The default mode network (DMN) in humans has been suggested to support a variety of cognitive functions and has been implicated in an array of neuropsychological disorders. However, its function (s) remains poorly understood. We show that rats possess a DMN that is broadly similar to the DMNs of nonhuman primates and humans. Our data suggest that, despite the distinct evolutionary paths between rodent and primate brain, a well-organized, intrinsically coherent DMN appears to be a fundamental feature in the mammalian brain whose primary functions might be to integrate multimodal sensory and affective information to guide behavior in anticipation of changing environmental contingencies.functional MRI | resting state | intrinsic activity | connectivity | spontaneous fluctuation I n the absence of an immediate need for goal-directed attention to the surrounding environment, our minds wander from recollection of past happenings to imagination of future events. Neuroimaging studies have consistently identified a set of interconnected brain areas that becomes less active during attentiondemanding cognitive tasks (1). This so-called default mode network (DMN) is posited to play a fundamental role in brain organization and supports a variety of self-referential functions such as understanding others' mental state, recollection and imagination (2), conceptual processing (3), and even in the sustenance of conscious awareness (4). Many of these functions have been considered to be unique to humans. Intriguingly, similar coherent structures have been shown to exist in anesthetized macaque monkeys and chimpanzees (5, 6). Furthermore, the functions of the default network are disrupted in such neuropsychological disorders as schizophrenia, Alzheimer's disease, and autism (7-9), underscoring the clear and critical need for further investigating the neurobiological basis of DMN using animal models.The evolutionary clade of rodents is about 35 million years earlier than that of old world monkeys and about 60 million years earlier than humans (10). Although many of the structures and functions of subcortical nuclei are conserved across these three species, the neocortex, in particular the "association" cortex, has extensively expanded in the primate as a result of evolutionary pressure, which is considered to be crucial in the development of higher cognitive and behavioral functions (10, 11). On the other hand, such structures as cingulate cortex, prefrontal cortex, and hippocampal formation, all of which are critical elements of the DMN, are also present in rodents (11). Given the distant evolutionary paths between rodent and primate brain, an intriguing question arises: Does the rat possess a similar DMN? Such a network, once demonstrated, would not only suggest that an operational DMN is a common feature in the mammalian brain, perhaps induced via parallel evolution as a result of natural selection, it would also offer a novel platform to explore the physiological basis and behavioral significance of the DMN. Such a demonstratio...

Experience with diffusion-weighted imaging (DWI) shows that signal attenuation is consistent with a multicompartmental theory of water diffusion in the brain. The source of this so-called nonexponential behavior is a topic of debate, because the cerebral cortex contains considerable microscopic heterogeneity and is therefore difficult to model. To account for this heterogeneity and understand its implications for current models of diffusion, a stretched-exponential function was developed to describe diffusion-related signal decay as a continuous distribution of sources decaying at different rates, with no assumptions made about the number of participating sources. DWI experiments were performed using a spin-echo diffusionweighted pulse sequence with b-values of 500 -6500 s/mm 2 in six rats. Signal attenuation curves were fit to a stretched-exponential function, and 20% of the voxels were better fit to the stretched-exponential model than to a biexponential model, even though the latter model had one more adjustable parameter. Based on the calculated intravoxel heterogeneity measure, the cerebral cortex contains considerable heterogeneity in diffusion. The use of a distributed diffusion coefficient (DDC) is suggested to measure mean intravoxel diffusion rates in the presence of such heterogeneity.Magn Two types of heterogeneity can be defined in MRI diffusion experiments: intravoxel and intervoxel. The goal of this work was to understand how intravoxel heterogeneity affects measurements of diffusion in the cerebral cortex using diffusion-weighted imaging (DWI). A stretched-exponential model was used to study the heterogeneity in DWI data.The motivation for understanding the biophysical basis of DWI lies partially in the potential of the technique for noninvasively detecting microscopic changes in tissue due to cerebral infarction and stroke (1). In addition, DWI studies of the changes in restrictions to intra-and extracellular water diffusion that occur with neoplastic invasion may lead to improved understanding and treatment of tumors (2,3). Finally, it has been shown that a reduction in the apparent diffusion coefficient (ADC) may occur during functional stimulation, which suggests the use of DWI as a functional contrast technique to study brain activation (4).Mathematical models of DWI have been tested in humans, animals, and cell cultures, but the controversy surrounding the identification of specific proton pools contributing to nonexponential behavior of the neural DWI signal remains (5-11). In vitro models, such as erythrocyte ghosts (10), have done much to establish the sensitivity of multiexponential models to cellular density, volume fractions, and exchange rates. However, the direct correspondence of these models to the results of brain imaging must still be established.The biexponential model of water diffusion assumes that there are two distinct proton pools inside each voxel, and that these proton pools have different diffusion rates that result in signal relaxation with b that is biexponential, whe...

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have recently been applied to investigate large-scale neuronal networks of the brain in the absence of specific task instructions. However, the underlying neural mechanisms of these fluctuations remain largely unknown. To this end, electrophysiological recordings and resting-state fMRI measurements were conducted in ␣-chloralose-anesthetized rats. Using a seed-voxel analysis strategy, region-specific, anesthetic dosedependent fMRI resting-state functional connectivity was detected in bilateral primary somatosensory cortex (S1FL) of the resting brain. Cortical electroencephalographic signals were also recorded from bilateral S1FL; a visual cortex locus served as a control site. Results demonstrate that, unlike the evoked fMRI response that correlates with power changes in the ␥ bands, the resting-state fMRI signal correlates with the power coherence in low-frequency bands, particularly the ␦ band. These data indicate that hemodynamic fMRI signal differentially registers specific electrical oscillatory frequency band activity, suggesting that fMRI may be able to distinguish the ongoing from the evoked activity of the brain.electroencephalogram ͉ spontaneous fluctuations ͉ functional connectivity T he human brain is thought to be composed of multiple coherent neuronal networks of variable scales that support sensory, motor, and cognitive functions (1). The traditional approach to studying such networks has been to use specific tasks to probe neurobiological responses. In contrast, recent studies have demonstrated the existence of spontaneous, low-frequency (i.e., Ͻ0.1 Hz) fluctuations in the functional MRI (fMRI) signal of the resting brain that exhibit coherence patterns within specific neuronal networks in the absence of overt task performance or explicit attentional demands (2-4). Such precisely patterned spontaneous activity has been reported in both awake human and anesthetized nonhuman primates (5). Recently, ''resting-state'' fMRI has been applied to study alterations in brain networks under such pathological conditions as Alzheimer's disease (6), multiple sclerosis (7), and spatial neglect syndrome (8). These studies collectively suggest that, rather than simple physiological artifacts induced by cardiac pulsations or respiration, as was originally suspected, these widely distributed coherent low-frequency fMRI fluctuations have a direct neural basis (9, 10). However, more than a decade since they were first identified, the linkage between neuronal activity and restingstate fMRI signal remains largely unknown, underscoring the clear and critical need for well controlled animal models to investigate this phenomenon.Across various states of vigilance, the electrical activity of neuronal networks is known to oscillate at various frequencies and amplitudes, with high-frequency oscillations confined to local networks, whereas large networks are recruited during slow oscillations (11,12). Imposed tasks alter local field potent...