Exploring Information Flow from Posteromedial Cortex during Visuospatial Working Memory: A Magnetoencephalography Study.

The posteromedial cortex (PMC) is a major hub of the brain's default mode network, and is implicated in a broad range of internally driven cognitions, including visuospatial working memory. However, its precise contribution to these cognitive processes remains unclear. Using MEG, we measured PMC activity in healthy human participants (young adults of both sexes) while they performed a visuospatial working memory task. Multivariate pattern classification analyses revealed stimulus-related information during encoding and retrieval in a set of a priori defined cortical ROIs, including prefrontal, occipital, and ventrotemporal cortices, in addition to PMC. We measured the extent to which this stimulus information was exchanged between areas in an information flow analysis, measuring Granger-causal relationships between areas over time. Consistent with the visual nature of the task, information from occipital cortex shaped other regions across most epochs. However, the PMC shaped object representations in occipital and prefrontal cortices during visuospatial working memory, influencing occipital cortex during retrieval and PFC across all task epochs. Our findings are consistent with a proposed role for the PMC in the representation of internal content, including remembered information, and in the comparison of external stimuli with remembered material.SIGNIFICANCE STATEMENT The human brain operates as a collection of highly interconnected regions. Mapping the function of this interconnectivity, as well as the specializations within different regions, is central to understanding the neural processes underlying cognition. The posteromedial cortex (PMC) is a highly connected cortical region, implicated in visuospatial working memory, although its precise contribution remains unclear. We measured the activity of PMC during a visuospatial working memory task, testing how different regions represented the stimuli, and whether these representations were driven by other cortical regions. We found that PMC influenced stimulus information in other regions across all task phases, suggesting that PMC plays a key role in shaping stimulus representations during visuospatial working memory.

A humanness dimension to visual object coding in the brain.

Neuroimaging studies investigating human object recognition have primarily focused on a relatively small number of object categories, in particular, faces, bodies, scenes, and vehicles. More recent studies have taken a broader focus, investigating hypothesized dichotomies, for example, animate versus inanimate, and continuous feature dimensions, such as biologically similarity. These studies typically have used stimuli that are identified as animate or inanimate, neglecting objects that may not fit into this dichotomy. We generated a novel stimulus set including standard objects and objects that blur the animate-inanimate dichotomy, for example, robots and toy animals. We used MEG time-series decoding to study the brain's emerging representation of these objects. Our analysis examined contemporary models of object coding such as dichotomous animacy, as well as several new higher order models that take into account an object's capacity for agency (i.e. its ability to move voluntarily) and capacity to experience the world. We show that early (0-200 â€‹ms) responses are predicted by the stimulus shape, assessed using a retinotopic model and shape similarity computed from human judgments. Thereafter, higher order models of agency/experience provided a better explanation of the brain's representation of the stimuli. Strikingly, a model of human similarity provided the best account for the brain's representation after an initial perceptual processing phase. Our findings provide evidence for a new dimension of object coding in the human brain - one that has a "human-centric" focus.

Screening for alcohol and substance use for older people in geriatric hospital and community health settings.

BACKGROUND: We aimed to determine the rates of alcohol and substance use in geriatric hospital and community health settings, and to evaluate the performance of screening instruments. METHOD: A two-phase cross-sectional study was undertaken in geriatric and aged care psychiatry wards and associated community services of a teaching hospital. Participants were screened with the Brief Alcohol Use Disorders Identification Test (AUDIT-C) and the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) for other substances; Geriatric Depression Scale-15 for mood; the Connor-Davidson Resilience Scale; and the Subjective Quality of Life scale. Medical conditions were established. Screen positives for risky substance use continued with the full AUDIT, full ASSIST, CAGE, Addenbrooke's Cognitive Examination-Revised, and the Functional Activities Questionnaire. Medical records were reviewed after three months to ascertain recognition and management of substance use. RESULTS: Of 210 participants aged 60+ (mean age 81.9, 63.3% female) without dementia or delirium and Mini Mental State Examination score ≥24, 41 (19.5%) were screen positive - 36 (17.1%) for alcohol, seven for non-medical benzodiazepine use (3.3%) (four alcohol and benzodiazepine) and two for non-medical opioid use (0.95%). Screen positives differed from screen negatives on few demographic or health measures. On the ASSIST, 26 (12.4%) were rated as medium/high risk. The AUDIT-C with cut-point of ≥5 was the optimal measure for detecting risky alcohol use. CONCLUSIONS: Many patients in geriatric health services have risky alcohol or substance use, but few clinical features distinguish them from other patients. Routine screening of alcohol and substance use is recommended.

