Parkinson's disease causes a characteristic combination of motor symptoms due to progressive neurodegeneration of dopaminergic neurons in the substantia nigra pars compacta. The core impairment of ...dopaminergic neurotransmission has motivated the use of functional magnetic resonance imaging (fMRI) in patients with Parkinson's disease to elucidate the role of dopamine in motor control and cognition in humans. Here we review the main insights from functional brain imaging in Parkinson's disease. Task-related fMRI revealed many disease-related alterations in brain activation patterns. However, the interpretation of these findings is complicated by the fact that task-dependent activity is influenced by complex interactions between the amount of dopaminergic neurodegeneration in the task-relevant nuclei, the state of medication, genetic factors and performance. Despite these ambiguities, fMRI studies in Parkinson's disease demonstrated a central role of dopamine in the generation of movement vigour (bradykinesia) and the control of excessive movements (dyskinesia), involving changes of both activity and connectivity of the putamen, premotor and motor regions, and right inferior frontal gyrus (rIFG). The fMRI studies addressing cognitive flexibility provided convergent evidence for a non-linear, U-shaped, relationship between dopamine levels and performance. The amount of neurodegeneration in the task-relevant dopaminergic nuclei and pharmacological dopamine replacement can therefore move performance either away or towards the task-specific optimum. Dopamine levels also strongly affect processing of reward and punishment for optimal learning. However, further studies are needed for a detailed understanding of the mechanisms underlying these effects.
•Parkinson's disease (PD) results in neurodegeneration of dopaminergic neurons.•Functional MRI in patients examines the role of dopamine in the human brain.•Evidence point to a central role of dopamine in securing movement vigour.•Dopamine levels and cognitive performance show an inverse U-shape relationship.•Dopamine is central for learning from rewards and punishments.
This study aimed to investigate the spatiotemporal changes in neuromelanin-sensitive MRI signal in the substantia nigra and their relation to clinical scores of disease severity in patients with ...early or progressing Parkinson's disease and patients with idiopathic rapid eye movement sleep behaviour disorder (iRBD) exempt of Parkinsonian signs compared to healthy control subjects. Longitudinal T1-weighted anatomical and neuromelanin-sensitive MRI was performed in two cohorts, including patients with iRBD, patients with early or progressing Parkinson's disease, and control subjects. Based on the aligned substantia nigra segmentations using a study-specific brain anatomical template, parametric maps of the probability of a voxel belonging to the substantia nigra were calculated for patients with various degrees of disease severity and controls. For each voxel in the substantia nigra, probability map of controls, correlations between signal-to-noise ratios on neuromelanin-sensitive MRI in patients with iRBD and Parkinson's disease and clinical scores of motor disability, cognition and mood/behaviour were calculated. Our results showed that in patients, compared to the healthy control subjects, the volume of the substantia nigra was progressively reduced for increasing disease severity. The neuromelanin signal changes appeared to start in the posterolateral motor areas of the substantia nigra and then progressed to more medial areas of this region. The ratio between the volume of the substantia nigra in patients with Parkinson's disease relative to the controls was best fitted by a mono-exponential decay. Based on this model, the pre-symptomatic phase of the disease started at 5.3 years before disease diagnosis, and 23.1% of the substantia nigra volume was lost at the time of diagnosis, which was in line with previous findings using post-mortem histology of the human substantia nigra and radiotracer studies of the human striatum. Voxel-wise patterns of correlation between neuromelanin-sensitive MRI signal-to-noise ratio and motor, cognitive and mood/behavioural clinical scores were localized in distinct regions of the substantia nigra. This localization reflected the functional organization of the nigrostriatal system observed in histological and electrophysiological studies in non-human primates (motor, cognitive and mood/behavioural domains). In conclusion, neuromelanin-sensitive MRI enabled us to assess voxel-wise modifications of substantia nigra's morphology in vivo in humans, including healthy controls, patients with iRBD and patients with Parkinson's disease, and identify their correlation with nigral function across all motor, cognitive and behavioural domains. This insight could help assess disease progression in drug trials of disease modification.
