Learning letters in adulthood: direct visualization of cortical plasticity for forming a new link between orthography and phonology

To identify which brain regions in adults show plasticity for learning letters, Hangul letters were experimentally associated with either speech sounds (HS condition) or nonspeech sounds (HN condition) in fMRI sessions over two consecutive days. Selective activations under the HS condition were found in several regions including the left posterior inferior temporal gyrus (PITG) and the parieto-occipital cortex (PO), as compared with activations under a condition for familiar letters and speech sounds, and with those under the HN condition. The left PITG showed a selective activation increase under the HS condition over two days, the degree of which predicted individual performance improvement. Further, functional connectivity between the left PITG and the left PO was selectively enhanced under the HS condition. These results demonstrate that a new link between orthography and phonology is formed by the plasticity of a functional system involving the left PITG in association with the left PO.     

The mismatch negativity as an index of the perception of speech sounds by the human brain

The present article outlines the contribution of the mismatch negativity (MMN), and its magnetic equivalent MMNm, to our understanding of the perception of speech sounds in the human brain. MMN data indicate that each sound, both speech and non-speech, develops its neural representation corresponding to the percept of this sound in the neurophysiological substrate of auditory sensory memory. The accuracy of this representation, determining the accuracy of the discrimination between different sounds, can be probed with MMN separately for any auditory feature or stimulus type such as phonemes. Furthermore, MMN data show that the perception of phonemes, and probably also of larger linguistic units (syllables and words), is based on language-specific phonetic traces developed in the posterior part of the left-hemisphere auditory cortex. These traces serve as recognition models for the corresponding speech sounds in listening to speech.     

Listening to speech in the presence of other sounds

Although most research on the perception of speech has been conducted with speech presented without any competing sounds, we almost always listen to speech against a background of other sounds which we are adept at ignoring. Nevertheless, such additional irrelevant sounds can cause severe problems for speech recognition algorithms and for the hard of hearing as well as posing a challenge to theories of speech perception. A variety of different problems are created by the presence of additional sound sources: detection of features that are partially masked, allocation of detected features to the appropriate sound sources and recognition of sounds on the basis of partial information. The separation of sounds is arousing substantial attention in psychoacoustics and in computer science. An effective solution to the problem of separating sounds would have important practical applications.     

Early specialization for voice and emotion processing in the infant brain

Human voices play a fundamental role in social communication, and areas of the adult "social brain" show specialization for processing voices and their emotional content (superior temporal sulcus, inferior prefrontal cortex, premotor cortical regions, amygdala, and insula). However, it is unclear when this specialization develops. Functional magnetic resonance (fMRI) studies suggest that the infant temporal cortex does not differentiate speech from music or backward speech, but a prior study with functional near-infrared spectroscopy revealed preferential activation for human voices in 7-month-olds, in a more posterior location of the temporal cortex than in adults. However, the brain networks involved in processing nonspeech human vocalizations in early development are still unknown. To address this issue, in the present fMRI study, 3- to 7-month-olds were presented with adult nonspeech vocalizations (emotionally neutral, emotionally positive, and emotionally negative) and nonvocal environmental sounds. Infants displayed significant differential activation in the anterior portion of the temporal cortex, similarly to adults. Moreover, sad vocalizations modulated the activity of brain regions involved in processing affective stimuli such as the orbitofrontal cortex and insula. These results suggest remarkably early functional specialization for processing human voice and negative emotions.     

