The cognitive neuroscience of visual working memory

Visual working memory allows us to temporarily maintain and manipulate visual information in order to solve a task. The study of the brain mechanisms underlying this function began more than half a century ago, with Scoville and Milner’s (1957) seminal discoveries with amnesic patients. This timely collection of papers brings together diverse perspectives on the cognitive neuroscience of visual working memory from multiple fields that have traditionally been fairly disjointed: human neuroimaging, electrophysiological, behavioural and animal lesion studies, investigating both the developing and the adult brain

Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony

Working memory (WM) is a primary cognitive function that corresponds to the ability to update, stably maintain, and manipulate short-term memory (STM) rapidly to perform ongoing cognitive tasks. A prevalent neural substrate of WM coding is persistent neural activity, the property of neurons to remain active after having been activated by a transient sensory stimulus. This persistent activity allows for online maintenance of memory as well as its active manipulation necessary for task performance. WM is tightly capacity limited. Therefore, selective gating of sensory and internally generated information is crucial for WM function. While the exact neural substrate of selective gating remains unclear, increasing evidence suggests that it might be controlled by modulating ongoing oscillatory brain activity. Here, we review experiments and models that linked selective gating, persistent activity, and brain oscillations, putting them in the more general mechanistic context of WM. We do so by defining several operations necessary for successful WM function and then discussing how such operations may be carried out by mechanisms suggested by computational models. We specifically show how oscillatory mechanisms may provide a rapid and flexible active gating mechanism for WM operations

Investigation of the multiple-demand network at multiple spatial scales

This dissertation investigates the frontoparietal ‘multiple-demand’ (MD) network that is involved in the processing of diverse cognitive demands. This network is active when the task at hand is made more demanding, in a variety of different tasks including working memory, task switching, inhibition, math, language etc. While the different MD regions have partly different functions, they are highly interconnected allowing them to function together as a network. The experiment in Chapter 2 looked at the interplay between functional differences as well as co-recruitment within this multiple-demand network. Quantitative differences between regions were more prominent in simple tasks. A strong co-recruitment was seen with increased challenge or incentive. In Chapter 3, task preferences were studied at the voxel level. MD regions were equally well localised in single-subjects using any of three task demands. Voxels localised by all three tasks also captured the underlying neural representations to a similar level in a separate criterion task. Chapter 4 investigated if task representations, as measured by multi-voxel patterns, were modified due to external motivation. The effect was limited to the cue phase and did not extend to the stimulus processing phase where the stimulus is integrated with the cue to arrive at the response. Chapter 5 examined neural representations in frontal and parietal regions more directly through single unit activity and local field potentials (LFPs), during a spatial working memory task. While single neurons showed dynamic coding of target information rather than persistent coding, LFPs held this information constant through time. The impact of reference voltages on LFP data was further investigated. Together, these results explore the functional differences between and within the MD regions, and provide evidence for flexible task representations at the voxel and neuronal level.Funded by Gates Cambridg

Exact neural mass model for synaptic-based working memory

A synaptic theory of Working Memory (WM) has been developed in the last decade as a possible alternative to the persistent spiking paradigm. In this context, we have developed a neural mass model able to reproduce exactly the dynamics of heterogeneous spiking neural networks encompassing realistic cellular mechanisms for short-term synaptic plasticity. This population model reproduces the macroscopic dynamics of the network in terms of the firing rate and the mean membrane potential. The latter quantity allows us to get insight on Local Field Potential and electroencephalographic signals measured during WM tasks to characterize the brain activity. More specifically synaptic facilitation and depression integrate each other to efficiently mimic WM operations via either synaptic reactivation or persistent activity. Memory access and loading are associated to stimulus-locked transient oscillations followed by a steady-state activity in the $\beta-\gamma$ band, thus resembling what observed in the cortex during vibrotactile stimuli in humans and object recognition in monkeys. Memory juggling and competition emerge already by loading only two items. However more items can be stored in WM by considering neural architectures composed of multiple excitatory populations and a common inhibitory pool. Memory capacity depends strongly on the presentation rate of the items and it maximizes for an optimal frequency range. In particular we provide an analytic expression for the maximal memory capacity. Furthermore, the mean membrane potential turns out to be a suitable proxy to measure the memory load, analogously to event driven potentials in experiments on humans. Finally we show that the $\gamma$ power increases with the number of loaded items, as reported in many experiments, while $\theta$ and $\beta$ power reveal non monotonic behaviours.Comment: 47 pages, 14 figure

