Task demands modulate sustained and transient neural activity during visual-matching tasks

The understanding of the adult proficiency in recognizing and extracting information from faces is still limited despite the number of studies over the last decade. Our knowledge on the development of these capacities is even more restricted, as only a handful of such studies exist. Here we present a combined reanalysis of four ERP studies in children from 4 to 15 years of age and adults (n = 424, across the studies), which investigated face processing in implicit and explicit tasks. We restricted these analyses to what was common across studies: early ERP components and upright face processing across all four studies and the inversion effect, investigated in three of the studies. These data demonstrated that processing faces implicates very rapid neural activity, even in young children— at the P1 component—with protracted age-related change in both P1 and N170, that were sensitive to the different task demands. Inversion produced latency and amplitude effects on the P1 from the youngest group, but on N170 only starting in mid childhood. These developmental data suggest that there are functionally different sources of the P1 and N170, related to the processing of different aspects of faces.

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Isolating Discriminant Neural Activity in the Presence of Eye Movements and Concurrent Task Demands

Frontiers in Human Neuroscience ◽

10.3389/fnhum.2017.00357 ◽

2017 ◽

Vol 11 ◽

Cited By ~ 4

Author(s):

Jon Touryan ◽

Vernon J. Lawhern ◽

Patrick M. Connolly ◽

Nima Bigdely-Shamlo ◽

Anthony J. Ries

Keyword(s):

Eye Movements ◽

Neural Activity ◽

Concurrent Task ◽

Task Demands

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Mindfulness meditation alters neural activity underpinning working memory during tactile distraction

10.1101/790584 ◽

2019 ◽

Cited By ~ 2

Author(s):

Michael Yufeng Wang ◽

Gabrielle Freedman ◽

Kavya Raj ◽

Bernadette Mary Fitzgibbon ◽

Caley Sullivan ◽

...

Keyword(s):

Working Memory ◽

Neural Activity ◽

Tactile Stimulation ◽

Mindfulness Meditation ◽

Brain Activity ◽

Alpha Activity ◽

Task Demands ◽

Attentional Processes ◽

Attentional Function ◽

Tactile Stimuli

AbstractEvidence suggests that mindfulness meditation (MM) improves selective attention and reduces distractibility by enhancing top-down neural modulation. Altered P300 and alpha neural activity from MM have been identified and may reflect the neural changes that underpin these improvements. Given the proposed role of alpha activity in supressing processing of task-irrelevant information, it is theorised that altered alpha activity may underlie increased availability of neural resources in meditators. The present study investigated attentional function in meditators using a cross-modal study design, examining the P300 during working memory (WM) and alpha activity during concurrent distracting tactile stimuli. Thirty-three meditators and 27 healthy controls participated in the study. Meditators showed a more frontal distribution of P300 neural activity following WM stimuli (p = 0.005, η² = 0.060) and more modulation of alpha activity at parietal-occipital regions between single (tactile stimulation only) and dual task demands (tactile stimulation plus WM task) (p < 0.001, η² = 0.065). Additionally, meditators performed more accurately than controls (p = 0.038, η² = 0.067). The altered distribution of neural activity concurrent with improved WM performance suggests greater attentional resources dedicated to task related functions such as WM in meditators. Thus, meditation-related neural changes are likely multi-faceted involving both altered distribution and also amplitudes of brain activity, enhancing attentional processes depending on task requirements.

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Task-demands and audio-visual stimulus configurations modulate neural activity in the human thalamus

NeuroImage ◽

10.1016/j.neuroimage.2012.10.018 ◽

2013 ◽

Vol 66 ◽

pp. 110-118 ◽

Cited By ~ 8

Author(s):

Björn Bonath ◽

Sascha Tyll ◽

Eike Budinger ◽

Kerstin Krauel ◽

Jens-Max Hopf ◽

...

Keyword(s):

Visual Stimulus ◽

Neural Activity ◽

Task Demands ◽

Human Thalamus

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High-fidelity musculoskeletal modeling reveals that motor planning variability contributes to the speed-accuracy tradeoff

eLife ◽

10.7554/elife.57021 ◽

2020 ◽

Vol 9 ◽

Author(s):

Mazen Al Borno ◽

Saurabh Vyas ◽

Krishna V Shenoy ◽

Scott L Delp

Keyword(s):

Neural Activity ◽

Three Dimensional ◽

Motor Planning ◽

Good Control ◽

Population Level ◽

Task Demands ◽

Movement Speed ◽

Fitts Law ◽

Speed Accuracy ◽

Accuracy Tradeoff

A long-standing challenge in motor neuroscience is to understand the relationship between movement speed and accuracy, known as the speed-accuracy tradeoff. Here, we introduce a biomechanically realistic computational model of three-dimensional upper extremity movements that reproduces well-known features of reaching movements. This model revealed that the speed-accuracy tradeoff, as described by Fitts’ law, emerges even without the presence of motor noise, which is commonly believed to underlie the speed-accuracy tradeoff. Next, we analyzed motor cortical neural activity from monkeys reaching to targets of different sizes. We found that the contribution of preparatory neural activity to movement duration (MD) variability is greater for smaller targets than larger targets, and that movements to smaller targets exhibit less variability in population-level preparatory activity, but greater MD variability. These results propose a new theory underlying the speed-accuracy tradeoff: Fitts’ law emerges from greater task demands constraining the optimization landscape in a fashion that reduces the number of ‘good’ control solutions (i.e., faster reaches). Thus, contrary to current beliefs, the speed-accuracy tradeoff could be a consequence of motor planning variability and not exclusively signal-dependent noise.

