A distinction between phenomenal and access consciousness has been influential in consciousness studies. Phenomenal consciousness is linked to iconic memory and a fragile short-term memory store with larger capacity than working memory, while access consciousness is linked to limited-capacity working memory. Visual attention was thought to affect only access consciousness, but some evidence suggests earlier attentional effects. An experiment using a change-detection task with delayed cueing and high- and low-priority colored objects found an attentional bias toward high-priority objects at longer cueing delays (600 and 1,200 ms) associated with fragile visual short-term memory, but not at shorter delays (16.
Selective attention produces both costs and benefits in iconic memory and fragile visual short-term memory, which are linked to phenomenal consciousness. In three experiments using a retro-cue paradigm, attentional costs disrupted visual maintenance at longer delays. Reducing the memory array exposure from 250 ms to 100 ms prevented participants from selecting objects based on their priorities, indicating a bottom-up factor. A pattern mask presented before transfer to visual working memory reduced overall performance but preserved the priority effect. These findings suggest that fragile-VSTM and iconic memory play distinct roles in feature-based attentional selection, with implications for phenomenal consciousness before conscious access.
The self in non-human animals is often studied in a limited, dichotomous way that separates low-level bodily and affective aspects from high-level cognitive ones. A proposed framework based on the Pattern Theory of Self (PTS) treats the self as a dynamic, multidimensional construct with graded, non-hierarchical dimensions—ranging from bodily and affective to intersubjective and normative. This approach accommodates variability within and across species, allowing researchers to investigate how the self emerges in different degrees and forms shaped by ecological niches and adaptive demands, without relying on anthropocentric biases.
People often show a double bias when attributing consciousness to non-human systems. Non-human animals receive low attributions of consciousness despite behavioral and neurobiological evidence suggesting subjective experience, while disembodied AI systems like large language models receive elevated attributions of consciousness despite lacking sensory or bodily substrates. This asymmetry indicates that folk judgments are shaped more by observers' cue-weighting heuristics than by the intrinsic properties of the systems. The authors propose that multidimensional, non-hierarchical frameworks, such as Birch's model and the Pattern Theory of Self, can serve as diagnostic tools to study how evidence dimensions are weighted in attributional contexts, replacing a ladder of human-like capacities with a landscape of profiles across taxa and system types.