Human brains experience whole-brain anatomic and functional changes throughout the lifespan. Age-related whole-brain network changes have been studied with functional magnetic resonance imaging (fMRI) to determine their low-frequency spatial and temporal characteristics. However, little is known about age-related changes in whole-brain fast dynamics at the scale of neuronal events. The present study investigated age-related whole-brain dynamics in resting-state electroencephalography (EEG) signals from 73 healthy participants from 6 to 65 years old via characterizing transient neuronal coactivations at a resolution of tens of milliseconds. These uncovered transient patterns suggest fluctuating brain states at different energy levels of global activations. Our results indicate that with increasing age, shorter lifetimes and more occurrences were observed in the brain states that show the global high activations and more consecutive visits to the global highest-activation brain state. There were also reduced transitional steps during consecutive visits to the global lowest-activation brain state. These age-related effects suggest reduced stability and increased fluctuations when visiting high-energy brain states and with a bias toward staying low-energy brain states. These age-related whole-brain dynamics changes are further supported by changes observed in classic alpha and beta power, suggesting its promising applications in examining the effect of normal healthy brain aging, brain development, and brain disease.
The study presented in this paper applies hidden Markov modeling (HMM) to uncover the recurring patterns within a neural activation dataset collected while designers engaged in a design concept generation task. HMM uses a probabilistic approach that describes data (here, fMRI neuroimaging data) as a dynamic sequence of discrete states. Without prior assumptions on the fMRI data's temporal and spatial properties, HMM enables an automatic inference on states in neurocognitive activation data that are highly likely to occur in concept generation. The states with a higher likelihood of occupancy show more activation in the brain regions from the executive control network, the default mode network, and the middle temporal cortex. Different activation patterns and transfers are associated with these states, linking to varying cognitive functions, for example, semantic processing, memory retrieval, executive control, and visual processing, that characterize possible transitions in cognition related to concept generation. HMM offers new insights into cognitive dynamics in design by uncovering the temporal and spatial patterns in neurocognition related to concept generation. Future research can explore new avenues of data analysis methods to investigate design neurocognition and provide a more detailed description of cognitive dynamics in design.
more » « less- Award ID(s):
- 2145432
- NSF-PAR ID:
- 10482207
- Publisher / Repository:
- Cambridge University Press
- Date Published:
- Journal Name:
- Artificial Intelligence for Engineering Design, Analysis and Manufacturing
- Volume:
- 37
- ISSN:
- 0890-0604
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract -
Neuroimaging provides a relatively new approach for advancing engineering education by exploring changes in neurocognition from educational interventions. The purpose of the research described in this paper is to present the results of a preliminary study that measured students’ neurocognition while concept mapping. Engineering design is an iterative process of exploring both the problem and solution spaces. To aid students in exploring these spaces, half of the 66 engineering students who participated in the study were first asked to develop a concept map and then construct a design problem statement. The concept mapping activity significantly reduced neurocognitive activation in the students’ left prefrontal cortex (PFC) compared to students who did not receive this intervention when constructing their problem statement. The sub-region in the left PFC that elicited less activation is generally associated with analytical judgment and goal-directed planning. The group of students who completed the concept mapping activity had greater focused neurocognitive activation in their right PFC. The right PFC is often associated with divergent thinking and ill-structured representation. Patterns of functional connectivity across students’ PFC also differed between the groups. The concept mapping activity reduced the network density in students’ PFC. Lower network density is one measure of lower cognitive effort. These results provide new insight into the neurocognition of engineering students when designing and how educational interventions can change engineering students’ neurocognition. A better understanding of how interventions like concept mapping shape students’ neurocognition, and how this relates to learning, can lay the groundwork for novel advances in engineering education that support new tools and pedagogy for engineering design.more » « less
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The research presented in this paper explores features of temporal design neurocognition by comparing regions of activation in the brain during concept generation. A total of 27 engineering graduate students used brainstorming, morphological analysis, and TRIZ to generate concepts to design problems. Students' brain activation in their prefrontal cortex (PFC) was measured using functional near-infrared spectroscopy (fNIRS). Temporal activations were compared between techniques. When using brainstorming and morphological analysis, highly activated regions are consistently situated in the medial and right part of the PFC over time. For both techniques, the temporal neuro-physiological patterns are similar. Cognitive functions associated to the medial and right part of the PFC suggest an association with divergent thinking and adaptive decision making. In contrast, highly activated regions over time when using TRIZ appear in the medial or the left part of the prefrontal cortex, usually associated with goal directed planning.more » « less
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Abstract Cognitive neuroscience methods can identify the fMRI-measured neural representation of familiar individual concepts, such as apple, and decompose them into meaningful neural and semantic components. This approach was applied here to determine the neural representations and underlying dimensions of representation of far more abstract physics concepts related to matter and energy, such as fermion and dark matter, in the brains of 10 Carnegie Mellon physics faculty members who thought about the main properties of each of the concepts. One novel dimension coded the measurability vs. immeasurability of a concept. Another novel dimension of representation evoked particularly by post-classical concepts was associated with four types of cognitive processes, each linked to particular brain regions: (1) Reasoning about intangibles, taking into account their separation from direct experience and observability; (2) Assessing consilience with other, firmer knowledge; (3) Causal reasoning about relations that are not apparent or observable; and (4) Knowledge management of a large knowledge organization consisting of a multi-level structure of other concepts. Two other underlying dimensions, previously found in physics students, periodicity, and mathematical formulation, were also present in this faculty sample. The data were analyzed using factor analysis of stably responding voxels, a Gaussian-naïve Bayes machine-learning classification of the activation patterns associated with each concept, and a regression model that predicted activation patterns associated with each concept based on independent ratings of the dimensions of the concepts. The findings indicate that the human brain systematically organizes novel scientific concepts in terms of new dimensions of neural representation.
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1017/S0890060423000021
