2006 |
Serences, John T |
F32Activity Code Description: To provide postdoctoral research training to individuals to broaden their scientific background and extend their potential for research in specified health-related areas. |
Role of Attention and Reward in Selective Perception @ Salk Institute For Biological Studies
[unreadable] DESCRIPTION (provided by applicant): We do not possess enough neural machinery to simultaneously process all incoming visual information; when multiple stimuli are present in the scene, they compete for cortical representation and limited access to memory and awareness. Selective attention serves to bias this competition in favor of the attended stimulus so that behaviorally relevant aspects of the environment dominate our perceptual experience. For instance, high attentional priority is assigned to regions of space known to contain relevant information, and stimuli presented in the attended location are processed preferentially over other nonattended stimuli. While such instances of voluntary attentional control may infuence the locus of attention, recent work also suggests that the reward history of a stimulus can influence its cortical representation. The goal of the present proposal is to examine the neural mechanisms in visual and parietal cortex that resolve competition between multiple stimuli by modulating attentional processes. Furthermore, the proposed experiments will directly explore the relationship between attention and reward, and the potentially separable effects that these two factors may play in biasing the cortical representation of stimuli in the environment. [unreadable] [unreadable]
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0.88 |
2009 — 2010 |
Serences, John |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Assessing Space and Feature Based Attention With Fmri and Multivoxel Pattern Anal @ University of California San Diego
Description (provided by applicant): Perception is the cornerstone of cognition;memory, reasoning, and the formation of motor plans all rely on the ability to create a stable representation of the surrounding environment. However, neurons that encode sensory input are inherently noisy, so repeated presentations of a stimulus never evoke the same pattern of neural activity twice. In addition, more stimuli are typically present in the environment than the brain can simultaneously process, so relevant and irrelevant items must compete for cortical representation. Given these obstacles, the brain's ability to form coherent percepts is quite remarkable and understanding how this feat is accomplished is an important first step towards revealing the neural mechanisms that support conscious awareness. Theoretical studies suggest that perception is based on small populations of neurons that pool their output, since averaging reduces noise (termed population coding models). In addition, attending to specific locations or features biases neural activity so that relevant stimuli win representation at the expense of irrelevant stimuli. Thus, population coding schemes are necessary to provide a reliable foundation for perception, and selective attention is required to ensure that representations of relevant stimuli dominate awareness. Unfortunately, the relationship between attention and population codes is not well understood, in part because of technical limitations and in part because little work has been done to link single-unit attention modulations with the efficiency of information encoding at the population level. Here, we use a simple computational model to provide an explicit link between attention modulations, population codes and perception. To test predictions generated by the model, we use a combination of psychophysics and novel multivariate functional magnetic resonance imaging (fMRI) analysis techniques that are sensitive to changes in population response profiles across feature-selective regions of visual cortex. Specifically, we present a method for measuring feature-selective `tuning-functions'within very small regions of early visual cortex. These fMRI-based tuning functions resemble the tuning functions routinely obtained using single-unit recording methods in non-human primates, providing a powerful tool for evaluating theories of information encoding in human sensory cortices. In the first Specific Aim, we will use this collection of tools to test different models of attention gain (e.g. multiplicative gain vs. contrast gain) and to determine if feature-based attention systematically biases population response profiles in early visual cortex even before a stimulus is presented. In the Second Aim, we critically evaluate the common intuition that attention gain should be applied to sensory neurons that are maximally responsive to a target stimulus. Instead, we will test the counter-intuitive prediction that gain should sometimes be applied to neurons that are actually not tuned to the attended feature in order to maximize the efficiency of population codes. Together, these efforts will shed light on how the behavioral goals of an observer can shape population response profiles so that information processing within the visual system can be optimized. Since perception is a fundamental aspect of human information processing, our findings will be of interest to investigators focusing on perceptual learning, decision making, and memory. Moreover, the knowledge gained here will provide an important foundation for future applied research into disorders of attention such as Attention Deficit Disorder (ADD). For example, developing a better understanding about how attention modulates sensory neurons may lead to more objective diagnostic tests so that these disorders may be identified earlier and with greater accuracy. PUBLIC HEALTH RELEVANCE Whether listening to a teacher in a classroom or driving a car down the road, the ability to pay attention to important parts of the environment is critical to our success and survival. In the present research proposal, we seek to understand how patterns of neural activity in the brain support attentive behavior so that an observer may more efficiently understand and represent incoming sensory information. This knowledge will aid in the development of more objective tests for common disorders of attention - such as attention deficit disorder - so that diagnosis can proceed with greater precision and so that interventions can be started earlier.
