What is it like to do a visuo-spatial working memory task: A qualitative phenomenological study of the visual span task.

Working memory is typically measured with specifically designed psychological tasks. When evaluating the validity of working memory tasks, we commonly focus on the reliability of the outcome measurements. Only rarely do we focus on how participants experience these tasks. Accounting for lived experience of working memory task may help us better understand variability in working memory performance and conscious experience in general. We replicated recently established protocols for the phenomenological investigation of working memory using the visual span task. We collected subjective reports from eighteen healthy participants (10 women) aged 21 to 35 years. We observed that working memory can be phenomenologically characterized at three different time scales: background feelings, strategies, and tactics. On the level of tactics, we identified transmodality (i.e., how one modality of lived experience can be transformed into another one) as the central phenomenological dynamic at play during working memory task performance.

Reward and loss incentives improve spatial working memory by shaping trial-by-trial posterior frontoparietal signals.

Integrating motivational signals with cognition is critical for goal-directed activities. The mechanisms that link neural changes with motivated working memory continue to be understood. Here, we tested how externally cued and non-cued (internally represented) reward and loss impact spatial working memory precision and neural circuits in human subjects using fMRI. We translated the classic delayed-response spatial working memory paradigm from non-human primate studies to take advantage of a continuous numeric measure of working memory precision, and the wealth of translational neuroscience yielded by these studies. Our results demonstrated that both cued and non-cued reward and loss improved spatial working memory precision. Visual association regions of the posterior prefrontal and parietal cortices, specifically the precentral sulcus (PCS) and intraparietal sulcus (IPS), had increased BOLD signal during incentivized spatial working memory. A subset of these regions had trial-by-trial increases in BOLD signal that were associated with better working memory precision, suggesting that these regions may be critical for linking neural signals with motivated working memory. In contrast, regions straddling executive networks, including areas in the dorsolateral prefrontal cortex, anterior parietal cortex and cerebellum displayed decreased BOLD signal during incentivized working memory. While reward and loss similarly impacted working memory processes, they dissociated during feedback when money won or avoided in loss was given based on working memory performance. During feedback, the trial-by-trial amount and valence of reward/loss received was dissociated amongst regions such as the ventral striatum, habenula and periaqueductal gray. Overall, this work suggests motivated spatial working memory is supported by complex sensory processes, and that the IPS and PCS in the posterior frontoparietal cortices may be key regions for integrating motivational signals with spatial working memory precision.

Dynamic Seat Assessment for Enabled Restlessness of Children with Learning Difficulties.

Children with Attention-Deficit/Hyperactivity Disorder (ADHD) face a range of learning difficulties in the school environment, thus several strategies have been developed to enhance or optimise their performance in school. One possible way is to actively enable appropriate restlessness using dynamic seats. In this paper, an assessment of the efficacy of a dynamic seat while solving school task is presented and compared to classic chair and therapy ball. To test the effectiveness of active seat, a study that examined task solving performance while observing the intensity of movement, in-seat behaviour and psychophysiological responses (electrodermal activity, facial temperature) was designed. A total of 23 school-aged children participated in the study, 11 children with a combined type of ADHD and 12 children without disorders. Children with ADHD achieved the best results when sitting in the active seat, where the most intense movement and best in-seat behaviour was observed. At the same time, psychophysiological parameters indicate that when performing better at the task children with ADHD were not too challenged and were consequently less agitated. Results have suggested that for a better cognitive performance of children with ADHD, it is crucial to provide a comfortable and pleasant workspace that enables them the right amount of restlessness.

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.

Schizophrenia Exhibits Bi-directional Brain-Wide Alterations in Cortico-Striato-Cerebellar Circuits.

