Patterns of cortical thinning in idiopathic rapid eye movement sleep behavior disorder.

Idiopathic rapid eye movement sleep behavior disorder is a parasomnia that is a risk factor for dementia with Lewy bodies and Parkinson's disease. Brain function impairments have been identified in this disorder, mainly in the frontal and posterior cortical regions. However, the anatomical support for these dysfunctions remains poorly understood. We investigated gray matter thickness, gray matter volume, and white matter integrity in patients with idiopathic rapid eye movement sleep behavior disorder. Twenty-four patients with polysomnography-confirmed idiopathic rapid eye movement sleep behavior disorder and 42 healthy individuals underwent a 3-tesla structural and diffusion magnetic resonance imaging examination using corticometry, voxel-based morphometry, and diffusion tensor imaging. In the patients with idiopathic rapid eye movement sleep behavior disorder, decreased cortical thickness was observed in the frontal cortex, the lingual gyrus, and the fusiform gyrus. Gray matter volume was reduced in the superior frontal sulcus only. Patients showed no increased gray matter thickness or volume. Diffusion tensor imaging analyses revealed no significant white matter differences between groups. Using corticometry in patients with idiopathic rapid eye movement sleep behavior disorder, several new cortical regions with gray matter alterations were identified, similar to those reported in dementia with Lewy bodies and Parkinson's disease. These findings provide some anatomical support for previously identified brain function impairments in this disorder.

Mild cognitive impairment in patients with Parkinson's disease is associated with increased cortical degeneration.

Mild cognitive impairment (MCI) can occur early in the course of Parkinson's disease (PD), and its presence increases the risk of developing dementia. Determining the cortical changes associated with MCI in PD, thus, may be useful in predicting the future development of dementia. To address this objective, 37 patients with PD, divided into 2 groups according to the presence or absence MCI (18 with and 19 without) and 16 matched controls, underwent anatomic magnetic resonance imaging. Corticometry analyses were performed to measure the changes in cortical thickness and surface area as well as their correlation with disease duration. Compared with healthy controls, the PD-MCI group exhibited increased atrophy and changes of local surface area in the bilateral occipital, left temporal, and frontal cortices; whereas the PD non-MCI group exhibited only unilateral thinning and decreased surface area in the occipital lobe and in the frontal cortex. In addition, a comparison between the PD-MCI and PD non-MCI groups revealed increased local surface area in the occipital lobe, temporal lobe, and postcentral gyrus for the cognitively impaired patients. It is noteworthy that, in the PD-MCI group, cortical thickness had a significant negative correlation with disease duration in the precentral, supramarginal, occipital, and superior temporal cortices; whereas, in the PD non-MCI group, such a correlation was absent. The findings from this study reveal that, at the same stage of PD evolution, the presence of MCI is associated with a higher level of cortical changes, suggesting that cortical degeneration is increased in patients with PD because of the presence of MCI.

Deep learning, data ramping, and uncertainty estimation for detecting artifacts in large, imbalanced databases of MRI images.

