@article{goldberg1984relation,
  title={Relation between discharge regularity and responses to externally applied galvanic currents in vestibular nerve afferents of the squirrel monkey},
  author={Goldberg, JM and Smith, CHARLES E and Fernandez, C},
  journal={Journal of neurophysiology},
  volume={51},
  number={6},
  pages={1236--1256},
  year={1984},
  publisher={American Physiological Society Bethesda, MD}
}
@article{benzi1981mechanism,
  title={The mechanism of stochastic resonance},
  author={Benzi, Roberto and Sutera, Alfonso and Vulpiani, Angelo},
  journal={Journal of Physics A: mathematical and general},
  volume={14},
  number={11},
  pages={L453},
  year={1981},
  publisher={iOP Publishing}
}
@article{palanca2015vivo,
author = {Palanca-Castan, Nicolas and K{\"{o}}ppl, Christine},
journal = {Brain, behavior and evolution},
number = {4},
pages = {271--286},
publisher = {Karger Publishers},
title = {{In vivo recordings from low-frequency nucleus laminaris in the barn owl}},
volume = {85},
year = {2015}
}
@article{Chapeau-blondeau1996,
author = {Chapeau-blondeau, Franqois and Godivier, Xavier and Chambet, Nicolas},
file = {:home/huben/Desktop/PhysRevE.53.1273.pdf:pdf},
number = {1},
pages = {3--5},
title = {s(t)=+„5(t},
volume = {53},
year = {1996}
}
@article{walz2014static,
author = {Walz, Henriette and Grewe, Jan and Benda, Jan},
journal = {Journal of Neurophysiology},
number = {4},
pages = {752--765},
publisher = {Am Physiological Soc},
title = {{Static frequency tuning accounts for changes in neural synchrony evoked by transient communication signals}},
volume = {112},
year = {2014}
}
@article{Chapeau-blondeau1996,
author = {Chapeau-blondeau, Franqois and Godivier, Xavier and Chambet, Nicolas},
file = {:home/huben/Desktop/PhysRevE.53.1273.pdf:pdf},
number = {1},
pages = {3--5},
title = {s(t)=+„5(t},
volume = {53},
year = {1996}
}
@article{lindner2016mechanisms,
author = {Lindner, Benjamin},
journal = {IEEE Transactions on Molecular, Biological and Multi-Scale Communications},
publisher = {IEEE},
title = {{Mechanisms of information filtering in neural systems}},
year = {2016}
}
@article{krahe2002stimulus,
author = {Krahe, R{\"{u}}diger and Kreiman, Gabriel and Gabbiani, Fabrizio and Koch, Christof and Metzner, Walter},
journal = {Journal of Neuroscience},
number = {6},
pages = {2374--2382},
publisher = {Soc Neuroscience},
title = {{Stimulus encoding and feature extraction by multiple sensory neurons}},
volume = {22},
year = {2002}
}
@article{ahn2014heterogeneity,
author = {Ahn, Jheeyae and Kreeger, Lauren J and Lubejko, Susan T and Butts, Daniel A and MacLeod, Katrina M},
journal = {Journal of neurophysiology},
number = {11},
pages = {2320--2331},
publisher = {Am Physiological Soc},
title = {{Heterogeneity of intrinsic biophysical properties among cochlear nucleus neurons improves the population coding of temporal information}},
volume = {111},
year = {2014}
}
@article{Krahe2008,
abstract = {Multiple topographic representations of sensory space are common in the nervous system and presumably allow organisms to separately process particular features of incoming sensory stimuli that vary widely in their attributes. We compared the response properties of sensory neurons within three maps of the body surface that are arranged strictly in parallel to two classes of stimuli that mimic prey and conspecifics, respectively. We used information-theoretic approaches and measures of phase locking to quantify neuronal responses. Our results show that frequency tuning in one of the three maps does not depend on stimulus class. This map acts as a low-pass filter under both conditions. A previously described stimulus-class-dependent switch in frequency tuning is shown to occur in the other two maps. Only a fraction of the information encoded by all neurons could be recovered through a linear decoder. Particularly striking were low-pass