2,369 research outputs found
Stimulus predictability reduces responses in primary visual cortex
No full textIn this functional magnetic resonance imaging study we tested whether the predictability of stimuli affects responses in primary visual cortex (V1). The results of this study indicate that visual stimuli evoke smaller responses in V1 when their onset or motion direction can be predicted from the dynamics of surrounding illusory motion. We conclude from this finding that the human brain anticipates forthcoming sensory input that allows predictable visual stimuli to be processed with less neural activation at early stages of cortical processing
CEREBRUM-7T: fast and fully volumetric brain segmentation of 7 Tesla MR volumes
No full textUltra-high-field magnetic resonance imaging (MRI) enables sub-millimetre resolution imaging of the human brain, allowing the study of functional circuits of cortical layers at the meso-scale. An essential step in many functional and structural neuroimaging studies is segmentation, the operation of partitioning the MR images in anatomical structures. Despite recent efforts in brain imaging analysis, the literature lacks in accurate and fast methods for segmenting 7-tesla (7T) brain MRI. We here present CEREBRUM-7T, an optimised end-to-end convolutional neural network, which allows fully automatic segmentation of a whole 7T T1w MRI brain volume at once, without partitioning the volume, pre-processing, nor aligning it to an atlas. The trained model is able to produce accurate multi-structure segmentation masks on six different classes plus background in only a few seconds. The experimental part, a combination of objective numerical evaluations and subjective analysis, confirms that the proposed solution outperforms the training labels it was trained on and is suitable for neuroimaging studies, such as layer functional MRI studies. Taking advantage of a fine-tuning operation on a reduced set of volumes, we also show how it is possible to effectively apply CEREBRUM-7T to different sites data. Furthermore, we release the code, 7T data, and other materials, including the training labels and the Turing test
Transfer of predictive signals across saccades
No full textPredicting visual information facilitates efficient processing of visual signals. Higher visual areas can support the processing of incoming visual information by generating predictive models that are fed back to lower visual areas. Functional brain imaging has previously shown that predictions interact with visual input already at the level of the primary visual cortex (V1; Harrison et al., 2007; Alink et al., 2010). Given that fixation changes up to four times a second in natural viewing conditions, cortical predictions are effective in V1 only if they are fed back in time for the processing of the next stimulus and at the corresponding new retinotopic position. Here, we tested whether spatio-temporal predictions are updated before, during, or shortly after an inter-hemifield saccade is executed, and thus, whether the predictive signal is transferred swiftly across hemifields. Using an apparent motion illusion, we induced an internal motion model that is known to produce a spatio-temporal prediction signal along the apparent motion trace in V1 (Muckli et al., 2005; Alink et al., 2010). We presented participants with both visually predictable and unpredictable targets on the apparent motion trace. During the task, participants saccaded across the illusion whilst detecting the target. As found previously, predictable stimuli were detected more frequently than unpredictable stimuli. Furthermore, we found that the detection advantage of predictable targets is detectable as early as 50–100 ms after saccade offset. This result demonstrates the rapid nature of the transfer of a spatio-temporally precise predictive signal across hemifields, in a paradigm previously shown to modulate V1
Fighting the Scanner Effect: a Coarse-to-Fine 3D Network for Multi-Site Brain MRI Segmentation
No full textCEREBRUM: a fast and fully-volumetric Convolutional Encoder-decodeR for weakly-supervised sEgmentation of BRain strUctures from out-of-the-scanner MRI
No full textMany functional and structural neuroimaging studies call for accurate morphometric segmentation of different brain structures starting from image intensity values of MRI scans. Current automatic (multi-) atlas-based segmentation strategies often lack accuracy on difficult-to-segment brain structures and, since these methods rely on atlas-to-scan alignment, they may take long processing times. Alternatively, recent methods deploying solutions based on Convolutional Neural Networks (CNNs) are enabling the direct analysis of out-of-the-scanner data. However, current CNN-based solutions partition the test volume into 2D or 3D patches, which are processed independently. This process entails a loss of global contextual information, thereby negatively impacting the segmentation accuracy. In