In Parkinson's disease, there is a progressive reduction in striatal dopaminergic function, and loss of neuromelanin-containing dopaminergic neurons and increased iron deposition in the substantia ...nigra. We tested the hypothesis of a relationship between impairment of the dopaminergic system and changes in the iron metabolism. Based on imaging data of patients with prodromal and early clinical Parkinson's disease, we assessed the spatiotemporal ordering of such changes and relationships in the sensorimotor, associative and limbic territories of the nigrostriatal system. Patients with Parkinson's disease (disease duration < 4 years) or idiopathic REM sleep behaviour disorder (a prodromal form of Parkinson's disease) and healthy controls underwent longitudinal examination (baseline and 2-year follow-up). Neuromelanin and iron sensitive MRI and dopamine transporter single-photon emission tomography were performed to assess nigrostriatal levels of neuromelanin, iron, and dopamine. For all three functional territories of the nigrostriatal system, in the clinically most and least affected hemispheres separately, the following was performed: cross-sectional and longitudinal intergroup difference analysis of striatal dopamine and iron, and nigral neuromelanin and iron; in Parkinson's disease patients, exponential fitting analysis to assess the duration of the prodromal phase and the temporal ordering of changes in dopamine, neuromelanin or iron relative to controls; and voxel-wise correlation analysis to investigate concomitant spatial changes in dopamine-iron, dopamine-neuromelanin and neuromelanin-iron in the substantia nigra pars compacta. The temporal ordering of dopaminergic changes followed the known spatial pattern of progression involving first the sensorimotor, then the associative and limbic striatal and nigral regions. Striatal dopaminergic denervation occurred first followed by abnormal iron metabolism and finally neuromelanin changes in the substantia nigra pars compacta, which followed the same spatial and temporal gradient observed in the striatum but shifted in time. In conclusion, dopaminergic striatal dysfunction and cell loss in the substantia nigra pars compacta are interrelated with increased nigral iron content.
Our knowledge on temporal lobe epilepsy (TLE) with hippocampal sclerosis has evolved towards the view that this syndrome affects widespread brain networks. Diffusion weighted imaging studies have ...shown alterations of large white matter tracts, most notably in left temporal lobe epilepsy, but the degree of altered connections between cortical and subcortical structures remains to be clarified. We performed a whole brain connectome analysis in 39 patients with refractory temporal lobe epilepsy and unilateral hippocampal sclerosis (20 right and 19 left) and 28 healthy subjects. We performed whole-brain probabilistic fiber tracking using MRtrix and segmented 164 cortical and subcortical structures with Freesurfer. Individual structural connectivity graphs based on these 164 nodes were computed by mapping the mean fractional anisotropy (FA) onto each tract. Connectomes were then compared using two complementary methods: permutation tests for pair-wise connections and Network Based Statistics to probe for differences in large network components. Comparison of pair-wise connections revealed a marked reduction of connectivity between left TLE patients and controls, which was strongly lateralized to the ipsilateral temporal lobe. Specifically, infero-lateral cortex and temporal pole were strongly affected, and so was the perisylvian cortex. In contrast, for right TLE, focal connectivity loss was much less pronounced and restricted to bilateral limbic structures and right temporal cortex. Analysis of large network components revealed furthermore that both left and right hippocampal sclerosis affected diffuse global and interhemispheric connectivity. Thus, left temporal lobe epilepsy was associated with a much more pronounced pattern of reduced FA, that included major landmarks of perisylvian language circuitry. These distinct patterns of connectivity associated with unilateral hippocampal sclerosis show how a focal pathology influences global network architecture, and how left or right-sided lesions may have differential and specific impacts on cerebral connectivity.
•We computed the structural network of 39 temporal lobe epilepsy (TLE) patients.•Two strategies, pairwise connection analysis and network based statistics, were used.•Widespread disconnections were found in TLE patients with respect to controls.•Left TLE patients were much more affected than right TLE patients.•Left TLE showed a strongly lateralized fronto-temporal disconnection pattern.
This review discusses the cerebral plasticity, and the role of the cortico-striatal system in particular, observed as one is learning or planning to execute a newly learned motor behavior up to when ...the skill is consolidated or has become highly automatized. A special emphasis is given to imaging work describing the neural substrate mediating motor sequence learning and motor adaptation paradigms. These results are then put into a plausible neurobiological model of motor skill learning, which proposes an integrated view of the brain plasticity mediating this form of memory at different stages of the acquisition process.
Purpose
We present and evaluate a new automated method based on support vector machine (SVM) classification of whole-brain anatomical magnetic resonance imaging to discriminate between patients with ...Alzheimer’s disease (AD) and elderly control subjects.
