Multi-level decoding of task sets in neurophysiological data during cognitive flexibility.
Ontology highlight
ABSTRACT:
SUBMITTER: Petruo V
PROVIDER: S-EPMC8654636 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Decoding models based on pattern recognition (PR) are becoming increasingly important tools for neuroimaging data analysis. In contrast to alternative (mass-univariate) encoding approaches that use hierarchical models to capture inter-subject variability, inter-subject differences are not typically handled efficiently in PR. In this work, we propose to overcome this problem by recasting the decoding problem in a multi-task learning (MTL) framework. In MTL, a single PR model is used to learn different but related "tasks" simultaneously. The primary advantage of MTL is that it makes more efficient use of the data available and leads to more accurate models by making use of the relationships between tasks. In this work, we construct MTL models where each subject is modelled by a separate task. We use a flexible covariance structure to model the relationships between tasks and induce coupling between them using Gaussian process priors. We present an MTL method for classification problems and demonstrate a novel mapping method suitable for PR models. We apply these MTL approaches to classifying many different contrasts in a publicly available fMRI dataset and show that the proposed MTL methods produce higher decoding accuracy and more consistent discriminative activity patterns than currently used techniques. Our results demonstrate that MTL provides a promising method for multi-subject decoding studies by focusing on the commonalities between a group of subjects rather than the idiosyncratic properties of different subjects.
| S-EPMC4010954 | biostudies-literature
Project description:Adaptive behavior requires finding, and adjusting, an optimal tradeoff between focusing on a current task-set (cognitive stability) and updating that task-set when the environment changes (cognitive flexibility). Such dynamic adjustments of cognitive flexibility are observed in cued task-switching paradigms, where switch costs tend to decrease as the proportion of switch trials over blocks increases. However, the learning mechanisms underlying this phenomenon, here referred to as the list-wide proportion switch effect (LWPSE), are currently unknown. We addressed this question across four behavioral experiments. Experiment 1 replicated the basic LWPSE reported in previous studies. Having participants switch between three instead of two tasks, Experiment 2 demonstrated that the LWPSE is preserved even when the specific alternate task to switch to cannot be anticipated. Experiments 3a and 3b tested for the generalization of list-wide switch-readiness to an unbiased "transfer task," presented equally often as switch and repeat trials, by intermixing the transfer task with biased tasks. Despite the list-wide bias, the LWPSE was only found for biased tasks, suggesting that the modulations of switch costs are task set and/or task stimulus (item)-specific. To evaluate these two possibilities, Experiment 4 employed biased versus unbiased stimuli within biased task sets and found switch-cost modulations for both stimuli sets. These results establish how people adapt their stability-flexibility tradeoff to different contexts. Specifically, our findings show that people learn to associate context-appropriate levels of switch readiness with switch-predictive cues, provided by task sets as well as specific task stimuli.
| S-EPMC7396276 | biostudies-literature
Project description:Executive functions, like the capacity to control and organize thoughts and behavior, develop from childhood to young adulthood. Although task switching and working memory processes are known to undergo strong developmental changes from childhood to adulthood, it is currently unknown how task switching processes are modulated between childhood and adulthood given that working memory processes are central to task switching. The aim of the current study is therefore to examine this question using a combined cue- and memory-based task switching paradigm in children (N = 25) and young adults (N = 25) in combination with neurophysiological (EEG) methods. We obtained an unexpected paradoxical effect suggesting that memory-based task switching is better in late childhood than in young adulthood. No group differences were observed in cue-based task switching. The neurophysiological data suggest that this effect is not due to altered attentional selection (P1, N1) or processes related to the updating, organization, and implementation of the new task-set (P3). Instead, alterations were found in the resolution of task-set conflict and the selection of an appropriate response (N2) when a task has to be switched. Our observation contrasts findings showing that cognitive control mechanisms reach their optimal functioning in early adulthood.
| S-EPMC4923946 | biostudies-literature
Project description:Distress intolerance (DI), a trait-like individual difference reflective of the inability to endure aversive affective states, is relevant to multiple forms of psychopathology, but its relations to theoretically relevant neurobiological systems have received little attention. Altered cognitive control-related neurobiology has been theorized to underlie individual differences in DI, but little empirical work has been conducted. To test this hypothesis, baseline data from a large community sample with elevated high levels of emotional psychopathology and comorbidity was utilized (N = 256). Participants completed a complex go/no-go task while EEG was recorded, and P2, N2, and P3 amplitudes were measured. Based upon prior findings on the relations between these components and response inhibition, a core cognitive control function, we hypothesized that DI would predict reduced no-go N2 and P3 amplitude while controlling for current anxious/depressive symptom severity (i.e., negative affect). Peak amplitudes from the raw data and principal components analysis were used to quantify amplitude of ERP components. Partially consistent with predictions, high DI was independently associated with reduced no-go N2 peak amplitude in the raw ERP data, and was significantly related to a frontal positivity factor in the N2 time window across no-go and go trials. Contrary to predictions, no relations between DI and the P3 were found. Overall, results support the theorized relevance of cognitive control-linked neurobiology to individual differences in tolerance of distress over and above distress severity itself, and suggest specific relations between DI and alterations in early controlled attention/conflict-monitoring but not response inhibition or response inhibition-related sequelae. (PsycINFO Database Record
| S-EPMC5858937 | biostudies-literature
Project description:Time-consuming processes of task-set reconfiguration have been shown to contribute to the costs of switching between cognitive tasks. We describe and probe a novel mechanism serving to reduce the costs of task-set reconfiguration. We propose that when individuals are uncertain about the currently valid task, one task set is activated for execution while other task sets are maintained at a pre-active state in cognitive cache. We tested this idea by assessing an event-related potential (ERP) index of task-set reconfiguration in a three-rule task-switching paradigm involving varying degrees of task uncertainty. In high-uncertainty conditions, two viable tasks were equally likely to be correct whereas in low-uncertainty conditions, one task was more likely than the other. ERP and performance measures indicated substantial costs of task-set reconfiguration when participants were required to switch away from a task that had been likely to be correct. In contrast, task-set-reconfiguration costs were markedly reduced when the previous task set was chosen under high task uncertainty. These results suggest that cognitive caching of alternative task sets adds to human cognitive flexibility under high task uncertainty.
