Extensive Tonotopic Mapping across Auditory Cortex Is Recapitulated by Spectrally Directed Attention and Systematically Related to Cortical Myeloarchitecture

Standardization of a silver stain to reveal mesoscale myelin in histological preparations of the mammalian brain

BACKGROUND

The brain is built of neurons supported by myelin, a fatty substance that improves cellular communication. Noninvasive magnetic resonance imaging (MRI) is now able to measure brain structure like myelin and requires histological validation.

NEW METHOD

Here we present work in small and large biomedical model mammals to standardize a silver impregnation method as a high-throughput histological myelin visualization procedure. Specifically, we built a new staining well plate to increase batch size, and then systematically varied the staining and clearing cycles to describe the staining response curve across taxa and conditions. We compared tissues fixed by immersion or perfusion, mounted versus free-floating, and cut as thicker or thinner slices, with two-weeks of post-fixation.

RESULTS

The staining response curves show optimal staining with a single exposure across taxa when incubation and clearing epochs are held to within 3-9 min. We show that clearing was slower in mounted vs free-floating tissue, and that staining was faster and caused fracturing earlier in thinner sliced and smaller volumes of tissue.

COMPARISON WITH EXISTING METHODS

We developed a batch processing approach to increase throughput while ensuring reproducibility and demonstrate the optimal conditions for fine myelinated fiber morphology visualization with short cycles (<9 minutes).

CONCLUSIONS

We present our optimized protocol to reveal mesoscale neuroanatomical myelin content in histology across mammals. This standard staining procedure will facilitate multiscale analyses of myelin content across development as well as in the presence of injury or disease.

Are neuronal mechanisms of attention universal across human sensory and motor brain maps?

One's experience of shifting attention from the color to the smell to the act of picking a flower seems like a unitary process applied, at will, to one modality after another. Yet, the unique and separable experiences of sight versus smell versus movement might suggest that the neural mechanisms of attention have been separately optimized to employ each modality to its greatest advantage. Moreover, addressing the issue of universality can be particularly difficult due to a paucity of existing cross-modal comparisons and a dearth of neurophysiological methods that can be applied equally well across disparate modalities. Here we outline some of the conceptual and methodological issues related to this problem and present an instructive example of an experimental approach that can be applied widely throughout the human brain to permit detailed, quantitative comparison of attentional mechanisms across modalities. The ultimate goal is to spur efforts across disciplines to provide a large and varied database of empirical observations that will either support the notion of a universal neural substrate for attention or more clearly identify the degree to which attentional mechanisms are specialized for each modality.

Parallel Encoding of Speech in Human Frontal and Temporal Lobes

Models of speech perception are centered around a hierarchy in which auditory representations in the thalamus propagate to primary auditory cortex, then to the lateral temporal cortex, and finally through dorsal and ventral pathways to sites in the frontal lobe. However, evidence for short latency speech responses and low-level spectrotemporal representations in frontal cortex raises the question of whether speech-evoked activity in frontal cortex strictly reflects downstream processing from lateral temporal cortex or whether there are direct parallel pathways from the thalamus or primary auditory cortex to the frontal lobe that supplement the traditional hierarchical architecture. Here, we used high-density direct cortical recordings, high-resolution diffusion tractography, and hemodynamic functional connectivity to evaluate for evidence of direct parallel inputs to frontal cortex from low-level areas. We found that neural populations in the frontal lobe show speech-evoked responses that are synchronous or occur earlier than responses in the lateral temporal cortex. These short latency frontal lobe neural populations encode spectrotemporal speech content indistinguishable from spectrotemporal encoding patterns observed in the lateral temporal lobe, suggesting parallel auditory speech representations reaching temporal and frontal cortex simultaneously. This is further supported by white matter tractography and functional connectivity patterns that connect the auditory nucleus of the thalamus (medial geniculate body) and the primary auditory cortex to the frontal lobe. Together, these results support the existence of a robust pathway of parallel inputs from low-level auditory areas to frontal lobe targets and illustrate long-range parallel architecture that works alongside the classical hierarchical speech network model.

