Anna Nigri

In medication-overuse headache, fMRI shows long-lasting dysfunction in midbrain areas.

The primary aim of our study was to evaluate if a group of medication‐overuse headache (MOH) patients present dysfunctions in the mesocorticolimbic dopamine circuit. The secondary aim was to disentangle the role of the medication overuse and of the acute/chronic headache in determining these alterations and to investigate their persistence.

Connectivity of the amygdala, piriform, and orbitofrontal cortex during olfactory stimulation: a functional MRI study.

The majority of existing functional MRI studies on olfactory perception have addressed the relationship between stimulus features and the intensity of activity in separate regions considered in isolation. However, anatomical studies as well as neurophysiological recordings in rats and insects suggest that odor features may also be represented in a sparse manner through the simultaneous activity of multiple cortical areas interacting as a network. Here, we aimed to map the interdependence of neural activity among regions of the human brain, representing functional connectivity, during passive smelling. Seventeen healthy participants were scanned while performing a blocked-design task alternating exposure to two unpleasant odorants and breathing fresh air. High efferent connectivity was detected for the piriform cortex and the amygdala bilaterally. By contrast, the medial orbitofrontal cortex was characterized by high afferent connectivity, notably in the absence of an overall change in the intensity of hemodynamic activity during olfactory stimulation. Our results suggest that, even in the context of an elementary task, information on olfactory stimuli is scattered by the amygdala and piriform cortex onto an anatomically sparse representation and then gathered and integrated in the medial orbitofrontal cortex.

Multimodal study of default-mode network integrity in disorders of consciousness

Understanding residual brain function in disorders of consciousness poses extraordinary challenges, and imaging examinations are needed to complement clinical assessment. The default‐mode network (DMN) is known to be dysfunctional, although correlation with level of consciousness remains controversial. We investigated DMN activity with resting‐state functional magnetic resonance imaging (rs‐fMRI), alongside its structural and metabolic integrity, aiming to elucidate the corresponding associations with clinical assessment.

Dysfunctional neural networks associated with impaired social interactions in early psychosis: an ICA analysis

The “default mode”, or baseline of brain function is a topic of great interest in schizophrenia research. Recent neuroimaging studies report that the symptoms of chronic schizophrenia subjects are associated with temporal frequency alterations as well as with the disruption of local spatial patterns in the default mode network (DMN). Previous studies both on chronic and medicated subjects with psychosis suffered from limitations; on this basis, it was hypothesized that the default mode network showed abnormal activation and connectivity in young and neuroleptic-naïve patients with first-episode psychosis. This study investigated emotional responses to pleasant and unpleasant/disgusting visual stimuli by a resting-state analysis of fMRI-data from 12 untreated first-episode psychosis patients with prevalently negative symptomatology versus 12 healthy subjects. We chose this experimental task to explore the functional link between default mode network and hedonic processing which has been proposed as a marker of cerebral dysfunction in psychotic disorder and implicated in its pathophysiology. Independent Component Analysis (ICA) was used to identify the default mode component. Both healthy and first-episode subjects showed significant spatial differences in the default mode network. In first-episode subjects, medial frontal hypoactivity and cerebellar hyperactivity were correlated with the severity of negative symptoms.

Frontal cortex BOLD signal changes in premanifest Huntington disease A possible fMRI biomarker

Objective: To identify a possible functional imaging biomarker sensitive to the earliest neural changes in premanifest Huntington disease (preHD), allowing early therapeutic approaches aimed at preventing or delaying clinical onset. Methods: Sixteen preHD and 18 healthy participants were submitted to anatomical acquisitions and functional MRI (fMRI) acquisitions during the execution of the exogenous covert orienting of attention task. Due to strong a priori hypothesis, all fMRI correlation analyses were restricted to the following: (1) the frontal oculomotor cortex identified by the means of a prosaccadic task, comprising frontal eye fields and supplementary frontal eye fields; and (2) the data collected during inhibition of return, a phenomenon occurring during the executed task. In preHD, multiple regression analysis was performed between fMRI data and the probability to develop the disease in the next 5 years (p5HD). Moreover, mean blood oxygen level–dependent (BOLD) signal changes in the frontal oculomotor cortex and striatal volumes were linearly correlated with p5HD. Results: In preHD, multiple regression analysis showed that clusters of activity strongly correlated with p5HD in the right frontal oculomotor cortex. Importantly, mean BOLD signal changes of this region correlated with p5HD (r2 = 0.52). Among the considered striatal volumes, a modest correlation (r2 = 0.29) was observed in the right putamen and p5HD. Conclusion: fMRI activations in the right-frontal oculomotor cortex during inhibition of return can be considered a possible functional imaging biomarker in preHD.

Detection of scale-freeness in brain connectivity by functional MRI: signal processing aspects and implementation of an open hardware co-processor.