Encoding of Natural Sounds at Multiple Spectral and Temporal Resolutions in the Human Auditory Cortex

Functional neuroimaging research provides detailed observations of the response patterns that natural sounds (e.g. human voices and speech, animal cries, environmental sounds) evoke in the human brain. The computational and representational mechanisms underlying these observations, however, remain largely unknown. Here we combine high spatial resolution (3 and 7 Tesla) functional magnetic resonance imaging (fMRI) with computational modeling to reveal how natural sounds are represented in the human brain. We compare competing models of sound representations and select the model that most accurately predicts fMRI response patterns to natural sounds. Our results show that the cortical encoding of natural sounds entails the formation of multiple representations of sound spectrograms with different degrees of spectral and temporal resolution. The cortex derives these multi-resolution representations through frequency-specific neural processing channels and through the combined analysis of the spectral and temporal modulations in the spectrogram. Furthermore, our findings suggest that a spectral-temporal resolution trade-off may govern the modulation tuning of neuronal populations throughout the auditory cortex. Specifically, our fMRI results suggest that neuronal populations in posterior/dorsal auditory regions preferably encode coarse spectral information with high temporal precision. Vice-versa, neuronal populations in anterior/ventral auditory regions preferably encode fine-grained spectral information with low temporal precision. We propose that such a multi-resolution analysis may be crucially relevant for flexible and behaviorally-relevant sound processing and may constitute one of the computational underpinnings of functional specialization in auditory cortex.     

The role of premotor cortex in speech perception: evidence from fMRI and rTMS.

This article discusses recent functional magnetic resonance imaging (fMRI) and repetitive Transcranial Magnetic Stimulation (rTMS) data that suggest a direct involvement of premotor cortical areas in speech perception. These new data map well onto psychological theories advocating an active role of motor structures in the perception of speech sounds. It is proposed that the perception of speech is enabled--at least in part--by a process that simulates speech production.     

Phase patterns of neuronal responses reliably discriminate speech in human auditory cortex

How natural speech is represented in the auditory cortex constitutes a major challenge for cognitive neuroscience. Although many single-unit and neuroimaging studies have yielded valuable insights about the processing of speech and matched complex sounds, the mechanisms underlying the analysis of speech dynamics in human auditory cortex remain largely unknown. Here, we show that the phase pattern of theta band (4-8 Hz) responses recorded from human auditory cortex with magnetoencephalography (MEG) reliably tracks and discriminates spoken sentences and that this discrimination ability is correlated with speech intelligibility. The findings suggest that an approximately 200 ms temporal window (period of theta oscillation) segments the incoming speech signal, resetting and sliding to track speech dynamics. This hypothesized mechanism for cortical speech analysis is based on the stimulus-induced modulation of inherent cortical rhythms and provides further evidence implicating the syllable as a computational primitive for the representation of spoken language.     

Basic auditory processes involved in the analysis of speech sounds

This paper reviews the basic aspects of auditory processing that play a role in the perception of speech. The frequency selectivity of the auditory system, as measured using masking experiments, is described and used to derive the internal representation of the spectrum (the excitation pattern) of speech sounds. The perception of timbre and distinctions in quality between vowels are related to both static and dynamic aspects of the spectra of sounds. The perception of pitch and its role in speech perception are described. Measures of the temporal resolution of the auditory system are described and a model of temporal resolution based on a sliding temporal integrator is outlined. The combined effects of frequency and temporal resolution can be modelled by calculation of the spectro-temporal excitation pattern, which gives good insight into the internal representation of speech sounds. For speech presented in quiet, the resolution of the auditory system in frequency and time usually markedly exceeds the resolution necessary for the identification or discrimination of speech sounds, which partly accounts for the robust nature of speech perception. However, for people with impaired hearing, speech perception is often much less robust.     

A Synchrony-Dependent Influence of Sounds on Activity in Visual Cortex Measured Using Functional Near-Infrared Spectroscopy (fNIRS)

