Neural decoding of emotional prosody in voice-sensitive auditory cortex predicts social communication abilities in children.

During social interactions, speakers signal information about their emotional state through their voice, which is known as emotional prosody. Little is known regarding the precise brain systems underlying emotional prosody decoding in children and whether accurate neural decoding of these vocal cues is linked to social skills. Here, we address critical gaps in the developmental literature by investigating neural representations of prosody and their links to behavior in children. Multivariate pattern analysis revealed that representations in the bilateral middle and posterior superior temporal sulcus (STS) divisions of voice-sensitive auditory cortex decode emotional prosody information in children. Crucially, emotional prosody decoding in middle STS was correlated with standardized measures of social communication abilities; more accurate decoding of prosody stimuli in the STS was predictive of greater social communication abilities in children. Moreover, social communication abilities were specifically related to decoding sadness, highlighting the importance of tuning in to negative emotional vocal cues for strengthening social responsiveness and functioning. Findings bridge an important theoretical gap by showing that the ability of the voice-sensitive cortex to detect emotional cues in speech is predictive of a child's social skills, including the ability to relate and interact with others.

A Neurodevelopmental Shift in Reward Circuitry from Mother's to Nonfamilial Voices in Adolescence.

The social worlds of young children primarily revolve around parents and caregivers, who play a key role in guiding children's social and cognitive development. However, a hallmark of adolescence is a shift in orientation toward nonfamilial social targets, an adaptive process that prepares adolescents for their independence. Little is known regarding neurobiological signatures underlying changes in adolescents' social orientation. Using functional brain imaging of human voice processing in children and adolescents (ages 7-16), we demonstrate distinct neural signatures for mother's voice and nonfamilial voices across child and adolescent development in reward and social valuation systems, instantiated in nucleus accumbens and ventromedial prefrontal cortex. While younger children showed greater activity in these brain systems for mother's voice compared with nonfamilial voices, older adolescents showed the opposite effect with increased activity for nonfamilial compared with mother's voice. Findings uncover a critical role for reward and social valuative brain systems in the pronounced changes in adolescents' orientation toward nonfamilial social targets. Our approach provides a template for examining developmental shifts in social reward and motivation in individuals with pronounced social impairments, including adolescents with autism.SIGNIFICANCE STATEMENT Children's social worlds undergo a transformation during adolescence. While socialization in young children revolves around parents and caregivers, adolescence is characterized by a shift in social orientation toward nonfamilial social partners. Here we show that this shift is reflected in neural activity measured from reward processing regions in response to brief vocal samples. When younger children hear their mother's voice, reward processing regions show greater activity compared with when they hear nonfamilial, unfamiliar voices. Strikingly, older adolescents show the opposite effect, with increased activity for nonfamilial compared with mother's voice. Findings identify the brain basis of adolescents' switch in social orientation toward nonfamilial social partners and provides a template for understanding neurodevelopment in clinical populations with social and communication difficulties.

Epidural labour analgesia and autism spectrum disorder: is the current evidence sufficient to dismiss an association?

Findings from a population-based study using a sibling-matched analysis published in this issue of the British Journal of Anaesthesia indicate that epidural labour analgesia is not associated with an increased risk of autism spectrum disorder. These findings are consistent with those from three other population-based studies that used similar methodological approaches. Cumulatively, these robust, high-quality epidemiological data support the assertion that there is no meaningful association between epidural labour analgesia and autism spectrum disorder in offspring.

Neural circuits underlying mother's voice perception predict social communication abilities in children.

