Network architectures supporting learnability

Philosophical Transactions of the Royal Society B Biological Sciences, Год журнала: 2020, Номер 375(1796), С. 20190323 - 20190323

Опубликована: Фев. 24, 2020

Human learners acquire complex interconnected networks of relational knowledge. The capacity for such learning naturally depends on two factors: the architecture (or informational structure) knowledge network itself and computational unit—the brain—that encodes processes information. That is, is reliant integrated architectures at levels: epistemic computational, or conceptual neural. Motivated by a wish to understand conventional human knowledge, here, we discuss emerging work assessing constraints learnability theories from statistical physics that instantiate principles thermodynamics information theory offer an explanatory model constraints. We then highlight similarities between those networks, one level, physical development patterns in neural systems, another both leading hierarchically modular networks. To support our discussion these similarities, employ operational distinction modeller (e.g. brain), single human’s knowledge) modelled present experiences). turn philosophical whether how can extend observations claim regarding explanation mechanism acquisition. What relation hierarchical levels, best facilitate learning? Are optimally learnable topological reflection comparably developed networks? Finally, contribute unified approach hierarchies levels biological proposing several epistemological norms analysing brain social epistemes, developing pedagogical conducive curious thought. This article part theme issue ‘Unifying essential concepts networks: insights foundations’.

Язык: Английский

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Disconnection from prediction: A systematic review on the role of right temporoparietal junction in aberrant predictive processing

Neuroscience & Biobehavioral Reviews, Год журнала: 2022, Номер 138, С. 104713 - 104713

Опубликована: Май 28, 2022

Язык: Английский

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A low-dimensional cognitive-network space in Alzheimer’s disease and frontotemporal dementia

Alzheimer s Research & Therapy, Год журнала: 2022, Номер 14(1)

Опубликована: Дек. 29, 2022

Alzheimer's disease (AD) and frontotemporal dementia (FTD) show network dysfunctions linked with cognitive deficits. Within this framework, abnormalities between AD FTD both convergent divergent patterns. However, these functional patterns are far from being established their relevance to processes remains be elucidated.We investigated the relationship cognition connectivity of major networks in diseases. Twenty-three bvFTD (age: 71±10), 22 72±6), 20 controls 72±6) underwent evaluation resting-state MRI. Principal component analysis was used describe variance across participants. Brain estimated connectome analysis. Connectivity matrices were created assessing correlations parcels within each network. The following considered: default mode (DMN), dorsal attention (DAN), ventral (VAN), frontoparietal (FPN) networks. assessed using a bootstrapping correlation interaction analyses.Three principal components explained more than 80% variance: first (cogPC1) loaded on memory, second (cogPC2) emotion language, third (cogPC3) visuo-spatial attentional domains. Compared HC, showed impairment all cogPCs (p<0.002), scored worse cogPC2 (p=0.031). At level, DMN significant association whole group cogPC1 VAN cogPC2. By contrast, DAN FPN pattern diagnosis for We confirmed results by means multivariate (canonical correlation).A low-dimensional representation can account large scores continuum normal pathological aging. Moreover, bvFTD. observed primarily involved diseases (i.e., VAN), while FC-cognitive mainly attention/executive language/emotion component, suggesting co-existence compensatory detrimental mechanisms underlying components.

Язык: Английский

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Sleep-like cortical dynamics during wakefulness and their network effects following brain injury

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Авг. 22, 2024

By connecting old and recent notions, different spatial scales, research domains, we introduce a novel framework on the consequences of brain injury focusing key role slow waves. We argue that long-standing finding EEG waves after reflects intrusion sleep-like cortical dynamics during wakefulness; illustrate how these are generated they can lead to functional network disruption behavioral impairment. Finally, outline scenario whereby post-injury be modulated reawaken parts have fallen asleep optimize rehabilitation strategies promote recovery. In this Perspective, authors propose result in slowing wakefulness. The generation their effects networks behavior discussed, as well future directions for neuromodulation.

Язык: Английский

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Can brain network connectivity facilitate the clinical development of disease-modifying anti-Alzheimer drugs?

Brain Communications, Год журнала: 2024, Номер 7(1)

Опубликована: Дек. 18, 2024

Abstract The preclinical phase of Alzheimer’s disease represents a crucial time window for therapeutic intervention but requires the identification clinically relevant biomarkers that are sensitive to effects disease-modifying drugs. Amyloid peptide and tau proteins, main histological hallmarks disease, have been widely used as anti-amyloid anti-tau However, these do not fully capture multiple biological pathways brain. Indeed, robust amyloid-target engagement by monoclonal antibodies has recently translated into modest cognitive clinical benefits in patients, albeit with potentially life-threatening side effects. Moreover, targeting pathway yet result any positive outcomes. Findings from computational neuroscience demonstrated brain regions work isolation interconnected within complex network structures. Brain connectivity studies suggest misfolded proteins can spread through connections, leading hypothesis is pathology disconnectivity. Based on assumptions, here we discuss how incorporating outcomes could better global functionality and, conjunction traditional biomarkers, facilitate development new anti-Alzheimer’s

Язык: Английский

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