Cognitive neuroscience has emerged in the last decade as an intensely active and influential discipline, forged from interactions among the cognitive sciences, neurology, neuroimaging (including physics and statistics), physiology, neuroscience, psychiatry, and other fields. Of particular importance for this discipline have been new methods for non-invasive functional neuroimaging of humans performing psychological tasks. As this field is reaching maturity, the National Science Foundation intends for the new cognitive neuroscience emphasis to spur the development of highly novel techniques and models directed toward enabling basic scientific understanding of a broad range of issues involving brain, cognition, and behavior. The emphasis at NSF will be placed on integration of the cognitive sciences, basic sciences, and engineering in service of insights into healthy functions of brain, cognition, and behavior.

The cross-disciplinary integration and exploitation of new techniques in cognitive neuroscience has generated a rapid growth in significant scientific advances. Research topics have included sensory processes (including olfaction, thirst, multi-sensory integration), higher perceptual processes (for faces, music, etc.), higher cognitive functions (e.g., decision-making, reasoning, mathematics, mental imagery, awareness), language (e.g., syntax, multi-lingualism, discourse), sleep, affect, social processes, learning, memory, attention, motor, and executive functions. Cognitive neuroscientists further clarify their findings by examining developmental and transformational aspects of such phenomena across the span of life, from infancy to late adulthood, and through evolutionary time.

New frontiers in cognitive neuroscience research have emerged from investigations that integrate data from a variety of techniques. One very useful technique has been neuroimaging, including positron emission tomography (PET), functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), optical imaging (near infrared spectroscopy or NIRS), anatomical MRI, and diffusion tensor imaging (DTI). A second class of techniques includes physiological recording such as subdural and deep brain electrode recording, electroencephalography (EEG), event-related electrical potentials (ERPs), and galvanic skin responses (GSRs). In addition, stimulation methods have been employed, including transcranial magnetic stimulation (TMS), subdural and deep brain electrode stimulation, and drug stimulation. A fourth approach involves cognitive and behavioral methods, such as lesion-deficit neuropsychology and experimental psychology. Other techniques have included genetic analysis, molecular modeling, and computational modeling. The foregoing variety of methods is used with individuals in healthy, neurological, psychiatric, and cognitively-impaired conditions. The data from such varied sources can be further clarified by comparison with invasive neurophysiological recordings in non-human primates and other mammals.

Findings from cognitive neuroscience can elucidate functional brain organization, such as the operations performed by a particular brain area and the system of distributed, discrete neural areas supporting a specific cognitive, perceptual, motor, or affective operation or representation. Moreover, these findings can reveal the effect on brain organization of individual differences (including genetic variation), plasticity, and recovery of function following damage to the nervous system.

Hypotheses springing from the data of a cognitive science, social, developmental, or life span study can now in some instances be constrained by brain-based data. Strategies for collecting brain-based data that bear on cognitive/behavioral hypotheses include but are not limited to the following four examples. Other powerful strategies are expected to evolve in future.  

• First, if a pattern of neural activity can be linked to a particular cognitive process, the presence of that pattern can be used as a marker of that cognitive process in studies of other mental performances.  

• Second, data from studies of stimulus adaptation during neuroimaging can elucidate the character of mental representations in a particular neural system. Thus, as in the "looking time" paradigms used with infants, the neural sensitivity to the "sameness" of stimuli can be used to provide rich descriptions of equivalence classes, invariances, and non-invariances for neural representations in each cortical region.  

• A third example of using brain data for evaluating cognitive hypotheses is experiments in which behavioral success on a given task is correlated with the intensity of a neuroimaging signal in a specific brain area. Such relationships between cognitive performance and neural activity are important indicators of a necessary relationship between a brain area and a component of cognitive/behavioral processing.  

• Fourth, hypotheses derived from behavioral data suggesting separable processes can be evaluated with respect to the functional brain organization implied by cognitive neuroscience findings. If a given theory hypothesizes that two specific cognitive states are supported by the same underlying process, but an alternative assumes those states are supported by different processes, data from cognitive neuroscience might favor one account. Neuroimaging data from healthy humans can be refined by comparison with findings from studies of cognitive/behavioral impairments exhibited either by humans with discrete lesions (stroke patients), humans with implanted deep brain stimulators, healthy humans with transient neural disruptions (via TMS), or humans stimulated by a pharmacological agent.
  
  

  Moreover, cognitive neuroscience also can elucidate the duration and sequencing of sub-processes, for example, by integrating high temporal resolution MEG data with high spatial resolution fMRI within subject and task. Such finely calibrated data can then inform cognitive and behavioral process models. Finally, subsequent comparisons of brain organization across species may allow the neural basis of such processes to be understood in an evolutionary context.

