Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

Translating cognitive neuroscience to fitness to drive using a neuroergonomic approach

Non-pathological or normal ageing is accompanied by brain alterations that are the result of natural changes occurring with age and our ability to compensate for them. Compared to younger adults, older adults have reduced vision, more difficulties in detecting relevant information they are not intending to and require more time to process sensorial information. Little is known on how these changes affect behaviour in a natural environment. Relying on a translational approach at the frontiers between neurobiology, psychophysics, neuropsychology and epidemiology, we were able to: explore the needs for innovative instrumentations to detect cerebral decline in clinical settings; develop and validate a new computed neuropsychological instrument designed to measure cerebral decline in healthy older adults; explore the link between processing speed and on-road driving performance; and investigate the effects of being able to anticipate on visual processing speed.

Combined neurostimulation and neuroimaging in cognitive neuroscience: past, present, and future

Modern neurostimulation approaches in humans provide controlled inputs into the operations of cortical regions, with highly specific behavioral consequences. This enables causal structure–function inferences, and in combination with neuroimaging, has provided novel insights into the basic mechanisms of action of neurostimulation on dis- tributed networks. For example,more recent work has established the capacity of transcranialmagnetic stimulation (TMS) to probe causal interregional influences, and their interaction with cognitive state changes. Combinations of neurostimulation and neuroimaging now face the challenge of integrating the known physiological effects of neu- rostimulationwith theoretical and biologicalmodels of cognition, for example,when theoretical stalemates between opposing cognitive theories need to be resolved. This will be driven by novel developments, including biologically informedcomputational network analyses for predicting the impactofneurostimulationonbrainnetworks, as well as novel neuroimaging and neurostimulation techniques. Such future developments may offer an expanded set of tools withwhich to investigate structure–function relationships, and to formulate and reconceptualize testable hypotheses about complex neural network interactions and their causal roles in cognition

Representation in cognitive neuroscience

This article discusses the possible representational nature of two brain cognitive functions: perceptual and executive. Assuming the Newellian definition of representational processes as those that establish an isomorphic relation between two structures, I claim that perceptual processes generate only a partial correspondence (between stimuli properties and brain states) and therefore should not be properly conceived as representational. on the other hand, executive processes encompass the combination of copies (i.e., representations) of perceptual patterns, generating new patterns that subserve behavior. In summary, I criticize the notion of perceptual representations, and propose that brain representational processes are related to executive functions, having a pragmatic dimension.

Time scales in cognitive neuroscience

Cognitive neuroscience boils down to describing the ways in which cognitive function results from brain activity. In turn, brain activity shows complex fluctuations, with structure at many spatio-temporal scales. Exactly how cognitive function inherits the physical dimensions of neural activity, though, is highly non-trivial, and so are generally the corresponding dimensions of cognitive phenomena. As for any physical phenomenon, when studying cognitive function, the first conceptual step should be that of establishing its dimensions. Here, we provide a systematic presentation of the temporal aspects of task-related brain activity, from the smallest scale of the brain imaging technique's resolution, to the observation time of a given experiment, through the characteristic time scales of the process under study. We first review some standard assumptions on the temporal scales of cognitive function. In spite of their general use, these assumptions hold true to a high degree of approximation for many cognitive (viz. fast perceptual) processes, but have their limitations for other ones (e.g., thinking or reasoning). We define in a rigorous way the temporal quantifiers of cognition at all scales, and illustrate how they qualitatively vary as a function of the properties of the cognitive process under study. We propose that each phenomenon should be approached with its own set of theoretical, methodological and analytical tools. In particular, we show that when treating cognitive processes such as thinking or reasoning, complex properties of ongoing brain activity, which can be drastically simplified when considering fast (e.g., perceptual) processes, start playing a major role, and not only characterize the temporal properties of task-related brain activity, but also determine the conditions for proper observation of the phenomena. Finally, some implications on the design of experiments, data analyses, and the choice of recording parameters are discussed.

