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Alain Dagher

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YNIMG Journal 2023 Journal Article

Development and validation of an fMRI-informed EEG model of reward-related ventral striatum activation

  • Neomi Singer
  • Gilad Poker
  • Netta Dunsky-Moran
  • Shlomi Nemni
  • Shira Reznik Balter
  • Maayan Doron
  • Travis Baker
  • Alain Dagher

Reward processing is essential for our mental-health and well-being. In the current study, we developed and validated a scalable, fMRI-informed EEG model for monitoring reward processing related to activation in the ventral-striatum (VS), a significant node in the brain's reward system. To develop this EEG-based model of VS-related activation, we collected simultaneous EEG/fMRI data from 17 healthy individuals while listening to individually-tailored pleasurable music - a highly rewarding stimulus known to engage the VS. Using these cross-modal data, we constructed a generic regression model for predicting the concurrently acquired Blood-Oxygen-Level-Dependent (BOLD) signal from the VS using spectro-temporal features from the EEG signal (termed hereby VS-related-Electrical Finger Print; VS-EFP). The performance of the extracted model was examined using a series of tests that were applied on the original dataset and, importantly, an external validation dataset collected from a different group of 14 healthy individuals who underwent the same EEG/FMRI procedure. Our results showed that the VS-EFP model, as measured by simultaneous EEG, predicted BOLD activation in the VS and additional functionally relevant regions to a greater extent than an EFP model derived from a different anatomical region. The developed VS-EFP was also modulated by musical pleasure and predictive of the VS-BOLD during a monetary reward task, further indicating its functional relevance. These findings provide compelling evidence for the feasibility of using EEG alone to model neural activation related to the VS, paving the way for future use of this scalable neural probing approach in neural monitoring and self-guided neuromodulation.

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YNICL Journal 2023 Journal Article

Network connectivity and local transcriptomic vulnerability underpin cortical atrophy progression in Parkinson’s disease

  • Andrew Vo
  • Christina Tremblay
  • Shady Rahayel
  • Golia Shafiei
  • Justine Y. Hansen
  • Yvonne Yau
  • Bratislav Misic
  • Alain Dagher

Parkinson's disease pathology is hypothesized to spread through the brain via axonal connections between regions and is further modulated by local vulnerabilities within those regions. The resulting changes to brain morphology have previously been demonstrated in both prodromal and de novo Parkinson's disease patients. However, it remains unclear whether the pattern of atrophy progression in Parkinson's disease over time is similarly explained by network-based spreading and local vulnerability. We address this gap by mapping the trajectory of cortical atrophy rates in a large, multi-centre cohort of Parkinson's disease patients and relate this atrophy progression pattern to network architecture and gene expression profiles. Across 4-year follow-up visits, increased atrophy rates were observed in posterior, temporal, and superior frontal cortices. We demonstrated that this progression pattern was shaped by network connectivity. Regional atrophy rates were strongly related to atrophy rates across structurally and functionally connected regions. We also found that atrophy progression was associated with specific gene expression profiles. The genes whose spatial distribution in the brain was most related to atrophy rate were those enriched for mitochondrial and metabolic function. Taken together, our findings demonstrate that both global and local brain features influence vulnerability to neurodegeneration in Parkinson's disease.

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YNICL Journal 2022 Journal Article

Advancing brain network models to reconcile functional neuroimaging and clinical research

  • Xenia Kobeleva
  • Gaël Varoquaux
  • Alain Dagher
  • Mohit H. Adhikari
  • Christian Grefkes
  • Matthieu Gilson

Functional magnetic resonance imaging (fMRI) captures information on brain function beyond the anatomical alterations that are traditionally visually examined by neuroradiologists. However, the fMRI signals are complex in addition to being noisy, so fMRI still faces limitations for clinical applications. Here we review methods that have been proposed as potential solutions so far, namely statistical, biophysical and decoding models, with their strengths and weaknesses. We especially evaluate the ability of these models to directly predict clinical variables from their parameters (predictability) and to extract clinically relevant information regarding biological mechanisms and relevant features for classification and prediction (interpretability). We then provide guidelines for useful applications and pitfalls of such fMRI-based models in a clinical research context, looking beyond the current state of the art. In particular, we argue that the clinical relevance of fMRI calls for a new generation of models for fMRI data, which combine the strengths of both biophysical and decoding models. This leads to reliable and biologically meaningful model parameters, which thus fulfills the need for simultaneous interpretability and predictability. In our view, this synergy is fundamental for the discovery of new pharmacological and interventional targets, as well as the use of models as biomarkers in neurology and psychiatry.

