Prediction-error signals to violated expectations about person identity and head orientation are doubly-dissociated across the dorsal and ventral visual streams

AbstractPredictive coding theories of perception suggest the importance of constantly updated internal models of the world in predicting future sensory inputs. One implication of such models is that cortical regions whose function is to resolve particular stimulus attributes should also signal prediction violations with respect to those same stimulus attributes. Previously, through carefully designed experiments, we have demonstrated early-mid latency EEG/MEG prediction-error signals in the dorsal visual stream to violated expectations about stimulus orientation/trajectory, with localisations consistent with cortical areas processing motion and orientation. Here we extend those methods to simultaneously investigate the predictive processes in both dorsal and ventral visual streams. In this MEG study we employed a contextual trajectory paradigm that builds expectations using a series of image presentations. We created expectations about both face orientation and identity, either of which can subsequently be violated. Crucially this paradigm allows us to parametrically test double dissociations between these different types of violations. The study identified double dissociations across the type of violation in the dorsal and ventral visual streams, such that the right fusiform gyrus showed greater evidence of prediction-error signals to Identity violations than to Orientation violations, whereas the left angular gyrus and postcentral gyrus showed the opposite pattern of results. Our results suggest comparable processes for error checking and context updating in high-level expectations instantiated across both perceptual streams. Perceptual prediction-error signalling is initiated in regions associated with the processing of different stimulus properties.Significance StatementVisual processing occurs along ‘what’ and ‘where’ information streams that run, respectively along the ventral and dorsal surface of the posterior brain. Predictive coding models of perception imply prediction-error detection processes that are instantiated at the level where particular stimulus attributes are parsed. This implies that, for instance, when considering face stimuli, signals arising through violated expectations about the person identity of the stimulus should localise to the ventral stream, whereas signals arising through violated expectations about head orientation should localise to the dorsal stream. We test this in a magnetoencephalography source localisation study. The analysis confirmed that prediction-error signals to identity versus head-orientation occur with similar latency, but activate doubly-dissociated brain regions along ventral and dorsal processing streams.

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Prediction-error signals to violated expectations about person identity and head orientation are doubly-dissociated across dorsal and ventral visual stream regions

NeuroImage ◽

10.1016/j.neuroimage.2019.116325 ◽

2020 ◽

Vol 206 ◽

pp. 116325 ◽

Cited By ~ 2

Author(s):

Jonathan E. Robinson ◽

Will Woods ◽

Sumie Leung ◽

Jordy Kaufman ◽

Michael Breakspear ◽

...

Keyword(s):

Prediction Error ◽

Head Orientation ◽

Visual Stream ◽

Person Identity ◽

Ventral Visual Stream ◽

Violated Expectations

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Differential neural mechanisms for early and late prediction error detection

Scientific Reports ◽

10.1038/srep24350 ◽

2016 ◽

Vol 6 (1) ◽

Cited By ~ 4

Author(s):

Rahim Malekshahi ◽

Anil Seth ◽

Amalia Papanikolaou ◽

Zenon Mathews ◽

Niels Birbaumer ◽

...

Keyword(s):

Error Detection ◽

Predictive Models ◽

Visual Processing ◽

Prediction Error ◽

Early Stage ◽

Predictive Coding ◽

Representational Content ◽

Saccadic Eye Movements ◽

Spatial Prediction ◽

Neural Responses

Abstract Emerging evidence indicates that prediction, instantiated at different perceptual levels, facilitate visual processing and enable prompt and appropriate reactions. Until now, the mechanisms underlying the effect of predictive coding at different stages of visual processing have still remained unclear. Here, we aimed to investigate early and late processing of spatial prediction violation by performing combined recordings of saccadic eye movements and fast event-related fMRI during a continuous visual detection task. Psychophysical reverse correlation analysis revealed that the degree of mismatch between current perceptual input and prior expectations is mainly processed at late rather than early stage, which is instead responsible for fast but general prediction error detection. Furthermore, our results suggest that conscious late detection of deviant stimuli is elicited by the assessment of prediction error’s extent more than by prediction error per se. Functional MRI and functional connectivity data analyses indicated that higher-level brain systems interactions modulate conscious detection of prediction error through top-down processes for the analysis of its representational content, and possibly regulate subsequent adaptation of predictive models. Overall, our experimental paradigm allowed to dissect explicit from implicit behavioral and neural responses to deviant stimuli in terms of their reliance on predictive models.

