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Great brain discoveries: when white spots disappear?
Nuclear Instruments and Methods in Physics Research A 502 (2003) 369–371
Great brain discoveries: when white spots disappear? W.L. Dunin-Barkowskia,b,* b
a Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia A.B. Kogan Research Institute for Neurocybernetics, Rostov State University, Rostov-on-Don, Russia
Abstract Knowledge progress about a particular object (e.g., brain) has characteristics of exponential growth in a limited volume. As soon as you know that a visible part of the whole volume is filled (1/2, 1/10, 1/1000 or 1/10 000—does not matter), the time for the whole volume to be filled has almost come. The time scale is in units of a total duration of the process of the filling in the limited volume, if you have started from zero level. We did not know how much we were ignorant about the brain even decade ago. The whole brain was just Terra Incognito. But recent progress in experimental and computational neuroscience shows that presently we know about 1/10 (and not less than 1/100 000) of all brain network mechanisms. That is why we can say that we are dealing with white spots on the map of knowledge about the brain and not with the Terra Incognito any more. The time for full understanding of the brain varies from 7 to 91 years estimated by different methods. A couple of well understood mechanisms of brain functioning (work of synchronous/asynchronous neuron ensembles in cortex, cerebellar data prediction machinery, etc.) exemplify recent progress in this field. r 2003 Elsevier Science B.V. All rights reserved. PACS: 87.18.Sn; 87.19.La; 87.80.Xa Keywords: Brain; Neurophysiology; Neuromechanics
Progress in time of a knowledge about a particular limited object, e.g. brain, has characteristics of an exponential growth in a limited volume. As soon as you know that visible part of the volume is filled (say, 1/2, 1/10, or even 1/ 1000—it does not matter) the time for the whole volume to be filled is measured by few time constants. In the 40 years of my life in neuroscience the situation has dramatically changed. *Corresponding author. Department of Physiology, Texas Tech University, Health Sciences Centre, 3601 4th Street STOP 6551, Lubbock, TX 79415-6551, USA. Tel.:+1-806-743-2522; fax:+1-806-743-1512. E-mail address: [email protected] (W.L. Dunin-Barkowski).
In the early 1960s, we did not know how much we are ignorant about the brain. The recent results in experimental and computational neuroscience show that presently, we know about 1/10 (and definitely not less than 1/100 000) of all brain mechanisms (see below). To estimate the half/ volume growth time constant any reliable physical parameter of the world neuroscience research can be used. Take, for example, the number of attendees of the world’s largest annual conference on neuroscience—The Annual Meetings of the Society for Neuroscience. The 2002 Meeting was held in Orlando, FL and has been attended by more than 25 000 participants. The attendance numbers for the previous 31 years (1971–2001)
0168-9002/03/$ - see front matter r 2003 Elsevier Science B.V. All rights reserved. doi:10.1016/S0168-9002(03)00445-5
370
W.L. Dunin-Barkowski / Nuclear Instruments and Methods in Physics Research A 502 (2003) 369–371
were: 1396, 1229, 2436, 2410, 4135, 4303, 4586, 4968, 5932, 5820, 6003, 6270, 9501, 8043, 8454, 12 000, 11 806, 13 385, 13 767, 13 626, 16 447, 17 271, 18 284, 22 243, 23 052, 25 062, 25 755, 24 038, 24 264, 25 849, 28 774 [1]. From these data, we estimate T1=2 ¼ 6:9 years. It yields the estimate for the ‘‘time to complete brain understanding’’ as 23–91 years, depending on how optimistic we evaluate the present state of affairs in this field. When I presented an abstract of my ACAT’2002 talk, I believed that the optimistic time for the ‘‘white spots disappearance’’ will be about 5 years, and the real figure (which I calculated later) was a bitter disappointment for me. Nevertheless at present young people have a good chance to live in times when a complete knowledge of brain mechanisms is available. This is an answer to the title of my talk and thus the work is done. It should be noted, however, that understanding the brain mechanisms is not the highest priority of the modern science. If it is given the highest priority, the time constant might decrease by a factor of 3–5. So, 7–30 years might be the total time for brain understanding, provided the society decisively turn its attention onto (into) the brain. I also list here arguments why I believe that we understand up to 1/10 (and more than 1/100 000) of the brain. The statements without references refer to any good modern textbook (e.g. Ref. [2]). Now we know much about brain which seemed to be a great mystery even recently: 1. The Human Genome project is (more or less) completed. Of course, this is not an achievement of the neuroscience, however moleculargenetic mechanisms underly all physiological processes, including neurophysiology. Due to this knowledge we understand the degree of diversity of molecular mechanisms, involved in the brain functioning. 2. More concretely, we know about a half (and may be more) of all molecular (bio-electrochemical) mechanisms of excitation generation and propagation in the neurons. We know several molecular-structural links between momentarily excitation-related neural processes and prolonged and/or permanent changes in properties of neural elements.
