scholarly journals The neural dynamics of hierarchical Bayesian inference in multisensory perception

2018 ◽  
Author(s):  
Tim Rohe ◽  
Ann-Christine Ehlis ◽  
Uta Noppeney
Keyword(s):  
Causal Structure ◽  
Model Averaging ◽  
Neural Mechanisms ◽  
Multisensory Perception ◽  
Alpha Power ◽  
Binding Problem ◽  
Prior Beliefs ◽  
Hierarchical Bayesian Inference ◽  
Integrated Or ◽  
The Brain

AbstractTransforming the barrage of sensory signals into a coherent multisensory percept relies on solving the binding problem – deciding whether signals come from a common cause and should be integrated, or instead be segregated. Human observers typically arbitrate between integration and segregation consistent with Bayesian Causal Inference, but the neural mechanisms remain poorly understood. We presented observers with audiovisual sequences that varied in the number of flashes and beeps. Combining Bayesian modelling and EEG representational similarity analyses, we show that the brain initially represents the number of flashes and beeps and their numeric disparity mainly independently. Later, it computes them by averaging the forced-fusion and segregation estimates weighted by the probabilities of common and independent cause models (i.e. model averaging). Crucially, prestimulus oscillatory alpha power and phase correlate with observers’ prior beliefs about the world’s causal structure that guide their arbitration between sensory integration and segregation.

scholarly journals Attention controls multisensory perception via 2 distinct mechanisms at different levels of the cortical hierarchy

PLoS Biology ◽  
2021 ◽  
Vol 19 (11) ◽  
pp. e3001465
Author(s):  
Ambra Ferrari ◽  
Uta Noppeney
Keyword(s):  
Causal Inference ◽  
Causal Structure ◽  
Multisensory Perception ◽  
Spatial Representations ◽  
Perceptual Inference ◽  
Sensory Signals ◽  
Cortical Hierarchy ◽  
Parietal Cortices ◽  
The Brain ◽  
Different Levels

To form a percept of the multisensory world, the brain needs to integrate signals from common sources weighted by their reliabilities and segregate those from independent sources. Previously, we have shown that anterior parietal cortices combine sensory signals into representations that take into account the signals’ causal structure (i.e., common versus independent sources) and their sensory reliabilities as predicted by Bayesian causal inference. The current study asks to what extent and how attentional mechanisms can actively control how sensory signals are combined for perceptual inference. In a pre- and postcueing paradigm, we presented observers with audiovisual signals at variable spatial disparities. Observers were precued to attend to auditory or visual modalities prior to stimulus presentation and postcued to report their perceived auditory or visual location. Combining psychophysics, functional magnetic resonance imaging (fMRI), and Bayesian modelling, we demonstrate that the brain moulds multisensory inference via 2 distinct mechanisms. Prestimulus attention to vision enhances the reliability and influence of visual inputs on spatial representations in visual and posterior parietal cortices. Poststimulus report determines how parietal cortices flexibly combine sensory estimates into spatial representations consistent with Bayesian causal inference. Our results show that distinct neural mechanisms control how signals are combined for perceptual inference at different levels of the cortical hierarchy.

scholarly journals To integrate or not to integrate: Temporal dynamics of hierarchical Bayesian Causal Inference

2018 ◽  
Author(s):  
Máté Aller ◽  
Uta Noppeney
Keyword(s):  
Causal Inference ◽  
Temporal Dynamics ◽  
Causal Structure ◽  
Visual Signal ◽  
Effective Interactions ◽  
Statistical Computation ◽  
Spatial Estimates ◽  
Hierarchical Nature ◽  
Integrated Or ◽  
The Brain

AbstractTo form a percept of the environment, the brain needs to solve the binding problem – inferring whether signals come from a common cause and be integrated, or come from independent causes and be segregated. Behaviourally, humans solve this problem near-optimally as predicted by Bayesian Causal Inference; but, the neural mechanisms remain unclear. Combining Bayesian modelling, electroencephalography (EEG), and multivariate decoding in an audiovisual spatial localization task, we show that the brain accomplishes Bayesian Causal Inference by dynamically encoding multiple spatial estimates. Initially, auditory and visual signal locations are estimated independently; next, an estimate is formed that combines information from vision and audition. Yet, it is only from 200 ms onwards that the brain integrates audiovisual signals weighted by their bottom-up sensory reliabilities and top-down task-relevance into spatial priority maps that guide behavioural responses. Critically, as predicted by Bayesian Causal Inference, these spatial priority maps take into account the brain’s uncertainty about the world’s causal structure and flexibly arbitrate between sensory integration and segregation. The dynamic evolution of perceptual estimates thus reflects the hierarchical nature of Bayesian Causal Inference, a statistical computation, crucial for effective interactions with the environment.

scholarly journals See what you hear – How the brain forms representations across the senses

