Cognitive Neuroscience最新文献

Federico et al. present an interesting framework for technological cognition distinguishing mechanical and digital technologies within a distributed brain network. We build on this contribution by emphasizing two key issues for neuropsychology. First, greater weight on semantic processing may not suffice for efficient digital tool use: selection mechanisms are crucial for translating abstract goals into concrete action sequences. Second, digital technologies must be considered in terms of what they offer (functional opportunities) and what they demand (user skills). These distinctions clarify pathways for assessment, rehabilitation, and inclusion, and highlight open questions essential to advancing digital neuropsychology.

Ritchie et al. propose a novel framework for understanding the organization of visual function in the occipitotemporal cortex (OTC). We argue that neuropsychological evidence from individuals with prosopometamorphopsia (PMO), a condition in which faces appear distorted, offers a unique opportunity to test models of OTC. Drawing on findings from a large-scale experiment that used naturalistic stimuli with five individuals with PMO, we show that distortions in two cases appear to be face-specific. These results highlight the value of integrating neuropsychological, computational, and behavioral approaches to constrain and refine models of the organization of visual function.

Studies in our field have often operated under an implicit assumption that the purpose of visual processing is categorization. I argue that our reliance on univariate category-selectivity has diverted attention from behaviorally critical dimensions, such as individuation, which are best captured in multivariate patterns. Category-focused localizers suppress within-category variability, masking signals at the level of individuals, exemplars, and items. By shifting the emphasis from univariate activation to multivariate discriminability, we can better align neural measures with the cognitive demands of everyday vision.

Ritchie et al. (this issue) argue that the complex landscape of selectivity in the human occipitotemporal cortex is better understood in terms of behavioral relevance than in terms of category. At the descriptive level, their suggestion is obviously very powerful because it allows to describe almost any type of selectivity that is found. Yet, it does not seem to suffice to explain the selectivity and its properties. Categories still play a crucial role in clarifying the functional organization of object representations in the brain, including the tuning for dimensions and the relationship to behavioral relevance.

Homo sapiens has evolved a specialized "prosthetic ability", necessary to integrate tools into the cognitive process. The neural toolkit associated with such technological extension is particularly influenced by the fronto-parietal system, the working memory network, and a set of unidentified skills linked to the concept of embodiment. The agenda for investigating these topics in the frame of evolution will require the refinement of proper definitions, and the application of experimental approaches in cognitive archeology. Of course, the fact that our technological ability is the result of natural selection does not mean that it is free from risks and drawbacks.

The model of technological cognition presented by Federico et al. does not specify how information is processed in and between the different hubs. Following Cisek's proposal for an 'ecological' perspective on cognition, I discuss the role of affordances in action specification and action selection. Artifacts afford a multitude of action, but most of them must be learned. This involves learning new causal mappings from actions to effects.

Federico et al. (this issue) present an integrated neurocognitive model of technological cognition encompassing causal-technical reasoning, semantic cognition, visuospatial abilities, motor control, and social learning. We propose extending this framework to include emotional and reward-related systems, particularly limbic circuits and episodic memory processes. These affective systems shape technological engagement, from adoption to problematic use, influencing salience, persistence, and emotional valence. The limbic system and frontostriatal circuits are integral components of technological cognition, working in concert with, rather than merely modulating, the core cognitive processes. Their integration enhances the model's explanatory power and bridges cognitive and affective neuroscience in understanding technological cognition.

While technical reasoning enables us to understand physical interactions, manipulation knowledge provides motor solutions grounded in prior experiences. Neuropsychological and neuroimaging studies suggest that mechanical knowledge is central, but manipulation knowledge may still play a supporting role in familiar contexts. We argue that these two systems coexist within the cognitive architecture, supported by partially distinct neural substrates. Clarifying their interactions is essential for developing a comprehensive model of tool use within the broader framework of technological cognition.