The human voice is a critical social cue, and listeners are extremely sensitive to the voices in their environment. One of the most salient voices in a child's life is mother's voice: Infants discriminate their mother's voice from the first days of life, and this stimulus is associated with guiding emotional and social function during development. Little is known regarding the functional circuits that are selectively engaged in children by biologically salient voices such as mother's voice or whether this brain activity is related to children's social communication abilities. We used functional MRI to measure brain activity in 24 healthy children (mean age, 10.2 y) while they attended to brief (<1 s) nonsense words produced by their biological mother and two female control voices and explored relationships between speech-evoked neural activity and social function. Compared to female control voices, mother's voice elicited greater activity in primary auditory regions in the midbrain and cortex; voice-selective superior temporal sulcus (STS); the amygdala, which is crucial for processing of affect; nucleus accumbens and orbitofrontal cortex of the reward circuit; anterior insula and cingulate of the salience network; and a subregion of fusiform gyrus associated with face perception. The strength of brain connectivity between voice-selective STS and reward, affective, salience, memory, and face-processing regions during mother's voice perception predicted social communication skills. Our findings provide a novel neurobiological template for investigation of typical social development as well as clinical disorders, such as autism, in which perception of biologically and socially salient voices may be impaired.

Neural signatures of co-occurring reading and mathematical difficulties.

Impaired abilities in multiple domains is common in children with learning difficulties. Co-occurrence of low reading and mathematical abilities (LRLM) appears in almost every second child with learning difficulties. However, little is known regarding the neural bases of this combination. Leveraging a unique and tightly controlled sample including children with LRLM, isolated low reading ability (LR), and isolated low mathematical ability (LM), we uncover a distinct neural signature in children with co-occurring low reading and mathematical abilities differentiable from LR and LM. Specifically, we show that LRLM is neuroanatomically distinct from both LR and LM based on reduced cortical folding of the right parahippocampal gyrus, a medial temporal lobe region implicated in visual associative learning. LRLM children were further distinguished from LR and LM by patterns of intrinsic functional connectivity between parahippocampal gyrus and brain circuitry underlying reading and numerical quantity processing. Our results critically inform cognitive and neural models of LRLM by implicating aberrations in both domain-specific and domain-general brain regions involved in reading and mathematics. More generally, our results provide the first evidence for distinct multimodal neural signatures associated with LRLM, and suggest that this population displays an independent phenotype of learning difficulty that cannot be explained simply as a combination of isolated low reading and mathematical abilities.

Individual Differences in Human Auditory Processing: Insights From Single-Trial Auditory Midbrain Activity in an Animal Model.

Auditory-evoked potentials are classically defined as the summations of synchronous firing along the auditory neuraxis. Converging evidence supports a model whereby timing jitter in neural coding compromises listening and causes variable scalp-recorded potentials. Yet the intrinsic noise of human scalp recordings precludes a full understanding of the biological origins of individual differences in listening skills. To delineate the mechanisms contributing to these phenomena, in vivo extracellular activity was recorded from inferior colliculus in guinea pigs to speech in quiet and noise. Here we show that trial-by-trial timing jitter is a mechanism contributing to auditory response variability. Identical variability patterns were observed in scalp recordings in human children, implicating jittered timing as a factor underlying reduced coding of dynamic speech features and speech in noise. Moreover, intertrial variability in human listeners is tied to language development. Together, these findings suggest that variable timing in inferior colliculus blurs the neural coding of speech in noise, and propose a consequence of this timing jitter for human behavior. These results hint both at the mechanisms underlying speech processing in general, and at what may go awry in individuals with listening difficulties.

Brain State Differentiation and Behavioral Inflexibility in Autism.

Autism spectrum disorders (ASDs) are characterized by social impairments alongside cognitive and behavioral inflexibility. While social deficits in ASDs have extensively been characterized, the neurobiological basis of inflexibility and its relation to core clinical symptoms of the disorder are unknown. We acquired functional neuroimaging data from 2 cohorts, each consisting of 17 children with ASDs and 17 age- and IQ-matched typically developing (TD) children, during stimulus-evoked brain states involving performance of social attention and numerical problem solving tasks, as well as during intrinsic, resting brain states. Effective connectivity between key nodes of the salience network, default mode network, and central executive network was used to obtain indices of functional organization across evoked and intrinsic brain states. In both cohorts examined, a machine learning algorithm was able to discriminate intrinsic (resting) and evoked (task) functional brain network configurations more accurately in TD children than in children with ASD. Brain state discriminability was related to severity of restricted and repetitive behaviors, indicating that weak modulation of brain states may contribute to behavioral inflexibility in ASD. These findings provide novel evidence for a potential link between neurophysiological inflexibility and core symptoms of this complex neurodevelopmental disorder.

