Daniel A. Abrams

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.

Right-Hemisphere Auditory Cortex Is Dominant for Coding Syllable Patterns in Speech

Cortical analysis of speech has long been considered the domain of left-hemisphere auditory areas. A recent hypothesis poses that cortical processing of acoustic signals, including speech, is mediated bilaterally based on the component rates inherent to the speech signal. In support of this hypothesis, previous studies have shown that slow temporal features (3–5 Hz) in nonspeech acoustic signals lateralize to right-hemisphere auditory areas, whereas rapid temporal features (20–50 Hz) lateralize to the left hemisphere. These results were obtained using nonspeech stimuli, and it is not known whether right-hemisphere auditory cortex is dominant for coding the slow temporal features in speech known as the speech envelope. Here we show strong right-hemisphere dominance for coding the speech envelope, which represents syllable patterns and is critical for normal speech perception. Right-hemisphere auditory cortex was 100% more accurate in following contours of the speech envelope and had a 33% larger response magnitude while following the envelope compared with the left hemisphere. Asymmetries were evident regardless of the ear of stimulation despite dominance of contralateral connections in ascending auditory pathways. Results provide evidence that the right hemisphere plays a specific and important role in speech processing and support the hypothesis that acoustic processing of speech involves the decomposition of the signal into constituent temporal features by rate-specialized neurons in right- and left-hemisphere auditory cortex.

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.

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.

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.

Auditory brainstem timing predicts cerebral asymmetry for speech.

The left hemisphere of the human cerebral cortex is dominant for processing rapid acoustic stimuli, including speech, and this specialized activity is preceded by processing in the auditory brainstem. It is not known to what extent the integrity of brainstem encoding of speech impacts patterns of asymmetry at cortex. Here, we demonstrate that the precision of temporal encoding of speech in auditory brainstem predicts cerebral asymmetry for speech sounds measured in a group of children spanning a range of language skills. Results provide strong evidence that timing deficits measured at the auditory brainstem negatively impact rapid acoustic processing by specialized structures of cortex, and demonstrate a delicate relationship between cortical activation patterns and the temporal integrity of cortical input.

Neurobiological Underpinnings of Math and Reading Learning Disabilities

The primary goal of this review is to highlight current research and theories describing the neurobiological basis of math (MD), reading (RD), and comorbid math and reading disability (MD+RD). We first describe the unique brain and cognitive processes involved in acquisition of math and reading skills, emphasizing similarities and differences in each domain. Next we review functional imaging studies of MD and RD in children, integrating relevant theories from experimental psychology and cognitive neuroscience to characterize the functional neuroanatomy of cognitive dysfunction in MD and RD. We then review recent research on the anatomical correlates of MD and RD. Converging evidence from morphometry and tractography studies are presented to highlight distinct patterns of white matter pathways which are disrupted in MD and RD. Finally, we examine how the intersection of MD and RD provides a unique opportunity to clarify the unique and shared brain systems which adversely impact learning and skill acquisition in MD and RD, and point out important areas for future work on comorbid learning disabilities.

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.

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.

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 Wernickes, Brocas, and Geschwinds areas.