Cerebellar Cortex 4–12 Hz Oscillations and Unit Phase Relation in the Awake Rat

Lévesque, Maxime; Gao, Hongying; Southward, Carla; Langlois, J. M. Pierre; Léna, Clément; Courtemanche, Richard

doi:10.3389/fnsys.2020.475948

Cited by 5 publications

(5 citation statements)

References 110 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The cerebellar cortex supports oscillatory activity occurring at a broad range of frequencies even in the absence of movement (Courtemanche et al, 2002(Courtemanche et al, , 2013Levesque et al, 2020). However, the occurrence of oscillations in the cerebellar nuclei remains controversial.…”

Section: Introductionmentioning

confidence: 99%

Cerebellar nuclei neurons display aberrant oscillations during harmaline-induced tremor

Baumel

Yamin

Cohen

2021

Heliyon

View full text Add to dashboard Cite

Essential tremor, a common, debilitating motor disorder, is thought to be caused by cerebellar malfunction. It has been shown that rhythmic Purkinje cell firing is both necessary and sufficient to induce body tremor. During tremor, cerebellar nuclei (CN) cells also display oscillatory activity. This study examined whether rhythmic activity in the CN characterizes the occurrence of body tremor, or alternatively, whether aberrant bursting activity underlies body tremor. Cerebellar nuclei activity was chronically recorded and analyzed in freely moving and in harmaline treated rats. CN neurons displayed rhythmic activity in both conditions, but the number of oscillatory neurons and the relative oscillation time were significantly higher under harmaline. The dominant frequencies of the oscillations were broadly distributed under harmaline and the likelihood that two simultaneously recorded neurons would co-oscillate and their oscillation coherence were significantly lower. It is argued that these alterations rather than neuronal rhythmicity per se underlie harmaline-induced body tremor.

show abstract

Section: Introductionmentioning

confidence: 99%

Cerebellar nuclei neurons display aberrant oscillations during harmaline-induced tremor

Baumel

Yamin

Cohen

2021

Heliyon

View full text Add to dashboard Cite

show abstract

“…As a final note, for the sake of brevity, we have not discussed the relationship between the spectrum of a process and its autocorrelation function ( Lamarre and Raynauld, 1965 ; Perkel et al, 1967 ; Lang et al, 1999 ; Lévesque et al, 2020 ). Readers wishing to expend on the theory of spectral estimation can find extended discussion in the book ‘Spectral Analysis for Physical Applications’ ( Percival and Walden, 1993 ).…”

Section: Discussionmentioning

confidence: 99%

Beyond rhythm – a framework for understanding the frequency spectrum of neural activity

Perrenoud,

Cardin

2023

Front. Syst. Neurosci.

View full text Add to dashboard Cite

Cognitive and behavioral processes are often accompanied by changes within well-defined frequency bands of the local field potential (LFP i.e., the voltage induced by neuronal activity). These changes are detectable in the frequency domain using the Fourier transform and are often interpreted as neuronal oscillations. However, aside some well-known exceptions, the processes underlying such changes are difficult to track in time, making their oscillatory nature hard to verify. In addition, many non-periodic neural processes can also have spectra that emphasize specific frequencies. Thus, the notion that spectral changes reflect oscillations is likely too restrictive. In this study, we use a simple yet versatile framework to understand the frequency spectra of neural recordings. Using simulations, we derive the Fourier spectra of periodic, quasi-periodic and non-periodic neural processes having diverse waveforms, illustrating how these attributes shape their spectral signatures. We then show how neural processes sum their energy in the local field potential in simulated and real-world recording scenarios. We find that the spectral power of neural processes is essentially determined by two aspects: (1) the distribution of neural events in time and (2) the waveform of the voltage induced by single neural events. Taken together, this work guides the interpretation of the Fourier spectrum of neural recordings and indicates that power increases in specific frequency bands do not necessarily reflect periodic neural activity.

show abstract

“…The definitions of the LFP and MUA band frequency ranges vary greatly in the literature. The limits of LFP and MUA are generally defined between 0.5–500 Hz ( Burns et al, 2010 ; Dubey and Ray, 2019 ; Lévesque et al, 2020 ; Baumel et al, 2021 ) and 300–10,000 Hz ( Heck et al, 2007 ; Burns et al, 2010 ; Asan and Sahin, 2019 ; Dubey and Ray, 2019 ) respectively. Thus, the choices of the exact division points of these bands are somewhat arbitrary.…”

Section: Methodsmentioning

confidence: 99%

Sensorimotor content of multi-unit activity recorded in the paramedian lobule of the cerebellum using carbon fiber microelectrode arrays

Cetinkaya,

Lang,

Sahin

2024

Front. Neurosci.

View full text Add to dashboard Cite

The cerebellum takes in a great deal of sensory information from the periphery and descending signals from the cerebral cortices. It has been debated whether the paramedian lobule (PML) in the rat and its paravermal regions that project to the interpositus nucleus (IPN) are primarily involved in motor execution or motor planning. Studies that have relied on single spike recordings in behaving animals have led to conflicting conclusions regarding this issue. In this study, we tried a different approach and investigated the correlation of field potentials and multi-unit signals recorded with multi-electrode arrays from the PML cortex along with the forelimb electromyography (EMG) signals in rats during behavior. Linear regression was performed to predict the EMG signal envelopes using the PML activity for various time shifts (±25, ±50, ±100, and ± 400 ms) between the two signals to determine a causal relation. The highest correlations (~0.5 on average) between the neural and EMG envelopes were observed for zero and small (±25 ms) time shifts and decreased with larger time shifts in both directions, suggesting that paravermal PML is involved both in processing of sensory signals and motor execution in the context of forelimb reaching behavior. EMG envelopes were predicted with higher success rates when neural signals from multiple phases of the behavior were utilized for regression. The forelimb extension phase was the most difficult to predict while the releasing of the bar phase prediction was the most successful. The high frequency (>300 Hz) components of the neural signal, reflecting multi-unit activity, had a higher contribution to the EMG prediction than did the lower frequency components, corresponding to local field potentials. The results of this study suggest that the paravermal PML in the rat cerebellum is primarily involved in the execution of forelimb movements rather than the planning aspect and that the PML is more active at the initiation and termination of the behavior, rather than the progression.

show abstract

Cerebellar Cortex 4–12 Hz Oscillations and Unit Phase Relation in the Awake Rat

Cited by 5 publications

References 110 publications

Cerebellar nuclei neurons display aberrant oscillations during harmaline-induced tremor

Cerebellar nuclei neurons display aberrant oscillations during harmaline-induced tremor

Beyond rhythm – a framework for understanding the frequency spectrum of neural activity

Sensorimotor content of multi-unit activity recorded in the paramedian lobule of the cerebellum using carbon fiber microelectrode arrays

Contact Info

Product

Resources

About