Emotional processing in RRMS patients: Dissociation between behavioural and neurophysiological response

The validation of the Italian version of multiple sclerosis neuropsychological screening questionnaire in Huntington's disease

INTRODUCTION

Multiple sclerosis neuropsychological questionnaire (MSNQ) is a brief questionnaire useful for screening patient's and informant's self-perception of cognitive dysfunctions in daily life activities. Our study aims to evaluate the MSNQ validity in Huntington's disease (HD) mutation carriers and to correlate MSNQ scores with neurological, cognitive, and behavioral variables.

METHODS

The study was conducted on a sample of 107 subjects from presymptomatic to the middle stage of HD recruited at LIRH Foundation and C.S.S. Mendel Institute in Rome. Unified Huntington's Disease Rating Scale (UHDRS), an internationally standardized and validated scale, was used to evaluate motor, functional cognitive, and behavioral domains.

RESULTS

Our results showed that in HD subjects, MSNQ has a unidimensional factor structure. Correlational analyses indicated a good correlation between the MSNQ-patient version (MSNQ-p) and clinical variables, specifically with cognitive dysfunction and behavioral alterations. Moreover, higher scores in MSNQ-p were associated with higher motor disease and functional impairment showing that patients in advanced stage of HD perceive a greater cognitive impairment. These results confirm the questionnaire's reliability.

CONCLUSIONS

The present study demonstrates the validity and adaptability of MSNQ in the HD population proposing it as a cognitive tool during routine clinical follow-ups, although further research is needed to determine an optimal cut-off score for this measure.

The role of emotional instability in borderline personality disorder: a systematic review

BACKGROUND

The emotional regulation process plays a pivotal role in daily-life functioning, modulating goal-directed and adaptive behavior. Conversely, altering this cognitive function can disrupt self-regulation and bring emotional dysregulation. Emotional instability could represent a core characteristic of BPD, also modulating the BPD symptom's onset. This systematic review aims to summarize the existing literature reporting the role of emotional instability in BPD to better define the role of the impairment of the emotional processes in the onset of the cognitive and behavioral symptoms of this complex mental disorder.

METHODS

MEDLINE, Scopus and Web of Science were independently searched for relevant studies. Eligible studies had to be identifiable through database searching, published and accessible. This systematic review was conducted according to PRISMA guidelines. The search period was from 2012 to 14 September 2022.

RESULTS

A pool of 120 studies was identified, out of which 11 met the selection criteria and were included. Overall, the studies confirm a relationship between emotional instability and borderline personality disorder.

CONCLUSIONS

The evidences retrieved seem to point out the role of the emotional impairment not only in worsening of the disorder, but could also be one of the risk factors for its onset.

Dynamics of the "Cognitive" Brain Wave P3b at Rest for Alzheimer Dementia Prediction in Mild Cognitive Impairment

Alzheimer's disease (AD) is the most common cause of dementia that involves a progressive and irrevocable decline in cognitive abilities and social behavior, thus annihilating the patient's autonomy. The theoretical assumption that disease-modifying drugs are most effective in the early stages hopefully in the prodromal stage called mild cognitive impairment (MCI) urgently pushes toward the identification of robust and individualized markers of cognitive decline to establish an early pharmacological intervention. This requires the combination of well-established neural mechanisms and the development of increasingly sensitive methodologies. Among the neurophysiological markers of attention and cognition, one of the sub-components of the 'cognitive brain wave' P300 recordable in an odd-ball paradigm -namely the P3b- is extensively regarded as a sensitive indicator of cognitive performance. Several studies have reliably shown that changes in the amplitude and latency of the P3b are strongly related to cognitive decline and aging both healthy and pathological. Here, we used a P3b spatial filter to enhance the electroencephalographic (EEG) characteristics underlying 175 subjects divided into 135 MCI subjects, 20 elderly controls (EC), and 20 young volunteers (Y). The Y group served to extract the P3b spatial filter from EEG data, which was later applied to the other groups during resting conditions with eyes open and without being asked to perform any task. The group of 135 MCI subjects could be divided into two subgroups at the end of a month follow-up: 75 with stable MCI (MCI-S, not converted to AD), 60 converted to AD (MCI-C). The P3b spatial filter was built by means of a signal processing method called Functional Source Separation (FSS), which increases signal-to-noise ratio by using a weighted sum of all EEG recording channels rather than relying on a single, or a small sub-set, of channels. A clear difference was observed for the P3b dynamics at rest between groups. Moreover, a machine learning approach showed that P3b at rest could correctly distinguish MCI from EC (80.6% accuracy) and MCI-S from MCI-C (74.1% accuracy), with an accuracy as high as 93.8% in discriminating between MCI-C and EC. Finally, a comparison of the Bayes factor revealed that the group differences among MCI-S and MCI-C were 138 times more likely to be detected using the P3b dynamics compared with the best performing single electrode (Pz) approach. In conclusion, we propose that P3b as measured through spatial filters can be safely regarded as a simple and sensitive marker to predict the conversion from an MCI to AD status eventually combined with other non-neurophysiological biomarkers for a more precise definition of dementia having neuropathological Alzheimer characteristics.