neurons the information of which in the high-frequency range could not be decoded linearly. We then explored whether intrinsic cellular mechanisms could partially account for the differences in frequency tuning across maps. Injection of a Ca2+ chelator had no effect in the map with low-pass characteristics. However, injection of the same Ca2+ chelator in the other two maps switched the tuning of neurons from band-pass/high-pass to low-pass. These results show that Ca2+-dependent processes play an important part in determining the functional roles of different sensory maps and thus shed light on the evolution of this important feature of the vertebrate brain.},
author = {Krahe, R{\"{u}}diger and Bastian, Joseph and Chacron, Maurice J},
doi = {10.1152/jn.90300.2008},
issn = {0022-3077},
journal = {Journal of Neurophysiology},
number = {2},
pages = {852--867},
publisher = {American Physiological Society},
title = {{Temporal Processing Across Multiple Topographic Maps in the Electrosensory System}},
url = {http://jn.physiology.org/content/100/2/852},
volume = {100},
year = {2008}
}
@article{walz2014static,
author = {Walz, Henriette and Grewe, Jan and Benda, Jan},
file = {:home/huben/Documents/Paper/Walz2014.pdf:pdf},
journal = {Journal of Neurophysiology},
number = {4},
pages = {752--765},
publisher = {Am Physiological Soc},
title = {{Static frequency tuning accounts for changes in neural synchrony evoked by transient communication signals}},
volume = {112},
year = {2014}
}
@article{Walz2014,
author = {Walz, Henriette and Grewe, Jan and Benda, Jan},
doi = {10.1152/jn.00576.2013},
file = {:home/huben/Documents/Paper/Walz2014.pdf:pdf},
isbn = {2154253113},
pages = {752--765},
title = {{Static frequency tuning accounts for changes in neural synchrony evoked by transient communication signals}},
year = {2014}
}
@article{white2000channel,
author = {White, John A and Rubinstein, Jay T and Kay, Alan R},
journal = {Trends in Neurosciences},
number = {3},
pages = {131--137},
publisher = {Elsevier},
title = {{Channel noise in neurons}},
volume = {23},
year = {2000}
}
@article{faisal2008noise,
author = {Faisal, A Aldo and Selen, Luc P J and Wolpert, Daniel M},
file = {:home/huben/Documents/Paper/Faisal2008.pdf:pdf},
journal = {Nature Reviews Neuroscience},
number = {4},
pages = {292--303},
publisher = {Nature Publishing Group},
title = {{Noise in the nervous system}},
volume = {9},
year = {2008}
}
@article{fourcaud2003spike,
author = {Fourcaud-Trocm{\'{e}}, Nicolas and Hansel, David and {Van Vreeswijk}, Carl and Brunel, Nicolas},
journal = {The Journal of Nneuroscience},
number = {37},
pages = {11628--11640},
publisher = {Soc Neuroscience},
title = {{How spike generation mechanisms determine the neuronal response to fluctuating inputs}},
volume = {23},
year = {2003}
}
@article{krahe2004burst,
author = {Krahe, R{\"{u}}diger and Gabbiani, Fabrizio},
journal = {Nature Reviews Neuroscience},
number = {1},
pages = {13--23},
publisher = {Nature Publishing Group},
title = {{Burst firing in sensory systems}},
volume = {5},
year = {2004}
}
@article{grewe2017synchronous,
  title={Synchronous spikes are necessary but not sufficient for a synchrony code in populations of spiking neurons},
  author={Grewe, Jan and Kruscha, Alexandra and Lindner, Benjamin and Benda, Jan},
  journal={Proceedings of the National Academy of Sciences},
  volume={114},
  number={10},
  pages={E1977--E1985},
  year={2017},
  publisher={National Acad Sciences}
}
@article{schreiber2002energy,
author = {Schreiber, Susanne and Machens, Christian K and Herz, Andreas V M and Laughlin, Simon B},
journal = {Neural Computation},
number = {6},
pages = {1323--1346},
publisher = {MIT Press},
title = {{Energy-efficient coding with discrete stochastic events}},
volume = {14},
year = {2002}
}
@article{neiman2011temporal,
