An Exploration of the Relations between External Representations and Working Memory

It is commonly hypothesized that external representations serve as memory aids and improve task performance by means of expanding the limited capacity of working memory. However, very few studies have directly examined this memory aid hypothesis. By systematically manipulating how information is available externally versus internally in a sequential number comparison task, three experiments were designed to investigate the relation between external representations and working memory. The experimental results show that when the task requires information from both external representations and working memory, it is the interaction of information from the two sources that determines task performance. In particular, when information from the two sources does not match well, external representations hinder instead of enhance task performance. The study highlights the important role the coordination among different representations plays in distributed cognition. The general relations between external representations and working memory are discussed.     

Coding of distributed, topographic and non-specific representations within the brain

This article explores the theoretical basis of coding within topographic representations, where neurons encoding specific features such as locations, are arranged into maps. A novel type of representation, termed non-specific, where each neuron does not encode specific features is also postulated. In common with the previously described distributed representations [Rolls, E.T., Treves, A., 1998. Neural Networks and Brain Function. Oxford University Press, Oxford], topographic representations display an exponential relationship between stimuli encoded and both number of neurons and maximum firing rate of those neurons. The non-specific representations described here display a binomial expansion between the number of stimuli encoded and the sum of the number of neurons and the maximum firing rate; therefore groups of non-specific neurons usually encode less stimuli than equivalent topographic layers of neurons. Lower and higher order sensory regions of the brain use either topographic or distributed representations to encode information. It is proposed that non-specific representations may occur in regions of the brain where different types of information may be represented by the same neurons, as occurs in the prefrontal cortex.     

Notation-dependent and -independent representations of numbers in the parietal lobes

It is a commonly held view that numbers are represented in an abstract way in both parietal lobes. This view is based on failures to find differences between various notational representations. Here we show that by using relatively smaller voxels together with an adaptation paradigm and analyzing subjects on an individual basis it is possible to detect specialized numerical representations. The current results reveal a left/right asymmetry in parietal lobe function. In contrast to an abstract representation in the left parietal lobe, the numerical representation in the right parietal lobe is notation dependent and thus includes nonabstract representations. Our results challenge the commonly held belief that numbers are represented solely in an abstract way in the human brain.     

Multiple time-scales and the developmental dynamics of social systems

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the 'coarseness' of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems.     

Learning, memory, and the role of neural network architecture

The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems.     

Measuring the magnitude of morphological integration: The effect of differences in morphometric representations and the inclusion of size

The magnitude of morphological integration is a major aspect of multivariate evolution, providing a simple measure of the intensity of association between morphological traits. Studies concerned with morphological integration usually translate phenotypes into morphometric representations to quantify how different morphological elements covary. Geometric and classic morphometric representations translate biological form in different ways, raising the question if magnitudes of morphological integration estimates obtained from different morphometric representations are compatible. Here we sought to answer this question using the relative eigenvalue variance of the covariance matrix obtained for both geometric and classical representations of empirical and simulated datasets. We quantified the magnitude of morphological integration for both shape and form and compared results between representations. Furthermore, we compared integration values between shape and form to evaluate the effect of the inclusion or not of size on the quantification of the magnitude of morphological integration. Results show that the choice of morphological representation has significant impact on the integration magnitude estimate, either for shape or form. Despite this, ordination of the integration values within representations is relatively the same, allowing for similar conclusions to be reached using different methods. However, the inclusion of size in the dataset significantly changes the estimates of magnitude of morphological integration, hindering the comparison of this statistic obtained from different spaces. Morphometricians should be aware of these differences and must consider how biological hypothesis translate into predictions about integration in each particular choice of representation.     

Effects of development and enculturation on number representation in the brain

A striking way in which humans differ from non-human primates is in their ability to represent numerical quantity using abstract symbols and to use these 'mental tools' to perform skills such as exact calculations. How do functional brain circuits for the symbolic representation of numerical magnitude emerge? Do neural representations of numerical magnitude change as a function of development and the learning of mental arithmetic? Current theories suggest that cultural number symbols acquire their meaning by being mapped onto non-symbolic representations of numerical magnitude. This Review provides an evaluation of this contention and proposes hypotheses to guide investigations into the neural mechanisms that constrain the acquisition of cultural representations of numerical magnitude.     