Neuroforum ◽  
2018 ◽  
Vol 24 (4) ◽  
pp. A169-A181
Author(s):  
Uta Noppeney ◽  
Samuel A. Jones ◽  
Tim Rohe ◽  
Ambra Ferrari
Keyword(s):  
Causal Inference ◽  
Sensory Processing ◽  
Sensory Integration ◽  
Causal Structure ◽  
Multisensory Perception ◽  
Common Source ◽  
Behavioural Research ◽  
Parietal Cortices ◽  
The Brain ◽  
Different Sources

Abstarct Our senses are constantly bombarded with a myriad of signals. To make sense of this cacophony, the brain needs to integrate signals emanating from a common source, but segregate signals originating from the different sources. Thus, multisensory perception relies critically on inferring the world’s causal structure (i. e. one common vs. multiple independent sources). Behavioural research has shown that the brain arbitrates between sensory integration and segregation consistent with the principles of Bayesian Causal Inference. At the neural level, recent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) studies have shown that the brain accomplishes Bayesian Causal Inference by dynamically encoding multiple perceptual estimates across the sensory processing hierarchies. Only at the top of the hierarchy in anterior parietal cortices did the brain form perceptual estimates that take into account the observer’s uncertainty about the world’s causal structure consistent with Bayesian Causal Inference.

Synaesthesia

2018 ◽  
Author(s):  
Bruno and
Keyword(s):  
Experimental Results ◽  
Multisensory Perception ◽  
Related Phenomenon ◽  
Perceptual Modality ◽  
Sensory Channel ◽  
Multisensory Interactions ◽  
Crossmodal Associations ◽  
The Brain

Synaesthesia is a curious anomaly of multisensory perception. When presented with stimulation in one sensory channel, in addition to the percept usually associated with that channel (inducer) a true synaesthetic experiences a second percept in another perceptual modality (concurrent). Although synaesthesia is not pathological, true synaesthetes are relatively rare and their synaesthetic associations tend to be quite idiosyncratic. For this reason, studying synaesthesia is difficult, but exciting new experimental results are beginning to clarify what makes the brain of synaesthetes special and the mechanisms that may produce the condition. Even more importantly, the related phenomenon known as ‘natural’ crossmodal associations is instead experienced by everyone, providing another useful domain for studying multisensory interactions with important implications for understanding our preferences for products in terms of spontaneously evoked associations, as well as for choosing appropriate names, labels, and packaging in marketing applications.

scholarly journals Antagonism between brain regions relevant for cognitive control and emotional memory facilitates the generation of humorous ideas

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Florian Bitsch ◽  
Philipp Berger ◽  
Andreas Fink ◽  
Arne Nagels ◽  
Benjamin Straube ◽  
...  
Keyword(s):  
Cognitive Control ◽  
Positive Emotions ◽  
Emotional Memory ◽  
Brain Regions ◽  
Neural Mechanisms ◽  
Functional Magnetic Resonance ◽  
Frontal Brain ◽  
Successful Resolution ◽  
Neural Underpinnings ◽  
The Brain

AbstractThe ability to generate humor gives rise to positive emotions and thus facilitate the successful resolution of adversity. Although there is consensus that inhibitory processes might be related to broaden the way of thinking, the neural underpinnings of these mechanisms are largely unknown. Here, we use functional Magnetic Resonance Imaging, a humorous alternative uses task and a stroop task, to investigate the brain mechanisms underlying the emergence of humorous ideas in 24 subjects. Neuroimaging results indicate that greater cognitive control abilities are associated with increased activation in the amygdala, the hippocampus and the superior and medial frontal gyrus during the generation of humorous ideas. Examining the neural mechanisms more closely shows that the hypoactivation of frontal brain regions is associated with an hyperactivation in the amygdala and vice versa. This antagonistic connectivity is concurrently linked with an increased number of humorous ideas and enhanced amygdala responses during the task. Our data therefore suggests that a neural antagonism previously related to the emergence and regulation of negative affective responses, is linked with the generation of emotionally positive ideas and may represent an important neural pathway supporting mental health.

Neural Mechanisms of Negative Symptoms

1989 ◽  
Vol 155 (S7) ◽  
pp. 93-98 ◽  
Author(s):  
Nancy C. Andreasen
Keyword(s):  
Frontal Cortex ◽  
Negative Symptoms ◽  
Neural Mechanism ◽  
Brain Regions ◽  
Brain Dysfunction ◽  
Neural Mechanisms ◽  
Dementia Praecox ◽  
Intellectual Abilities ◽  
The Brain ◽  
Psychic Mechanisms

When Kraepelin originally defined and described dementia praecox, he assumed that it was due to some type of neural mechanism. He hypothesised that abnormalities could occur in a variety of brain regions, including the prefrontal, auditory, and language regions of the cortex. Many members of his department, including Alzheimer and Nissl, were actively involved in the search for the neuropathological lesions that would characterise schizophrenia. Although Kraepelin did not use the term ‘negative symptoms', he describes them comprehensively and states explicitly that he believes the symptoms of schizophrenia can be explained in terms of brain dysfunction:“If it should be confirmed that the disease attacks by preference the frontal areas of the brain, the central convolutions and central lobes, this distribution would in a certain measure agree with our present views about the site of the psychic mechanisms which are principally injured by the disease. On various grounds, it is easy to believe that the frontal cortex, which is specially well developed in man, stands in closer relation to his higher intellectual abilities, and these are the faculties which in our patients invariably suffer profound loss in contrast to memory and acquired ability.” Kraepelin (1919, p. 219)

scholarly journals Representation of Grammatical Categories of Words in the Brain

