Functional Connectivity of the Human Red Nucleus in the Brain Resting State at 3T

Materials and Methods

Statistical Analysis

Preprocessing.

Functional images were preprocessed and analyzed with use of Statistical Parametric Analysis (SPM5) (http://www.fil.ion.ucl.uk/spm). Data were successively format-converted, motion-corrected, corrected for errors in section-timing, spatially smoothed with a 6-mm full width at half maximum of Gaussian kernel, and coregistered with use of the template brain of the Montreal Neurologic Institute proportional spatial scaling.

ROIs.

The red nuclei and SN appear as a strong hypointense signal intensity on T2-weighted images in the mesencephalon so that their borders are easily identifiable (Fig 1). For all subjects and all nuclei, the ROIs were manually drawn (by the same experimenter) to precisely delineate each nucleus (on both sides) on axial T2*-weighted images with use of FSLview (tool of the FMRIB Software Library [FSL. Version 4; Oxford Centre of Functional MR imaging of the Brain, UK; http://www.fmrib.ox.ac.uk/fsl]). For each subject, it was verified that no overlapping existed between red nuclear and nigral ROIs. The ROIs were then format-converted from NIFTI to .mat files with use of the MARSBAR option of SPM5 to carry out functional connectivity analysis.

• Download figure
• Open in new tab
• Download powerpoint

Fig 1.

Axial T2*-weighted images through the mesencephalon showing the RN and SN on the right and left sides, with a strong signal hypointensity.

Functional connectivity analysis.

These 2 ROIs were used for separate fcMRI analyses. For each subject, the mean time-series from the task-free scans were extracted from the ROI by averaging the time-series of all voxels in the ROI. To minimize the effect of global drift, we scaled the voxel intensities by dividing the value of each time point by the mean value of the whole-brain image at that point. The resulting time-series was then used as a covariate of interest in a whole-brain, linear regression, statistical parametric analysis. Contrast images corresponding to the ROI time-series regressor were entered into a second-level, random-effects analysis (height and extent thresholds: P < .01 and k = 50, for significant clusters, corrected at the whole brain) to determine the brain areas that showed functional connectivity across subjects.

Results

Red nuclei.

For each nucleus, clusters were observed bilaterally, as shown in Fig 2 and Table 1: prefrontal cortex (BA, 11/45/47), occipital cortex (BA 17/37), posterior hippocampus (BA 35), caudal insula (BA 13), claustrum, ventrolateral and posterior thalamus, posteroinferior pallidum with a possible extension within the contiguous putamen, hypothalamus, contralateral RN, and mesencephalic tegmentum. Clusters were also found in the right and left precuneus (BA 7) for the right RN, anterosuperior temporal gyrus (BA 20), and dorsolateral prefrontal cortex (BA 9) for the left RN, and the right cerebellum (hemisphere of lobule V) for both red nuclei. The rubral cluster may extend within the SN.

• Download figure
• Open in new tab
• Download powerpoint

Fig 2.

Resting-state neural connectivity maps (n = 14; P < .01; and k = 50) showing regions positively correlated with the right RN (A-C) and also found with the left RN. A, Axial sections. B, Sagittal section. C, Coronal sections. D, Sagittal section showing temporal region correlated with the left RN. D, T-score is represented by a color gradient (vertical colored bar). ACC, anterior cingulate cortex; CL, claustrum; CER, cerebellum; FOP, fronto-opercular cortex; HIPP, hippocampus; HYP, hypothalamus; INS, insula; LN, lentiform nucleus (pallidum and putamen); MES, mesencephalon; PFC, prefrontal cortex; RN, red nucleus; SN, substantia nigra; ST, striatum; THAL, thalamus; TC, temporal cortex; TM, tegmentum of the mesencephalon; m, medial; OFC, orbito-frontal cortex; HV, hemisphere of lobule V; OCC, occipital cortex.

View this table:

• View inline
• View popup

Table 1:

Cluster localizations of the red nuclei

Substantia nigra.

For each nucleus, clusters were observed bilaterally, as shown in Fig 3 and Table 2: prefrontal cortex (BA 11/47), premotor and motor cortices (BA 4/6), posterior hippocampus (BA 35), rostral insula (BA 13), claustrum, striatum including the caudate and lentiform nuclei, anteroventral thalamus, hypothalamus, and mesencephalic tegmentum. The prefrontal clusters were more widespread for the right nucleus (BA 8/9/46); clusters were also found in the right temporal (BA 21) and occipital cortices (BA 19/39), right and left anterior (para-) cingulate cortex (BA 24/32), and right pons. For the left nucleus, clusters were also located in the cerebellar vermis (lobules V-VI).

• Download figure
• Open in new tab
• Download powerpoint

Fig 3.

Resting-state neural connectivity maps (n = 14; P < .01; and k = 50) showing regions positively correlated with the left SN (most of them are also found with the right SN; Table 2). A, Axial sections. B, Coronal sections. C, Sagittal sections. T-score is represented by a color gradient (vertical colored bar).

