# Reaction Time Improvements by Neural Bistability

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## Abstract

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## 1. Introduction

## 2. Sensorimotor Tasks Induce Reaction Delays

## 3. Materials and Methods

#### 3.1. Participants of the Experiment

#### 3.2. Measurements

#### 3.3. Computational Equipment

## 4. Results

#### 4.1. Models with at Least Two Stable States Depict Learning

#### 4.2. Complimentary Work

#### 4.3. The FitzHugh-Nagumo (FHN) Model

#### 4.4. Results of the Experiments

## 5. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Ethics Approval

## Conflicts of Interest

## Appendix A

## References

- Abernethy, B. Training the Visual-Perceptual Skills of Athletes: Insights From the Study of Motor Expertise. Am. J. Sports Med.
**1996**, 24, 89–92. [Google Scholar] [CrossRef] - Burris, K.; Vittetoe, K.; Ramger, B.; Suresh, S.; Tokdar, S.T.; Reiter, J.P.; Appelbaum, L.G. Sensorimotor abilities predict on-field performance in professional baseball. Sci. Rep.
**2018**, 8, 1–9. [Google Scholar] - Rathelot, J.; Dum, R.P.; Strick, P.L. Posterior parietal cortex contains a command apparatus for hand movements. Proc. Natl. Acad. Sci. USA
**2017**, 114, 4255–4260. [Google Scholar] [CrossRef] - Scott, S.H. The computational and neural basis of voluntary motor control and planning. Trends Cogn. Sci.
**2012**, 16, 541–549. [Google Scholar] [CrossRef] [PubMed] - Jana, S.; Gopal, A.; Murthy, A. A Computational Framework for Understanding Eye-Hand Coordination. J. Indian Inst. Sci.
**2017**, 97, 543–554. [Google Scholar] [CrossRef] - Jana, S.; Gopal, A.; Murthy, A. Evidence of common and separate eye and hand accumulators underlying flexible eye-hand coordination. J. Neurophysiol.
**2017**, 117, 348–364. [Google Scholar] [CrossRef] [PubMed] - Gopal, A.; Jana, S.; Murthy, A. Contrasting speed accuracy trade-offs for eye and hand movements reveal the optimal nature of saccade kinematics. J. Neurophysiol.
**2017**, 118, 1664–1667. [Google Scholar] [CrossRef] [PubMed] - Weiler, J.; Gribble, P.L.; Pruszynski, J.A. Spinal stretch reflexes support efficient hand control. Nat. Neurosci.
**2019**, 1–11. [Google Scholar] [CrossRef] - Appelbaum, L.G.; Schroeder, J.E.; Cain, M.S.; Mitroff, S.R. Improved visual cognition through stroboscopic training. Front. Psychol.
**2011**, 2, 1–13. [Google Scholar] [CrossRef] - Savazzi, S.; Marzi, C.A. Speeding Up Reaction Time with Invisible Stimuli. Curr. Biol.
**2002**, 12, 403–407. [Google Scholar] [PubMed] - Curtis, C.E.; Connolly, J.D. Saccade Preparation Signals in the Human Frontal and Parietal Cortices. J. Neurophysiol.
**2007**, 99, 133–145. [Google Scholar] [CrossRef] [PubMed] - Britten, K.H.; Shadlen, M.N.; Newsome, W.T.; Movshon, J.A. The Analysis of Visual Motion: A Comparison of Neuronal and Psychophysical Performance. J. Neurosci.
**1992**, 12, 4745–4765. [Google Scholar] [CrossRef] - Smith, T.Q.; Mitroff, S.R. Stroboscopic Training Enhances Anticipatory Timing. Int. J. Exerc. Sci.
**2012**, 5, 344–353. [Google Scholar] [PubMed] - Appelbaum, L.G.; Cain, M.S.; Schroeder, J.E.; Darling, E.F.; Mitroff, S.R. Stroboscopic visual training improves information encoding in short-term memory. Atten. Percept. Psychophys.
**2012**, 74, 1681–1691. [Google Scholar] [CrossRef] - Mitroff, S.R.; Friesen, P.; Bennett, D.; Yoo, H.; Reichow, A.W. Enhancing Ice Hockey Skills Through Stroboscopic Visual Training: A Pilot Study. Athl. Train. Sport. Health Care
**2013**, 5, 261–264. [Google Scholar] [CrossRef] - Smith, P.L.; Lilburn, S.D.; Corbett, E.A.; Sewell, D.K. The attention-weighted sample-size model of visual short-term memory: Attention capture predicts resource allocation and memory load. Cogn. Psychol.
