P50, N100, and P200 Sensory Gating in Panic Disorder

P50 sensory gating, cognitive deficits and depressive symptoms in first-episode antipsychotics-naïve schizophrenia

OBJECTIVE

Sensory gating P50 (SG-P50) may be involved in the pathophysiological mechanisms of impaired cognition in schizophrenia (SCZ). Comorbid depressive symptoms are common in SCZ patients and are also found to be associated with their cognitive impairment. However, it is unclear whether SG-P50 is abnormal in first episode antipsychotics naïve (FEAN) SCZ patients with depressive symptoms. Our aimed to investigate the relationships between SG-P50, depressive symptoms and neurocognition in FEAN-SCZ patients.

METHODS

We recruited 103 FEAN-SCZ patients (depression: n = 63; non-depression: n = 40) and 55 healthy controls. SG-P50 was measured using the standard auditory dual-click (S1&S2) paradigm. Clinical symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Hamilton Depression Rating Scale-17 (HDRS-17). Cognitive performance was evaluated using the MATRICS Consensus Cognitive Battery (MCCB).

RESULTS

Compared with non-depressive patients, depressive patients had a significantly larger S2 amplitude (p = 0.005) and a higher S2/S1 ratio at trend level (p = 0.075) after corrected. There were significant differences in the scores of CPT-IP and Mazes (NAB) between depressive and non-depressive FEAN-SCZ patients (both p values < 0.05). For all patients, the SG-P50 S2/S1 ratio was significantly correlated with HDRS-17 score (r = 0.23, p = 0.020) and MCCB-Symbol coding (r = -0.16, p = 0.043). For depressive FEAN-SCZ patients, S2 amplitude was an independent predictor of the MCCB-Mazes (NAB) (β = -0.31, t = -2.52, p = 0.015).

CONCLUSIONS

SG-P50 deficit may be an informational biomarker for depressive symptoms and neurocognitive impairments in FEAN-SCZ patients.

Cognitive fatigue-related sensory gating deficits in people with multiple sclerosis

BACKGROUND

Cognitive fatigue is highly prevalent in people with multiple sclerosis (pwMS) and significantly limits their quality of life. Fatigue can be subdivided into a subjective feeling of constant (trait) or current (state) exhaustion, as well as an objective performance decline, also known as fatigability. However, the current fatigue diagnosis in pwMS is purely subjective, leaving fatigability mostly unattended. Sensorimotor and sensory gating deficits have recently been described as possible objective markers for fatigability in healthy subjects. Thus, this study aimed to investigate the potential of prepulse inhibition (PPI) ratios and the P50 sensory gating suppression as surrogate markers for cognitive fatigue in pwMS.

METHODS

PPI and P50 sensory gating ratios were assessed before and after a 30-min fatigability-inducing AX- continuous performance task. Subjective trait fatigue was operationalized via self-report questionnaires, subjective state fatigue via visual analog scales (VAS), and fatigability via the change in both gating ratios. The data were analyzed using Linear Mixed Models and Pearson correlations.

RESULTS

We included 18 pwMS and 20 healthy controls (HC) in the final analyses. The task-induced fatigability was more pronounced in pwMS. While the initial PPI and P50 ratios were similar in both groups, P50 sensory gating was significantly disrupted after fatigability induction in pwMS. PPI, on the other hand, decreased in both groups. Moreover, initial P50 sensory gating ratios were negatively associated with subjective trait fatigue in pwMS, indicating that higher trait fatigue is associated with disrupted sensory gating. Finally, fatigability-related changes in P50 sensory gating were associated with the changes in VAS ratings, but only in HC.

CONCLUSIONS

This study demonstrated that P50 sensory gating is a promising objective fatigue and fatigability parameter. Importantly, P50 sensory gating correlated with subjective trait and state fatigue ratings. Our results extend the subjective fatigue diagnosis and broaden the understanding of pathophysiological neuronal mechanisms in MS-related fatigue. This is the first study to present fatigue-related disruption of sensory gating in pwMS.