Respiratory, postural and spatio-kinetic motor stabilization, internal models, top-down timed motor coordination and expanded cerebello-cerebral circuitry: a review

Human dexterity, bipedality, and song/speech vocalization in Homo are reviewed within a motor evolution perspective in regard to 

(i) brain expansion in cerebello-cerebral circuitry, 
(ii) enhanced predictive internal modeling of body kinematics, body kinetics and action organization, 
(iii) motor mastery due to prolonged practice, 
(iv) task-determined top-down, and accurately timed feedforward motor adjustment of multiple-body/artifact elements, and 
(v) reduction in automatic preflex/spinal reflex mechanisms that would otherwise restrict such top-down processes. 

Dual-task interference and developmental neuroimaging research argues that such internal modeling based motor capabilities are concomitant with the evolution of 
(vi) enhanced attentional, executive function and other high-level cognitive processes, and that 
(vii) these provide dexterity, bipedality and vocalization with effector nonspecific neural resources. 

The possibility is also raised that such neural resources could 
(viii) underlie human internal model based nonmotor cognitions. 
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Advances in Clinical Neurophysiology

Including some of the newest advances in the field of neurophysiology, this book can be considered as one of the treasures that interested scientists would like to collect. It discusses many disciplines of clinical neurophysiology that are, currently, crucial in the practice as they explain methods and findings of techniques that help to improve diagnosis and to ensure better treatment. While trying to rely on evidence-based facts, this book presents some new ideas to be applied and tested in the clinical practice. Advances in Clinical Neurophysiology is important not only for the neurophysiologists but also for clinicians interested or working in wide range of specialties such as neurology, neurosurgery, intensive care units, pediatrics and so on. Generally, this book is written and designed to all those involved in, interpreting or requesting neurophysiologic tests

Characterizing persistent Developmental Dyscalculia: A cognitive neuroscience approach

Developmental dyscalculia (DD) is a specific learning disorder of calculation abilities. In the present thesis I report a series behavioural and functional neuroimaging studies to further elucidate the core numerical deficits underlying DD. I recruited a sample of children with DD who demonstrated persistent impairments in arithmetic. In Chapter 2, to validate the selection criteria, I compared the performance of children with and without persistent DD on a test of numerical magnitude processing. The data showed that only children with persistent DD presented with deficits in numerical magnitude processing, while those with inconsistent DD perform at the level of age-matched typically developing (TD) controls. In Chapter 3, I compared the performance of children with persistent DD on tasks assessing symbolic (e.g. Arabic digits) and non-symbolic (e.g. dot arrays) processing skills. Children with DD performed significantly worse on symbolic but not non-symbolic numerical magnitude processing tasks. These findings suggest that DD arises not from a format-independent magnitude processing deficit, but rather from difficulties in processing symbolic number representations. In Chapter 4, I investigated the influence of non-numerical variables (e.g. size) on non-symbolic numerical magnitude processing in children with and without DD. Children with DD were found to exhibit deficits in non-symbolic processing only when the visual perceptual cues were anticorrelated with numerical magnitude. When numerical magnitude and area were congruent no group differences in performance emerged. Therefore, rather than presenting with a core deficit in non-symbolic processing, children with DD have difficulties in disentangling numerical and non-numerical cues. In Chapter 5, I used functional neuroimaging to investigate whether children with DD exhibit atypical brain activation during numerical magnitude processing (symbolic, non-symbolic and mixed comparison). The data from this study revealed atypical cortical activity in the Intraparietal Sulcus (IPS) during symbolic and mixed format (comparing symbolic with non-symbolic) tasks. In contrast, children with DD did not exhibit differences in the IPS during non-symbolic numerical magnitude processing. These neuroimaging findings complement the behavioral data in Chapter 3 and 4 by suggesting that children with DD have a deficit in semantic representation of symbolic numerical magnitudes rather than a core deficit in representing both symbolic and non-symbolic numerical magnitudes. The findings from these studies provide converging evidence to support a core deficit in processing the semantic meaning of symbolic numerals in children with persistent DD

