Tracking Cognitive Change over 24 Weeks with Longitudinal Functional Magnetic Resonance Imaging in Alzheimer’s Disease

McLaren, Donald G.; Sreenivasan, Aishwarya; Diamond, Eli L.; Mitchell, Meghan B.; Dijk, Koene R. A. Van; DeLuca, Amy; O’Brien, Jacqueline; Rentz, Dorene M.; Sperling, Reisa A.; Atri, Alireza

doi:10.1159/000335876

Cited by 44 publications

(34 citation statements)

References 120 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The data presented here is the baseline data from a longitudinal pharmacological fMRI study in subjects with mild AD dementia. FMRI data from some subjects has been used in previous publications (Atri et al, 2011; Diamond et al, 2007; McLaren et al, 2012b). …”

Section: Methodsmentioning

confidence: 99%

“…This study employs an established block design face-name associative encoding fMRI paradigm that probes the functional neuroanatomical specificity of associative memory encoding processes(Atri et al, 2011; Celone et al, 2006; Diamond et al, 2007; McLaren et al, 2012b; Pihlajamaki and Sperling, 2009; Putcha et al, 2011; Sperling, 2007; Sperling et al, 2003a; Sperling et al, 2002; Sperling et al, 2003b; Sperling et al, 2001). The task consists of three conditions presented in blocks: ( i ) novel face-name pairs, in which unfamiliar faces are paired with first names each shown once (5-sec duration); ( ii ) repeated face-name pairs, in which two face-name pairs are repeatedly alternated during each block; and ( iii ) fixation cross.…”

Section: Methodsmentioning

confidence: 99%

“…Then the following pre-processing steps were completed in SPM8 (Wellcome Department of Imaging Neuroscience, University College London, UK): (1) motion corrected; (2) spatially normalized to the MNI EPI template image; (3) re-sampled to 2 mm isotropic voxels; and (4) smoothed with an 8 mm full-width at half maximum Gaussian kernel. General linear models (GLM) were used to derive single subject activations for the novel encoding and repeated encoding blocks(McLaren et al, 2012b). Novel and repeated blocks were separately convolved with a canonical hemodynamic response function to form task regressors.…”

Section: Methodsmentioning

confidence: 99%

“…The use of fMRI methods to reveal relationships between behavior and cognitive function, whether in cognitively normal individuals or in patients with cognitive impairments due to conditions such as Alzheimer’s disease (AD), can be divided into three key areas: resting connectivity (Balthazar et al, 2014; Biswal et al, 1995; Damoiseaux et al, 2012; Fox et al, 2006; Kelly et al, 2008; Li et al, 2013; Sala-Llonch et al, 2012; Shehzad et al, 2014), evoked task-related activity (Atri et al, 2011; DeYoe et al, 1994; Diamond et al, 2007; Dolcos et al, 2013; Ewbank et al, 2009; Friston et al, 1995a; Friston et al, 1995b; McLaren et al, 2012b; Putcha et al, 2011; Simon et al, 2010; Wig et al, 2008), and more recently context-dependent connectivity (Chatham et al, 2014; Farr et al, 2012; Friston et al, 2003; McLaren et al, 2012a; Raz et al, 2014). …”

Section: Introductionmentioning

confidence: 99%

“…The objective of this study was to determine, in individuals with mild AD dementia, the characteristics of context-dependent hippocampal-whole brain functional connectivity analysis using our fMRI associative memory encoding paradigm in conjunction with performance outside the scanner on clinical and behavioral measures(Diamond et al, 2007; McLaren et al, 2012b; Sperling et al, 2003a). More broadly, the question assessed is whether differences in hippocampal-whole brain connectivity between conditions are related to behavior in AD?…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Flexible modulation of network connectivity related to cognition in Alzheimer's disease