**2016**, 89, 71–105. [Google Scholar] [CrossRef] [PubMed] - Brazier, M.A.B. Studies of the EEG activity of limbic structures in man. Electroencephalogr. Clin. Neurophysiol.
**1968**, 25, 309–318. [Google Scholar] [CrossRef] - Melnik, A.; Hairston, W.D.; Ferris, D.P.; König, P. EEG correlates of sensorimotor processing: Independent components involved in sensory and motor processing. Sci. Rep.
**2017**, 7, 4461. [Google Scholar] [CrossRef] [PubMed] - Samoilenko, A.; Petryshyn, R. Multifrequency Oscillations of Nonlinear Systems; KluwerAcademic Publishers: New York, NY, USA, 2004; ISBN 1402020317. [Google Scholar]
- Schmidt, H.; Avitabile, D.; Montbrio, E.; Roxin, A. Network mechanisms underlying the role of oscillations in cognitive tasks. PLoS Comput. Biol.
**2018**, 14, e1006430. [Google Scholar] - Ahissar, M. Perceptual training: A tool for both modifying the brain and exploring it. Proc. Natl. Acad. Sci. USA
**2001**, 98, 11842–11843. [Google Scholar] [CrossRef] - Wright, B.A.; Fitzgerald, M.B. Different patterns of human discrimination learning for two interaural cues to sound-source location. Proc. Natl. Acad. Sci. USA
**2001**, 98, 12307–12312. [Google Scholar] [CrossRef] [PubMed] - Ho, H.T.; Leung, J.; Burr, D.C.; Alais, D.; Ho, H.T.; Leung, J.; Burr, D.C.; Alais, D.; Morrone, M.C. Auditory Sensitivity and Decision Criteria Oscillate at Different Frequencies Separately for the Two Ears. Curr. Biol.
**2017**, 27, 3643–3649. [Google Scholar] [CrossRef] [PubMed] - Marek, S.; Tervo-Clemmens, B.; Klein, N.; Foran, W.; Ghuman, A.S.; Luna, B. Adolescent development of cortical oscillations: Power, phase, and support of cognitive maturation. PLoS Biol.
**2018**, 16, e2004188. [Google Scholar] [CrossRef] [PubMed] - Kriegeskorte, N.; Douglas, P.K. Cognitive computational neuroscience. Nat. Neurosci.
**2018**, 21, 1148–1160. [Google Scholar] [CrossRef] - Güllich, A. International medallists’ and non-medallists’ developmental sport activities—A matched-pairs analysis. J. Sports Sci.
**2017**, 35, 2281–2288. [Google Scholar] [CrossRef] - Cecchi, G.A.; Sigman, M.; Alonso, J.-M.; Martinez, L.; Chialvo, D.R.; Magnasco, M.O. Noise in neurons is message-dependent. Proc. Natl. Acad. Sci. USA
**2000**, 97, 5557–5561. [Google Scholar] [CrossRef] - Vidoni, E.D.; McCarley, J.S.; Edwards, J.D.; Boyd, L.A. Manual and oculomotor performance develop contemporaneously but independently during continuous tracking. Exp. Brain Res.
**2009**, 195, 611–620. [Google Scholar] [CrossRef] - Dean, H.L.; Martí, D.; Tsui, E.; Rinzel, J.; Pesaran, B. Reaction Time Correlations during Eye–Hand Coordination: Behavior and Modeling. J. Neurosci.
**2011**, 31, 2399–2412. [Google Scholar] [CrossRef] [PubMed] - Haak, K.V.; Beckmann, C.F. Objective analysis of the topological organization of the human cortical visual connectome suggests three visual pathways. Cortex
**2018**, 98, 73–83. [Google Scholar] [CrossRef] [PubMed] - Ambrosio, B.; Aziz-Alaoui, M.A. Synchronization and control of coupled reaction-diffusion systems of the FitzHugh-Nagumo type. Comput. Math. Appl.
**2012**, 64, 934–943. [Google Scholar] [CrossRef] - Ebsch, C.; Rosenbaum, R. Imbalanced amplification: A mechanism of amplification and suppression from local imbalance of excitation and inhibition in cortical circuits. PLoS Comput. Biol.
**2018**, 14, e1006048. [Google Scholar] [CrossRef] - Graham, N.V. Beyond multiple pattern analyzers modeled as linear filters (as classical V1 simple cells): Useful additions of the last 25 years. Vis. Res.
