Clinical interest in mapping functional connectivity with MRI continues to grow as the technique has demonstrated the ability to detect alterations in patients with disorders such as Alzheimer’s (1
), schizophrenia (2
), and depression (3
). Despite this promising evidence of sensitivity to clinically relevant changes, the interpretation of functional connectivity data remains limited by our incomplete understanding of the interactions between the local changes in neural activity, metabolism, and hemodynamics that lead to the low frequency BOLD fluctuations.
To elucidate the origins of functional connectivity, several groups have turned to animal models (4
). Their work has demonstrated that functional connectivity similar to that observed in awake humans can be detected in other species such as rodents, even though anesthesia is typically required to facilitate imaging. These animal models provide a platform for investigations of the relationship between spontaneous neural activity, local metabolic changes, variations in blood flow, and MRI signal fluctuations (9
). The rodent brain in particular has been well-characterized by neuroscientists through recording techniques, selective lesioning, and behavioral studies, providing an extensive framework for the design and interpretation of functional connectivity experiments. Rodent models also offer the advantage of high inter-subject homogeneity, and the use of high-field dedicated small animal MRI systems provides excellent spatial and temporal resolution.
In humans, functional connectivity studies are performed almost exclusively with BOLD contrast (11
). In animal models, however, both BOLD and cerebral blood volume (CBV) weighting have been used to map correlated signal fluctuations (6
), raising the issue of whether BOLD and CBV-weighted studies supply comparable measurements of functional connectivity. The BOLD signal comprises a complicated combination of several hemodynamic and metabolic properties including CBV, cerebral blood flow (CBF), and the local rate of oxygen consumption (CMRO2). It is not yet clear if spontaneous fluctuations in each of these parameters are equally linked to spontaneous fluctuations in neural activity. For example, 0.1 Hz oscillations in CBF and CBV have been observed with multiple modalities and are often attributed to vasomotion, and some studies have not found a clear link between these oscillations and electrical activity (15
). By measuring hemodynamic parameters that contribute to the BOLD signal, such as CBV, it may be possible to determine if particular contrasts are more closely related to neural activity than others.
Previous work with stimulus-induced activation suggests that CBV-weighted imaging may offer enhanced sensitivity and increased functional localization compared to BOLD (18
), partially due to reduced contributions from large vessels. It is possible that this same property will improve localization in functional connectivity studies. In this study, BOLD and CBV-weighted data are acquired sequentially from the same rat to determine the relative sensitivity and specificity of the two techniques.
In addition to examining the steady-state characteristics of the BOLD and CBV functional connectivity maps, this study also compares the spatiotemporal dynamics of the signal fluctuations. Functional connectivity scans are conventionally analyzed using seed region-based cross-correlation techniques (11
); however, a recent article by Majeed et al. (21
) describes a method for visualizing the spatiotemporal dynamics of the low frequency fluctuations. The data presented by Majeed et al. challenges standard interpretations of functional connectivity maps acquired in the anesthetized rodent, as waves of BOLD signal propagate along the cortex, connecting areas that exhibit little correlation in their time courses.
Dynamic spatiotemporal analysis of resting state functional connectivity (RSFC) scans has only been conducted using the BOLD signal to date. At short TRs, the BOLD signal is heavily weighted toward CBF due to inflow effects, which could be partially responsible for the spatiotemporal dynamics observed in Majeed’s work (21
). CBV-weighted imaging using ultra-small paramagnetic iron oxide (USPIO) particles to provide contrast is not typically susceptible to inflow effects because the signal from the blood is diminished due to the presence of iron oxide, so the presence of propagating waves in the CBV-weighted signal would suggest that they are not primarily due to inflow effects.
The purpose of this study is twofold; first, to determine whether measurements of BOLD and CBV RSFC provide comparable information for functional connectivity mapping and second, to provide insight into the relative contribution of CBV information to the BOLD signal. BOLD and CBV-weighted data from the same rats will be examined using spectral analysis, traditional cross correlation analysis, and dynamic spatiotemporal visualization. The results of this study show that BOLD and CBV provide similar maps of functional connectivity and demonstrate that the propagating waves previously observed in the BOLD signal can be detected with CBV-weighted imaging, suggesting that these dynamics are a general hemodynamic phenomenon widely observed in anesthetized rodents.