 female) age 20–40 years (male: mean 26.3, SD 5.15;

female: mean 25.5, SD 4.28) recruited for a functional MRI

study were additionally examined with a DTI sequence. All

subjects gave written informed consent to the data acqui-

sition and its evaluation for research purposes. The Ethics

committee of the University of Tubingen approved the

study.

MR data acquisition

Data acquisition was performed on a 1.5 T MR-Scanner

(Sonata, Siemens, Erlangen, Germany) with a standard

8-channel head coil and an DTI echo planar imaging (EPI)

sequence (12 directions and one volume without diffusion

weighting; repetition time (TR) = 6,700 ms; echo time

(TE) = 82 ms, 52 axial slices (b value = 800 s/mm2). In

plane, resolution was 2 9 2 mm2, slice thickness 2.5 mm.

1620 Brain Struct Funct (2015) 220:1619–1635

123

Additional anatomical MRI scans in all subjects were per-

formed using a T1-weighted MDEFT sequence (TR =

7.92 ms; TE = 2.48 ms; inversion time (TI) = 910 ms; flip

angle (FA) = 16�; voxel size: 1 9 1 9 1 mm3, field of view

(FoV) = 176 9 256 9 256 mm3.

Data preprocessing

The data have been processed cognisant to recent literature

to minimize DTI analysis pitfalls reported in the literature

(Jones and Cercignani 2010) and in recent mailing lists

(Smith et al. 2004). For the analysis, an improved version

of segmentation algorithm was applied (Mang et al. 2012)

by adding cluster reordering, redefined cluster colors and

cluster stability detection at different probabilities using the

following software packages: FSL 4.1 & 5.0 (www.fmrib.

ox.ac.uk/fsl) (Smith et al. 2004), Camino-R1010 (Cook

et al. 2006), SPM 5 (http://www.fil.ion.ucl.ac.uk/spm)

(Friston et al. 1994), SPSS Statistics 19.0, BrainVoyager

2.4 (Goebel et al. 2006), and the freeview GUI utility from

FreeSurfer v5.1.0/5.2.0 (http://surfer.nmr.mgh.harvard.edu/

) (Dale et al. 1999) installed on windows & Fedora

workstations.

For automated comparison of the individual data, all

data sets were aligned and normalized to the MNI152

brain template (2 mm3) using the FSL (Smith et al.

2004). First, the T1-weighted anatomy images were

aligned with the MNI template using the ‘‘flirt’’ routine

in FSL. Then, an affine transformation (flirt from FSL)

was used to match the individual diffusion-weighted

images to the anatomy. This step also compensated for

motion during the DWI acquisition. The corresponding

gradient directions were accordingly adapted (Alexander

et al. 2001; Rohde et al. 2004; Leemans and Jones 2009).

The tensor was then estimated from the aligned data

using the ‘‘analyzedti’’ function from Camino. Then, a

nonlinear warp was applied to normalize the anatomy

image to the MNI template (fnirt function from the FSL

library). This transformation was also applied to all

individual tensor elements. Finally, the orientation of the

tensors was corrected using the ‘‘reorient’’ routine from

the Camino library (Alexander et al. 2001; Cook et al.

2006) before the dominant diffusion orientations (DDO)

were extracted from these tensors.

Thalamic mask definition

The digital model of the 3D anatomy of the thalamus

according to the atlas of Morel was obtained by a written

consent with Prof. G. Szekely from the Computer Vision

Laboratory of the ETH Zurich. The atlas mask was further

realigned with thalamus connectivity-based probability

atlas available in FSL library (Smith et al. 2004). The FSL

thalamus probability template was thresholded to contain

only voxels inside the thalamus with a probability above

50 % (see Fig. 2d). The boundaries of the thalamic mask

were also visually inspected on high-resolution T1-

weighted scans by clinically experienced neuroradiologist

(WG).

Individual segmentation

The automatic segmentation method as described in detail

(Mang et al. 2012) is based on the classification of local

DDO. For each voxel, the DDO is computed by diago-

nalization of the second-order diffusion tensor, which is

assumed to be equal to the eigenvector and corresponds to

the largest eigenvalue. The direction of the diffusion pro-

cess determined from DTI data is presumably symmetric,

i.e., equal in either direction on an orientation axis. To

identify thalamic areas with similar DDOs, a set of pre-

defined reference orientations was used (see Fig. 1) to

classify every voxel in a data set based on similarity

between reference orientations. We used the set of refer-

ence directions from earlier work (Unrath et al. 2008) on

the thalamus parcellation. Each reference direction defines

a diffusion orientation class or cluster. To construct the set

of reference directions first the three main axes (cluster #1,

#4, and #7) were used, which define the octants of a unit

sphere serving as basis for further subdivision. Each octant

has a similar subdivision into nine regions. Beside the three

main axes, each octant has three reference directions con-

sisting of a mixture of two of the main axes (xy—#8, #9;

xz—#2, #3; yz—#5, #6) and three reference directions

mixing all three axes (class #10–21), this results in 21

clusters, which were used for the color-sphere representa-

tion (see Fig. 1b).

Group segmentation and statistics analysis

To restrict the volume and CoG evaluation to clusters that

are located inside the thalamus, the thalamus was masked

as a whole. The mask containing 1,887 voxels on each side

was applied after classification therefore could not affect

the segmentation process and similar individual segmented

clusters could not exceed the mask. As each voxel and each

cluster within this mask were labeled after having a unique

match with the predefined reference table of angular

directions, we assume that no additional errors exist. We

used a 2 9 2 ANOVA with the factors laterality (left/right)

and gender (female/male) to determine the difference in

hemispheres and gender for different clusters.

To compare high-resolution T1-weighted images with

the electronic version of the histology atlas (Krauth et al.

2010), group probability maps were calculated (including

only clusters showing in[50 and[90 % of all subjects in

Brain Struct Funct (2015) 220:1619–1635 1621

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http://www.fmrib.ox.ac.uk/fsl

http://www.fmrib.ox.ac.uk/fsl

http://www.fil.ion.ucl.ac.uk/spm

http://surfer.nmr.mgh.harvard.edu/

the male and female group) to depict the overlap of cor-

responding individual clusters of all subjects. If the prob-

ability in a voxel was 100 %, it was similarly classified in

all subjects. Second, the volume and CoG of all 21 clusters

were separately determined in each male and female sub-

ject for the left and right hemisphere.