The Cognitive Neuroscience program seeks sharply innovative proposals aimed at advancing a rigorous understanding of how the human brain supports thought, perception, affect, action, social processes, and other aspects of cognition and behavior. Topics may bear on core functions such as sensory, learning, language, reasoning, emotion, and executive processes, or more specialized processes such as empathy, creativity, representation of self and other, or intentionality, among many other possibilities. Topics may also include how such processes develop and change in the brain.

The program is particularly interested in supporting the development of new techniques and technologies for recording, analyzing, and modeling complex brain activity. Such projects should include a plan for sharing new software and other technologies with the research community at large.

Studies of disease states (e.g., brain damaged patients) may be components of projects supported by this program. However, the emphasis in such projects must be to advance basic scientific understanding of neural mechanisms, and not on disease etiology, diagnosis, or treatment.

The program also intends to foster projects that integrate perspectives across disciplines, e.g., from the cognitive sciences, developmental sciences, biology, computer science, engineering, education, anthropology, physics, mathematics and statistics. For example, projects that involve collaborations among individuals with expertise in one of the cognitive sciences, neuroimaging, neural microcircuitry, and modeling complex systems are strongly encouraged. Other interdisciplinary emphases are also of keen interest.

Examples of appropriate grant proposals include, but are not be limited to, the following. It is to be expected that scientific advances will overtake many of the following issues, and that other research and development matters will emerge as key enablers to progress in basic cognitive neuroscience.

• Approaches addressing research questions with a novel range of techniques (e.g., using neuroimaging, lesion-deficit data, and computational modeling).

• Hypotheses based on cognitive/behavioral/social/developmental research that lead to tests either of systems level or neuro-computational models of psychological processes. The computational models should involve vertical integration over realistic neural circuitry at specified scales.

• Development of new methods for acquisition-time representation of functional neuroimaging data, e.g., providing output which can be used to control online continuous, experimental manipulations of behavioral/cognitive (stimulus) variables.

• Study of the relation between cognitive/behavioral performance and structural features of brain such as white/gray matter ratio, neurotransmitter sites, connectivity maps, unfolded topological models of cortex, morphology, or diffusion tensor imaging.

• Integrated use of techniques involving both human and animal models to provide convergent evidence about a specific research problem (e.g., the neural codes for perceptual representations, the role of endogenous neurochemicals in social bonding).

• Development of quantitative techniques for meta-analysis and modeling of functional neuroimaging data with respect to localization, temporal dynamics, and componential modeling of cognitive/behavioral processes.

• Neuroimaging of the infant and child brain for comparsion with adults in order to understand the development of functional brain organization.

• Development of new methods for characterizing the morphology of activation clusters in neuroimaging data (going beyond the stereotactic location of peak activation).

• Comparative gene expression studies in nonhuman primates of the neural regions governing higher cognitive functions within an evolutionary framework.

• Study of the development and character of specialization of brain areas for particular cognitive, perceptual, affective, and action processes.

• Development of new techniques for integrating independent measurements of the dynamic interactions in time and space of specific neural activity.

• Mathematical analyses of stable individual differences in brain organization (e.g., modeling individual differences in localized neural activity for elementary psychological operations).

• Adaptation of advanced experimental psychology methods for adults and children afflicted with neurological or cognitive impairments in order to characterize more fully the effects of dysfunctions of specific brain areas, clarifying thereby the functions of those areas. (For instance, do brain areas compromised by Parkinson's Disease support non-motor cognitive or executive functions?)

• The effect of environmental factors (impoverishment or enrichment) on the development and function of specific brain areas.

• Development of effective techniques for mapping receptor/ligand binding profiles during cognitive functions such as working memory, selective attention, and implicit memory in healthy humans.

FUNDING OPPORTUNTIES

(1) Individual Investigator Research Projects. Many research topics are studied most effectively by individual research scientists or by small teams of collaborating investigators. Investigators are invited to submit proposals that focus on cognitive neuroscience topics, including but not limited to those illustrated above.

(2) Workshops. Workshops will be supported that bring together diverse scientific partners around specific topics. Meetings will be focused on topics that can benefit from intensive small group discussions. It is anticipated that most workshops will require $15,000-$20,000 of support for 12 months, including indirect costs. However, larger requests will also be considered.

(3) Doctoral dissertation improvement grants. To improve training in neuroscientific approaches to cognitive, affective, perceptual, social, and developmental research, support will be provided to graduate students in the form of doctoral dissertation improvement grants. These awards can provide funds for items not normally available through the students' university, for significant data-gathering projects, and to conduct research away from the student's home campus. The maximum request can be $18,000 for 12 months, with no indirect costs, stipend, or tuition expenses allowed.