Magnetic resonance imaging (MRI) is increasingly being used to delineate morphological changes underlying neurological disorders. Successfully detecting these changes depends on the MRI data quality. Unfortunately, image artifacts frequently compromise the MRI utility, making it critical to screen the data. Currently, quality assessment requires visual inspection, a time-consuming process that suffers from inter-rater variability. Automated methods to detect MRI artifacts could improve the efficiency of the process. Such automated methods have achieved high accuracy using small datasets, with balanced proportions of MRI data with and without artifacts. With the current trend towards big data in neuroimaging, there is a need for automated methods that achieve accurate detection in large and imbalanced datasets. Deep learning (DL) is the ideal MRI artifact detection algorithm for large neuroimaging databases. However, the inference generated by DL does not commonly include a measure of uncertainty. Here, we present the first stochastic DL algorithm to generate automated, high-performing MRI artifact detection implemented on a large and imbalanced neuroimaging database. We implemented Monte Carlo dropout in a 3D AlexNet to generate probabilities and epistemic uncertainties. We then developed a method to handle class imbalance, namely data-ramping to transfer the learning by extending the dataset size and the proportion of the artifact-free data instances. We used a 34,800 scans (98% clean) dataset. At baseline, we obtained 89.3% testing accuracy (F1 = 0.230). Following the transfer learning (with data-ramping), we obtained 94.9% testing accuracy (F1 = 0.357) outperforming focal cross-entropy (92.9% testing accuracy, F1 = 0.304) incorporated for comparison at handling class imbalance. By implementing epistemic uncertainties, we improved the testing accuracy to 99.5% (F1 = 0.834), outperforming the results obtained in previous comparable studies. In addition, we estimated aleatoric uncertainties by incorporating random flips to the MRI volumes, and demonstrated that aleatoric uncertainty can be implemented as part of the pipeline. The methods we introduce enhance the efficiency of managing large databases and the exclusion of artifact images from big data analyses.

Color discrimination deficits in Parkinson's disease are related to cognitive impairment and white-matter alterations.

Color discrimination deficit is a common nonmotor manifestation of Parkinson's disease (PD). However, the pathophysiology of this dysfunction remains poorly understood. Although retinal structure changes found in PD have been suggested to cause color discrimination deficits, the impact of cognitive impairment and cortical alterations remains to be determined. We investigated the contribution of cognitive impairment to color discrimination deficits in PD and correlated them with cortical anomalies. Sixty-six PD patients without dementia and 20 healthy controls performed the Farnsworth-Munsell 100 hue test and underwent a comprehensive neuropsychological assessment for mild cognitive impairment diagnosis. In a subgroup of 26 PD patients, we also used high-definition neuroanatomical magnetic resonance imaging for cortical thickness and diffusion tensor analysis. PD patients with mild cognitive impairment performed poorly on the Farnsworth-Munsell 100 hue test compared with PD patients without mild cognitive impairment and controls. In PD patients, performance on the Farnsworth-Munsell 100 hue test was correlated with measures of visuospatial abilities and executive functions. Neuroimaging analysis revealed higher mean and radial diffusivity values in right posterior white-matter structures that correlated with poor performance on the Farnsworth-Munsell 100 hue test. No cortical thickness correlation reached significance. This study showed that cognitive impairment makes a major contribution to the color discrimination deficits reported in PD. Thus, performance on the Farnsworth-Munsell 100 hue test may reflect cognitive impairment more than color discrimination deficits in PD. Poor performance on the Farnsworth-Munsell 100 hue test was also associated with white-matter alterations in right posterior brain regions.

Fronto-striatal contribution to lexical set-shifting.

Fronto-striatal circuits in set-shifting have been examined in neuroimaging studies using the Wisconsin Card Sorting Task (WCST) that requires changing the classification rule for cards containing visual stimuli that differ in color, shape, and number. The present study examined whether this fronto-striatal contribution to the planning and execution of set-shifts is similar in a modified sorting task in which lexical rules are applied to word stimuli. Young healthy adults were scanned with functional magnetic resonance imaging while performing the newly developed lexical version of the WCST: the Wisconsin Word Sorting Task. Significant activation was found in a cortico-striatal loop that includes area 47/12 of the ventrolateral prefrontal cortex (PFC), and the caudate nucleus during the planning of a set-shift, and in another that includes the posterior PFC and the putamen during the execution of a set-shift. However, in the present lexical task, additional activation peaks were observed in area 45 of the ventrolateral PFC area during both matching periods. These results provide evidence that the functional contributions of the various fronto-striatal loops are not dependent on the modality of the information to be manipulated but rather on the specific executive processes required.

Patterns of cortical thickness and surface area in early Parkinson's disease.

