Altered Oscillation and Synchronization of Default-Mode Network Activity in Mild Alzheimer’s Disease Compared to Mild Cognitive Impairment: An Electrophysiological Study

Some researchers have suggested that the default mode network (DMN) plays an important role in the pathological mechanisms of Alzheimer’s disease (AD). To examine whether the cortical activities in DMN regions show significant difference between mild AD from mild cognitive impairment (MCI), electrophysiological responses were analyzed from 21 mild Alzheimer’s disease (AD) and 21 mild cognitive impairment (MCI) patients during an eyes closed, resting-state condition. The spectral power and functional connectivity of the DMN were estimated using a minimum norm estimate (MNE) combined with fast Fourier transform and imaginary coherence analysis. Our results indicated that source-based EEG maps of resting-state activity showed alterations of cortical spectral power in mild AD when compared to MCI. These alterations are characteristic of attenuated alpha or beta activities in the DMN, as are enhanced delta or theta activities in the medial temporal, inferior parietal, posterior cingulate cortex and precuneus. With regard to altered synchronization in AD, altered functional interconnections were observed as specific connectivity patterns of connection hubs in the precuneus, posterior cingulate cortex, anterior cingulate cortex and medial temporal regions. Moreover, posterior theta and alpha power and altered connectivity in the medial temporal lobe correlated significantly with scores obtained on the Mini-Mental State Examination (MMSE). In conclusion, EEG is a useful tool for investigating the DMN in the brain and differentiating early stage AD and MCI patients. This is a promising finding; however, further large-scale studies are needed.     

Functional organization of the brain cortical areas at rest condition in children 5, 6 and 7 years old

Functional connectivity at rest was studied in children of 5, 6 and 7 years old. Connection strengths were estimated using coherence function taken at the frequencies of the major EEG rhythms. Factor analysis of the raw coherence data revealed 4 different cortico-cortical functional connectivity patterns. These patterns are stable across the studied age span although particular functional links may change reflecting the general trend of heterchronous maturation of the cortex.     

The research of constructing dynamic cognition model based on brain network

Estimating the functional interactions and connections between brain regions to corresponding process in cognitive, behavioral and psychiatric domains is a central pursuit for understanding the human connectome. Few studies have examined the effects of dynamic evolution on cognitive processing and brain activation using brain network model in scalp electroencephalography (EEG) data. Aim of this study was to investigate the brain functional connectivity and construct dynamic programing model from EEG data and to evaluate a possible correlation between topological characteristics of the brain connectivity and cognitive evolution processing. Here, functional connectivity between brain regions is defined as the statistical dependence between EEG signals in different brain areas and is typically determined by calculating the relationship between regional time series using wavelet coherence. We present an accelerated dynamic programing algorithm to construct dynamic cognitive model that we found that spatially distributed regions coherence connection difference, the topologic characteristics with which they can transfer information, producing temporary network states. Our findings suggest that brain dynamics give rise to variations in complex network properties over time after variation audio stimulation, dynamic programing model gives the dynamic evolution processing at different time and frequency. In this paper, by applying a new construct approach to understand whole brain network dynamics, firstly, brain network is constructed by wavelet coherence, secondly, different time active brain regions are selected by network topological characteristics and minimum spanning tree. Finally, dynamic evolution model is constructed to understand cognitive process by dynamic programing algorithm, this model is applied to the auditory experiment, results showed that, quantitatively, more correlation was observed after variation audio stimulation, the EEG function connection dynamic evolution model on cognitive processing is feasible with wavelet coherence EEG recording.     

Only Low Frequency Event-Related EEG Activity Is Compromised in Multiple Sclerosis: Insights from an Independent Component Clustering Analysis

