Individual differences in conflict-monitoring: testing means and covariance hypothesis about the Simon and the Eriksen Flanker task

Conflict and context slow-down have been proposed as indicators of a conflict-monitoring system that initiates cognitive control to resolve conflicts in information processing. We investigated individual differences in conflict-monitoring and their associations with working memory (WM) and impulsivity. A total of 150 adults completed a Simon and an Eriksen flanker task, together with measures of WM and impulsivity. On both tasks, responses were slower and less accurate on incompatible than on compatible trials (conflict effect), and the conflict effect was larger when the preceding trial was compatible than when it was incompatible (context effect). Stimulus repetition did not explain the context effect. Individual differences could be attributed to three separable factors for each task: general speeded performance, conflict effect, and context effect. Evidence for across-task generality of these factors was sparse. Associations of these factors with impulsivity were weak at best. WM was correlated with general speed, and also with some but not all factors reflecting conflict-related processes.     

Numbers and space: a computational model of the SNARC effect

The SNARC (spatial numerical associations of response codes) effect reflects the tendency to respond faster with the left hand to relatively small numbers and with the right hand to relatively large numbers (S. Dehaene, S. Bossini, & P. Giraux, 1993). Using computational modeling, the present article aims to provide a framework for conceptualizing the SNARC effect. In line with models of spatial stimulus-response congruency, the authors modeled the SNARC effect as the result of parallel activation of preexisting links between magnitude and spatial representation and short-term links created on the basis of task instructions. This basic dual-route model simulated all characteristics associated with the SNARC effect. In addition, 2 experiments tested and confirmed new predictions derived from the model.     

Understanding team adaptation: a conceptual analysis and model

This endeavor provides a multidisciplinary, multilevel, and multiphasic conceptualization of team adaptation with theoretical roots in the cognitive, human factors, and industrial-organizational psychology literature. Team adaptation and the emergent nature of adaptive team performance are defined from a multilevel, theoretical standpoint. An input-throughput-output model is advanced to illustrate a series of phases unfolding over time that constitute the core processes and emergent states underlying adaptive team performance and contributing to team adaptation. The cross-level mixed-determinants model highlights team adaptation in a nomological network of lawful relations. Testable propositions, practical implications, and directions for further research in this area are also advanced.     

Face recognition algorithms and the other‐race effect: computational mechanisms for a developmental contact hypothesis

People recognize faces of their own race more accurately than faces of other races. The “contact” hypothesis suggests that this “other‐race effect” occurs as a result of the greater experience we have with own‐ versus other‐race faces. The computational mechanisms that may underlie different versions of the contact hypothesis were explored in this study. We replicated the other‐race effect with human participants and evaluated four classes of computational face recognition algorithms for the presence of an other‐race effect. Consistent with the predictions of a developmental contact hypothesis, “experience‐based models” demonstrated an other‐race effect only when the representational system was developed through experience that warped the perceptual space in a way that was sensitive to the overall structure of the model's experience with faces of different races. When the model's representation relied on a feature set optimized to encode the information in the learned faces, experience‐based algorithms recognized minority‐race faces more accurately than majority‐race faces. The results suggest a developmental learning process that warps the perceptual space to enhance the encoding of distinctions relevant for own‐race faces. This feature space limits the quality of face representations for other‐race faces.     

Temporal constraints on visual learning: a computational model

Given a constant stream of perceptual stimuli, how can the underlying invariances associated with a given input be learned? One approach consists of using generic truths about the spatiotemporal structure of the physical world as constraints on the types of quantities learned. The learning methodology employed here embodies one such truth: that perceptually salient properties (such as stereo disparity) tend to vary smoothly over time. Unfortunately, the units of an artificial neural network tend to encode superficial image properties, such as individual grey-level pixel values, which vary rapidly over time. However, if the states of units are constrained to vary slowly, then the network is forced to learn a smoothly varying function of the training data. We implemented this temporal-smoothness constraint in a backpropagation network which learned stereo disparity from random-dot stereograms. Temporal smoothness was formalized with the use of regularization theory by modifying the standard cost function minimised during training of a network. Temporal smoothness was found to be similar to other techniques for improving generalisation, such as early stopping and weight decay. However, in contrast to these, the theoretical underpinnings of temporal smoothing are intimately related to fundamental characteristics of the physical world. Results are discussed in terms of regularization theory and the physically realistic assumptions upon which temporal smoothing is based.     

