Human white matter myelinates faster in utero than ex utero.

The formation of myelin, the fatty sheath that insulates nerve fibers, is critical for healthy brain function. A fundamental open question is what impact being born has on myelin growth. To address this, we evaluated a large (n = 300) cross-sectional sample of newborns from the Developing Human Connectome Project (dHCP). First, we developed software for the automated identification of 20 white matter bundles in individual newborns that is well suited for large samples. Next, we fit linear models that quantify how T1w/T2w (a myelin-sensitive imaging contrast) changes over time at each point along the bundles. We found faster growth of T1w/T2w along the lengths of all bundles before birth than right after birth. Further, in a separate longitudinal sample of preterm infants (N = 34), we found lower T1w/T2w than in full-term peers measured at the same age. By applying the linear models fit on the cross-section sample to the longitudinal sample of preterm infants, we find that their delay in T1w/T2w growth is well explained by the amount of time they spent developing in utero and ex utero. These results suggest that white matter myelinates faster in utero than ex utero. The reduced rate of myelin growth after birth, in turn, explains lower myelin content in individuals born preterm and could account for long-term cognitive, neurological, and developmental consequences of preterm birth. We hypothesize that closely matching the environment of infants born preterm to what they would have experienced in the womb may reduce delays in myelin growth and hence improve developmental outcomes.

Both mOTS-words and pOTS-words prefer emoji stimuli over text stimuli during a lexical judgment task.

The visual word form area in the occipitotemporal sulcus (here OTS-words) is crucial for reading and shows a preference for text stimuli. We hypothesized that this text preference may be driven by lexical processing. Hence, we performed three fMRI experiments (n = 15), systematically varying participants' task and stimulus, and separately evaluated middle mOTS-words and posterior pOTS-words. Experiment 1 contrasted text with other visual stimuli to identify both OTS-words subregions. Experiment 2 utilized an fMRI adaptation paradigm, presenting compound words as texts or emojis. In experiment 3, participants performed a lexical or color judgment task on compound words in text or emoji format. In experiment 2, pOTS-words, but not mOTS-words, showed fMRI adaptation for compound words in both formats. In experiment 3, both subregions showed higher responses to compound words in emoji format. Moreover, mOTS-words showed higher responses during the lexical judgment task and a task-stimulus interaction. Multivariate analyses revealed that distributed responses in pOTS-words encode stimulus and distributed responses in mOTS-words encode stimulus and task. Together, our findings suggest that the function of the OTS-words subregions goes beyond the specific visual processing of text and that these regions are flexibly recruited whenever semantic meaning needs to be assigned to visual input.

White matter connections of high-level visual areas predict cytoarchitecture better than category-selectivity in childhood, but not adulthood.

Ventral temporal cortex (VTC) consists of high-level visual regions that are arranged in consistent anatomical locations across individuals. This consistency has led to several hypotheses about the factors that constrain the functional organization of VTC. A prevailing theory is that white matter connections influence the organization of VTC, however, the nature of this constraint is unclear. Here, we test 2 hypotheses: (1) white matter tracts are specific for each category or (2) white matter tracts are specific to cytoarchitectonic areas of VTC. To test these hypotheses, we used diffusion magnetic resonance imaging to identify white matter tracts and functional magnetic resonance imaging to identify category-selective regions in VTC in children and adults. We find that in childhood, white matter connections are linked to cytoarchitecture rather than category-selectivity. In adulthood, however, white matter connections are linked to both cytoarchitecture and category-selectivity. These results suggest a rethinking of the view that category-selective regions in VTC have category-specific white matter connections early in development. Instead, these findings suggest that the neural hardware underlying the processing of categorical stimuli may be more domain-general than previously thought, particularly in childhood.

White matter fascicles and cortical microstructure predict reading-related responses in human ventral temporal cortex.