this work, we design and test an optimised end-to-end CNN architecture that makes the exploitation of global spatial information computationally tractable, allowing to process a whole MRI volume at once. We adopt a weakly supervised learning strategy by exploiting a large dataset composed of 947 out-of-the-scanner (3 Tesla T1-weighted 1mm isotropic MP-RAGE 3D sequences) MR Images. The resulting model is able to produce accurate multi-structure segmentation results in only a few seconds. Different quantitative measures demonstrate an improved accuracy of our solution when compared to state-of-the-art techniques. Moreover, through a randomised survey involving expert neuroscientists, we show that subjective judgements favour our solution with respect to widely adopted atlas-based software
Reptricket. Förord till Lars Gustafsson: Mot noll
No full textIntroduction to a collection of philosophical essays by Swedish author Lars Gustafsson (b. 1936)
Contributions of cortical feedback to sensory processing in primary visual cortex
No full textClosing the structure-function divide is more challenging in the brain than in any other organ (Lichtman and Denk, 2011). For example, in early visual cortex, feedback projections to V1 can be quantified (e.g., Budd, 1998) but the understanding of feedback function is comparatively rudimentary (Muckli and Petro, 2013). Focusing on the function of feedback, we discuss how textbook descriptions mask the complexity of V1 responses, and how feedback and local activity reflects not only sensory processing but internal brain states
Author Functions in Lars Kepler\u27s The Hypnotist: An Analysis
No full textThis paper examines Foucault\u27s notion of the author function as it pertains to Lars Kepler\u27s bestselling 2011 crime thriller, The Hypnotist. Lars Kepler is the pseudonym of a Swedish husband-wife writing duo, making him the perfect subject for analysis centering on illusory notion of the author. This paper will answer these questions: Who is the true author of The Hypnotist? What factors influence the author function of this bestelling novel? And what can The Hypnotist phenomenon tell us about the relationships between authors and their readers? This paper will demonstrate that no literary works may be ascribed to an individual person, and that authors hold no privileged knowledge of the works they produce, because authors cease to be authors the moment pen is lifted from page
Nonstimulated early visual areas carry information about surrounding context
No full textEven within the early sensory areas, the majority of the input to any given cortical neuron comes from other cortical neurons. To extend our knowledge of the contextual information that is transmitted by such lateral and feedback connections, we investigated how visually nonstimulated regions in primary visual cortex (V1) and visual area V2 are influenced by the surrounding context. We used functional magnetic resonance imaging (fMRI) and pattern-classification methods to show that the cortical representation of a nonstimulated quarter-field carries information that can discriminate the surrounding visual context. We show further that the activity patterns in these regions are significantly related to those observed with feed-forward stimulation and that these effects are driven primarily by V1. These results thus demonstrate that visual context strongly influences early visual areas even in the absence of differential feed-forward thalamic stimulation
Separate cortical stages in amodal completion revealed by functional magnetic resonance adaptation
No full textBackground:
Objects in our environment are often partly occluded, yet we effortlessly perceive them as whole and complete. This phenomenon is called visual amodal completion. Psychophysical investigations suggest that the process of completion starts from a representation of the (visible) physical features of the stimulus and ends with a completed representation of the stimulus. The goal of our study was to investigate both stages of the completion process by localizing both brain regions involved in processing the physical features of the stimulus as well as brain regions representing the completed stimulus.
Results:
Using fMRI adaptation we reveal clearly distinct regions in the visual cortex of humans involved in processing of amodal completion: early visual cortex – presumably V1 -processes the local contour information of the stimulus whereas regions in the inferior temporal cortex represent the completed shape. Furthermore, our data suggest that at the level of inferior temporal cortex information regarding the original local contour information is not preserved but replaced by the representation of the amodally completed percept.
Conclusion:
These findings provide neuroimaging evidence for a multiple step theory of amodal completion and further insights into the neuronal correlates of visual perception
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