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| Year |
Degree |
Department |
Institute |
| 2010–2011 |
Post-doctoral
fellow |
Department
of Physics |
The University of Chicago |
| 2008–2010 |
Post-doctoral fellow |
Department
of Neurobiology |
Weizmann Institute of Science |
| |
The
Department of Psychology |
The University of Maryland, U.S.A |
|
| 2006-2008 |
Ph.D |
Biology
Department of Animal Physiology and the Max
Planck institute for Biological Cybernetics |
Tübingen
University |
| 2005-2006 |
M.Sc |
Department
of Neuro-Biochemistry, Life Science Faculty |
Tel-Aviv University, Israel. |
| 2001-2004 |
B.Sc |
Life Science Faculty |
Tel-Aviv
University , Israel |
| 2002-2005 |
B.Sc |
The
Exact Sciences Faculty |
Tel-Aviv
University , Israel |
Research Interests
While the field of neuroscience is constantly developing new sophisticated methods to analyze neuronal activity, the methodologies to study the ultimate output of this activity – namely the behavior of the organism – remain decades behind. To date, many behavioral studies are either conducted in natural surroundings using quite primitive methods, or are conducted in controlled laboratory environments that are highly un-natural, using artificial tasks. The general goal of my work is to establish better quantitative and computational methods to study natural behavior focusing mainly on sensory behavior. I term this Neuroecology - understanding the animal’s behavior (determined by the brain) as it is driven by its natural environment.

Myotis
myotis in a complex statistical world
(c) D. Nill
Echolocating bats can regulate almost all aspects of information acquisition what makes them fascinating to study active sensing : they can control acquisition timing, signal design and directionality. Because they emit the energy with which the sense their surroundings, one can record a bat from a distant (without even seeing it) and capture its behavior.
Rousettus aegyptiacus in flight
The active nature of echolocation also makes it one of the most tightly-controlled sensory systems. Most sensory systems allow some active control on the information acquired from the environment. Echolocating bats can regulate almost all aspects of information acquisition: they can control acquisition timing, signal design and directionality. Some of the questions I plan to work on include:
1. Behavioral strategies and sensory adaptations for optimal sensory acquisition: how does the animal move and operate its sensors in order to optimize information acquisition from the surroundings and how are the sensors adapted for this goal?

Egyptian fruit bats direct their beam such that the slope and not the peak falls on the object
2. Representation of the world in the brain (using fMRI) : what is the role of experience and what is that of innateness in creating a sensory representation of the world in the brain? How do the representations of different sensory modalities (vision, auditory, olfactory) influence each other? And how plastic are all of the above?
legend: Greater mouse-eared in a classical two-alternative-choice experiment bats link:http://news.bbc.co.uk/2/hi/science/nature/8085477.stm
3. Social behavior and swarming: we plan to follow long range navigating bats in the wild using GPSs and learn about swarm dynamics, information transfer between members of the colony and more.
Myotis bechsteinii
(c) D. Nill
New technologies enable studying these complex behaviors in a quantitative manner for the first time. Some of these methods include: artificial SONAR to simulate bat echolocation, ultrasonic-microphone arrays to reconstruct bats’ emitted beams, mini-microphones mounted on the bat’s head to record the world as it receives it, mini-GPSs to record natural trajectories of bats in the wild and fMRI to study the representation of sensory information in the brain. All projects include an experimental work aside a modeling part.
Publications
1) Y. Yovel, B. Falk, C. F. Moss, N. Ulanovsky, (2011) Active control of acoustic field-of-view in a biosonar system, PLoS Biology, 9(9): e1001147.
2) M. Franz Y. Yovel, M. L. Melcón, P. Stilz, H-U. Schnitzler (2011) Systematische Merkmalsbewertung in komplexen Ultraschallsignalen mit Lernmaschinen Informatik-Spektrum 1-6
3) Y. Yovel, M. Geva, N. Ulanovsky, (2011) Click based echolocation: not so primitive after all, J. Comp. Physiol. J. Comp. Physiol. 197: 515-530.
4) Y. Yovel, M. Franz, P. Stilz, H-U. Schnitzler, (2011) Complex echo classification by echo-locating bats: a review, J. Comp. Physiol. 197: 475-490.
5) M.L. Melcon, Y. Yovel, (equal contribution), A. Denzinger, H-U Schnitzler, (2011) How greater mouse-eared bats deal with ambiguous echoic scences. J. Comp. Physiol. 197: 505-514.
6) Y. Yovel, WWL. Au (2010) How Can Dolphins Recognize Fish According to Their Echoes? A Statistical Analysis of Fish Echoes. PLoS ONE 5(11): e14054.
7) Y. Yovel, B. Falk, C. F. Moss, N. Ulanovsky, (2010) Optimal localization by pointing off-axis. Science 327, 701-704.
8) Y. Yovel, M.L. Melcon (equal contribution), M.O. Franz, A. Denzinger, H-U Schnitzler, (2009) The voice of bats: how greater mouse-eared bats recognize individuals based on their echolocation calls. PLoS Comput Biol 4(3): e1000400.
9) Y. Yovel, P. Stilz, M.O. Franz, A. Boonman,H-U Schnitzler, (2009) What a plant sounds like: the statistics of vegetation echoes as received by echolocating bats. PLoS Comput Biol 5(7): e1000429.
10) A. Mezer, Y. Yovel, O. Pasternak, T. Gorfine, Y. Assaf, (2009) Cluster analysis of resting-state fMRI time series. Neuroimage 45(4), 1117-1125.
11) Y. Yovel, M. O. Franz, P. Stilz, H-U. Schnitzler (2008) Plant Classification from Bat-Like Echolocation Signals. PLoS Comput Biol 4(3): e1000032.
12) Y. Assaf, T. Blumenfeld-Katzir, Y. Yovel, P. J. Basser (2008) AxCaliber: a method for measuring axon diameter distribution from diffusion MRI. Magnetic Resonance in Medicine 59, 1347–1354.
13) Y. Yovel and Y. Assaf )2007) Virtual Definition of Neuronal Tissue by Cluster Analysis of Multi-parametric Imaging (virtual-dot-com imaging). NeuroImage 35(1), 58–69.
14) E. Levin, A. Barnea, Y. Yovel and Y. Yom-Tov (2006) Have introduced fish initiated piscivory among the long-fingered bat? Mamm Biol 71, 139–143.
Peer-reviewed conference articles:
1) B. Petreska, and Y. Yovel (2008) A Neural Model of Demyelination of the Mouse Spinal Cord. In Proceedings of IEEE World Congress on Computational Intelligence (WCCI2008). Won the award for best student work





