Low Functional network integrity in cognitively unimpaired and MCI subjects with depressive symptoms: results from a multi-center fMRI study.

Evidence suggests that depressive symptomatology is a consequence of network dysfunction rather than lesion pathology. We studied whole-brain functional connectivity using a Minimum Spanning Tree as a graph-theoretical approach. Furthermore, we examined functional connectivity in the Default Mode Network, the Frontolimbic Network (FLN), the Salience Network, and the Cognitive Control Network. All 183 elderly subjects underwent a comprehensive neuropsychological evaluation and a 3 Tesla brain MRI scan. To assess the potential presence of depressive symptoms, the 13-item version of the Beck Depression Inventory (BDI) or the Geriatric Depression Scale (GDS) was utilized. Participants were assigned into three groups based on their cognitive status: amnestic mild cognitive impairment (MCI), non-amnestic MCI, and healthy controls. Regarding affective symptoms, subjects were categorized into depressed and non-depressed groups. An increased mean eccentricity and network diameter were found in patients with depressive symptoms relative to non-depressed ones, and both measures showed correlations with depressive symptom severity. In patients with depressive symptoms, a functional hypoconnectivity was detected between the Anterior Cingulate Cortex (ACC) and the right amygdala in the FLN, which impairment correlated with depressive symptom severity. While no structural difference was found in subjects with depressive symptoms, the volume of the hippocampus and the thickness of the precuneus and the entorhinal cortex were decreased in subjects with MCI, especially in amnestic MCI. The increase in eccentricity and diameter indicates a more path-like functional network configuration that may lead to an impaired functional integration in depression, a possible cause of depressive symptomatology in the elderly.

Comparison of the diagnostic accuracy of resting-state fMRI driven machine learning algorithms in the detection of mild cognitive impairment.

Mild cognitive impairment (MCI) is a potential therapeutic window in the prevention of dementia; however, automated detection of early cognitive deterioration is an unresolved issue. The aim of our study was to compare various classification approaches to differentiate MCI patients from healthy controls, based on rs-fMRI data, using machine learning (ML) algorithms. Own dataset (from two centers) and ADNI database were used during the analysis. Three fMRI parameters were applied in five feature selection algorithms: local correlation, intrinsic connectivity, and fractional amplitude of low frequency fluctuations. Support vector machine (SVM) and random forest (RF) methods were applied for classification. We achieved a relatively wide range of 78-87% accuracy for the various feature selection methods with SVM combining the three rs-fMRI parameters. In the ADNI datasets case we can also see even 90% accuracy scores. RF provided a more harmonized result among the feature selection algorithms in both datasets with 80-84% accuracy for our local and 74-82% for the ADNI database. Despite some lower performance metrics of some algorithms, most of the results were positive and could be seen in two unrelated datasets which increase the validity of our methods. Our results highlight the potential of ML-based fMRI applications for automated diagnostic techniques to recognize MCI patients.

EEG Alpha and Beta Band Functional Connectivity and Network Structure Mark Hub Overload in Mild Cognitive Impairment During Memory Maintenance.

