Bilateral advantage in visual working memory is observed when individual hemisphere’s capacity is exceeded

What are the mechanisms of visual information maintenance that underlie its highly limited capacity is a key question in visual working memory research. Previous studies emphasized the role of posterior brain regions, which enable the formation of visual representations. Their contralateral organization allows individuals to maintain more information when they are presented across both visual hemifields and are processed by both hemispheres. This phenomenon is known as bilateral advantage. Based on previous findings on bilateral advantage in visual information maintenance, the aim of our study was to assess at what working memory load can bilateral advantage be observed, and whether in the case of bilateral presentation of information participants can take full advantage of joint left and right hemisphere’s capacities. Eighteen students (13 woman) aged between 19 and 41 participated in the study and completed a change detection task, in which they were asked to recognize a change in the orientation of the objects presented to the left, right, or both visual hemifields. The results showed that the participants were able to maintain more visual information and gave quicker responses when objects were distributed across both visual hemifields, which is in line with the assumption that bilateral display facilitates the use of both hemispheres’ capacities. Furthermore, the results showed that bilateral advantage occurs only when visual working memory load exceeds the capacity of the individual hemispheres. Despite significant bilateral advantage, bilateral presentation of visual information, however, does not allow the participants to utilize the full joint capacity of the two hemispheres, suggesting that the capacity of visual working memory is limited not only by the ability to form representations, but also by an additional cognitive system

CORTICAL BRAIN PERFUSION AND COGNITIVE EVENT RELATED POTENTIALS IN PATIENTS WITH PSYCHOMOTOR RETARDATION IN LATE ONSET DEPRESSION

Background: Late onset depression is characterised by pronounced cognitive impairment, more somatic complaints and psychomotor retardation. Psychomotor slowing may be due to impairment in either motor or cognitive domain. Electrophysiology may be particularly convenient as a tool in studies of psychomotor retardation, as it can separate central cognitive processing from the motor processing. Subjects and methods: In this study we compared event related potentials (ERP) in the two groups of patients with late onset depression and psychomotor slowing as measured by reaction time (RT): a group of patients with lower RT was compared to a group with a higher RT. Twenty patients with late onset depression were included in the study after they had reached remission. Four weeks after reaching remission patients were reevaluated clinically using Hamilton Depression Rating Scale, Mini Mental State Examination, and with a computer version of the Stroop task. ERP, accuracy and RTs were simultaneously recorded. Both groups of patients aditionaly underwent a perfusion SPECT imaging. Results: There were no differences between the short and long RT groups of patients in amplitudes of the late positive Stroop related potentials. The group of patients with longer RTs showed significant hyperperfusion in precentral gyrus, parietal regions, cuneus and hypoperfusion within insular, frontal, temporal and limbic (parahyppocampal gyrus and anterior cingulate) cortices, as well as cerebellum. Conclusion: We found no ERP differences between the two groups suggesting that although patients may differ on psychomotor retardation measured as RT, their cognitive abilities may be quite similar. Perfusion SPECT imaging however revealed a significant difference between them. This may be due to a process of compensation and applying different strategies to cope with cognitive impairment in the two groups

Dense attention network identifies EEG abnormalities during working memory performance of patients with schizophrenia

IntroductionPatients with schizophrenia typically exhibit deficits in working memory (WM) associated with abnormalities in brain activity. Alterations in the encoding, maintenance and retrieval phases of sequential WM tasks are well established. However, due to the heterogeneity of symptoms and complexity of its neurophysiological underpinnings, differential diagnosis remains a challenge. We conducted an electroencephalographic (EEG) study during a visual WM task in fifteen schizophrenia patients and fifteen healthy controls. We hypothesized that EEG abnormalities during the task could be identified, and patients successfully classified by an interpretable machine learning algorithm.MethodsWe tested a custom dense attention network (DAN) machine learning model to discriminate patients from control subjects and compared its performance with simpler and more commonly used machine learning models. Additionally, we analyzed behavioral performance, event-related EEG potentials, and time-frequency representations of the evoked responses to further characterize abnormalities in patients during WM.ResultsThe DAN model was significantly accurate in discriminating patients from healthy controls, ACC = 0.69, SD = 0.05. There were no significant differences between groups, conditions, or their interaction in behavioral performance or event-related potentials. However, patients showed significantly lower alpha suppression in the task preparation, memory encoding, maintenance, and retrieval phases F(1,28) = 5.93, p = 0.022, η2 = 0.149. Further analysis revealed that the two highest peaks in the attention value vector of the DAN model overlapped in time with the preparation and memory retrieval phases, as well as with two of the four significant time-frequency ROIs.DiscussionThese results highlight the potential utility of interpretable machine learning algorithms as an aid in diagnosis of schizophrenia and other psychiatric disorders presenting oscillatory abnormalities

