Tracking dynamic adjustments to decision making and performance monitoring processes in conflict tasks

Feuerriegel, Daniel; Jiwa, Matthew; Turner, William; Andrejević, Milan; Hester, Robert; Bode, Stefan

doi:10.1016/j.neuroimage.2021.118265

Cited by 13 publications

(9 citation statements)

References 73 publications

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“…Furthermore, before the onset of sensory evidence the ‘starting levels’ of the signals reflect biased motor preparation when prior expectations are biased ( de Lange et al, 2013 ), and are higher under speed pressure for both alternatives ( Kelly et al, 2021 ; Murphy et al, 2016 ; Steinemann et al, 2018 ), implementing the well-established decision variable (DV) adjustments assumed in models ( Bogacz et al, 2010 ; Hanks et al, 2014 ; Mulder et al, 2012 ). The signal contralateral to the chosen hand then reaches a highly similar level at response irrespective of stimulus conditions or RT, consistent with a fixed, action-triggering threshold ( Devine et al, 2019 ; Feuerriegel et al, 2021 ; Kelly et al, 2021 ; O’Connell et al, 2012 ; Steinemann et al, 2018 ). The level of beta before stimulus onset also predicts RT, and its post-stimulus buildup-rate scales with evidence strength, underlining that this signal reflects both evidence-independent and evidence-dependent contributions to the decision process ( Steinemann et al, 2018 ).…”

Section: Resultssupporting

confidence: 65%

“…It is plausible that the LRP ‘bolus’ in our study could arise from a related mechanism in which the value cue automatically ‘primes’ a response, although it seems likely that value-biased responding is more intentional since it may confer a benefit in terms of the increased reward. Indeed, the patterns of biased anticipatory motor preparation we see in this study cannot be present in tasks where the conflict does not arise until after stimulus onset; in such tasks the anticipatory mu/beta buildup activity while present is unbiased ( Feuerriegel et al, 2021 ). In the case of these beta signals, the fact that the buildup happens earlier under speed pressure ( Kelly et al, 2021 ) suggests that they are much more likely to be strategic rather than automatic, and we would not expect a bottom-up lateralization in response to the physical appearance of the cues due to their symmetric design.…”

Section: Discussionmentioning

confidence: 76%

“…First, when stimulus onset is predictable, anticipatory activity in motor preparation regions can begin to forge a decision even before the stimulus appears. While standard models do allow for anticipatory processing in the setting of the starting point from which the accumulator evolves after sensory encoding, neurophysiological data have revealed that anticipatory motor preparation is often dynamic, proceeding on a trajectory aimed at eventually crossing an action-triggering threshold by itself even in the absence of sensory input ( Feuerriegel et al, 2021 ; Kelly et al, 2021 ; Stanford et al, 2010 ). This represents a pre-stimulus signature of a signal identified in neurophysiology studies known as urgency—defined in accumulator models as an evidence-independent buildup component that continues to operate throughout the decision process, adding to sensory evidence accumulation so that the criterion amount of cumulative evidence to terminate the decision reduces with time ( Churchland et al, 2008 ; Hanks et al, 2014 ; Murphy et al, 2016 ; Shinn et al, 2020 ; Steinemann et al, 2018 ; Thura and Cisek, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

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Multiphasic value biases in fast-paced decisions

Corbett

Martinez-Rodriguez

Judd

et al. 2023

eLife

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Perceptual decisions are biased toward higher-value options when overall gains can be improved. When stimuli demand immediate reactions, the neurophysiological decision process dynamically evolves through distinct phases of growing anticipation, detection, and discrimination, but how value biases are exerted through these phases remains unknown. Here, by parsing motor preparation dynamics in human electrophysiology, we uncovered a multiphasic pattern of countervailing biases operating in speeded decisions. Anticipatory preparation of higher-value actions began earlier, conferring a ‘starting point’ advantage at stimulus onset, but the delayed preparation of lower-value actions was steeper, conferring a value-opposed buildup-rate bias. This, in turn, was countered by a transient deflection toward the higher-value action evoked by stimulus detection. A neurally-constrained process model featuring anticipatory urgency, biased detection, and accumulation of growing stimulus-discriminating evidence, successfully captured both behavior and motor preparation dynamics. Thus, an intricate interplay of distinct biasing mechanisms serves to prioritise time-constrained perceptual decisions.

