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

2020 ◽  
Author(s):  
Michael P. Broderick ◽  
Edmund C. Lalor
Keyword(s):  
Predictive Coding ◽  
Empirical Support ◽  
Temporal Analysis ◽  
Language Models ◽  
Natural Speech ◽  
Speech Comprehension ◽  
Top Down ◽  
Linguistic Information ◽  
Electrophysiological Responses ◽  
Eeg Recordings

AbstractPrior 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.

scholarly journals Hierarchical Frequency Tagging reveals neural markers of predictive coding under varying uncertainty

2016 ◽  
Author(s):  
Noam Gordon ◽  
Roger Koenig-Robert ◽  
Naotsugu Tsuchiya ◽  
Jeroen van Boxtel ◽  
Jakob Hohwy
Keyword(s):  
Sensory Input ◽  
Predictive Coding ◽  
Prediction Errors ◽  
The Novel ◽  
Top Down ◽  
Bottom Up ◽  
Visual Hierarchy ◽  
Core Elements ◽  
Neural Markers ◽  
Eeg Recordings

AbstractUnderstanding the integration of top-down and bottom-up signals is essential for the study of perception. Current accounts of predictive coding describe this in terms of interactions between state units encoding expectations or predictions, and error units encoding prediction error. However, direct neural evidence for such interactions has not been well established. To achieve this, we combined EEG methods that preferentially tag different levels in the visual hierarchy: Steady State Visual Evoked Potential (SSVEP at 10Hz, tracking bottom-up signals) and Semantic Wavelet-Induced Frequency Tagging (SWIFT at 1.3Hz tracking top-down signals). Importantly, we examined intermodulation components (IM, e.g., 11.3Hz) as a measure of integration between these signals. To examine the influence of expectation and predictions on the nature of such integration, we constructed 50-second movie streams and modulated expectation levels for upcoming stimuli by varying the proportion of images presented across trials. We found SWIFT, SSVEP and IM signals to differ in important ways. SSVEP was strongest over occipital electrodes and was not modified by certainty. Conversely, SWIFT signals were evident over temporo- and parieto-occipital areas and decreased as a function of increasing certainty levels. Finally, IMs were evident over occipital electrodes and increased as a function of certainty. These results link SSVEP, SWIFT and IM signals to sensory evidence, predictions, prediction errors and hypothesis-testing - the core elements of predictive coding. These findings provide neural evidence for the integration of top-down and bottom-up information in perception, opening new avenues to studying such interactions in perception while constraining neuronal models of predictive coding.SIGNIFICANCE STATEMENTThere is a growing understanding that both top-down and bottom-up signals underlie perception. But how do these signals interact? And how does this process depend on the signals’ probabilistic properties? ‘Predictive coding’ theories of perception describe this in terms how well top-down predictions fit with bottom-up sensory input. Identifying neural markers for such signal integration is therefore essential for the study of perception and predictive coding theories in particular. The novel Hierarchical Frequency Tagging method simultaneously tags top-down and bottom-up signals in EEG recordings, while obtaining a measure for the level of integration between these signals. Our results suggest that top-down predictions indeed integrate with bottom-up signals in a manner that is modulated by the predictability of the sensory input.

scholarly journals Delta-band Cortical Tracking of Acoustic and Linguistic Features in Natural Spoken Narratives

2020 ◽  
Author(s):  
Cheng Luo ◽  
Nai Ding
Keyword(s):  
Large Scale ◽  
Cortical Activity ◽  
Natural Speech ◽  
Speech Comprehension ◽  
Neural Encoding ◽  
Linguistic Features ◽  
Linguistic Information ◽  
Cortical Dynamics ◽  
Delta Band ◽  
Linguistic Units

