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Schnitzler, A.

Publications and source records attributed to Schnitzler, A..

At least 19 recordsLinked to original sources

Cholinergic and noradrenergic modulation of perceptual decision making and learning

Decision making often requires the integration of noisy bottom-up sensory evidence with top-down prior expectations learned from past experiences. Acetylcholine and noradrenaline have been proposed to shape these computations, yet it remains unclear whether they directly influence the weighting of sensory evidence and prior expectations during decision making or instead shape the learning process that gives rise to these expectations. To disentangle this, healthy participants (n = 62) completed a perceptual decision-making task under the influence of either the muscarinic acetylcholine receptor antagonist biperiden, the {beta}-adrenoceptor antagonist propranolol, or placebo, in a within-subject crossover design. The task required the integration of sensory evidence with learned expectations. The reliability of these two sources of information varied independently. We show that both drugs led to a faster updating of current beliefs in response to new evidence. Under propranolol, these effects were specific to reward outcomes, whereas under biperiden, faster updating in response to both reward and non-reward outcomes resulted in less stable beliefs. Notably, neither drug affected the degree to which choices were governed by the strength of the sensory evidence. Together, these findings suggest that acetylcholine and noradrenaline guide perceptual decision making by modulating the updating of top-down prior expectations in response to new bottom-up evidence during learning.

neuroscience↗

Role of GABA and NMDA receptors in shaping cortical timescales and large-scale network dynamics

Cortical brain regions integrate information across different timescales, ranging from fast sensory processing to longer integration windows, allowing cognitive functions like working memory. At the large-scale, brain regions organize into transient network states that rapidly switch over time and similarly contribute to cognition. Both cortical timescales and large-scale network dynamics are proposed to be determined by the balance between recurrent synaptic excitation and GABAergic inhibition. Here, we pharmacologically manipulated synaptic transmission at GABAA and NMDA receptors in 60 healthy male participants and acquired resting-state magnetoencephalography. Neuronal timescales followed a hierarchical gradient with shorter timescales in early sensory regions. Increasing GABAergic activity prolonged neuronal timescales across cortical regions. This effect was most prominent in the frontal default mode and in the dorsal attention network. Notably, dynamic network analyses revealed that the occurrence probability of the frontal default mode network increased, whereas the occurrence of the dorsal attention network was reduced. NMDA receptor modulation resulted in no significant changes. Together, these findings provide causal evidence that GABAergic inhibition is a key regulator of cortical temporal organization, linking microscale synaptic mechanisms to neuronal timescales and network dynamics that support diverse cognitive function.

neuroscience↗

Beyond beta: Aperiodic broadband power reflects Parkinson's disease severity - a multicenter study

Parkinsons disease is linked to increased beta oscillations in the subthalamic nucleus, which correlate with motor symptoms. However, findings across studies have varied. Our standardized analysis of multicenter datasets shows that small sample sizes contributed to these discrepancies--a challenge we address by pooling datasets into one large cohort (n=119). Moving beyond beta power, we disentangled spectral components reflecting distinct neural processes. Combining aperiodic offset, low beta, and low gamma oscillations explained significantly more variance in symptom severity than beta alone. Moreover, interhemispheric within-patient analyses showed that, unlike beta oscillations, aperiodic broadband power-likely reflecting spiking activity-was increased in the more affected hemisphere. These findings identify aperiodic broadband power as a potential biomarker for adaptive deep brain stimulation and provide novel insights into the relationship between subthalamic hyperactivity and motor symptoms in human Parkinsons disease.

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Modulations of thalamo-cortical coupling during voluntary movement in patients with essential tremor