View this table:

• View inline
• View popup

Table 2:

Cluster localizations of the substantia nigra group-analysis P < .01, k = 50 MNI coordinates (mm)

Discussion

Our study of fcMRI confirms, clarifies, and extends our previous structural results concerning the corticorubral network11,12 showing that, during the brain resting state: 1) the human RN participates in a widespread functional network including associative prefrontal, parietal, occipital, and temporal areas, and limbic areas such as the ventral lentiform nucleus, hypothalamus, and mesencephalic tegmentum; 2) this network does not include motor areas and was not recruited by overt motor performance; and 3) this network can be dissociated from a nigro-centered striatal network despite the anatomic proximity between the RN and SN.

First, the present data agree with previous analyses of human clinical cases reporting possible projections from associative cortices to the RN including the frontal and prefrontal cortices (BA 4/6/8/9/10/45/46/47),14–16 insula (BA 13), and temporal and parietal cortices.14 However, we found more limited prefrontal clusters (BA 11/45/46/47), and clusters were also observed in the hippocampus, claustrum, and primary and associative occipital cortices (BA17/3/37). No direct connections between the RN and these brain regions have been previously described. Furthermore, no correlations were detected between the RN and the premotor and sensorimotor cortices, though strong connections between these structures are observed in monkeys and humans.11,12 To reconcile all these results, we can test the hypothesis that part of our data reflect sources or targets of direct rubral afferents or efferents, especially those for which tractography revealed anatomic relationships,11,12 whereas the other part consists of areas encompassed in the functional network centered on the RN, though as-yet-unknown anatomic connections cannot be ruled out. This must be the case for the thalamus, as no rubrothalamic projections exist in the monkey.31 Absence of “activation” of the premotor and sensorimotor cortices could therefore be ascribed to their absence of recruitment and to the correlative reallocation of the functional connectivity to areas more specifically engaged in the brain resting state.

Although it appears difficult to precisely define the role of the RN in this study, 2 points must be emphasized. The RN is exclusively functionally associated with cortical areas devoted to cognitive function such as vision or mental imagery (occipital cortex); emotion (cortex orbitofrontal BA 11 and insula); episodic memory (hippocampus BA 35 and precuneus); working memory, episodic and semantic memory, and reasoning (prefrontal cortex BA 45/46/47); consciousness; mental imagery; and agency (precuneus and insula).30,32,33 These cortical areas participate in at least 2 well-known networks specific for the brain resting state: the salience network (orbitofrontal, fronto-opercular, and insular cortices)34 and the default-mode network (precuneus and hippocampus).35,36 It can be speculated that these associative regions may exert a modulatory action on the olivocerebellar system via the RN, which massively projects to the principal olivary nucleus via the central tegmental tract. It is also tempting to ascribe the cognitive impairments (short- and long-term memory, verbal fluency, intellectual fatigability)18 observed in patients with rubral lesions to alterations of the cerebello-rubro-olivo-cerebellar loop and, in particular, to the lack of modulatory effect of the rubral afferents on the cognitive and affective cerebellum. In a very unexpected turn, only the right cerebellar anterior lobe (HV) exhibited correlated fluctuations with the right and left red nuclei. A threshold problem may account for this observation as well as the fact that in some volunteers: 1) the dentate nucleus and the very posterior cerebellar lobe were not covered by the sections, and 2) image distortions in the caudal pons and posterior cerebellum from aeration of the sphenoid sinus were present. The anterior cerebellar lobe received inputs from the mediocaudal basilar pontine nucleus,37 which is interconnected with the hypothalamus and limbic and autonomic cortical areas.38 This cerebellar region may therefore represent one of the targets of the rubro-olivary system mobilized in the brain resting state and may participate in a limbic/autonomic loop anchored in the RN. It is noteworthy that the inferior olive and cerebellum (HV), and apparently the rubral area, are specifically recruited while encoding temporal information of “unexpected” sensory events.39 In our study, the RN could constitute a relay for salience detection of affective/autonomic information.

Second, functional connectivity was also found between the RN and subcortical loci (hypothalamus, SN, mesencephalic tegmentum). These results are in keeping with previous data obtained in monkeys40 and humans,41 showing connections between the RN and midbrain areas such as the mesencephalic reticular formation, periaqueductal gray matter, superior colliculus, SN, and hypothalamus. It is noteworthy that these structures also belong to the salience network34 involved in emotional salience processing. Moreover, functional imaging24 has demonstrated activation in the RN, SN, and periaqueductal gray matter during pain processing, especially the emotive salience of visceral pain. Therefore, the red nuclear activity must be influenced by cortical and subcortical emotional information and may then modulate the cognitive and affective cerebellum17,38 via the bulbar olivary nucleus or directly via, at least, the interposed nucleus.41 Correlated BOLD fluctuations within the contralateral RN were also found for each RN and mostly in the bilateral homologous cortical and subcortical regions. This bilaterality can be explained by 1) rubro-rubral fibers passing through the posterior commissure41 and 2) possible bilateral cortical and subcortical projections, as demonstrated in monkeys for the supplementary motor area.42

