The investigation of resting-state functional connectivity of pulvinar in old age individuals and Parkinson’s patients

doi:10.21203/rs.3.rs-1780551/v1

The pulvinar is largest thalamic nucleus and has been subdivided into anterior pulvinar (PuA), inferior pulvinar (PuI), medial pulvinar (PuM) and, lateral pulvinar (PuL). Although the function of pulvinar is well known, its role in neurodegenerative diseases is still unclear. We aimed to examine the functional connectivity of PuA, PuI, PuM and, PuL in healthy controls (HC) and patients with Parkinson’s disease (PD). Resting-state fMRI and T1 weighted images of 15 healthy control (HC), and 12 PD patients were used in this study. SPM12 and CONN software were used to preprocessing the imaging data using published pipelines. Seed based resting-state fMRI analyses were carried out to compare the functional connectivity changes between groups. Besides, voxel-based morphometry (VBM) analysis was performed to compare gray matter volume differences between two groups. The bilateral PuI, PuL and PuM exhibited a decreased functional connectivity in the PD group compared to the HC group in the bilateral thalamus, posterior cingulate cortex, cerebellum, and brainstem. Moreover, pulvinar nuclei in each hemisphere had significantly smaller volume in the patients with PD compared to HC. This study highlights that the patients with PD have a smaller volume in pulvinar nuclei in each hemisphere compared to HC. The pulvinar showed less connectivity in the PD group compared to the HC, the diminished connectivity may be associated with hallucination, executive function, and working memory dysfunctions in PD.

Health sciences/Neurology/Neurological disorders/Parkinson's disease

Biological sciences/Neuroscience

Pulvinar

thalamus

Parkinson’s disease

resting-state fMRI

volumetric analyses

The pulvinar nucleus, which is the largest nucleus of the thalamus, constitutes approximately 30% of thalamic volume. It is cytoarchitectonically subdivided into anterior pulvinar (PuA), inferior pulvinar (PuI), medial pulvinar (PuM) and, lateral pulvinar (PuL)¹,².

The pulvinar is a higher order nucleus that receives most of its inputs from the cortex and sends efferent to the cortex ³. The extensive and reciprocal connectivity of the pulvinar with cortical areas including the frontal, parietal, temporal, occipital, and cingulate cortex hints at its contributions to advanced cognitive ⁴,⁵ emotional ⁶,⁷ and somatosensory ³ capabilities. The PuA is the least studied subdivision of the pulvinar in humans and has mainly somatosensory functions ⁸. On the other hand, the PuM is the largest part among the pulvinar’s subdivisions. Considering the reciprocal connectivity of PuM with the posterior parietal, inferior temporal, cingulate, restrosplenial and prefrontal cortical area, it has been associated with directed attention, executive functions, working memory ⁹, as well as visuomotor, auditory, somatosensory and other higher cognitive processing ⁴. The PuI and PuL have been interconnected with visual cortical areas, extending from the occipital lobe to the temporal and parietal lobes, thus they have commonly known as ‘visual pulvinar’¹⁰. Kaas and Lyon presented a set of evidence that the PuI could serve as a subcortical component of the dorsal stream, while the PuL was devoted to the ventral stream of cortical processing ¹¹.

It has been documented that non-motor ^8,12 and motor symptoms ^13–15 may be seen in the pulvinar dysfunctions and lesions. The role of pulvinar pathology has been investigated in a range of neurodegenerative disorders. In this respect, several studies have suggested the critical role of pulvinar both in Lewy Body dementia and Alzheimer’s disease ¹⁶,¹⁷. The pulvinar abnormalities have been related to the cognitive declines in Parkinson’s disease (PD). Matsuro et al. reported that the hypointensity in the pulvinar was suggested to the cognitive worsening and existence of hallucinations in patients with PD after deep brain stimulation surgery ¹⁸.

Although there have been numerous studies implicating the pulvinar in attention states and functional connectivity of it in healthy populations, it remains less clear the functional connectivity of pulvinar in PD. Hence, the present study aims to investigate the resting state functional connectivity of PuA, PuI, PuL, and PuM in elderly individuals and patients with PD. The PuA is considered with somatosensory connections ¹⁹, whereas the PuM could contribute to executive and higher cognitive functions through its connection with prefrontal and cingulate cortices ^4,9. Moreover, the PuI and PuL have been known as a component of the visual attention networks with connection occipital and temporal regions ¹¹. Attention deficits, motor symptoms and executive dysfunctions characterized by planning, and decision-making can be damaged in the PD ²⁰²¹. The unclear association between PuA, PuI, PuL, PuM and neurodegenerative diseases prompted us to the hypothesis that functional connectivity of the PuA, PuI, PuL, and PuM would be altered in the PD patients.

