Functional Connectivity of Language-Related Cerebellar Regions Is Reduced in Schizophrenia Patients.

Schizophrenia (SZ) is a widespread psychiatric disorder that is traditionally characterized by positive and negative symptoms. However, recent focus has shifted to cognitive deficits as a crucial aspect. The cerebellum, conventionally tied to motor coordination, is now recognized as pivotal in the pathophysiology of SZ cognitive impairments. Proposed disruptions in the cortico-cerebellar-thalamic-cortico circuit contribute to these deficits. Despite evidence of cerebellar abnormalities, within-cerebellum functional connectivity is often overlooked. This study explores spontaneous functional interactions within the cerebellum and their link to cognitive deficits in SZ. Using a multi-domain task battery (MDTB) parcellation, fMRI data from SZ patients and healthy controls were analyzed. Significant differences in cerebellar connectivity emerged, particularly in regions related to attention, language, and memory processing. Correlations between connectivity values and SZ symptomatology were identified. A post hoc analysis, considering the patients' hallucination vulnerability, revealed distinct connectivity patterns. Non-hallucinating and low-hallucinating SZ patients exhibited higher cerebellar connectivity than high-hallucinating patients, especially in language and motor control regions. These findings suggest a gradient of cerebellar connectivity alterations corresponding to hallucination vulnerability in SZ patients. This study offers novel insights into cerebellar impairments in SZ, highlighting the role of within-cerebellum connectivity in cognitive deficits. The observed connectivity patterns in language-related regions contribute to understanding language development and auditory verbal hallucinations in SZ.

Motor imagery ability scores are related to cortical activation during gait imagery.

Motor imagery (MI) is the mental execution of actions without overt movements that depends on the ability to imagine. We explored whether this ability could be related to the cortical activity of the brain areas involved in the MI network. To this goal, brain activity was recorded using high-density electroencephalography in nineteen healthy adults while visually imagining walking on a straight path. We extracted Event-Related Desynchronizations (ERDs) in the θ, α, and ß band, and we measured MI ability via (i) the Kinesthetic and Visual Imagery Questionnaire (KVIQ), (ii) the Vividness of Movement Imagery Questionnaire-2 (VMIQ), and (iii) the Imagery Ability (IA) score. We then used Pearson's and Spearman's coefficients to correlate MI ability scores and average ERD power (avgERD). Positive correlations were identified between VMIQ and avgERD of the middle cingulum in the ß band and with avgERD of the left insula, right precentral area, and right middle occipital region in the θ band. Stronger activation of the MI network was related to better scores of MI ability evaluations, supporting the importance of testing MI ability during MI protocols. This result will help to understand MI mechanisms and develop personalized MI treatments for patients with neurological dysfunctions.

Neural correlates of transfer of learning in motor coordination tasks: role of inhibitory and excitatory neurometabolites.

We aimed to investigate transfer of learning, whereby previously acquired skills impact new task learning. While it has been debated whether such transfer may yield positive, negative, or no effects on performance, very little is known about the underlying neural mechanisms, especially concerning the role of inhibitory (GABA) and excitatory (Glu) (measured as Glu + glutamine (Glx)) neurometabolites, as measured by magnetic resonance spectroscopy (MRS). Participants practiced a bimanual coordination task across four days. The Experimental group trained a task variant with the right hand moving faster than the left (Task A) for three days and then switched to the opposite variant (Task B) on Day4. The control group trained Task B across four days. MRS data were collected before, during, and after task performance on Day4 in the somatosensory (S1) and visual (MT/V5) cortex. Results showed that both groups improved performance consistently across three days. On Day4, the Experimental group experienced performance decline due to negative task transfer while the control group continuously improved. GABA and Glx concentrations obtained during task performance showed no significant group-level changes. However, individual Glx levels during task performance correlated with better (less negative) transfer performance. These findings provide a first window into the neurochemical mechanisms underlying task transfer.

Frequency-dependent connectivity in large-scale resting-state brain networks during sleep.