Underconnectivity between voice-selective cortex and reward circuitry in children with autism.

Individuals with autism spectrum disorders (ASDs) often show insensitivity to the human voice, a deficit that is thought to play a key role in communication deficits in this population. The social motivation theory of ASD predicts that impaired function of reward and emotional systems impedes children with ASD from actively engaging with speech. Here we explore this theory by investigating distributed brain systems underlying human voice perception in children with ASD. Using resting-state functional MRI data acquired from 20 children with ASD and 19 age- and intelligence quotient-matched typically developing children, we examined intrinsic functional connectivity of voice-selective bilateral posterior superior temporal sulcus (pSTS). Children with ASD showed a striking pattern of underconnectivity between left-hemisphere pSTS and distributed nodes of the dopaminergic reward pathway, including bilateral ventral tegmental areas and nucleus accumbens, left-hemisphere insula, orbitofrontal cortex, and ventromedial prefrontal cortex. Children with ASD also showed underconnectivity between right-hemisphere pSTS, a region known for processing speech prosody, and the orbitofrontal cortex and amygdala, brain regions critical for emotion-related associative learning. The degree of underconnectivity between voice-selective cortex and reward pathways predicted symptom severity for communication deficits in children with ASD. Our results suggest that weak connectivity of voice-selective cortex and brain structures involved in reward and emotion may impair the ability of children with ASD to experience speech as a pleasurable stimulus, thereby impacting language and social skill development in this population. Our study provides support for the social motivation theory of ASD.

Multivariate activation and connectivity patterns discriminate speech intelligibility in Wernicke's, Broca's, and Geschwind's areas.

The brain network underlying speech comprehension is usually described as encompassing fronto-temporal-parietal regions while neuroimaging studies of speech intelligibility have focused on a more spatially restricted network dominated by the superior temporal cortex. Here we use functional magnetic resonance imaging with a novel whole-brain multivariate pattern analysis (MVPA) to more fully characterize neural responses and connectivity to intelligible speech. Consistent with previous univariate findings, intelligible speech elicited greater activity in bilateral superior temporal cortex relative to unintelligible speech. However, MVPA identified a more extensive network that discriminated between intelligible and unintelligible speech, including left-hemisphere middle temporal gyrus, angular gyrus, inferior temporal cortex, and inferior frontal gyrus pars triangularis. These fronto-temporal-parietal areas also showed greater functional connectivity during intelligible, compared with unintelligible, speech. Our results suggest that speech intelligibly is encoded by distinct fine-grained spatial representations and within-task connectivity, rather than differential engagement or disengagement of brain regions, and they provide a more complete view of the brain network serving speech comprehension. Our findings bridge a divide between neural models of speech comprehension and the neuroimaging literature on speech intelligibility, and suggest that speech intelligibility relies on differential multivariate response and connectivity patterns in Wernicke's, Broca's, and Geschwind's areas.

Atypical pattern separation memory and its association with restricted interests and repetitive behaviors in autistic children.

LAY ABSTRACT: Memory challenges remain understudied in childhood autism. Our study investigates one specific aspect of memory function, known as pattern separation memory, in autistic children. Pattern separation memory refers to the critical ability to store unique memories of similar stimuli; however, its role in childhood autism remains largely uncharted. Our study first uncovered that the pattern separation memory was significantly reduced in autistic children, and then showed that reduced memory performance was linked to their symptoms of repetitive, restricted interest and behavior. We also identified distinct subgroups with profiles of reduced and increased generalization for pattern separation memory. More than 72% of autistic children showed a tendency to reduce memory generalization, focusing heavily on unique details of objects for memorization. This focus made it challenging for them to identify commonalities across similar entities. Interestingly, a smaller proportion of autistic children displayed an opposite pattern of increased generalization, marked by challenges in differentiating between similar yet distinct objects. Our findings advance the understanding of memory function in autism and have practical implications for devising personalized learning strategies that align with the unique memory patterns exhibited by autistic children. This study will be of broad interest to researchers in psychology, psychiatry, and brain development as well as teachers, parents, clinicians, and the wider public.