Neural network mechanisms of working memory interference

[eng] Our ability to memorize is at the core of our cognitive abilities. How could we effectively make decisions without considering memories of previous experiences? Broadly, our memories can be divided in two categories: long-term and short-term memories. Sometimes, short-term memory is also called working memory and throughout this thesis I will use both terms interchangeably. As the names suggest, long-term memory is the memory you use when you remember concepts for a long time, such as your name or age, while short-term memory is the system you engage while choosing between different wines at the liquor store. As your attention jumps from one bottle to another, you need to hold in memory characteristics of previous ones to pick your favourite. By the time you pick your favourite bottle, you might remember the prices or grape types of the other bottles, but you are likely to forget all of those details an hour later at home, opening the wine in front of your guests. The overall goal of this thesis is to study the neural mechanisms that underlie working memory interference, as reflected in quantitative, systematic behavioral biases. Ultimately, the goal of each chapter, even when focused exclusively on behavioral experiments, is to nail down plausible neural mechanisms that can produce specific behavioral and neurophysiological findings. To this end, we use the bump-attractor model as our working hypothesis, with which we often contrast the synaptic working memory model. The work performed during this thesis is described here in 3 main chapters, encapsulation 5 broad goals: In Chapter 4.1, we aim at testing behavioral predictions of a bump-attractor (1) network when used to store multiple items. Moreover, we connected two of such networks aiming to model feature-binding through selectivity synchronization (2). In Chapter 4.2, we aim to clarify the mechanisms of working memory interference from previous memories (3), the so-called serial biases. These biases provide an excellent opportunity to contrast activity-based and activity-silent mechanisms because both mechanisms have been proposed to be the underlying cause of those biases. In Chapter 4.3, armed with the same techniques used to seek evidence for activity-silent mechanisms, we test a prediction of the bump-attractor model with short-term plasticity (4). Finally, in light of the results from aim 4 and simple computer simulations, we reinterpret previous studies claiming evidence for activity-silent mechanisms (5)

Error Observation in Schizophrenia

Despite the pervasive and impairing nature of social difficulties in schizophrenia, the causes of these problems are not fully understood. It has been suggested that problems with cognitive functioning contribute to the social deficits of schizophrenia. However, little is known about the neural mechanisms that underlie cognitive processes directly linked to social dysfunction in schizophrenia. Recent studies of the mirror neuron system have focused on the error-related negativity (ERN), a negatively-deflected event-related brain potential that is elicited following the commission of an erroneous response. This study examined ERN activity in schizophrenia patients and psychiatrically healthy controls during performance and observation of a confederate performing a computerized flanker task. The lateralized readiness potential (LRP) allowed for a direct comparison of brain activation reflecting response readiness verses error signaling. Correlations between ERN activity during flanker observation, social cognition (i.e., theory of mind), and community social functioning were explored. Finally, correlations between verbal memory, executive functioning, and social functioning were examined and social cognition was explored as a mediator between neurocognition and social functioning. Results indicated that controls produced a robust ERN during execution of the flanker task, whereas ERN activity among patients was comparatively attenuated in amplitude. During observation, there were no significant group differences and no identifiable observation ERN; however, there was greater negative activity following error than correct trials in this condition for all participants. LRP activity did not parallel that of the ERN, supporting the differentiation of motor activity and error-related processing during observation. The only significant correlation to emerge between ERN activity and social cognition and social functioning was between occupational status and execution ERN activity among controls only. Unexpectedly, neurocognition and social functioning were negatively correlated in the patient group. Expectedly, these variables were positively correlated among controls. Therefore, regression analyses were conducted separately by group; however, neither neurocognition nor social cognition predicted a significant proportion of the variance in social functioning. Despite limitations, this research is discussed as a starting point for integrating the study of psychophysiological activity with social behavior and functioning, particularly in a clinical population with pronounced social deficits