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YNIMG Journal 2022 Journal Article

Correspondence between gene expression and neurotransmitter receptor and transporter density in the human brain

  • Justine Y. Hansen
  • Ross D. Markello
  • Lauri Tuominen
  • Martin Nørgaard
  • Elena Kuzmin
  • Nicola Palomero-Gallagher
  • Alain Dagher
  • Bratislav Misic

Neurotransmitter receptors modulate signaling between neurons. Thus, neurotransmitter receptors and transporters play a key role in shaping brain function. Due to the lack of comprehensive neurotransmitter receptor/transporter density datasets, microarray gene expression measuring mRNA transcripts is often used as a proxy for receptor densities. In the present report, we comprehensively test the spatial correlation between gene expression and protein density for a total of 27 neurotransmitter receptors, receptor binding-sites, and transporters across 9 different neurotransmitter systems, using both PET and autoradiography radioligand-based imaging modalities. We find poor spatial correspondences between gene expression and density for all neurotransmitter receptors and transporters except four single-protein metabotropic receptors (5-HT 1 A, CB 1, D 2, and MOR). These expression-density associations are related to gene differential stability and can vary between cortical and subcortical structures. Altogether, we recommend using direct measures of receptor and transporter density when relating neurotransmitter systems to brain structure and function.

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YNIMG Journal 2022 Journal Article

Impact of weight loss on brain age: Improved brain health following bariatric surgery

  • Yashar Zeighami
  • Mahsa Dadar
  • Justine Daoust
  • Mélissa Pelletier
  • Laurent Biertho
  • Léonie Bouvet-Bouchard
  • Stephanie Fulton
  • André Tchernof

Individuals living with obesity tend to have increased brain age, reflecting poorer brain health likely due to grey and white matter atrophy related to obesity. However, it is unclear if older brain age associated with obesity can be reversed following weight loss and cardiometabolic health improvement. The aim of this study was to assess the impact of weight loss and cardiometabolic improvement following bariatric surgery on brain health, as measured by change in brain age estimated based on voxel-based morphometry (VBM) measurements. We used three distinct datasets to perform this study: 1) CamCAN dataset to train the brain age prediction model, 2) Human Connectome Project (HCP) dataset to investigate whether individuals with obesity have greater brain age than individuals with normal weight, and 3) pre-surgery, as well as 4, 12, and 24 month post-surgery data from participants (n = 87, age: 44. 0 ± 9. 2 years, BMI: 43. 9 ± 4. 2 kg/m2) who underwent a bariatric surgery to investigate whether weight loss and cardiometabolic improvement as a result of bariatric surgery lowers the brain age. As expected, our results from the HCP dataset showed a higher brain age for individuals with obesity compared to individuals with normal weight (T-value = 7. 08, p-value < 0. 0001). We also found significant improvement in brain health, indicated by a decrease of 2. 9 and 5. 6 years in adjusted delta age at 12 and 24 months following bariatric surgery compared to baseline (p-value < 0. 0005 for both). While the overall effect seemed to be driven by a global change across all brain regions and not from a specific region, our exploratory analysis showed lower delta age in certain brain regions (mainly in somatomotor, visual, and ventral attention networks) at 24 months. This reduced age was also associated with post-surgery improvements in BMI, systolic/diastolic blood pressure, and HOMA-IR (T-valueBMI=4. 29, T-valueSBP=4. 67, T-valueDBP=4. 12, T-valueHOMA-IR=3. 16, all p-values < 0. 05). In conclusion, these results suggest that obesity-related brain health abnormalities (as measured by delta age) might be reversed by bariatric surgery-induced weight loss and widespread improvements in cardiometabolic alterations.

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YNIMG Journal 2021 Journal Article

Spontaneous neural activity changes after bariatric surgery: A resting-state fMRI study

  • Yashar Zeighami
  • Sylvain Iceta
  • Mahsa Dadar
  • Mélissa Pelletier
  • Mélanie Nadeau
  • Laurent Biertho
  • Annie Lafortune
  • André Tchernof