As shown in Table 1, PD and HC patients did differ in age, and MMSE scores. PD group had significant higher ages and lower cognitive performance according to the scores in the MMSE compared to HC group (p <0.001). In order to show the possible effects of the age difference and MMSE scores between groups, the demeaned age and MMSE scores were included as covariate in the functional connectivity analysis that suggested special role of pulvinar in PD patients.

Within Group Functional Connectivity

The resting state seed based functional connectivity of the HC and PD groups were computed separately and shown in table 2 and 3 for all seeds. As revealed in tables, all seeds were connected to both cortical and subcortical gray matter structures in the HC group. Furthermore, all seeds had the greatest cluster size with the thalamus in both groups. We also observed that the left and right PuM had the most extensive connectivity among all seeds in the HC group (Table 2-3). In addition, the PD group showed connectivity with fewer brain regions than the HC group (Fig. 1-2).

In the HC group, the right pulvinar seeds showed connectivity to the thalamus, hippocampus, brainstem, cerebellum, and cortical areas, including parietal, temporal, occipital, frontal, insular, cingulate. The left pulvinar seeds showed connectivity to the thalamus, hippocampus, amygdala, cerebellum, and cortical areas, including parietal, temporal, occipital, frontal, cingulate (Table 2-3). The functional connectivity of pulvinar seeds in the PD group were found between the right pulvinar and thalamus, hippocampus, brainstem, cerebellum, cingulate cortex; left pulvinar and thalamus, hippocampus, brainstem, and temporal cortex (Table 2-3).

Between Groups Functional Connectivity

Although there was a significant difference in age between the HC and PD groups (p<0.001), no significant effect of age was found between the two groups for functional connectivity. However, there was a significant effect of MMSE score in connectivity between two groups (Table 4). The analysis revealed the MMSE score related changes in connectivity of the pulvinar subdivisions. In particular, the stronger connectivity was observed in left PuI with bilateral thalamus, PCC, left hippocampus, brainstem; left PuL with the left thalamus; left PuM with bilateral thalamus; right PuI with bilateral thalamus, left hippocampus and brainstem; right PuL with right thalamus; right PuM with bilateral thalamus in HC group than in PD group.

Volumes of the pulvinar nuclei and thalamus

As a quality check, we carried out VBM analysis to segment the anatomical images into the gray matter, white matter, and cerebrospinal fluid. VBM analysis revealed that there were significant differences in the volumes of pulvinar nuclei between HC and patients with PD. Relative to the HC, volume reductions in the PD group were observed in the pulvinar nuclei (p<0.000), as expected. Moreover, we found that right and left thalamus volumes were significantly increased (p<0.000, p=0.003) in HC group compared with the patients. The mean volumes of the pulvinar nuclei and thalamus are shown in Table 5.

Table 1

The demographic features and MMSE scores of participants.

	HC	PD	p*
N	15	12	NS
Age	60.26±9.37	75.75±10.07	0.001
Sex (male/female)	6 / 9	8 /4	NS
MMSE	27.6 ± 1.80	19.08±4.16	0.000

Data presented as mean ± SD. p*<0.001 NS: not significant

Table 2

Clusters of within-group functional connectivity for the right hemisphere seeds.