Strain and sex differences in somatosensation and sociability during experimental autoimmune encephalomyelitis

Multiple Sclerosis (MS) is an immune-mediated disease that results in major locomotor deficits. However, recent studies have revealed that fatigue, slow processing speed, and memory impairment are the top variables impacting employment status for MS patients. These suggest that cognitive effects may have a greater impact on productivity, lifestyle, and quality of life than do disease-related motor deficits. However, these debilitating non-locomotive effects have been largely overlooked in rodent models of the disease, such as experimental autoimmune encephalomyelitis (EAE). We hypothesized that murine EAE can also be used to assess non-locomotive dysfunctions (mood, sociability, muscle strength, and balance), as well as potential biases in these dysfunctions due to sex and/or strain. We actively immunized male and female C57BL/6 (B6) and SJL mice for EAE and evaluated their performance on the Deacon's weight grip test, Kondziela's inverted screen test, Hall's rope grip test, manual von Frey test for somatic nociception, and a three-chamber social preference paradigm. We hypothesized that EAE progression is associated with changes in muscle strength, balance, pain, and sociability and that these variations are linked to sex and/or strain. Our results indicate that strain but not sex influenced differences in muscle strength and balance during EAE, and both sex and strain have an impact on mechanical nociception, regardless of EAE disease status. Furthermore, both sex and strain had complex effects on differences in sociability. In conclusion, testing these additional modalities during EAE helps to unveil other signs and symptoms that could be used to determine the efficacy of a drug or treatment in the modulation of a MS-like behavior.

Proof-of-concept evidence for trimodal simultaneous investigation of human brain function

The link between spatial (where) and temporal (when) aspects of the neural correlates of most psychological phenomena is not clear. Elucidation of this relation, which is crucial to fully understand human brain function, requires integration across multiple brain imaging modalities and cognitive tasks that reliably modulate the engagement of the brain systems of interest. By overcoming the methodological challenges posed by simultaneous recordings, the present report provides proof‐of‐concept evidence for a novel approach using three complementary imaging modalities: functional magnetic resonance imaging (fMRI), event‐related potentials (ERPs), and event‐related optical signals (EROS). Using the emotional oddball task, a paradigm that taps into both cognitive and affective aspects of processing, we show the feasibility of capturing converging and complementary measures of brain function that are not currently attainable using traditional unimodal or other multimodal approaches. This opens up unprecedented possibilities to clarify spatiotemporal integration of brain function.

