Brain plasticity in aphasic patients: intra- and inter-hemispheric reorganisation of the whole linguistic network probed by N150 and N350 components

A Novel Approach for Aphasia Evaluation Based on ROI-Based Features From Structural Magnetic Resonance Image

Aphasia, affecting one-third of stroke survivors, impairs language comprehension and speech production, leading to challenges in daily interactions, social isolation, and economic losses. Assessing aphasia is crucial for effective rehabilitation and recovery in patients. However, the conventional behavioral-based evaluation, reliant on speech pathologists, is susceptible to individual variability, resulting in high labor costs, time-consuming processes, and low robustness. To address these limitations, this study introduces a novel evaluation method based on medical image processing and artificial intelligence. Magnetic resonance imaging (MRI) provides exceptional spatial resolution while mitigating the impact of individual variability. The image processing techniques were employed to extract pathological features, specifically region-of-interest (ROI)-based features. Subsequently, the evaluation models were trained using ROI-based features which initially identify the occurrence of aphasia and then categorize the type of aphasia, aiding clinicians in tailoring treatment to various therapeutic approaches and intensities. The evaluation models also predict the severity and generate scores for four types of language function: spontaneous speech, auditory comprehension, naming, and repetition. Both aphasia occurrence detection and aphasia type classification attain impressive accuracy rates of 100.00 $\pm$ 0.00% and 85.00 $\pm$ 13.23%, respectively. The severity prediction yields the lowest root mean square error (RMSE) of 17.03 $\pm$ 2.75, while the assessment of four language functions achieves the best RMSE of 1.27 $\pm$ 0.82. Utilising the advantages of a medical imaging-based automation approach, the proposed aphasia evaluation method provides a comprehensive procedure and generates rather accurate results. Hence it could assist the aphasia rehabilitation and substantially reduce clinicians' workload.

EEG reveals brain network alterations in chronic aphasia during natural speech listening

Aphasia is a common consequence of a stroke which affects language processing. In search of an objective biomarker for aphasia, we used EEG to investigate how functional network patterns in the cortex are affected in persons with post-stroke chronic aphasia (PWA) compared to healthy controls (HC) while they are listening to a story. EEG was recorded from 22 HC and 27 PWA while they listened to a 25-min-long story. Functional connectivity between scalp regions was measured with the weighted phase lag index. The Network-Based Statistics toolbox was used to detect altered network patterns and to investigate correlations with behavioural tests within the aphasia group. Differences in network geometry were assessed by means of graph theory and a targeted node-attack approach. Group-classification accuracy was obtained with a support vector machine classifier. PWA showed stronger inter-hemispheric connectivity compared to HC in the theta-band (4.5-7 Hz), whilst a weaker subnetwork emerged in the low-gamma band (30.5-49 Hz). Two subnetworks correlated with semantic fluency in PWA respectively in delta- (1-4 Hz) and low-gamma-bands. In the theta-band network, graph alterations in PWA emerged at both local and global level, whilst only local changes were found in the low-gamma-band network. Network metrics discriminated PWA and HC with AUC = 83%. Overall, we demonstrate the potential of EEG-network metrics for the development of informative biomarkers to assess natural speech processing in chronic aphasia. We hypothesize that the detected alterations reflect compensatory mechanisms associated with recovery.

The Dark and Gloomy Brain: Grey Matter Volume Alterations in Major Depressive Disorder-Fine-Grained Meta-Analyses

Background

While the brain correlates of major depressive disorder (MDD) have been extensively studied, there is no consensus conclusion so far. Various meta-analyses tried to determine the most consistent findings, but the results are often discordant for grey matter volume (GMV) atrophy and hypertrophy. Applying rigorous and stringent inclusion criteria and controlling for confounding factors, such as the presence of anxiety comorbidity, we carried out two novel meta-analyses on the existing literature to unveil MDD signatures.

Methods

A systematic literature search was performed up to January 2023. Seventy-three studies on MDD patients reporting GMV abnormalities were included in the first meta-analysis, for a total of 6167 patients and 6237 healthy controls (HC). To test the effects of anxiety comorbidity, we conducted a second meta-analysis, by adding to the original pure MDD sample a new cohort of MDD patients with comorbid anxiety disorders (308 patients and 342 HC). An activation likelihood estimation (ALE) analysis and a coordinate-based mapping approach separate for atrophy and hypertrophy were used to identify common brain structural alterations among patients.

Results

The pure MDD sample exhibited atrophy in the left insula, as well as hypertrophy in the bilateral amygdala and parahippocampal gyri. When we added patients with comorbid anxiety to the original sample, bilateral insula atrophy emerged, whereas the hypertrophy results were not replicated.

Conclusions

Our findings revealed important structural alterations in pure MDD patients, particularly in the insula and amygdala, which play key roles in sensory input integration and in emotional processing, respectively. Additionally, the amygdala and parahippocampal gyrus hypertrophy may be related to MDD functional overactivation to emotional stimuli, rumination, and overactive self-referential thinking. Conversely, the presence of anxiety comorbidity revealed separate effects which were not seen in the pure MDD sample, underscoring the importance of strict inclusion criteria for investigations of disorder-specific effects.