Bootstrapping the lexicon: a computational model of infant speech segmentation

Prelinguistic infants must find a way to isolate meaningful chunks from the continuous streams of speech that they hear. BootLex, a new model which uses distributional cues to build a lexicon, demonstrates how much can be accomplished using this single source of information. This conceptually simple probabilistic algorithm achieves significant segmentation results on various kinds of language corpora - English, Japanese, and Spanish; child- and adult-directed speech, and written texts; and several variations in coding structure - and reveals which statistical characteristics of the input have an influence on segmentation performance. BootLex is then compared, quantitatively and qualitatively, with three other groups of computational models of the same infant segmentation process, paying particular attention to functional characteristics of the models and their similarity to human cognition. Commonalities and contrasts among the models are discussed, as well as their implications both for theories of the cognitive problem of segmentation itself, and for the general enterprise of computational cognitive modeling.     

ICAT: a computational model for the adaptive control of fixation durations

Eye movements depend on cognitive processes related to visual information processing. Much has been learned about the spatial selection of fixation locations, while the principles governing the temporal control (fixation durations) are less clear. Here, we review current theories for the control of fixation durations in tasks like visual search, scanning, scene perception, and reading and propose a new model for the control of fixation durations. We distinguish two local principles from one global principle of control. First, an autonomous saccade timer initiates saccades after random time intervals (local-I). Second, foveal inhibition permits immediate prolongation of fixation durations by ongoing processing (local-II). Third, saccade timing is adaptive, so that the mean timer value depends on task requirements and fixation history (Global). We demonstrate by numerical simulations that our model qualitatively reproduces patterns of mean fixation durations and fixation duration distributions observed in typical experiments. When combined with assumptions of saccade target selection and oculomotor control, the model accounts for both temporal and spatial aspects of eye movement control in two versions of a visual search task. We conclude that the model provides a promising framework for the control of fixation durations in saccadic tasks.     

Discussion on the reverberatory model of short-term memory: a computational approach

Up to now a number of models have been proposed to underlie memory formation in the central nervous system. Two of these models are the reverberatory circuit model and the other one the self-feedback loop model. This paper considers these two models regarding their ability to preserve neural activity and to hold information. In the self-feedback loop model, the activity level of the loop output is computed regarding the short lasting initial input. In the reverberatory circuit model, the activity levels of the proposed two-layer network outputs were computed regarding the short lasting initial inputs of the network. In the self-feedback loop model, the activity level of the loop output changes with each reverberation until it reaches a specific limit and then remains at that level. In the reverberatory circuit model, the activity levels of the proposed two-layer network outputs display an oscillatory behavior. These models can preserve the input activity, but they change its level with each reverberation. Information carried by a single neuron is related to its activity level. Therefore these models change the information during the reverberation. Short-term memory must hold the information for a certain period of time, so these models cannot be proposed to underlie short-term memory formation.     

