scholarly journals Simultaneous multi-area recordings suggest that attention improves performance by reshaping stimulus representations

2018 ◽  
Author(s):  
Douglas A. Ruff ◽  
Marlene R. Cohen
Keyword(s):  
Sensory Information ◽  
The Novel ◽  
Neuronal Responses ◽  
Visual Neurons ◽  
Neuronal Mechanisms ◽  
Oculomotor Neurons ◽  
Health And Disease ◽  
Neural Underpinnings ◽  
And Behavior ◽  
The Relationship

AbstractVisual attention dramatically improves subjects’ ability to see and also modulates the responses of neurons in every known visual and oculomotor area, but whether those modulations can account for perceptual improvements remains unclear. We measured the relationship between populations of visual neurons, oculomotor neurons, and behavior during detection and discrimination tasks. We found that neither of the two prominent hypothesized neuronal mechanisms underlying attention (which concern changes in information coding and the way sensory information is read out) provide a satisfying account of the observed behavioral improvements. Instead, our results are more consistent with the novel hypothesis that attention reshapes the representation of attended stimuli to more effectively influence behavior. Our results suggest a path toward understanding the neural underpinnings of perception and cognition in health and disease by analyzing neuronal responses in ways that are constrained by behavior and interactions between brain areas.

scholarly journals Topological insights into the neural basis of flexible behavior

2021 ◽  
Author(s):  
Tevin C. Rouse ◽  
Amy M. Ni ◽  
Chengcheng Huang ◽  
Marlene R. Cohen
Keyword(s):  
Mechanistic Model ◽  
Network Control ◽  
Topological Data Analysis ◽  
Neural Basis ◽  
Visual Neurons ◽  
Neural Computations ◽  
Flexible Behavior ◽  
Health And Disease ◽  
The Subject ◽  
And Behavior

1AbstractIt is widely accepted that there is an inextricable link between neural computations, biological mechanisms, and behavior, but there exists no framework that can simultaneously explain all three. Here, we show that topological data analysis (TDA) provides that necessary bridge. We demonstrate that cognitive processes change the topological description of the shared activity of populations of visual neurons. These topological changes provide uniquely strong constraints on a mechanistic model, explain behavior, and, via a link with network control theory, reveal a tradeoff between improving sensitivity to subtle visual stimulus changes and increasing the chance that the subject will stray off task. These discoveries provide a blueprint for using TDA to uncover the biological and computational mechanisms by which cognition affects behavior in health and disease.

scholarly journals The relationship between multisensory associative learning and multisensory integration

2020 ◽  
Author(s):  
Sébastien Á. Lauzon ◽  
Arin. E. Abraham ◽  
Kristina Curcin ◽  
Ryan A. Stevenson
Keyword(s):  
Associative Learning ◽  
Multisensory Integration ◽  
Sensory Information ◽  
Race Model ◽  
Neural Underpinnings ◽  
Eeg Recordings ◽  
Stimulus Features ◽  
Learning Guide ◽  
Response Task ◽  
The Relationship

AbstractOur perception of the world around us is inherently multisensory, and integrating sensory information from multiple modalities leads to more precise and efficient perception and behaviour. Determining which sensory information from different modalities should be perceptually bound is a key component of multisensory integration. To accomplish this feat, our sensory systems rely on both low-level stimulus features, as well as multisensory associations learned throughout development based on the statistics of our environment. The present study explored the relationship between multisensory associative learning and multisensory integration using encephalography (EEG) and behavioural measures. Sixty-one participants completed a three-phase study. First, participants were exposed to novel pairings audiovisual shape-tone pairings with frequent and infrequent stimulus pairings and complete a target detection task. EEG recordings of the mismatch negativity (MMN) and P3 were calculated as neural indices of multisensory associative learning. Next, the same learned stimulus pairs presented in audiovisual as well as unisensory auditory and visual modalities while both early (<120 ms) and late neural indices of multisensory integration were recorded. Finally, participants completed an analogous behavioural speeded-response task, with behavioural indices of multisensory gain calculated using the race model. Significant relationships were found in fronto-central and occipital areas between neural measures of associative learning and both early and late indices of multisensory integration in frontal and centro-parietal areas, respectively. Participants who showed stronger indices of associative learning also exhibited stronger indices of multisensory integration of the stimuli they learned to associate. Furthermore, a significant relationship was found between neural index of early multisensory integration and behavioural indices of multisensory gain. These results provide insight into the neural underpinnings of how higher-order processes such as associative learning guide multisensory integration.

