Results of our study demonstrate local decrease of FA and/or increase of MD values, in patients compared with controls, within several functionally specific fronto-thalamic tracts, including the projections to and from DLPFC, ACC, BA 44/45, frontal pole, orbitofrontal cortex and inferior prefrontal cortex. These findings were independent of IQ, parental socioeconomic status, and age. To the best of our knowledge, the present study is the first to combine a BA-specific ROI selection and a tract parametrization technique. It is also the first study that applies this technique to thalamo-frontal white matter connections in schizophrenia. Of further note, our results indicate disrupted fiber integrity (FA decreases) and disrupted tissue microstructures (MD increases) in schizophrenia that concur with results of previous histopathologic studies where abnormalities in oligodendrocyte function have been reported (Uranova et al., 2001
Previous studies investigating these connections have used more generic approaches. For example, some studies have focused on the integrity and asymmetry of the AL-IC, using a voxel-based morphometry (VBM) approach, and reported decreased FA, altered magnetization transfer (MT) and diminished asymmetry within this region (Park et al., 2004
; Kubicki et al., 2005
). Others have used fiber tractography, measuring the length of fronto-thalamic fiber tracts and reporting their shortening in schizophrenia (Buchsbaum et al., 2006
). Finally, Kim et al. (2008)
used sulcal/gyral parcellation to separate and measure anatomically specific thalamo-cortical projections, and reported increased mean MD in thalamo-orbitofrontal and thalamo-parietal-occipital-temporal fiber tracts in patients with schizophrenia.
As opposed to other tractography approaches, our investigation attempted to separate fronto-thalamic tracts based on functional, rather than anatomical cortical segmentation. The advantage of this method is that extracted fiber tracts carry information to and from functionally homogenous regions of gray matter, and their integrity is inevitably related to particular brain function of specific BA that was used for tract segmentation. In this way, the relationship between anatomy and function, and their associated abnormalities in schizophrenia, are likely easier to establish. In addition, we included tract parametrization, which allows us to perform group comparison at any given position along the extracted fiber bundles, thus further increasing sensitivity and specificity. Our approach essentially combines the strengths of two different conventional methods: 1) In the VBM approach, group comparison of white matter integrity can be studied for every voxel of the human brain, but differences cannot be straight-forwardly assigned to specific fiber bundle (Park et al., 2004
; Kubicki et al., 2005
). Using inverse normalization of significant difference regions, however, one can conduct post-hoc tractography to assign fiber tracts to regional differences. Nonetheless, this approach will require additional efforts to warrant intersubject homology of each voxel in each subject. Alternatively, we tried to define intersubject homologous points using a tract-oriented method called tract parametrization. More importantly, our method is less affected by inter-subject registration of white matter features and its errors. 2) In the tractography approach, specific tracts are extracted, but group comparison is being carried on the diffusion properties averaged over the entire tract, rather than studied for each voxel of the tract separately (and thus the possible local, subtle differences might be washed out by the averaging) (Rosenberger et al., 2008
; Kim et al., 2008
Region-by-region descriptions with respect to FA and/or MD differences are as follows: 1) The DLPFC related part of the AL-IC, that is the tract carrying connections mostly between DLPFC and medial-dorsal thalamic nucleus (MDN), demonstrated both decreased FA and increased MD values. This bundle, by virtue of its anatomical connections, likely plays an important role in affect, association and working memory functions, all reported to be abnormal in schizophrenia (Bunney and Bunney, 2000
; Cannon et al., 2005
; Schlosser et al., 2007). 2) Decreased fiber integrity in thalamic projection to BA 44/45, which includes Broca’s area, suggests a disruption in the language network (Felleman and Van Essen, 1991; Petrides and Pandya, 1988) that might elucidate language process abnormalities in schizophrenia (Burns et al., 2003; Hubl et al., 2004
). The ACC, thalamic projection to which showed decreased FA values as well, is related to cognitive functions including executive attention, reward anticipation, decision-making and affective functions, which are also abnormal in schizophrenia (Quintana et al., 2004
; Szeszko et al., 2007
). 3) Although not frequently addressed in previous studies, increased MD values in IC projections to orbitofrontal cortex and inferior prefrontal cortex are likely important as they underlie cognitive processes, including decision-making in orbitofrontal cortex (Hutton et al., 2002
), and syntax processing in spoken and signed languages in inferior prefrontal cortex (Kubicki et al., 2003
), all reported to be abnormal in schizophrenia.
