Function and nature of Serial order in Working Memory

Verbal WM defines our ability to temporarily maintain verbal information in an activated and conscious state. This ability not only allows us to maintain the stimuli that have been presented, but importantly, also the order in which the stimuli occur. In the first part of my talk I will demonstrate that this specific aspect of WM, the order processes, are crucial in many cognitive operations such as sentence processing, new vocabulary learning, mental calculation, reading and writing abilities. Using longitudinal, cross-sectional and neuroimaging designs in typical and neurodevelopmental atypical populations, we demonstrated a specific link between serial order WM abilities and different learning abilities. In thesecond part of my talk I will address a fundamental question about the nature of serial order coding in WM. Many current WM models agree on the existence of positional markers for binding items and their serial position in a WM task. However, the models diverge when it comes to defining the nature of serial order coding. These models suggest the possibility of the existence of domain general ordinal positional codes, shared with other domains such as numerical or alphabetical, and based on space and/or time representations. To demonstrate this I will present two recent fMRI studies using MVPA analyses investigating the nature of ordinal representation. The aim of this talk is to give a precise idea of what order WM processing is, what it is used for and how it works

Serial order in working memory: Function and nature of this coding

Verbal WM defines our ability to temporarily maintain verbal information in an activated and conscious state. This ability not only allows us to maintain the stimuli that have been presented, but importantly, also the order in which the stimuli occur. In the first part of my talk I will demonstrate that this specific aspect of WM, the order processes, are crucial in many cognitive operations such as sentence processing, new vocabulary learning, mental calculation, reading and writing abilities. Using longitudinal, cross-sectional and neuroimaging designs in typical and neurodevelopmental atypical populations, we demonstrated a specific link between serial order WM abilities and different learning abilities. In the second part of my talk I will address a fundamental question about the nature of serial order coding in WM. Many current WM models agree on the existence of positional markers for binding items and their serial position in a WM task. However, the models diverge when it comes to defining the nature of serial order coding. These models suggest the possibility of the existence of domain general ordinal positional codes, shared with other domains such as numerical or alphabetical, and based on space and/or time representations. To demonstrate this I will present two recent fMRI studies using MVPA analyses investigating the nature of ordinal representation. The aim of this talk is to give a precise idea of what order WM processing is, what it is used for and how it works

The representation of ordinal information: domain specific or domain general ?

Ordinal processing involves processing of the sequential relations between stimuli of a stimulus set. This crucial ability has been studied extensively and separately in different domains such as working memory (WM) and numerical cognition. Several behavioural and neuroimaging studies suggest the possibility of common ordinal coding mechanisms across different domains. This fMRI study assessed the hypothesis of common ordinal representational mechanisms across the WM, the number and the letter domains. We administered three ordinal judgement tasks (for alphabetical, numerical, and verbal WM judgment) with further manipulation of ordinal distance, and a luminance judgment control task. Our results demonstrated between-task predictions of ordinal distance in fronto-parietal cortices were robust between serial order WM, alphabetical order judgment tasks as well as a luminance judgment control task but not when involving the numerical order judgment tasks. They suggest that common neural substrates characterize processing of ordinal information in WM and alphabetical but not numerical domains. Moreover, additional results suggest that the commonality may reflect attentional control processes involved in judging ordinal distances rather than the intervention of domain-general ordinal codes

The neural representation of ordinal information: domain-specific or domain-general?

Ordinal processing allows for the representation of the sequential relations between stimuli and is a fundamental aspect of different cognitive domains such as verbal working memory (WM), language and numerical cognition. Several studies suggest common ordinal coding mechanisms across these different domains but direct between-domain comparisons of ordinal coding are rare and have led to contradictory evidence. This fMRI study examined the commonality of ordinal representations across the WM, the number and the letter domains by using a multivoxel pattern analysis approach and by focusing on triplet stimuli associated with robust ordinal distance effects. Neural patterns in fronto-parietal cortices distinguished ordinal distance in all domains. Critically, between-task predictions of ordinal distance in fronto-parietal cortices were robust between serial order WM, alphabetical order judgment but not when involving the numerical order judgment tasks. Moreover, frontal ROIs further supported between-task prediction of distance for the luminance judgment control task, the serial order WM and the alphabetical tasks. These results suggest that common neural substrates characterize processing of ordinal information in WM and alphabetical but not numerical domains. This commonality, particularly in frontal cortices, may however reflect attentional control processes involved in judging ordinal distances rather than the intervention of domain-general ordinal codes

Temporal preparation in aging: a dissociation between automatic and controlled processes?

