A Large-scale Neurocomputational Model of Task-oriented Behavior Selection and Working Memory in Prefrontal Cortex

2006 ◽  
Vol 18 (2) ◽  
pp. 242-257 ◽  
Author(s):  
George L. Chadderdon ◽  
Olaf Sporns
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Large Scale ◽  
Memory Task ◽  
Brain Regions ◽  
Synaptic Activity ◽  
Dynamic State ◽  
Memory Representation ◽  
Behavioral Repertoire ◽  
Behavior Selection

The prefrontal cortex (PFC) is crucially involved in the executive component of working memory, representation of task state, and behavior selection. This article presents a large-scale computational model of the PFC and associated brain regions designed to investigate the mechanisms by which working memory and task state interact to select adaptive behaviors from a behavioral repertoire. The model consists of multiple brain regions containing neuronal populations with realistic physiological and anatomical properties, including extrastriate visual cortical regions, the inferotemporal cortex, the PFC, the striatum, and midbrain dopamine (DA) neurons. The onset of a delayed match-to-sample or delayed nonmatch-to-sample task triggers tonic DA release in the PFC causing a switch into a persistent, stimulus-insensitive dynamic state that promotes the maintenance of stimulus representations within prefrontal networks. Other modeled prefrontal and striatal units select cognitive acceptance or rejection behaviors according to which task is active and whether prefrontal working memory representations match the current stimulus. Working memory task performance and memory fields of prefrontal delay units are degraded by extreme elevation or depletion of tonic DA levels. Analyses of cellular and synaptic activity suggest that hyponormal DA levels result in increased prefrontal activation, whereas hypernormal DA levels lead to decreased activation. Our simulation results suggest a range of predictions for behavioral, single-cell, and neuroimaging response data under the proposed task set and under manipulations of DA concentration.

scholarly journals Layer-dependent activity in human prefrontal cortex during working memory

2018 ◽  
Author(s):  
Emily S. Finn ◽  
Laurentius Huber ◽  
David C. Jangraw ◽  
Peter A. Bandettini
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Memory Task ◽  
Brain Regions ◽  
Cognitive Information Processing ◽  
Dependent Activity ◽  
Dorsolateral Prefrontal ◽  
Cognitive Information ◽  
Series Of Functions ◽  
Layer Specificity

Working memory involves a series of functions: encoding a stimulus, maintaining or manipulating its representation over a delay, and finally making a behavioral response. While working memory engages dorsolateral prefrontal cortex (dlPFC), few studies have investigated whether these subfunctions are localized to different cortical depths in this region, and none have done so in humans. Here, we use high-resolution functional MRI to interrogate the layer specificity of neural activity during different epochs of a working memory task in dlPFC. We detect activity timecourses that follow the hypothesized patterns: superficial layers are preferentially active during the delay period, while deeper layers are preferentially active during the response. Results demonstrate that layer-specific fMRI can be used in higher-order brain regions to non-invasively map cognitive information processing along cortical circuitry in humans.

scholarly journals Information interactions between prefrontal cortex and hippocampus during performance of a spatial working memory task

2021 ◽  
Author(s):  
Wei Zhang ◽  
Lei Guo ◽  
Dongzhao Liu ◽  
Guizhi Xu
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Information Transmission ◽  
Spatial Information ◽  
Spatial Working Memory ◽  
Effective Connectivity ◽  
Memory Task ◽  
Brain Regions ◽  
Directed Networks ◽  
Medial Pfc

Abstract Spatial working memory (SWM) refers to a short-term system for temporary manipulation of spatial information and requires the cooperation of multiple brain regions. Despite evidence that hippocampus (HPC) and prefrontal cortex (PFC) are involved in SWM, how PFC and HPC coordinate the neural information during SWM remains puzzling. In this study, local field potentials (LFPs) were recorded simultaneously from rat ventral HPC and medial PFC during SWM tasks. Then cross-frequency coupling algorithm was used as functional connectivity for construction of undirected networks; Grange causality algorithm was used as effective connectivity for construction of directed networks. Finally, information interactions across two brain regions were analyzed based on undirected and directed networks. Experimental results show that LFPs power in PFC and HPC both decreased over learning days and peaked before the reference point during SWM, moreover, LFPs mainly distributed in theta and gamma. From the undirected aspect, undirected PFC subnetwork and HPC subnetwork have the same effect on information transmission for SWM; the PAC between PFC-gamma and HPC-theta in undirected PFC-HPC network is related to SWM formation and contributes to information interactions between PFC and HPC. From the directed aspect, the effect of information transmission in directed HPC subnetwork is greater than PFC subnetwork; the enhancement of coordination between directed PFC and HPC subnetworks contributes to correct execution of SWM tasks; directed HPC→PFC network plays a predominant role in information interaction; with the increasing of learning days, PFC and HPC tend to be the causal sink and causal source of information flow.

scholarly journals Prefrontal and Parietal Attractor Networks Mediate Working Memory Judgments

2020 ◽  
Author(s):  
Sihai Li ◽  
Christos Constantinidis ◽  
Xue-Lian Qi
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Dorsolateral Prefrontal Cortex ◽  
Critical Role ◽  
Memory Task ◽  
Delayed Response ◽  
Persistent Activity ◽  
Neural Basis ◽  
Brain Areas ◽  
Dorsolateral Prefrontal

