scholarly journals Neural surprise in somatosensory Bayesian learning

2021 ◽  
Vol 17 (2) ◽  
pp. e1008068
Author(s):  
Sam Gijsen ◽  
Miro Grundei ◽  
Robert T. Lange ◽  
Dirk Ostwald ◽  
Felix Blankenburg
Keyword(s):  
Bayesian Learning ◽  
Model Updating ◽  
Selection Procedure ◽  
Stimulus Onset ◽  
Learning System ◽  
Somatosensory Processing ◽  
Somatosensory Cortices ◽  
Statistical Regularities ◽  
Leaky Integration ◽  
Underlying Mechanisms

Tracking statistical regularities of the environment is important for shaping human behavior and perception. Evidence suggests that the brain learns environmental dependencies using Bayesian principles. However, much remains unknown about the employed algorithms, for somesthesis in particular. Here, we describe the cortical dynamics of the somatosensory learning system to investigate both the form of the generative model as well as its neural surprise signatures. Specifically, we recorded EEG data from 40 participants subjected to a somatosensory roving-stimulus paradigm and performed single-trial modeling across peri-stimulus time in both sensor and source space. Our Bayesian model selection procedure indicates that evoked potentials are best described by a non-hierarchical learning model that tracks transitions between observations using leaky integration. From around 70ms post-stimulus onset, secondary somatosensory cortices are found to represent confidence-corrected surprise as a measure of model inadequacy. Indications of Bayesian surprise encoding, reflecting model updating, are found in primary somatosensory cortex from around 140ms. This dissociation is compatible with the idea that early surprise signals may control subsequent model update rates. In sum, our findings support the hypothesis that early somatosensory processing reflects Bayesian perceptual learning and contribute to an understanding of its underlying mechanisms.

scholarly journals Neural surprise in somatosensory Bayesian learning

2020 ◽  
Author(s):  
Sam Gijsen ◽  
Miro Grundei ◽  
Robert T. Lange ◽  
Dirk Ostwald ◽  
Felix Blankenburg
Keyword(s):  
Perceptual Learning ◽  
Bayesian Learning ◽  
Model Updating ◽  
Selection Procedure ◽  
Learning Model ◽  
Learning System ◽  
Somatosensory Processing ◽  
Eeg Data ◽  
Statistical Regularities ◽  
The Brain

AbstractTracking statistical regularities of the environment is important for shaping human behavior and perception. Evidence suggests that the brain learns environmental dependencies using Bayesian principles. However, much remains unknown about the employed algorithms, for somesthesis in particular. Here, we describe the cortical dynamics of the somatosensory learning system to investigate both the form of the generative model as well as its neural surprise signatures. Specifically, we recorded EEG data from 40 participants subjected to a somatosensory roving-stimulus paradigm and performed single-trial modeling across peri-stimulus time in both sensor and source space. Our Bayesian model selection procedure indicates that evoked potentials are best described by a non-hierarchical learning model that tracks transitions between observations using leaky integration. From around 70ms post-stimulus onset, secondary somatosensory cortices are found to represent confidence-corrected surprise as a measure of model inadequacy. Primary somatosensory cortex is found to encode Bayesian surprise, reflecting model updating, from around 140ms. As such, this dissociation indicates that early surprise signals may control subsequent model update rates. In sum, our findings support the hypothesis that early somatosensory processing reflects Bayesian perceptual learning and contribute to an understanding of its precise mechanisms.Author summaryOur environment features statistical regularities, such as a drop of rain predicting imminent rainfall. Despite the importance for behavior and survival, much remains unknown about how these dependencies are learned, particularly for somatosensation. As surprise signalling about novel observations indicates a mismatch between one’s beliefs and the world, it has been hypothesized that surprise computation plays an important role in perceptual learning. By analyzing EEG data from human participants receiving sequences of tactile stimulation, we compare different formulations of surprise and investigate the employed underlying learning model. Our results indicate that the brain estimates transitions between observations. Furthermore, we identified different signatures of surprise computation and thereby provide a dissociation of the neural correlates of belief inadequacy and belief updating. Specifically, early surprise responses from around 70ms were found to signal the need for changes to the model, with encoding of its subsequent updating occurring from around 140ms. These results provide insights into how somatosensory surprise signals may contribute to the learning of environmental statistics.

