Matteo Diano

Amygdala Response to Emotional Stimuli without Awareness: Facts and Interpretations

Over the past two decades, evidence has accumulated that the human amygdala exerts some of its functions also when the observer is not aware of the content, or even presence, of the triggering emotional stimulus. Nevertheless, there is as of yet no consensus on the limits and conditions that affect the extent of amygdala’s response without focused attention or awareness. Here we review past and recent studies on this subject, examining neuroimaging literature on healthy participants as well as brain-damaged patients, and we comment on their strengths and limits. We propose a theoretical distinction between processes involved in attentional unawareness, wherein the stimulus is potentially accessible to enter visual awareness but fails to do so because attention is diverted, and in sensory unawareness, wherein the stimulus fails to enter awareness because its normal processing in the visual cortex is suppressed. We argue this distinction, along with data sampling amygdala responses with high temporal resolution, helps to appreciate the multiplicity of functional and anatomical mechanisms centered on the amygdala and supporting its role in non-conscious emotion processing. Separate, but interacting, networks relay visual information to the amygdala exploiting different computational properties of subcortical and cortical routes, thereby supporting amygdala functions at different stages of emotion processing. This view reconciles some apparent contradictions in the literature, as well as seemingly contrasting proposals, such as the dual stage and the dual route model. We conclude that evidence in favor of the amygdala response without awareness is solid, albeit this response originates from different functional mechanisms and is driven by more complex neural networks than commonly assumed. Acknowledging the complexity of such mechanisms can foster new insights on the varieties of amygdala functions without awareness and their impact on human behavior.

Concordance of white matter and gray matter abnormalities in autism spectrum disorders: A voxel-based meta-analysis study

There are at least two fundamental unanswered questions in the literature on autism spectrum disorders (ASD): Are abnormalities in white (WM) and gray matter (GM) consistent with one another? Are WM morphometric alterations consistent with alterations in the GM of regions connected by these abnormal WM bundles and vice versa? The aim of this work is to bridge this gap. After selecting voxel‐based morphometry and diffusion tensor imaging studies comparing autistic and normally developing groups of subjects, we conducted an activation likelihood estimation (ALE) meta‐analysis to estimate consistent brain alterations in ASD. Multidimensional scaling was used to test the similarity of the results. The ALE results were then analyzed to identify the regions of concordance between GM and WM areas. We found statistically significant topological relationships between GM and WM abnormalities in ASD. The most numerous were negative concordances, found bilaterally but with a higher prevalence in the right hemisphere. Positive concordances were found in the left hemisphere. Discordances reflected the spatial distribution of negative concordances. Thus, a different hemispheric contribution emerged, possibly related to pathogenetic factors affecting the right hemisphere during early developmental stages. Besides, WM fiber tracts linking the brain structures involved in social cognition showed abnormalities, and most of them had a negative concordance with the connected GM regions. We interpreted the results in terms of altered brain networks and their role in the pervasive symptoms dramatically impairing communication and social skills in ASD patients. Hum Brain Mapp 35:2073–2098, 2014.

Multimodal fMRI Resting-State Functional Connectivity in Granulin Mutations: The Case of Fronto-Parietal Dementia

Background Monogenic dementias represent a great opportunity to trace disease progression from preclinical to symptomatic stages. Frontotemporal Dementia related to Granulin (GRN) mutations presents a specific framework of brain damage, involving fronto-temporal regions and long inter-hemispheric white matter bundles. Multimodal resting-state functional MRI (rs-fMRI) is a promising tool to carefully describe disease signature from the earliest disease phase. Objective To define local connectivity alterations in GRN related pathology moving from the presymptomatic (asymptomatic GRN mutation carriers) to the clinical phase of the disease (GRN- related Frontotemporal Dementia). Methods Thirty-one GRN Thr272fs mutation carriers (14 patients with Frontotemporal Dementia and 17 asymptomatic carriers) and 38 healthy controls were recruited. Local connectivity measures (Regional Homogeneity (ReHo), Fractional Amplitude of Low Frequency Fluctuation (fALFF) and Degree Centrality (DC)) were computed, considering age and gender as nuisance variables as well as the influence of voxel-level gray matter atrophy. Results Asymptomatic GRN carriers had selective reduced ReHo in the left parietal region and increased ReHo in frontal regions compared to healthy controls. Considering Frontotemporal Dementia patients, all measures (ReHo, fALFF and DC) were reduced in inferior parietal, frontal lobes and posterior cingulate cortex. Considering GRN mutation carriers, an inverse correlation with age in the posterior cingulate cortex, inferior parietal lobule and orbitofrontal cortex was found. Conclusions GRN pathology is characterized by functional brain network alterations even decades before the clinical onset; they involve the parietal region primarily and then spread to the anterior regions of the brain, supporting the concept of molecular nexopathies.