Distributed neural dysconnectivity is considered a hallmark feature of schizophrenia (SCZ), yet a tension exists between studies pinpointing focal disruptions versus those implicating brain-wide disturbances. The cerebellum and the striatum communicate reciprocally with the thalamus and cortex through monosynaptic and polysynaptic connections, forming cortico-striatal-thalamic-cerebellar (CSTC) functional pathways that may be sensitive to brain-wide dysconnectivity in SCZ. It remains unknown if the same pattern of alterations persists across CSTC systems, or if specific alterations exist along key functional elements of these networks. We characterized connectivity along major functional CSTC subdivisions using resting-state functional magnetic resonance imaging in 159 chronic patients and 162 matched controls. Associative CSTC subdivisions revealed consistent brain-wide bi-directional alterations in patients, marked by hyper-connectivity with sensory-motor cortices and hypo-connectivity with association cortex. Focusing on the cerebellar and striatal components, we validate the effects using data-driven k-means clustering of voxel-wise dysconnectivity and support vector machine classifiers. We replicate these results in an independent sample of 202 controls and 145 patients, additionally demonstrating that these neural effects relate to cognitive performance across subjects. Taken together, these results from complementary approaches implicate a consistent motif of brain-wide alterations in CSTC systems in SCZ, calling into question accounts of exclusively focal functional disturbances.

Mapping the human brain's cortical-subcortical functional network organization.

Understanding complex systems such as the human brain requires characterization of the system's architecture across multiple levels of organization - from neurons, to local circuits, to brain regions, and ultimately large-scale brain networks. Here we focus on characterizing the human brain's large-scale network organization, as it provides an overall framework for the organization of all other levels. We developed a highly principled approach to identify cortical network communities at the level of functional systems, calibrating our community detection algorithm using extremely well-established sensory and motor systems as guides. Building on previous network partitions, we replicated and expanded upon well-known and recently-identified networks, including several higher-order cognitive networks such as a left-lateralized language network. We expanded these cortical networks to subcortex, revealing 358 highly-organized subcortical parcels that take part in forming whole-brain functional networks. Notably, the identified subcortical parcels are similar in number to a recent estimate of the number of cortical parcels (360). This whole-brain network atlas - released as an open resource for the neuroscience community - places all brain structures across both cortex and subcortex into a single large-scale functional framework, with the potential to facilitate a variety of studies investigating large-scale functional networks in health and disease.

Functional hierarchy underlies preferential connectivity disturbances in schizophrenia.

Schizophrenia may involve an elevated excitation/inhibition (E/I) ratio in cortical microcircuits. It remains unknown how this regulatory disturbance maps onto neuroimaging findings. To address this issue, we implemented E/I perturbations within a neural model of large-scale functional connectivity, which predicted hyperconnectivity following E/I elevation. To test predictions, we examined resting-state functional MRI in 161 schizophrenia patients and 164 healthy subjects. As predicted, patients exhibited elevated functional connectivity that correlated with symptom levels, and was most prominent in association cortices, such as the fronto-parietal control network. This pattern was absent in patients with bipolar disorder (n = 73). To account for the pattern observed in schizophrenia, we integrated neurobiologically plausible, hierarchical differences in association vs. sensory recurrent neuronal dynamics into our model. This in silico architecture revealed preferential vulnerability of association networks to E/I imbalance, which we verified empirically. Reported effects implicate widespread microcircuit E/I imbalance as a parsimonious mechanism for emergent inhomogeneous dysconnectivity in schizophrenia.

Altered Global Signal Topography in Schizophrenia.

Schizophrenia (SCZ) is a disabling neuropsychiatric disease associated with disruptions across distributed neural systems. Resting-state functional magnetic resonance imaging has identified extensive abnormalities in the blood-oxygen level-dependent signal in SCZ patients, including alterations in the average signal over the brain-i.e. the "global" signal (GS). It remains unknown, however, if these "global" alterations occur pervasively or follow a spatially preferential pattern. This study presents the first network-by-network quantification of GS topography in healthy subjects and SCZ patients. We observed a nonuniform GS contribution in healthy comparison subjects, whereby sensory areas exhibited the largest GS component. In SCZ patients, we identified preferential GS representation increases across association regions, while sensory regions showed preferential reductions. GS representation in sensory versus association cortices was strongly anti-correlated in healthy subjects. This anti-correlated relationship was markedly reduced in SCZ. Such shifts in GS topography may underlie profound alterations in neural information flow in SCZ, informing development of pharmacotherapies.