The ventral intermediate nucleus of the thalamus (VIM) is the main thalamic hub for processing cerebellar inputs and the main deep brain stimulation target for the treatment of essential tremor (ET). As such, it presumably plays a critical role in motor control. So far, however, this structure has been rarely investigated in humans, and almost all of the existing studies focus on tremor. Here, we set out to study neural oscillations in the VIM and their coupling to cortical oscillations during voluntary movement. We investigated thalamo-cortical coupling by means of simultaneous recordings of thalamic local field potentials and magnetoencephalography in 10 ET patients with externalized deep brain stimulation electrodes. Brain activity was measured while patients were pressing a button repeatedly in response to a visual cue. In a whole-brain analysis of coherence between VIM and cortex, we contrasted activity around a pre-movement baseline and button pressing. Button pressing was associated with a bilateral decrease of thalamic power in the alpha (8- 12 Hz) and beta (13-21 Hz) band and a contralateral power increase in the gamma (35- 90 Hz) band. Moreover, changes in VIM-cortex coherence were observed. Alpha/low beta (8- 20 Hz) coherence decreased before and during movement, and the effect localized to the supplementary motor area and premotor cortex. A rebound of high beta (21-35 Hz) coherence occurred in the same region, but was more focal than the suppression. Pre-movement levels of thalamo-cortex low-beta coherence correlated with reaction time. Our results demonstrate that voluntary movement is associated with modulations of behaviourally relevant thalamic coupling, primarily to premotor areas. We observed a clear distinction between low- and high-beta frequencies and our results suggest that the concept of "antikinetic" beta oscillations, originating from research on Parkinsons disease, is transferable to ET.

neuroscience↗

IKZF2-ERBB4 gene fusion leads to ERBB4 overexpression in Anal Squamous Cell Carcinoma but with no benefit for ERBB4 inhibition

Anal squamous cell carcinoma (ASCC) is a rare tumour, but with increasing incidence for local and metastatic tumours. Current therapy is based on chemoradiotherapy, associated with immunotherapy in advanced stages, with frequent side effects, poor results in advanced stages and recurrence. New therapeutics, including targeted therapies, are then needed. In this context, we identified here a IKZF2-ERBB4 gene fusion in a patient ASCC tumour, leading to overexpressed mRNA encoding a functional ERBB4 protein. This gene fusion has been already reported in other tumour types but not yet investigated as therapeutical target. The matched patient tumour-derived xenograft displays the same gene fusion and mRNA overexpression. It provided biological material for anti-ERBB4 testing in different cell models (in vivo xenograft, in vitro cell cultures). We used afatinib and lapatinib, 2 chemical pan-ERBB inhibitors approved in clinics, with anti-ERBB4 properties. ERBB4 inhibition did not lead to tumour growth inhibition although afatinib and lapatinib dramatically decreased ERBB4 phosphorylation with impact on downstream signalling MAPK/ERK but not PI3K/AKT pathways. Likewise, specific ERBB4 knock-outing did not affect tumour cell proliferation. These negative results must be put in line with reported potential crosstalk between PI3K/AKT and MAPK/ERK pathways in therapeutic resistance.

cancer biology↗

Oscillatory coupling between thalamus, cerebellum and motor cortex in essential tremor

BackgroundEssential tremor is hypothesized to emerge from synchronized oscillatory activity within the cerebello-thalamo-cortical circuit. However, this hypothesis has not yet been tested using local field potentials directly recorded from the thalamus alongside signals from both the cortex and cerebellum, leaving a gap in the understanding of essential tremor. ObjectivesTo clarify the importance of cerebello-thalamo-cortical oscillatory coupling for essential tremor. MethodsWe investigated oscillatory coupling between thalamic local field potentials and simultaneously recorded magnetoencephalography in 19 essential tremor patients with externalized deep brain stimulation electrodes. Brain activity was measured while patients repeatedly adopted a tremor-provoking posture and while pouring rice from one cup to another. In a whole-brain analysis of coherence between the ventral intermediate nucleus of the thalamus and cortex, we contrasted epochs containing tremor and epochs lacking tremor. ResultsBoth postural and kinetic tremor were associated with an increase of thalamic power and thalamo-cortex coherence at individual tremor frequency in the bilateral cerebellum and primary sensorimotor cortex contralateral to tremor. These areas also exhibited an increase in corticomuscular coherence in the presence of tremor. The coupling of motor cortex to both thalamus and muscle correlated with tremor amplitude during postural tremor. ConclusionsThese results demonstrate that essential tremor is indeed associated with increased oscillatory coupling at tremor frequency within a cerebello-thalamo-cortical network, with coupling strength directly reflecting tremor severity.

