|Home | About | Journals | Submit | Contact Us | Français|
The ascending reticular activating system (ARAS) mediates arousal, an essential component of human consciousness. Lesions of the ARAS cause coma, the most severe disorder of consciousness. Because of current methodological limitations, including of postmortem tissue analysis, the neuroanatomic connectivity of the human ARAS is poorly understood. We applied the advanced imaging technique of high angular resolution diffusion imaging (HARDI) to elucidate the structural connectivity of the ARAS in 3 adult human brains, 2 of which were imaged postmortem. HARDI tractography identified the ARAS connectivity previously described in animals and also revealed novel human pathways connecting the brainstem to the thalamus, hypothalamus, and basal forebrain. Each pathway contained different distributions of fiber tracts from known neurotransmitter-specific ARAS nuclei in the brainstem. The histologically guided tractography findings reported here provide initial evidence for human-specific pathways of the ARAS. The unique composition of neurotransmitter-specific fiber tracts within each ARAS pathway suggests structural specializations that subserve the different functional characteristics of human arousal. This ARAS connectivity analysis provides proof of principle that HARDI tractography may impact the study of human consciousness and its disorders, including in neuropathologic studies of patients dying in coma and the persistent vegetative state.
Human consciousness consists of 2 critical components: arousal and awareness (1, 2). Arousal pathways originating in the brainstem activate awareness networks in the cerebral cortex via synapses in the thalamus and basal forebrain (3–5), or alternatively, via direct innervation of the cortex itself (4, 5). Without arousal, awareness is not possible, as evidenced by comatose patients with brainstem lesions but an anatomically intact cerebral cortex (6, 7). The physiological and neuroanatomic basis of arousal in the brainstem has historically been conceptualized as the ascending reticular activating system (ARAS), an idea introduced by Moruzzi and Magoun in 1949 (8). In classic studies in cats, electrical stimulation of the dorsal midbrain produced widespread, bihemispheric activation of the cerebral cortex, as demonstrated by electroencephalography (EEG). The pathways of the ARAS were initially thought to originate solely in the central core of the upper brainstem called the reticular formation because of its net-like histological appearance (5). In this original model of the ascending arousal system, neural projections from the reticular formation (e.g. the cuneiform/subcuneiform nucleus in the midbrain and pontis oralis in the rostral pons) were believed to activate the cerebral cortex via excitatory (glutamatergic) relays in the thalamus.
It is now recognized that the ARAS is comprised of a complex and diffuse network of neurons projecting from multiple brainstem source nuclei (within and adjacent to the classical reticular core) to the cortex via thalamic (9) and extra-thalamic pathways (1, 2, 4, 5, 10). These pathways are typically called “neurotransmitter-specific,” and include serotonergic fibers from the raphe subnuclei of the rostral pons and midbrain (11), noradrenergic fibers from the locus coeruleus of the rostral pons (12), dopaminergic fibers from the ventral tegmental area of the caudal midbrain (13), cholinergic fibers from the pedunculopontine nucleus and laterodorsal tegmental nucleus of the caudal midbrain and rostral pons (3), and glutamatergic fibers from the parabrachial complex in the rostral pons (14). Arousal is further mediated by ARAS connectivity with the hypothalamus, which participates in the regulation of autonomic function (15) and circadian sleep-wake cycles (16), and with the basal forebrain, which participates in cortical activation and autonomic integration (5, 14). Thus, in this report “ARAS” refers to the reticular core and extended source nuclei in the brainstem that mediate arousal, as well as their rostral projections to the hypothalamus, thalamus, basal forebrain, and cortex. Of note, these extended source nuclei are the so-called neurotransmitter-specific nuclei. In this modern model of the ARAS, the thalamus is not simply a relay center; rather, it integrates and modulates the interactions between brainstem arousal networks and cortical awareness networks (17).
The elucidation of the neuroanatomic basis of the human ARAS is essential for determining the structural features of human arousal and for treating disorders of consciousness, such as traumatic or stroke-related coma. In addition, postmortem analyses of ARAS connections and their disruption are of major importance for neuropathologists in the elucidation of the neuroanatomic substrate of coma (7), the persistent vegetative state (18), and the minimally conscious state (19) directly in the human brain. Yet, current neuroanatomic models of the human ARAS are based largely upon extrapolations from animal studies, which may not be directly relevant to humans given the unique features of human consciousness. Indeed, it is unknown which pathways in the human ARAS are evolutionarily conserved, and which pathways may have formed new connections during evolutionary development of the human arousal system, as suggested by prior studies showing interspecies differences in brainstem connectivity (20). The critical methodological barrier preventing a detailed connectivity analysis of the human ARAS at autopsy is the limited feasibility of histological tract tracing using postmortem dye injections. This limitation is attributable to excessively long diffusion times (i.e. months) and inability of tracers to diffuse long distances along myelinated axons (21, 22). Moreover, conventional magnetic resonance imaging (MRI) of the brainstem does not provide sufficient resolution to identify the small (i.e. millimeters), discrete components of the ARAS. While functional neuroimaging studies in humans have revealed activation in the brainstem and thalamus during arousal (23), these studies do not provide information about neuroanatomic connectivity between different network nodes. Even tractography reconstructions of diffusion tensor MRI data lack the angular resolution needed to identify the crossing nerve fibers (24) that are a prominent structural feature of the ARAS (5).
