Schizophrenia is a severe mental illness characterized by alterations in processes that regulate both synaptic plasticity and functional connectivity between brain regions. Antipsychotics are the cornerstone of schizophrenia pharmacological treatment and, beyond occupying dopamine D2 receptors, can affect multiple molecular targets, pre- and postsynaptic sites, as well as intracellular effectors. Multiple lines of evidence point to the involvement of antipsychotics in sculpting synaptic architecture and remodeling the neuronal functional unit. Furthermore, there is an increasing awareness that antipsychotics with different receptor profiles could yield different interregional patterns of co-activation. In the present systematic review, we explored the fundamental changes that occur under antipsychotics’ administration, the molecular underpinning, and the consequences in both acute and chronic paradigms. In addition, we investigated the relationship between synaptic plasticity and functional connectivity and systematized evidence on different topographical patterns of activation induced by typical and atypical antipsychotics.

Background: Speech patterns in multiple sclerosis (MS) are poorly characterized. Software such as Dysarthria Analyzer (DA) performs a detailed speech analysis. Objective: The objective of the study is (1) to explore speech features in patients with MS and (2) to investigate correlations between speech features and clinic-demographic characteristics. Methods: Patients underwent clinical assessments (Expanded Disability Status Scale (EDSS) and Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS)) and speech evaluation using the DA. Each patient performed 6 vocal tasks: phonation A, phonation I, reading, monologue, fast syllables repetitions. The DA extracted 23 speech features as age-, gender-, and education-adjusted z-scores against healthy controls. A principal component analysis was conducted. Correlations between the components and clinic-demographic features were assessed through stepwise analysis. Results: We enrolled 72 patients (50 females; mean age 48.1 ± 10.9 years; median EDSS of 3 (1.5–6.5)). Principal component analysis (PCA) identified a 7-component model: Voice Intensity, Voice Intensity Variation, Motor Coordination, Speech Diadochokinesis, Speech Speed, Voice Strength, Speech Latency. Higher EDSS is associated with worse Voice Intensity Variation ( r = –0.23; p = 0.05), Speech Speed ( r = –0.40; p = 0.001) and Speech Latency ( r = –0.23; p = 0.05). Progressive MS patients showed worse Voice Intensity Variation (coeff. = −1.20; p = 0.002). Worse cognitive functioning correlated with worse Speech Speed (coeff. = −0.38; p = 0.02). Conclusion: Detailed speech analysis can reveal useful clinical information about physical and cognitive disability in MS possibly representing an additional tool to assess disability.