abstract = {The manner in which information is encoded in neural signals is a major issue in Neuroscience. A common distinction is between rate codes, where information in neural responses is encoded as the number of spikes within a specified time frame (encoding window), and temporal codes, where the position of spikes within the encoding window carries some or all of the information about the stimulus. One test for the existence of a temporal code in neural responses is to add artificial time jitter to each spike in the response, and then assess whether or not information in the response has been degraded. If so, temporal encoding might be inferred, on the assumption that the jitter is small enough to alter the position, but not the number, of spikes within the encoding window. Here, the effects of artificial jitter on various spike train and information metrics were derived analytically, and this theory was validated using data from afferent neurons of the turtle vestibular and paddlefish electrosensory systems, and from model neurons. We demonstrate that the jitter procedure will degrade information content even when coding is known to be entirely by rate. For this and additional reasons, we conclude that the jitter procedure by itself is not sufficient to establish the presence of a temporal code.},
author = {Neiman, Alexander B and Russell, David F and Rowe, Michael H},
doi = {10.1371/journal.pone.0027380},
journal = {PLOS ONE},
number = {11},
pages = {1--13},
publisher = {Public Library of Science},
title = {{Identifying Temporal Codes in Spontaneously Active Sensory Neurons}},
url = {http://dx.doi.org/10.1371{\%}2Fjournal.pone.0027380},
volume = {6},
year = {2011}
}
@article{gabbiani1996coding,
author = {Gabbiani, Fabrizio},
journal = {Network: Computation in Neural Systems},
number = {1},
pages = {61--85},
publisher = {Citeseer},
title = {{Coding of time-varying signals in spike trains of linear and half-wave rectifying neurons}},
volume = {7},
year = {1996}
}
@article{gammaitoni1998resonance,
author = {Gammaitoni, Luca and H{\"{a}}nggi, Peter and Jung, Peter and Marchesoni, Fabio},
doi = {10.1103/RevModPhys.70.223},
journal = {Rev. Mod. Phys.},
number = {1},
pages = {223--287},
publisher = {American Physical Society},
title = {{Stochastic resonance}},
url = {http://link.aps.org/doi/10.1103/RevModPhys.70.223},
volume = {70},
year = {1998}
}
@article{davtyan2016protein,
author = {Davtyan, Aram and Platkov, Max and Gruebele, Martin and Papoian, Garegin A},
doi = {10.1002/cphc.201501125},
issn = {1439-7641},
journal = {ChemPhysChem},
keywords = {F{\"{o}}rster resonance energy transfer,brownian dynamics,molecular dynamics,protein folding,stochastic resonance},
number = {9},
pages = {1305--1313},
title = {{Stochastic Resonance in Protein Folding Dynamics}},
url = {http://dx.doi.org/10.1002/cphc.201501125},
volume = {17},
year = {2016}
}
@article{VanderGroen2016,
abstract = {Random noise enhances the detectability of weak signals in nonlinear systems, a phenomenon known as stochastic resonance (SR). Though counterintuitive at first, SR has been demonstrated in a variety of naturally occurring processes, including human perception, where it has been shown that adding noise directly to weak visual, tactile, or auditory stimuli enhances detection performance. These results indicate that random noise can push subthreshold receptor potentials across the transfer threshold, causing action potentials in an otherwise silent afference. Despite the wealth of evidence demonstrating SR for noise added to a stimulus, relatively few studies have explored whether or not noise added directly to cortical networks enhances sensory detection. Here we administered transcranial random noise stimulation (tRNS; 100–640 Hz zero-mean Gaussian white noise) to the occipital region of human participants. For increasing tRNS intensities (ranging from 0 to 1.5 mA), the detection accuracy of a visual stimuli changed according to