Histological comparison

From the 3D volumes of the atlas of Morel (2007), the

volume and CoG of each thalamic nucleus and of all 29

Morel nuclei were determined. Segmented DTI cluster,

which was common in at least 90 % of all subjects, was

taken into account for histological concordance analysis.

The CoG and the percentage overlap between the DTI

cluster, thalamic nuclei or nuclei groups were calculated,

and the shortest distance in CoG and maximal overlap

was chosen for a pictorial comparison with atlas from

Mai and Paxinos (Morel 2007; Mai et al. 2008). Anterior

commissure (AC) and posterior commissure (PC) line and

AC–PC mid were determined from the Mai and Paxinos

atlas (Mai et al. 2008). Distances between MNI 1 mm

brain and the atlas were accordingly aligned and the

closest corresponding cluster location was compared (see

Fig. 4).

Probabilistic tractography

Probabilistic tractography analysis was performed using

FSL (Smith et al. 2004). Seed region selection was done

Fig. 1 DTI Segmentation, spatial assignments, and 3D rendered

views of the thalamus. a Example slice of the thalamus at level 4 mm

cranial to the AC–PC plane with depiction of major eigenvectors

(MEV) (red lines), fractional anisotropy (FA) map and color-coded

segmentation results of 21 segmentation classes. b Color-coding

schema on the unit sphere with 21 reference orientations and the

number assignment used for spatial assignments. c, d Results of

thalamic segmentation depicted in fronto-dorsal and cranio-caudal

views for males (1st and 2nd row) and females (3rd and 4th row) for a

single subject (1st column), at group level (2nd column), and at 50 and

90 % probability levels (3rd and 4th column). e Corresponding 3D

thalamus outline scheme of the histology atlas (left thalamus with 29

nuclei and right thalamus with four major nuclei groups) according to

Morel (2007). f Corresponding 3D thalamus outline scheme of the

Oxford connectivity atlas (2005)


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with group clusters common to at least 90 % of all subjects

containing at least 10 connected voxels. For the thalamo-

cortical tracking, the cortical masks of both hemispheres

were taken from the FreeSurfer (Dale et al. 1999) for

automatic segmentation of T1-weighted 3D MP-Rage

anatomy. Standard DTI preprocessing steps were followed

i.e., eddy current correction, head motion correction, reg-

istration, b-matrix rotation, FA map calculation on each

individual dataset. Connectivity analysis was performed on

individual data sets after visual inspection of individual FA

maps and the assigned RGB orientation. To generate

connectivity distributions for each selected regions the

common default parameters of bedpost and probtrackx

(number of samples = 5,000, curvature threshold 0.2,

Maximum number of steps = 2,000, step length = 0.5)

were applied.

Statistical analysis

For each cluster, the corresponding tractograms were

divided by the number corresponding to the total number of

generated tracts (waytotal) and then multiplied by 100 to

normalize them for comparison (as suggested in FSL

mailing list). From each seed target, the number of con-

nections was separately determined. Subsequently an

ANOVA was performed to evaluate hemispheric and

gender differences for each of the tractograms, which were

then used to assess the described intrathalamic, subcortical

and cortical connectivity pattern.

Connectivity, track rendering and surface visualization

The connectivity profiles of five clusters were determined

using the corresponding areas with 90 % probability level

as seed regions for probabilistic tracking (a) to nine

selected subcortical and (b) to the whole cortex using FSL

(Smith et al. 2004). The subcortical areas were chosen from

the FSL-Harvard Oxford subcortical atlas. In the ipsilateral

cortex areas, we first determined the total number of tracts

and then the number of cortical target voxels at 50 and

90 % probability level to the complete ipsilateral hemi-

sphere. Each tractogram was imported as volume of

interest and color coded according to the assigned cluster

color using BrainVoyager (Goebel et al. 2006), and then

volume and surface-based group probabilistic maps were

calculated. The volume and surface probability maps were

threshold at 50 and 90 % (we considered only tracks that

were common to[50 and[90 % of all subjects). For five

thalamic clusters, the rendered volume maps for subcortical

and cortical connectivity were finally displayed on a

slightly inflated brain.

Results

Size and localization

An overview over localization and size of all thalamic

clusters is given in rendered 3D views for males and

females in Fig. 1 together with thalamic masks derived

from the histological atlas of Morel (2007) and the Oxford

connectivity atlas (Johansen-Berg et al. 2005). The first

column shows the segmentation of a representative single

subject of each group, and columns 2–4, the corresponding

group evaluations. First, the segmentation of all subjects is

shown without any threshold; we then introduced a group

probability threshold of 50 and 90 %.

In general, the figure shows that (1) the method allows a

complete parcellation of the whole thalamus in single

subjects as well as in groups, (2) the clusters vary con-

siderably in size, (3) a number of smaller sub-clusters with

similar spatial orientation occur at different locations,

indicating that the segmentation does not account for spa-

tial congruency, (4) the cluster volumes diminish with

increasing probability thresholding but remain stable in

location, (5) differences exist in respect to laterality and

gender, and (6) no simple correspondence emerges in

comparison to anatomical-defined nuclei and connectivity-

defined thalamic regions.

The number of voxel and their hemispheric distribu-

tion are displayed in Fig. 2 and their values are sum-

marized in Tables 1 and 2. Each thalamus contained

1,887 voxel corresponding to 7,548 mm3. The cluster

sizes ranged from a maximum of 560 voxel (#7 male

right) to a minimum of 3 voxels (#10 female left) but

only 7 clusters (#1, 3, 6, 7, 13, 14 and 15) contained on

average more than 100 voxels in both groups. Smaller

sub-clusters of major clusters (#4, 6, 7, 18, 19, and 21)

occurring at different locations were not considered in

the succeeding evaluation unless they exceeded the

minimal cluster size of 10 voxels.

