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Broderick, M. P.

Publications and source records attributed to Broderick, M. P..

4 recordsLinked to original sources

More than Words: Neurophysiological Correlates of Semantic Dissimilarity Depend on Comprehension of the Speech Narrative

Speech comprehension relies on the ability to understand the meaning of words within a coherent context. Recent studies have attempted to obtain electrophysiological indices of this process by modelling how brain activity is affected by a words semantic dissimilarity to preceding words. While the resulting indices appear robust and are strongly modulated by attention, it remains possible that, rather than capturing the contextual understanding of words, they may actually reflect word-to-word changes in semantic content without the need for a narrative-level understanding on the part of the listener. To test this possibility, we recorded EEG from subjects who listened to speech presented in either its original, narrative form, or after scrambling the word order by varying amounts. This manipulation affected the ability of subjects to comprehend the narrative content of the speech, but not the ability to recognize the individual words. Neural indices of semantic understanding and low-level acoustic processing were derived for each scrambling condition using the temporal response function (TRF) approach. Signatures of semantic processing were observed for conditions where speech was unscrambled or minimally scrambled and subjects were able to understand the speech. The same markers were absent for higher levels of scrambling when speech comprehension dropped below chance. In contrast, word recognition remained high and neural measures related to envelope tracking did not vary significantly across the different scrambling conditions. This supports the previous claim that electrophysiological indices based on the semantic dissimilarity of words to their context reflect a listeners understanding of those words relative to that context. It also highlights the relative insensitivity of neural measures of low-level speech processing to speech comprehension.

neuroscience↗

Co-existence of prediction and error signals in electrophysiological responses to natural speech

Prior knowledge facilitates perception and allows us to interpret our sensory environment. However, the neural mechanisms underlying this process remain unclear. Theories of predictive coding propose that feedback connections between cortical levels carry predictions about upcoming sensory events whereas feedforward connections carry the error between the prediction and the sensory input. Although predictive coding has gained much ground as a viable mechanism for perception, in the context spoken language comprehension it lacks empirical support using more naturalistic stimuli. In this study, we investigated theories of predictive coding using continuous, everyday speech. EEG recordings from human participants listening to an audiobook were analysed using a 2-stage regression framework. This tested the effect of top-down linguistic information, estimated using computational language models, on the bottom-up encoding of acoustic and phonetic speech features. Our results show enhanced encoding of both semantic predictions and surprising words, based on preceding context. This suggests that signals pertaining to prediction and error units can be observed in the same electrophysiological responses to natural speech. In addition, temporal analysis of these signals reveals support for theories of predictive coding that propose that perception is first biased towards what is expected followed by what is informative. Significance StatementOver the past two decades, predictive coding has grown in popularity as an explanatory mechanism for perception. However, there has been lack of empirical support for this theory in research studying natural speech comprehension. We address this issue by developing an analysis framework that tests the effects of top-down linguistic information on the auditory encoding of continuous speech. Our results provide evidence for the co-existence of prediction and error signals and support theories of predictive coding using more naturalistic stimuli.

neuroscience↗

Dissociable electrophysiological measures of natural language processing reveal differences in comprehension strategy in healthy ageing

Healthy ageing leads to changes in the brain that impact upon sensory and cognitive processing. It is not fully clear how these changes affect the processing of everyday spoken language. Prediction is thought to play an important role in language comprehension, where information about upcoming words is pre-activated across multiple representational levels. However, evidence from electrophysiology suggests differences in how older and younger adults use context-based predictions, particularly at the level of semantic representation. We investigate these differences during natural speech comprehension by presenting older and younger subjects with continuous, narrative speech while recording their electroencephalogram. We use linear regression to test how distinct computational measures of 1) semantic dissimilarity and 2) lexical surprisal are processed in the brains of both groups. Our results reveal dissociable neural correlates of these two measures that suggest differences in how younger and older adults successfully comprehend speech. Specifically, our results suggest that, while younger and older subjects both employ context-based lexical predictions, older subjects are significantly less likely to pre-activate the semantic features relating to upcoming words. Furthermore, across our group of older adults, we show that the weaker the neural signature of this semantic pre-activation mechanism, the lower a subjects semantic verbal fluency score. We interpret these findings as prediction playing a generally reduced role at a semantic level in the brains of older listeners during speech comprehension and that these changes may be part of an overall strategy to successfully comprehend speech with reduced cognitive resources.

neuroscience↗

Electrophysiological correlates of semantic dissimilarity reflect the comprehension of natural, narrative speech.

Understanding natural speech requires that the human brain convert complex spectrotemporal patterns of acoustic input into meaning in a rapid manner that is reasonably tightly time-locked to the incoming speech signal. However, neural evidence for such a time-locked process has been lacking. Here, we sought such evidence by using a computational model to quantify the meaning carried by each word based on how semantically dissimilar it was to its preceding context and then regressing this quantity against electroencephalographic (EEG) data recorded from subjects as they listened to narrative speech. This produced a prominent negativity at a time-lag of 200- 600 ms on centro-parietal EEG electrodes. Subsequent EEG experiments involving time-reversed speech, cocktail party attention and audiovisual speech-in-noise demonstrated that this response was exquisitely sensitive to whether or not subjects were understanding the speech they heard. These findings demonstrate that, when successfully comprehending natural speech, the human brain encodes meaning as a function of the amount of new information carried by each word in a relatively time-locked fashion.

neuroscience↗