JourVND3_08MikhailovaLO

ÜìêçÄã ÇõëòÖâ çÖêÇçéâ ÑÖüíÖãúçéëíà, 2008, ÚÓÏ 58, ‹ 3, Ò. 302–308

302 çÂÈÓÍÓÏÔ¸˛ÚÂÌ˚È ËÌÚÂÙÂÈÒ (çäà) ËÎË ËÌÚÂÙÂÈÒ ÏÓÁ„ – ÍÓÏÔ¸˛ÚÂ (Brain- Com-puter-Interface, ËÎË BCI) ËÒÔÓθÁÛÂÚ ˝ÎÂÍÚ˘Â-ÒÍË Ò˄̇Î˚ ÍÓ˚ ÏÓÁ„‡ ˜ÂÎÓ‚Â͇ ‰Îfl ÛÔ‡‚ÎÂ-ÌËfl ‚̯ÌËÏË ÚÂıÌ˘ÂÒÍËÏË ÛÒÚÓÈÒÚ‚‡ÏË (ÍÓÏÔ¸˛ÚÂ‡ÏË, ÔÓÚÂÁ‡ÏË, ‰‚ËÊÛ˘ËÏËÒfl Ó·˙-ÂÍÚ‡ÏË). óËÒÎÓ ÔÛ·ÎË͇ˆËÈ ‚ ˝ÚÓÈ Ó·Î‡ÒÚË ·˚ÒÚÓ ‡ÒÚÂÚ, ıÓÚfl ¯ËÓÍÓ„Ó ‚̉ÂÌËfl Ëı ÂÁÛθڇÚÓ‚ ‚ Ô‡ÍÚËÍÛ ÔÓ͇ Ì ÔÓËÁÓ¯ÎÓ (ÒÏ. Ó·ÁÓ˚ [2, 5, 12, 15]). åÂÊ‰Û ÚÂÏ ËÒÒΉÓ-‚‡ÌËfl ˝ÎÂÍÚ˘ÂÒÍÓÈ ‡ÍÚË‚ÌÓÒÚË ÏÓÁ„‡ ‰‡˛Ú ‚ÓÁÏÓÊÌÓÒÚ¸ ‡Á‡·ÓÚ‡Ú¸

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© 2008 „. Ö. ë. åËı‡ÈÎÓ‚‡, Ç. Ä. ó˘ÂÓ‚, Ö. Ä. èÚÛ¯ÂÌÍÓ, à. Ä. ò‚Â΂ àÌÒÚËÚÛÚ ‚˚Ò¯ÂÈ ÌÂ‚ÌÓÈ ‰ÂflÚÂθÌÓÒÚË Ë ÌÂÈÓÙËÁËÓÎÓ„ËË êÄç, åÓÒÍ‚‡

e-mail: [email protected]

èÓÒÚÛÔË· ‚ ‰‡ÍˆË˛ 29.08.2007 „. èËÌflÚ‡ ‚ Ô˜‡Ú¸ 12.11.2007 „. ì 12 Á‰ÓÓ‚˚ı ‚ÁÓÒÎ˚ı ËÒÔ˚ÚÛÂÏ˚ı ËÒÒΉӂ‡ÎË ÓÒÚÓÚÛ Ì‡ÒÚÓÈÍË ÁËÚÂθÌÓ„Ó ‚ÌËχÌËfl ÔË ÓÔÓÁ̇ÌËË “ÌÂÈÓÍÓÏÔ¸˛ÚÂÌ˚Ï ËÌÚÂÙÂÈÒÓÏ” Á‡‰ÛχÌÌ˚ı ËÒÔ˚ÚÛÂÏ˚Ï ·ÛÍ‚. Ç Í‡˜ÂÒÚ‚Â ÔÓ͇Á‡ÚÂÎfl ÓÒÚÓÚ˚ ̇ÒÚÓÈÍË ÁËÚÂθÌÓ„Ó ‚ÌËχÌËfl ̇ Á̇˜ËÏÛ˛ ·ÛÍ‚Û ËÒÔÓθÁÓ‚‡ÎË ‚ÂÚË͇θ-Ì˚È Ë „ÓËÁÓÌڇθ‚ÂÚË͇θ-Ì˚È ÔÓÒÚ‡ÌÒÚ‚ÂÌ‚ÂÚË͇θ-Ì˚È „‡‰ËÂÌÚ ÔÎÓ˘‡‰Ë ÔÓ‰ ‚ÓÎÌÓÈ ê300 ÛÒ‰ÌÂÌÌÓ„Ó ÁË-ÚÂθÌÓ„Ó ‚˚Á‚‡ÌÌÓ„Ó ÔÓÚÂ̈ˇ·. é·Ì‡ÛÊÂ̇ ‚˚ÒÓ͇fl ÓÒÚÓÚ‡ ̇ÒÚÓÈÍË ÁËÁË-ÚÂθÌÓ„Ó ‚ÌËχÌËfl (¯ËË̇ ÍË‚ÓÈ Ì‡ÒÚÓÈÍË Ì‡  ÔÓÎÛ‚˚ÒÓÚ ÓÍÓÎÓ 1.6 „‡‰), ÍÓÚÓ‡fl Ì Á‡‚ËÒËÚ ÓÚ ÔÓÎÓÊÂÌËfl Á̇-˜ËÏÓÈ ·ÛÍ‚˚ ̇ χÚËˆÂ Ë Ì‰ÓÒÚÓ‚ÂÌÓ ‡Á΢‡ÂÚÒfl ‰Îfl „ÓËÁÓÌڇθÌÓ„Ó Ë ‚ÂÚË͇θÌÓ„Ó „‡‰Ë-ÂÌÚÓ‚. ÉÓËÁÓÌڇθÌ˚È „‡‰ËÂÌÚ Ó·Ì‡ÛÊËÎ ÔËÁ̇ÍË Î‡ÚÂ‡Î¸ÌÓ„Ó ÚÓÏÓÊÂÌËfl: ÒÌËÊÂÌË ÔÎÓ-˘‡‰Ë ÔÓ‰ ‚ÓÎÌÓÈ ê300 ÔË ˝ÍÒÔÓÁˈËË ÍÓÎÓÌÓÍ ·ÛÍ‚, ‡ÒÔÓÎÓÊÂÌÌ˚ı fl‰ÓÏ ÒÓ Á̇˜ËÏÓÈ ÍÓÎÓÌ-ÍÓÈ Ï‡Úˈ˚. éÒÚÓÚ‡ ̇ÒÚÓÈÍË Ó͇Á‡Î‡Ò¸ ‰ÓÒÚÓ‚ÂÌÓ Ë ÔflÏÓ Ò‚flÁ‡ÌÌÓÈ Ò ÔÎÓ˘‡‰¸˛ ‚ÓÎÌ˚ ê300. èÓÎÛ˜ÂÌÌ˚ ‰‡ÌÌ˚ ӷÒÛʉ‡˛ÚÒfl ‚ Ò‚flÁË Ò ÔÓ·ÎÂÏÓÈ ËÁ·Ë‡ÚÂθÌÓÒÚË ÁËÚÂθÌÓ„Ó ‚ÌËχÌËfl. äβ˜Â‚˚ ÒÎÓ‚‡: ÁËÚÂθÌ˚È ‚˚Á‚‡ÌÌ˚È ÔÓÚÂ̈ˇÎ, ‚ÓÎ̇ ê300, ÌÂÈÓÍÓÏÔ¸˛ÚÂÌ˚È ËÌ-ÚÂÙÂÈÒ, ÓÔÓÁ̇ÌËÂ, ·ÛÍ‚‡, ÔÓÒÚ‡ÌÒÚ‚ÂÌÌ˚È „‡‰ËÂÌÚ, ËÁ·Ë‡ÚÂθÌÓ ‚ÌËχÌËÂ, ˜ÂÎÓ‚ÂÍ.

Spatial

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E. S. Mikhailova, V. A. Chicherov, Ö. Ä. Ptushenko, I. A. Shevelev InstituteofHigherNervousActivityandNeurophysiology, RussianAcademyofSciences, Moscow,

e-mail:[email protected]

In 12 adult healthy subjects we studied Brain-Computer-Interface recognition of different intended letters by the square of P300 wave in the averaged VEP. Horizontal and vertical spatial gradient of this square was studied as well as tuning acuteness of visual attention to a significant letter. High acuteness of this tuning was found (width of the tuning curve at its half height was equal to 1.6 grad) independent of the letter position on the letter matrix. Horizontal and vertical gradient of P300 were found to be very similar, but in the half of cases the first one revealed some kind of the “lateral inhibition”: decrease of P300 square for the columns neighboring to the meaningful one. Tuning acuteness was found to be reliable and directly interrelated with P300 square. The data are discussed in relation to selectivity of the local visual attention. Key words: human, visual evoked potentials, P300 wave, Brain-Computer-Interface (BCI), recognition, letters, attention, selectivity.

