Biology subjects

Ellis, C. T.

Publications and source records attributed to Ellis, C. T..

14 recordsLinked to original sources

bioRxiv2026

Eccentricity, but not category, organizes infant ventral temporal cortex

Scene- and word-selective regions in adult ventral temporal cortex occupy consistent locations across individuals and align with eccentricity biases for peripheral versus central parts of the visual field, respectively. This relationship may reflect a developmental sequence in which initial preferences for visual field location influence the emergence of category-selectivity in these regions, driven by where each category appears in the visual field. To test this account, we used fMRI in awake, behaving infants aged 2-10 months, independently manipulating stimulus size (40{degrees} versus 6{degrees}) and category (scenes versus letters). We found eccentricity gradients across early visual cortex and ventral temporal cortex. Crucially, the collateral sulcus -- a scene-selective, peripherally-biased region in adults -- showed greater responses to big over small stimuli in infants, but no reliable preference for scenes over letters. These findings suggest that an eccentricity bias could provide a scaffold for later category specialization.

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bioRxiv2026

Enhanced processing of cartoons in infant visual cortex

Developing sensory systems may have heightened sensitivity to exaggerated features that emphasize diagnostic information, as shown by the benefits of infant-directed speech for language acquisition. Here, we examine this sensory exaggeration hypothesis in the visual domain by testing whether cartoons elicit stronger and more consistent neural representations than realistic movies in human infants. We collected fMRI data while 24 awake infants (4-15 months) watched the same 3-minute clip of the opening sequence from the original animated version of The Lion King (1994) and its shot-for-shot remake with photorealistic CGI (2019). A computer vision model confirmed that the movies differed in low-level features while depicting similar high-level content. Consistent with sensory exaggeration, the animated version yielded more reliable neural responses and better decoding of visual features than the CGI version throughout occipital cortex. This effect was not observed in adults nor in higher-order regions in infants and could not be explained by differential head motion or looking time. These results suggest that the developing visual system may be attuned to diagnostic features and that cartoons may (unwittingly) exploit this early neural preference.

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bioRxiv2025

Data retention in awake infant fMRI: Lessons from more than 750 scanning sessions

Functional magnetic resonance imaging (fMRI) in awake infants has the potential to reveal how the early developing brain gives rise to cognition and behavior. However, awake infant fMRI poses significant methodological challenges that have hampered wider adoption. The present work takes stock after the collection of a substantial amount of awake infant fMRI data across multiple studies from two labs at different institutions. These data were leveraged to glean insights on participant recruitment, experimental design, and data acquisition that could be useful to consider for future studies. Across 766 fMRI sessions with awake infants aged 1-36 months, the authors explored the factors that influenced how much usable data were obtained per session. The age of an infant predicted whether they would successfully enter the scanner (younger more likely) and, if they did enter, the number of minutes of functional data collected (linear, younger more) and retained after preprocessing with lab-specific protocols or harmonized motion exclusion thresholds (quadratic, 12-24 months more than younger and older). The amount of functional data retained was also influenced by assigned sex (female more), experimental paradigm (movies better than blocks and events), and stimulus content (social better than abstract). There were many differences in the research approach between labs making head-to-head comparisons difficult, but Yale was more likely to get infants into the scanner, MIT collected more data from infants who entered, and the amount of data retained after preprocessing did not differ statistically between labs (9 minutes). In addition, the authors assessed the value of attempting to collect multiple experiments per session, an approach that yielded more than one usable experiment averaging across all sessions. Although any given scan is unpredictable, these findings support the feasibility of awake infant fMRI and suggest practices to optimize future research.

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bioRxiv2023

Movies reveal the fine-grained organization of infant visual cortex

Studying infant minds with movies is a promising way to increase engagement relative to traditional tasks. However, the spatial specificity and functional significance of movie-evoked activity in infants remains unclear. Here we investigated what movies can reveal about the organization of the infant visual system. We collected fMRI data from 15 awake infants and toddlers aged 5-23 months who attentively watched a movie. The activity evoked by the movie reflected the functional profile of visual areas. Namely, homotopic areas from the two hemispheres responded similarly to the movie, whereas distinct areas responded dissim-ilarly, especially across dorsal and ventral visual cortex. Moreover, visual maps that typi-cally require time-intensive and complicated retinotopic mapping could be predicted, albeit imprecisely, from movie-evoked activity in both data-driven analyses (i.e., independent com-ponent analysis) at the individual level and by using functional alignment into a common low-dimensional embedding to generalize across participants. These results suggest that the infant visual system is already structured to process dynamic, naturalistic information and that fine-grained cortical organization can be discovered from movie data.