Idiopathic Parkinson's disease (PD) is a neurodegenerative disorder diagnosed on the basis of motor symptoms, but that also includes cognitive and visuo-spatial deficits. Though PD is known to initially affect subcortical regions, the cortex also exhibits neuronal loss in the course of the disease as post mortem studies have shown. So far, PD-related pattern of cortical damage remains unclear, because of disease-caused heterogeneity, and also in part because of methodological issues such as the limitations of Voxel Based Morphometry. Here corticometry was used, a technique that decouples local surface from thickness, to obtain a better picture of PD corticomorphometric patterns. We acquired MRI volumes for 33 healthy controls (HC) and 49 PD patients, extracted local cortical thickness and surface area and modeled both of them as a function of group and age for each participant. Cortical thickness averaged on the whole cortex did not differ between the two groups while mean surface area was significantly larger in the PD group. The bilateral parietal lobule, the right superior frontal gyrus, the left cingulate cortex and the left insular cortex exhibited larger local surface area in the PD group. The right precuneus exhibited cortical thinning associated with age in the PD group and not in the HC group. Furthermore, cortical thinning was observed in the PD group compared with the control group in the left medial supplementary motor area (SMA) and in the right dorsal pre-SMA. Finally, we found the left temporal pole thickness to correlate with disease duration, as well as the bilateral occipital cortex and Broca's area. These results suggest that PD etiology is associated with specific cortical alterations, which could account for cognitive deficits that arise as the disease evolves. Finally, our results observed in the occipital cortex as a function of disease duration may indicate the increase in PD-related visuo-spatial deficits, which can sometimes result in hallucinations later on in the disease. In the future, MRI-generated corticometry, combined with additional behavioral markers, may prove to be a useful diagnosis tool to characterize the evolution of motor and cognitive deficits in PD.

Broca's area and the hierarchical organization of human behavior.

The prefrontal cortex subserves executive control, i.e., the organization of action or thought in relation to internal goals. This brain region hosts a system of executive processes extending from premotor to the most anterior prefrontal regions that governs the temporal organization of behavior. Little is known, however, about the prefrontal executive system involved in the hierarchical organization of behavior. Here, we show using magnetic resonance imaging in humans that the posterior portion of the prefrontal cortex, including Broca's area and its homolog in the right hemisphere, contains a system of executive processes that control start and end states and the nesting of functional segments that combine in hierarchically organized action plans. Our results indicate that Broca's area and its right homolog process hierarchically structured behaviors regardless of their temporal organization, suggesting a fundamental segregation between prefrontal executive systems involved in the hierarchical and temporal organization of goal-directed behaviors.

Serial organization of human behavior in the inferior parietal cortex.

The parietal cortex is involved in a wide range of cognitive functions in humans including associative functions between multiple sensorimotor spaces, attentional control, and working memory. Little is known, however, about the role and the functional organization of the parietal cortex in action planning and sequential cognition. Moreover, the respective contributions of parietal and frontal regions to action planning remains poorly understood. To address this issue, we designed a functional magnetic resonance imaging protocol requiring subjects to perform overlearned sequences of motor acts and sequences of cognitive tasks. The results reveal only a single bilateral region in the cerebral cortex located in the intraparietal sulcus (IPS; Brodmann's area 40) exhibiting sustained activations during the execution of both motor and task sequences. Additional analyses of phasic activations during sequence execution further suggest a functional dissociation between the left IPS, involved in representing and processing the abstract serial structure of ongoing behavioral sequences regardless of their hierarchical structure, and the right IPS, involved in preparing successive sensorimotor sets that compose such behavioral sequences. We show that this parietal system functionally differs from the frontal system that was previously identified as controlling action selection with respect to the hierarchical rather than serial structure of behavioral plans. Thus, our results reveal the central role of the bilateral intraparietal sulcus in high-order sequential cognition and suggest a major functional segregation within the frontoparietal network mediating action planning, with the frontal and parietal sector involved in processing the hierarchical and serial structure of action plans, respectively.

Striatal and hippocampal involvement in motor sequence chunking depends on the learning strategy.