Region	Peak MNI coordinates (x, y, z)	Size	Size- pFWE	t-Max	Region	Peak MNI coordinates (x, y, z)	Size	Size- pFWE	t-Max
Healthy Control					Parkinson Disease’s
R-PuA
L-R thalamus, R- insular cortex	10 -20 10	1673	0.000000	15.81	L- R thalamus	12 -22 10	626	0.000000	15.09
ACC	08 20 32	205	0.000787	7.28	R- planum temporale	62 -26 12	149	0.002019	8.13
R-PuI
R-L thalamus, L-R hippocampus, PCC	16 -28 00	1136	0.000000	14.93	L-R thalamus, brainstem L-R hippocampus	16 -30 00	1098	0.000000	13.83
Precuneus cortex	02 -64 24	524	0.000000	5.60
L- MFG	-30 36 24	183	0.001604	-7.50
R-PuL
L-R thalamus	12 -22 14	1315	0.000000	11.15	L-R thalamus	12 -22 14	583	0.000000	16.04
Precuneus cortex	-02 -42 50	246	0.000356	7.51
R-PuM
L-R thalamus, PCC	10 -26 08	3719	0.000000	17.65	L-R thalamus	14 -30 10	1559	0.000000	17.60
Brainstem	12 -16 -26	830	0.000000	9.55	R-fusiform cortex, R-ITG	34 -16 -28	187	0.001904	7.60
R- SMG	54 -34 28	459	0.000001	-9.01
L- insular cortex	-36 -04-12	458	0.000001	-9.68
L-R ICC, L-R lingual gyrus	06 -64 08	395	0.000003	-7.30
R- L IFG, R-L PreCG	42 04 18	340	0.000015	-7.72
L-R cerebellum	06 -50 -46	312	0.000033	8.37
R- hippocampus, R- fusiform cortex	36 -14 -24	280	0.000087	9.00
Cingulate cortex	-02 -12 38	200	0.001145	6.58
L- MFG	-46 02 46	187	0.001793	-6.27
R- PostCG	08 -28 72	170	0.003275	8.93
R- SPL, R- angular gyrus	42 -48 54	158	0.005070	-6.07

Abbreviations: L, left; R, right; ACC, anterior cingulate cortex; ICC, intracalcarine cortex; IFG, inferior frontal gyrus; ITG, inferior temporal gyrus; MFG, middle frontal gyrus; PCC, posterior cingulate cortex; PreCG, precentral gyrus; PostCG, postcentral gyrus; SMG, supramarginal gyrus; SPL, superior parietal lobule

Table 3

Clusters of within-group functional connectivity for the left hemisphere seeds.

Region	Peak MNI coordinates (x, y, z)	Size	Size- pFWE	t-Max	Region	Peak MNI coordinates (x, y, z)	Size	Size- pFWE	t-Max
Healthy Control					Parkinson Disease’s
L-PuA
L-R thalamus	-12 -22 08	1189	0.000000	13.07	L-R thalamus	-12 -22 12	803	0.000000	14.92
L-fusiform cortex, L-ITG, L-PPHG	-34 -32-16	255	0.000211	7.27
PCC, precuneus	02 -54 10	250	0.000247	6.68
L-PuI
L-R thalamus, L-R hippocampus	-18 -30 00	1686	0.000000	17.44	L-R thalamus, L-R hippocampus, PCC, brainstem, L-cerebellum	-18 -30 02	1547	0.000000	11.95
L- ITG, L- fusiform cortex	-46 -48-22	139	0.007013	6.86
L-PuL
L-R thalamus	-12 -22 14	1369	0.000000	13.95	L-R thalamus	-14 -24 14	665	0.000000	14.26
Precuneus cortex, L-R LOC, L- SPL	14 -76 50	571	0.000000	8.66
FMC	-46 44 -16	455	0.000000	-9.71
R- amygdala,	14 02 -16	150	0.004708	-6.84
L-PuM
L-R thalamus, PCC	-12 -30 06	3063	0.000000	18.23	L-R thalamus	-14 -30 06	1712	0.000000	17.53
ACC, R-PreCG, R-L paracingulate gyrus	42 02 44	905	0.000000	-8.77
R-L SMG	62 -24 36	474	0.000000	-9.15
Precuneus cortex	06 -46 36	384	0.000003	6.87
R- lingual Gyrus, R- ICC	10 -86 02	338	0.000012	-8.22
R-MTG, R- fusiform cortex	36 -14 -24	319	0.000022	9.87
L- SFG, L-MFG	-28 24 52	301	0.000037	10.37
R- LOC	10 -64 60	281	0.000069	-6.50
R- cerebellum	30 -60 -26	178	0.002133	-13.39

Abbreviations: L, left; R, right; ACC, anterior cingulate cortex; FMC, frontal medial cortex; ICC, intracalcarine cortex; ITG, inferior temporal gyrus; LOC, lateral occipital cortex; MFG, middle frontal gyrus; MTG, middle temporal gyrus; PCC, posterior cingulate cortex; PreCG, precentral gyrus; PPHG, posterior parahippocampal gyrus; SFG, superior frontal gyrus; SMG, supramarginal gyrus; SPL, superior parietal lobule.

