Functional Connectivity of Ventral and Dorsal Visual Streams in Posterior Cortical Atrophy

Abstract

Background:

Posterior cortical atrophy (PCA) induces progressive dysfunction of ventral and dorsal visual networks. Little is known, however, about corresponding changes in functional connectivity (FC).

Objectives:

To investigate FC changes in the visual networks, their relationship with cortical atrophy, and the association with Alzheimer’s disease (AD) pathology.

Methods:

Ten PCA patients and 28 age-matched controls participated in the study. Using resting state fMRI, we measured FC in ventral and dorsal cortical visual networks, defined on the basis of a priori knowledge of long-range white matter connections. To assess the relationships with AD, we determined AD biomarkers in cerebrospinal fluid and FC in the default mode network (DMN), which is vulnerable to AD pathology. Voxel-based morphometry analysis assessed the pattern of grey matter (GM) atrophy.

Results:

PCA patients showed GM atrophy in bilateral occipital and inferior parietal regions. PCA patients had lower FC levels in a ventral network than controls, but higher FC in inferior components of the dorsal network. In particular, the increased connectivity correlated with greater GM atrophy in occipital regions. All PCA patients had positive cerebrospinal fluid biomarkers for AD; however, FC in global DMN did not differ from controls.

Conclusions:

FC in PCA reflects brain structure in a non-univocal way. Hyperconnectivity of dorsal networks may indicate aberrant communication in response to posterior brain atrophy or processes of neural resilience during the initial stage of brain dysfunction. The lack of difference from controls in global DMN FC highlights the atypical nature of PCA with respect to typical AD.

Keywords

Brain resilience dorsal stream functional connectivity posterior cortical atrophy ventral stream

INTRODUCTION

Posterior cortical atrophy (PCA) is a rare neurodegenerative dementia, often considered as an atypical variant of Alzheimer’s disease (AD) [1, 2]. Patients with PCA usually present with progressive high-level visual and visuomotor deficits, including visual agnosia, environmental disorientation, elements of Bálint’s or Gerstmann’s syndromes, along with praxic and language deficits [3]. Consistent with their clinical presentation, PCA patients show hypometabolism/hypoperfusion [4] and grey matter (GM) atrophy in parieto-occipital and posterior temporal cortices [5].

McMonagle et al. [3] proposed a classification of PCA into dorsal and ventral subtypes, with reference to the classic dichotomy of ventral and dorsal cortical visual streams [6]. According to current models [7], a ventral stream carries out information about perceptual features and substantiates perceptual identification. A more dorsal stream processes instead information about object locations, and mediates the visual control of skilled actions. PCA patients may present with “ventral” deficits such as pure alexia [8], or with “dorsal” deficits such as optic ataxia or visuo-spatial neglect [9 –11]. However, overlapping clinical presentations are very often observed [12].

Anatomically, occipital and anterior temporal regions linked by the inferior longitudinal fasciculus represent a main component of the ventral stream [13]. The dorsal stream corresponds to inferior and superior parietal brain regions connected with the frontal lobes by a long-range white matter (WM) bundle, the superior longitudinal fasciculus (SLF) [13]. Migliaccio et al. [9] investigated the GM and WM correlates of the neuropsychological profile in a group of patients with PCA, who showed either predominantly ventral or additional dorsal cognitive deficits. The combined results of voxel-based morphometry (VBM) (for GM) and DTI-tractography (for WM) suggested that selective visuo-perceptual and visuo-spatial deficits typical of PCA do not result from cortical damage alone, but by a network-level dysfunction including WM damage along the major visual pathways [9, 10]. However, functional interactions within ventral and dorsal networks in PCA remain unknown.

In this study, for the first time, we explored functional connectivity (FC) between brain areas along ventral and dorsal networks, based on evidence showing a tight relationship between resting-state FC and structural connectivity [14]. Because PCA is frequently associated with AD pathology, we determined AD biomarkers in cerebrospinal fluid (CSF), and explored FC in the default mode network (DMN), which is highly vulnerable to deposition of amyloid-β [15].