Recently, a more sophisticated magnetic resonance technique, high angular resolution diffusion imaging (HARDI) tractography (25), has advanced the study of complex neural networks by enhancing crossing fiber detection (26). Similar to diffusion tensor tractography, HARDI tractography is based on the principle that the neuroanatomic trajectory of axon bundles can be delineated by measuring the directionality of water diffusion along these axons (27, 28). The major methodological advantage of HARDI tractography over diffusion tensor tractography is the ability to resolve multiple axonal bundles traversing in different directions within the same volume of space, or voxel (26). HARDI tractography may, therefore, provide greater spatial and angular resolution for connectivity analyses in the adult human brain than currently available imaging or tissue labeling methods. We hypothesized that HARDI tractography elucidates the complex neuroanatomic connectivity of the human ARAS in the brainstem, hypothalamus, thalamus, and basal forebrain. To test this hypothesis, we performed ARAS connectivity analyses in 2 postmortem human brain specimens, including one in which extensive histological correlation analyses were performed, and in one living human subject. We analyzed the components of the ARAS that originate in the classical reticular core and the extended neurotransmitter-specific nuclei. We refer here to these latter nuclei relative to their known key neurotransmitter according to convention, although we did not perform neurotransmitter-specific immunocytochemical analysis of the postmortem brains. Also of note, we define “connectivity” between neuroanatomic regions by the presence of a bundle of fiber tracts the ends of which terminate within each respective region. This definition of structural connectivity, as delineated by HARDI tractography, does not prove synaptic connectivity, which will require future correlative structural-functional studies of the ARAS.
The brains of 3 adults without neurological disease were analyzed with HARDI tractography: 2 were brains from autopsy (Cases 1 and 2), and one was in a living subject (Case 3). Autopsies were performed in Cases 1 and 2 with consent of the family and included permission for research under our institutional review-board approved protocol. For Case 3, an in vivo HARDI scan was performed with consent from the subject under a separate institutional review-board approved protocol. The brain of Case 1 was used as the index case in which histological data were correlated with the neuroanatomic localization of ARAS nuclei and the connectivity sites of ARAS fiber tracts, as identified by HARDI tractography.
Case 1 was a 53-year-old woman with a history of breast cancer (stage I) and a more recent diagnosis of high-grade, pleomorphic sarcoma involving the pelvis. She had no history of neurological illness, brain metastases, or brain radiation. A normal neurological examination was documented during her last hospitalization, 1 month prior to her death in a long-term care facility. The death was attributed to systemic complications of cancer. At autopsy, the fresh brain weight was normal (1,250 g [normal range: 1,200 – 1,500 g]). The leptomeninges showed mild fibrosis. There was mild atherosclerosis of the basilar, middle cerebral, and posterior cerebral arteries, but no occlusions or emboli. The cerebrum and cerebellum showed no macroscopic evidence of atrophy, hemorrhage, or infarcts. Standard sections in a survey of all brain regions demonstrated mild arteriolosclerosis and agonal hypoxic-ischemic changes in the cerebellar cortex. Microscopic examination of the serial sections of the specimen imaged with HARDI tractography was unremarkable.
Case 2 was a 49-year-old man with a history of hypertension, hyperlipidemia, diabetes, and T-cell prolymphocytic leukemia, status-post unrelated donor stem cell transplantation, who died of sepsis 48 days post-transplant. He had no history of neurological disease or neurological complications of his hematologic malignancy, and a normal neurological examination was documented during his final hospitalization. At autopsy, the fresh brain weight was normal (1,350 g). There was no evidence of atherosclerosis, occlusions, or emboli in the cerebral vasculature; the leptomeninges appeared normal. The cerebrum and cerebellum showed no macroscopic evidence of atrophy, hemorrhage, or infarcts. Standard sections in a survey of all brain regions were stained with hematoxylin and eosin, Luxol fast blue for myelin, and Bodian silver for axons. Microscopic analysis showed mild arteriolosclerosis and scattered reactive astrocytes in gray and white matter. Two microscopic foci of myelin pallor on Luxol fast blue were noted: 1 in the right periventricular white matter and in 1 the cerebellar white matter adjacent to the dentate nucleus, both immediately abutting the ependymal surface. These regions each measured <0.3 cm and showed relative preservation of axons. There were no inflammatory infiltrates. Because of these incidental findings, for which no clinical correlate could be identified on review of all available medical records, an extensive analysis was performed of the brainstem and diencephalic regions that were the focus of our tractography analysis. No additional incidental lesions were identified in the pons, midbrain, hypothalamus, thalamus, or basal forebrain on hematoxylin and eosin or Luxol fast blue stains. Case 3 was a 32-year-old man with no history of medical or neurological disease.
To scan the ARAS with high spatial and angular resolution, which is critical for tractography analyses of fiber pathways with complex branching patterns and high angles of curvature (24), a small horizontal-bore, high-field (4.7 Tesla) Bruker Biospec MRI scanner was used in Case 1. To fit the specimen into the small bore of the scanner, the cerebral hemispheres were dissected from the thalamus and basal forebrain, and the cerebellum was dissected from the brainstem, such that the scanned specimen consisted of the pons, midbrain, hypothalamus, thalamus, basal forebrain, and basal ganglia (Figure, Supplemental Digital Content 1, http://links.lww.com/NEN/A333). The dimensions of the dissected specimen were 7.0 cm (rostral-caudal axis) × 4.0 cm (anterior-posterior axis at level of thalami) × 5.9 cm (medial-lateral axis at level of thalami). The dissection was performed 80 days after the patient’s death and imaging data were acquired 103 days after death.
Immediately prior to scanning, the dissected brain specimen was transferred from a 10% formaldehyde solution to a Fomblin solution (perfluoropolyether, Ausimont USA, Inc., Thorofare, NJ), which reduces magnetic susceptibility artifacts that may occur during image acquisition (29). The HARDI sequence utilized in this scan was a 3-dimensional (3D) diffusion-weighted spin-echo echo-planar imaging (DW-SE-EPI) sequence with 60 diffusion-weighted measurements, corresponding to a cubic lattice in Q-space of b = 4057 s/mm2, using gradient strength of 12.4 G/cm, duration = 13.4 msec and intertemporal pulse offset = 25 msec. Repetition time (TR) was 1000 msec, echo time (TE) was 72.5 msec, the field of view was 7.2 × 7.8 × 8.2 cm, and the imaging matrix was 128 × 128 × 128 pixels, yielding a spatial resolution of 562 × 609 × 641 µm. One dataset of 3D DW-SE-EPI data with b = 0 s/mm2 was also acquired to calculate quantitative diffusion properties in each voxel. Total image acquisition time was 130 minutes.