Laterality and gender

The summarized laterality difference for all clusters

amounted for ±119 voxels in the male group and

±109 voxels in the female group and thus accounted for

±6.3 % (males) and for ±5.8 % (females) of the thalamic

volume (1,887 voxel). In all cases, cluster #10 was the

smallest (3–4 voxels) and cluster #7 the largest

(457–560 voxels). In respect to hemispheric differences, 10

clusters were 16–25 % larger on the right and 11 clusters

were 33–56 % larger on the left. The hemispheric differ-

ence reached significance (p\ 0.001) in both groups for

clusters #1, 3, 4, 7, 9, 13, 14, 18, 18, 20, and 21.


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(a) (b) (c)

Fig. 2 Hemispheric distribution: a Number of voxels (mean

and ± SD) for the male and female group for 21 clusters of the left

and right hemisphere. b Differences between both hemispheres; stars

indicate significant hemispheric and gender signs indicate significant

gender differences. c Corresponding number of voxels at 50 %

probability level. Note the decrease of size except for # 1, 3 and 7.

From the largest clusters seven survive at 50 % with C100 voxels

while at 90 % probability only five cluster with[10 voxels remain

Table 1 Mean value, standard deviation (SD), standard error (SE), and difference of number of voxels from 21 clusters of the right and left

thalamus determined from 32 males (left) and 31 females (right) with as well as hemispheric and gender differences

Cluster no. Male (voxel) Female (voxel) Significance

Hemispheric Gender

Right Left Diff. R–L Right Left Diff. R–L M/F Interaction M/F

Mean SD Mean SD Voxel Mean SD Mean SD Voxel p\ p\ p\

1 161.6 45.4 152.9 40.7 8.7 148.8 36.9 138.3 35.0 10.5 0.010* 0.809 0.147

2 34.4 11.4 37.2 14.2 -2.8 38.0 17.9 42.1 21.3 -4.2 0.107 0.746 0.245

3 122.9 39.7 156.0 37.1 -33.1 154.2 49.4 183.4 33.1 -29.2 0.000* 0.645 0.002*

4 (2) 30.4 14.5 43.8 18.6 -13.5 35.1 12.1 46.6 13.4 -11.5 0.000* 0.548 0.274

5 59.0 28.3 53.0 24.1 6.0 57.6 19.0 51.3 21.0 6.4 0.026* 0.948 0.771

6 (2) 104.8 31.5 106.1 33.7 -1.3 111.1 22.6 121.2 24.7 -10.1 0.023* 0.076 0.119

7 (2*) 560.2 92.0 501.0 93.1 59.3 506.4 76.4 457.5 81.5 49.0 0.000* 0.357 0.024*

8 86.9 32.4 82.8 36.0 4.1 87.3 33.7 82.6 34.0 4.7 0.330 0.948 0.990

9 62.3 24.5 57.9 33.3 4.3 64.2 20.0 55.4 21.3 8.7 0.032* 0.459 0.957

10 4.0 3.5 3.7 3.3 0.4 4.5 2.8 3.4 3.3 1.1 0.161 0.489 0.925

11 72.2 19.2 69.5 22.5 2.7 70.5 32.1 72.7 22.6 -2.3 0.936 0.390 0.891

12 52.3 23.5 47.0 19.5 5.3 46.7 13.8 44.2 17.7 2.5 0.108 0.571 0.321

13 70.8 32.7 96.7 28.8 -25.9 84.8 32.9 108.2 30.0 -23.4 0.000* 0.640 0.090

14 131.8 51.1 110.2 42.1 21.7 129.7 35.1 108.0 29.2 21.7 0.000* 0.994 0.823

15 167.8 43.7 161.7 42.9 6.2 168.0 45.4 164.7 45.7 3.3 0.335 0.766 0.872

16 10.6 5.9 11.3 8.2 -0.7 12.9 6.2 14.5 15.0 -1.6 0.413 0.741 0.160

17 43.7 12.4 46.5 10.0 -2.8 40.2 11.5 38.5 11.1 1.7 0.722 0.145 0.022*

18 (2) 51.7 15.0 68.3 16.1 -16.6 50.1 14.7 65.4 23.1 -15.3 0.000* 0.786 0.528

19 (2) 19.9 8.7 31.1 13.0 -11.2 30.6 24.5 35.5 9.8 -4.8 0.000* 0.110 0.027*

20 14.4 8.4 20.0 12.3 -5.5 18.9 20.5 21.3 10.8 -2.4 0.045* 0.420 0.311

21(2) 25.1 17.0 30.5 15.3 -5.4 27.4 19.5 32.2 11.1 -4.8 0.036* 0.911 0.549

Sum*/Ave‘ 1,887* 26.7‘ 1,887* 26.9‘ ±118.6 1,887* 26.0‘ 1,887* 24.5‘ ±109.5

Number in brackets in the cluster number indicates the number of sub-clusters. Clusters # 1, 3, 4, 5, 6, 7, 9, 13, 14, 18, 19, 20, 21 show significant

(p\ 0.05) hemispheric difference in both groups (*indicated) and gender differences in clusters # 3, 7, 17, 19


123

The summarized gender difference for all clusters

amounted for ±82 voxels in the right and ±79 voxel in the

left hemisphere and thus accounted for ±4.4 % (right) and

±4.2 % (left) of the thalamic volume. In the right hemi-

sphere, 10 clusters in males and 13 clusters in females were

larger. The greatest difference was found in male cluster #12

(11 %) and in female cluster #19 (54 %). In the left hemi-

sphere, 9 clusters in males and 11 clusters in females were

larger. The greatest difference was found in male cluster #17

(17 %) and female cluster #16 (29 %). The difference

reached significance (p\ 0.05) for clusters #3, 7, 17, and 19.

Stability

As the majority of clusters contained \100 voxels, we

consecutively selected only five clusters (#1, 3, 6, 7, and

13), which were common to more than 90 % of all subjects

and contained at least 10 voxels to confine spatial assign-

ment and avoid false tracking.

For those five clusters, location and size at 50 and 90 %

probability levels were determined (Fig. 3). Laterality at

different levels remained stable in three clusters (#3 and #13

to the left, #7 to the right) in both groups. However, cluster #1

exhibited a change in laterality at the 90 % level and for

cluster #6 laterality changed with different probability (s.