Inter-subject synchronization of brain responses during natural music listening.

Music is a cultural universal and a rich part of the human experience. However, little is known about common brain systems that support the processing and integration of extended, naturalistic 'real-world' music stimuli. We examined this question by presenting extended excerpts of symphonic music, and two pseudomusical stimuli in which the temporal and spectral structure of the Natural Music condition were disrupted, to non-musician participants undergoing functional brain imaging and analysing synchronized spatiotemporal activity patterns between listeners. We found that music synchronizes brain responses across listeners in bilateral auditory midbrain and thalamus, primary auditory and auditory association cortex, right-lateralized structures in frontal and parietal cortex, and motor planning regions of the brain. These effects were greater for natural music compared to the pseudo-musical control conditions. Remarkably, inter-subject synchronization in the inferior colliculus and medial geniculate nucleus was also greater for the natural music condition, indicating that synchronization at these early stages of auditory processing is not simply driven by spectro-temporal features of the stimulus. Increased synchronization during music listening was also evident in a right-hemisphere fronto-parietal attention network and bilateral cortical regions involved in motor planning. While these brain structures have previously been implicated in various aspects of musical processing, our results are the first to show that these regions track structural elements of a musical stimulus over extended time periods lasting minutes. Our results show that a hierarchical distributed network is synchronized between individuals during the processing of extended musical sequences, and provide new insight into the temporal integration of complex and biologically salient auditory sequences.

Aberrant Emotional Prosody Circuitry Predicts Social Communication Impairments in Children With Autism.

BACKGROUND: Emotional prosody provides acoustical cues that reflect a communication partner's emotional state and is crucial for successful social interactions. Many children with autism have deficits in recognizing emotions from voices; however, the neural basis for these impairments is unknown. We examined brain circuit features underlying emotional prosody processing deficits and their relationship to clinical symptoms of autism. METHODS: We used an event-related functional magnetic resonance imaging task to measure neural activity and connectivity during processing of sad and happy emotional prosody and neutral speech in 22 children with autism and 21 matched control children (7-12 years old). We employed functional connectivity analyses to test competing theoretical accounts that attribute emotional prosody impairments to either sensory processing deficits in auditory cortex or theory of mind deficits instantiated in the temporoparietal junction (TPJ). RESULTS: Children with autism showed specific behavioral impairments for recognizing emotions from voices. They also showed aberrant functional connectivity between voice-sensitive auditory cortex and the bilateral TPJ during emotional prosody processing. Neural activity in the bilateral TPJ during processing of both sad and happy emotional prosody stimuli was associated with social communication impairments in children with autism. In contrast, activity and decoding of emotional prosody in auditory cortex was comparable between autism and control groups and did not predict social communication impairments. CONCLUSIONS: Our findings support a social-cognitive deficit model of autism by identifying a role for TPJ dysfunction during emotional prosody processing. Our study underscores the importance of tuning in to vocal-emotional cues for building social connections in children with autism.

Atypical cognitive training-induced learning and brain plasticity and their relation to insistence on sameness in children with autism.