| S-EPMC4672338 | biostudies-other
Project description:Chromosome conformation capture methods are being increasingly used to study three-dimensional genome architecture in multiple cell types and species. An important challenge is to examine changes in three-dimensional architecture across cell types and species. We present Arboretum-Hi-C, a multi-task spectral clustering method, to identify common and context-specific aspects of genome architecture. Compared to standard clustering, Arboretum-Hi-C produced more biologically consistent patterns of conservation. Most clusters are conserved and enriched for either high- or low-activity genomic signals. Most genomic regions diverge between clusters with similar chromatin state except for a few that are associated with lamina-associated domains and open chromatin.
| S-EPMC4882777 | biostudies-literature
Project description:Mental disorders are a major source of disability, with few effective treatments. It has recently been argued that these diseases might be effectively treated by focusing on decision-making, and specifically remediating decision-making deficits that act as "ingredients" in these disorders. Prior work showed that direct electrical brain stimulation can enhance human cognitive control, and consequently decision-making. This raises a challenge of detecting cognitive control lapses directly from electrical brain activity. Here, we demonstrate approaches to overcome that challenge. We propose a novel method, referred to as maximal variance node merging (MVNM), that merges nodes within a brain region to construct informative inter-region brain networks. We employ this method to estimate functional (correlational) and effective (causal) networks using local field potentials (LFP) during a cognitive behavioral task. The effective networks computed using convergent cross mapping differentiate task engagement from background neural activity with 85% median classification accuracy. We also derive task engagement networks (TENs): networks that constitute the most discriminative inter-region connections. Subsequent graph analysis illustrates the crucial role of the dorsolateral prefrontal cortex (dlPFC) in task engagement, consistent with a widely accepted model for cognition. We also show that task engagement is linked to prefrontal cortex theta (4-8 Hz) oscillations. We, therefore, identify objective biomarkers associated with task engagement. These approaches may generalize to other cognitive functions, forming the basis of a network-based approach to detecting and rectifying decision deficits.
| S-EPMC8428572 | biostudies-literature
Project description:Humans and animals have an impressive ability to juggle multiple tasks in a constantly changing environment. This flexibility, however, leads to decreased performance under uncertain task conditions. Here, we combined monkey electrophysiology, human psychophysics, and artificial neural network modeling to investigate the neuronal mechanisms of this performance cost. We developed a behavioural paradigm to measure and influence participants' decision-making and perception in two distinct perceptual tasks. Our data revealed that both humans and monkeys, unlike an artificial neural network trained for the same tasks, make less accurate perceptual decisions when the task is uncertain. We generated a mechanistic hypothesis by comparing this neural network trained to produce correct choices with another network trained to replicate the participants' choices. We hypothesized, and confirmed with further behavioural, physiological, and causal experiments, that the cost of task flexibility comes from what we term task interference. Under uncertain conditions, interference between different tasks causes errors because it results in a stronger representation of irrelevant task features and entangled neuronal representations of different features. Our results suggest a tantalizing, general hypothesis: that cognitive capacity limitations, both in health and disease, stem from interference between neural representations of different stimuli, tasks, or memories.
| S-EPMC10942291 | biostudies-literature
Project description:Demanding tasks like cognitive flexibility show time-related deterioration of performance (i.e. fatigability effects). Fatigability has been associated with structural and functional properties of the prefrontal cortex. However, the electrophysiological underpinnings of these processes are not well understood. We examined n?=?34 healthy participants with a task switching paradigm in which switches were either signaled by cues or needed to be maintained by working memory processes. We analyzed event-related potentials (ERPs) and performed residue iteration decomposition (RIDE) to account for effects of fatigue on intra-individual variability of neurophysiological data. This was combined with source localization methods. We show that task switching is affected by time on task (TOT) effects mostly when working memory processes are needed. On a neurophysiological level, this effect could not be observed in standard ERPs, but only after accounting for intra-individual variability using RIDE. The RIDE data suggests that during task switching, fatigability specifically affects response recoding processes that are associated with functions of the middle frontal gyrus (MFG; BA10). The results underline propositions of the 'opportunity cost model', which states that fatigability effects of executive functions depend on the degree to which tasks engage similar prefrontal regions - in this case working memory and task switching mechanisms.
| S-EPMC5913330 | biostudies-literature
Project description:The human brain exhibits fundamental limitations in multitasking. When subjects engage in a primary task, their ability to respond to a second stimulus is degraded. Two competing models of multitasking have been proposed: either cognitive resources are shared between tasks, or they are allocated to each task serially. Using a novel combination of magneto-encephalography and multivariate pattern analyses, we obtained a precise spatio-temporal decomposition of the brain processes at work during multitasking. We discovered that each task relies on a sequence of brain processes. These sequences can operate in parallel for several hundred milliseconds but beyond ? 500 ms, they repel each other: processes evoked by the first task are shortened, while processes of the second task are either lengthened or postponed. These results contradict the resource-sharing model and further demonstrate that the serial model is incomplete. We therefore propose a new theoretical framework for the computational architecture underlying multitasking.
| S-EPMC5635959 | biostudies-literature