Slow Brain Potential and Oscillatory EEG Manifestations of Impaired Temporal Preparation in Parkinson's Disease

Abstract

Performance in behavioral tasks is influenced by temporal expectations shaped by the temporal structure of the task. Such implicit temporal preparation is reflected in slow brain potentials and electroencephalographic oscillations and is attributed to interval timing mechanisms that probably depend on intact basal ganglia function. We investigated implicit timing in Parkinson's disease using a choice reaction task with two temporally regular stimulus presentation regimes, both including occasional deviant interstimulus intervals. Control subjects, but not patients, demonstrated temporal preparation in the form of an adjustment in time course of slow brain potentials to the duration of the interstimulus interval. However, in both groups, timing perturbations were accompanied by a slow brain potential amplitude drop at the time of expected stimulus occurrence, demonstrating intact representation of time in patients. In patients, oscillatory activity in beta and alpha bands showed attenuated preparatory desynchronization and reduced postmovement event-related synchronization, reflecting abnormal engagement and disengagement of sensorimotor and parietal areas. The results demonstrate profoundly deficient temporal preparation with preserved encoding of temporal information, a dissociation that may be explained by impaired dopamine-dependent motor learning. The results are discussed in the context of recent work on oscillatory activity in the basal ganglia.

Medial frontal ∼4-Hz activity in humans and rodents is attenuated in PD patients and in rodents with cortical dopamine depletion

“…In previous studies, it was found that temporal processing in PD appears to markedly affect beta and alpha rhythms in PD in motor cortex, although previous investigators did not focus on lower frequencies (Praamstra and Pope 2007). Recent work has implicated decreased theta in addition to alpha and beta frequencies in diagnosis of PD, in distinct brain regions (Benz et al 2014;Gu et al 2014Han et al 2013Praamstra and Pope 2007).…”

“…In previous studies, it was found that temporal processing in PD appears to markedly affect beta and alpha rhythms in PD in motor cortex, although previous investigators did not focus on lower frequencies (Praamstra and Pope 2007). Recent work has implicated decreased theta in addition to alpha and beta frequencies in diagnosis of PD, in distinct brain regions (Benz et al 2014;Gu et al 2014Han et al 2013Praamstra and Pope 2007). Our work extends this line of research by focusing on MFC and linking spectral activity in PD patients with mechanistic theories (Cavanagh and Frank 2014) and single neuron activity that is consistently involved in temporal processing (Bekolay et al 2014;Kim et al 2013;Matell and Meck 2004;Narayanan and Laubach 2009;Niki and Watanabe 1979;Parker et al 2014;Xu et al 2014).…”

Combining spatial and temporal expectations to improve visual perception

“…These results have been supported by studies in humans showing enhancement of the early visual P1 potential in response to targets with high temporal expectation (Doherty, Rao, Mesulam, & Nobre, 2005;Zanto et al, 2011). Additionally, studies in humans and nonhuman primates have shown that temporal expectation modulates anticipatory neural activity to enhance the perceptual processing of events occurring at expected times (Besle et al, 2011;Cravo, Rohenkohl, Wyart, & Nobre, 2013;Green & McDonald, 2010;Lima et al, 2011;Praamstra, Kourtis, Kwok, & Oostenveld, 2006;Praamstra & Pope, 2007;Stefanics et al, 2010;van Ede, de Lange, Jensen, & Maris, 2011).…”

Tracking Temporal Hazard in the Human Electroencephalogram Using a Forward Encoding Model

“…The sign and sources of this peak, localized to the bilateral SMA and adjacent regions, strongly argues for a relation to the well-described contingent negative variation (CNV; Walter et al, 1964) thought to emerge from the SMA. The CNV has often been described in explicit timing tasks (Macar et al, 1999; Macar and Vidal, 2004; Praamstra and Pope, 2007; Wiener et al, 2010; Merchant et al, 2013; Herbst et al, 2014). Note, however, that we did not observe a clear CNV in the event-related potential analysis presented in Herbst and Obleser (2017), which shows that the encoding model approach exhibits higher sensitivity.…”