Background: While decreased alpha and beta-band functional connectivity (FC) and changes in network topology have been reported in Alzheimer's disease, it is not yet entirely known whether these differences can mark cognitive decline in the early stages of the disease. Our study aimed to analyze electroencephalography (EEG) FC and network differences in the alpha and beta frequency band during visuospatial memory maintenance between Mild Cognitive Impairment (MCI) patients and healthy elderly with subjective memory complaints. Methods: Functional connectivity and network structure of 17 MCI patients and 20 control participants were studied with 128-channel EEG during a visuospatial memory task with varying memory load. FC between EEG channels was measured by amplitude envelope correlation with leakage correction (AEC-c), while network analysis was performed by applying the Minimum Spanning Tree (MST) approach, which reconstructs the critical backbone of the original network. Results: Memory load (increasing number of to-be-learned items) enhanced the mean AEC-c in the control group in both frequency bands. In contrast to that, after an initial increase, the MCI group showed significantly (p < 0.05) diminished FC in the alpha band in the highest memory load condition, while in the beta band this modulation was absent. Moreover, mean alpha and beta AEC-c correlated significantly with the size of medial temporal lobe structures in the entire sample. The network analysis revealed increased maximum degree, betweenness centrality, and degree divergence, and decreased diameter and eccentricity in the MCI group compared to the control group in both frequency bands independently of the memory load. This suggests a rerouted network in the MCI group with a more centralized topology and a more unequal traffic load distribution. Conclusion: Alpha- and beta-band FC measured by AEC-c correlates with cognitive load-related modulation, with subtle medial temporal lobe atrophy, and with the disruption of hippocampal fiber integrity in the earliest stages of cognitive decline. The more integrated network topology of the MCI group is in line with the "hub overload and failure" framework and might be part of a compensatory mechanism or a consequence of neural disinhibition.

Subclinical epileptiform activity accelerates the progression of Alzheimer's disease: A long-term EEG study.

OBJECTIVE: While many studies suggest that patients with Alzheimer's disease have a higher chance for developing epileptic seizures, only a few studies are available examining independent epileptic discharges. The major aims of our study was to determine the prevalence of subclinical epileptiform activity (SEA) in AD compared to healthy elderly controls with the hypothesis that SEA is more frequent in AD than in cognitively normal individuals. Another aim was to analyze the effect of baseline SEA captured with electroencephalography on the progression of the disease with longitudinal cognitive testing. METHODS: We investigated 52 Alzheimer patients with no history of epileptic seizures and 20 healthy individuals. All participants underwent a 24-hour electroencephalography, neurology, neuroimaging and neuropsychology examination. Two independent raters analyzed visually the electroencephalograms and both raters were blind to the diagnoses. Thirty-eight Alzheimer patients were enrolled in a 3-year long prospective follow-up study with yearly repeated cognitive evaluation. RESULTS: Subclinical epileptiform discharges were recorded significantly (p:0.018) more frequently in Alzheimer patients (54%) than in healthy elderly (25%). Epileptiform discharges were associated with lower performance scores in memory. Alzheimer patients with spikes showed 1.5-times faster decline in global cognitive scores than patients without (p < 0.001). The decline in cognitive performance scores showed a significant positive correlation with spike frequency (r:+0.664; p < 0.001). CONCLUSIONS: Subclinical epileptiform activity occurs in half of Alzheimer patients who have never suffered epileptic seizures. Alzheimer patients with subclinical epileptiform activity showed accelerated cognitive decline with a strong relation to the frequency and spatial distribution (left temporal) of spikes. SIGNIFICANCE: Our findings suggest the prominent role of epileptiform discharges in the pathomechanism of Alzheimer's disease which might serve as potential therapeutic target.

Prevalence, Semiology, and Risk Factors of Epilepsy in Alzheimer's Disease: An Ambulatory EEG Study.

BACKGROUND: Alzheimer's disease (AD) is the primary cause of cognitive decline. A growing body of evidence suggests that AD patients have a higher risk to develop epileptic seizures; however, results are contradictory due to different methodological approaches of previous studies. OBJECTIVE: We aimed to identify the prevalence, semiology, and risk factors of epilepsy in AD using long-term EEG. METHODS: We selected forty-two AD patients and examined them using 24-hour ambulatory EEG. Neurological and epileptological data were collected with retro- and prospective methods. We analyzed the semiology of the identified seizures and the possible risk factors using logistic regression analysis. RESULTS: We identified seizures confirmed by EEG in 24%. The majority of the seizures were aware focal (72%) without any motor activity (55%). We found epileptiform discharges without seizures in 28%. Patients with seizures and only with epileptic EEG activity showed similar clinical and demographical features. Higher education (OR:1.8) and lower Addenbrooke Examination Score (OR: 0.9) were identified as risk factors of epilepsy. Increase of 0.1 point in the Verbal-Language/Orientation-Memory ratio (VLOM) was associated with higher epilepsy risk as well (OR:2.9). CONCLUSION: Epilepsy is a frequent comorbidity of AD. Since most of the seizures are aware non-motor focal seizures, sensitive EEG techniques are required for precise diagnosis of epilepsy. Long-term ambulatory EEG is a safe and well-tolerated option. Epileptiform EEG in AD signals the presence of concomitant epilepsy. Clinicians have to pay attention to comorbid epilepsy in dementia patients with high education, with high VLOM ratio and severe stage.