Psychopathological Comorbidities and Clinical Variables in Patients With Medication Overuse Headache

The psychopathological profile of patients with medication overuse headache (MOH) appears to be particularly complex. To better define it, we evaluated their performance on a targeted psychological profile assessment. We designed a case-control study comparing MOH patients and matched healthy controls (HC). Headache frequency, drug consumption, HIT-6, and MIDAS scores were recorded. All participants filled in the following questionnaires: Beck Depression Inventory-II Edition (BDI-2), trait subtest of State-Trait Anxiety Inventory (STAI-Y), Difficulties in Emotion Regulation Scale (DERS), Barratt Impulsiveness Scale (BIS-11), Toronto Alexithymia Scale (TAS-20). The primary endpoint was to establish if MOH patients have an altered psychopathological profile. The secondary endpoint was to establish whether the worst profile correlates with the worsening of headache and disability measures. We enrolled 48 consecutive MOH patients and 48 HC. MOH patients showed greater difficulty in recognition/regulation of emotions (DERS, TAS-20), depression (BDI-2), anxiety (STAI-Y), and impulsiveness (BIS-11). We found a positive correlation among DERS, BDI-2, STAI-Y, and BIS scores and MIDAS and HIT-6 scores and among DERS and headache frequency and drug consumption. MOH patients showed a high rate of emotion regulation difficulties, depression, and anxiety, which may negatively affect their headaches. The ability to regulate/recognize emotions may play a central role in sustaining medication overuse.

A cross-sectional study of alexithymia in patients with relapse remitting form of multiple sclerosis

Background:

Alexithymia is one's incapacity to identify, comprehend, and describe emotions. There is almost no literature data about the levels of alexithymia among patients with relapse remitting type of multiple sclerosis.

Aim:

The objective of the present study was to assess the levels of alexithymia in patients with relapse remitting type of multiple sclerosis in relation to their sociodemographic variables and clinical characteristics of the disease.

Methods:

This cross-sectional study included 106 consecutively assessed patients with relapse remitting type of multiple sclerosis. In addition to the data regarding disease duration, number of demyelinating relapses, and degree of neurological disability, assessed by the expanded disability scale score (EDSS), we used Toronto alexithymia scale (TAS), fatigue severity scale (FSS) and, Hamilton scale for the assessment of anxiety and depression and sociodemographic questionnaire.

Results:

Study included 74 female and 32 male patients, with a median age of 44 years, median disease duration 90 months, and median EDSS 4. About 29.55% of patients had alexithymia and borderline alexithymia was observed in 31.15% patients. Alexithymia correlated with anxiety and depression (P < 0.01) on all TAS subscales. Higher levels of neurological disability based on EDSS, severe fatigue based on FSS scores, and severe relapse remitting type of multiple sclerosis with more relapses and longer disease duration correlated with alexithymia (P < 0.01), depression (P < 0.01), and anxiety (P < 0.01). Higher rates of alexithymia were noticed in older, unemployed, single patients, and those having fewer children.

Conclusions:

Alexithymia was found in a relatively high percentage in patients with relapse remitting type of multiple sclerosis.

A functional source separation algorithm to enhance error-related potentials monitoring in noninvasive brain-computer interface

BACKGROUND AND OBJECTIVES

An Error related Potential (ErrP) can be noninvasively and directly measured from the scalp through electroencephalography (EEG), as response, when a person realizes they are making an error during a task (as a consequence of a cognitive error performed from the user). It has been shown that ErrPs can be automatically detected with time-discrete feedback tasks, which are widely applied in the Brain-Computer Interface (BCI) field for error correction or adaptation. In this work, a semi-supervised algorithm, namely the Functional Source Separation (FSS), is proposed to estimate a spatial filter for learning the ErrPs and to enhance the evoked potentials.

METHODS

EEG data recorded on six subjects were used to evaluate the proposed method based on FFS algorithm in comparison with the xDAWN algorithm. FSS- and xDAWN-based methods were compared also to the Cz and FCz single channel. Single-trial classification was considered to evaluate the performances of the approaches. (Both the approaches were evaluated on single-trial classification of EEGs.) RESULTS: The results presented using the Bayesian Linear Discriminant Analysis (BLDA) classifier, show that FSS (accuracy 0.92, sensitivity 0.95, specificity 0.81, F1-score 0.95) overcomes the other methods (Cz - accuracy 0.72, sensitivity 0.74, specificity 0.63, F1-score 0.74; FCz - accuracy 0.72, sensitivity 0.75, specificity 0.61, F1-score 0.75; xDAWN - accuracy 0.75, sensitivity 0.79, specificity 0.61, F1-score 0.79) in terms of single-trial classification.

