scholarly journals Linking Models with Brain Measures

2020 ◽  
Author(s):  
Bradley C. Love
Keyword(s):  
Information Flow ◽  
Cognitive Processes ◽  
Brain Activity ◽  
Cognitive Model ◽  
Brain Regions ◽  
Learning Models ◽  
Model Based ◽  
Theoretical Significance ◽  
Brain Data ◽  
The Brain

Linking models and brain measures offers a number of advantages over standard analyses. Models that have been evaluated on previous datasets can provide theoretical constraints and assist in integrating findings across studies. Model-based analyses can be more sensitive and allow for evaluation of hypotheses that would not otherwise be addressable. For example, a cognitive model that is informed from several behavioural studies could be used to examine how multiple cognitive processes unfold across time in the brain. Models can be linked to brain measures in a number of ways. The information flow and constraints can be from model to brain, brain to model, or reciprocal. Likewise, the linkage from model and brain can be univariate or multivariate, as in studies that relate patterns of brain activity with model states. Models have multiple aspects that can be related to different facets of brain activity. This is well illustrated by deep learning models that have multiple layers or representations that can be aligned with different brain regions. Model-based approaches offer a lens on brain data that is complementary to popular multivariate decoding and representational similarity analysis approaches. Indeed, these approaches can realise greater theoretical significance when situated within a model-based approach.

Neural Mechanisms of Evaluation and Memory of Product

2014 ◽  
Author(s):  
Kazutaka Ueda
Keyword(s):  
Cognitive Processes ◽  
Declarative Memory ◽  
Brain Activity ◽  
Neural Model ◽  
Product Evaluation ◽  
Brain Regions ◽  
Preference Rating ◽  
Gamma Frequency ◽  
The Brain ◽  
Healthy Participants

A consumer’s emotional response to a product is influenced by cognitive processes, such as memories associated with use of the product and expectations of its performance. Here, we propose a cognitive neural model of Expectology, called PEAM (Prediction - Experience - Appraisal - Memory), as a novel tool that considers consumers’ emotional responses in order to aid in product design. The PEAM model divides cognitive processes associated with product use into 4 phases: prediction, experience, appraisal, and memory. We examined the spatiotemporal changes in brain activity associated with product evaluation and memory during the prediction phase, by obtaining electroencephalograms (EEGs). EEGs of 10 healthy participants with normal or corrected-to-normal vision were recorded while they viewed images of products as well as when they provided a preference rating for each product. Our results revealed significantly increased neural activity in the gamma frequency in the temporal areas, the brain regions where declarative memory is stored, and in the prefrontal area for products that were rated as preferable. Our data suggest that memory is used for product evaluation in the prediction phase. These findings also suggest that activity in these specific brain areas are reliable predictors for product evaluation.

Inefficient Encoding as an Explanation for Age-Related Deficits in Recollection-Based Processing

2014 ◽  
Vol 28 (3) ◽  
pp. 148-161 ◽  
Author(s):  
David Friedman ◽  
Ray Johnson
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Cognitive Processes ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Semantic Retrieval ◽  
Age Related ◽  
The Face ◽  
Episodic Memories

A cardinal feature of aging is a decline in episodic memory (EM). Nevertheless, there is evidence that some older adults may be able to “compensate” for failures in recollection-based processing by recruiting brain regions and cognitive processes not normally recruited by the young. We review the evidence suggesting that age-related declines in EM performance and recollection-related brain activity (left-parietal EM effect; LPEM) are due to altered processing at encoding. We describe results from our laboratory on differences in encoding- and retrieval-related activity between young and older adults. We then show that, relative to the young, in older adults brain activity at encoding is reduced over a brain region believed to be crucial for successful semantic elaboration in a 400–1,400-ms interval (left inferior prefrontal cortex, LIPFC; Johnson, Nessler, & Friedman, 2013 ; Nessler, Friedman, Johnson, & Bersick, 2007 ; Nessler, Johnson, Bersick, & Friedman, 2006 ). This reduced brain activity is associated with diminished subsequent recognition-memory performance and the LPEM at retrieval. We provide evidence for this premise by demonstrating that disrupting encoding-related processes during this 400–1,400-ms interval in young adults affords causal support for the hypothesis that the reduction over LIPFC during encoding produces the hallmarks of an age-related EM deficit: normal semantic retrieval at encoding, reduced subsequent episodic recognition accuracy, free recall, and the LPEM. Finally, we show that the reduced LPEM in young adults is associated with “additional” brain activity over similar brain areas as those activated when older adults show deficient retrieval. Hence, rather than supporting the compensation hypothesis, these data are more consistent with the scaffolding hypothesis, in which the recruitment of additional cognitive processes is an adaptive response across the life span in the face of momentary increases in task demand due to poorly-encoded episodic memories.