Table 4

The effect of MMSE on connectivity in groups. Between-groups functional connectivity differences for HC > PD contrast.

	MNI Coordinate	Region	Clusters Size	FWE
L-PuI	14 -30 00	L-R thalamus PCC L-hippocampus brainstem	529	0.000004
L-PuL	-14 -28 16	L- thalamus	288	0.001083
L-PuM	-10 -28 08	L-R thalamus	266	0.002346
R-PuI	-16 -30 00	L- thalamus L-hippocampus	290	0.000883
R-PuI	14 -30 00	R-thalamus brainstem	269	0.001449
R-PuL	16 -26 18	R-thalamus	338	0.000406
R-PuM	-04 -32 14	R-L thalamus	280	0.00194

Abbreviations: L, left; R, right, PCC, posterior cingulate cortex

Table 5 Comparisons of pulvinar seeds volumes in patients with Parkinson disease and healthy controls

	Healthy Controls		Parkinson Disease’s		Mean Differences (p-value)
	Mean, %	SD, %	Mean, %	SD, %	HC > PD
R- Pulvinar	0.82069	0.084392	0.62975	0.112525	**0.000
L- Pulvinar	0.64909	0.067201	0.52966	0.064898	**0.000
R-Thalamus	4.92291	0.281830	3.94133	0.567563	**0.000
L-Thalamus	4.82235	0.276868	4.06551	0.470424	**0.003

SD standard deviation, L: left, R: right. *p < 0.05, **p < 0.01.

The pulvinar has been considered as an important component for integrating activity across cortical areas of the brain and modulating visual attention processing ²²,²³, furthermore, the lesions of the pulvinar can result in attentional deficits ²⁴, neglect syndromes ²⁵, motor movement abnormalities ¹⁵,²⁶ as well as fear recognition difficulty ¹². Identifying the functional connectivity of PuA, PuI, PuL, and PuM in PD could provide insight to understand the functions of each pulvinar subdivision in this neurodegenerative disease. We analyzed the functional connectivity of the PuA, PuI, PuL, and PuM in the HC and PD groups. We hypothesized that the functional connectivity of the pulvinar subdivisions could be altered in the PD group compared to the HC group, particularly in the motor, visual attention, and executive function areas of the brain, we showed that the bilateral PuI, PuL and PuM in the PD group has decreased connectivity to thalamic and extra-thalamic regions of the brain than the PD group.

We observed that the intrathalamic network connectivity of Pul, PuL, and PuM in each hemisphere was decreased in PD group compared to the HC group. In accordance with this, we detected a decreased connectivity among left PuI and PCC, left hippocampus and brainstem; right PuI and left hippocampus, brainstem. The connectivity between pulvinar and hippocampus has been previously reported in some studies ⁵,⁸. The hippocampus is an important part of the limbic system and plays a critical role in converting information from short-term memory to long-term memory. Several studies suggested that abnormalities in the hippocampus play an important role in cognitive impairment in PD. For instance, Kandiah et al. reported the hippocampal volume might be a predictive factor for cognitive impairment in PD ²⁷, Also, Sveinbjornsdottir established a relationship between visual hallucinations, , and neuropathological changes in the hippocampus in PD ²⁸. Since the PuI is considered as visual pulvinar since it’s connectivity with the occipital and temporal regions. we considered that visual hallucinations seen in PD may be associated with decreased connectivity between bilateral PuI and left hippocampus in PD. We observed , that left PuI in the PD group had less connectivity to PCC compared to the HC. This is in line with a study conducted by Zhan et. al. showing that the connectivity alteration in PCC were associated with connectivity abnormalities and cognitive performance changes in PD patients ²⁹. In addition, Garofalo stated that PCC dysfunction may play a role in the pathogenesis of PD psychosis by supporting previous studies ³⁰. Considering all of these evidences, it seems plausible that further studies, which take functional connectivity between the left PuI and the PCC in PD into account, need to be undertaken to enlighten the unclarity. Interestingly, the less connectivity between pulvinar and hippocampus as well as PCC has been also observed in schizophrenia patients compared to the healthy controls ³¹.