Evidence from human neuroimaging and animal electrophysiological studies suggests that signals from different sensory modalities interact early in cortical processing, including in primary sensory cortices. The present study aimed to test whether functional near-infrared spectroscopy (fNIRS), an emerging, non-invasive neuroimaging technique, is capable of measuring such multisensory interactions. Specifically, we tested for a modulatory influence of sounds on activity in visual cortex, while varying the temporal synchrony between trains of transient auditory and visual events. Related fMRI studies have consistently reported enhanced activation in response to synchronous compared to asynchronous audiovisual stimulation. Unexpectedly, we found that synchronous sounds significantly reduced the fNIRS response from visual cortex, compared both to asynchronous sounds and to a visual-only baseline. It is possible that this suppressive effect of synchronous sounds reflects the use of an efficacious visual stimulus, chosen for consistency with previous fNIRS studies. Discrepant results may also be explained by differences between studies in how attention was deployed to the auditory and visual modalities. The presence and relative timing of sounds did not significantly affect performance in a simultaneously conducted behavioral task, although the data were suggestive of a positive relationship between the strength of the fNIRS response from visual cortex and the accuracy of visual target detection. Overall, the present findings indicate that fNIRS is capable of measuring multisensory cortical interactions. In multisensory research, fNIRS can offer complementary information to the more established neuroimaging modalities, and may prove advantageous for testing in naturalistic environments and with infant and clinical populations.     

Reconstructing speech from human auditory cortex

How the human auditory system extracts perceptually relevant acoustic features of speech is unknown. To address this question, we used intracranial recordings from nonprimary auditory cortex in the human superior temporal gyrus to determine what acoustic information in speech sounds can be reconstructed from population neural activity. We found that slow and intermediate temporal fluctuations, such as those corresponding to syllable rate, were accurately reconstructed using a linear model based on the auditory spectrogram. However, reconstruction of fast temporal fluctuations, such as syllable onsets and offsets, required a nonlinear sound representation based on temporal modulation energy. Reconstruction accuracy was highest within the range of spectro-temporal fluctuations that have been found to be critical for speech intelligibility. The decoded speech representations allowed readout and identification of individual words directly from brain activity during single trial sound presentations. These findings reveal neural encoding mechanisms of speech acoustic parameters in higher order human auditory cortex.     

Functional imaging reveals numerous fields in the monkey auditory cortex

Anatomical studies propose that the primate auditory cortex contains more fields than have actually been functionally confirmed or described. Spatially resolved functional magnetic resonance imaging (fMRI) with carefully designed acoustical stimulation could be ideally suited to extend our understanding of the processing within these fields. However, after numerous experiments in humans, many auditory fields remain poorly characterized. Imaging the macaque monkey is of particular interest as these species have a richer set of anatomical and neurophysiological data to clarify the source of the imaged activity. We functionally mapped the auditory cortex of behaving and of anesthetized macaque monkeys with high resolution fMRI. By optimizing our imaging and stimulation procedures, we obtained robust activity throughout auditory cortex using tonal and band-passed noise sounds. Then, by varying the frequency content of the sounds, spatially specific activity patterns were observed over this region. As a result, the activity patterns could be assigned to many auditory cortical fields, including those whose functional properties were previously undescribed. The results provide an extensive functional tessellation of the macaque auditory cortex and suggest that 11 fields contain neurons tuned for the frequency of sounds. This study provides functional support for a model where three fields in primary auditory cortex are surrounded by eight neighboring “belt” fields in non-primary auditory cortex. The findings can now guide neurophysiological recordings in the monkey to expand our understanding of the processing within these fields. Additionally, this work will improve fMRI investigations of the human auditory cortex.     

The essential role of premotor cortex in speech perception

Besides the involvement of superior temporal regions in processing complex speech sounds, evidence suggests that the motor system might also play a role [1-4]. This suggests that the hearer might perceive speech by simulating the articulatory gestures of the speaker [5, 6]. It is still an open question whether this simulation process is necessary for speech perception. We applied repetitive transcranial magnetic stimulation to the premotor cortex to disrupt subjects' ability to perform a phonetic discrimination task. Subjects were impaired in discriminating stop consonants in noise but were unaffected in a control task that was matched in difficulty, task structure, and response characteristics. These results show that the disruption of human premotor cortex impairs speech perception, thus demonstrating an essential role of premotor cortices in perceptual processes.     