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1 |
2011 — 2012 |
Serences, John |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Adaptive Allocation of Attention During Perception, Working Memory, and Decision @ University of California San Diego
DESCRIPTION (provided by applicant): Human sensory systems are continuously bombarded with far more input than they can process. As a result, attentional mechanisms have evolved so that available capacity is dedicated to encoding only the most salient and behaviorally relevant stimuli in the environment. In turn, the most important stimuli dominate perceptual awareness and have privileged access to memory stores and to the neural mechanisms that control decisions about how to best interact with external objects. In this proposal, we will use the visual system as a model to understand the basic brain-behavior processes involved in selective attention influence perception, working memory, and the computation of sensorimotor decisions. In addition, we will develop and employ new methods that use fMRI to non-invasively study attentional modulations and the information encoding capacity of sensory systems, in line with the strategic aim of the NIMH to develop novel tools and methodologies for understanding how populations of neural cells work together within and between brain regions. Traditional accounts hold that attention operates to magnify the neural response evoked by important stimuli, which makes a stimulus easier to perceive. This general framework is intuitive, and has been successfully guiding empirical studies for more than three decades. However, recent theoretical work suggests that attention should not simply increase the gain of neurons tuned to a relevant stimulus. Instead, attention should modulate the activity of sensory neurons in a more dynamic manner in order to maximize the probability that a specific perceptual task will be successfully completed. Often times, this counterintuitively requires enhancing the activity of neurons that are most responsive to stimuli that are not physically present in the visual field, because these neurons carry more information about very difficult discriminations between similar items (e.g. when a radiologist searches for a cancerous mass in a low-quality x-ray image). Recent empirical studies support this general framework, and further raise the intriguing possibility that individual differences in the optimality of attention can predict overall performance on difficult discriminations as well as the ability to improve on difficult discriminations with practice (learning). Here, we will critically evaluate this new theoretical perspective, and we will also explore how differences in attention across individuals can influence the precision of short-term memory and the efficiency of simple decision making processes. Collectively, our goal is to provide insights into the operation of attentional mechanisms so that we can more precisely characterize how the system should ideally operate. In turn, this should dramatically improve our ability to isolate specific aspects of attentional processing that can sometimes go awry, thereby enabling more targeted diagnoses and interventions in clinical settings. PUBLIC HEALTH RELEVANCE: Whether listening to a teacher in a classroom or driving a car down the road, the ability to pay attention to important sensory stimuli in the environment is critical to success and survival. In the present research proposal, we will use the visual system as a model to better understand how attention selectively changes the activity of sensory neurons to promote more efficient perception, memory, and decision making. This knowledge will aid in the development of more objective tests for common disorders of attention - such as attention deficit disorder - so that diagnosis can proceed with greater precision and interventions can be started earlier.