Cognitive impairment (CI), often examined with neuropsychological tests such as the Paced Auditory Serial Addition Test (PASAT), affects approximately 65% of multiple sclerosis (MS) patients. The P3b event-related potential (ERP), evoked when an infrequent target stimulus is presented, indexes cognitive function and is typically compared across subjects'' scalp electroencephalography (EEG) data. However, the clustering of independent components (ICs) is superior to scalp-based EEG methods because it can accommodate the spatiotemporal overlap inherent in scalp EEG data. Event-related spectral perturbations (ERSPs; event-related mean power spectral changes) and inter-trial coherence (ITCs; event-related consistency of spectral phase) reveal a more comprehensive overview of EEG activity. Ninety-five subjects (56 MS patients, 39 controls) completed visual and auditory two-stimulus P3b event-related potential tasks and the PASAT. MS patients were also divided into CI and non-CI groups (n = 18 in each) based on PASAT scores. Data were recorded from 128-scalp EEG channels and 4 IC clusters in the visual, and 5 IC clusters in the auditory, modality were identified. In general, MS patients had significantly reduced ERSP theta power versus controls, and a similar pattern was observed for CI vs. non-CI MS patients. The ITC measures were also significantly different in the theta band for some clusters. The finding that MS patients had reduced P3b task-related theta power in both modalities is a reflection of compromised connectivity, likely due to demyelination, that may have disrupted early processes essential to P3b generation, such as orientating and signal detection. However, for posterior sources, MS patients had a greater decrease in alpha power, normally associated with enhanced cognitive function, which may reflect a compensatory mechanism in response to the compromised early cognitive processing.     

Analysis of phase-locking is informative for studying event-related EEG activity

 A new method is presented for quantitative evaluation of single-sweep phase and amplitude electroencephalogram (EEG) characteristics that is a more informative approach in comparison with conventional signal averaging. In the averaged potential, phase-locking and amplitude effects of the EEG response cannot be separated. To overcome this problem, single-trial EEG sweeps are decomposed into separate presentations of their phase relationships and amplitude characteristics. The stability of the phase-coupling to stimulus is then evaluated independently by analyzing the single-sweep phase presentations. The method has the following advantages: information about stability of the phase-locking can be used to assess event-related oscillatory activity; the method permits evaluation of the timing of event-related phase-locking; and a global assessment and comparison of the phase-locking of ensembles of single sweeps elicited in different processing conditions is possible. The method was employed to study auditory alpha and theta responses in young and middle-aged adults. The results showed that whereas amplitudes of frequency responses tended to decrease, the phase-locking increased significantly with age. The synchronization with stimulus (phase-locking) was the only parameter reliably to differentiate the brain responses of the two age groups, as well as to reveal specific age-related changes in frontal evoked alpha activity. Thus, the present approach can be used to evaluate dynamic brain processes more precisely. Received: 12 February 1996 / Accepted in revised form: 11 October 1996     

Coherence and phase locking in the scalp EEG and between LORETA model sources, and microstates as putative mechanisms of brain temporo-spatial functional organization.

Brain electric mechanisms of temporary, functional binding between brain regions are studied using computation of scalp EEG coherence and phase locking, sensitive to time differences of few milliseconds. However, such results if computed from scalp data are ambiguous since electric sources are spatially oriented. Non-ambiguous results can be obtained using calculated time series of strength of intracerebral model sources. This is illustrated applying LORETA modeling to EEG during resting and meditation. During meditation, time series of LORETA model sources revealed a tendency to decreased left-right intracerebral coherence in the delta band, and to increased anterior-posterior intracerebral coherence in the theta band. An alternate conceptualization of functional binding is based on the observation that brain electric activity is discontinuous, i.e., that it occurs in chunks of up to about 100 ms duration that are detectable as quasi-stable scalp field configurations of brain electric activity, called microstates. Their functional significance is illustrated in spontaneous and event-related paradigms, where microstates associated with imagery- versus abstract-type mentation, or while reading positive versus negative emotion words showed clearly different regions of cortical activation in LORETA tomography. These data support the concept that complete brain functions of higher order such as a momentary thought might be incorporated in temporal chunks of processing in the range of tens to about 100 ms as quasi-stable brain states; during these time windows, subprocesses would be accepted as members of the ongoing chunk of processing.     

Resting-State Network Disruption and APOE Genotype in Alzheimer's Disease: A lagged Functional Connectivity Study

Background

The apolipoprotein E epsilon 4 (APOE-4) is associated with a genetic vulnerability to Alzheimer''s disease (AD) and with AD-related abnormalities in cortical rhythms. However, it is unclear whether APOE-4 is linked to a specific pattern of intrinsic functional disintegration of the brain after the development of the disease or during its different stages. This study aimed at identifying spatial patterns and effects of APOE genotype on resting-state oscillations and functional connectivity in patients with AD, using a physiological connectivity index called “lagged phase synchronization”.