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Section: Resultssupporting

confidence: 65%

Section: Discussionmentioning

confidence: 76%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multiphasic value biases in fast-paced decisions

Corbett

Martinez-Rodriguez

Judd

et al. 2023

eLife

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“…En el diario vivir del ser humano se produce una constante adaptación de las estrategias que utiliza en el proceso de toma de decisiones con la finalidad de adecuarlas a las demandas del entorno, donde una de las principales áreas de investigación es la manera como se maneja la información durante un conflicto, particularmente en contextos en los que varias características de un estímulo se asocian con acciones motoras, según lo manifestado por los autores Feuerriegel et al (2021).…”

Section: Patrones Para La Toma De Decisionesunclassified

Los estilos de negociación y su incidencia en el clima organizacional de los almacenes de electrodomésticos Electromart de la ciudad de Machala

et al. 2021

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Los estilos de negociación aplicados en la gestión y el comportamiento departamental en una empresa son relevantes, es necesario conocer y establecer cómo inciden en el talento de dichas organizaciones; las personas en cualquier instante podrían involucrarse en procesos de negociación; así mismo, el ambiente de trabajo y el comportamiento del cliente influyen en lograr el buen clima organizacional deseado; ante la relevancia se pretende analizar los estilos de negociación predominantes en los almacenes de electrodomésticos Electromart de la ciudad de Machala por medio de un estudio cualitativo que permita la identificación de su incidencia en el clima organizacional para el aprovechamiento en la gestión del talento humano con su retroalimentación y con ello la mejora de los estilos que utilizan.La fundamentación científica se realizó mediante revisión bibliográfica, se aplicaron técnicas de observación y entrevista, el enfoque es cualitativo apoyado en el ATLAS Ti, que permitió un análisis crítico de los resultados de negociación manejada en los diferentes departamentos; a su vez, estos resultados apoyaron a la identificación de las incidencias en el clima organizacional de la empresa. Se determinó la incidencia de los estilos de negociación en el clima organizacional de los almacenes Electromart, también se especifica que estilo de negociación es el que está presente en cada uno de los jefes y la forma de mejorarlo o qué estilo de negociador es el más idóneo para poder alcanzar los objetivos del almacén.

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“…This widespread positive RT-BOLD relationship was found even in the case of fast and homogenous saccadic responses (Domagalik et al, 2014). Finally, numerous M/EEG indicators present similar tendencies for changing linearly with decision time, e.g., centroparietal positivity (O’Connell et al, 2012; Twomey et al, 2015), non-phase locked MFT (Cohen and Donner, 2013; Duprez et al, 2020; Feuerriegel et al, 2021), or motor beta and gamma frequency bands (Donner et al, 2009; Fischer et al, 2018; Rogge et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

A thin line between conflict and reaction time effects on EEG and fMRI brain signals

Beldzik

Ullsperger

2023

Preprint

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The last two decades of electrophysiological and neuroimaging research converged that the activity in the medial frontal cortex plays a pivotal role in cognitive control processes. Notably, the midfrontal theta (MFT) oscillatory EEG power, as well as activity in the anterior midcingulate cortex (aMCC) or pre-supplementary motor area (preSMA), were consistently proclaimed as markers of conflict processing. However, these brain signals are strongly correlated with response time (RT) variability in various non-conflict tasks, which overshadows the true nature of their involvement. Our previous study (Beldzik et al., 2022) successfully identified these brain signals during a simultaneous EEG-fMRI experiment implementing Stroop and Simon tasks. Based on the assumption that overcoming the habitual prepotent response during high interference trials require additional neural resources beyond simple decision variable represented in RTs, here we aim to verify if these markers exhibit a congruency effect beyond RT variations. Furthermore, we explored if these brain signals represent either proactive or reactive cognitive control mechanisms by investigating two widely known behavioral phenomena observed in conflict tasks: proportion congruency and congruency sequence effects. The results revealed partially null findings for MFT activity, yet a distinct cognitive control specialization between aMCC and preSMA. Our study provides novel evidence that the former is involved in proactive control mechanisms, possibly contingency learning, whereas the latter reflects reactive control mechanisms by exhibiting a strong congruency effect regardless of RT variation and responding to adaptive behavior.

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Tracking dynamic adjustments to decision making and performance monitoring processes in conflict tasks

Cited by 13 publications

References 73 publications

Multiphasic value biases in fast-paced decisions

Multiphasic value biases in fast-paced decisions

Los estilos de negociación y su incidencia en el clima organizacional de los almacenes de electrodomésticos Electromart de la ciudad de Machala

A thin line between conflict and reaction time effects on EEG and fMRI brain signals

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