Motor sequences can be learned using an incremental approach by starting with a few elements and then adding more as training evolves (e.g., learning a piano piece); conversely, one can use a global approach and practice the whole sequence in every training session (e.g., shifting gears in an automobile). Yet, the neural correlates associated with such learning strategies in motor sequence learning remain largely unexplored to date. Here we used functional magnetic resonance imaging to measure the cerebral activity of individuals executing the same 8-element sequence after they completed a 4-days training regimen (2 sessions each day) following either a global or incremental strategy. A network comprised of striatal and fronto-parietal regions was engaged significantly regardless of the learning strategy, whereas the global training regimen led to additional cerebellar and temporal lobe recruitment. Analysis of chunking/grouping of sequence elements revealed a common prefrontal network in both conditions during the chunk initiation phase, whereas execution of chunk cores led to higher mediotemporal activity (involving the hippocampus) after global than incremental training. The novelty of our results relate to the recruitment of mediotemporal regions conditional of the learning strategy. Thus, the present findings may have clinical implications suggesting that the ability of patients with lesions to the medial temporal lobe to learn and consolidate new motor sequences may benefit from using an incremental strategy.

Effect of mild cognitive impairment on the patterns of neural activity in early Parkinson's disease.

We have previously observed decreased activation of corticostriatal loops involved in planning (cognitive loop) and execution (motor loop) of a set shift in patients with early Parkinson's disease (PD) compared with control subjects. Here, we aimed to assess whether cognitive impairment in PD could drive these differences. Nondemented patients underwent a comprehensive neuropsychological evaluation and participated in our Wisconsin Card Sorting task functional magnetic resonance imaging protocol. Patients were separated into 2 groups according to the presence of mild cognitive impairment (MCI). Patients with MCI displayed reduced activity in the cognitive corticostriatal loop, which includes the caudate nucleus and prefrontal cortex while planning a set shift, whereas non-MCI patients exhibited activation patterns similar to those of healthy participants from our previous studies. Furthermore, reduced activation was observed in the premotor cortex of the MCI patients. Finally, hippocampal activity, correlated with individual memory scores, suggesting a compensatory mechanism in patients with preserved memory. These results suggest that the presence of MCI in PD affects activity in the prefrontal cortex and caudate nucleus as well as motor-related regions.

Coping with task demand in aging using neural compensation and neural reserve triggers primarily intra-hemispheric-based neurofunctional reorganization.

It has been proposed that cognitive reserve is supported by two neural mechanisms: neural compensation and neural reserve. The purpose of this study was to test how these neural mechanisms are solicited in aging in the context of visual selective attention processing and whether they are inter- or intra-hemispheric. Younger and older participants were scanned using fMRI during a visual letter-matching task with two attentional load levels. The results show that in the low-load condition, the older participants activated frontal superior gyri bilaterally; these regions were not activated in the younger participants, in accordance with the compensation mechanism and the Posterior-Anterior Shift in Aging (PASA) phenomenon. However, when task demand increased, the older participants recruited the same regions (parietal) as the younger ones, showing the involvement of a similar neural reserve mechanism. This result suggests that successful cognitive aging relies on the concurrent use of both neural compensation and neural reserve in high-demand tasks, calling on the frontoparietal network. In addition, the finding of intra-hemispheric-based neurofunctional reorganization with a PASA phenomenon for all attentional load levels suggests that the PASA phenomenon is a function more of compensation than of reserve.

The influence of pain on cerebral functioning after mild traumatic brain injury.