an inverted-U-shaped function, typical of the SR phenomenon. When the optimal level of noise was added to visual cortex, detection performance improved significantly relative to a zero noise condition (9.7 ± 4.6{\%}) and to a similar extent as optimal noise added to the visual stimuli (11.2 ± 4.7{\%}). Our results demonstrate that adding noise to cortical networks can improve human behavior and that tRNS is an appropriate tool to exploit this mechanism.SIGNIFICANCE STATEMENT Our findings suggest that neural processing at the network level exhibits nonlinear system properties that are sensitive to the stochastic resonance phenomenon and highlight the usefulness of tRNS as a tool to modulate human behavior. Since tRNS can be applied to all cortical areas, exploiting the SR phenomenon is not restricted to the perceptual domain, but can be used for other functions that depend on nonlinear neural dynamics (e.g., decision making, task switching, response inhibition, and many other processes). This will open new avenues for using tRNS to investigate brain function and enhance the behavior of healthy individuals or patients.},
author = {van der Groen, Onno and Wenderoth, Nicole},
journal = {The Journal of Neuroscience},
number = {19},
pages = {5289 LP -- 5298},
title = {{Transcranial Random Noise Stimulation of Visual Cortex: Stochastic Resonance Enhances Central Mechanisms of Perception}},
url = {http://www.jneurosci.org/content/36/19/5289.abstract},
volume = {36},
year = {2016}
}
@article{shapira2016sound,
author = {Shapira, Einat and Pujol, R{\'{e}}my and Plaksin, Michael and Kimmel, Eitan},
journal = {Physics in Medicine},
publisher = {Elsevier},
title = {{Sound-induced motility of outer hair cells explained by stochastic resonance in nanometric sensors in the lateral wall}},
year = {2016}
}
@article{mileva2016short,
author = {Mileva, G R and Kozak, I J and Lewis, J E},
file = {:home/huben/Desktop/1-s2.0-S0306452216000336-main.pdf:pdf},
journal = {Neuroscience},
pages = {1--11},
publisher = {Elsevier},
title = {{Short-term synaptic plasticity across topographic maps in the electrosensory system}},
volume = {318},
year = {2016}
}
@article{shimokawa1999stochastic,
author = {Shimokawa, T and Rogel, A and Pakdaman, K and Sato, S},
journal = {Physical Review E},
number = {3},
pages = {3461},
publisher = {APS},
title = {{Stochastic resonance and spike-timing precision in an ensemble of leaky integrate and fire neuron models}},
volume = {59},
year = {1999}
}
@incollection{benda2013neural,
author = {Benda, Jan and Grewe, Jan and Krahe, R{\"{u}}diger},
booktitle = {Animal Communication and Noise},
pages = {331--372},
publisher = {Springer},
title = {{Neural noise in electrocommunication: from burden to benefits}},
year = {2013}
}
@article{hupe2008effect,
author = {Hup{\'{e}}, Ginette J and Lewis, John E and Benda, Jan},
journal = {Journal of Physiology-Paris},
number = {4},
pages = {164--172},
publisher = {Elsevier},
title = {{The effect of difference frequency on electrocommunication: chirp production and encoding in a species of weakly electric fish, Apteronotus leptorhynchus}},
volume = {102},
year = {2008}
}
@article{collins1995stochastic,
  title={Stochastic resonance without tuning},
  author={Collins, JJ and Chow, Carson C and Imhoff, Thomas T},
  journal={Nature},
  volume={376},
  number={6537},
  pages={236},
  year={1995},
  publisher={Nature Publishing Group}
}
@article{collins1995aperiodic,
  title={Aperiodic stochastic resonance in excitable systems},
  author={Collins, JJ and Chow, Carson C and Imhoff, Thomas T},
  journal={Physical Review E},
  volume={52},
  number={4},
  pages={R3321},
  year={1995},
  publisher={APS}
}

@article{lindner2002maximizing,
author = {Lindner, Benjamin and Schimansky-Geier, Lutz and Longtin, Andr{\'{e}}},
file = {:home/huben/Desktop/PhysRevE.66.031916.pdf:pdf},
journal = {Physical Review E},