Methodology/Principal Findings

Resting EEG was recorded during awake, eyes-closed state in 125 patients with AD and 60 elderly controls. Source current density and functional connectivity were determined using eLORETA. Patients with AD exhibited reduced parieto-occipital alpha oscillations compared with controls, and those carrying the APOE-4 allele had reduced alpha activity in the left inferior parietal and temporo-occipital cortex relative to noncarriers. There was a decreased alpha2 connectivity pattern in AD, involving the left temporal and bilateral parietal cortex. Several brain regions exhibited increased lagged phase synchronization in low frequencies, specifically in the theta band, across and within hemispheres, where temporal lobe connections were particularly compromised. Areas with abnormal theta connectivity correlated with cognitive scores. In patients with early AD, we found an APOE-4-related decrease in interhemispheric alpha connectivity in frontal and parieto-temporal regions.

Conclusions/Significance

In addition to regional cortical dysfunction, as indicated by abnormal alpha oscillations, there are patterns of functional network disruption affecting theta and alpha bands in AD that associate with the level of cognitive disturbance or with the APOE genotype. These functional patterns of nonlinear connectivity may potentially represent neurophysiological or phenotypic markers of AD, and aid in early detection of the disorder.     

Resting-state quantitative electroencephalography reveals increased neurophysiologic connectivity in depression

Symptoms of Major Depressive Disorder (MDD) are hypothesized to arise from dysfunction in brain networks linking the limbic system and cortical regions. Alterations in brain functional cortical connectivity in resting-state networks have been detected with functional imaging techniques, but neurophysiologic connectivity measures have not been systematically examined. We used weighted network analysis to examine resting state functional connectivity as measured by quantitative electroencephalographic (qEEG) coherence in 121 unmedicated subjects with MDD and 37 healthy controls. Subjects with MDD had significantly higher overall coherence as compared to controls in the delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), and beta (12-20 Hz) frequency bands. The frontopolar region contained the greatest number of "hub nodes" (surface recording locations) with high connectivity. MDD subjects expressed higher theta and alpha coherence primarily in longer distance connections between frontopolar and temporal or parietooccipital regions, and higher beta coherence primarily in connections within and between electrodes overlying the dorsolateral prefrontal cortical (DLPFC) or temporal regions. Nearest centroid analysis indicated that MDD subjects were best characterized by six alpha band connections primarily involving the prefrontal region. The present findings indicate a loss of selectivity in resting functional connectivity in MDD. The overall greater coherence observed in depressed subjects establishes a new context for the interpretation of previous studies showing differences in frontal alpha power and synchrony between subjects with MDD and normal controls. These results can inform the development of qEEG state and trait biomarkers for MDD.     

Resting-state EEG source localization and functional connectivity in schizophrenia-like psychosis of epilepsy

Background

It is unclear whether, like in schizophrenia, psychosis-related disruption in connectivity between certain regions, as an index of intrinsic functional disintegration, occurs in schizophrenia-like psychosis of epilepsy (SLPE). In this study, we sought to determine abnormal patterns of resting-state EEG oscillations and functional connectivity in patients with SLPE, compared with nonpsychotic epilepsy patients, and to assess correlations with psychopathological deficits.

Methodology/Principal Findings

Resting EEG was recorded in 21 patients with focal epilepsy and SLPE and in 21 clinically-matched non-psychotic epilepsy controls. Source current density and functional connectivity were determined using eLORETA software. For connectivity analysis, a novel nonlinear connectivity measure called “lagged phase synchronization” was used. We found increased theta oscillations in regions involved in the default mode network (DMN), namely the medial and lateral parietal cortex bilaterally in the psychotic patients relative to their nonpsychotic counterparts. In addition, patients with psychosis had increased beta temporo-prefrontal connectivity in the hemisphere with predominant seizure focus. This functional connectivity in temporo-prefrontal circuits correlated with positive symptoms. Additionally, there was increased interhemispheric phase synchronization between the auditory cortex of the affected temporal lobe and the Broca''s area correlating with auditory hallucination scores.

