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Franco Cauda

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10 papers

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YNIMG Journal 2024 Journal Article

Local functional connectivity abnormalities in mild cognitive impairment and Alzheimer's disease: A meta-analytic investigation using minimum Bayes factor activation likelihood estimation

Tommaso Costa
Enrico Premi
Barbara Borroni
Jordi Manuello
Franco Cauda
Sergio Duca
Donato Liloia

Functional magnetic resonance imaging research employing regional homogeneity (ReHo) analysis has uncovered aberrant local brain connectivity in individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) in comparison with healthy controls. However, the precise localization, extent, and possible overlap of these aberrations are still not fully understood. To bridge this gap, we applied a novel meta-analytic and Bayesian method (minimum Bayes Factor Activation Likelihood Estimation, mBF-ALE) for a systematic exploration of local functional connectivity alterations in MCI and AD brains. We extracted ReHo data via a standardized MEDLINE database search, which included 35 peer-reviewed experiments, 1,256 individuals with AD or MCI, 1,118 healthy controls, and 205 x-y-z coordinates of ReHo variation. We then separated the data into two distinct datasets: one for MCI and the other for AD. Two mBF-ALE analyses were conducted, thresholded at "very strong evidence" (mBF ≥ 150), with a minimum cluster size of 200 mm³. We also assessed the spatial consistency and sensitivity of our Bayesian results using the canonical version of the ALE algorithm. For MCI, we observed two clusters of ReHo decrease and one of ReHo increase. Decreased local connectivity was notable in the left precuneus (Brodmann area - BA 7) and left inferior temporal gyrus (BA 20), while increased connectivity was evident in the right parahippocampal gyrus (BA 36). The canonical ALE confirmed these locations, except for the inferior temporal gyrus. In AD, one cluster each of ReHo decrease and increase were found, with decreased connectivity in the right posterior cingulate cortex (BA 30 extending to BA 23) and increased connectivity in the left posterior cingulate cortex (BA 31). These locations were confirmed by the canonical ALE. The identification of these distinct functional connectivity patterns sheds new light on the complex pathophysiology of MCI and AD, offering promising directions for future neuroimaging-based interventions. Additionally, the use of a Bayesian framework for statistical thresholding enhances the robustness of neuroimaging meta-analyses, broadening its applicability to small datasets.

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YNICL Journal 2021 Journal Article

Gray matter abnormalities follow non-random patterns of co-alteration in autism: Meta-connectomic evidence

Donato Liloia
Lorenzo Mancuso
Lucina Q. Uddin
Tommaso Costa
Andrea Nani
Roberto Keller
Jordi Manuello
Sergio Duca

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by atypical brain anatomy and connectivity. Graph-theoretical methods have mainly been applied to detect altered patterns of white matter tracts and functional brain activation in individuals with ASD. The network topology of gray matter (GM) abnormalities in ASD remains relatively unexplored. METHODS: An innovative meta-connectomic analysis on voxel-based morphometry data (45 experiments, 1,786 subjects with ASD) was performed in order to investigate whether GM variations can develop in a distinct pattern of co-alteration across the brain. This pattern was then compared with normative profiles of structural and genetic co-expression maps. Graph measures of centrality and clustering were also applied to identify brain areas with the highest topological hierarchy and core sub-graph components within the co-alteration network observed in ASD. RESULTS: Individuals with ASD exhibit a distinctive and topologically defined pattern of GM co-alteration that moderately follows the structural connectivity constraints. This was not observed with respect to the pattern of genetic co-expression. Hub regions of the co-alteration network were mainly left-lateralized, encompassing the precuneus, ventral anterior cingulate, and middle occipital gyrus. Regions of the default mode network appear to be central in the topology of co-alterations. CONCLUSION: These findings shed new light on the pathobiology of ASD, suggesting a network-level dysfunction among spatially distributed GM regions. At the same time, this study supports pathoconnectomics as an insightful approach to better understand neuropsychiatric disorders.

