Lack of neural load modulation explains attention and working memory deficits in first-episode schizophrenia

Decoding cognition in neurodevelopmental, psychiatric and neurological conditions with multivariate pattern analysis of EEG data

Multivariate pattern analysis (MVPA) of electroencephalographic (EEG) data represents a revolutionary approach to investigate how the brain encodes information. By considering complex interactions among spatio-temporal features at the individual level, MVPA overcomes the limitations of univariate techniques, which often fail to account for the significant inter- and intra-individual neural variability. This is particularly relevant when studying clinical populations, and therefore MVPA of EEG data has recently started to be employed as a tool to study cognition in brain disorders. Here, we review the insights offered by this methodology in the study of anomalous patterns of neural activity in conditions such as autism, ADHD, schizophrenia, dyslexia, neurological and neurodegenerative disorders, within different cognitive domains (perception, attention, memory, consciousness). Despite potential drawbacks that should be attentively addressed, these studies reveal a peculiar sensitivity of MVPA in unveiling dysfunctional and compensatory neurocognitive dynamics of information processing, which often remain blind to traditional univariate approaches. Such higher sensitivity in characterizing individual neurocognitive profiles can provide unique opportunities to optimise assessment and promote personalised interventions.

Prioritizing flexible working memory representations through retrospective attentional strengthening

Previous work has proposed two potential benefits of retrospective attention on working memory (WM): target strengthening and non-target inhibition. It remains unknown which hypothesis contributes to the improved WM performance, yet the neural mechanisms responsible for this attentional benefit are unclear. Here, we recorded electroencephalography (EEG) signals while 33 participants performed a retrospective-cue WM task. Multivariate pattern classification analysis revealed that only representations of target features were enhanced by valid retrospective attention during retention, supporting the target strengthening hypothesis. Further univariate analysis found that mid-frontal theta inter-trial phase coherence (ITPC) and ERP components were modulated by valid retrospective attention and correlated with individual differences and moment-to-moment fluctuations on behavioral outcomes, suggesting that both trait- and state-level variability in attentional preparatory processes influence goal-directed behavior. Furthermore, task-irrelevant target spatial location could be decoded from EEG signals, indicating that enhanced spatial binding of target representation is vital to high WM precision. Importantly, frontoparietal theta-alpha phase-amplitude coupling was increased by valid retrospective attention and predicted the reduced random guessing rates. This long-range connection supported top-down information flow in the engagement of frontoparietal networks, which might organize attentional states to integrate target features. Altogether, these results provide neurophysiological bases that retrospective attention improves WM precision by enhancing flexible target representation and emphasize the critical role of the frontoparietal attentional network in the control of WM representations.

Transcranial photobiomodulation enhances visual working memory capacity in humans

Transcranial photobiomodulation (tPBM) is a safe and noninvasive intervention that has shown promise for improving cognitive performance. Whether tPBM can modulate brain activity and thereby enhance working memory (WM) capacity in humans remains unclear. In this study, we found that 1064-nm tPBM applied to the right prefrontal cortex (PFC) improves visual working memory capacity and increases occipitoparietal contralateral delay activity (CDA). The CDA set-size effect during retention mediated the effect between the 1064-nm tPBM and subsequent WM capacity. The behavioral benefits and the corresponding changes in the CDA set-size effect were absent with tPBM at a wavelength of 852 nm or with stimulation of the left PFC. Our findings provide converging evidence that 1064-nm tPBM applied to the right PFC can improve WM capacity.

Information-based multivariate decoding reveals imprecise neural encoding in children with attention deficit hyperactivity disorder during visual selective attention

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in school-age children. Attentional orientation is a potential clinical diagnostic marker to aid in the early diagnosis of ADHD. However, the underlying pathophysiological substrates of impaired attentional orienting in childhood ADHD remain unclear. Electroencephalography (EEG) was measured in 135 school-age children (70 with childhood ADHD and 65 matched typically developing children) to directly investigate target localization during spatial selective attention through univariate ERP analysis and information-based multivariate pattern machine learning analysis. Compared with children with typical development, a smaller N2pc was found in the ADHD group through univariate ERP analysis. Children with ADHD showed a lower parieto-occipital multivariate decoding accuracy approximately 240-340 ms after visual search onset, which predicts a slower reaction time and larger standard deviation of reaction time. Furthermore, a significant correlation was found between N2pc and decoding accuracy in typically developing children but not in children with ADHD. These observations reveal that impaired attentional orienting in ADHD may be due to inefficient neural encoding responses. By using a personalized information-based multivariate machine learning approach, we have advanced the understanding of cognitive deficits in neurodevelopmental disorders. Our study provides potential research directions for the early diagnosis and optimization of personalized intervention in children with ADHD.