January 1, 2012 The Evolution of Overconfidence presented by Daniel

When: January 1, 2012 12:00
Where: Physics 377
Presenter: Daniel Soudry (Electrical Engineering)
Link to paper: http://www.nature.com/nature/journal/v477/n7364/full/nature10384.html

The evolution of overconfidence

• Dominic D. P. Johnson
• & James H. Fowler

Confidence is an essential ingredient of success in a wide range of domains ranging from job performance and mental health to sports, business and combat. Some authors have suggested that not just confidence but overconfidence—believing you are better than you are in reality—is advantageous because it serves to increase ambition, morale, resolve, persistence or the credibility of bluffing, generating a self-fulfilling prophecy in which exaggerated confidence actually increases the probability of success. However, overconfidence also leads to faulty assessments, unrealistic expectations and hazardous decisions, so it remains a puzzle how such a false belief could evolve or remain stable in a population of competing strategies that include accurate, unbiased beliefs. Here we present an evolutionary model showing that, counterintuitively, overconfidence maximizes individual fitness and populations tend to become overconfident, as long as benefits from contested resources are sufficiently large compared with the cost of competition. In contrast, unbiased strategies are only stable under limited conditions. The fact that overconfident populations are evolutionarily stable in a wide range of environments may help to explain why overconfidence remains prevalent today, even if it contributes to hubris, market bubbles, financial collapses, policy failures, disasters and costly wars.

December 11, 2011 Information Transduction Capacity of Noisy Biochemical Signaling Networks presented by Daniel

When: December 11, 2011 12:00
Where: Physics 377
Presenter: Daniel Hexner (Dov Levine's group, physics)
Link to paper: http://www.sciencemag.org/content/334/6054/354.full

Information Transduction Capacity of Noisy Biochemical Signaling Networks

1. Raymond Cheong, 
2. Alex Rhee, 
3. Chiaochun Joanne Wang, 
4. Ilya Nemenman, 
5. Andre Levchenko

1. 
   

Molecular noise restricts the ability of an individual cell to resolve input signals of different strengths and gather information about the external environment. Transmitting information through complex signaling networks with redundancies can overcome this limitation. We developed an integrative theoretical and experimental framework, based on the formalism of information theory, to quantitatively predict and measure the amount of information transduced by molecular and cellular networks. Analyzing tumor necrosis factor (TNF) signaling revealed that individual TNF signaling pathways transduce information sufficient for accurate binary decisions, and an upstream bottleneck limits the information gained via multiple integrated pathways. Negative feedback to this bottleneck could both alleviate and enhance its limiting effect, despite decreasing noise. Bottlenecks likewise constrain information attained by networks signaling through multiple genes or cells.