The brain specimen for Case 2 was scanned as a whole brain on a 3 Tesla Tim Trio MRI scanner (Siemens Medical Solutions, Erlangen, Germany) using a 32-channel head coil. As in Case 1, the specimen for Case 2 was transferred from a 10% formaldehyde solution to a Fomblin solution immediately prior to imaging, which was performed 8 months and 16 days after death. To increase diffusion sensitivity on the clinical 3 Tesla MRI scanner that was required to scan a whole brain specimen, diffusion data were acquired using a 3D diffusion-weighted steady-state free-precession (DW-SSFP) sequence (30, 31), with a 3DFT readout using following parameters: TR = 27.8 msec, TE = 22.9 msec, flip angle = 60 degrees, bandwidth = 150 Hz/pixel, diffusion gradient duration = 18 msec, diffusion gradient amplitude = 3.2 G/cm, matrix size = 192 × 176 × 128 pixels, and field of view = 19.2 × 17.6 × 12.8 cm, yielding a spatial resolution of 1.0 × 1.0 × 1.0 mm. Four datasets of non-diffusion-weighted volumes (b = 0 s/mm2) and 44 datasets of diffusion-weighted volumes were acquired, resulting in a total scan time of 5 hours and 35 minutes. Of note, in a DW-SSFP sequence, diffusion-weighting is not defined by a single global b value, as in the DW-SE-EPI sequence utilized in Case 1, because the diffusion signal in a DW-SSFP sequence cannot be readily dissociated from other imaging properties, such as the T1 relaxation time, the T2 relaxation time, TR, and the flip angle (30, 32). The diffusion weighting in a DW-SSFP study is therefore characterized by the diffusion gradient duration and amplitude, as reported above.
Imaging was performed for Case 3 on a 3 Tesla Tim Trio MRI scanner (Siemens Medical Solutions, Erlangen, Germany) with a 32-channel head coil. HARDI data were acquired utilizing a twice-refocused SE EPI sequence (33) with the following parameters: TR/TE = 12750/130 msec, bandwidth = 1395 Hz/pixel, matrix size = 128 × 128, and field of view = 256 × 256 cm2, yielding an in-plane spatial resolution of 2.0 × 2.0 mm. Seventy-four slices of 2 mm slice thickness were acquired. Twenty datasets of non-diffusion-weighted volumes (b = 0 s/mm2) and 120 datasets of diffusion-weighted volumes were acquired with a prespecified b value of 4000 s/mm2, resulting in a total scan time of 29 minutes and 45 seconds.
At the completion of image acquisition, the dissected brain specimen of Case 1, consisting of the pons, midbrain, hypothalamus, thalamus, basal forebrain, and basal ganglia en bloc (Figure, Supplemental Digital Content 1, http://links.lww.com/NEN/A333) was divided into 7 blocks, approximately 0.5- to 1.5-cm-thick that were then embedded in paraffin. Serial transverse sections of the pons and midbrain and coronal sections of the hypothalamus, thalamus, and basal forebrain were prepared at 10-µm thickness with a microtome (LEICA RM2255, Leica Microsystems, Buffalo Grove, IL). Every 50th section was stained with hematoxylin and eosin for nuclear boundaries and counterstained with the myelin stain, Luxol fast blue, for fiber tract boundaries. Each examined section was separated by 500 µm, for a total of 74 sections from mid-pons through the entire hypothalamus, thalamus, basal forebrain, and basal ganglia.
ARAS fiber tracts were identified using regions of interest (ROIs) that were manually traced on the diffusion images using TrackVis (version 5.1), an interactive image analysis software program that is available to the scientific community without charge (34). For Case 1, each diffusion image was compared to its corresponding histological section to ensure that radiologic ROIs shared the same borders, size, and contours as the histological ROIs. Histological ROIs were delineated by visual inspection with a light microscope and were confirmed by standard atlases of human neuroanatomy (35–37). ROIs were identified for all of the key ARAS source nuclei implicated in arousal: cuneiform/subcuneiform nucleus, pontis oralis, median and dorsal raphe, locus coeruleus, pedunculopontine nucleus, parabrachial complex (combined medial and lateral parabrachial nuclei), and ventral tegmental area (Fig. 1A, B; Figure, Supplemental Digital Content 2, http://links.lww.com/NEN/A336 and Figure, Supplement Digital Content 3, http://links.lww.com/NEN/A337). ROIs were also traced using histological guidance for the thalamic nuclei implicated in the modulation, or gating, of arousal: the reticular nucleus, the central lateral nucleus, and the centromedian/parafascicular nuclear complex (Figure, Supplemental Digital Content 2, http://links.lww.com/NEN/A336). Each brainstem and thalamic ROI served as a seed point from which fiber tracts were generated. Because the brainstem ROIs are known to change in shape, size and contour along the rostro-caudal axis, histological guidance of ROI tracing was performed for every axial diffusion image using its corresponding histological section. Similarly, each thalamic nucleus was traced on the coronal diffusion images with direct guidance by the location of the stained nuclei on corresponding coronal tissue sections. For the intrathalamic connectivity analyses, a 2-ROI-tractography technique was utilized, based on methods developed by Catani et al (38). Specifically, fiber tracts passing between the reticular nucleus and central lateral nucleus were “virtually dissected” from fiber tracts passing between the reticular nucleus and the centromedian/parafascicular nuclear complex. For Cases 2 and 3, brainstem and thalamic nuclei were traced in accordance with the aforementioned neuroanatomic atlases. We also compared the neuroanatomic localization, contours, and boundaries of these ROIs in Cases 1, 2, and 3 to ensure consistency in the tractography analyses.
There are variations in nomenclature pertaining to the source nuclei of the ARAS in standard neuroanatomic atlases of the human brainstem. In this study, the neuroanatomic localization of the pedunculopontine nucleus was traced according to the brainstem atlas of Paxinos and Huang (35), extending from the caudal midbrain to the caudal border of the red nuclei. The neuroanatomic localization of the parabrachial complex was traced according to the brainstem atlas of Olszewski and Baxter (36), extending from the mid-pons to the rostral pons.