Generalization of auditory expertise in audio engineers and instrumental musicians

From auditory perception to general cognition, the ability to play a musical instrument has been associated with skills both related and unrelated to music. However, it is unclear if these effects are bound to the specific characteristics of musical instrument training, as little attention has been paid to other populations such as audio engineers and designers whose auditory expertise may match or surpass that of musicians in specific auditory tasks or more naturalistic acoustic scenarios. We explored this possibility by comparing students of audio engineering (n = 20) to matched conservatory-trained instrumentalists (n = 24) and to naive controls (n = 20) on measures of auditory discrimination, auditory scene analysis, and speech in noise perception. We found that audio engineers and performing musicians had generally lower psychophysical thresholds than controls, with pitch perception showing the largest effect size. Compared to controls, audio engineers could better memorise and recall auditory scenes composed of non-musical sounds, whereas instrumental musicians performed best in a sustained selective attention task with two competing streams of tones. Finally, in a diotic speech-in-babble task, musicians showed lower signal-to-noise-ratio thresholds than both controls and engineers; however, a follow-up online study did not replicate this musician advantage. We also observed differences in personality that might account for group-based self-selection biases. Overall, we showed that investigating a wider range of forms of auditory expertise can help us corroborate (or challenge) the specificity of the advantages previously associated with musical instrument training.

Auditory category learning is robust across training regimes

Multiple lines of research have developed training approaches that foster category learning, with important translational implications for education. Increasing exemplar variability, blocking or interleaving by category-relevant dimension, and providing explicit instructions about diagnostic dimensions each have been shown to facilitate category learning and/or generalization. However, laboratory research often must distill the character of natural input regularities that define real-world categories. As a result, much of what we know about category learning has come from studies with simplifying assumptions. We challenge the implicit expectation that these studies reflect the process of category learning of real-world input by creating an auditory category learning paradigm that intentionally violates some common simplifying assumptions of category learning tasks. Across five experiments and nearly 300 adult participants, we used training regimes previously shown to facilitate category learning, but here drew from a more complex and multidimensional category space with tens of thousands of unique exemplars. Learning was equivalently robust across training regimes that changed exemplar variability, altered the blocking of category exemplars, or provided explicit instructions of the category-diagnostic dimension. Each drove essentially equivalent accuracy measures of learning generalization following 40 min of training. These findings suggest that auditory category learning across complex input is not as susceptible to training regime manipulation as previously thought.

Mesoscopic in vivo human T2* dataset acquired using quantitative MRI at 7 Tesla

Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for advancing neuroscience and bridging the resolution gap with animal models. Despite the variety of MRI contrasts measured in recent years at the mesoscopic scale, in vivo quantitative imaging of T₂^* has not been performed. Here we provide a dataset containing empirical T₂^* measurements acquired at 0.35 × 0.35 × 0.35 mm³ voxel resolution using 7 Tesla MRI. To demonstrate unique features and high quality of this dataset, we generate flat map visualizations that reveal fine-scale cortical substructures such as layers and vessels, and we report quantitative depth-dependent T₂^* (as well as R₂^*) values in primary visual cortex and auditory cortex that are highly consistent across subjects. This dataset is freely available at https://doi.org/10.17605/OSF.IO/N5BJ7, and may prove useful for anatomical investigations of the human brain, as well as for improving our understanding of the basis of the T₂^*-weighted (f)MRI signal.

Selective attention sharpens population receptive fields in human auditory cortex

Selective attention enables the preferential processing of relevant stimulus aspects. Invasive animal studies have shown that attending a sound feature rapidly modifies neuronal tuning throughout the auditory cortex. Human neuroimaging studies have reported enhanced auditory cortical responses with selective attention. To date, it remains unclear how the results obtained with functional magnetic resonance imaging (fMRI) in humans relate to the electrophysiological findings in animal models. Here we aim to narrow the gap between animal and human research by combining a selective attention task similar in design to those used in animal electrophysiology with high spatial resolution ultra-high field fMRI at 7 Tesla. Specifically, human participants perform a detection task, whereas the probability of target occurrence varies with sound frequency. Contrary to previous fMRI studies, we show that selective attention resulted in population receptive field sharpening, and consequently reduced responses, at the attended sound frequencies. The difference between our results to those of previous fMRI studies supports the notion that the influence of selective attention on auditory cortex is diverse and may depend on context, stimulus, and task.

Topological Maps and Brain Computations From Low to High

We first briefly summarize data from microelectrode studies on visual maps in non-human primates and other mammals, and characterize differences among the features of the approximately topological maps in the three main sensory modalities. We then explore the almost 50% of human neocortex that contains straightforward topological visual, auditory, and somatomotor maps by presenting a new parcellation as well as a movie atlas of cortical area maps on the FreeSurfer average surface, fsaverage. Third, we review data on moveable map phenomena as well as a recent study showing that cortical activity during sensorimotor actions may involve spatially locally coherent traveling wave and bump activity. Finally, by analogy with remapping phenomena and sensorimotor activity, we speculate briefly on the testable possibility that coherent localized spatial activity patterns might be able to ‘escape’ from topologically mapped cortex during ‘serial assembly of content’ operations such as scene and language comprehension, to form composite ‘molecular’ patterns that can move across some cortical areas and possibly return to topologically mapped cortex to generate motor output there.