AbstractSpeech contains rich acoustic and linguistic information. During speech comprehension, cortical activity tracks the acoustic envelope of speech. Recent studies also observe cortical tracking of higher-level linguistic units, such as words and phrases, using synthesized speech deprived of delta-band acoustic envelope. It remains unclear, however, how cortical activity jointly encodes the acoustic and linguistic information in natural speech. Here, we investigate the neural encoding of words and demonstrate that delta-band cortical activity tracks the rhythm of multi-syllabic words when naturally listening to narratives. Furthermore, by dissociating the word rhythm from acoustic envelope, we find cortical activity primarily tracks the word rhythm during speech comprehension. When listeners’ attention is diverted, however, neural tracking of words diminishes, and delta-band activity becomes phase locked to the acoustic envelope. These results suggest that large-scale cortical dynamics in the delta band are primarily coupled to the rhythm of linguistic units during natural speech comprehension.

scholarly journals Predictive Coding Models for Pain Perception

2019 ◽  
Author(s):  
Yuru Song ◽  
Mingchen Yao ◽  
Helen Kemprecos ◽  
Áine Byrne ◽  
Zhengdong Xiao ◽  
...  
Keyword(s):  
Experimental Data ◽  
Chronic Pain ◽  
Pain Perception ◽  
Predictive Coding ◽  
Oscillatory Activity ◽  
Top Down ◽  
Perceptual Inference ◽  
Bottom Up ◽  
Temporal Coordination ◽  
Mechanistic Insight

AbstractPain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we use a predictive coding paradigm to characterize both evoked and spontaneous pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats—two regions known to encode the sensory-discriminative and affective-emotional aspects of pain, respectively. We further propose a framework of predictive coding to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Specifically, we develop a high-level, empirical and phenomenological model to describe the macroscopic dynamics of bottom-up and top-down activity. Supported by recent experimental data, we also develop a mechanistic mean-field model to describe the mesoscopic population neuronal dynamics in the S1 and ACC populations, in both naive and chronic pain-treated animals. Our proposed predictive coding models not only replicate important experimental findings, but also provide new mechanistic insight into the uncertainty of expectation, placebo or nocebo effect, and chronic pain.Author SummaryPain perception in the mammalian brain is encoded through multiple brain circuits. The experience of pain is often associated with brain rhythms or neuronal oscillations at different frequencies. Understanding the temporal coordination of neural oscillatory activity from different brain regions is important for dissecting pain circuit mechanisms and revealing differences between distinct pain conditions. Predictive coding is a general computational framework to understand perceptual inference by integrating bottom-up sensory information and top-down expectation. Supported by experimental data, we propose a predictive coding framework for pain perception, and develop empirical and biologically-constrained computational models to characterize oscillatory dynamics of neuronal populations from two cortical circuits—one for the sensory-discriminative experience and the other for affective-emotional experience, and further characterize their temporal coordination under various pain conditions. Our computational study of biologically-constrained neuronal population model reveals important mechanistic insight on pain perception, placebo analgesia, and chronic pain.

scholarly journals Signature patterns for top-down and bottom-up information processing via cross-frequency coupling in macaque auditory cortex

2018 ◽  
Author(s):  
Christian D. Márton ◽  
Makoto Fukushima ◽  
Corrie R. Camalier ◽  
Simon R. Schultz ◽  
Bruno B. Averbeck
Keyword(s):  
Information Processing ◽  
Auditory Cortex ◽  
Predictive Coding ◽  
Low Frequency ◽  
Information Need ◽  
Top Down ◽  
Bottom Up ◽  
Low Frequencies ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