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Visuopathy of prematurity: is retinopathy just the tip of the iceberg?

Pediatric Research ◽

10.1038/s41390-021-01625-0 ◽

2021 ◽

Author(s):

Sigrid Hegna Ingvaldsen ◽

Tora Sund Morken ◽

Dordi Austeng ◽

Olaf Dammann

Keyword(s):

Visual Processing ◽

Structural Changes ◽

Developmental Trajectories ◽

Visual Pathway ◽

Visual Stream ◽

Visual Deficits ◽

Cortical Areas ◽

Cellular Architecture ◽

Increased Risk ◽

Dorsal Visual Stream

AbstractResearch on retinopathy of prematurity (ROP) focuses mainly on the abnormal vascularization patterns that are directly visible for ophthalmologists. However, recent findings indicate that children born prematurely also exhibit changes in the retinal cellular architecture and along the dorsal visual stream, such as structural changes between and within cortical areas. Moreover, perinatal sustained systemic inflammation (SSI) is associated with an increased risk for ROP and the visual deficits that follow. In this paper, we propose that ROP might just be the tip of an iceberg we call visuopathy of prematurity (VOP). The VOP paradigm comprises abnormal vascularization of the retina, alterations in retinal cellular architecture, choroidal degeneration, and abnormalities in the visual pathway, including cortical areas. Furthermore, VOP itself might influence the developmental trajectories of cerebral structures and functions deemed responsible for visual processing, thereby explaining visual deficits among children born preterm.

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#3083 Fibromyalgia and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS): an interoceptive predictive coding model of pain and fatigue expression

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp-2021-bnpa.10 ◽

2021 ◽

Vol 92 (8) ◽

pp. A3.3-A4

Author(s):

Harriet Sharp ◽

Kristy Themelis ◽

Marisa Amato ◽

Andrew Barritt ◽

Kevin Davies ◽

...

Keyword(s):

Prediction Error ◽

Predictive Coding ◽

Chronic Fatigue ◽

Self Report ◽

Subjective Experiences ◽

Double Blind ◽

Pain Thresholds ◽

Pressure Pain Thresholds ◽

Interoceptive Accuracy ◽

Bodily States

IntroductionThe aetiology and pathophysiology of fibromyalgia and ME/CFS are poorly characterised but altered inflammatory, autonomic and interoceptive processes have been implicated. Interoception has been conceptualised as a predictive coding process; where top-down prediction signals compare to bottom-up afferents, resulting in prediction error signals indicating mismatch between expected and actual bodily states. Chronic dyshomeostasis and elevated interoceptive prediction error signals have been theorised to contribute to the expression of pain and fatigue in fibromyalgia and ME/CFS.Objectives/AimsTo investigate how altered interoception and prediction error relates to baseline expression of pain and fatigue in fibromyalgia and ME/CFS and in response to an inflammatory challenge.MethodsSixty-five patients with fibromyalgia and/or ME/CFS diagnosis and 26 matched controls underwent baseline assessment: self-report questionnaires assessing subjective pain and fatigue and objective measurements of pressure-pain thresholds. Participants received injections of typhoid (inflammatory challenge) or saline (placebo) in a randomised, double-blind, crossover design, then completed heartbeat tracking task (assessing interoceptive accuracy). Porges Body Questionnaire assessed interoceptive sensibility. Interoceptive prediction error (IPE) was calculated as discrepancy between objective accuracy and subjective sensibility.ResultsPatients with fibromyalgia and ME/CFS had significantly higher IPE (suggesting tendency to over-estimate interoceptive ability) and interoceptive sensibility, despite no differences in interoceptive accuracy. IPE and sensibility correlated positively with all self-report fatigue and pain measures, and negatively with pain thresholds. Following inflammatory challenge, IPE correlated negatively with the mismatch between subjective and objective measures of pain induced by inflammation.ConclusionsThis is the first study to reveal altered interoception processes in patients with fibromyalgia and ME/CFS, who are known to have dysregulated autonomic function. Notably, we found elevated IPE in patients, correlating with their subjective experiences of pain and fatigue. We hypothesise a predictive coding model, where mismatch between expected and actual internal bodily states (linked to autonomic dysregulation) results in prediction error signalling which could be metacognitively interpreted as chronic pain and fatigue. Our results demonstrate potential for further exploration of interoceptive processing in patients with fibromyalgia and ME/CFS, aiding understanding of these poorly defined conditions and providing potential new targets for diagnostic and therapeutic intervention.