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YNIMG Journal 2021 Journal Article

The pathoconnectivity network analysis of the insular cortex: A morphometric fingerprinting

Andrea Nani
Jordi Manuello
Lorenzo Mancuso
Donato Liloia
Tommaso Costa
Alessandro Vercelli
Sergio Duca
Franco Cauda

Brain disorders tend to impact on many different regions in a typical way: alterations do not spread randomly; rather, they seem to follow specific patterns of propagation that show a strong overlap between different pathologies. The insular cortex is one of the brain areas more involved in this phenomenon, as it seems to be altered by a wide range of brain diseases. On these grounds we thoroughly investigated the impact of brain disorders on the insular cortices analyzing the patterns of their structural co-alteration. We therefore investigated, applying a network analysis approach to meta-analytic data, 1) what pattern of gray matter alteration is associated with each of the insular cortex parcels; 2) whether or not this pattern correlates and overlaps with its functional meta-analytic connectivity; and, 3) the behavioral profile related to each insular co-alteration pattern. All the analyses were repeated considering two solutions: one with two clusters and another with three. Our study confirmed that the insular cortex is one of the most altered cerebral regions among the cortical areas, and exhibits a dense network of co-alteration including a prevalence of cortical rather than sub-cortical brain regions. Regions of the frontal lobe are the most involved, while occipital lobe is the less affected. Furthermore, the co-alteration and co-activation patterns greatly overlap each other. These findings provide significant evidence that alterations caused by brain disorders are likely to be distributed according to the logic of network architecture, in which brain hubs lie at the center of networks composed of co-altered areas. For the first time, we shed light on existing differences between insula sub-regions even in the pathoconnectivity domain.

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YNIMG Journal 2020 Journal Article

A meta-analytic approach to mapping co-occurrent grey matter volume increases and decreases in psychiatric disorders

Lorenzo Mancuso
Alex Fornito
Tommaso Costa
Linda Ficco
Donato Liloia
Jordi Manuello
Sergio Duca
Franco Cauda

Numerous studies have investigated grey matter (GM) volume changes in diverse patient groups. Reports of disorder-related GM reductions are common in such work, but many studies also report evidence for GM volume increases in patients. It is unclear whether these GM increases and decreases are independent or related in some way. Here, we address this question using a novel meta-analytic network mapping approach. We used a coordinate-based meta-analysis of 64 voxel-based morphometry studies of psychiatric disorders to calculate the probability of finding a GM increase or decrease in one region given an observed change in the opposite direction in another region. Estimating this co-occurrence probability for every pair of brain regions allowed us to build a network of concurrent GM changes of opposing polarity. Our analysis revealed that disorder-related GM increases and decreases are not independent; instead, a GM change in one area is often statistically related to a change of opposite polarity in other areas, highlighting distributed yet coordinated changes in GM volume as a function of brain pathology. Most regions showing GM changes linked to an opposite change in a distal area were located in salience, executive-control and default mode networks, as well as the thalamus and basal ganglia. Moreover, pairs of regions showing coupled changes of opposite polarity were more likely to belong to different canonical networks than to the same one. Our results suggest that regional GM alterations in psychiatric disorders are often accompanied by opposing changes in distal regions that belong to distinct functional networks.

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YNIMG Journal 2019 Journal Article

The alteration landscape of the cerebral cortex

Franco Cauda
Andrea Nani
Jordi Manuello
Donato Liloia
Karina Tatu
Ugo Vercelli
Sergio Duca
Peter T. Fox

Growing evidence is challenging the assumption that brain disorders are diagnostically clear-cut categories. Transdiagnostic studies show that a set of cerebral areas is frequently altered in a variety of psychiatric as well as neurological syndromes. In order to provide a map of the altered areas in the pathological brain we devised a metric, called alteration entropy (A-entropy), capable of denoting the “structural alteration variety” of an altered region. Using the whole voxel-based morphometry database of BrainMap, we were able to differentiate the brain areas exhibiting a high degree of overlap between different neuropathologies (or high value of A-entropy) from those exhibiting a low degree of overlap (or low value of A-entropy). The former, which are parts of large-scale brain networks with attentional, emotional, salience, and premotor functions, are thought to be more vulnerable to a great range of brain diseases; while the latter, which include the sensorimotor, visual, inferior temporal, and supramarginal regions, are thought to be more informative about the specific impact of brain diseases. Since low A-entropy areas appear to be altered by a smaller number of brain disorders, they are more informative than the areas characterized by high values of A-entropy. It is also noteworthy that even the areas showing low values of A-entropy are substantially altered by a variety of brain disorders. In fact, no cerebral area appears to be only altered by a specific disorder. Our study shows that the overlap of areas with high A-entropy provides support for a transdiagnostic approach to brain disorders but, at the same time, suggests that fruitful differences can be traced among brain diseases, as some areas can exhibit an alteration profile more specific to certain disorders than to others.

