Understanding the Prefrontal Cortex

Author(s):  
Richard E. Passingham

The primate prefrontal cortex sits at the top of the sensory, motor, and outcome processing hierarchies of the neocortex. It transforms sensory inputs into motor outputs, determining the response that is appropriate given the current context and desired outcome. This transformation involves conditional rules. The dorsal prefrontal cortex supports the learning of behavioural sequences, where the next action is conditional on the previous one. The ventral prefrontal cortex supports associations between objects, where the choice of one object is conditional on the presence of another object. However, because hierarchical processing supports the extraction of abstract representations, the primate prefrontal cortex is able to represent conditional rules that are abstract, meaning that they apply irrespective of the specific inputs. The selective advantage is that by learning these rules, primates can solve new problems rapidly when they have the same conditional logic as prior problems. The human prefrontal cortex has the same fundamental organization as in other primates. The dorsal prefrontal cortex supports the understanding of sequences and the ventral prefrontal cortex supports the ability to learn semantic associations. Thus the human prefrontal cortex has co-opted and elaborated mechanisms that were present in ancestral primates. These mechanisms can be used for new ends. For example, words have been associated with objects so as to communicate with others. This means that to understand human intelligence it is necessary to take into account the fact that the abstract rules are transmitted verbally from one generation to another.

Author(s):  
Kohitij Kar ◽  
James J DiCarlo

SummaryDistributed neural population spiking patterns in macaque inferior temporal (IT) cortex that support core visual object recognition require additional time to develop for specific (“late-solved”) images suggesting the necessity of recurrent processing in these computations. Which brain circuit motifs are most responsible for computing and transmitting these putative recurrent signals to IT? To test whether the ventral prefrontal cortex (vPFC) is a critical recurrent circuit node in this system, here we pharmacologically inactivated parts of the vPFC and simultaneously measured IT population activity, while monkeys performed object discrimination tasks. Our results show that vPFC inactivation deteriorated the quality of the late-phase (>150 ms from image onset) IT population code, along with commensurate, specific behavioral deficits for “late-solved” images. Finally, silencing vPFC caused the monkeys’ IT activity patterns and behavior to become more like those produced by feedforward artificial neural network models of the ventral stream. Together with prior work, these results argue that fast recurrent processing through the vPFC is critical to the production of behaviorally-sufficient object representations in IT.


2021 ◽  
pp. 191-235
Author(s):  
Richard E. Passingham

The dorsal prefrontal (PF) cortex generates and plans the goals or targets for foveal search and manual foraging. The goals are conditional on the relative recency of prior events and actions, and the connections of areas 9/46 and 46 explain how these areas can support the ability to generate the next goal. Area 9/46 can generate sequences of eye movements because it has visuospatial inputs from the cortex in the intraparietal sulcus and outputs to the frontal eye field and superior colliculus. Area 46 can generate sequences of hand and arm movements because it has inputs from the inferior parietal areas PFG and SII and outputs to the forelimb regions of the premotor areas and thence to the motor cortex. Both areas get timing and order information indirectly from the parietal cortex and hippocampus, and colour and shape information from the ventral prefrontal cortex. Inputs from the orbital prefrontal cortex enable both areas to integrate generate goals in accordance with current needs.


1996 ◽  
Vol 39 (11) ◽  
pp. 919-928 ◽  
Author(s):  
Michael D.C. Simpson ◽  
Daniel I. Lubman ◽  
Paul Slater ◽  
J.F. William Deakin

2010 ◽  
Vol 68 ◽  
pp. e373
Author(s):  
Daisuke Takahara ◽  
Yoshihiro Hirata ◽  
Ken-ichi Inoue ◽  
Sigehiro Miyachi ◽  
Atsushi Nambu ◽  
...  

2012 ◽  
Vol 108 (5) ◽  
pp. 1335-1348 ◽  
Author(s):  
Cynthia Poon ◽  
Lisa G. Chin-Cottongim ◽  
Stephen A. Coombes ◽  
Daniel M. Corcos ◽  
David E. Vaillancourt

It is well established that the prefrontal cortex is involved during memory-guided tasks whereas visually guided tasks are controlled in part by a frontal-parietal network. However, the nature of the transition from visually guided to memory-guided force control is not as well established. As such, this study examines the spatiotemporal pattern of brain activity that occurs during the transition from visually guided to memory-guided force control. We measured 128-channel scalp electroencephalography (EEG) in healthy individuals while they performed a grip force task. After visual feedback was removed, the first significant change in event-related activity occurred in the left central region by 300 ms, followed by changes in prefrontal cortex by 400 ms. Low-resolution electromagnetic tomography (LORETA) was used to localize the strongest activity to the left ventral premotor cortex and ventral prefrontal cortex. A second experiment altered visual feedback gain but did not require memory. In contrast to memory-guided force control, altering visual feedback gain did not lead to early changes in the left central and midline prefrontal regions. Decreasing the spatial amplitude of visual feedback did lead to changes in the midline central region by 300 ms, followed by changes in occipital activity by 400 ms. The findings show that subjects rely on sensorimotor memory processes involving left ventral premotor cortex and ventral prefrontal cortex after the immediate transition from visually guided to memory-guided force control.


1981 ◽  
Vol 209 (2) ◽  
pp. 375-394 ◽  
Author(s):  
Carl E. Rosenkilde ◽  
Richard H. Bauer ◽  
Joaquin M. Fuster

2011 ◽  
Vol 31 (17) ◽  
pp. 6266-6276 ◽  
Author(s):  
T. Meyer ◽  
X.-L. Qi ◽  
T. R. Stanford ◽  
C. Constantinidis

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