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bioRxiv2023

Functional networks in the infant brain during sleep and wake states

Functional brain networks are assessed differently early in development than at maturity: infants are almost universally scanned during sleep, whereas adults are typically scanned awake while resting or performing tasks. Observed differences between infant and adult functional networks may thus reflect these differing states of consciousness rather than or in addition to developmental changes. We explore this question by comparing functional networks in fMRI scans acquired from infants during natural sleep and awake movie-watching. As a reference, we also acquired fMRI scans in adults during awake rest and awake movie-watching. Whole-brain functional connectivity was more similar within-state (sleep-sleep, wake-wake) than across-state (sleep-wake) in infants, demonstrating that movies elicit a different network configuration than typical sleep acquisitions. Indeed, a classifier trained on patterns of functional connectivity during infant sleep versus wake robustly decoded the state of additional infants and even generalized to decode rest versus movie in adults; interestingly, a classifier trained on rest versus movie in adults did not generalize nearly as well to sleep versus wake in infants. Moreover, the overall level of similarity between infant and adult functional connectivity was modulated by adult state (stronger for movie than rest) but not infant state (equivalent for sleep and wake). Nevertheless, the network connections that drove similarity between infants and adults, particularly in frontoparietal network, were modulated by infant state. In sum, infant functional connectivity can differ between sleep and wake states, highlighting the potential value of awake data for studying the early development of functional brain networks. Significance statementFunctional networks in the infant brain provide a foundation for early cognitive abilities and act as a marker of brain maturation and developmental disorders. What we know about these networks comes from fMRI data acquired during sleep, given the challenges of awake infant fMRI. This contrasts with the dominant approach in older populations of assessing networks during awake rest or tasks. These differing levels of consciousness cloud the interpretation of developmental changes. Here we show that whole-brain functional connectivity differs between sleeping and awake infants, and that the similarity of these infant states to adults loads on dissociable network connections. This research suggests that a full understanding of early functional brain networks will benefit from complementary insights in awake infants.

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bioRxiv2022

Automated and manual segmentation of the hippocampus in human infants

The hippocampus, critical for learning and memory, undergoes substantial changes early in life. Investigating the developmental trajectory of hippocampal structure and function requires an accurate method for segmenting this region from anatomical MRI scans. Although manual segmentation is regarded as the "gold standard" approach, it is laborious and subjective. This has fueled the pursuit of automated segmentation methods in adults. However, little is known about the reliability of these protocols in human infants, particularly when anatomical scan quality is low from increased head motion or shorter sequences that minimize head motion. During a task-based fMRI protocol, we collected quiet T1-weighted anatomical scans from 42 sessions with awake infants aged 4-23 months. We first had two expert tracers manually segment the hippocampus bilaterally and assess inter-rater reliability. We then attempted to predict these manual segmentations using four protocols: average adult template, average infant template, FreeSurfer software, and Automated Segmentation of Hippocampal Subfields (ASHS) software. ASHS generated the most reliable hippocampal segmentations in infants, exceeding manual inter-rater reliability of the experts. Automated methods can thus provide robust hippocampal segmentations of noisy T1-weighted infant scans, opening new possibilities for interrogating early hippocampal development. HighlightsO_LIInter-rater reliability of manual segmentation of infant hippocampus is moderate. C_LIO_LITemplate-based methods and FreeSurfer provide reasonably accurate segmentations. C_LIO_LIASHS produces highly accurate segmentations, exceeding manual inter-rater reliability. C_LI

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bioRxiv2022

Face processing in the infant brain after pandemic lockdown

The role of visual experience in the development of face processing has long been debated. We present a new angle on this question through a serendipitous study that cannot easily be repeated. Infants viewed short blocks of faces during fMRI in a repetition suppression task. The same identity was presented multiple times in half of the blocks (Repeat condition) and different identities were presented once each in the other half (Novel condition). In adults, the fusiform face area (FFA) tends to show greater neural activity for Novel vs. Repeat blocks in such designs, suggesting that it can distinguish same vs. different face identities. As part of an ongoing study, we collected data before the COVID-19 pandemic and after an initial State lockdown was lifted. The resulting sample of 12 infants (9-24 months) divided equally into pre- and post-lockdown groups with matching ages and data quantity/quality. The groups had strikingly different FFA responses: pre-lockdown infants showed repetition suppression (Novel>Repeat), whereas post-lockdown infants showed the opposite (Repeat>Novel), often referred to as repetition enhancement. These findings provide speculative evidence that altered visual experience during the lockdown, or other correlated environmental changes, may have affected face processing in the infant brain.

