Dissecting Motor and Cognitive Component Processes of a Finger-Tapping Task With Hybrid Dopamine Positron Emission Tomography and Functional Magnetic Resonance Imaging

Effects of deep brain stimulation on dopamine D2 receptor binding in patients with treatment-refractory depression

BACKGROUND

Depression is a chronic psychiatric disorder related to diminished dopaminergic neurotransmission. Deep brain stimulation (DBS) has shown effectiveness in treating patients with treatment-refractory depression (TRD). This study aimed to evaluate the effect of DBS on dopamine D2 receptor binding in patients with TRD.

METHODS

Six patients with TRD were treated with bed nucleus of the stria terminalis (BNST)-nucleus accumbens (NAc) DBS were recruited. Ultra-high sensitivity [11C]raclopride dynamic total-body positron emission tomography (PET) imaging was used to assess the brain D2 receptor binding. Each patient underwent a [11C]raclopride PET scan for 60-min under DBS OFF and DBS ON, respectively. A simplified reference tissue model was used to generate parametric images of binding potential (BPND) with the cerebellum as reference tissue.

RESULTS

Depression and anxiety symptoms improved after 3-6 months of DBS treatment. Compared with two-day-nonstimulated conditions, one-day BNST-NAc DBS decreased [11C]raclopride BPND in the amygdala (15.9 %, p < 0.01), caudate nucleus (15.4 %, p < 0.0001) and substantia nigra (10.8 %, p < 0.01).

LIMITATIONS

This study was limited to the small sample size and lack of a healthy control group.

CONCLUSIONS

Chronic BNST-NAc DBS improved depression and anxiety symptoms, and short-term stimulation decreased D2 receptor binding in the amygdala, caudate nucleus, and substantia nigra. The findings suggest that DBS relieves depression and anxiety symptoms possibly by regulating the dopaminergic system.

Novel voxelwise residual analysis of [11C]raclopride PET data improves detection of low-amplitude dopamine release

Existing methods for voxelwise transient dopamine (DA) release detection rely on explicit kinetic modeling of the [11C]raclopride PET time activity curve, which at the voxel level is typically confounded by noise, leading to poor performance for detection of low-amplitude DA release-induced signals. Here we present a novel data-driven, task-informed method-referred to as Residual Space Detection (RSD)-that transforms PET time activity curves to a residual space where DA release-induced perturbations can be isolated and processed. Using simulations, we demonstrate that this method significantly increases detection performance compared to existing kinetic model-based methods for low-magnitude DA release (simulated +100% peak increase in basal DA concentration). In addition, results from nine healthy controls injected with a single bolus of [11C]raclopride performing a finger tapping motor task are shown as proof-of-concept. The ability to detect relatively low magnitudes of dopamine release in the human brain using a single bolus injection, while achieving higher statistical power than previous methods, may additionally enable more complex analyses of neurotransmitter systems. Moreover, RSD is readily generalizable to multiple tasks performed during a single PET scan, further extending the capabilities of task-based single-bolus protocols.

Amphetamine-induced dopamine release in rat: Whole-brain spatiotemporal analysis with [11C]raclopride and positron emission tomography

Whole-brain mapping of drug effects are needed to understand the neural underpinnings of drug-related behaviors. Amphetamine administration is associated with robust increases in striatal dopamine (DA) release. Dopaminergic terminals are, however, present across several associative brain regions, which may contribute to behavioral effects of amphetamine. Yet the assessment of DA release has been restricted to a few brain regions of interest. The present work employed positron emission tomography (PET) with [11C]raclopride to investigate regional and temporal characteristics of amphetamine-induced DA release across twenty sessions in adult female Sprague Dawley rats. Amphetamine was injected intravenously (2 mg/kg) to cause displacement of [11C]raclopride binding from DA D2-like receptors, assessed using temporally sensitive pharmacokinetic PET model (lp-ntPET). We show amphetamine-induced [11C]raclopride displacement in the basal ganglia, and no changes following saline injections. Peak occupancy was highest in nucleus accumbens, followed by caudate-putamen and globus pallidus. Importantly, significant amphetamine-induced displacement was also observed in several extrastriatal regions, and specifically in thalamus, insula, orbitofrontal cortex, and secondary somatosensory area. For these, peak occupancy occurred later and was lower as compared to the striatum. Collectively, these findings demonstrate distinct amphetamine-induced DA responses across the brain, and that [11C]raclopride-PET can be employed to detect such spatiotemporal differences.

Dopamine release in human associative striatum during reversal learning

The dopaminergic system is firmly implicated in reversal learning but human measurements of dopamine release as a correlate of reversal learning success are lacking. Dopamine release and hemodynamic brain activity in response to unexpected changes in action-outcome probabilities are here explored using simultaneous dynamic [11C]Raclopride PET-fMRI and computational modelling of behavior. When participants encounter reversed reward probabilities during a card guessing game, dopamine release is observed in associative striatum. Individual differences in absolute reward prediction error and sensitivity to errors are associated with peak dopamine receptor occupancy. The fMRI response to perseverance errors at the onset of a reversal spatially overlap with the site of dopamine release. Trial-by-trial fMRI correlates of absolute prediction errors show a response in striatum and association cortices, closely overlapping with the location of dopamine release, and separable from a valence signal in ventral striatum. The results converge to implicate striatal dopamine release in associative striatum as a central component of reversal learning, possibly signifying the need for increased cognitive control when new stimuli-responses should be learned.

Delayed and More Variable Unimanual and Bimanual Finger Tapping in Alzheimer's Disease: Associations with Biomarkers and Applications for Classification

BACKGROUND

Despite reports of gross motor problems in mild cognitive impairment (MCI) and Alzheimer's disease (AD), fine motor function has been relatively understudied.

OBJECTIVE

We examined if finger tapping is affected in AD, related to AD biomarkers, and able to classify MCI or AD.

METHODS

Forty-seven cognitively normal, 27 amnestic MCI, and 26 AD subjects completed unimanual and bimanual computerized tapping tests. We tested 1) group differences in tapping with permutation models; 2) associations between tapping and biomarkers (PET amyloid-β, hippocampal volume, and APOEɛ4 alleles) with linear regression; and 3) the predictive value of tapping for group classification using machine learning.

RESULTS

AD subjects had slower reaction time and larger speed variability than controls during all tapping conditions, except for dual tapping. MCI subjects performed worse than controls on reaction time and speed variability for dual and non-dominant hand tapping. Tapping speed and variability were related to hippocampal volume, but not to amyloid-β deposition or APOEɛ4 alleles. Random forest classification (overall accuracy = 70%) discriminated control and AD subjects, but poorly discriminated MCI from controls or AD.

CONCLUSIONS

MCI and AD are linked to more variable finger tapping with slower reaction time. Associations between finger tapping and hippocampal volume, but not amyloidosis, suggest that tapping deficits are related to neuropathology that presents later during the disease. Considering that tapping performance is able to differentiate between control and AD subjects, it can offer a cost-efficient tool for augmenting existing AD biomarkers.