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.

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.

Hearing voices in the head: Two meta-analyses on structural correlates of auditory hallucinations in schizophrenia

Past voxel-based morphometry (VBM) studies demonstrate reduced grey matter volume (GMV) in schizophrenia (SZ) patients' brains in various cortical and subcortical regions. Probably due to SZ symptoms' heterogeneity, these results are often inconsistent and difficult to integrate. We hypothesized that focusing on auditory verbal hallucinations (AVH) - one of the most common SZ symptoms - would allow reducing heterogeneity and discovering further compelling evidence of SZ neural correlates. We carried out two voxel-based meta-analyses of past studies that investigated the structural correlates of AVH in SZ. The review of whole-brain VBM studies published until June 2022 in PubMed and PsychInfo databases yielded (a) 13 studies on correlations between GMV and AVH severity in SZ patients (n = 472; 86 foci), and (b) 11 studies involving comparisons between hallucinating SZ patients (n = 504) and healthy controls (n = 524; 74 foci). Data were analyzed using the Activation Likelihood Estimation method. AVH severity was associated with decreased GMV in patients' left superior temporal gyrus (STG) and left posterior insula. Compared with healthy controls, hallucinating SZ patients showed reduced GMV on the left anterior insula and left inferior frontal gyrus (IFG). Our findings revealed important structural dysfunctions in a left lateralized cluster of brain regions, including the insula and temporo-frontal regions, that significantly contribute to the severity and persistence of AVH. Structural atrophy found in circuits involved in generating and perceiving speech, as well as in auditory signal processing, might reasonably be considered a biological marker of AVH in SZ.

Effect of Rehabilitation on Brain Functional Connectivity in a Stroke Patient Affected by Conduction Aphasia

Stroke is a medical condition that affects the brain and represents a leading cause of death and disability. Associated with drug therapy, rehabilitative treatment is essential for promoting recovery. In the present work, we report an EEG-based study concerning a left ischemic stroke patient affected by conduction aphasia. Specifically, the objective is to compare the brain functional connectivity before and after an intensive rehabilitative treatment. The analysis was performed by means of local and global efficiency measures related to the execution of three tasks: naming, repetition and reading. As expected, the results showed that the treatment led to a balancing of the values of both parameters between the two hemispheres since the rehabilitation contributed to the creation of new neural patterns to compensate for the disrupted ones. Moreover, we observed that for both name and repetition tasks, shortly after the stroke, the global and local connectivity are lower in the affected lobe (left hemisphere) than in the unaffected one (right hemisphere). Conversely, for the reading task, global and local connectivity are higher in the impaired lobe. This apparently contrasting trend can be due to the effects of stroke, which affect not only the site of structural damage but also brain regions belonging to a functional network. Moreover, changes in network connectivity can be task-dependent. This work can be considered a first step for future EEG-based studies to establish the most suitable connectivity measures for supporting the treatment of stroke and monitoring the recovery process.

The role and use of event-related potentials in aphasia: A scoping review

Event-related potentials (ERPs) can provide important insights into underlying language processes in both unimpaired and neurologically impaired populations and may be particularly useful in aphasia. This scoping review was conducted to provide a comprehensive summary of how ERPs have been used with people with aphasia (PWA), with the goal of exploring the potential clinical application of ERPs in aphasia assessment and treatment. We identified 117 studies that met inclusionary criteria, reflecting six thematic domains of inquiry that relate to understanding both unimpaired and aphasic language processing and the use of ERPs with PWA. In these studies, a wide variety of ERP components were reported. Inconsistencies in reporting of participant characteristics and study protocols limit our ability to generalize beyond the individual studies and understand implications for clinical applicability. We discuss the potential roles of ERPs in aphasia management and make recommendations for further developing ERPs for clinical utility in PWA.

Neural Representation in Visual Word Form Area during Word Reading

The visual word form area (VWFA) has been consistently identified as a crucial structure in visual word processing. Nevertheless, it is controversial whether the VWFA represents external visual information (e.g., case information) of visual words. To address that question, we functionally localized VWFA at the group level (gVWFA) and at the individual level (iVWFA), and used multivariate pattern analysis (MVPA) to explore the information representation in the VWFA during an implicit reading task (i.e., a passive viewing task). Univariate activation analysis revealed that participants showed stronger activations for uppercase English words compared to lowercase ones in the VWFA. MVPA further revealed that the classifier trained based on lowercase words versus letter strings significantly distinguished uppercase words versus letter strings in the iVWFA, while that trained based on lowercase words versus uppercase words distinguished lowercase letter strings versus uppercase letter strings neither in the gVWFA nor in the iVWFA. These results suggest that the VWFA does not represent case information, but represents case-independent linguistic information. Our findings elaborate the function in the VWFA and support the VWFA hypothesis.

