Perceptual inference

Aggelopoulos, Nikolaos C.

doi:10.1016/j.neubiorev.2015.05.001

Cited by 39 publications

(26 citation statements)

References 263 publications

(233 reference statements)

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“…I propose that linguistic structure building is a form of perceptual inference or the ability to infer the presence of a stimulus, often from incomplete or partial sensory information. Perceptual inference is based on information stored in neural representations that were acquired through experience (Aggelopoulos, 2015) and that are generated internally in response to stimulation (Martin, 2016). I posit a processing mechanism for perceptual inference via the neural transformation of sensory codes to structured representations.…”

Section: Introductionmentioning

confidence: 99%

A Compositional Neural Architecture for Language

Martin

2020

Journal of Cognitive Neuroscience

175

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Hierarchical structure and compositionality imbue human language with unparalleled expressive power and set it apart from other perception–action systems. However, neither formal nor neurobiological models account for how these defining computational properties might arise in a physiological system. I attempt to reconcile hierarchy and compositionality with principles from cell assembly computation in neuroscience; the result is an emerging theory of how the brain could convert distributed perceptual representations into hierarchical structures across multiple timescales while representing interpretable incremental stages of (de)compositional meaning. The model's architecture—a multidimensional coordinate system based on neurophysiological models of sensory processing—proposes that a manifold of neural trajectories encodes sensory, motor, and abstract linguistic states. Gain modulation, including inhibition, tunes the path in the manifold in accordance with behavior and is how latent structure is inferred. As a consequence, predictive information about upcoming sensory input during production and comprehension is available without a separate operation. The proposed processing mechanism is synthesized from current models of neural entrainment to speech, concepts from systems neuroscience and category theory, and a symbolic-connectionist computational model that uses time and rhythm to structure information. I build on evidence from cognitive neuroscience and computational modeling that suggests a formal and mechanistic alignment between structure building and neural oscillations, and moves toward unifying basic insights from linguistics and psycholinguistics with the currency of neural computation.

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Section: Introductionmentioning

confidence: 99%

A Compositional Neural Architecture for Language

Martin

2020

Journal of Cognitive Neuroscience

175

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“…The generative models of perception, such as predictive coding [5,[67][68][69], commonly consider the brain as an unconscious inference machine that uses hidden states to predict observed sensory inputs [68,70]. However, the physiological basis of the underlying computations remains unclear.…”

Section: Discussionmentioning

confidence: 99%

Perceptual inference employs intrinsic alpha frequency to resolve perceptual ambiguity

Shen

Han²,

Chen

et al. 2018

Preprint

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The brain uses its intrinsic dynamics to actively predict observed sensory inputs, especially under perceptual ambiguity. However, it remains unclear how this inference process is neurally implemented in biasing perception of ambiguous inputs towards the predicted percepts. Using electroencephalography and intracranial recordings, we first show that the alpha-band frequency defines a unified time window for perceptual grouping across both space and time: information segments, either spatially or temporally segregated, will be integrated if they fall within the same alpha cycle. Moreover, predictions employ this prior knowledge on intrinsic alpha frequency to shift perceptual inference towards the most possibly observed percepts. Multivariate decoding analysis showed that perceptual inference, based on variance in prestimulus alpha frequency (PAF), biases post-stimulus neural representations by inducing preactivation of the predicted percepts. fMRI results additionally showed that prestimulus activity and intrinsic organization status in the frontoparietal attentional network predict perceptual outcomes, probably by modulating occipitoparietal PAFs.

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“…Compared to the irregular sequences, the regular sequences elicited greater responses in the population of neurons in primary auditory cortex. Such facilitation has been hypothesised to be characteristic of the activation of forward models and, consequently, to underlie perceptual enhancements (Aggelopoulos, ). We did not find evidence for adaptation that is also commonly observed for predicted stimuli and leads to a diminished response to that stimulus.…”

Section: Discussionmentioning

confidence: 99%

Predictive cues for auditory stream formation in humans and monkeys

Aggelopoulos

Deike

Selezneva

et al. 2018

Eur J of Neuroscience

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Auditory perception is improved when stimuli are predictable, and this effect is evident in a modulation of the activity of neurons in the auditory cortex as shown previously. Human listeners can better predict the presence of duration deviants embedded in stimulus streams with fixed interonset interval (isochrony) and repeated duration pattern (regularity), and neurons in the auditory cortex of macaque monkeys have stronger sustained responses in the 60-140 ms post-stimulus time window under these conditions. Subsequently, the question has arisen whether isochrony or regularity in the sensory input contributed to the enhancement of the neuronal and behavioural responses. Therefore, we varied the two factors isochrony and regularity independently and measured the ability of human subjects to detect deviants embedded in these sequences as well as measuring the responses of neurons the primary auditory cortex of macaque monkeys during presentations of the sequences. The performance of humans in detecting deviants was significantly increased by regularity. Isochrony enhanced detection only in the presence of the regularity cue. In monkeys, regularity increased the sustained component of neuronal tone responses in auditory cortex while isochrony had no consistent effect. Although both regularity and isochrony can be considered as parameters that would make a sequence of sounds more predictable, our results from the human and monkey experiments converge in that regularity has a greater influence on behavioural performance and neuronal responses.

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Perceptual inference

Cited by 39 publications

References 263 publications

A Compositional Neural Architecture for Language

A Compositional Neural Architecture for Language

Perceptual inference employs intrinsic alpha frequency to resolve perceptual ambiguity

Predictive cues for auditory stream formation in humans and monkeys

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