Effective connectivity during haptic perception: A study using Granger causality analysis of functional magnetic resonance imaging data
Introduction
It is now firmly established that human tactile perception routinely evokes activity in visual cortical areas (reviewed by Sathian and Lacey, 2007). However, the mechanisms underlying such cross-modal recruitment of visual cortex remain uncertain. One idea is that visual imagery could be responsible (Sathian et al., 1997, Sathian and Zangaladze, 2001, Stoesz et al., 2003, Zangaladze et al., 1999, Zhang et al., 2004), whereas other work argues in favor of a common multisensory representation that is engaged by both visual and tactile processing (Amedi et al., 2001, Amedi et al., 2002, James et al., 2002, Lacey et al., 2007). The visual imagery explanation implies involvement of top-down connections from prefrontal or posterior parietal cortex into visual cortical areas (Mechelli et al., 2004), while a multisensory representation might be derived from bottom-up tactile inputs into “visual” cortical areas. Examining the connectivity of the active areas could therefore help to distinguish between these possibilities. Two types of connectivity analysis are commonly distinguished: effective connectivity analysis involves estimation of the direction and strength of connections between regions of interest (ROIs), whereas functional connectivity analysis relies on discerning correlations between activity in various ROIs (Büchel and Friston, 2001).
In an earlier report (Peltier et al., 2007), we examined the effective connectivity of parietal and occipital cortical regions during haptic shape perception, using exploratory structural equation modeling (ESEM). ESEM was introduced to allow examination of connectivity without a priori assumptions about the underlying model (Zhuang et al., 2005). However, owing to the computational limitations imposed by the exponential increase in the number of possible models to be tested as the number of ROIs is increased in ESEM, we had to limit analysis to five ROIs. We chose in this earlier report (Peltier et al., 2007) to focus on a subset of parietal and occipital shape-selective areas active during haptic perception, out of a larger set of shape- and texture-selective areas identified in a functional magnetic resonance imaging (fMRI) study, the activation data from which have been published separately (Stilla and Sathian, 2007). The ESEM analysis revealed the existence of bidirectional information flow between parietal and occipital areas, suggesting that both bottom-up and top-down paths might be present. In the present report, we expanded the scope of effective connectivity analysis by including all 25 significantly activated ROIs from the study of Stilla and Sathian (2007), both shape- and texture-selective, using a different approach, analysis of Granger causality.
Granger causality is based on the principle of temporal predictability (Granger, 1969). Accordingly, increased predictability of the future temporal evolution of activity in one region of interest, ROI-1, from knowledge of the past temporal evolution of activity in another ROI, ROI-2, would imply that the ROI-2 time series “Granger causes” the ROI-1 time series. This basic concept has been utilized in formulating bivariate (Roebroeck et al., 2005, Abler et al., 2006) and multivariate Granger causality models (Kus et al., 2004, Deshpande et al., in press, Stilla et al., 2007) which have been successfully applied to electrophysiological data (Ding et al., 2000, Kaminski et al., 2001, Korzeniewska et al., 2003, Kus et al., 2004, Blinowska et al., 2004) as well as fMRI data measuring the blood oxygenation-level dependent (BOLD) response (Roebroeck et al., 2005, Abler et al., 2006, Deshpande et al., in press, Stilla et al., 2007). In the present study, we employed a multivariate Granger causality model (Kus et al., 2004, Deshpande et al., in press, Stilla et al., 2007) capable of capturing simultaneous directional interactions between a large number of ROIs (25 ROIs in this study) in a computationally tractable manner. While such a model allows us to obtain effective connectivity networks from a large number of ROIs without any a priori assumptions about the underlying model, interpreting the resulting network could be quite challenging. Therefore, we introduce a principled way of reducing the size of the network by eliminating ROIs which do not contribute significantly to overall network connectivity. This approach allowed us to consider all significantly activated ROIs in the initial stage of analysis while narrowing interpretation to the most significant ROIs in the later stage.
The primary aim of the present study was to use multivariate Granger causality analysis of effective connectivity to test two alternative, but not necessarily mutually exclusive hypotheses to explain cross-modal visual cortical recruitment during touch: (1) that haptic perception is associated with top-down inputs from prefrontal and/or posterior parietal cortex to visual cortex, offering a potential substrate for visual imagery mediation, and (2) that haptic perception is associated with bottom-up inputs from somatosensory to visual cortex, providing a potential substrate for haptic recruitment of a multisensory representation housed in “visual” cortex. A secondary aim was to refine available methods for multivariate Granger causality analysis to allow execution of the primary aim.
Section snippets
MR imaging of haptic perception
Full details of subjects, stimulation, image acquisition and analysis can be found in the published report of haptic shape and texture selectivity (Stilla and Sathian, 2007); only a brief summary is given here. All procedures were approved by the Institutional Review Board of Emory University. The study was performed, with informed consent, on six neurologically normal, right-handed subjects (3 males and 3 females, mean age 22 years, age range 19–24 years). MR scans were performed on a 3 T
Activations
Haptically shape-selective regions (HS > HT) were located bilaterally in extensive regions spanning the postcentral sulcus (PCS) and the intraparietal sulcus (IPS), within which separable activations could be distinguished bilaterally in a number of regions: the PCS; anterior, posterior and ventral parts of the IPS (aIPS, pIPS and vIPS); the lateral occipital complex (LOC), ventral premotor cortex (PMv) and supplementary motor area (SMA). Unilateral activations could be resolved in the left
Methodological considerations
The present study demonstrates that it is feasible to employ multivariate analysis of Granger causality to investigate effective connectivity in neural circuits using BOLD-fMRI data. The approach is more tractable than ESEM, and the multivariate implementation permits simultaneous analysis of interactions between multiple ROIs, thereby overcoming a key limitation of bivariate Granger causality analysis. Moreover, our procedures allow quantitative comparison of the weights of different paths in
Conclusions
We conclude that it is feasible to employ multivariate Granger causality analysis followed by network reduction to eliminate regions whose connectivity does not contribute significantly to assess effective connectivity within a network of active regions, thereby fulfilling the secondary aim of the present study. Effective connectivity within the circuit of haptic shape-selective and haptic texture-selective regions is quite complex, involving interactions between areas usually regarded as
Acknowledgments
This work was supported by NIH grants R01 EY12440 and K24 EY17332 to KS, and R01 EB002009 to XH. Support to KS and RS from the Veterans Administration is also gratefully acknowledged. We thank Stephen LaConte and Marty Woldorff for helpful discussions.
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