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1 |
2013 — 2020 |
Serences, John |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Adaptive Allocation of Attentional Gain @ University of California San Diego
DESCRIPTION (provided by applicant): Human sensory systems are continuously bombarded with far more input than they can process. As a result, attentional mechanisms have evolved so that available capacity is dedicated to encoding only the most salient and behaviorally relevant stimuli in the environment. In turn, the most important stimuli dominate perceptual awareness and have privileged access to memory stores and to the neural mechanisms that control decisions about how to best interact with external objects. In this proposal, we will use the visual system as a model to understand the basic brain-behavior processes involved in selective attention influence perception, working memory, and the computation of sensorimotor decisions. In addition, we will develop and employ new methods that use fMRI to non-invasively study attentional modulations and the information encoding capacity of sensory systems, in line with the strategic aim of the NIMH to develop novel tools and methodologies for understanding how populations of neural cells work together within and between brain regions. Traditional accounts hold that attention operates to magnify the neural response evoked by important stimuli, which makes a stimulus easier to perceive. This general framework is intuitive, and has been successfully guiding empirical studies for more than three decades. However, recent theoretical work suggests that attention should not simply increase the gain of neurons tuned to a relevant stimulus. Instead, attention should modulate the activity of sensory neurons in a more dynamic manner in order to maximize the probability that a specific perceptual task will be successfully completed. Often times, this counterintuitively requires enhancing the activity of neurons that are most responsive to stimuli that are not physically present in the visual field, because these neurons carry more information about very difficult discriminations between similar items (e.g. when a radiologist searches for a cancerous mass in a low-quality x-ray image). Recent empirical studies support this general framework, and further raise the intriguing possibility that individual differences in the optimality of attention can predict overall performance on difficult discriminations as well as the ability to improve on difficult discriminations with practice (learning). Here, we will critically evaluate this new theoretical perspective, and we will also explore how differences in attention across individuals can influence the precision of short-term memory and the efficiency of simple decision making processes. Collectively, our goal is to provide insights into the operation of attentional mechanisms so that we can more precisely characterize how the system should ideally operate. In turn, this should dramatically improve our ability to isolate specific aspects of attentional processing that can sometimes go awry, thereby enabling more targeted diagnoses and interventions in clinical settings.
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1 |
2014 — 2015 |
Serences, John |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Oscillatory Dynamics and Sensory Processing @ University of California San Diego
DESCRIPTION (provided by applicant): Human sensory systems are continuously bombarded with far more input than can be processed at a single time. As a result, attentional mechanisms have evolved so that available processing capacity is dedicated to encoding only the most salient and behaviorally relevant stimuli in the environment. In turn, the most important stimuli dominate perceptual awareness and have privileged access to the neural mechanisms that control decisions about how to best interact with external objects. Recently, investigators have proposed the counterintuitive hypothesis that selective attention operates to gate relevant sensory information in time with slow intrinsic cortical oscillations in the theta and alpha bands (i.e. ~4-12Hz). For example, behavioral performance on basic visual tasks waxes and wanes in time with alpha oscillations, and experimentally disrupting these rhythms impairs perception. Here we will test the hypothesis that these rhythmic fluctuations in behavior reflect oscillations n the fidelity of sensory representations in early cortical areas (sensory-modulation hypothesis). We will use a combination of formal models of decision making coupled with novel EEG analysis techniques that can non- invasively measure feature-selective representations with a high degree of temporal resolution. Thus, this work will test a focused hypothesis about the nature of intrinsic cortical oscillations and their link to rhythmic changes in human information processing. In addition, our novel approach to analyzing high-dimensional EEG data sets will provide a non-invasive and well-tolerated means of measuring feature selective responses in human cortex with high temporal resolution, in line with the strategic aim of the NIH to develop novel tools and methodologies for understanding how populations of neural cells work together within and between brain regions.
