E-mail: [email protected]
ACAT’2002, Moscow, Russia, June 24-28, 2002
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
Knowledge:
Finite or Infinite =
= Universe:
http://www.physiology.ttuhsc.edu/wldb/Witali/Witali.htm
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 thejar will be filled with the microbes.Q.: How much time it would take to fill 1/2 ofthe 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
0
10000
20000
30000
40000
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
T1/2 = 6.9 years
Topt = 23 years
Tpsm = 91 years
Society for Neuroscience Annual MeetingsNumber of Attendees (1970 - 2001)
Neural Mechanics:
The First Two Uncovered Mechanisms
1. Sensory Cortex
2. The Cerebellum
http://www.physiology.ttuhsc.edu/wldb
New Hopfield's Paradigm in Computational Neuroscience
1. J.J. Hopfield, C.D. BrodyProc. Nat. Acad. Sci., Vol. 97, No. 25, pp. 13919-13924, Dec., 2000.
2. J.J. Hopfield, C.D. BrodyProc. Nat. Acad. Sci., Vol. 98, No. 3, pp. 1282-1287, Jan., 2001.
Understanding the Brain: Role of John Hopfield
In 1982-1984 he has discovered NEUROMAGNETICS
Hopfield’s paper animal (HPA)
HPA
HPA: Mechanisms
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
HPA: experimental verification
Hopfield & Brody, 2001,Fig. 9
THE CEREBELLUM: 10 % OF THE BRAIN MASS
You CAN live without cerebellum
http://www.physiology.ttuhsc.edu/wldb
DETAILS ONLY:
90 % OF BRAIN NEURONS ? % OF UNIQUE BRAIN
FUNCTIONS
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Mauk’s Equations (esp. (2) and (4))
Total synaptic inflow to climbing fiber cell (1), synaptic inflowfrom extra-cerebellar sources (2), and climbing fiber cell impulses (3) in a transient state of (left) and in the steadystate (right).
Density of climbing fiber cellfiring vs. phase of template signal(1) - transient, (2) - steady states.
How equalization works
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
Poincare plot of sequential intervals between CFC impulses
Intervals between CFC impulses vs. impulse order number
1 1001
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HEP-TYPE EXPERIMENT IN NEUROPHYSIOLOGYDunin-Barkowski, Markin, Podladchikova, Wunsch, 1999
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. PacemakerMechanisms.
Intraneuronal Mechanisms and MuscleContraction: Ryanodine Receptors
Ca-dependent Ca release. Contraction demands large amounts of Ca.To make the process independent of extracellular Ca concentrations it is releasedfrom intracellular cisterns.
A fast mediator is needed to transfer eventsat 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 canprovide 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
We should also keep searching for new components andtheir 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:
Understanding the Brain: Operational Tools
We know a lot about the components
23 y. < Tfin < 91 y.