Fig. 3c; Table 2). Apparently, the use of a higher probability

results in a stronger spatial confinement and causes changes in

laterality; variations that probably reflect underlying hetero-

geneities in cellularity andfiber arrangement. In a second step,

these five clusters were later taken to assess their anatomical

location and to determine their connectivity. For the sake of

simplicity, we decided to rename the clusters in accordance to

their thalamic location: #6 in anterior (AN), #7 in medial

(MED, #13 in lateral-anterior (LA), #3 in lateral-posterior

(LP), and, #1 in posterior (PO) cluster. These assignmentswill

be used in the following sections (s. Fig. 3b).

Anatomical correspondence and connectivity

To assess the anatomical relation of five clusters common to

90 %, a pictorial comparison of the male group (left hemi-

sphere) with the atlas of (Mai et al. 2008) and Morel (2007)

was performed (s. Figs. 4, 5, 6, 7). Hereby overlap and dis-

tance between each cluster and its closest thalamic nucleus

were determined using the electronic version electronic atlas

of Morel (Krauth et al. 2010). Considering the various ana-

tomical assignments of thalamic nuclei,we hereby refer to the

nomenclature of Morel. The size and CoG of five male

Table 2 Cluster size at 50 and

90 % probability levels for the

male and female group and the

corresponding group differences

Note the decrease in size and

the vanishing of smaller clusters

with increasing probability.

Only the clusters # 1.3 6. 7. 13

with[10 voxels survived in at

least C90 % volunteers

Cluster no. Male Female

50 % 90 % 50 % 90 %

Right Left Diff.

R–L

Right Left Diff.

R–L

Right Left Diff.

R–L

Right Left Diff.

R–L

1 143 126 17 25 38 -13 128 113 15 23 32 -9

2 23 26 -3 9 8 1 25 29 -4 7 9 -2

3 94 125 -31 25 48 -23 120 148 -28 43 73 -30

4 10 21 -11 2 5 -3 12 23 -11 2 6 -4

5 20 9 11 0 0 19 11 8 0 0

6 82 72 10 23 11 12 89 106 -17 20 18 2

7 553 478 75 242 191 51 484 443 41 234 175 59

8 46 43 3 0 0 61 54 7 1 0 1

9 4 1 3 0 0 12 6 6 0 0

10 0 0 0 0 0 0 0 0

11 51 60 -9 2 5 -3 54 60 -6 2 8 -6

12 17 14 3 0 2 -2 23 15 8 1 1

13 34 68 -34 1 18 -17 49 84 -35 5 26 -21

14 99 67 32 8 6 2 92 64 28 5 8 -3

15 101 104 -3 3 10 -7 121 117 4 5 7 -2

16 4 1 3 0 0 4 0 4 0 0

17 32 37 -5 1 5 -4 33 30 3 2 0 2

18 19 21 -2 3 5 -2 20 25 -5 5 4 1

19 7 15 -8 1 2 -1 10 20 -10 2 5 -3

20 0 0 0 0 0 0 0 0

21 1 7 -6 0 2 -2 3 9 -6 1 4 -3


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clusterswith thalamic structures obtained from theMorel and

Oxford atlas are given in Tables S1 and S2 in the supplement.

The connectivity profiles of five clusters were deter-

mined using the 90 % probability areas as seed regions for

probabilistic tracking (a) to nine selected subcortical areas,

and (b) to the ipsilateral cortex using FSL (Smith et al.

2004). The subcortical areas were ipsilateral the nucleus

accumbens (Acc), amygdala (Amy), brainstem (BS), cau-

date nucleus (Cau), hippocampus (Hip), pallidum (Pal),

putamen (Put), red nucleus (Red), and contralateral the

dentate nucleus (Den). All structures were chosen from the

FSL-Harvard Oxford subcortical atlas. In general, we

found that the subcortical compared to cortical projections

exhibit a limited number of connections (mean 370–461) as

they project to small spatially confined masks. We defined

subcortical connections as weak, moderate, strong for

\500,[500,[1,000 tracks. In contrast, the cortical tracks

encircling the whole hemisphere were quite numerous

(a) (b)

(c)

(d)

Fig. 3 Location, size and probability of 5 selected clusters and number

of cortical tracks. a Cluster outline in axial views of five clusters with

different probability levels for males (top) and females (bottom). Note

the decrease in size but the stability in localization. b Color-coded

outline of five selected clusters renamed according to their thalamic

location: #1 in posterior (PO), #3 in lateral-posterior (LP), #6 in anterior

(AN), #7 in medial (MED), and #13 in lateral-anterior (LA). c Corre-sponding hemispheric and gender distribution (top row) and differences

(bottom row) for the five clusters given in number of voxels for the left

(negative values) and right hemisphere (positive values). Depicted are

the values for the mean and at 50 and 90 % probability levels for males

(black bars) and females (gray bars). indicate significant hemispheric

differences and indicate significant gender differences. The color-

coding at 90 % indicates clusters selected for the connectivity analysis.

Negative abscissae values indicate the left hemisphere. Note the

variability of the hemispheric differences, in which cluster 3, 7, and 13

show stable preferences to the left (#3 and #13) or right (#7), while

cluster 1 and 6 possess variable preferences. d Bar graph of the mean

number of cortical tracks (top) and corresponding hemispheric

differences (bottom) in thousands of tracks to the ipsilateral cortex for

the male and female group


123

(mean 47–65,000). To diminish tracking variability and to

assess major connectivity features the tracking was

threshold to a probability level of 50 and 90 % in each

group. This resulted in a reduction of distant connections at

group level and allowed a better visualization. The ana-

tomical assignments and their corresponding connectivity

profiles are subsequently described and displayed in

Figs. 4, 5, 6, 7. The corresponding data are given in Tables

S3 and S4 in the supplement.

