scholarly journals Prefrontal GABAergic Interneurons Gate Long-Range Afferents to Regulate Prefrontal Cortex-Associated Complex Behaviors

2021 ◽  
Vol 15 ◽  
Author(s):  
Sha-Sha Yang ◽  
Nancy R. Mack ◽  
Yousheng Shu ◽  
Wen-Jun Gao
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Long Range ◽  
Basolateral Amygdala ◽  
Spatial Working Memory ◽  
Gabaergic Interneurons ◽  
Subcortical Structures ◽  
Precise Control ◽  
Regulatory Effects ◽  
Fear Expression

Prefrontal cortical GABAergic interneurons (INs) and their innervations are essential for the execution of complex behaviors such as working memory, social behavior, and fear expression. These behavior regulations are highly dependent on primary long-range afferents originating from the subcortical structures such as mediodorsal thalamus (MD), ventral hippocampus (vHPC), and basolateral amygdala (BLA). In turn, the regulatory effects of these inputs are mediated by activation of parvalbumin-expressing (PV) and/or somatostatin expressing (SST) INs within the prefrontal cortex (PFC). Here we review how each of these long-range afferents from the MD, vHPC, or BLA recruits a subset of the prefrontal interneuron population to exert precise control of specific PFC-dependent behaviors. Specifically, we first summarize the anatomical connections of different long-range inputs formed on prefrontal GABAergic INs, focusing on PV versus SST cells. Next, we elaborate on the role of prefrontal PV- and SST- INs in regulating MD afferents-mediated cognitive behaviors. We also examine how prefrontal PV- and SST- INs gate vHPC afferents in spatial working memory and fear expression. Finally, we discuss the possibility that prefrontal PV-INs mediate fear conditioning, predominantly driven by the BLA-mPFC pathway. This review will provide a broad view of how multiple long-range inputs converge on prefrontal interneurons to regulate complex behaviors and novel future directions to understand how PFC controls different behaviors.

scholarly journals The role of prefrontal cortex in working memory: examining the contents of consciousness

1998 ◽  
Vol 353 (1377) ◽  
pp. 1819-1828 ◽  
Author(s):  
◽  
S. M. Courtney ◽  
L. Petit ◽  
J. V. Haxby ◽  
L. G. Ungerleider
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Visual Processing ◽  
Right Hemisphere ◽  
Functional Organization ◽  
Spatial Working Memory ◽  
Domain Specificity ◽  
Long Term Memory ◽  
Present Evidence ◽  
The Right

Working memory enables us to hold in our ‘mind's eye’ the contents of our conscious awareness, even in the absence of sensory input, by maintaining an active representation of information for a brief period of time. In this review we consider the functional organization of the prefrontal cortex and its role in this cognitive process. First, we present evidence from brain–imaging studies that prefrontal cortex shows sustained activity during the delay period of visual working memory tasks, indicating that this cortex maintains on–line representations of stimuli after they are removed from view. We then present evidence for domain specificity within frontal cortex based on the type of information, with object working memory mediated by more ventral frontal regions and spatial working memory mediated by more dorsal frontal regions. We also propose that a second dimension for domain specificity within prefrontal cortex might exist for object working memory on the basis of the type of representation, with analytic representations maintained preferentially in the left hemisphere and image–based representations maintained preferentially in the right hemisphere. Furthermore, we discuss the possibility that there are prefrontal areas brought into play during the monitoring and manipulation of information in working memory in addition to those engaged during the maintenance of this information. Finally, we consider the relationship of prefrontal areas important for working memory, both to posterior visual processing areas and to prefrontal areas associated with long–term memory.

scholarly journals Spatial Working Memory in Humans Depends on Theta and High Gamma Synchronization in the Prefrontal Cortex

2016 ◽  
Vol 26 (12) ◽  
pp. 1513-1521 ◽  
Author(s):  
Ivan Alekseichuk ◽  
Zsolt Turi ◽  
Gabriel Amador de Lara ◽  
Andrea Antal ◽  
Walter Paulus
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Spatial Working Memory ◽  
High Gamma

A whole-brain map of long-range inputs to GABAergic interneurons in the mouse medial prefrontal cortex

2019 ◽  
Vol 22 (8) ◽  
pp. 1357-1370 ◽  
Author(s):  
Qingtao Sun ◽  
Xiangning Li ◽  
Miao Ren ◽  
Mengting Zhao ◽  
Qiuyuan Zhong ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Long Range ◽  
Medial Prefrontal Cortex ◽  
Gabaergic Interneurons ◽  
Whole Brain

scholarly journals Making Working Memory Work: A Computational Model of Learning in the Prefrontal Cortex and Basal Ganglia

2006 ◽  
Vol 18 (2) ◽  
pp. 283-328 ◽  
Author(s):  
Randall C. O'Reilly ◽  
Michael J. Frank
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Basal Ganglia ◽  
Computational Model ◽  
Computational Models ◽  
Memory Task ◽  
Learning Mechanisms ◽  
Subcortical Structures ◽  
Credit Assignment ◽  
Gating Mechanism

The prefrontal cortex has long been thought to subserve both working memory (the holding of information online for processing) and executive functions (deciding how to manipulate working memory and perform processing). Although many computational models of working memory have been developed, the mechanistic basis of executive function remains elusive, often amounting to a homunculus. This article presents an attempt to deconstruct this homunculus through powerful learning mechanisms that allow a computational model of the prefrontal cortex to control both itself and other brain areas in a strategic, task-appropriate manner. These learning mechanisms are based on subcortical structures in the midbrain, basal ganglia, and amygdala, which together form an actor-critic architecture. The critic system learns which prefrontal representations are task relevant and trains the actor, which in turn provides a dynamic gating mechanism for controlling working memory updating. Computationally, the learning mechanism is designed to simultaneously solve the temporal and structural credit assignment problems. The model's performance compares favorably with standard backpropagation-based temporal learning mechanisms on the challenging 1-2-AX working memory task and other benchmark working memory tasks.

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