ìÑä 612.821

ÙËÁËÓÎÓ„Ëfl ‚˚Ò¯ÂÈ ÌÂ‚ÌÓÈ (ÔÒËı˘ÂÒÍÓÈ) ‰ÂflÚÂθÌÓÒÚË ˜ÂÎÓ‚Â͇

ÔÓÒÚ‡ÌÒÚ‚ÂÌÌ˚È „‡‰ËÂÌÚ ‚ÓÎÌ˚ ê300 303 „‡ÏÏÌ˚ ÒËÒÚÂÏ˚, ÔÓÁ‚ÓÎfl˛˘Ë ÏÓÁ„Û ˜ÂÎÓ-‚Â͇ ÔflÏÓ ÛÔ‡‚ÎflÚ¸ ‚̯ÌËÏË ÛÒÚÓÈÒÚ‚‡-ÏË. åÂÚÓ‰˚ çäà ÓÒÌÓ‚‡Ì˚ ̇ ÍÓÏÔ¸˛ÚÂÌÓÈ ÓˆÂÌÍ ÔÓÒÚ‡ÌÒÚ‚ÂÌÌÓ-˜‡ÒÚÓÚÌÓ„Ó ‡ÒÔ‰Â-ÎÂÌËfl ‚ ÏÓÁ„ ËÚÏÓ‚ ùùÉ ÎË·Ó ı‡‡ÍÚÂËÒÚËÍ ‚˚Á‚‡ÌÌ˚ı ÔÓÚÂ̈ˇÎÓ‚ (Çè) ÔÓÒΠÔ‰‚‡Ë-ÚÂθÌÓÈ ‡‰‡ÔÚ‡ˆËË ÍÓÏÔ¸˛ÚÂÌÓÈ ÒËÒÚÂÏ˚. чÌÌ˚ ÎËÚÂ‡ÚÛ˚ ҂ˉÂÚÂθÒÚ‚Û˛Ú [1, 2, 4, 5, 8, 9, 11–13, 15], ˜ÚÓ çäà ÔÓÁ‚ÓÎflÂÚ ÛÔ‡‚ÎflÚ¸ ÍÛÒÓÓÏ Ì‡ ˝Í‡Ì ÍÓÏÔ¸˛ÚÂ‡, ‚˚·ÓÓÏ ·ÛÍ‚ ̇ ‚ËÚۇθÌÓÈ Í·‚ˇÚÛ ËÎË ‰‚ËÊÂÌË-ÂÏ ÏÓÚÓËÁÓ‚‡ÌÌÓÈ ËÌ‚‡ÎˉÌÓÈ ÍÓÎflÒÍË ·Óθ-Ì˚ÏË Ò ÔÓÚÂÂÈ ‰‚Ë„‡ÚÂθÌÓÈ ‡ÍÚË‚ÌÓÒÚË (̇-ÔËÏÂ, ÔË “lock-in” ÒË̉ÓÏÂ) [2]. Ç Ì‡¯ÂÈ Ô‰˚‰Û˘ÂÈ ‡·ÓÚ [1] ÓÔË҇̇ ÌÂÈÓÍÓÏÔ¸˛ÚÂ̇fl ÒËÒÚÂχ ‰Îfl ÔÓ·ÛÍ‚ÂÌÌÓ-„Ó Ì‡·Ó‡ ÚÂÍÒÚ‡ ‚ ‡θÌÓÏ ‚ÂÏÂÌË Ì‡ ˝Í‡Ì ÍÓÏÔ¸˛ÚÂÌÓ„Ó ‰ËÒÔÎÂfl Ò ÔÓÏÓ˘¸˛ Ï˚ÒÎÂÌ-Ì˚ı ÍÓχ̉ (“mentaltypewriter”). Ç ˝ÚÓÈ ‡·ÓÚ ·˚ÎÓ ÓÔ‰ÂÎÂÌÓ ÓÔÚËχθÌÓ Óڂ‰ÂÌË ùùÉ-Ò˄̇· ‚ ӷ·ÒÚË Pz Ë Ô‡‡ÏÂÚ˚ ÁËÚÂθÌÓÈ ÒÚËÏÛÎflˆËË, ÔÓ‚˚¯‡˛˘Ë ̇‰ÂÊÌÓÒÚ¸ ÓÔÓ-Á̇ÌËfl ·ÛÍ‚ [1]. ùÚÓÚ ÏÂÚÓ‰ ÓÒÌÓ‚‡Ì [1, 2, 4, 5, 11, 15] ̇ Ò‚ÓÈÒÚ‚‡ı ‚ÓÎÌ˚ ê300 ‚˚Á‚‡ÌÌÓ„Ó ÔÓÚÂ̈ˇ· ÏÓÁ„‡ ˜ÂÎÓ‚Â͇, ‚ÓÁÌË͇˛˘ÂÈ Ì‡ Á̇˜ËÏ˚È ÒÚËÏÛÎ, Ô‰˙fl‚ÎflÂÏ˚È ÂÊÂ, ˜ÂÏ ÌÂÁ̇˜ËÏ˚È (“oddball”-paradigm [15]).

