scholarly journals Action Intention-based and Stimulus Regularity-based Predictions: Same or Different?

2019 ◽  
Vol 31 (12) ◽  
pp. 1917-1932 ◽  
Author(s):  
Betina Korka ◽  
Erich Schröger ◽  
Andreas Widmann
Keyword(s):  
Button Press ◽  
Oddball Paradigm ◽  
Prediction Errors ◽  
Top Down ◽  
Processing Level ◽  
Future Events ◽  
Left And Right ◽  
Sensory Predictions ◽  
Action Intention ◽  
Environmental Demands

We act on the environment to produce desired effects, but we also adapt to the environmental demands by learning what to expect next, based on experience: How do action-based predictions and sensory predictions relate to each other? We explore this by implementing a self-generation oddball paradigm, where participants performed random sequences of left and right button presses to produce frequent standard and rare deviant tones. By manipulating the action–tone association as well as the likelihood of a button press over the other one, we compare ERP effects evoked by the intention to produce a specific tone, tone regularity, and both intention and regularity. We show that the N1b and Tb components of the N1 response are modulated by violations of tone regularity only. However, violations of action intention as well as of regularity elicit MMN responses, which occur similarly in all three conditions. Regardless of whether the predictions at sensory levels were based on either intention, regularity, or both, the tone deviance was further and equally well detected at hierarchically higher processing level, as reflected in similar P3a effects between conditions. We did not observe additive prediction errors when intention and regularity were violated concurrently, suggesting the two integrate despite presumably having independent generators. Even though they are often discussed as individual prediction sources in the literature, this study represents to our knowledge the first to directly compare them. Finally, these results show how, in the context of action, our brain can easily switch between top–down intention-based expectations and bottom–up regularity cues to efficiently predict future events.

scholarly journals Frontostriatal Contribution to the Interplay of Flexibility and Stability in Serial Prediction

2017 ◽  
Vol 29 (2) ◽  
pp. 298-309 ◽  
Author(s):  
Ima Trempler ◽  
Anne-Marike Schiffer ◽  
Nadiya El-Sourani ◽  
Christiane Ahlheim ◽  
Gereon R. Fink ◽  
...  
Keyword(s):  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Individual Performance ◽  
Button Press ◽  
Prediction Errors ◽  
Performance History ◽  
Cognitive States ◽  
Medial Pfc ◽  
Behavioral Requirements ◽  
Environmental Demands

Surprising events may be relevant or irrelevant for behavior, requiring either flexible adjustment or stabilization of our model of the world and according response strategies. Cognitive flexibility and stability in response to environmental demands have been described as separable cognitive states, associated with activity of striatal and lateral prefrontal regions, respectively. It so far remains unclear, however, whether these two states act in an antagonistic fashion and which neural mechanisms mediate the selection of respective responses, on the one hand, and a transition between these states, on the other. In this study, we tested whether the functional dichotomy between striatal and prefrontal activity applies for the separate functions of updating (in response to changes in the environment, i.e., switches) and shielding (in response to chance occurrences of events violating expectations, i.e., drifts) of current predictions. We measured brain activity using fMRI while 20 healthy participants performed a task that required to serially predict upcoming items. Switches between predictable sequences had to be indicated via button press while sequence omissions (drifts) had to be ignored. We further varied the probability of switches and drifts to assess the neural network supporting the transition between flexible and stable cognitive states as a function of recent performance history in response to environmental demands. Flexible switching between models was associated with activation in medial pFC (BA 9 and BA 10), whereas stable maintenance of the internal model corresponded to activation in the lateral pFC (BA 6 and inferior frontal gyrus). Our findings extend previous studies on the interplay of flexibility and stability, suggesting that different prefrontal regions are activated by different types of prediction errors, dependent on their behavioral requirements. Furthermore, we found that striatal activation in response to switches and drifts was modulated by participants' successful behavior toward these events, suggesting the striatum to be responsible for response selections following unpredicted stimuli. Finally, we observed that the dopaminergic midbrain modulates the transition between different cognitive states, thresholded by participants' individual performance history in response to temporal environmental demands.

scholarly journals Decoding the future from past experience: learning shapes predictions in early visual cortex

2015 ◽  
Vol 113 (9) ◽  
pp. 3159-3171 ◽  
Author(s):  
Caroline D. B. Luft ◽  
Alan Meeson ◽  
Andrew E. Welchman ◽  
Zoe Kourtzi
Keyword(s):  
Visual Cortex ◽  
Large Scale ◽  
Sequence Structure ◽  
Neural Populations ◽  
Early Visual Cortex ◽  
Temporal Structures ◽  
Future Events ◽  
Sensory Predictions ◽  
Actual Stimulus ◽  
The Brain

