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E-mail: witali.duninbarkowski@ttuhsc.edu. Great Brain Discoveries: When White Spots Disappear?. Witali L. Dunin-Barkowski, Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia Department of Physiology, TTU Health Sciences Center, Lubbock, Texas, USA.
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E-mail: witali.duninbarkowski@ttuhsc.edu Great Brain Discoveries: When White Spots Disappear? Witali L. Dunin-Barkowski, Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia Department of Physiology, TTU Health Sciences Center, Lubbock, Texas, USA ACAT’2002, Moscow, Russia, June 24-28, 2002
http://www.physiology.ttuhsc.edu/wldb/Witali/Witali.htm ? ? Knowledge: Finite or Infinite = = Universe: Open or Closed Understanding Brain: Fascinating but Finite Problem The best known precedent: Walking Simpler Problem: Flying
Exponential Growth in a Limited Space Microbes in a Jar Task formulation: A microbe divides in two in a second (Tm=1 s). At the start of experiment (T(0)=0) there is one microbe in the 3 liter jar. In Tf=24 hours the jar will be filled with the microbes. Q.: How much time it would take to fill 1/2 of the jar? 1/1000 of the jar? A.: T(J/2)=24 hrs- 1 s; T(J/1000)=24hrs-10 s
Understanding Brain: Finding a Time Constant Society for Neuroscience Annual Meetings Number of Attendees (1970 - 2001)
http://www.physiology.ttuhsc.edu/wldb Neural Mechanics: The First Two Uncovered Mechanisms 1. Sensory Cortex 2. The Cerebellum
Understanding the Brain: Role of John Hopfield In 1982-1984 he has discovered NEUROMAGNETICS New Hopfield's Paradigm in Computational Neuroscience 1. J.J. Hopfield, C.D. Brody Proc. Nat. Acad. Sci., Vol. 97, No. 25, pp. 13919-13924, Dec., 2000. 2. J.J. Hopfield, C.D. Brody Proc. Nat. Acad. Sci., Vol. 98, No. 3, pp. 1282-1287, Jan., 2001.
HPA: experimental verification Hopfield & Brody, 2001, Fig. 9 Dunin-Barkowski W.L., Lovering A.T., Orem J.M., Vidruk E.T., Sirota M.G., Beloozerova I.N. Submitted to Computational Neuroscience Meeting, Chicago, July, 2002
http://www.physiology.ttuhsc.edu/wldb THE CEREBELLUM: 10 % OF THE BRAIN MASS 90 % OF BRAIN NEURONS ? % OF UNIQUE BRAIN FUNCTIONS DETAILS ONLY: You CAN live without cerebellum
Mauk’s Equations (esp. (2) and (4)) (1) (2) (2`) (3) (4)
How equalization works Total synaptic inflow to climbing fiber cell (1), synaptic inflow from extra-cerebellar sources (2), and climbing fiber cell impulses (3) in a transient state of (left) and in the steady state (right). Density of climbing fiber cell firing vs. phase of template signal (1) - transient, (2) - steady states. Equalization is unstable when plasticity depends on ionotropics 1 and 2 as above; climbing fiber cell impulses are not shown: they are highly correlated with the phase of template signal all time. Red bar denotes short period of “attempted” equalization.
“Intracellular” record of the membrane potential of the model climbing fiber cell
Minimal model: Mutual inhibition with accommodation Accommodation: hot topic [Hopfield & Brody, 2001] Respiratory Pattern Generator - is a first example of a physiological system, where the tentative physiological role of accommodation as a time-scale factor was first proposed [Reiss, 1964]. Underlying mechanisms: Ca++-dependent potassium conductance (proposed for RPG in [Rybak, Payton & Schwaber, 1997])
Respiratory Rhythms: Network vs. Pacemaker Mechanisms.
Intraneuronal Mechanisms and Muscle Contraction: Ryanodine Receptors Ca-dependent Ca release. Contraction demands large amounts of Ca. To make the process independent of extracellular Ca concentrations it is released from intracellular cisterns. A fast mediator is needed to transfer events at the membrane inside the cell. The most convenient substance - Ca. Just as a signal, not as a catalyzing substance.
Ca-dependent K-channels: accommodation. Release of Ca from intracellular compartments produces cell inhibition. Three factors: (1) external excitation; (2) Ca-dependent K-channels; and (3) Ca- dependent Ca release acting in concert can provide both conditional pacemakers and flip-flop oscillations. Network mode of operation depends on a single parameter: strength of inhibitory connections between opposing neuron pools.
Model 1 Model 2 In Vivo Dunin-Barkowski W.L., Escobar A. L., Lovering A.T., Orem J.M., Submitted to Soc. for Neuroscience Annual Meeting, Orlando, Florida, November, 2002
Model 1 Model 2 Dunin-Barkowski W.L., Escobar A. L., Lovering A.T., Orem J.M., Submitted to Soc. for Neuroscience Annual Meeting, Orlando, Florida, November, 2002
Understanding the Brain: Operational Tools We know a lot about the components We should also keep searching for new components and their combinations The work is demanding and rewarding: We reveal ourselves. The final results are soon to come. Although, may be not so soon, as one could hope: