Timing variability and midfrontal ~4 Hz rhythms correlate with cognition in Parkinson’s disease

Abstract

Patients with Parkinson's disease (PD) can have significant cognitive dysfunction; however, the mechanism of these cognitive symptoms are unknown. Here, we used scalp electroencephalography (EEG) to investigate the cortical basis for PD-related cognitive impairments during interval timing, which requires participants to estimate temporal intervals of several seconds. Time estimation is an ideal task demand for investigating cognition in PD because it is simple, requires medial frontal cortical areas, and recruits basic executive processes such as working memory and attention. However, interval timing has never been systematically studied in PD patients with cognitive impairments. We report three main findings. First, 71 PD patients had increased temporal variability compared to 37 demographically-matched controls, and this variability correlated with cognitive dysfunction as measured by the Montreal Cognitive Assessment (MOCA). Second, PD patients had attenuated ~4 Hz EEG oscillatory activity at midfrontal electrodes in response to the interval-onset cue, which was also predictive of MOCA. Finally, trial-by-trial linear mixed-effects modeling demonstrated that cue-triggered ~4 Hz power predicted subsequent temporal estimates as a function of PD and MOCA. Our data suggest that impaired cue-evoked midfrontal ~4 Hz activity predicts increased timing variability that is indicative of cognitive dysfunction in PD. These findings link PD-related cognitive dysfunction with cortical mechanisms of cognitive control, which could advance novel biomarkers and neuromodulation for PD.

Experience-related remapping of temporal encoding by striatal ensembles

“…The first is that we cannot dissociate MSN subtypes that express D1 vs. D2 dopamine receptors, and we are uncertain how the powerful neuromodulator dopamine affects striatal networks (Cui et al , 2013). Second, we cannot fully dissociate ramping activity from movements, which would require alternative task designs (Church & Deluty, 1977), although one critical advantage of our task design is that it readily translates to humans (Ward et al , 2011; Kim et al , 2017; Parker et al , 2017), particularly with Parkinson’s disease (Singh et al , 2021). Third, with our approach, we were unable to identify oscillatory or state-based coding schemes in the striatum that change with experience, although our analytical approach may not be suited to identify these network properties.…”

“…Precisely guiding movements in time is critical for human behaviors, such as cooking, driving, and crossing the street (Buhusi & Meck, 2005). Temporal control of action is disrupted in diseases such as Parkinson’s disease (PD) and schizophrenia (Ward et al , 2011; Parker et al , 2013; Singh et al , 2021). A brain structure that is affected by both diseases and is key for controlling movements in time is the dorsal striatum (Matell & Meck, 2004; Meck, 2006).…”

No difference in cognitive task-related oscillations between human internal globus pallidus and subthalamic nucleus

“…These steps defined the width (or 'cycles') of each frequency band, increasing from three to ten cycles, between 1 and 50 Hz, and taking the inverse FFT (Singh et al, 2021;Singh et al, 2018).…”

“…The power was normalized by converting the spectral amplitude to a decibel (dB) scale using the formula 10 * 10 ( / ), allowing us to compare the effects across frequency bands directly. As in our previous work, the baseline for each frequency was calculated by averaging power from −300 to −200 ms before the onset of the stimulus/response (Singh et al, 2020;Singh et al, 2021;Singh et al, 2018). Afterward, epochs were segmented from -500 to +1000 ms.…”

“…These tf-ROIs were based on previous studies (Singh et al, 2020;Singh et al, 2021;Singh et al, 2018).…”