Sparse regularized regression identifies behaviorally-relevant stimulus features from psychophysical data

2012 ◽  
Vol 131 (5) ◽  
pp. 3953-3969 ◽  
Author(s):  
Vinzenz H. Schönfelder ◽  
Felix A. Wichmann
Keyword(s):  
Regularized Regression ◽  
Relevant Stimulus ◽  
Psychophysical Data ◽  
Stimulus Features

scholarly journals Basing Perceptual Decisions on the Most Informative Sensory Neurons

2010 ◽  
Vol 104 (4) ◽  
pp. 2266-2273 ◽  
Author(s):  
Miranda Scolari ◽  
John T. Serences
Keyword(s):  
Sensory Neurons ◽  
Functional Magnetic Resonance ◽  
Relevant Stimulus ◽  
Unit Recording ◽  
Channel Activation ◽  
Specific Stimulus ◽  
Stimulus Features ◽  
Perceptual Acuity ◽  
Predictive Relationship ◽  
Extensive Practice

Single unit recording studies show that perceptual decisions are often based on the output of sensory neurons that are maximally responsive (or “tuned”) to relevant stimulus features. However, when performing a difficult discrimination between two highly similar stimuli, perceptual decisions should instead be based on the activity of neurons tuned away from the relevant feature ( off-channel neurons) as these neurons undergo a larger firing rate change and are thus more informative. To test this hypothesis, we measured feature-selective responses in human primary visual cortex (V1) using functional magnetic resonance imaging and show that the degree of off-channel activation predicts performance on a difficult visual discrimination task. Moreover, this predictive relationship between off-channel activation and perceptual acuity is not simply the result of extensive practice with a specific stimulus feature (as in studies of perceptual learning). Instead, relying on the output of the most informative sensory neurons may represent a general, and optimal, strategy for efficiently computing perceptual decisions.

Auditory Warning Signals Affect Mechanisms of Response Selection

2010 ◽  
Vol 57 (2) ◽  
pp. 89-97 ◽  
Author(s):  
Rico Fischer ◽  
Franziska Plessow ◽  
Andrea Kiesel
Keyword(s):  
Selective Attention ◽  
Response Selection ◽  
Reaction Times ◽  
Relevant Stimulus ◽  
Attention Task ◽  
Stimulus Response ◽  
Spatial Stimulus ◽  
Direct Route ◽  
Stimulus Features ◽  
Indirect Route

Irrelevant tone (accessory) stimuli facilitate performance in simple and choice reaction time tasks. In the present study, we combined accessory stimulation with a selective attention paradigm in order to investigate its influence on mechanisms of response selection. In the framework of a spatial stimulus-response compatibility task (Simon task), we tested whether accessory stimuli selectively affect bottom up triggered response activation processes (e.g., direct route processing), processing of task-relevant stimulus features (indirect route processing), or both/none. Results suggest a two-component effect of accessory stimuli within this selective attention task. First, accessory stimuli increased the Simon effect due to beneficial direct route processing. Second, accessory stimuli generally decreased reaction times indicating facilitation of indirect route processing.

Perceptual Deficit in Schizophrenia: A Defect in Redundancy Utilization, Filtering or Scanning?

1980 ◽  
Vol 137 (4) ◽  
pp. 352-360 ◽  
Author(s):  
D. J. Caudrey ◽  
K. Kirk ◽  
P. C. Thomas ◽  
K. O. Ng
Keyword(s):  
Selective Attention ◽  
Irrelevant Stimulus ◽  
Relevant Stimulus ◽  
Control Groups ◽  
Perceptual Field ◽  
Schizophrenic Patients ◽  
Stimulus Features ◽  
Feature Dimension ◽  
Selective Attention Deficits ◽  
Holistic Manner

SummaryThe perception by schizophrenic patients of stimuli with more than one feature (dimension) was investigated using psychiatric and non-psychiatric control groups. Indices of the ability (a) to make use of redundant stimulus cues, (b) to ‘screen out’ or filter irrelevant stimulus features, and (c) to scan the perceptual field for relevant stimulus features, indicated that only filtering was consistently poor in schizophrenia. It has been suggested that the schizophrenic patient may tend to perceive his environment in an undifferentiated holistic manner rather than in an analytic manner and the implication for the theory of left hemisphere pathology in schizophrenia is discussed. However, the performance of the schizophrenic subjects did not differ significantly from that of the group of depressed patients, which suggests that the selective attention deficits previously observed in schizophrenia are not specific to the disorder.