ñÂθ˛ ̇ÒÚÓfl˘ÂÈ ‡·ÓÚ˚ ÒÚ‡ÎÓ ËÒÒΉӂ‡-ÌË ‚ÂÚË͇θÌÓ„Ó Ë „ÓËÁÓÌڇθÌÓ„Ó ÔÓ-ÒÚ‡ÌÒÚ‚ÂÌÌÓ„Ó „‡‰ËÂÌÚ‡ ÔÎÓ˘‡‰Ë ÔÓ‰ ‚ÓÎ-ÌÓÈ ê300 ‚ ÁËÚÂθÌÓÏ Çè Ë ÚÂÏ Ò‡Ï˚Ï ÓÒÚÓ-Ú˚ ÁËÚÂθÌÓ„Ó ‚ÌËχÌËfl ̇ Á̇˜ËÏÛ˛ ·ÛÍ‚Û ‚ Á‡‚ËÒËÏÓÒÚË ÓÚ Â ÔÓÎÓÊÂÌËfl ̇ ·ÛÍ‚ÂÌÌÓÈ Ï‡Úˈ çäà. åÖíéÑàäÄ àÒÔ˚ÚÛÂÏ˚Â. ꇷÓÚ‡ ‚˚ÔÓÎÌÂ̇ ‚ ˝ÍÒÔÂ-ËÏÂÌÚ‡ı Ò 12 Á‰ÓÓ‚˚ÏË ‚ÁÓÒÎ˚ÏË (‚ÓÁ‡ÒÚ 18–22 „Ó‰‡) ËÒÔ˚ÚÛÂÏ˚ÏË (11 ÏÛʘËÌ Ë Ó‰Ì‡ ÊÂÌ˘Ë̇) Ò ÌÓχθÌ˚Ï ÁÂÌËÂÏ. ÇÓ ‚ÒÂı ÒÎÛ-˜‡flı ·˚ÎÓ ÔÓÎÛ˜ÂÌÓ ˝Ú˘ÂÒÍÓ Òӄ·ÒË ËÒÔ˚-ÚÛÂÏ˚ı ̇ Ôӂ‰ÂÌË ˝ÍÒÔÂËÏÂÌÚÓ‚; Û˜‡-ÒÚË ‚ ‡·ÓÚ ÓÔ·˜Ë‚‡ÎÓÒ¸. ëÚËÏÛÎflˆËfl. àÒÔ˚ÚÛÂÏ˚ ÒˉÂÎË ‚ ÍÂÒΠ‚ Ò‚ÂÚÓËÁÓÎËÓ‚‡ÌÌÓÈ Í‡ÏÂÂ Ò ÙÓÚÓÔ˘ÂÒÍÓÈ ÙÓÌÓ‚ÓÈ ÓÒ‚Â˘ÂÌÌÓÒÚ¸˛ (6 Ò‚/Ï2_{). ç‡ÔÓÚË‚} ËÒÔ˚ÚÛÂÏÓ„Ó Ì‡ ‡ÒÒÚÓflÌËË 120 ÒÏ ÓÚ „·Á ‡Ò-ÔÓ·„‡ÎÒfl ‰ËÒÔÎÂÈ (‰Ë‡„Ó̇θÌ˚È Û„ÎÓ‚ÓÈ ‡Á-ÏÂ ·ËÌÓÍÛÎflÌÓ Ì‡·Î˛‰‡ÂÏÓ„Ó ËÁÓ·‡ÊÂÌËfl ÒÓÒÚ‡‚ÎflÎ 18.8 „‡‰). ç‡ ˜ÂÌÓÏ ÙÓÌ ˝Í‡Ì‡ ÔÓÒÚÓflÌÌÓ ˝ÍÒÔÓÌËÓ‚‡ÎË ·ÛÍ‚˚ ÛÒÒÍÓ„Ó ‡Î-Ù‡‚ËÚ‡ ‚ÏÂÒÚ ÒÓ ÒÎÛÊ·Ì˚ÏË ÒËÏ‚Ó·ÏË, ‡Ò-ÔÓ·„‡‚¯ËÂÒfl ‚ ‚ˉ ÔflÏÓÛ„ÓθÌÓÈ Ï‡Úˈ˚ ËÁ 6 × 6 Á̇ÍÓ‚ (ËÒ. 1). ä‡Ê‰‡fl ·ÛÍ‚‡ ·˚· ‚ˉ̇ ÔÓ‰ Û„ÎÓÏ ÓÚ 0.8±0.88 „‡‰ ‰Ó 1.4± ±0.88„‡‰. ëÚËÏÛÎflˆËfl Á‡Íβ˜‡Î‡Ò¸ ‚ ‰ÓÔÓÎ-ÌËÚÂθÌÓÈ ÔÓ‰Ò‚ÂÚÍ ̇ 100 ÏÒ ÚÓÈ ËÎË ËÌÓÈ ÒÚÓÍË ËÎË ÒÚÓηˆ‡ ·ÛÍ‚ ‚ ÒÎÛ˜‡ÈÌÓÏ ÔÓfl‰ÍÂ. ÇÂÓflÚÌÓÒÚ¸ ÔÓfl‚ÎÂÌËfl ͇ʉÓÈ ËÁ Á̇˜ËÏ˚ı ·ÛÍ‚ ÒÓÒÚ‡‚Îfl· 16.7%. ÑÎËÚÂθÌÓÒÚ¸ ÏÂÊÒÚË-ÏÛθÌÓ„Ó ËÌÚÂ‚‡Î‡ – 5±1 Ò. àÌÒÚÛ͈Ëfl: “ëÏÓÚËÚ ̇ ˝Í‡Ì, „‰Â ̇-ıÓ‰ËÚÒfl χÚˈ‡ ËÁ ·ÛÍ‚ ÛÒÒÍÓ„Ó ‡ÎÙ‡‚ËÚ‡. èÓ ËÌÒÚÛ͈ËË ˝ÍÒÔÂËÏÂÌÚ‡ÚÓ‡ Á‡‰ÛχÈÚ ӉÌÛ ËÁ ·ÛÍ‚. Ç˚ ‰ÓÎÊÌ˚ ÒÏÓÚÂÚ¸ ̇ ÌÂÂ Ë Ò˜ËÚ‡Ú¸ ˜ËÒÎÓ Â ÔÓ‰Ò‚ÂÚÓÍ”. ê„ËÒÚ‡ˆË˛ ùùÉ ÔÓ‚Ó‰ËÎË ÌÂÔÂ˚‚ÌÓ, ÏÓÌÓÔÓÎflÌÓ Ò 32 ˝ÎÂÍÚÓ‰Ó‚, ‡ÒÔÓÎÓÊÂÌ-Ì˚ı ÔÓ ÒËÒÚÂÏ 10–10% (ÍÓÏÔ¸˛ÚÂ̇fl ùùÉ-ÒËÒÚÂχ “Neocortex-Pro” ÙËÏ˚ “ Neuro-botics”, êÓÒÒËfl) Ò ˜‡ÒÚÓÚÓÈ Í‚‡ÌÚÓ‚‡ÌËfl Ò˄̇-· 1000 Ɉ/͇̇Î. à̉ËÙÙÂÂÌÚÌ˚Ï ·˚Î Ô‡‚˚È Û¯ÌÓÈ ˝ÎÂÍÚÓ‰. ëÓÔÓÚË‚ÎÂÌË ˝ÎÂÍ-ÚÓ‰Ó‚ Ì Ô‚˚¯‡ÎÓ 5 ÍéÏ. èÓÎÓÒÛ ÔÓÔÛÒ-͇ÌËfl ÛÒËÎËÚÂÎÂÈ Ó„‡Ì˘˂‡ÎË ÔÓÎÓÒÓÈ 0.5– 70 Ɉ. éڂ‰ÂÌËfl Fp1 Ë Fp2 ËÒÔÓθÁÓ‚‡ÎË ‰Îfl ÍÓÌÚÓÎfl „·ÁÌ˚ı ‰‚ËÊÂÌËÈ ÔÓ ˝ÎÂÍÚÓÓÍÛÎÓ-„‡ÏÏÂ.

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–1 0 1 2 3 4 1 0 –1 –2 –3 –4 êËÒ. 1. å‡Úˈ‡ ·ÛÍ‚ Ë Á̇ÍÓ‚ ÛÒÒÍÓ„Ó ‡ÎÙ‡-‚ËÚ‡, ˝ÍÒÔÓÌËÛÂχfl ËÒÔ˚ÚÛÂÏÓÏÛ. ÉÓËÁÓÌ-ڇθÌ˚Ï Ë ‚ÂÚË͇θÌ˚Ï ÔÛÌÍÚËÌ˚ÏË Ôfl-ÏÓÛ„ÓθÌË͇ÏË ÒıÂχÚ˘ÂÒÍË ÔÓ͇Á‡Ì˚ ÒÚÓ-͇ Ë ÒÚÓηˆ ÔӉ҂˜ÂÌÌ˚ı ·ÛÍ‚, ÒÓ‰Âʇ˘Ë Á‡‰ÛχÌÌÛ˛ ËÒÔ˚ÚÛÂÏ˚Ï ·ÛÍ‚Û “ä”. ñËÙ˚ Ò΂‡ ÓÚ ·ÛÍ‚ÂÌÌÓÈ Ï‡Úˈ˚ Ë ÔÓ‰ ÌÂÈ – ÔÓÎÓ-ÊÂÌË ÒÚÓÍ Ë ÒÚÓηˆÓ‚ ·ÛÍ‚ ÔÓ ÓÚÌÓ¯ÂÌ˲ Í ÒÚÓÍ‡Ï Ë ÒÚÓηˆ‡Ï, ÒÓ‰Âʇ˘ËÏ Á̇˜ËÏÛ˛ (Á‡‰ÛχÌÌÛ˛) ·ÛÍ‚Û “ä”, ÍÓÓ‰Ë̇Ú˚ ÍÓÚÓÓÈ ÔËÌflÚ˚ Í‡Í ÌÛ΂˚Â. é·˙flÒÌÂÌË ‚ ÚÂÍÒÚÂ.

Fig. 1.MatrixoflettersandsomesignsofRussian alphabet. Horizontaland vertical dottedrectangles indicate row and column with significant letter (“ä”). Numbers to the left and bottom of the matrix indicate the position of lines and columns relative to the significant letter taken as zero.