We hypothesized that ventral and dorsal functional networks should be altered in PCA proportionally to posterior atrophy, with consequent loss of efficiency in information exchange. Moreover, since parietal and posterior temporal regions, usually atrophic in PCA, are comprised in the DMN [1, 16], and because PCA is considered a variant of early age of onset AD, we also wondered whether differences in global DMN FC between PCA patients and controls might occur.

METHODS

Subjects

Ten PCA patients and 28 age-matched healthy subjects without history of neurological or psychiatric disease participated in the study (Table 1). Clinical and cognitive data were acquired at the Centre National de Référence ‘Démences Rares’, located at the “Institut de la memoire et de la maladie d’Alzheimer” (IM2A), in the Pitié-Salpêtrière Hospital, Paris. Clinical diagnosis was based on a multi-disciplinary evaluation including clinical history and neurological examination, caregiver interview, and a neuropsychological test battery. Medical records of patients clinically diagnosed with PCA were reviewed by two neurologists (RM and LT) to ensure they met PCA diagnostic criteria. Following criteria proposed by McMonagle [3], and modified by Alladi [17] were applied: 1) presentation with progressive visual or visuospatial impairment in the absence of ophthalmologic impairment; 2) evidence of complex visual disorder on examination: elements of Balint’s (and Gerstmann’s) syndrome, visual agnosia, dressing apraxia, or environmental disorientation; 3) proportionately less memory loss. To meet criteria, patients were required to present with early complaints of visual and visuospatial impairment in the absence of memory complaints. Subjects with early episodic memory impairment, ophthalmologic disease, extrapyramidal symptoms or signs, hallucinations, cognitive fluctuations, or substantial MRI T2 white matter hyperintensities in the occipito-parietal regions were not included in this study.

All patients underwent a neuropsychological screening battery. Patients also underwent a detailed exploration of “posterior” cognitive functions (i.e., those based on occipito-temporal and occipito-parieto-frontal circuits), through a battery specifically conceived for PCA patients. Neuropsychological assessment was performed by an experienced neuropsychologist blind to the MRI results, and included global cognitive assessment with Mini-Mental State Examination (MMSE) [18], the Frontal Assessment Battery (FAB) [19], and the Clinical Dementia Rating (CDR) scale [20]. General memory, language, and executive tests were also performed, such as the Free and Cued Selective Reminding Test [21] and the Rey Auditory Verbal Learning Test [22], word generation tasks for category and letter fluency [23], as well as visual and verbal direct and backward span [24]. Limb apraxia was evaluated clinically by assessing ideomotor apraxia on verbal instruction as well as gesture imitation. Evaluation of visual and visuospatial deficits included the “Cookie Theft” picture from the Boston Diagnostic Aphasia Examination [25], or the five series of overlapping figures [26] to assess simultanagnosia, confrontation naming to assess visual agnosia [25, 27] (in which the patient has to name a series of images shown by the examiner), and reading of six lines of text to assess alexia. Signs of Balint’s and Gerstmann’s syndromes were assessed as detailed in Kas et al. [4]. Briefly, assessment included evaluation of oculomotor apraxia (defined as the inability to voluntarily direct one’s gaze to a particular point), optic ataxia (impaired goal-directed hand movements toward visually presented targets), right– left distinction, finger agnosia, acalculia, and agraphia. Visual neglect was assessed by using standardized visuo-spatial tests such as line bisection, bells cancellation, and copy of drawing [28]. Clinically, visual agnosia and alexia were considered as “ventral” deficits, whereas elements of Balint’s and Gerstmann’s syndromes, visual neglect, and ideomotor apraxia were considered as resulting from more “dorsal” deficits.