TRoPICALS: a computational embodied neuroscience model of compatibility effects

Perceiving objects activates the representation of their affordances. For example, experiments on compatibility effects showed that categorizing objects by producing certain handgrips (power or precision) is faster if the requested responses are compatible with the affordance elicited by the size of objects (e.g., small or large). The article presents a neural-network architecture that provides a general framework to account for compatibility effects. The model was designed with a methodological approach (computational embodied neuroscience) that aims to provide increasingly general accounts of brain and behavior (4 sources of constraints are used: neuroscientific data, behavioral data, embodied systems, reproduction of learning processes). The model is based on 4 principles of brain organization that we claim underlie most compatibility effects. First, visual perception and action are organized in the brain along a dorsal neural pathway encoding affordances and a ventral pathway encoding goals. Second, the prefrontal cortex within the ventral pathway gives a top-down bias to action selection by integrating information on stimuli, context, and goals. Third, reaction times depend on dynamic neural competitions for action selection that integrate bottom-up and top-down information. The congruence or incongruence between affordances and goals explains the different reaction times found in the experiments. Fourth, as words trigger internal simulations of their referents, they can cause compatibility effects as objects do. We validated the model by reproducing and explaining 3 types of compatibility effects and showed its heuristic power by producing 2 testable predictions. We also assessed the explicative power of the model by comparing it with related models and showed how it can be extended to account for other compatibility effects.     

Strategic calibration and spatial alignment: a model from prism adaptation

Two types of adaptive processes involved in prism adaptation have been identified&colon: Slower spatial realignment among the several unique sensorimotor coordinate systems (spatial maps) and faster strategic motor control responses(including skill learning and calibration) to spatial misalignment. One measures the 1st process by assessing the aftereffects of prism exposure, whereas direct effects of the prism during exposure are a measure of the 2nd process. A model is described that relates those adaptive processes and distinguishes between extraordinary alignment and ordinary calibration. A conformal translation algorithm that operates on the hypothesized circuitry is proposed. The authors apply to the model to explain the advantage of visual calibration when the limb is seen in the starting position prior to movement initiation. Implications of the model for the use of prism adaptation as a tool for investigation of motor control and learning are discussed.     

Item-specific processing reduces false recognition in older and younger adults: Separating encoding and retrieval using signal detection and the diffusion model

Our study examined processing effects in improving memory accuracy in older and younger adults. Specifically, we evaluated the effectiveness of item-specific and relational processing instructions relative to a read-only control task on correct and false recognition in younger and older adults using a categorized-list paradigm. In both age groups, item-specific and relational processing improved correct recognition versus a read-only control task, and item-specific encoding decreased false recognition relative to both the relational and read-only groups. This pattern was found in older adults despite overall elevated rates of false recognition. We then applied signal-detection and diffusion-modeling analyses, which separately utilized recognition responses and the latencies to those responses to estimate contributions of encoding and monitoring processes on recognition decisions. Converging evidence from both analyses demonstrated that item-specific processing benefits to memory accuracy were due to improvements of both encoding (estimates of d′ and drift rate) and monitoring (estimates of lambda and boundary separation) processes, and, importantly, occurred similarly in both younger and older adults. Thus, older and younger adults showed similar encoding-based and test-based benefits of item-specific processing to enhance memory accuracy.     

Item-specific control of automatic processes: Stroop process dissociations

The influence of word reading on Stroop color naming decreases as a function of the proportion of test items that are incongruent. This proportion-congruent effect is usually ascribed to strategies (e.g., maintaining task set) that operate at a general level to moderate the extent to which participants are influenced by word reading. However, in three experiments, effects at the level of specific items were found. Interference and facilitation were smaller for color names usually presented in an incongruent color than for color names usually presented in their congruent colors. This item-specific proportioncongruent manipulation affected the process dissociation (PD) estimate of the influence of word-reading processes but not that of color-naming processes. The results (1) indicate that item-specific, as opposed to general, mechanisms can reduce the influence of word-reading processes on Stroop performance and (2) demonstrate the PD procedure’s utility in studying Stroop phenomena.     

