Giuseppe Rabini

Background: Apathy is a common early symptom of Parkinson's disease (PD), often co‐occurring with cognitive decline and associated with fronto‐striatal and mesocortico‐limbic dysfunctions. Discrepancies between self‐ and caregiver‐reported apathy have been preliminarily associated with cognitive impairments affecting patients’ awareness and self‐report accuracy. Objectives: This study investigates discrepancies between PD patient‐ and informant‐reported apathy in relation to the cognitive status (unimpaired‐CU vs. impaired‐CI), and explores neural correlates of apathy using magnetic resonance imaging (MRI). Methods: Apathy was assessed in 23 PD participants using self‐report (AES‐S) and informant (AES‐I) versions of the Italian Apathy Evaluation Scale. Discrepancy scores (ΔAES) were compared between groups and correlated with cognitive performance. Resting‐state fMRI examined associations between AES indices and connectivity from the bilateral nucleus accumbens, while whole‐brain structural analyses assessed associations with gray matter (GM) volume. Results: PD‐CI participants showed higher ΔAES, underestimating their apathy compared to PD‐CU. ΔAES values correlated with attentional and visuospatial functioning. Higher AES‐I scores were associated with hyperconnectivity between right nucleus accumbens, paracingulate, and medial frontal cortices. Structural analyses revealed associations between both AES‐I and ΔAES values and GM volume in the cingulate gyrus. Discussion: These findings highlight the impact of cognitive dysfunction on apathy evaluation in PD, emphasizing the importance of caregiver perspective. Neuroimaging results further validated caregiver ratings, showing an association between fronto‐striatal network changes and apathy. Further research is needed to clarify the role of such discrepancy in apathy assessment in predicting disease progression.

Recent studies have reported social cognitive deficits, particularly in emotional processing, in Parkinson's disease (PD). However, a comprehensive characterization of these deficits and their underlying neural correlates remains elusive. Therefore, this study aims to investigate the association between deficits in the recognition of complex mental states and structural/functional brain changes in non‐demented PD individuals. To reach this aim, 24 PD participants underwent clinical assessment, neuropsychological testing and the FAcial Complex Expressions (FACE) test, a novel test of complex mental state recognition from faces. Patients were classified as clinically impaired (n = 8) or unimpaired (n = 16) based on performance on this test. Magnetic resonance imaging data were acquired to investigate the association between FACE test performance and both resting‐state functional connectivity and grey matter volume, within the emotion understanding network and at the whole‐brain level. Statistical analyses also included the comparison of imaging metrics between the impaired and unimpaired groups. Results showed that complex mental state recognition in PD was significantly associated with both defective and compensatory mechanisms at the functional and anatomical level within the emotion understanding network, particularly involving the amygdala, dorsomedial prefrontal cortex, primary/secondary somatosensory cortices, and right anterior temporal cortex. Whole‐brain results extended the network to temporal and medial frontal areas. In conclusion, reduced recognition of complex mental states in non‐demented PD patients is associated with alterations in the emotion understanding network A comprehensive characterization of early emotional deficits in these patients may have significant implications in the characterization of the cognitive phenotype, with potential benefit for tailored non‐pharmacological intervention.

Pharmacological treatments in Parkinson’s disease (PD), albeit effective in alleviating many motor symptoms, have limited effects in non-motor signatures as cognitive impairment, as well as in other aspects included postural instability. Consequently, complementary interventions are nowadays a prerogative of clinical practice managing PD symptomatology. In this pilot longitudinal study, we recruited twenty-four PD patients participating in one of two interventions: adapted Argentine Tango or group-based physiotherapy. Participants underwent a motor and neuropsychological evaluation before and after four months of activities, carried out twice a week. We found a general stabilization of motor and cognitive abilities, with significant improvements in several motor skills, mainly pertaining to static and dynamic balance, similarly in both groups. At cognitive level, we measured a significant improvement in both groups in the Action Naming task. Interestingly, only PD patients in the Tango group improved their performance in the test measuring facial emotion recognition. These findings highlight the crucial role that physical activities have in the stabilization and slowdown of disease’s progression in PD. They further highlight the beneficial effects of a group-based physical intervention, which, especially in the case of Tango, could lead to behavioral ameliorations in domains other than the motor, such as emotion recognition.