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bioRxiv2021

Neural event segmentation of continuous experience in human infants

How infants experience the world is fundamental to understanding their cognition and development. A key principle of adult experience is that, despite receiving continuous sensory input, we perceive this input as discrete events. Here we investigate such event segmentation in infants and how it differs from adults. Research on event cognition in infants often uses simplified tasks in which (adult) experimenters help solve the segmentation problem for infants by defining event boundaries or presenting discrete actions/vignettes. This presupposes which events are experienced by infants and leaves open questions about the principles governing infant segmentation. We take a different, data-driven approach by studying infant event segmentation of continuous input. We collected whole-brain fMRI data from awake infants (and adults, for comparison) watching a cartoon and used a hidden Markov model to identify event states in the brain. We quantified the existence, timescale, and organization of multiple event representations across brain regions. The adult brain exhibited a known hierarchical gradient of event timescales, from shorter events in early visual regions to longer events in later visual and associative regions. In contrast, the infant brain only represented longer events, even in early visual regions, with no timescale hierarchy. The boundaries defining these infant events only partially overlapped with boundaries defined from adult brain activity and behavioral judgments. These findings suggest that events are organized differently in infants, with longer timescales and more stable neural patterns, even in sensory regions. This may indicate greater temporal integration and reduced temporal precision during dynamic, naturalistic perception. Significance StatementSensory input is continuous and yet humans perceive discrete events. This event segmentation has been studied in adults by asking them to indicate natural breaks in continuous input. This classic parsing task is impossible in infants who cannot understand or follow instructions. We circumvent this barrier by testing how the infant brain parses. We applied a computational model to rare awake fMRI data from infants to identify how their brains transitioned between stable states during a cartoon. Whereas adults showed a gradient in event timescales, from shorter events in sensory regions to longer events in associative regions, infants persistently segmented fewer, longer events across the cortical hierarchy. These findings provide new neuroscientific insight into how infants represent their environment.

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bioRxiv2020

Retinotopic organization of visual cortex in human infants

Vision develops rapidly during infancy, yet how visual cortex is organized during this period is unclear. One possibility is that the retinotopic organization of visual cortex emerges gradually as perceptual abilities improve. This may result in a hierarchical maturation of visual areas from striate to extrastriate cortex. Another possibility is that retinotopic organization is present from early infancy. This early maturation of area boundaries and tuning could scaffold further developmental changes. Here we test the functional maturity of infant visual cortex by performing retinotopic mapping with fMRI. Infants aged 5-23 months had retinotopic maps, with alternating preferences for vertical and horizontal meridians indicative of area boundaries from V1 to V4, and an orthogonal gradient of preferences from high to low spatial frequencies indicative of growing receptive field sizes. Although present in the youngest infants, these retinotopic maps showed subtle agerelated changes, suggesting that early maturation undergoes continued refinement.

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bioRxiv2020

Attention recruits frontal cortex in human infants

Young infants learn about the world by overtly shifting their attention to perceptually salient events. In adults, attention recruits several brain regions spanning the frontal and parietal lobes. However, these regions are thought to have a protracted maturation and so it is unclear whether they are recruited in infancy and, more generally, how infant attention is supported by the brain. We used event-related fMRI with 24 awake behaving infants 3-12 months old while they performed a child-friendly attentional cuing task. A target was presented to either the left or right of the infants fixation and eye-tracking was used to measure the latency with which they saccaded to the target. To manipulate attention, a brief cue was presented before the target in three conditions: on the same side as the upcoming target (valid), on the other side (invalid), or on both sides (neutral). All infants were faster to look at the target on valid versus invalid trials, with valid faster than neutral and invalid slower than neutral, indicating that the cues effectively captured attention. We then compared the fMRI activity evoked by these trial types. Regions of adult attention networks activated more strongly for invalid than valid trials, particularly frontal regions such as anterior cingulate cortex. Neither behavioral nor neural effects varied by infant age within the first year, suggesting that these regions may function early in development to support the reorienting of attention. Together, this furthers our mechanistic understanding of how the infant brain controls the allocation of attention.