Sensory gating in tobacco-naïve cannabis users is unaffected by acute nicotine administration

OBJECTIVES

Long-term cannabis use has been associated with the appearance of psychotic symptoms and schizophrenia-like cognitive impairments; however these studies may be confounded by concomitant use of tobacco by cannabis users. We aimed to determine if previously observed cannabis-associated deficits in sensory gating would be seen in cannabis users with no history of tobacco use, as evidenced by changes in the P50, N100, and P200 event-related potentials. A secondary objective of this study was to examine the effects of acute nicotine administration on cannabis users with no tobacco use history.

METHODS

Three components (P50, N100, P200) of the mid-latency auditory-evoked response (MLAER) were elicited by a paired-stimulus paradigm in 43 healthy, non-tobacco smoking male volunteers between the ages of 18-30. Cannabis users (CU, n = 20) were administered nicotine (6 mg) and placebo gum within a randomized, double-blind design. Non-cannabis users (NU, n = 23) did not receive nicotine.

RESULTS

Between-group sensory gating effects were only observed for the N100, with CUs exhibiting a smaller N100 to S1 of the paired stimulus paradigm, in addition to reduced dN100 (indicating poorer gating). Results revealed no significant sensory gating differences with acute administration of nicotine compared to placebo cannabis conditions.

CONCLUSIONS

These findings suggest a relationship between gating impairment and cannabis use; however, acute nicotine administration nicotine does not appear to impact sensory gating function.

Dysfunctional frontal activation of mismatch negativity in panic disorder: A magnetoencephalographic study

BACKGROUND

Mismatch negativity (MMN) or its magnetic counterpart (MMNm) is a neurophysiological signal to reflect the automatic change-detection ability. However, MMN studies in patients with panic disorder (PD) showed contrasting results using electroencephalographic (EEG) recordings. The present study attempted to overcome the limitations of EEG methodology by means of a whole-head magnetoencephalography (MEG) combined with the depth-weighted minimum norm estimate method to conduct an in-depth investigation on the MMNm at the cortical level in patients with PD.

METHODS

We recruited 22 healthy controls (HC) and 20 patients with PD to perform auditory oddball paradigm during MEG recordings. The cortical MMNm amplitudes and latencies in the superior temporal gyrus, inferior parietal lobule, and inferior frontal gyrus (IFG) were compared between the HC and PD groups. The correlations between MMNm responses and clinical measurement were also examined.

RESULTS

Compared with the HC group, the PD group demonstrated significantly reduced MMNm amplitudes in the IFG. Furthermore, higher trait scores of the State-Trait Anxiety Inventory were associated with lower MMNm amplitudes of the right IFG among patients with PD.

LIMITATIONS

Generalization of the current results to other settings or samples should be made cautiously due to the use of different medication regimens and presence of comorbidities in our patients.

CONCLUSIONS

Our data suggest dysfunctional pre-attentive change-detection ability in patients with PD, particularly in the IFG.

Machine Learning-Based Electroencephalographic Phenotypes of Schizophrenia and Major Depressive Disorder

Background: Psychiatric diagnosis is formulated by symptomatic classification; disease-specific neurophysiological phenotyping could help with its fundamental treatment. Here, we investigated brain phenotyping in patients with schizophrenia (SZ) and major depressive disorder (MDD) by using electroencephalography (EEG) and conducted machine-learning-based classification of the two diseases by using EEG components. Materials and Methods: We enrolled healthy controls (HCs) (n = 30) and patients with SZ (n = 34) and MDD (n = 33). An auditory P300 (AP300) task was performed, and the N1 and P3 components were extracted. Two-group classification was conducted using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Positive and negative symptoms and depression and/or anxiety symptoms were evaluated. Results: Considering both the results of statistical comparisons and machine learning-based classifications, patients and HCs showed significant differences in AP300, with SZ and MDD showing lower N1 and P3 than HCs. In the sum of amplitudes and cortical sources, the findings for LDA with classification accuracy (SZ vs. HCs: 71.31%, MDD vs. HCs: 74.55%), sensitivity (SZ vs. HCs: 77.67%, MDD vs. HCs: 79.00%), and specificity (SZ vs. HCs: 64.00%, MDD vs. HCs: 69.67%) supported these results. The SVM classifier showed reasonable scores between SZ and HCs and/or MDD and HCs. The comparison between SZ and MDD showed low classification accuracy (59.71%), sensitivity (65.08%), and specificity (54.83%). Conclusions: Patients with SZ and MDD showed deficiencies in N1 and P3 components in the sum of amplitudes and cortical sources, indicating attentional dysfunction in both early and late sensory/cognitive gating input. The LDA and SVM classifiers in the AP300 are useful to distinguish patients with SZ and HCs and/or MDD and HCs.

