Donner Lab

@donner_lab

The goal of our research is to understand how brain states shape decision-making, and how this process goes awry in certain neurological & psychiatric disorders

Vrijeme pridruživanja: listopad 2015.

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  1. Prikvačeni tweet
    31. sij

    Interested in decision-making, evidence accumulation, normative or circuit models, oscillations, cortical hierarchy, feedback, or brainstem arousal systems? Check out our new paper on ()! Led by , summary below. (1/11)

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  2. prije 16 sati

    Our results also challenge the dominant feedforward framework of perceptual decision-making, and establish a new link between evidence accumulation and the frequency bands of cortical population activity. (10/10)

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  3. prije 16 sati

    Our findings are the first physiological confirmation of key predictions from cortical circuit models for decision-making with feedback from decision to sensory stage () (9/10)

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  4. prije 16 sati

    Indeed, we found that V1-gamma reflected the feedforward influence of contrast information on choice; V1-alpha was unrelated to the stimulus, but mirrored (with 100 ms delay) the build-up of choice-predictive activity in motor cortex. (8/10)

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  5. prije 16 sati

    We then tested for choice-predictive activity fluctuations (“choice probability”) in V1, as a function of different frequency bands. Gamma-band activity has been linked with feedforward and alpha-band activity with feedback signalling ()(7/10)

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  6. prije 16 sati

    The observed dynamics of sensory and choice information across cortex was consistent with an accumulation of evidence provided by V1 into an action plan formed in parietal and motor cortex. (6/11)

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  7. prije 16 sati

    Activity in the latter, action-related regions also reliably predicted the ensuing choice, in a way that built up over time. (5/11)

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  8. prije 16 sati

    Instantaneous ‘sensory evidence’ (contrast information) was encoded in early visual cortex (including V1), whereas accumulated evidence was encoded in parietal and motor regions involved in action planning. (4/10)

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  9. prije 16 sati

    We asked human subjects to accumulate fluctuating contrast information towards a categorical choice. They overweighted early relative to late contrast samples, as is often observed in such tasks. (3/10)

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  10. prije 16 sati

    We developed an MEG approach to track the dynamics of sensory and choice-related activity during perceptual decision-making across cortex. We then used this approach to pinpoint feedback of choice-related activity to sensory cortex (2/10).

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  11. prije 16 sati

    New from the lab () that shows choice-predictive feedforward/back signals in V1! Led by . Relevant for anyone interested in , , , . Thread. (1/10)

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  12. proslijedio/la je Tweet
    3. velj

    New out on ! \w , , Nicole de Ru & Sander Nieuwenhuis, we show that temporal expectation enhances perception by speeding up the the decision process onset without affecting its evolution! below (1/10)

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  13. 31. sij

    Our insights link computations for adaptive decision-making with large-scale neural mechanisms for their implementation: normative evidence accumulation in a changing world emerges from the interplay of cortical circuit dynamics and neuromodulatory input. (11/11)

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  14. 31. sij

    Changes in environmental state were also closely tracked by pupil-linked arousal, which in turn modulated evidence-encoding signatures in behavior and cortical dynamics. (10/11)

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  15. 31. sij

    The measured accumulation behavior and dynamics of choice-predictive activity emerged naturally from the non-linear dynamics of an established, biophysically-detailed model of cortical decision circuits. (9/11)

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  16. 31. sij

    Visual cortical alpha-band activity reflected selective feedback of the decision variable, most prominently the late activity in primary visual cortex (V1). (8/11)

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  17. 31. sij

    Evidence and decision variable encoding were widely also distributed across the visual cortical hierarchy, and expressed in distinct frequency bands. Visual cortical gamma-band activity encoded sensory evidence. (7/11)

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  18. 31. sij

    Regions in posterior parietal and (pre-)motor cortex involved in action planning closely tracked the normative decision variable, with modulation of evidence encoding by surprise and uncertainty. (6/11)

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  19. 31. sij

    We combined multi-area recordings (via atlas-based MEG), pupillometry, and cortical circuit modelling to illuminate the large-scale mechanisms underlying the adaptive accumulation process. (5/11)

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  20. 31. sij

    Surprise and uncertainty modulated the evidence accumulation of human subjects in a task with hidden changes in environmental state. The normative model fitted human behavior better than several alternative, widely used models. (4/11)

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  21. 31. sij

    A normative model of decision-making in this context entails a non-linear accumulation of evidence. We show that this non-linearity can be expressed as heightened sensitivity to evidence that is surprising or encountered under uncertainty. (3/11)

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