Our findings showed that grey matter volume decreased in the whole pulvinar and thalamus in the PD group compared to the HC group. The previous studies reported the volume reduction of pulvinar in patients with Alzheimer’s disease ^32,33 and Lewy body dementia ¹⁶ and associated this volume reduction with symptoms such as attention impairment and executive function deficit in these neurodegenerative diseases. Furthermore, Matsuuro et al. found a smaller pulvinar in PD patients with pulvinar hypo-intensity compared to those without pulvinar hypo-intensity after performing deep brain stimulation ¹⁸. Our study confirms that the volumes of pulvinar were decreased in PD compared with healthy controls and supports evidence from previous observations. In agreement with this, the association of pulvinar volume remained significant after adjustment the effect of MMSE and age on relevant networks.

To our best knowledge, this is the first study directly investigating functional connectivity of the PuA, PuI, PuL, and PuM subdivisions using seed-based resting-state fMRI in PD, along with HC. Although, previous studies suggested the role of PuI in visual attention and processing, our findings of decreased connectivity of PuI with other cognitively relevant areas, such as hippocampus and suggest the contribution of the PuI to attention, executive function, and working memory in PD.

Despite providing valuable neuroimaging evidence for the cognitive role of pulvinar in PD, the present study has the limitation that we could not evaluate some additional parameters (i.e., motor, and mood performances). In conclusion, although preliminary, our findings may pave the way for translating PD-specific neuroimaging measures into clinical scores, particularly if replicated by other investigators.

Participants

Resting-state fMRI and T1 weighted images of 15 HC who had no neurological disease and traumatic history, and 12 PD patients were retrospectively used in this study. PD patients were assessed with the Hoehn and Yahr ³⁴. We used the Mini-Mental State Examination (MMSE) to ascertain the presence of cognitive impairment. The mean age of the HC was 60.26±9.37 while it was 75.75±10.07 for the PD group. All PD patients had a Hoehn and Yahr scores greater than or equal to 2, which means that patients had movement disorders without impairment of balance. The demographic features and MMSE scores of the participants are shown in Table 1 for all participants. The institutional ethical committee of the Istanbul Medipol University approved the study (Ethical Report: E-10840098-772.02-6112-E. 1139).

Magnetic resonance imaging data acquisition

All images were acquired with the Philips Achieva 3 Tesla (Philips Medical Systems, Best, Holland). The anatomical image and resting-state functional activity of participants was recorded after the participants were positioned in MR device. The imaging parameters for T1-weighted image of the sagittal section were as follows: 190 slices, FOV = 256x256x190 mm, voxel size= 1x1x1 mm, TR = 8.1 ms, TE = 3.7 ms flip angle = 8^◦. The resting-state fMRI scans were acquired by the T2* weighted Gradient-echo Echo-planar Imaging (GE-EPI) sequence as following parameters: 300 volumes, 35 axial slices, FOV = 240x240x140 mm, voxel size =3x3x4, flip angle 77◦, repetition time (TR) 2230 ms, echo time (TE) 30 ms with a duration 12 min. It was requested from participants to keep eyes open and stay without a move in order to get a good quality resting image.

Segmentation of thalamic nuclei for pulvinar seeds

FreeSurfer (http://surfer.nmr. mgh.harvard.edu/) was used to create the seeds in the current study. The thalamic nuclei of Montreal Neurological Institute (MNI) 2 mm standard space were segmented using the “recon-all” function in the FreeSurfer program ³⁵. Following the thalamus parcellation, the PuA, PuI, PuL, and PuM in each hemisphere were selected as seeds (Fig. 3). The instructions provided by Williams ³⁶ were followed in order to convert the seeds from FreeSurfer format (.mgh/.mgz) to Nifti (.nii/.nii.gz) format.

