Cortex-wide topography of 1/f-exponent in Parkinson's disease

Human sensorimotor resting state beta events and aperiodic activity show good test-retest reliability

OBJECTIVE

Diseases affecting sensorimotor function impair physical independence. Reliable functional clinical biomarkers allowing early diagnosis or targeting treatment and rehabilitation could reduce this burden. Magnetoencephalography (MEG) non-invasively measures brain rhythms such as the somatomotor 'rolandic' rhythm which shows intermittent high-amplitude beta (14-30 Hz) 'events' that predict behavior across tasks and species and are altered by sensorimotor neurological diseases.

METHODS

We assessed test-retest stability, a prerequisite for biomarkers, of spontaneous sensorimotor aperiodic (1/f) signal and beta events in 50 healthy human controls across two MEG sessions using the intraclass correlation coefficient (ICC). Beta events were determined using an amplitude-thresholding approach on a narrow-band filtered amplitude envelope obtained using Morlet wavelet decomposition.

RESULTS

Resting sensorimotor characteristics showed good to excellent test-retest stability. Aperiodic component (ICC 0.77-0.88) and beta event amplitude (ICC 0.74-0.82) were very stable, whereas beta event duration was more variable (ICC 0.55-0.7). 2-3 minute recordings were sufficient to obtain stable results. Analysis automatization was successful in 86%.

CONCLUSIONS

Sensorimotor beta phenotype is a stable feature of an individual's resting brain activity even for short recordings easily measured in patients.

SIGNIFICANCE

Spontaneous sensorimotor beta phenotype has potential as a clinical biomarker of sensorimotor system integrity.

Alterations of Cortical Structure and Neurophysiology in Parkinson's Disease Are Aligned with Neurochemical Systems

OBJECTIVE

Parkinson's disease (PD) affects the structural integrity and neurophysiological signaling of the cortex. These alterations are related to the motor and cognitive symptoms of the disease. How these changes are related to the neurochemical systems of the cortex is unknown.

METHODS

We used T1-weighted magnetic resonance imaging (MRI) and magnetoencephalography (MEG) to measure cortical thickness and task-free neurophysiological activity in patients with idiopathic PD (nMEG = 79, nMRI = 65) and matched healthy controls (nMEG = 65, nMRI = 37). Using linear mixed-effects models, we examined the topographical alignment of cortical structural and neurophysiological alterations in PD with cortical atlases of 19 neurotransmitter receptor and transporter densities.

RESULTS

We found that neurophysiological alterations in PD occur primarily in brain regions rich in acetylcholinergic, serotonergic, and glutamatergic systems, with protective implications for cognitive and psychiatric symptoms. In contrast, cortical thinning occurs preferentially in regions rich in noradrenergic systems, and the strength of this alignment relates to motor deficits.

INTERPRETATION

This study shows that the spatial organization of neurophysiological and structural alterations in PD is relevant for nonmotor and motor impairments. The data also advance the identification of the neurochemical systems implicated. The approach uses novel nested atlas modeling methodology that is transferrable to research in other neurological and neuropsychiatric diseases and syndromes. ANN NEUROL 2024;95:802-816.

The selfish network: how the brain preserves behavioral function through shifts in neuronal network state

Neuronal networks possess the ability to regulate their activity states in response to disruptions. How and when neuronal networks turn from physiological into pathological states, leading to the manifestation of neuropsychiatric disorders, remains largely unknown. Here, we propose that neuronal networks intrinsically maintain network stability even at the cost of neuronal loss. Despite the new stable state being potentially maladaptive, neural networks may not reverse back to states associated with better long-term outcomes. These maladaptive states are often associated with hyperactive neurons, marking the starting point for activity-dependent neurodegeneration. Transitions between network states may occur rapidly, and in discrete steps rather than continuously, particularly in neurodegenerative disorders. The self-stabilizing, metastable, and noncontinuous characteristics of these network states can be mathematically described as attractors. Maladaptive attractors may represent a distinct pathophysiological entity that could serve as a target for new therapies and for fostering resilience.

Oscillatory and non-oscillatory features of the magnetoencephalic sensorimotor rhythm in Parkinson's disease

Parkinson's disease (PD) is associated with changes in neural activity in the sensorimotor alpha and beta bands. Using magnetoencephalography (MEG), we investigated the role of spontaneous neuronal activity within the somatosensory cortex in a large cohort of early- to mid-stage PD patients (N = 78) on Parkinsonian medication and age- and sex-matched healthy controls (N = 60) using source reconstructed resting-state MEG. We quantified features of the time series data in terms of oscillatory alpha power and central alpha frequency, beta power and central beta frequency, and 1/f broadband characteristics using power spectral density. Furthermore, we characterised transient oscillatory burst events in the mu-beta band time-domain signals. We examined the relationship between these signal features and the patients' disease state, symptom severity, age, sex, and cortical thickness. PD patients and healthy controls differed on PSD broadband characteristics, with PD patients showing a steeper 1/f exponential slope and higher 1/f offset. PD patients further showed a steeper age-related decrease in the burst rate. Out of all the signal features of the sensorimotor activity, the burst rate was associated with increased severity of bradykinesia, whereas the burst duration was associated with axial symptoms. Our study shows that general non-oscillatory features (broadband 1/f exponent and offset) of the sensorimotor signals are related to disease state and oscillatory burst rate scales with symptom severity in PD.

