Biology subjects

Tsuchiya, N.

Publications and source records attributed to Tsuchiya, N..

27 records · Page 2Linked to original sources

bioRxiv2019

A general spectral decomposition of causal influences applied to integrated information

Quantifying causal influences between elements of a system remains a central topic in many fields of research. In neuroscience, causal influences among neurons, quantified as integrated information, have been suggested to play a critical role in supporting subjective conscious experience. Recent empirical work has shown that the spectral decomposition of causal influences can reveal frequency-specific influences that are not observed in the time-domain. To date however, a spectral decomposition of integrated information has not been put forward. In this paper, we propose a spectral decomposition of integrated information in linear autoregressive processes. Our proposal is based on a general and flexible framework for deriving the spectral decompositions of causal influences in autoregressive processes. We show that the framework can retrieve the spectral decompositions of other well-known measures such as Granger causality. In simulation, we demonstrate a complex interplay between the spectral decomposition of integrated information and other measures that is not observed in the time-domain. We propose that the spectral decomposition of integrated information will be particularly useful when the underlying frequency-specific causal influences are masked in the time-domain. The proposed method opens the door for empirically investigating the relevance of integrated information to subjective conscious experience in a frequency-specific manner.\n\nAuthor summaryUnderstanding how different parts of the brain influence each other is fundamental to neuroscience. Integrated information measures overall causal influences in the brain and has been theorized to directly relate to subjective consciousness experience. For example, integrated information is predicted to be high during wakefulness and low during sleep or general anesthesia. At the same time, neural activity is characterized by well-known spectral signatures. For example, there is a prominent increase in low frequency power of neural activity during sleep and general anesthesia. Taking account of the spectral characteristics of neural activity, it is important to separately quantify integrated information at each frequency. In this paper, we propose a method for decomposing integrated information in the frequency domain. The proposed framework is general and can be used to derive the spectral decomposition of other well-known measures such as Granger causality. The spectral decomposition of integrated information we propose will allow empirically investigating the relationship between neural spectral signatures, integrated information and subjective consciousness experience.

neuroscience↗

bioRxiv2019

Surprising threats accelerate evidence accumulation for conscious perception

Our survival depends on how well we can rapidly detect threats in our environment. To facilitate this, the brain is faster to bring threatening or rewarding visual stimuli into conscious awareness than neutral stimuli. Unexpected events may indicate a potential threat, and yet we tend to respond slower to unexpected than expected stimuli. It is unclear if or how these effects of emotion and expectation interact with ones conscious experience. To investigate this, we presented neutral and fearful faces with different probabilities of occurance in a breaking continuous flash suppression (bCFS) paradigm. Across two experiments, we discovered that fulfilled prior expectations hastened responses to neutral faces but had either no significant effect (Experiment 1) or the opposite effect (Experiment 2) on fearful faces. Drift diffusion modelling revealed that, while prior expectations accelerated stimulus encoding time (associated with the visual cortex), evidence was accumulated at an especially rapid rate for unexpected fearful faces (associated with activity in the right inferior frontal gyrus). Hence, these findings demonstrate a novel interaction between emotion and expectation during bCFS, driven by a unique influence of surprising fearful stimuli that expedites evidence accumulation in a fronto-occipital network.

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bioRxiv2018

Frequency-tagging visual background information enables multi-target perceptual filling-in to be distinguished from phenomenally matched replay

Perceptual filling-in (PFI) occurs when a physically-present visual target disappears from conscious perception, with its location filled in by the surrounding visual background. Compared to other visual illusions, these perceptual changes are crisp and simple, and can occur for multiple spatially-separated targets simultaneously. Contrasting neural activity during the presence or absence of PFI may complement other multistable phenomena to reveal the neural correlates of consciousness (NCC). We presented four peripheral targets over a background dynamically updating at 20 Hz. While participants reported on target disappearances/reappearances via button press/release, we tracked neural activity entrained by the background during PFI using steady-state visually evoked potentials (SSVEPs) recorded in the electroencephalogram. We found background SSVEPs closely correlated with subjective report, and increased with an increasing amount of PFI. Unexpectedly, we found that as the number of filled-in targets increased, the duration of target disappearances also increased, suggesting facilitatory interactions exist between targets in separate visual quadrants. We also found distinct spatiotemporal correlates for the background SSVEP harmonics. Prior to genuine PFI, the response at the second harmonic (40 Hz) increased before the first (20 Hz), which we tentatively link to an attentional effect. There was no difference between harmonics for physically removed stimuli. These results demonstrate that PFI can be used to study multi-object perceptual suppression when frequency-tagging the background of a visual display, and because there are distinct neural correlates for endogenously and exogenously induced changes in consciousness, that it is ideally suited to study the NCC.\n\nHighlightsO_LIPerceptual filling-in (PFI) has distinct advantages for investigating the neural correlates of consciousness.\nC_LIO_LIParticipants can accurately report graded changes in consciousness using four simultaneous buttons.\nC_LIO_LIFrequency-tagging of visual background information tracks changes in visual perception.\nC_LIO_LISpatiotemporal EEG responses differentiate PFI from phenomenally matched physical disappearances.\nC_LI

