scholarly journals Desirability, availability, credit assignment, category learning, and attention: Cognitive-emotional and working memory dynamics of orbitofrontal, ventrolateral, and dorsolateral prefrontal cortices

2018 ◽  
Vol 2 ◽  
pp. 239821281877217 ◽  
Author(s):  
Stephen Grossberg
Keyword(s):  
Working Memory ◽  
Category Learning ◽  
Posterior Parietal Cortex ◽  
Spatial Working Memory ◽  
Temporal Cortex ◽  
Brain Regions ◽  
Credit Assignment ◽  
Temporal Area ◽  
Dorsolateral Prefrontal ◽  
Prefrontal Cortices

Background: The prefrontal cortices play an essential role in cognitive-emotional and working memory processes through interactions with multiple brain regions. Methods: This article further develops a unified neural architecture that explains many recent and classical data about prefrontal function and makes testable predictions. Results: Prefrontal properties of desirability, availability, credit assignment, category learning, and feature-based attention are explained. These properties arise through interactions of orbitofrontal, ventrolateral prefrontal, and dorsolateral prefrontal cortices with the inferotemporal cortex, perirhinal cortex, parahippocampal cortices; ventral bank of the principal sulcus, ventral prearcuate gyrus, frontal eye fields, hippocampus, amygdala, basal ganglia, hypothalamus, and visual cortical areas V1, V2, V3A, V4, middle temporal cortex, medial superior temporal area, lateral intraparietal cortex, and posterior parietal cortex. Model explanations also include how the value of visual objects and events is computed, which objects and events cause desired consequences and which may be ignored as predictively irrelevant, and how to plan and act to realise these consequences, including how to selectively filter expected versus unexpected events, leading to movements towards, and conscious perception of, expected events. Modelled processes include reinforcement learning and incentive motivational learning; object and spatial working memory dynamics; and category learning, including the learning of object categories, value categories, object-value categories, and sequence categories, or list chunks. Conclusion: This article hereby proposes a unified neural theory of prefrontal cortex and its functions.

How Prefrontal Cortex Works

2021 ◽  
pp. 517-538
Author(s):  
Stephen Grossberg
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Executive Functions ◽  
Category Learning ◽  
Spatial Working Memory ◽  
Brain Regions ◽  
Resonance Theory ◽  
Dorsolateral Prefrontal ◽  
Prefrontal Functions ◽  
Controlling Actions

This chapter describes a unified theory of how the prefrontal cortex interacts with multiple brain regions to carry out the higher cognitive, emotional, and decision-making processes that define human intelligence, while also controlling actions to achieve valued goals. This predictive Adaptive Resonance Theory, or pART, model builds upon the foundation in earlier chapters. Prefrontal functions are often called executive functions. Executive functions regulate flexible and adaptive behaviors, notably in novel situations, while suppressing actions that are no longer appropriate, notably reflexive responses to current sensory inputs. Working memory is particularly involved in contextually appropriate behaviors. Prefrontal properties of desirability, availability, credit assignment, category learning, and feature-based attention are explained. These properties arise through interactions of orbitofrontal, ventrolateral prefrontal, and dorsolateral prefrontal cortices with inferotemporal cortex, perirhinal cortex, parahippocampal cortices; ventral bank of the principal sulcus, ventral prearcuate gyrus, frontal eye fields, hippocampus, amygdala, basal ganglia, hypothalamus, and visual cortical areas V1, V2, V3A, V4, MT, MST, LIP, and PPC. Model explanations include how the value of visual objects and events is computed, which objects and events cause desired consequences and which may be ignored as predictively irrelevant, and how to plan and act to realize these consequences, including how to selectively filter expected vs. unexpected events, leading to movements towards, and conscious perception of, expected events. Modeled processes include reinforcement learning and incentive motivational learning; object and spatial working memory dynamics; and category learning, including the learning of object categories, value categories, object-value categories, and sequence categories, or list chunks.

Drifts in Prefrontal and Parietal Neuronal Activity Influence Working Memory Judgments

2021 ◽  
Author(s):  
Sihai Li ◽  
Christos Constantinidis ◽  
Xue-Lian Qi
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Dorsolateral Prefrontal Cortex ◽  
Posterior Parietal Cortex ◽  
Spatial Working Memory ◽  
Critical Role ◽  
Predictive Ability ◽  
Neuronal Firing ◽  
Delayed Response ◽  
Dorsolateral Prefrontal