**2011**, 51, 1397–1430. [Google Scholar] [CrossRef] - Alexik, M. Modelling and identification of eye-hand dynamics. Simul. Pract. Theory
**2000**, 8, 25–38. [Google Scholar] [CrossRef] - Schmidt-Hieber, C.; Nolan, M.F. Synaptic integrative mechanisms for spatial cognition. Nat. Neurosci.
**2017**, 20, 1483–1492. [Google Scholar] [CrossRef] [PubMed] - Kaminski, M.; Ding, M.; Truccolo, W.A.; Bressler, S.L. Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance. Biol. Cybern.
**2001**, 85, 145–157. [Google Scholar] [CrossRef] [PubMed] - Stefanescu, R.A.; Jirsa, V.K. A low dimensional description of globally coupled heterogeneous neural networks of excitatory and inhibitory neurons. PLoS Comput. Biol.
**2008**, 4, e1000219. [Google Scholar] [CrossRef] [PubMed] - Senk, J.; Schuecker, J.; Hagen, E.; Diesmann, M.; Helias, M. Conditions for traveling waves in spiking neural networks. arXiv, 2018; arXiv:1801.06046. [Google Scholar]
- Bastin, J.; Lebranchu, P.; Jerbi, K.; Kahane, P.; Orban, G.; Lachaux, J.; Berthoz, A. NeuroImage Direct recordings in human cortex reveal the dynamics of gamma-band [50–150 Hz] activity during pursuit eye movement control. Neuroimage
**2012**, 63, 339–347. [Google Scholar] [CrossRef] [PubMed] - Hafed, Z.M. Alteration of Visual Perception prior to Microsaccades. Neuron
**2013**, 77, 775–786. [Google Scholar] [CrossRef] - Irwin, D.E. Where does attention go when you blink? Attent. Percept. Psychophys.
**2011**, 73, 1374–1384. [Google Scholar] [CrossRef] [PubMed] - Terhune, D.B.; Sullivan, J.G.; Simola, J.M. Time dilates after spontaneous blinking. Curr. Biol.
**2016**, 26, R459–R460. [Google Scholar] [CrossRef] - Hoppe, D.; Helfmann, S.; Rothkopf, C.A. Humans quickly learn to blink strategically in response to environmental task demands. Proc. Natl. Acad. Sci. USA
**2018**, 115, 2246–2251. [Google Scholar] [CrossRef] [PubMed] - Donner, T.H.; Siegel, M.; Oostenveld, R.; Fries, P.; Bauer, M.; Engel, A.K. Population Activity in the Human Dorsal Pathway Predicts the Accuracy of Visual Motion Detection. J. Neurosci.
**2007**, 98, 345–359. [Google Scholar] [CrossRef] - Panchuk, A.; Rosin, D.P.; Hoevel, P.; Schoell, E. Synchronization of coupled neural oscillators with heterogeneous delays. Int. J. Bifurc. Chaos
**2012**, 23, 1330039. [Google Scholar] [CrossRef] - Toit, P.J.; Krüger, P.E.; Mahomed, A.F.; Kleynhans, M.; Jay-du Preez, T.; Govender, C.; Mercier, J. The effect of ports vision exercises on the visual skills of university students. Afr. J. Phys. Health Educ. Recreat. Dance
**2011**, 17, 429–440. [Google Scholar] - Clark, J.F.; Ellis, J.K.; Bench, J.; Khoury, J.; Graman, P. High-performance vision training improves batting statistics for University of Cincinnati baseball players. PLoS ONE
**2012**, 7, e29109. [Google Scholar] [CrossRef] [PubMed] - Melstrom, A.J. Effectiveness of a Low-Budget Sports Vision Training Program for Improving Statistics of an NCAA Division I Baseball Team; South Dakota State University: Brookings, SD, USA, 2018. [Google Scholar]
- Kioumourtzoglou, E.; Kourtessis, T.; Michalopoulou, M.; Derri, V. Differences in Several Perceptual Abilities between Experts and Novices in Basketball, Volleyball and Water-Polo. Percept. Mot. Skills