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YNICL Journal 2018 Journal Article

How do morphological alterations caused by chronic pain distribute across the brain? A meta-analytic co-alteration study

Karina Tatu
Tommaso Costa
Andrea Nani
Matteo Diano
Danilo G. Quarta
Sergio Duca
A. Vania Apkarian
Peter T. Fox

It was recently suggested that in brain disorders neuronal alterations does not occur randomly, but tend to form patterns that resemble those of cerebral connectivity. Following this hypothesis, we studied the network formed by co-altered brain regions in patients with chronic pain. We used a meta-analytical network approach in order to: i) find out whether the neuronal alterations distribute randomly across the brain; ii) find out (in the case of a non-random pattern of distribution) whether a disease-specific pattern of brain co-alterations can be identified and characterized in terms of altered areas (nodes) and propagation links between them (edges); iii) verify whether the co-alteration pattern overlaps with the pattern of functional connectivity; iv) describe the topological properties of the co-alteration network and identify the highly connected nodes that are supposed to have a pre-eminent role in the diffusion timing of neuronal alterations across the brain. Our results indicate that: i) gray matter (GM) alterations do not occur randomly; ii) a symptom-related pattern of structural co-alterations can be identified for chronic pain; iii) this co-alteration pattern resembles the pattern of brain functional connectivity; iv) within the co-alteration network a set of highly connected nodes can be identified. This study provides further support to the hypothesis that neuronal alterations may spread according to the logic of a network-like diffusion suggesting that this type of distribution may also apply to chronic pain.

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YNIMG Journal 2014 Journal Article

Drawing lines while imagining circles: Neural basis of the bimanual coupling effect during motor execution and motor imagery

Francesca Garbarini
Federico D'Agata
Alessandro Piedimonte
Katiuscia Sacco
Marco Rabuffetti
Fred Tam
Franco Cauda
Lorenzo Pia

When people simultaneously draw lines with one hand and circles with the other hand, both trajectories tend to assume an oval shape, showing that hand motor programs interact (the so-called “bimanual coupling effect”). The aim of the present study was to investigate how motor parameters (drawing trajectories) and the related brain activity vary during bimanual movements both in real execution and in motor imagery tasks. In the ‘Real’ modality, subjects performed right hand movements (lines) and, simultaneously, Congruent (lines) or Non-congruent (circles) left hand movements. In the ‘Imagery’ modality, subjects performed only right hand movements (lines) and, simultaneously, imagined Congruent (lines) or Non-congruent (circles) left hand movements. Behavioral results showed a similar interference of both the real and the imagined circles on the actually executed lines, suggesting that the coupling effect also pertains to motor imagery. Neuroimaging results showed that a prefrontal–parietal network, mostly involving the pre-Supplementary Motor Area (pre-SMA) and the posterior parietal cortex (PPC), was significantly more active in Non-congruent than in Congruent conditions, irrespective of task (Real or Imagery). The data also confirmed specific roles of the right superior parietal lobe (SPL) in mediating spatial interference, and of the left PPC in motor imagery. Collectively, these findings suggest that real and imagined Non-congruent movements activate common circuits related to the intentional and predictive operation generating bimanual coupling, in which the pre-SMA and the PPC play a crucial role.

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YNICL Journal 2014 Journal Article

Gray matter alterations in chronic pain: A network-oriented meta-analytic approach

Franco Cauda
Sara Palermo
Tommaso Costa
Riccardo Torta
Sergio Duca
Ugo Vercelli
Giuliano Geminiani
Diana M.E. Torta

Several studies have attempted to characterize morphological brain changes due to chronic pain. Although it has repeatedly been suggested that longstanding pain induces gray matter modifications, there is still some controversy surrounding the direction of the change (increase or decrease in gray matter) and the role of psychological and psychiatric comorbidities. In this study, we propose a novel, network-oriented, meta-analytic approach to characterize morphological changes in chronic pain. We used network decomposition to investigate whether different kinds of chronic pain are associated with a common or specific set of altered networks. Representational similarity techniques, network decomposition and model-based clustering were employed: i) to verify the presence of a core set of brain areas commonly modified by chronic pain; ii) to investigate the involvement of these areas in a large-scale network perspective; iii) to study the relationship between altered networks and; iv) to find out whether chronic pain targets clusters of areas. Our results showed that chronic pain causes both core and pathology-specific gray matter alterations in large-scale networks. Common alterations were observed in the prefrontal regions, in the anterior insula, cingulate cortex, basal ganglia, thalamus, periaqueductal gray, post- and pre-central gyri and inferior parietal lobule. We observed that the salience and attentional networks were targeted in a very similar way by different chronic pain pathologies. Conversely, alterations in the sensorimotor and attention circuits were differentially targeted by chronic pain pathologies. Moreover, model-based clustering revealed that chronic pain, in line with some neurodegenerative diseases, selectively targets some large-scale brain networks. Altogether these findings indicate that chronic pain can be better conceived and studied in a network perspective.