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Predictive coding of action intentions in dorsal and ventral visual stream is based on visual anticipations, memory-based information and motor preparation

10.1101/480590 ◽

2018 ◽

Author(s):

Simona Monaco ◽

Giulia Malfatti ◽

Alessandro Zendron ◽

Elisa Pellencin ◽

Luca Turella

Keyword(s):

Visual Information ◽

Visual Memory ◽

Visual Recognition ◽

Predictive Coding ◽

Action Planning ◽

Neural Signals ◽

Motor Representation ◽

Visual Stream ◽

Ventral Visual Stream ◽

Action Intention

AbstractPredictions of upcoming movements are based on several types of neural signals that span the visual, somatosensory, motor and cognitive system. Thus far, pre-movement signals have been investigated while participants viewed the object to be acted upon. Here, we studied the contribution of information other than vision to the classification of preparatory signals for action, even in absence of online visual information. We used functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis (MVPA) to test whether the neural signals evoked by visual, memory-based and somato-motor information can be reliably used to predict upcoming actions in areas of the dorsal and ventral visual stream during the preparatory phase preceding the action, while participants were lying still. Nineteen human participants (nine women) performed one of two actions towards an object with their eyes open or closed. Despite the well-known role of ventral stream areas in visual recognition tasks and the specialization of dorsal stream areas in somato-motor processes, we decoded action intention in areas of both streams based on visual, memory-based and somato-motor signals. Interestingly, we could reliably decode action intention in absence of visual information based on neural activity evoked when visual information was available, and vice-versa. Our results show a similar visual, memory and somato-motor representation of action planning in dorsal and ventral visual stream areas that allows predicting action intention across domains, regardless of the availability of visual information.

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Smoking as a Common Modulator of Sensory Gating and Reward Learning in Individuals with Psychotic Disorders

Brain Sciences ◽

10.3390/brainsci11121581 ◽

2021 ◽

Vol 11 (12) ◽

pp. 1581

Author(s):

Alexis E. Whitton ◽

Kathryn E. Lewandowski ◽

Mei-Hua Hall

Keyword(s):

Bipolar Disorder ◽

Prediction Error ◽

Psychotic Disorders ◽

Predictive Coding ◽

Sensory Gating ◽

Event Related Potential ◽

Reward Learning ◽

Smoking History ◽

Impaired Performance ◽

Psychotic Bipolar Disorder

Motivational and perceptual disturbances co-occur in psychosis and have been linked to aberrations in reward learning and sensory gating, respectively. Although traditionally studied independently, when viewed through a predictive coding framework, these processes can both be linked to dysfunction in striatal dopaminergic prediction error signaling. This study examined whether reward learning and sensory gating are correlated in individuals with psychotic disorders, and whether nicotine—a psychostimulant that amplifies phasic striatal dopamine firing—is a common modulator of these two processes. We recruited 183 patients with psychotic disorders (79 schizophrenia, 104 psychotic bipolar disorder) and 129 controls and assessed reward learning (behavioral probabilistic reward task), sensory gating (P50 event-related potential), and smoking history. Reward learning and sensory gating were correlated across the sample. Smoking influenced reward learning and sensory gating in both patient groups; however, the effects were in opposite directions. Specifically, smoking was associated with improved performance in individuals with schizophrenia but impaired performance in individuals with psychotic bipolar disorder. These findings suggest that reward learning and sensory gating are linked and modulated by smoking. However, disorder-specific associations with smoking suggest that nicotine may expose pathophysiological differences in the architecture and function of prediction error circuitry in these overlapping yet distinct psychotic disorders.