Reading-related responses in the lateral ventral temporal cortex (VTC) show a consistent spatial layout across individuals, which is puzzling, since reading skills are acquired during childhood. Here, we tested the hypothesis that white matter fascicles and gray matter microstructure predict the location of reading-related responses in lateral VTC. We obtained functional (fMRI), diffusion (dMRI), and quantitative (qMRI) magnetic resonance imaging data in 30 adults. fMRI was used to map reading-related responses by contrasting responses in a reading task with those in adding and color tasks; dMRI was used to identify the brain's fascicles and to map their endpoint densities in lateral VTC; qMRI was used to measure proton relaxation time (T1), which depends on cortical tissue microstructure. We fit linear models that predict reading-related responses in lateral VTC from endpoint density and T1 and used leave-one-subject-out cross-validation to assess prediction accuracy. Using a subset of our participants (N=10, feature selection set), we find that i) endpoint densities of the arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), and vertical occipital fasciculus (VOF) are significant predictors of reading-related responses, and ii) cortical T1 of lateral VTC further improves the predictions of the fascicle model. In the remaining participants (N=20, validation set), we show that a linear model that includes T1, AF, ILF and VOF significantly predicts i) the map of reading-related responses across lateral VTC and ii) the location of the visual word form area, a region critical for reading. Overall, our data-driven approach reveals that the AF, ILF, VOF and cortical microstructure have a consistent spatial relationship with an individual's reading-related responses in lateral VTC.

A preference for mathematical processing outweighs the selectivity for Arabic numbers in the inferior temporal gyrus.

A region in the posterior inferior temporal gyrus (ITG), referred to as the number form area (NFA, here ITG-numbers) has been implicated in the visual processing of Arabic numbers. However, it is unknown if this region is specifically involved in the visual encoding of Arabic numbers per se or in mathematical processing more broadly. Using functional magnetic resonance imaging (fMRI) during experiments that systematically vary tasks and stimuli, we find that mathematical processing, not preference to Arabic numbers, consistently drives both mean and distributed responses in the posterior ITG. While we replicated findings of higher responses in ITG-numbers to numbers than other visual stimuli during a 1-back task, this preference to numbers was abolished when participants engaged in mathematical processing. In contrast, an ITG region (ITG-math) that showed higher responses during an adding task vs. other tasks maintained this preference for mathematical processing across a wide range of stimuli including numbers, number/letter morphs, hands, and dice. Analysis of distributed responses across an anatomically-defined posterior ITG expanse further revealed that mathematical task but not Arabic number form can be successfully and consistently decoded from these distributed responses. Together, our findings suggest that the function of neuronal regions in the posterior ITG goes beyond the specific visual processing of Arabic numbers. We hypothesize that they ascribe numerical content to the visual input, irrespective of the format of the stimulus.

Neuroimaging Evidence of a Bilateral Representation for Visually Presented Numbers.

The clustered architecture of the brain for different visual stimulus categories is one of the most fascinating topics in the cognitive neurosciences. Interestingly, recent research suggests the existence of additional regions for newly acquired stimuli such as letters (letter form area; LFA; Thesen et al., 2012) and numbers (visual number form area; NFA; Shum et al., 2013). However, neuroimaging methods thus far have failed to visualize the NFA in healthy participants, likely due to fMRI signal dropout caused by the air/bone interface of the petrous bone (Shum et al., 2013). In the current study, we combined a 64-channel head coil with high spatial resolution, localized shimming, and liberal smoothing, thereby decreasing the signal dropout and increasing the temporal signal-to-noise ratio in the neighborhood of the NFA. We presented subjects with numbers, letters, false numbers, false letters, objects and their Fourier randomized versions. A group analysis showed significant activations in the inferior temporal gyrus at the previously proposed location of the NFA. Crucially, we found the NFA to be present in both hemispheres. Further, we could identify the NFA on the single-subject level in most of our participants. A detailed analysis of the response profile of the NFA in two separate experiments confirmed the whole-brain results since responses to numbers were significantly higher than to any other presented stimulus in both hemispheres. Our results show for the first time the existence and stimulus selectivity of the NFA in the healthy human brain. SIGNIFICANCE STATEMENT: This fMRI study shows for the first time a cluster of neurons selective for visually presented numbers in healthy human adults. This visual number form area (NFA) was found in both hemispheres. Crucially, numbers have gained importance for humans too recently for neuronal specialization to be established by evolution. Therefore, investigations of this region will greatly advance our understanding of learning and plasticity in the brain. In addition, these results will aid our knowledge regarding related neurological illnesses (e.g., dyscalculia). To overcome the fMRI signal dropout in the neighborhood of the NFA, we combined high spatial resolution with liberal smoothing. We believe that this approach will be useful to the broad neuroimaging community.