AbstractPredictive coding is a theoretical framework that provides a functional interpretation of top-down and bottom up interactions in sensory processing. The theory has suggested that specific frequency bands relay bottom-up and top-down information (e.g. “γ up, β down”). But it remains unclear whether this notion generalizes to cross-frequency interactions. Furthermore, most of the evidence so far comes from visual pathways. Here we examined cross-frequency coupling across four sectors of the auditory hierarchy in the macaque. We computed two measures of cross-frequency coupling, phase-amplitude coupling (PAC) and amplitude-amplitude coupling (AAC). Our findings revealed distinct patterns for bottom-up and top-down information processing among cross-frequency interactions. Both top-down and bottom-up made prominent use of low frequencies: low-to-low frequency (θ, α, β) and low frequency-to-high γ couplings were predominant top-down, while low frequency-to-low γ couplings were predominant bottom-up. These patterns were largely preserved across coupling types (PAC and AAC) and across stimulus types (natural and synthetic auditory stimuli), suggesting they are a general feature of information processing in auditory cortex. Moreover, our findings showed that low-frequency PAC alternated between predominantly top-down or bottom-up over time. Altogether, this suggests sensory information need not be propagated along separate frequencies upwards and downwards. Rather, information can be unmixed by having low frequencies couple to distinct frequency ranges in the target region, and by alternating top-down and bottom-up processing over time.1SignificanceThe brain consists of highly interconnected cortical areas, yet the patterns in directional cortical communication are not fully understood, in particular with regards to interactions between different signal components across frequencies. We employed a a unified, computationally advantageous Granger-causal framework to examine bi-directional cross-frequency interactions across four sectors of the auditory cortical hierarchy in macaques. Our findings extend the view of cross-frequency interactions in auditory cortex, suggesting they also play a prominent role in top-down processing. Our findings also suggest information need not be propagated along separate channels up and down the cortical hierarchy, with important implications for theories of information processing in the brain such as predictive coding.

scholarly journals Cortical Tracking of Global and Local Variations of Speech Rhythm during Connected Natural Speech Perception

2018 ◽  
Vol 30 (11) ◽  
pp. 1704-1719 ◽  
Author(s):  
Anna Maria Alexandrou ◽  
Timo Saarinen ◽  
Jan Kujala ◽  
Riitta Salmelin
Keyword(s):  
Speech Perception ◽  
Parietal Cortex ◽  
Temporal Structure ◽  
Temporal Cortex ◽  
Speaking Rate ◽  
Natural Speech ◽  
Speech Signals ◽  
Speech Rhythm ◽  
Linguistic Information ◽  
Evolutionary Tuning

During natural speech perception, listeners must track the global speaking rate, that is, the overall rate of incoming linguistic information, as well as transient, local speaking rate variations occurring within the global speaking rate. Here, we address the hypothesis that this tracking mechanism is achieved through coupling of cortical signals to the amplitude envelope of the perceived acoustic speech signals. Cortical signals were recorded with magnetoencephalography (MEG) while participants perceived spontaneously produced speech stimuli at three global speaking rates (slow, normal/habitual, and fast). Inherently to spontaneously produced speech, these stimuli also featured local variations in speaking rate. The coupling between cortical and acoustic speech signals was evaluated using audio–MEG coherence. Modulations in audio–MEG coherence spatially differentiated between tracking of global speaking rate, highlighting the temporal cortex bilaterally and the right parietal cortex, and sensitivity to local speaking rate variations, emphasizing the left parietal cortex. Cortical tuning to the temporal structure of natural connected speech thus seems to require the joint contribution of both auditory and parietal regions. These findings suggest that cortical tuning to speech rhythm operates on two functionally distinct levels: one encoding the global rhythmic structure of speech and the other associated with online, rapidly evolving temporal predictions. Thus, it may be proposed that speech perception is shaped by evolutionary tuning, a preference for certain speaking rates, and predictive tuning, associated with cortical tracking of the constantly changing-rate of linguistic information in a speech stream.

scholarly journals Deconstructing information literacy discourse: Peeling back the layers in higher education

2020 ◽  
pp. 096100062096602
Author(s):  
Alison Hicks ◽  
Annemaree Lloyd
Keyword(s):  
Higher Education ◽  
Information Literacy ◽  
English Language ◽  
Research Programme ◽  
Language Models ◽  
Analysis Method ◽  
Literacy Practice ◽  
Top Down ◽  
Behaviour Modification ◽  
Knowledge And Skills

The discourses of information literacy practice create epistemological assumptions about how the practice should happen, who should be responsible and under what conditions instruction should be given. This paper employs a discourse analysis method (Potter, 2008) to identify discourses of information literacy and the learner from within higher education focused professional texts. Texts analysed include 4 recent English-language models of information literacy and 16 textbooks. Analysis suggests that within higher education, information literacy is shaped by 2 conflicting narratives. The outward facing narrative positions information literacy as an empowering practice that equips learners with the knowledge and skills that they need within complex and fast-paced information environments. The inward facing narrative positions learners as incompetent or as lacking the ability to operate within higher education. This deficit perception consequently threatens the sustainability of information literacy practice by reframing empowerment as a process of top-down behaviour modification. This paper represents the first in a research programme that interrogates the epistemological premises and discourses of information literacy within higher education.

