Moving outside the lab: The viability of conducting sensorimotor learning studies online

JS Tsay, A Lee, RB Ivry, G Avraham - arXiv preprint arXiv:2107.13408, 2021 - arxiv.org
Collecting data online via crowdsourcing platforms has proven to be a very efficient way to
recruit a large and diverse sample. Studies of motor learning, however, have been largely …

Predicting memory from the network structure of naturalistic events

H Lee, J Chen - Nature Communications, 2022 - nature.com
When we remember events, we often do not only recall individual events, but also the
connections between them. However, extant research has focused on how humans segment …

How humans learn and represent networks

CW Lynn, DS Bassett - … of the National Academy of Sciences, 2020 - National Acad Sciences
Humans receive information from the world around them in sequences of discrete items—
from words in language or notes in music to abstract concepts in books and websites on the …

On curiosity: a fundamental aspect of personality, a practice of network growth

P Zurn, DS Bassett - Personality Neuroscience, 2018 - cambridge.org
Human personality is reflected in patterns—or networks—of behavior, either in thought or
action. Curiosity is an oft-treasured component of one's personality, commonly associated …

Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data

M Bönstrup, I Iturrate, MN Hebart, N Censor… - npj Science of …, 2020 - nature.com
Performance improvements during early human motor skill learning are suggested to be
driven by short periods of rest during practice, at the scale of seconds. To reveal the …

Human information processing in complex networks

CW Lynn, L Papadopoulos, AE Kahn, DS Bassett - Nature Physics, 2020 - nature.com
Humans communicate using systems of interconnected stimuli or concepts—from language
and music to literature and science—yet it remains unclear how, if at all, the structure of …

Network architectures supporting learnability

P Zurn, DS Bassett - … Transactions of the Royal Society B, 2020 - royalsocietypublishing.org
Human learners acquire complex interconnected networks of relational knowledge. The
capacity for such learning naturally depends on two factors: the architecture (or informational …

Sleep targets highly connected global and local nodes to aid consolidation of learned graph networks

GB Feld, M Bernard, AB Rawson, HJ Spiers - Scientific Reports, 2022 - nature.com
Much of our long-term knowledge is organised in complex networks. Sleep is thought to be
critical for abstracting knowledge and enhancing important item memory for long-term …

Abstract representations of events arise from mental errors in learning and memory

CW Lynn, AE Kahn, N Nyema, DS Bassett - Nature communications, 2020 - nature.com
Humans are adept at uncovering abstract associations in the world around them, yet the
underlying mechanisms remain poorly understood. Intuitively, learning the higher-order …

[HTML][HTML] Reduced functional connectivity supports statistical learning of temporally distributed regularities

J Park, K Janacsek, D Nemeth, HA Jeon - NeuroImage, 2022 - Elsevier
Statistical learning is a powerful ability that extracts regularities from our environment and
makes predictions about future events. Using functional magnetic resonance imaging, we …