304 ÜìêçÄã ÇõëòÖâ çÖêÇçéâ ÑÖüíÖãúçéëíà      ÚÓÏ 58      ‹ 3      2008 ÏËı‡ÈÎÓ‚‡ Ë ‰. Ä̇ÎËÁ ‰‡ÌÌ˚ı. чÌÌ˚ ùùÉ Ó·‡·‡Ú˚‚‡-ÎË ‚ ÔÓ„‡Ïχı “Neocortex-Pro” Ë “BESA” (ÙËχ “MEGIS Software GmbH”, ÉÂχÌËfl). èÓÒΠÓÔ˚Ú‡ ÔË ‚ËÁۇθÌÓÏ ‡Ì‡ÎËÁ ËÒÍβ-˜‡ÎË Ù‡„ÏÂÌÚ˚ ùùÉ Ò Ï˚¯Â˜Ì˚ÏË ‡ÚÂÙ‡Í-Ú‡ÏË ËÎË Ò ˝ÎÂÍÚÓÓÍÛÎÓ„‡Ù˘ÂÒÍËÏË ÔÓÚÂÌ-ˆË‡Î‡ÏË Ò ‡ÏÔÎËÚÛ‰ÓÈ ·ÓΠ25 ÏÍÇ. ìÒ‰ÌÂ-ÌË Çè ÔÓ‚Ó‰ËÎË ÔÓ 30–35 ·ÂÁ‡ÚÂÙ‡ÍÚÌ˚Ï ÓÚÂÁÍ‡Ï ùùÉ. èÎÓ˘‡‰¸ ÔÓ‰ ‚ÓÎÌÓÈ ê300 ‚˚-˜ËÒÎflÎË Í‡Í ËÌÚ„‡Î ÓÚ ÔÓÚÂ̈ˇ· ÔÓ ‚ÂÏÂ-ÌË ‚ Ô‰Â·ı ÚÓ˜ÂÍ ÔÂÂÒ˜‚ÂÏÂ-ÌËfl ÂÂ Ò ËÁÓÎË‚ÂÏÂ-ÌË- ËÁÓÎËÌË-ÂÈ. Ç˚˜ËÒÎÂÌË ˝ÚÓÈ ÔÎÓ˘‡‰Ë ÔÓ‚Ó‰ËÎË Ò ÔÓ-ÏÓ˘¸˛ ÓË„Ë̇θÌÓÈ ÔÓ„‡ÏÏ˚, ̇ÔËÒ‡ÌÌÓÈ Ì‡ flÁ˚Í “MATLAB”. á‡ÚÂÏ ÒÚÓËÎË ÍË‚˚ Á‡‚ËÒËÏÓÒÚË ÔÎÓ˘‡‰Ë ÔÓ‰ ˝ÚÓÈ ‚ÓÎÌÓÈ ÓÚ ÔÓ-ÎÓÊÂÌËfl ·ÛÍ‚˚ ‚ ÒÚÓÍ ËÎË ÒÚÓηˆÂ. ëÚ‡ÚËÒÚ˘ÂÒÍÛ˛ Ó·‡·ÓÚÍÛ ‰‡ÌÌ˚ı ÔÓ‚Ó-‰ËÎË ÏÂÚÓ‰‡ÏË ‚‡ˇˆËÓÌÌÓÈ ÒÚ‡ÚËÒÚËÍË – ËÒ-ÔÓθÁÓ‚‡ÎË t-ÚÂÒÚ ‰Îfl Ò‚flÁ‡ÌÌ˚ı ‚˚·ÓÓÍ Ë ÍÓ˝ÙÙˈËÂÌÚ ÍÓÂÎflˆËË ÔÓ ëÔËÏÂÌÛ (ÔÓ-„‡ÏÏÌ˚È Ô‡ÍÂÚ “Statistica 6”). êÖáìãúíÄíõ àëëãÖÑéÇÄçàâ ê‡Á΢Ëfl ÔÎÓ˘‡‰Ë ‚ÓÎÌ˚ ê300 ̇ Á̇˜Ë-Ï˚Â Ë ÌÂÁ̇˜ËÁ̇˜Ë-Ï˚ ÒÚËÏÛÎ˚. ÖÒÎË ‰‡ÂÚÒfl ËÌ-ÒÚÛ͈Ëfl, ˜ÚÓ Ì‡ Ó‰ÌÛ ËÁ ·ÛÍ‚ χÚˈ˚ ÌÛÊÌÓ ‚ÌËχÚÂθÌÓ ÒÏÓÚÂÚ¸ Ë Ò˜ËÚ‡Ú¸ ˜ËÒÎÓ Â ÔÓ-fl‚ÎÂÌËÈ, ÚÓ ‚ Çè ̇ Ú‡ÍÓÈ Á̇˜ËÏ˚È, ÌÓ ÓÚÌÓ-ÒËÚÂθÌÓ ‰ÍÓ ÔӉ҂˜˂‡ÂÏ˚È ÒÚËÏÛÎ ÔÓfl‚-ÎflÂÚÒfl ·Óθ¯‡fl ÔÓÁËÚ˂̇fl ‚ÓÎ̇ Ò Î‡ÚÂÌÚÌÓ-ÒÚ¸˛ ÔË͇ ÔÓfl‰Í‡ 300 ÏÒ. ç‡ ·ÓΠ˜‡ÒÚÓ ÔӉ҂˜˂‡ÂÏ˚ ÒÚÓÍË ËÎË ÒÚÓηˆ˚ χÚË-ˆ˚, ÒÓ‰Âʇ˘Ë ÌÂÁ̇˜ËÏ˚ ·ÛÍ‚˚, ‡ÏÔÎËÚÛ-‰‡ ‚ÓÎÌ˚ ê300 Ì‚ÂÎË͇. íÓÔÓ„‡ÙËfl χÍÒËÏÛχ ‚ÓÎÌ˚ ê300 ̇ Á̇-˜ËÏ˚ fl‰˚ Ë ÍÓÎÓÌÍË. Ç ‰‚Ûı ÚÂÚflı ÒÎÛ˜‡Â‚ χÍÒËχθÌÛ˛ ÔÓ ÔÎÓ˘‡‰Ë ‚ÓÎÌÛ ê300 „Ë-ÒÚËÓ‚‡ÎË ÔÓ Ò‰ÌÂÈ ÎËÌËË „ÓÎÓ‚˚ ‚ ˆÂÌ-Ú‡Î¸ÌÓÈ (Cz) Ë ÚÂÏÂÌÌÓÈ (Pz) ӷ·ÒÚflı. Ç ÓÒڇθÌ˚ı ÒÎÛ˜‡flı χÍÒËÏÛÏ ‚ÓÎÌ˚ ·˚Î ÎÓ͇-ÎËÁÓ‚‡Ì ‚ ·ÓΠÙÓÌڇθÌ˚ı (Fz Ë Fëz) ËÎË Í‡Û‰‡Î¸Ì˚ı ӷ·ÒÚflı ÎÂ‚Ó„Ó ÔÓÎÛ¯‡Ëfl (ê3 Ë êé1). ÑÎfl ‰‡Î¸ÌÂÈ¯Â„Ó ‡Ì‡ÎËÁ‡ ‚˚·Ë‡ÎË ÓÚ-‚‰ÂÌËÂ Ò Ï‡ÍÒËχθÌÓÈ ‚ÓÎÌÓÈ ê300. èËÏÂ Ë̉˂ˉۇθÌ˚ı ÔÓÒÚ‡ÌÒÚ‚ÂÌ-Ì˚ı „‡‰ËÂÌÚÓ‚ ÔÎÓ˘‡‰Ë ‚ÓÎÌ˚ ê300 ÔË‚Â-‰ÂÌ Ì‡ ËÒ. 2, ‡ Ë ·. ÑÎfl Í‡Ê‰Ó„Ó ËÒÔ˚ÚÛÂÏÓ„Ó Ë Í‡Ê‰ÓÈ ËÁ Á̇˜ËÏ˚ı ·ÛÍ‚ ÒÚÓËÎË ‰‚‡ „‡-ÙË͇ – ‰Îfl ÒÚÓÍ Ë ‰Îfl ÒÚÓηˆÓ‚: ÔÓ ÓÒË ‡·Ò-ˆËÒÒ ÓÚÍ·‰˚‚‡ÎË ÌÓÏÂ ÒÚÓηˆ‡ (‡) ËÎË ÒÚÓ-ÍË (·), ÔÓ ÓÒË Ó‰ËÌ‡Ú – ÔÎÓ˘‡‰¸ ÔÓ‰ ‚ÓÎÌÓÈ ê300. ÇˉÌÓ, ˜ÚÓ ‰Îfl ‰‡ÌÌÓ„Ó ËÒÔ˚ÚÛÂÏÓ„Ó (à.à.) ÓÚ‚ÂÚ Ì‡ Á̇˜ËÏÛ˛ ·ÛÍ‚Û (“ä”) ÓÚ΢‡-ÂÚÒfl ÓÚ ÓÚ‚ÂÚÓ‚ ̇ β·Û˛ ËÁ ÌÂÁ̇˜ËÏ˚ı ·ÛÍ‚ ÔËÏÂÌÓ ‚ 2 ‡Á‡ Í‡Í ‚ ÍÓÎÓÌ͇ı (‡), Ú‡Í Ë ‚ fl‰‡ı (·) ·ÛÍ‚. èÓÒÚ‡ÌÒÚ‚ÂÌÌ˚È „‡‰ËÂÌÚ ê300 ÔÓ ÛÒ‰ÌÂÌÌ˚Ï ‰‡ÌÌ˚Ï. ç‡ ËÒ. 3 Ô˂‰ÂÌ˚ Ò‰ÌË „ÛÔÔÓ‚˚ ‰‡ÌÌ˚ ‰Îfl 12 ËÒÔ˚ÚÛÂÏ˚ı ÔÓ „ÓËÁÓÌڇθÌÓÈ ÓÒË ·ÛÍ‚ÂÌÌÓÈ Ï‡Úˈ˚ (Ò‚ÂÚÎ˚ ÍÛÊÍË), Ú.Â. ‚ ÍÓÎÓÌ͇ı, Ë ÔÓ ‚ÂÚË-͇θÌÓÈ ÓÒË (ÚÂÏÌ˚ ÍÛÊÍË), Ú.Â. ‚ fl‰‡ı. èÎÓ-˘‡‰¸ ‚ÓÎÌ˚ ê300 ·˚ÒÚÓ ÒÔ‡‰‡ÂÚ ÔË Û‰‡ÎÂÌËË ÓÚ Á̇˜ËÏÓÈ ·ÛÍ‚˚ Í‡Í ÔÓ „ÓËÁÓÌÚ‡ÎË, Ú‡Í Ë ÔÓ ‚ÂÚË͇ÎË (0.0001 < p < 0.001, ANOVA-Re-peated Measures). ùÚÓ ÒÌËÊÂÌË ‚˚ÒÓÍÓ‰ÓÒÚÓ-‚ÂÌÓ ÔË ÔÂÂıÓ‰Â Í ÒÓÒ‰ÌÂÈ ÍÓÎÓÌÍ ËÎË Í ÒÓÒ‰ÌÂÏÛ fl‰Û, ‡ ÔË ‰‡Î¸ÌÂȯÂÏ Û‰‡ÎÂÌËË ÔÎÓ˘‡‰¸ ÔÓ‰ ‚ÓÎÌÓÈ ê300 ÛÊ ÒÛ˘ÂÒÚ‚ÂÌÌÓ Ì ÏÂÌflÂÚÒfl. 2000 200 0 –5 0 èÓÎÓÊÂÌË ÍÓÎÓÌÍË Ì‡ χÚˈ èÎÓ˘‡‰¸ ‚ÓÎÌ˚ P300, ÓÚÌ. ‰. 1800 1600 1400 1200 1000 800 600 400 –4 –3 –2 –1 1 2 ‡ 2200 200 0 –2 3 èÓÎÓÊÂÌË fl‰‡ ̇ χÚˈ èÎÓ˘‡‰¸ ‚ÓÎÌ˚ P300, ÓÚÌ. ‰. 1800 1600 1400 1200 1000 800 600 400 –1 0 1 2 4 5 · 2000 êËÒ. 2. à̉˂ˉۇθÌ˚È ÔËÏÂ Á‡‚ËÒËÏÓÒÚË ÔÎÓ˘‡‰Ë ÔÓ‰ ‚ÓÎÌÓÈ ê300 ÛÒ‰ÌÂÌÌÓ„Ó Çè ÓÚ ÌÓÏÂ‡ ÍÓ-ÎÓÌÍË (‡) Ë fl‰‡ (·). чÌÌ˚ ËÒÔ˚ÚÛÂÏÓ„Ó à.à.