Functional connectivity (FC) during sleep has been shown to break down as non-rapid eye movement (NREM) sleep deepens before returning to a state closer to wakefulness during rapid eye movement (REM) sleep. However, the specific spatial and temporal signatures of these fluctuations in connectivity patterns remain poorly understood. This study aimed to investigate how frequency-dependent network-level FC fluctuates during nocturnal sleep in healthy young adults using high-density electroencephalography (hdEEG). Specifically, we examined source-localized FC in resting-state networks during NREM2, NREM3 and REM sleep (sleep stages scored using a semi-automatic procedure) in the first three sleep cycles of 29 participants. Our results showed that FC within and between all resting-state networks decreased from NREM2 to NREM3 sleep in multiple frequency bands and all sleep cycles. The data also highlighted a complex modulation of connectivity patterns during the transition to REM sleep whereby delta and sigma bands hosted a persistence of the connectivity breakdown in all networks. In contrast, a reconnection occurred in the default mode and the attentional networks in frequency bands characterizing their organization during wake (i.e., alpha and beta bands, respectively). Finally, all network pairs (except the visual network) showed higher gamma-band FC during REM sleep in cycle three compared to earlier sleep cycles. Altogether, our results unravel the spatial and temporal characteristics of the well-known breakdown in connectivity observed as NREM sleep deepens. They also illustrate a complex pattern of connectivity during REM sleep that is consistent with network- and frequency-specific breakdown and reconnection processes.

Baseline GABA+ levels in areas associated with sensorimotor control predict initial and long-term motor learning progress.

Synaptic plasticity relies on the balance between excitation and inhibition in the brain. As the primary inhibitory and excitatory neurotransmitters, gamma-aminobutyric acid (GABA) and glutamate (Glu), play critical roles in synaptic plasticity and learning. However, the role of these neurometabolites in motor learning is still unclear. Furthermore, it remains to be investigated which neurometabolite levels from the regions composing the sensorimotor network predict future learning outcome. Here, we studied the role of baseline neurometabolite levels in four task-related brain areas during different stages of motor skill learning under two different feedback (FB) conditions. Fifty-one healthy participants were trained on a bimanual motor task over 5 days while receiving either concurrent augmented visual FB (CA-VFB group, N = 25) or terminal intrinsic visual FB (TA-VFB group, N = 26) of their performance. Additionally, MRS-measured baseline GABA+ (GABA + macromolecules) and Glx (Glu + glutamine) levels were measured in the primary motor cortex (M1), primary somatosensory cortex (S1), dorsolateral prefrontal cortex (DLPFC), and medial temporal cortex (MT/V5). Behaviorally, our results revealed that the CA-VFB group outperformed the TA-VFB group during task performance in the presence of augmented VFB, while the TA-VFB group outperformed the CA-VFB group in the absence of augmented FB. Moreover, baseline M1 GABA+ levels positively predicted and DLPFC GABA+ levels negatively predicted both initial and long-term motor learning progress in the TA-VFB group. In contrast, baseline S1 GABA+ levels positively predicted initial and long-term motor learning progress in the CA-VFB group. Glx levels did not predict learning progress. Together, these findings suggest that baseline GABA+ levels predict motor learning capability, yet depending on the FB training conditions afforded to the participants.

fMRI fluctuations within the language network are correlated with severity of hallucinatory symptoms in schizophrenia.