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis.

BACKGROUND: Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome. METHODS: We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models. RESULTS: We included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region. INTERPRETATION: Neurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission.

Reaction times predict dynamic brain representations measured with MEG for only some object categorisation tasks.

Behavioural categorisation reaction times (RTs) provide a useful way to link behaviour to brain representations measured with neuroimaging. In this framework, objects are assumed to be represented in a multidimensional activation space, with the distances between object representations indicating their degree of neural similarity. Faster RTs have been reported to correlate with greater distances from a classification decision boundary for animacy. Objects inherently belong to more than one category, yet it is not known whether the RT-distance relationship, and its evolution over the time-course of the neural response, is similar across different categories. Here we used magnetoencephalography (MEG) to address this question. Our stimuli included typically animate and inanimate objects, as well as more ambiguous examples (i.e., robots and toys). We conducted four semantic categorisation tasks on the same stimulus set assessing animacy, living, moving, and human-similarity concepts, and linked the categorisation RTs to MEG time-series decoding data. Our results show a sustained RT-distance relationship throughout the time course of object processing for not only animacy, but also categorisation according to human-similarity. Interestingly, this sustained RT-distance relationship was not observed for the living and moving category organisations, despite comparable classification accuracy of the MEG data across all four category organisations. Our findings show that behavioural RTs predict representational distance for an organisational principle other than animacy, however further research is needed to determine why this relationship is observed only for some category organisations and not others.

Decoding the time-course of object recognition in the human brain: From visual features to categorical decisions.

Visual object recognition is a complex, dynamic process. Multivariate pattern analysis methods, such as decoding, have begun to reveal how the brain processes complex visual information. Recently, temporal decoding methods for EEG and MEG have offered the potential to evaluate the temporal dynamics of object recognition. Here we review the contribution of M/EEG time-series decoding methods to understanding visual object recognition in the human brain. Consistent with the current understanding of the visual processing hierarchy, low-level visual features dominate decodable object representations early in the time-course, with more abstract representations related to object category emerging later. A key finding is that the time-course of object processing is highly dynamic and rapidly evolving, with limited temporal generalisation of decodable information. Several studies have examined the emergence of object category structure, and we consider to what degree category decoding can be explained by sensitivity to low-level visual features. Finally, we evaluate recent work attempting to link human behaviour to the neural time-course of object processing.

Body distortions in Anorexia Nervosa: Evidence for changed processing of multisensory bodily signals.

Body size and shape distortion is a core feature of Anorexia Nervosa (AN) - patients experience their body as fat while objectively being very thin. The cause of this distortion is unclear and disturbances in body perception could be involved. Body perception comprises estimating shape and location of one's body and requires integrating multisensory signals. We investigated if and how body location perception is changed and tested 23 AN patients and 23 healthy controls (HC) in a Rubber Hand Illusion (RHI) reaching paradigm. We presented two types of multisensory conflicts (visual-proprioceptive hand location; visual-tactile touch synchrony) and tested if the impact of visual-proprioceptive and visual-tactile signals on hand location perception differs between AN and HC groups. We found significant group differences in shifts of reaching trajectories, indicating that the influence of proprioceptive signals on hand location estimates is reduced in AN. Hand location estimates were relatively more biased towards external visual information, and shorter illness durations predicted a larger visual bias. Although touch synchrony also significantly influenced hand location estimates, this effect did not differ between groups. Our findings provide compelling evidence that multisensory body location perception - specifically the processing of visual-proprioceptive signals - is changed in AN.