Temporal coding in the auditory cortex

Arnal, Luc H.; Poeppel, David; Giraud, Anne Lise

doi:10.1016/b978-0-444-62630-1.00005-6

Cited by 41 publications

(41 citation statements)

References 104 publications

(91 reference statements)

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“…Recent work has investigated the neural dynamics that support language and sensory processing [40–42] and how these dynamics may be altered in RD [36,43]. We integrate these emerging lines of research to propose that excess neural noise (Box 1) within cortical regions implicated in reading may be a distal contributor to RD.…”

Section: Premise Of the Neural Noise Hypothesismentioning

confidence: 99%

Neural Noise Hypothesis of Developmental Dyslexia

Hancock

Pugh

Hoeft

2017

Trends in Cognitive Sciences

118

104

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Developmental dyslexia (decoding-based reading disorder; RD) is a complex trait with multifactorial origins at the genetic, neural and cognitive levels. There is evidence that low-level sensory processing deficits precede and underlie phonological problems, which are one of the best-documented aspects of RD. RD is also associated with impairments in integrating visual symbols with their corresponding speech sounds. Although causal relationships between sensory processing, print-speech integration and fluent reading, and their neural bases are debated, these processes all require precise timing mechanisms across distributed brain networks. Neural excitability and neural noise are fundamental to these timing mechanisms. We propose that neural noise stemming from increased neural excitability in cortical networks implicated in reading is one key, distal contributor to RD.

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Section: Premise Of the Neural Noise Hypothesismentioning

confidence: 99%

Neural Noise Hypothesis of Developmental Dyslexia

Hancock

Pugh

Hoeft

2017

Trends in Cognitive Sciences

118

104

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“…Other populations represent amplitude modulations through a mean population firing rate. This rate code is observed in response to fast temporal modulations (<30 Hz) associated with phonemes (Arnal et al, 2015).…”

Section: Representation Of the Multiscale Temporal Features Of Speechmentioning

confidence: 98%

“…There are neurons that represent amplitude modulations through the synchronized timing of their spikes (Wang, 2007;Wang et al, 2008). This synchrony is observed in response to slow temporal modulations (<5 Hz), which are associated with word and syllable boundaries (Arnal et al, 2015). Other populations represent amplitude modulations through a mean population firing rate.…”

Section: Representation Of the Multiscale Temporal Features Of Speechmentioning

confidence: 99%

Using Neural Circuit Interrogation in Rodents to Unravel Human Speech Decoding

Neophytou

Oviedo

2020

Front. Neural Circuits

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The neural circuits responsible for social communication are among the least understood in the brain. Human studies have made great progress in advancing our understanding of the global computations required for processing speech, and animal models offer the opportunity to discover evolutionarily conserved mechanisms for decoding these signals. In this review article, we describe some of the most well-established speech decoding computations from human studies and describe animal research designed to reveal potential circuit mechanisms underlying these processes. Human and animal brains must perform the challenging tasks of rapidly recognizing, categorizing, and assigning communicative importance to sounds in a noisy environment. The instructions to these functions are found in the precise connections neurons make with one another. Therefore, identifying circuit-motifs in the auditory cortices and linking them to communicative functions is pivotal. We review recent advances in human recordings that have revealed the most basic unit of speech decoded by neurons is a phoneme, and consider circuit-mapping studies in rodents that have shown potential connectivity schemes to achieve this. Finally, we discuss other potentially important processing features in humans like lateralization, sensitivity to fine temporal features, and hierarchical processing. The goal is for animal studies to investigate neurophysiological and anatomical pathways responsible for establishing behavioral phenotypes that are shared between humans and animals. This can be accomplished by establishing cell types, connectivity patterns, genetic pathways and critical periods that are relevant in the development and function of social communication.

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“…Recent work has investigated the neural dynamics that support language and sensory processing [40][41][42] and how these dynamics may be altered in RD [36,43]. We integrate these emerging lines of research to propose that excess neural noise (Box 1) within cortical regions implicated in reading may be a distal contributor to RD.…”

Section: Premise Of the Neural Noise Hypothesismentioning

confidence: 99%

Neural Noise Hypothesis of Developmental Dyslexia

Hancock¹,

Pugh²,

Hoeft³

2017

Trends in Cognitive Sciences

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Developmental dyslexia (decoding-based reading disorder; RD) is a complex trait with multifactorial origins at the genetic, neural, and cognitive levels. There is evidence that low-level sensory-processing deficits precede and underlie phonological problems, which are one of the best-documented aspects of RD. RD is also associated with impairments in integrating visual symbols with their corresponding speech sounds. Although causal relationships between sensory processing, print-speech integration, and fluent reading, and their neural bases are debated, these processes all require precise timing mechanisms across distributed brain networks. Neural excitability and neural noise are fundamental to these timing mechanisms. Here, we propose that neural noise stemming from increased neural excitability in cortical networks implicated in reading is one key distal contributor to RD. Premise of the Neural Noise HypothesisDevelopmental dyslexia (specific reading disabilities/disorders, or decoding-based RD) is a neurodevelopmental disorder contributed to by multiple genetic, neural, and cognitive factors [1], yet neurobiological models that account for the diversity of RD phenotypes remain elusive. An increasing number of studies have investigated the function of RD risk genes in animal models [2][3][4][5][6][7][8][9][10][11][12][13], and the neurobiological and behavioral consequences of genetic RD risk variants in humans [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31], motivating the need for a synthesis of these findings, especially because they relate to emerging avenues of human research on the role of neurochemistry [32] and neural oscillations [33][34][35][36] in RD. Here, we present a timely integration of diverse lines of current research linking some of the key neural and behavioral deficits associated with RD to basic neural processes.A variety of neurobiological contributors to RD have been proposed, ranging from disrupted structural and functional connectivity [37,38] to atypical neural migration [39]. Recent work has investigated the neural dynamics that support language and sensory processing [40][41][42] and how these dynamics may be altered in RD [36,43]. We integrate these emerging lines of research to propose that excess neural noise (Box 1) within cortical regions implicated in reading may be a distal contributor to RD. We suggest that multifactorial sources of neural noise, for example arising from neural hyperexcitability related to RD risk genes, disrupt two key processes important for reading [phonological awareness [44] (see Glossary) and multisensory integration of visual symbols with their corresponding speech sounds [45,46]] through the impact of excess noise on neural synchrony and sensory representations (Figure 1). The neural noise hypothesis of RD synthesizes a range of neurobiological findings, providing a mechanistic framework for understanding the deficits observed in RD and identifying targets for systems-level intervention. While the potential for noisy proce...

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Temporal coding in the auditory cortex

Cited by 41 publications

References 104 publications

Neural Noise Hypothesis of Developmental Dyslexia

Neural Noise Hypothesis of Developmental Dyslexia

Using Neural Circuit Interrogation in Rodents to Unravel Human Speech Decoding

Neural Noise Hypothesis of Developmental Dyslexia

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