Conclusions/Significance

In addition to dysfunction of parietal regions that are part of the DMN, resting-state disrupted connectivity of the medial temporal cortex with prefrontal areas that are either involved in the DMN or implicated in psychopathological dysfunction may be critical to schizophrenia-like psychosis, especially in individuals with temporal lobe epilepsy. This suggests that DMN deficits might be a core neurobiological feature of the disorder, and that abnormalities in theta oscillations and beta phase synchronization represent the underlying neural activity.     

Increased Intrinsic Connectivity of the Default Mode Network in Temporal Lobe Epilepsy: Evidence from Resting-State MEG Recordings

The electrophysiological signature of resting state oscillatory functional connectivity within the default mode network (DMN) during spike-free periods in temporal lobe epilepsy (TLE) remains unclear. Using magnetoencephalographic (MEG) recordings, this study investigated how the connectivity within the DMN was altered in TLE, and we examined the effect of lateralized TLE on functional connectivity. Sixteen medically intractable TLE patients and 22 controls participated in this study. Whole-scalp 306-channel MEG epochs without interictal spikes generated from both MEG and EEG data were analyzed using a minimum norm estimate (MNE) and source-based imaginary coherence analysis. With this processing, we obtained the cortical activation and functional connectivity within the DMN. The functional connectivity was increased between DMN and the right medial temporal (MT) region at the delta band and between DMN and the bilateral anterior cingulate cortex (ACC) regions at the theta band. The functional change was associated with the lateralization of TLE. The right TLE showed enhanced DMN connectivity with the right MT while the left TLE demonstrated increased DMN connectivity with the bilateral MT. There was no lateralization effect of TLE upon the DMN connectivity with ACC. These findings suggest that the resting-state functional connectivity within the DMN is reinforced in temporal lobe epilepsy during spike-free periods. Future studies are needed to examine if the altered functional connectivity can be used as a biomarker for treatment responses, cognitive dysfunction and prognosis in patients with TLE.     

EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful.     

Power spectral density and coherence analysis of Alzheimer’s EEG

In this paper, we investigate the abnormalities of electroencephalograph (EEG) signals in the Alzheimer’s disease (AD) by analyzing 16-scalp electrodes EEG signals and make a comparison with the normal controls. The power spectral density (PSD) which represents the power distribution of EEG series in the frequency domain is used to evaluate the abnormalities of AD brain. Spectrum analysis based on autoregressive Burg method shows that the relative PSD of AD group is increased in the theta frequency band while significantly reduced in the alpha2 frequency bands, particularly in parietal, temporal, and occipital areas. Furthermore, the coherence of two EEG series among different electrodes is analyzed in the alpha2 frequency band. It is demonstrated that the pair-wise coherence between different brain areas in AD group are remarkably decreased. Interestingly, this decrease of pair-wise electrodes is much more significant in inter-hemispheric areas than that in intra-hemispheric areas. Moreover, the linear cortico-cortical functional connectivity can be extracted based on coherence matrix, from which it is shown that the functional connections are obviously decreased, the same variation trend as relative PSD. In addition, we combine both features of the relative PSD and the normalized degree of functional network to discriminate AD patients from the normal controls by applying a support vector machine model in the alpha2 frequency band. It is indicated that the two groups can be clearly classified by the combined feature. Importantly, the accuracy of the classification is higher than that of any one feature. The obtained results show that analysis of PSD and coherence-based functional network can be taken as a potential comprehensive measure to distinguish AD patients from the normal, which may benefit our understanding of the disease.     

Frontal bilateral synchronous theta waves and the resting EEG coherence in children aged 7–8 and 9–10 with learning difficulties

The resting state cortical functional connectivity was studied in children of 7–8 (N = 29) and 9–10 (N = 23) years with learning difficulties whose EEG showed the frontal bilateral synchronous theta waves (FTW) and in the control children of 7–8 (N = 32) and 9–10 (N = 16) years who did not experience school difficulties and whose EEG did not show signs of abnormality. The functional connectivity was estimated in the θ, α₁, α₂, and β₁ frequency bands via measuring the coherence for the resting EEG that was free from any abnormal patterns. Compared to control children, there was a reduction in the strength of the functional coupling between the frontal and anterior temporal cortices found predominantly in the left hemisphere of FTW children. The relative weakness of the coupling between the frontal cortex and the other cortical areas was more pronounced in children of 7–8 than in children of 9–10 years. These between-group differences were unaffected by the frequency band or gender factors.     