BACKGROUND: Metabolic disorders associated with obesity could lead to alterations in brain structure and function. Whether these changes can be reversed after weight loss is unclear. Bariatric surgery provides a unique opportunity to address these questions because it induces marked weight loss and metabolic improvements which in turn may impact the brain in a longitudinal fashion. Previous studies found widespread changes in grey matter (GM) and white matter (WM) after bariatric surgery. However, findings regarding changes in spontaneous neural activity following surgery, as assessed with the fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity of neural activity (ReHo), are scarce and heterogenous. In this study, we used a longitudinal design to examine the changes in spontaneous neural activity after bariatric surgery (comparing pre- to post-surgery), and to determine whether these changes are related to cardiometabolic variables. METHODS: ) who underwent sleeve gastrectomy (SG), biliopancreatic diversion with duodenal switch (BPD), or Roux-en-Y gastric bypass (RYGB), scanned prior to bariatric surgery and at follow-up visits of 4 months (N = 36), 12 months (N = 29), and 24 months (N = 14) after surgery. We examined fALFF and ReHo measures across 1022 cortical and subcortical regions (based on combined Schaeffer-Xiao parcellations) using a linear mixed effect model. Voxel-based morphometry (VBM) based on T1-weighted images was also used to measure GM density in the same regions. We also used an independent sample from the Human Connectome Project (HCP) to assess regional differences between individuals who had normal-weight (N = 46) or severe obesity (N = 46). RESULTS: We found a global increase in the fALFF signal with greater increase within dorsolateral prefrontal cortex, precuneus, inferior temporal gyrus, and visual cortex. This effect was more significant 4 months after surgery. The increase within dorsolateral prefrontal cortex, temporal gyrus, and visual cortex was more limited after 12 months and only present in the visual cortex after 24 months. These increases in neural activity measured by fALFF were also significantly associated with the increase in GM density following surgery. Furthermore, the increase in neural activity was significantly related to post-surgery weight loss and improvement in cardiometabolic variables, such as blood pressure. In the independent HCP sample, normal-weight participants had higher global and regional fALFF signals, mainly in dorsolateral/medial frontal cortex, precuneus and middle/inferior temporal gyrus compared to the obese participants. These BMI-related differences in fALFF were associated with the increase in fALFF 4 months post-surgery especially in regions involved in control, default mode and dorsal attention networks. CONCLUSIONS: Bariatric surgery-induced weight loss and improvement in metabolic factors are associated with widespread global and regional increases in neural activity, as measured by fALFF signal. These findings alongside the higher fALFF signal in normal-weight participants compared to participants with severe obesity in an independent dataset suggest an early recovery in the neural activity signal level after the surgery.

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YNIMG Journal 2020 Journal Article

Neuroanatomical changes in white and grey matter after sleeve gastrectomy

  • Andréanne Michaud
  • Mahsa Dadar
  • Mélissa Pelletier
  • Yashar Zeighami
  • Isabel Garcia-Garcia
  • Sylvain Iceta
  • Yvonne Yau
  • Mélanie Nadeau

Background MRI studies show that obese adults have reduced grey matter (GM) and white matter (WM) tissue density as well as altered WM integrity. Bariatric surgery can lead to substantial weight loss and improvements in metabolic parameters, but it remains to be examined if it induces structural brain changes. The aim of this study was to characterize GM and WM density changes measured with MRI in a longitudinal setting following sleeve gastrectomy, and to determine whether any changes are related to inflammation and cardiometabolic blood markers. Methods 29 participants with obesity (age: 45. 9 ​± ​7. 8 years) scheduled to undergo sleeve gastrectomy were recruited. High-resolution T1-weighted anatomical images were acquired 1 month prior to as well as 4 and 12 months after surgery. GM and WM densities were quantified using voxel-based morphometry (VBM). Circulating lipid profile, glucose, insulin and inflammatory markers (interleukin-6, C-reactive protein and lipopolysaccharide-binding protein) were measured at each time point. A linear mixed effect model was used to compare brain changes before and after SG, controlling for age, sex, initial BMI and diabetic status. To assess the associations between changes in adiposity, metabolism and inflammation and changes in GM or WM density, the mean GM and WM densities were extracted across all the participants using atlas-derived regions of interest, and linear mixed-effect models were used. Results As expected, weight, BMI, waist circumference and neck circumference significantly decreased after SG compared with baseline (p ​< ​0. 001 for all). A widespread increase in WM density was observed after surgery, particularly in the cerebellum, brain stem, cerebellar peduncle, cingulum, corpus callosum and corona radiata (p ​< ​0. 05, after FDR correction). Significant increases in GM density were observed 4 months after SG compared to baseline in several brain regions such as the bilateral occipital cortex, temporal cortex, postcentral gyrus, cerebellum, hippocampus and insula as well as right fusiform gyrus, right parahippocampal gyrus, right lingual gyrus and right amygdala. These GM and WM increases were more pronounced and widespread after 12 months and were significantly associated with post-operative weight loss and the improvement of metabolic alterations. A linear mixed-effect model also showed associations between post-operative reductions in lipopolysaccharide-binding protein, a marker of inflammation, and increased WM density. To confirm our results, we tested whether the peak of each significant region showed BMI-related differences in an independent dataset (Human Connectome Project). We matched a group of individuals who were severely obese with a group of individuals who were lean for age, sex and ethnicity. Severe obesity was associated with reduced WM density in the brain stem and cerebellar peduncle as well as reduced GM density in cerebellum, regions that significantly changed after surgery (p ​< ​0. 01 for all clusters). Conclusions Bariatric surgery-induced weight loss and improvement in metabolic alterations is associated with widespread increases in WM and GM densities. These post-operative changes overlapped with baseline brain differences between participants who were severely obese and those who were normal-weight in a separate dataset, which may suggest a recovery of WM and GM alterations after bariatric surgery.