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bioRxiv2018

Expectation and attention increase the integration of top-down and bottom-up signals in perception through different pathways

Perception results from the integration of incoming sensory information with pre-existing information available in the brain. In this EEG (electroencephalography) study we utilised the Hierarchical Frequency Tagging method to examine how such integration is modulated by expectation and attention. Using intermodulation (IM) components as a measure of non-linear signal integration, we show in three different experiments that both expectation and attention enhance integration between top-down and bottom-up signals. Based on multispectral phase coherence, we present two direct physiological measures to demonstrate the distinct yet related mechanisms of expectation and attention. Specifically, our results link expectation to the modulation of prediction signals and the integration of top-down and bottom-up information at lower levels of the visual hierarchy. Meanwhile, they link attention to the propagation of ascending signals and the integration of information at higher levels of the visual hierarchy. These results are consistent with the predictive coding account of perception.

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bioRxiv2018

Attention periodically samples competing stimuli during binocular rivalry

The attentional sampling hypothesis suggests that attention rhythmically enhances sensory processing when attending to a single (~8 Hz), or multiple (~4 Hz) objects. Here we investigated using binocular rivalry whether attention samples sensory representations that are not part of the conscious percept, during competition for perceptual dominance. When crossmodally cued toward a conscious image, subsequent changes in consciousness occurred at ~8 Hz, consistent with rates of undivided attentional sampling. However, when attention was cued toward the suppressed image, changes in consciousness slowed to ~3.5 Hz, indicating the division of attention away from the conscious visual image. In the electroencephalogram, we found that at 3.5 and 8 Hz, the strength of inter-trial phase coherence over fronto-temporal and parieto-occipital regions correlated with behavioral measures of changes in perception. When cues were not task-relevant, these effects disappeared, confirming that perceptual changes were dependent upon the allocation of attention, and that attention can flexibly sample away from a conscious image in a task-dependent manner.

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bioRxiv2017

Deep Brain Stimulation for Parkinson’s disease changes perception in the Rubber Hand Illusion

Parkinsons disease (PD) alters cortico-basal ganglia-thalamic circuitry and susceptibility to an illusion of bodily awareness, the Rubber Hand Illusion (RHI). Bodily awareness is thought to result from multisensory integration in a predominantly cortical network; the role of subcortical connections is unknown. We studied the effect of modulating cortico-subcortical circuitry on multisensory integration for bodily awareness in PD patients treated with subthalamic nucleus (STN) deep brain stimulation (DBS) using the RHI experiment. Typically, synchronous visuo-tactile cues induce a false perception of touch on the rubber hand as if it were the subjects hand, whereas asynchronous visuo-tactile cues do not. However, we found that in the asynchronous condition, patients in the off-stimulation state did not reject the RHI as strongly as healthy controls; switching on STN-DBS partially normalised their responses. Patients in the off-stimulation state also misjudged the position of their hand, indicating it to be closer to the rubber hand than controls. However, STN-DBS did not affect proprioceptive judgements or subsequent arm movements altered by the perceptual effects of the illusion. Our findings support the idea that the STN and subcortical connections have a key role in multisensory integration for bodily awareness. Decisionmaking in multisensory bodily illusions is discussed.