Using high density EEG to assess TMS treatment in patients with schizophrenia

We present preliminary results from the ongoing study entitled “Icelandic AVH-TMS” which aim is to study the effectiveness of repetitive transcranial magnetic stimulation (rTMS) treatment for patients with schizophrenia and with persistent auditory verbal hallucinations (AVH) using symptoms and psychometric scales and high-density EEG system (256 channels). The aim of the present work was to describe cortical topography of the auditory evoked responses like P50 and N100-P300 complex in healthy participants and patients with schizophrenia and to define a robust methodology of signal quantification using dense-array EEG. Preliminary data is shown for three healthy participants and three patients in baseline conditions and for two patients we show the results recorded before and after 10 days rTMS treatment. Our results show differences in sensory gating (P50 suppresion) and a stronger N100-P300 response to rare audio stimulus after the treatment. Moreover we show the value of assessing brain electrical activity from high-density EEG (256 channels) analyzing the results in different regions of interest. However, it is premature and hazardous to assume that rTMS treatment effectiveness in patients with AVH can be assessed using P50 suppression ratio.

P50, N100, and P200 Auditory Sensory Gating Deficits in Schizophrenia Patients

BACKGROUND

Sensory gating describes neurological processes of filtering out redundant or unnecessary stimuli during information processing, and sensory gating deficits may contribute to the symptoms of schizophrenia. Among the three components of auditory event-related potentials reflecting sensory gating, P50 implies pre-attentional filtering of sensory information and N100/P200 reflects attention triggering and allocation processes. Although diminished P50 gating has been extensively documented in patients with schizophrenia, previous studies on N100 were inconclusive, and P200 has been rarely examined. This study aimed to investigate whether patients with schizophrenia have P50, N100, and P200 gating deficits compared with control subjects.

METHODS

Control subjects and clinically stable schizophrenia patients were recruited. The mid-latency auditory evoked responses, comprising P50, N100, and P200, were measured using the auditory-paired click paradigm without manipulation of attention. Sensory gating parameters included S1 amplitude, S2 amplitude, amplitude difference (S1-S2), and gating ratio (S2/S1). We also evaluated schizophrenia patients with PANSS to be correlated with sensory gating indices.

RESULTS

One hundred four patients and 102 control subjects were examined. Compared to the control group, schizophrenia patients had significant sensory gating deficits in P50, N100, and P200, reflected by larger gating ratios and smaller amplitude differences. Further analysis revealed that the S2 amplitude of P50 was larger, while the S1 amplitude of N100/P200 was smaller, in schizophrenia patients than in the controls. We found no correlations between sensory gating indices and schizophrenia positive or negative symptom clusters. However, we found a negative correlation between the P200 S2 amplitude and Bell's emotional discomfort factor/Wallwork's depressed factor.

CONCLUSION

Till date, this study has the largest sample size to analyze P50, N100, and P200 collectively by adopting the passive auditory paired-click paradigm without distractors. With covariates controlled for possible confounds, such as age, education, smoking amount and retained pairs, we found that schizophrenia patients had significant sensory gating deficits in P50-N100-P200. The schizophrenia patients had demonstrated a unique pattern of sensory gating deficits, including repetition suppression deficits in P50 and stimulus registration deficits in N100/200. These results suggest that sensory gating is a pervasive cognitive abnormality in schizophrenia patients that is not limited to the pre-attentive phase of information processing. Since P200 exhibited a large effect size and did not require additional time during recruitment, future studies of P50-N100-P200 collectively are highly recommended.