Although schizophrenia (SZ) represents a complex multiform psychiatric disorder, one of its most striking symptoms are auditory verbal hallucinations (AVH). While the neurophysiological origin of this pervasive symptom has been extensively studied, there is so far no consensus conclusion on the neural correlates of the vulnerability to hallucinate. With a network-based fMRI approach, following the hypothesis of altered hemispheric dominance (Crow, 1997), we expected that LN alterations might result in self-other distinction impairments in SZ patients, and lead to the distressing subjective experiences of hearing voices. We used the independent component analysis of resting-state fMRI data, to first analyze LN connectivity in three groups of participants: SZ patients with and without hallucinations (AVH/D+ and AVH/D-, respectively), and a matched healthy control (HC) group. Then, we assessed the fMRI fluctuations using additional analyses based on fractional Amplitude of Low Frequency-Fluctuations (fALFF), both at the network- and region of interest (ROI)-level. Specific LN nodes were recruited in the right hemisphere (insula and Broca homologous area) for AVH/D+ , but not for HC and AVH/D-, consistent with a left hemisphere deficit in AVH patients. The fALFF analysis at the ROI level showed a negative correlation between fALFF Slow-4 and P1 Delusions PANSS subscale and a positive correlation between the fALFF Slow-5 and P3 Hallucination PANSS subscale for AVH/D+ only. These effects were not a consequence of structural differences between groups, as morphometric analysis did not evidence any group differences. Given the role of language as an emerging property resulting from the integration of many high-level cognitive processes and the underlying cortical areas, our results suggest that LN features from fMRI connectivity and fluctuations can be a marker of neurophysiological features characterizing SZ patients depending on their vulnerability to hallucinate.

Monitoring Resistance Training in Real Time with Wearable Technology: Current Applications and Future Directions.

Resistance training is an exercise modality that involves using weights or resistance to strengthen and tone muscles. It has become popular in recent years, with numerous people including it in their fitness routines to ameliorate their strength, muscle mass, and overall health. Still, resistance training can be complex, requiring careful planning and execution to avoid injury and achieve satisfactory results. Wearable technology has emerged as a promising tool for resistance training, as it allows monitoring and adjusting training programs in real time. Several wearable devices are currently available, such as smart watches, fitness trackers, and other sensors that can yield detailed physiological and biomechanical information. In resistance training research, this information can be used to assess the effectiveness of training programs and identify areas for improvement. Wearable technology has the potential to revolutionize resistance training research, providing new insights and opportunities for developing optimized training programs. This review examines the types of wearables commonly used in resistance training research, their applications in monitoring and optimizing training programs, and the potential limitations and challenges associated with their use. Finally, it discusses future research directions, including the development of advanced wearable technologies and the integration of artificial intelligence in resistance training research.

Neural oscillations modulation during working memory in pre-manifest and early Huntington's disease.

INTRODUCTION: We recently demonstrated specific spectral signatures associated with updating of memory information, working memory (WM) maintenance and readout, with relatively high spatial resolution by means of high-density electroencephalography (hdEEG). WM is impaired already in early symptomatic HD (early-HD) and in pre-manifest HD (pre-HD). The aim of this study was to test whether hdEEG coupled to source localization allows for the identification of neuronal oscillations in specific frequency bands in 16 pre-HD and early-HD during different phases of a WM task. METHODS: We examined modulation of neural oscillations by event-related synchronization and desynchronization (ERS/ERD) of θ, ß, gamma low, γLOW and γHIGH EEG bands in a-priori selected large fronto-parietal network, including the insula and the cerebellum. RESULTS: We found: (i) Reduced θ oscillations in HD with respect to controls in almost all the areas of the WM network during the update and readout phases; (ii) Modulation of ß oscillations, which increased during the maintenance phase of the WM task in both groups; (iii) correlation of γHIGH oscillations during WM task with disease burden score in HD patients. CONCLUSIONS: Our data show reduced phase-specific modulation of oscillations in pre-HD and early-HD, even in the presence of preserved dynamic of modulation. Particularly, reduced synchronization in the θ band in the areas of the WM network, consistent with abnormal long-range coordination of neuronal activity within this network, was found in update and readout phases in HD groups.

Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach.

