Short-term memory and long-term memory are still different.

A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term memory. If true, this would overturn a central tenet of cognitive psychology-the idea that there are functionally and neurobiologically distinct short- and long-term stores. Here I present an updated case for a separation between short- and long-term stores, focusing on the computational demands placed on any STM system. STM must support memory for previously unencountered information, the storage of multiple tokens of the same type, and variable binding. None of these can be achieved simply by activating long-term memory. For example, even a simple sequence of digits such as "1, 3, 1" where there are 2 tokens of the digit "1" cannot be stored in the correct order simply by activating the representations of the digits "1" and "3" in LTM. I also review recent neuroimaging data that has been presented as evidence that STM is activated LTM and show that these data are exactly what one would expect to see based on a conventional 2-store view. (PsycINFO Database Recor

Reading positional codes with fMRI: Problems and solutions.

Neural mechanisms which bind items into sequences have been investigated in a large body of research in animal neurophysiology and human neuroimaging. However, a major problem in interpreting this data arises from a fact that several unrelated processes, such as memory load, sensory adaptation, and reward expectation, also change in a consistent manner as the sequence unfolds. In this paper we use computational simulations and data from two fMRI experiments to show that a host of unrelated neural processes can masquerade as sequence representations. We show that dissociating such unrelated processes from a dedicated sequence representation is an especially difficult problem for fMRI data, which is almost exclusively the modality used in human experiments. We suggest that such fMRI results must be treated with caution and in many cases the assumed neural representation might actually reflect unrelated processes.This study was funded via the UK Medical Research Council intramural grant MCA060-5PR30

Sequence learning recodes cortical representations instead of strengthening initial ones.

We contrast two computational models of sequence learning. The associative learner posits that learning proceeds by strengthening existing association weights. Alternatively, recoding posits that learning creates new and more efficient representations of the learned sequences. Importantly, both models propose that humans act as optimal learners but capture different statistics of the stimuli in their internal model. Furthermore, these models make dissociable predictions as to how learning changes the neural representation of sequences. We tested these predictions by using fMRI to extract neural activity patterns from the dorsal visual processing stream during a sequence recall task. We observed that only the recoding account can explain the similarity of neural activity patterns, suggesting that participants recode the learned sequences using chunks. We show that associative learning can theoretically store only very limited number of overlapping sequences, such as common in ecological working memory tasks, and hence an efficient learner should recode initial sequence representations

Task-Dependent Masked Priming Effects in Visual Word Recognition

A method used widely to study the first 250 ms of visual word recognition is masked priming: These studies have yielded a rich set of data concerning the processes involved in recognizing letters and words. In these studies, there is an implicit assumption that the early processes in word recognition tapped by masked priming are automatic, and masked priming effects should therefore be invariant across tasks. Contrary to this assumption, masked priming effects are modulated by the task goal: For example, only word targets show priming in the lexical decision task, but both words and non-words do in the same-different task; semantic priming effects are generally weak in the lexical decision task but are robust in the semantic categorization task. We explain how such task dependence arises within the Bayesian Reader account of masked priming (Norris and Kinoshita, 2008), and how the task dissociations can be used to understand the early processes in lexical access

Visual recency bias is explained by a mixture model of internal representations.

Human bias towards more recent events is a common and well-studied phenomenon. Recent studies in visual perception have shown that this recency bias persists even when past events contain no information about the future. Reasons for this suboptimal behavior are not well understood and the internal model that leads people to exhibit recency bias is unknown. Here we use a well-known orientation estimation task to frame the human recency bias in terms of incremental Bayesian inference. We show that the only Bayesian model capable of explaining the recency bias relies on a weighted mixture of past states. Furthermore, we suggest that this mixture model is a consequence of participants' failure to infer a model for data in visual short-term memory, and reflects the nature of the internal representations used in the task

A shared representation of order between encoding and recognition in visual short-term memory.

Many complex tasks require people to bind individual events into a sequence that can be held in short term memory (STM). For this purpose information about the order of the individual events in the sequence needs to be maintained in an active and accessible form in STM over a period of few seconds. Here we investigated how the temporal order information is shared between the presentation and response phases of an STM task. We trained a classification algorithm on the fMRI activity patterns from the presentation phase of the STM task to predict the order of the items during the subsequent recognition phase. While voxels in a number of brain regions represented positional information during either presentation and recognition phases, only voxels in the lateral prefrontal cortex (PFC) and the anterior temporal lobe (ATL) represented position consistently across task phases. A shared positional code in the ATL might reflect verbal recoding of visual sequences to facilitate the maintenance of order information over several seconds

Chunking and redintegration in verbal short-term memory.

Memory for verbal material improves when words form familiar chunks. But how does the improvement due to chunking come about? Two possible explanations are that the input might be actively recoded into chunks, each of which takes up less memory capacity than items not forming part of a chunk (a form of data compression), or that chunking is based on redintegration. If chunking is achieved by redintegration, representations of chunks exist only in long-term memory (LTM) and help to reconstructing degraded traces in short-term memory (STM). In 6 experiments using 2-alternative forced choice recognition and immediate serial recall we find that when chunks are small (2 words) they display a pattern suggestive of redintegration, whereas larger chunks (3 words), show a pattern consistent with data compression. This concurs with previous data showing that there is a cost involved in recoding material into chunks in STM. With smaller chunks this cost seems to outweigh the benefits of recoding words into chunks. (PsycInfo Database Record (c) 2020 APA, all rights reserved)

Orthographic and phonological priming effects in the same-different task.

Masked priming tasks have been used widely to study early orthographic processes-the coding of letter position and letter identity. Recently, using masked priming in the same-different task Lupker, Nakayama, and Perea (2015a) reported finding a phonological priming effect with primes presented in Japanese Katakana, and English target words presented in the Roman alphabet, and based on this finding, suggested that previously reported effects in the same-different task in the literature could be based on phonology rather than orthography. In this article, the authors explain why the design of Lupker et al.'s experiment does not address this question; they then report 2 new experiments that do. The results indicate that the priming produced by orthographically similar primes in the same-different task for letter strings presented in the Roman alphabet is almost exclusively orthographic in origin, and phonology makes little contribution. The authors offer an explanation for why phonological priming was observed when the prime and target are presented in different scripts but not when they are presented in the same script. (PsycINFO Database Record (c) 2018 APA, all rights reserved)

Learning nonwords: the Hebb repetition effect as a model of word learning.

Page and Norris [(2008). Is there a common mechanism underlying word-form learning and the Hebb repetition effect? Experimental data and a modelling framework. In A. Thorn & M. P. A. Page (Eds.), Interactions between short-term and long-term memory in the verbal domain; (2009). A model linking immediate serial recall, the Hebb repetition effect and the learning of phonological word forms. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1536), 3737-3753. doi:10.1098/rstb.2009.0173] have suggested that the Hebb [(1961). Distinctive features of learning in the higher animal. In J. F. Delafresnaye (Ed.), Brain mechanisms and learning (pp. 37-46). Oxford: Blackwell] repetition paradigm can be considered as a laboratory analogue of word learning. In Hebb learning experiments, the lists of items to be learned are presented as discrete sequences. In contrast, novel words are, by definition, always heard as a single coarticulated whole. Might this undermine the claim that Hebb learning can shed light on word learning? Here we report an experiment comparing learning sequences of isolated syllables with learning the same sequences spoken as a single coarticulated nonword. The pattern of learning was similar in the two cases, suggesting that the Hebb repetition paradigm can indeed provide valuable insights into the way novel word forms are learned