PET of Brain Prion Protein Amyloid in Gerstmann–Sträussler–Scheinker Disease

In vivo amyloid PET imaging was carried out on six symptomatic and asymptomatic carriers of PRNP mutations associated with the Gerstmann-Sträussler-Scheinker (GSS) disease, a rare familial neurodegenerative brain disorder demonstrating prion amyloid neuropathology, using 2-(1-{6-[(2-[F-18]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile ([F-18]FDDNP). 2-Deoxy-2-[F-18]fluoro-d-glucose PET ([F-18]FDG) and magnetic resonance imaging (MRI) scans were also performed in each subject. Increased [F-18]FDDNP binding was detectable in cerebellum, neocortex and subcortical areas of all symptomatic gene carriers in close association with the experienced clinical symptoms. Parallel glucose metabolism ([F-18]FDG) reduction was observed in neocortex, basal ganglia and/or thalamus, which supports the close relationship between [F-18]FDDNP binding and neuronal dysfunction. Two asymptomatic gene carriers displayed no cortical [F-18]FDDNP binding, yet progressive [F-18]FDDNP retention in caudate nucleus and thalamus was seen at 1- and 2-year follow-up in the older asymptomatic subject. In vitro FDDNP labeling experiments on brain tissue specimens from deceased GSS subjects not participating in the in vivo studies indicated that in vivo accumulation of [F-18]FDDNP in subcortical structures, neocortices and cerebellum closely related to the distribution of prion protein pathology. These results demonstrate the feasibility of detecting prion protein accumulation in living patients with [F-18]FDDNP PET, and suggest an opportunity for its application to follow disease progression and monitor therapeutic interventions

QuNex—An integrative platform for reproducible neuroimaging analytics

Introduction: Neuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces challenges in method integration, particularly across multiple modalities and species. Specifically, researchers often have to rely on siloed approaches which limit reproducibility, with idiosyncratic data organization and limited software interoperability.Methods: To address these challenges, we have developed Quantitative Neuroimaging Environment & Toolbox (QuNex), a platform for consistent end-to-end processing and analytics. QuNex provides several novel functionalities for neuroimaging analyses, including a “turnkey” command for the reproducible deployment of custom workflows, from onboarding raw data to generating analytic features.Results: The platform enables interoperable integration of multi-modal, community-developed neuroimaging software through an extension framework with a software development kit (SDK) for seamless integration of community tools. Critically, it supports high-throughput, parallel processing in high-performance compute environments, either locally or in the cloud. Notably, QuNex has successfully processed over 10,000 scans across neuroimaging consortia, including multiple clinical datasets. Moreover, QuNex enables integration of human and non-human workflows via a cohesive translational platform.Discussion: Collectively, this effort stands to significantly impact neuroimaging method integration across acquisition approaches, pipelines, datasets, computational environments, and species. Building on this platform will enable more rapid, scalable, and reproducible impact of neuroimaging technology across health and disease

The mode of response and the Stroop effect: A reaction time analysis

While the classical card versions of the Stroop colour-word tasks employ verbal mode of response (the participants have to read the stimuli or name their ink colour aloud), the single-item computerised versions of the task frequently rely on manual mode of response (the participants need to signal the meaning of the stimuli or its ink colour by pressing the appropriate key). An experiment was carried out to directly assess possible ERP and reaction times differences between a verbal and a manual response mode version of the task. The comparison of reaction time results obtained on 22 students of psychology performing both verbal and manual response mode version of the task show longer reaction times for the manual version as well as important differences between the patterns of reaction times of individual conditions obtained in each version of the task. The result demonstrated a qualitative difference between the two versions of the task, which can be attributed to a stronger influence of automatic word reading in the verbal response mode version. The differences shown warn against a direct comparison of results obtained with different response mode versions of the Stroop colour-word task

Cognitive Neuroscience and the "Mind-Body problem"

In recent years we have witnessed an upsurge of interest in the study of the human mind and how it relates to the material body, the brain. Cognitive neuroscience is a multidisciplinary science that tries to explain how the mind arises from the structure and workings of the brain. Can we equate the study of mind-body relationship with cognitive neuroscience? Are there aspects of mind-body relationship that are not covered by cognitive neuroscience? Is cognitive neuroscience able to explain human behaviour and experience? These are the questions that are addressed in this "Beginner's Guide to Cognitive neuroscience and it's relation to the Body-Mind question"