Elsevier

NeuroImage

Volume 60, Issue 1, March 2012, Pages 830-846
NeuroImage

Modelling neural correlates of working memory: A coordinate-based meta-analysis

https://doi.org/10.1016/j.neuroimage.2011.11.050Get rights and content

Abstract

Working memory subsumes the capability to memorize, retrieve and utilize information for a limited period of time which is essential to many human behaviours. Moreover, impairments of working memory functions may be found in nearly all neurological and psychiatric diseases.

To examine what brain regions are commonly and differently active during various working memory tasks, we performed a coordinate-based meta-analysis over 189 fMRI experiments on healthy subjects. The main effect yielded a widespread bilateral fronto-parietal network. Further meta-analyses revealed that several regions were sensitive to specific task components, e.g. Broca's region was selectively active during verbal tasks or ventral and dorsal premotor cortex were preferentially involved in memory for object identity and location, respectively. Moreover, the lateral prefrontal cortex showed a division in a rostral and a caudal part based on differential involvement in task set and load effects. Nevertheless, a consistent but more restricted “core” network emerged from conjunctions across analyses of specific task designs and contrasts.

This “core” network appears to comprise the quintessence of regions, which are necessary during working memory tasks. It may be argued that the core regions form a distributed executive network with potentially generalized functions for focussing on competing representations in the brain.

The present study demonstrates that meta-analyses are a powerful tool to integrate the data of functional imaging studies on a (broader) psychological construct, probing the consistency across various paradigms as well as the differential effects of different experimental implementations.

Introduction

Most psychological and neurobiological models on the organization of human memory share the long-held dichotomy between short-term (STM) and long-term memory (LTM) (Atkinson and Shiffrin, 1968, Brown, 1958, Hebb, 1949, Peterson and Petersen, 1959). STM serves storing a limited but immediately accessible amount of information for a shorter time (Brown, 1958, Peterson and Petersen, 1959), whereas LTM may permanently store vast amounts of information, which, however, require specific recall processes to be accessed. It has been assumed that this distinction reflects differences in the way storage is implemented neuronally. LTM seems to be largely implemented by structural features, e.g., long-term potentiation of synaptic efficacy (Laroche, 1994), structural changes of synaptic boutons, and even the growth of new connections between neurons (Bailey, 1999, Barkai, 2005, Ramirez-Amaya et al., 2001). In contrast, STM seems to be more dependent on functional electro-chemical phenomena, i.e., activation states (Frost et al., 1988, Schiffmann, 1989). It should be noted though, that at the ultra-structural level this distinction appears to become blurred as even temporarily circulating information may lead to short-term ultra-structural adaptation (Doubell and Stewart, 1993). Importantly, both systems (STM and LTM) interact with each other, as STM may be considered the (potential) input into LTM while in turn information from LTM may be retrieved into STM (Atkinson and Shiffrin, 1968).

In this context, it has to be mentioned that, particularly over the last years, the terms “STM” and “working memory (WM)” have been used virtually indistinguishably. This stems in part from the apparent lack of an unequivocally accepted distinction between both concepts (Cowan, 2008). It has been proposed that STM should refer to the pure storage of information, while WM includes (the possibility of) content manipulation and transfer between inputs (e.g., visual or tactile sensory information) and outputs (e.g., manual actions or speech) (Engle et al., 1999). We consider this tentative distinction as a gradual difference in the degree of manipulation (i.e. the number of different cognitive operations on the stored information) required by the different tasks that tap mnemonic functions across a shorter period of time. In this paper, therefore, the apparently broader term working memory (WM) will be used throughout.

The organization of human WM has long been the topic of psychological models (Atkinson and Shiffrin, 1968, Hebb, 1949), with maybe the most influential having been proposed by Baddeley and Hitch (1974). These authors hypothesized the existence of a central executive controlling the priority of incoming information and their dissemination to two subsystems: the phonological loop, responsible for storing verbal material, and the visuospatial sketchpad, responsible for integrating visual input, spatial information (e.g., locations) and object properties (i.e. colour and size) (Baddeley, 2003). Later the concept of an “episodic buffer” was added, forming a limited-capacity system for the ultrashort-term, intermediate storage of incoming sensory information (Baddeley, 2000, Baddeley, 2003). While other models have expanded and modified this view, several key features have remained influential to the present date (Brown et al., 1996, Snowling et al., 1991). In particular, the distinction between spatial and verbal components with specific buffer capacities and the idea of an amodal central executive (Stuss and Knight, 2002) remains dominant. The central executive is not only considered to control the flow of information to the specific subsystems, but is also thought to play a pivotal role in integrating stored material and executive functions needed for comparison, manipulation or, more generally, the further use of the stored material.

