Pre-articulatory electrical activity associated with correct naming in individuals with aphasia

Abstract

Picture naming is a language task that involves multiple neural networks and is used to probe aphasia-induced language deficits. The pattern of neural activation seen in healthy individuals during picture naming is disrupted in individuals with aphasia, but the time-course of the disruption remains unclear. Specifically, it remains unclear which anatomical and temporal aspects of neural processing are necessary for correct naming. Here, we tested two individuals with stroke induced aphasia, and compared the differences in the event-related potentials (ERPs) and current sources when they made correct vs. erroneous responses during picture naming. The pre-articulatory ERP activity was significantly different between the two responses. Current source analysis revealed that the ability to recruit left temporal and frontal areas within a 300-550 ms time window after stimulus onset contributed to correct responses. These results suggest that targeted neuromodulation in these areas could lead to better treatment outcomes in patients with aphasia.

Alterations to dual stream connectivity predicts response to aphasia therapy following stroke

“…Further, during treatment, the directionality of functional interactions between cortical regions are highly informative in uncovering which cortical regions are involved in modulating language recovery potential. Recent work also suggests that EEG may be able to predict naming performance in aphasia on a trial-by-trial basis 48 highlighting the extended possibility of EEG monitoring in neurorehabilitation of aphasia.…”

Semantic Categorization of Naming Responses Based on Prearticulatory Electrical Brain Activity

“…Electrodes were placed on a standard electrode cap (Easy-Cap GmbH, Germany) following the 64-electrode layout based on the 10-20 system (https://www.easycap.de). 16,20 A common reference and a BrainVision actiCHamp amplifier (Brain Products GmbH, Germany) on a computer using Pycorder software were used to record EEG signals at a sampling rate of 1 kHz while applying a low-pass antialiasing filter of 200 Hz.…”

“…Nevertheless, recent studies are promising for EEG use in decoding speech in individuals with brain damage, especially if many electrodes are available (so-called high-density EEG [hdEEG] with 3 64 scalp channels). 16,17…”

“…Nevertheless, recent studies are promising for EEG use in decoding speech in individuals with brain damage, especially if many electrodes are available (so-called highdensity EEG [hdEEG] with 3 64 scalp channels). 16,17 The aim of this study is to assess the extent to which hdEEG combined with machine learning can be used to decode prearticulatory brain activity associated with language production. We conducted a study using machine learning with hdEEG recordings of healthy individuals to predict animate and inanimate semantic categories of naming responses.…”

Structural disconnection of the posterior medial frontal cortex reduces speech error monitoring

“…Although there have been a number of recent studies on lesions associated with production of speech errors in aphasia ( Mirman et al, 2015 , Schwartz et al, 2009 , Schwartz et al, 2012 , Singh et al, 2018 , Stark et al, 2019 , Wilmskoetter et al, 2019 ), there have not been many studies on lesions associated with monitoring speech errors. Only a few studies to date have systematically investigated the neural correlates of speech error monitoring in aphasia.…”