Abstract:
:There is substantial variability in speech recognition ability across patients with cochlear implants (CIs), auditory brainstem implants (ABIs), and auditory midbrain implants (AMIs). To better understand how this variability is related to central processing differences, the current electroencephalography (EEG) study compared hearing abilities and auditory-cortex activation in patients with electrical stimulation at different sites of the auditory pathway. Three different groups of patients with auditory implants (Hannover Medical School; ABI: n = 6, CI: n = 6; AMI: n = 2) performed a speeded response task and a speech recognition test with auditory, visual, and audio-visual stimuli. Behavioral performance and cortical processing of auditory and audio-visual stimuli were compared between groups. ABI and AMI patients showed prolonged response times on auditory and audio-visual stimuli compared with NH listeners and CI patients. This was confirmed by prolonged N1 latencies and reduced N1 amplitudes in ABI and AMI patients. However, patients with central auditory implants showed a remarkable gain in performance when visual and auditory input was combined, in both speech and non-speech conditions, which was reflected by a strong visual modulation of auditory-cortex activation in these individuals. In sum, the results suggest that the behavioral improvement for audio-visual conditions in central auditory implant patients is based on enhanced audio-visual interactions in the auditory cortex. Their findings may provide important implications for the optimization of electrical stimulation and rehabilitation strategies in patients with central auditory prostheses. Hum Brain Mapp 38:2206-2225, 2017. © 2017 Wiley Periodicals, Inc.
journal_name
Hum Brain Mappjournal_title
Human brain mappingauthors
Schierholz I,Finke M,Kral A,Büchner A,Rach S,Lenarz T,Dengler R,Sandmann Pdoi
10.1002/hbm.23515subject
Has Abstractpub_date
2017-04-01 00:00:00pages
2206-2225issue
4eissn
1065-9471issn
1097-0193journal_volume
38pub_type
杂志文章abstract::Independent component analysis (ICA) has been shown as a promising tool for the analysis of functional magnetic resonance imaging (fMRI) time series. Each of these studies, however, used a general-purpose algorithm for performing ICA and the computational efficiency and accuracy of elicited neuronal activations have n...
journal_title:Human brain mapping
pub_type: 临床试验,杂志文章
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journal_title:Human brain mapping
pub_type: 杂志文章
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journal_title:Human brain mapping
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journal_title:Human brain mapping
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journal_title:Human brain mapping
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journal_title:Human brain mapping
pub_type: 杂志文章
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pub_type: 杂志文章
doi:10.1002/hbm.23209
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journal_title:Human brain mapping
pub_type: 杂志文章
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pub_type: 杂志文章
doi:10.1002/hbm.10133
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pub_type: 杂志文章,多中心研究
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更新日期:2017-01-01 00:00:00
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journal_title:Human brain mapping
pub_type: 杂志文章
doi:10.1002/hbm.23033
更新日期:2016-01-01 00:00:00
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pub_type: 杂志文章
doi:10.1002/hbm.23580
更新日期:2017-06-01 00:00:00
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pub_type: 杂志文章
doi:10.1002/hbm.22530
更新日期:2014-10-01 00:00:00
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pub_type: 杂志文章
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journal_title:Human brain mapping
pub_type: 杂志文章
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更新日期:2017-07-01 00:00:00
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journal_title:Human brain mapping
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journal_title:Human brain mapping
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