Dynamic changes in amygdala psychophysiological connectivity reveal distinct neural networks for facial expressions of basic emotions

The quest to characterize the neural signature distinctive of different basic emotions has recently come under renewed scrutiny. Here we investigated whether facial expressions of different basic emotions modulate the functional connectivity of the amygdala with the rest of the brain. To this end, we presented seventeen healthy participants (8 females) with facial expressions of anger, disgust, fear, happiness, sadness and emotional neutrality and analyzed amygdala’s psychophysiological interaction (PPI). In fact, PPI can reveal how inter-regional amygdala communications change dynamically depending on perception of various emotional expressions to recruit different brain networks, compared to the functional interactions it entertains during perception of neutral expressions. We found that for each emotion the amygdala recruited a distinctive and spatially distributed set of structures to interact with. These changes in amygdala connectional patters characterize the dynamic signature prototypical of individual emotion processing, and seemingly represent a neural mechanism that serves to implement the distinctive influence that each emotion exerts on perceptual, cognitive, and motor responses. Besides these differences, all emotions enhanced amygdala functional integration with premotor cortices compared to neutral faces. The present findings thus concur to reconceptualise the structure-function relation between brain-emotion from the traditional one-to-one mapping toward a network-based and dynamic perspective.

Intact hemisphere and corpus callosum compensate for visuomotor functions after early visual cortex damage.

Significance The brain is resilient to injury and the possibility to promote recovery rests with our ability to understand the nature of postlesional plasticity. After damage to the visual cortex some patients with clinical blindness still react to unseen stimuli with appropriate motor responses, a phenomenon known as “blindsight.” Our findings in one patient with early primary visual cortex damage suggest that this nonconscious visuomotor ability depends partly on the compensatory activity of the intact hemisphere, which can be dynamically recruited through the corpus callosum. Functional interactions between the damaged and intact hemisphere are subserved by changes in the underlying anatomical connections. These observations provide a framework for future investigations of functional recovery after brain damage and on mechanisms that mediate nonconscious abilities. Unilateral damage to the primary visual cortex (V1) leads to clinical blindness in the opposite visual hemifield, yet nonconscious ability to transform unseen visual input into motor output can be retained, a condition known as “blindsight.” Here we combined psychophysics, functional magnetic resonance imaging, and tractography to investigate the functional and structural properties that enable the developing brain to partly overcome the effects of early V1 lesion in one blindsight patient. Visual stimuli appeared in either the intact or blind hemifield and simple responses were given with either the left or right hand, thereby creating conditions where visual input and motor output involve the same or opposite hemisphere. When the V1-damaged hemisphere was challenged by incoming visual stimuli, or controlled manual responses to these unseen stimuli, the corpus callosum (CC) dynamically recruited areas in the visual dorsal stream and premotor cortex of the intact hemisphere to compensate for altered visuomotor functions. These compensatory changes in functional brain activity were paralleled by increased connections in posterior regions of the CC, where fibers connecting homologous areas of the parietal cortex course.

Looking for Neuroimaging Markers in Frontotemporal Lobar Degeneration Clinical Trials: A Multi-Voxel Pattern Analysis Study in Granulin Disease

In light of future pharmacological interventions, neuroimaging markers able to assess the response to treatment would be crucial. In Granulin (GRN) disease, preclinical data will prompt pharmacological trials in the future. Two main points need to be assessed: (1) to identify target regions in different disease stages and (2) to determine the most accurate functional and structural neuroimaging index to be used. To this aim, we have taken advantage of the multivariate approach of multi-voxel pattern analysis (MVPA) to explore the information of brain activity patterns in a cohort of GRN Thr272fs carriers at different disease stages (14 frontotemporal dementia (FTD) patients and 17 asymptomatic carriers) and a group of 33 healthy controls. We studied structural changes by voxel-based morphometry (VBM), functional connectivity by assessing salience, default mode, fronto-parietal, dorsal attentional, executive networks, and local connectivity by regional homogeneity, amplitude of low frequency fluctuations (ALFF), fractional ALFF (fALFF), degree centrality, and voxel-mirrored homotopic connectivity. In FTD patients with GRN mutation, the most predictive measure was VBM structural analysis, while in asymptomatic carriers the best predictor marker was the local connectivity measure (fALFF). Altogether, all indexes demonstrated fronto-temporo-parietal damage in GRN pathology, with widespread structural damage of fronto-parietal and temporal regions when disease is overt. MVPA could be of aid in identifying the most accurate neuroimaging marker for clinical trials. This approach was able to identify both the target region and the best neuroimaging approach, which would be specific in the different disease stages. Further studies are needed to simultaneously integrate multimodal indexes in a classifier able to trace the disease progression moving from preclinical to clinical stage of the disease.