Causal evidence of the involvement of the number form area in the visual detection of numbers and letters.

Recent research suggests the existence of a visual area selectively processing numbers in the human inferior temporal cortex (number form area (NFA); Abboud et al., 2015; Grotheer et al., 2016; Shum et al., 2013). The NFA is thought to be involved in the preferential encoding of numbers over false characters, letters and non-number words (Grotheer et al., 2016; Shum et al., 2013), independently of the sensory modality (Abboud et al., 2015). However, it is not yet clear if this area is mandatory for normal number processing. The present study exploited the fact that high-resolution fMRI can be applied to identify the NFA individually (Grotheer et al., 2016) and tested if transcranial magnetic stimulation (TMS) of this area interferes with stimulus processing in a selective manner. Double-pulse TMS targeted at the right NFA significantly impaired the detection of briefly presented and masked Arabic numbers in comparison to vertex stimulation. This suggests the NFA to be necessary for fluent number processing. Surprisingly, TMS of the NFA also impaired the detection of Roman letters. On the other hand, stimulation of the lateral occipital complex (LO) had neither an effect on the detection of numbers nor on letters. Our results show, for the first time, that the NFA is causally involved in the early visual processing of numbers as well as of letters.

Repetition probability effects depend on prior experiences.

The magnitude of repetition suppression (RS) in the Fusiform Face Area is influenced by the probability of repetitions of faces (Summerfield et al., 2008), implying that perceptual expectations affect repetition-related processes. Surprisingly, however, macaque single-cell (Kaliukhovich and Vogels, 2011) and human fMRI (Kovács et al., 2013) studies have failed to find repetition probability [P(rep)] modulations of RS with nonface stimuli in the occipitotemporal cortex, suggesting that the effect is face specific. One possible explanation of this category selectivity is that the extensive experience humans have with faces affects the neural mechanisms of RS specifically, creating P(rep) modulatory effects. To address this question, we used fMRI to test the P(rep) effects for another well trained stimulus category, upright letters of the roman alphabet as well as for unfamiliar false fonts. We observed significant RS for both stimulus sets in the Letter Form Area as well as in the caudodorsal part of the lateral occipital complex. Interestingly, the influence of P(rep) on RS was dependent on the stimulus: while we observed P(rep) modulations for the roman letters, no such effects were found for the unfamiliar false fonts in either area. Our findings suggest that P(rep) effects on RS are manifest for nonface stimuli as well, but that they depend on the experience of the subjects with the stimulus category. This shows, for the first time, that prior experience affects the influence of contextual predictive information on RS in the human occipitotemporal cortex.

Repetition probability effects for inverted faces.

It has been shown, that the repetition related reduction of the blood-oxygen level dependent (BOLD) signal is modulated by the probability of repetitions (P(rep)) for faces (Summerfield et al., 2008), providing support for the predictive coding (PC) model of visual perception (Rao and Ballard, 1999). However, the stage of face processing where repetition suppression (RS) is modulated by P(rep) is still unclear. Face inversion is known to interrupt higher level configural/holistic face processing steps and if modulation of RS by P(rep) takes place at these stages of face processing, P(rep) effects are expected to be reduced for inverted when compared to upright faces. Therefore, here we aimed at investigating whether P(rep) effects on RS observed for face stimuli originate at the higher-level configural/holistic stages of face processing by comparing these effects for upright and inverted faces. Similarly to previous studies, we manipulated P(rep) for pairs of stimuli in individual blocks of fMRI recordings. This manipulation significantly influenced repetition suppression in the posterior FFA, the OFA and the LO, independently of stimulus orientation. Our results thus reveal that RS in the ventral visual stream is modulated by P(rep) even in the case of face inversion and hence strongly compromised configural/holistic face processing. An additional whole-brain analysis could not identify any areas where the modulatory effect of probability was orientation specific either. These findings imply that P(rep) effects on RS might originate from the earlier stages of face processing.

Both mOTS-words and pOTS-words prefer emoji stimuli over text stimuli during a reading task.