Slow phase-locked modulations support selective attention to sound

To make sense of complex soundscapes, listeners must select and attend to task-relevant streams while ignoring uninformative sounds. One possible neural mechanism underlying this process is alignment of endogenous oscillations with the temporal structure of the target sound stream. Such a mechanism has been suggested to mediate attentional modulation of neural phase-locking to the rhythms of attended sounds. However, such modulations are compatible with an alternate framework, where attention acts as a filter that enhances exogenously-driven neural auditory responses. Here we attempted to test several predictions arising from the oscillatory account by playing two tone streams varying across conditions in tone duration and presentation rate; participants attended to one stream or listened passively. Attentional modulation of the evoked waveform was roughly sinusoidal and scaled with rate, while the passive response did not. However, there was only limited evidence for continuation of modulations through the silence between sequences. These results suggest that attentionally-driven changes in phase alignment reflect synchronization of slow endogenous activity with the temporal structure of attended stimuli.

Test-retest reliability of multi-parametric maps (MPM) of brain microstructure

Multiparameter mapping (MPM) is a quantitative MRI protocol that is promising for studying microstructural brain changes in vivo with high specificity. Reliability values are an important prior knowledge for efficient study design and facilitating replicable findings in development, aging and neuroplasticity research. To explore longitudinal reliability of MPM we acquired the protocol in 31 healthy young subjects twice over a rescan interval of 4 weeks. We assessed the within-subject coefficient of variation (WCV), the between-subject coefficient of variation (BCV), and the intraclass correlation coefficient (ICC). Using these metrics, we investigated the reliability of (semi-) quantitative magnetization transfer saturation (MT_sat), proton density (PD), transversal relaxation (R2*) and longitudinal relaxation (R1). To increase relevance for explorative studies in development and training-induced plasticity, we assess reliability both on local voxel- as well as ROI-level. Finally, we disentangle contributions and interplay of within- and between-subject variability to ICC and assess the optimal degree of spatial smoothing applied to the data. We reveal evidence that voxelwise ICC reliability of MPMs is moderate to good with median values in cortex (subcortical GM): MT: 0.789 (0.447) PD: 0.553 (0.264) R1: 0.555 (0.369) R2*: 0.624 (0.477). The Gaussian smoothing kernel of 2 to 4 mm FWHM resulted in optimal reproducibility. We discuss these findings in the context of longitudinal intervention studies and the application to research designs in neuroimaging field.

Distortion of mental body representations

Our body is central to our sense of self, and distorted body representations are found in several serious medical conditions. This paper reviews evidence that distortions of body representations are also common in healthy individuals, and occur in domains including tactile spatial perception, proprioception, and the conscious body image. Across domains, there is a general tendency for body width to be overestimated compared to body length. Intriguingly, distortions in both eating disorders and chronic pain appear to be exaggerations of this baseline pattern of distortions, suggesting that these conditions may relate to dysfunction of mechanisms for body perception. Distortions of body representations provide a revealing window into basic aspects of self-perception.

Dimension-selective attention and dimensional salience modulate cortical tracking of acoustic dimensions

Some theories of auditory categorization suggest that auditory dimensions that are strongly diagnostic for particular categories - for instance voice onset time or fundamental frequency in the case of some spoken consonants - attract attention. However, prior cognitive neuroscience research on auditory selective attention has largely focused on attention to simple auditory objects or streams, and so little is known about the neural mechanisms that underpin dimension-selective attention, or how the relative salience of variations along these dimensions might modulate neural signatures of attention. Here we investigate whether dimensional salience and dimension-selective attention modulate the cortical tracking of acoustic dimensions. In two experiments, participants listened to tone sequences varying in pitch and spectral peak frequency; these two dimensions changed at different rates. Inter-trial phase coherence (ITPC) and amplitude of the EEG signal at the frequencies tagged to pitch and spectral changes provided a measure of cortical tracking of these dimensions. In Experiment 1, tone sequences varied in the size of the pitch intervals, while the size of spectral peak intervals remained constant. Cortical tracking of pitch changes was greater for sequences with larger compared to smaller pitch intervals, with no difference in cortical tracking of spectral peak changes. In Experiment 2, participants selectively attended to either pitch or spectral peak. Cortical tracking was stronger in response to the attended compared to unattended dimension for both pitch and spectral peak. These findings suggest that attention can enhance the cortical tracking of specific acoustic dimensions rather than simply enhancing tracking of the auditory object as a whole.