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YNICL Journal 2020 Journal Article

Predicting severity and prognosis in Parkinson's disease from brain microstructure and connectivity

  • Nooshin Abbasi
  • Seyed-Mohammad Fereshtehnejad
  • Yashar Zeighami
  • Kevin Michel-Herve Larcher
  • Ronald B. Postuma
  • Alain Dagher

OBJECTIVES: Investigating biomarkers to demonstrate progression of Parkinson's disease (PD) is of high priority. We investigated the association of brain structural properties with progression of clinical outcomes and their ability to differentiate clinical subtypes of PD. METHODS: A comprehensive set of clinical features was evaluated at baseline and 4.5-year follow-up for 144 de-novo PD patients from the Parkinson's Progression Markers Initiative. We created a global composite outcome (GCO) by combining z-scores of non-motor and motor symptoms, motor signs, overall activities of daily living and global cognition, as a single numeric indicator of prognosis. We classified patients into three subtypes based on multi-domain clinical criteria: 'mild motor-predominant', 'intermediate' and 'diffuse-malignant'. We analyzed diffusion-weighted scans at the early drug-naïve stage and extracted fractional anisotropy and mean diffusivity (MD) of basal ganglia and cortical sub-regions. Then, we employed graph theory to calculate network properties and used network-based statistic to investigate our primary hypothesis. RESULTS: Baseline MD of globus pallidus was associated with worsening of motor severity, cognition, and GCO after 4.5 years of follow-up. Connectivity disruption at baseline was correlated with decline in cognition, and increase in GCO. Baseline MD of nucleus accumbens, globus pallidus and basal-ganglia were linked to clinical subtypes at 4.5-year of follow-up. Disruption in sub-cortical networks associated with being subtyped as 'diffuse-malignant' versus 'mild motor-predominant' after 4.5 years. CONCLUSIONS: Diffusion imaging analysis at the early de-novo stage of PD was able to differentiate clinical sub-types of PD after 4.5 years and was highly associated with future clinical outcomes of PD.

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YNIMG Journal 2019 Journal Article

A clinical-anatomical signature of Parkinson's disease identified with partial least squares and magnetic resonance imaging

  • Yashar Zeighami
  • Seyed-Mohammad Fereshtehnejad
  • Mahsa Dadar
  • D. Louis Collins
  • Ronald B. Postuma
  • Bratislav Mišić
  • Alain Dagher

Parkinson's disease (PD) is a neurodegenerative disorder characterized by a wide array of motor and non-motor symptoms. It remains unclear whether neurodegeneration in discrete loci gives rise to discrete symptoms, or whether network-wide atrophy gives rise to the unique behavioural and clinical profile associated with PD. Here we apply a data-driven strategy to isolate large-scale, multivariate associations between distributed atrophy patterns and clinical phenotypes in PD. In a sample of N = 229 de novo PD patients, we estimate disease-related atrophy using deformation based morphometry (DBM) of T1 weighted MR images. Using partial least squares (PLS), we identify a network of subcortical and cortical regions whose collective atrophy is associated with a clinical phenotype encompassing motor and non-motor features. Despite the relatively early stage of the disease in the sample, the atrophy pattern encompassed lower brainstem, substantia nigra, basal ganglia and cortical areas, consistent with the Braak hypothesis. In addition, individual variation in this putative atrophy network predicted longitudinal clinical progression in both motor and non-motor symptoms. Altogether, these results demonstrate a pleiotropic mapping between neurodegeneration and the clinical manifestations of PD, and that this mapping can be detected even in de novo patients.

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YNICL Journal 2019 Journal Article

Assessment of a prognostic MRI biomarker in early de novo Parkinson's disease

  • Yashar Zeighami
  • Seyed-Mohammad Fereshtehnejad
  • Mahsa Dadar
  • D. Louis Collins
  • Ronald B. Postuma
  • Alain Dagher