peer reviewedThe ability to predict when a stimulus is more likely to appear – Temporal preparation (TP) - is fundamental for optimal processing. TP can be achieved through four distinct components considered as requiring more or less controlled processes. The impact of aging on these four abilities, and specifically on the more controlled forms of TP, have been poorly investigated. In this study, after validating in young adults (N=120) a protocol assessing the four TP components in a simple detection task, we tested whether TP was preserved in a group of elderly participants. Bayesian analyses provided evidence for a specific alteration of the endogenous orienting system, that is, the ability to benefit from symbolic cues; but preserved abilities for the foreperiod and for more automatic processes such as sequential effects or regular rhythmic sequences. Overall, these results suggest a specific alteration of the more controlled and resources demanding form of TP in elderly participants (endogenous temporal orienting). These results have specific implications such as understanding the impact of aging on temporal preparation but also more global implications as the understanding of the nature of the four components

The contribution of serial order short-term memory and long-term learning to reading acquisition : a longitudinal study

There is increasing evidence for an association between both serial order short-term memory (STM) and the long-term learning (LTL) of serial order information and reading abilities. In this developmental study, we examined the hypothesis that STM for serial order supports online grapheme-to-phoneme conversion processes during the initial stages of reading acquisition, whereas the LTL of serial order serves reading abilities at later stages, when reading starts to rely on more stable, long-term orthographic representations. We followed a sample of 116 French-speaking children from first (Time 1 [T1]) grade of primary school through second (Time 2 [T2]) and third (Time 3 [T3]) grade. Their serial order STM and LTL abilities as well as their reading abilities were assessed. Overall, we observed that early reading abilities were only predicted by serial order STM performance, while more advanced reading abilities were predicted by both serial order STM and LTL performance. These results point toward a predictive role of serial order memory performance in reading acquisition and suggest that serial order STM and LTL support reading at different stages of acquisition. We further discuss our findings in the light of advancing knowledge about the relationship between memory and reading

The role of semantic codes in verbal working memory maintenance: an fMRI investigation

Although the impact of long-term memory (LTM) knowledge on working memory (WM) performance has been well demonstrated, the nature of the interactions between WM and semantic LTM remains poorly understood. While some theoretical models consider that this intervention indicates a temporary and direct activation of LTM during WM maintenance, others consider that LTM only intervenes during recall, in order to reconstruct degraded memory traces. The aim of this study was to examine the extent to which semantic knowledge in LTM is temporarily activated during the maintenance phase in WM, by determining, via fMRI, whether brain markers of semantic knowledge are observable during the maintenance phase in verbal WM. Twenty-seven healthy participants (18-35 years old) participated in this study. The multivariate brain signals of four semantic categories were pre-determined via an implicit semantic activation task (reading aloud of words from four semantic categories). Next, the participants were asked to maintain words in a verbal WM task, these words being the names of the four semantic categories implicitly activated in the preceding task. Via multi-voxel pattern analyses, we were able to distinguish the neural patterns associated with the four semantic categories both in the semantic activation task and during the maintenance stage of the WM task (Bayesian factors BF10>1,078 e+7 and BF10>2.058, respectively, for category decoding against chance level decoding). However, when attempting to predict the neural patterns associated with the semantic categories between the two tasks, prediction rates did not exceed chance level, indicating that the multivariate brain signals associated with the maintenance of semantic category names in the WM task and those associated with semantic categories in the implicit semantic activation task differ. These results indicate that deep semantic representations in LTM are not necessarily activated during maintenance in WM and suggest a more limited intervention of semantic LTM in WM

Neural patterns in linguistic cortices discriminate the content of verbal working memory

Verbal working memory (WM) is characterized by the presence of psycholinguistic effects, whereby items associated with richer linguistic representations are usually better recalled, such as words vs. nonwords (lexicality effect). This effect is accounted for by language-based models, assuming a direct and obligatory involvement of lexical linguistic knowledge at all stages of WM processing or by redintegration models considering that lexical linguistic knowledge only intervenes during post-memory trace reconstructive processes. We contrasted these two accounts in functional neuroimaging experiment by assessing to what extent and at what WM stage word and nonword memoranda can be distinguished based on their multivariate neural patterns in linguistic cortices. fMRI scans were obtained from 28 healthy young adult participants. The participants were invited to encode lists composed of word or nonword items presented at a very fast rate (2 items/s) and to maintain the items over a 6-second delay or not, followed by a probe recognition phase. Multivariate voxel pattern analyses successfully decoded word and nonword stimuli during the encoding phase in all conditions, as well as during the maintenance phase but only during the active maintenance condition. This study supports language-based WM models assuming continuous support of linguistic knowledge during all WM stages