Moreover, all PCA patients had a lumbar puncture to search for AD biomarkers, with quantification of total tau (hereafter tau), phosphorylated tau at threonine 181 (P-tau) and amyloid-β peptide 1-42 (Aβ_1 - 42) (for procedure see [29]). Diagnosis of AD was made on the basis of current biological criteria based on CSF analyses. In the present study, Aβ_1 - 42 and tau (T-tau or P-tau) were used in combination, because the CSF AD signature, which combines low Aβ_1 - 42 and high T-tau or P-tau concentrations, significantly increases the accuracy of AD diagnosis [30]. Ratios were also considered. With respect to biomarker values predictive of AD, a previous study of our department has provided two main cut-offs, namely a P-tau/Aβ_1 - 42 cut-off of <0.211 pg/ml and a tau/Aβ_1 - 42 cut-off of <1.23 pg/ml [31] (see also [29] for a recent application). These cut-offs had respective sensitivities of 91.7% and 95%, and respective specificities of 89.1% and 84.8% in distinguishing AD from other neurodegenerative dementias. Moreover, the ratio of tau/Aβ_1 - 42 was the best biomarker to differentiate AD from frontotemporal lobar degeneration, and showed a specificity of 96.6% in a series of patients with diagnostic confirmation either by genetics or by postmortem examination [32]. The study was approved by the local committee on human research. All subjects provided written informed consent before participating.

Imaging protocol

The MR protocol was carried out with a 3T whole-body system (Siemens, Erlangen, Germany) at the Center for Magnetic Resonance Research (CENIR), Brain and Spine Institute (ICM), Paris. The functional images were acquired by T2*-weighted fast echo planar imaging (flip angle = 90°, echo time = 30 ms, repetition time = 2.26 s) from 45 interleaved axial slices (gap = 0.3 mm) with a 3×3×3 mm³ voxel size for the resting state. The resting-state fMRI experiment consisted of one 8-minute run in which participants were asked to relax with their eyes closed, without falling asleep. Each run consisted of 200 EPI volumes. A high-resolution structural volume was also acquired using a T1-weighted 3D magnetization prepared rapid gradient echo (MP-RAGE) sequence (160 sagittal images; thickness 1 mm; FOV 256×256 mm²; matrix size 256×256).

Structural and functional MRI analysis

VBM study was performed using SPM8 and the Diffeomorphic Anatomical Registration Exponentiated Lie Algebra (DARTEL) registration method [33]. Briefly, (i) T1-weighted images were segmented [34] to produce GM, WM, and CSF probability maps in the Montreal Neurological Institute (MNI) space; (ii) tissue segmentations were averaged across participants and smoothed with an 8 mm full-width at half-maximum (FWHM) Gaussian kernel to create customized prior probability maps; (iii) original T1-weighted images were segmented a second time using the custom priors to obtain new segmentation and normalization parameters; (iv) T1-weighted images were rigidly aligned (using the rigid-body component of the normalization parameters from step [iii]), segmented into GM and WM (using the segmentation parameters from step [iii]) and resampled to 1.5 mm isotropic voxels; (v) GM segments were imported in DARTEL and coregistered; (vi) study-specific DARTEL template was created [from GM segments imported (v)] and the obtained flow fields were applied to the rigidly-aligned segments to warp them to the common DARTEL space and then modulated using the Jacobian determinants. Since the DARTEL process warps to a common space that is smaller than the MNI space, the modulated images from DARTEL were normalized to the MNI template using an affine transformation estimated from the DARTEL GM template and the a priori GM probability map without re-sampling (http://brainmap.wisc.edu/normalizeDARTELtoMontreal Neurological Institute). Finally, images were smoothed with an 8-mm full-width at half-maximum Gaussian kernel. GM maps were compared between patients and controls using an ANOVA model in Statistical Parametric Mapping (SPM8), adjusting for subject’s age, gender, and total intracranial volume. A significance threshold of p < 0.05 corrected for multiple comparisons (Family Wise Error [FWE]) was adopted. Given that our PCA patients had relatively short disease duration, and thus showed less atrophy than more advanced patients, we also calculated VBM results at an uncorrected threshold (p < 0.001).

The values of atrophy to be used for statistical correlations was obtained by subtracting from 1 the mean smoothed Jacobian-modulated gray matter and white matter estimates (corrected for total intracranial volume), for each atrophic regions (occipital, parietal, posterior temporal).