Hemispheric organization of verbal memory functions in seasonal winter depression: electrophysiological analysis

Spatial organization of EEG power and coherence during memorization of dichotically presented lists of words were studied in patients with winter depression (N = 17) and control subjects (N = 22). In contrast to the control subjects, the depressed patients were characterized by the higher theta power in the right parietal and posterior temporal regions and the dominance of the alpha 2 in the left midfrontal area. The patients also differed in the lower theta 2 coherence in the left hemisphere and lower alpha 1 coherence in the right hemisphere. These effects showed different intrahemispheric distribution. The interhemispheric EEG coherence in the theta 2 range between the frontal areas and alpha 1 coherence between the left frontal and right posterior areas was lower in the patients than in the control subjects. Verbal-emotional interaction in depressions are discussed.     

Classification of the adolescent EEG by the spectral and segmental characteristics for normals

The 16-channel EEG records of 45 adolescents with schizophrenia and 39 healthy adolescents were subjected to statistical combinatorial analysis of 160 elementary EEG characteristics (6 spectral and 4 segmental EEG characteristics for a channel). Employing pattern recognition algorithm "Kora-n", a list of 37 combined EEG patterns was compiled. This list characterized with a minimal error the EEG of healthy adolescents in such a way that none of these characters featured the EEG of adolescents with schizophrenia. Analysis of this list of EEG characteristics suggests that the contrast between EEG of healthy and ill adolescents is the sharpest in the F4, Cz, T3 and O1 derivations. Compared to EEG samples of schizophrenic subjects, EEGs of healthy subjects exhibit lower levels of delta and theta activity mainly in the frontal and temporal regions of the cortex and higher level of alpha activity predominantly in the occipital region. Applicability of the list of EEG patterns for diagnostics of schizophrenia-type disorders of adolescents is discussed.     

Functional Connectivity Changes in Resting-State EEG as Potential Biomarker for Amyotrophic Lateral Sclerosis

Background

Amyotrophic Lateral Sclerosis (ALS) is heterogeneous and overlaps with frontotemporal dementia. Spectral EEG can predict damage in structural and functional networks in frontotemporal dementia but has never been applied to ALS.

Methods

18 incident ALS patients with normal cognition and 17 age matched controls underwent 128 channel EEG and neuropsychology assessment. The EEG data was analyzed using FieldTrip software in MATLAB to calculate simple connectivity measures and scalp network measures. sLORETA was used in nodal analysis for source localization and same methods were applied as above to calculate nodal network measures. Graph theory measures were used to assess network integrity.

Results

Cross spectral density in alpha band was higher in patients. In ALS patients, increased degree values of the network nodes was noted in the central and frontal regions in the theta band across seven of the different connectivity maps (p<0.0005). Among patients, clustering coefficient in alpha and gamma bands was increased in all regions of the scalp and connectivity were significantly increased (p=0.02). Nodal network showed increased assortativity in alpha band in the patients group. The Clustering Coefficient in Partial Directed Connectivity (PDC) showed significantly higher values for patients in alpha, beta, gamma, theta and delta frequencies (p=0.05).

Discussion

There is increased connectivity in the fronto-central regions of the scalp and areas corresponding to Salience and Default Mode network in ALS, suggesting a pathologic disruption of neuronal networking in early disease states. Spectral EEG has potential utility as a biomarker in ALS.     

Electrophysiological Correlates of Morphological Neuroplasticity in Human Callosal Dysgenesis

In search for the functional counterpart of the alternative Probst and sigmoid bundles, considered as morphological evidence of neuroplasticity in callosal dysgenesis, electroencephalographic (EEG) coherence analysis was combined with high resolution and diffusion tensor magnetic resonance imaging. Data of two patients with callosal agenesis, plus two with typical partial dysgenesis with a remnant genu, and one atypical patient with a substantially reduced genu were compared to those of fifteen neurotypic controls. The interhemispheric EEG coherence between homologous nontemporal brain regions corresponded to absence or partial presence of callosal connections. A generalized coherence reduction was observed in complete acallosal patients, as well as coherence preservation in the anterior areas of the two patients with a remnant genu. jThe sigmoid bundles found in three patients with partial dysgenesis correlated with augmented EEG coherence between anterior regions of one hemisphere and posterior regions of the other. These heterologous (crossed) interhemispheric connections were asymmetric in both imaging and EEG patterns, with predominance of the right-anterior-to-left-posterior connections over the mirror ones. The Probst bundles correlated with higher intrahemispheric long-distance coherence in all patients. The significant correlations observed for the delta, theta and alpha bands indicate that these alternative pathways are functional, although the neuropsychological nature of this function is still unknown.     