BACKGROUND: Commonly used neuroimaging biomarkers in Parkinson's disease (PD) are useful for diagnosis but poor at predicting outcomes. We explored whether an atrophy pattern from whole-brain structural MRI, measured in the drug-naïve early stage, could predict PD prognosis. METHODS: I ioflupane single photon emission computed tomography, the postural-instability-gait-disturbance score, and cerebrospinal fluid markers. FINDINGS: After 4.5 years follow-up, PD-specific atrophy network score at baseline significantly predicted change in UPDRS-part III (r = -0.197, p = .003), MoCA (r = 0.253, p = .0002) and global composite outcome (r = -0.249, p = .0002). Compared with the 3rd tertile (i.e. least atrophy), the tertile with the highest baseline atrophy (i.e. the 1st tertile) had a 3-point annual faster progression in UPDRS-part III (p = .012), faster worsening of posture-instability gait scores (+0.21 further annual increase, p < .0001), faster decline in MoCA (-0.74 further annual decline in MoCA, p = .0372) and a + 0.38 (p = .0029) faster annual increase in the global composite z-score. All findings were replicated in a validation analysis using 1.5T MRI. Receiver operating characteristic analysis confirmed the superiority of the MRI biomarker, although it had modest AUC values (0.63). By comparison, the other biomarkers were limited in their ability to predict prognosis either in the main or validation analysis. INTERPRETATION: A PD-specific network atrophy pattern predicts progression of motor, cognitive, and global outcome in PD, and is a better predictor of prognosis than any of the other tested biomarkers. Therefore, it has potential as a prognostic biomarker for clinical trials of early PD.

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RLDM Conference 2019 Conference Abstract

Reward system connectivity during self-regulation with non-drug reward im- agery in cocaine users

  • Matthias Kirschner
  • Amelie Haugg
  • Philipp Stämpflie
  • Etna Engeli
  • Lea Hulka
  • James Sulzer
  • Erich Seifritz
  • Alain Dagher

Introduction: Humans can voluntary up-regulate brain activity with reward imagery and improve this ability with real-time fMRI (rt-fMRI) Neurofeedback (NFB). Using internal non-drug-related reward imagery cocaine users (CU) were able to activate the ventral tegmental area (VTA) and other regions includ- ing the ventral and dorsal striatum (VS, DS), Hippocampus (Hipp), and medial prefrontal cortex (mPFC). However, it is unknown how interactions among these regions modulate self-regulation and whether connec- tivity is disrupted in CU. Here, we used DCM to investigate whether VTA self-regulation is achieved via the mPFC, VS or VTA, directly and tested whether cocaine craving influences effective connectivity. Methods: Dynamic causal modeling (DCM) was applied on our previous published pre- and post rt-fMRI NFB data from 28 HC and 22 CU. DCM Bayesian Model Selection (BMS) and Averaging (BMA) using a model space of (3 families×1024 models) were performed. In CU, correlation analyses were performed on the posterior DCM parameters to investigate the effects of acute and chronic craving on connectivity. Results: BMS revealed that the mPFC was the exclusive entry point for successful self-regulation with non-drug reward imagery, while reward imagery caused VTA and striatal activation only indirectly via mPFC. In CU, Hipp to mPFC connectivity was reduced before rt-fMRI NFB and restored after rt-fMRI NFB. Severity of chronic craving was associated with reduced intrinsic VTA connectivity, while severity of acute craving was associ- ated with reduced task-dependent DS connectivity. Conclusion: This study showed that the mPFC integrates and transmits representations of non-drug reward imagery to the mesolimbic reward system, thereby initiat- ing successful self-regulation. Disrupted DS connectivity and VTA connectivity was differentially related to acute and chronic craving suggesting separate neural mechanisms contributing to impaired non-drug reward processing in CU.

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YNICL Journal 2018 Journal Article

White matter hyperintensities are linked to future cognitive decline in de novo Parkinson's disease patients

  • Mahsa Dadar
  • Yashar Zeighami
  • Yvonne Yau
  • Seyed-Mohammad Fereshtehnejad
  • Josefina Maranzano
  • Ronald B. Postuma
  • Alain Dagher
  • D. Louis Collins

White Matter Hyperintensities (WMHs) are associated with cognitive decline in aging and Alzheimer's disease. However, the pathogenesis of cognitive decline in Parkinson's disease (PD) is not as clearly related to vascular causes, and therefore the role of WMHs as a marker of small-vessel disease (SVD) in PD is less clear. Currently, SVD in PD is assessed and treated independently of the disease. However, if WMH as the major MRI sign of SVD has a higher impact on cognitive decline in PD patients than in healthy controls, vascular pathology needs to be assessed and treated with a higher priority in this population. Here we investigate whether the presence of WMHs leads to increased cognitive decline in de novo PD, and if these effects relate to cortical atrophy. WMHs and cortical thickness were measured in de novo PD patients and age-matched controls (NPD = 365, NControl = 174) from Parkinson's Progression Markers Initiative (PPMI) to study the relationship between baseline WMHs, future cognitive decline (follow-up: 4. 09 ± 1. 14 years) and cortical atrophy (follow-up: 1. 05 ± 0. 10 years). PD subjects with high baseline WMH loads had significantly greater cognitive decline than i) PD subjects with low WMH load, and ii) control subjects with high WMH load. Furthermore, in PD subjects, high WMH load resulted in more cortical thinning in the right frontal lobe. Theses results show that the presence of WMHs in de novo PD patients predicts greater future cognitive decline and cortical atrophy than in normal aging.