Using high spatial resolution fMRI to understand representation in the auditory network

Following rapid methodological advances, ultra-high field (UHF) functional and anatomical magnetic resonance imaging (MRI) has been repeatedly and successfully used for the investigation of the human auditory system in recent years. Here, we review this work and argue that UHF MRI is uniquely suited to shed light on how sounds are represented throughout the network of auditory brain regions. That is, the provided gain in spatial resolution at UHF can be used to study the functional role of the small subcortical auditory processing stages and details of cortical processing. Further, by combining high spatial resolution with the versatility of MRI contrasts, UHF MRI has the potential to localize the primary auditory cortex in individual hemispheres. This is a prerequisite to study how sound representation in higher-level auditory cortex evolves from that in early (primary) auditory cortex. Finally, the access to independent signals across auditory cortical depths, as afforded by UHF, may reveal the computations that underlie the emergence of an abstract, categorical sound representation based on low-level acoustic feature processing. Efforts on these research topics are underway. Here we discuss promises as well as challenges that come with studying these research questions using UHF MRI, and provide a future outlook.

Parallel and distributed encoding of speech across human auditory cortex

Speech perception is thought to rely on a cortical feedforward serial transformation of acoustic into linguistic representations. Using intracranial recordings across the entire human auditory cortex, electrocortical stimulation, and surgical ablation, we show that cortical processing across areas is not consistent with a serial hierarchical organization. Instead, response latency and receptive field analyses demonstrate parallel and distinct information processing in the primary and nonprimary auditory cortices. This functional dissociation was also observed where stimulation of the primary auditory cortex evokes auditory hallucination but does not distort or interfere with speech perception. Opposite effects were observed during stimulation of nonprimary cortex in superior temporal gyrus. Ablation of the primary auditory cortex does not affect speech perception. These results establish a distributed functional organization of parallel information processing throughout the human auditory cortex and demonstrate an essential independent role for nonprimary auditory cortex in speech processing.

Categorical Encoding of Vowels in Primary Auditory Cortex

Speech perception involves mapping from a continuous and variable acoustic speech signal to discrete, linguistically meaningful units. However, it is unclear where in the auditory processing stream speech sound representations cease to be veridical (faithfully encoding precise acoustic properties) and become categorical (encoding sounds as linguistic categories). In this study, we used functional magnetic resonance imaging and multivariate pattern analysis to determine whether tonotopic primary auditory cortex (PAC), defined as tonotopic voxels falling within Heschl's gyrus, represents one class of speech sounds-vowels-veridically or categorically. For each of 15 participants, 4 individualized synthetic vowel stimuli were generated such that the vowels were equidistant in acoustic space, yet straddled a categorical boundary (with the first 2 vowels perceived as [i] and the last 2 perceived as [i]). Each participant's 4 vowels were then presented in a block design with an irrelevant but attention-demanding level change detection task. We found that in PAC bilaterally, neural discrimination between pairs of vowels that crossed the categorical boundary was more accurate than neural discrimination between equivalently spaced vowel pairs that fell within a category. These findings suggest that PAC does not represent vowel sounds veridically, but that encoding of vowels is shaped by linguistically relevant phonemic categories.

Imperfect spoiling in variable flip angle T1 mapping at 7T: Quantifying and minimizing impact

Purpose

The variable flip angle (VFA) approach to T₁ mapping assumes perfectly spoiled transverse magnetisation at the end of each repetition time (TR). Despite radiofrequency (RF) and gradient spoiling, this condition is rarely met, leading to erroneous T₁ estimates (T1app). Theoretical corrections can be applied but make assumptions about tissue properties, for example, a global T₂ time. Here, we investigate the effect of imperfect spoiling at 7T and the interaction between the RF and gradient spoiling conditions, additionally accounting for diffusion. We provide guidance on the optimal approach to maximise the accuracy of the T₁ estimate in the context of 3D multi‐echo acquisitions.

Methods

The impact of the spoiling regime was investigated through numerical simulations, phantom and invivo experiments.

Results

The predicted dependence of T1app on tissue properties, system settings, and spoiling conditions was observed in both phantom and in vivo experiments. Diffusion effects modulated the dependence of T1app on both B1+ efficiency and T₂ times.

Conclusion

Error in T1app can be minimized by using an RF spoiling increment and gradient spoiler moment combination that minimizes T₂‐dependence and safeguards image quality. Although the diffusion effect was comparatively small at 7T, correction factors accounting for this effect are recommended.