Children with autism spectrum disorders (ASD) often display atypical learning styles, however little is known regarding learning-related brain plasticity and its relation to clinical phenotypic features. Here, we investigate cognitive learning and neural plasticity using functional brain imaging and a novel numerical problem-solving training protocol. Children with ASD showed comparable learning relative to typically developing children but were less likely to shift from rule-based to memory-based strategy. Critically, while learning gains in typically developing children were associated with greater plasticity of neural representations in the medial temporal lobe and intraparietal sulcus, learning in children with ASD was associated with more stable neural representations. Crucially, the relation between learning and plasticity of neural representations was moderated by insistence on sameness, a core phenotypic feature of ASD. Our study uncovers atypical cognitive and neural mechanisms underlying learning in children with ASD, and informs pedagogical strategies for nurturing cognitive abilities in childhood autism.

Atypical cognitive training-induced learning and brain plasticity and their relation to insistence on sameness in children with autism.

Children with autism spectrum disorders (ASDs) often display atypical learning styles; however, little is known regarding learning-related brain plasticity and its relation to clinical phenotypic features. Here, we investigate cognitive learning and neural plasticity using functional brain imaging and a novel numerical problem-solving training protocol. Children with ASD showed comparable learning relative to typically developing children but were less likely to shift from rule-based to memory-based strategy. While learning gains in typically developing children were associated with greater plasticity of neural representations in the medial temporal lobe and intraparietal sulcus, learning in children with ASD was associated with more stable neural representations. Crucially, the relation between learning and plasticity of neural representations was moderated by insistence on sameness, a core phenotypic feature of ASD. Our study uncovers atypical cognitive and neural mechanisms underlying learning in children with ASD, and informs pedagogical strategies for nurturing cognitive abilities in childhood autism.

Replicable Patterns of Memory Impairments in Children With Autism and Their Links to Hyperconnected Brain Circuits.

BACKGROUND: Memory impairments have profound implications for social communication and educational outcomes in children with autism spectrum disorder (ASD). However, the precise nature of memory dysfunction in children with ASD and the underlying neural circuit mechanisms remain poorly understood. The default mode network (DMN) is a brain network that is associated with memory and cognitive function, and DMN dysfunction is among the most replicable and robust brain signatures of ASD. METHODS: We used a comprehensive battery of standardized episodic memory assessments and functional circuit analyses in 25 8- to 12-year-old children with ASD and 29 matched typically developing control children. RESULTS: Memory performance was reduced in children with ASD compared with control children. General and face memory emerged as distinct dimensions of memory difficulties in ASD. Importantly, findings of diminished episodic memory in children with ASD were replicated in 2 independent data sets. Analysis of intrinsic functional circuits associated with the DMN revealed that general and face memory deficits were associated with distinct, hyperconnected circuits: Aberrant hippocampal connectivity predicted diminished general memory while aberrant posterior cingulate cortex connectivity predicted diminished face memory. Notably, aberrant hippocampal-posterior cingulate cortex circuitry was a common feature of diminished general and face memory in ASD. CONCLUSIONS: Our results represent a comprehensive appraisal of episodic memory function in children with ASD and identify extensive and replicable patterns of memory reductions in children with ASD that are linked to dysfunction of distinct DMN-related circuits. These findings highlight a role for DMN dysfunction in ASD that extends beyond face memory to general memory function.

Decoding temporal structure in music and speech relies on shared brain resources but elicits different fine-scale spatial patterns.

Music and speech are complex sound streams with hierarchical rules of temporal organization that become elaborated over time. Here, we use functional magnetic resonance imaging to measure brain activity patterns in 20 right-handed nonmusicians as they listened to natural and temporally reordered musical and speech stimuli matched for familiarity, emotion, and valence. Heart rate variability and mean respiration rates were simultaneously measured and were found not to differ between musical and speech stimuli. Although the same manipulation of temporal structure elicited brain activation level differences of similar magnitude for both music and speech stimuli, multivariate classification analysis revealed distinct spatial patterns of brain responses in the 2 domains. Distributed neuronal populations that included the inferior frontal cortex, the posterior and anterior superior and middle temporal gyri, and the auditory brainstem classified temporal structure manipulations in music and speech with significant levels of accuracy. While agreeing with previous findings that music and speech processing share neural substrates, this work shows that temporal structure in the 2 domains is encoded differently, highlighting a fundamental dissimilarity in how the same neural resources are deployed.