More than 75% of patients with mild traumatic brain injury (MTBI) report chronic pain whose potential detrimental effects on cognitive recovery need to be identified. The objective of this study was to investigate the relationship between pain, performance on a working memory task, gray matter density, and mid-dorsolateral prefrontal cortex (mid-DLPFC) activation in subjects with a MTBI. For comparison purposes, we performed identical correlation analyses with a group of subjects without MTBI who sustained sports injuries. Twenty-four subjects who experienced a MTBI in the past 12 months, 16 control subjects, and 29 subjects with sport injuries were included. One hour prior to entering the magnetic resonance scanner, the subjects were asked to fill out the pain Visual Analogue Scale. Subsequently, a high-resolution T1-weighted image was acquired followed by a functional magnetic resonance imaging session using the visual externally ordered working memory task. Results showed that MTBI subjects reporting severe pain in the hour preceding the testing had reduced mid-DLPFC activation during the working memory task and poorer performance on the task. Subjects with sport injuries and severe levels of pain showed the reverse pattern: pain was associated with higher activation in the mid-DLPFC and did not correlate with performance. Gray matter density measures were independent of pain level. This study showed that behavioral performance and cerebral functioning are affected by pain after a MTBI. Moreover, this study suggests that pain, cognition, and cerebral functioning interactions could not easily be generalized from one clinical population to another.

L-dopa medication in Parkinson's disease restores activity in the motor cortico-striatal loop but does not modify the cognitive network.

BACKGROUND: The goal of this study was to evaluate the effects of L-Dopa medication in Parkinson's disease (PD) on brain activation during the performance of a set-shifting task. Using fMRI, we have previously studied the patterns of activity observed in patients with PD after overnight removal of dopaminergic medication compared with control participants during the performance of different stages of the Wisconsin Card Sorting Task (WCST). The results revealed decreased cortical activity in the PD group compared to controls in the conditions that significantly required striatum, while increased cortical activity was observed when striatum was not involved. However, the effect of dopaminergic medication in PD patients on those patterns of activity has not yet been studied. METHODOLOGY/PRINCIPAL FINDINGS: Here, eleven PD patients at early stage of the disease taking L-Dopa medication were recruited and underwent two fMRI sessions while performing the WCST: one session while taking their normal dose of medication and the other following overnight dopaminergic medication withdrawal. We found that L-dopa medication helped restoring a normal pattern of activity when matching and not planning was required, by increasing cortical activity in the premotor cortex. This effect was even stronger in the motor loop, i.e. when the putamen was required for controls, when matching following negative feedback. However, the medication did not change the pattern of activity in conditions relying primarily on a cognitive loop, i.e. when the caudate nucleus was required. CONCLUSIONS/SIGNIFICANCE: These studies provide explanation at the neural level regarding the relatively poor effects of L-Dopa on the cognitive deficits observed in PD.

Regional brain stem atrophy in idiopathic Parkinson's disease detected by anatomical MRI.

Idiopathic Parkinson's disease (PD) is a neurodegenerative disorder characterized by the dysfunction of dopaminergic dependent cortico-basal ganglia loops and diagnosed on the basis of motor symptoms (tremors and/or rigidity and bradykinesia). Post-mortem studies tend to show that the destruction of dopaminergic neurons in the substantia nigra constitutes an intermediate step in a broader neurodegenerative process rather than a unique feature of Parkinson's disease, as a consistent pattern of progression would exist, originating from the medulla oblongata/pontine tegmentum. To date, neuroimaging techniques have been unable to characterize the pre-symptomatic stages of PD. However, if such a regular neurodegenerative pattern were to exist, consistent damages would be found in the brain stem, even at early stages of the disease. We recruited 23 PD patients at Hoenn and Yahr stages I to II of the disease and 18 healthy controls (HC) matched for age. T1-weighted anatomical scans were acquired (MPRAGE, 1 mm3 resolution) and analyzed using an optimized VBM protocol to detect white and grey matter volume reduction without spatial a priori. When the HC group was compared to the PD group, a single cluster exhibited statistical difference (p<0.05 corrected for false detection rate, 4287 mm3) in the brain stem, between the pons and the medulla oblongata. The present study provides in-vivo evidence that brain stem damage may be the first identifiable stage of PD neuropathology, and that the identification of this consistent damage along with other factors could help with earlier diagnosis in the future. This damage could also explain some non-motor symptoms in PD that often precede diagnosis, such as autonomic dysfunction and sleep disorders.