Diffusion data were processed in Diffusion Toolkit (version 6.0) (34) utilizing a HARDI reconstruction in which the orientation distribution function of angular water diffusion is calculated for each voxel on a spherical harmonic basis (39). By calculating an orientation distribution function for each voxel, the HARDI reconstruction allows for multiple diffusion directions within each voxel, as opposed to the single diffusion direction that is calculated in a diffusion tensor imaging reconstruction. Fiber tracking was performed in TrackVis (version 5.1) (34) utilizing a streamline, deterministic tractography method. Fiber tract propagation is based on the coherence of directional water diffusion in adjacent voxels (40), as determined by the orientation distribution functions generated by the HARDI reconstruction. When the direction of water diffusion is similar in adjacent voxels, the tractography model displays these voxels as being part of a coherent fiber tract. When directional diffusion in multiple voxels is potentially coherent, the tractography algorithm consistently pursues the water diffusion vector of least voxel-to-voxel curvature, thereby reducing the possibility of identifying spurious, inaccurate fiber tracts. In this experiment, fiber tracts were terminated when the angle between water diffusion vectors in adjacent voxels exceeded a prespecified threshold of 60°. Whereas tracts tend to terminate at sites of fiber crossing in diffusion tensor tractography, the improved angular resolution provided by HARDI allows tracts to continue in multiple directions at sites of fiber crossing (26). Given that low measurements of directional water diffusion, or fractional anisotropy (FA), have been observed in the dorsal pons, midbrain (41), and thalamus (42) in humans, no FA threshold was applied to the tractography analyses. For intrathalamic connectivity analyses, a length threshold was applied in order to eliminate the long fiber tracts connecting the thalamic nuclei to the brainstem. This length threshold was necessary in order to isolate the comparatively shorter intrathalamic fiber tracts.
To test whether the HARDI data were of sufficient quality for tractography reconstructions (i.e. connectivity modeling), we calculated the signal-to-noise ratio for each HARDI scan by dividing the mean signal within the white matter of the internal capsule by the standard deviation of the signal outside the specimen (i.e. noise) on the trace diffusion-weighted images and the non-diffusion-weighted images with b = 0 s/mm2 (b0). The diffusion-weighted images signal-to-noise ratio for Cases 1, 2, and 3 were 466, 186, and 137, respectively. The b0 signal-to-noise ratio were 49, 106, and 308 respectively, values that are more than sufficient to produce high-quality tractography results (25). For the HARDI scans in Cases 1 and 3, we also performed Diffusion Toolkit diffusion tensor reconstructions for standard quantitative measurements of water diffusion – FA and the apparent diffusion coefficient (ADC) – since these measurements have not previously been performed in ARAS fiber tracts. For comparison, FA and ADC were also measured within the corticospinal tract, a structure in which water diffusion has been well characterized in studies of ex vivo (43) and in vivo (44) human brains. The purpose of these comparative FA and ADC analyses was to ascertain how water diffusion in the complex network of ARAS fiber tracts compared to water diffusion within the more homogeneous, parallel fibers of the corticospinal tract. FA and ADC values were not calculated for Case 2 because (as stated above), a single b value cannot be precisely calculated for the DW-SSFP sequence that was used in Case 2. As a result, whereas the DW-SSFP sequence provides well validated measurements of the directionality of water diffusion for tractography modeling in the human brain (31, 45), the complex signal evolution in the DW-SSFP sequence (32) precludes standard quantitative diffusion measurements (31).
To optimize the specificity of ARAS tract identification, we rigorously eliminated non-ARAS fiber tracts from the ARAS tractography analysis. Non-ARAS ROIs that were in close neuroanatomic proximity to ARAS ROIs were first identified and traced on the diffusion images for Case 1 using histological guidance, and then all fiber tracts passing through these non-ARAS ROIs were excluded from subsequent ARAS tractography analyses. We eliminated all fiber tracts passing through the superior cerebellar peduncle (both the brachium and the decussation), middle cerebellar peduncle, cranial nerve III, cerebral peduncle (including the frontopontine fibers), medial lemniscus, ventral trigeminothalamic tract (which runs dorsal to the medial lemniscus in the rostral pons), and the medial longitudinal fasciculus (which ascends at the ventro-medial margin of the periventricular and peri-aqueductal grey). Once these non-ARAS fiber tracts were eliminated, ARAS connectivity was determined by analyzing the trajectories and termination sites of the ARAS fiber tracts within the brainstem, hypothalamus, thalamus, basal forebrain, and basal ganglia. For Cases 2 and 3, non-ARAS pathways were eliminated by tracing non-ARAS ROIs using guidance from neuroanatomic atlases. Because the HARDI scans for Cases 2 and 3 were performed on whole brains, we also eliminated fiber tracts from the fornix, a structure that was not present in the dissected specimen of Case 1.
HARDI tractography revealed a bilateral fiber bundle connecting the cuneiform/subcuneiform nucleus in the rostral midbrain to the thalamus, hypothalamus, and basal forebrain (Table 1; Fig. 1). The originating source of this fiber bundle also included the pontis oralis of the rostral pons (Fig. 2). In the rostral midbrain, the bilateral fiber bundle bifurcated into ventral and dorsal bundles (Figs. 1, ,2,2, ,3A).3A). Here we suggest the labels ventral tegmental tract (VTT) and dorsal tegmental tract (DTT) for these 2 large divergent bundles in the human brain, names with historical precedent in experimental animals (46–48). The human VTT bifurcated yet again into 2 additional fiber bundles, one a distinct caudal pathway connecting with the hypothalamus, zona incerta, Forel’s fields, basal forebrain and globus pallidus, and the other a rostral pathway connecting with the paraventricular (midline) region of the thalamus (Table 1; Fig. 3A, 4). We labeled the human hypothalamic VTT pathway as the VTT caudal (VTTC), and the thalamic VTT pathway as the VTT rostral (VTTR).