Orienting and Focusing in Voluntary and Involuntary Visuospatial Attention Conditions

2010 ◽  
Vol 24 (3) ◽  
pp. 198-209 ◽  
Author(s):  
Yan Wang ◽  
Jianhui Wu ◽  
Shimin Fu ◽  
Yuejia Luo
Keyword(s):  
Gain Control ◽  
Event Related Potentials ◽  
Stimulus Onset ◽  
Orientation Discrimination ◽  
Involuntary Attention ◽  
Attention Condition ◽  
Voluntary Attention ◽  
Visual Spatial ◽  
Related Potentials ◽  
Underlying Mechanisms

In the present study, we used event-related potentials (ERPs) and behavioral measurements in a peripherally cued line-orientation discrimination task to investigate the underlying mechanisms of orienting and focusing in voluntary and involuntary attention conditions. Informative peripheral cue (75% valid) with long stimulus onset asynchrony (SOA) was used in the voluntary attention condition; uninformative peripheral cue (50% valid) with short SOA was used in the involuntary attention condition. Both orienting and focusing were affected by attention type. Results for attention orienting in the voluntary attention condition confirmed the “sensory gain control theory,” as attention enhanced the amplitude of the early ERP components, P1 and N1, without latency changes. In the involuntary attention condition, compared with invalid trials, targets in the valid trials elicited larger and later contralateral P1 components, and smaller and later contralateral N1 components. Furthermore, but only in the voluntary attention condition, targets in the valid trials elicited larger N2 and P3 components than in the invalid trials. Attention focusing in the involuntary attention condition resulted in larger P1 components elicited by targets in small-cue trials compared to large-cue trials, whereas in the voluntary attention condition, larger P1 components were elicited by targets in large-cue trials than in small-cue trials. There was no interaction between orienting and focusing. These results suggest that orienting and focusing of visual-spatial attention are deployed independently regardless of attention type. In addition, the present results provide evidence of dissociation between voluntary and involuntary attention during the same task.

scholarly journals Sound-identity processing in early areas of the auditory ventral stream in the macaque

2012 ◽  
Vol 107 (4) ◽  
pp. 1123-1141 ◽  
Author(s):  
Paweł Kuśmierek ◽  
Michael Ortiz ◽  
Josef P. Rauschecker
Keyword(s):  
Rhesus Macaques ◽  
Population Analysis ◽  
Activity Patterns ◽  
Dorsal Stream ◽  
Stimulus Onset ◽  
Ventral Stream ◽  
Underlying Mechanisms ◽  
Species Specific ◽  
Rostral Region ◽  
Identity Processing

Auditory cortical processing is thought to be accomplished along two processing streams. The existence of a posterior/dorsal stream dealing, among others, with the processing of spatial aspects of sound has been corroborated by numerous studies in several species. An anterior/ventral stream for the processing of nonspatial sound qualities, including the identification of sounds such as species-specific vocalizations, has also received much support. Originally discovered in anterolateral belt cortex, most recent work on the anterior/ventral pathway has been performed on far anterior superior temporal (ST) areas and on ventrolateral prefrontal cortex (VLPFC). Regions of the anterior/ventral stream near its origin in early auditory areas have been less explored. In the present study, we examined three early auditory regions with different anteroposterior locations (caudal, middle, and rostral) in awake rhesus macaques. We analyzed how well classification based on sound-evoked activity patterns of neuronal populations replicates the original stimulus categories. Of the three regions, the rostral region (rR), which included core area R and medial belt area RM, yielded the greatest classification success across all stimulus classes or between classes of natural sounds. Starting from ∼80 ms past stimulus onset, clustering based on the population response in rR became clearly more successful than clustering based on responses from any other region. Our study demonstrates that specialization for sound-identity processing can be found very early in the auditory ventral stream. Furthermore, the fact that this processing develops over time can shed light on underlying mechanisms. Finally, we show that population analysis is a more sensitive method for revealing functional specialization than conventional types of analysis.