Rethinking the gender identity crossover hypothesis: A test of a new model

Both self-report and projective assessment techniques were used to examine whether there exists a gender identity crossover at midlife such that men develop a communal or affiliative orientation and women become more interested in agency and power. A sample of 150 predominantly Caucasian men and women ages 24–84 were divided into three age groups for comparison: (1) young (ages 20–39); (2) middle-aged (ages 40–65); and (3) old (ages 66–84). Measures included six pictures from the Thematic Apperception Test, which were coded for achievement, power, intimacy, and affiliation needs, and the Goldberg 50-Bipolar, from which items were selected to derive agency and communion scales. Middle-aged men were lower in the need for power and higher in the need for affiliation than were younger men; there were no age differences in self attributions of agency and communion. Results are discussed in terms of the traditionality of the men and the nontraditionality of the women with respect to work and family roles.This research was supported in part by grants to Margie Lachman from the John D. and Catherine T. MacArthur Foundation Research Network on Successful Midlife Development and the National Institute on Aging (AG06038).     

Being seaward-handed: a computational model of the acquisition of language-specific spatial references

Empirical findings of cross-linguistic studies reveal three different frames of spatial reference: intrinsic, relative, and absolute. Of special interest are relative and absolute systems because they have antagonistic logical implications concerning the dependence on standpoint and orientation of the speaker/hearer. On the background of these findings it becomes crucial to show how an agent can form such language-specific spatial representations. In this paper, the system Locator is introduced as a model of concept formation in the spatial domain. It is assumed that an agent creates necessary discriminative features in processes of self-organization and selection and cannot just discover or find them in its environment. A number of simulations show that agents successfully create concepts of either a relative system (German) or an absolute system (Marquesan), relying solely on multimodal input (visual and linguistic).

Age vs Alzheimer's: a computational model of changes in representation

Previous research has demonstrated that the language of older adults leads to denser representations in a high dimensional model of memory than does the language of younger adults (Conley & Burgess, in press), and thus that density in the model (HAL or the hyperspace analogue to language) may constitute a useful metric in comparing memory for younger and older adults. This paper extends the previous research by examining the role of density in semantic representations that emerged from the language generated by adults with Alzheimer' s and comparing the results with age-matched normal controls. We found that, just as older adults have denser representations in semantic space than do younger adults, adults with Alzheimer's have still denser representations than normal older adults. These results support the hypothesis that greater density, normally associated in the model with good semantic depth, may in fact reach a "saturation point" and affect retrieval in older adults and especially adults with Alzheimer's.     

Strategy generalization across orientation tasks: testing a computational cognitive model

Humans use their spatial information processing abilities flexibly to facilitate problem solving and decision making in a variety of tasks. This article explores the question of whether a general strategy can be adapted for performing two different spatial orientation tasks by testing the predictions of a computational cognitive model. Human performance was measured on an orientation task requiring participants to identify the location of a target either on a map (find-on-map) or within an egocentric view of a space (find-in-scene). A general strategy instantiated in a computational cognitive model of the find-on-map task, based on the results from Gunzelmann and Anderson (2006) , was adapted to perform both tasks and used to generate performance predictions for a new study. The qualitative fit of the model to the human data supports the view that participants were able to tailor a general strategy to the requirements of particular spatial tasks. The quantitative differences between the predictions of the model and the performance of human participants in the new experiment expose individual differences in sample populations. The model provides a means of accounting for those differences and a framework for understanding how human spatial abilities are applied to naturalistic spatial tasks that involve reasoning with maps.     

Comprehension of simple quantifiers: empirical evaluation of a computational model

We examine the verification of simple quantifiers in natural language from a computational model perspective. We refer to previous neuropsychological investigations of the same problem and suggest extending their experimental setting. Moreover, we give some direct empirical evidence linking computational complexity predictions with cognitive reality. In the empirical study we compare time needed for understanding different types of quantifiers. We show that the computational distinction between quantifiers recognized by finite-automata and push-down automata is psychologically relevant. Our research improves upon, the hypotheses and explanatory power of recent neuroimaging studies as well as provides evidence for the claim that human linguistic abilities are constrained by computational complexity.