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Effects of auditory selective attention on neural phase: individual differences and short-term training

How does the brain follow a sound that is mixed with others in a noisy environment? One possible strategy is to allocate attention to task-relevant time intervals. Prior work has linked auditory selective attention to alignment of neural modulations with stimulus temporal structure. However, since this prior research used relatively easy tasks and focused on analysis of main effects of attention across participants, relatively little is known about the neural foundations of individual differences in auditory selective attention. Here we investigated individual differences in auditory selective attention by asking participants to perform a 1-back task on a target auditory stream while ignoring a distractor auditory stream presented 180° out of phase. Neural entrainment to the attended auditory stream was strongly linked to individual differences in task performance. Some variability in performance was accounted for by degree of musical training, suggesting a link between long-term auditory experience and auditory selective attention. To investigate whether short-term improvements in auditory selective attention are possible, we gave participants 2 ​h of auditory selective attention training and found improvements in both task performance and enhancements of the effects of attention on neural phase angle. Our results suggest that although there exist large individual differences in auditory selective attention and attentional modulation of neural phase angle, this skill improves after a small amount of targeted training.

Is Human Auditory Cortex Organization Compatible With the Monkey Model? Contrary Evidence From Ultra-High-Field Functional and Structural MRI

It is commonly assumed that the human auditory cortex is organized similarly to that of macaque monkeys, where the primary region, or "core," is elongated parallel to the tonotopic axis (main direction of tonotopic gradients), and subdivided across this axis into up to 3 distinct areas (A1, R, and RT), with separate, mirror-symmetric tonotopic gradients. This assumption, however, has not been tested until now. Here, we used high-resolution ultra-high-field (7 T) magnetic resonance imaging (MRI) to delineate the human core and map tonotopy in 24 individual hemispheres. In each hemisphere, we assessed tonotopic gradients using principled, quantitative analysis methods, and delineated the core using 2 independent (functional and structural) MRI criteria. Our results indicate that, contrary to macaques, the human core is elongated perpendicular rather than parallel to the main tonotopic axis, and that this axis contains no more than 2 mirror-reversed gradients within the core region. Previously suggested homologies between these gradients and areas A1 and R in macaques were not supported. Our findings suggest fundamental differences in auditory cortex organization between humans and macaques.

hMRI - A toolbox for quantitative MRI in neuroscience and clinical research

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.

Dimension-selective attention as a possible driver of dynamic, context-dependent re-weighting in speech processing

The contribution of acoustic dimensions to an auditory percept is dynamically adjusted and reweighted based on prior experience about how informative these dimensions are across the long-term and short-term environment. This is especially evident in speech perception, where listeners differentially weight information across multiple acoustic dimensions, and use this information selectively to update expectations about future sounds. The dynamic and selective adjustment of how acoustic input dimensions contribute to perception has made it tempting to conceive of this as a form of non-spatial auditory selective attention. Here, we review several human speech perception phenomena that might be consistent with auditory selective attention although, as of yet, the literature does not definitively support a mechanistic tie. We relate these human perceptual phenomena to illustrative nonhuman animal neurobiological findings that offer informative guideposts in how to test mechanistic connections. We next present a novel empirical approach that can serve as a methodological bridge from human research to animal neurobiological studies. Finally, we describe four preliminary results that demonstrate its utility in advancing understanding of human non-spatial dimension-based auditory selective attention.

Neural representation of vowel formants in tonotopic auditory cortex

Speech sounds are encoded by distributed patterns of activity in bilateral superior temporal cortex. However, it is unclear whether speech sounds are topographically represented in cortex, or which acoustic or phonetic dimensions might be spatially mapped. Here, using functional MRI, we investigated the potential spatial representation of vowels, which are largely distinguished from one another by the frequencies of their first and second formants, i.e. peaks in their frequency spectra. This allowed us to generate clear hypotheses about the representation of specific vowels in tonotopic regions of auditory cortex. We scanned participants as they listened to multiple natural tokens of the vowels [ɑ] and [i], which we selected because their first and second formants overlap minimally. Formant-based regions of interest were defined for each vowel based on spectral analysis of the vowel stimuli and independently acquired tonotopic maps for each participant. We found that perception of [ɑ] and [i] yielded differential activation of tonotopic regions corresponding to formants of [ɑ] and [i], such that each vowel was associated with increased signal in tonotopic regions corresponding to its own formants. This pattern was observed in Heschl's gyrus and the superior temporal gyrus, in both hemispheres, and for both the first and second formants. Using linear discriminant analysis of mean signal change in formant-based regions of interest, the identity of untrained vowels was predicted with ∼73% accuracy. Our findings show that cortical encoding of vowels is scaffolded on tonotopy, a fundamental organizing principle of auditory cortex that is not language-specific.