The Effects of Sleep Deprivation in Working Memory Using the N-back Task

Martínez-Cancino, D. P.; Azpiroz-Leehan, J.; Jiménez-Ángeles, Luis

doi:10.1007/978-3-319-13117-7_108

Cited by 6 publications

(7 citation statements)

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“…Using a paired t-test, we found that SD led to a significant decline in WM (t 21 = 9.508, p < 0.0001, see Figure 2 and Table 1), which is consistent with previous studies (Drummond et al, 2012;Martínez-Cancino et al, 2015;Lu, 2016;Tempesta et al, 2017;Harrington et al, 2018). rostrolateral prefrontal cortices, and left and right supramarginal gyri.…”

Section: Physiological Datasupporting

confidence: 90%

“…In recent decades, the n-back paradigm has been widely used in the study of WM because the task is of moderate difficulty and sensitivity. This paradigm is often used to measure executive control in WM and to explore the neural mechanism of WM based on resting-state fMRI data (Martínez-Cancino et al, 2015;Soveri et al, 2017;Costers et al, 2020). The task requires the subject to monitor a stimulus sequence to determine if the stimulus currently presented is the same as that presented before several trials.…”

Section: Wm Task Paradigmmentioning

confidence: 99%

“…Sleep deprivation causes a decline in many cognitive functions, one of the most sensitive of which is WM (Chee et al, 2006;Preece, 2012;Martínez-Cancino et al, 2015). Behavioral studies of WM after SD found that the longer the duration of SD, the longer the response time and the lower the accuracy rate (Lu, 2016;Tempesta et al, 2017;Harrington et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Effects of Sleep Deprivation on Working Memory: Change in Functional Connectivity Between the Dorsal Attention, Default Mode, and Fronto-Parietal Networks

Dai

Zhang²,

Cai

et al. 2020

Front. Hum. Neurosci.

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Sleep deprivation (SD) is very common in modern society and has a profound effect on cognitive function, in particular on working memory (WM). This type of memory is required for completion of many tasks and is adversely affected by SD. However, the cognitive neural mechanism by which SD affects WM, remains unclear. In this study, we investigated the changes in the brain network involved in WM after SD. Twentytwo healthy subjects underwent functional magnetic resonance imaging scan while in a state of resting wakefulness and again after 36 h of total SD and performed a WM task before each scanning session. Nineteen main nodes of the default mode network (DMN), dorsal attention network (DAN), fronto-parietal network (FPN), salience network (SN), and other networks were selected for functional analysis of brain network connections. Functional connectivity measures were computed between seed areas for region of interest (ROI)-to-ROI analysis and to identify patterns of ROI-to-ROI connectivity. The relationship between the significant changes in functional connectivity in the brain network and WM performance were then examined by Pearson's correlation analysis. WM performance declined significantly after SD. Compared with the awake state, the functional connectivity between DAN and DMN significantly increased after SD while that between FPN and DMN significantly decreased. Correlation analysis showed that the enhanced functional connectivity between DAN and DMN was negatively correlated with the decline in WM performance and that the decline in functional connectivity between FPN and DMN was positively correlated with decreased WM performance. These findings suggested that SD may affect WM by altering the functional connectivity among DMN, DAN, and FPN.

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Section: Physiological Datasupporting

confidence: 90%

Section: Wm Task Paradigmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effects of Sleep Deprivation on Working Memory: Change in Functional Connectivity Between the Dorsal Attention, Default Mode, and Fronto-Parietal Networks

Dai

Zhang²,

Cai

et al. 2020

Front. Hum. Neurosci.

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“…By using an n-back task with conditions that vary in difficulty, studies have also demonstrated that cognitive load selectively influenced the disrupting effect of pain on updating [35]. In addition, studies have indicated that updating can be impaired following sleep deprivation [36]. As a headache is a 'core' hangover symptom [1], and individuals experience sleep disruptions after heavy alcohol consumption (e.g., decreased efficiency and REM sleep, increased night-time awakenings [37], and decreased sleep duration [38]), updating ability may also be compromised by a hangover.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Alcohol Hangover on Executive Functions

Gunn

Fairchild

Verster

et al. 2020

JCM

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Recent research has suggested that processes reliant on executive functions are impaired by an alcohol hangover, yet few studies have investigated the effect of hangovers on core executive function processes. Therefore, the current study investigated the effect of hangovers on the three core components of the unity/diversity model of executive functions: the ability to switch attention, update information in working memory, and maintain goals. Thirty-five 18-to-30-year-old non-smoking individuals who reported experiencing a hangover at least once in the previous month participated in this study. They completed tasks measuring switching (number-switching task), updating (n-back task), and goal maintenance (AX Continuous Performance Test, AX-CPT) whilst experiencing a hangover and without a hangover in a ‘naturalistic’ within-subjects crossover design. Participants made more errors in the switching task (p = 0.019), more errors in both the 1- (p < 0.001) and 2-back (p < 0.001) versions of the n-back, and more errors in the AX-CPT (p = 0.007) tasks when experiencing a hangover, compared to the no-hangover condition. These results suggest that an alcohol hangover impairs core executive function processes that are important for everyday behaviours, such as decision-making, planning, and mental flexibility.

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“…A esta baja activación se suma el aburrimiento y baja concentración. 52 Por lo tanto, estos parámetros deben tomarse en cuenta y ser valorarlos en los pacientes antes de la aplicación de la prueba.…”

Section: Discussionunclassified

Propuesta de un paradigma computarizado para valorar memoria de trabajo.

et al. 2020

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Se validó un paradigma para evaluar memoria de trabajo con el uso de las tareas N-back en un programa informático para ser aplicado dentro de Resonancia Magnética Funcional (RMF). La hipótesis de estudio se basa en que un nivel de dificultad 2-back verbal aumenta el éxito en el desempeño de la tarea en memoria de trabajo, válido para ser usado en RMF. Por medio de un estudio cuantitativo transversal se adaptó el paradigma N-back a un programa informático PshicoPy. La tarea consistió en responder al estímulo o letra que sea igual al que apareció dos puestos atrás (2 back). Se presentaron 4 bloques de 30 segundos cada uno, y 4 bloques de reposo de 30 segundos; en total tiene una duración de 4 minutos. Para estudiar la validez del paradigma se realizó una validación por expertos y una prueba piloto con la participación de 18 sujetos adultos universitarios. Los datos se tabularon en una hoja de cálculo, usando pruebas estadísticas de tabla de contingencia; y de sensibilidad y especificidad. Los resultados ofrecieron datos mayores a 80 % de sensibilidad y especificidad en cuanto al desempeño del sujeto ante la prueba, y de la validez de los estímulos. Se concluye que la prueba puede ser usada para valorar memoria de trabajo por medio de un programa informático, el mismo que también puede ser usado en aplicaciones como la RMF.

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The Effects of Sleep Deprivation in Working Memory Using the N-back Task

Cited by 6 publications

References 0 publications

Effects of Sleep Deprivation on Working Memory: Change in Functional Connectivity Between the Dorsal Attention, Default Mode, and Fronto-Parietal Networks

Effects of Sleep Deprivation on Working Memory: Change in Functional Connectivity Between the Dorsal Attention, Default Mode, and Fronto-Parietal Networks

The Effects of Alcohol Hangover on Executive Functions

Propuesta de un paradigma computarizado para valorar memoria de trabajo.

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