Long-term effects of early pain and injury: animal models

2013 ◽  
pp. 20-29 ◽  
Author(s):  
Suellen M. Walker
Keyword(s):  
Nervous System ◽  
Tissue Injury ◽  
Afferent Input ◽  
Somatosensory Processing ◽  
Laboratory Studies ◽  
Long Term Effects ◽  
Nociceptive Pathways ◽  
Acute Responses ◽  
Noxious Stimuli ◽  
Underlying Mechanisms

Nociceptive pathways are functional following birth and acute responses to noxious stimuli have been documented from early development in both clinical and laboratory studies. The ability of noxious afferent input to alter the level of sensitivity of nociceptive pathways in the adult nervous system, with, for example the development of central sensitization, is well established (Woolf, 2011). However, the developing nervous system has additional susceptibilities to alterations in neural activity, and increases due to pain and injury in early life may produce effects not seen following the same input at older ages. As a result, early tissue injury may lead to persistent changes in somatosensory processing and altered sensitivity to future noxious stimuli. The impact of early pain and injury cannot be simply viewed as increasing or decreasing sensitivity as results vary depending on the type and severity of injury and the outcomes used for assessment. Laboratory studies allow evaluation of different forms of injury, potential confounding factors, underlying mechanisms, and potential for modulation by analgesia.

Somatosensory Processing in the Human Inferior Prefrontal Cortex

2002 ◽  
Vol 88 (3) ◽  
pp. 1400-1406 ◽  
Author(s):  
Matthew C. Hagen ◽  
David H. Zald ◽  
Tricia A. Thornton ◽  
José V. Pardo
Keyword(s):  
Inferior Frontal Gyrus ◽  
Sensory Stimulation ◽  
Brain Regions ◽  
Somatosensory Processing ◽  
Somatosensory Stimulation ◽  
Tactile Stimuli ◽  
Somatosensory Cortices ◽  
Frontal Operculum ◽  
Frontal Activity ◽  
Ventral Area

Three inferior prefrontal regions in the monkey receive afferents from somatosensory cortices: the orbitofrontal cortex (OFC), the ventral area of the principal sulcus, and the anterior frontal operculum. To determine whether these areas show responses to tactile stimuli in humans, we examined data from an ongoing series of PET studies of somatosensory processing. Unlike previous work showing ventral frontal activity to hedonic (pleasant/unpleasant) sensory stimulation, the tactile stimuli used in these studies had a neutral hedonic valence. Our data provide evidence for at least two discrete ventral frontal brain regions responsive to somatosensory stimulation: 1) the posterior inferior frontal gyrus (IFG) and adjacent anterior frontal operculum, and 2) the OFC. The former region (posterior IFG/anterior frontal operculum) may have a more specific role in attending to tactile stimuli.

scholarly journals Training the Interpretation of Ambiguity

2021 ◽  
Author(s):  
◽  
Jessica Clifton
Keyword(s):  
Ambiguity Resolution ◽  
Stimulus Onset ◽  
Test Phase ◽  
Ambiguous Sentence ◽  
Decision Task ◽  
Interpretive Bias ◽  
Ambiguous Words ◽  
Target Stimulus Onset Asynchrony ◽  
Underlying Mechanisms ◽  
Selection Of