Altered global brain signal in schizophrenia.

Neuropsychiatric conditions like schizophrenia display a complex neurobiology, which has long been associated with distributed brain dysfunction. However, no investigation has tested whether schizophrenia shows alterations in global brain signal (GS), a signal derived from functional MRI and often discarded as a meaningless baseline in many studies. To evaluate GS alterations associated with schizophrenia, we studied two large chronic patient samples (n = 90, n = 71), comparing them to healthy subjects (n = 220) and patients diagnosed with bipolar disorder (n = 73). We identified and replicated increased cortical power and variance in schizophrenia, an effect predictive of symptoms yet obscured by GS removal. Voxel-wise signal variance was also increased in schizophrenia, independent of GS effects. Both findings were absent in bipolar patients, confirming diagnostic specificity. Biologically informed computational modeling of shared and nonshared signal propagation through the brain suggests that these findings may be explained by altered net strength of overall brain connectivity in schizophrenia.

Early-course unmedicated schizophrenia patients exhibit elevated prefrontal connectivity associated with longitudinal change.

Strong evidence implicates prefrontal cortex (PFC) as a major source of functional impairment in severe mental illness such as schizophrenia. Numerous schizophrenia studies report deficits in PFC structure, activation, and functional connectivity in patients with chronic illness, suggesting that deficient PFC functional connectivity occurs in this disorder. However, the PFC functional connectivity patterns during illness onset and its longitudinal progression remain uncharacterized. Emerging evidence suggests that early-course schizophrenia involves increased PFC glutamate, which might elevate PFC functional connectivity. To test this hypothesis, we examined 129 non-medicated, human subjects diagnosed with early-course schizophrenia and 106 matched healthy human subjects using both whole-brain data-driven and hypothesis-driven PFC analyses of resting-state fMRI. We identified increased PFC connectivity in early-course patients, predictive of symptoms and diagnostic classification, but less evidence for "hypoconnectivity." At the whole-brain level, we observed "hyperconnectivity" around areas centered on the default system, with modest overlap with PFC-specific effects. The PFC hyperconnectivity normalized for a subset of the sample followed longitudinally (n = 25), which also predicted immediate symptom improvement. Biologically informed computational modeling implicates altered overall connection strength in schizophrenia. The initial hyperconnectivity, which may decrease longitudinally, could have prognostic and therapeutic implications.

Characterizing thalamo-cortical disturbances in schizophrenia and bipolar illness.

Schizophrenia is a devastating neuropsychiatric syndrome associated with distributed brain dysconnectivity that may involve large-scale thalamo-cortical systems. Incomplete characterization of thalamic connectivity in schizophrenia limits our understanding of its relationship to symptoms and to diagnoses with shared clinical presentation, such as bipolar illness, which may exist on a spectrum. Using resting-state functional magnetic resonance imaging, we characterized thalamic connectivity in 90 schizophrenia patients versus 90 matched controls via: (1) Subject-specific anatomically defined thalamic seeds; (2) anatomical and data-driven clustering to assay within-thalamus dysconnectivity; and (3) machine learning to classify diagnostic membership via thalamic connectivity for schizophrenia and for 47 bipolar patients and 47 matched controls. Schizophrenia analyses revealed functionally related disturbances: Thalamic over-connectivity with bilateral sensory-motor cortices, which predicted symptoms, but thalamic under-connectivity with prefrontal-striatal-cerebellar regions relative to controls, possibly reflective of sensory gating and top-down control disturbances. Clustering revealed that this dysconnectivity was prominent for thalamic nuclei densely connected with the prefrontal cortex. Classification and cross-diagnostic results suggest that thalamic dysconnectivity may be a neural marker for disturbances across diagnoses. Present findings, using one of the largest schizophrenia and bipolar neuroimaging samples to date, inform basic understanding of large-scale thalamo-cortical systems and provide vital clues about the complex nature of its disturbances in severe mental illness.