Data Processing

The functional connectivity toolbox v18 (CONN) was used to preprocess all images in MATLAB R2021a (Mathworks, Sherborne, MA, United States) ³⁷. Each participant's functional images were realigned to account for head movements. Previous research has found that realignment alone is insufficient to eliminate motion artefacts, and that head movements can influence functional connectivity results ^38,39. As a result, outlier scans for functional images were detected using Artifact detection tools (ART) based scrubbing ⁴⁰. A conservative 95 percent percentile was used to set the threshold, which includes linear motion parameters > 0.5 mm and a global brain signal change of z > 3. To control for confounding effects, the detected outlier scans were used as a covariate in the denoising procedure. The structural and functional images were registered after scrubbing. As a result, low-resolution functional images were aligned to the plane of high-resolution structural images and made ready for the normalization step. Following that, tissue probability maps are used to separate the structural images into different segments such as white matter, gray matter, and cerebrospinal fluid. The functional and structural images were resized to 2 mm x 2 mm x 2 mm and normalized into the Montreal Neurological Institute (MNI) space. Finally, an 8-mm full width at half maximum (FWHM) Gaussian kernel was used to smooth the functional images. The age and MMSE scores were included as covariates for this analysis.

Voxel-based morphometry analysis

Voxel based morphometry (VBM) analysis was performed using Computational Anatomy Toolbox (CAT12, http://dbm.neuro.uni-jena.de/cat/), an extension toolbox of Statistical Parametric Mapping software (SPM12, http://www.fil.ion.ucl.ac.uk/spm/software/) in MATLAB (20b) ⁴¹. The high-resolution 3D T1 images were segmented into the standard Montreal Neurological Institute's (MNI) space using different tissue probability maps (such as gray matter, white matter and cerebrospinal fluid) and then all the tissue segments were modulated and normalized to the standard MNI space. In addition, total intracranial volume (TIV) was calculated to account for varying brain sizes and volumes as well. To improve the signal-to-noise ratio, the normalized gray matter images were smoothed with an 8-mm FWHM Gaussian kernel using the standard SPM module "Smooth." A quality assessment was done after the preprocessing to verify the homogeneity of the gray matter tissues.

Paired samples t test was used to assess differences in gray matter volumes between groups. We incorporated the subject’s age and TIVs in the design matrix as covariates, since several researchers found that the age and TIV of subjects have an impact on the VBM results ⁴². The results are provided after correction for multiple comparisons as voxel-level threshold: uncorrected p<0.001, cluster level threshold: family-wise error (FWE) p<0.05.

Statistical analysis

SPSS 21 was used to examine demographic features and MMSE scores. To compare continuous variables including age, and MMSE scores, independent sample t-tests were used, and a chi-square test was used to look at gender differences between groups Table 1. Seed to voxel correlation analysis was performed using the functional connectivity toolbox v18 implemented in MATLAB R2021a to explore connectivity variations between HC and PD group on large-scale networks (Mathworks, Sherborne, MA, United States) ³⁷. To reduce the effect of noise, functional images were band-pass filtered to 0.008 - 0.09 Hz after preprocessing. The six motion parameters and their first-order derivatives were then regressed, as well as the signals obtained from white matter, cerebrospinal fluid as an anatomical component-based noise correction process (aCompCor), and the confounding factors originating from the resting condition ⁴³. Predefined eight ROIs were added to the CONN software. The voxels in all ROIs were averaged for the BOLD time series in the first-level analysis, and the correlation coefficients between the BOLD time series obtained from each brain voxel were computed. These correlation coefficients were then z-transformed using the Fisher transformation for statistical analysis. The Z values of all ROIs were compared between the two groups using ANOVA at the second level, with thresholds of p_unc < 0.001 at the voxel level and FWE adjusted p_FWE < 0.05 at the cluster level. After p-values were corrected for multiple comparisons (p_FWE-BC< 0.00625), the Bonferroni-corrected results were presented.

Data availability

Research data are not publicly available since it is protected health information.

Acknowledgement

This article has been produced from the first author's master’s thesis.

Author Contributions

B.A. Conceptualization, Data curation, Writing - original draft, Visualization. H.A.V. Supervision, Acquisition of data, Interpretation of data. S.A. Conceptualization, Data curation, Visualization. B.S. Software, Methodology. L.H. Patient diagnosing, Supervision. Z.B. Analyze processing supervision. S.Y. Data collection. U.S. Supervision. B.Y. Writing - review & editing, Supervision.

Corresponding author

Correspondence to Halil Aziz Velioglu.

Ethics declarations

Competing interests

The authors declare no competing interests.

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The investigation of resting-state functional connectivity of pulvinar in old age individuals and Parkinson’s patients

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Abstract

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