We aimed to investigate electroencephalographic (EEG) markers of aberrant hyperfocusing, a novel framework of impaired selective attention, in schizophrenia patients by using theta phase-gamma ...amplitude coupling (TGC).
Fifty-four schizophrenia patients and 73 healthy controls (HCs) underwent EEG recording during an auditory oddball paradigm. For the standard and target conditions, TGC was calculated using the source signals from 25 brain regions of interest (ROIs) related to attention networks and sensory processing; TGC values were then compared across groups and conditions using two-way analysis of covariance. Correlations of altered TGC with performance on the Trail Making Test Parts A and B (TMT-A/B), were explored.
Compared to HCs, schizophrenia patients showed elevated TGC in the left inferior frontal gyrus (IFG) and superior temporal gyrus in the standard condition but not in the target condition. Correlation analyses revealed that the TGC in the left IFG was positively correlated with the TMT-A/B completion times.
Aberrant hyperfocusing, as reflected by elevated TGC in attention-related brain regions, was related to behavioral performance on the TMT-A/B in schizophrenia patients.
This study suggests that TGC is a electrophysiological marker for aberrant hyperfocusing of attentional processes that may result in cognitive impairments in schizophrenia patients.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The Bayesian brain framework has been proposed to explain how the brain processes and interprets sensory information. Magnetoencephalography (MEG) and electroencephalography (EEG) are two ...neuroimaging techniques commonly used with decoding models to study neural responses to auditory, visual and somatosensory stimuli. Our study aims to investigate neural responses to auditory stimuli using MEG data and to determine which temporal components in MEG data are sufficient for decoding surprise based on Bayesian models.
MEG data acquired from 18 subjects during an auditory binary oddball task was used. The data were pre-processed, and features were selected from different time windows. Five Bayesian learning models were applied to the experimental task stimuli, and each single trial's surprise value was calculated. The relationship between the extracted features in MEG data and the surprise regressors was investigated using linear regression and 5-fold cross-validation.
The results showed that the middle and late components of the MEG evoked potentials were significantly more informative than the early components. The results indicated that the Dirichlet-Categorical model outperformed the other model's decoding performance as demonstrated by higher R-squared values and lower MSE and BIC values.
The findings of this study provide evidence for the existence of a neural network that generates surprise in the human brain and highlight the importance of the middle and late components of the MEG evoked potentials for decoding the surprise value of auditory stimuli.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objective
In this paper, we develop a dynamic functional network connectivity (FNC) analysis approach using correlations between windowed time-courses of different brain networks (components) ...estimated via spatial independent component analysis (sICA). We apply the developed method to fMRI data to evaluate it and to study task-modulation of functional connections.
Materials and methods
We study the theoretical basis of the approach, perform a simulation analysis and apply it to fMRI data from schizophrenia patients (SP) and healthy controls (HC). Analyses on the fMRI data include: (a) group sICA to determine regions of significant task-related activity, (b) static and dynamic FNC analysis among these networks by using maximal lagged-correlation and time–frequency analysis, and (c) HC–SP group differences in functional network connections and in task-modulation of these connections.
Results
This new approach enables an assessment of task-modulation of connectivity and identifies meaningful inter-component linkages and differences between the two study groups during performance of an auditory oddball task (AOT). The static FNC results revealed that connectivities involving medial visual–frontal, medial temporal–medial visual, parietal–medial temporal, parietal–medial visual and medial temporal–anterior temporal were significantly greater in HC, whereas only the right lateral fronto-parietal (RLFP)–orbitofrontal connection was significantly greater in SP. The dynamic FNC revealed that task-modulation of motor–frontal, RLFP–medial temporal and posterior default mode (pDM)–parietal connections were significantly greater in SP, and task modulation of orbitofrontal–pDM and medial temporal–frontal connections were significantly greater in HC (all
P
< 0.05).
Conclusion
The task-modulation of dynamic FNC provided findings and differences between the two groups that are consistent with the existing hypothesis that schizophrenia patients show less segregated motor, sensory, cognitive functions and less segregated default mode network activity when engaged with a task. Dynamic FNC, based on sICA, provided additional results which are different than, but complementary to, those of static FNC. For example, it revealed dynamic changes in default mode network connectivities with other regions which were significantly different in schizophrenia in terms of task-modulation, findings which were not possible to discover by static FNC.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Schizophrenia is a psychiatric disorder that has been shown to disturb the dynamic top-down processing of sensory information. Various imaging techniques have revealed abnormalities in brain activity ...associated with this disorder, both locally and between cerebral regions. However, there is increasing interest in investigating dynamic network response to novel and relevant events at the network level during an attention-demanding task with high-temporal-resolution techniques. The aim of the work was: (i) to test the capacity of a novel algorithm to detect recurrent brain meta-states from auditory oddball task recordings; and (ii) to evaluate how the dynamic activation and behavior of the aforementioned meta-states were altered in schizophrenia, since it has been shown to impair top-down processing of sensory information.
A novel unsupervised method for the detection of brain meta-states based on recurrence plots and community detection algorithms, previously tested on resting-state data, was used on auditory oddball task recordings. Brain meta-states and several properties related to their activation during target trials in the task were extracted from electroencephalography data from patients with schizophrenia and cognitively healthy controls.