ùÚÓÚ ˝ÙÙÂÍÚ ÒÚ‡ÚËÒÚ˘ÂÒÍË Ì Á‡‚ËÒÂÎ ÓÚ ÔÓÎÓÊÂÌËfl Á̇˜ËÏÓÈ ·ÛÍ‚˚ ̇ χÚˈ (Ú.Â. ÓÚ ÌÓÏÂ‡ ÍÓÎÓÌÍË ËÎË fl‰‡) Ë ·˚Î ÒıÓ‰ÂÌ ‰Îfl ·ÛÍ‚, ‡ÒÔÓÎÓÊÂÌÌ˚ı ‚ ˆÂÌÚ χÚˈ˚ Ë Ì‡  Í‡flı. ùÚÓ ÔÓÁ‚ÓÎËÎÓ ÔÓÒÚÓËÚ¸ ÛÒ‰ÌÂÌ-ÌÛ˛ ÍË‚Û˛ Á‡‚ËÒËÏÓÒÚË ÔÎÓ˘‡‰Ë ÔÓ‰ ê300 ÓÚ ‡ÒÔÓÎÓÊÂÌËfl fl‰‡ ËÎË ÍÓÎÓÌÍË ÔÓ ÓÚÌÓ¯Â-Ì˲ Í Á̇˜ËÏÓÈ (ËÒ. 3), ‚Íβ˜Ë‚ ‚ „‡ÙËÍË ÔÓ 5 ÌÂÁ̇˜ËÏ˚ı ÍÓÎÓÌÓÍ ·ÛÍ‚ Ò΂‡ Ë ÒÔ‡‚‡ ÓÚ Á̇˜ËÏÓÈ ÍÓÎÓÌÍË, ‡ Ò‚ÂıÛ Ë ÒÌËÁÛ ÓÚ Á̇˜Ë-ÏÓ„Ó fl‰‡ ·ÛÍ‚ – 4 Ë 5 ÌÂÁ̇˜ËÏ˚ı fl‰Ó‚ ÒÓÓÚ-‚ÂÚÒÚ‚ÂÌÌÓ. ùÙÙÂÍÚ “·ÓÍÓ‚Ó„Ó ÚÓÏÓÊÂÌËfl”. å˚ ̇-¯ÎË ÌÂÍÓÚÓ˚ ‡Á΢Ëfl ÏÂÊ‰Û „ÓËÁÓÌڇθ-Ì˚Ï Ë ‚ÂÚË͇θ„ÓËÁÓÌڇθ-Ì˚Ï „‡‰ËÂÌÚ‡ÏË ÔÎÓ˘‡‰Ë ‚ÓÎÌ˚ ê300 (ËÒ. 4). é͇Á‡ÎÓÒ¸, ˜ÚÓ ‚ ÔÓÎÓ‚Ë-Ì ÒÎÛ˜‡Â‚ (Û 6 ËÒÔ˚ÚÛÂÏ˚ı ËÁ 12) ‚ „ÓËÁÓÌ-ڇθÌÓÏ „‡‰ËÂÌÚ ÔÓfl‚ËÎÒfl ˝ÙÙÂÍÚ, ÛÒÎÓ‚-ÌÓ Ì‡Á‚‡ÌÌ˚È Ì‡ÏË “·ÓÍÓ‚˚Ï”, ËÎË “·ÚÂ‡Î¸-Ì˚Ï”, ÚÓÏÓÊÂÌËÂÏ [7]. é͇Á‡ÎÓÒ¸, ˜ÚÓ ‰‚ ÍÓÎÓÌÍË ·ÛÍ‚, ‡ÒÔÓÎÓÊÂÌÌ˚Â Ò ‰‚Ûı ÒÚÓÓÌ fl‰ÓÏ Ò ÍÓÎÓÌÍÓÈ, ÒÓ‰Âʇ˘ÂÈ Á̇˜ËÏÛ˛ ·ÛÍ-‚Û, ‰‡˛Ú ÏÂ̸¯Û˛ ÔÓ ÔÎÓ˘‡‰Ë ‚ÓÎÌÛ ê300, ˜ÂÏ ·ÓΠ‰‡ÎÂÍË ÓÚ Ì ·ÛÍ‚˚ (ÒÏ. ÒÚÂÎÍË Ì‡ „‡ÙËÍ ‡). ùÚÓÚ ˝ÙÙÂÍÚ Ô‡ÍÚ˘ÂÒÍË ÌËÍÓ„‰‡ Ì ÔÓfl‚ÎflÎÒfl ‚ ‚ÂÚË͇θÌÓÏ „‡‰ËÂÌÚ (·). éÔ‰ÂÎÂÌË ÓÒÚÓÚ˚ ÁËÚÂθÌÓ„Ó ÔÓ-ÒÚ‡ÌÒÚ‚ÂÌÌÓ„Ó ‚ÌËχÌËfl. èÓ Ë̉˂ˉۇθ-Ì˚Ï ‰Ë‡„‡ÏÏ‡Ï Á‡‚ËÒËÏÓÒÚË ÔÎÓ˘‡‰Ë ‚ÓÎÌ˚ ê300 ÓÚ ÔÓÎÓÊÂÌËfl Á̇˜ËÏÓÈ ·ÛÍ‚˚ ̇ χÚË-ˆÂ ‡ÒÒ˜ËÚ˚‚‡ÎË ¯ËËÌÛ “̇ÒÚÓÈÍË” ̇ Á̇-˜ËÏÛ˛ ·ÛÍ‚Û. óÚÓ·˚ ‚Íβ˜ËÚ¸ ‚ ÓˆÂÌÍÛ ‰‡Ì-Ì˚ ‰Îfl ·ÛÍ‚, ÎÂʇ˘Ëı ̇ Í‡˛ χÚˈ˚, Ï˚ ‚˚·‡ÎË ÔÓ͇Á‡ÚÂθ ÔÓÎÛ¯ËËÌ˚ ÍË‚ÓÈ Ì‡  ÔÓÎÛ‚˚ÒÓÚÂ, Ú.Â. ̇ ÔÓÎÓ‚ËÌ ‡ÒÒÚÓflÌËfl ÓÚ ÏËÌËÏÛχ ‰Ó χÍÒËÏÛχ ÔÎÓ˘‡‰Ë ‚ÓÎÌ˚ ê300. èË ˝ÚÓÏ ÏÂ̸¯ËÏ Á̇˜ÂÌËflÏ ¯ËËÌ˚ ÒÓÓÚ-‚ÂÚÒÚ‚ÛÂÚ ·óθ¯‡fl ÓÒÚÓÚ‡ ̇ÒÚÓÈÍË, Ú.Â. ÓÒÚÓÚ‡ ÔÓÒÚ‡ÌÒÚ‚ÂÌÌÓ„Ó ‚ÌËχÌËfl. èÓ Ò‰ÌËÏ ‰‡ÌÌ˚Ï, ˝ÚÓÚ ÔÓ͇Á‡ÚÂθ ‚ ÍÓ-ÎÓÌ͇ı, Ú.Â. ÔÓ „ÓËÁÓÌÚ‡ÎË, Ó͇Á‡ÎÒfl ‡‚Ì˚Ï 0.76 ± 0.05 „‡‰, ‡ ‚ fl‰‡ı, Ú.