Anterior cluster (AN)

Anatomy

The anterior cluster AN (#6) is located 6 mm posterior to

the AC in the anterior nuclei group (Fig. 4a). Morel (2007)

divides the anterior group into the anteroventral (AV),

anteromedial (AM), anterodorsal (AD), and lateral dorsal

(LD) group. The anterior cluster with its oblique cranio-

Fig. 4 Anterior cluster (AN): anatomical correspondence, subcortical

and cortical connectivity: a Comparison of anterior cluster AN (#6)

with the atlas of Mai et al. (2008) and of Morel (Krauth et al. 2010).

Top row rendered axial and coronal views of the thalamus and cluster

#6 (left) and AV as the closest Morel nucleus (right) as well as

corresponding axial outlines with depiction of the CoG (red point

Morel, green point cluster) and their closest distance in mm. Bottom

row pictorial comparison of the cluster AN probability map (left) with

coronal views of the histology (2nd row), the scheme of May et al.

(3rd row), and the scheme of Morel (last row). b Subcortical

connectivity for AN. Left Bar graph of mean number and SD of

subcortical tracks to nine subcortical structures for the male and

female group. Right rendered subcortical tracks at 90 % probability

level overlaid on left- and right-lateral and cranio-caudal views of

semitransparent target structures. c Rendered cortical tracks for AN at

50 % probability level in medio-lateral and bottom views for males

(left) and females (right). d Corresponding cortical areas at 90 % at

probability level in medial and lateral views as well as bottom views

for the male (left) and the female group (right). e Rendered

subcortical target structures with color-coded anatomical assign-

ments. Please note, that the axial view for the subcortical in (b) andcortical projections in (c, d) changes from neurological (top view) in

(b) to radiological convention (bottom view) in (c)


123

caudal-oriented fibers mostly overlaps (91 %) with AV.

The anterior nuclear group is concerned as the limbic

thalamus as the AV and LD nuclei are reciprocally con-

nected with the limbic cortex of the cingulate gyrus, the

retrosplenial area and the pre- and parasubiculum (Nie-

uwenhuys et al. 2008). AV and AM also receive axons

from the basal nucleus of the amygdala in macaques

(Percheron et al. 1996).

Connectivity

The anterior cluster possesses subcortical strong

([1,000) left dominant connections to Amy, Cau, Den,

Hip, and Red, which are with the exception to Den

lower in females, while all other projections were

moderate ([500) or weak (\500) (Fig. 4b). However,

those strong connections to Den ([1,100) in both

groups are only present in a subgroup of the subjects

(8-14/14-18: R-L for males/females, s. Table S3) and

vanish at higher probability. Therefore, it can be

assumed that in the connectivity profile to Den sub-

groups exist. In contrast, connections to Acc, Amy,

Cau and Hip persist in both groups. The 90 % rendered

tracts show major connections anteriorly to Acc and

Cau and posteriorly along the fornix to Hip and Amy.

The number of cortical tracks (s. Table S4) reveal a

slight left-side dominance, which is more pronounced

in females (10/50 %: m/f). The major tracts run (1)

posteriorly via the body of the fornix to the Hip and

Amy and (2) anteriorly via mammillothalamic tract and

Fig. 5 Medial Cluster (MED): anatomical correspondence, subcorti-

cal and cortical connectivity profiles: a Comparison of medial cluster

MED (#7) with the atlas of Mai et al. (2008) and of Morel (Krauth

et al. 2010). Top row rendered axial and coronal views of the

thalamus and cluster #7 (left) and MD as the closest Morel nucleus

(right) as well as corresponding axial outlines with depiction of the

CoG (red point Morel, green point cluster) and their closest distance

in mm. Bottom row pictorial comparison of the clusters probability

map (left) with coronal views of the histology (2nd row), the scheme

of May et al. (3rd row), and of Morel (last row). b Subcortical

connectivity of MED. Left: bar graph of mean number and SD of

subcortical tracks to nine subcortical structures for male and female

group. Right: rendered subcortical tracks at 90 % probability level

overlaid on left- and right-lateral and cranio-caudal views of

semitransparent target structures. c Rendered cortical tracks for

MED at 50 % probability level in medio-lateral and bottom views for

males (left) and females (right). d Corresponding cortical areas at

90 % at probability level in medial and lateral views as well as

bottom or top views for the male (left) and the female group (right).

Please note, that the axial view for the subcortical in (b) and cortical

projections in (c, d) changes from neurological (top view) in (b) toradiological convention (bottom view) in (c)


123

post-commissural fibers to the hypothalamus and cor-

pora mamillaria, and (3) from the septal nuclei to

orbito-frontal areas and via the AC back to the

amygdala (Fig. 4c). In addition, (4) in females a

prominent left-sided track arises from junction of the

AC with the amygdala and projects via the posterior

limb of the internal capsule to left occipito-parietal

areas [red arrow in Fig. 4c), and finally (5)] weak

connections project to the primary visual cortices.

Corresponding to the dominant subcortical profile the

cortical areas are confined to orbito- and medio-frontal

areas and the primary visual cortex. However, here in

contrast to the overall left-sided dominance the orbito-

frontal areas are pronounced in females to the right and

bilaterally expressed in males (red arrows in Fig. 4d).

Medial cluster (MED)

Anatomy

The medial cluster MED (#7) being significantly larger on the

right in both groups contains fibers strictly oriented along y-axis

and is located at AC–PC midline in the medial nuclei group

(Fig. 5a). The medial group can be divided in the mediodorsal

nucleus (MD), the intralaminar and the midline group. The

cluster lies almost completely (91 %) in MD, which is located

at the medial wall of the thalamus and particularly large in

humans (Spinks et al. 2002). Human MD reaches its peak

dimensions and cytoarchitectonic complexity in parallel with

the expansion of the prefrontal cortex (Jones 2007). Medio-

dorsal nucleus is an associative nucleus and can be subdivided

Fig. 6 Posterior Cluster (PO): anatomical correspondence, subcorti-

cal and cortical connectivity profiles: a Comparison of posterior

cluster (#1) with the atlas of Mai et al. (2008) and the atlas of Morel

(Krauth et al., 2010). Top row rendered axial and coronal view of the

thalamus and cluster #1 (left) and PuM as the closest Morel nucleus

(right) as well as corresponding axial outlines with depiction of the

CoG (red point Morel, green point cluster) and their closest distance

in mm. Bottom row pictorial comparison of the clusters PO

probability map (left) with coronal views of the histology (2nd

row), the scheme of May et al. (3rd row), and of Morel (last row).

b Subcortical connectivity for PO. Left: bar graph of mean number

and SD of subcortical tracks to nine subcortical structures for male

and female group. Right: rendered subcortical tracks at 90 %

probability level overlaid on left- and right-lateral and cranio-caudal

views of semitransparent target structures. c Rendered cortical tracks

for PO at 50 % probability level in medio-lateral and bottom views

for males (left) and females (right). d Corresponding cortical areas at

90 % at probability level in medial and lateral views as well as

bottom or top views for the male (left) and the female group (right).