McLaren¹,

Sperling²,

Atri³

2014

NeuroImage

Self Cite

View full text Add to dashboard Cite

Functional neuroimaging tools, such as fMRI methods, may elucidate the neural correlates of clinical, behavioral, and cognitive performance. Most functional imaging studies focus on regional task-related activity or resting state connectivity rather than how changes in functional connectivity across conditions and tasks are related to cognitive and behavioral performance. To investigate the promise of characterizing context-dependent connectivity-behavior relationships, this study applies the method of generalized psychophysiological interactions (gPPI) to assess the patterns of associative-memory-related fMRI hippocampal functional connectivity in Alzheimer’s disease (AD) associated with performance on memory and other cognitively demanding neuropsychological tests and clinical measures. Twenty-four subjects with mild AD dementia (ages 54–82, nine females) participated in a face-name paired-associate encoding memory study. Generalized PPI analysis was used to estimate the connectivity between the hippocampus and the whole brain during encoding. The difference in hippocampal-whole brain connectivity between encoding novel and repeated face-name pairs was used in multiple-regression analyses as an independent predictor for 10 behavioral, neuropsychological and clinical tests. The analysis revealed connectivity-behavior relationships that were distributed, dynamically overlapping, and task-specific within and across intrinsic networks; hippocampal-whole brain connectivity-behavior relationships were not isolated to single networks, but spanned multiple brain networks. Importantly, these spatially distributed performance patterns were unique for each measure. In general, out-of-network behavioral associations with encoding novel greater than repeated face-name pairs hippocampal-connectivity were observed in the default-mode network, while correlations with encoding repeated greater than novel face-name pairs hippocampal-connectivity were observed in the executive control network (p<0.05, cluster corrected). Psychophysiological interactions revealed significantly more extensive and robust associations between paired-associate encoding task-dependent hippocampal-whole brain connectivity and performance on memory and behavioral/clinical measures than previously revealed by standard activity-behavior analysis. Compared to resting state and task-activation methods, gPPI analyses may be more sensitive to reveal additional complementary information regarding subtle within- and between-network relations. The patterns of robust correlations between hippocampal-whole brain connectivity and behavioral measures identified here suggest that there are ‘coordinated states’ in the brain; that the dynamic range of these states is related to behavior and cognition; and that these states can be observed and quantified, even in individuals with mild AD.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Flexible modulation of network connectivity related to cognition in Alzheimer's disease

McLaren¹,

Sperling²,

Atri³

2014

NeuroImage

Self Cite

View full text Add to dashboard Cite

show abstract

Functional MRI technologies in the study of medication treatment effect on Alzheimer's disease

et al. 2018

View full text Add to dashboard Cite

Alzheimer's disease (AD) is the most common cause of late-life dementia. Characterized by progressive neurodegeneration, the disease is expressed as gradual memory loss together with decline in cognitive abilities and other brain functions. Despite extensive research over the past decade, the cause and cure of AD both remain largely unknown. Several AD-associated deficits have been targeted for interventions, including those based on amyloid-beta, tau, and inflammation hypotheses. Only 2 types of medications-cholinesterase inhibitors and memantine-have been approved, to control the cognitive symptoms of AD such as the loss of memory, language, and executive function. Noninvasive in vivo functional magnetic resonance imaging (MRI) technologies, including the blood oxygen level-dependent functional MRI, arterial spin labeling-based perfusion MRI, and the proton magnetic resonance spectroscopy have been used to study the effect of ChEIs and memantine in the brain. Most of these studies have demonstrated increased functional activation and connectivity, increased regional brain blood flow and volume post-treatment, and positive responses of critical brain metabolites reflecting neuronal status and functionality in patients with AD and mild cognitive impairment. The findings have contributed to the understanding of the mechanisms underlying the medication treatments and support the crucial role of functional MRI technologies in the development and refinement of AD medication therapies.

show abstract

Integrated cerebellar radiomic‐network model for predicting mild cognitive impairment in Alzheimer's disease

Chen,

Qi,

et al. 2024

Alzheimer's & Dementia

View full text Add to dashboard Cite

INTRODUCTIONPathological and neuroimaging alterations in the cerebellum of Alzheimer's disease (AD) patients have been documented. However, the role of cerebellum‐derived radiomic and structural connectome modeling in the prediction of AD progression remains unclear.METHODSRadiomic features were extracted from magnetic resonance imaging (MRI) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (n = 1319) and an in‐house dataset (n = 308). Integrated machine learning models were developed to predict the conversion risk of normal cognition (NC) to mild cognitive impairment (MCI) over a 6‐year follow‐up.RESULTSThe cerebellar models outperformed hippocampal models in distinguishing MCI from NC and in predicting transitions from NC to MCI across both cohorts. Key predictors included textural features in the right III and left I and II lobules, and network properties in Vermis I and II, which were associated with cognitive decline in AD.DISCUSSIONCerebellum‐derived radiomic‐network modeling shows promise as a tool for early identification and prediction of disease progression during the preclinical stage of AD.Highlights Altered cerebellar radiomic features and topological networks were identified in the subjects with mild cognitive impairment (MCI). The cerebellar radiomic‐network integrated models outperformed hippocampal models in distinguishing MCI from normal cognition. The cerebellar radiomic model effectively predicts MCI risk and can stratify individuals into distinct risk categories. Specific cerebellar radiomic features are associated with cognitive impairment across various stages of amyloid beta and tau pathology.

show abstract

Tracking Cognitive Change over 24 Weeks with Longitudinal Functional Magnetic Resonance Imaging in Alzheimer’s Disease

Cited by 44 publications

References 120 publications

Flexible modulation of network connectivity related to cognition in Alzheimer's disease

Flexible modulation of network connectivity related to cognition in Alzheimer's disease

Functional MRI technologies in the study of medication treatment effect on Alzheimer's disease

Integrated cerebellar radiomic‐network model for predicting mild cognitive impairment in Alzheimer's disease

Contact Info

Product

Resources

About