Â. ÔÓ ‚ÂÚË͇ÎË, ÌÂ-‰ÓÒÚÓ‚ÂÌÓ ¯Ë – 0.81 ± 0.05 „‡‰ (p = 0.3). í‡-ÍËÏ Ó·‡ÁÓÏ, ‰ÓÒÚÓ‚ÂÌ˚ı ‡Á΢ËÈ ÏÂÊ‰Û ÔÓÎÛ¯ËËÌÓÈ “̇ÒÚÓÈÍË” ‚ fl‰‡ı Ë ÍÓÎÓÌ͇ı Ì ӷ̇ÛÊÂÌÓ. ë Û˜ÂÚÓÏ ‰‡ÌÌ˚ı Ó ‡ÒÒÚÓflÌËË ÏÂÊ‰Û ÍÓÎÓÌ͇ÏË Ë fl‰‡ÏË ‚ Û„ÎÓ‚˚ı „‡‰ÛÒ‡ı Ò‰ÌËÈ ‡ÁÏÂ ‡‰ËÛÒ‡ “ÔflÚ̇ ‚ÌËχÌËfl” ‚ ÛÒÎÓ‚Ëflı ̇¯Ëı ÓÔ˚ÚÓ‚ Ë ÔÓ ËÁ·‡ÌÌÓÏÛ ÍË-ÚÂ˲ ÓˆÂÌÍË Ó͇Á‡ÎÒfl ‡‚Ì˚Ï 1.6 ± 0.1 „‡‰. ë‚flÁ¸ ¯ËËÌ˚ “̇ÒÚÓÈÍË” ̇ Á̇˜ËÏÛ˛ ·ÛÍ‚Û Ò ÔÎÓ˘‡‰¸˛ ‚ÓÎÌ˚ ê300. ç‡ ËÒ. 5, ‡ Ô˂‰Â̇ ‰Ë‡„‡Ïχ ‡ÒÒÂË‚‡ÌËfl, ËÎβÒÚË-Û˛˘‡fl Ó·‡ÚÌÛ˛ Ò‚flÁ¸ ˝ÚËı ÔÓ͇Á‡ÚÂÎÂÈ. ÇˉÌÓ, ˜ÚÓ ˜ÂÏ ·Óθ¯Â ÔÎÓ˘‡‰¸ ‚ÓÎÌ˚ ê300, ÚÂÏ ‚ Ò‰ÌÂÏ Ê ÍË‚‡fl ̇ÒÚÓÈÍË (ÍÓ˝ÙÙË-ˆËÂÌÚ ÍÓÂÎflˆËË ÓÚˈ‡ÚÂÎÂÌ Ë ‡‚ÂÌ –0.4, p < 0.006). àÌ˚ÏË ÒÎÓ‚‡ÏË, ˜ÂÏ ·Óθ¯Â ‚ÓÎ̇ ê300 ̇ Á̇˜ËÏÛ˛ ·ÛÍ‚Û, ÚÂÏ ‚ Ò‰ÌÂÏ ÓÒÚ ̇ÒÚÓÈ͇ ̇ ˝ÚÛ ·ÛÍ‚Û. ÇˉÌÓ ‡Á‰ÂÎÂÌË ‚ÒÂÈ ÒÓ‚ÓÍÛÔÌÓÒÚË ‰‡ÌÌ˚ı ̇ ‰‚ ÔÓ‰„ÛÔÔ˚ Ò ‡ÁÌÓÈ ‚Á‡ËÏÓÒ‚flÁ¸˛ ‰‚Ûı ÔÓ͇Á‡ÚÂÎÂÈ. è‰-ÔÓÎÓÊËÚÂθÌ˚ ÎËÌËË „ÂÒÒËË ‰Îfl ˝ÚËı „ÛÔÔ ÔÓ͇Á‡Ì˚ ÔÛÌÍÚËÌÓÈ ÎËÌËÂÈ. éÅëìÜÑÖçàÖ êÖáìãúíÄíéÇ èÓÎÛ˜ÂÌÌ˚ ‚ ‡·ÓÚ ‰‡ÌÌ˚ ҂ˉÂÚÂθ-ÒÚ‚Û˛Ú Ó ÒÚÓ„ÓÈ ÎÓ͇θÌÓÒÚË ÁËÚÂθÌÓ„Ó ‚ÌËχÌËfl Í Á̇˜ËÏÓÈ ·ÛÍ‚Â. ùÚÓ Ó·ÛÒÎÓ‚ÎË‚‡-ÂÚ Â ̇‰ÂÊÌÓ ‚˚‰ÂÎÂÌË ËÁ ·ÛÍ‚ÂÌÌÓÈ Ï‡Ú-ˈ˚ ‚ Ô‡‡‰Ë„Ï ÌÂÈÓÍÓÏÔ¸˛ÚÂÌÓ„Ó ËÌ-ÚÂÙÂÈÒ‡, ÓÒÌÓ‚‡ÌÌÓ„Ó Ì‡ ‡Ì‡ÎËÁ ÔÎÓ˘‡‰Ë ‚ÓÎÌ˚ ê300 ÁËÚÂθÌÓ„Ó Çè. èӂ‰ÂÌÌÓ ËÒ-ÒΉӂ‡ÌË ÔÓÁ‚ÓÎflÂÚ ‰‡Ú¸ ÓˆÂÌÍÛ ‡ÁÏÂ‡ “ÔflÚ̇ ‚ÌËχÌËfl”, ̇ ÓÒÌÓ‚Â ÍÓÚÓÓ„Ó ÔÓËÒ-ıÓ‰ËÚ ‚˚‰ÂÎÂÌË ËÁ ·ÛÍ‚ÂÌÌÓÈ Ï‡Úˈ˚ Á̇-˜ËÏÓÈ ·ÛÍ‚˚ ‚ “‚ËÚۇθÌÓÈ ÔË¯Û˘ÂÈ Ï‡-¯ËÌÍ” (“mental typewriter”) [15]. ç‡ÔÓÏÌËÏ, ˜ÚÓ ‡Ì ÔË Ì‡¯ÂÏ Û˜‡ÒÚËË ·˚Î ÒÓÁ‰‡Ì Ë ËÒ-ÒΉӂ‡Ì çäà, ÔÓÁ‚ÓÎfl˛˘ËÈ Ì‡·Ë‡Ú¸ ÚÂÍÒÚ Ì‡ ˝Í‡Ì ‰ËÒÔÎÂfl Ò ÔÓÏÓ˘¸˛ Ï˚ÒÎÂÌÌ˚ı ÍÓ-Û´ 200 0 –6 0 èÓÎÓÊÂÌË ÒÚÓηˆ‡ Ë ÒÚÓÍË Ì‡ χÚˈ èÎÓ˘‡‰¸ ‚ÓÎÌ˚ P300, ÓÚÌ. ‰. 1200 1000 800 600 400 –4 –3 –2 –1 1 4 –5 2 3 5 6 êËÒ. 3. èÎÓ˘‡‰¸ ÔÓ‰ ‚ÓÎÌÓÈ ê300 (ÓÒ¸ Ó‰Ë̇Ú, ÓÚÌ. ‰.) Í‡Í ÙÛÌ͈Ëfl ‡ÒÔÓÎÓÊÂÌËfl ÍÓÎÓÌÓÍ (Ò‚ÂÚÎ˚ ÍÛÊÍË) ËÎË fl‰Ó‚ (ÚÂÏÌ˚ ÍÛÊÍË) ̇ χÚˈ ·ÛÍ‚ (ÓÒ¸ ‡·ÒˆËÒÒ, Á‡ ÌÛ΂ӠÔË-ÌflÚÓ ÔÓÎÓÊÂÌË Á̇˜ËÏÓÈ ·ÛÍ‚˚). è˂‰ÂÌ˚ Ò‰ÌË „ÛÔÔÓ‚˚ ‰‡ÌÌ˚Â Ë Ëı ӯ˷ÍË ‰Îfl 12 ËÒÔ˚ÚÛÂÏ˚ı. é·˙flÒÌÂÌË ‚ ÚÂÍÒÚÂ.