One of the motivations underlying the long-standing efforts to understand the organization of the human WM system is the fact that WM impairments have been described in a large variety of neurological and psychiatric diseases. These deficits often have a considerable impact on the quality of life and the socio-economic status of patients. For example, virtually all forms of dementia show WM deficits (Huntley and Howard, 2010, Iachini et al., 2009, Maestu et al., 2011) as do patients with movement disorders like Parkinson's (Beato et al., 2008, Gilbert et al., 2005, Possin et al., 2008) and Huntington's disease (Huber and Paulson, 1987, Lemiere et al., 2004). Interestingly, some WM deficits may be irreversible, (e.g., as part of the debilitating negative symptoms seen in patients with chronic schizophrenia) (Berberian et al., 2009, Driesen et al., 2008, Fuller et al., 2009, Horan et al., 2008, Yi et al., 2009), whereas others are only evident in the acute phase of a disease (e.g. in depression; cf. (Christopher and MacDonald, 2005, Rose and Ebmeier, 2006). Understanding the neural organization of human WM is therefore not only important from a psychological perspective but may also help to unravel the differential pathophysiology of its various impairments.

To date there have been numerous functional neuroimaging studies addressing neural activation patterns associated with WM functions. In spite of this large body of literature, however, there is little agreement on various issues pertaining to the organization of human WM. These include:

  • Are effects related to WM task performance per se and effects of increasing WM load represented in the same areas?

  • How do representations of verbal and non-verbal material differ from each other, i.e., which brain regions may implement phonological and visuospatial buffers?

  • Do different to-be-retained object features (e.g., location vs. identify) or task demands entail differential brain responses?

  • Which regions are consistently involved in WM independently of experimental peculiarities?

One of the main reasons for this discrepancy between the large amount of available data and the relatively little knowledge gained from it may be the heterogeneity of tasks used in WM experiments. In particular, over the years, researchers have employed multiple paradigms, of which four have been used most widely: the n-back task, the Sternberg task as well as delayed matching to sample (DMTS) and delayed simple matching tasks (comparison 12). N-back tasks include a consecutive presentation of stimuli, each requiring a decision whether the current one is the same as the previous (1-back) or the second to last (2-back). While in Sternberg tasks a set of stimuli is presented followed by a single probe stimulus requiring the decision whether the probe was part of the set, in DMTS tasks a single stimulus is presented first and has to be recognized afterwards among a set of multiple stimuli. Finally, delayed simple matching tasks entail the presentation of a single stimulus that has to be compared to a second, subsequently presented one. That is, there are already at least four major experimental approaches to examine the neural correlates of WM. This diversity was further enhanced by less common paradigms as well as the fact that researchers employed a large variety of stimuli (e.g. verbal material, natural objects or abstract symbols) and various additional experimental manipulations (such as varying load, retention interval or distraction). Further considering that the results of functional imaging studies strongly depend on the chosen contrast, given the relative nature of neuroimaging signals, it may not surprise that results are diverse and consensus is sparse.

From this short overview, it may not surprise, that there is a very large but also extremely heterogeneous and at times inconsistent body of work related to the neural correlates of working memory. In the present study, we now sought to integrate the current literature on the neural correlates of human WM as identified by functional neuroimaging using quantitative coordinate-based meta-analysis over almost 200 individual experiments. Such synthesis of the available neuroimaging data should help to reach a consensus among the extensive literature and to trace back inconsistencies to variations in the experimental approaches. Using this approach towards an unbiased summary of the literature, we thus strive to identify consistent findings, answer the main questions outlined earlier and provide an overview on the neural organization of human WM.

Section snippets

Criteria selection of data used for meta-analysis

Neuroimaging experiments using functional magnetic resonance imaging (fMRI) included in this meta-analysis were obtained from the BrainMap database (www.brainmap.org; (Fox and Lancaster, 2002, Laird et al., 2005) and a PubMed literature search (www.pubmed.org, search-strings: “fMRI,” [“working memory” OR “short term memory”], “healthy subjects”). Further studies were identified by review articles and reference tracing of retrieved studies. Only studies that reported results of whole-brain group

Main effect: working memory network

Brain regions showing consistent activation across all 189 WM experiments were observed symmetrically across both hemispheres in frontal areas BA44/45, the anterior insula, posterior superior frontal gyrus (dorsal premotor cortex — dPMC) and inferior frontal gyrus (ventral premotor cortex — vPMC; extending into area 44). Bilateral activation was moreover found in the medial (pre-) supplementary motor area (pre-)SMA), as well as the intraparietal sulcus (IPS areas hIP1-3, but mainly hIP3), the

Summary of findings

This performed meta-analyses of neuroimaging studies on WM demonstrated consistent activation of a widespread fronto-parietal network and the existence of a “core” network emerging from a conjunction across analyses of different WM tasks, designs and contrasts. Furthermore, several noteworthy differences were observed: Whereas task-set effects were more prominent in the left hemisphere including rostral LPFC and SPL/IPS as well as the anterior insula, load effects were more consistently seen in

Conclusions

In the present study, we used quantitative coordinate-based meta-analyses to integrate the current neuroimaging literature on human working memory as a (broader) psychological construct. This synthesis revealed i) a highly consistent core network, which, however, may not be limited to WM but span several higher cognitive functions. ii) a distinction of at least two WM-related regions within the DLPFC, with the rostral one showing a stronger predilection for task-set effects, the caudal one for

Acknowledgments

This work was partly funded by the Human Brain Project (R01-MH074457-01A1), the Helmholtz Alliance on Systems Biology (Human Brain Model), the DFG (IRTG 1328) and the medical faculty of the RWTH Aachen (Rotation Program).

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