Third, the rubral network could also have reflected 1) the whole cerebellar system, as its main input originates in the dentate nucleus; and 2) the striatal system as, because of partial volume effects, the ROI may have included part of the SN and as GABAergic43 nigrorubral projections29 have been described in animals. Allen et al44 seeded the dentate nuclei to carry out functional connectivity of the cerebellar system. They found a widespread neural network comprising the prefrontal, temporal, parietal, and occipital cortices; hippocampus; thalamus; hypothalamus; caudate and lentiform nuclei; and cerebellum, but did not report any cluster within the RN. Our rubral circuit may therefore constitute, at rest, a distinct cerebellar subsystem with more limited, though partly overlapping, neural nodes compared with the functional network anchored in the dentate nucleus. This observation reinforces the hypothesis that this rubral circuit may subserve a more focused activity such as detection of salience.

The functional connectivity of the SN also showed a widespread network markedly different from the rubral network, especially with frontal, prefrontal, and orbitofrontal (BA 4/8/9/25), cingulate,24 and temporal (BA 21) cortices, striatal and anterior vermian relays not present in the rubral circuit. Moreover, our results concerning SN are in agreement with previous data obtained in animals.30,45–48 The pars reticulata of SN (prSN) participates in a direct cortico-striato-nigro-thalamo-cortical circuit and an indirect cortico-striato-subthalamo-nigro-thalamo-cortical circuit.30 These circuits are subdivided into motor, limbic, and associative parallel closed loops according to their cortical origins (motor, cingulate and hippocampal, and prefrontal areas, respectively).49 The pcSN also sends fibers to the superior colliculi and the pedunculopontine tegmental nucleus. The pars compacta of SN (pcSN) participates in a striato-nigro-striatal circuit. More precisely, prSN is connected with the motor cortex, temporal cortex (TE), prefrontal eye field (BA 8), and prefrontal cortex (BA 9/12/46) in monkeys.47,48 Our in vivo human study confirms these previous observations and shows that these circuits are clearly identifiable during the brain resting state, though it is difficult to clearly distinguish direct and indirect circuits. However, we found a more extensive prefrontal (BA 11/47) “activation” and associative occipital (BA 19/39) and orbitofrontal (BA 25) “activations” not previously reported, as well as vermian recruitment (lobuli V-VI). This subregion of the cerebellum receives hypothalamic, tectal, and perihypoglossal nuclei30 (visual attention and saccadic movements). The basal ganglia are involved in supervised, rule- and reward-based learning of motor and cognitive habits and also subserve visuospatial and executive functions,50 so that they could coordinate other cortical networks, such as executive defaults and salience networks,34,35 activated during the brain resting state. Finally, although nigrorubral connections exist, the rubral and nigral networks remain functionally independent during the brain resting state. At least 2 hypotheses can be proposed: either the inhibitory nigro-rubral projections contribute to decouple rubral and nigral functioning, or the part of the SN linked with the RN is different from the part of the SN included in the striatal loops.

Fourth, some technical points and limitations must be emphasized. We used a TR of 2500 ms, which can cause aliasing because of respiratory- and cardiac-related fluctuations. Moreover, the statistical threshold for significant clusters was fixed at less than 0.01, though it is usually fixed at less than 0.001, increasing the risk for false-positive results. Finally, given the section thickness and the small size of the RN and SN, the partial volume in the selected ROIs may have contributed to errors. Therefore, functional connectivity data must be interpreted with caution. However, as aforementioned, our results were coherent with known anatomy and physiology. Furthermore, the main partial volume error may have concerned the rubral and nigral nuclei, but we showed that the RN-centered and SN-centered networks were clearly distinct. Of course, it cannot be ruled out that small parts of adjacent subcortical structures such as the zona incerta, reticular formation, subthalamic nucleus, and thalamus could have been included in the ROIs. One possibility to address these problems and to verify our results would be to complement our study by a model-free, independent component analysis.27 This method is well suited to discriminate sources of noise, such as physiologic aliasing, and to identify statistically independent neural networks. Moreover, an unbiased template-matching procedure could be applied to the individual independent component analysis maps, including the RN and SN, to identify previously described intrinsically connected brain networks such as salience and executive control networks.34

Conclusions

To our knowledge, this is the first functional connectivity study devoted to the RN and, incidentally, to the SN in humans. During the brain resting state, the RN displays strong functional coherence with associative prefrontal, insular, temporal, and parietal cortices; the thalamus; and the hypothalamus, but not with the sensorimotor cortex. These results support a cognitive role of the RN, probably related to salience detection and executive control. This rubral circuit, which seems to constitute a modular cerebellar subsystem, clearly differs from the striatal loops passing through the very close and anatomically associated SN. Our study also confirms previous results for the SN obtained in monkeys, reporting corticonigral connections with the prefrontal, temporal, and occipital cortices. Finally, our study demonstrates that this fcMRI technique can be successfully applied to small subcortical structures. However, further investigation is warranted to fully elucidate the specific clinical significance of the rubral and nigral networks that have been demonstrated in this preliminary and exploratory study.