| Literature DB >> 26400624 |
Mehdi Behroozi1,2,3, Mohammad Reza Daliri4,5, Babak Shekarchi6.
Abstract
Oscillations of electroencephalographic signals represent the cognitive processes arose from the behavioral task and sensory representations across the mental state activity. Previous studies have shown the relation between event-related EEG and sensory-cognitive representation and revealed that categorization of presented object can be successfully recognized using recorded EEG signals when subjects view objects. Here, EEG signals in conjunction with a multivariate pattern recognition technique were used for investigating the possibility to identify conceptual representation based on the presentation of 12 semantic categories of objects (5 exemplars per category). Using multivariate stimulus decoding methods, surprisingly, we demonstrate that how objects are discriminated from phase pattern of EEG signals across the time in low-frequency band (1-4 Hz), but not from power of oscillatory brain signals in the same frequency band. In contrast, discrimination accuracy from the power of EEG signals has significantly higher than the performance from phase of EEG signal in the high-frequency band (20-30 Hz). Moreover, our results indicate that how the accuracy of prediction changes between various areas of brain continuously across the time. In particular, we find that, during the object categorization task, the inter-trial phase coherence in low-frequency band is significantly higher than other frequency in various regions of interests. This measure is associated with decoding pattern across the time. These results suggest that the mechanism underlying conceptual representation can be mediated by the phase of oscillatory neural activity.Keywords: Categorization; Delta band; Hilbert transform; Inter-trial phase coherence; Naïve Bayes classifier; Oscillations
Mesh:
Year: 2015 PMID: 26400624 DOI: 10.1007/s11517-015-1391-7
Source DB: PubMed Journal: Med Biol Eng Comput ISSN: 0140-0118 Impact factor: 2.602