Decreased Event-Related Beta Synchronization During Memory Maintenance Marks Early Cognitive Decline in Mild Cognitive Impairment.

Mild cognitive impairment (MCI) refers to a measurable deficit in cognition in the absence of dementia or impairment in activities of daily living. Working memory impairment is among the earliest signs of MCI. Oscillatory analysis of working memory might be a potential tool for identifying patients at increased risk of developing dementia. Our study aimed to assess the temporospatial pattern of spectral differences during working memory maintenance between MCI patients and healthy controls and to compare the sources of oscillatory activity between the two groups. Event-related spectral perturbation of 17 MCI patients and 21 healthy control participants was studied with 128-channel EEG during the Sternberg working memory task. Source localization was performed by using the eLORETA software. Among the participants, 13 MCI and 15 control participants underwent a structural brain MRI examination. Event-related synchronization (ERS) in the alpha and beta frequency band was significantly lower in MCI patients compared to healthy control participants during retention. Both study groups showed significant memory load-related enhancement in both frequency band. In the MCI group, source localization revealed significantly attenuated beta oscillatory activity in the inferior and middle temporal gyrus, in the fusiform gyrus, and in the cuneus. Beta ERS correlated significantly with the size of the hippocampus, entorhinal cortex, and parahippocampal gyrus. During the retention period, MCI is characterized by decreased alpha and beta ERS compared to controls indicating early impairment in neural networks serving working memory maintenance. The assessment of electrophysiological changes in the beta frequency range may provide a useful diagnostic tool for the early detection of cognitive impairment.

[Four-year follow-up of a neurosyphilis case presenting psychiatric symptoms]. / Pszichiátriai tünetekkel jelentkezo neuroszifilisz négyéves utánkövetése.

The authors present a case of neurosyphilis associated with predominant psychiatric symptoms. The elderly man was admitted because of confused behavior, maniform state, lack of critical judgement and grandiose delusions. On admission, right central facial nerve paresis, hand tremor and parkinsonism were also found. Acute brain imaging and routine laboratory tests failed to identify a firm etiology of the confusional state. The psychiatric treatment resulted in complete recovery from delirium. Afterwards, maniform psychosis dominated the clinical picture for which antipsychotics were administered. Later, rapid cognitive deterioration and progression of motor symptoms were observed. MRI revealed cortical and hippocampal atrophy and white matter hyperintensities. Lumbar puncture found pleocytosis and elevated cerebrospinal fluid protein levels. Neurosyphilis had been confirmed by serologic tests. The cognitive symptoms improved and the psychiatric symptoms remitted under penicillin treatment. Four years after diagnosis, there is a gradual progression in the cognitive decline. Two additional hospitalizations were necessary due to the relapses of psychiatric symptoms. Orv Hetil. 2018; 159(6): 234-238.

What can DTI tell about early cognitive impairment? - Differentiation between MCI subtypes and healthy controls by diffusion tensor imaging.