Materials and methods
We studied 16 patients with AD mean age ± standard deviation (SD) = 74.1 ± 5.2 years, mini-mental score examination (MMSE) = 23.1 ± 2.9 and 22 elderly controls (72.3 ± 5.0 years, MMSE = 28.5 ± 1.3). Three-dimensional T1-weighted MR images of each subject were automatically parcellated into regions of interest (ROIs). Based upon the characteristics of gray matter extracted from each ROI, we used an SVM algorithm to classify the subjects and statistical procedures based on bootstrap resampling to ensure the robustness of the results.
Results
We obtained 94.5% mean correct classification for AD and control subjects (mean specificity, 96.6%; mean sensitivity, 91.5%).
Conclusions
Our method has the potential in distinguishing patients with AD from elderly controls and therefore may help in the early diagnosis of AD.
We describe a new method to automatically discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly controls, based on multidimensional classification ...of hippocampal shape features. This approach uses spherical harmonics (SPHARM) coefficients to model the shape of the hippocampi, which are segmented from magnetic resonance images (MRI) using a fully automatic method that we previously developed. SPHARM coefficients are used as features in a classification procedure based on support vector machines (SVM). The most relevant features for classification are selected using a bagging strategy. We evaluate the accuracy of our method in a group of 23 patients with AD (10 males, 13 females, age±standard-deviation (SD)=73±6 years, mini-mental score (MMS)=24.4±2.8), 23 patients with amnestic MCI (10 males, 13 females, age±SD=74±8 years, MMS=27.3±1.4) and 25 elderly healthy controls (13 males, 12 females, age±SD=64±8 years), using leave-one-out cross-validation. For AD vs controls, we obtain a correct classification rate of 94%, a sensitivity of 96%, and a specificity of 92%. For MCI vs controls, we obtain a classification rate of 83%, a sensitivity of 83%, and a specificity of 84%. This accuracy is superior to that of hippocampal volumetry and is comparable to recently published SVM-based whole-brain classification methods, which relied on a different strategy. This new method may become a useful tool to assist in the diagnosis of Alzheimer's disease.
Gait disorders and postural instability, which are commonly observed in elderly patients with Parkinson disease (PD), respond poorly to dopaminergic agents used to treat other parkinsonian symptoms. ...The brain structures underlying gait disorders and falls in PD and aging remain to be characterized. Using functional MRI in healthy human subjects, we have shown here that activity of the mesencephalic locomotor region (MLR), which is composed of the pedunculopontine nucleus (PPN) and the adjacent cuneiform nucleus, was modulated by the speed of imagined gait, with faster imagined gait activating a discrete cluster within the MLR. Furthermore, the presence of gait disorders in patients with PD and in aged monkeys rendered parkinsonian by MPTP intoxication correlated with loss of PPN cholinergic neurons. Bilateral lesioning of the cholinergic part of the PPN induced gait and postural deficits in nondopaminergic lesioned monkeys. Our data therefore reveal that the cholinergic neurons of the PPN play a central role in controlling gait and posture and represent a possible target for pharmacological treatment of gait disorders in PD.
To prospectively evaluate the accuracy of automated hippocampal volumetry to help distinguish between patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and elderly ...controls, by using established criteria for patients with AD and MCI as the reference standard.
The regional ethics committee approved the study and written informed consent was obtained from all participants. The study included 25 patients with AD (11 men, 14 women; mean age +/- standard deviation SD, 73 years +/- 6; Mini-Mental State Examination (MMSE) score, 24.4 +/- 2.7), 24 patients with amnestic MCI (10 men, 14 women; mean age +/- SD, 74 years +/- 8; MMSE score, 27.2 +/- 1.4) and 25 elderly healthy controls (13 men, 12 women; mean age +/- SD, 64 years +/- 8). For each participant, the hippocampi were automatically segmented on three-dimensional T1-weighted magnetic resonance (MR) images with high spatial resolution. Segmentation was performed by using recently developed software that allows fast segmentation with minimal user input. Group differences in hippocampal volume were assessed by using Student t tests. To obtain robust estimates of P values, the correct classification rate, sensitivity, and specificity, bootstrap methods were used.
Significant hippocampal volume reductions were detected in all groups of patients (-32% in AD patients vs controls, P < .001; -19% in MCI patients vs controls, P < .001; and -15% in AD patients vs MCI patients, P < .01). Individual classification on the basis of hippocampal volume resulted in 84% correct classification (sensitivity, 84%; specificity, 84%) between AD patients and controls and 73% correct classification (sensitivity, 75%; specificity, 70%) between MCI patients and controls.
This automated method can serve as an alternative to manual tracing and may thus prove useful in assisting with the diagnosis of AD.
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