An outstanding issue in graph-theoretical studies of brain functional connectivity is the lack of formal criteria for choosing parcellation granularity and correlation threshold. Here, we propose detectability of scale-freeness as a benchmark to evaluate time-series extraction settings. Scale-freeness, i.e., power-law distribution of node connections, is a fundamental topological property that is highly conserved across biological networks, and as such needs to be manifest within plausible reconstructions of brain connectivity. We demonstrate that scale-free network topology only emerges when adequately fine cortical parcellations are adopted alongside an appropriate correlation threshold, and provide the full design of the first open-source hardware platform to accelerate the calculation of large linear regression arrays.

The Coma Recovery Scale Modified Score: a new scoring system for the Coma Recovery Scale-revised for assessment of patients with disorders of consciousness.

The differential diagnosis between vegetative state and minimally conscious state is still complex and the development of an evaluation systems is one of the challenging tasks for researchers and professionals. The Coma Recovery Scale-revised is considered the gold standard for clinical/behavioral assessment and for the differential diagnosis of patients with disorder of consciousness. However, the scale presents some limitations in that (i) scores may partially overlap between different diagnoses and (ii) there is an underlying assumption that if a patient is able to show higher-level behaviors, he/she is also able to show lower-level responses. In the present study, a procedure to calculate a modified Coma Recovery Scale-revised score is presented that attempts to avoid these problems. To exemplify this new scoring approach, 60 patients with disorder of consciousness were studied and the results showed the usefulness of the Modified Score.

A Neural Network Approach to fMRI Binocular Visual Rivalry Task Analysis

The purpose of this study was to investigate whether artificial neural networks (ANN) are able to decode participants’ conscious experience perception from brain activity alone, using complex and ecological stimuli. To reach the aim we conducted pattern recognition data analysis on fMRI data acquired during the execution of a binocular visual rivalry paradigm (BR). Twelve healthy participants were submitted to fMRI during the execution of a binocular non-rivalry (BNR) and a BR paradigm in which two classes of stimuli (faces and houses) were presented. During the binocular rivalry paradigm, behavioral responses related to the switching between consciously perceived stimuli were also collected. First, we used the BNR paradigm as a functional localizer to identify the brain areas involved the processing of the stimuli. Second, we trained the ANN on the BNR fMRI data restricted to these regions of interest. Third, we applied the trained ANN to the BR data as a ‘brain reading’ tool to discriminate the pattern of neural activity between the two stimuli. Fourth, we verified the consistency of the ANN outputs with the collected behavioral indicators of which stimulus was consciously perceived by the participants. Our main results showed that the trained ANN was able to generalize across the two different tasks (i.e. BNR and BR) and to identify with high accuracy the cognitive state of the participants (i.e. which stimulus was consciously perceived) during the BR condition. The behavioral response, employed as control parameter, was compared with the network output and a statistically significant percentage of correspondences (p-value <0.05) were obtained for all subjects. In conclusion the present study provides a method based on multivariate pattern analysis to investigate the neural basis of visual consciousness during the BR phenomenon when behavioral indicators lack or are inconsistent, like in disorders of consciousness or sedated patients.

Resting state fMRI in cluster headache: which role?

The pathophysiology of cluster headache (CH) is not well-known. For several years, the most widely accepted theory was that CH was triggered by hypothalamus with secondary activation of the trigeminal-autonomic reflex. However, it was recently suggested that the posterior hypothalamus might be an actor of the pain modulating network more involved in terminating rather than triggering attacks. To investigate this hypothesis, resting state fMRI could provide valuable information on functional connectivity between brainstem and hypothalamus, as well as other brain structures that could be involved in CH pathophysiology. In this framework, here we review recent studies investigating functional connectivity by means of resting state fMRI. Despite the important findings of these studies, we suggest that important steps in the comprehension of CH pathophysiology will be done when the scientific community will use the new methodological approaches recently suggested to study functional connectivity in the brainstem.

Sleep patterns associated with the severity of impairment in a large cohort of patients with chronic disorders of consciousness

OBJECTIVE We assessed sleep patterns in 85 patients with chronic disorders of consciousness (DOC) in order to reveal any relationship with the degree of the impairment. METHODS Nocturnal polysomnography (PSG) was scored in patients classified as being in an unresponsive wakefulness syndrome/vegetative state (UWS/VS; n = 49) or a minimally conscious state (MCS; n = 36) in accordance with the rules of the American Academy of Sleep Medicine. The PSG data in the two diagnostic groups were compared, and the PSG parameters associated with the degree of impairment were analysed. RESULTS In 19/49 UWS/VS patients, signal attenuation was the only EEG pattern detectable in sleep. Non-REM 2 (NREM2) and slow-wave sleep (SWS) (but not REM) stages were more frequent in the MCS patients. The presence of SWS was the most appropriate factor for classifying patients as UWS/VS or MCS, and the duration of SWS was the main factor that significantly correlated with revised Coma Recovery Scale scores. CONCLUSION The presence of NREM sleep (namely SWS) reflects better preservation of the circuitry and structures needed to sustain this stage of sleep in DOC patients. SIGNIFICANCE PSG is a simple and effective technique, and sleep patterns may reflect the degree of impairment in chronic DOC patients.