number = {3},
pages = {31916},
publisher = {APS},
title = {{Maximizing spike train coherence or incoherence in the leaky integrate-and-fire model}},
volume = {66},
year = {2002}
}
@article{Chapeau-blondeau1996,
author = {Chapeau-blondeau, Franqois and Godivier, Xavier and Chambet, Nicolas},
file = {:home/huben/Desktop/PhysRevE.53.1273.pdf:pdf},
number = {1},
pages = {3--5},
title = {s(t)=+„5(t},
volume = {53},
year = {1996}
}
@article{borst1999information,
author = {Borst, Alexander and Theunissen, Fr{\'{e}}d{\'{e}}ric E},
journal = {Nature Neuroscience},
number = {11},
pages = {947--957},
publisher = {Nature Publishing Group},
title = {{Information theory and neural coding}},
volume = {2},
year = {1999}
}
@article{krahe2014neural,
author = {Krahe, R{\"{u}}diger and Maler, Leonard},
file = {:home/huben/Downloads/1-s2.0-S0959438813001724-main.pdf:pdf},
journal = {Current opinion in Neurobiology},
pages = {13--21},
publisher = {Elsevier},
title = {{Neural maps in the electrosensory system of weakly electric fish}},
volume = {24},
year = {2014}
}
@article{stocks2000suprathreshold,
author = {Stocks, N G},
file = {:home/huben/Desktop/PhysRevLett.84.2310.pdf:pdf},
journal = {Physical Review Letters},
number = {11},
pages = {2310},
publisher = {APS},
title = {{Suprathreshold stochastic resonance in multilevel threshold systems}},
volume = {84},
year = {2000}
}
@article{stocks2001information,
  title={Information transmission in parallel threshold arrays: Suprathreshold stochastic resonance},
  author={Stocks, NG},
  journal={Physical Review E},
  volume={63},
  number={4},
  pages={041114},
  year={2001},
  publisher={APS}
}
@article{stocks2002application,
  title={The application of suprathreshold stochastic resonance to cochlear implant coding},
  author={Stocks, NG and Allingham, D and Morse, RP},
  journal={Fluctuation and noise letters},
  volume={2},
  number={03},
  pages={L169--L181},
  year={2002},
  publisher={World Scientific}
}

@article{beiran2018coding,
  title={Coding of time-dependent stimuli in homogeneous and heterogeneous neural populations},
  author={Beiran, Manuel and Kruscha, Alexandra and Benda, Jan and Lindner, Benjamin},
  journal={Journal of computational neuroscience},
  volume={44},
  number={2},
  pages={189--202},
  year={2018},
  publisher={Springer}
}

@article{stocks2001generic,
  title={Generic noise-enhanced coding in neuronal arrays},
  author={Stocks, NG and Mannella, Riccardo},
  journal={Physical Review E},
  volume={64},
  number={3},
  pages={030902},
  year={2001},
  publisher={APS}
}
@article{nottebohm1972neural,
  title={Neural lateralization of vocal control in a passerine bird. II. Subsong, calls, and a theory of vocal learning},
  author={Nottebohm, Fernando},
  journal={Journal of Experimental Zoology},
  volume={179},
  number={1},
  pages={35--49},
  year={1972},
  publisher={Wiley Online Library}
}
@article{bastian1976frequency,
  title={Frequency response characteristics of electroreceptors in weakly electric fish (Gymnotoidei) with a pulse discharge},
  author={Bastian, Joseph},
  journal={Journal of Comparative Physiology},
  volume={112},
  number={2},
  pages={165--180},
  year={1976},
  publisher={Springer}
}

@article{gabbiani1996stimulus,
author = {Gabbiani, Fabrizio and Metzner, Walter and Wessel, Ralf and Koch, Christof and Others},
journal = {Nature},
number = {6609},
pages = {564--567},
title = {{From stimulus encoding to feature extraction in weakly electric fish}},
volume = {384},
year = {1996}
}
@article{douglass1993noise,
  title={Noise enhancement of information transfer in crayfish mechanoreceptors by stochastic resonance},
  author={Douglass, John K and Wilkens, Lon and Pantazelou, Eleni and Moss, Frank},
  journal={Nature},
  volume={365},
  number={6444},
  pages={337},
  year={1993},
  publisher={Nature Publishing Group}
}
@article{levin1996broadband,
