Impact of task-related changes in heart rate on estimation of hemodynamic response and model fit

Resting-state and Vocabulary Tasks Distinctively Inform On Age-Related Differences in the Functional Brain Connectome

Most of the current knowledge about age-related differences in brain neurofunctional organization stems from neuroimaging studies using either a "resting state" paradigm, or cognitive tasks for which performance decreases with age. However, it remains to be known if comparable age-related differences are found when participants engage in cognitive activities for which performance is maintained with age, such as vocabulary knowledge tasks. A functional connectivity analysis was performed on 286 adults ranging from 18 to 80 years old, based either on a resting state paradigm or when engaged in vocabulary tasks. Notable increases in connectivity of regions of the language network were observed during task completion. Conversely, only age-related decreases were observed across the whole connectome during resting-state. While vocabulary accuracy increased with age, no interaction was found between functional connectivity, age and task accuracy or proxies of cognitive reserve, suggesting that older individuals typically benefits from semantic knowledge accumulated throughout one's life trajectory, without the need for compensatory mechanisms.

Methods for cleaning the BOLD fMRI signal

Blood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has rapidly become a popular technique for the investigation of brain function in healthy individuals, patients as well as in animal studies. However, the BOLD signal arises from a complex mixture of neuronal, metabolic and vascular processes, being therefore an indirect measure of neuronal activity, which is further severely corrupted by multiple non-neuronal fluctuations of instrumental, physiological or subject-specific origin. This review aims to provide a comprehensive summary of existing methods for cleaning the BOLD fMRI signal. The description is given from a methodological point of view, focusing on the operation of the different techniques in addition to pointing out the advantages and limitations in their application. Since motion-related and physiological noise fluctuations are two of the main noise components of the signal, techniques targeting their removal are primarily addressed, including both data-driven approaches and using external recordings. Data-driven approaches, which are less specific in the assumed model and can simultaneously reduce multiple noise fluctuations, are mainly based on data decomposition techniques such as principal and independent component analysis. Importantly, the usefulness of strategies that benefit from the information available in the phase component of the signal, or in multiple signal echoes is also highlighted. The use of global signal regression for denoising is also addressed. Finally, practical recommendations regarding the optimization of the preprocessing pipeline for the purpose of denoising and future venues of research are indicated. Through the review, we summarize the importance of signal denoising as an essential step in the analysis pipeline of task-based and resting state fMRI studies.

The use of resting state data in an integrative approach to studying neurocognitive ageing - Commentary on Campbell and Schacter (2016)

This is a commentary on Campbell and Schacter (2016), 'Ageing and the Resting State: Is Cognition Obsolete?'. Campbell and Schacter argue that resting state data have a limited ability to contribute to the study of neurocognitive ageing and that the field should focus more on results from carefully controlled experimental designs. In this commentary, we argue for a different perspective on future research directions in neurocognitive ageing. Specifically for the need to use a more integrative approach; combining rest and task data as well as information from different modalities to obtain a better understanding of the neural mechanisms that underlie healthy cognitive ageing. Potential benefits of this integrative approach are illustrated with a number of examples. In addition, we discuss some of the advantages of using resting state data as part of this integrative approach.

Aging and the Resting State: Is Cognition Obsolete?

Recent years have seen the rise in popularity of the resting state approach to neurocognitive aging, with many studies examining age differences in functional connectivity at rest and relating these differences to cognitive performance outside the scanner. There are many advantages to the resting state that likely contribute to its popularity and indeed, many insights have been gained from this work. However, there are also several limitations of the resting state approach that restrict its ability to contribute to the study of neurocognitive aging. In this opinion piece, we consider some of those limitations and argue that task-based studies are still essential to developing a mechanistic understanding of how age affects the brain in a cognitively relevant manner - a fundamental goal of neuroscientific research into aging.