The human DTT bifurcated into 2 additional fiber bundles that each projected to a different distribution of thalamic nuclei. One subdivision, which we labeled the DTT lateral (DTTL), projected laterally to the thalamic reticular nucleus and, to a lesser extent, the basal forebrain, pulvinar, and lateral geniculate nucleus of the thalamus (Table 1; Fig. 1C, D, ,2,2, ,3A,3A, 5). The second subdivision of the DTT, which we labeled DTT medial (DTTM), projected medially to thalamic intralaminar nuclei (central lateral nucleus and centromedian/parafascicular nuclear complex). In addition, several DTTM fibers projected beyond the intralaminar nuclei along a rostral and lateral course to the reticular nucleus (Figs. 3A, 5). Of note, examination of the cuneiform/subcuneiform fiber tracts revealed both short and long rostral projections, and fibers crossing to the contralateral side of the brainstem (Figure, Supplemental Digital Content 4, http://links.lww.com/NEN/A338), well-recognized features of the brainstem reticular formation (48). In Cases 2 and 3, tractography analyses of ARAS brainstem ROIs revealed VTTR, VTTC, DTTL, and DTTM pathways whose trajectories and sites of connectivity were consistent with the findings in Case 1 (Fig. 5; Figure, Supplemental Digital Content 5, http://links.lww.com/NEN/A339).
Comparative FA and ADC analyses in the cuneiform/subcuneiform, pontis oralis, and corticospinal fiber tracts demonstrated that FA values were lower and ADC values were higher in the cuneiform/subcuneiform and pontis oralis fiber tracts than in the corticospinal fiber tracts for both Case 1 and Case 3 (Table 2). FA and ADC measurements in the corticospinal fiber tracts in Case 1 were consistent with those reported for ex vivo human brains (43). Of note, the lower ADC values observed in Case 1 as compared to Case 3 are expected because ADC values have been demonstrated to be lower in the postmortem human brain than in the living human brain (43). Interestingly, FA values were similar in Cases 1 and 3, consistent with prior studies showing that tissue death and fixation do not affect FA as much as ADC (43). Whereas there are few prior studies of FA or ADC in living human subjects imaged at high b values, our corticospinal tract FA and ADC measurements are generally consistent with the results of Yoshiura et al, who measured FA and ADC in the internal capsule using the same b value of 4000 s/mm2 that was utilized in Case 3 (49). Also of note, the in vivo white matter ADC values of approximately 400 to 500 × 10−6 mm2/s acquired with a b value of 4000 s/mm2 in this study and in (50) are significantly lower than the ADC values of approximately 700 × 10−6 mm2/s that have been reported in prior in vivo studies of human white matter using b values ranging from 700 to 1000 s/mm2 (49, 50). This decline in ADC is explained by the non-monoexponential relationship between b value and ADC at high b values (where high is typically considered as b > 2000 s/mm2 for in vivo human studies) (49, 51).
Subdivisions of the VTT and DTT were further demonstrated to carry fibers of the known monoaminergic-, cholinergic-, and glutamatergic-related source nuclei in the brainstem. Each of these source nuclei had specific patterns of connectivity with the thalamus (Figs. 3A, ,6,6, ,7;7; Figure, Supplemental Digital Content 6, http://links.lww.com/NEN/A341; Figure, Supplemental Digital Content 7, http://links.lww.com/NEN/A342; Figure, Supplemental Digital Content 8, http://links.lww.com/NEN/A343; Figure, Supplemental Digital Content 9, http://links.lww.com/NEN/A344; Figure, Supplemental Digital Content 10, http://links.lww.com/NEN/A345), hypothalamus (Figs. 4, ,6,6, ,7;7; Figure, Supplemental Digital Content 6, http://links.lww.com/NEN/A341; Figure, Supplemental Digital Content 7, http://links.lww.com/NEN/A342; Figure, Supplemental Digital Content 8, http://links.lww.com/NEN/A343; Figure, Supplemental Digital Content 9, http://links.lww.com/NEN/A344; Figure, Supplemental Digital Content 10, http://links.lww.com/NEN/A345), and basal forebrain (Table 1; Figure, Supplemental Digital Content 7, http://links.lww.com/NEN/A342). Of note, diffuse thalamic projections that are known to arise from serotonergic neurons in the raphe and noradrenergic neurons in the locus coeruleus were not identified with ex vivo HARDI tractography in Case 1 but were identified with ex vivo HARDI tractography in Case 2 and in vivo HARDI tractography in Case 3 (Figure, Supplemental Digital Content 11, http://links.lww.com/NEN/A346).
We delineated connections between the thalamic nuclei implicated in gating of the inputs of the ascending arousal system to the cerebral cortex (17, 52). The reticular nucleus connected with both the central lateral nucleus and the centromedian/parafascicular nuclear complex via dense bundles of fibers with direct, linear trajectories (Fig. 3B). These intrathalamic fiber bundles were interspersed with the DTTM fibers traveling through the intralaminar nuclei to the reticular nucleus (Figure, Supplemental Digital Content 12, http://links.lww.com/NEN/A347). Also of note, a group of fiber tracts was observed to connect the reticular nucleus with Forel’s fields and zona incerta by passing through the central lateral and centromedian/parafascicular nuclei (Figs. 3B, 6). The termination points of these fiber tracts within Forel’s fields and zona incerta were in close proximity to the termination points of brainstem source nuclei pathways that connected with these same regions (Fig. 6).