Illusory memories: A cognitive neuroscience analysis

Memory illusions and distortions have long been of interest to psychology researchers studying memory, but neuropsychologists and neuroscientists have paid relatively little attention to them. This article attempts to lay the foundation for a cognitive neuroscience analysis of memory illusions and distortions by reviewing relevant evidence from a patient with a right frontal lobe lesion, patients with amnesia produced by damage to the medial temporal lobes, normal aging, and healthy young volunteers studied with functional neuroimaging techniques. Particular attention is paid to the contrasting roles of prefrontal cortex and medial temporal lobe structures in accurate and illusory remembering. Converging evidence suggests that the study of illusory memories can provide a useful tool for delineating the brain processes and systems involved in constructive aspects of remembering.

Organizational cognitive neuroscience

Organizational cognitive neuroscience (OCN) is the cognitive neuroscientific study of organizational behavior. OCN lets us start to understand the relationship between our organizational behavior and our brains and allows us to dissect specific social processes at the neurobiological level and apply a wider range of analysis to specific organizational research questions. The current paper examines the utility of OCN to address specific organizational research questions. A brief history and definition of the approach is first provided. Next, a discussion of the rationale for OCN as a research framework is provided, and then, finally, an overview of the range of techniques that the organizational researcher should (or shouldnot) use is described.

The brain in business:the case for organizational cognitive neuroscience?

The application of cognitive neuroscientific techniques to understanding social behaviour has resulted in many discoveries. Yet advocates of the ‘social cognitive neuroscience’ approach maintain that it suffers from a number of limitations. The most notable of these is its distance from any form of real-world applicabity. One solution to this limitation is ‘Organisational Cognitive Neuroscience’ – the study of the cognitive neuroscience of human behaviour in, and in response to, organizations. Given that all of us will spend most of our lives in some sort of work related organisation, organisational cognitive neuroscience allows us to examine the cognitive underpinnings of social behaviour that occurs in what may be our most natural ecology. Here we provide a brief overview of this approach, a definition and also some possible questions that the new approach would be best suited to address.

The social cognitive neuroscience of organisations

Social cognitive neuroscience is an emerging branch of cognitive neuroscience that bridges together social psychology and neuroscience. At its core is an understanding of the relationship between the brain and social interaction. The social cognitive neuroscientist places empirical endeavor within a three–stage framework, and questions falling under the SCN rubric undergo interrogation at each of these three levels. Firstly, we seek to understand a neuroscience of social interactions at the social level. Here we need to understand the motivational and other social factors that drive our behavior and experience in the real world. It goes without saying that any study of the cognitive neuroscience of socially interactive behavior must first be informed by social psychological theory to maintain ecological validity. Second, the social cognitive neuroscientist must be an adroit cognitive psychologist and be able to examine interactive behavior from the cognitive level. It is here that information–processing models and theories are applied to the understanding of our social behavior. Finally, studies at the neural level seek to inform us about the cortical structures, as well as the way they interact with other, in the mediation of the previous cognitive level. This volume brings together contributions from leading thinkers in both the social cognitive neurosciences and business to provide a comprehensive introduction and overview of a social cognitive neuroscience of the business brain. NOTE: Annals volumes are available for sale as individual books or as a journal. For information on institutional journal subscriptions, please visit www.blackwellpublishing.com/nyas. ACADEMY MEMBERS: Please contact the New York Academy of Sciences directly to place your order (www.nyas.org). Members of the New York Academy of Science receive full–text access to the Annals online and discounts on print volumes. Please visit http://www.nyas.org/MemberCenter/Join.aspx for more information about becoming a member

Research possibilities for organisational cognitive neuroscience

In this article, we identify research possibilities for organizational cognitive neuroscience that emerge from the papers in this special issue. We emphasize the intriguing finding that the papers share a common theme-the use of cognitive neuroscience to investigate the role of emotions in organizational behavior; this suggests a research agenda in its own right. We conclude the article by stressing that there is much yet to discover about how the mind works, especially in organizational settings.