An fMRI Study of Audiovisual Speech Perception Reveals Multisensory Interactions in Auditory Cortex

Research on the neural basis of speech-reading implicates a network of auditory language regions involving inferior frontal cortex, premotor cortex and sites along superior temporal cortex. In audiovisual speech studies, neural activity is consistently reported in posterior superior temporal Sulcus (pSTS) and this site has been implicated in multimodal integration. Traditionally, multisensory interactions are considered high-level processing that engages heteromodal association cortices (such as STS). Recent work, however, challenges this notion and suggests that multisensory interactions may occur in low-level unimodal sensory cortices. While previous audiovisual speech studies demonstrate that high-level multisensory interactions occur in pSTS, what remains unclear is how early in the processing hierarchy these multisensory interactions may occur. The goal of the present fMRI experiment is to investigate how visual speech can influence activity in auditory cortex above and beyond its response to auditory speech. In an audiovisual speech experiment, subjects were presented with auditory speech with and without congruent visual input. Holding the auditory stimulus constant across the experiment, we investigated how the addition of visual speech influences activity in auditory cortex. We demonstrate that congruent visual speech increases the activity in auditory cortex.     

Speech recognition by an artificial neural network using findings on the afferent auditory system

An artificial neural network which uses anatomical and physiological findings on the afferent pathway from the ear to the cortex is presented and the roles of the constituent functions in recognition of continuous speech are examined. The network deals with successive spectra of speech sounds by a cascade of several neural layers: lateral excitation layer (LEL), lateral inhibition layer (LIL), and a pile of feature detection layers (FDL's). These layers are shown to be effective for recognizing spoken words. Namely, first, LEL reduces the distortion of sound spectrum caused by the pitch of speech sounds. Next, LIL emphasizes the major energy peaks of sound spectrum, the formants. Last, FDL's detect syllables and words in successive formants, where two functions, time-delay and strong adaptation, play important roles: time-delay makes it possible to retain the pattern of formant changes for a period to detect spoken words successively; strong adaptation contributes to removing the time-warp of formant changes. Digital computer simulations show that the network detect isolated syllables, isolated words, and connected words in continuous speech, while reproducing the fundamental responses found in the auditory system such as ON, OFF, ON-OFF, and SUSTAINED patterns.     

Effective Cerebral Connectivity during Silent Speech Reading Revealed by Functional Magnetic Resonance Imaging

Seeing the articulatory gestures of the speaker (“speech reading”) enhances speech perception especially in noisy conditions. Recent neuroimaging studies tentatively suggest that speech reading activates speech motor system, which then influences superior-posterior temporal lobe auditory areas via an efference copy. Here, nineteen healthy volunteers were presented with silent videoclips of a person articulating Finnish vowels /a/, /i/ (non-targets), and /o/ (targets) during event-related functional magnetic resonance imaging (fMRI). Speech reading significantly activated visual cortex, posterior fusiform gyrus (pFG), posterior superior temporal gyrus and sulcus (pSTG/S), and the speech motor areas, including premotor cortex, parts of the inferior (IFG) and middle (MFG) frontal gyri extending into frontal polar (FP) structures, somatosensory areas, and supramarginal gyrus (SMG). Structural equation modelling (SEM) of these data suggested that information flows first from extrastriate visual cortex to pFS, and from there, in parallel, to pSTG/S and MFG/FP. From pSTG/S information flow continues to IFG or SMG and eventually somatosensory areas. Feedback connectivity was estimated to run from MFG/FP to IFG, and pSTG/S. The direct functional connection from pFG to MFG/FP and feedback connection from MFG/FP to pSTG/S and IFG support the hypothesis of prefrontal speech motor areas influencing auditory speech processing in pSTG/S via an efference copy.     