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory representations as early as in primary visual cortex.

scholarly journals LEARNING HYPERPLANES THAT CAPTURES THE GEOMETRIC STRUCTURE OF CLASS REGIONS

2013 ◽  
pp. 7-12
Author(s):  
PRAMOD PATIL ◽  
ALKA LONDHE ◽  
PARAG KULKARNI
Keyword(s):  
Decision Tree ◽  
Decision Trees ◽  
Geometric Structure ◽  
Gini Index ◽  
Decision Tree Algorithm ◽  
Top Down ◽  
Angle Bisector ◽  
Eigen Value ◽  
Tree Algorithms ◽  
Left And Right

Most of the decision tree algorithms rely on impurity measures to evaluate the goodness of hyperplanes at each node while learning a decision tree in a top-down fashion. These impurity measures are not differentiable with relation to the hyperplane parameters. Therefore the algorithms for decision tree learning using impurity measures need to use some search techniques for finding the best hyperplane at every node. These impurity measures don’t properly capture the geometric structures of the data. In this paper a Two-Class algorithm for learning oblique decision trees is proposed. Aggravated by this, the algorithm uses a strategy, to evaluate the hyperplanes in such a way that the (linear) geometric structure in the data is taken into consideration. At each node of the decision tree, algorithm finds the clustering hyperplanes for both the classes. The clustering hyperplanes are obtained by solving the generalized Eigen-value problem. Then the data is splitted based on angle bisector and recursively learn the left and right sub-trees of the node. Since, in general, there will be two angle bisectors; one is selected which is better based on an impurity measure gini index. Thus the algorithm combines the ideas of linear tendencies in data and purity of nodes to find better decision trees. This idea leads to small decision trees and better performance.

Filtering Compensation for Delays and Prediction Errors during Sensorimotor Control

2019 ◽  
Vol 31 (4) ◽  
pp. 738-764 ◽  
Author(s):  
F. Crevecoeur ◽  
M. Gevers
Keyword(s):  
Stability Margin ◽  
Optimal Estimation ◽  
Sensorimotor Control ◽  
Movement Planning ◽  
Prediction Errors ◽  
Loop Control ◽  
Major Function ◽  
Sensory Predictions ◽  
The Stability ◽  
Low Dimensional

Compensating for sensorimotor noise and for temporal delays has been identified as a major function of the nervous system. Although these aspects have often been described separately in the frameworks of optimal cue combination or motor prediction during movement planning, control-theoretic models suggest that these two operations are performed simultaneously, and mounting evidence supports that motor commands are based on sensory predictions rather than sensory states. In this letter, we study the benefit of state estimation for predictive sensorimotor control. More precisely, we combine explicit compensation for sensorimotor delays and optimal estimation derived in the context of Kalman filtering. We show, based on simulations of human-inspired eye and arm movements, that filtering sensory predictions improves the stability margin of the system against prediction errors due to low-dimensional predictions or to errors in the delay estimate. These simulations also highlight that prediction errors qualitatively account for a broad variety of movement disorders typically associated with cerebellar dysfunctions. We suggest that adaptive filtering in cerebellum, instead of often-assumed feedforward predictions, may achieve simple compensation for sensorimotor delays and support stable closed-loop control of movements.

Top–Down Inhibitory Control Exerted by the Medial Frontal Cortex during Action Selection under Conflict

2013 ◽  
Vol 25 (10) ◽  
pp. 1634-1648 ◽  
Author(s):  
Julie Duque ◽  
Etienne Olivier ◽  
Matthew Rushworth
Keyword(s):  
Frontal Cortex ◽  
Primary Motor Cortex ◽  
Single Pulse ◽  
Medial Frontal Cortex ◽  
Button Press ◽  
Top Down ◽  
Motor Representation ◽  
Visuomotor Task ◽  
Response Alternatives

