Frequency-Specific Biomarkers in Neurodegenerative Disorders: Implications of Alpha and Beta Oscillations in Motor Behaviour

Cohan, Rémy; Bearss, Karolina A.; DeSouza, Joseph F. X.

doi:10.29245/2572.942x/2019/3.1207

Cited by 2 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This decomposition enables the extraction of frequency-domain features, such as dominant frequency bands or spectral power, which can be indicative of specific brain diseases. For example, abnormalities in certain frequency bands, like alpha or beta rhythms, can be associated with conditions like epilepsy or Parkinson's disease [15]. By quantifying these features using wavelet analysis, researchers and clinicians can create discriminative metrics for disease detection.…”

Section: Application 1 -Feature Extractionmentioning

confidence: 99%

Wavelet Theories and Techniques for Brain Disease: Diagnosis and Treatmentz

2023

Preprint

View full text Add to dashboard Cite

This paper first introduces the main classification of brain diseases and the main causes of these diseases. It is followed by wavelet analysis, which is a mathematical function or wave-like pattern used to transform data, which can decompose the signal into different wavelet functions, each of which is related to a specific scale or frequency. Wavelet analysis has been applied in many fields such as image processing, data analysis and engineering. In addition, wavelet is also used in the analysis of biological signals. Wavelet analysis breaks down brain signals, such as EEG or fMRI data, into various frequency components at different scales. Wavelet analysis provides time-frequency localization. Pattern recognition can be enhanced by isolating salient features in the data. Wavelet denoising can effectively separate noise from underlying brain signals. Wavelet denoising usually adopts threshold method. Wavelet analysis can enhance pattern recognition by isolating salient features in the data. Researchers can train machine learning models based on these wavelet-derived features to recognize specific patterns associated with different neurological disorders. Wavelet analysis can track these changes by continuously evaluating the frequency content of the neuroimage data over time. Through continuous efforts, wavelet theory and technology have become valuable tools in the field of neuroscience and brain disease research.

show abstract

Section: Application 1 -Feature Extractionmentioning

confidence: 99%

Wavelet Theories and Techniques for Brain Disease: Diagnosis and Treatmentz

2023

Preprint

View full text Add to dashboard Cite

show abstract

Post-Movement Beta Rebound in Sensorimotor Cortex Endures One Week After Three Days of Practice

Sisti,

Amarnath,

Balcha

et al. 2024

Preprint

View full text Add to dashboard Cite

The post-movement beta rebound (PMBR) is the tightly coupled increase in beta power that occurs in the sensorimotor cortex upon movement termination. It is a potential biomarker of motor control; abnormal responses could signal disease. With respect to its interaction with learning, both decreases and increases have been observed. In this study, we examined the effect of two types of practice schedules, blocked and randomized, on memory retention one week later. A blocked schedule leads to better performance during acquisition but poorer performance during long-term retention, a phenomenon known as the contextual interference effect. The aim of the present study is two-fold: (1) test the contextual interference effect using a visuomotor bimanual tracking task (2) determine whether three days of practice leads to a decreased PMBR at retention test one week later. We hypothesized that learning with either schedule would lead to decreased PMBR. Our data demonstrated no main effect of practice schedule. It is most likely that the task variants were not sufficiently different to induce the contextual interference phenomenon. Further, the PMBR was not attenuated by learning. It was evident before and after three days of practice. This has important implications for its putative role as a biomarker.

show abstract

Frequency-Specific Biomarkers in Neurodegenerative Disorders: Implications of Alpha and Beta Oscillations in Motor Behaviour

Cited by 2 publications

References 0 publications

Wavelet Theories and Techniques for Brain Disease: Diagnosis and Treatmentz

Wavelet Theories and Techniques for Brain Disease: Diagnosis and Treatmentz

Post-Movement Beta Rebound in Sensorimotor Cortex Endures One Week After Three Days of Practice

Contact Info

Product

Resources

About