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bioRxiv2020

Evidence of hippocampal learning in human infants

The hippocampus is essential for human memory. Thus, memory deficiencies in infants are often attributed to hippocampal immaturity. However, the functionality of the infant hippocampus has never been tested directly. Here we report that the human hippocampus is indeed active in infancy. We recorded hippocampal activity using fMRI while awake infants aged 3-24 months viewed sequences of objects. Greater activity was observed when the order of the sequence contained regularities that could be learned compared to when the order was random. The involvement of the hippocampus in such statistical learning, with additional recruitment of the medial prefrontal cortex, is consistent with findings from adults. These results suggest that the hippocampus supports the important ability of infants to extract the structure of their environment through experience.

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bioRxiv2020

Emergence and organization of adult brain function throughout child development

Adult cognitive neuroscience has guided the study of human brain development by identifying regions associated with cognitive functions at maturity. The activity, connectivity, and structure of a region can be compared across ages to characterize the developmental trajectory of the corresponding function. However, observed developmental differences may not only reflect the maturation of the function but also its organization across the brain. That is, a function may be mature in children but supported by different brain regions and thus underestimated by focusing on adult regions. To test these possibilities, we investigated the presence, maturity, and localization of adult functions in children using probabilistic shared response modeling, a machine learning approach for functional alignment. After learning a lower-dimensional feature space from fMRI activity as adults watched a movie, we translated these shared features into the anatomical brain space of children 3-12 years old. To evaluate functional maturity, we correlated this reconstructed activity with the childrens actual fMRI activity as they watched the same movie. We found reliable correlations throughout cortex, even in the youngest children. The strength of the correlation in the precuneus, inferior frontal gyrus, and lateral occipital cortex increased over development and predicted chronological age. These age-related changes were driven by three types of developmental trajectories across distinct features of adult function: emergence from absence to presence, consistency in anatomical expression, and reorganization from one anatomical region to another. This data-driven approach to studying brain-wide function during naturalistic perception provides an abstract description of cognitive development throughout childhood. Significance StatementWhen watching a movie, your brain processes many types of information--plotlines, characters, locations, etc. A child watching this movie receives the same input, but some of their cognitive abilities (e.g., motion detection) are more developed than others (e.g., emotional reasoning). Beyond anatomical differences, when does the child brain begin to function like an adult brain? We used a data-driven approach to extract different aspects of brain activity from adults while they watched a movie during fMRI. We then predicted what the brain activity of a child would look like if they had processed the movie the same way. Comparing this prediction with actual brain activity from children allowed us to track the development of human brain function.

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bioRxiv2020

How to read a baby's mind: Re-imagining fMRI for awake, behaving infants

Thousands of functional magnetic resonance imaging (fMRI) studies have provided important insight into the human brain. However, only a handful of these studies tested infants while they were awake, because of the significant and unique methodological challenges involved. We report our efforts over the past five years to address these challenges, with the goal of creating methods for infant fMRI that can reveal the inner workings of the developing, preverbal mind. We use these methods to collect and analyze two fMRI datasets obtained from infants during cognitive tasks, released publicly with this paper. In these datasets, we explore data quantity and quality, task-evoked activity, and preprocessing decisions to derive and evaluate recommendations for infant fMRI. We disseminate these methods by sharing two software packages that integrate infant-friendly cognitive tasks and behavioral monitoring with fMRI acquisition and analysis. These resources make fMRI a feasible and accessible technique for cognitive neuroscience in human infants.

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bioRxiv2018

Limitations of Topological Data Analysis for event-related fMRI

Recent fMRI research shows that perceptual and cognitive representations are instantiated in high-dimensional multi-voxel patterns in the brain. However, the methods for detecting these representations are limited. Topological Data Analysis (TDA) is a new approach, based on the mathematical field of topology, that can detect unique types of geometric features in patterns of data. Several recent studies have successfully applied TDA to study various forms of neural data; however, to our knowledge, TDA has not been successfully applied to data from event-related fMRI designs. Event-related fMRI is very common but limited in terms of the number of events that can be run within a practical time frame and the effect size that can be expected. Here, we investigate whether persistent homology -- a popular TDA tool that identifies topological features in data and quantifies their robustness -- can identify known signals given these constraints. We use fmrisim, a Python-based simulator of realistic fMRI data, to assess the plausibility of recovering a simple topological representation under a variety of conditions. Our results suggest that persistent homology can be used under certain circumstances to recover topological structure embedded in realistic fMRI data simulations.

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