Mild cognitive impairment (MCI) gained a lot of interest recently, especially that the conversion rate to Alzheimer Disease (AD) in the amnestic subtype (aMCI) is higher than in the non-amnestic subtype (naMCI). We aimed to determine whether and how diffusion-weighted MRI (DWI) using the diffusion tensor model (DTI) can differentiate MCI subtypes from healthy subjects. High resolution 3D T1W and DWI images of patients (aMCI, n = 18; naMCI, n = 20; according to Petersen criteria) and controls (n = 27) were acquired at 3T and processed using ExploreDTI and SPM. Voxel-wise and region of interest (ROI) analyses of fractional anisotropy (FA) and mean diffusivity (MD) were performed with ANCOVA; MD was higher in aMCI compared to controls or naMCI in several grey and white matter (GM, WM) regions (especially in the temporal pole and the inferior temporal lobes), while FA was lower in WM ROI-s (e.g. left Cingulum). Moreover, significant correlations were identified between verbal fluency, visual and verbal memory performance and DTI metrics. Logistic regression showed that measuring FA of the crus of fornix along GM volumetry improves the discrimination of aMCI from naMCI. Additional information from DWI/DTI aids preclinical detection of AD and may help detecting early non-Alzheimer type dementia, too.

[Psychogenic nonepileptic seizures: overview and implications for practice]. / Pszichogén nem epilepsziás rosszullétek a klinikai gyakorlatban.

Psychogenic nonepileptic seizures are enigmatic disorders at the interface of neurology and psychiatry. Seizures resemble epileptic seizures but are not associated with electrical discharges in the brain. Symptoms typically start in early adulthood and women are far more affected than men. Video-EEG is widely considered to be the gold standard for diagnosis. Still psychogenic nonepileptic seizures are often misdiagnosed and treated as epilepsy for years that is burdensome to patients and costly to the healthcare system. Patients having psychogenic nonepileptic seizures show a high prevalence of traumatic life events, therefore, psychosocial factors are thought to play an important role in the etiology. Neurobiological factors may also contribute to the development of seizures as a subgroup of patients are characterized by cognitive impairment and subtle structural and functional brain abnormalities. Treatment includes psychotherapeutic procedures, particularly cognitive behavioral therapy and additional pharmacological interventions. This article presents an overview of the clinical context, diagnosis, etiology and treatment of psychogenic nonepileptic seizures.

The Differentiation of Amnestic Type MCI from the Non-Amnestic Types by Structural MRI.

INTRODUCTION: While amnestic mild cognitive impairment (aMCI) and non-amnestic mild cognitive impairment (naMCI) are theoretically different entities, only a few investigations studied the structural brain differences between these subtypes of mild cognitive impairment. The aim of the study was to find the structural differences between aMCI and naMCI, and to replicate previous findings on the differentiation between aMCI and healthy controls. METHODS: Altogether 62 aMCI, naMCI, and healthy control subjects were included into the study based on the Petersen criteria. All patients underwent a routine brain MR examination, and a detailed neuropsychological examination. RESULTS: The sizes of the hippocampus, the entorhinal cortex and the amygdala were decreased in aMCI relative to naMCI and to controls. Furthermore the cortical thickness of the entorhinal cortex, the fusiform gyrus, the precuneus and the isthmus of the cingulate gyrus were significantly decreased in aMCI relative to naMCI and healthy controls. The largest differences relative to controls were detected for the volume of the hippocampus (18% decrease vs. controls) and the cortical thickness (20% decrease vs. controls) of the entorhinal cortex: 1.6 and 1.4 in terms of Cohen's d. Only the volume of the precuneus were decreased in the naMCI group (5% decrease) compared to the control subjects: 0.9 in terms of Cohen's d. Significant between group differences were also found in the neuropsychological test results: a decreased anterograde, retrograde memory, and category fluency performance was detected in the aMCI group relative to controls and naMCI subjects. Subjects with naMCI showed decreased letter fluency relative to controls, while both MCI groups showed decreased executive functioning relative to controls as measured by the Trail Making test part B. Memory performance in the aMCI group and in the entire sample correlated with the thickness of the entorhinal cortex and with the volume of the amygdala. CONCLUSION: The amnestic mild cognitive impairment/non-amnestic mild cognitive impairment separation is not only theoretical but backed by structural imaging methods and neuropsychological tests. A better knowledge of the MCI subtypes can help to predict the direction of progression and create targeted prevention.