The electrophysiological correlates of the working memory subcomponents: evidence from high-density EEG and coherence analysis.

Synchronization between prefrontal (executive) and posterior (association) cortices seems a plausible mechanism for temporary maintenance of information. However, while EEG studies reported involvement of (pre)frontal midline structures in synchronization, functional neuroimaging elucidated the importance of lateral prefrontal cortex (PFC) in working memory (WM). Verbal and spatial WM rely on lateralized subsystems (phonological loop and visuospatial sketchpad, respectively), yet only trends for hemispheric dissociation of networks supporting rehearsal of verbal and spatial information were identified by EEG. As oscillatory activity is WM load dependent, we applied an individually tailored submaximal load for verbal (V) and spatial (S) task to enhance synchronization in the relevant functional networks. To map these networks, we used high-density EEG and coherence analysis. Our results imply that the synchronized activity is limited to highly specialized areas that correspond well with the areas identified by functional neuroimaging. In both V and S task, two independent networks of theta synchronization involving dorsolateral PFC of each hemisphere were revealed. In V task, left prefrontal and left parietal areas were functionally coupled in gamma frequencies. Theta synchronization thus provides the necessary interface for storage and manipulation of information, while left-lateralized gamma synchronization could represent the EEG correlate of the phonological loop.

NMDA receptor function in large-scale anticorrelated neural systems with implications for cognition and schizophrenia.

Glutamatergic neurotransmission mediated by N-methyl-d-aspartate (NMDA) receptors is vital for the cortical computations underlying cognition and might be disrupted in severe neuropsychiatric illnesses such as schizophrenia. Studies on this topic have been limited to processes in local circuits; however, cognition involves large-scale brain systems with multiple interacting regions. A prominent feature of the human brain's global architecture is the anticorrelation of default-mode vs. task-positive systems. Here, we show that administration of an NMDA glutamate receptor antagonist, ketamine, disrupted the reciprocal relationship between these systems in terms of task-dependent activation and connectivity during performance of delayed working memory. Furthermore, the degree of this disruption predicted task performance and transiently evoked symptoms characteristic of schizophrenia. We offer a parsimonious hypothesis for this disruption via biophysically realistic computational modeling, namely cortical disinhibition. Together, the present findings establish links between glutamate's role in the organization of large-scale anticorrelated neural systems, cognition, and symptoms associated with schizophrenia in humans.

Ketamine induces multiple individually distinct whole-brain functional connectivity signatures.

Background: Ketamine has emerged as one of the most promising therapies for treatment-resistant depression. However, inter-individual variability in response to ketamine is still not well understood and it is unclear how ketamine's molecular mechanisms connect to its neural and behavioral effects. Methods: We conducted a single-blind placebo-controlled study, with participants blinded to their treatment condition. 40 healthy participants received acute ketamine (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hr). We quantified resting-state functional connectivity via data-driven global brain connectivity and related it to individual ketamine-induced symptom variation and cortical gene expression targets. Results: We found that: (i) both the neural and behavioral effects of acute ketamine are multi-dimensional, reflecting robust inter-individual variability; (ii) ketamine's data-driven principal neural gradient effect matched somatostatin (SST) and parvalbumin (PVALB) cortical gene expression patterns in humans, while the mean effect did not; and (iii) behavioral data-driven individual symptom variation mapped onto distinct neural gradients of ketamine, which were resolvable at the single-subject level. Conclusions: These results highlight the importance of considering individual behavioral and neural variation in response to ketamine. They also have implications for the development of individually precise pharmacological biomarkers for treatment selection in psychiatry. Funding: This study was supported by NIH grants DP5OD012109-01 (A.A.), 1U01MH121766 (A.A.), R01MH112746 (J.D.M.), 5R01MH112189 (A.A.), 5R01MH108590 (A.A.), NIAAA grant 2P50AA012870-11 (A.A.); NSF NeuroNex grant 2015276 (J.D.M.); Brain and Behavior Research Foundation Young Investigator Award (A.A.); SFARI Pilot Award (J.D.M., A.A.); Heffter Research Institute (Grant No. 1-190420) (FXV, KHP); Swiss Neuromatrix Foundation (Grant No. 2016-0111) (FXV, KHP); Swiss National Science Foundation under the framework of Neuron Cofund (Grant No. 01EW1908) (KHP); Usona Institute (2015 - 2056) (FXV). Clinical trial number: NCT03842800.