Introduction: gender,migration and the media

Abstract

Mediated representations of gender, ethnicity and migration play an increasingly important role in the way these categories are understood in the public sphere and the private realm. As media often intervene in processes of individual and institutional communication, they provide frameworks for the production and consumption of representations of these categories. Thus media – in their production, representations and consumption – need to be analysed, not only as reflections as pre-existing socio-political realities, but also as constitutive elements in the production of meanings of the self and the Other. This special issue includes a number of articles that examine the articulations of gendered ethnic identities and of gendered citizenship as these are shaped in media production, media representations and media consumption.     

A neural field model of the somatosensory cortex: formation, maintenance and reorganization of ordered topographic maps

We investigate the formation and maintenance of ordered topographic maps in the primary somatosensory cortex as well as the reorganization of representations after sensory deprivation or cortical lesion. We consider both the critical period (postnatal) where representations are shaped and the post-critical period where representations are maintained and possibly reorganized. We hypothesize that feed-forward thalamocortical connections are an adequate site of plasticity while cortico-cortical connections are believed to drive a competitive mechanism that is critical for learning. We model a small skin patch located on the distal phalangeal surface of a digit as a set of 256 Merkel ending complexes (MEC) that feed a computational model of the primary somatosensory cortex (area 3b). This model is a two-dimensional neural field where spatially localized solutions (a.k.a. bumps) drive cortical plasticity through a Hebbian-like learning rule. Simulations explain the initial formation of ordered representations following repetitive and random stimulations of the skin patch. Skin lesions as well as cortical lesions are also studied and results confirm the possibility to reorganize representations using the same learning rule and depending on the type of the lesion. For severe lesions, the model suggests that cortico-cortical connections may play an important role in complete recovery.     

In the eye of the beholder: visual experience and categories in the human brain

How does experience change representations of visual objects in the brain? Do cortical object representations reflect category membership? In this issue of Neuron, Jiang et al. show that category training leads to sharpening of neural responses in high-level visual cortex; in contrast, category boundaries may be represented only in prefrontal cortex.     

Attention Enhances the Retrieval and Stability of Visuospatial and Olfactory Representations in the Dorsal Hippocampus

A key question in the analysis of hippocampal memory relates to how attention modulates the encoding and long-term retrieval of spatial and nonspatial representations in this region. To address this question, we recorded from single cells over a period of 5 days in the CA1 region of the dorsal hippocampus while mice acquired one of two goal-oriented tasks. These tasks required the animals to find a hidden food reward by attending to either the visuospatial environment or a particular odor presented in shifting spatial locations. Attention to the visuospatial environment increased the stability of visuospatial representations and phase locking to gamma oscillations—a form of neuronal synchronization thought to underlie the attentional mechanism necessary for processing task-relevant information. Attention to a spatially shifting olfactory cue compromised the stability of place fields and increased the stability of reward-associated odor representations, which were most consistently retrieved during periods of sniffing and digging when animals were restricted to the cup locations. Together, these results suggest that attention selectively modulates the encoding and retrieval of hippocampal representations by enhancing physiological responses to task-relevant information.     

Hierarchical representations in the auditory cortex

Understanding the neural mechanisms of invariant object recognition remains one of the major unsolved problems in neuroscience. A common solution that is thought to be employed by diverse sensory systems is to create hierarchical representations of increasing complexity and tolerance. However, in the mammalian auditory system many aspects of this hierarchical organization remain undiscovered, including the prominent classes of high-level representations (that would be analogous to face selectivity in the visual system or selectivity to bird's own song in the bird) and the dominant types of invariant transformations. Here we review the recent progress that begins to probe the hierarchy of auditory representations, and the computational approaches that can be helpful in achieving this feat.     