Abstract The dorsolateral prefrontal cortex (dlPFC) plays a critical role in spatial working memory and its activity predicts behavioral responses in delayed response tasks. Here, we addressed if this predictive ability extends to other working memory tasks and if it is present in other brain areas. We trained monkeys to remember the location of a stimulus and determine whether a second stimulus appeared at the same location or not. Neurophysiological recordings were performed in the dorsolateral prefrontal cortex and posterior parietal cortex (PPC). We hypothesized that random drifts causing the peak activity of the network to move away from the first stimulus location and toward the location of the second stimulus would result in categorical errors. Indeed, for both areas, in nonmatching trials, when the first stimulus appeared in a neuron’s preferred location, the neuron showed significantly higher firing rates in correct than in error trials; and vice versa, when the first stimulus appeared at a nonpreferred location, 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 neuronal firing rate deviations are revealing of the contents of working memory.

scholarly journals Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance

2021 ◽  
Author(s):  
Adeline Jabès ◽  
Giuliana Klencklen ◽  
Paolo Ruggeri ◽  
Christoph M. Michel ◽  
Pamela Banta Lavenex ◽  
...  
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Resting State ◽  
Cognitive Aging ◽  
Temporal Dynamics ◽  
Spatial Working Memory ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Age Related

AbstractAlterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.

scholarly journals Dissociable Mechanisms of Verbal Working Memory Revealed through Multivariate Lesion Mapping

2019 ◽  
Vol 30 (4) ◽  
pp. 2542-2554 ◽  
Author(s):  
Maryam Ghaleh ◽  
Elizabeth H Lacey ◽  
Mackenzie E Fama ◽  
Zainab Anbari ◽  
Andrew T DeMarco ◽  
...  
Keyword(s):  
Working Memory ◽  
Spatial Working Memory ◽  
Superior Temporal Gyrus ◽  
Verbal Working Memory ◽  
Brain Structures ◽  
Brain Regions ◽  
Task Demands ◽  
Auditory Information ◽  
Verbal Information ◽  
Task Conditions

Abstract Two maintenance mechanisms with separate neural systems have been suggested for verbal working memory: articulatory-rehearsal and non-articulatory maintenance. Although lesion data would be key to understanding the essential neural substrates of these systems, there is little evidence from lesion studies that the two proposed mechanisms crucially rely on different neuroanatomical substrates. We examined 39 healthy adults and 71 individuals with chronic left-hemisphere stroke to determine if verbal working memory tasks with varying demands would rely on dissociable brain structures. Multivariate lesion–symptom mapping was used to identify the brain regions involved in each task, controlling for spatial working memory scores. Maintenance of verbal information relied on distinct brain regions depending on task demands: sensorimotor cortex under higher demands and superior temporal gyrus (STG) under lower demands. Inferior parietal cortex and posterior STG were involved under both low and high demands. These results suggest that maintenance of auditory information preferentially relies on auditory-phonological storage in the STG via a nonarticulatory maintenance when demands are low. Under higher demands, sensorimotor regions are crucial for the articulatory rehearsal process, which reduces the reliance on STG for maintenance. Lesions to either of these regions impair maintenance of verbal information preferentially under the appropriate task conditions.

scholarly journals Functional MRI and the Study of Human Consciousness

2002 ◽  
Vol 14 (6) ◽  
pp. 818-831 ◽  
Author(s):  
Dan Lloyd
Keyword(s):  
Spatial Working Memory ◽  
Cognitive Task ◽  
Response Competition ◽  
Temporal Cortex ◽  
Brain Regions ◽  
Functional Brain Imaging ◽  
Future Research ◽  
Single Subject ◽  
Neural Activation ◽  
Human Consciousness

Functional brain imaging offers new opportunities for the study of that most pervasive of cognitive conditions, human consciousness. Since consciousness is attendant to so much of human cognitive life, its study requires secondary analysis of multiple experimental datasets. Here, four preprocessed datasets from the National fMRI Data Center are considered: Hazeltine et al., Neural activation during response competition; Ishai et al., The representation of objects in the human occipital and temporal cortex; Mechelli et al., The effects of presentation rate during word and pseudoword reading; and Postle et al., Activity in human frontal cortex associated with spatial working memory and saccadic behavior. The study of consciousness also draws from multiple disciplines. In this article, the philosophical subdiscipline of phenomenology provides initial characterization of phenomenal structures conceptually necessary for an analysis of consciousness. These structures include phenomenal intentionality, phenomenal superposition, and experienced temporality. The empirical predictions arising from these structures require new interpretive methods for their confirmation. These methods begin with single-subject (preprocessed) scan series, and consider the patterns of all voxels as potential multivariate encodings of phenomenal information. Twenty-seven subjects from the four studies were analyzed with multivariate methods, revealing analogues of phenomenal structures, particularly the structures of temporality. In a second interpretive approach, artificial neural networks were used to detect a more explicit prediction from phenomenology, namely, that present experience contains and is inflected by past states of awareness and anticipated events. In all of 21 subjects in this analysis, nets were successfully trained to extract aspects of relative past and future brain states, in comparison with statistically similar controls. This exploratory study thus concludes that the proposed methods for “neurophenomenology” warrant further application, including the exploration of individual differences, multivariate differences between cognitive task conditions, and exploration of specific brain regions possibly contributing to the observations. All of these attractive questions, however, must be reserved for future research.