Neurofunctional signature of hyperfamiliarity for unknown faces

Hyperfamiliarity for unknown faces is a rare selective disorder that consists of the disturbing and abnormal feeling of familiarity for unknown faces, while recognition of known faces is normal. In one such patient we investigated with a multimodal neuroimaging design the hitherto undescribed neural signature associated with hyperfamiliarity feelings. Behaviorally, signal detection methods revealed that the patient’s discrimination sensitivity between familiar and unfamiliar faces was significantly lower than that of matched controls, and her response criterion for familiarity decisions was significantly more liberal. At the neural level, while morphometric analysis and single-photon emission CT (SPECT) showed the atrophy and hypofunctioning of the left temporal regions, functional magnetic resonance imaging (fMRI) revealed that hyperfamiliarity feelings were selectively associated to enhanced activity in the right medial and inferior temporal cortices. We therefore characterize the neurofunctional signature of hyperfamiliarity for unknown faces as related to the loss of coordinated activity between the complementary face processing functions of the left and right temporal lobes.

Cerebellar clustering and functional connectivity during pain processing

The cerebellum has been traditionally considered a sensory-motor structure, but more recently has been related to other cognitive and affective functions. Previous research and meta-analytic studies suggested that it could be involved in pain processing. Our aim was to distinguish the functional networks subserved by the cerebellum during pain processing. We used functional magnetic resonance imaging (fMRI) on 12 subjects undergoing mechanical pain stimulation and resting state acquisition. For the analysis of data, we used fuzzy c-mean to cluster cerebellar activity of each participant during nociception. The mean time courses of the clusters were used as regressors in a general linear model (GLM) analysis to explore brain functional connectivity (FC) of the cerebellar clusters. We compared our results with the resting state FC of the same cluster and explored with meta-analysis the behavior profile of the FC networks. We identified three significant clusters: cluster V, involving the culmen and quadrangular lobules (vermis IV-V, hemispheres IV-V-VI); cluster VI, involving the posterior quadrangular lobule and superior semilunar lobule (hemisphere VI, crus 1, crus 2), and cluster VII, involving the inferior semilunar lobule (VIIb, crus1, crus 2). Cluster V was more connected during pain with sensory-motor areas, cluster VI with cognitive areas, and cluster VII with emotional areas. Our results indicate that during the application of mechanical punctate stimuli, the cerebellum is not only involved in sensory functions but also with areas typically associated with cognitive and affective functions. Cerebellum seems to be involved in various aspects of nociception, reflecting the multidimensionality of pain perception.

Node Detection Using High-Dimensional Fuzzy Parcellation Applied to the Insular Cortex

Several functional connectivity approaches require the definition of a set of regions of interest (ROIs) that act as network nodes. Different methods have been developed to define these nodes and to derive their functional and effective connections, most of which are rather complex. Here we aim to propose a relatively simple “one-step” border detection and ROI estimation procedure employing the fuzzy c-mean clustering algorithm. To test this procedure and to explore insular connectivity beyond the two/three-region model currently proposed in the literature, we parcellated the insular cortex of 20 healthy right-handed volunteers scanned in a resting state. By employing a high-dimensional functional connectivity-based clustering process, we confirmed the two patterns of connectivity previously described. This method revealed a complex pattern of functional connectivity where the two previously detected insular clusters are subdivided into several other networks, some of which are not commonly associated with the insular cortex, such as the default mode network and parts of the dorsal attentional network. Furthermore, the detection of nodes was reliable, as demonstrated by the confirmative analysis performed on a replication group of subjects.

Beyond the "Pain Matrix," inter-run synchronization during mechanical nociceptive stimulation.

Pain is a complex experience that is thought to emerge from the activity of multiple brain areas, some of which are inconsistently detected using traditional fMRI analysis. One hypothesis is that the traditional analysis of pain-related cerebral responses, by relying on the correlation of a predictor and the canonical hemodynamic response function (HRF)- the general linear model (GLM)- may under-detect the activity of those areas involved in stimulus processing that do not present a canonical HRF. In this study, we employed an innovative data-driven processing approach- an inter-run synchronization (IRS) analysis- that has the advantage of not establishing any pre-determined predictor definition. With this method we were able to evidence the involvement of several brain regions that are not usually found when using predictor-based analysis. These areas are synchronized during the administration of mechanical punctate stimuli and are characterized by a BOLD response different from the canonical HRF. This finding opens to new approaches in the study of pain imaging.