3. We know much about elementary memory and learning processes in hippocampus, brain hemisphere cortex and cerebellum. The well-established classical experimental and infrastructure schemes of conditioned reflexes are supplemented with abstract theory of memorizing neural networks [3,4] and theories of particular neural structures [5]. 4. One (of a few) of the general principles of neural system operation emerges from the data on temporary synchronism of individual neuron firing in cerebral cortex [6] and examples of high efficiency of synchronicity-based functional neural networks [7] (see also one of the earliest reference to this functional property in Ref. [8]). 5. A lot is known about sensory-motor coordination and several types of rhythmic processes in the neural system. 6. The science of vision, from retinal processes to brain integration, understands now a significant share of all natural vision mechanisms from cellular to the systemic level [9]. 7. After 30 years of experimental research inspired by theoretical insights [3,5] we know a principal scheme of operations in the cerebellum [10–13], which represents 10% of the whole brain. This list (as well as the appended references) is more subjective than generally acknowledged; it might not be exhaustive also. It serves only to demonstrate that our quantitative estimate of the share of the known processes in the brain has an adequate basis.
References [1] http://apu.sfn.org/content/Meetings Events/FutureandPastAnnualMeetings/AnnualMeetingStatistics/amstats.html [2] G.M. Shepherd (Ed.), The Synaptic Organization of the Brain, 4th Edition, Oxford University Press, New York, 1998. [3] G. Brindley, Proc. R. Soc. B 174 (1969) 193. [4] J.J. Hopfield, Proc. Natl. Acad. Sci. 79 (1982) 2554. [5] L. Vaina (Ed.), From Retina to the Neocortex. Selected Papers by David Marr, Birkhauser, Boston, 1991. [6] W. Singer, C.M. Gray, Annu. Rev. Neurosci. 18 (1995) 555.
W.L. Dunin-Barkowski / Nuclear Instruments and Methods in Physics Research A 502 (2003) 369–371 [7] J.J. Hopfield, C.D. Brody, Proc. Natl. Acad. Sci. 97 (2000) 13919; J.J. Hopfield, C.D. Brody, Proc. Natl. Acad. Sci. 98 (2001) 1282. [8] W.L. Dunin-Barkowski, Biofizika 16 (1971) 698. [9] D.C. Marr, Vision, Freeman, New York, 1982.
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[10] M. Mauk, N.H. Donegan, Learning and Memory 3 (1997) 130. [11] J. Spoelstra, N. Schweighopher, M. Arbib, Biol. Cybern. 82, 321. [12] M. Ito, Physiol. Rev. 81 (2001) 1143. [13] W.L. Dunin-Barkowski, Neurocomputing 44–46 (2002) 391.
Great brain discoveries: when white spots disappear? W.L. Dunin-Barkowskia,b,* b
a Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia A.B. Kogan Research Institute for Neurocybernetics, Rostov State University, Rostov-on-Don, Russia
Abstract Knowledge progress about a particular object (e.g., brain) has characteristics of exponential growth in a limited volume. As soon as you know that a visible part of the whole volume is filled (1/2, 1/10, 1/1000 or 1/10 000—does not matter), the time for the whole volume to be filled has almost come. The time scale is in units of a total duration of the process of the filling in the limited volume, if you have started from zero level. We did not know how much we were ignorant about the brain even decade ago. The whole brain was just Terra Incognito. But recent progress in experimental and computational neuroscience shows that presently we know about 1/10 (and not less than 1/100 000) of all brain network mechanisms. That is why we can say that we are dealing with white spots on the map of knowledge about the brain and not with the Terra Incognito any more. The time for full understanding of the brain varies from 7 to 91 years estimated by different methods. A couple of well understood mechanisms of brain functioning (work of synchronous/asynchronous neuron ensembles in cortex, cerebellar data prediction machinery, etc.) exemplify recent progress in this field. r 2003 Elsevier Science B.V. All rights reserved. PACS: 87.18.Sn; 87.19.La; 87.80.Xa Keywords: Brain; Neurophysiology; Neuromechanics
Progress in time of a knowledge about a particular limited object, e.g. brain, has characteristics of an exponential growth in a limited volume. As soon as you know that visible part of the volume is filled (say, 1/2, 1/10, or even 1/ 1000—it does not matter) the time for the whole volume to be filled is measured by few time constants. In the 40 years of my life in neuroscience the situation has dramatically changed. *Corresponding author. Department of Physiology, Texas Tech University, Health Sciences Centre, 3601 4th Street STOP 6551, Lubbock, TX 79415-6551, USA. Tel.:+1-806-743-2522; fax:+1-806-743-1512. E-mail address: [email protected] (W.L. Dunin-Barkowski).