The methodology successfully detected meta-states during an auditory oddball task, and they appeared to show both frequency-dependent time-locked and non-time-locked activity with respect to the stimulus onset. Moreover, patients with schizophrenia displayed higher network diversity, and showed more sluggish meta-state transitions, reflected in increased dwell times, less complex meta-state sequences, decreased meta-state space speed, and abnormal ratio of negative meta-state correlations.
Abnormal cognition in schizophrenia is also reflected in decreased brain flexibility at the dynamic network level, which may hamper top-down processing, possibly indicating impaired decision-making linked to dysfunctional predictive coding. Moreover, the results showed the ability of the methodology to find meaningful and task-relevant changes in dynamic connectivity and pathology-related group differences.
Connectivity analysis using functional magnetic resonance imaging (fMRI) data is an important area, useful for the identification of biomarkers for various mental disorders, including schizophrenia. ...Most studies to date have focused on resting data, while the study of functional connectivity during task and the differences between task and rest are of great interest as well. In this work, we examine the graph-theoretical properties of the connectivity maps constructed using spatial components derived from independent component analysis (ICA) for healthy controls and patients with schizophrenia during an auditory oddball task (AOD) and at extended rest. We estimate functional connectivity using the higher-order statistical dependence, i.e., mutual information among the ICA spatial components, instead of the typically used temporal correlation. We also define three novel topological metrics based on the modules of brain networks obtained using a clustering approach. Our experimental results show that although the schizophrenia patients preserve the small-world property, they present a significantly lower small-worldness during both AOD task and rest when compared to the healthy controls, indicating a consistent tendency towards a more random organization of brain networks. In addition, the task-induced modulations to topological measures of several components involving motor, cerebellum and parietal regions are altered in patients relative to controls, providing further evidence for the aberrant connectivity in schizophrenia.
► Functional connectivity is quantified using higher-order spatial information. ► Connectivity during task and rest is studied using graph-theoretical analysis. ► Novel metrics are proposed based on the modules obtained by a clustering approach. ► Meaningful task-induced modulations to connectivity are found in the healthy group. ► Altered topological properties of connectivity are observed in schizophrenia group.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
To assess the integration of peripheral (heart rate, HR) and central (event-related potential, P300) measures of cognition, the present study varied inter-stimulus presentation time (ISI) and ...employed comparable data reduction methods for the HR and ERP data. Young adults (n=33) performed an auditory oddball count task in which the ISI was varied (short vs. long, to maximize target detection for both measures) and task condition (single stimulus, short-ISI oddball, long-ISI oddball, to assay stimulus presentation condition between HR and P300). The off-line cardiotachometer method parallels signal averaging and was applied to HR data reduction. The main goal was to characterize target vs. standard processing in each measurement type using appropriate recording approaches with respect to differentiating the two stimuli in each task (target vs. silence, target vs. standard short-ISI, target vs. standard long-ISI). Results demonstrated reliable differences between target/standard stimuli for both the biphasic HR (deceleration/acceleration) signal and for P300 amplitude production, with larger amplitudes for target than standard. The short and long ISIs yielded no reliable initial HR deceleration differences, but the late acceleration was observed for the long-ISI condition only. Correlational analysis between HR and P300 measures indicated that people with smaller HR deceleration had larger P300 amplitude suggesting that the larger target/standard differences for HR deceleration and P300 amplitude, observed at an experimental level, are reversed at an individual level. The contributions of simultaneously recording HR and P300 to characterize cognition and theoretical implications are discussed.
•Heart rate and P300 can be successfully integrated in the oddball paradigm if using appropriate inter-stimulus intervals.•The two cardiac components of the response can be fully detected only if using inter-stimulus intervals longer the 3 seconds.•Both cardiac components covary differently with P300 helping to disentangle the attention and memory components of P300.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The aim of the study was to investigate differences in electrophysiological brain activity between children diagnosed with attention deficit hyperactivity disorder combined type (ADHD-Com) and ...normally developing children, using the auditory 2-tone oddball paradigm. Forty right-handed subjects aged between 6.9 and 12.3years participated in the present study, with 16 boys and 4 girls in each of the control and ADHD-Com groups. Children were individually age- and gender-matched. The auditory oddball task consisted of 155 standards (1 KHz, p=.66) and 80 targets (1.5KHz, p=.34), presented randomly one at a time. Subjects were instructed to listen to the sounds and count the rare tones. Task performance in ADHD children did not differ compared to that in the control group. Event-related potentials (ERPs) elicited to target and standard stimuli were analyzed for between-group differences. The ADHD group showed enhanced P2 and reduced N2 component to both oddball stimuli, followed by reduced P3 component to attended targets compared with controls. The difference in the P3 amplitude between targets and standards was smaller in the ADHD group, particularly over the right hemisphere. These results suggest deficiencies in both automatic and controlled processing in children with ADHD. Enhanced amplitude of the P2 in ADHD children may reflect an early orienting deficit which affects later processing stages in the oddball task. Reduced amplitude of the N2 in the clinical group may be associated with stimulus discrimination impairment and inappropriate conflict monitoring. Reduced amplitude of target P3 and its asymmetrical distribution in ADHD children may reflect a deficit in higher-level executive functions, such as attention allocation and stimulus evaluation, accompanied by an impairment of global aspects of attentional processing that are under right hemisphere control.
► ADHD-Com children do not differ from controls on performance measures. ► Amplitude of target and standard P2 is enhanced in ADHD-Com children. ► Amplitude of target and standard N2 is reduced in ADHD-Com children. ► Amplitude of target P3 is reduced in ADHD-Com children.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
PDF