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A role for acetylcholine in reinforcement learning and decision making under uncertainty

The neuromodulator acetylcholine has been suggested to govern learning under uncertainty. Here, we investigated the role of muscarinic acetylcholine receptors in reward-guided learning and decision making under different degrees of uncertainty. We administered the muscarinic antagonist biperiden (4 mg) to healthy male participants (n = 43) in a within-subjects, placebo-controlled design. Participants performed a gambling and a learning task involving different levels of uncertainty, while magnetoencephalography (MEG) was recorded. We show that biperiden did not affect decision making in the gambling task, where no learning was required. However, in the learning task, where option values were associated with uncertainty, biperiden reduced the sensitivity to probabilities, particularly when choice-outcome-contingencies switched frequently. Reinforcement learning models revealed that the change in behaviour was caused by noisier estimates of probabilities resulting from increased learning rates for rewarded choices under biperiden. These behavioural findings were paralleled by elimination of the lateral prefrontal representation of learnt reward probability in high-beta (20 - 30 Hz) power under biperiden. Together, these findings suggest that muscarinic acetylcholine transmission controls learning in highly uncertain contexts, when the demand for carefully calibrated adjustments is highest.

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Beta Waves in Action: Context-Dependent Modulations of Subthalamo-Cortical Synchronization during Rapid Reversals of Movement Direction

The role of beta band activity in cortico-basal ganglia interactions during motor control has been studied extensively in resting-state and for simple movements, such as button pressing. However, little is known about how beta oscillations change and interact in more complex situations involving rapid changes of movement in various contexts. To close this knowledge gap, we combined magnetoencephalography (MEG) and local field potential recordings from the subthalamic nucleus (STN) in Parkinsons disease patients to study beta dynamics during initiation, stopping, and rapid reversal of rotational movements. The action prompts were manipulated to be predictable vs. unpredictable. We observed movement-related beta suppression at motor sequence start, and a beta rebound after motor sequence stop in STN power, motor cortical power, and STN-cortex coherence. Despite involving a brief stop of movement, no clear rebound was observed during reversals of turning direction. On the cortical level, beta power decreased bilaterally following reversals, but more so in the hemisphere ipsilateral to movement, due to a floor effect on the contralateral side. In the STN, power modulations varied across patients, with patients revealing brief increases or decreases of high-beta power. Importantly, cue predictability affected these modulations. Event-related increases of STN-cortex beta coherence were generally stronger in the unpredictable than in the predictable condition. In summary, this study reveals the influence of movement context on beta oscillations in basal ganglia-cortex loops when humans change ongoing movements according to external cues. We find that movement scenarios requiring higher levels of caution involve enhanced modulations of subthalamo-cortical beta synchronization. Further, our results confirm that beta oscillations reflect the start and end of motor sequences better than movement changes within a sequence. Significance StatementBeta synchrony between motor cortex and the subthalamic nucleus is intensified when instructional cues within a continuous motor sequence become less predictable, calling for more cautious behavior.

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Altered Cortical Network Dynamics during Observing and Preparing Action in Patients with Corticobasal Syndrome

Besides parkinsonism, higher order cortical dysfunctions such as apraxia are hallmarks of the corticobasal syndrome (CBS). To date, little is known about the electrophysiological underpinnings of these symptoms. To shed more light on the pathophysiology of CBS, we recorded the magnetoencephalogram of 17 CBS patients and 20 age-matched controls engaged in an observe-to-imitate task. The task involved the display of a tool-use video in first person view (action observation), a written instruction to withhold movement until the presentation of a Go cue (movement preparation), and unilateral tool-use imitation. We investigated modulations of spectral power on the source level. Action observation was associated with an event-related desynchronization in the beta-band (13-30Hz), which was weaker in CBS patients than in healthy controls. The group effect localized to superior parietal, primary motor, premotor and inferior frontal cortex bilaterally. While participants awaited the Go cue, beta power was again suppressed in the hemisphere contralateral to movement, and the rate of suppression correlated with reaction time. This modulation, too, was weaker in the CBS group. Immediately before movement onset, however, beta power was similar in both groups. Our results reveal that action observation triggers beta suppression, likely reflecting motor cortical disinhibition, which is reduced in CBS patients. This pathological alteration might be a neural correlate of a selective deficit in the embedding of observed action into a motor representation (visuo-motor mapping). The suboptimal timing of the beta-power suppression to the upcoming Go cue presumably reflects a deficit in learning the trials temporal structure rather than a deficit in movement initialization. HighlightsO_LIAction observation elicits a suppression of cortical beta power. C_LIO_LIThis suppression is diminished in CBS patients relative to controls. C_LIO_LIThe timing of beta desynchronization to an upcoming Go cue is impaired in CBS patients. C_LIO_LINo evidence for an alteration of movement initialization in CBS patients. C_LI

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Prestimulus alpha phase modulates visual temporal integration