Time-Based Expectancy for Task Relevant Stimulus Features

2016 ◽  
Vol 4 (3) ◽  
pp. 248-270 ◽  
Author(s):  
Roland Thomaschke ◽  
Joachim Hoffmann ◽  
Carola Haering ◽  
Andrea Kiesel
Keyword(s):  
Choice Experiment ◽  
Target Stimulus ◽  
Forced Choice ◽  
Behavioral Pattern ◽  
The Other ◽  
Relevant Stimulus ◽  
Response Expectancy ◽  
Frequent Interval ◽  
Stimulus Features

When a particular target stimulus appears more frequently after a certain interval than after another one, participants adapt to such regularity, as evidenced by faster responses to frequent interval-target combinations than to infrequent ones. This phenomenon is known as time-based expectancy. Previous research has suggested that time-based expectancy is primarily motor-based, in the sense that participants learn to prepare a particular response after a specific interval. Perceptual time-based expectancy — in the sense of learning to perceive a certain stimulus after specific interval — has previously not been observed. We conducted a Two-Alternative-Forced-Choice experiment with four stimuli differing in shape and orientation. A subset of the stimuli was frequently paired with a certain interval, while the other subset was uncorrelated with interval. We varied the response relevance of the interval-correlated stimuli, and investigated under which conditions time-based expectancy transfers from trials with interval-correlated stimuli to trials with interval-uncorrelated stimuli. Transfer was observed only where transfer of perceptual expectancy and transfer of response expectancy predicted the same behavioral pattern, not when they predicted opposite patterns. The results indicate that participants formed time-based expectancy for stimuli as well as for responses. However, alternative interpretations are also discussed.

scholarly journals Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent Stickiness

2016 ◽  
Vol 28 (2) ◽  
pp. 333-349 ◽  
Author(s):  
Matthew Balcarras ◽  
Salva Ardid ◽  
Daniel Kaping ◽  
Stefan Everling ◽  
Thilo Womelsdorf
Keyword(s):  
Reinforcement Learning ◽  
Choice Behavior ◽  
Selection Process ◽  
Attentional Selection ◽  
Stimulus Selection ◽  
Action Plans ◽  
Relevant Stimulus ◽  
Learning Mechanisms ◽  
Feature Based ◽  
Stimulus Features

Attention includes processes that evaluate stimuli relevance, select the most relevant stimulus against less relevant stimuli, and bias choice behavior toward the selected information. It is not clear how these processes interact. Here, we captured these processes in a reinforcement learning framework applied to a feature-based attention task that required macaques to learn and update the value of stimulus features while ignoring nonrelevant sensory features, locations, and action plans. We found that value-based reinforcement learning mechanisms could account for feature-based attentional selection and choice behavior but required a value-independent stickiness selection process to explain selection errors while at asymptotic behavior. By comparing different reinforcement learning schemes, we found that trial-by-trial selections were best predicted by a model that only represents expected values for the task-relevant feature dimension, with nonrelevant stimulus features and action plans having only a marginal influence on covert selections. These findings show that attentional control subprocesses can be described by (1) the reinforcement learning of feature values within a restricted feature space that excludes irrelevant feature dimensions, (2) a stochastic selection process on feature-specific value representations, and (3) value-independent stickiness toward previous feature selections akin to perseveration in the motor domain. We speculate that these three mechanisms are implemented by distinct but interacting brain circuits and that the proposed formal account of feature-based stimulus selection will be important to understand how attentional subprocesses are implemented in primate brain networks.

