Author name cluster

Markus Ploner

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

5 papers

1 author row

YNICL Journal 2026 Journal Article

Resting-state EEG activity in depression: a systematic review and meta-analysis

Henrik Heitmann
Jean-François Siani
Paul Theo Zebhauser
Peter Henningsen
Stefan Leucht
Josef Priller
Markus Ploner

Depression is a highly prevalent and disabling disorder affecting approximately 5% of the adult population worldwide. Despite its impact, the underlying pathophysiology remains insufficiently understood, and current treatments are only partially effective. Understanding electrophysiological correlates of depression offers promise for a better grasp of the underlying brain mechanisms and might even guide novel treatment approaches, including neuromodulation. EEG is particularly attractive for this purpose due to its wide availability, cost-effectiveness, and potential for direct neuromodulatory targeting. We conducted a PROSPERO-registered systematic review in accordance with PRISMA guidelines to assess resting-state EEG activity in adult patients with depression, diagnosed according to DSM-IV/V or ICD-10/11. Included studies reported cross-sectional or correlational data on well-established quantitative EEG measures such as power, cordance, peak frequency, and alpha asymmetry. Semiquantitative analyses using modified albatross plots and meta-analyses were performed. Study quality was assessed with a modified Newcastle-Ottawa Scale. Fifty-two studies met the inclusion criteria. Semiquantitative findings showed a trend for increased low-frequency (delta and theta) and high-frequency (beta and gamma) power, as well as left frontal alpha asymmetry, in depressed patients compared to healthy controls. However, meta-analysis only confirmed a significant increase in beta power. Results regarding disease severity correlations and data on peak alpha frequency and cordance were insufficient for interpretation. Risk of bias across studies was high. Our results support a potential role for increased beta oscillations in depression. These oscillations may reflect disrupted corticolimbic control and reward processing and partially overlap with mechanisms implicated in chronic pain and fatigue. Further investigation is warranted into their potential as a diagnostic tool or even a biomarker, as well as their potential use as a neuromodulatory treatment target.

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YNICL Journal 2023 Journal Article

Resting-state EEG and MEG biomarkers of pathological fatigue – A transdiagnostic systematic review

Henrik Heitmann
Paul Theo Zebhauser
Vanessa D. Hohn
Peter Henningsen
Markus Ploner

Fatigue is a highly prevalent and disabling symptom of many disorders and syndromes, resulting from different pathomechanisms. However, whether and how different mechanisms converge and result in similar symptomatology is only partially understood, and transdiagnostic biomarkers that could further the diagnosis and treatment of fatigue are lacking. We, therefore, performed a transdiagnostic systematic review (PROSPERO: CRD42022330113) of quantitative resting-state electroencephalography (EEG) and magnetoencephalography (MEG) studies in adult patients suffering from pathological fatigue in different disorders. Studies investigating fatigue in healthy participants were excluded. The risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semi-quantitative data synthesis was conducted using modified albatross plots. After searching MEDLINE, Web of Science Core Collection, and EMBASE, 26 studies were included. Cross-sectional studies revealed increased brain activity at theta frequencies and decreased activity at alpha frequencies as potential diagnostic biomarkers. However, the risk of bias was high in many studies and domains. Together, this transdiagnostic systematic review synthesizes evidence on how resting-state M/EEG might serve as a diagnostic biomarker of pathological fatigue. Beyond, this review might help to guide future M/EEG studies on the development of fatigue biomarkers.