scholarly journals Prefrontal solution to the bias-variance tradeoff during reinforcement learning

2020 ◽  
Author(s):  
Dongjae Kim ◽  
Jaeseung Jeong ◽  
Sang Wan Lee
Keyword(s):  
Adaptive Control ◽  
Reinforcement Learning ◽  
Prediction Error ◽  
Brain Regions ◽  
Decision Task ◽  
Prediction Errors ◽  
Model Based ◽  
Model Free ◽  
Bias Variance ◽  
The Brain

AbstractThe goal of learning is to maximize future rewards by minimizing prediction errors. Evidence have shown that the brain achieves this by combining model-based and model-free learning. However, the prediction error minimization is challenged by a bias-variance tradeoff, which imposes constraints on each strategy’s performance. We provide new theoretical insight into how this tradeoff can be resolved through the adaptive control of model-based and model-free learning. The theory predicts the baseline correction for prediction error reduces the lower bound of the bias–variance error by factoring out irreducible noise. Using a Markov decision task with context changes, we showed behavioral evidence of adaptive control. Model-based behavioral analyses show that the prediction error baseline signals context changes to improve adaptability. Critically, the neural results support this view, demonstrating multiplexed representations of prediction error baseline within the ventrolateral and ventromedial prefrontal cortex, key brain regions known to guide model-based and model-free learning.One sentence summaryA theoretical, behavioral, computational, and neural account of how the brain resolves the bias-variance tradeoff during reinforcement learning is described.

scholarly journals Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

2021 ◽  
Author(s):  
Takashi Nakano ◽  
Masahiro Takamura ◽  
Haruki Nishimura ◽  
Maro Machizawa ◽  
Naho Ichikawa ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Fmri Data ◽  
Independent Test ◽  
The Individual ◽  
The Brain

AbstractNeurofeedback (NF) aptitude, which refers to an individual’s ability to change its brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical NF applications. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude independent of NF-targeting brain regions. We combined the data in fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect the resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Next we validated the prediction model using independent test data from another site. The result showed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting NF aptitude may be involved in the attentional mode-orientation modulation system’s characteristics in task-free resting-state brain activity.

scholarly journals Brain Activity during Visual and Auditory Word Rhyming Tasks in Cantonese–Mandarin–English Trilinguals

2020 ◽  
Vol 10 (12) ◽  
pp. 936
Author(s):  
Yujia Wu ◽  
Jingwen Ma ◽  
Lei Cai ◽  
Zengjian Wang ◽  
Miao Fan ◽  
...  
Keyword(s):  
Phonological Processing ◽  
Brain Activity ◽  
Brain Regions ◽  
Writing Systems ◽  
Significant Interaction Effect ◽  
Chinese College Students ◽  
Second Languages ◽  
Auditory Word ◽  
Visual Tasks ◽  
The Brain

