Working memory load-dependent spatio-temporal activity of single-trial P3 response detected with an adaptive wavelet denoiser

Behavioural and neurophysiological differences in working memory function of depressed patients and healthy controls

OBJECTIVE

Major depressive disorder (MDD) is associated with deficits in working memory. Several cognitive subprocesses interact to produce working memory, including attention, encoding, maintenance and manipulation. We sought to clarify the contribution of functional deficits in these subprocesses in MDD by varying cognitive load during a working memory task.

METHODS

41 depressed participants and 41 age and gender-matched healthy controls performed the n-back working memory task at three levels of difficulty (0-, 1-, and 2-back) in a pregistered study. We assessed response times, accuracy, and event-related electroencephalography (EEG), including P2 and P3 amplitudes, and frontal theta power (4-8 Hz).

RESULTS

MDD participants had prolonged response times and more positive frontal P3 amplitudes (i.e., Fz) relative to controls, mainly in the most difficult 2-back condition. Working memory accuracy, P2 amplitudes and frontal theta event-related synchronisation did not differ between groups at any level of task difficulty.

CONCLUSIONS

Depression is associated with generalized psychomotor slowing of working memory processes, and may involve compensatory hyperactivity in frontal and parietal regions.

SIGNIFICANCE

These findings provide insights into MDD working memory deficits, indicating that depressed individuals dedicate greater levels of cortical processing and cognitive resources to achieve comparable working memory performance to controls.

Skipping Breakfast Affects the Early Steps of Cognitive Processing

Abstract. It has been generally accepted that skipping breakfast adversely affects cognition, mainly disturbing the attentional processes. However, the effects of short-term fasting upon brain functioning are still unclear. We aimed to evaluate the effect of skipping breakfast on cognitive processing by studying the electrical brain activity of young healthy individuals while performing several working memory tasks. Accordingly, the behavioral results and event-related brain potentials (ERPs) of 20 healthy university students (10 males) were obtained and compared through analysis of variances (ANOVAs), during the performance of three n-back working memory (WM) tasks in two morning sessions on both normal (after breakfast) and 12-hour fasting conditions. Significantly fewer correct responses were achieved during fasting, mainly affecting the higher WM load task. In addition, there were prolonged reaction times with increased task difficulty, regardless of breakfast intake. ERP showed a significant voltage decrement for N200 and P300 during fasting, while the amplitude of P200 notably increased. The results suggest skipping breakfast disturbs earlier cognitive processing steps, particularly attention allocation, early decoding in working memory, and stimulus evaluation, and this effect increases with task difficulty.

Potential Mechanisms for the Ketamine-Induced Reduction of P3b Amplitudes

In specific dosages, the N-methyl-D-aspartate receptor (NMDA) antagonist ketamine can be used to model transient psychotic symptoms in healthy individuals that resemble those of schizophrenia. Ketamine administration also temporarily impairs cognitive functions, which can be studied by event-related potentials (ERPs). ERPs also allow dissecting what stages of information processing are affected by ketamine and what stages remain functional. For tasks requiring the differentiation of targets and non-targets, it has repeatedly been shown that ketamine administration in healthy individuals leads to decreased amplitudes of the ERP component P3b in response to target stimuli. However, it could be argued that this ketamine-induced P3b reduction is the consequence of an increased difficulty to differentiate targets from non-targets, primarily mediated by ketamine's psychotomimetic rather than pharmacological effects. The current review of ERP studies seeks to clarify the issue whether P3b effects of ketamine may indeed be explained as the consequence of an experienced increase in task difficulty or whether alternative mechanisms are perhaps more plausible. The review first summarizes the effects of task difficulty on ERP components related to intentional stimulus categorization (P3b), involuntary attention switches to distractors (P3a), as well as sensory processing (P1, N1). Secondly, the ERP effects of task difficulty are contrasted with those observed in ketamine studies in healthy individuals. Findings show that P3b amplitudes are consistently diminished by an increased task difficulty, as well as after ketamine administration. In contrast and as most important difference, increased task difficulty leads to increased P3a amplitudes to distractors presented in same modality as targets, whereas ketamine leads to reduced P3a amplitudes for such distractors. This dissociation indicates that the decreased P3b amplitudes after ketamine cannot be explained by a drug-induced increase in task difficulty. The conjoint reductions of P3a and P3b amplitudes instead suggest that working memory operations, in particular working memory updating are impaired after ketamine, which is in line with previous behavioral findings.

Network Entropy for the Sequence Analysis of Functional Connectivity Graphs of the Brain

Dynamic representation of functional brain networks involved in the sequence analysis of functional connectivity graphs of the brain (FCGB) gains advances in uncovering evolved interaction mechanisms. However, most of the networks, even the event-related ones, are highly heterogeneous due to spurious interactions, which bring challenges to revealing the change patterns of interactive information in the complex dynamic process. In this paper, we propose a network entropy (NE) method to measure connectivity uncertainty of FCGB sequences to alleviate the spurious interaction problem in dynamic network analysis to realize associations with different events during a complex cognitive task. The proposed dynamic analysis approach calculated the adjacency matrices from ongoing electroencephalpgram (EEG) in a sliding time-window to form the FCGB sequences. The probability distribution of Shannon entropy was replaced by the connection sequence distribution to measure the uncertainty of FCGB constituting NE. Without averaging, we used time frequency transform of the NE of FCGB sequences to analyze the event-related changes in oscillatory activity in the single-trial traces during the complex cognitive process of driving. Finally, the results of a verification experiment showed that the NE of the FCGB sequences has a certain time-locked performance for different events related to driver fatigue in a prolonged driving task. The time errors between the extracted time of high-power NE and the recorded time of event occurrence were distributed within the range [−30 s, 30 s] and 90.1% of the time errors were distributed within the range [−10 s, 10 s]. The high correlation (r = 0.99997, p < 0.001) between the timing characteristics of the two types of signals indicates that the NE can reflect the actual dynamic interaction states of brain. Thus, the method may have potential implications for cognitive studies and for the detection of physiological states.

Localized Fluctuant Oscillatory Activity by Working Memory Load: A Simultaneous EEG-fMRI Study

Working memory (WM) is a resource-limited memory system for temporary storage and processing of brain information during the execution of cognitive tasks. Increased WM load will increase the amount and difficulty of memory information. Several studies have used electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) to explore load-dependent cognition processing according to the time courses of electrophysiological activity or the spatial pattern of blood oxygen metabolic activity. However, the relationships between these two activities and the underlying neural mechanism are still unclear. In this study, using simultaneously collected EEG and fMRI data under an n-back verbal WM task, we modeled the spectral perturbation of EEG oscillation and fMRI activation through joint independent component analysis (JICA). Multi-channel oscillation features were also introduced into the JICA model for further analysis. The results showed that time-locked activity of theta and beta were modulated by memory load in the early stimuli evaluation stage, corresponding to the enhanced activation in the frontal and parietal lobe, which were involved in stimulus discrimination, information encoding and delay-period activity. In the late response selection stage, alpha and gamma activity changes dependent on the load correspond to enhanced activation in the areas of frontal, temporal and parietal lobes, which played important roles in attention, information extraction and memory retention. These findings suggest that the increases in memory load not only affect the intensity and time course of the EEG activities, but also lead to the enhanced activation of brain regions which plays different roles during different time periods of cognitive process of WM.