The visual word form area in the occipitotemporal sulcus (OTS), here referred to as OTS-words, responds more strongly to text than other visual stimuli and is crucial for reading. We hypothesized, that this text preference may be driven by a preference for reading tasks, as in most prior fMRI studies only the text stimuli were readable. Hence, we performed three fMRI experiments (N=15) and systematically varied the participant's task and the stimulus, investigating mOTS-words and pOTS-words subregions. In experiment 1, we contrasted text stimuli with non-readable visual stimuli (faces, limbs, houses, objects). Experiment 2 utilized an fMRI adaptation paradigm, presenting compound words in text or emoji formats. In experiment 3, participants performed a reading or a color task on compound words in text or emoji format. Using experiment 1 data, we identified mOTS-words and pOTS-words by contrasting texts with non-readable stimuli. In experiment 2, pOTS-words, but not mOTS-words, showed fMRI adaptation for compound words in both text and emoji formats. In experiment 3, surprisingly, both subregions showed higher responses to compound words in emoji than text format. Moreover, mOTS-words showed higher responses during the reading than the color task and a task-stimulus interaction. Multivariate analyses revealed that distributed responses in pOTS-words encode the visual stimulus, while responses in mOTS-words encode both stimulus and task. Together, our findings suggest that the function of the OTS-words subregions goes beyond the specific visual processing of text and that these regions are flexibly recruited whenever semantic meaning needs to be assigned to visual input.

A practical guide for combining functional regions of interest and white matter bundles.

Diffusion-weighted imaging (DWI) is the primary method to investigate macro- and microstructure of neural white matter in vivo. DWI can be used to identify and characterize individual-specific white matter bundles, enabling precise analyses on hypothesis-driven connections in the brain and bridging the relationships between brain structure, function, and behavior. However, cortical endpoints of bundles may span larger areas than what a researcher is interested in, challenging presumptions that bundles are specifically tied to certain brain functions. Functional MRI (fMRI) can be integrated to further refine bundles such that they are restricted to functionally-defined cortical regions. Analyzing properties of these Functional Sub-Bundles (FSuB) increases precision and interpretability of results when studying neural connections supporting specific tasks. Several parameters of DWI and fMRI analyses, ranging from data acquisition to processing, can impact the efficacy of integrating functional and diffusion MRI. Here, we discuss the applications of the FSuB approach, suggest best practices for acquiring and processing neuroimaging data towards this end, and introduce the FSuB-Extractor, a flexible open-source software for creating FSuBs. We demonstrate our processing code and the FSuB-Extractor on an openly-available dataset, the Natural Scenes Dataset.

White matter connections of human ventral temporal cortex are organized by cytoarchitecture, eccentricity, and category-selectivity from birth.

Category-selective regions in ventral temporal cortex (VTC) have a consistent anatomical organization, which is hypothesized to be scaffolded by white matter connections. However, it is unknown how white matter connections are organized from birth. Here, we scanned newborn to 6-month-old infants and adults and used a data-driven approach to determine the organization of the white matter connections of VTC. We find that white matter connections are organized by cytoarchitecture, eccentricity, and category from birth. Connectivity profiles of functional regions in the same cytoarchitectonic area are similar from birth and develop in parallel, with decreases in endpoint connectivity to lateral occipital, and parietal, and somatosensory cortex, and increases to lateral prefrontal cortex. Additionally, connections between VTC and early visual cortex are organized topographically by eccentricity bands and predict eccentricity biases in VTC. These data have important implications for theories of cortical functional development and open new possibilities for understanding typical and atypical white matter development.

Establishing the functional relevancy of white matter connections in the visual system and beyond.

