Cognitive Association Formation in Human Memory Revealed by Spatiotemporal Brain Imaging

Kounios, John; Smith, Roderick W.; Yang, Wei; Bachman, Peter; D’Esposito, Mark

doi:10.1016/s0896-6273(01)00199-4

Cited by 55 publications

(33 citation statements)

References 33 publications

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“…Even when the estimated activity in deeper brain regions is unrealistically small, statistical analysis can reveal whether differences between experimental conditions are reliable. In this way, for example, differential activity in the thalamus was previously reported in a memory task (Kounios et al, 2001).…”

Section: Methodological Considerationsmentioning

confidence: 62%

Non-retinotopic feature integration decreases response-locked brain activity as revealed by electrical neuroimaging

et al. 2009

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When presented with dynamic scenes, the brain integrates visual elements across space and time. Such nonretinotopic processing has been intensively studied from a psychophysical point of view, but little is known about the underlying neural processes. Here we used high-density EEG to reveal neural correlates of nonretinotopic feature integration. In an offset-discrimination task we presented sequences of lines for which feature integration depended on a small, endogenous shift of attention. Attention effects were observed in the stimulus-locked evoked potentials but non-retinotopic feature integration was reflected in voltage topographies time-locked to the behavioral response, lasting for about 400 ms. Statistical parametric mapping of estimated current densities revealed that this integration reduced electrical activity in an extensive network of brain areas, with the effects progressing from high-level visual, via frontal, to central ones. The results suggest that endogenously timed neural processes, rather than bottom-up ones, underlie non-retinotopic feature integration.

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Section: Methodological Considerationsmentioning

confidence: 62%

Non-retinotopic feature integration decreases response-locked brain activity as revealed by electrical neuroimaging

et al. 2009

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“…To assess activity during encoding that predicted later priming, we used a Dm approach to examine ERPs during the study phase as a function of response speed during the subsequent test. The two study conditions were laterfastest and later-slowest, with each individual trial categorized based on each subject's median-split on response times during the test, as above (a method similar to that used by Kounios et al, 2001). Response times for these categories did not differ significantly during study [later-fastest mean ϭ 1260, later-slowest mean ϭ 1268, t (15) ϭ 0.6, p ϭ 0.56].…”

Section: Electrophysiological Findings During Studymentioning

confidence: 99%

Real-Time Neural Signals of Perceptual Priming with Unfamiliar Geometric Shapes

Voss¹,

Paller²

2010

Journal of Neuroscience

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Perceptual priming is a type of item-specific implicit memory that is distinct from explicit memory. Neural signals of the processing responsible for perceptual priming can be difficult to isolate due to concurrent conceptual processing and explicit recognition. We successfully identified neural correlates of perceptual priming by using minimally meaningful, difficult-to-recognize, kaleidoscope images. Human participants were required to quickly indicate the number of colors present in each stimulus, and priming was shown by faster and more accurate visual discriminations for repeated compared with initial presentations. Electroencephalographic responses linked with this differential perceptual fluency were identified as negative potentials 100 -300 ms poststimulus onset. Furthermore, different potentials recorded during initial presentations were indicative of perceptual learning, in that their amplitude predicted the magnitude of later priming. These electrophysiological findings show that the degree of perceptual learning engaged upon first encountering a novel visual stimulus predicts the degree of perceptual fluency experienced when the stimulus is processed a second time. It is thus possible to isolate multiple neural processing stages relevant to perceptual priming by using real-time measures of relevant neurophysiological activity in conjunction with experimental circumstances that limit the contaminating influences of other neurocognitive events.

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“…It is based on two constraints: it searches for the smoothest of all possible solutions, using cortical gray matter and the hippocampus of the Talairach human brain model. In the past 5 years, this tomography approach has been used in several neuroscience studies (for example, see Gomez et al, 2003;Kounios et al, 2001;Mulert et al, 2001;Pizzagalli et al, 2001). The LORETA version used in this study reconstructed the sources of activation in 2394 voxels distributed in the Talairach human brain (Pascual-Marqui, 1999).…”

Section: Introductionmentioning

confidence: 99%

Combined ICA-LORETA analysis of mismatch negativity

Marco-Pallarés

Grau

Ruffini³

2005

NeuroImage

222

152

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A major challenge for neuroscience is to map accurately the spatiotemporal patterns of activity of the large neuronal populations that are believed to underlie computing in the human brain. To study a specific example, we selected the mismatch negativity (MMN) brain wave (an event-related potential, ERP) because it gives an electrophysiological index of a bprimitive intelligenceQ capable of detecting changes, even abstract ones, in a regular auditory pattern. ERPs have a temporal resolution of milliseconds but appear to result from mixed neuronal contributions whose spatial location is not fully understood. Thus, it is important to separate these sources in space and time. To tackle this problem, a two-step approach was designed combining the independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. Here we implement this approach to analyze the subsecond spatiotemporal dynamics of MMN cerebral sources using trial-by-trial experimental data. We show evidence that a cerebral computation mechanism underlies MMN. This mechanism is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, which activate at distinct time intervals and are grouped in six main statistically independent components. D 2004 Elsevier Inc. All rights reserved.

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Cognitive Association Formation in Human Memory Revealed by Spatiotemporal Brain Imaging

Cited by 55 publications

References 33 publications

Non-retinotopic feature integration decreases response-locked brain activity as revealed by electrical neuroimaging

Non-retinotopic feature integration decreases response-locked brain activity as revealed by electrical neuroimaging

Real-Time Neural Signals of Perceptual Priming with Unfamiliar Geometric Shapes

Combined ICA-LORETA analysis of mismatch negativity

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