When presented shortly after another, discrete pictures are naturally perceived as continuous. The neuronal mechanism underlying such continuous or discrete perception are not well understood. While continuous alpha oscillations are a candidate for orchestrating such neuronal mechanisms, recent evidence is mixed. In this study, we investigated the influence of prestimulus alpha oscillation on visual temporal perception. Specifically, we were interested whether prestimulus alpha phase modulates neuronal and perceptual processes underlying discrete or continuous perception. Participant had to report the location of a missing object in a visual temporal integration task, while simultaneously MEG data was recorded. Using source reconstruction, we evaluated local phase effects by contrasting phase angle values between correctly and incorrectly integrated trials. Our results show a phase opposition cluster between - 0.8 to - 0.5 s (relative to stimulus presentation) and between 6 - 20 Hz. These momentary phase angle values were correlated with behavioural performance and event related potential amplitude. There was no evidence that frequency defined a window of temporal integration. Significance StatementIn light with the current debate if our visual perception is a rhythmic or discrete process, we give new insight to this debate. We investigated potential underling mechanism defining potential rhythmic perception and highlight the complexity of this process. This will help us further understand how our brain operates and processes incoming unimodal visual stimuli. In a visual temporal integration task, we were able to show that the incoming information were processed in rhythmic fashion. Our data supports the idea that the phase of prestimulus alpha oscillation modulates poststimulus visual processing by defining good and less good phases for early visual processes. We were not able to show that prestimulus alpha oscillation defines windows were two visual stimuli are integrated into one single event.

neuroscience↗

Dopaminergic and Cholinergic Modulation of Human Cost-Benefit Decision Making

In everyday life, we encounter situations that require tradeoffs between potential rewards and associated costs, such as time and (physical) effort. The literature indicates a prominent role for dopamine in discounting of both delay and effort, with mixed findings for delay discounting in humans. Moreover, the reciprocal antagonistic interaction between dopaminergic and cholinergic transmission in the striatum suggests a potential opponent role of acetylcholine in these processes. We found opposing effects of dopamine D2 (haloperidol) and acetylcholine M1 receptor (biperiden) antagonism on specific components of effort-based decision making in healthy humans: haloperidol decreased, whereas biperiden increased the willingness to exert physical effort. In contrast, delay discounting was reduced under haloperidol, but not affected by biperiden. Together, our data suggest that dopamine, acting at D2 receptors, modulates both effort and delay discounting, while acetylcholine, acting at M1 receptors, appears to exert a more specific influence on effort discounting only.

neuroscience↗

Deep brain stimulation device-specific artefacts in MEG recordings

BackgroundDeep brain stimulation (DBS) has strong beneficial effects for treating movement disorders. The related cortical mechanisms can be studied with magnetoencephalography (MEG) during active DBS. However, MEG is prone to artefacts induced by the electrical stimulation and the movement of ferromagnetic DBS components. Although artefacts might vary between DBS devices from different manufacturers, no such comparison has been performed. To date, no combined MEG-DBS studies have been conducted within Yokogawa MEG systems. ObjectiveThe aim of the present study was to compare DBS artefacts in MEG phantom recordings acquired with two MEG systems (Neuromag, Yokogawa) using DBS devices from three different manufacturers (Abbott, Boston Scientifc, Medtronic) and to test whether established cleaning methods can sufficiently reduce artefacts. MethodsDBS devices, electrodes, and extension cables were attached to a gelatine MEG phantom, and data was acquired in a Neuromag and a Yokogawa MEG system. ResultsThere are device-specific differences in movement-related artefacts with weaker artefacts for Boston Scientific (BSC) devices. Stimulation-, movement- and IPG-related artefacts are best cleaned when combining the ICA-MI and Hampel filter across recordings and DBS devices. However, the cleaning of movement-related artefacts can result in artefactual spectral peaks in physiologically relevant frequencies below 20 Hz. ConclusionsDevice-specific IPG-related artefacts have to be considered for MEG-DBS studies and can be cleaned with combinations of published cleaning methods for MEG and EEG data. Critically, cleaning movement-related artefacts can potentially result in spectral peaks, which resemble physiological activity. Finally, combined MEG-DBS recordings are feasible in Yokogawa-MEG systems.

