Emergence of prediction error along the human auditory hierarchy

Font-Alaminos, Marta; Ribas-Prats, Teresa; Gorina-Careta, Natàlia; Escera, Carles

doi:10.1016/j.heares.2020.107954

Cited by 12 publications

(11 citation statements)

References 75 publications

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“…Thus, while P1 emerged as a potential marker of learning in both conditions, the FFR and P2 emerged only in the easier condition where learning was robust across participants. Our findings converge with other work to suggest that predictive coding occurs both cortically and subcortically but that it varies in its representation across brainstem and different cortical regions (Nieto-Diego and Malmierca, 2016;Font-Alaminos et al, 2021), and that it reflects long-term experience with sound that involves complex computations that go beyond low-level stimulus characteristics like inter-tone TPs (Kraus, 2021). Our constellation of findings also paints a complex picture of the possible timeline and top-down directionality of auditory network changes during rapid learning and they support the idea that learning emerge from multi-level representations of stimulus coding (Carbajal and Malmierca, 2018).…”

Section: Discussionsupporting

confidence: 91%

“…Here we focus on both. To study the neural correlates of rapid pattern learning we coupled behavioral measures of learning with electroencephalogram (EEG) recordings, using an approach that allowed us to extract cortical and subcortical activity from the same EEG recording (Font-Alaminos et al, 2021). EEG was recorded while adult humans passively listened to continuous sequences comprised of eight musical tones (C4, D4, E4, F4, F#4, G4, G#4, and A4) ranging in fundamental frequency (F0) (262-440 Hz).…”

Section: Introductionmentioning

confidence: 99%

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Auditory Cortical Changes Precede Brainstem Changes During Rapid Implicit Learning: Evidence From Human EEG

et al. 2021

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The auditory system is sensitive to stimulus regularities such as frequently occurring sounds and sound combinations. Evidence of regularity detection can be seen in how neurons across the auditory network, from brainstem to cortex, respond to the statistical properties of the soundscape, and in the rapid learning of recurring patterns in their environment by children and adults. Although rapid auditory learning is presumed to involve functional changes to the auditory network, the chronology and directionality of changes are not well understood. To study the mechanisms by which this learning occurs, auditory brainstem and cortical activity was simultaneously recorded via electroencephalogram (EEG) while young adults listened to novel sound streams containing recurring patterns. Neurophysiological responses were compared between easier and harder learning conditions. Collectively, the behavioral and neurophysiological findings suggest that cortical and subcortical structures each provide distinct contributions to auditory pattern learning, but that cortical sensitivity to stimulus patterns likely precedes subcortical sensitivity.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Auditory Cortical Changes Precede Brainstem Changes During Rapid Implicit Learning: Evidence From Human EEG

et al. 2021

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“…[1,4,39,40]), they have not been reported in subcortical nuclei to-date. Our study breaks with a long tradition on research on subcortical SSA [7,[9][10][11][12][13][14][15][16][17][18][19][20][41][42][43][44][45] by defining the predictions based on abstract rules that were orthogonal to the regularity of the stimulus local statistics. Only one study attempted to investigate the impact of abstract rules on SSA using alternating tone sequences in anaesthetised rats [5].…”

Section: Discussionmentioning

confidence: 98%

“…Several previous studies have interpreted response properties of subcortical sensory nuclei within a predictive coding framework [6][7][8]18,19,23]. These studies have , however, used designs were predictions were generated based on the regularities of the local stimulus statistics.…”

Section: Discussionmentioning

confidence: 99%

“…In the auditory modality, SSA is typically elicited using sequences consisting of repetitions of a standard sound (typically a pure tone of a given frequency) incorporating a single, randomly located, deviant (a pure tone of the same duration and loudness but with a different frequency). Although SSA is often taken to support the view of predictive coding [6,8,18,19], it can also be explained in terms of habituation [24], where neurons show decreased responsiveness to increased regularities in their local statistics independently of their predictability (see [4,25] for reviews). These local effects have been proposed to be caused by synaptic fatigue [26], network habituation [27,28], or sharpening of the receptive fields after stimulus repetition [25]; they occur even at the level of the retina [29] and the cochlea [30].…”

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confidence: 99%

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Abstract rules drive adaptation in the subcortical sensory pathway

Tabas

Mihai

Kiebel

et al. 2020

eLife

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The subcortical sensory pathways are the fundamental channels for mapping the outside world to our minds. Sensory pathways efficiently transmit information by adapting neural responses to the local statistics of the sensory input. The long-standing mechanistic explanation for this adaptive behaviour is that neural activity decreases with increasing regularities in the local statistics of the stimuli. An alternative account is that neural coding is directly driven by expectations of the sensory input. Here, we used abstract rules to manipulate expectations independently of local stimulus statistics. The ultra-high-field functional-MRI data show that abstract expectations can drive the response amplitude to tones in the human auditory pathway. These results provide first unambiguous evidence of abstract processing in a subcortical sensory pathway. They indicate that the neural representation of the outside world is altered by our prior beliefs even at initial points of the processing hierarchy.

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What Do Mismatch Negativity (MMN) Responses Tell Us About Tinnitus?

Yukhnovich,

Alter,

Sedley

2024

JARO

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Due to the heterogeneous causes, symptoms and associated comorbidities with tinnitus, there remains an unmet need for a clear biomarker of tinnitus presence. Previous research has suggested a “final pathway” of tinnitus presence, which occurs regardless of the specific mechanisms that resulted in alterations of auditory predictions and, eventually, tinnitus perception. Predictive inference mechanisms have been proposed as the possible basis for this final unifying pathway. A commonly used measure of prediction violation is mismatch negativity (MMN), an electrical potential generated in response to most stimuli that violate an established regularity. This narrative review discusses 16 studies comparing MMN between tinnitus and non-tinnitus groups. Methods varied considerably, including type of deviant, type of paradigm and carrier frequency. A minority of studies matched groups for age, sex and hearing, with few measuring hyperacusis. Frequency deviants were the most widely studied; at frequencies remote from tinnitus, MMN was consistently smaller in tinnitus groups, though hyperacusis or altered distress or attention could not be ruled out as explanatory factors. Few studies have used tinnitus-related frequencies; these showed larger MMN to upward frequency deviants above the tinnitus frequency, and larger MMN to upward intensity deviants at or close to the tinnitus frequency. However, the latter appears a correlate of hyperacusis rather than tinnitus, and tinnitus groups without hyperacusis instead show larger MMN to downward intensity deviants than controls. Other factors that affect MMN amplitudes included age, attention, and the specific characteristics of the range of stimuli across a particular experiment paradigm. As such, MMN cannot presently be considered a specific biomarker of tinnitus, but showed potential to objectively characterise a number of auditory processing traits relevant to tinnitus and hyperacusis.

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Emergence of prediction error along the human auditory hierarchy

Cited by 12 publications

References 75 publications

Auditory Cortical Changes Precede Brainstem Changes During Rapid Implicit Learning: Evidence From Human EEG

Auditory Cortical Changes Precede Brainstem Changes During Rapid Implicit Learning: Evidence From Human EEG

Abstract rules drive adaptation in the subcortical sensory pathway

What Do Mismatch Negativity (MMN) Responses Tell Us About Tinnitus?

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