Background: Stroke is a debilitating disease affecting millions of people worldwide. Despite the survival rate has significantly increased over the years, many stroke survivors are left with severe impairments impacting their quality of life. Rehabilitation programs have proved to be successful in improving the recovery process. However, a reliable model of sensorimotor recovery and a clear identification of predictive markers of rehabilitation-induced recovery are still needed. This article introduces the cross-modality protocols designed to investigate the rehabilitation treatment's effect in a group of stroke survivors. Methods/design: A total of 75 stroke patients, admitted at the IRCCS San Camillo rehabilitation Hospital in Venice (Italy), will be included in this study. Here, we describe the rehabilitation programs, clinical, neuropsychological, and physiological/imaging [including electroencephalography (EEG), transcranial magnetic stimulation (TMS), and magnetic resonance imaging (MRI) techniques] protocols set up for this study. Blood collection for the characterization of predictive biological biomarkers will also be taken. Measures derived from data acquired will be used as candidate predictors of motor recovery. Discussion/summary: The integration of cutting-edge physiological and imaging techniques, with clinical and cognitive assessment, dose of rehabilitation and biological variables will provide a unique opportunity to define a predictive model of recovery in stroke patients. Taken together, the data acquired in this project will help to define a model of rehabilitation induced sensorimotor recovery, with the final aim of developing personalized treatments promoting the greatest chance of recovery of the compromised functions.

Language Network Connectivity of Euthymic Bipolar Patients Is Altered at Rest and during a Verbal Fluency Task.

Abnormalities of the Language Network (LN) have been found in different psychiatric conditions (e.g., schizophrenia and bipolar disorder), supporting the hypothesis that language plays a central role in a high-level integration/connectivity of second-level cognitive processes and the underlying cortical regions. This view implies a continuum of shared neural alterations along the psychotic disorder spectrum. In particular, bipolar disorder (BD) patients were recently documented to have an altered LN asymmetry during resting state. The extent to which the LN architecture is altered and stable also during a language task has yet to be investigated. To address this question, we analyzed fMRI data recorded during an open-eyes resting state session and a silent verbal fluency task in 16 euthymic BD patients and 16 matched healthy controls (HC). Functional connectivity in the LN of both groups was computed using spatial independent component analysis, and group comparisons were carried out to assess the network organization during both rest and active linguistic task conditions. The LN of BD patients involved left and right brain areas during both resting state and linguistic task. Compared to the left-lateralized network found in HC, the BD group was characterized by two anterior clusters (in left frontal and right temporo-insular regions) and the disengagement of the posterior language areas, especially during the verbal fluency task. Our findings support the hypothesis that reduced language lateralization may represent a biological marker across different psychotic disorders and that the altered language network connectivity found at rest in bipolar patients is stable and pervasive as it is also impaired during a verbal fluency task.

Education differentiates cognitive performance and resting state fMRI connectivity in healthy aging.

Objectives: In healthy aging, the way people cope differently with cognitive and neural decline is influenced by exposure to cognitively enriching life-experiences. Education is one of them, so that in general, the higher the education, the better the expected cognitive performance in aging. At the neural level, it is not clear yet how education can differentiate resting state functional connectivity profiles and their cognitive underpinnings. Thus, with this study, we aimed to investigate whether the variable education allowed for a finer description of age-related differences in cognition and resting state FC. Methods: We analyzed in 197 healthy individuals (137 young adults aged 20-35 and 60 older adults aged 55-80 from the publicly available LEMON database), a pool of cognitive and neural variables, derived from magnetic resonance imaging, in relation to education. Firstly, we assessed age-related differences, by comparing young and older adults. Then, we investigated the possible role of education in outlining such differences, by splitting the group of older adults based on their education. Results: In terms of cognitive performance, older adults with higher education and young adults were comparable in language and executive functions. Interestingly, they had a wider vocabulary compared to young adults and older adults with lower education. Concerning functional connectivity, the results showed significant age- and education-related differences within three networks: the Visual-Medial, the Dorsal Attentional, and the Default Mode network (DMN). For the DMN, we also found a relationship with memory performance, which strengthen the evidence that this network has a specific role in linking cognitive maintenance and FC at rest in healthy aging. Discussion: Our study revealed that education contributes to differentiating cognitive and neural profiles in healthy older adults. Also, the DMN could be a key network in this context, as it may reflect some compensatory mechanisms relative to memory capacities in older adults with higher education.