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Working memory as persistent neural activity

10.31234/osf.io/jh6e3 ◽

2019 ◽

Author(s):

Joshua J. Foster ◽

Edward K. Vogel ◽

Ed Awh

Keyword(s):

Working Memory ◽

Cognitive Processing ◽

Neural Activity ◽

Operational Definition ◽

Task Demands ◽

Neural Representation ◽

Long Term Memory ◽

Intelligent Behavior ◽

Dynamic Collaboration ◽

Definition Of

Working memory (WM) is an online memory system that allows us to hold information “in mind” in service of ongoing cognitive processing. Here, we emphasize that short-term retention of information typically involves an interplay between WM and long-term memory (LTM), especially when task demands or interruptions divert our focus from remembered items. We suggest that active neural representation may distinguish between “online” representations in WM and “offline” representations in LTM. This perspective is at odds with “activity-silent” models of WM, which hold that WM representations can be sustained without persistent neural activity. We suggest that activity-silent representations might be more productively conceptualized as offline representations in LTM because accessing these representations shows multiple signatures of retrieval from LTM. Moreover, active neural traces track WM load, predict individual differences in performance, and respect sharp item limits in WM storage. Thus, we argue that using neural activity as an operational definition of WM may provide strong traction for studying the dynamic collaboration between WM and LTM that is critical for intelligent behavior.

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Increased cognitive complexity reveals abnormal brain network activity in individuals with corpus callosum dysgenesis

10.1101/312629 ◽

2018 ◽

Author(s):

Luke J. Hearne ◽

Ryan J. Dean ◽

Gail A. Robinson ◽

Linda J. Richards ◽

Jason B. Mattingley ◽

...

Keyword(s):

Corpus Callosum ◽

Neural Activity ◽

Network Architecture ◽

Cognitive Complexity ◽

Cognitive Task ◽

Brain Network ◽

Task Demands ◽

Network Activity ◽

Network Analyses ◽

Cognitive Reasoning

AbstractCognitive reasoning is thought to require functional interactions between whole-brain networks. Such networks rely on both cerebral hemispheres, with the corpus callosum providing cross-hemispheric communication. Here we used high-field functional magnetic resonance imaging (7T fMRI), a well validated cognitive task, and brain network analyses to investigate the functional networks underlying cognitive reasoning in individuals with corpus callosum dysgenesis (CCD), an anatomical abnormality that affects the corpus callosum. Participants with CCD were asked to solve cognitive reasoning problems while their brain activity was measured using fMRI. The complexity of these problems was parametrically varied by changing the complexity of relations that needed to be established between shapes within each problem matrix. Behaviorally, participants showed a typical reduction in task performance as problem complexity increased. Task-evoked neural activity was observed in brain regions known to constitute two key cognitive control systems: the fronto-parietal and cingulo-opercular networks. Under low complexity demands, network topology and the patterns of local neural activity in the CCD group closely resembled those observed in neurotypical controls. By contrast, when asked to solve more complex problems, participants with CCD showed a reduction in neural activity and connectivity within the fronto-parietal network. These complexity-induced, as opposed to resting-state, differences in functional network activity help resolve the apparent paradox between preserved network architecture found at rest in CCD individuals, and the heterogeneous deficits they display in response to cognitive task demands [preprint: https://doi.org/10.1101/312629].

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Late cortical potentials are not a reliable marker of somatosensory awareness

10.1101/2020.10.01.322651 ◽

2020 ◽

Author(s):

Pia Schröder ◽

Till Nierhaus ◽

Felix Blankenburg

Keyword(s):

Target Detection ◽

Event Related Potentials ◽

Neural Correlates ◽

Task Demands ◽

Matching Task ◽

Perceptual Awareness ◽

Attentional Processes ◽

Related Potentials ◽

Visual Matching ◽

Reliable Marker

AbstractTwo types of scalp-recorded event-related potentials have been proposed as neural correlates of perceptual awareness in humans: an early, modality-specific negativity and a late, modality-independent positivity. However, whether these potentials genuinely reflect perception or result from task demands remains controversial. To address this question, we compared results from a classical somatosensory detection task (direct report task) to a somatosensory-visual matching task, in which overt reports were decorrelated from target detection, equated the behavioural relevance of detected and undetected stimuli, and mitigated the influence of attentional processes. By means of Bayesian model selection, we show that the early N140 component was the first to reflect target detection in both tasks, whereas the late P300 component was task dependent, with strong detection effects in the direct report task that were absent in the matching task. We conclude that the P300 is not a genuine correlate of somatosensory awareness but reflects postperceptual processing.