Ketamine is a widely used anesthetic as well as a popular illegal recreational drug. Recently, it has also gained attention as a potential treatment for depression, particularly in cases that don't respond to conventional therapies. However, individuals can vary in their response to ketamine. For example, the drug can alter some people's perception, such as seeing objects as larger or small than they are, while other individuals are unaffected. Although a single dose of ketamine was shown to improve depression symptoms in approximately 65% of patients, the treatment does not work for a significant portion of patients. Understanding why ketamine does not work for everyone could help to identify which patients would benefit most from the treatment. Previous studies investigating ketamine as a treatment for depression have typically included a group of individuals given ketamine and a group given a placebo drug. Assuming people respond similarly to ketamine, the responses in each group were averaged and compared to one another. However, this averaging of results may have masked any individual differences in response to ketamine. As a result, Moujaes et al. set out to investigate whether individuals show differences in brain activity and behavior in response to ketamine. Moujaes et al. monitored the brain activity and behavior of 40 healthy individuals that were first given a placebo drug and then ketamine. The results showed that brain activity and behavior varied significantly between individuals after ketamine administration. Genetic analysis revealed that different gene expression patterns paired with differences in ketamine response in individuals ­ an effect that was hidden when the results were averaged. Ketamine also caused greater differences in brain activity and behavior between individuals than other drugs, such as psychedelics, suggesting ketamine generates a particularly complex response in people. In the future, extending these findings in healthy individuals to those with depression will be crucial for determining whether differences in response to ketamine align with how effective ketamine treatment is for an individual.

Global connectivity of prefrontal cortex predicts cognitive control and intelligence.

Control of thought and behavior is fundamental to human intelligence. Evidence suggests a frontoparietal brain network implements such cognitive control across diverse contexts. We identify a mechanism--global connectivity--by which components of this network might coordinate control of other networks. A lateral prefrontal cortex (LPFC) region's activity was found to predict performance in a high control demand working memory task and also to exhibit high global connectivity. Critically, global connectivity in this LPFC region, involving connections both within and outside the frontoparietal network, showed a highly selective relationship with individual differences in fluid intelligence. These findings suggest LPFC is a global hub with a brainwide influence that facilitates the ability to implement control processes central to human intelligence.

Static and dynamic functional connectomes represent largely similar information.

Functional connectivity (FC) of blood-oxygen-level-dependent (BOLD) fMRI time series can be estimated using methods that differ in sensitivity to the temporal order of time points (static vs. dynamic) and the number of regions considered in estimating a single edge (bivariate vs. multivariate). Previous research suggests that dynamic FC explains variability in FC fluctuations and behavior beyond static FC. Our aim was to systematically compare methods on both dimensions. We compared five FC methods: Pearson's/full correlation (static, bivariate), lagged correlation (dynamic, bivariate), partial correlation (static, multivariate) and multivariate AR model with and without self-connections (dynamic, multivariate). We compared these methods by (i) assessing similarities between FC matrices, (ii) by comparing node centrality measures, and (iii) by comparing the patterns of brain-behavior associations. Although FC estimates did not differ as a function of sensitivity to temporal order, we observed differences between the multivariate and bivariate FC methods. The dynamic FC estimates were highly correlated with the static FC estimates, especially when comparing group-level FC matrices. Similarly, there were high correlations between the patterns of brain-behavior associations obtained using the dynamic and static FC methods. We conclude that the dynamic FC estimates represent information largely similar to that of the static FC.