In the early 1960s, we did not know how much we are ignorant about the brain. The recent results in experimental and computational neuroscience show that presently, we know about 1/10 (and definitely not less than 1/100 000) of all brain mechanisms (see below). To estimate the half/ volume growth time constant any reliable physical parameter of the world neuroscience research can be used. Take, for example, the number of attendees of the world’s largest annual conference on neuroscience—The Annual Meetings of the Society for Neuroscience. The 2002 Meeting was held in Orlando, FL and has been attended by more than 25 000 participants. The attendance numbers for the previous 31 years (1971–2001)
0168-9002/03/$ - see front matter r 2003 Elsevier Science B.V. All rights reserved. doi:10.1016/S0168-9002(03)00445-5
370
W.L. Dunin-Barkowski / Nuclear Instruments and Methods in Physics Research A 502 (2003) 369–371
were: 1396, 1229, 2436, 2410, 4135, 4303, 4586, 4968, 5932, 5820, 6003, 6270, 9501, 8043, 8454, 12 000, 11 806, 13 385, 13 767, 13 626, 16 447, 17 271, 18 284, 22 243, 23 052, 25 062, 25 755, 24 038, 24 264, 25 849, 28 774 [1]. From these data, we estimate T1=2 ¼ 6:9 years. It yields the estimate for the ‘‘time to complete brain understanding’’ as 23–91 years, depending on how optimistic we evaluate the present state of affairs in this field. When I presented an abstract of my ACAT’2002 talk, I believed that the optimistic time for the ‘‘white spots disappearance’’ will be about 5 years, and the real figure (which I calculated later) was a bitter disappointment for me. Nevertheless at present young people have a good chance to live in times when a complete knowledge of brain mechanisms is available. This is an answer to the title of my talk and thus the work is done. It should be noted, however, that understanding the brain mechanisms is not the highest priority of the modern science. If it is given the highest priority, the time constant might decrease by a factor of 3–5. So, 7–30 years might be the total time for brain understanding, provided the society decisively turn its attention onto (into) the brain. I also list here arguments why I believe that we understand up to 1/10 (and more than 1/100 000) of the brain. The statements without references refer to any good modern textbook (e.g. Ref. [2]). Now we know much about brain which seemed to be a great mystery even recently: 1. The Human Genome project is (more or less) completed. Of course, this is not an achievement of the neuroscience, however moleculargenetic mechanisms underly all physiological processes, including neurophysiology. Due to this knowledge we understand the degree of diversity of molecular mechanisms, involved in the brain functioning. 2. More concretely, we know about a half (and may be more) of all molecular (bio-electrochemical) mechanisms of excitation generation and propagation in the neurons. We know several molecular-structural links between momentarily excitation-related neural processes and prolonged and/or permanent changes in properties of neural elements.
3. We know much about elementary memory and learning processes in hippocampus, brain hemisphere cortex and cerebellum. The well-established classical experimental and infrastructure schemes of conditioned reflexes are supplemented with abstract theory of memorizing neural networks [3,4] and theories of particular neural structures [5]. 4. One (of a few) of the general principles of neural system operation emerges from the data on temporary synchronism of individual neuron firing in cerebral cortex [6] and examples of high efficiency of synchronicity-based functional neural networks [7] (see also one of the earliest reference to this functional property in Ref. [8]). 5. A lot is known about sensory-motor coordination and several types of rhythmic processes in the neural system. 6. The science of vision, from retinal processes to brain integration, understands now a significant share of all natural vision mechanisms from cellular to the systemic level [9]. 7. After 30 years of experimental research inspired by theoretical insights [3,5] we know a principal scheme of operations in the cerebellum [10–13], which represents 10% of the whole brain. This list (as well as the appended references) is more subjective than generally acknowledged; it might not be exhaustive also. It serves only to demonstrate that our quantitative estimate of the share of the known processes in the brain has an adequate basis.
References [1] http://apu.sfn.org/content/Meetings Events/FutureandPastAnnualMeetings/AnnualMeetingStatistics/amstats.html [2] G.M. Shepherd (Ed.), The Synaptic Organization of the Brain, 4th Edition, Oxford University Press, New York, 1998. [3] G. Brindley, Proc. R. Soc. B 174 (1969) 193. [4] J.J. Hopfield, Proc. Natl. Acad. Sci. 79 (1982) 2554. [5] L. Vaina (Ed.), From Retina to the Neocortex. Selected Papers by David Marr, Birkhauser, Boston, 1991. [6] W. Singer, C.M. Gray, Annu. Rev. Neurosci. 18 (1995) 555.
W.L. Dunin-Barkowski / Nuclear Instruments and Methods in Physics Research A 502 (2003) 369–371 [7] J.J. Hopfield, C.D. Brody, Proc. Natl. Acad. Sci. 97 (2000) 13919; J.J. Hopfield, C.D. Brody, Proc. Natl. Acad. Sci. 98 (2001) 1282. [8] W.L. Dunin-Barkowski, Biofizika 16 (1971) 698. [9] D.C. Marr, Vision, Freeman, New York, 1982.
371
[10] M. Mauk, N.H. Donegan, Learning and Memory 3 (1997) 130. [11] J. Spoelstra, N. Schweighopher, M. Arbib, Biol. Cybern. 82, 321. [12] M. Ito, Physiol. Rev. 81 (2001) 1143. [13] W.L. Dunin-Barkowski, Neurocomputing 44–46 (2002) 391.