ABSTRACTThe dorsolateral prefrontal cortex plays a critical role in spatial working memory and its activity predicts behavioral responses in delayed response tasks. Here we addressed whether this predictive ability extends to categorical judgments based on information retained in working memory, and is present in other brain areas. We trained monkeys in a novel, Match-Stay, Nonmatch-Go task, which required them to observe two stimuli presented in sequence with an intervening delay period between them. If the two stimuli were different, the monkeys had to saccade to the location of the second stimulus; if they were the same, they held fixation. Neurophysiological recordings were performed in areas 8a and 46 of the dlPFC and 7a and lateral intraparietal cortex (LIP) of the PPC. We hypothesized that random drifts causing the peak activity of the network to move away from the first stimulus location and towards the location of the second stimulus would result in categorical errors. Indeed, for both areas, when the first stimulus appeared in a neuron’s preferred location, the neuron showed significantly higher firing rates in correct than in error trials. When the first stimulus appeared at a nonpreferred location and the second stimulus at a preferred, activity in error trials was higher than in correct. The results indicate that the activity of both dlPFC and PPC neurons is predictive of categorical judgments of information maintained in working memory, and the magnitude of neuronal firing rate deviations is revealing of the contents of working memory as it determines performance.SIGNIFICANCE STATEMENTThe neural basis of working memory and the areas mediating this function is a topic of controversy. Persistent activity in the prefrontal cortex has traditionally been thought to be the neural correlate of working memory, however recent studies have proposed alternative mechanisms and brain areas. Here we show that persistent activity in both the dorsolateral prefrontal cortex and posterior parietal cortex predicts behavior in a working memory task that requires a categorical judgement. Our results offer support to the idea that a network of neurons in both areas act as an attractor network that maintains information in working memory, which informs behavior.

scholarly journals Large-scale functional coactivation patterns reflect the structural connectivity of the medial prefrontal cortex

2020 ◽  
Author(s):  
Dale T Tovar ◽  
Robert S Chavez
Keyword(s):  
Prefrontal Cortex ◽  
Medial Prefrontal Cortex ◽  
Large Scale ◽  
Spatial Scales ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Machine Learning Techniques ◽  
Affective Processing ◽  
Affective Neuroscience ◽  
Psychological Phenomena

Abstract The medial prefrontal cortex (MPFC) is among the most consistently implicated brain regions in social and affective neuroscience. Yet, this region is also highly functionally heterogeneous across many domains and has diverse patterns of connectivity. The extent to which the communication of functional networks in this area is facilitated by its underlying structural connectivity fingerprint is critical for understanding how psychological phenomena are represented within this region. In the current study, we combined diffusion magnetic resonance imaging and probabilistic tractography with large-scale meta-analysis to investigate the degree to which the functional co-activation patterns of the MPFC is reflected in its underlying structural connectivity. Using unsupervised machine learning techniques, we compared parcellations between the two modalities and found congruence between parcellations at multiple spatial scales. Additionally, using connectivity and coactivation similarity analyses, we found high correspondence in voxel-to-voxel similarity between each modality across most, but not all, subregions of the MPFC. These results provide evidence that meta-analytic functional coactivation patterns are meaningfully constrained by underlying neuroanatomical connectivity and provide convergent evidence of distinct subregions within the MPFC involved in affective processing and social cognition.

Activation of the prefrontal cortex in a nonspatial working memory task with functional MRI

1994 ◽  
Vol 1 (4) ◽  
pp. 293-304 ◽  
Author(s):  
Jonathan D. Cohen ◽  
Steven D. Forman ◽  
Todd S. Braver ◽  
B. J. Casey ◽  
David Servan-Schreiber ◽  
...  
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Functional Mri ◽  
Memory Task

Neural Ensemble Coding during Working Memory Task in Rat Prefrontal Cortex

2011 ◽  
Vol 467-469 ◽  
pp. 1291-1296
Author(s):  
Wen Wen Bai ◽  
Xin Tian
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Firing Rate ◽  
Memory Task ◽  
Neural Population ◽  
Average Firing Rate ◽  
Population Activity ◽  
Ensemble Coding ◽  
Neural Ensemble ◽  
Ensemble Activity

Working memory is one of important cognitive functions and recent studies demonstrate that prefrontal cortex plays an important role in working memory. But the issue that how neural activity encodes during working memory task is still a question that lies at the heart of cognitive neuroscience. The aim of this study is to investigate neural ensemble coding mechanism via average firing rate during working memory task. Neural population activity was measured simultaneously from multiple electrodes placed in prefrontal cortex while rats were performing a working memory task in Y-maze. Then the original data was filtered by a high-pass filtering, spike detection and spike sorting, spatio-temporal trains of neural population were ultimately obtained. Then, the average firing rates were computed in a selected window (500ms) with a moving step (125ms). The results showed that the average firing rate were higher during workinig memory task, along with obvious ensemble activity. Conclusion: The results indicate that the working memory information is encoded with neural ensemble activity.

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