Digits backward (DB) is a widely used neuropsychological measure that is believed to be a simple and effective index of the capacity of the verbal working memory. However, its neural correlates remain elusive. The aim of this study is to investigate the neural correlates of DB in 299 healthy young adults by combining voxel-based morphometry (VBM) and resting-state functional connectivity (rsFC) analyses. The VBM analysis showed positive correlations between the DB scores and the gray matter volumes in the right anterior superior temporal gyrus (STG), the right posterior STG, the left inferior frontal gyrus and the left Rolandic operculum, which are four critical areas in the auditory phonological loop of the verbal working memory. Voxel-based correlation analysis was then performed between the positive rsFCs of these four clusters and the DB scores. We found that the DB scores were positively correlated with the rsFCs within the salience network (SN), that is, between the right anterior STG, the dorsal anterior cingulate cortex and the right fronto-insular cortex. We also found that the DB scores were negatively correlated with the rsFC within an anti-correlation network of the SN, between the right posterior STG and the left posterior insula. Our findings suggest that DB performance is related to the structural and functional organizations of the brain areas that are involved in the auditory phonological loop and the SN.

Introduction

Working memory (WM) refers to a limited system that provides for the temporary storage and manipulation of the information necessary for complex cognitive tasks and that provides an interface between perception, long-term memory and action [1], [2]. The definition of WM has evolved from the concept of short-term memory but is defined in three different ways: as short-term memory applied to cognitive tasks; as a multi-component system that holds and manipulates the information in the short-term memory; and as the use of attention to manage the short-term memory [3]. A widely accepted model of WM has proposed that it consists of four subsystems, including the central executive system, the phonological loop, the visuospatial sketchpad, and the episodic buffer [1], [2], [4]–[6]. The phonological loop is specialized for processing verbal materials and is assumed to be a crucial component of the WM system for language acquisition [7]. Moreover, the phonological loop includes two subsystems: a phonological store, which has a limited information capacity and temporal trace (information can be held for a few seconds before it fades); and a subvocal rehearsal system, which continually repeats information to revive the memory trace in WM [2], [6]. The visuospatial sketchpad is a parallel to the phonological loop but exists and serves for the processing of visual and spatial information. The central executive system is an attentional control system that is responsible for strategy selection and for the regulation and coordination of the various processes involved in the phonological loop and the visuospatial sketchpad [2], [6]. The episodic buffer is assumed to be a limited-capacity system that depends heavily on executive processing but that differs from the central executive system in being principally concerned with the storage of information rather than with attentional control. The episodic buffer is capable of binding information from different modalities into a single multi-faceted code [7].

Most of our knowledge of the neural correlates of WM is derived from lesion studies and functional imaging studies, which have revealed that the phonological store depends largely upon the left inferior parietal cortex [8], [9]; the rehearsal processes are based on the left inferior frontal gyrus (IFG) (typically described as Broca's area), the premotor area and the supplementary motor area [10]–[14]; and the central executive system relies heavily on the frontal lobe, particularly the dorsolateral prefrontal cortex (DLPFC) and the dorsal anterior cingulate cortex (ACC) [15]. Although functional imaging can be used to identify the brain regions engaged in WM, it cannot be used to identify the neural correlates of WM capacity because functional imaging measures active processing, whereas capacity is a constraint on processing and not a process itself [16].

WM capacity is typically assessed using behavioral measures such as the digit-span test, in which participants are asked to perform the immediate recall of digit sequences of increasing length. Digits forward (DF) has been characterized as a simple span test and is thought to measure the storage and maintenance components of the WM by deemphasizing the manipulation of the material. However, Digits backward (DB) requires a transformation to reorder the input verbal digits into a reversed sequence and is believed to involve the phonological loop (phonological store and rehearsal process) and the central executive system in the putative WM model. DB is thought to be a sensitive measure of WM and has been widely used in neuropsychological research and clinical evaluations [17]–[19]. However, the neural correlates of DB capacity have not been well established.

Several studies have been performed to investigate the relationship between the gray matter volume (GMV) and the performance of the digit-span test in different populations using voxel-based morphometry (VBM) analysis. In 109 healthy elderly people, the performance of the digit-span test was positively correlated with the gray matter ratio, i.e., the GMV divided by the intracranial volume [20]. In a study of 34 normal and 40 dyslexic adults, researchers identified a region in the left posterior superior temporal sulcus where the gray matter density was positively correlated with the performance of DF and DB [16]. A study of 58 patients with neurodegenerative diseases found that the DB scores were correlated with the GMVs of the DLPFC and the inferior parietal lobule [21]. However, there is a lack of studies with large sample sizes that investigate the structural correlates of DB capacity in healthy young adults. Furthermore, none of the previous studies have substantiated the question using rsFC analysis, which investigates the correlations of the time series between a region of interest (ROI) and other voxels of the brain.

In the present study, using a VBM analysis across the whole brain, we firstly identified positive correlations between the GMV and the DB score in the right anterior superior temporal gyrus (STG), the right posterior STG, the left IFG and the left Rolandic operculum. Many previous studies on brain disorders have revealed that brain areas with changes in the GMV are commonly accompanied by altered rsFCs between these regions and other related brain areas [22]–[24]. For example, the hippocampus had both a reduced GMV [25] and rsFCs in patients with Alzheimer disease [26]. These findings suggest that structural (i.e., GMV) change in a brain area may be associated with rsFC alteration in this area and that the combination of VBM and rsFC analyses can improve our understanding of the pathology of brain diseases. We further hypothesize that the combination of these two methods may improve our understanding of the neural correlates of DB capacity. Thus, we also investigated the correlations between the DB scores and the rsFCs of the four clusters found in the VBM analysis.