Environmental influences on brain and cognition are often studied as isolated influences, although their significance depends on multilevel integrated processes. This editorial introduces the Special Issue “Physical, Social and Economic Environmental Effects on Brain and Cognition” and develops an ecological account of neurocognitive adaptation. Contributions addressing socioeconomic deprivation, selective attention, school climate, prenatal maternal anxiety, acute psychosocial stress, aviation expertise, cultural and evolutionary constraints reveal processes operating across multiple timescales. They converge in suggesting neural and cognitive differences should be interpreted in relation to environmental demands, adaptive functions, physiological costs, and opportunities for recovery. Locally functional responses may carry disadvantages elsewhere, while preserved behavioral performance may conceal compensatory mechanisms. Supportive environments can modify developmental trajectories, and early exposures influence probabilities rather than establish immutable outcomes. Integrating allostasis, interactive specialization, developmental calibration, and resilience, this editorial identifies priorities for longitudinal, multimodal, and ecologically informative research. These include measuring demands and resources directly, connecting brain and body processes, testing contextual benefits and costs, and treating schools, workplaces, and socioeconomic conditions as intervention targets. An ecological approach can explain how vulnerability, compensation, specialization, and resilience emerge through transactions among brains, bodies, behavior, and contexts throughout development and across changing environmental conditions.
Clinical neuropsychology was forged in a pre-digital era, and many of its core instruments still bear that imprint. Patients are still commonly assessed with paper-and-pencil tests in quiet rooms, under conditions that only weakly approximate the technology-saturated environments in which cognition is now expressed. Over the past decade, the field has advanced substantially: tele-neuropsychology has broadened access, artificial intelligence has begun to support scoring and documentation, and calls to modernise neuropsychological assessment have intensified. Yet these developments, while important, largely optimise the delivery of existing practice rather than reconsidering what should be measured, why, and how. Here, I argue that three critical gaps remain. First, neuropsychology lacks a framework for assessing technological cognition. Second, candidate neuroimaging measures remain insufficiently integrated into multimodal diagnostic or prognostic modelling. Third, digital data from smartphones and wearables remain underused for capturing cognition in situ during everyday life, while virtual reality remains underexploited as a means of simulating ecologically relevant activities under controlled conditions. Drawing on preliminary evidence that digital technologies may recruit partly distinct neural systems, on the recent hub-and-processors model of technological cognition, and on research into cognitive offloading, attention fragmentation, technology-mediated navigation, as well as on recent meta-analytic evidence on technology use in cognitive ageing, I outline a roadmap for addressing these gaps. I propose that the field now requires a Cognitive Neuroscience of Technology programme, conceived as an interdisciplinary, lifespan-oriented research framework aimed at understanding how technologies recruit, extend, and reshape the human brain, and at translating this knowledge into clinical practice. The task is not to celebrate or condemn modern technologies, but to determine, patient by patient, when they augment cognition, compensate for impairment, or undermine cognitive function, and to redesign assessment, diagnosis, and rehabilitation accordingly.
How does extensively practiced speech memory remain dependent on momentary sensory input, and how does this interaction shape brain activity during development? This perspective integrates exploratory behavioral and event-related potential (ERP) findings from a culturally situated spoken-sequence recognition paradigm with a working memory episodic-buffer account. We reanalyzed data from children and young adults who had memorized Quranic passages despite limited Arabic comprehension. Participants heard incomplete passages with or without static noise and selected the missing final word from phonologically plausible alternatives. Noise reduced recognition accuracy, and children generally responded more slowly. Descriptive ERP patterns revealed larger, more spatially distributed responses in children, spanning early auditory processing, mid-latency positivity, and later negative activity. We propose that recognition requires temporary binding of acoustic input, serial and rhythmic expectations, visual response cues, and consolidated sequence knowledge within an episodic buffer under executive control. Noise may impair perceptual fidelity and matching between transient input and stored representations. Developmental ERP differences may reflect representational coordination rather than neural efficiency. These preliminary findings motivate testable predictions concerning cross-modal congruence, familiarity, comprehension, and independently measured expertise. Culturally embedded learning practices provide informative contexts for examining interactions among working memory, long-term knowledge, and developing neural systems supporting cognition.
Understanding novel metaphors (e.g., Passion is a storm) requires semantic control processes to activate relevant semantic properties (i.e., intense) rather than irrelevant properties (i.e., weather). The degree to which the left inferior frontal gyrus (LIFG), which is traditionally considered a literal language semantic control region, is functionally involved in metaphor processing remains unresolved in neurocognitive theories of semantic processing. Here, high-definition transcranial direct current stimulation (HD-tDCS) was applied to the LIFG to examine its functional role in metaphor comprehension. Participants received either anodal stimulation (n = 20), which increases the excitability of neurons, or sham stimulation (n = 20), and subsequently rated metaphorical (e.g., Passion is a storm), literal (e.g., A gorilla is an ape), and nonsensical (e.g., Depression is a party) sentences on comprehensibility. Participants who received anodal stimulation rated metaphors to be less comprehensible than participants who received sham stimulation. No effects were observed for literal or nonsensical sentences. In addition, word-level semantic characteristics affected metaphor comprehensibility ratings but not literal or nonsensical sentences. These findings demonstrate that the LIFG plays a causal role in the controlled retrieval of semantic properties that is necessary for metaphor comprehension.
While known primarily for respiratory symptoms, COVID-19 has also been linked to cognitive impairments, or "brain fog", which affects attention, memory, and processing speed. Brain-fog related cognitive deficits are well-documented in hospitalized patients but less understood in non-hospitalized individuals. Brain fog may reflect dysfunction in cortical structures supporting higher-level cognition, including hippocampal, frontotemporal, and cingulate areas. These regions contribute to the P3b response, an electrophysiological measure of attention and memory used to assess cognitive deficits across neurological conditions, though sparingly in COVID-19. This study examined P3b mean amplitudes in individuals with and without COVID-19-related brain fog and pre-pandemic controls using a visual n-back paradigm. It was hypothesized that the brain fog group would show reduced amplitudes under higher cognitive loads. Results revealed reduced target-related P3b mean amplitudes in the brain fog group relative to both comparison groups, with no group differences for non-targets. This reduction was most apparent over parietal recording sites but did not significantly vary by scalp region. The brain fog group demonstrated lower accuracy and slower reaction times relative to controls. These differences persisted an average of 22.58 months following symptom resolution, suggesting brain fog may be associated with attentional resource deficits that extend beyond subjective recovery.