  title={Broadband neural encoding in the cricket cereal sensory system enhanced by stochastic resonance},
  author={Levin, Jacob E and Miller, John P},
  journal={Nature},
  volume={380},
  number={6570},
  pages={165},
  year={1996},
  publisher={Nature Publishing Group}
}

@article{gabbiani1996codingLIF,
  title={Coding of time-varying signals in spike trains of integrate-and-fire neurons with random threshold},
  author={Gabbiani, Fabrizio and Koch, Christof},
  journal={Neural Computation},
  volume={8},
  number={1},
  pages={44--66},
  year={1996},
  publisher={MIT Press}
}
@article{Gjorgjieva2014,
author = {Gjorgjieva, Julijana and Sompolinsky, Haim and Meister, Markus},
doi = {10.1523/JNEUROSCI.1032-14.2014},
file = {:home/huben/Downloads/12127.full.pdf:pdf},
journal = {Journal of Neuroscience,},
keywords = {efficient coding,off,on,optimality,parallel pathways,retina,sensory processing},
number = {36},
pages = {12127--12144},
title = {{Benefits of Pathway Splitting in Sensory Coding}},
volume = {34},
year = {2014}
}
@article{Maler,
author = {Maler, Leonard},
doi = {10.1016/j.conb.2013.08.013},
file = {:home/huben/Downloads/1-s2.0-S0959438813001724-main.pdf:pdf},
title = {{Neural maps in the electrosensory system of weakly electric fish ¨}},
year = {2014}
}
@article{Huang2016,
author = {Huang, Chengjie G. and Chacron, Maurice J.},
doi = {10.1523/JNEUROSCI.1433-16.2016},
file = {:home/huben/Downloads/parallelcodingchacron2016.pdf:pdf},
keywords = {adaptation,electrosensory,envelope,features,have no or significant,in the same sensory,influence on their,neural coding,neuron type can either,off-type response to first-order,responses to second-order stimulus,significance statement,sk channels,stimulus attributes has no,we demonstrate that heterogeneities,weakly electric fish,while an on- or},
number = {38},
pages = {9859--9872},
title = {{Optimized Parallel Coding of Second-Order Stimulus Features by Heterogeneous Neural Populations}},
volume = {36},
year = {2016}
}
@article{stocks2001suprathreshold,
  title={Suprathreshold stochastic resonance: an exact result for uniformly distributed signal and noise},
  author={Stocks, NG},
  journal={Physics Letters A},
  volume={279},
  number={5-6},
  pages={308--312},
  year={2001},
  publisher={Elsevier}
}
@article{nowak1997influence,
  title={Influence of low and high frequency inputs on spike timing in visual cortical neurons.},
  author={Nowak, Lionel G and Sanchez-Vives, Maria V and McCormick, David A},
  journal={Cerebral cortex (New York, NY: 1991)},
  volume={7},
  number={6},
  pages={487--501},
  year={1997}
}
@article{mainen1995reliability,
  title={Reliability of spike timing in neocortical neurons},
  author={Mainen, Zachary F and Sejnowski, Terrence J},
  journal={Science},
  volume={268},
  number={5216},
  pages={1503--1506},
  year={1995},
  publisher={American Association for the Advancement of Science}
}
@article{mcdonnell2002characterization,
  title={A characterization of suprathreshold stochastic resonance in an array of comparators by correlation coefficient},
  author={Mcdonnell, Mark D and Abbott, Derek and Pearce, Charles EM},
  journal={Fluctuation and Noise Letters},
  volume={2},
  number={03},
  pages={L205--L220},
  year={2002},
  publisher={World Scientific}
}
@article{bulsara1996threshold,
  title={Threshold detection of wideband signals: A noise-induced maximum in the mutual information},
  author={Bulsara, Adi R and Zador, Anthony},
  journal={Physical Review E},
  volume={54},
  number={3},
  pages={R2185},
  year={1996},
  publisher={APS}
}

@article{Sadeghi2007,
author = {Sadeghi, Soroush G and Chacron, Maurice J and Taylor, Michael C and Cullen, Kathleen E},
doi = {10.1523/JNEUROSCI.4690-06.2007},
file = {:home/huben/Downloads/31{\_}sadeghi{\_}chacron{\_}taylor{\_}cullen{\_}2007.pdf:pdf},
keywords = {detection threshold,heterogeneity,information theory,regular afferents,spike timing,vestibular afferents},