Monitoring the early signs of cognitive decline in elderly by computer games: an MRI study.

BACKGROUND: It is anticipated that current and future preventive therapies will likely be more effective in the early stages of dementia, when everyday functioning is not affected. Accordingly the early identification of people at risk is particularly important. In most cases, when subjects visit an expert and are examined using neuropsychological tests, the disease has already been developed. Contrary to this cognitive games are played by healthy, well functioning elderly people, subjects who should be monitored for early signs. Further advantages of cognitive games are their accessibility and their cost-effectiveness. PURPOSE: The aim of the investigation was to show that computer games can help to identify those who are at risk. In order to validate games analysis was completed which measured the correlations between results of the 'Find the Pairs' memory game and the volumes of the temporal brain regions previously found to be good predictors of later cognitive decline. PARTICIPANTS AND METHODS: 34 healthy elderly subjects were enrolled in the study. The volume of the cerebral structures was measured by MRI. Cortical reconstruction and volumetric segmentation were performed by Freesurfer. RESULTS: There was a correlation between the number of attempts and the time required to complete the memory game and the volume of the entorhinal cortex, the temporal pole, and the hippocampus. There was also a correlation between the results of the Paired Associates Learning (PAL) test and the memory game. CONCLUSIONS: The results gathered support the initial hypothesis that healthy elderly subjects achieving lower scores in the memory game have increased level of atrophy in the temporal brain structures and showed a decreased performance in the PAL test. Based on these results it can be concluded that memory games may be useful in early screening for cognitive decline.

[Pharmacological and other options in preventing dementia: a literature review]. / Demenciák megelozésének gyógyszeres és egyéb lehetoségei: irodalmi összefoglaló

BACKGROUND: At present 34 million people live with Alzheimer's disease around the world. This figure is expected to triple in the next 40 years. The major cause of this increase is the well-known aging of the society in Europe and in the US as well. AIMS AND METHODS: In this paper we review the results of the last 10 years, and discuss those pharmaceutical and other methods, which can be effective in the prevention of dementias. RESULTS: The most important pharmaceutical agents are beta secretase inhibitors, and active and passive immunizations. Several drugs in these groups are in phase III at the moment. The results from studies with intranasal insulin are also encouraging. As a non-drug option Mediterranean diet can be effective. However at present cognitive trainings seem to be the most effective in the prevention of dementias. These remediation therapies are based on the lifelong plasticity of the human brain. CONCLUSIONS: In summary we can conclude that there are promising drug developments in progess for the prevention of dementias, but the breakthrough has not been achieved yet. At present the best option is decreasing risk factors, that is treatment of hypertension, prevention of obesity and diabetes, and cognitive trainings are recommended for prevention.

EEG network connectivity changes in mild cognitive impairment - Preliminary results.

Resting state EEGs were compared between patients with amnestic subtype of mild cognitive impairment (aMCI) and matched elderly controls at two times over a one year period. The study aimed at investigating the role of functional connectivity between and within different brain regions in relation to the progression of cognitive deficit in MCI. The EEG was recorded in two sessions during eyes closed and eyes open resting conditions. Functional brain connectivity was investigated based on the measurement of phase synchronization in different frequency bands. Delta and theta synchronization characteristics indicated decreased level of local and large-scale connectivity in the patients within the frontal, between the frontal and temporal, and frontal and parietal brain areas which was more pronounced 1year later. As a consequence of opening the eyes connectivity in the alpha1 band within the parietal lobe decreased compared to the eyes closed condition but only in the control group. The lack of alpha1 band reactivity following eye opening could reliably differentiate patients from controls. Our preliminary results support the notion that the functional disconnection between distant brain areas is a characteristic feature of MCI, and may prove to be predictive in terms of the progression of this condition.

[Movement disorders is psychiatric diseases]. / Mozgászavarok pszichiátriai betegségekben.