Fig. 3. Square of ê300 wave (ordinate in relative units) vs. position of the columns (open dots) or rows (closed dotes) in the letter matrix (abscissa, the position of the meaningful letter is taken as zero). Mean group data and their SEM. for 12 subjects.

306 ÜìêçÄã ÇõëòÖâ çÖêÇçéâ ÑÖüíÖãúçéëíà      ÚÓÏ 58      ‹ 3      2008 ÏËı‡ÈÎÓ‚‡ Ë ‰. χ̉ [1]. Ç ÓÒÌÓ‚Û ‡·ÓÚ˚ ˝ÚÓÈ ÒËÒÚÂÏ˚ ·˚ÎÓ ÔÓÎÓÊÂÌÓ Ò‡‚ÌÂÌË ‚ÓÎÌ˚ ê300 ÁËÚÂθÌÓ„Ó ‚˚Á‚‡ÌÌÓ„Ó ÔÓÚÂ̈ˇ· ̇ Á̇˜ËÏ˚ (Á‡‰Û-χÌÌ˚ ˜ÂÎÓ‚ÂÍÓÏ) Ë ÌÂÁ̇˜ËÏ˚ ·ÛÍ‚˚ (“odd ball paradigm”). ëÛÚ¸ ÏÂÚÓ‰‡ ‚ ÚÓÏ, ˜ÚÓ ‡Ì‡ÎË-ÁËÛÂÚÒfl ÒÛÏχ̇fl ˝ÎÂÍÚ˘ÂÒ͇fl ‡͈Ëfl ÏÓÁ„‡, Ò‚flÁ‡Ì̇fl Ò ÔÓËÁ‚ÓθÌ˚Ï ËÁ·Ë‡ÚÂθ-Ì˚Ï ‚ÌËχÌËÂÏ ˜ÂÎÓ‚Â͇ Í Á‡‰ÛχÌÌÓÈ ËÏ 200 0 0 èÓÎÓÊÂÌË ÍÓÎÓÌÍË Ì‡ χÚˈ èÎÓ˘‡‰¸ ‚ÓÎÌ˚ P300, ÓÚÌ. ‰. 1200 1000 800 600 400 –4 –3 –2 –1 1 2 200 0 0 èÓÎÓÊÂÌË fl‰‡ ̇ χÚˈ èÎÓ˘‡‰¸ ‚ÓÎÌ˚ P300, ÓÚÌ. ‰. 1200 1000 800 600 400 –3 –2 –1 1 2 · 3 ‡ 3 4 êËÒ. 4. ᇂËÒËÏÓÒÚ¸ ÔÎÓ˘‡‰Ë ÔÓ‰ ‚ÓÎÌÓÈ ê300 ÓÚ ÌÓÏÂ‡ ÍÓÎÓÌÍË (‡) Ë fl‰‡ (·). ë‰ÌË ‰‡ÌÌ˚Â Ë Ëı ӯ˷ÍË ‰Îfl 6 ËÒÔ˚ÚÛÂÏ˚ı. ëÚÂÎÍË Ì‡ „‡ÙËÍ ‡ Û͇Á˚‚‡˛Ú ̇ ˝ÙÙÂÍÚ˚ “·ÓÍÓ‚Ó„Ó ÚÓÏÓÊÂÌËfl”. éÒڇθÌ˚ ӷÓÁ̇˜ÂÌËfl Í‡Í Ì‡ ËÒ. 3.

Fig. 4. The same as in Fig. 3 but for 6 subjects with “lateral inhibition” effects (shown by arrows). Graphs (‡) for columns and (·) for rows.

2.0 0.4 200 2200 èÎÓ˘‡‰¸ ÔÓ‰ ‚ÓÎÌÓÈ P300, ÓÚÌ. ‰. èÓÎÛ¯ËË̇ ̇ÒÚÓÈÍË, ÓÚÌ. ‰. 1.6 1.2 0.8 600 1000 1400 1800 1 2 4 3 ‡ · êËÒ. 5. ë‚flÁ¸ ÔÓÎÛ¯ËËÌ˚ ̇ÒÚÓÈÍË Ì‡ Á̇˜ËÏÛ˛ ·ÛÍ‚Û Ò ÔÎÓ˘‡‰¸˛ ÔÓ‰ ‚ÓÎÌÓÈ ê300. ç‡ ‡: ÔÓ ÓÒË Ó-‰ËÌ‡Ú – ÔÓÎÛ¯ËË̇ ̇ÒÚÓÈÍË (ÓÚÌ. ‰.), ÔÓ ÓÒË ‡·ÒˆËÒÒ – ÔÎÓ˘‡‰¸ ÔÓ‰ ‚ÓÎÌÓÈ ê300 (ÓÚÌ. ‰.). ä‡Ê‰‡fl ÚӘ͇ ̇ „‡ÙËÍ – ‰‡ÌÌ˚ ‰Îfl Ó‰ÌÓÈ ËÁ ÔÓÚÂÒÚËÓ‚‡ÌÌ˚ı Á̇˜ËÏ˚ı ·ÛÍ‚ (n = 48). ç‡ · – ÒıÂÏ˚ ÍË-‚˚ı ̇ÒÚÓÈÍË ‰Îfl Ò··Ó„Ó (1 Ë 3) Ë ÒËθÌÓ„Ó Ò˄̇· (2 Ë 4) ·ÂÁ ·ÓÍÓ‚Ó„Ó ÚÓÏÓÊÂÌËfl (1 Ë 2) Ë Ò ÌËÏ (4). íÓÏÓÁÌ˚ „‡‰ËÂÌÚ˚ ̇ ÒıÂÏ 4 Á‡˜ÂÌÂÌ˚. ÉÓËÁÓÌڇθÌ˚ ÔÛÌÍÚËÌ˚ ÎËÌËË Ôӂ‰ÂÌ˚ ̇ ÛÓ‚Ì 0.5 ÓÚ Ï‡ÍÒËÏÛχ ÙÛÌ͈ËË. é·˙flÒÌÂÌË ‚ ÚÂÍÒÚÂ.

Fig. 5. a – relation of half-width at half height of tuning to the meaningful letter (ordinate in angle degrees) to the square of ê300 wave (abscissa in relative units). Each dot represents the data for one tested significant letter (n = = 48). · – schemes of the tuning curves for low (1 and 3) and high signals (2 and 4) without lateral inhibition (1 and 2) and with it (blackened in 4). Horizontal dofted lines correspond to 0.5 of the function maximum. Explanations see in the text.