number = {4},
pages = {771--781},
title = {{Neural Variability, Detection Thresholds, and Information Transmission in the Vestibular System}},
journal = {Journal of Neuroscience,},
volume = {27},
year = {2007}
}
@article{hoch2003optimal,
  title={Optimal noise-aided signal transmission through populations of neurons},
  author={Hoch, Thomas and Wenning, Gregor and Obermayer, Klaus},
  journal={Physical Review E},
  volume={68},
  number={1},
  pages={011911},
  year={2003},
  publisher={APS}
}

@article{mcdonnell2006optimal,
  title={Optimal information transmission in nonlinear arrays through suprathreshold stochastic resonance},
  author={McDonnell, Mark D and Stocks, Nigel G and Pearce, Charles EM and Abbott, Derek},
  journal={Physics Letters A},
  volume={352},
  number={3},
  pages={183--189},
  year={2006},
  publisher={Elsevier}
}

@article{mcdonnell2007optimal,
  title={Optimal stimulus and noise distributions for information transmission via suprathreshold stochastic resonance},
  author={McDonnell, Mark D and Stocks, Nigel G and Abbott, Derek},
  journal={Physical Review E},
  volume={75},
  number={6},
  pages={061105},
  year={2007},
  publisher={APS}
}

@article{Borst1999,
author = {Borst, Alexander},
file = {:home/huben/Downloads/nn1199{\_}947.pdf:pdf},
pages = {13--16},
title = {{Information theory and neural coding}},
year = {1999}
}
@book{Walz2016,
author = {Walz, Henriette and Maler, Leonard and Longtin, Andre and Benda, Jan},
file = {:home/huben/Downloads/punitModel.pdf:pdf},
isbn = {2154253113},
title = {{A simple neuron model of spike generation accurately describes frequency tuning of an electroreceptor population.}},
year = {2016}
}
@article{Stocks2000,
  title={Suprathreshold stochastic resonance in multilevel threshold systems},
  author={Stocks, NG},
  journal={Physical Review Letters},
  volume={84},
  number={11},
  pages={2310},
  year={2000},
  publisher={APS}
}
@article{Strong1998,
author = {Strong, S P and Koberle, Roland and Bialek, William},
file = {:home/huben/Desktop/PhysRevLett.80.197.pdf:pdf},
pages = {197--200},
title = {{Entropy and Information in Neural Spike Trains}},
year = {1998}
}
@article{deweese1995information,
  title={Information flow in sensory neurons},
  author={DeWeese, M and Bialek, W},
  journal={Il Nuovo Cimento D},
  volume={17},
  number={7-8},
  pages={733--741},
  year={1995},
  publisher={Springer}
}
@article{bialek1993bits,
  title={Bits and brains: Information flow in the nervous system},
  author={Bialek, William and DeWeese, Michael and Rieke, Fred and Warland, David},
  journal={Physica A: Statistical Mechanics and its Applications},
  volume={200},
  number={1-4},
  pages={581--593},
  year={1993},
  publisher={Elsevier}
}

@article{wiesenfeld1995stochastic,
  title={Stochastic resonance and the benefits of noise: from ice ages to crayfish and SQUIDs},
  author={Wiesenfeld, Kurt and Moss, Frank},
  journal={Nature},
  volume={373},
  number={6509},
  pages={33},
  year={1995},
  publisher={Nature Publishing Group}
}

@article{Chapeau-blondeau1996,
author = {Chapeau-blondeau, Franqois and Godivier, Xavier and Chambet, Nicolas},
file = {:home/huben/Desktop/PhysRevE.53.1273.pdf:pdf},
number = {1},
pages = {3--5},
title = {s(t)=+„5(t},
volume = {53},
year = {1996}
}
@article{Lindner2002,
author = {Lindner, Benjamin and Schimansky-geier, Lutz},
doi = {10.1103/PhysRevE.66.031916},
file = {:home/huben/Desktop/PhysRevE.66.031916.pdf:pdf},
pages = {1--6},
title = {{Maximizing spike train coherence or incoherence in the leaky integrate-and-fire model}},
year = {2002}
}

@article{Farkhooi2009,
author = {Farkhooi, Farzad and Strube-Bloss, Martin F and Nawrot, Martin P},
journal = {Physical Review E},
month = {feb},
number = {2},
pages = {21905},
publisher = {American Physical Society},
