Biology subjects

Hazeltine, E.

Publications and source records attributed to Hazeltine, E..

4 recordsLinked to original sources

bioRxiv2024

Decoding task representations that support generalization in hierarchical task

Task knowledge can be encoded hierarchically such that complex tasks can be built by associating simpler tasks. This associative organization supports generalization to facilitate learning of related but novel complex tasks. To study how the brain implements generalization in hierarchical task learning, we trained human participants on two complex tasks that shared a simple task and tested them on novel complex tasks whose association could be inferred via the shared simple task. Behaviorally, we observed faster learning of the novel complex tasks than control tasks. Using electroencephalogram (EEG) data, we decoded constituent simple tasks when performing a complex task (i.e., EEG association effect). Crucially, the shared simple task, although not part of the novel complex task, could be reliably decoded from the novel complex task. This decoding strength was correlated with EEG association effect and behavioral generalization effect. The findings demonstrate how task learning can be accelerated by associative inference. Significance StatementHumans can generalize knowledge of existing tasks to accelerate the learning of new tasks. We hypothesize that this generalization is achieved by building complex tasks that associate simple (sub)tasks that can be reused. Using electroencephalogram (EEG) data, we showed that constituent simple tasks can be decoded from the EEG data of humans learning new complex tasks. Crucially, when participants represent complex tasks as associations between multiple simple tasks, the simple tasks can be decoded from the new complex task, even when they are not part of the new complex task. These findings demonstrate the importance of the reinstatement of simple tasks in task learning through generalization.

neuroscience↗

bioRxiv2023

Global functional connectivity of cognitive control network predicts task-switching performance in older adults

Executive Function (EF) is a complex higher order cognitive process that involves integrating subprocesses of attention, working memory, inhibition, and task switching and known to be one of the first cognitive functions to be affected by age related declines. Global Functional Connectivity (GFC), a measure of whole brain connectivity in brain networks such as the Cognitive Control Network (CCN), has been shown to measure the maintained EF abilities in older adults with cognitive impairment. However, this relationship has not been explored in a sample comprised of mostly cognitively normal older adults nor with the use of an experimental EF task sensitive to sub-processes most sensitive to aging. Task-switch paradigm studies have shown age-related deficits in holding and responding to rule sets while inhibiting another rule set in working memory (i.e., mixing cost). The present study aims to elucidate the relationship seen in EF performance using GFC and leveraging a task-switch paradigm that manipulates response overlap to increase cognitive demands on switching between tasks (e.g., mixing cost). Results show that greater negative DMN GFC coincides with older adults lower mixing costs, not CCN GFC. Findings indicate that DMN GFC, not CCN, may be important for EF performance in older adults.

neuroscience↗

bioRxiv2022

Lingering neural representations of past task features adversely affect future behavior

During goal-directed behavior, humans purportedly form and retrieve so called event files - conjunctive representations that link context-specific information about stimuli, their associated actions, and the expected action-outcomes. The automatic formation - and later retrieval - of such conjunctive event file representations can substantially facilitate efficient action selection. However, recent behavioral work suggests that these event-files may also adversely affect future behavior, especially when action requirements have changed between successive instances of the same task context (e.g., during task-switching). Here, we directly tested this hypothesis through a recently developed method that allows measuring the strength of the neural representations of context-specific stimulus-action conjunctions (i.e., event files). Thirty-five male and female adult humans performed a task-switching paradigm while undergoing EEG recordings. Replicating previous behavioral work, we found that changes in action requirements between two spaced repetitions of the same task incurred a significant reaction time cost. By combining multi-variate pattern analysis and representational similarity analysis of the EEG recordings with linear mixed-effects modeling of trial-to-trial behavior, we then found that the magnitude of this behavioral cost was directly proportional to the strength of the conjunctive representation formed during the most recent previous exposure to the same task - i.e., the most recent event file. This confirms that the formation of conjunctive representations of specific task contexts, stimuli, and actions in the brain can indeed adversely affect future behavior. Moreover, these findings demonstrate the potential of neural decoding of complex task set representations towards the prediction of behavior beyond the current trial.

neuroscience↗

bioRxiv2019

Cardiorespiratory fitness predicts greater hippocampal volume and rate of episodic associative learning in older adults

Declining episodic memory is common among otherwise healthy older adults, in part due to negative effects of aging on hippocampal circuits. However, there is significant variability between individuals in severity of aging effects on the hippocampus and subsequent memory decline. Importantly, variability may be influenced by modifiable protective physiological factors such as cardiorespiratory fitness (CRF). More research is needed to better understand which aspects of cognition that decline with aging benefit most from CRF. The current study evaluated the relation of CRF with learning rate in the Episodic Associative Learning (EAL) task, a task designed specifically to target hippocampal-dependent relational binding and to evaluate learning with repeated occurrences. Results show that higher CRF was associated with larger hippocampal volume and faster learning rate. Larger hippocampal volume was also associated with faster learning rate, and hippocampal volume partially mediated the relationship between CRF and learning rate. Further, to support the distinction between learning item relations and learning higher-order sequences, which declines with aging but is largely reliant on extra-hippocampal learning systems, we found that EAL learning rate was not related to motor sequence learning on the alternating serial reaction time task. Motor sequence learning was also not correlated with hippocampal volume. Thus, for the first time we show that higher CRF in healthy older adults is related to enhanced rate of relational memory acquisition, in part mediated by benefits on the hippocampus.

neuroscience↗