Top–down control is critical to select goal-directed actions in changeable environments, particularly when several conflicting options compete for selection. In humans, this control system is thought to involve an inhibitory mechanism that suppresses the motor representation of unwanted responses to favor selection of the most appropriate action. Here, we aimed to evaluate the role of a region of the medial frontal cortex, the pre-SMA, in this form of inhibition by using a double coil TMS protocol combining repetitive TMS (rTMS) over the pre-SMA and a single-pulse TMS over the primary motor cortex (M1) during a visuomotor task that required participants to choose between a left or right button press according to an imperative cue. M1 stimulation allowed us to assess changes in motor excitability related to selected and nonselected (unwanted) actions, and rTMS was used to produce transient disruption of pre-SMA functioning. We found that when rTMS was applied over pre-SMA, inhibition of the nonselected movement representation was reduced. Importantly, this effect was only observed when the imperative cue produced a substantial amount of competition between the response alternatives. These results are consistent with previous studies pointing to a role of pre-SMA in competition resolution. In addition, our findings indicate that this function of pre-SMA involves the control of inhibitory influences directed at unwanted action representations.

scholarly journals Suggested visual blockade during hypnosis: Top-down modulation of stimulus processing in a visual oddball task

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257380
Author(s):  
Marcel Franz ◽  
Barbara Schmidt ◽  
Holger Hecht ◽  
Ewald Naumann ◽  
Wolfgang H. R. Miltner
Keyword(s):  
Computing Time ◽  
Event Related Potentials ◽  
Source Analysis ◽  
Oddball Paradigm ◽  
Top Down ◽  
Time Frequency ◽  
Frontoparietal Network ◽  
Related Potentials ◽  
Visual Oddball ◽  
Hypnotic Suggestions

Several theories of hypnosis assume that responses to hypnotic suggestions are implemented through top-down modulations via a frontoparietal network that is involved in monitoring and cognitive control. The current study addressed this issue re-analyzing previously published event-related-potentials (ERP) (N1, P2, and P3b amplitudes) and combined it with source reconstruction and connectivity analysis methods. ERP data were obtained from participants engaged in a visual oddball paradigm composed of target, standard, and distractor stimuli during a hypnosis (HYP) and a control (CON) condition. In both conditions, participants were asked to count the rare targets presented on a video screen. During HYP participants received suggestions that a wooden board in front of their eyes would obstruct their view of the screen. The results showed that participants’ counting accuracy was significantly impaired during HYP compared to CON. ERP components in the N1 and P2 window revealed no amplitude differences between CON and HYP at sensor-level. In contrast, P3b amplitudes in response to target stimuli were significantly reduced during HYP compared to CON. Source analysis of the P3b amplitudes in response to targets indicated that HYP was associated with reduced source activities in occipital and parietal brain areas related to stimulus categorization and attention. We further explored how these brain sources interacted by computing time-frequency effective connectivity between electrodes that best represented frontal, parietal, and occipital sources. This analysis revealed reduced directed information flow from parietal attentional to frontal executive sources during processing of target stimuli. These results provide preliminary evidence that hypnotic suggestions of a visual blockade are associated with a disruption of the coupling within the frontoparietal network implicated in top-down control.

scholarly journals Auditory predictions and prediction errors in response to self-initiated vowels

2019 ◽  
Author(s):  
Franziska Knolle ◽  
Michael Schwartze ◽  
Erich Schröger ◽  
Sonja A. Kotz
Keyword(s):  
Error Correction ◽  
Speech Production ◽  
Button Press ◽  
List Type ◽  
Prediction Errors ◽  
Speech Sounds ◽  
Suppression Effect ◽  
Auditory Speech ◽  
Internal Forward Model ◽  
Processing Activity

AbstractIt has been suggested that speech production is accomplished by an internal forward model, reducing processing activity directed to self-produced speech in the auditory cortex. The current study uses an established N1-suppression paradigm comparing self- and externally-initiated natural speech sounds to answer two questions:Are forward predictions generated to process complex speech sounds, such as vowels, initiated via a button press?Are prediction errors regarding self-initiated deviant vowels reflected in the corresponding ERP components?Results confirm an N1-suppression in response to self-initiated speech sounds. Furthermore, our results suggest that predictions leading to the N1-suppression effect are specific, as self-initiated deviant vowels do not elicit an N1-suppression effect. Rather, self-initiated deviant vowels elicit an enhanced N2b and P3a compared to externally-generated deviants, externally-generated standard, or self-initiated standards, again confirming prediction specificity.Results show that prediction errors are salient in self-initiated auditory speech sounds, which may lead to more efficient error correction in speech production.

scholarly journals Sensory prediction errors increase coding efficiency in mouse visual cortex through gain amplification