Movement disorders are common in psychiatry. The movement disorder can either be the symptom of a psychiatric disorder, can share a common aetiological factor with it, or can be the consequence of psychopharmacological therapy. Most common features include tic, stereotypy, compulsion, akathisia, dyskinesias, tremor, hypokinesia and disturbances of posture and gait. We discuss characteristics and clinical importance of these features. Movement disorders are frequently present in mood disorders, anxiety disorders, schizophrenia, catatonia, Tourette-disorder and psychogenic movement disorder, leading to differential-diagnostic and therapeutical difficulties in everyday practice. Movement disorders due to psychopharmacotherapy can be classified as early-onset, late-onset and tardive. Frequent psychiatric comorbidity is found in primary movement disorders, such as Parkinson's disease, Wilson's disease, Huntington's disease, diffuse Lewy-body disorder. Complex neuropsychiatric approach is effective concerning overlapping clinical features and spectrums of disorders in terms of movement disorders and psychiatric diseases.

[Differentiation between mild cognitive impairment and healthy elderly population using neuropsychological tests]. / Az enyhe kognitív deficitben szenvedok differenciálása az egészséges idos populációtól neuropszichológiai tesztek segítségével.

OBJECTIVE: Paired Associates Learning (PAL) test assesses brain functions in those brain regions affected earliest by Alzheimer's dementia. The aim of the present study was to assess the usability of our implementation of the PAL test for screening mild cognitive impairment. METHODOLOGY: Based on Petersen criteria, 14 out of the 63 subjects were diagnosed with mild cognitive impairment. Visuospatial learning was assessed by our implementation of PAL test. The ability of the PAL test to differentiate between study groups was compared to the Addenbrook Cognitive Examination (ACE) and to the Mini Mental State Examination (MMSE). Linear logistic regression was used for statistical analysis, and the results are presented as Receiver Operating Characteristics (ROC) curves. All analyses were performed by SAS 9.2. RESULTS: All the results of neuropsychological tests differed significantly between the study groups. However, considerable difference could be detected between the tests regarding specificity and sensitivity. The PAL test reached the sensitivity of the ACE, while its specificity was slightly under the ACE. DISCUSSION: The PAL test developed in the framework of the present study is found to be able to differentiate between MCI and healthy controls. It outperformed the MMSE in terms of sensitivity and specificity, while it needs comparable time to perform. Its sensitivity, the important parameter for screening, is comparable to ACE, while it needs significantly shorter time and less assistance.

[Depression in neuropsychiatric diseases]. / Depresszió neuropszichiátriai betegségekben.

Depression is frequently observed together with neurological disorders. Moreover this connection is bidirectional in the case of several neurological disorders, as depression can be either a comorbide syndrome or also a risk factor of them. Neurobiological background of depression involves neuroanatomical structures, their interconnected networks, disturbances of neurotransmitters, neurohormonal, neuroimmunological and neurotrophic changes, genetic background. Disfunction of these systems also plays a role in the pathogenesis of comorbid depression of neurological disorders. Interactions and clinical aspects of biological factors involved in the pathogenesis of depression in dementias, Parkinson's disease, cerebrovascular disorders and epilepsy are discussed further. Depression as a result of neurobiological factors responsible for both neurological and psychiatric consequencies of these disorders, are often atypical as a clinical manifestation, however chracteristic for the particular neurological disorder. Evaluation of the biological backgound and clinical features of depression in neurological disorders makes the complex neuropsychiatric approach of these disorders possible.

[Neurological symptoms in psychiatry]. / Neurológiai tünetek a pszichiátriában.

