Evidence of hippocampal learning in human infants

Ellis, Cameron T.; Skalaban, Lena J.; Yates, Tristan S; Bejjanki, Vikranth R.; Córdova, Natalia; Turk‐Browne, Nicholas B.

doi:10.1016/j.cub.2021.04.072

Cited by 58 publications

(60 citation statements)

References 55 publications

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“…We found that the effect of predictability is reflected in every recorded region. This pattern of results provides evidence for a) the frontal lobe involvement in sequential learning and replicates and extends previous work with younger infants using EEG using a very similar paradigm (Basirat et al, 2014) and adds to broader evidence that the frontal lobe is involved in various types of learning in infancy including statistical learning (Ellis et al, 2021), audiovisual associative learning (Emberson et al, 2015;Kersey and Emberson, 2017;Kouider et al, 2015); b) provides from suggestive evidence that these learning based changes are not constrained to the frontal lobe but are also present in posterior perceptual cortices suggesting a role for the frontal lobe and feedback neural connections in these posterior changes; c) that the infant brain is highly plastic and readily shaped through experience with patterns and relatedly learning.…”

Section: Discussionsupporting

confidence: 85%

“…Humans are highly sensitive to statistical information and learn from statistical information incidentally starting early in infancy (need citations). While behavioral studies have made significant progress in understanding the computational mechanisms that underlie statistical learning (Siegelman et al, 2019;Thiessen, 2017), the underlying neural mechanisms that support statistical learning are not yet well understood (Schapiro et al, 2012;Turk-Browne et al, 2009) and there is even less known about the brain regions involved in statistical learning in infants (though see Ellis et al, 2021;Emberson et al, 2015;Kabdebon et al, 2015;Kersey and Emberson, 2017). Importantly, understanding the neural mechanisms supporting statistical learning in infancy will shed light on the mechanisms supporting development, and provide a foundation upon which we can investigate how these learning mechanisms change across conditions, stimuli and over development.…”

Section: Introductionmentioning

confidence: 99%

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Sequence learning attenuates cortical responses in both frontal and perceptual cortices in early infancy

Jaffe-Dax

Herbolzheimer

Bejjanki

et al. 2021

Preprint

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Prior work has found that the frontal lobe is involved in higher-order sequential and statistical learning in young infants. Separate lines of work have found evidence of modulation of posterior sensory cortices during and after learning tasks. How do these processes relate? Here, we build evidence the infant frontal lobe was modulated during sequential learning and ask whether posterior perceptual cortices show corresponding modulation. First, replicating and extending past work, we found evidence of frontal lobe involvement in this task. Second, consistent with our hypotheses, we found that there is a corresponding attenuation of neural responses in the posterior perceptual cortices (temporal and occipital) to predictable compared to unpredictable audiovisual sequences. This study provides convergent evidence that the frontal lobe is crucial for higher-level learning in young infants but that it likely works as part of a large, distributed network of regions to modulate infant neural responses during learning. Overall, this work challenges the view that the infant brain is not dynamic and disconnected, lacking in long-range neural connections. Instead, this paper reveals patterns of a highly dynamic and interconnected infant brain that change rapidly as a result of new, learnable experiences.

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Section: Discussionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Sequence learning attenuates cortical responses in both frontal and perceptual cortices in early infancy

Jaffe-Dax

Herbolzheimer

Bejjanki

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…In particular, it has been suggested that there are two separate, specialized circuits for learning within the hippocampus (Schapiro et al, 2017) that support slower learning of general groups and rapid encoding of specific associations, respectively. While we would expect based on recent findings that the hippocampus would be engaged during statistical learning in infancy (Ellis et al, 2021), it may be through a restricted circuitry relative to adults. Namely, the intra-hippocampal pathways develop at different rates , indicating that perhaps only memory for general groups (via the monosynaptic pathway) would be available to infants (Gomez, 2016;Gómez & Edgin, 2016;Schapiro et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Here, we used a visual statistical learning paradigm-shown to involve the hippocampus both among adults (Schapiro et al, 2012(Schapiro et al, , 2014(Schapiro et al, , 2016 and in development (Ellis et al, 2021;Finn et al, 2019;Schlichting et al, 2016)-to assess the formation of memory for both the specific associations and higher-order relationships embedded within the same experience. We presented participants with a continuous stream of simple shapes shown one at a time.…”

mentioning

confidence: 99%

Memories of structured input become increasingly distorted across development - Working Paper

Forest¹,

Abolghasem²,

Finn³

2021

Preprint

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As early as infancy, humans extract patterns from structured input, and demonstrate the ability to distinguish between reliably experienced patterns and new ones. However, the nature of memories that support these behaviors—and how their structure might change across childhood—remains unknown. Here, we ask what children and adults remember after exposure to a continuous stream of shapes: the particular sequence in which the shapes occurred, their higher-level group structure, or both? We showed 5- to 9-year-olds and adults (N=211) a stream of shapes comprising three triplets (groups of three shapes) that always occurred in a fixed order, followed by an old-new memory test including lure sequences that matched the exposure stream on a particular dimension (e.g., group structure). Given the early emergence of simple associative memories that increase in complexity over development, we predicted that the youngest children in our sample would remember specific shape-shape sequences, while older children and adults would additionally represent groups. After accounting for developmental improvements in overall memory, we found all ages were sensitive to specific transitions: Participants responded “old” to lures with intact shape-shape transitions at above-baseline levels. In contrast, order-independent group memory—as measured by “old” responses to shuffled triplets—was only observed in older children and adults. Our results show that while young children form memories for specific aspects of a structured experience, memory for commonalities across events is refined later—underscoring that even after identical experiences, adults and young children form different memories for those events.

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“…Brain networks expand in cycles reminiscent of intellectual development . Bayesian rule extraction may start from as early as 3 months of age in anterior hippocampus, even before episodic memories are formed (Ellis et al, 2021), laying the ground for building blocks of LoT, when connections with the medial prefrontal cortex are established.…”

Section: Where Does Change In G Come From?mentioning

confidence: 99%

The future of intelligence: The central meaning-making unit of intelligence in the mind, the brain, and artificial intelligence

et al. 2021

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This paper focuses on general intelligence, g. We first point to broadly accepted facts about g: it is robust, reliable, and sensitive to learning. We then summarize conflicting theories about its nature and development (Mutualism, Process Overlap Theory, and Dynamic Mental Field Theory) and suggest how future research may resolve their disputes. A model is proposed for g involving a core meaning-making mechanism, noetron, drawing on Alignment, Abstraction, and Cognizance, perpetually generating new mental content. Noetron develops through several levels of control: episodic → attentional → inferential → truth → epistemic control in infancy, preschool, childhood, adolescence, and adulthood, respectively. Finally, we propose an agenda for future brain, assuming a brain noetron, and artificial intelligence research, assuming an artificial noetron, that might uncover the underlying brain mechanisms of g and generate artificial general intelligence.

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Evidence of hippocampal learning in human infants

Cited by 58 publications

References 55 publications

Sequence learning attenuates cortical responses in both frontal and perceptual cortices in early infancy

Sequence learning attenuates cortical responses in both frontal and perceptual cortices in early infancy

Memories of structured input become increasingly distorted across development - Working Paper

The future of intelligence: The central meaning-making unit of intelligence in the mind, the brain, and artificial intelligence

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