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Combining Magnetoencephalography with Telemetric Streaming of Intracranial Recordings and Deep Brain Stimulation - a Feasibility Study

The combination of subcortical Local Field Potential (LFP) recordings and stimulation with Magnetoencephalography (MEG) in Deep Brain Stimulation (DBS) patients enables the investigation of cortico-subcortical communication patterns and provides insights into DBS mechanisms. Until now, these recordings have been carried out in post-surgical patients with externalised leads. However, a new generation of telemetric stimulators makes it possible to record and stream LFP data in chronically implanted patients. Nevertheless, whether such streaming can be combined with MEG has not been tested. In the present study, we tested the most commonly implanted telemetric stimulator - Medtronic Percept PC with a phantom in three different MEG systems: two cryogenic scanners (CTF and MEGIN) and an experimental Optically Pumped Magnetometry (OPM)-based system. We found that when used in combination with the new SenSight segmented leads, Percept PC telemetric streaming only generates band-limited interference in the MEG at 123Hz and harmonics. However, the legacy streaming mode used with older lead models generates multiple, dense artefact peaks in the physiological range of interest (below 50Hz). The effect of stimulation on MEG critically depends on whether it is done in bipolar (between two contacts on the lead) or monopolar (between a lead contact and the stimulator case) mode. Monopolar DBS creates severe interference in the MEG as previously reported. However, we found that the OPM system is more resilient to this interference and could provide artefact-free measurements at least for limited frequency ranges. A resting measurement in the MEGIN system from a Parkinsons patient implanted with Percept PC and subthalamic SenSight leads revealed artefact patterns consistent with our phantom recordings. Moreover, analysis of LFP-MEG coherence in this patient showed oscillatory coherent networks consistent in their frequency and topography with those described in published group studies done with externalised leads. In conclusion, Percept PC telemetric streaming with SenSight leads is compatible with MEG. Furthermore, OPM sensors could provide additional new opportunities for studying DBS effects.

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The AGNOSTIC MRS Benchmark Dataset: Deep Learning for Out-of-voxel Artifacts

Neural networks are potentially valuable for many of the challenges associated with MRS data. The purpose of this manuscript is to describe the AGNOSTIC dataset, which contains 259,200 synthetic 1H MRS examples for training and testing neural networks. AGNOSTIC was created using 270 basis sets that were simulated across 18 field strengths and 15 echo times. The synthetic examples were produced to resemble in vivo brain data with combinations of metabolite, macromolecule, residual water signals, and noise. To demonstrate the utility, we apply AGNOSTIC to train two Convolutional Neural Networks (CNNs) to address out-of-voxel (OOV) echoes. A Detection Network was trained to identify the point-wise presence of OOV echoes, providing proof of concept for real-time detection. A Prediction Network was trained to reconstruct OOV echoes, allowing subtraction during post-processing. Complex OOV signals were mixed into 85% of synthetic examples to train two separate CNNs for the detection and prediction of OOV signals. AGNOSTIC is available through Dryad and all Python 3 code is available through GitHub. The Detection network was shown to perform well, identifying 95% of OOV echoes. Traditional modeling of these detected OOV signals was evaluated and may prove to be an effective method during linear-combination modeling. The Prediction Network greatly reduces OOV echoes within FIDs and achieved a median log10 normed-MSE of -1.79, an improvement of almost two orders of magnitude.

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Parkinsonian rest tremor can be distinguished from voluntary hand movements based on subthalamic and cortical activity using machine learning

Tremor is one of the cardinal symptoms of Parkinsons disease. The neurophysiology of tremor is not completely understood, and so far it has not been possible to distinguish tremor from voluntary hand movements based on local brain signals. Here, we re-analyzed magnetoencephalography and local field potential recordings from the subthalamic nucleus of six patients with Parkinsons disease. Data were obtained after withdrawal from dopaminergic medication (Med Off) and after administration of levodopa (Med On). Using gradient-boosted tree learning, we classified epochs as tremor, self-paced fist-clenching, static forearm extension or tremor-free rest. While decoding performance was low when using subthalamic activity as the only feature (balanced accuracy mean: 38%, std: 7%), we could distinguish the four different motor states when considering cortical and subthalamic features (balanced accuracy mean: 75%, std: 17%). Adding a single cortical area improved classification by 17% on average, as compared to classification based on subthalamic activity alone. In most patients, the most informative cortical areas were sensorimotor cortical regions. Decoding performance was similar in Med On and Med Off. Our results demonstrate the advantage of monitoring cortical signals in addition to subthalamic activity for movement classification. By combining cortical recordings, subcortical recordings and machine learning, future adaptive systems might be able to detect tremor specifically and distinguish between several motor states.