2021 ◽  
Author(s):  
Matthew Tang ◽  
Ehsan Kheradpezhouh ◽  
Conrad Lee ◽  
J Dickinson ◽  
Jason Mattingley ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Visual Stimuli ◽  
Population Level ◽  
Prediction Errors ◽  
V1 Neurons ◽  
Coding Efficiency ◽  
Two Photon ◽  
Future Events ◽  
Mouse Visual Cortex ◽  
Sensory Prediction

Abstract The efficiency of sensory coding is affected both by past events (adaptation) and by expectation of future events (prediction). Here we employed a novel visual stimulus paradigm to determine whether expectation influences orientation selectivity in the primary visual cortex. We used two-photon calcium imaging (GCaMP6f) in awake mice viewing visual stimuli with different levels of predictability. The stimuli consisted of sequences of grating stimuli that randomly shifted in orientation or systematically rotated with occasionally unexpected rotations. At the single neuron and population level, there was significantly enhanced orientation-selective response to unexpected visual stimuli through a boost in gain, which was prominent in awake mice but also present to a lesser extent under anesthesia. We implemented a computational model to demonstrate how neuronal responses were best characterized when adaptation and expectation parameters were combined. Our results demonstrated that adaptation and prediction have unique signatures on activity of V1 neurons.

scholarly journals Event-related potentials reflect prediction errors and pop-out during comprehension of degraded speech

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Leah Banellis ◽  
Rodika Sokoliuk ◽  
Conor J Wild ◽  
Howard Bowman ◽  
Damian Cruse
Keyword(s):  
Prediction Error ◽  
Event Related Potentials ◽  
Event Related Potential ◽  
Prediction Errors ◽  
Top Down ◽  
Degraded Speech ◽  
Related Potentials ◽  
Task Goals ◽  
Post Hoc

Abstract Comprehension of degraded speech requires higher-order expectations informed by prior knowledge. Accurate top-down expectations of incoming degraded speech cause a subjective semantic ‘pop-out’ or conscious breakthrough experience. Indeed, the same stimulus can be perceived as meaningless when no expectations are made in advance. We investigated the event-related potential (ERP) correlates of these top-down expectations, their error signals and the subjective pop-out experience in healthy participants. We manipulated expectations in a word-pair priming degraded (noise-vocoded) speech task and investigated the role of top-down expectation with a between-groups attention manipulation. Consistent with the role of expectations in comprehension, repetition priming significantly enhanced perceptual intelligibility of the noise-vocoded degraded targets for attentive participants. An early ERP was larger for mismatched (i.e. unexpected) targets than matched targets, indicative of an initial error signal not reliant on top-down expectations. Subsequently, a P3a-like ERP was larger to matched targets than mismatched targets only for attending participants—i.e. a pop-out effect—while a later ERP was larger for mismatched targets and did not significantly interact with attention. Rather than relying on complex post hoc interactions between prediction error and precision to explain this apredictive pattern, we consider our data to be consistent with prediction error minimization accounts for early stages of processing followed by Global Neuronal Workspace-like breakthrough and processing in service of task goals.

scholarly journals Difficulty of Discrimination Modulates Attentional Capture by Regulating Attentional Focus

2009 ◽  
Vol 21 (2) ◽  
pp. 359-371 ◽  
Author(s):  
Risa Sawaki ◽  
Jun'ichi Katayama
Keyword(s):  
Spatial Attention ◽  
Attentional Capture ◽  
Attentional Focus ◽  
Oddball Paradigm ◽  
Top Down ◽  
Brain Potentials ◽  
Central Location ◽  
Cognitive Mechanism ◽  
Capture Event

Attentional capture for distractors is enhanced by increasing the difficulty of discrimination between the standard and the target in the three-stimulus oddball paradigm. In this study, we investigated the cognitive mechanism of this modulation of attentional capture. Event-related brain potentials were recorded from participants while they performed a visual three-stimulus oddball paradigm (frequent standard, rare target, and rare distractor). The discrimination difficulty between standard and target was manipulated in the central location. Distractor stimuli were presented in the central or surrounding locations. The P3a component was elicited by distractor stimuli and was used as a measure of attentional capture. The results revealed that discrimination difficulty had opposite effects on the P3a response between central and surrounding locations. With an increase in the difficulty of discrimination, the P3a response was enhanced when distractor stimuli were presented in the central location. In contrast, the P3a response was reduced when distractor stimuli were presented in a surrounding location. This finding suggests that spatial attention was focused by the difficulty of discrimination, and deviant processing was increased within its focus but decreased outside its focus. Therefore, attentional capture for deviant distractors is modulated by top–down controlled attentional focus.

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