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Unrestricted eye movements strengthen causal connectivity from hippocampal to oculomotor regions during scene construction

10.1101/2021.09.23.461606 ◽

2021 ◽

Author(s):

Natalia Ladyka-Wojcik ◽

Zhong-Xu Liu ◽

Jennifer D. Ryan

Keyword(s):

Eye Movements ◽

Visual Processing ◽

Oculomotor System ◽

Visual Input ◽

Causal Modeling ◽

Oculomotor Control ◽

Visual Stream ◽

Functional Connections ◽

Free Viewing ◽

Scene Construction

Scene construction is a key component of memory recall, navigation, and future imagining, and relies on the medial temporal lobes (MTL). A parallel body of work suggests that eye movements may enable the imagination and construction of scenes, even in the absence of external visual input. There are vast structural and functional connections between regions of the MTL and those of the oculomotor system. However, the directionality of connections between the MTL and oculomotor control regions, and how it relates to scene construction, has not been studied directly in human neuroimaging. In the current study, we used dynamic causal modeling (DCM) to investigate this relationship at a mechanistic level using a scene construction task in which participants' eye movements were either restricted (fixed-viewing) or unrestricted (free-viewing). By omitting external visual input, and by contrasting free- versus fixed- viewing, the directionality of neural connectivity during scene construction could be determined. As opposed to when eye movements were restricted, allowing free viewing during construction of scenes strengthened top-down connections from the MTL to the frontal eye fields, and to lower-level cortical visual processing regions, suppressed bottom-up connections along the visual stream, and enhanced vividness of the constructed scenes. Taken together, these findings provide novel, non-invasive evidence for the causal architecture between the MTL memory system and oculomotor system associated with constructing vivid mental representations of scenes.

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Informative neural representations of unseen objects during higher-order processing in human brains and deep artificial networks

10.1101/2021.01.12.426428 ◽

2021 ◽

Author(s):

Ning Mei ◽

Roberto Santana ◽

David Soto

Keyword(s):

Visual Processing ◽

Visual Information ◽

Model Simulation ◽

Conscious Experience ◽

Neural Representation ◽

Visual Stream ◽

Order Processing ◽

High Level ◽

Unseen Objects ◽

Human Brains

AbstractDespite advances in the neuroscience of visual consciousness over the last decades, we still lack a framework for understanding the scope of unconscious processing and how it relates to conscious experience. Previous research observed brain signatures of unconscious contents in visual cortex, but these have not been identified in a reliable manner, with low trial numbers and signal detection theoretic constraints not allowing to decisively discard conscious perception. Critically, the extent to which unconscious content is represented in high-level processing stages along the ventral visual stream and linked prefrontal areas remains unknown. Using a within-subject, high-precision, highly-sampled fMRI approach, we show that unconscious contents, even those associated with null sensitivity, can be reliably decoded from multivoxel patterns that are highly distributed along the ventral visual pathway and also involving prefrontal substrates. Notably, the neural representation in these areas generalised across conscious and unconscious visual processing states, placing constraints on prior findings that fronto-parietal substrates support the representation of conscious contents and suggesting revisions to models of consciousness such as the neuronal global workspace. We then provide a computational model simulation of visual information processing/representation in the absence of perceptual sensitivity by using feedforward convolutional neural networks trained to perform a similar visual task to the human observers. The work provides a novel framework for pinpointing the neural representation of unconscious knowledge across different task domains.

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The dynamic neural code of the retina for natural scenes

10.1101/340943 ◽

2018 ◽

Cited By ~ 5

Author(s):

Niru Maheswaranathan ◽

Lane T. McIntosh ◽

Hidenori Tanaka ◽

Satchel Grant ◽

David B. Kastner ◽

...

Keyword(s):

Visual Processing ◽

Ganglion Cells ◽

Predictive Coding ◽

Neural Code ◽

Natural Scenes ◽

Large Set ◽

Fundamental Limits ◽

Fundamental Goal ◽

Latent Effects ◽

Highly Correlated

AbstractUnderstanding how the visual system encodes natural scenes is a fundamental goal of sensory neuroscience. We show here that a three-layer network model predicts the retinal response to natural scenes with an accuracy nearing the fundamental limits of predictability. The model’s internal structure is interpretable, in that model units are highly correlated with interneurons recorded separately and not used to fit the model. We further show the ethological relevance to natural visual processing of a diverse set of phenomena of complex motion encoding, adaptation and predictive coding. Our analysis uncovers a fast timescale of visual processing that is inaccessible directly from experimental data, showing unexpectedly that ganglion cells signal in distinct modes by rapidly (< 0.1 s) switching their selectivity for direction of motion, orientation, location and the sign of intensity. A new approach that decomposes ganglion cell responses into the contribution of interneurons reveals how the latent effects of parallel retinal circuits generate the response to any possible stimulus. These results reveal extremely flexible and rapid dynamics of the retinal code for natural visual stimuli, explaining the need for a large set of interneuron pathways to generate the dynamic neural code for natural scenes.

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