Corrigendum: autohrf-an R package for generating data-informed event models for general linear modeling of task-based fMRI data.

[This corrects the article DOI: 10.3389/fnimg.2022.983324.].

Static and dynamic fMRI-derived functional connectomes represent largely similar information.

Functional connectivity (FC) of blood oxygen level-dependent (BOLD) fMRI time series can be estimated using methods that differ in sensitivity to the temporal order of time points (static vs. dynamic) and the number of regions considered in estimating a single edge (bivariate vs. multivariate). Previous research suggests that dynamic FC explains variability in FC fluctuations and behavior beyond static FC. Our aim was to systematically compare methods on both dimensions. We compared five FC methods: Pearson's/full correlation (static, bivariate), lagged correlation (dynamic, bivariate), partial correlation (static, multivariate), and multivariate AR model with and without self-connections (dynamic, multivariate). We compared these methods by (i) assessing similarities between FC matrices, (ii) by comparing node centrality measures, and (iii) by comparing the patterns of brain-behavior associations. Although FC estimates did not differ as a function of sensitivity to temporal order, we observed differences between the multivariate and bivariate FC methods. The dynamic FC estimates were highly correlated with the static FC estimates, especially when comparing group-level FC matrices. Similarly, there were high correlations between the patterns of brain-behavior associations obtained using the dynamic and static FC methods. We conclude that the dynamic FC estimates represent information largely similar to that of the static FC.

The Diversity of Strategies Used in Working Memory for Colors, Orientations, and Positions: A Quantitative Approach to a First-Person Inquiry.

The study of individual experience during the performance of a psychological task using a phenomenological approach is a relatively new area of research. The aim of this paper was to combine first- and third-person approaches to investigate whether the strategies individuals use during a working memory task are associated with specific task conditions, whether the strategies combine to form stable patterns, and whether the use of specific strategies is related to task accuracy. Thirty-one participants took part in an experiment in which they were instructed to remember colors, orientations, or positions of stimuli presented in a change detection task. After every 7th-15th trial, participants took part in an in-depth phenomenological interview in which they described their experiences during the trial that immediately preceded the interview. Qualitative analysis revealed a set of 18 strategies that participants used while performing the task, which we divided into active and passive strategies of encoding, maintenance, and retrieval. Quantitative analysis revealed that while many strategies were used in all task conditions, some strategies and their combinations may be better suited to the specific task demands, while others are more general in nature. The results also suggest a distinction between strategies for encoding object identity and spatial features. Finally, our results did not provide robust evidence for a relationship between specific strategies and task accuracy.

Human brain state dynamics reflect individual neuro-phenotypes.

Neural activity and behavior manifest state and trait dynamics, as well as variation within and between individuals. However, the mapping of state-trait neural variation to behavior is not well understood. To address this gap, we quantify moment-to-moment changes in brain-wide co-activation patterns derived from resting-state functional magnetic resonance imaging. In healthy young adults, we identify reproducible spatio-temporal features of co-activation patterns at the single subject level. We demonstrate that a joint analysis of state-trait neural variations and feature reduction reveal general motifs of individual differences, encompassing state-specific and general neural features that exhibit day-to-day variability. The principal neural variations co-vary with the principal variations of behavioral phenotypes, highlighting cognitive function, emotion regulation, alcohol and substance use. Person-specific probability of occupying a particular co-activation pattern is reproducible and associated with neural and behavioral features. This combined analysis of state-trait variations holds promise for developing reproducible neuroimaging markers of individual life functional outcome.