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bioRxiv2017

A unified framework for dissecting the effects of common signals on functional and effective connectivity analyses: power, coherence, and Granger causality

When analyzing neural data it is important to consider the limitations of the particular experimental setup. An enduring issue in the context of electrophysiology is the presence of common signals. For example a non-silent reference electrode adds a common signal across all recorded data and this adversely affects functional and effective connectivity analysis. To address the common signals problem, a number of methods have been proposed, but relatively few detailed investigations have been carried out. We address this gap by analyzing local field potentials recorded from the small brains of fruit flies. We conduct our analysis following a solid mathematical framework that allows us to make precise predictions regarding the nature of the common signals. We demonstrate how a framework that jointly analyzes power, coherence and quantities from the Granger causality framework allows us to detect and assess the nature of the common signals. Our analysis revealed substantial common signals in our data, in part due to a non-silent reference electrode. We further show that subtracting spatially adjacent signals (bipolar rereferencing) largely removes the effects of the common signals. However, in some special cases this operation itself introduces a common signal. The mathematical framework and analysis pipeline we present can readily be used by others to detect and assess the nature of the common signals in their data, thereby reducing the chance of misinterpreting the results of functional and effective connectivity analysis.

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bioRxiv2017

Isoflurane reduces feedback in the fruit fly brain

Hierarchically organized brains communicate through feedforward and feedback pathways. In mammals, feedforward and feedback are mediated by higher and lower frequencies during wakefulness. Feedback is preferentially impaired by general anesthetics. This suggests feedback serves critical functions in waking brains. The brain of Drosophila melanogaster (fruit fly) is also hierarchically organized, but the presence of feedback in these brains is not established. Here we studied feedback in the fruit fly brain, by simultaneously recording local field potentials (LFPs) from low-order peripheral structures and higher-order central structures. Directed connectivity analysis revealed that low frequencies (0.1-5Hz) mediated feedback from the center to the periphery, while higher frequencies (10-45Hz) mediated feedforward in the opposite direction. Further, isoflurane anesthesia preferentially reduced feedback. Our results imply that similar spectral characteristics of feedforward and feedback may be a signature of hierarchically organized brains and that general anesthetics may induce unresponsiveness by targeting the mechanisms that support feedback.

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bioRxiv2016

Hierarchical Frequency Tagging reveals neural markers of predictive coding under varying uncertainty

Understanding the integration of top-down and bottom-up signals is essential for the study of perception. Current accounts of predictive coding describe this in terms of interactions between state units encoding expectations or predictions, and error units encoding prediction error. However, direct neural evidence for such interactions has not been well established. To achieve this, we combined EEG methods that preferentially tag different levels in the visual hierarchy: Steady State Visual Evoked Potential (SSVEP at 10Hz, tracking bottom-up signals) and Semantic Wavelet-Induced Frequency Tagging (SWIFT at 1.3Hz tracking top-down signals). Importantly, we examined intermodulation components (IM, e.g., 11.3Hz) as a measure of integration between these signals. To examine the influence of expectation and predictions on the nature of such integration, we constructed 50-second movie streams and modulated expectation levels for upcoming stimuli by varying the proportion of images presented across trials. We found SWIFT, SSVEP and IM signals to differ in important ways. SSVEP was strongest over occipital electrodes and was not modified by certainty. Conversely, SWIFT signals were evident over temporo- and parieto-occipital areas and decreased as a function of increasing certainty levels. Finally, IMs were evident over occipital electrodes and increased as a function of certainty. These results link SSVEP, SWIFT and IM signals to sensory evidence, predictions, prediction errors and hypothesis-testing - the core elements of predictive coding. These findings provide neural evidence for the integration of top-down and bottom-up information in perception, opening new avenues to studying such interactions in perception while constraining neuronal models of predictive coding.\n\nSIGNIFICANCE STATEMENTThere is a growing understanding that both top-down and bottom-up signals underlie perception. But how do these signals interact? And how does this process depend on the signals probabilistic properties? Predictive coding theories of perception describe this in terms how well top-down predictions fit with bottom-up sensory input. Identifying neural markers for such signal integration is therefore essential for the study of perception and predictive coding theories in particular. The novel Hierarchical Frequency Tagging method simultaneously tags top-down and bottom-up signals in EEG recordings, while obtaining a measure for the level of integration between these signals. Our results suggest that top-down predictions indeed integrate with bottom-up signals in a manner that is modulated by the predictability of the sensory input.

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