Eric Fortune

Dr. Eric Fortune


Research Focus & Metrics

Academic Career Length

35Years (1992-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2001 in Trends in Neurosciences
Verified
Journal Article
Closed access
EFEric Fortune
Eric Fortune
GRGary J. Rose
Gary J. Rose

25 September 1995 in Journal of Comparative Neurology
Verified
Journal Article
Closed access
PDF file
EFEric Fortune
Eric Fortune
DMDaniel Margoliash
Daniel Margoliash

15 November 1992 in Journal of Comparative Neurology
Verified
Journal Article
Closed access
PDF file
EFEric Fortune
Eric Fortune
DMDaniel Margoliash
Daniel Margoliash

3 June 2014 in Integrative and Comparative Biology
Verified
Journal Article
Open access
PDF file
NCNoah J. Cowan
Noah J. Cowan
MAMustafa Mert Ankarali
Mustafa Mert Ankarali
JDJonathan P. Dyhr
Jonathan P. Dyhr
MMManu S. Madhav
Manu S. Madhav
EREatai Roth
Eatai Roth
TDThomas L. Daniel
Thomas L. Daniel
Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathematical basis for understanding the role of feedback in the stability (or change) of dynamical systems. It provides a framework for understanding any system with regulation via feedback, including biological ones such as regulatory gene networks, cellular metabolic systems, sensorimotor dynamics of moving animals, and even ecological or evolutionary dynamics of organisms and populations. Here, we focus on four case studies of the sensorimotor dynamics of animals, each of which involves the application of principles from control theory to probe stability and feedback in an organism’s response to perturbations. We use examples from aquatic (two behaviors performed by electric fish), terrestrial (following of walls by cockroaches), and aerial environments (flight control by moths) to highlight how one can use control theory to understand the way feedback mechanisms interact with the physical dynamics of animals to determine their stability and response to sensory inputs and perturbations. Each case study is cast as a control problem with sensory input, neural processing, and motor dynamics, the output of which feeds back to the sensory inputs. Collectively, the interaction of these systems in a closed loop determines the behavior of the entire system.

4 November 2011 in Science
Verified
Journal Article
Closed access
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EFEric Fortune
Eric Fortune
CRCarlos Rodríguez
Carlos Rodríguez
DLDavid Li
David Li
GBGregory F. Ball
Gregory F. Ball
MCMelissa J. Coleman
Melissa J. Coleman
Plain-tailed wrens (Pheugopedius euophrys) cooperate to produce a duet song in which males and females rapidly alternate singing syllables. We examined how sensory information from each wren is used to coordinate singing between individuals for the production of this cooperative behavior. Previous findings in nonduetting songbird species suggest that premotor circuits should encode each bird’s own contribution to the duet. In contrast, we find that both male and female wrens encode the combined cooperative output of the pair of birds. Further, behavior and neurophysiology show that both sexes coordinate the timing of their singing based on feedback from the partner and suggest that females may lead the duet.

4 November 2013 in Proceedings of the National Academy of Sciences
Verified
Journal Article
Closed access
SSShahin Sefati
Shahin Sefati
INIzaak D. Neveln
Izaak D. Neveln
EREatai Roth
Eatai Roth
TMTerence R. T. Mitchell
Terence R. T. Mitchell
JSJames B. Snyder
James B. Snyder
NCNoah J. Cowan
Noah J. Cowan
Significance: Animals often produce substantial forces in directions that do not directly contribute to movement. For example, running and flying insects produce side-to-side forces as they travel forward. These forces generally “cancel out,” and so their role remains a mystery. Using a multidisciplinary approach, we show that mutually opposing forces can enhance both maneuverability and stability at the same time, although at some energetic cost. In addition to challenging the maneuverability–stability dichotomy within locomotion, our results challenge the same tradeoff within the engineering of mobile robots. This may inspire the exploration of a new set of strategies for the design and control of mobile systems.