Resting state fMRI study

Pre-processing

K-space functional data were first processed to reduce physiological noise using a retrospective estimation of respiration and heart beat [35]. Then, statistical parametric mapping (SPM) 8 software was used to correct for subject’s motion, reduce low-frequency drift of the signal (high-pass filter with cutoff frequency 4.16×10^–3 Hz) and smooth the images with an isotropic spatial Gaussian filter (FWHM = 5 mm)

Regions of interest selection

We aimed at exploring the status of the functional connectivity within the dorsal and ventral visual networks, by using a priori knowledge of long-range WM connections. The dorsal network was parceled by following the three main branches of the superior longitudinal fasciculus (superior, SLF I; middle, SLF II; inferior, SLF III) [36]. The ventral network was defined by the anatomical trajectory of the inferior longitudinal fasciculus [37]. The definition of ventral and dorsal ROIs, belonging to the networks, was based on previous anatomical tractography studies [37, 38]. Cortical regions of interest (ROI) were obtained automatically by using the PickAtlas SPM8 toolbox [39]. Figure 1 shows all the seed regions. All the networks were separately explored in the left and in the right hemisphere.

More specifically, the dorsal network included: i) a superior component comprising the superior parietal lobule and precuneus (Brodmann area, BA, 5 and 7) and superior medial and lateral frontal regions (BA 8, 9, 32); ii) a middle component, comprising the angular and supramarginal gyri (BA 39 and 40), along with superior and lateral frontal regions partially overlapping with the superior component (BA 8, 9); iii) an inferior component, comprising the supramarginal gyrus (BA 40), and lateral middle and inferior frontal regions (BA 44, 45, and 47).

The ventral network included the occipital lobe (BA 17, 18, and 19) and the anterior temporal pole (BA 38).

We also explored FC within the DMN. DMN included the following brain regions: precuneus, posterior cingulate, inferior parietal lobules, and medial frontal areas including the anterior cingulate cortex, bilaterally [40].

Data analysis and statistics

To quantify the between- and within-network connectivity, we used a measure derived from entropy, hierarchical integration, which is aimed at quantifying information exchanges between areas constituting the networks [41]. Hierarchical integration is particularly adapted to the global estimation of FC at the network level. We hereafter refer to hierarchical integration as FC (see [42 –47] for recent applications). The value of hierarchical integration, for each network, was used for group comparison (PCA patients versus controls). To do so, the values of integration were inferred by using a Bayesian numerical sampling scheme (5,000 samples) that approximated the posterior distribution of the parameters of interest in a group analysis [42]. In that framework, we tested that the posterior probability p(A|y) of the assertion A that “patients have lower between-networks integration than healthy controls” related to any pair of networks (dorsal-superior, middle and inferior- and ventral). The validity of the assertion could be tested using evidence e(A|y), measured in decibels (dB), equal to the ratio of the probability that A to be true to the probability that A to be false, in a base 10 logarithmic scale [48]. According to this measure, two values of integration will be considered as significantly different when |e(A|y)|>10 dB, that is to say that the probability of A being true is 10 times higher than the probability of A being false. A significant positive value of evidence shows that the assertion A is true, whereas a significant negative value shows that the complementary assertion $\bar{A}$ has to be considered as true.

We assessed the relationship between connectivity values in altered network and cortical atrophy (occipital, parietal, posterior temporal regions) by calculating Spearman correlation coefficients for small samples.

RESULTS

Cognitive and biological profile

Patients demonstrated a mild-to-moderate global cognitive impairment on the tests assessing the global cognitive status, such as MMSE, FAB, and CDR (Table 1). Working memory was also impaired in both the verbal and the visuospatial modalities. Conversely, phonemic and categorical fluency were in the normal range. The most frequent “dorsal” deficits were spatial neglect (100%), ideomotor apraxia (90%), and acalculia (80%), simultanagnosia (70%), and optic ataxia (70%). Concerning “ventral” deficits, visual agnosia was present in 70% of patients (Table 1). Supplementary Table 1 also reports the starting clinical picture for each PCA patient. All PCA patients had a CSF biomarkers profile compatible with AD pathology (Table 1).

Structural and functional MRI results

VBM results

In PCA patients, compared to healthy subjects, VBM demonstrated GM atrophy centered on bilateral occipital, parietal and posterior temporal regions, with right-side predominance (Fig. 2 and Table 2) (all p < 0.05, FWE). Lowering the threshold disclosed smaller areas of atrophy in the frontal regions and cingulate cortex (Table 2) (p < 0.001).