This study provides proof of principle that HARDI tractography is a potent tool for dissecting the complex neuroanatomic substrate of the human ARAS. Virtual dissection of ARAS pathways was demonstrated in the human brain, both in vivo and ex vivo, suggesting that HARDI tractography may be used in living patients and in postmortem neuropathologic analyses to study the neuroanatomic basis of consciousness and its disorders. We found that the human ARAS shares several important features with that of experimental animals: 1) ARAS brainstem source nuclei connect primarily with the intralaminar, paraventricular, and reticular nuclei of the thalamus; 2) the known monoaminergic-, cholinergic-, and glutamatergic-related nuclei in the upper brainstem all connect with the hypothalamus; 3) the basal forebrain is connected with multiple brainstem source nuclei of the ARAS; and 4) the reticular, central lateral, and centromedian/parafascicular thalamic nuclei connect with each other, providing a structural basis for human intrinsic thalamic networks that modulate ARAS activation of thalamocortical networks. The short and long rostral projections of the cuneiform/subcuneiform tracts and the fibers crossing to the contralateral side of the brainstem in our 3 cases are also well-recognized features of the brainstem reticular formation (48) and are consistent with the recognized complexity of the ARAS network (5). Yet, we also defined new human pathways, the VTT and DTT and their subdivisions, which are distinct in their trajectory, connectivity, and source nuclei origins from the VTT and DTT pathways described in animals with tract tracing methods (46–48). In the following discussion, we highlight our findings in the context of the current understanding of ARAS neuroanatomy, with emphasis upon how our data expand upon previous findings in animals and humans. We begin with a consideration of key methodological issues and limitations of HARDI tractography for consideration in the interpretation of our data.
It is important to emphasize that HARDI tractography provides an inferential model, and not a direct measurement, of white matter connectivity in the human brain. In HARDI studies, the accuracy of the neuroanatomic connectivity model depends upon several methodological factors that must be considered in both the data acquisition and post-processing stages of the experiment. For example, the sensitivity of HARDI tractography for detecting fiber tracts depends primarily on the spatial and angular resolution of the water diffusion measurements that are performed during the scan (data acquisition), which provide the basis for reconstructing a model of white matter connectivity. The specificity of HARDI tractography data is related to the ability to eliminate fiber tracts from non-relevant neuroanatomic pathways (data post-processing). In this study, we optimized the sensitivity of ARAS tract identification by acquiring HARDI data with extremely high spatial and angular resolution, particularly in the index case (Case 1), as evidenced by the high number of diffusion gradients (n = 60) (53, 54), the strength of the gradients (12.4 G/cm), which allows for high b-values with relatively short gradient duration times (55), and the high field-strength of the magnet (4.7 Tesla), which allows for high in-plane resolution (56). Furthermore, the postmortem, ex vivo data acquisition in Cases 1 and 2 further increases HARDI’s sensitivity for identifying ARAS pathways by allowing for a long duration of scan time (2 hours and 10 minutes for Case 1; 5 hours and 35 minutes for Case 2), as well as the elimination of movement artifacts and susceptibility artifacts caused by the skull base and air-filled sinuses. In Case 3, we increased the sensitivity of in vivo HARDI data acquisition by utilizing a high number of directional diffusion gradients (n = 120) and a high b value (4000 s/mm2). The specificity of ARAS tract identification was optimized during the post-processing stage by rigorously excluding non-ARAS fiber tracts and by defining each ARAS ROI as precisely as possible using histological guidance, as discussed above. However, it should be noted that the ARAS is comprised of multisynaptic pathways that ascend and descend throughout the brainstem; and because HARDI tractography does not provide functional data about the direction of electrical signaling within these pathways, we cannot eliminate the possibility that some of the ARAS pathways identified in this study contained descending fiber tracts. On the other hand, the structural (as opposed to functional) nature of HARDI tractography data enables application of this imaging technique to both in vivo clinical studies and ex vivo neuropathologic studies.
While HARDI and related techniques, such as diffusion spectrum imaging, are better able to resolve crossing fibers than diffusion tensor imaging (24, 26), there is currently a limit at which the spatial and angular resolution, and hence the sensitivity, of these techniques is exceeded. This methodological limitation is particularly relevant for in vivo HARDI studies because of the long duration of scan time that is required to optimize the resolution of HARDI data. We have demonstrated that acquisition of HARDI data with sufficient resolution to identify ARAS connectivity is feasible in a healthy human subject, but human patients with neurological disease may not be able to tolerate long-duration HARDI scans (e.g. 30 minutes for Case 3). If HARDI data acquisition parameters are not optimized because of limitations on the duration of scan time, it is possible that small fiber bundles with complex branching patterns may evade detection by HARDI tractography, thereby producing false negative connectivity results. For example, while the VTTR pathway to the paraventricular region of the thalamus was identified by HARDI tractography in all 3 cases in this study, the complex trajectory of this pathway was more clearly delineated in Case 1 than in Cases 2 and 3, likely because of higher spatial resolution of the HARDI data (i.e. smaller voxel size) in the former. Efforts are ongoing to shorten the duration of HARDI data acquisition, improve spatial and angular resolution, and thereby facilitate clinical implementation (57). Yet, even with expected improvements in HARDI data acquisition and post-processing, HARDI structural connectivity data should be interpreted with caution and should not be considered as proof of functional synaptic connectivity.
Another methodological consideration is that our post-processing efforts to increase the specificity of ARAS tract identification likely minimized, but did not completely eliminate, the possibility that HARDI tractography could generate spurious tracts, i.e. it may display a connection between 2 fiber bundles that travel through or end within the same voxel but that do not in fact connect (58). False positive connectivity errors that may occur in HARDI tractography experiments may be analogous to leakage of an injected label across neuronal membranes into adjacent, non-relevant cells in histological tract tracing studies (21). This methodological uncertainty is a particular concern when studying the brainstem components of the ARAS, which arguably contain the greatest concentration of complex crossing fibers of any brain region.
