In debates in philosophy and cognitive science concerning short-term memory mechanisms and perceptual experience, most discussion has focused on the working memory and the various forms of sensory memory such as iconic memory. In this paper, I present a summary of some evidence for a proposed further form of memory termed conceptual short-term memory. I go on to outline some of the ways in which this additional distinctive sort of (...) class='Hi'>short-term memory might be of relevance to ongoing philosophical debates, specifically in relation to questions about high-level perceptual phenomenology, the relationship between consciousness and reportability, and the boundary between cognition and perception. I conclude that conceptual short-term memory offers a promising new direction of research and philosophical investigation. (shrink)

Future work is needed to establish that pure short-term memory is a coherent individual difference attribute that is separable from traditional compound short-term memory measures. Psychometric support for latent pure short-term memory capacity will provide an important starting point for future fine-grained analyses of the intrinsic factors that influence individual differences in math skills.

Previous studies of verbal short-term memory indicate that STM for serial order may be linked to language development and developmental language disorder. To clarify whether a domain-general mechanism is impaired in DLD, we studied the relations between age, non-verbal serial STM, and language competence. We hypothesized that non-verbal serial STM differences between groups of children with DLD and typically developing children are linked to their language acquisition differences. Fifty-one children with DLD and sixty-six TD children participated as (...) part of the HelSLI project in this cross-sectional study. The children were 4–6-year-old monolingual native Finnish speakers. They completed several tests of language and cognitive functioning, as well as new game-like tests of visual and auditory non-verbal serial STM. We used regression analyses to examine how serial STM moderates the effect of age on language. A non-verbal composite measure of serial visual and auditory STM moderated cross-sectional development of receptive language in the children with DLD. This moderation was not observed in the TD children. However, we found more rapid cross-sectional development of non-verbal serial STM in the TD children than in the children with DLD. The results suggest that children with DLD may be more likely to have compromised general serial STM processing and that superior non-verbal serial STM may be associated with better language acquisition in children with DLD. (shrink)

Music can express people’s thoughts and emotions. Music therapy is to stimulate and hypnotize the human brain by using various forms of music activities, such as listening, singing, playing and rhythm. With the empowerment of artificial intelligence, music therapy technology has made innovative development in the whole process of “diagnosis, treatment and evaluation.” It is necessary to make use of the advantages of artificial intelligence technology to innovate music therapy methods, ensure the accuracy of treatment schemes, and provide more paths (...) for the development of the medical field. This paper proposes an long short-term memory -based generation and classification algorithm for multi-voice music data. A Multi-Voice Music Generation system called MVMG based on the algorithm is developed. MVMG contains two main steps. At first, the music data are modeled to the MDPI and text sequence data by using an autoencoder model, including music features extraction and music clip representation. And then an LSTM-based music generation and classification model is developed for generating and analyzing music in specific treatment scenario. MVMG is evaluated based on the datasets collected by us: the single-melody MIDI files and the Chinese classical music dataset. The experiment shows that the highest accuracy of the autoencoder-based feature extractor can achieve 95.3%. And the average F1-score of LSTM is 95.68%, which is much higher than the DNN-based classification model. (shrink)

ABSTRACTWhile some research has now started to suggest that there are long-term memory deficits in alexithymia, short-term memory in alexithymia remained largely unexplored. This study...

This paper provides an interpretation of Hans-Jörg Rheinberger’s notions of epistemic things and historical epistemology . I argue that Rheinberger’s approach articulates a unique contribution to current debates about integrated HPS, and I propose some modifications and extensions of this contribution. Drawing on examples from memory research, I show that Rheinberger is right to highlight a particular feature of many objects of empirical research (“epistemic things”)—especially in the contexts of exploratory experimentation—namely our lack of knowledge about them. I argue (...) that this analysis needs to be supplemented with an account of what scientists do know, and in particular, how they are able to attribute rudimentary empirical contours to objects of research. These contours are closely connected to paradigmatic research designs, which in turn are tied to basic methodological rules for the exploration of the purported phenomena. I suggest that we engage with such rules in order to develop our own normative (epistemological) categories, and I tie this proposal to the idea of a methodological naturalism in philosophy of science. (shrink)

We provide additional support for Cowan's claim that short term memory (STM) involves a range of 3–5 tokens, on the basis of language correlational analyses. If language is at least partly learned, linguistic dependency structure should reflect properties of the cognitive components mediating learning; one such component is STM. In this view, the range over which statistical regularity extends in ordinary text would be suggestive of STM span. Our analyses of eight languages are consistent with STM span (...) being about four chunks. (shrink)

Performance on working memory (WM) tasks may partially be supported by long-term memory (LTM) processing. Hence, brain activation recently being implicated in WM may actually have been driven by (incidental) LTM formation. We examined which brain regions actually support successful WM processing, rather than being confounded by LTM processes, during the maintenance and probe phase of a WM task. We administered a four-pair (faces and houses) associative delayed-match-to-sample (WM) task using event-related fMRI and a subsequent associative recognition (...) LTM task, using the same stimuli. This enabled us to analyze subsequent memory effects for both the WM and the LTM test by contrasting correctly recognized pairs with incorrect pairs for either task. Critically, with respect to the subsequent WM effect, we computed this analysis exclusively for trials that were forgotten in the subsequent LTM recognition task. Hence, brain activity associated with successful WM processing was less likely to be confounded by incidental LTM formation. The subsequent LTM effect, in contrast, was analyzed exclusively for pairs that previously had been correctly recognized in the WM task, disclosing brain regions involved in successful LTM formation after successful WM processing. Results for the subsequent WM effect showed no significantly activated brain areas for WM maintenance, possibly due to an insensitivity of fMRI to mechanisms underlying active WM maintenance. In contrast, a correct decision at WM probe was linked to activation in the “retrieval success network” (anterior and posterior midline brain structures). The subsequent LTM analyses revealed greater activation in left dorsolateral prefrontal cortex and posterior parietal cortex in the early phase of the maintenance stage. No supra-threshold activation was found during the WM probe. Together, we obtained clearer insights in which brain regions support successful WM and LTM without the potential confound of the respective memory system. (shrink)

Cowan argues that the true short-term memory (STM) capacity limit is about 4 items. Functional neuroimaging data converge with this conclusion, indicating distinct neural activity patterns depending on whether or not memory task-demands exceed this limit. STM for verbal information within that capacity invokes focal prefrontal cortical activation that increases with memory load. STM for verbal information exceeding that capacity invokes widespread prefrontal activation in regions associated with executive and attentional processes that may mediate chunking (...) processes to accommodate STM capacity limits. (shrink)