Resting state fMRI results

In their dorsal networks, PCA patients showed a bilateral increase of FC in the inferior components (0.98 < p < 1) (Fig. 1). The bilateral middle component showed a tendency toward a slight increase of FC in patients compared to controls (0.76 < p < 0.84). Finally, there was no group difference in the bilateral superior component (0.74 < p < 0.76).

Conversely, FC decreased bilaterally between the occipital areas and the temporal areas (ventral network) in PCA patients compared to controls (p = 0.98).

No differences emerged in global DMN FC between PCA patients and controls (p = 0.54).

In the right hemisphere, the amount of grey matter of the occipital cortex negatively correlated with FC in the inferior dorsal component (Rho = –0.83, p = 0.0056) (Supplementary Figure 1). In a few words, the greater the occipital atrophy, the higher the FC in the inferior component of dorsal network. We have not found correlations between other brain areas and functional networks.

DISCUSSION

We assessed functional connectivity in ventral and dorsal functional networks in a well-characterized group of patients with PCA and positive AD biomarkers, on the basis of anatomical knowledge of the normal architecture of these networks. Atrophy occurred in bilateral occipital, posterior temporal, and inferior parietal cortices, with right-side predominance. FC demonstrated an expected reduction in ventral occipital-temporal pathways. In contrast, the inferior component of the dorsal network demonstrated a bilateral increase of FC levels, which was less pronounced or absent in the middle and superior components. In the most severely affected right hemisphere, higher FC in the inferior component of the dorsal networks correlated with the amount of GM atrophy in the occipital cortex. Finally, contrary to our expectation, global DMN FC did not differ between PCA patients and controls.

The present study shows for the first time the occurrence of FC bi-directional changes in ventral and dorsal visual networks, in PCA. The present findings support the general hypothesis that clinical deficits in PCA result from dysfunctions in large-scale networks, as previously demonstrated in other neurodegenerative dementias [49]. In this vein, exploring the white matter, we suggested that the clinical features in PCA might not result from cortical atrophy alone but by damage along dorsal and ventral visual pathways in particular in the right hemisphere [9 , 50]. Here, we showed that FC was reduced in ventral networks with severe occipital atrophy, as expected. The possible physiological basis of increased connectivity in the inferior components of the dorsal networks, and its correlation with occipital atrophy will be specifically discussed.

Parieto-frontal networks, anatomically connected by the SLF III (inferior dorsal component), are important for attentional mechanisms, including vigilant and sustained attention [51, 52], especially in the right hemisphere. All PCA patients included in our study showed signs of visual neglect, which affected the left hemispace in nine out of ten cases. Dysfunction of the inferior component of the dorsal networks in the right hemisphere is a crucial mechanism of visual neglect, and can even contribute to right-sided neglect in neurodegenerative patients [53, 54]. In the present series, however, left-sided neglect was much more frequent than right-sided neglect, consistent with evidence from other studies of neglect in neurodegeneration [55]. In this framework and because our patients had relatively short disease duration, increased FC in this network could be considered as an early signature of PCA. Recent fMRI studies on typical AD [56] or mild cognitive impairment [57] suggest that states of functional hyperconnectivity, which can later progress to hypoconnectivity, may indicate an early phase of brain dysfunction. Increased FC can also occur in psychiatric conditions such as schizophrenia [58]: disease-induced impaired connectivity may lead to isolation of some brain systems, which can then demonstrate increased FC because they become less susceptible to influence from other systems [58].