For over a century, researchers have examined the functional relevancy of white matter bundles. Consequently, many large-scale bundles spanning several centimeters have been associated in their entirety with specific brain functions, such as language or attention. However, these coarse structural-functional relationships are at odds with modern understanding of the fine-grained functional organization of human cortex, such as the mosaic of category-selective regions in ventral temporal cortex. Here, we review a multimodal approach that combines fMRI to define functional regions of interest within individual's brains with dMRI tractography to identify the white matter bundles of the same individual. Combining these data allows to determine which subsets of streamlines within a white matter bundle connect to specific functional regions in each individual. That is, this approach identifies the functionally defined white matter sub-bundles of the brain. We argue that this approach not only enhances the accuracy of interpreting the functional relevancy of white matter bundles, but also enables segmentation of these large-scale bundles into meaningful functional units, which can then be linked to behavior with enhanced precision. Importantly, this approach has the potential for making new discoveries of the fine-grained functional relevancy of white matter connections in the visual system and the brain more broadly, akin to the flurry of research that has identified functional regions in cortex.

White matter myelination during early infancy is linked to spatial gradients and myelin content at birth.

Development of myelin, a fatty sheath that insulates nerve fibers, is critical for brain function. Myelination during infancy has been studied with histology, but postmortem data cannot evaluate the longitudinal trajectory of white matter development. Here, we obtained longitudinal diffusion MRI and quantitative MRI measures of longitudinal relaxation rate (R1) of white matter in 0, 3 and 6 months-old human infants, and developed an automated method to identify white matter bundles and quantify their properties in each infant's brain. We find that R1 increases from newborns to 6-months-olds in all bundles. R1 development is nonuniform: there is faster development in white matter that is less mature in newborns, and development rate increases along inferior-to-superior as well as anterior-to-posterior spatial gradients. As R1 is linearly related to myelin fraction in white matter bundles, these findings open new avenues to elucidate typical and atypical white matter myelination in early infancy.

Infants' cortex undergoes microstructural growth coupled with myelination during development.

Development of cortical tissue during infancy is critical for the emergence of typical brain functions in cortex. However, how cortical microstructure develops during infancy remains unknown. We measured the longitudinal development of cortex from birth  to six months of age  using multimodal quantitative imaging of cortical microstructure. Here we show that infants' cortex undergoes profound microstructural tissue growth during the first six months of human life. Comparison of postnatal to prenatal transcriptomic gene expression data demonstrates that myelination and synaptic processes are dominant contributors to this postnatal microstructural tissue growth. Using visual cortex as a model system, we find hierarchical microstructural growth: higher-level visual areas have less mature tissue at birth than earlier visual areas but grow at faster rates. This overturns the prominent view that visual areas that are most mature at birth develop fastest. Together, in vivo, longitudinal, and quantitative measurements, which we validated with ex vivo transcriptomic data, shed light on the rate, sequence, and biological mechanisms of developing cortical systems during early infancy. Importantly, our findings propose a hypothesis that cortical myelination is a key factor in cortical development during early infancy, which has important implications for diagnosis of neurodevelopmental disorders and delays in infants.

Evaluating the Reliability of Human Brain White Matter Tractometry.

The validity of research results depends on the reliability of analysis methods. In recent years, there have been concerns about the validity of research that uses diffusion-weighted MRI (dMRI) to understand human brain white matter connections in vivo, in part based on the reliability of analysis methods used in this field. We defined and assessed three dimensions of reliability in dMRI-based tractometry, an analysis technique that assesses the physical properties of white matter pathways: (1) reproducibility, (2) test-retest reliability, and (3) robustness. To facilitate reproducibility, we provide software that automates tractometry (https://yeatmanlab.github.io/pyAFQ). In measurements from the Human Connectome Project, as well as clinical-grade measurements, we find that tractometry has high test-retest reliability that is comparable to most standardized clinical assessment tools. We find that tractometry is also robust: showing high reliability with different choices of analysis algorithms. Taken together, our results suggest that tractometry is a reliable approach to analysis of white matter connections. The overall approach taken here both demonstrates the specific trustworthiness of tractometry analysis and outlines what researchers can do to establish the reliability of computational analysis pipelines in neuroimaging.

Significant repetition probability effects in schizophrenia.