Affective pictures processing is reflected by an increased long-distance EEG connectivity

Analysis of affective picture processing by means of EEG has invaded the literature. The methodology of event-related EEG coherence is one of the essential methods used to analyze functional connectivity. The aims of the present study are to find out the long range EEG connectivity changes in perception of different affective pictures and analyze gender differences in these long range connected networks. EEGs of 28 healthy subjects (14 female) were recorded at 32 locations. The participants passively viewed emotional pictures (IAPS, unpleasant, pleasant, neutral). The long-distance intra-hemispheric event-related coherence was analyzed for delta (1–3.5 Hz), theta (4–7.5 Hz), and alpha (8–13 Hz) frequency ranges for F₃–T₇, F₄–T₈, F₃–TP₇, F₄–TP₈, F₃–P₃, F₄–P₄, F₃–O₁, F₄–O₂, C₃–O₁, C₄–O₂ electrode pairs. Unpleasant pictures elicited significantly higher delta coherence values than neutral pictures (p < 0.05), over fronto-parietal, fronto-occipital, and centro-occipital electrode pairs. Furthermore, unpleasant pictures elicited higher theta coherence values than pleasant (p < 0.05) and neutral pictures (p < 0.05). The present study showed that female subjects had higher delta (p < 0.05) and theta (p < 0.05) coherence values than male subjects. This difference was observed more for emotional pictures than for neutral pictures. This study showed that the brain connectivity was higher during emotional pictures than neutral pictures. Females had higher connectivity between different parts of the brain than males during emotional processes. According to these results, we may comment that increased valence and arousal caused increased brain activity. It seems that not just single sources but functional networks were also activated during perception of emotional pictures.     

Bilateral frontal theta-waves in EEG of 7-8-year-old children with learning difficulties: qualitative and quantitative analysis

We analyzed EEG recorded in the rest condition (eye closed) in 22 children aged from 7 to 8 years old who experienced learning difficulties and whose EEG recordings were characterized by sporadic short-term appearance of bilateral synchronous slow waves over the frontal and/or central cortices--frontal theta-waves (FTW). The vector autoregressive modeling was used in order to assess the strength of directed cortico-cortical functional connectivity pattern for FTW and for surrounding EEG. The comparison of the two patterns showed that FTW is characterized by diffuse strengthening of the functional links connecting frontal, central and (to some extent) temporal cortices as well as the links directed to the above regions from the other cortical areas. The results of the study suggest that FTW is most probably caused by the common for the fronto-central cortices neuronal theta activity synchronized via cortico-subcortical links. This suggestion is in a good agreement with the view that FTW reflects the alterations in functioning of fronto-thalamic system.     

Bilateral frontal theta-waves in EEG of 7–8-year-old children with learning difficulties: Qualitative and quantitative analysis

We analyzed EEG recorded in the rest condition (eye closed) in 22 children aged from 7 to 8 years old who experienced learning difficulties and whose EEG recordings were characterized by sporadic shortterm appearance of bilateral synchronous slow waves over the frontal and/or frontal and central cortices??frontal theta-waves (FTW). The vector autoregressive modeling was used in order to assess the strength of directed cortico-cortical functional connectivity pattern for FTW and for surrounding EEG. The comparison of the two patterns showed that FTW is characterized by diffuse strengthening of the functional links connecting frontal, central and (to some extent) temporal cortices as well as the links directed to the above regions from the other cortical areas. The results of the study suggest that FTW is most probably caused by the common for the frontal and central cortices neuronal theta activity synchronized via cortico-subcortical links. This suggestion is in a good agreement with the view that FTW reflects the alterations in functioning of fronto-thalamic system.