scholarly journals Sensory computations in the cuneate nucleus of macaques

2021 ◽  
Author(s):  
Aneesha K Suresh ◽  
Charles M. Greenspon ◽  
Qinpu He ◽  
Joshua M Rosenow ◽  
Lee E Miller ◽  
...  
Keyword(s):  
Somatosensory Cortex ◽  
Receptive Fields ◽  
Nerve Fibers ◽  
Geometric Features ◽  
Cuneate Nucleus ◽  
Relevant Stimulus ◽  
Tactile Information ◽  
Conventional View ◽  
Random Dot Patterns ◽  
Stimulus Features

In primates, the responses of individual neurons in primary somatosensory cortex (S1) reflect convergent input from multiple classes of nerve fibers and are selective for behaviorally relevant stimulus features. The conventional view is that these response properties reflect computations that are effected in cortex, implying that sensory signals are not meaningfully processed in the two intervening structures - the Cuneate Nucleus (CN) and the thalamus. To test this hypothesis, we recorded the responses evoked in CN to a battery of stimuli that have been extensively used to characterize tactile coding, including skin indentations, vibrations, random dot patterns, and scanned edges. We found that CN responses are more similar to their S1 counterparts than they are to their inputs: CN neurons receive input from multiple sub-modalities, have spatially complex receptive fields, and exhibit selectivity for geometric features. Thus, CN plays a key role in the processing of tactile information.

scholarly journals Neural correlations enable invariant coding and perception of natural stimuli in weakly electric fish

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Michael G Metzen ◽  
Volker Hofmann ◽  
Maurice J Chacron
Keyword(s):  
Electric Fish ◽  
Neural Circuit ◽  
Neural Representation ◽  
Weakly Electric Fish ◽  
Relevant Stimulus ◽  
Invariant Representation ◽  
Natural Stimuli ◽  
Neural Representations ◽  
Stimulus Features ◽  
Weakly Electric

Neural representations of behaviorally relevant stimulus features displaying invariance with respect to different contexts are essential for perception. However, the mechanisms mediating their emergence and subsequent refinement remain poorly understood in general. Here, we demonstrate that correlated neural activity allows for the emergence of an invariant representation of natural communication stimuli that is further refined across successive stages of processing in the weakly electric fish Apteronotus leptorhynchus. Importantly, different patterns of input resulting from the same natural communication stimulus occurring in different contexts all gave rise to similar behavioral responses. Our results thus reveal how a generic neural circuit performs an elegant computation that mediates the emergence and refinement of an invariant neural representation of natural stimuli that most likely constitutes a neural correlate of perception.

scholarly journals Evidence for an attentional priority map in inferotemporal cortex

2019 ◽  
Vol 116 (47) ◽  
pp. 23797-23805 ◽  
Author(s):  
Heiko Stemmann ◽  
Winrich A. Freiwald
Keyword(s):  
Brain Area ◽  
Sensory Information ◽  
Attentional Selection ◽  
Inferotemporal Cortex ◽  
Relevant Stimulus ◽  
Motion Direction ◽  
Object Properties ◽  
Priority Map ◽  
Attention Tasks ◽  
Stimulus Features

From incoming sensory information, our brains make selections according to current behavioral goals. This process, selective attention, is controlled by parietal and frontal areas. Here, we show that another brain area, posterior inferotemporal cortex (PITd), also exhibits the defining properties of attentional control. We discovered this area with functional magnetic resonance imaging (fMRI) during an attentive motion discrimination task. Single-cell recordings from PITd revealed strong attentional modulation across 3 attention tasks yet no tuning to task-relevant stimulus features, like motion direction or color. Instead, PITd neurons closely tracked the subject’s attention state and predicted upcoming errors of attentional selection. Furthermore, artificial electrical PITd stimulation controlled the location of attentional selection without altering feature discrimination. These are the defining properties of a feature-blind priority map encoding the locus of attention. Together, these results suggest area PITd, located strategically to gather information about object properties, as an attentional priority map.

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