**1998**, 86, 899–912. [Google Scholar] [CrossRef] [PubMed] - Ghuntla, T.P.; Mehta, H.B.; Gokhale, P.A.; Shah, C.J. A comparative study of visual reaction time in basketball players and healthy controls. Indian J. Physiol. Pharmacol.
**2012**, 3, 49–51. [Google Scholar] - Ghasemi, A.; Momeni, M.; Rezaee, M.; Gholami, A. The Difference in Visual Skills Between Expert Versus Novice Soccer Referees. J. Hum. Kinet.
**2009**, 22, 15–20. [Google Scholar] [CrossRef] - Wilkins, L.; Nelson, C.; Tweddle, S. Stroboscopic Visual Training: A Pilot Study with Three Elite Youth Football Goalkeepers. J. Cogn. Enhanc.
**2017**, 2, 3–11. [Google Scholar] [CrossRef] - Ellison, P.H. Eye-Hand Coordination: An Exploration of Measurement and Different Training methods using the SVT; Edge Hill University: Ormskirk, UK, 2015. [Google Scholar]
- Du Toit, P.J.; Van Vuuren, P.J.; Le Roux, S.; Henning, E.; Kleynhans, M.; Terblanche, H.C.; Crafford, D.; Grobbelaar, C.; Wood, P.S.; Grant, C.C.; et al. The effect of sport specific exercises on the visual skills of rugby players. Conf. Proc. IEEE Int. Conf. Syst. Man Cybern.
**2012**, 6, 1158–1161. [Google Scholar] - Tseng, C.H.; Gobell, J.L.; Lu, Z.-L.L.; Sperling, G. When motion appears stopped: Stereo motion standstill. Proc. Natl. Acad. Sci. USA
**2006**, 103, 14953–14958. [Google Scholar] [CrossRef] - Appelbaum, L.G.; Lu, Y.; Khanna, R.; Detwiler, K.R. The Effects of Sports Vision Training on Sensorimotor Abilities in Collegiate Softball Athletes. Athl. Train. Sport. Health Care
**2016**, 8, 154–163. [Google Scholar] [CrossRef] - Hughes, P.K.; Bhundell, N.L.; Waken, J.M. Visual and psychomotor performance of elite, intermediate and novice table tennis competitors. Clin. Exp. Optom.
**1993**, 76, 51–60. [Google Scholar] [CrossRef] - Reschke, M.F.; Somers, J.T.; Ford, G. Stroboscopic Vision as a Treatment forMotion Sickness: Strobe Lightning vs. Shutter Glasses. Aviat. Space Environ. Med.
**2006**, 77, 2–7. [Google Scholar] [PubMed] - Berry, A.S.; Zanto, T.P.; Clapp, W.C.; Hardy, J.L.; Delahunt, P.B.; Mahncke, H.W.; Gazzaley, A. The Influence of Perceptual Training on Working Memory in Older Adults. PLoS ONE
**2010**, 5, e11537. [Google Scholar] [CrossRef] [PubMed] - Nyquist, J.B.; Lappin, J.S.; Zhang, R.; Tadin, D. Perceptual training yields rapid improvements in visually impaired youth. Sci. Rep.
**2016**, 6, 37431. [Google Scholar] [CrossRef] - Schmidt, J.T.; Buzzard, M. Activity-driven sharpening of the retinotectal projection in goldfish: Development under stroboscopic illumination prevents sharpening. J. Neurobiol.
**1993**, 24, 384–399. [Google Scholar] [CrossRef] [PubMed] - Erickson, G. Sports Vision; Butterworth-Heinemann Elsevier Ltd.: Oxford, UK, 2007; ISBN 978-7506-7577-2. [Google Scholar]
- Singhal, A.; Culham, J.C.; Chinellato, E.; Goodale, M.A. Dual-task interference is greater in delayed grasping than in visually guided grasping. J. Vis.
**2007**, 7, 1–12. [Google Scholar] [PubMed] - Vidnyanszky, Z.; Sohn, W. Learning to suppress task-irrelevant visual stimuli with attention. Vis. Res.
**2005**, 45, 677–685. [Google Scholar] [CrossRef] - Paradiso, M.A.; Meshi, D.; Pisarcik, J.; Levine, S. Eye movements reset visual perception. J. Vis.
**2012**, 12, 11. [Google Scholar] [CrossRef] [PubMed] - Appelbaum, L.G.; Erickson, G. Sports vision training: A review of the state-of-the-art in digital training techniques. Int. Rev. Sport Exerc. Psychol.
**2016**, 11, 160–189. [Google Scholar] [CrossRef] - FitzHugh, R. Impulses and physiological states in theoretical models of nerve membrane. Biophys. J.
**1961**, 1, 445–446. [Google Scholar] [CrossRef] - Nagumo, J.; Arimoto, S.; Yoshizawa, S. An active pulse transmission line simulating nerve axon. Proc. Inst. Radio Eng. IRE
**1962**, 50, 2061–2070. [Google Scholar] [CrossRef] - Dmochowski, J.P.; Norcia, A.M. Cortical Components of Reaction-Time during Perceptual Decisions in Humans. PLoS ONE
**2015**, 10, e0143339. [Google Scholar] - Marino, B.; Borghi, A.M.; Gemmi, L.; Cacciari, C.; Riggio, L. Neural Adaptation Effects in Conceptual Processing. Behav. Sci.
