Flexible Control of Mutual Inhibition: A Neural Model of Two-Interval Discrimination

Machens, Christian K.; Romo, Ranulfo; Brody, Carlos D.

doi:10.1126/science.1104171

Cited by 485 publications

(542 citation statements)

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“…Although a substantial number of the neurons that initially carried only sensory information later developed a differential signal that predicted the motor choice, such link is difficult to prove. Another point to consider is that the MPc may be part of a larger network subserving working memory (32)(33)(34)(35)(36). This is consistent with the fact that responses similar to those reported here have been recorded in the ventral premotor cortex and in the prefrontal cortex (R.R., L.L., A.H., R.L., and A.Z., unpublished results).…”

Section: Discussionsupporting

confidence: 75%

“…It is possible, for instance, that the neurons that store information about the stimuli during the postponed decision report period are linked to the neurons that compute the difference between stimulus frequencies and thus the motor choice (32,35). Although a substantial number of the neurons that initially carried only sensory information later developed a differential signal that predicted the motor choice, such link is difficult to prove.…”

Section: Discussionmentioning

confidence: 95%

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Neural correlates of a postponed decision report

Lemus

Hernandez

Luna

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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Depending on environmental demands, a decision based on a sensory evaluation may be either immediately reported or postponed for later report. If postponed, the decision must be held in memory. But what exactly is stored by the underlying memory circuits, the final decision itself or the sensory information that led to it? Here, we report that, during a postponed decision report period, the activity of medial premotor cortex neurons encodes both the result of the sensory evaluation that corresponds to the monkey's possible choices and past sensory information on which the decision is based. These responses could switch back and forth with remarkable flexibility across the postponed decision report period. Moreover, these responses covaried with the animal's decision report. We propose that maintaining in working memory the original stimulus information on which the decision is based could serve to continuously update the postponed decision report in this task.medial premotor cortex ͉ monkeys ͉ sensory discrimination ͉ working memory S tudies in behaving monkeys that combine psychophysical and neurophysiological experiments have provided new insights into how a neural representation of a sensory stimulus relates to perception (1-8), memory (9-12), and decision making (13-19). In particular, there has been important progress regarding the neural codes associated with these cognitive functions in the visual and somatic modality (20,21). The basic philosophy of this approach has been to investigate these cognitive functions by using highly simplified stimuli, so that diverse subcortical and cortical areas can be studied during the same behavior.In the task we previously used, monkeys report whether the second stimulus frequency (f2) is higher or lower than the first stimulus frequency (f1) (22). This cognitive operation requires that subjects compare information of f1 temporally stored in working memory to the current information of f2 to form a decision of whether f2 Ͼ f1 or f2 Ͻ f1, and to immediately report the outcome by pressing one of two push buttons. We found that the activity of the recorded neurons of several cortical areas encodes f1 in a monotonic firing rate code beginning in the primary somatosensory cortex (5-7), continuing in the secondary somatosensory cortex (5), the ventral premotor cortex (19), the prefrontal cortex (10), and the medial premotor cortex (MPc) (18). Except for the primary somatosensory cortex, these cortical areas encode information of f1 during the delay period between f1 and f2 (5,10,11,(17)(18)(19). During presentation of f2, some neurons of all these cortical areas respond to f2, but some other neurons reflect past information of f1, or of the difference between f2 and f1, and generate a differential response consistent with the decision motor report (17)(18)(19). In this chain of neural processes, the primary motor cortex becomes engaged only during the motor report period (19,21). These results showed that the stimulus parameters of f1 and f2 and their interactions can be dec...

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Section: Discussionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 95%

Neural correlates of a postponed decision report

Lemus

Hernandez

Luna

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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“…To the extent that they are, their control in further experiments may result in better isolation of the passive WM described in their model. Alternatively, one might anticipate that it is inherently difficult to separate static representations from the transformations performed on them (see, for example, Machens et al 2005). Either way, it is plausible that these variables play a role in the robustness of WM.…”

Section: Discussionmentioning

confidence: 99%

Attractor models of working memory and their modulation by reward

2007

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This work reports an empirical examination of two key issues in theoretical neuroscience: distractibility in the context of working memory (WM) and its reward dependence. While these issues have been examined fruitfully in isolation (e.g. Macoveanu et al. in Biol Cybern 96(4): 407-19, 2007), we address them here in tandem, with a focus on how distractibility and reward interact. In particular, we parameterise an observation model that embodies the nonlinear form of such interactions, as described in a recent neuronal network model (Gruber et al. in J Comput Neurosci 20:153-166, 2006). We observe that memory for a target stimulus can be corrupted by distracters in the delay period. Interestingly, in contrast to our theoretical predictions, this corruption was only partial. Distracters do not simply overwrite target; rather, a compromise is reached between target and distracter. Finally, we observed a trend towards a reduced distractibility under conditions of high reward. We discuss the implications of these findings for theoretical formulations of basal and dopamine (DA)-modulated neural bumpattractor networks of working memory.

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“…To elucidate functional significance of feature interactions in working memory revealed by the backward and forward aftereffects and the exaggerated angular difference, we first consider how lines' absolute orientations and their ordinal relationship are stored in working memory during the delay between stimulus disappearance and report. Absolute orientation of a line has a continuous value requiring a continuous attractor to represent it in neuronal working memory (42). Such representations are unstable in the presence of noise and become distorted with time (30,31), contributing to the biases and variances in the observed absolute distributions ( Fig.…”

Section: Perception As Retrospective Bayesian Decoding In Working Memorymentioning

confidence: 99%

Visual perception as retrospective Bayesian decoding from high- to low-level features

Ding

Cueva

Tsodyks

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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When a stimulus is presented, its encoding is known to progress from low-to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low-to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding.Bayesian prior | interreport correlation | bidirectional tilt aftereffect | efficient coding | adaptation theory V isual stimuli evoke neuronal responses (a process termed encoding), which lead to our perceptual estimation of the stimuli (decoding). Experimental studies have firmly established that encoding is hierarchical, progressing from lower-level representations of simpler and less invariant features to higher-level representations of more complex and invariant features along visual pathways (1). Researchers have also studied decoding by using models to relate neuronal responses to perceptual estimation. Most models posit, explicitly or implicitly, that decoding follows the same low-to high-level hierarchy, often in the form of what we call the absolute-to-relative assumption (2-6). For example, these models may decode V1 responses to a line into a perceived orientation of, say 51.2°(or a distribution around it). Psychophysically, this is termed an absolute judgment. To determine the relationship between two lines, the models first decode each orientation separately and the two resulting absolute orientations are then compared. For instance, the two absolute orientations may be subtracted to obtain the angle between the lines (relative orientation), or the sign of the difference may be used to determine whether the second line is clockwise or counterclockwise from the first (ordinal orientation discrimination). Absolute orientation of a single line is a simpler, less invariant, lower-...

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Flexible Control of Mutual Inhibition: A Neural Model of Two-Interval Discrimination

Cited by 485 publications

References 30 publications

Neural correlates of a postponed decision report

Neural correlates of a postponed decision report

Attractor models of working memory and their modulation by reward

Visual perception as retrospective Bayesian decoding from high- to low-level features

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