Probabilistic Decision Making by Slow Reverberation in Cortical Circuits (original) (raw)
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Synaptic dynamics and decision making
Proceedings of the National Academy of Sciences, 2010
During decision making between sequential stimuli, the first stimulus must be held in memory and then compared with the second. Here, we show that in systems that encode the stimuli by their firing rate, neurons can use synaptic facilitation not only to remember the first stimulus during the delay but during the presentation of the second stimulus so that they respond to a combination of the first and second stimuli, as has been found for "partial differential" neurons recorded in the ventral premotor cortex during vibrotactile flutter frequency decision making. Moreover, we show that such partial differential neurons provide important input to a subsequent attractor decisionmaking network that can then compare this combination of the first and second stimuli with inputs from other neurons that respond only to the second stimulus. Thus, both synaptic facilitation and neuronal attractor dynamics can account for sequential decision making in such systems in the brain.
Frontiers in Computational Neuroscience, 2007
How do neurons in a decision circuit integrate time-varying signals, in favor of or against alternative choice options? To address this question, we used a recurrent neural circuit model to simulate an experiment in which monkeys performed a direction-discrimination task on a visual motion stimulus. In a recent study, it was found that brief pulses of motion perturbed neural activity in the lateral intraparietal area (LIP), and exerted corresponding effects on the monkey's choices and response times. Our model reproduces the behavioral observations and replicates LIP activity which, depending on whether the direction of the pulse is the same or opposite to that of a preferred motion stimulus, increases or decreases persistently over a few hundred milliseconds. Furthermore, our model accounts for the observation that the pulse exerts a weaker influence on LIP neuronal responses when the pulse is late relative to motion stimulus onset. We show that this violation of time-shift invariance (TSI) is consistent with a recurrent circuit mechanism of time integration. We further examine time integration using two consecutive pulses of the same or opposite motion directions. The induced changes in the performance are not additive, and the second of the paired pulses is less effective than its standalone impact, a prediction that is experimentally testable. Taken together, these findings lend further support for an attractor network model of time integration in perceptual decision making.
Invariant neuronal activity associated to decision making in a rewarded choice reaction time task
Freely-moving rats were trained in a decision-making reaction time task to provide data that can be compared with noise-compatibility paradigms previously obtained in humans. A group of subjects was trained at first to positively discriminate an auditory pitch in a rewarded Go/Nogo response choice task. In a subsequent phase the same tones were simultaneously presented in different combinations from two locations, such that only the correct tone presented at the correct location is triggering a reward. Other subjects were trained either to discriminate at first the location cue, whereas the pitch cue was introduced in the subsequent phase or to categorize human vowels. At the end of the second phase the rats were chronically recorded with multiple electrodes located in the auditory and inferolimbic cerebral cortical areas. Invariant preferred firing sequences both within, and across cell spike trains tended to appear in association with the response predicted by the subject, as suggested by faster reaction times, or in association with specific errors of decision.
Neuronal Correlates of a Perceptual Decision in Ventral Premotor Cortex
Neuron, 2004
f1), maintaining it in working memory, encoding the second stimulus frequency (f2), comparing it to the memory trace left by f1, and communicating the result Ranulfo Romo,* Adriá n Herná ndez, and Antonio Zainos Instituto de Fisiología Celular Universidad Nacional Autó noma de Mé xico of the comparison to the motor apparatus (Romo and Salinas, 2001). Here we report that the activity of VPC 04510 Mé xico D.F. Mé xico neurons reflect the entire processing path required to solving this perceptual task. Many neurons encoded f1 during both the stimulus presentation and during the delay period between f1 and f2. The responses during Summary the comparison period were a function of both the remembered (f1) and current (f2) stimulus and were ob-The ventral premotor cortex (VPC) is involved in the transformation of sensory information into action, al-served to change, after a few hundred milliseconds, into responses that were correlated with the animal's though the exact neuronal operation is not known. We addressed this problem by recording from single decision. In addition, we reanalyze and discuss the relative contributions of some other cortical areas re-neurons in VPC while trained monkeys report a decision based on the comparison of two mechanical vi-sponding during the vibrotactile discrimination task (Herná ndez et al., . brations applied sequentially to the fingertips. Here we report that the activity of VPC neurons reflects
Decoding a Decision Process in the Neuronal Population of Dorsal Premotor Cortex
Neuron, 2017
When trained monkeys discriminate the temporal structure of two sequential vibrotactile stimuli, dorsal premotor cortex (DPC) showed high heterogeneity among its neuronal responses. Notably, DPC neurons coded stimulus patterns as broader categories and signaled them during working memory, comparison, and postponed decision periods. Here, we show that such population activity can be condensed into two major coding components: one that persistently represented in working memory both the first stimulus identity and the postponed informed choice and another that transiently coded the initial sensory information and the result of the comparison between the two stimuli. Additionally, we identified relevant signals that coded the timing of task events. These temporal and task-parameter readouts were shown to be strongly linked to the monkeys' behavior when contrasted to those obtained in a non-demanding cognitive control task and during error trials. These signals, hidden in the hetero...