**2015**, 5, 353–371. [Google Scholar] [PubMed] - Mamassian, P.; Goutcher, R. Temporal dynamics in bistable perception. J. Vis.
**2005**, 5, 361–375. [Google Scholar] [CrossRef] - Noest, A.J.; van Ee, R.; Nijs, M.M.; van Wezel, R.J.A. Percept-choice sequences driven by interrupted ambiguous stimuli: A low-level neural model. J. Vis.
**2007**, 7, 10. [Google Scholar] [CrossRef] - Fürstenau, N. Computational nonlinear dynamics model of percept switching with ambiguous stimuli. In Proceedings of the Second International Conference on Digital Human Modeling, San Diego, CA, USA, 19–24 July 2009. [Google Scholar]
- Kloosterman, N.A. Brain state and changes of mind: Probing the neural bases of multi-stable perceptual dynamics. Ph.D. Thesis, University of Amsterdam, Amsterdam, The Netherlands, 2015. [Google Scholar]
- Pisarchik, A.N.; Bashkirtseva, I.A.; Ryashko, L.B. Controlling bistability in a stochastic perception model. Eur. Phys. J. Spec. Top.
**2015**, 224, 1477–1484. [Google Scholar] - Safaai, H.; Neves, R.; Eschenko, O.; Logothetis, N.K.; Panzeri, S. Modeling the effect of locus coeruleus firing on cortical state dynamics and single-trial sensory processing. Proc. Natl. Acad. Sci. USA
**2015**, 112, 12834–12839. [Google Scholar] [CrossRef] - Montbrió, E.; Pazó, D.; Roxin, A. Macroscopic description for networks of spiking neurons. Phys. Rev. X
**2015**, 5, 1–15. [Google Scholar] [CrossRef] - Jia, J.; Liu, H.; Xu, C.; Yan, F. Dynamic effects of time delay on a coupled FitzHugh-Nagumo neural system. Alexandria Eng. J.
**2015**, 54, 241–250. [Google Scholar] [CrossRef] - Hodgkin, A.L.; Huxley, A.F. A quantitative description of membrane current and its application to conduction and excitation in nerves. J. Physiol.
**1952**, 117, 500–544. [Google Scholar] [CrossRef] - Loffing, F. Left-handedness and time pressure in elite interactive ball games. Biol. Lett.
**2017**, 13, 10–13. [Google Scholar] [CrossRef] - Chen, N.; Majda, A.J. Beating the curse of dimension with accurate statistics for the Fokker–Planck equation in complex turbulent systems. Proc. Natl. Acad. Sci. USA
**2017**, 114, 12864–12869. [Google Scholar] [CrossRef] [PubMed] - Dahlem, M.A.; Hiller, G.; Panchuk, A.; Schoell, E. Dynamics of delay-coupled excitable neural systems. Int. J. Bifurc. Chaos
**2008**, 19, 745–753. [Google Scholar] [CrossRef] - Caksan, C.; Lehnert, J.; Schoell, E. Heterogeneous delays in neural networks. Eur. Phys. J. B
**2014**, 87, 54. [Google Scholar] [CrossRef] - Zhou, J.; Yu, W.; Li, X.; Small, M.; Lu, J. Identifying the Topology of a Coupled FitzHugh–Nagumo Neurobiological Network via a Pinning Mechanism. IEEE Trans. Neural Netw.
**2009**, 20, 1679–1684. [Google Scholar] [CrossRef] - Zeng, C.; Zeng, C.; Gong, A.; Nie, L. Effect of time delay in FitzHugh–Nagumo neural model with correlations between multiplicative and additive noises. Physica A
**2010**, 389, 5117–5127. [Google Scholar] [CrossRef] - Marquie, P.; Comte, J.C.; Morfu, S. Analog simulation of neural information propagation using an electrical FitzHugh – Nagumo lattice. Chaos Solitons Fractals
**2004**, 19, 27–30. [Google Scholar] [CrossRef] - FitzHugh, R. An electronic model of the nerve membrane for demonstration purposes. J. Appl. Physiol.
**1966**, 21, 305–308. [Google Scholar] [CrossRef] [PubMed] - Panchuk, A.; Dahlem, M.; Schoell, E. Regular spiking in asymmetrically delay-coupled FitzHugh-Nagumo systems. arXiv, 2009; arXiv:0911.2071. [Google Scholar]
- Yanchuk, S.; Perlikowski, P.; Popovych, O.V.; Tass, P.A. Variability of spatio-temporal patterns in non-homogeneous rings of spiking neurons. Chaos
