FIACH: A biophysical model for automatic retrospective noise control in fMRI.

Different noise sources in fMRI acquisition can lead to spurious false positives and reduced sensitivity. We have developed a biophysically-based model (named FIACH: Functional Image Artefact Correction Heuristic) which extends current retrospective noise control methods in fMRI. FIACH can be applied to both General Linear Model (GLM) and resting state functional connectivity MRI (rs-fcMRI) studies. FIACH is a two-step procedure involving the identification and correction of non-physiological large amplitude temporal signal changes and spatial regions of high temporal instability. We have demonstrated its efficacy in a sample of 42 healthy children while performing language tasks that include overt speech with known activations. We demonstrate large improvements in sensitivity when FIACH is compared with current methods of retrospective correction. FIACH reduces the confounding effects of noise and increases the study's power by explaining significant variance that is not contained within the commonly used motion parameters. The method is particularly useful in detecting activations in inferior temporal regions which have proven problematic for fMRI. We have shown greater reproducibility and robustness of fMRI responses using FIACH in the context of task induced motion. In a clinical setting this will translate to increasing the reliability and sensitivity of fMRI used for the identification of language lateralisation and eloquent cortex. FIACH can benefit studies of cognitive development in young children, patient populations and older adults.

Maturation of language networks in children: A systematic review of 22years of functional MRI.

Understanding how language networks change during childhood is important for theories of cognitive development and for identifying the neural causes of language impairment. Despite this, there is currently little systematic evidence regarding the typical developmental trajectory for language from the field of neuroimaging. We reviewed functional MRI (fMRI) studies published between 1992 and 2014, and quantified the evidence for age-related changes in localisation and lateralisation of fMRI activation in the language network (excluding the cerebellum and subcortical regions). Although age-related changes differed according to task type and input modality, we identified four consistent findings concerning the typical maturation of the language system. First, activation in core semantic processing regions increases with age. Second, activation in lower-level sensory and motor regions increases with age as activation in higher-level control regions reduces. We suggest that this reflects increased automaticity of language processing as children become more proficient. Third, the posterior cingulate cortex and precuneus (regions associated with the default mode network) show increasing attenuation across childhood and adolescence. Finally, language lateralisation is established by approximately 5years of age. Small increases in leftward lateralisation are observed in frontal regions, but these are tightly linked to performance.