Monkeys match the number of voices they hear to the number of faces they see

Convergent evidence demonstrates that adult humans possess numerical representations that are independent of language [1, 2, 3, 4, 5 and 6]. Human infants and nonhuman animals can also make purely numerical discriminations, implicating both developmental and evolutionary bases for adult humans' language-independent representations of number [7 and 8]. Recent evidence suggests that the nonverbal representations of number held by human adults are not constrained by the sensory modality in which they were perceived [9]. Previous studies, however, have yielded conflicting results concerning whether the number representations held by nonhuman animals and human infants are tied to the modality in which they were established [10, 11, 12, 13, 14 and 15]. Here, we report that untrained monkeys preferentially looked at a dynamic video display depicting the number of conspecifics that matched the number of vocalizations they heard. These findings suggest that number representations held by monkeys, like those held by adult humans, are unfettered by stimulus modality.     

Abnormalities in the awareness and control of action

Much of the functioning of the motor system occurs without awareness. Nevertheless, we are aware of some aspects of the current state of the system and we can prepare and make movements in the imagination. These mental representations of the actual and possible states of the system are based on two sources: sensory signals from skin and muscles, and the stream of motor commands that have been issued to the system. Damage to the neural substrates of the motor system can lead to abnormalities in the awareness of action as well as defects in the control of action. We provide a framework for understanding how these various abnormalities of awareness can arise. Patients with phantom limbs or with anosognosia experience the illusion that they can move their limbs. We suggest that these representations of movement are based on streams of motor commands rather than sensory signals. Patients with utilization behaviour or with delusions of control can no longer properly link their intentions to their actions. In these cases the impairment lies in the representation of intended movements. The location of the neural damage associated with these disorders suggests that representations of the current and predicted state of the motor system are in parietal cortex, while representations of intended actions are found in prefrontal and premotor cortex.     

Distributed representation of perceptual categories in the auditory cortex

Categorical perception is a process by which a continuous stimulus space is partitioned to represent discrete sensory events. Early experience has been shown to shape categorical perception and enlarge cortical representations of experienced stimuli in the sensory cortex. The present study examines the hypothesis that enlargement in cortical stimulus representations is a mechanism of categorical perception. Perceptual discrimination and identification behaviors were analyzed in model auditory cortices that incorporated sound exposure-induced plasticity effects. The model auditory cortex with over-representations of specific stimuli exhibited categorical perception behaviors for those specific stimuli. These results indicate that enlarged stimulus representations in the sensory cortex may be a mechanism for categorical perceptual learning.     

A Hierarchy of Time-Scales and the Brain

In this paper, we suggest that cortical anatomy recapitulates the temporal hierarchy that is inherent in the dynamics of environmental states. Many aspects of brain function can be understood in terms of a hierarchy of temporal scales at which representations of the environment evolve. The lowest level of this hierarchy corresponds to fast fluctuations associated with sensory processing, whereas the highest levels encode slow contextual changes in the environment, under which faster representations unfold. First, we describe a mathematical model that exploits the temporal structure of fast sensory input to track the slower trajectories of their underlying causes. This model of sensory encoding or perceptual inference establishes a proof of concept that slowly changing neuronal states can encode the paths or trajectories of faster sensory states. We then review empirical evidence that suggests that a temporal hierarchy is recapitulated in the macroscopic organization of the cortex. This anatomic-temporal hierarchy provides a comprehensive framework for understanding cortical function: the specific time-scale that engages a cortical area can be inferred by its location along a rostro-caudal gradient, which reflects the anatomical distance from primary sensory areas. This is most evident in the prefrontal cortex, where complex functions can be explained as operations on representations of the environment that change slowly. The framework provides predictions about, and principled constraints on, cortical structure–function relationships, which can be tested by manipulating the time-scales of sensory input.     

Coding of cognitive magnitude: compressed scaling of numerical information in the primate prefrontal cortex

Whether cognitive representations are better conceived as language-based, symbolic representations or perceptually related, analog representations is a subject of debate. If cognitive processes parallel perceptual processes, then fundamental psychophysical laws should hold for each. To test this, we analyzed both behavioral and neuronal representations of numerosity in the prefrontal cortex of rhesus monkeys. The data were best described by a nonlinearly compressed scaling of numerical information, as postulated by the Weber-Fechner law or Stevens' law for psychophysical/sensory magnitudes. This nonlinear compression was observed on the neural level during the acquisition phase of the task and maintained through the memory phase with no further compression. These results suggest that certain cognitive and perceptual/sensory representations share the same fundamental mechanisms and neural coding schemes.