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YNICL Journal 2016 Journal Article

Compensatory striatal–cerebellar connectivity in mild–moderate Parkinson's disease

  • Alison C. Simioni
  • Alain Dagher
  • Lesley K. Fellows

Dopamine depletion in the putamen is associated with altered motor network functional connectivity in people with Parkinson's disease (PD), but the functional significance of these changes remains unclear, attributed to either pathological or compensatory mechanisms in different studies. Here, we examined the effects of PD on dorsal caudal putamen functional connectivity, off and on dopamine replacement therapy (DRT), using resting state fMRI. Motor performance was assessed with the Purdue pegboard task. Twenty-one patients with mild-moderate Parkinson's disease were studied twice, once after an overnight DRT washout and once after the administration of a standard dose of levodopa (Sinemet), and compared to 20 demographically-matched healthy control participants. PD patients off DRT showed increased putamen functional connectivity with both the cerebellum (lobule V) and primary motor cortex (M1), relative to healthy controls. Greater putamen-cerebellar functional connectivity was significantly correlated with better motor performance, whereas greater putamen-M1 functional connectivity was predictive of poorer motor performance. The administration of levodopa improved motor performance in the PD group, as expected, and reduced putamen-cerebellar connectivity to levels comparable to the healthy control group. The strength of putamen-cerebellar functional connectivity continued to predict motor performance in the PD group while on levodopa. These findings argue that increased putamen-M1 functional connectivity reflects a pathological change, deleterious to motor performance. In contrast, increased putamen-cerebellar connectivity reflects a compensatory mechanism.

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YNIMG Journal 2015 Journal Article

Striatal D1 and D2 signaling differentially predict learning from positive and negative outcomes

  • Sylvia M.L. Cox
  • Michael J. Frank
  • Kevin Larcher
  • Lesley K. Fellows
  • Crystal A. Clark
  • Marco Leyton
  • Alain Dagher

The extent to which we learn from positive and negative outcomes of decisions is modulated by the neurotransmitter dopamine. Dopamine neurons burst fire in response to unexpected rewards and pause following negative outcomes. This dual signaling mechanism is hypothesized to drive both approach and avoidance behavior. Here we test a prediction deriving from a computational reinforcement learning model, in which approach is mediated via activation of the direct cortico-striatal pathway due to striatal D1 receptor stimulation, while avoidance occurs via disinhibition of indirect pathway striatal neurons secondary to a reduction of D2 receptor stimulation. Using positron emission tomography with two separate radioligands, we demonstrate that individual differences in human approach and avoidance learning are predicted by variability in striatal D1 and D2 receptor binding, respectively. Moreover, transient dopamine precursor depletion improved learning from negative outcomes. These findings support a bidirectional modulatory role for striatal dopamine in reward and avoidance learning via segregated D1 and D2 cortico-striatal pathways.

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YNIMG Journal 2012 Journal Article

Genetic variation in CYP2A6 predicts neural reactivity to smoking cues as measured using fMRI

  • Deborah W. Tang
  • Brian Hello
  • Margaret Mroziewicz
  • Lesley K. Fellows
  • Rachel F. Tyndale
  • Alain Dagher

Smoking cues trigger craving for cigarettes and relapse. Nicotine metabolism, mediated by the enzyme CYP2A6, also influences smoking behavior. In this study, we investigated how nicotine metabolism and genetic variation in CYP2A6 influence the neural response to smoking cues in humans using functional magnetic resonance imaging (fMRI). We hypothesized that individuals with faster rates of nicotine metabolism would have stronger conditioned responses to smoking cues because of closer coupling in everyday life between exposure to cigarettes and surges in blood nicotine concentration. In contrast, individuals with reduced rates of metabolism, who have relatively constant nicotine blood levels throughout the day, should be less likely to develop conditioned responses to cues. We screened 169 smokers for their rate of nicotine metabolism and CYP2A6 genotype, and selected 31 smokers with the fastest and slowest rates for fMRI, matched for daily cigarette intake. We measured their neural response to visual smoking and non-smoking cues using fMRI. As predicted, fast metabolizers, by phenotype or genotype, had significantly greater responses to visual cigarette cues than slow metabolizers in the amygdala, hippocampus, striatum, insula, and cingulate cortex. These results support the theory that drug cues are conditioned stimuli, and explain why fast metabolizers who smoke have lower cessation rates. They also provide insight into how genetics can shape human vulnerability to addiction, and have implications for tailoring smoking cessation programs based on individual genetics.