White matter and neurochemical mechanisms underlying age-related differences in motor processing speed.

Aging is associated with changes in the central nervous system and leads to reduced life quality. Here, we investigated the age-related differences in the CNS underlying motor performance deficits using magnetic resonance spectroscopy and diffusion MRI. MRS measured N-acetyl aspartate (NAA), choline (Cho), and creatine (Cr) concentrations in the sensorimotor and occipital cortex, whereas dMRI quantified apparent fiber density (FD) in the same voxels to evaluate white matter microstructural organization. We found that aging was associated with increased reaction time and reduced FD and NAA concentration in the sensorimotor voxel. Both FD and NAA mediated the association between age and reaction time. The NAA concentration was found to mediate the association between age and FD in the sensorimotor voxel. We propose that the age-related decrease in NAA concentration may result in reduced axonal fiber density in the sensorimotor cortex which may ultimately account for the response slowness of older participants.

Are Motor Imagery Ability scores related to cortical activity during gait imagery?

Motor imagery (MI) is the mental execution of actions without overt movements that depends on the ability to imagine. We explored whether this ability could be related to the cortical activity of the brain areas involved in the MI network. To this goal, brain activity was recorded using high-density electroencephalography (hdEEG) in nineteen healthy adults while visually imagining walking on a straight path. We extracted Event-Related Desynchronizations (ERDs) in the ß band, and we measured MI ability via (i) the Kinesthetic and Visual Imagery Questionnaire (KVIQ), (ii) the Vividness of Movement Imagery Questionnaire-2 (VMIQ), and (iii) the Imagery Ability (IA) score. We then used Pearson's and Spearman's coefficients to correlate MI ability scores and average ERD power (avgERD). VMIQ was positively correlated with avgERD of frontal and cingulate areas, whereas IA SCORE was positively correlated with avgERD of left inferior frontal and superior temporal regions. Stronger activation of the MI network was related to better scores of MI ability evaluations, supporting the importance of testing MI ability during MI protocols. This result will help to understand MI mechanisms and develop personalized MI treatments for patients with neurological dysfunctions.

Task matters: Individual MEG signatures from naturalistic and neurophysiological brain states.

The discovery that human brain connectivity data can be used as a "fingerprint" to identify a given individual from a population, has become a burgeoning research area in the neuroscience field. Recent studies have identified the possibility to extract these brain signatures from the temporal rich dynamics of resting-state magneto encephalography (MEG) recordings. Nevertheless, it is still uncertain to what extent MEG signatures can serve as an indicator of human identifiability during task-related conduct. Here, using MEG data from naturalistic and neurophysiological tasks, we show that identification improves in tasks relative to resting-state, providing compelling evidence for a task dependent axis of MEG signatures. Notably, improvements in identifiability were more prominent in strictly controlled tasks. Lastly, the brain regions contributing most towards individual identification were also modified when engaged in task activities. We hope that this investigation advances our understanding of the driving factors behind brain identification from MEG signals.

Organization of neurochemical interactions in young and older brains as revealed with a network approach: Evidence from proton magnetic resonance spectroscopy (1H-MRS).