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YNIMG Journal 2012 Journal Article

Meta-analytic clustering of the insular cortex

Franco Cauda
Tommaso Costa
Diana M.E. Torta
Katiuscia Sacco
Federico D'Agata
Sergio Duca
Giuliano Geminiani
Peter T. Fox

The human insula has been parcellated on the basis of resting state functional connectivity and diffusion tensor imaging. Little is known about the organization of the insula when involved in active tasks. We explored this issue using a novel meta-analytic clustering approach. We queried the BrainMap database asking for papers involving normal subjects that recorded activations in the insular cortex, retrieving 1305 papers, involving 22, 872 subjects and a total of 2957 foci. Data were analyzed with several different methodologies, some of which expressly designed for this work. We used meta-analytic connectivity modeling and meta-analytic clustering of data obtained from the BrainMap database. We performed cluster analysis to subdivide the insula in areas with homogeneous connectivity, and density analysis of the activated foci using Voronoi tessellation. Our results confirm and extend previous findings obtained investigating the resting state connectivity of the anterior–posterior and left–right insulae. They indicate, for the first time, that some blocks of the anterior insula play the role of hubs between the anterior and the posterior insulae, as confirmed by their activation in several different paradigms. This finding supports the view that the network to which the anterior insula belongs is related to saliency detection. The insulae of both sides can be parcellated in two clusters, the anterior and the posterior: the anterior is characterized by an attentional pattern of connectivity with frontal, cingulate, parietal, cerebellar and anterior insular highly connected areas, whereas the posterior is characterized by a more local connectivity pattern with connections to sensorimotor, temporal and posterior cingulate areas. This antero–posterior subdivision, better characterized on the right side, results sharper with the connectivity based clusterization than with the behavioral based clusterization. The circuits belonging to the anterior insula are very homogeneous and their blocks in multidimensional scaling of MACM-based profiles are in central position, whereas those belonging to the posterior insula, especially on the left, are located at the periphery and sparse, thus suggesting that the posterior circuits bear a more heterogeneous connectivity. The anterior cluster is mostly activated by cognition, whereas the posterior is mostly activated by interoception, perception and emotion.

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YNIMG Journal 2011 Journal Article

Functional connectivity of the insula in the resting brain

Franco Cauda
Federico D'Agata
Katiuscia Sacco
Sergio Duca
Giuliano Geminiani
Alessandro Vercelli

The human insula is hidden in the depth of the cerebral hemisphere by the overlying frontal and temporal opercula, and consists of three cytoarchitectonically distinct regions: the anterior agranular area, posterior granular area, and the transitional dysgranular zone; each has distinct histochemical staining patterns and specific connectivity. Even though there are several studies reporting the functional connectivity of the insula with the cingulated cortex, its relationships with other brain areas remain elusive in humans. Therefore, we decided to use resting state functional connectivity to elucidate in details its connectivity, in terms of cortical and subcortical areas, and also of lateralization. We investigated correlations in BOLD fluctuations between specific regions of interest of the insula and other brain areas of right-handed healthy volunteers, on both sides of the brain. Our findings document two major complementary networks involving the ventral-anterior and dorsal-posterior insula: one network links the anterior insula to the middle and inferior temporal cortex and anterior cingulate cortex, and is primarily related to limbic regions which play a role in emotional aspects; the second links the middle-posterior insula to premotor, sensorimotor, supplementary motor and middle-posterior cingulate cortices, indicating a role for the insula in sensorimotor integration. The clear bipartition of the insula was confirmed by negative correlation analysis. Correlation maps are partially lateralized: the salience network, related to the ventral anterior insula, displays stronger connections with the anterior cingulate cortex on the right side, and with the frontal cortex on the left side; the posterior network has stronger connections with the superior temporal cortex and the occipital cortex on the right side. These results are in agreement with connectivity studies in primates, and support the use of resting state functional analysis to investigate connectivity in the living human brain.

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