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YNIMG Journal 2009 Journal Article

Motion correction of multi-frame PET data in neuroreceptor mapping: Simulation based validation

  • Nicolas Costes
  • Alain Dagher
  • Kevin Larcher
  • Alan C. Evans
  • D. Louis Collins
  • Anthonin Reilhac

Patient motion during positron emission tomography scanning can affect the accuracy of the data analysis in two ways: 1) movement occurring during emission data acquisition alters the time activity curves (TACs), measured at a voxel or region of interest (ROI), and hence introduces errors in the parameter estimates derived from kinetic modeling; 2) emission–transmission mismatches introduce errors during attenuation and scatter correction, and hence in the radioactivity distribution estimates for each time frame of the scan. With the aim of designing an algorithm-based frame realignment method, we first conducted investigations that aimed at optimizing the parameters of a coregistration method, such as the choice of the target volume and the similarity criterion. Based on these results we designed a novel frame realignment strategy in a multi-step algorithm using uncorrected reconstructed images, cross-correlation similarity criteria for the determination of inter-frame motion parameters and emission-transmission mismatch for each frame. Features and validation results are reported here based on a multi-subject simulated [11C]raclopride dynamic PET scan database incorporating intra-frame movements of various magnitudes and with various times of occurrence. Performances of the proposed algorithm were evaluated at regional and voxel-based level for binding potential parametric images.

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YNIMG Journal 2008 Journal Article

Striatal dopamine transmission in healthy humans during a passive monetary reward task

  • Hélène S. Hakyemez
  • Alain Dagher
  • Stephen D. Smith
  • David H. Zald

Research on dopamine (DA) transmission has emphasized the importance of increased phasic DA cell firing in the presence of unpredictable rewards. Using [11C]raclopride PET, we previously reported that DA transmission was both suppressed and enhanced in different regions of the striatum during an unpredictable reward task [Zald, D. H. , Boileau, I. , El Dearedy, W. , Gunn, R. , McGlone, F. , Dichter, G. S. et al. (2004). Dopamine transmission in the human striatum during monetary reward tasks. J. Neurosci. 24, 4105–4112]. However, it was unclear if reductions in DA release during this task reflected a response to the high proportion of nonrewarding trials, and whether the behavioral demands of the task influenced the observed response. To test these issues, we presented 10 healthy subjects with an automated (passive) roulette wheel game in which the amount of reward and its timing were unpredictable and the rewarding trials greatly outnumbered the nonrewarding ones. As in the previous study, DA transmission in the putamen was significantly suppressed relative to a predictable control condition. A similar suppression occurred when subjects were presented with temporally unpredictable novel pictures and sounds. At present, models of DA functioning during reward do not account for this suppression, but given that it has been observed in two different studies using different reward paradigms, this phenomenon warrants attention. Neither the unpredictable reward nor the novelty conditions produced consistent increases in striatal DA transmission. These data suggest that active behavioral engagement may be necessary to observe robust statewise increases in DA release in the striatum.

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YNIMG Journal 2007 Journal Article

Focal cortical atrophy in multiple sclerosis: Relation to lesion load and disability

  • Arnaud Charil
  • Alain Dagher
  • Jason P. Lerch
  • Alex P. Zijdenbos
  • Keith J. Worsley
  • Alan C. Evans

Multiple sclerosis (MS) is thought to predominantly affect white matter (WM). Recently, however, loss of cortical gray matter has also been described. Little is known about the cause of cortical atrophy in MS, whether it occurs early in the disease course, and whether it affects all cortical regions equally or if there is a preferential pattern of focal cortical atrophy. An automated method was used to compute the thickness at every vertex of the cortical surface of the brains of 425 early relapsing–remitting MS patients. We correlated cortical thickness with the WM lesion load and the Expanded Disability Status Scale score. Mean cortical thickness correlated with WM lesion load and disability. The correlations of cortical thickness with total lesion load and disability were most significant in cingulate gyrus, insula, and associative cortical regions. Conversely, primary sensory, visual, and motor areas showed a less significant relationship. The highest amount of atrophy per lesion volume or disability scale unit was in the anterior cingulate cortex. This study confirms the relation between cortical atrophy, WM lesion load, and disability in MS, and suggests that cortical atrophy occurs even in MS patients with only mild disability. Most interestingly, we show a specific regional pattern of focal atrophy in MS that is distinctively different from the one in normal aging. The predilection of the atrophic process for areas that are heavily inter-connected with other brain regions suggests that interruption of WM tracts by MS plaques contributes, at least in part, to the development of cortical atrophy.

