Hegel and Heidegger on Time This Element discusses Heidegger’s early (1924–1931) reading and critique of Hegel, which revolve around the topic of time. The standard view is that Heidegger distances himself from Hegel by arguing that whereas he takes time to be ‘originarily’ Dasein’s ‘temporality,’ Hegel has a ‘vulgar’ conception of time as ‘now-time’ (the succession of formal nows). The Element defends the thesis that while this difference concerning the nature of time is certainly a part of Heidegger’s ‘confrontation’ with Hegel, it is not its kernel. What Heidegger aspired to convey with his Hegel-critique is that they have a divergent conception of man’s understanding of being (ontology). Whereas Heidegger takes ontology to be grounded in temporality, Hegel thinks it is grounded in ‘the concept,’ which has a dimension (‘logos’) manifesting eternity or timelessness. It is argued, contra Kojève, that Heidegger’s reading (but not necessarily his critique) of Hegel is, in an important respect, correct.
Heidegger on Technology’s Danger and Promise in the Age of AI How exactly is technology transforming us and our worlds, and what (if anything) can and should we do about it? Heidegger already felt this philosophical question concerning technology pressing in on him in 1951, and his thought-full and deliberately provocative response is still worth pondering today. What light does his thinking cast not just on the nuclear technology of the atomic age but also on more contemporary technologies such as genome engineering, synthetic biology, and the latest advances in information technology, so-called “generative AIs” like ChatGPT? These are some of the questions this book addresses, situating the latest controversial technologies in the light of Heidegger’s influential understanding of technology as an historical mode of ontological disclosure. In this way, we seek to take the measure of Heidegger’s ontological understanding of technology as a constellation of intelligibility with an important philosophical heritage and a dangerous but still promising future.
On the complexity of metacognitive judgments of memory: evidence from retrospective confidence, feeling of knowing, and older adults Dissociations in types of memory tasks emerge when comparing feeling-of-knowing (FOK) judgments, predictions of upcoming performance, and retrospective confidence. This pattern has been used to construct theories of metacognitive access to memory, particularly in memory-impaired groups. In particular, older adults’ metacognitive sensitivity appears to vary between episodic (impaired) and semantic (intact) memory. However, this could be explained by the limitations of metacognitive measures and/or memory differences. We aimed to test these dissociations of metacognition with aging by comparing metacognitive efficiency in episodic and semantic tasks using two types of judgment: retrospective confidence judgments (RCJs) and FOK judgments. Metacognitive efficiency was estimated in 240 participants aged 19–79 years using a hierarchical Bayesian framework. Results showed that metacognitive efficiency for RCJs declined with age in the semantic task, even though task performance increased with age, while metacognitive efficiency was stable in the episodic task. Surprisingly, metacognitive efficiency was very low (although significantly higher than zero) for both FOK tasks regardless of age compared to similar previous studies. We suggested this might be due to the online testing. These results point to metacognition being multifaceted and varying according to judgment, domains, and populations.
Multimodal imaging to identify brain markers of human prosocial behavior How humans achieve such a high degree of prosocial behavior is a subject of considerable interest. Exploration of the neural foundations of human prosociality has garnered significant attention in recent decades. Nevertheless, the neural mechanisms underlying human prosociality remain to be elucidated. To address this knowledge gap, we analyzed multimodal brain imaging data and data from 15 economic games. The results revealed several significant associations between brain characteristics and prosocial behavior, including stronger interhemispheric connectivity and larger corpus callosum volume. Greater functional segregation and integration, alongside fewer myelin maps combined with a thicker cortex, was linked to prosocial behavior, particularly within the social brain regions. The current study demonstrates that these metrics serve as brain markers of human prosocial behavior and provides novel insights into the structural and functional brain basis of human prosocial behavior.