Alternatively, the paradoxical increase of FC may reflect the engagement of compensatory mechanisms at the initial stages of PCA. This might be a general mechanism in the early phases of several neurodegenerative diseases, and in particular in focal variants. For example, DMN connectivity in patients with early-onset AD was increased in the anterior temporal areas, and positively correlated with memory performance [59]. The finding of elevated connectivity in the dorsal component is also consistent with previous studies showing differences in anterior (hyperconnected) versus posterior (hypoconnected) networks in AD [60]. Taken together, this evidence possibly indicates a resilience mechanism in parieto-frontal network, as a response to reduced connectivity in more ventral network. Resilience to neuropathological damage corresponds to the ability to optimize performance through effective recruitment of brain networks [61]. As long as the inferior parietal cortex is sufficiently preserved at the structural level at the early stage of the disease, it may ensure information processing and transmission to the prefrontal cortex. More generally, parieto-frontal systems in particular might play a role of “brain/cognitive reserve”, and delay cognitive impairment in neurodegenerative diseases, perhaps through the activity of noradrenergic circuits [62]. Thus, partially preserved brain regions (such as the inferior parietal lobule) could try to compensate for neuronal and functional degradation. Some example of the resilience neuronal has been reported in the literature of PCA. A patient with preserved numerical skills demonstrated increased fMRI activation in temporal structures during numerical processing [63]. Unfortunately, given the small number of subjects in the present study and the lack of homogeneous cognitive scores, we cannot calculate correlations with neuroimaging in order to verify this hypothesis.

We also found a negative correlation between the degree of occipital atrophy and the higher FC level in the inferior component of the right dorsal component. Severe atrophy in the right occipital lobe seems to influence particularly this inferior parieto-frontal network, which would explain its hyperconnectivity state. This correlation can be explained supposing the presence of elective connections between these regions. The presence of structural connections between specific visual areas (e.g., V6) and intraparietal regions has been demonstrated on awake macaque monkeys, by injecting neuronal tracers. These reciprocal connections play a pivotal role in the dorsal visual stream, by distributing the visual information coming from the occipital lobe to parietal cortex [64]. The presence of human homologue of V6 has been showed [65], and resting-state MRI functional connectivity studies in humans have shown strong functional connectivity between parietal and visual areas (included human homologue of V6) [65].

Our results are in agreement with a very recent study [66], exploring the DMN, as well as different non-DMN networks, in distinctive phenotypes of AD, included PCA. Consistent with present data, PCA patients had impaired connectivity in non-DMN, termed “higher visual network” (broadly corresponding to our ventral network). Unfortunately, the authors did not study any dorsal component [66]. Very importantly, and in agreement with our data, the authors did not find striking difference in DMN [66]. All together these results highlight the atypical nature of PCA as compared to AD [1] in term of disease onset and perhaps progression. Finally and very interestingly, the same authors found that patients affected by another focal variant of AD (so-called logopenic aphasia) showed higher connectivity in the anterior subcomponent of DMN, compared with controls. To explain the increase of FC in logopenic patients, these authors have also evoked a compensatory mechanism [66].

This study has several limitations. First, the relatively small number of included PCA patients, due to the rarity of this syndrome, perhaps contributed to the absence of correlations with neuropsychological scores. A greater number of well-explored PCA patients (i.e., categorized on a biological level, and explored by using advanced imaging techniques) is certainly desirable for future studies. Another limitation is the absence of typical AD patients as control group. However, a large literature is already available on FC changes in typical AD. Moreover, the damage along ventral and dorsal streams seems specific to PCA, and has never been described in typical AD patients to our knowledge.

In conclusion, we have demonstrated that FC reflects the brain structure in a non-univocal/bi-directional way. PCA patients showed a paradoxical hyperconnectivity of attention-related dorsal networks, either as a result of early network dysfunction or as a sign of attempt of compensation in response to occipital atrophy early in the course of the disease. Parieto-frontal regions thus constitute crucial nodes of networks vulnerable to AD pathology in PCA patients, consistent with the neuronal vulnerability hypothesis of neurodegenerative diseases [49]. At variance with typical AD, where the disease progression mainly occurs within the DMN, in PCA it rather implicates ventral and dorsal cortical visual streams.

Footnotes

ACKNOWLEDGMENTS

Raffaella Migliaccio is supported by the “France Alzheimer” and “Philippe Chatrier” Foundations. Paolo Bartolomeo gratefully acknowledges the support of an AP-HP translational research grant. Cecile Gallea was supported by IHU-A-ICM (‘Investissement d’avenir’ program, ANR-10-IAIHU-06).

Authors’ disclosures available online ().

Appendix

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