scholarly journals An orderly single-trial organization of population dynamics in premotor cortex predicts behavioral variability

2018 ◽  
Author(s):  
Ziqiang Wei ◽  
Hidehiko Inagaki ◽  
Nuo Li ◽  
Karel Svoboda ◽  
Shaul Druckmann
Keyword(s):  
Decision Making ◽  
Brain Function ◽  
Premotor Cortex ◽  
Neural Correlates ◽  
Neural Population ◽  
Behavioral Variability ◽  
Perceptual Decision Making ◽  
Population Activity ◽  
Long Time ◽  
Dynamical Nature

AbstractAnimals are not simple input-output machines. Their responses to even very similar stimuli are variable. A key, long-standing question in neuroscience is understanding the neural correlates of such behavioral variability. To reveal these correlates, behavior and neural population must be related to one another on single trials. Such analysis is challenging due to the dynamical nature of brain function (e.g. decision making), neuronal heterogeneity and signal to noise difficulties. By analyzing population recordings from mouse frontal cortex in perceptual decision-making tasks, we show that an analysis approach tailored to the coarse grain features of the dynamics was able to reveal previously unrecognized structure in the organization of population activity. This structure was similar on error and correct trials, suggesting what may be the underlying circuit mechanisms, was able to predict multiple aspects of behavioral variability and revealed long time-scale modulation of population activity.

scholarly journals Can binocular rivalry reveal neural correlates of consciousness?

2014 ◽  
Vol 369 (1641) ◽  
pp. 20130211 ◽  
Author(s):  
Randolph Blake ◽  
Jan Brascamp ◽  
David J. Heeger
Keyword(s):  
Decision Making ◽  
Binocular Rivalry ◽  
Neural Activity ◽  
Neural Correlates ◽  
Causal Link ◽  
Neural Dynamics ◽  
Perceptual Decision Making ◽  
Neural Correlate ◽  
Neural Correlates Of Consciousness ◽  
Neural Correlate Of Consciousness

This essay critically examines the extent to which binocular rivalry can provide important clues about the neural correlates of conscious visual perception. Our ideas are presented within the framework of four questions about the use of rivalry for this purpose: (i) what constitutes an adequate comparison condition for gauging rivalry's impact on awareness, (ii) how can one distinguish abolished awareness from inattention, (iii) when one obtains unequivocal evidence for a causal link between a fluctuating measure of neural activity and fluctuating perceptual states during rivalry, will it generalize to other stimulus conditions and perceptual phenomena and (iv) does such evidence necessarily indicate that this neural activity constitutes a neural correlate of consciousness? While arriving at sceptical answers to these four questions, the essay nonetheless offers some ideas about how a more nuanced utilization of binocular rivalry may still provide fundamental insights about neural dynamics, and glimpses of at least some of the ingredients comprising neural correlates of consciousness, including those involved in perceptual decision-making.

scholarly journals Slow drift of neural activity as a signature of impulsivity in macaque visual and prefrontal cortex

2020 ◽  
Author(s):  
Benjamin R. Cowley ◽  
Adam C. Snyder ◽  
Katerina Acar ◽  
Ryan C. Williamson ◽  
Byron M. Yu ◽  
...  
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Neural Activity ◽  
Internal State ◽  
Sensory Stimulus ◽  
Perceptual Decision Making ◽  
Population Activity ◽  
Perceptual Decision ◽  
Slow Drift ◽  
Sensory Evidence

AbstractAn animal’s decision depends not only on incoming sensory evidence but also on its fluctuating internal state. This internal state is a product of cognitive factors, such as fatigue, motivation, and arousal, but it is unclear how these factors influence the neural processes that encode the sensory stimulus and form a decision. We discovered that, over the timescale of tens of minutes during a perceptual decision-making task, animals slowly shifted their likelihood of reporting stimulus changes. They did this unprompted by task conditions. We recorded neural population activity from visual area V4 as well as prefrontal cortex, and found that the activity of both areas slowly drifted together with the behavioral fluctuations. We reasoned that such slow fluctuations in behavior could either be due to slow changes in how the sensory stimulus is processed or due to a process that acts independently of sensory processing. By analyzing the recorded activity in conjunction with models of perceptual decision-making, we found evidence for the slow drift in neural activity acting as an impulsivity signal, overriding sensory evidence to dictate the final decision. Overall, this work uncovers an internal state embedded in the population activity across multiple brain areas, hidden from typical trial-averaged analyses and revealed only when considering the passage of time within each experimental session. Knowledge of this cognitive factor was critical in elucidating how sensory signals and the internal state together contribute to the decision-making process.