Our ability to know and access complex factual information has far reaching effects, influencing our scholastic, professional and social lives. Here we employ functional MRI to assess the relationship between individual differences in semantic aptitude in the task-based activation and resting-state functional connectivity. Using psychometric and behavioural measures, we quantified the semantic and executive aptitude of individuals and had them perform a general-knowledge semantic-retrieval task (N = 41) and recorded resting-state data (N = 43). During the semantic-retrieval task, participants accessed general-knowledge facts drawn from four different knowledge-domains (people, places, objects and ‘scholastic’). Individuals with greater executive capacity more strongly recruit anterior sections of prefrontal cortex (PFC) and the precuneus, and individuals with lower semantic capacity more strongly activate a posterior section of the dorsomedial PFC (dmPFC). The role of these regions in semantic processing was validated by analysis of independent resting-state data, where increased connectivity between a left anterior PFC and the precuneus predict higher semantic aptitude, and increased connectivity between left anterior PFC and posterior dmPFC predict lower semantic aptitude. Results suggest that coordination between core semantic regions in the precuneus and anterior prefrontal regions associated with executive processes support greater semantic aptitude.

In Parkinson's disease (PD), impairment of Theory of Mind (ToM) has recently attracted an increasing number of neuroscientific investigations. If and how functional connectivity of the ToM network is altered in PD is still an open question. First, we explored whether ToM network connectivity shows potential PD-specific functional alterations when compared to healthy controls (HC). Second, we tested the role of the duration of PD in the evolution of functional alterations in the ToM network. Between-group connectivity alterations were computed adopting resting-state functional magnetic resonance imaging (rs-fMRI) data of four groups: PD patients with short disease duration (PD-1, n = 72); PD patients with long disease duration (PD-2, n = 22); healthy controls for PD-1 (HC-1, n = 69); healthy controls for PD-2 (HC-2, n = 22). We explored connectivity differences in the ToM network within and between its three subnetworks: Affective, Cognitive and Core. PD-1 presented a global pattern of decreased functional connectivity within the ToM network, compared to HC-1. The alterations mainly involved the Cognitive and Affective ToM subnetworks and their reciprocal connections. PD-2-those with longer disease duration-showed an increased connectivity spanning the entire ToM network, albeit less consistently in the Core ToM network, compared to both the PD-1 and the HC-2 groups. Functional connectivity within the ToM network is altered in PD. The alterations follow a graded pattern, with decreased connectivity at short disease duration, which broadens to a generalized increase with longer disease duration. The alterations involve both the Cognitive and Affective subnetworks of ToM.

Functional alterations in brain connectivity have previously been described in Parkinson’s disease, but it is not clear whether individual differences in connectivity profiles might be also linked to severity of motor-symptom manifestation. Here we investigated the relevance of individual functional connectivity patterns measured with resting-state fMRI with respect to motor-symptom severity in Parkinson’s disease, through a whole-brain, data-driven approach (connectome-based predictive modeling). Neuroimaging and clinical data of Parkinson’s disease patients from the Parkinson’s Progression Markers Initiative were derived at baseline (session 1, n = 81) and at follow-up (session 2, n = 53). Connectome-based predictive modeling protocol was implemented to predict levels of motor impairment from individual connectivity profiles. The resulting predictive model comprised a network mainly involving functional connections between regions located in the cerebellum, and in the motor and frontoparietal networks. The predictive power of the model was stable along disease progression, as the connectivity within the same network could predict levels of motor impairment, even at a later stage of the disease. Finally, connectivity profiles within this network could be identified at the individual level, suggesting the presence of individual fingerprints within resting-state fMRI connectivity associated with motor manifestations in Parkinson’s disease.

An open discussion in studies of intrinsic brain functional connectivity is the mitigation of head motion-related artifacts, particularly in the presence of peculiar symptomatology such as in Parkinson’s disease (PD). Previous studies show that Independent Component Analysis (ICA) denoising improves the reproducibility of functional connectivity findings by detecting sources of non-neural signals. However, there is still no consensus about which pre-processing pipeline should be applied in natural high motion populations such as PD, particularly in relation to novel functional network descriptions derived from dynamic connectivity analyses. In this study, we investigated how different pre-processing pipelines affect intrinsic brain connectivity metrics, both static and dynamic, derived from a group of young healthy controls (HC) and a group of PD participants. A total of 20 HC and 20 PD subjects participated in this 3 T MRI study. Resting-state functional MRI images were used to test the effects of the pre-processing pipeline of static (sFC) and temporal-varying functional connectivity (dFC) estimations. Both MRI datasets were pre-processed using three different workflows differing in the motion correction approach: (i) standard motion realignment ( mc ); (ii) motion outlier detection and deweighting based on image intensity change estimations ( DVARS ) and (iii) ICA-based noise removal using reference noise features ( AROMA ). Furthermore, the PD dataset was also processed with a fourth method by applying an ICA-based denoising ( FIX ), previously trained on the HC group. sFC analysis was performed using Group ICA, by temporally concatenating different pre-processing types in pairs of different runs. Two types of dFC analyses were considered: innovation-driven co-activation patterns (iCAPs) and co-activation patterns (CAPs). CAPs allow dFC estimations that do not require the deconvolution of the hemodynamic response function and its derivative, thus potentially being less sensitive to head-motion related noise. We found that regardless of substantial head motion differences in the two groups, sFC results were consistent across denoising strategies. Conversely, dFC was extremely sensitive to denoising strategies, particularly for the PD group with the transient-based dFC analyses. Indeed, the use of the peak-based dFC framework enables the detection of time-varying networks but in a way that is highly dependent on the motion correction pipeline. In conclusion, we show that dynamic functional network representations are highly sensitive to both head motion and to fMRI denoising methods. These findings stress the importance of considering and reporting these experimental aspects to help with the reproducibility and interpretation of different studies. Future work is needed to further investigate transient-based dFC strategies that are more robust to head motion.