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YNIMG Journal 2004 Journal Article

Cognitive- and motor-related regions in Parkinson's disease: FDOPA and FDG PET studies

  • Atsuko Nagano-Saito
  • Takashi Kato
  • Yutaka Arahata
  • Yukihiko Washimi
  • Akinori Nakamura
  • Yuji Abe
  • Takako Yamada
  • Katsushige Iwai

Objective: Using 6-[18F]fluoro-l-dopa (FDOPA) and [18F]fluorodeoxyglucoce (FDG) positron emission tomography (PET), multiple regression analyses were performed to determine the specific brain regions that are related to cognitive and motor symptoms in nondemented patients with Parkinson's disease. Methods: Spatially normalized images of FDOPA influx rate constant (Ki) values and relative regional cerebral metabolic rates for glucose (rrCMRglc) were created. Raven's Coloured Progressive Matrices (RCPM) scores and the Unified Parkinson's Disease Rating Scale (UPDRS) motor scores were used to determine the patients' cognitive and motor functions, respectively. Multiple correlation analyses between the FDOPA and FDG images and the cognitive and motor scores were performed for each voxel. Results: RCPM score was significantly positively correlated with the FDOPA Ki in the left hippocampus and with the rrCMRglc in the left middle frontal gyrus and right retrosplenial cortex. Motor function was significantly positively correlated with the FDOPA Ki in the bilateral striatum and with the rrCMRglc in association areas and primary visual cortex. The level of motor function was significantly inversely correlated with the FDOPA Ki in the anterior cingulate gyrus and with the rrCMRglc in bilateral primary motor cortex and right putamen. Conclusions: Changes of striatal FDOPA uptake and rrCMRglc in the primary motor cortex likely represent dysfunction in the motor system involving the corticobasal ganglia-thalamocortical loop. Change of FDOPA uptake in the anterior cingulate gyrus may be related to up-regulation of dopamine synthesis in surviving dopamine neurons. The regions where correlation with cognitive function was observed belong to a cognitive frontoparietal–hippocampal network.

Details DOI

YNIMG Journal 2003 Journal Article

Feeding-induced dopamine release in dorsal striatum correlates with meal pleasantness ratings in healthy human volunteers

  • Dana M Small
  • Marilyn Jones-Gotman
  • Alain Dagher

Seven healthy subjects underwent two [11C]raclopride positron emission tomography (PET) scans, one following a 16-h fast and the other after consumption of a favorite meal (following a 16-h fast) in counterbalanced fashion. Before and after each scan subjects gave ratings of hunger/fullness and desire to eat. In addition, meal pleasantness ratings were collected immediately after consumption of the favorite meal. PET data were analyzed using brain parametric maps to generate regions of statistically significant change, as well as regions of interest manually drawn on each individual's coregistered anatomical image. [11C]Raclopride binding potential was compared across the two states (hungry and full). A significant reduction in binding potential was observed in the full compared to the hungry state in the dorsal putamen and caudate nucleus, indicative of dopamine release. There were no changes elsewhere in the striatum. A correlation was observed between the reduction in [11C]raclopride binding and meal pleasantness ratings, but not with desire to eat (hunger) or satiety after eating. These results suggest that feeding is associated with dopamine release in the dorsal, but not the ventral striatum, and that the amount of dopamine released correlates with the degree of experienced pleasure.

Details DOI

YNIMG Journal 2003 Journal Article

Statistical mapping analysis of lesion location and neurological disability in multiple sclerosis: application to 452 patient data sets

  • Arnaud Charil
  • Alex P Zijdenbos
  • Jonathan Taylor
  • Cyrus Boelman
  • Keith J Worsley
  • Alan C Evans
  • Alain Dagher

In multiple sclerosis (MS), the correlation between disability and the volume of white matter lesions on magnetic resonance imaging (MRI) is usually weak. This may be because lesion location also influences the extent and type of functional disability. We applied an automatic lesion-detection algorithm to 452 MRI scans of patients with relapsing-remitting MS to identify the regions preferentially responsible for different types of clinical deficits. Statistical parametric maps were generated by performing voxel-wise linear regressions between lesion probability and different clinical disability scores. There was a clear distinction between lesion locations causing physical and cognitive disability. Lesion likelihood correlated with the Expanded Disability Status Scale (EDSS) in the left internal capsule and in periventricular white matter mostly in the left hemisphere. Pyramidal deficits correlated with only one area in the left internal capsule that was also present in the EDSS correlation. Cognitive dysfunction correlated with lesion location at the grey-white junction of associative, limbic, and prefrontal cortex. Coordination impairment correlated with areas in interhemispheric and pyramidal periventricular white matter tracts, and in the inferior and superior longitudinal fascicles. Bowel and bladder scores correlated with lesions in the medial frontal lobes, cerebellum, insula, dorsal midbrain, and pons, areas known to be involved in the control of micturition. This study demonstrates for the first time a relationship between the site of lesions and the type of disability in large scale MRI data set in MS.

Details DOI
v2026.09.13