BACKGROUND: A growing body of evidence suggests that the comparison of expected and incoming sensory stimuli (the prediction-error (ε) processing) is impaired in schizophrenia patients (SZ). For example, in studies of mismatch negativity, an ERP component that signals ε, SZ patients show deficits in the auditory and visual modalities. To test the role of impaired ε processing further in SZ, using neuroimaging methods, we applied a repetition-suppression (RS) paradigm. METHODS: Patients diagnosed with SZ (n = 17) as well as age- and sex- matched healthy control subjects (HC, n = 17) were presented with pairs of faces, which could either repeat or alternate. Additionally, the likelihood of repetition/alternation trials was modulated in individual blocks of fMRI recordings, testing the effects of repetition probability (P(rep)) on RS. RESULTS: We found a significant RS in the fusiform and occipital face areas as well as in the lateral occipital cortex that was similar in healthy controls and SZ patients SZ. More importantly, we observed similar P(rep) effects (larger RS in blocks with high frequency of repetitions than in blocks with low repetition likelihood) in both the control and the patient group. CONCLUSION: Our findings suggest that repetition_probability modulations affect the neural responses in schizophrenia patients and healthy participants similarly. This suggests that the neural mechanisms determining perceptual inferences based on stimulus probabilities remain unimpaired in schizophrenia.

Separate lanes for adding and reading in the white matter highways of the human brain.

Math and reading involve distributed brain networks and have both shared (e.g. encoding of visual stimuli) and dissociated (e.g. quantity processing) cognitive components. Yet, to date, the shared vs. dissociated gray and white matter substrates of the math and reading networks are unknown. Here, we define these networks and evaluate the structural properties of their fascicles using functional MRI, diffusion MRI, and quantitative MRI. Our results reveal that there are distinct gray matter regions which are preferentially engaged in either math (adding) or reading, and that the superior longitudinal and arcuate fascicles are shared across the math and reading networks. Strikingly, within these fascicles, reading- and math-related tracts are segregated into parallel sub-bundles and show structural differences related to myelination. These findings open a new avenue of research that examines the contribution of sub-bundles within fascicles to specific behaviors.

Similar Expectation Effects for Immediate and Delayed Stimulus Repetitions.

A prior cue or stimulus allows prediction of the future occurrence of an event and therefore reduces the associated neural activity in several cortical areas. This phenomenon is labeled expectation suppression (ES) and has recently been shown to be independent of the generally observed effects of stimulus repetitions (repetition suppression, RS: reduced neuronal response after the repetition of a given stimulus). While it has been shown that attentional cueing is strongly affected by the length of the cue-target delay, we have no information on the temporal dynamics of expectation effects, as in most prior studies of ES the delay between the predictive cue and the target (i.e., the inter-stimulus interval, ISI) was in the range of a few hundred milliseconds. Hence, we presented participants with pairs of faces where the first face could be used to build expectations regarding the second one, in the sense that one gender indicated repetition of the same face while the other gender predicted the occurrence of novel faces. In addition, we presented the stimulus pairs with two different ISIs (0.5 s for Immediate and 1.75 or 3.75 s for Delayed ISIs). We found significant RS as well as a reduced response for correctly predicted when compared to surprising trials in the fusiform face area. Importantly, the effects of repetition and expectation were both independent of the length of the ISI period. This implies that Immediate and Delayed cue-target stimulus arrangements lead to similar expectation effects in the face sensitive-visual cortex.

The relationship between repetition suppression and face perception.

Repetition of identical face stimuli leads to fMRI response attenuation (fMRI adaptation, fMRIa) in the core face-selective occipito-temporal visual cortical network, involving the bilateral fusiform face area (FFA) and the occipital face area (OFA). However, the functional relevance of fMRIa observed in these regions is unclear as of today. Therefore, here we aimed at investigating the relationship between fMRIa and face perception ability by measuring in the same human participants both the repetition-induced reduction of fMRI responses and identity discrimination performance outside the scanner for upright and inverted face stimuli. In the correlation analysis, the behavioral and fMRI results for the inverted faces were used as covariates to control for the individual differences in overall object perception ability and basic visual feature adaptation processes, respectively. The results revealed a significant positive correlation between the participants' identity discrimination performance and the strength of fMRIa in the core face processing network, but not in the extrastriate body area (EBA). Furthermore, we found a strong correlation of the fMRIa between OFA and FFA and also between OFA and EBA, but not between FFA and EBA. These findings suggest that there is a face-selective component of the repetition-induced reduction of fMRI responses within the core face processing network, which reflects functionally relevant adaptation processes involved in face identity perception.