According to our results above, not all ROI connections were affected in the same way (see and ). Since we found significant FA (but not MD) changes in IC connections to area 9, and MD (but not FA) changes in IC projections to area 46, DLPFC connectivity results should be treated with caution. One possible source of such a differential pattern of changes in schizophrenia might be due to an anatomical difference in the way that the thalamocortical tracts are affected for these two ROIs in schizophrenia, as well as individual variability of Brodmann areas 9 and 46, which was demonstrated previously by Rajkowska and Goldman-Rakic (1995)
. Since the intersubject variability for most regions was equal or smaller than intrasubject (regional) variability, we believe it is appropriate to perform not only “bulky” tract analysis (i.e., ANOVAs) but also “regional” tract analysis (i.e., parameterization). However, since BA 47 showed greater intersubject variability of MD values, this region should be treated with more caution.
Interestingly, MD differences were seen along the tracts when reaching the cortex, and all correspond with rostral BAs. Indeed, we have utilized line scan diffusion imaging (LSDI) for DTI acquisition. Since this imaging technique is relatively free from image distortions observed with EPI-based DTIs, we think the results are not an artifact. Instead, we think that the nature of this dissociation could be due to the fact that the mean diffusivity (MD) measures, which basically reflect tissue micro structure disruption, could be more influenced by architectural, neuro-developmental, and more importantly, cortical reorganization than FA, and that MD might be more sensitive to changes in low coherence regions, and FA in more coherent regions.
The following limitations should be noted when interpreting our results. As noted by Smith et al. (2006)
, our parametrization method, similar to all parametrization-based approaches tends to be more reliable for large fiber tracts but less so for smaller bundles.
As mentioned above, our tracts of interest (frontal projection of the IC tracts) interconnect gray matter regions including frontal lobe and thalamus. To better construct these gray matter-relevant areas, we chose a relatively low FA threshold (0.1) for the seeding and stopping criteria of fiber tractography. Although low FA values, which also imply high fiber orientation uncertainties, can cause possible shape variability of the reconstructed white matter tracts, the parametrization has been regularized by cutting tracts between two ROIs ().
Based on whole brain seeding, we were able to improve the robustness of the fiber tractography in the presence of uncertainty of the fiber orientation due to noise and fiber crossings. Whole brain tractography, however, is not an ultimate solution for these problems, and methods that explicitly model tract orientation uncertainty (such as stochastic approaches (Behrens et al., 2003
; Parker et al., 2003; Friman et al., 2003)) need to be applied. Another consideration is to use high angular resolution diffusion imaging (HARDI), including Q-ball imaging (Tuch, 2004
) as used by Schmahmann et al. (2007)
, although such an approach might be unrealistic in clinical studies due to the extremely long acquisition time.
As demonstrated by Rajkowska and Goldman-Rakic (1995)
, Amunts et al. (2007)
and Malikovic et al. (2007)
, individual variability of Brodmann areas, not captured by a BA template approach, should be considered when interpreting the results. One study has also been conducted using gyral and sulcal borderlines for tract definition on the basis of cortical surface parametrization (Park et al., 2008
). Since each approach has their pros and cons (more functional specificity for Brodmann ROIs vs. better anatomical precision for gyral ROIs), more experiments are needed in order to demonstrate the pros and cons of one method versus another. In addition, BA ROIs are easy-to-define using simple spatial transformation, which is the reason why voxel-based analyses are so popular in all neuroimaging studies.
Finally, we should note that the spatial resolution of our scans was relatively low, and thus partial volume effects might cause potential artifacts in data analysis and coregistration. We also note that the sample size of participants, although comparable with most DTI studies to date, was relatively small. In addition, we evaluated chronic schizophrenia only, medicated subjects only, and men only. Future studies need to evaluate patients with schizophrenia early in their illness long term neuroleptic use is minimal. Previous publications suggest that history of substance abuse, especially its duration (Pfefferbaum et al., 2008
), as well as dependence could be a potential confounding factor for DTI results. We, however, excluded subjects with a history of substance dependence and we excluded subjects with substance abuse in the last year. We nonetheless did not have the data available to test more specifically for such a relationship, and future studies should include more detailed information regarding substance abuse and dependence in schizophrenia and its possible association with white matter pathology. Female patients should also be included to evaluate gender differences in this disorder. Similarly, due to using anisotropic voxels and relatively fewer number of diffusion gradient directions, we can expect the statistical results might be biased by partial volume effects that can not be radically resolved by image volume interpolation. In addition, there is an argument that interpolating potentially underestimates FA values, and that FA estimation errors depends on resolution, especially in regions of fiber crossings (Oouchi et al., 2007