Brain mechanisms for perceptual and reward-related decision-making
Progress in neurobiology, 2013
Phenomenological models of decision-making, including the drift-diffusion and race models, are compared with mechanistic, biologically plausible models, such as integrate-and-fire attractor neuronal network models. The attractor network models show how decision confidence is an emergent property; and make testable predictions about the neural processes (including neuronal activity and fMRI signals) involved in decision-making which indicate that the medial prefrontal cortex is involved in reward value-based decision-making. Synaptic facilitation in these models can help to account for sequential vibrotactile decision-making, and for how postponed decision-related responses are made. The randomness in the neuronal spiking-related noise that makes the decision-making probabilistic is shown to be increased by the graded firing rate representations found in the brain, to be decreased by the diluted connectivity, and still to be significant in biologically large networks with thousands o...
Dynamics of Cortical Neuronal Ensembles Transit from Decision Making to Storage for Later Report
Journal of Neuroscience, 2012
Decisions based on sensory evaluation during single trials may depend on the collective activity of neurons distributed across brain circuits. Previous studies have deepened our understanding of how the activity of individual neurons relates to the formation of a decision and its storage for later report. However, little is known about how decision-making and decision maintenance processes evolve in single trials. We addressed this problem by studying the activity of simultaneously recorded neurons from different somatosensory and frontal lobe cortices of monkeys performing a vibrotactile discrimination task. We used the hidden Markov model to describe the spatiotemporal pattern of activity in single trials as a sequence of firing rate states. We show that the animal's decision was reliably maintained in frontal lobe activity through a selective state sequence, initiated by an abrupt state transition, during which many neurons changed their activity in a concomitant way, and for which both latency and variability depended on task difficulty. Indeed, transitions were more delayed and more variable for difficult trials compared with easy trials. In contrast, state sequences in somatosensory cortices were weakly decision related, had less variable transitions, and were not affected by the difficulty of the task. In summary, our results suggest that the decision process and its subsequent maintenance are dynamically linked by a cascade of transient events in frontal lobe cortices.
A Recurrent Network Mechanism of Time Integration in Perceptual Decisions
Journal of Neuroscience, 2006
Recent physiological studies using behaving monkeys revealed that, in a two-alternative forced-choice visual motion discrimination task, reaction time was correlated with ramping of spike activity of lateral intraparietal cortical neurons. The ramping activity appears to reflect temporal accumulation, on a timescale of hundreds of milliseconds, of sensory evidence before a decision is reached. To elucidate the cellular and circuit basis of such integration times, we developed and investigated a simplified two-variable version of a biophysically realistic cortical network model of decision making. In this model, slow time integration can be achieved robustly if excitatory reverberation is primarily mediated by NMDA receptors; our model with only fast AMPA receptors at recurrent synapses produces decision times that are not comparable with experimental observations. Moreover, we found two distinct modes of network behavior, in which decision computation by winner-take-all competition is instantiated with or without attractor states for working memory. Decision process is closely linked to the local dynamics, in the "decision space" of the system, in the vicinity of an unstable saddle steady state that separates the basins of attraction for the two alternative choices. This picture provides a rigorous and quantitative explanation for the dependence of performance and response time on the degree of task difficulty, and the reason for which reaction times are longer in error trials than in correct trials as observed in the monkey experiment. Our reduced two-variable neural model offers a simple yet biophysically plausible framework for studying perceptual decision making in general.
The Journal of Neuroscience : The Official Journal of the Society for Neuroscience
Decisions about the visual world can take time to form, especially when information is unreliable. We studied the neural correlate of gradual decision formation by recording activity from the lateral intraparietal cortex (area LIP) of rhesus monkeys during a combined motion-discrimination reaction-time task. Monkeys reported the direction of random-dot motion by making an eye movement to one of two peripheral choice targets, one of which was within the response field of the neuron. We varied the difficulty of the task and measured both the accuracy of direction discrimination and the time required to reach a decision. Both the accuracy and speed of decisions increased as a function of motion strength. During the period of decision formation, the epoch between onset of visual motion and the initiation of the eye movement response, LIP neurons underwent ramp-like changes in their discharge rate that predicted the monkey's decision. A steeper rise in spike rate was associated with ...
Temporal precision of neuronal information in a rapid perceptual judgment
Journal of neurophysiology, 2009
In many situations, such as pedestrians crossing a busy street or prey evading predators, rapid decisions based on limited perceptual information are critical for survival. The brevity of these perceptual judgments constrains how neuronal signals are integrated or pooled over time because the underlying sequence of processes, from sensation to perceptual evaluation to motor planning and execution, all occur within several hundred milliseconds. Because most previous physiological studies of these processes have relied on tasks requiring considerably longer temporal integration, the neuronal basis of such rapid decisions remains largely unexplored. In this study, we examine the temporal precision of neuronal activity associated with a rapid perceptual judgment. We find that the activity of individual neurons over tens of milliseconds can reliably convey information about sensory events and was well correlated with the animals' judgments. There was a strong correlation between sensory reliability and the correlation with behavioral choice, suggesting that rapid decisions were preferentially based on the most reliable sensory signals. We also find that a simple model in which the responses of a small number of individual neurons (Ͻ5) are summed can completely explain behavioral performance. These results suggest that neuronal circuits are sufficiently precise to allow for cognitive decisions to be based on small numbers of action potentials from highly reliable neurons.