Mothers adapt their voice during children's adolescent development.

Mothers alter their speech in a stereotypical manner when addressing infants using high pitch, a wide pitch range, and distinct timbral features. Mothers reduce their vocal pitch after early childhood; however, it is not known whether mother's voice changes through adolescence as children become increasingly independent from their parents. Here we investigate the vocal acoustics of 50 mothers of older children (ages 7-16) to determine: (1) whether pitch changes associated with child-directed speech decrease with age; (2) whether other acoustical features associated with child-directed speech change with age; and, (3) the relative contribution of acoustical features in predicting child's age. Results reveal that mothers of older children used lower pitched voices than mothers of younger children, and mother's voice pitch height predicted their child's age. Crucially, these effects were present after controlling for mother's age, accounting for aging-related pitch reductions. Brightness, a timbral feature correlated with pitch height, also showed an inverse relation with child's age but did not improve prediction of child's age beyond that accounted for by pitch height. Other acoustic features did not predict child age. Findings suggest that mother's voice adapts to match their child's developmental progression into adolescence and this adaptation is independent of mother's age.

Abnormal cortical processing of the syllable rate of speech in poor readers.

Children with reading impairments have long been associated with impaired perception for rapidly presented acoustic stimuli and recently have shown deficits for slower features. It is not known whether impairments for low-frequency acoustic features negatively impact processing of speech in reading-impaired individuals. Here we provide neurophysiological evidence that poor readers have impaired representation of the speech envelope, the acoustical cue that provides syllable pattern information in speech. We measured cortical-evoked potentials in response to sentence stimuli and found that good readers indicated consistent right-hemisphere dominance in auditory cortex for all measures of speech envelope representation, including the precision, timing, and magnitude of cortical responses. Poor readers showed abnormal patterns of cerebral asymmetry for all measures of speech envelope representation. Moreover, cortical measures of speech envelope representation predicted up to 41% of the variability in standardized reading scores and 50% in measures of phonological processing across a wide range of abilities. Our findings strongly support a relationship between acoustic-level processing and higher-level language abilities, and are the first to link reading ability with cortical processing of low-frequency acoustic features in the speech signal. Our results also support the hypothesis that asymmetric routing between cerebral hemispheres represents an important mechanism for temporal encoding in the human auditory system, and the need for an expansion of the temporal processing hypothesis for reading disabilities to encompass impairments for a wider range of speech features than previously acknowledged.

Sparse logistic regression for whole-brain classification of fMRI data.

Multivariate pattern recognition methods are increasingly being used to identify multiregional brain activity patterns that collectively discriminate one cognitive condition or experimental group from another, using fMRI data. The performance of these methods is often limited because the number of regions considered in the analysis of fMRI data is large compared to the number of observations (trials or participants). Existing methods that aim to tackle this dimensionality problem are less than optimal because they either over-fit the data or are computationally intractable. Here, we describe a novel method based on logistic regression using a combination of L1 and L2 norm regularization that more accurately estimates discriminative brain regions across multiple conditions or groups. The L1 norm, computed using a fast estimation procedure, ensures a fast, sparse and generalizable solution; the L2 norm ensures that correlated brain regions are included in the resulting solution, a critical aspect of fMRI data analysis often overlooked by existing methods. We first evaluate the performance of our method on simulated data and then examine its effectiveness in discriminating between well-matched music and speech stimuli. We also compared our procedures with other methods which use either L1-norm regularization alone or support vector machine-based feature elimination. On simulated data, our methods performed significantly better than existing methods across a wide range of contrast-to-noise ratios and feature prevalence rates. On experimental fMRI data, our methods were more effective in selectively isolating a distributed fronto-temporal network that distinguished between brain regions known to be involved in speech and music processing. These findings suggest that our method is not only computationally efficient, but it also achieves the twin objectives of identifying relevant discriminative brain regions and accurately classifying fMRI data.