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Todorova, L.

Publications and source records attributed to Todorova, L..

3 recordsLinked to original sources

Overlapping Neural Representations for Dynamic Visual Imagery and Stationary Storage in Spatial Working Memory

Representations in working memory need to be flexibly transformed to adapt to our dynamic environment and variable task demands. Recent work has demonstrated that activity in the alpha frequency band enables precise decoding of visual information during both perception and sustained storage in working memory. Extant work, however, has focused exclusively on the representation of static visual images. Here we used EEG recordings to examine whether alpha-band activity supports the dynamic transformation of representations in spatial working memory using an imagery task that required the active shifting of a stored position to a new position. In line with recent findings, a common format of alpha-band activity precisely tracked both the initial position stored in working memory as well as the transformed position, with the latter emerging approximately 800-1200 ms following an auditory cue to "rotate" to a new position. Moreover, the time course of this transformation of alpha activity predicted between-subject differences in manual reaction time to indicate the new position (Experiment 1), as well as within-subject variations in saccade latency in a speeded version of the task (Experiment 2). Finally, cross-training analyses revealed robust generalization of alpha-band reconstruction of working memory contents before and after mental transformation. These findings demonstrate that alpha activity tracks dynamic transformations of representations in spatial working memory, and that the format of this activity is preserved across the initial and transformed memory representations. These findings highlight a new approach for measuring voluntary shifts in online memory representations and show common representational formats during dynamic mental imagery and the maintenance of static representations in working memory.

neuroscience↗

Time-delay model of perceptual decision making in cortical networks

It is known that cortical networks operate on the edge of instability, in which oscillations can appear. However, the influence of this dynamic regime on performance in decision making, is not well understood. In this work, we propose a population model of decision making based on a winner-take-all mechanism. Using this model, we demonstrate that local slow inhibition within the competing neuronal populations can lead to Hopf bifurcation. At the edge of instability, the system exhibits ambiguity in the decision making, which can account for the perceptual switches observed in human experiments. We further validate this model with fMRI datasets from an experiment on semantic priming in perception of ambivalent (male versus female) faces. We demonstrate that the model can correctly predict the drop in the variance of the BOLD within the Superior Parietal Area and Inferior Parietal Area while watching ambiguous visual stimuli.\n\nAuthor summaryHuman cortex is a complex structure composed of thousands of tangled neural circuits. These circuits exhibit multiple modes of activity, depending on the local balance between excitatory and inhibitory activity. In particular, these circuits can exhibit oscillatory behavior, which is believed to be a manifestation of a so-called criticality: balancing on the edge between stable and unstable dynamics. Circuits in the cortex are responsible for higher cognitive functions such as, in example, perceptual decision making, i.e., evaluating properties of objects appearing in the visual field. However, it is not well known how aforementioned balancing on the edge of instability influences perceptual decision making.\n\nIn this work, we build a model to simulate dynamics of a very simple decision-making network consisting of two subpopulations. We then demonstrate that criticality in the network can account for ambiguity in decision making, and cause perceptual switches observed in human experiments. We further validate our model with datasets coming from a functional Magnetic Resonance Imaging experiment on semantic priming in perception of ambivalent (male versus female) faces. We demonstrate that the model can correctly predict the drop in the variance of the BOLD within the parietal areas of the cortex while watching ambiguous visual stimuli.

neuroscience↗

Eye movement-related confounds in neural decoding of visual working memory representations

The study of visual working memory (VWM) has recently seen revitalization with the emergence of new insights and theories regarding its neural underpinnings. One crucial ingredient responsible for this progress is the rise of neural decoding techniques. These techniques promise to uncover the representational contents of neural signals, as well as the underlying code and the dynamic profile thereof. Here, we aimed to contribute to the field by subjecting human volunteers to a combined VWM/imagery task, while recording and decoding their neural signals as measured by MEG. At first sight, the results seem to provide evidence for a persistent, stable representation of the memorandum throughout the delay period. However, control analyses revealed that these findings can be explained by subtle, VWM-specific eye movements. As a potential remedy, we demonstrate the use of a functional localizer, which was specifically designed to target bottom-up sensory signals and as such avoids eye movements, to train the neural decoders. This analysis revealed a sustained representation for approximately 1 second, but no longer throughout the entire delay period. We conclude by arguing for more awareness of the potentially pervasive and ubiquitous effects of eye movement-related confounds.\n\nSignificance statementVisual working memory is an important aspect of higher cognition and has been subject of much investigation within the field of cognitive neuroscience. Over recent years, these studies have increasingly relied on the use of neural decoding techniques. Here, we show that neural decoding may be susceptible to confounds induced by stimulus-specific eye movements. Such eye movements during working memory have been reported before, and may in fact be a common phenomenon. Given the widespread use of neural decoding and the potentially contaminating effects of eye movements, we therefore believe that our results are of significant relevance for the field.

neuroscience↗