Despite these limitations, HARDI tractography has the ability to generate connectivity maps of complex neural networks in the postmortem human brain more effectively than currently available histological labeling techniques, which are unable to identify long white matter tracts in adults (21). In addition, a significant advantage of HARDI tractography is that it is a non-invasive technique that can be used to investigate white matter connectivity in vivo and ex vivo. Indeed, in vivo tractography data from HARDI and diffusion spectrum imaging studies have been correlated with known neuroanatomic pathways in humans (24, 59), and ex vivo tractography data from these techniques have been correlated with known neuroanatomic pathways in monkeys (24, 60), as well as with histological data in cats (61) and monkeys (60). Furthermore, the feasibility of applying HARDI tractography to postmortem neuropathologic analyses is supported by evidence that the fixation of brain specimens does not alter HARDI data, even when the imaging is performed more than 3 years after death. In a recent diffusion imaging study of 11 human brain specimens that were fixed at an average of 46.2 hours (range 21–69 hours) and imaged at an average of 25.2 months (range 2–40 months) postmortem, the tractography results were consistent with those obtained from in vivo human connectivity studies (43). Although quantitative water diffusion measurements within white matter tracts may be partially dependent on the time to fixation and the time to image acquisition, there was no evidence that these alterations affected the reliability of the postmortem tractography results (43). Importantly, in this study Case 1 was imaged 103 days after death and Case 2 was imaged 8 months and 16 days after death. Thus, imaging of both postmortem brain specimens was performed well within the time window established by Miller et al (2011).
The major finding of our study is that HARDI tractography revealed a bilateral fiber bundle connecting the cuneiform/subcuneiform nucleus in the rostral midbrain to the thalamus, hypothalamus, and basal forebrain, providing a structural basis in the human brain for the physiologic ascending arousal pathway discovered by Moruzzi and Magoun in cats (8). The originating source of this fiber bundle also included the pontis oralis of the rostral pons, consistent with its role in the ARAS based on clinicopathologic studies (6, 7). In the rostral midbrain, the bilateral fiber bundle originating from the mesencephalic and pontine reticular formation, i.e. the reticular core of the classical ARAS, bifurcates into the VTT and DTT, names with historical precedent in experimental animals (46–48). In animal studies, the ventral bundle is mainly a hypothalamic pathway, with divergent projections also to the thalamic reticular nucleus, zona incerta, and Forel’s fields (47, 48). The human VTT, however, bifurcates yet again into 2 additional fiber bundles, one labeled the VTTC, which is a distinct caudal pathway connecting with the hypothalamus, zona incerta, Forel’s fields, basal forebrain and globus pallidus, and the other labeled the VTTR, which is a rostral pathway unexpectedly connecting with the paraventricular (midline) region of the thalamus.
The DTT has been shown in animals to project principally to the thalamic intralaminar and paraventricular nuclei, but not the reticular nucleus of the thalamus (47). In humans, however, we found that the DTT bifurcated into 2 additional fiber bundles that each projected to a different distribution of thalamic nuclei. One subdivision, which we labeled the DTT lateral (DTTL), projected laterally to the thalamic reticular nucleus and, to a lesser extent, the basal forebrain, and the pulvinar and lateral geniculate nucleus in the thalamus. The second subdivision of the DTT, which we labeled DTT medial (DTTM), projected medially to thalamic intralaminar nuclei (central lateral nucleus and centromedian/parafascicular nuclear complex). In addition, several DTTM fibers projected beyond the intralaminar nuclei along a rostral and lateral course to the reticular nucleus.
Thus, the newly defined human VTTR, VTTC, DTTL, and DTTM pathways are distinct in their trajectory, connectivity, and source nuclei origins from the VTT and DTT pathways described in animals with tract tracing methods (46–48). We implicate the DTT and VTT pathways in the mediation of arousal because they connect with thalamic, hypothalamic, and basal forebrain end-points well established to be crucial to this function. Our structural connectivity findings therefore have significant implications for future functional studies of human arousal, sleep-wake cycling, and conscious awareness. Similar to animal studies, this human ARAS analysis suggests a chain of connectivity whereby brainstem source nuclei in the upper pons and midbrain project to the intralaminar nuclei in the thalamus, which in turn project diffusely to the cerebral cortex to activate it (52), thereby enabling cognitive processing. In the human brain, we postulate that the DTTM pathway to the intralaminar nuclei is the main conduit for direct ARAS activation of thalamocortical networks (62). The human DTTL pathway, on the other hand, connects to the thalamic reticular nucleus, which is known to inhibit excitatory input to the cortex via connections with the intralaminar nuclei and which produces the synchronized 7 to 14 Hz oscillations on cortical EEG during the initial stage of sleep (17). Our tractography findings thus suggest a structural basis for the human ARAS to modulate arousal by both direct activation of thalamocortical networks (via DTTM) and by regulation of intrathalamic inhibitory networks (via DTTL).
In this study, the finding that the known neurotransmitter-specific components of the ARAS connect in different patterns with the thalamus, hypothalamus, and basal forebrain underscores the concept that these components underlie different behavioral and/or EEG aspects of the human arousal system. Indeed, each neurotransmitter-specific pathway is believed to become active in anticipation of arousal from sleep, yet with distinct electrophysiological activation patterns (17). The extensive connectivity between known brainstem monoaminergic-, cholinergic-, and glutamatergic-related nuclei and the anterior hypothalamus, which modulates circadian sleep-wake cycles (16), is consistent with animal data (63) and provides support for current hypotheses that cyclical behavioral states are mediated by reciprocal interactions between interconnected neurotransmitter networks (64). Furthermore, we provide a potential neuroanatomic basis in the human brain for visual imagery in the dream state, as the pathway connecting the pedunculopontine nucleus to the lateral geniculate nucleus (essential to visual processing) is consistent with evidence for cholinergic activation of REM sleep (65).
A potential limitation of HARDI tractography in mapping the connectivity of the human ARAS is related to the observation that our ex vivo connectivity analyses in Case 1 did not identify a wide set of projections to the thalamus from serotonergic- and noradrenergic-related source nuclei. These projections have been suggested by in vivo human neuroimaging studies with serotonergic and noradrenergic ligands (66, 67), and by postmortem neurochemical studies of the thalamus in animals and humans (68–71). We did, however, identify extensive locus coeruleus and dorsal raphe connectivity with the thalamus (particularly with the reticular and centromedian/parafascicular nuclei) in Case 2 (ex vivo) and Case 3 (in vivo), suggesting that HARDI tractography can indeed identify these important noradrenergic and serotonergic pathways in postmortem brain specimens and living subjects.