Spectral Slope and Lempel-Ziv Complexity as Robust Markers of Brain States during Sleep and Wakefulness

Nonoscillatory measures of brain activity such as the spectral slope and Lempel-Ziv complexity are affected by many neurological disorders and modulated by sleep. A multitude of frequency ranges, particularly a broadband (encompassing the full spectrum) and a narrowband approach, have been used especially for estimating the spectral slope. However, the effects of choosing different frequency ranges have not yet been explored in detail. Here, we evaluated the impact of sleep stage and task engagement (resting, attention, and memory) on slope and complexity in a narrowband (30-45 Hz) and broadband (1-45 Hz) frequency range in 28 healthy male human subjects (21.54 ± 1.90 years) using a within-subject design over 2 weeks with three recording nights and days per subject. We strived to determine how different brain states and frequency ranges affect slope and complexity and how the two measures perform in comparison. In the broadband range, the slope steepened, and complexity decreased continuously from wakefulness to N3 sleep. REM sleep, however, was best discriminated by the narrowband slope. Importantly, slope and complexity also differed between tasks during wakefulness. While narrowband complexity decreased with task engagement, the slope flattened in both frequency ranges. Interestingly, only the narrowband slope was positively correlated with task performance. Our results show that slope and complexity are sensitive indices of brain state variations during wakefulness and sleep. However, the spectral slope yields more information and could be used for a greater variety of research questions than Lempel-Ziv complexity, especially when a narrowband frequency range is used.

Associations between neuromelanin depletion and cortical rhythmic activity in Parkinson's disease

Background and Objectives

Parkinson's disease (PD) is marked by the death of neuromelanin-rich dopaminergic and noradrenergic cells in the substantia nigra (SN) and the locus coeruleus (LC), respectively, resulting in motor and cognitive impairments. While SN dopamine dysfunction has clear neurophysiological effects, the impact of reduced LC norepinephrine signaling on brain activity in PD remains to be established.

Methods

We used neuromelanin-sensitive T1-weighted MRI (NPD = 58; NHC = 27) and task-free magnetoencephalography (NPD = 58; NHC = 65) to identify neuropathophysiological factors related to the degeneration of the LC and SN in patients with PD.

Results

We found pathological increases in rhythmic alpha (8 - 12 Hz) activity in patients with decreased LC neuromelanin, with a stronger association in patients with worse attentional impairments. This negative alpha-LC neuromelanin relationship is also stronger in fronto-motor cortices, which are regions with high densities of norepinephrine transporters in the healthy brain, and where alpha activity is negatively related to attention scores. These observations support a noradrenergic association between LC integrity and alpha band activity. Our data also show that rhythmic beta (15 - 29 Hz) activity in the left somato-motor cortex decreases with lower levels of SN neuromelanin; the same regions where beta activity reflects axial motor symptoms.

Discussion

Together, our findings clarify the association of well-documented alterations of rhythmic neurophysiology in PD with cortical and subcortical neurochemical systems. Specifically, attention-related alpha activity reflects dysfunction of the noradrenergic system, and beta activity with relevance to motor impairments reflects dopaminergic dysfunction.

Human Sensorimotor Beta Event Characteristics and Aperiodic Signal Are Highly Heritable

Individuals' phenotypes, including the brain's structure and function, are largely determined by genes and their interplay. The resting brain generates salient rhythmic patterns that can be characterized noninvasively using functional neuroimaging such as magnetoencephalography (MEG). One of these rhythms, the somatomotor (rolandic) beta rhythm, shows intermittent high amplitude "events" that predict behavior across tasks and species. Beta rhythm is altered in neurological disease. The aperiodic (1/f) signal present in electrophysiological recordings is also modulated by some neurological conditions and aging. Both sensorimotor beta and aperiodic signal could thus serve as biomarkers of sensorimotor function. Knowledge about the extent to which these brain functional measures are heritable could shed light on the mechanisms underlying their generation. We investigated the heritability and variability of human spontaneous sensorimotor beta rhythm events and aperiodic activity in 210 healthy male and female adult siblings' spontaneous MEG activity. The most heritable trait was the aperiodic 1/f signal, with a heritability of 0.87 in the right hemisphere. Time-resolved beta event amplitude parameters were also highly heritable, whereas the heritabilities for overall beta power, peak frequency, and measures of event duration remained nonsignificant. Human sensorimotor neural activity can thus be dissected into different components with variable heritability. We postulate that these differences partially reflect different underlying signal-generating mechanisms. The 1/f signal and beta event amplitude measures may depend more on fixed, anatomical parameters, whereas beta event duration and its modulation reflect dynamic characteristics, guiding their use as potential disease biomarkers.