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YNIMG Journal 2017 Journal Article

Brain oscillations differentially encode noxious stimulus intensity and pain intensity

Moritz M. Nickel
Elisabeth S. May
Laura Tiemann
Paul Schmidt
Martina Postorino
Son Ta Dinh
Joachim Gross
Markus Ploner

Noxious stimuli induce physiological processes which commonly translate into pain. However, under certain conditions, pain intensity can substantially dissociate from stimulus intensity, e. g. during longer-lasting pain in chronic pain syndromes. How stimulus intensity and pain intensity are differentially represented in the human brain is, however, not yet fully understood. We therefore used electroencephalography (EEG) to investigate the cerebral representation of noxious stimulus intensity and pain intensity during 10min of painful heat stimulation in 39 healthy human participants. Time courses of objective stimulus intensity and subjective pain ratings indicated a dissociation of both measures. EEG data showed that stimulus intensity was encoded by decreases of neuronal oscillations at alpha and beta frequencies in sensorimotor areas. In contrast, pain intensity was encoded by gamma oscillations in the medial prefrontal cortex. Contrasting right versus left hand stimulation revealed that the encoding of stimulus intensity in contralateral sensorimotor areas depended on the stimulation side. In contrast, a conjunction analysis of right and left hand stimulation revealed that the encoding of pain in the medial prefrontal cortex was independent of the side of stimulation. Thus, the translation of noxious stimulus intensity into pain is associated with a change from a spatially specific representation of stimulus intensity by alpha and beta oscillations in sensorimotor areas to a spatially independent representation of pain by gamma oscillations in brain areas related to cognitive and affective-motivational processes. These findings extend the understanding of the brain mechanisms of nociception and pain and their dissociations during longer-lasting pain as a key symptom of chronic pain syndromes.

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YNIMG Journal 2012 Journal Article

Decoding the perception of pain from fMRI using multivariate pattern analysis

Kay H. Brodersen
Katja Wiech
Ekaterina I. Lomakina
Chia-shu Lin
Joachim M. Buhmann
Ulrike Bingel
Markus Ploner
Klaas Enno Stephan

Pain is known to comprise sensory, cognitive, and affective aspects. Despite numerous previous fMRI studies, however, it remains open which spatial distribution of activity is sufficient to encode whether a stimulus is perceived as painful or not. In this study, we analyzed fMRI data from a perceptual decision-making task in which participants were exposed to near-threshold laser pulses. Using multivariate analyses on different spatial scales, we investigated the predictive capacity of fMRI data for decoding whether a stimulus had been perceived as painful. Our analysis yielded a rank order of brain regions: during pain anticipation, activity in the periaqueductal gray (PAG) and orbitofrontal cortex (OFC) afforded the most accurate trial-by-trial discrimination between painful and non-painful experiences; whereas during the actual stimulation, primary and secondary somatosensory cortex, anterior insula, dorsolateral and ventrolateral prefrontal cortex, and OFC were most discriminative. The most accurate prediction of pain perception from the stimulation period, however, was enabled by the combined activity in pain regions commonly referred to as the ‘pain matrix’. Our results demonstrate that the neural representation of (near-threshold) pain is spatially distributed and can be best described at an intermediate spatial scale. In addition to its utility in establishing structure-function mappings, our approach affords trial-by-trial predictions and thus represents a step towards the goal of establishing an objective neuronal marker of pain perception.

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YNIMG Journal 2006 Journal Article

Oscillatory activity reflects the excitability of the human somatosensory system

Markus Ploner
Joachim Gross
Lars Timmermann
Bettina Pollok
Alfons Schnitzler

The neuronal activity of the resting human brain is dominated by spontaneous oscillations in primary sensory and motor areas. These oscillations are thought to reflect the excitability of sensory and motor systems that can be modulated according to the actual behavioral demands. However, so far, evidence for an association between oscillatory activity and excitability has been inconsistent. Here, we used magnetoencephalography to reinvestigate the relationship between oscillatory activity and excitability in the somatosensory system on a single trial basis. Brief painful stimuli were applied to relate pain-induced suppressions of oscillatory activity to pain-induced increases in excitability. The analysis reveals a significant negative correlation between sensorimotor oscillatory activity, particularly in the α-band, and excitability of somatosensory cortices. Oscillatory activity outside the somatosensory system did not correlate with somatosensory excitability. These findings demonstrate that modulations of sensorimotor oscillatory activity specifically reflect modulations in excitability of the somatosensory system and thus provide direct evidence for the basic tenet of an association between oscillatory activity and cortical excitability.

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