Please note, that the axial views for the subcortical in (b) and cortical

projections in (c, d) change from neurological (top view) in (b) toradiological convention (bottom view) in (c)


123

Fig. 7 Lateral-Anterior (LA) and Lateral-Posterior Cluster (LP):

anatomical correspondence, subcortical and cortical connectivity

profiles: a Comparison of lateral-anterior cluster LA (#13) cluster

with the atlas of Mai et al. (2008) and the atlas of Morel (Krauth et al.

2010). Top row rendered axial and coronal view of the thalamus and

of cluster #13 (left) and VM as the closest Morel nucleus (right) as

well as corresponding axial outlines with depiction of the CoG (red

point Morel, green point cluster) and their closest distance in mm.

Bottom row pictorial comparison of the clusters probability map (left)

with coronal views of the histology (2nd row), the scheme of May

et al. (3rd row), and of Morel (last row). b Subcortical connectivity

for LA. Left: bar graph of mean number and SD of subcortical tracks

to nine subcortical structures for male and female group. Right:

rendered subcortical tracks at 90 % probability level overlaid on left-

and right-lateral and cranio-caudal views of semitransparent target

structures. c Comparison of lateral-posterior LP (#3) cluster with the

atlas of Mai et al. (2008) and the atlas of Morel (Krauth et al., 2010).

Top row rendered axial and coronal view of the cluster#3 (left) and

VPI as the closest Morel nucleus (right) as well as corresponding

axial outlines with depiction of the CoG and their closest distance in

mm. Bottom row pictorial comparison of the clusters probability map

(left) with coronal views of the histology (2nd row), the scheme of

May et al. (3rd row), and of Morel (last row). d Subcortical

connectivity for LP. Left: bar graph of mean number of subcortical

tracks to nine subcortical structures for male and female group. Right:

rendered subcortical tracks at 90 % probability level overlaid on left-

and right-lateral and cranio-caudal views of semitransparent target

structures. e Rendered cortical tracks at 50 % probability level for LA

(red) and LP (green) in medio-lateral and bottom views for males

(left) and females (right). f Corresponding cortical areas at 90 % at

probability level in medial and lateral views as well as bottom or top

views for the male (left) and the female group (right). Please note, that

the axial view for the subcortical in (b) and (d) and cortical

projections in (e, f) changes from neurological (top view) in (b and

d) to radiological convention (bottom view) in (e and f)


123

intomedialmagnocellular and lateral parvocellular parts (Akert

1964; Ray and Price 1992). The magnocellular part is recip-

rocally connected with olfactory-related areas in medial pre-

frontal and orbito-frontal regions of the neocortex (Spinks et al.

2002). The frontal efferents of the MD are so extensive that

Fuster defines the prefrontal cortex as cortical tissue havingMD

connectivity (Fuster 1997). Mediodorsal nucleus also receives

fibers from the medial temporal lobe especially the amygdala

via the inferior thalamic peduncle (Aggleton and Mishkin

1984), aswell as from entorhinal and perirhinal cortices and the

temporal pole (Nieuwenhuys et al. 2008). In addition, direct

fibers from the retina to theMDhave been described recently in

a new world primate, suggesting a possible regulation of the

MD by visual activity (De Sousa et al. 2013).

Connectivity

The medial cluster (Fig. 5b) shows subcortical except of

moderate bilateral connections to Den only weak connec-

tions in both groups. The 90 % tracking profile nicely

reveals the associative nature of the nucleus, which encir-

cles almost the whole thalamus as it mediates connections

of other nuclei as well as to subcortical and cortical target

areas. In contrast, the cortical projections possess the most

numerous tracks (s. Fig. 5c; Table S4) revealing a slight

right-sided dominance (4.9/6.8 %; m/f). The tracks show

extensive bilateral connections (1) via the anterior limb of

the internal capsule to medio-frontal areas and via (2) the

uncinate fasciculus and inferior thalamic peduncle to

anterior and medio-temporal areas. The orbito-frontal areas

are more prominent in females on the right (red arrows in

Fig. 5c). Furthermore, stable projections run posteriorly via

the fornix and pulvinar to Hip and Amy and anteriorly along

the AC to medial and anterior temporal areas. In addition, in

both groups, occipital projections exist, which are, however,

confined to the calcarine fissure. The cortical projections are

complementarily reflected in the cortical targets (Fig. 5d),

which show selected areas along the calcarine fissure and

extended medio- and orbito-frontal areas including the

anterior cingulate as well as anterior-medial and inferior

areas of the temporal lobe, which are known to receive

neocortical projections from Amy (Ray and Price 1992).

Posterior cluster (PO)

Anatomy

The posterior cluster PO (#1) is located 2 mm dorsal to the

PC without clear laterality. It contains horizontally oriented

fibers running in parallel with the x-axis (Fig. 6a). The

cluster lies almost completely (95 %) within the medial

pulvinar (PuM) of the posterior nuclei group. The pulvinar

is an associative nucleus as most of its input and output

relations are associated with parieto-occipito-temporal

cortical areas. It can be divided in four areas (anterior,

inferior, lateral and medial) and is involved in visual and

auditory processing, in attention and language functions

(Shipp 2003; Saalmann et al. 2012; Troiani and Schultz

2013; Hebb and Ojemann 2013), and plays an important

role in gating neuronal activity of the visual cortex (Fischer

and Whitney 2012).

