The Swartz Foundation


"A science of the mind must reduce [complexities of behavior] to

their elements. A science of the brain must

point out the functions of its elements.

A science of the relations of mind and brain must show

how the elementary ingredients of the former

correspond to the elementary functions of the latter."


-- William James, The Principles of Psychology, Chapter 2 (1890)

I. Vision Statement

The strategic intent of the Swartz Foundation is to integrate problem-solving approaches from physics, mathematics, electrical engineering and computer science into neuroscience research, to better understand the relationship between the human brain and mind, one of the great frontiers of 21st-century science. Theoretical neuroscience (including computational neuroscience) studies how brains process information by mathematically modeling them at the biophysical (molecular and cellular), circuit and network, and whole brain system, behavioral and social interaction levels. The Foundation supports theoretical neuroscience research that investigates basic principles and mechanisms of brain function.


Neuroscience has developed on a number of levels, appropriate to the study of a complex and large-scale adaptive system. In computer science, the OSI "stack" (Open System Interconnect) defines such a layered model for computer networking and data communications, ranging from the physical to data link layer, to network, transport, session and presentation layers, up to application functionality. A useful framework [Multi-level (“Brain Stack”) Framework] for understanding the brain might be similarly layered: from molecular to single synapse/ neuron, to local circuits/cortical columns, to complex networks/the whole brain system…up to nonconscious/conscious cognitive and behavioral levels, and out to social interaction (see Sept., 2006, Multi-level Brain Modeling Workshop). Developing the working relationship between these levels will lead to a deeper understanding of brain function and the mind/brain connection.

II. Research Interests

(1) Brain Dynamics:

What are the dynamical connections between neural function and behavior at different temporal and spatial scales? We wish to explore the relations between behavior, macroscopic brain dynamics (observed extracranially by high-resolution EEG, MEG, and fMRI), mesoscopic activity (intracranially-recorded local field potentials), and neural microdynamics in small networks of neurons.

(2) Circuit/Network Models:

We hope to identify fundamental system neurobiology principles by looking for brain circuits and networks that underlie defined neural response properties and behavior. In cortex, for example, is there a small fundamental set of "unit circuits" that can be used to support diverse computational functions? We'd also like to better understand the source and nature of brain rhythms that appear to be correlated with specific behavioral states and brain functions and to characterize the circuits that underlie these important oscillators.

Learning and memory is another area where the Foundation believes theoretical neurobiology approaches will make a difference. Unlike today's silicon-based inorganic computers, carbon-based organic brains learn and adapt by remodeling and rewiring their circuits. Experimental psychologists have been describing the behavioral principles of learning and memory in increasing detail since the late 19th century, and we've seen an unprecedented growth in our understanding of the molecular and cellular mechanisms involved in the underlying synaptic plasticity. We have not seen similar progress at the intervening cortical circuit and network levels. Will physical or computer science models help us understand how memory fidelity is maintained?

(1) Systems/engineering/mathematical applications:

New information theoretic concepts originating from computer science/engineering can be applied to neuroscience in mutually informative ways. For instance, there are certainly insights to be gained on how brain networks operate by considering hybrid analog/digital models. Conversely, discoveries in brain science can provide models for engineering complex and robust systems to do tasks that the brain performs well.

Some areas of brain research clearly invite the application of physical/mathematical approaches. For instance, neural coding questions will certainly benefit from information theoretic analysis. Physical optimality principles are another example. Can elements of brain structure and function be understood as arising from optimality principles, such as minimum wiring length, optimal encoding under various criteria (e.g., finding the independent components of natural scenes), or energy minimization?

(2) Global models:

Among other things, we're interested in data-based models of higher brain function, ranging from how the brain manages to parse complex scenes and build a three-dimensional (or higher) world of 'information' inside our heads, to the influence of emotion on brain activity, to questions about consciousness (and the adaptive nonconscious). Researchers are now taking conscious and unconscious processing seriously as neuroscience problems. What are the neural correlates of consciousness and other high-level properties of the human brain? Is consciousness a local phenomenon in the brain or a distributed one? Can consciousness be measured? Modeled? Even if we come to understand perceptual consciousness, it appears from both introspection and experiment that the conscious "I" has precious little access to much of what's going on in the brain. The Swartz Foundation has recently focused its attention on nonconscious (cognitive) processing. Can we define the nature, and discover the brain substrates, of those cognitive faculties that are largely unavailable to consciousness, ones that we call "intuition", "vision", or "gut feeling"? The Swartz Foundation seeks to sponsor large-scale fMRI and EEG data analysis and modeling efforts to gain neurobiological insights to these questions.


Our funding is motivated by specific research themes.  As a general rule, support will be awarded on a project-by-project basis. As a start, we made a major funding commitment in the area of Brain Dynamics at the Swartz Center for Computational Neuroscience at UCSD. Besides aligning with SF research directions, other grant considerations include:

• Work difficult to fund from traditional sources
• New researchers [you needn't be a PI to apply]
• Seed funding to achieve proof-of-concept
• Current SF-supported researchers.

We are especially interested in projects that involve collaborations between laboratories and between institutions, and research ideas that reach through layers of the brain "stack".

The Virtual Neuroscience Institute:

A major operational goal of the Swartz Foundation is to promote intellectual and practical collaboration and communication between neurobiologists and scientists outside the traditional neuroscience field, as participants in a "Virtual Neuroscience Institute". We hope that such informal associations, focused on the common strategic polestar of exploring the mind/brain connection, and identifying underlying fundamental principles will help to generate new and robust paths for analysis and understanding.

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For more information, contact the Swartz Foundation.

Sunday, July 14, 2024
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