Abstract
Name recognition plays important role in self-related cognitive processes and also contributes to a variety of clinical applications, such as autism spectrum disorder diagnosis and consciousness disorder analysis. However, most previous name-related studies usually adopted noninvasive EEG or fMRI recordings, which were limited by low spatial resolution and temporal resolution, respectively, and thus millisecond-level response latencies in precise brain regions could not be measured using these noninvasive recordings. By invasive stereo-electroencephalography (SEEG) recordings that have high resolution in both the spatial and temporal domain, the current study distinguished the neural response to one's own name or a stranger's name, and explored common active brain regions in both auditory and visual modalities. The neural activities were classified using spatiotemporal features of high-gamma, beta, and alpha band. Results showed that different names could be decoded using multi-region SEEG signals, and the best classification performance was achieved at high gamma (60–145 Hz) band. In this case, auditory and visual modality-based name classification accuracies were 84.5 ± 8.3 and 79.9 ± 4.6%, respectively. Additionally, some single regions such as the supramarginal gyrus, middle temporal gyrus, and insula could also achieve remarkable accuracies for both modalities, supporting their roles in the processing of self-related information. The average latency of the difference between the two responses in these precise regions was 354 ± 63 and 285 ± 59 ms in the auditory and visual modality, respectively. This study suggested that name recognition was attributed to a distributed brain network, and the subsets with decoding capabilities might be potential implanted regions for awareness detection and cognition evaluation.
Highlights
One’s name is one of the most socially self-related stimuli
The results show that these two different names could be predicted using SEEG signals recorded from multiple brain regions, where the high-frequency activity produced superior decoding accuracy within the used spectral features
To quantify the extent to which the classification accuracy was caused by the physical difference between the two stimuli, we evaluated the physical difference between stimuli using cross-correlation, and implemented a least-square linear regression analysis between the cross-correlation values and the classification accuracies in the cross-modal regions
Summary
One’s name is one of the most socially self-related stimuli. Cognitive neuroscientists have highlighted the differences between the brain responses to one’s own name. Studies based on fMRI have demonstrated that stimulus of own name elicited unique brain functional activations in the medial prefrontal cortex, inferior frontal gyri, anterior cingulate, and anterior insula, while these activations were not shown under the stimulus of other’s name (Carmody and Lewis, 2006; Tacikowski et al, 2011, 2013; Qin et al, 2012). In electroencephalography (EEG) studies, the own name could elicit unique event-related potentials (ERP) (Tateuchi et al, 2012; Tamura et al, 2016). The own name resulted in higher P300 (a positive-going ERP) amplitude and shorter latency compared to other names (Tacikowski and Nowicka, 2010; Kotlewska and Nowicka, 2015)
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