Re‐Examining the Effect of Top‐Down Linguistic Information on Speaker‐Voice Discrimination

2020 ◽  
Vol 44 (10) ◽  
Author(s):  
Ashley Quinto ◽  
Sandy Abu El Adas ◽  
Susannah V. Levi
Keyword(s):  
Top Down ◽  
Linguistic Information ◽  
Voice Discrimination

scholarly journals Top-down modulation in the infant brain: Learning-induced expectations rapidly affect the sensory cortex at 6 months

2015 ◽  
Vol 112 (31) ◽  
pp. 9585-9590 ◽  
Author(s):  
Lauren L. Emberson ◽  
John E. Richards ◽  
Richard N. Aslin
Keyword(s):  
Near Infrared ◽  
Predictive Coding ◽  
Empirical Support ◽  
Occipital Cortex ◽  
Theoretical Work ◽  
Functional Near Infrared Spectroscopy ◽  
Extensive Experience ◽  
Neural Organization ◽  
Repetition Suppression ◽  
Rudimentary Form

Recent theoretical work emphasizes the role of expectation in neural processing, shifting the focus from feed-forward cortical hierarchies to models that include extensive feedback (e.g., predictive coding). Empirical support for expectation-related feedback is compelling but restricted to adult humans and nonhuman animals. Given the considerable differences in neural organization, connectivity, and efficiency between infant and adult brains, it is a crucial yet open question whether expectation-related feedback is an inherent property of the cortex (i.e., operational early in development) or whether expectation-related feedback develops with extensive experience and neural maturation. To determine whether infants’ expectations about future sensory input modulate their sensory cortices without the confounds of stimulus novelty or repetition suppression, we used a cross-modal (audiovisual) omission paradigm and used functional near-infrared spectroscopy (fNIRS) to record hemodynamic responses in the infant cortex. We show that the occipital cortex of 6-month-old infants exhibits the signature of expectation-based feedback. Crucially, we found that this region does not respond to auditory stimuli if they are not predictive of a visual event. Overall, these findings suggest that the young infant’s brain is already capable of some rudimentary form of expectation-based feedback.

scholarly journals Speaking Style Influences the Brain's Electrophysiological Response to Grammatical Errors in Speech Comprehension

2017 ◽  
Vol 29 (7) ◽  
pp. 1132-1146 ◽  
Author(s):  
Malte C. Viebahn ◽  
Mirjam Ernestus ◽  
James M. McQueen
Keyword(s):  
Native Speakers ◽  
Electrophysiological Study ◽  
Grammatical Gender ◽  
Speech Comprehension ◽  
Brain Response ◽  
Electrophysiological Response ◽  
Electrophysiological Responses ◽  
Grammatical Errors ◽  
Casual Speech ◽  
Speaking Style

This electrophysiological study asked whether the brain processes grammatical gender violations in casual speech differently than in careful speech. Native speakers of Dutch were presented with utterances that contained adjective–noun pairs in which the adjective was either correctly inflected with a word-final schwa (e.g., een spannende roman, “a suspenseful novel”) or incorrectly uninflected without that schwa ( een spannend roman). Consistent with previous findings, the uninflected adjectives elicited an electrical brain response sensitive to syntactic violations when the talker was speaking in a careful manner. When the talker was speaking in a casual manner, this response was absent. A control condition showed electrophysiological responses for carefully as well as casually produced utterances with semantic anomalies, showing that listeners were able to understand the content of both types of utterance. The results suggest that listeners take information about the speaking style of a talker into account when processing the acoustic–phonetic information provided by the speech signal. Absent schwas in casual speech are effectively not grammatical gender violations. These changes in syntactic processing are evidence of contextually driven neural flexibility.

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