Connectivity

The cluster shows subcortical moderate bilateral connec-

tions to Acc and strong connections to Den and Red

(Fig. 6b). The latter are pronounced to left Red (1551) in

males but strongest to right Red (2446) in females. In

contrast, the cortical tracks display no significant laterality

and gender difference (Fig. 6c). In both groups the tracks

mainly project bilateral (1) via the inferior longitudinal

fasciculus to medio-occipital and medio-temporal areas

and connect visual (and auditory) areas with Hip and Amy

and (2) via the uncinate fasciculus the anterior temporal

lobe with orbito-frontal areas (Catani and Thiebaut de

Schotten 2008). In addition, a third pathway exists, which

links the pulvinar via intrathalamic fibers and anterior limb

of the internal capsule with medio-frontal areas. Finally, an

interhemispheric connection via the splenium of the corpus

callosum is found, which is more pronounced in females.

Accordingly, the cortical areas are bilateral confined to the

calcarine fissure and collateral sulcus, the insula, the gyrus

rectus, and the subgenual part of the anterior cingulate;

hereby the orbito-frontal and anterior temporal areas are

slightly more pronounced in males (red arrows in Fig. 6d).

Lateral-anterior cluster (LA)

Anatomy

The lateral-anterior cluster LA (#13) is located 3 mm

anterior to the AC–PC midline in lateral nuclei group (Fig.

7a) and possesses clear left-side dominance in both groups

(Fig. 3a). Its fibers mainly project oblique in caudo-cranial

direction similar to those of the adjacent internal capsule.

The lateral group is according to Morel (2007) divided in

the ventral posterior complex (VP), the ventral lateral

posterior (VLp) and ventral lateral anterior (VLa), the

ventral anterior (VA) and ventral medial (VM) group. The

cluster lies adjacent to VLa and partly overlaps (17 %)

with VM. VLa is concerned as part of the motor thalamus

as it receives afferents from the pars reticulata of the

substantia nigra and, to a lesser extent, from the internal

segment of the pallidum and is reciprocally connected with


123

the frontal eye field (Brodmann area 8) and the prefrontal

cortex including the cingulate cortex (Nieuwenhuys et al.

2008). In addition, pallidofugal fibers project to the VLa

and particularly to the anterior part giving off collateral

branches to the centromedian nucleus.

Connectivity

The subcortical tracks show moderate connections to right

Cau and strong connections to left Den and Red in males

(Fig. 7b). In addition, females exhibit moderate, bilateral

connections to Acc, Amy and Hip as well as strong,

bilateral connections to Den and Red. The cortical tracts

show significant left laterality and slight gender difference;

especially the hemispheric differences are in males

([350 %) in contrast to females (59 %) pronounced (s.

Table S4). The tracts invariably project to left premotor

and primary motor areas, whereby in females a branching

into motor and premotor areas occurs (red arrow in

Fig. 7e). The tracking seems to reflect the left dominant

motor function of the lateral-anterior cluster, which as part

of the motor thalamus receives inputs from the cerebellum

and gives output to primary motor and premotor cortex

(Mai and Forutan 2012). A pattern that most probably is

due to the right-handedness of all subjects.

Lateral-posterior cluster (LP)

Anatomy

The lateral-posterior cluster LP (#3) lies 2 mm anterior to

PC in ventral posterior complex VP of the lateral nuclei

group (Fig. 7c) and exhibits only weak laterality and

gender differences (Fig. 3c). VP is part of the somatosen-

sory thalamus and comprises two major divisions, the

ventral posterolateral (VPL) and ventral posteromedial

(VPM) nuclei, as well as the smaller ventral posterior

inferior nucleus (VPI) located inferiorly between both.

Within VP, the cluster with its oblique fronto-cranial-ori-

ented fibers mostly overlaps (37 %) with VPI. Both VPL

and VPM represent the principal somatosensory relay

nuclei. VPL gets projections from the contralateral medial

cuneate and gracile nuclei via the medial lemniscus and

receives spinothalamic afferents from the contralateral side

of the spinal cord (Percheron et al. 1996; Nieuwenhuys

et al. 2008).

Connectivity

This cluster shows strong subcortical connections bilateral

to Amy, Cau, Den, Hip, and Red in males (Fig. 7d). The

female profile is similar with the exception that

connections to Amy, Cau, Den and Hip are less but to Acc

and Red are more pronounced. Overall, the dominant

connections to Amy, Red and Den probably indicate the

receipt of spinothalamic afferents. In the cortical connec-

tivity, only a small laterality difference of \10 % to the

right is found for males (s. Table S4); however, this dif-

ference did not reach significance (p[ 0.05). The cortical

tracking pattern reveals compact bilateral projections,

which run (1) upwards through the posterior limb of the

internal capsule and branches within the corona radiata to

pre- and post-central areas and (2) project downwards via

the medial lemniscus to the midbrain and medulla (Fig.

7e). The cortical projections areas are in accordance with

the somatosensory nature of the VP complex strictly con-

fined to apical and medial areas around the central sulcus

and adjacent parietal areas exhibiting no significant

asymmetry (Fig. 7f).

Discussion

The thalamus remains largely an enigma in terms of its

connectivity patterns, the functioning of its circuitry, and

its functional relationship to the cerebral cortex (Sherman

and Guillery 2009). Although thalamic abnormalities play

a prominent role in the pathophysiology of psychiatric and

neurodegenerative disorders, thalamic substructures are

still delineated by their cytoarchitectonic appearance using

postmortem atlases to identify and localize structures for

neurosurgical or radio-surgical intervention (Lemaire et al.

2007). Consequently, an increasing need exists to parcel-

late the human thalamus into meaningful subdivisions

in vivo to better serve scientific and clinical demands.

The segmentation method proposed by Behrens et al.