Familiarity with speech affects cortical processing of auditory distance cues and increases acuity

Several acoustic cues contribute to auditory distance estimation. Nonacoustic cues, including familiarity, may also play a role. We tested participants' ability to distinguish the distances of acoustically similar sounds that differed in familiarity. Participants were better able to judge the distances of familiar sounds. Electroencephalographic (EEG) recordings collected while participants performed this auditory distance judgment task revealed that several cortical regions responded in different ways depending on sound familiarity. Surprisingly, these differences were observed in auditory cortical regions as well as other cortical regions distributed throughout both hemispheres. These data suggest that learning about subtle, distance-dependent variations in complex speech sounds involves processing in a broad cortical network that contributes both to speech recognition and to how spatial information is extracted from speech.     

Development of Auditory-Vocal Perceptual Skills in Songbirds

Songbirds are one of the few groups of animals that learn the sounds used for vocal communication during development. Like humans, songbirds memorize vocal sounds based on auditory experience with vocalizations of adult “tutors”, and then use auditory feedback of self-produced vocalizations to gradually match their motor output to the memory of tutor sounds. In humans, investigations of early vocal learning have focused mainly on perceptual skills of infants, whereas studies of songbirds have focused on measures of vocal production. In order to fully exploit songbirds as a model for human speech, understand the neural basis of learned vocal behavior, and investigate links between vocal perception and production, studies of songbirds must examine both behavioral measures of perception and neural measures of discrimination during development. Here we used behavioral and electrophysiological assays of the ability of songbirds to distinguish vocal calls of varying frequencies at different stages of vocal learning. The results show that neural tuning in auditory cortex mirrors behavioral improvements in the ability to make perceptual distinctions of vocal calls as birds are engaged in vocal learning. Thus, separate measures of neural discrimination and behavioral perception yielded highly similar trends during the course of vocal development. The timing of this improvement in the ability to distinguish vocal sounds correlates with our previous work showing substantial refinement of axonal connectivity in cortico-basal ganglia pathways necessary for vocal learning.     

Degraded auditory processing in a rat model of autism limits the speech representation in non‐primary auditory cortex

Although individuals with autism are known to have significant communication problems, the cellular mechanisms responsible for impaired communication are poorly understood. Valproic acid (VPA) is an anticonvulsant that is a known risk factor for autism in prenatally exposed children. Prenatal VPA exposure in rats causes numerous neural and behavioral abnormalities that mimic autism. We predicted that VPA exposure may lead to auditory processing impairments which may contribute to the deficits in communication observed in individuals with autism. In this study, we document auditory cortex responses in rats prenatally exposed to VPA. We recorded local field potentials and multiunit responses to speech sounds in primary auditory cortex, anterior auditory field, ventral auditory field. and posterior auditory field in VPA exposed and control rats. Prenatal VPA exposure severely degrades the precise spatiotemporal patterns evoked by speech sounds in secondary, but not primary auditory cortex. This result parallels findings in humans and suggests that secondary auditory fields may be more sensitive to environmental disturbances and may provide insight into possible mechanisms related to auditory deficits in individuals with autism. © 2014 Wiley Periodicals, Inc. Develop Neurobiol 74: 972–986, 2014     

Auditory physiology: cortical assistance for the auditory signals-to-symbols transformation

How the temporal information that is crucial for understanding speech and music is processed in the brain is poorly understood, but a new study shows how the auditory cortex is tuned to the spectro-temporal acoustic features characteristic of natural biological sounds.     

Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus

We have developed a sparse mathematical representation of speech that minimizes the number of active model neurons needed to represent typical speech sounds. The model learns several well-known acoustic features of speech such as harmonic stacks, formants, onsets and terminations, but we also find more exotic structures in the spectrogram representation of sound such as localized checkerboard patterns and frequency-modulated excitatory subregions flanked by suppressive sidebands. Moreover, several of these novel features resemble neuronal receptive fields reported in the Inferior Colliculus (IC), as well as auditory thalamus and cortex, and our model neurons exhibit the same tradeoff in spectrotemporal resolution as has been observed in IC. To our knowledge, this is the first demonstration that receptive fields of neurons in the ascending mammalian auditory pathway beyond the auditory nerve can be predicted based on coding principles and the statistical properties of recorded sounds.