**2011**, 21, 047511. [Google Scholar] [CrossRef] - Shepelev, I.A.; Shamshin, D.V.; Strelkova, G.I.; Vadivasova, T.E. Bifurcations of spatiotemporal structures in a medium of FitzHugh–Nagumo neurons with diffusive coupling. Chaos Solit. Fract.
**2017**, 104, 153–160. [Google Scholar] [CrossRef] - Shepelev, I.A.; Vadivasova, T.E.; Bukh, A.V.; Strelkova, G.I.; Anishchenko, V.S. New type of chimera structures in a ring of bistable FitzHugh–Nagumo oscillators with nonlocal interaction. Phys. Lett. Sect. A Gen. At. Solid State Phys.
**2017**, 381, 1398–1404. [Google Scholar] [CrossRef] - Churchland, M.M.; Yu, B.M.; Cunningham, J.P.; Sugrue, L.P.; Cohen, M.R.; Corrado, G.S.; Newsome, W.T.; Clark, A.M.; Hosseini, P.; Scott, B.B.; et al. Stimulus onset quenches neural variability: A widespread cortical phenomenon. Nat. Neurosci.
**2010**, 13, 369–378. [Google Scholar] [CrossRef] [PubMed] - Chang, J. Flipping Biological Switches: Solving for Optimal Control. Ph.D. Thesis, University of Massachesetts, Worcester, MA, USA, 2015. [Google Scholar]
- Kwon, O.-S.; Tadin, D.; Knill, D.C. Unifying account of visual motion and position perception. Proc. Natl. Acad. Sci. USA
**2015**, 112, 8142–8147. [Google Scholar] [CrossRef] - Plotnikov, S.A.; Lehnert, J.; Fradkov, A.L.; Schöll, E. Synchronization in heterogeneous FitzHugh-Nagumo networks with hierarchical architecture. Int. J. Bifurc. Chaos
**2016**, 94, 012203. [Google Scholar] [CrossRef] - Manafian, J.; Lakestani, M. New Improvement of the Expansion Methods for Solving the Generalized Fitzhugh-Nagumo Equation with Time-Dependent Coefficients. Int. J. Eng. Math.
**2015**, 2015, 107978. [Google Scholar] [CrossRef] - Singh, B.K.; Arora, G.; Singh, M.K. A numerical scheme for the generalized Burgers-Huxley equation. J. Egypt. Math. Soc.
**2016**, 24, 629–637. [Google Scholar] [CrossRef] - Chang, C.-J.; Jazayeri, M. Integration of speed and time for estimating time to contact. Proc. Natl. Acad. Sci. USA
**2018**, 115, E2879–E2887. [Google Scholar] [CrossRef] [PubMed] - Johns, M.; Crowley, K.; Chapman, R.; Tucker, A.; Hocking, C. The effect of blinks and saccadic eye movements on visual reaction times. Atten. Percept. Psychophys.
**2009**, 71, 783–788. [Google Scholar] [CrossRef] - Van Vugt, B.; Dagnino, B.; Vartak, D.; Safaai, H.; Panzeri, S.; Dehaene, S. The threshold for conscious report: Signal loss and response bias in visual and frontal cortex. Science
**2018**, 360, 537–542. [Google Scholar] [CrossRef] - Ghadirzadeh, A.; Maki, A.; Bjorkman, M. A sensorimotor approach for self-learning of hand-eye coordination. IEEE Int. Conf. Intell. Robot. Syst.
**2015**, 4969–4975. [Google Scholar] - Rao, H.M.; Khanna, R.; Zielinski, D.J.; Lu, Y.; Clements, J.M.; Potter, N.D.; Sommer, M.A.; Kopper, R. Sensorimotor Learning during a Marksmanship Task in Immersive Virtual Reality. Front. Psychol.
**2018**, 9, 58. [Google Scholar] [CrossRef] [PubMed] - Ahmed, M.T.; Khan, K.; Akbar, M.A. Study of Nonlinear Evolution Equations to Construct Traveling Wave Solutions via Modified Simple Equation Method. Phys. Rev. Res. Int.
**2013**, 3, 490–503. [Google Scholar] - Khan, K.; Akbar, M.A.; Koppelaar, H. Study of coupled nonlinear partial differential equations for finding exact analytical solutions. R. Soc. Open Sci.
**2015**, 2, 140406. [Google Scholar] [CrossRef] - Khan, K.; Koppelaar, H.; Akbar, M.A. Exact and numerical soliton solutions to nonlinear wave equations. Casp. J. Comput. Math. Eng.
**2016**, 2, 5–22. [Google Scholar] - Vasiev, B.N. Classification of patterns in excitable systems with lateral inhibition. Phys. Lett. A
**2004**, 323, 194–203. [Google Scholar] [CrossRef]

