Er EEG en nyttig undersøkelse i voksenpsykiatrien?

Sand, Trond; Bjørk, Marte Helene; Vaaler, Arne

doi:10.4045/tidsskr.12.1253

Cited by 8 publications

(5 citation statements)

References 47 publications

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“…Specific assessment tools such as the DRS-R98 and / or EEG can assist these efforts in more complex cases. 30 Table 2 outlines relatively distinguishing and overlapping features of delirium and depression.…”

Section: Assessment In Clinical Practicementioning

confidence: 99%

Delirium and depression: inter-relationship and clinical overlap in elderly people

O’Sullivan

Inouye

Meagher

2014

The Lancet Psychiatry

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Delirium and depression are complex neuropsychiatric syndromes that are common in the elderly and associated with a variety of poor healthcare outcomes. Accurate detection is key to providing optimal care for these conditions but is complicated by their considerable clinical overlap. This includes shared symptom profiles as well as comorbidity. Careful assessment of symptom character as well as the context and course of disturbances can allow for more accurate diagnosis. Prior depressive illness is a common finding in patients with delirium, while depressive illness is a recognised sequel of delirium. Evidence points to similar pathophysiological mechanisms involving disturbances in stress and inflammatory responses, monoaminergic and melatonergic functions, that in turn point to avenues for therapeutic intervention. Development of better tools for systematic assessment for delirium and depression in populations at high risk by virtue of age, diminished cognitive reserve and frailty is a key target to achieve improved healthcare outcomes.

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Section: Assessment In Clinical Practicementioning

confidence: 99%

Delirium and depression: inter-relationship and clinical overlap in elderly people

O’Sullivan

Inouye

Meagher

2014

The Lancet Psychiatry

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“…Quantitative electroencephalography is at its Renaissance stage in last decades (Sand et al, 2013) and has developed toward some forms of research in modern psychiatry (Kamarajan and Porjesz, 2015; Martínez-Rodrigo et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Analysis of Decision-Making Process Using Methods of Quantitative Electroencephalography and Machine Learning Tools

Wójcik

Masiak

Kawiak

et al. 2019

Front. Neuroinform.

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The electroencephalographic activity of particular brain areas during the decision making process is still little known. This paper presents results of experiments on the group of 30 patients with a wide range of psychiatric disorders and 41 members of the control group. All subjects were performing the Iowa Gambling Task that is often used for decision process investigations. The electroencephalographical activity of participants was recorded using the dense array amplifier. The most frequently active Brodmann Areas were estimated by means of the photogrammetry techniques and source localization algorithms. The analysis was conducted in the full frequency as well as in alpha, beta, gamma, delta, and theta bands. Next the mean electric charge flowing through each of the most frequently active areas and for each frequency band was calculated. The comparison of the results obtained for the subjects and the control groups is presented. The difference in activity of the selected Brodmann Areas can be observed in all variants of the task. The hyperactivity of amygdala is found in both the patients and the control group. It is noted that the somatosensory association cortex, dorsolateral prefrontal cortex, and primary visual cortex play an important role in the decision-making process as well. Some of our results confirm the previous findings in the fMRI experiments. In addition, the results of the electroencephalographic analysis in the broadband as well as in specific frequency bands were used as inputs to several machine learning classifiers built in Azure Machine Learning environment. Comparison of classifiers' efficiency is presented to some extent and finding the most effective classifier may be important for planning research strategy toward finding decision-making biomarkers in cortical activity for both healthy people and those suffering from psychiatric disorders.

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“…The clinical interview is still the main diagnostic method used in current psychiatry. However, the EEG seems to be a useful tool to support the psychiatrist (Sand et al, 2013 ). A wide range of psychiatric disorders is not possible to be diagnosed based on MRI, while some EEG methods seem to be appropriate for the diagnosis support in psychiatry (Kamarajan and Porjesz, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

New Protocol for Quantitative Analysis of Brain Cortex Electroencephalographic Activity in Patients With Psychiatric Disorders

Wójcik

Masiak

Kawiak

et al. 2018

Front. Neuroinform.

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The interview is still the main and most important tool in psychiatrist's work. The neuroimaging methods such as CT or MRI are widely used in other fields of medicine, for instance neurology. However, psychiatry lacks effective quantitative methods to support of diagnosis. A novel neuroinformatic approach to help clinical patients by means of electroencephalographic technology in order to build foundations for finding neurophysiological biomarkers of psychiatric disorders is proposed. A cohort of 30 right-handed patients (21 males, 9 females) with psychiatric disorders (mainly with panic and anxiety disorder, Asperger syndrome as well as with phobic anxiety disorders, schizophrenia, bipolar affective disorder, obsessive-compulsive disorder, nonorganic hypersomnia, and moderate depressive episode) were examined using the dense array EEG amplifier in the P300 experiment. The results were compared with the control group of 30 healthy, right-handed male volunteers. The quantitative analysis of cortical activity was conducted using the sLORETA source localization algorithm. The most active Brodmann Areas were pointed out and a new quantitative observable of electrical charge flowing through the selected Brodmann Area is proposed. The precise methodology and research protocol for collecting EEG data as well as the roadmap of future investigations in this area are presented. The essential result of this study is the idea proven by the initial results of our experiments that it is possible to determine quantitatively biomarkers of particular psychiatric disorders in order to support the process of diagnosis and hopefully choose most appropriate medical treatment later.

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Er EEG en nyttig undersøkelse i voksenpsykiatrien?

Abstract: EEG should be undertaken in case of newly occurring psychoses and for conditions with a fluctuating or progradiating loss of cognitive function. Adult psychiatric patients with seizure symptoms or rapid changes in affective states should also be referred to EEG.

Cited by 8 publications

References 47 publications

Delirium and depression: inter-relationship and clinical overlap in elderly people

Delirium and depression: inter-relationship and clinical overlap in elderly people

Analysis of Decision-Making Process Using Methods of Quantitative Electroencephalography and Machine Learning Tools

New Protocol for Quantitative Analysis of Brain Cortex Electroencephalographic Activity in Patients With Psychiatric Disorders

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