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Flexible information coding in frontoparietal cortex across the functional stages of cognitive processing

10.1101/246132 ◽

2018 ◽

Author(s):

Joyce M. G. Vromen ◽

Stefanie I. Becker ◽

Oliver Baumann ◽

Jason B. Mattingley ◽

Roger W. Remington

Keyword(s):

Cognitive Processing ◽

Neural Activity ◽

Target Selection ◽

Task Demands ◽

Anterior Cingulate ◽

Information Representation ◽

Complex Tasks ◽

Cognitive Domains ◽

Frontoparietal Cortex ◽

Response Execution

AbstractNeural activity in frontoparietal cortex shows overlap across cognitive domains and has been proposed to reflect flexible information processing according to current task demands (Dosenbach et al., 2007; Duncan, 2001). However, a strong assertion of flexibility requires investigating activity across stages of cognitive processing. The current study assessed neural activity in Multiple Demand (MD) regions across the stages of processing that form the core of long-standing cognitive models (Welford, 1952). Specifically, many complex tasks share a comparable structure of subsequent operations: target selection, stimulus-response (SR) mapping, and response execution. We independently manipulated the difficulty of target selection and SR mapping in identical stimulus displays and assessed changes in frontoparietal activity with increased demands in either stage. The results confirmed flexibility in MD regions, with enhanced information representation during difficult target selection as well as SR mapping. Additionally, anterior insula (AI) and anterior cingulate cortex (ACC) showed preferential representation of SR stage information, whereas the medial frontal gyrus (MFG) and inferior parietal sulcus (IPS) showed preferential representation of target selection-stage information. Together these results suggest that MD regions dynamically alter the information they represent with changing task demands. This is the first study to demonstrate that MD regions support flexible goal-directed cognition across multiple processing stages. At the same time we show a preference for the representation of information from a specific processing stage in a subset of MD regions.Significance StatementGoal-directed cognition in complex tasks is critical to key life outcomes including longevity and academic performance. Nevertheless, the mechanisms underlying cognition in complex tasks are not well understood. Distinct neural networks are critical to the navigation of specific cognitive domains (e.g. attention), but frontoparietal activity shows cross-domain and -task overlap and supports flexible representation of goal-critical information. This study links flexible frontoparietal processing to longstanding models of meta-cognition that propose a unifying structure of operations underlying most tasks: target selection, SR mapping, and response execution. Our results demonstrate that flexible information representation in frontoparietal cortex is not limited to the SR mapping stage, but applies across the functional stages of cognitive processing, thus maximizing neural efficiency and supporting flexible cognition.

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Electrophysiological Signatures of Numerosity Encoding in a Delayed Match-to-Sample Task

Frontiers in Human Neuroscience ◽

10.3389/fnhum.2021.750582 ◽

2022 ◽

Vol 15 ◽

Author(s):

Wanlu Fu ◽

Serena Dolfi ◽

Gisella Decarli ◽

Chiara Spironelli ◽

Marco Zorzi

Keyword(s):

Neural Activity ◽

General System ◽

Task Demands ◽

Numerical Magnitude ◽

Memory Retention ◽

Retention Period ◽

Match To Sample ◽

Small Set ◽

Neural Signature ◽

Mixed Format

The number of elements in a small set of items is appraised in a fast and exact manner, a phenomenon called subitizing. In contrast, humans provide imprecise responses when comparing larger numerosities, with decreasing precision as the number of elements increases. Estimation is thought to rely on a dedicated system for the approximate representation of numerosity. While previous behavioral and neuroimaging studies associate subitizing to a domain-general system related to object tracking and identification, the nature of small numerosity processing is still debated. We investigated the neural processing of numerosity across subitizing and estimation ranges by examining electrophysiological activity during the memory retention period in a delayed numerical match-to-sample task. We also assessed potential differences in the neural signature of numerical magnitude in a fully non-symbolic or cross-format comparison. In line with behavioral performance, we observed modulation of parietal-occipital neural activity as a function of numerosity that differed in two ranges, with distinctive neural signatures of small numerosities showing clear similarities with those observed in visuospatial working memory tasks. We also found differences in neural activity related to numerical information in anticipation of single vs. cross-format comparison, suggesting a top-down modulation of numerical processing. Finally, behavioral results revealed enhanced performance in the mixed-format conditions and a significant correlation between task performance and symbolic mathematical skills. Overall, we provide evidence for distinct mechanisms related to small and large numerosity and differences in numerical encoding based on task demands.

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