scholarly journals Structured sequence processing and combinatorial binding: neurobiologically and computationally informed hypotheses

2019 ◽  
Vol 375 (1791) ◽  
pp. 20190304 ◽  
Author(s):  
Ryan Calmus ◽  
Benjamin Wilson ◽  
Yukiko Kikuchi ◽  
Christopher I. Petkov
Keyword(s):  
Temporal Cortex ◽  
Brain Regions ◽  
Position Information ◽  
Sequence Processing ◽  
Oscillatory Dynamics ◽  
Structured Representations ◽  
Dorsolateral Prefrontal ◽  
Frontal Operculum ◽  
Structured Information ◽  
The Brain

Understanding how the brain forms representations of structured information distributed in time is a challenging endeavour for the neuroscientific community, requiring computationally and neurobiologically informed approaches. The neural mechanisms for segmenting continuous streams of sensory input and establishing representations of dependencies remain largely unknown, as do the transformations and computations occurring between the brain regions involved in these aspects of sequence processing. We propose a blueprint for a neurobiologically informed and informing computational model of sequence processing (entitled: Vector-symbolic Sequencing of Binding INstantiating Dependencies, or VS-BIND). This model is designed to support the transformation of serially ordered elements in sensory sequences into structured representations of bound dependencies, readily operates on multiple timescales, and encodes or decodes sequences with respect to chunked items wherever dependencies occur in time. The model integrates established vector symbolic additive and conjunctive binding operators with neurobiologically plausible oscillatory dynamics, and is compatible with modern spiking neural network simulation methods. We show that the model is capable of simulating previous findings from structured sequence processing tasks that engage fronto-temporal regions, specifying mechanistic roles for regions such as prefrontal areas 44/45 and the frontal operculum during interactions with sensory representations in temporal cortex. Finally, we are able to make predictions based on the configuration of the model alone that underscore the importance of serial position information, which requires input from time-sensitive cells, known to reside in the hippocampus and dorsolateral prefrontal cortex. This article is part of the theme issue ‘Towards mechanistic models of meaning composition’.

Prefrontal Task-Related Activity Representing Visual Cue Location or Saccade Direction in Spatial Working Memory Tasks

2002 ◽  
Vol 87 (1) ◽  
pp. 567-588 ◽  
Author(s):  
Kazuyoshi Takeda ◽  
Shintaro Funahashi
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Spatial Working Memory ◽  
Delay Period ◽  
Neuron Activity ◽  
Delayed Response ◽  
Related Activity ◽  
Visual Cue ◽  
Response Period ◽  
Dorsolateral Prefrontal

To examine what kind of information task-related activity encodes during spatial working memory processes, we analyzed single-neuron activity in the prefrontal cortex while two monkeys performed two different oculomotor delayed-response (ODR) tasks. In the standard ODR task, monkeys were required to make a saccade to the cue location after a 3-s delay, whereas in the rotatory ODR (R-ODR) task, they were required to make a saccade 90° clockwise from the cue location after the 3-s delay. By comparing the same task-related activities in these two tasks, we could determine whether such activities encoded the location of the visual cue or the direction of the saccade. One hundred twenty one neurons exhibited task-related activity in relation to at least one task event in both tasks. Among them, 41 neurons exhibited directional cue-period activity, most of which encoded the location of the visual cue. Among 56 neurons with directional delay-period activity, 86% encoded the location of the visual cue, whereas 13% encoded the direction of the saccade. Among 57 neurons with directional response-period activity, 58% encoded the direction of the saccade, whereas 35% encoded the location of the visual cue. Most neurons whose response-period activity encoded the location of the visual cue also exhibited directional delay-period activity that encoded the location of the visual cue as well. The best directions of these two activities were identical, and most of these response-period activities were postsaccadic. Therefore this postsaccadic activity can be considered a signal to terminate unnecessary delay-period activity. Population histograms encoding the location of the visual cue showed tonic sustained activation during the delay period. However, population histograms encoding the direction of the saccade showed a gradual increase in activation during the delay period. These results indicate that the transformation from visual input to motor output occurs in the dorsolateral prefrontal cortex. The analysis using population histograms suggests that this transformation occurs gradually during the delay period.

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