title = {{Serial correlation in neural spike trains: Experimental evidence, stochastic modeling, and single neuron variability}},
url = {http://link.aps.org/doi/10.1103/PhysRevE.79.021905},
volume = {79},
year = {2009}
}
@article{Mileva2016,
author = {Mileva, G R and Kozak, I J and Lewis, J E},
doi = {10.1016/j.neuroscience.2016.01.014},
file = {:home/huben/Desktop/1-s2.0-S0306452216000336-main.pdf:pdf},
issn = {0306-4522},
journal = {NEUROSCIENCE},
keywords = {facilitation,synaptic depression,weakly electric},
pages = {1--11},
publisher = {IBRO},
title = {{Short-term synaptic plasticity across topographic maps in the electrosensory system}},
url = {http://dx.doi.org/10.1016/j.neuroscience.2016.01.014},
volume = {318},
year = {2016}
}
@article{Maler2009,
abstract = {The electric fish Apteronotus leptorhynchus emits a high-frequency electric organ discharge (EOD) sensed by specialized electroreceptors (P-units) distributed across the fish's skin. Objects such as prey increase the amplitude of the EOD over the underlying skin and thus cause an increase in P-unit discharge. The resulting localized intensity increase is called the electric image and is detected by its effect on the P-unit population; the electric image peak value and the extent to its spreads are cues utilized by these fish to estimate the location and size of its prey. P-units project topographically to three topographic maps in the electrosensory lateral line lobe (ELL): centromedial (CMS), centrolateral (CLS), and lateral (LS) segments. In a companion paper I have calculated the receptive fields (RFs) in these maps: RFs were small in CMS and very large in LS, with intermediate values in CLS. Here I use physiological data to create a simple model of the RF structure within the three ELL maps and to compute the response of these model maps to simulated prey. The Fisher information (FI) method was used to compute the optimal estimates possible for prey localization across the three maps. The FI predictions were compared with behavioral studies on prey detection. These comparisons were used to frame alternative hypotheses on the functions of the three maps and on the constraints that RF size and synaptic strength impose on weak signal detection and estimation.},
author = {Maler, Leonard},
doi = {10.1002/cne.22120},
file = {:home/huben/Desktop/Maler2009a-2.pdf:pdf},
issn = {00219967},
journal = {Journal of Comparative Neurology},
keywords = {Electric fish,Electrosensory lateral line lobe,Fisher information,Receptive field,Stimulus estimation,Topographic maps},
number = {5},
pages = {394--422},
pmid = {19655388},
title = {{Receptive field organization across multiple electrosensory maps. II. Computational analysis of the effects of receptive field size on prey localization}},
volume = {516},
year = {2009}
}
@article{Cumming2007,
abstract = {Error bars commonly appear in figures in publications, but experimental biologists are often unsure how they should be used and interpreted. In this article we illustrate some basic features of error bars and explain how they can help communicate data and assist correct interpretation. Error bars may show confidence intervals, standard errors, standard deviations, or other quantities. Different types of error bars give quite different information, and so figure legends must make clear what error bars represent. We suggest eight simple rules to assist with effective use and interpretation of error bars.},
archivePrefix = {arXiv},
arxivId = {Error bars in experimental biology},
author = {Cumming, G. and Fidler, F. and Vaux, D.L.},
doi = {10.1083/jcb.200611141},
eprint = {Error bars in experimental biology},
isbn = {0021-9525 (Print)},
issn = {0021-9525},
journal = {The Journal of Cell Biology},
number = {1},
pages = {7--11},
pmid = {17420288},
title = {{Error bars in experimental biology}},
url = {http://www.jcb.org/cgi/doi/10.1083/jcb.200611141},
volume = {177},
year = {2007}
}