scholarly journals Neural Correlates of Optimal Multisensory Decision Making

2018 ◽  
Author(s):  
Han Hou ◽  
Qihao Zheng ◽  
Yuchen Zhao ◽  
Alexandre Pouget ◽  
Yong Gu
Keyword(s):  
Decision Making ◽  
Neural Correlates ◽  
Time Varying ◽  
Population Code ◽  
Close Approximation ◽  
Linear Combinations ◽  
Population Activity ◽  
Lateral Intraparietal Area ◽  
Sensory Inputs ◽  
Time Invariant

AbstractPerceptual decisions are often based on multiple sensory inputs whose reliabilities rapidly vary over time, yet little is known about how our brain integrates these inputs to optimize behavior. Here we show multisensory evidence with time-varying reliability can be accumulated near optimally, in a Bayesian sense, by simply taking time-invariant linear combinations of neural activity across time and modalities, as long as the neural code for the sensory inputs is close to an invariant linear probabilistic population code (ilPPC). Recordings in the lateral intraparietal area (LIP) while macaques optimally performed a vestibular-visual multisensory decision-making task revealed that LIP population activity reflects an integration process consistent with the ilPPC theory. Moreover, LIP accumulates momentary evidence proportional to vestibular acceleration and visual velocity which are encoded in sensory areas with a close approximation to ilPPCs. Together, these results provide a remarkably simple and biologically plausible solution to optimal multisensory decision making.

scholarly journals Neural Correlates of Evidence and Urgency During Human Perceptual Decision-Making in Dynamically Changing Conditions

2020 ◽  
Vol 30 (10) ◽  
pp. 5471-5483
Author(s):  
Y Yau ◽  
M Dadar ◽  
M Taylor ◽  
Y Zeighami ◽  
L K Fellows ◽  
...  
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Sensory Information ◽  
Neural Correlates ◽  
Primate Research ◽  
Perceptual Decision Making ◽  
Emotional Information ◽  
Perceptual Decision ◽  
The Face ◽  
The Brain

Abstract Current models of decision-making assume that the brain gradually accumulates evidence and drifts toward a threshold that, once crossed, results in a choice selection. These models have been especially successful in primate research; however, transposing them to human fMRI paradigms has proved it to be challenging. Here, we exploit the face-selective visual system and test whether decoded emotional facial features from multivariate fMRI signals during a dynamic perceptual decision-making task are related to the parameters of computational models of decision-making. We show that trial-by-trial variations in the pattern of neural activity in the fusiform gyrus reflect facial emotional information and modulate drift rates during deliberation. We also observed an inverse-urgency signal based in the caudate nucleus that was independent of sensory information but appeared to slow decisions, particularly when information in the task was ambiguous. Taken together, our results characterize how decision parameters from a computational model (i.e., drift rate and urgency signal) are involved in perceptual decision-making and reflected in the activity of the human brain.

scholarly journals Neural Correlates of Sequence Learning with Stochastic Feedback

2011 ◽  
Vol 23 (6) ◽  
pp. 1346-1357
Author(s):  
Bruno B. Averbeck ◽  
James Kilner ◽  
Christopher D. Frith
Keyword(s):  
Decision Making ◽  
Sequence Learning ◽  
Premotor Cortex ◽  
Learning Task ◽  
Neural Correlates ◽  
Single Step ◽  
Button Press ◽  
Behavioral Models ◽  
Sequential Decision ◽  
Early Effect

Although much is known about decision making under uncertainty when only a single step is required in the decision process, less is known about sequential decision making. We carried out a stochastic sequence learning task in which subjects had to use noisy feedback to learn sequences of button presses. We compared flat and hierarchical behavioral models and found that although both models predicted the choices of the group of subjects equally well, only the hierarchical model correlated significantly with learning-related changes in the magneto-encephalographic response. The significant modulations in the magneto-encephalographic signal occurred 83 msec before button press and 67 msec after button press. We also localized the sources of these effects and found that the early effect localized to the insula, whereas the late effect localized to the premotor cortex.