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1 |
2021 |
Serences, John T |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Adaptive Population Codes For Flexible Visually-Guided Behaviors @ University of California, San Diego
Summary/Abstract Active vision requires encoding and remembering relevant information based on current task goals. Classic accounts posit that sensory encoding, attentional selection and working memory are mediated by persistent changes in the firing rates, or the gain, of visually responsive neurons that have a fixed tuning profile (termed ?pure? or ?fixed-selectivity? neurons). The focus on gain modulations in fixed-selectivity neurons has revealed a great deal about the basic mechanisms of attention and memory. However, it is becoming increasingly clear that dynamic changes in task demands may require more flexible coding schemes. For example, holding information in working memory in the same format as the stimulus-evoked response may lead to interference with new sensory inputs. Similarly, flexibly encoding sensory representations to complete one task ? say a simple choice between two motor responses ? might require a reconfiguration of the representation if another stimulus- response mapping suddenly becomes relevant. Finally, sensory codes must be flexible in the sense that early in processing they should form high-dimensional representations to represent as much information as possible about the current state of the world. Later in processing, when a decision or motor response needs to be made, the code should collapse to only represent the smaller subset of relevant choices. All of these computations are more naturally accomplished via the operation of neurons that have flexible tuning for both sensory features and for task demands (termed ?mixed-selectivity? neurons). Based on these considerations, we hypothesize that flexible behaviors are supported by mixed-selectivity neurons that ?rotate? high-dimensional neural codes to become robust to interference or to sub-serve other changes in task demands. We will use modelling, psychophysics, and functional magnetic resonance imaging (fMRI) to test predictions about how mixed-selectivity should modulate large-scale activation patterns that are measured non-invasively in human subjects. Collectively, this work will challenge traditional theories of sensory encoding, attention, and working memory that are based on the notion of fixed-selectivity, and will provide important constraints on models of visual information processing to support more targeted diagnoses and interventions in clinical settings.
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0.958 |
2021 — 2023 |
Serences, John Adam, Kirsten |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Probing Interactions of Working- and Long-Term Memory
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). This award was provided as part of NSF's Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. John Serences at the University of California San Diego, this postdoctoral fellowship award supports an early career scientist investigating the interaction of working memory and long-term memory. Working memory refers to the ability to hold information temporarily in mind over the short term. Long-term memory refers to the ability to encode and retrieve information over longer periods (from moments to decades). Researchers have taken great pains to separately measure each kind of memory, in part because they naturally tend to cooperate (e.g., compare holding the letters XZK-FGC-KZPW vs. DOG-CAT-BIRD in working memory). To estimate working memory capacity without support from long-term memory, laboratory studies often use contrived stimuli (e.g., arbitrary color-location pairings). This reductionist approach has revealed that working- and long-term memory have unique behavioral signatures and rely on dissociable neural mechanisms. However, this approach skews our understanding of how working memory functions. In everyday life, to-be-remembered items are rarely devoid of meaning and multiple memory systems are used in tandem (e.g., when asked at trivia to write an alphabetical list of Beatles members, you must first retrieve the information from long-term memory and then manipulate it with working memory). Thus, the interaction of working- and long-term memory is critically important to human memory, and the objective of this research program is to better understand when and why these canonically dissociable memory systems interact. Because working- and long-term memory are intertwined in everyday life, cognition can fail due to difficulties with one or both constructs. Accordingly, this basic science work also has implications for understanding co-occurring working- and long-term memory deficits in normal aging and in clinical populations, as well as implications for how working- and long-term memory work in tandem in educational settings (e.g., when students encounter novel information they must hold in working memory and then later recall).
Building on decades of research on the separable neural mechanisms that support working- and long-term memory, the project will use fMRI to test competing predictions about the interaction of active working memory maintenance signatures in cortex (i.e., decoding the identity of items held in mind) with neural signatures of support from long-term memory (i.e., hippocampal activation). The first two experiments address competing accounts of the capacity limits of active, cortical working memory codes and how hippocampal activity may support WM when this capacity limit is exceeded. The remaining two experiments address competing accounts of activity-silent working memory – a recently popularized idea that rapid synaptic plasticity within cortex can support working memory maintenance in the absence of persistent activity. This project investigates the alternative account that working memory behaviors may rely upon hippocampal-dependent cortical reinstatement of active codes if persistent activity is lost. The proposed research will leverage fMRI and multivariate modeling to inform competing theoretical accounts of working- and long-term memory. Regardless of the outcome, the findings will inform and extend existing theories of human memory, and the methods developed and refined in the proposed work have the potential to inform future questions (e.g., the ability to decode the identity 4 items held in mind would be useful for other open questions in the memory literature).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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0.903 |