Comparison of frontal and parietal cortices in the control of visual attention

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2008.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 178-186).The ability to switch between tasks reflects a fundamental part of our intelligence. A foundation of this ability lies in perceiving and processing information pertinent to the situation at hand. It is our capacity to attend to specific objects and, more importantly, our ability to switch our attention from object to object, that supports complex cognitive behavior. Therefore, by understanding the neural mechanisms involved in directing attention we hope to better understand cognition. Previous work investigating the ability to control attention has suggested that attention is influenced from two sources -- attention can either be driven from external sources in an bottom-up, exogenous manner or directed internally in an top-down, endogenous manner.This project will utilize two different forms of visual search in order to emphasize these two different types of attentional control. Both the prefrontal and parietal regions are implicated as the source of this control. In order to investigate their relative roles we recorded simultaneously from both parietal cortex (specifically, the lateral intraparietal cortex) and prefrontal cortex (specifically, the frontal eye fields and dorsolateral prefrontal cortex). We address four main questions. First, we contrast the respective roles of frontal and parietal cortex in the direction of attention when it is under either top-down or bottom-up control. We use the timing of attention signals between frontal and parietal cortex to establish that frontal cortex directs top-down attention back into parietal cortex, while bottom-up attention is reflected first in parietal cortex, flowing forward to frontal cortex. Secondly, we investigated the role of synchrony and the inter-areal relationships underlying top-down and bottom-up control of attention. Our results suggest synchrony between areas shifts as the task shifts, likely aiding in the selection of the network best suited to the current task. Third, we compare the neural mechanisms between internal and external control of attention.(cont) Finally, we investigate the neural correlates of the putative parallel and serial mechanisms underlying visual search, finding support for the existence of a serial search and for the role of the frontal eye fields in the direction of spatial attention.by Timothy J. Buschman.Ph.D

Intrinsic neuronal dynamics predict distinct functional roles during working memory

Working memory (WM) is characterized by the ability to maintain stable representations over time; however, neural activity associated with WM maintenance can be highly dynamic. We explore whether complex population coding dynamics during WM relate to the intrinsic temporal properties of single neurons in lateral prefrontal cortex (lPFC), the frontal eye fields (FEF), and lateral intraparietal cortex (LIP) of two monkeys (Macaca mulatta). We find that cells with short timescales carry memory information relatively early during memory encoding in lPFC; whereas long-timescale cells play a greater role later during processing, dominating coding in the delay period. We also observe a link between functional connectivity at rest and the intrinsic timescale in FEF and LIP. Our results indicate that individual differences in the temporal processing capacity predict complex neuronal dynamics during WM, ranging from rapid dynamic encoding of stimuli to slower, but stable, maintenance of mnemonic information.Biotechnology and Biological Sciences Research Council (Great Britain) (BB/M010732/1)United States. Office of Naval Research (N00014-14-1-0681)National Institute of Mental Health (U.S.) (R00MH092715)National Institute of Mental Health (U.S.) (R37MH087027)Massachusetts Institute of Technology. Picower Innovation FundUnited States. Office of Naval Research. Multidisciplinary University Research Initiative (grant N00014-16-1-2832)National Institute for Health Research (Great Britain). Wellcome Trust (203139/Z/16/Z

Gamma and Beta Bursts Underlie Working Memory

Working memory is thought to result from sustained neuron spiking. However, computational models suggest complex dynamics with discrete oscillatory bursts. We analyzed local field potential (LFP) and spiking from the prefrontal cortex (PFC) of monkeys performing a working memory task. There were brief bursts of narrow-band gamma oscillations (45–100 Hz), varied in time and frequency, accompanying encoding and re-activation of sensory information. They appeared at a minority of recording sites associated with spiking reflecting the to-be-remembered items. Beta oscillations (20–35 Hz) also occurred in brief, variable bursts but reflected a default state interrupted by encoding and decoding. Only activity of neurons reflecting encoding/decoding correlated with changes in gamma burst rate. Thus, gamma bursts could gate access to, and prevent sensory interference with, working memory. This supports the hypothesis that working memory is manifested by discrete oscillatory dynamics and spiking, not sustained activity.National Institute of Mental Health (U.S.) (Grant 5R01MH091174-05)National Institute of Mental Health (U.S.) (Grant 5R37MH087027-07