Aging is associated with alterations in the brain including structural and metabolic changes. Previous research has focused on neurometabolite level differences associated to age in a variety of brain regions, but the relationship among metabolites across the brain has been much less studied. Investigating these relationships can reveal underlying neurometabolic processes, their interdependency, and their progress throughout the lifespan. Using 1H-MRS, we investigated the relationship among metabolite concentrations of N-acetylaspartate (NAA), creatine (Cr), choline (Cho), myo-Inositol (mIns) and glutamate-glutamine complex (Glx) in seven voxel locations, i.e., bilateral sensorimotor cortex, bilateral striatum, pre-supplementary motor area, right inferior frontal gyrus and occipital cortex. These measurements were performed on 59 human participants divided in two age groups: young adults (YA: 23.2 ± 4.3; 18-34 years) and older adults (OA: 67.5 ± 3.9; 61-74 years). Our results showed age-related differences in NAA, Cho, and mIns across brain regions, suggesting the presence of neurodegeneration and altered gliosis. Moreover, associative patterns among NAA, Cho and Cr were observed across the selected brain regions, which differed between young and older adults. Whereas most of metabolite concentrations were inhomogeneous across different brain regions, Cho levels were shown to be strongly related across brain regions in both age groups. Finally, we found metabolic associations between homologous brain regions (SM1 and striatum) in the OA group, with NAA showing a significant correlation between bilateral sensorimotor cortices (SM1) and mIns levels being correlated between the bilateral striata. We posit that a network perspective provides important insights regarding the potential interactions among neurochemicals underlying metabolic processes at a local and global level and their relationship with aging.

Intrinsic functional clustering of the macaque insular cortex.

The functional organization of the primate insula has been studied using a variety of techniques focussing on regional differences in either architecture, connectivity, or function. These complementary methods offered insights into the complex organization of the insula and proposed distinct parcellation schemes at varying levels of detail and complexity. The advent of imaging techniques that allow non-invasive assessment of structural and functional connectivity, has popularized data-driven connectivity-based parcellation methods to investigate the organization of the human insula. Yet, it remains unclear if the subdivisions derived from these data-driven clustering methods reflect meaningful descriptions of the functional specialization of the insula. In this study, we employed hierarchical clustering to examine the cluster parcellations of the macaque insula. As our aim was exploratory, we examined parcellations consisting of two up to ten clusters. Three different cluster validation methods (fingerprinting, silhouette, elbow) converged on a four-cluster solution as the most optimal representation of our data. Examining functional response properties of these clusters, in addition to their brain-wide functional connectivity suggested a functional specialization related to processing gustatory, somato-motor, vestibular and social visual cues. However, a more detailed functional differentiation aligning with previous functional investigations of insula subfields became evident at higher cluster numbers beyond the proposed optimal four clusters. Overall, our findings demonstrate that resting-state-based hierarchical clustering can provide a meaningful description of the insula's functional organization at some level of detail. Nonetheless, cluster parcellations derived from this method are best combined with data obtained through other modalities, to provide a more comprehensive and detailed account of the insula's complex functional organization.

Cannabidiol and brain function: current knowledge and future perspectives.

Cannabidiol (CBD) is a naturally occurring non-psychoactive cannabinoid found in Cannabis sativa, commonly known as cannabis or hemp. Although currently available CBD products do not meet the safety standards of most food safety authorities to be approved as a dietary supplement or food additive, CBD has been gaining widespread attention in recent years due to its various potential health benefits. While primarily known for its therapeutic effects in managing epileptic seizures, psychosis, anxiety, (neuropathic) pain, and inflammation, CBD's influence on brain function has also piqued the interest of researchers and individuals seeking to enhance cognitive performance. The primary objective of this review is to gather, synthesize, and consolidate scientifically proven evidence on the impact of CBD on brain function and its therapeutic significance in treating neurological and mental disorders. First, basic background information on CBD, including its biomolecular properties and mechanisms of action is presented. Next, evidence for CBD effects in the human brain is provided followed by a discussion on the potential implications of CBD as a neurotherapeutic agent. The potential effectiveness of CBD in reducing chronic pain is considered but also in reducing the symptoms of various brain disorders such as epilepsy, Alzheimer's, Huntington's and Parkinson's disease. Additionally, the implications of using CBD to manage psychiatric conditions such as psychosis, anxiety and fear, depression, and substance use disorders are explored. An overview of the beneficial effects of CBD on aspects of human behavior, such as sleep, motor control, cognition and memory, is then provided. As CBD products remain largely unregulated, it is crucial to address the ethical concerns associated with their use, including product quality, consistency, and safety. Therefore, this review discusses the need for responsible research and regulation of CBD to ensure its safety and efficacy as a therapeutic agent for brain disorders or to stimulate behavioral and cognitive abilities of healthy individuals.

