Dynamic speech representations in the human temporal lobe

Leonard, Matthew K.; Chang, Edward F.

doi:10.1016/j.tics.2014.05.001

Cited by 90 publications

(62 citation statements)

References 98 publications

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“…All subjects also had an FNC during picture naming with interactions between posterior superior temporal gyrus or supramarginal gyrus and either sensorimotor cortex, Broca’s area, or both (red/triangles in Figure 4 and Supplementary Figure 2), with timing strongly aligned to verbal response onset (red in Figure 6 and Supplementary Figure 3). This alignment is consistent with pSTG’s role in auditory processing of speech (Price et al, 1992; Steinschneider et al, 2011; Leonard and Chang, 2014). …”

Section: Discussionsupporting

confidence: 85%

Cortical subnetwork dynamics during human language tasks

et al. 2016

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Language tasks require the coordinated activation of multiple subnetworks—groups of related cortical interactions involved in specific components of task processing. Although electrocorticography (ECoG) has sufficient temporal and spatial resolution to capture the dynamics of event-related interactions between cortical sites, it is difficult to decompose these complex spatiotemporal patterns into functionally discrete subnetworks without explicit knowledge of each subnetwork’s timing. We hypothesized that subnetworks corresponding to distinct components of task-related processing could be identified as groups of interactions with co-varying strengths. In this study, five subjects implanted with ECoG grids over language areas performed word repetition and picture naming. We estimated the interaction strength between each pair of electrodes during each task using a time-varying dynamic Bayesian network (tvDBN) model constructed from the power of high gamma (70–110 Hz) activity, a surrogate for population firing rates. We then reduced the dimensionality of this model using principal component analysis (PCA) to identify groups of interactions with co-varying strengths, which we term functional network components (FNCs). This data-driven technique estimates both the weight of each interaction’s contribution to a particular subnetwork, and the temporal profile of each subnetwork’s activation during the task. We found FNCs with temporal and anatomical features consistent with articulatory preparation in both tasks, and with auditory and visual processing in the word repetition and picture naming tasks, respectively. These FNCs were highly consistent between subjects with similar electrode placement, and were robust enough to be characterized in single trials. Furthermore, the interaction patterns uncovered by FNC analysis correlated well with recent literature suggesting important functional-anatomical distinctions between processing external and self-produced speech. Our results demonstrate that subnetwork decomposition of event-related cortical interactions is a powerful paradigm for interpreting the rich dynamics of large-scale, distributed cortical networks during human cognitive tasks.

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Section: Discussionsupporting

confidence: 85%

Cortical subnetwork dynamics during human language tasks

et al. 2016

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“…There is accumulating evidence that later activity in more anterior STG neural populations reflects the higher-order hierarchical processing of speech as part of the ventral stream of word recognition (Crinion, Lambon- Ralph, Warburton, Howard, & Wise, 2003; DeWitt & Rauschecker, 2012; Hickok & Poeppel, 2007; Leonard & Chang, 2014; Rauschecker & Scott, 2009). In contrast, auditory-evoked activity in frontal motor areas has generated a lively debate regarding the role of motor regions in speech perception (Hickok et al, 2011; Saur et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

The peri-Sylvian cortical network underlying single word repetition revealed by electrocortical stimulation and direct neural recordings

et al. 2019

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Verbal repetition requires the coordination of auditory, memory, linguistic, and motor systems. To date, the basic dynamics of neural information processing in this deceptively simple behavior are largely unknown. Here, we examined the neural processes underlying verbal repetition using focal interruption (electrocortical stimulation) in 59 patients undergoing awake craniotomies, and neurophysiological recordings (electrocorticography) in 8 patients while they performed a single word repetition task. Electrocortical stimulation revealed that sub-components of the left peri-Sylvian network involved in single word repetition could be differentially interrupted, producing transient perceptual deficits, paraphasic errors, or speech arrest. Electrocorticography revealed the detailed spatio-temporal dynamics of cortical activation, involving a highly-ordered, but overlapping temporal progression of cortical high gamma (75–150Hz) activity throughout the peri-Sylvian cortex. We observed functionally distinct serial and parallel cortical processing corresponding to successive stages of general auditory processing (posterior superior temporal gyrus), speech-specific auditory processing (middle and posterior superior temporal gyrus), working memory (inferior frontal cortex), and motor articulation (sensorimotor cortex). Together, these methods reveal the dynamics of coordinated activity across peri-Sylvian cortex during verbal repetition.

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“…Incoming acoustic input is not simply sequentially matched with stored templates, but rather is processed in the context of deeply learned knowledge about other words in the language that share important lexical features (Toscano, Anderson, & McMurray, 2013). This provides empirical information about how spatially and temporally distributed lexical representations (Marslen-Wilson, 1997; McClelland & Elman, 1986) are stored and accessed rapidly during speech perception, often dependent on the context in which they are heard (Leonard & Chang, 2014). …”

Section: Discussionmentioning

confidence: 99%

The influence of lexical statistics on temporal lobe cortical dynamics during spoken word listening

et al. 2015

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Neural representations of words are thought to have a complex spatio-temporal cortical basis. It has been suggested that spoken word recognition is not a process of feed-forward computations from phonetic to lexical forms, but rather involves the online integration of bottom-up input with stored lexical knowledge. Using direct neural recordings from the temporal lobe, we examined cortical responses to words and pseudowords. We found that neural populations were not only sensitive to lexical status (real vs. pseudo), but also to cohort size (number of words matching the phonetic input at each time point) and cohort frequency (lexical frequency of those words). These lexical variables modulated neural activity from the posterior to anterior temporal lobe, and also dynamically as the stimuli unfolded on a millisecond time scale. Our findings indicate that word recognition is not purely modular, but relies on rapid and online integration of multiple sources of lexical knowledge.

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Dynamic speech representations in the human temporal lobe

Cited by 90 publications

References 98 publications

Cortical subnetwork dynamics during human language tasks

Cortical subnetwork dynamics during human language tasks

The peri-Sylvian cortical network underlying single word repetition revealed by electrocortical stimulation and direct neural recordings

The influence of lexical statistics on temporal lobe cortical dynamics during spoken word listening

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