Drexel Laboratory for Adaptive Cognition

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In memoriam, David C. Knill

Dave Knill was my post-doctoral mentor for four years. He was a friend, but it's probably more accurate to say that I was in awe of him. Here is a small sample of the qualities I saw in Dave at our every meeting: His ability to immediately see through to the absolute heart of a scientific question, his insistence on tackling hard and meaningful problems rather than low hanging fruit, his dedication to understanding the brain as it functions in the world rather than in the laboratory, and his uncanny ability to design a simple experiment that would break new ground in a field regardless of the outcome. These qualities alone would make a great scientist, but Dave also brought incredible mathematical rigor and elegance to every problem he studied. I have learned so much, and benefitted greatly from my time working with Dave. I hope to emulate his qualities as a tribute to his memory. But sadly, Dave's passing is a tremendous and irreplaceable loss to cognitive science.

Special colloquium Series: Cognition, Computation, Rationality.

The Applied Cognitive and Brain Sciences (ACBS) program at Drexel University is pleased to host a special colloquium series for the 2014-2015 academic year. The topic of this series is 'Cognition, Computation, Rationality: Consilience at the frontiers of computational, cognitive, neural, and decision sciences'. Head over to this page for details.

The Adaptive Nature of Visual Working Memory

A new paper is out in print: 'The Adaptive Nature of Visual Working Memory'. This is an accessible overview of how statistical learning plays a key role in visual memory, and highlights the crucial role of computational theory in psychology. Head on over to the publications page to download a copy.

Seeking new graduate students!

Dr. Sims is seeking Ph.D. students to begin in the Fall term of 2015. If you are a talented undergraduate with a passion for studying the human mind you are encouraged to contact Dr. Sims by email. Our research lab is especially interested in individuals with an interest or background in applying quantitative and computational methods to understand human cognition. See the research descriptions on this site for an idea of ongoing projects and possibilities.

Drexel Laboratory for Adaptive Cognition

Our laboratory is interested in answering the following question: How is the brain able to efficiently accomplish complex goals in an uncertain world?

This fundamental question spans multiple areas of cognitive science: decision-making, learning from feedback, perception, and motor control. Even a seemingly simple task like reaching to pick up a glass of water involves solving tremendous challenges: the brain must compensate for time-delayed and uncertain sensory signals, and process this information extremely rapidly to control a noisy and error-prone motor system. Similarly, when we look at a photograph and try to remember some particular detail, we face a complex challenge as the capacity of visual memory is severely limited. Therefore the brain faces a decision regarding what visual information to attend to, what to ignore, and how best to store it in memory in order to achieve our goals. These examples illustrate that low-level perception, memory, and basic motor control all involve complex forms of decision-making under uncertainty. Our laboratory is interested in understanding these processes.

In everyday life, the incredible complexity of the problems solved by the brain is hidden from our awareness. Oftentimes, it is only when we try to replicate the breadth and robustness of human performance in a computational model is the extent of the mind's complexity apparent. Computational models of human cognition serve an important role in all of the research carried out in our laboratory. They serve as an explicit statement of a scientific theory, but they can also generate novel predictions that can be tested experimentally. In many cases, human performance exceeds that of any existing algorithm (for example, in categorizing images or recognizing faces). By studying human behavior and building computational models of cognition, we can also advance the state of the art in engineering and applied sciences.

Recent and ongoing research projects in the lab focus on:

If you are interested in becoming involved in our research, please feel free to contact us.