An official website of the United States government
ABSTRACT Behavioral variation within a population can be influenced by physical factors such as size, sex, and body condition. This variation may contribute to intraspecific niche breadth by enabling individuals to exploit different niches. To examine how anatomy shapes behavior, we conducted open field tests on desert kangaroo rats (Dipodomys deserti, n=16) and compared their activity to sex, morphology, and body condition. We constructed an arena within the species' natural habitat to simulate ecologically relevant conditions and recorded behavior over 15 min. We quantified speed and distance traveled, used principal component analysis to explore behavioral patterns, and used linear models to test for associations between behavior, locomotor traits, and anatomical variables. We found that individuals with lower body condition scores spent more time exploring, males were more exploratory than females, and individuals with longer feet – a proxy for skeletal size – traveled further. However, behavior and locomotor performance were not significantly correlated. Lastly, individuals moved faster and farther on full moon nights compared to new moon nights, indicating that moonlight influences movement strategy – potentially reflecting trade-offs between foraging and predation risk. These findings highlight species-specific drivers of behavioral variation and underscore the importance of understanding behavioral variability of desert mammals.
more »
« less
High performers demonstrate greater neural synchrony than low performers across behavioral domains
Abstract Heterogeneity in brain activity can give rise to heterogeneity in behavior, which in turn comprises our distinctive characteristics as individuals. Studying the path from brain to behavior, however, often requires making assumptions about how similarity in behavior scales with similarity in brain activity. Here, we expand upon recent work (Finn et al., 2020) which proposes a theoretical framework for testing the validity of such assumptions. Using intersubject representational similarity analysis in two independent movie-watching functional MRI (fMRI) datasets, we probe how brain-behavior relationships vary as a function of behavioral domain and participant sample. We find evidence that, in some cases, the neural similarity of two individuals is not correlated with behavioral similarity. Rather, individuals with higher behavioral scores are more similar to other high scorers whereas individuals with lower behavioral scores are dissimilar from everyone else. Ultimately, our findings motivate a more extensive investigation of both the structure of brain-behavior relationships and the tacit assumption that people who behave similarly will demonstrate shared patterns of brain activity.
more »
« less
- Award ID(s):
- 2043740
- PAR ID:
- 10508006
- Publisher / Repository:
- MIT Press
- Date Published:
- Journal Name:
- Imaging Neuroscience
- Volume:
- 2
- ISSN:
- 2837-6056
- Page Range / eLocation ID:
- 1 to 17
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Traditional tests of concept knowledge generate scores to assess how well a learner understands a concept. Here, we investigated whether patterns of brain activity collected during a concept knowledge task could be used to compute a neural ‘score’ to complement traditional scores of an individual’s conceptual understanding. Using a novel data-driven multivariate neuroimaging approach—informational network analysis—we successfully derived a neural score from patterns of activity across the brain that predicted individual differences in multiple concept knowledge tasks in the physics and engineering domain. These tasks include an fMRI paradigm, as well as two other previously validated concept inventories. The informational network score outperformed alternative neural scores computed using data-driven neuroimaging methods, including multivariate representational similarity analysis. This technique could be applied to quantify concept knowledge in a wide range of domains, including classroom-based education research, machine learning, and other areas of cognitive science.more » « less
-
Abstract Multiple human behaviors improve early in life, peaking in young adulthood, and declining thereafter. Several properties of brain structure and function progress similarly across the lifespan. Cognitive and neuroscience research has approached aging primarily using associations between a few behaviors, brain functions, and structures. Because of this, the multivariate, global factors relating brain and behavior across the lifespan are not well understood. We investigated the global patterns of associations between 334 behavioral and clinical measures and 376 brain structural connections in 594 individuals across the lifespan. A single-axis associated changes in multiple behavioral domains and brain structural connections (r = 0.5808). Individual variability within the single association axis well predicted the age of the subject (r = 0.6275). Representational similarity analysis evidenced global patterns of interactions across multiple brain network systems and behavioral domains. Results show that global processes of human aging can be well captured by a multivariate data fusion approach.more » « less
-
Abstract Patterns of whole-brain fMRI functional connectivity, or connectomes, are unique to individuals. Previous work has identified subsets of functional connections within these patterns whose strength predicts aspects of attention and cognition. However, overall features of these connectomes, such as how stable they are over time and how similar they are to a group-average (typical) or high-performance (optimal) connectivity pattern, may also reflect cognitive and attentional abilities. Here, we test whether individuals who express more stable, typical, optimal, and distinctive patterns of functional connectivity perform better on cognitive tasks using data from three independent samples. We find that individuals with more stable task-based functional connectivity patterns perform better on attention and working memory tasks, even when controlling for behavioral performance stability. Additionally, we find initial evidence that individuals with more typical and optimal patterns of functional connectivity also perform better on these tasks. These results demonstrate that functional connectome stability within individuals and similarity across individuals predicts individual differences in cognition.more » « less
-
Nonergodicity and Simpson’s paradox present significant, yet underappreciated challenges in neuroscience. Leveraging brain imaging and behavioral data from over 4,000 children and a Bayesian computational model of cognitive dynamics, we investigated brain-behavior relationships underlying cognitive control at both between-subjects and within-subjects levels. Strikingly, we observed a reversal of associations of inhibitory control brain activations with dynamic behavioral measures when comparing between-subjects and within-subjects analyses, revealing the nonergodic nature of these processes. This nonergodicity was pervasive throughout the brain but most pronounced in the salience network. Additionally, within-subjects analysis uncovered dissociated brain representations of reactive and proactive control processes, as well as distinct brain-behavior associations for individuals who adaptively versus maladaptively regulated cognitive control. Our findings offer insights into dynamic neural mechanisms of cognitive control during a critical developmental period. This work highlights the importance of embracing nonergodicity in human neuroscience, with implications for both theoretical understanding and applications to AI and psychopathology.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1162/imag_a_00128