(2003b) uses cortical connectivity profiles to distinguish

between different thalamic regions. Therefore, this par-

cellation depends on the number of pre-segmented cortical

targets, which then corresponds to the number of regions

within the thalamus. As many cortical target regions are

connected to more than one thalamic nucleus and many

nuclei connected to more than one cortical target they bi-

narized the individual results and included only those

thalamic voxels with a connection probability [25 % to

achieve a delineation of different zones. The resulting

connectivity map (Behrens et al. 2003b; Johansen-Berg

et al. 2005) reveals that this parcellation divides the thal-

amus (s. Figs. 2, 3 of the Behrens paper) in seven oblique

latero-caudally oriented stripe-like zones, which in size and

their anterior–posterior sequence resemble that of their

cortical target regions. This pre-segmentation consequently

restricts the resolution and the subsequent tracking cannot

distinguish between cortico-thalamic and thalamo-cortical

connectivity pattern. As a consequence, details of the


123

thalamic parcellation can be blurred or obscured. This is

obvious for the prefrontal region, which is connected to

MD, parts of the anterior complex as well as parts of the

medial and inferior pulvinar. Thus, their statement ‘‘that

the relative volumes of these connectivity-defined sub-

regions correlate well with volumetric predictions based on

a histological atlas’’, slightly overstates their findings.

The DTI method presented here relies on prior work,

which enabled us to identify meaningful thalamic sub-

regions. However, as the method is based on a simple

diffusion evaluation it possesses important restrictions.

Most prominently, it does not account for spatial congru-

ency and does not consider partial volume effects and

various intra-voxel diffusion profiles. Similarly, the num-

ber of 21 orientations was arbitrarily chosen and could be

expanded or rotated. In addition, diffusion tensor-based

segmentation and tracking methods have their own limi-

tations because of the high intrinsic uncertainties (Behrens

et al. 2003b). Therefore, tensor-based and other higher-

order diffusion imaging methods like Q-ball imaging and

diffusion spectrum imaging need to be evaluated for seg-

mentation of subcortical structures. However, a recent

study (Schultz 2011) comparing tensor and Q-ball based

thalamic segmentation did not find significant differences.

Consequently, for a detailed anatomical and connectivity

analysis, we had to confine ourselves to a restricted number

of clusters.

Considering that individual variability of thalamic

nuclei is seen as a major problem that has always influ-

enced the anatomical description in humans (Mai and

Forutan 2012) the differences in laterality and gender as

determined here are with ±6 % resp. ±4 % rather mod-

erate. This may be related to the simplicity of our

approach as well as to the age restriction in our sample.

These differences are most probably caused by or related

to differences in cellularity and axonal branching. And the

determined variations are in line with recent findings on

gender differences in the human thalamus, where higher

values of fractional anisotropy and lower radial diffusivity

in males were found (Menzler et al. 2011) suggesting

gender differences in the underlying microstructure.

Similarly, a postmortem study reported on a structural

asymmetry of MD, where glial cell density in men was

greater on the right, while in women it was greater on the

left (Amunts 2008). However, our result cannot simply be

compared with histological findings, where thalamic

subdivisions are delimited on the basis of multiple criteria

provided by the staining of sections (Morel 2007; Krauth

et al. 2010), as those neurochemical procedures most

likely have no significant influence on the DTI

acquisition.

In respect to the anatomical assignments, it must be

stated that despite severe methodological restriction

mentioned above, the diffusion-based clusters are stable and

most likely caused by the local, dominant fiber arrange-

ment. Using an electronic version of the Morel atlas, the

clusters could tentatively be assigned to histological defined

structures. In addition, the tracking provides impressive

views on the connectivity profile of the thalamus and sup-

ports and expands the classic view that the thalamus serves

as a gateway, which links all information from the sensory

systems and the cerebellum to the cortex (Jones 2007).

In respect to the specific anatomical findings of the

cluster, we found an overall agreement as provided by

various atlases and textbooks. The AN cluster located

within the anterior nuclei group encircles all major struc-

tures known as the circuit of Papez (Papez 1937; Granziera

et al. 2011). Its close connection with the Hip and Amy is

in line with the limbic profile of the anterior nuclei group

and the left laterality is supported by a majority of imaging

studies (Baas et al. 2004). Even the pronounced connec-

tivity profile in females might be linked to behavior, as

females are better than males at understanding the emo-

tions of themselves and others (Baron-Cohen and Wheel-

wright 2004), although, imaging studies on lateralization of

emotional processing yielded ambiguous results. Wagner

et al. (2003) did not find support for the hypothesis of

overall lateralization of emotional function, while in a

recent study on valence effects reported on a pronounced

hemispheric lateralization to the right (Vrticka et al. 2013).

The cluster MD shows the expected extensive bilateral

cortical connectivity to the frontal lobe and selective con-

nection to the primary visual cortex. However, the right

lateralization of MD and its prominence in females has not

been reported. Spinks et al. (2002) using manually defined

start regions and an artificial neural network to automati-

cally define both the whole thalamus and the MD in 15

males and 15 females found slightly larger values for the

left MD (0.72 versus 0.70 cm3) but no gender difference.

The posterior cluster PO exhibits no significant laterality

and gender differences. However, its intense projections

were not confined to the visual cortices but include con-

nections to auditory and medio-frontal areas as well as to

the Hip and Amy. This complex connectivity may indicate

a close linkage of visual processing with memory recall,

attention and awareness. Thus, its inherent processing

functions may go beyond an ‘‘automatic fashion’’ accord-

ing to a stimulus’s biological significance (Padmala et al.

2010; Sladky et al. 2012). Finally, the similarity of the AN,

MED, and PO connections to Hip, Amy, and orbito-frontal

and visual areas is in our view remarkable. Those joint

connections arising from different loci may indicate that

the thalamus not merely serves as a gateway but acts as

central core unit in guiding attention and linking various

sensory, emotional and cognitive processing with memory

encoding and recall.


123

Acknowledgments The digital model of the 3D anatomy of the

thalamus according to the atlas of Morel (Krauth et al. 2010) was

obtained by a written consent with Prof. G. Szekely from the Com-

puter Vision Laboratory of the ETH Zurich. We thank Susanne

Reiterer for providing the data, Klaus Scheffler for giving access to

analysis facilities, Bernd Kardatzki for technical support, Ute Habel,

and Eugene Datta for reviewing the manuscript. The German research

council (DFG) Grant GR 833/9-1 in part supported this work.

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Direct diffusion-based parcellation of the human thalamus

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