**Figure 1.**An FHN activator neuron’s initial spike splits and spreads in time. The time delays are visible by decreasingly paler black shades.

**Figure 3.**Scaled FHN Nullclines in the phase plane showing two stable points (zero-crossings of the third order Nullcline curve) and one unstable point in the origin.

**Figure 4.**Summary of the above result: Reaction Times: 60 s without delay FITLIGHT Trainer™ equipment. Sample size of 85 men and women. Baseline sample mean 0.721 s, $\sigma =\pm $0.1075, and Final mean 0.646 s with $\sigma =\pm $0.0989. P-value 0.0000914155. Result: Hypothesis of NO-Effect of training is: Rejected.

**Figure 5.**Summary of the above result. Reaction Times: 32 lamps FITLIGHT Trainer™ equipment. Sample size of 71 men and women. Baseline sample mean 0.650 s, $\sigma =\pm $ 0.1075 and Final mean 0.577 s with $\sigma =\pm $ 0.0988966. P-value 0.0000383454. Result: Hypothesis of NO-Effect of training is: Rejected.

**Figure 6.**Summary of the above results. Reaction Times: 60 s dynamic delay FITLIGHT Trainer™ equipment. Sample size of 69 men and women. Baseline sample mean 0.687 s, $\sigma =\pm $ 0.1194, and Final mean 0.614 s with $\sigma =\pm $ 0.1099. P-value 0.0000914155. Result: Hypothesis of NO-Effect of training is: Rejected. The mean outcome of the 225 Reaction Time experiments is: Reaction Time performance improvement of +10.8% against the initial intake measurement.

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**MDPI and ACS Style**

Koppelaar, H.; Kordestani Moghadam, P.; Khan, K.; Kouhkani, S.; Segers, G.; van Warmerdam, M.
Reaction Time Improvements by Neural Bistability. *Behav. Sci.* **2019**, *9*, 28.
https://doi.org/10.3390/bs9030028

**AMA Style**

Koppelaar H, Kordestani Moghadam P, Khan K, Kouhkani S, Segers G, van Warmerdam M.
Reaction Time Improvements by Neural Bistability. *Behavioral Sciences*. 2019; 9(3):28.
https://doi.org/10.3390/bs9030028

**Chicago/Turabian Style**

Koppelaar, Henk, Parastou Kordestani Moghadam, Kamruzzaman Khan, Sareh Kouhkani, Gijs Segers, and Martin van Warmerdam.
2019. "Reaction Time Improvements by Neural Bistability" *Behavioral Sciences* 9, no. 3: 28.
https://doi.org/10.3390/bs9030028