Adaptive chunking improves effective working memory capacity in a prefrontal cortex and basal ganglia circuit How and why is working memory (WM) capacity limited? Traditional cognitive accounts focus either on limitations on the number or items that can be stored (slots models), or loss of precision with increasing load (resource models). Here, we show that a neural network model of prefrontal cortex and basal ganglia can learn to reuse the same prefrontal populations to store multiple items, leading to resource-like constraints within a slot-like system, and inducing a trade-off between quantity and precision of information. Such ‘chunking’ strategies are adapted as a function of reinforcement learning and WM task demands, mimicking human performance and normative models. Moreover, adaptive performance requires a dynamic range of dopaminergic signals to adjust striatal gating policies, providing a new interpretation of WM difficulties in patient populations such as Parkinson’s disease, ADHD, and schizophrenia. These simulations also suggest a computational rather than anatomical limit to WM capacity.
The mediation role of reading-related endophenotypes in the gene-to-reading pathway Although individual differences in reading-related skills are largely influenced by genetic variation, the molecular basis of the heritability of this phenotype is far from understood. Functional single-nucleotide polymorphisms spanning reading-candidate genes and genome-wide significant top hits were identified. By using a multiple-predictor/multiple-mediator framework, we investigated whether relationships between functional genetic variants (DYX1C1-rs3743205, DYX1C1-rs57809907, KIAA0319-rs9461045, and KIAA0319-Haplotype) and genome-wide significant top hits (rs11208009 on chromosome 1) and reading skills could be explained by reading-related cognitive and sensory endophenotypes in a sample of 328 8-year-old twins. The association between rs3743205 and rs57809907 with reading skills is partially mediated by phonological awareness (PA). Specifically, the rs3743205-C/C genotype and carrying the minor ‘A’ allele of rs57809907 were associated with lower PA scores which in turn was correlated with poorer reading skills. These findings reveal insights into the sequential gene-behavior cascade in reading acquisition and contribute to the growing literature on the neurogenetic machinery of reading development.
A Shift Toward Supercritical Brain Dynamics Predicts Alzheimer’s Disease Progression Alzheimer’s disease (AD) is the most common form of dementia with continuum of disease progression of increasing severity from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) and lastly to AD. The transition from MCI to AD has been linked to brain hypersynchronization, but the underlying mechanisms leading to this are unknown. Here, we hypothesized that excessive excitation in AD disease progression would shift brain dynamics toward supercriticality across an extended regime of critical-like dynamics. In this framework, healthy brain activity during aging preserves operation at near the critical phase transition at balanced excitation–inhibition (E/I). To test this hypothesis, we used source-reconstructed resting-state MEG data from a cross-sectional cohort (N = 343) of individuals with SCD, MCI, and healthy controls (HC) as well as from a longitudinal cohort (N = 45) of MCI patients. We then assessed brain criticality by quantifying long-range temporal correlations (LRTCs) and functional EI (fE/I) of neuronal oscillations. LRTCs were attenuated in SCD in spectrally and anatomically constrained regions while this breakdown was progressively more widespread in MC. In parallel, fE/I was increased in the MCI but not in the SC cohort. Both observations also predicted the disease progression in the longitudinal cohort. Finally, using machine learning trained on functional (LRTCs, fE/I) and structural (MTL volumes) features, we show that LRTCs and f/EI are the most informative features for accurate classification of individuals with SCD while structural changes accurate classify the individuals with MCI. These findings establish that a shift toward supercritical brain dynamics reflects early AD disease progression.
The concept of representation in the brain sciences: The current status and ways forward This article outlines the motivations and main findings of Favela and Machery’s “Investigating the concept of representation in the neural and psychological sciences”, and discusses what to do with the concept of representation in the brain sciences moving forward.
Contextualizing, eliminating, or glossing: What to do with unclear scientific concepts like representation In this article, we respond to Rosa Cao’s, Frances Egan’s, and John Krakauer’s comments, defending our interpretation of our experimental results and the significance of an epistemology of the imprecise.