It is unclear whether the brain activity during phonological processing of second languages (L2) is similar to that of the first language (L1) in trilingual individuals, especially when the L1 is logographic, and the L2s are logographic and alphabetic, respectively. To explore this issue, this study examined brain activity during visual and auditory word rhyming tasks in Cantonese–Mandarin–English trilinguals. Thirty Chinese college students whose L1 was Cantonese and L2s were Mandarin and English were recruited. Functional magnetic resonance imaging (fMRI) was conducted while subjects performed visual and auditory word rhyming tasks in three languages (Cantonese, Mandarin, and English). The results revealed that in Cantonese–Mandarin–English trilinguals, whose L1 is logographic and the orthography of their L2 is the same as L1—i.e., Mandarin and Cantonese, which share the same set of Chinese characters—the brain regions for the phonological processing of L2 are different from those of L1; when the orthography of L2 is quite different from L1, i.e., English and Cantonese who belong to different writing systems, the brain regions for the phonological processing of L2 are similar to those of L1. A significant interaction effect was observed between language and modality in bilateral lingual gyri. Regions of interest (ROI) analysis at lingual gyri revealed greater activation of this region when using English than Cantonese and Mandarin in visual tasks.

scholarly journals Sensorimotor brain dynamics reflect architectural affordances

2019 ◽  
Vol 116 (29) ◽  
pp. 14769-14778 ◽  
Author(s):  
Zakaria Djebbara ◽  
Lars Brorson Fich ◽  
Laura Petrini ◽  
Klaus Gramann
Keyword(s):  
Cognitive Processes ◽  
Cognitive Neuroscience ◽  
Brain Activity ◽  
Physical Structure ◽  
Ongoing Debate ◽  
Head Mounted Displays ◽  
Actual Movement ◽  
Imaging Approach ◽  
Essential Function ◽  
The Brain

Anticipating meaningful actions in the environment is an essential function of the brain. Such predictive mechanisms originate from the motor system and allow for inferring actions from environmental affordances, and the potential to act within a specific environment. Using architecture, we provide a unique perspective on the ongoing debate in cognitive neuroscience and philosophy on whether cognition depends on movement or is decoupled from our physical structure. To investigate cognitive processes associated with architectural affordances, we used a mobile brain/body imaging approach recording brain activity synchronized to head-mounted displays. Participants perceived and acted on virtual transitions ranging from nonpassable to easily passable. We found that early sensory brain activity, on revealing the environment and before actual movement, differed as a function of affordances. In addition, movement through transitions was preceded by a motor-related negative component that also depended on affordances. Our results suggest that potential actions afforded by an environment influence perception.

Neurocognitive Aging and Functional Connectivity Using Functional Magnetic Resonance Imaging

2018 ◽  
Author(s):  
Hana Burianová
Keyword(s):  
Functional Connectivity ◽  
Cognitive Processes ◽  
Large Scale ◽  
Healthy Aging ◽  
Brain Activity ◽  
Brain Regions ◽  
Effective Strategies ◽  
Cognitive Improvement ◽  
Age Related ◽  
Neurocognitive Aging

Determining the mechanisms that underlie neurocognitive aging, such as compensation or dedifferentiation, and facilitating the development of effective strategies for cognitive improvement is essential due to the steadily rising aging population. One approach to study the characteristics of healthy aging comprises the assessment of functional connectivity, delineating markers of age-related neurocognitive plasticity. Functional connectivity paradigms characterize complex one-to-many (or many-to-many) structure–function relations, as higher-level cognitive processes are mediated by the interaction among a number of functionally related neural areas rather than localized to discrete brain regions. Task-related or resting-state interregional correlations of brain activity have been used as reliable indices of functional connectivity, delineating age-related alterations in a number of large-scale brain networks, which subserve attention, working memory, episodic retrieval, and task-switching. Together with behavioral and regional activation studies, connectivity studies and modeling approaches have contributed to our understanding of the mechanisms of age-related reorganization of distributed functional networks; specifically, reduced neural specificity (dedifferentiation) and associated impairment in inhibitory control and compensatory neural recruitment.

scholarly journals Transient brain networks underlying interpersonal strategies during synchronized action

2020 ◽  
Author(s):  
Ole Adrian Heggli ◽  
Ivana Konvalinka ◽  
Joana Cabral ◽  
Elvira Brattico ◽  
Morten L Kringelbach ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Network ◽  
Human Interaction ◽  
Action Perception ◽  
Network Information ◽  
Mutual Adaptation ◽  
Underlying Mechanisms ◽  
The Brain