scholarly journals Subject- and task-independent neural correlates and prediction of decision confidence in perceptual decision making

2021 ◽  
Author(s):  
Jacobo Fernandez-Vargas ◽  
Christoph Tremmel ◽  
Davide Valeriani ◽  
Saugat Bhattacharyya ◽  
Caterina Cinel ◽  
...  
Keyword(s):  
Decision Making ◽  
Neural Correlates ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Decision Confidence ◽  
And Task

scholarly journals Residual dynamics resolves recurrent contributions to neural computation

2021 ◽  
Author(s):  
Aniruddh R Galgali ◽  
Maneesh Sahani ◽  
Valerio Mante
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Neural Circuit ◽  
Neural Population ◽  
Perceptual Decision Making ◽  
Neural Recordings ◽  
Fine Grained ◽  
Neural Computations ◽  
Population Trajectory ◽  
The Mean

Relating neural activity to behavior requires an understanding of how neural computations arise from the coordinated dynamics of distributed, recurrently connected neural populations. However, inferring the nature of recurrent dynamics from partial recordings of a neural circuit presents significant challenges. Here, we show that some of these challenges can be overcome by a fine-grained analysis of the dynamics of neural residuals, i.e. trial-by-trial variability around the mean neural population trajectory for a given task condition. Residual dynamics in macaque pre-frontal cortex (PFC) in a saccade-based perceptual decision-making task reveals recurrent dynamics that is time-dependent, but consistently stable, and implies that pronounced rotational structure in PFC trajectories during saccades are driven by inputs from upstream areas. The properties of residual dynamics restrict the possible contributions of PFC to decision-making and saccade generation, and suggest a path towards fully characterizing distributed neural computations with large-scale neural recordings and targeted causal perturbations.

scholarly journals Frequency shifts and depth dependence of premotor beta band activity during perceptual decision-making

2018 ◽  
Author(s):  
Chandramouli Chandrasekaran ◽  
Iliana E. Bray ◽  
Krishna V. Shenoy
Keyword(s):  
Decision Making ◽  
Rhesus Macaques ◽  
Premotor Cortex ◽  
Arm Movement ◽  
Frequency Range ◽  
Perceptual Decision Making ◽  
Beta Band ◽  
High Beta ◽  
Beta Frequency ◽  
Band Activity

ABSTRACTNeural activity in the premotor and motor cortex shows prominent structure in the beta frequency range (13-30 Hz). Currently, the behavioral relevance of beta band activity (BBA) in premotor and motor regions is not well understood. The underlying source of motor BBA and how it changes as a function of cortical depth is also unknown. Here, we addressed these unresolved questions by investigating BBA recorded using laminar electrodes in the dorsal premotor cortex (PMd) of two male rhesus macaques performing a visual reaction time (RT) reach discrimination task. We observed robust BBA before and after the onset of the visual stimulus but not during the arm movement. While post-stimulus BBA was positively correlated with RT throughout the beta frequency range, pre-stimulus correlation varied by frequency. Low beta frequencies (~15 to 20 Hz) were positively correlated with RT and high beta frequencies (~25 to 30 Hz) were negatively correlated with RT. Simulations suggested that these frequency-dependent correlations could be due to a shift in the component frequencies of the pre-stimulus BBA as a function of RT, such that faster RTs are accompanied by greater power in high beta frequencies. We also observed a laminar dependence of BBA, with deeper electrodes demonstrating stronger power in low beta frequencies both pre- and post-stimulus. The heterogeneous nature of BBA and the changing relationship between BBA and RT in different task epochs may be a sign of the differential network dynamics involved in expectation, decision-making, and motor preparation.

Neural correlates of bias in perceptual decision making

2013 ◽  
Author(s):  
Martijn J. Mulder ◽  
Eric-Jan Wagenmakers ◽  
Roger Ratcliff ◽  
Wouter Boekel ◽  
Birte U. Forstmann
Keyword(s):  
Decision Making ◽  
Neural Correlates ◽  
Perceptual Decision Making ◽  
Perceptual Decision
Sign in / Sign up

Export Citation Format

Share Document