There are several potential explanations for these locus coeruleus and dorsal raphe connectivity findings, which were unexpected because the spatial resolution in Case 1 was higher than in Cases 2 and 3, and since the angular resolution was similar in Cases 1 and 2. First, HARDI tractography may currently have low sensitivity for identifying tracts with multidirectional branching patterns (72), small axonal diameters (11), and lack of myelination (11)–all known characteristics of the rostral serotonergic and noradrenergic axonal projections. Second, the formaldehyde fixative may interfere with MRI water diffusion measurements along poorly myelinated fiber tracts, although it is unclear why this potential fixative effect would impact the locus coeruleus and dorsal raphe tractography results in Case 1 more than in Case 2 since there was a shorter postmortem interval before imaging in Case 1. Third, while the b values used for ex vivo analysis in Case 1 and in vivo analysis in Case 3 were similar (4057 s/mm2 and 4000 s/mm2, respectively), it is possible that at a given b value, the effective diffusion contrast may be greater for in vivo experimental conditions than for ex vivo experimental conditions because global brain water diffusivity is invariably lower in fixed postmortem tissue. In other words, it may be necessary to use even higher b values (i.e. > 4057 s/mm2) in studies of fixed brain tissue to reach the level of diffusion contrast that can reliably identify the poorly myelinated locus coeruleus and dorsal raphe fiber tracts. Additional studies are therefore needed to determine the optimal HARDI data acquisition parameters (voxel size, number of diffusion gradients, and b value) for identification of each ARAS pathway ex vivo and in vivo. Furthermore, validation of neuroanatomic connectivity models generated by HARDI tractography in ex vivo and in vivo studies ultimately depends upon correlation with anatomic tract tracing studies—either those already available in the literature (47, 60, 73) or, alternatively, in prospective experimental studies designed to confirm unexpected connections. In this regard, the novel ARAS connections that we report here warrant follow-up in neuroanatomic studies in human tissues and/or animal models.
The intrathalamic connectivity findings in this study provide a neuroanatomic basis for thalamic modulation, or gating, of the inputs of the ascending arousal system to the cerebral cortex (17, 52). Although we cannot exclude the possibility that some fiber tracts passing between the intralaminar nuclei and the reticular nuclei are thalamocortical projections passing through but not to the reticular nuclei, our finding that the reticular nucleus connects with both the central lateral nucleus and the centromedian/parafascicular nuclear complex is consistent with electrophysiological studies in animals demonstrating specialization of thalamic intralaminar nuclei and the existence of disynaptic intrathalamic pathways mediated by the reticular nucleus (74). Our observation that both the reticular nucleus of the thalamus and the brainstem nuclei of the ARAS connect with Forel’s fields and zona incerta suggests an expanded role for these subthalamic regions as nodes in the neuroanatomic network mediating human arousal, consistent with animal studies (75). Future studies in humans examining ARAS modulation of the activity of the thalamic reticular nucleus may therefore consider the 3 distinct neuroanatomic pathways defined here: 1) the DTTL; 2) the intrathalamic extension of the DTTM; and 3) a potential monosynaptic pathway from the brainstem to Forel’s fields and zona incerta to the reticular nucleus.
In conclusion, the ARAS connectivity results in this study suggest that HARDI tractography has the potential to facilitate the study of the human ascending arousal system in its many physiological manifestations, e.g. sleep-wake cycling and anesthesia (76), as well as its pathological conditions such as sleep disorders and coma (6, 7, 77). The multiplicity and redundancy of the ascending arousal system suggest an adaptive mechanism for the recovery of consciousness when one component, but not the full system, is clinically disrupted (6). It remains to be determined which or how many of the multiple components of the ARAS are sufficient for arousal, and hence consciousness, in humans. The examination of HARDI data from multiple patients with different types of ARAS lesions and with different levels of consciousness may ultimately provide us with the answers to such provocative questions as which and how many connections are essential for human cognition. The precise identification of focal disruptions in arousal networks in the brainstem, hypothalamus, thalamus, and basal forebrain of patients with disorders of consciousness may also enable clinicians to target individually tailored pharmacologic (78, 79) and electrophysiologic (e.g. deep brain stimulation (80)), therapies to specific neuroanatomic sites of injury. In addition to its many clinical applications, HARDI tractography can be used in neuropathologic studies to investigate the structural basis for developmental differences in consciousness among the newborn, infant, child, adolescent, and adult, as well as the neuroanatomic basis of coma, vegetative, and minimally conscious states in pediatric and adult patients. We envision that postmortem tractography will be a future adjunct to neuropathologic studies of patients with disorders of consciousness. Specific sites of disruption of ARAS pathways that are not appreciated on gross macroscopic analysis may be identified with postmortem HARDI tractography, and these imaging data may then be used to guide microscopic sectioning, thereby ensuring precise clinicopathologic correlations. The exquisite neuroanatomic delineation of the ARAS by HARDI tractography thus suggests that this advanced imaging technique has the potential to significantly advance the study of the physiology and pathology of human consciousness.
The authors are grateful to Dr. Martin A. Samuels for his ongoing support of this work. We also thank Ms. Marian Slaney, Ms. Michelle Siciliano, Ms. Elisha Johnson and Ms. Allison Stevens for expert technical processing of the postmortem brain specimens, Dr. Andre van der Kouwe for assistance with acquisition of in vivo HARDI data, and Dr. Jennifer A. McNab for helpful consultation regarding signal properties of the diffusion-weighted steady-state free-precession imaging sequence.
This work was supported by grants from the National Institutes of Health (R25 NS065743 [BLE], R01 HD20991 [HCK], and P41 RR14075 [Athinoula A. Martinos Center for Biomedical Imaging]), and by the Neuropathology Division, Department of Pathology, Brigham and Women’s Hospital, Boston, MA.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.