Abstract Interpersonal coordination is a core part of human interaction, and its underlying mechanisms have been extensively studied using social paradigms such as joint finger-tapping. Here, individual and dyadic differences have been found to yield a range of dyadic synchronization strategies, such as mutual adaptation, leading–leading, and leading–following behaviour, but the brain mechanisms that underlie these strategies remain poorly understood. To identify individual brain mechanisms underlying emergence of these minimal social interaction strategies, we contrasted EEG-recorded brain activity in two groups of musicians exhibiting the mutual adaptation and leading–leading strategies. We found that the individuals coordinating via mutual adaptation exhibited a more frequent occurrence of phase-locked activity within a transient action–perception-related brain network in the alpha range, as compared to the leading–leading group. Furthermore, we identified parietal and temporal brain regions that changed significantly in the directionality of their within-network information flow. Our results suggest that the stronger weight on extrinsic coupling observed in computational models of mutual adaptation as compared to leading–leading might be facilitated by a higher degree of action–perception network coupling in the brain.

scholarly journals Experience-dependent plasticity modulates ongoing activity in the antennal lobe and enhance odor representations

2021 ◽  
Author(s):  
Luis M. Franco ◽  
Emre Yaksi
Keyword(s):  
Antennal Lobe ◽  
Internal State ◽  
Brain Activity ◽  
Fruit Fly ◽  
Brain Regions ◽  
Projection Neurons ◽  
Ongoing Activity ◽  
Dependent Plasticity ◽  
Olfactory Glomeruli ◽  
The Brain

ABSTRACTOngoing neural activity has been observed across several brain regions and thought to reflect the internal state of the brain. Yet, it is not fully understood how ongoing brain activity interacts with sensory experience and shape sensory representations. Here, we show that projection neurons of the fruit fly antennal lobe exhibit spatiotemporally organized ongoing activity in the absence of odor stimulation. Upon repeated exposure to odors, we observe a gradual and long-lasting decrease in the amplitude and frequency of spontaneous calcium events, as well as a reorganization of correlations between olfactory glomeruli during ongoing activity. Accompanying these plastic changes, we find that repeated odor experience reduces trial-to-trial variability and enhances the specificity of odor representations. Our results reveal a previously undescribed experience-dependent plasticity of ongoing and sensory driven activity at peripheral levels of the fruit fly olfactory system.

scholarly journals The Relationship Between Cognition and Cerebrovascular Reactivity: Implications for Task-Based fMRI

2021 ◽  
Vol 9 ◽  
Author(s):  
Rebecca J. Williams ◽  
M. Ethan MacDonald ◽  
Erin L. Mazerolle ◽  
G. Bruce Pike
Keyword(s):  
Cognitive Processes ◽  
Brain Function ◽  
Vascular Function ◽  
Brain Regions ◽  
Cerebrovascular Reactivity ◽  
Vascular Health ◽  
Vascular Changes ◽  
Future Directions ◽  
The Relationship ◽  
The Brain

Elucidating the brain regions and networks associated with cognitive processes has been the mainstay of task-based fMRI, under the assumption that BOLD signals are uncompromised by vascular function. This is despite the plethora of research highlighting BOLD modulations due to vascular changes induced by disease, drugs, and aging. On the other hand, BOLD fMRI-based assessment of cerebrovascular reactivity (CVR) is often used as an indicator of the brain's vascular health and has been shown to be strongly associated with cognitive function. This review paper considers the relationship between BOLD-based assessments of CVR, cognition and task-based fMRI. How the BOLD response reflects both CVR and neural activity, and how findings of altered CVR in disease and in normal physiology are associated with cognition and BOLD signal changes are discussed. These are pertinent considerations for fMRI applications aiming to understand the biological basis of cognition. Therefore, a discussion of how the acquisition of BOLD-based CVR can enhance our ability to map human brain function, with limitations and potential future directions, is presented.

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