The understanding of linguistic messages can be made extremely complex by the simultaneous presence of interfering sounds, especially when they are also linguistic in nature. In two experiments, we tested if visual cues directing attention to spatial or temporal components of speech in noise can improve its identification. The hearing-in-noise task required identification of a five-digit sequence (target) embedded in a stream of time-reversed speech. Using a custom-built device located in front of the participant, we delivered visual cues to orient attention to the location of target sounds and/or their temporal window. In Exp. 1 ( ), we validated this visual-to-auditory cueing method in normal-hearing listeners, tested under typical binaural listening conditions. In Exp. 2 ( ), we assessed the efficacy of the same visual cues in normal-hearing listeners wearing a monaural ear plug, to study the effects of simulated monaural and conductive hearing loss on visual-to-auditory attention orienting. While Exp. 1 revealed a benefit of both spatial and temporal visual cues for hearing in noise, Exp. 2 showed that only the temporal visual cues remained effective during monaural listening. These findings indicate that when the acoustic experience is altered, visual-to-auditory attention orienting is more robust for temporal compared to spatial attributes of the auditory stimuli. These findings have implications for the relation between spatial and temporal attributes of sound objects, and when planning devices to orient audiovisual attention for subjects suffering from hearing loss.

The human capacity for semantic knowledge entails not only the representation of single concepts but the capacity to combine these concepts into the increasingly complex ideas that underlie human thought. This process involves not only the combination of concepts from within the same semantic category but frequently the conceptual combination across semantic domains. In this fMRI study (N = 24) we investigate the cortical mechanisms underlying our ability to combine concepts across different semantic domains. Using five different semantic domains (People, Places, Food, Objects, and Animals), we present sentences depicting concepts drawn from a single semantic domain as well as sentences that combine concepts from two of these domains. Contrasting single-category and combined-category sentences reveals that the precuneus is more active when concepts from different domains have to be combined. At the same time, we observe that distributed category selectivity representations persist when higher-order meaning involves the combination of categories and that this category-selective response is captured by the combination of the single categories composing the sentence. Collectively, these results suggest that the precuneus plays a role in the combination of concepts across different semantic domains, potentially functioning to link together category-selective representations distributed across the cortex.

In early deaf individuals, the auditory deprived temporal brain regions become engaged in visual processing. In our study we tested further the hypothesis that intrinsic functional specialization guides the expression of cross-modal responses in the deprived auditory cortex. We used functional MRI to characterize the brain response to horizontal, radial and stochastic visual motion in early deaf and hearing individuals matched for the use of oral or sign language. Visual motion showed enhanced response in the ‘deaf’ mid-lateral planum temporale , a region selective to auditory motion as demonstrated by a separate auditory motion localizer in hearing people. Moreover, multivariate pattern analysis revealed that this reorganized temporal region showed enhanced decoding of motion categories in the deaf group, while visual motion-selective region hMT+/V5 showed reduced decoding when compared to hearing people. Dynamic Causal Modelling revealed that the ‘deaf’ motion-selective temporal region shows a specific increase of its functional interactions with hMT+/V5 and is now part of a large-scale visual motion selective network. In addition, we observed preferential responses to radial, compared to horizontal, visual motion in the ‘deaf’ right superior temporal cortex region that also show preferential response to approaching/receding sounds in the hearing brain. Overall, our results suggest that the early experience of auditory deprivation interacts with intrinsic constraints and triggers a large-scale reallocation of computational load between auditory and visual brain regions that typically support the multisensory processing of motion information. Highlights: Auditory motion-sensitive regions respond to visual motion in the deaf Reorganized auditory cortex can discriminate between visual motion trajectories Part of the deaf auditory cortex shows preference for in-depth visual motion Deafness might lead to computational reallocation between auditory/visual regions.