neuroscience↗

Subthalamic stimulation evoked cortical responses relate to motor performance in Parkinson's disease

Subthalamic deep brain stimulation is effective in alleviating motor symptoms in Parkinsons disease. Establishing the clinically best stimulation settings often requires time-consuming test sessions and creates a need for biomarkers to optimize this process. While stimulation-evoked cortical responses have been proposed as such a neurophysiological marker, their relationship to motor performance has not yet been studied systematically. For this aim, we recorded finger-tapping movements and cortical responses evoked by different stimulation amplitudes of 22 patients with Parkinsons disease using magnetoencephalography. The motor cortex amplitude was a significant predictor of a higher finger tap frequency and a more regular tapping profile. In addition, subthalamic stimulation evoked responses in the inferior and middle frontal gyrus, and the supplementary motor area. While earlier studies relied on a limited cortical coverage, we reveal a cortical distribution of responses that aligns with the basal ganglia-thalamo-cortical network. Our study sheds light on the relationship between cortical responses evoked by subthalamic stimulation and motor performance based on objective quantitative parameters. Stimulation-evoked responses could guide clinical programming in the future.

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Slowing of Frontocentral Beta Oscillations in Atypical Parkinsonism

Diagnosis of atypical parkinsonian syndromes mostly relies on clinical presentation as well as structural and molecular brain imaging. It has not been investigated whether cortical oscillatory activity exhibits features distinguishing these syndromes. Therefore, we measured resting-state magnetoencephalography in 13 patients with corticobasal syndrome, 10 patients with progressive supranuclear palsy, 23 patients with idiopathic Parkinsons disease and 23 healthy controls. We compared spectral power as well as amplitude and frequency of power peaks between the groups. Atypical Parkinsonism was associated with spectral slowing, distinguishing both corticobasal syndrome and progressive supranuclear palsy from age-matched healthy controls and Parkinsons disease. Patients with atypical Parkinsonism showed a shift of beta peaks (13-30 Hz) towards lower frequencies in frontal and central areas bilaterally. A concomitant increase in theta/alpha power relative to controls was observed in both atypical parkinsonian syndromes and in Parkinsons disease. Our results demonstrate that slowing of frontocentral beta oscillations is characteristic of atypical Parkinsonism. Spectral slowing with a different topography has previously been observed in other neurodegenerative disorders, such as Alzheimers disease, suggesting that spectral slowing might be an electrophysiological marker of cortical neurodegeneration. As such, it might support differential diagnosis of parkinsonian syndromes in the future. HighlightsO_LISlowing of beta oscillations distinguishes atypical parkinsonian syndromes from healthy controls and idiopathic Parkinsons disease C_LIO_LISpectral slowing is most pronounced in frontocentral areas C_LIO_LIBeta oscillations are shifted towards lower frequencies independent of their amplitude C_LI

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Separating neural oscillations from aperiodic 1/f activity: challenges and recommendations

Electrophysiological power spectra typically consist of two components: An aperiodic part usually following an 1/f power law P{propto}1/f{beta}and periodic components appearing as spectral peaks. While the investigation of the periodic parts, commonly referred to as neural oscillations, has received considerable attention, the study of the aperiodic part has only recently gained more interest. The periodic part is usually quantified by center frequencies, powers, and bandwidths, while the aperiodic part is parameterized by the y-intercept and the 1/f exponent {beta}. For investigation of either part, however, it is essential to separate the two components. In this article, we scrutinize two frequently used methods, FOOOF (Fitting Oscillations & One-Over-F) and IRASA (Irregular Resampling Auto-Spectral Analysis), that are commonly used to separate the periodic from the aperiodic component. We evaluate these methods using diverse spectra obtained with electroencephalography (EEG), magnetoencephalography (MEG), and local field potential (LFP) recordings relating to three independent research datasets. Each method and each dataset poses distinct challenges for the extraction of both spectral parts. The specific spectral features hindering the periodic and aperiodic separation are highlighted by simulations of power spectra emphasizing these features. Through comparison with the simulation parameters defined a priori, the parameterization error of each method is quantified. Based on the real and simulated power spectra, we evaluate the advantages of both methods, discuss common challenges, note which spectral features impede the separation, assess the computational costs, and propose recommendations on how to use them.

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