Certain psychiatric diseases have biological pathomechanisms, and as a result they are accompanied by various neurological symptoms. Neurological examination is a simple method to assess these symptoms. Neurological signs come in two varieties; they are either of the hard or the soft type. Hard symptoms appear primarily in organic psychiatric disorders or as side effects of psychiatric therapy. They can also be encountered during neurological diseases of psychiatric patients. Their use in diagnostics and therapy is widely accepted. In contrast, soft neurological symptoms often stay unnoticed, even though they may contain important pieces of information. For this reason they will form the focus of our discussion. Soft neurological symptoms have been studied in different psychiatric disorder-groups. Up to now most attention has been devoted to schizophrenia. The study suggests that the soft symptoms are trait markers of schizophrenia. Furthermore they also signal disease activity and predict the outcome of the disease. Neurological symptoms are also important pointers for psychiatry. However, more systematic studies may increase the theoretical and practical implications of soft symptoms.

Quantitative EEG in early Alzheimer's disease patients - power spectrum and complexity features.

The goal of this study was to investigate the EEG signs of early stage Alzheimer's disease (AD) by conventional analyses and by methods quantifying linear and nonlinear EEG-complexity. The EEG was recorded in 12 mild AD patients and in an age-matched healthy control group (24 subjects) in both eyes open and eyes closed conditions. Frequency spectra, Omega-complexity and Synchronization likelihood were calculated on the data. In the patients a significant decrease of the relative alpha and increase of the theta power were found. Remarkably increased Omega-complexity and lower Synchronization likelihood were observed in AD in the 0.5-25 Hz frequency ranges. It is concluded that both spectral- and EEG-complexity changes can be found already in the early stage of AD in a wide frequency range. Application of conventional EEG analysis methods in combination with quantification of EEG-complexity may improve the chances of early diagnosis of AD.

Changes of EEG spectra and coherence following performance in a cognitive task in Alzheimer's disease.

Electroencephalographic measures combined with cognitive tasks are widely used for the assessment of cognitive and pathophysiological changes in Alzheimer's disease (AD). Instead of the analysis of EEG data obtained during the performance of the task, in this study data recorded in the immediate after-task period were analyzed. It was expected that this period would correspond to the electrophysiological consequences of the cognitive effort. Data of 14 patients with AD (MMS score: 16-24) were compared to that of 10 healthy control subjects. Reverse counting of a fix duration was used as a cognitive task. Changes of relative frequency spectra, and those of inter-and intrahemispheric coherence were analyzed. Relative theta power was significantly higher in AD patients compared to the controls both before and after the task. The performance of the task resulted in an increase of the relative alpha2 band in the AD group, whereas it slightly decreased in the control group. The most prominent coherence differences between AD and controls were found in the alpha1 band, especially for long-range coherence values. Coherence in this frequency band increased in the control group following the task, not seen in the AD group. We conclude that EEG parameters calculated from epochs following the completion of a cognitive task clearly differentiates patients with AD from normal controls. The electrophysiological changes found in AD may correspond to the decrease of functional connectivity of cortical areas and to the malfunctioning of the networks engaged in the cognitive task investigated.

[Event-related EEG and evoked potential investigations in clinical practice]. / Eseményfüggo EEG- es kiváltottválasz-vizsgálatok a klinikai gyakorlatban.

Considering the limits of the traditional EEG techniques the authors review the main methods and clinical importance of the event-related EEG investigations. According to methods, these can be classified into the spectral analysis of task-related, pre-task and post-task recordings as well as stimulus-controlled measurements based on evoked potential techniques. The main results of clinical studies on the event-related EEG methods are summarized according to chief disease groups (Alzheimer's disease, epilepsy, schizophrenia, Parkinson's disease, dyslexia, depression). The authors discuss the stimulus-dependent EEG discharges (P300, cognitive potential) in detail. They present the meta-analysis of 224 recent publications on human application of these methods. They analyze the involved scientific areas and the frequency by which these methods were applied in each. Following this, the results of 83 selected clinical studies are summarized. The frequency of the application of the various event-related EEG methods and the tested wave components and other parameters are listed. Finally a summary of the main clinical results is presented again by groups of diseases (schizophrenia, behavioral disorders, traumatic lesions, enuresis nocturna, depression, memory disturbance and dementia, drug effect). Finally, the potential perspectives and the limitations of the event-related EEG methods are briefly discussed.