<p>The interpretation of emotionally ambiguous words, sentences, or scenarios can be biased through training procedures that are collectively called Cognitive Bias Modification for Interpretation (CBM-I). Little CBM-I research has examined the underlying mechanisms responsible for the induction of emotional interpretive biases, or the potential for this line of enquiry to inform psycholinguistic models of meaning activation and selection. In this thesis a novel CBM-I paradigm was developed and then systematically manipulated in order to discriminate between two mechanistic accounts of changes in interpretive bias – the Emotional Priming Account and the Ambiguity Resolution Account. In Experiment 1 participants completed word fragments that were consistently related to either a negative or benign interpretation of an ambiguous sentence. In a subsequent semantic priming task they demonstrated an interpretation bias, in that they were faster to judge the relatedness of targets that were associated with the training-congruent than the training-incongruent meaning of an emotionally ambiguous homograph. In Experiment 2 the time between the presentation of the prime and the target (Stimulus Onset Asynchrony; SOA) at test was shortened. Interpretive biases were not observed at a short SOA suggesting that training did not induce biases at an early lexical activation stage. Interpretive bias was then eliminated when participants simply completed valenced word fragments (Experiment 3) or completed fragments related to emotional but unambiguous sentences (Experiment 4) during training. Only when participants were required to actively resolve emotionally ambiguous sentences during training did changes in interpretation emerge at test. These findings suggest that CBM-I achieves its effects by altering a production rule that aids the selection of a single meaning from alternatives, in line with an Ambiguity Resolution account. Finally, no interpretive biases were observed when the task in the test phase was substituted with a lexical decision task (Experiment 5). Participants only showed biases in the selection of meanings when the test phase encouraged them to interpret the prime. This pattern of results suggests that the alteration of selection patterns in word recognition depend on the strategies employed by participants in the test phase. Overall the findings are discussed with regards to the Ambiguity Resolution and Emotional Priming accounts of modified interpretive biases. Implications for current psycholinguistic models of meaning activation and selection are considered.</p>

scholarly journals The Role of Premature Evidence Accumulation in Making Difficult Perceptual Decisions under Temporal Uncertainty

2019 ◽  
Author(s):  
Ciara A. Devine ◽  
Christine Gaffney ◽  
Gerard Loughnane ◽  
Simon P. Kelly ◽  
Redmond G. O’Connell
Keyword(s):  
Temporal Structure ◽  
Preceding Trial ◽  
Relevant Information ◽  
Stimulus Onset ◽  
Joint Analysis ◽  
Recent Experience ◽  
Temporal Uncertainty ◽  
Onset Timing ◽  
Neural Processes ◽  
Statistical Regularities

AbstractThe computations and neural processes underpinning decision making have primarily been investigated using highly simplified tasks in which stimulus onsets cue observers to start accumulating choice-relevant information. Yet, in daily life we are rarely afforded the luxury of knowing precisely when choice-relevant information will appear. Here, we examined neural indices of decision formation while subjects discriminated subtle stimulus feature changes whose timing relative to stimulus onset (‘foreperiod’) was uncertain. Joint analysis of behavioral error patterns and neural decision signal dynamics indicated that subjects systematically began the accumulation process before any informative evidence was presented, and further, that accumulation onset timing varied systematically as a function of the foreperiod of the preceding trial. These results suggest that the brain can adjust to temporal uncertainty by strategically modulating accumulation onset timing according to statistical regularities in the temporal structure of the sensory environment with particular emphasis on recent experience.

scholarly journals Sparse representation for damage identification of structural systems

2020 ◽  
pp. 147592172092697
Author(s):  
Zhao Chen ◽  
Hao Sun
Keyword(s):  
Sparse Representation ◽  
Structural Damage ◽  
Bayesian Learning ◽  
Damage Identification ◽  
Model Updating ◽  
Computational Cost ◽  
Bayesian Optimization ◽  
Structural Systems ◽  
Least Squares Regression ◽  
Shear Type

Identifying damage of structural systems is typically characterized as an inverse problem which might be ill-conditioned due to aleatory and epistemic uncertainties induced by measurement noise and modeling error. Sparse representation can be used to perform inverse analysis for the case of sparse damage. In this article, we propose a novel two-stage sensitivity analysis–based framework for both model updating and sparse damage identification. Specifically, an [Formula: see text] Bayesian learning method is first developed for updating the intact model and uncertainty quantification so as to set forward a baseline for damage detection. A sparse representation pipeline built on a quasi-[Formula: see text] method, for example, sequential threshold least squares regression, is then presented for damage localization and quantification. In addition, Bayesian optimization together with cross-validation is developed to heuristically learn hyperparameters from data, which saves the computational cost of hyperparameter tuning and produces more reliable identification result. The proposed framework is verified by three examples, including a 10-story shear-type building, a complex truss structure, and a shake-table test of an eight-story steel frame. Results show that the proposed approach is capable of both localizing and quantifying structural damage with high accuracy.

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