1995 ◽  
Vol 7 (3) ◽  
pp. 396-407 ◽  
Author(s):  
Argye E. Hillis ◽  
Alfonso Caramazza
Keyword(s):  
Neural Mechanisms ◽  
Single Patient ◽  
Grammatical Category ◽  
Lexical Knowledge ◽  
Double Dissociation ◽  
Category Information ◽  
Orthographic Representations ◽  
Organizational Principle ◽  
The Brain ◽  
Verbal Output

We report the performance of a patient who, as a consequence of left frontal and temporoparietal strokes, makes far more errors on nouns than on verbs in spoken output tasks, but makes far more errors on verbs than on nouns in written input tasks. This double dissociation within a single patient with respect to grammatical category provides evidence for the hypothesis that phonological and orthographic representations of nouns and verbs are processed by independent neural mechanisms. Furthermore, the opposite dissociation in the verbal output modality, an advantage for nouns over verbs in spoken tasks, by a different patient using the same stimuli has also been reported (Caramazza & Hillis, 1991). This double dissociation across patients on the same task indicates that results cannot be ascribed to "greater difficulty" with one type of stimulus, and provides further evidence for the view that grammatical category information is an important organizational principle of lexical knowledge in the brain.

scholarly journals Talent in the taxi: a model system for exploring expertise

2009 ◽  
Vol 364 (1522) ◽  
pp. 1407-1416 ◽  
Author(s):  
Katherine Woollett ◽  
Hugo J. Spiers ◽  
Eleanor A. Maguire
Keyword(s):  
Model System ◽  
Neural Mechanisms ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Taxi Drivers ◽  
The Brain ◽  
Use Of Expertise ◽  
Widespread Interest ◽  
Key Questions ◽  
Extensive Practice

While there is widespread interest in and admiration of individuals with exceptional talents, surprisingly little is known about the cognitive and neural mechanisms underpinning talent, and indeed how talent relates to expertise. Because many talents are first identified and nurtured in childhood, it can be difficult to determine whether talent is innate, can be acquired through extensive practice or can only be acquired in the presence of the developing brain. We sought to address some of these issues by studying healthy adults who acquired expertise in adulthood. We focused on the domain of memory and used licensed London taxi drivers as a model system. Taxi drivers have to learn the layout of 25 000 streets in London and the locations of thousands of places of interest, and pass stringent examinations in order to obtain an operating licence. Using neuropsychological assessment and structural and functional magnetic resonance imaging, we addressed a range of key questions: in the context of a fully developed brain and an average IQ, can people acquire expertise to an exceptional level; what are the neural signatures, both structural and functional, associated with the use of expertise; does expertise change the brain compared with unskilled control participants; does it confer any cognitive advantages, and similarly, does it come at a cost to other functions? By studying retired taxi drivers, we also consider what happens to their brains and behaviour when experts stop using their skill. Finally, we discuss how the expertise of taxi drivers might relate to the issue of talent and innate abilities. We suggest that exploring talent and expertise in this manner could have implications for education, rehabilitation of patients with cognitive impairments, understanding individual differences and possibly conditions such as autism where exceptional abilities can be a feature.

Domain-Specific Knowledge Systems in the Brain: The Animate-Inanimate Distinction

1998 ◽  
Vol 10 (1) ◽  
pp. 1-34 ◽  
Author(s):  
Alfonso Caramazza ◽  
Jennifer R. Shelton
Keyword(s):  
Knowledge Systems ◽  
Neural Mechanisms ◽  
Specific Knowledge ◽  
Knowledge Framework ◽  
Semantic Categories ◽  
Domain Specific ◽  
Domain Specific Knowledge ◽  
Cognitive Neuropsychological ◽  
The Brain ◽  
Selective Impairment

We claim that the animate and inanimate conceptual categories represent evolutionarily adapted domain-specific knowledge systems that are subserved by distinct neural mechanisms, thereby allowing for their selective impairment in conditions of brain damage. On this view, (some of) the category-specific deficits that have recently been reported in the cognitive neuropsychological literature—for example, the selective damage or sparing of knowledge about animals—are truly categorical effects. Here, we articulate and defend this thesis against the dominant, reductionist theory of category-specific deficits, which holds that the categorical nature of the deficits is the result of selective damage to noncategorically organized visual or functional semantic subsystems. On the latter view, the sensory/functional dimension provides the fundamental organizing principle of the semantic system. Since, according to the latter theory, sensory and functional properties are differentially important in determining the meaning of the members of different semantic categories, selective damage to the visual or the functional semantic subsystem will result in a category-like deficit. A review of the literature and the results of a new case of category-specific deficit will show that the domain-specific knowledge framework provides a better account of category-specific deficits than the sensory/functional dichotomy theory.

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