Interaction between Attention and Bottom-Up Saliency Mediates the Representation of Foreground and Background in an Auditory Scene

Bottom-up (stimulus-driven) and top-down (attentional) processes interact when a complex acoustic scene is parsed. Both modulate the neural representation of the target in a manner strongly correlated with behavioral performance

From behavior to neural dynamics: An integrated theory of attention

The brain has a limited capacity and therefore needs mechanisms to selectively enhance the information most relevant to one’s current behavior. We refer to these mechanisms as ‘attention’. Attention acts by increasing the strength of selected neural representations and preferentially routing them through the brain’s large-scale network. This is a critical component of cognition and therefore has been a central topic in cognitive neuroscience. Here we review a diverse literature that has studied attention at the level of behavior, networks, circuits and neurons. We then integrate these disparate results into a unified theory of attention

Cortical circuits for the control of attention

How are some thoughts favored over others? A wealth of data at the level of single neurons has yielded candidate brain areas and mechanisms for our best-understood model: visual attention. Recent work has naturally evolved toward efforts at a more integrative, network, understanding. It suggests that focusing attention arises from interactions between widespread cortical and subcortical networks that may be regulated via their rhythmic synchronization.National Institute of Mental Health (U.S.)/United States. Intelligence Advanced Research Projects Activity (United States. Dept. of Interior Contract D10PC20023

Synchronous Oscillatory Neural Ensembles for Rules in the Prefrontal Cortex

Intelligent behavior requires acquiring and following rules. Rules define how our behavior should fit different situations. To understand its neural mechanisms, we simultaneously recorded from multiple electrodes in dorsolateral prefrontal cortex (PFC) while monkeys switched between two rules (respond to color versus orientation). We found evidence that oscillatory synchronization of local field potentials (LFPs) formed neural ensembles representing the rules: there were rule-specific increases in synchrony at “beta” (19–40 Hz) frequencies between electrodes. In addition, individual PFC neurons synchronized to the LFP ensemble corresponding to the current rule (color versus orientation). Furthermore, the ensemble encoding the behaviorally dominant orientation rule showed increased “alpha” (6–16 Hz) synchrony when preparing to apply the alternative (weaker) color rule. This suggests that beta-frequency synchrony selects the relevant rule ensemble, while alpha-frequency synchrony deselects a stronger, but currently irrelevant, ensemble. Synchrony may act to dynamically shape task-relevant neural ensembles out of larger, overlapping circuits.National Science Foundation (U.S.) (CELEST Grant GC-208001NGA)National Institute of Mental Health (U.S.) (Grant P50-MH058880

Cortical information flow during flexible sensorimotor decisions

During flexible behavior, multiple brain regions encode sensory inputs, the current task, and choices. It remains unclear how these signals evolve. We simultaneously recorded neuronal activity from six cortical regions [middle temporal area (MT), visual area four (V4), inferior temporal cortex (IT), lateral intraparietal area (LIP), prefrontal cortex (PFC), and frontal eye fields (FEF)] of monkeys reporting the color or motion of stimuli. After a transient bottom-up sweep, there was a top-down flow of sustained task information from frontoparietal to visual cortex. Sensory information flowed from visual to parietal and prefrontal cortex. Choice signals developed simultaneously in frontoparietal regions and travelled to FEF and sensory cortex. This suggests that flexible sensorimotor choices emerge in a frontoparietal network from the integration of opposite flows of sensory and task information.National Institute of Mental Health (U.S.) (Grant 5R37MH087027)Picower Institute for Learning and Memory (Innovation Fund)National Institutes of Health (U.S.) (Grant R00 MH092715)Deutsche Forschungsgemeinschaft. Centre for Integrative Neuroscience (EXC 307