Persistence of hippocampal and striatal multivoxel patterns during awake rest after motor sequence learning.

Memory consolidation, the process by which newly encoded and fragile memories become more robust, is thought to be supported by the reactivation of brain regions - including the hippocampus - during post-learning rest. While hippocampal reactivations have been demonstrated in humans in the declarative memory domain, it remains unknown whether such a process takes place after motor learning. Using multivariate analyses of task-related and resting state fMRI data, here we show that patterns of brain activity within both the hippocampus and striatum elicited during motor learning persist into post-learning rest, indicative of the reactivation of learning-related neural activity patterns. Moreover, results indicate that hippocampal reactivation reflects the spatial representation of the learned motor sequence. These results thus provide insights into the functional significance of neural reactivation after motor sequence learning.

Altered language network lateralization in euthymic bipolar patients: a pilot study.

Bipolar patients (BD) in the euthymic phase show almost no symptoms, nevertheless possibility of relapse is still present. We expected to find a psychobiological trace of their vulnerability by analyzing a specific network-the Language Network (LN)-connecting many high-level processes and brain regions measured at rest. According to Crow's hypothesis on the key role of language in the origin of psychoses, we expected an altered asymmetry of the LN in euthymic BDs. Eighteen euthymic BD patients (10 females; age = 54.50 ± 11.38 years) and 16 healthy controls (HC) (8 females; age = 51.16 ± 11.44 years) underwent a functional magnetic resonance imaging scan at rest. The LN was extracted through independent component analysis. Then, LN time series was used to compute the fractional amplitude of the low-frequency fluctuation (fALFF) index, which was then correlated with clinical scales. Compared with HC, euthymic patients showed an altered LN with greater activation of Broca's area right homologous and anterior insula together with reduced activation of left middle temporal gyrus. The normalized fALFF analysis on BD patients' LN time series revealed that the Slow-5 fALFF band was positively correlated with residual mania symptoms but negatively associated with depression scores. In line with Crow's hypothesis postulating an altered language hemispheric asymmetry in psychoses, we revealed, in euthymic BD patients, a right shift involving both the temporal and frontal linguistic hubs. The fALFF applied to LN allowed us to highlight a number of significant correlations of this measure with residual mania and depression psychiatric symptoms.

Default mode network alterations underlie auditory verbal hallucinations in schizophrenia.

Although alterations of the default mode network (DMN) in schizophrenia (SZ) have been largely investigated, less research has been carried out on DMN alterations in different sub-phenotypes of this disorder. The aim of this pilot study was to compare DMN features among SZ patients with and without auditory verbal hallucinations (AVH). Three groups of 17 participants each were considered: patients with hallucinations (AVH-SZ), patients without hallucinations (nAVH-SZ) and age-matched healthy controls (HC). The DMN spatial pattern was similar between the nAVH-SZ and HC, but the comparison between these two groups and the AVH-SZ group revealed alterations in the left Angular Gyrus (lAG) node of the DMN. Using a novel approach based on normalized fractional Amplitude of Low-Frequency Fluctuations (fALFF), the AVH-SZ subgroup showed altered spectral activity in the DMN compared with the other two groups, especially in the lower-frequency bands (0.017-0.04 Hz). Significant positive correlations were found for both SZ groups collapsed, and for the nAVH-SZ group alone between delusional scores (PANSS-P1) and slow fALFF bands of the DMN. Narrowing the analysis to the ROI centered on the lAG, significant correlations were found in the AVH-SZ group for hallucination scores (PANSS-P3) and Slow-5 and Slow-4 (both positive), and Slow-3 (negative) fALFF bands. Our results reveal the central role of the lAG in relation to hallucinations, an important cortical area connecting auditory cortex with several hubs (including frontal linguistic centers) and involved in auditory process monitoring.