Left frontotemporal effective connectivity during semantic feature judgments in patients with chronic aphasia and age-matched healthy controls

Abstract

Traditional models of neural reorganization of language skills in patients with chronic stroke-induced aphasia (PWA) propose activation of reperfused or spared left hemisphere tissue results in the most favorable language outcomes. However, these models do not fully explain variable behavioral recovery patterns observed in chronic patients. Instead, investigation of connectivity patterns of critical network nodes may elucidate better-informed recovery models. In the present study, we combined fMRI and dynamic causal modeling (DCM) to examine effective connectivity of a simple three-node left hemisphere network during a semantic feature decision task in 25 PWA and 18 age-matched neurologically intact healthy controls. The DCM model space utilized in Meier, Kapse, & Kiran (2016), which was organized according to exogenous input to one of three regions (i.e., left inferior frontal gyrus, pars triangularis [LIFGtri], left posterior middle temporal gyrus [LpMTG], or left middle frontal gyrus [LMFG]) implicated in various levels of lexical-semantic processing, was interrogated. This model space included all possible combinations of uni- and bidirectional task-modulated connections between LIFGtri, LMFG and LpMTG, resulting in 72 individual models that were partitioned into three separate families (i.e., Family #1: Input to LIFGtri, Family #2: Input to LMFG, Family #3: Input to LpMTG). Family-wise Bayesian model selection revealed Family #2: Input to LMFG best fit both patient and control data at a group level. Both groups relied heavily on LMFG's modulation of the other two model regions. By contrast, between-group differences in task-modulated coupling of LIFGtri and LpMTG were observed. Within the patient group, the strength of activity in LIFGtri and connectivity of LpMTG → LIFGtri were positively associated with lexical-semantic abilities inside and outside of the scanner, whereas greater recruitment of LpMTG was associated with poorer lexical-semantic skills.

A lesion and connectivity-based hierarchical model of chronic aphasia recovery dissociates patients and healthy controls

“…Procedures similar to those utilized in Meier et al (2018) were used to ensure activity was extracted from a similar anatomical location within each ROI across participants. Regions that were active at the 2nd level in patients and/or controls were included in the final model space.…”

“…First, if the subject was a patient who did not exhibit activation within a highly-damaged left hemisphere region (i.e., < approximately 50% spared tissue within the regional bounding mask), a noisy signal (at p = 1.0, uncorrected) was extracted at the group-level MNI coordinate for that region. Noisy VOIs have been used in previous DCM studies of stroke patients (Meier et al, 2018; Seghier et al, 2012, Seghier et al, 2014) as they represent a good approximation of damage to a region due to lesion (Seghier et al, 2010) and allow for the inclusion of patients who would otherwise be excluded from the analysis due to incompatible DCM matrices. Second, if a participant in either group did not exhibit activation within a region outside the “classic” language network (i.e., left dorsolateral prefrontal cortex, any right hemisphere ROI), a noisy signal was similarly extracted.…”

“…Greater activation of domain-general cortex in the subacute phase has been shown to predict language abilities by the chronic recovery stage (Geranmayeh et al, 2017). Furthermore, patients with chronic aphasia have demonstrated a reliance on domain-general networks and connectivity of domain-general regions during language tasks (Brownsett et al, 2014; Geranmayeh et al, 2016; Meier et al, 2018; Meier et al, 2016a; Sharp et al, 2010).…”

Brain hothubs and dark functional networks: correlation analysis between amplitude and connectivity for Broca’s aphasia

“…However, various variables can influence the outcomes of linguistic therapy, including but not limited to semantic and phonological factors in picture-naming ( Nakagawa et al., 2019 ; Shrubsole et al., 2017 ). One future direction is to find links between graph measures and behavioral performances ( Meier, Johnson & Kiran, 2018 ; Meier, Kapse & Kiran, 2016 ; Palva et al., 2010 ). Another future work is to find associations between variables embedded in stimuli, such as semantic components based on semantic feature norms ( Feng, 2015 ), and graph measures of hothubs and coldhubs.…”

Language networks in aphasia and health: a 1000 participant Activation Likelihood Estimate analysis

“…Third, as is typical, the current analysis is based on massunivariate BOLD activation differences. It is possible that 'neural reprogramming' poststroke might entail differences in utilisation that are only observable using connectivity analyses (Schofield et al, 2012;Meier et al, 2018) or multivariate techniques (Fischer-Baum et al, 2017;Lee et al, 2017). Currently, there are very few studies that have used such techniques in PSA.…”