CONCLUSIONS

The proposed FSS-based method increases the single-trial detection accuracy of ErrPs with respect to both single channel (Cz, FCz) and xDAWN spatial filter.

Emotional experience in patients with clinically isolated syndrome and early multiple sclerosis

BACKGROUND AND PURPOSE

Evidence suggests that there are changes in the processing of emotional information (EP) in people with multiple sclerosis (MS). It is unclear which functional domains of EP are affected, whether these changes are secondary to other MS-related neuropsychological or psychiatric symptoms and if EP changes are present in early MS. The aim of the study was to investigate EP in patients with early MS (clinically isolated syndrome and early relapsing/remitting MS) and healthy controls (HCs).

METHODS

A total of 29 patients without neuropsychological or psychiatric deficits and 29 matched HCs were presented with pictures from the International Affective Picture System with negative, positive or neutral content. Participants rated the induced emotion regarding valence and arousal using nine-level Likert scales. A speeded recognition test assessed memory for the emotional stimuli and for the emotional modulation of response time. A subgroup of participants was tested during a magnetic resonance imaging (MRI) session.

RESULTS

Patients in the MRI subgroup rated the experience induced by pictures with positive or negative emotional content significantly more weakly than HCs. Further, these patients were significantly less aroused when watching the pictures from the International Affective Picture System. There were no effects in the non-MRI subgroup or effects on emotional memory or response times.

CONCLUSIONS

Emotional processing changes may be present in early MS in the form of flattened emotional experience on both the valence and arousal dimensions. These changes do not appear to be secondary to neuropsychological or psychiatric deficits. The fact that emotional flattening was only found in the MRI setting suggests that EP changes may be unmasked within stressful environments and points to the potential yet underestimated impact of the MRI setting on behavioral outcomes.

Effect of brightness of visual stimuli on EEG signals

The aim of this study was to examine brightness effect, which is the perceptual property of visual stimuli, on brain responses obtained during visual processing of these stimuli. For this purpose, brain responses of the brain to changes in brightness were explored comparatively using different emotional images (pleasant, unpleasant and neutral) with different luminance levels. In the study, electroencephalography recordings from 12 different electrode sites of 31 healthy participants were used. The power spectra obtained from the analysis of the recordings using short time Fourier transform were analyzed, and a statistical analysis was performed on features extracted from these power spectra. Statistical findings were compared with those obtained from behavioral data. The results showed that the brightness of visual stimuli affected the power of brain responses depending on frequency, time and location. According to the statistically verified findings, the increase in the brightness of pleasant and neutral images increased the average power of responses in the parietal and occipital regions whereas the increase in the brightness of unpleasant images decreased the average power of responses in these regions. Moreover, the statistical results obtained for unpleasant images were found to be in accordance with the behavioral data. The results revealed that the brightness of visual stimuli could be represented by changing the activity power of the brain cortex. The findings emphasized that the brightness of visual stimuli should be viewed as an important parameter in studies using emotional image techniques such as image classification, emotion evaluation and neuro-marketing.

Low Complexity Automatic Stationary Wavelet Transform for Elimination of Eye Blinks from EEG

The electroencephalogram signal (EEG) often suffers from various artifacts and noises that have physiological and non-physiological origins. Among these artifacts, eye blink, due to its amplitude is considered to have the most influence on EEG analysis. In this paper, a low complexity approach based on Stationary Wavelet Transform (SWT) and skewness is proposed to remove eye blink artifacts from EEG signals. The proposed method is compared against Automatic Wavelet Independent Components Analysis (AWICA) and Enhanced AWICA. Normalized Root Mean Square Error (NRMSE), Peak Signal-to-Noise Ratio (PSNR), and correlation coefficient ( ρ ) between filtered and pure EEG signals are utilized to quantify artifact removal performance. The proposed approach shows smaller NRMSE, larger PSNR, and larger correlation coefficient values compared to the other methods. Furthermore, the speed of execution of the proposed method is considerably faster than other methods, which makes it more suitable for real-time processing.