scholarly journals A general decoding strategy explains the relationship between behavior and correlated variability

2020 ◽  
Author(s):  
Amy M. Ni ◽  
Chengcheng Huang ◽  
Brent Doiron ◽  
Marlene R. Cohen
Keyword(s):  
Stimulus Change ◽  
Sensory Information ◽  
Neuronal Responses ◽  
Attention Task ◽  
Population Responses ◽  
Stimulus Response ◽  
Natural Vision ◽  
Perceptual Performance ◽  
The Relationship ◽  
Single Set

ABSTRACTIncreases in perceptual performance correspond to decreases in the correlated variability of sensory neuron responses. No sensory information decoding mechanism has yet explained this relationship. We hypothesize that when observers must respond to a stimulus change of any magnitude, decoders prioritize generality: a single set of neuronal weights to decode any stimulus response. Our mechanistic circuit model supports that a general decoding strategy explains the inverse relationship between perceptual performance and V4 correlated variability observed in two rhesus monkeys performing a visual attention task. Further, based on the recorded V4 population responses, a monkey’s decoding mechanism was more closely matched the more broad the range of stimulus changes used to compute a sensory information decoder. These results support that observers use a general sensory information decoding strategy based on a single set of decoding weights, capable of decoding neuronal responses to the wide variety of stimuli encountered in natural vision.

scholarly journals Dynamic task-belief is an integral part of decision-making

2021 ◽  
Author(s):  
Cheng Xue ◽  
Lily E Kramer ◽  
Marlene R Cohen
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Task Demands ◽  
Perceptual Decision Making ◽  
Visual Neurons ◽  
Dynamic Task ◽  
Neuronal Populations ◽  
Health And Disease ◽  
Belief Changes ◽  
And Behavior

Unlike in laboratory settings, natural decisions are often made under uncertain beliefs about task demands. To quantify the unexplored dynamics between task-belief and decisions, we trained macaque monkeys to make perceptual discriminations under implicitly evolving task rules. By analyzing task- and perception-related signals from simultaneously recorded neuronal populations in cortical areas 7a and V1, we demonstrated that fluctuating task-belief and perceptual decision-making are inextricably linked. Stronger task-belief is correlated with better perception, and in turn, response fluctuations in visual neurons affect task-belief changes. Our results demonstrate that combining large-scale inter-area recordings with rigorously controlled complex, realistic behaviors can bring new understanding of the relationship between cognition and behavior in health and disease.

PERSEPSI PETERNAK PADA KEPEMIMPINAN PENDAMPING DAN HUBUNGANNYA DENGAN PRODUKTIVITAS USAHA TERNAK DI PAGUYUBAN AL-AWWALIYAH, PASIRWANGI, GARUT, JAWA BARAT

2019 ◽  
Vol 12 (1) ◽  
pp. 42-51
Author(s):  
Dwi Indah Sulistiani ◽  
Ujang Maman ◽  
Junaidi J
Keyword(s):  
Data Analysis ◽  
Secondary Data ◽  
Primary Data ◽  
Leadership Qualities ◽  
Chi Square ◽  
Education Experience ◽  
Spss Software ◽  
Chi Square Analysis ◽  
And Behavior ◽  
The Relationship

Objective of this research; 1) determine the perception of ranchers against the properties and behavior of the leadership of the companion in the Society of Al-Awwaliyah 2) analyze the relationship between productivity breeder with productivity of livestock in the Society of Al-Awwaliyah 3) identify the relationship perceptions of ranchers against the leadership companion with productivity of livestock in the Society of Al-Awwaliyah , The data used in this study are primary and secondary data. Primary data were obtained from questionnaires which stem from ranchers while secondary data sourced from literature in the form of books and articles. Data processing was performed using Chi-square analysis using SPSS software version 21. One of the factors relating to the productivity of ranchers is the perception of ranchers against the leadership of their companion. Leadership companion views of the nature and behavior of which is owned by a companion. Productivity ranchers indirectly related to the productivity of the cattle business. Characteristics breeder visits of age, years of education, experience ranchers, and businesses in addition to ranchers. The results of data analysis showed that there is a significant relationship between business other than ranchers with ranchers productivity. The relationship between the perception of the nature of the companion breeder with productivity ranchers produce Pearson Chi-Square value is 9.751 and Asymp. Sig. (2-sided) of 0.002. This is due to interest ranchers against leadership qualities possessed by a companion who produce prolific ranchers. Ranchers consider that a companion of his leadership qualities are ideal as a companion.

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