scholarly journals Focal versus distributed temporal cortex activity for speech sound category assignment

2017 ◽  
Author(s):  
Sophie Bouton ◽  
Valérian Chambon ◽  
Rémi Tyrand ◽  
Adrian G. Guggisberg ◽  
Margitta Seeck ◽  
...  

SummaryPercepts and words can be decoded from largely distributed neural activity measures. The existence of widespread representations might, however, conflict with the fundamental notions of hierarchical processing and efficient coding. Using fMRI and MEG during syllable identification, we first show that sensory and decisional activity co-localize to a restricted part of the posterior superior temporal cortex. Next, using intracortical recordings we demonstrate that early and focal neural activity in this region distinguishes correct from incorrect decisions and can be machine-decoded to classify syllables. Crucially, significant machine-decoding was possible from neuronal activity sampled across widespread regions, despite weak or absent sensory or decision-related responses. These findings show that a complex behavior like speech sound categorization relies on an efficient readout of focal neural activity, while distributed activity, although decodable by machine-learning, reflects collateral processes of sensory perception and decision.

2018 ◽  
Vol 115 (6) ◽  
pp. E1299-E1308 ◽  
Author(s):  
Sophie Bouton ◽  
Valérian Chambon ◽  
Rémi Tyrand ◽  
Adrian G. Guggisberg ◽  
Margitta Seeck ◽  
...  

Percepts and words can be decoded from distributed neural activity measures. However, the existence of widespread representations might conflict with the more classical notions of hierarchical processing and efficient coding, which are especially relevant in speech processing. Using fMRI and magnetoencephalography during syllable identification, we show that sensory and decisional activity colocalize to a restricted part of the posterior superior temporal gyrus (pSTG). Next, using intracortical recordings, we demonstrate that early and focal neural activity in this region distinguishes correct from incorrect decisions and can be machine-decoded to classify syllables. Crucially, significant machine decoding was possible from neuronal activity sampled across different regions of the temporal and frontal lobes, despite weak or absent sensory or decision-related responses. These findings show that speech-sound categorization relies on an efficient readout of focal pSTG neural activity, while more distributed activity patterns, although classifiable by machine learning, instead reflect collateral processes of sensory perception and decision.


2021 ◽  
Author(s):  
Kyle Rupp ◽  
Jasmine Leah Hect ◽  
Madison Remick ◽  
Avniel Ghuman ◽  
Bharath Chandresekaran ◽  
...  

The ability to recognize abstract features of voice during auditory perception is a complex, yet poorly understood, feat of human audition. For the listener, this occurs in near-automatic fasion to seamlessly extract complex cues from a highly variable auditory signal. Voice perception depends on specialized regions of auditory cortex, including superior temporal gyrus (STG) and superior temporal sulcus (STS). However, the nature of voice encoding at the cortical level remains poorly understoood. We leverage intracerebral recordings across human auditory cortex during presentation of voice and non-voice acoustic stimuli to examine voice encoding in auditory cortex, in eight patient-participants undergoing epilepsy surgery evaluation. We show that voice-selectivity increases along the auditory hierarchy from supratemporal plane (STP) to the STG and STS. Results show accurate decoding of vocalizations from human auditory cortical activity even in the complete absence of linguistic content. These findings show an early, less-selective temporal window of neural activity in the STG and STS followed by a sustained, strongly voice-selective window. We then developed encoding models that demonstrate divergence in the encoding of acoustic features along the auditory hierarchy, wherein STG/STS responses were best explained by voice category as opposed to the acoustic features of voice stimuli. This is in contrast to neural activity recorded from STP, in which responses were accounted for by acoustic features. These findings support a model of voice perception that engages categorical encoding mechanisms within STG and STS.


2007 ◽  
Vol 18 (1) ◽  
pp. 230-242 ◽  
Author(s):  
Stephen M. Wilson ◽  
Istvan Molnar-Szakacs ◽  
Marco Iacoboni

NeuroImage ◽  
1996 ◽  
Vol 3 (3) ◽  
pp. S230
Author(s):  
R.D. Lane ◽  
E.M. Reiman ◽  
G.L. Ahern ◽  
G.E. Schwartz ◽  
R.J. Davidson ◽  
...  

2003 ◽  
Vol 60 (1) ◽  
pp. 75
Author(s):  
J.F. Smiley ◽  
A.J. Dwork ◽  
N. Davceva ◽  
B. Mancevski ◽  
A. Duma ◽  
...  

2018 ◽  
Vol 08 (07) ◽  
pp. 415-429
Author(s):  
Vickie Y. Yu ◽  
Darren S. Kadis ◽  
Debra Goshulak ◽  
Aravind K. Namasivayam ◽  
Margit Pukonen ◽  
...  

Autism ◽  
2019 ◽  
Vol 24 (2) ◽  
pp. 364-373
Author(s):  
Talitha C Ford ◽  
David P Crewther ◽  
Ahmad Abu-Akel

Continued human and animal research has strengthened evidence for aberrant excitatory–inhibitory neural processes underlying autism and schizophrenia spectrum disorder psychopathology, particularly psychosocial functioning, in clinical and nonclinical populations. We investigated the extent to which autistic traits and schizotypal dimensions were modulated by the interactive relationship between excitatory glutamate and inhibitory GABA neurotransmitter concentrations in the social processing area of the superior temporal cortex using proton magnetic resonance spectroscopy. In total, 38 non-clinical participants (20 females; age range = 18–35 years, mean (standard deviation) = 23.22 (5.52)) completed the autism spectrum quotient and schizotypal personality questionnaire, and underwent proton magnetic resonance spectroscopy to quantify glutamate and GABA concentrations in the right and left superior temporal cortex. Regression analyses revealed that glutamate and GABA interactively modulated autistic social skills and schizotypal interpersonal features ( pcorr < 0.05), such that those with high right superior temporal cortex glutamate but low GABA concentrations exhibited poorer social and interpersonal skills. These findings evidence an excitation–inhibition imbalance that is specific to psychosocial features across the autism and schizophrenia spectra.


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