Biology subjects

Grahek, I.

Publications and source records attributed to Grahek, I..

5 recordsLinked to original sources

bioRxiv2025

Slower transitions between control states lead to reductions in cognitive flexibility over the lifespan

Declines in cognitive flexibility are a hallmark of cognitive aging, but their causes remain elusive. Here, we examine a previously untested source of aging-related cognitive inflexibility, building on a dynamical systems framework for flexible cognition. We propose that cognitive inflexibility can arise in part from slower transitions through the space of distinct configurations of cognitive control needed to pursue different goals. To test this model, we had participants across the lifespan (aged 19-88) perform a cognitive task under different performance goals, each of which induced a different configuration of cognitive control. Using computational modeling, we measured dynamic changes in two control signals (attentional focus and response caution) as participants pursued distinct goals. This allowed us to test three potential sources of age-related decreases in cognitive flexibility: 1) diminished control capacity in environments that require more goal switching; 2) diminished range of control adjustments; and 3) slower transitions between control configurations. Of these, we found that age was only associated with transition speed. When given sufficient time to maintain a given goal, older adults were able to adjust control to a similar extent as younger adults. However, older adults were more likely to undershoot their target control configuration when frequently switching between goals, consistent with longer transition times between configurations. Our findings demonstrate the critical role that cognitive dynamics play in explaining the mechanisms through which cognitive inflexibility arises in older adulthood. SignificanceMeeting the shifting demands of daily life requires a person to constantly adjust the way in which they allocate their cognitive resources. As people get older, it becomes increasingly difficult to achieve the same levels of cognitive flexibility. We show that these deficits can be explained by age-related changes in the dynamics governing adjustments between cognitive states. Older adults take longer to adapt their cognitive state to a new goal, despite demonstrating preserved ability to reach desired states when given sufficient time. These findings validate a new model of cognitive flexibility and its variability across individuals, including forms of inflexibility seen in healthy aging and across a range of psychiatric and neurological disorders.

animal behavior and cognition↗

bioRxiv2023

Control adjustment costs limit goal flexibility: Empirical evidence and a theoretical account

A cornerstone of human intelligence is the ability to flexibly adjust our cognition and behavior as our goals change. For instance, achieving some goals requires efficiency, while others require caution. Different goals require us to engage different control processes, such as adjusting how attentive and cautious we are. Here, we show that performance incurs control adjustment costs when people adjust control to meet changing goals. Across four experiments, we provide evidence of these costs, and validate a dynamical systems model explaining the source of these costs. Participants performed a single cognitively demanding task under varying performance goals (e.g., being fast or accurate). We modeled control allocation to include a dynamic process of adjusting from ones current control state to a target state for a given performance goal. By incorporating inertia into this adjustment process, our model accounts for our empirical finding that people under-shoot their target control state more (i.e., exhibit larger adjustment costs) when goals switch rather than remain fixed (Study 1). Further validating our model, we show that the magnitude of this cost is increased when: distances between target states are larger (Study 2), there is less time to adjust to the new goal (Study 3), and goal switches are more frequent (Study 4). Our findings characterize the costs of adjusting control to meet changing goals, and show that these costs emerge directly from cognitive control dynamics. In so doing, they shed new light on the sources of and constraints on flexibility of goal-directed behavior.

neuroscience↗

bioRxiv2021

Dynamic interplay between reward and voluntary attention determines stimulus processing in visual cortex

Reward enhances stimulus processing in the visual cortex, but the mechanisms through which this effect occurs remain unclear. Reward prospect can both increase the deployment of voluntary attention and increase the salience of previously neutral stimuli. In this study we orthogonally manipulated reward and voluntary attention while human participants performed a global motion detection task. We recorded steady-state visual evoked potentials (SSVEPs) to simultaneously measure the processing of attended and unattended stimuli linked to different reward probabilities, as they compete for attentional resources. The processing of the high rewarded feature was enhanced independently of voluntary attention, but this gain diminished once rewards were no longer available. Neither the voluntary attention nor the salience account alone can fully explain these results. Instead, we propose how these two accounts can be integrated to allow for the flexible balance between reward-driven increase in salience and voluntary attention.

neuroscience↗

bioRxiv2020

Learning when effort matters: Neural dynamics underlying updating and adaptation to changes in performance efficacy

To determine how much cognitive control to invest in a task, people need to consider whether exerting control matters for obtaining rewards. In particular, they need to account for the efficacy of their performance - the degree to which rewards are determined by performance or by independent factors. Yet it remains unclear how people learn about their performance efficacy in an environment. Here we combined computational modeling with measures of task performance and EEG, to provide a mechanistic account of how people (a) learn and update efficacy expectations in a changing environment, and (b) proactively adjust control allocation based on current efficacy expectations. Across two studies subjects performed an incentivized cognitive control task while their performance efficacy (the likelihood that rewards are performance- contingent or random) varied over time. We show that people update their efficacy beliefs based on prediction errors - leveraging similar neural and computational substrates as those that underpin reward learning - and adjust how much control they allocate according to these beliefs. Using computational modeling, we show that these control adjustments reflect changes in information processing, rather than the speed-accuracy tradeoff. These findings demonstrate the neurocomputational mechanism through which people learn how worthwhile their cognitive control is.

neuroscience↗

bioRxiv2018

Motivation and Cognitive Control in Depression

Depression is linked to deficits in cognitive control and a host of other cognitive impairments arise as a consequence of these deficits. Despite of their important role in depression, there are no mechanistic models of cognitive control deficits in depression. In this paper we propose how these deficits can emerge from the interaction between motivational and cognitive processes. We review depression-related impairments in key components of motivation along with new cognitive neuroscience models that focus on the role of motivation in the decision-making about cognitive control allocation. Based on this review we propose a unifying framework which connects motivational and cognitive impairments in depression. This framework is rooted in computational models of cognitive control and offers a mechanistic understanding of cognitive control deficits in depression.

neuroscience↗