Coding serial order of information is a fundamental ability of our cognitive system, and still, little is known about its neural substrate. This study examined the neural substrates involved in the retrieval of information that is serially stored in verbal working memory task using a sensitive multivariate analysis approach. We compared neural activity for memorized items stemming from the beginning versus the end of a memory list assessing the degree of neural pattern discordance between order positions (beginning vs. end). The present results confirmed and refined the role of the intraparietal sulcus in the processing of serial order information in working memory. An important finding is that the hippocampus showed sensitivity to serial order information. Our results indicate that the representation of serial order information relies on a broader set of neural areas and highlight the role of the intraparietal sulcus and the hippocampus, in addition to the supramarginal gyrus and the SMA. The contribution of different neural regions might reflect the involvement of distinct levels of serial order coding (i.e., spatial, attentional, temporal) that support the representation of serial order information.

This fMRI study aimed at unraveling the neural basis of learning alphabet arithmetic facts, as a proxy of the transition from slow and effortful procedural counting-based processing to fast and effortless processing as it occurs in learning addition arithmetic facts. Neural changes were tracked while participants solved alphabet arithmetic problems in a verification task (e.g., F + 4 = J). Problems were repeated across four learning blocks. Two neural networks with opposed learning-related changes were identified. Activity in a network consisting of basal ganglia and parieto-frontal areas decreased with learning, which is in line with a reduction of the involvement of procedure-based processing. Conversely, activity in a network involving the left angular gyrus and, to a lesser extent, the hippocampus gradually increases with learning, evidencing the gradual involvement of retrieval-based processing. Connectivity analyses gave insight in the functional relationship between the two networks. Despite the opposing learning-related trajectories, it was found that both networks become more integrated. Taking alphabet arithmetic as a proxy for learning arithmetic, the present results have implications for current theories of learning arithmetic facts and can give direction to future developments.

Multiplication is thought to be primarily solved via direct retrieval from memory. Two of the main factors known to influence the retrieval of multiplication facts are problem size and interference. Because these factors are often intertwined, we sought to investigate the unique influences of problem size and interference on both performance and neural responses during multiplication fact retrieval in healthy adults. Behavioral results showed that both problem size and interference explained separate unique portions of RT variance, but with significantly stronger contribution from problem size, which contrasts with previous work in children. Whole-brain fMRI results relying on a paradigm that isolated multiplication fact retrieval from response selection showed highly overlapping brain areas parametrically modulated by both problem size and interference in a large network of frontal, parietal, and subcortical brain areas. Subsequent analysis within these regions revealed problem size to be the stronger and more consistent “unique” modulating factor in overlapping regions as well as those that appeared to respond only to problem size or interference at the whole-brain level, thus underscoring the need to look beyond anatomical overlap using arbitrary thresholds. Additional unique contributions of interference (beyond problem size) were identified in right angular gyrus and subcortical regions associated with procedural processing. Together, our results suggest that problem size, relative to interference, tends to be the more dominant factor in driving behavioral and neural responses during multiplication fact retrieval in adults. Nevertheless, unique contributions of both factors demonstrate the importance of considering the overlapping and unique contributions of each in explaining the cognitive and neural bases of mental multiplication.

Although many neuroimaging studies have considered verbal and visual short-term memory (STM) as relying on neurally segregated short-term buffer systems, the present study explored the existence of shared neural correlates supporting verbal and visual STM. We hypothesized that networks involved in attentional and executive processes, as well as networks involved in serial order processing, underlie STM for both verbal and visual list information, with neural specificity restricted to sensory areas involved in processing the specific items to be retained. Participants were presented sequences of nonwords or unfamiliar faces, and were instructed to maintain and recognize order or item information. For encoding and retrieval phases, null conjunction analysis revealed an identical fronto-parieto-cerebellar network comprising the left intraparietal sulcus, bilateral dorsolateral prefrontal cortex, and the bilateral cerebellum, irrespective of information type and modality. A network centered around the right intraparietal sulcus supported STM for order information, in both verbal and visual modalities. Modality-specific effects were observed in left superior temporal and mid-fusiform areas associated with phonological and orthographic processing during the verbal STM tasks, and in right hippocampal and fusiform face processing areas during the visual STM tasks, wherein these modality effects were most pronounced when storing item information. The present results suggest that STM emerges from the deployment of modality-independent attentional and serial ordering processes toward sensory networks underlying the processing and storage of modality-specific item information.

This article addresses the representation of numerical information conveyed by nonsymbolic and symbolic stimuli. In a first simulation study, we show how number-selective neurons develop when an initially uncommitted neural network is given nonsymbolic stimuli as input (e.g., collections of dots) under unsupervised learning. The resultant network is able to account for the distance and size effects, two ubiquitous effects in numerical cognition. Furthermore, the properties of the network units conform in detail to the characteristics of recently discovered number-selective neurons. In a second study, we simulate symbol learning by presenting symbolic and nonsymbolic input simultaneously. The same number-selective neurons learn to represent the numerical meaning of symbols. In doing so, they show properties reminiscent of the originally available number-selective neurons, but at the same time, the representational efficiency of the neurons is increased when presented with symbolic input. This finding presents a concrete proposal on the linkage between higher order numerical cognition and more primitive numerical abilities and generates specific predictions on the neural substrate of number processing.

The close behavioral parallels between the processing of quantitative information conveyed by symbolic and non-symbolic stimuli led to the hypothesis that there exists a common cerebral representation of quantity (Dehaene, Dehaene-Lambertz, & Cohen, 1998). The neural basis underlying the encoding of number magnitude has been localized to regions in and around the intraparietal sulcus (IPS) by brain-imaging studies. However, it has never been demonstrated that these same regions are also involved in the quantitative processing of nonsymbolic stimuli. Using functional brain imaging, we explicitly tested the hypothesis of a common substrate. Angles, lines, and two-digit numbers were presented pairwise, one to the left and one to the right of the fixation point. In the three comparison tasks, participants ( n = 18) pressed the key on the side of the largest quantity. In the three control tasks, they indicated the side on which dimming occurred. A conjunction analysis between the three subtractions (comparison task-control task) revealed a site in left IPS that is specifically responsive when two stimuli have to be compared quantitatively, irrespective of stimulus format. The results confirm the hypothesis that quantity is represented by a common mechanism for both symbolic and nonsymbolic stimuli in IPS. In addition, the interaction between task and type of stimulus identified a region anterior to the conjunction site, not specific for quantitative processing, but reflecting general processes loaded by number processing.

The aim of the present positron emission tomography (PET) study was to investigate how visual processing in dorsal and ventral streams depends on the quantitative nature of the task. In the same—different task, participants identified the presence of an orientation difference between two gratings, presented centrally in succession. In the quantification task, participants estimated the magnitude of the difference and compared it to a fixed standard. Detection of dimming of the fixation point was used as a control task. Visual input, motor responses, and performance were equated across tasks. Subtracting same— different from quantification yielded significant activation in the left superior parietal lobule and left ventral premotor cortex, consistent with results obtained in number-processing tasks. The reverse subtraction yielded activation in the right inferior temporal gyrus, in agreement with earlier results. These results demonstrate that a single attribute can be processed either in the ventral or dorsal stream, depending on the cognitive operations required by the tasks.