Cortical Reorganization after Rehabilitation in a Patient with Conduction Aphasia Using High-Density EEG

Conduction aphasia is a language disorder occurred after a left-brain injury. It is characterized by fluent speech production, reading, writing and normal comprehension, while speech repetition is impaired. The aim of this study is to investigate the cortical responses, induced by language activities, in a sub-acute stroke patient affected by conduction aphasia before and after an intensive speech therapy training. The patient was examined by using High-Density Electroencephalogram (HD-EEG) examination, while was performing language tasks. the patient was evaluated at baseline and after two months after rehabilitative treatment. Our results showed that an intensive rehabilitative process, in sub-acute stroke, could be useful for a good outcome of language deficits. HD-EEG results showed that left parieto-temporol-frontal areas were more activated after 2 months of rehabilitation training compared with baseline. Our results provided evidence that an intensive rehabilitation process could contribute to an inter- and intra-hemispheric reorganization.

Evidence of language-related left hypofrontality in Major Depression: An EEG Beta band study

Major depression (MDD) has been associated with an altered EEG frontal asymmetry measured in resting state; nevertheless, this association has showed a weak consistency across studies. In the present study, which starts from an evolutionistic view of psychiatric disorders, we investigated frontal asymmetry in MDD, using language as a probe to test the integrity of large inter- and intra-hemispheric networks and processes. Thirty MDD patients (22 women) and 32 matched controls (HC) were recruited for an EEG recording in resting state and during two linguistic tasks, phonological and semantic. Normalized alpha and beta EEG spectral bands were measured across all three conditions in the two groups. EEG alpha amplitude showed no hemispheric asymmetry, regardless of group, both at rest and during linguistic tasks. During resting state, analysis of EEG beta revealed a lack of hemispheric asymmetry in both groups, but during linguistic tasks, HC exhibited the typical greater left frontal beta activation, whereas MDD patients showed a lack of frontal asymmetry and a significantly lower activation of left frontal sites. In depressed patients, positive affect was negatively correlated with depression levels and positively correlated with left frontal EEG beta amplitude. Language represents the human process that requires the largest level of integration between and within the hemispheres; thus, language asymmetry was a valid probe to test the left frontal alteration encompassing highly impairing psychiatric disorders, such as schizophrenia and MDD. Indeed, these severe diseases are marked by delusions, ruminations, thought disorders, and hallucinations, all of which have a clear linguistic or metalinguistic basis.

Electrophysiological Characteristics in Depressive Personality Disorder: An Event-Related Potential Study

This study aimed to investigate the neurophysiological characteristics of young people with depressive personality disorder using event-related potentials (ERP). To explore the effects of visual-emotional words on ERP, mainly N350, we recruited 19 individuals with a depressive personality disorder and 10 healthy controls. ERP were recorded while the subjects took decisions on target words that were classified into three categories: emotionally positive, negative, and neutral. The ERP signals were then separately averaged according to the subjects' classifications. Data analysis showed that the amplitude of N350 was larger in response to positive and negative words than to neutral words. The latency of N350 was longer in negative words, in contrast with positive and neutral words. However, no difference was found between the two groups. These results suggest that neurophysiological characteristics of young people with a depressive personality disorder in visual-emotional word processing have not yet been influenced by their personality traits. To some extent, N350 reflected semantic processes and was not sensitive to participants' mood state.

Supine posture affects cortical plasticity in elderly but not young women during a word learning-recognition task

The present research investigated the hypothesis that elderly and horizontal body position contribute to impair learning capacity. To this aim, 30 young (mean age: 23.2 years) and 20 elderly women (mean age: 82.8 years) were split in two equal groups, one assigned to the Seated Position (SP), and the other to the horizontal Bed Rest position (hBR). In the Learning Phase, participants were shown 60 words randomly distributed, and in the subsequent Recognition Phase they had to recognize them mixed with a sample of 60 new words. Behavioral analyses showed age-group effects, with young women exhibiting faster response times and higher accuracy rates than elderly women, but no interaction of body position with age group was found. Analysis of the RP component (250-270ms) revealed greater negativity in the left Occipital gyrus/Cuneus of both sitting age-groups, but significantly left-lateralized RP in left Lingual gyrus only in young bedridden women. Elderly hBR women showed a lack of left RP lateralization, the main generator being located in the right Cuneus. Young participants had the typical old/new effect (450-800ms) in different portions of left Frontal gyri/Uncus, whereas elderly women showed no differences in stimulus processing and its location. EEG alpha activity analyzed during a 3min resting state, soon after the recognition task, revealed greater alpha amplitude (i.e., cortical inhibition) in posterior sites of hBR elderly women, a result in line with their inhibited posterior RP. In elderly women the left asymmetry of RP was positively correlated with both greater accuracy and faster responses, thus pointing to a dysfunctional role, rather than a compensatory shift, of the observed right RP asymmetry in this group. This finding may have important clinical implications, with particular regard to the long-term side-effects of forced Bed Rest on elderly patients.