·ÛÍ‚Â. ÇÒÔ˚ıË‚‡ÌË ÒÚÓÍ Ë ÒÚÓηˆÓ‚ ÔÓËÒ-ıÓ‰ËÚ ‚ ÒÎÛ˜‡ÈÌÓÏ ÔÓfl‰ÍÂ, Ë ‚ÂÓflÚÌÓÒÚ¸ ÚÓ-„Ó, ˜ÚÓ ‚ ‰‡ÌÌ˚È ÏÓÏÂÌÚ Û‚Â΢ËÚÒfl flÍÓÒÚ¸ ‚˚·‡ÌÌÓÈ ËÒÔ˚ÚÛÂÏ˚Ï ·ÛÍ‚˚ ‚ ÒÓÒÚ‡‚ ÒÚÓ-ÍË ËÎË ÒÚÓηˆ‡ ÒÓÒÚ‡‚ÎflÂÚ ‚ ̇¯Ëı ÛÒÎÓ‚Ëflı 16.7%, ‡ ‚ÂÓflÚÌÓÒÚ¸ ÔÓ‰Ò‚ÂÚÍË ÌÂÁ̇˜ËÏ˚ı ÒÚÓÍ (ÒÚÓηˆÓ‚) ̇ÏÌÓ„Ó ‚˚¯Â – 83.3%. èË Ú‡ÍÓÈ ‡ÁÌˈ ̇ Á̇˜ËÏ˚È ÒËÏ‚ÓÎ ‚ Çè ˜ÂÎÓ-‚Â͇ ‚ÓÁÌË͇ÂÚ ‚˚ÒÓÍÓ‡ÏÔÎËÚÛ‰Ì˚È ÍÓÏÔÓ-ÌÂÌÚ ê300. èӂ‰ÂÌÌ˚È ‡Ì ‡Ì‡ÎËÁ ‚˚fl‚ËΠ̇Ë-·Óθ¯Û˛ ÚÓ˜ÌÓÒÚ¸ ÓÔÓÁ̇ÌËfl Á‡‰ÛχÌÌ˚ı ËÒ-Ô˚ÚÛÂÏ˚Ï ÒÎÓ‚ ÔË ÓˆÂÌÍ ‚ÓÎÌ˚ ê300 ‚ ÓÚ‚Â-‰ÂÌËË Pz, „‰Â Ó̇ ·˚· χÍËχθ̇ ÔÓ ‡ÏÔÎË-ÚÛ‰Â Ë ÔÎÓ˘‡‰Ë [1]. Ç Ì‡ÒÚÓfl˘ÂÈ ‡·ÓÚ ˝ÚË ‰‡ÌÌ˚ ÛÚÓ˜ÌÂÌ˚: Ó͇Á‡ÎÓÒ¸, ˜ÚÓ ‡ÏÔÎËÚÛ‰-Ì˚È Ï‡ÍÒËÏÛÏ ‚ÓÎÌ˚ ê300 ‚ Óڂ‰ÂÌËË êz ı‡-‡ÍÚÂÂÌ ‰Îfl ‰‚Ûı ÚÂÚÂÈ ÒÎÛ˜‡Â‚, ‡ ‚ ÓÒڇθ-Ì˚ı ÓÌ ‡ÒÔÓ·„‡ÂÚÒfl ‚ Óڂ‰ÂÌËflı ëz Ë FCz. ùÚÓ ‡ÒıÓʉÂÌË ÏÓÊÂÚ ·˚Ú¸ Ò‚flÁ‡ÌÓ Ò ÚÂÏ, ˜ÚÓ ‚ ̇ÒÚÓfl˘ÂÈ ‡·ÓÚ Ï˚ ‡Ì‡ÎËÁËÓ‚‡ÎË ‚ÓÎÌÛ ê300 ÚÓθÍÓ ‚ ÔÂ‚˚ı, Ú‡Í Ì‡Á˚‚‡ÂÏ˚ı ÚÂÌËÓ‚Ó˜Ì˚ı ÒÂÒÒËflı, ‡ ‚ ̇¯ÂÈ Ô‰˚‰Û-˘ÂÈ ‡·ÓÚ [1] Ô˂‰ÂÌ˚ ‰‡ÌÌ˚ ÔÓ ·ÓΠ‰ÎËÚÂθÌÓÏÛ Ó·Û˜ÂÌ˲ (ÌÂÒÍÓθÍÓ ÒÂËÈ), ÔË ÍÓÚÓÓÏ ÏËÌËÏËÁËÛ˛ÚÒfl ˝ÙÙÂÍÚ˚ ˝ÏÓ-ˆËÓ̇θÌÓ„Ó Ì‡ÔflÊÂÌËfl, ‚ÓÁÏÓÊÌÓ, ‚ÎËfl˛-˘Ë ̇ ÎÓ͇ÎËÁ‡ˆË˛ χÍÒËÏÛχ ‚ÓÎÌ˚ ê300. ç‡Ë·ÓΠËÌÚÂÂÒÌ˚Ï Ë ‚‡ÊÌ˚Ï ÂÁÛθڇ-ÚÓÏ Ôӂ‰ÂÌÌÓ„Ó ËÒÒΉӂ‡ÌËfl Ô‰ÒÚ‡‚ÎflÂÚ-Òfl ‚˚ÒÓ͇fl ÓÒÚÓÚ‡ ÁËÚÂθÌÓ„Ó ‚ÌËχÌËfl Í Á‡‰ÛχÌÌÓÈ ·ÛÍ‚Â: ÔË Û‰‡ÎÂÌËË ÓÚ Ì ÔÎÓ-˘‡‰¸ ÔÓ‰ ‚ÓÎÌÓÈ ê300 ÒÚÂÏËÚÂθÌÓ Û·˚‚‡ÂÚ, ‡ Á‡ÚÂÏ, ‚ ·ÓΠÓÚ‰‡ÎÂÌÌ˚ı ÍÓÎÓÌ͇ı ËÎË fl-‰‡ı Ó̇ ÔÓ˜ÚË Ì ËÁÏÂÌflÂÚÒfl. òËË̇ ̇ÒÚÓÈ-ÍË Ë ÔÓ „ÓËÁÓÌÚ‡ÎË, Ë ÔÓ ‚ÂÚË͇ÎË ÒÓÒÚ‡‚Îfl-ÂÚ ÓÍÓÎÓ 1.6 „‡‰, ˜ÚÓ ·ÎËÁÍÓ Í ‡ÒÒÚÓflÌ˲ ÏÂÊ‰Û ÒÓÒ‰ÌËÏË fl‰‡ÏË ËÎË ÍÓÎÓÌ͇ÏË Ì‡-¯ÂÈ ·ÛÍ‚ÂÌÌÓÈ Ï‡Úˈ˚. àÏÂÌÌÓ Ú‡ÍÓÈ ÂÁ-ÍËÈ ÒÔ‡‰ ÔÎÓ˘‡‰Ë ‚ÓÎÌ˚ ê300 ‚ ÒÓÒ‰ÌÂÈ ÒÓ Á̇˜ËÏÓÈ ÍÓÎÓÌÍ ËÎË fl‰Û Ó·ÂÒÔ˜˂‡ÂÚ ‚˚-ÒÓÍÛ˛ ˝ÙÙÂÍÚË‚ÌÓÒÚ¸ ‡·ÓÚ˚ ËÒÒΉӂ‡ÌÌÓ-„Ó çäà [1]. Ç˚ÒÓ͇fl ÓÒÚÓÚ‡ ÁËÚÂθÌÓÈ Ì‡ÒÚÓÈÍË ÔË ÓÔÓÁ̇ÌËË ·ÛÍ‚ ÔÓ Ôӂ‰Â̘ÂÒÍËÏ ‰‡ÌÌ˚Ï ·˚· ÓÔË҇̇ ê. îËχÌÓÏ [6]. éÌ Ì‡¯ÂÎ, ˜ÚÓ ‰Îfl ·ÂÁӯ˷ӘÌÓ„Ó ÓÔÓÁ̇ÌËfl ·ÛÍ‚ ‰ÓÒÚ‡ÚÓ˜-ÌÓ ‡ÒÒÚÓflÌËfl ÏÂÊ‰Û ÌËÏË ‚ 0.5 „‡‰. Ç ˝ÚÓÈ Ê ‡·ÓÚ ‡‚ÚÓ Ó·‡˘‡ÂÚ ‚ÌËχÌË ̇ ·ÓΠÚÓ˜ÌÛ˛ ̇ÒÚÓÈÍÛ ÔÓ „ÓËÁÓÌÚ‡ÎË ÔÓ Ò‡‚ÌÂ-Ì˲ Ò ‚ÂÚË͇θ˛, ˜ÚÓ ÒÓÓÚ‚ÂÚÒÚ‚ÛÂÚ ÚẨÂÌ-ˆËË, ‚˚fl‚ÎÂÌÌÓÈ ‚ ̇¯Ëı ÓÔ˚Ú‡ı. ùÚË ‰‡ÌÌ˚ ÍÓÂÎËÛ˛Ú Ò ·ÓΠ‚˚ÒÓÍÓÈ ÒÍÓÓÒÚ¸˛ ˜ÚÂ-ÌËfl ÔÓ „ÓËÁÓÌÚ‡ÎË, ˜ÂÏ ÔÓ ‚ÂÚË͇ÎË [3, 14], Ë Ò ·ÓΠ·˚ÒÚ˚Ï ÓÔÓÁ̇ÌËÂÏ ·ÛÍ‚ ÔË Ëı ‡Ò-ÔÓÎÓÊÂÌËË ‚ fl‰‡ı ÔÓ Ò‡‚ÌÂÌ˲ Ò ÍÓÎÓÌ͇ÏË [10]. í‡ÍË „ÓËÁÓÌڇθÌÓ-‚ÂÚË͇θÌ˚ ‡Á-΢Ëfl Ô‰ÔÓÎÓÊËÚÂθÌÓ Ò‚flÁ˚‚‡˛Ú Ò ‚ÎËflÌË-ÂÏ ÓÔ˚Ú‡ ˜ÚÂÌËfl. ÇÂÓflÚÌÓÒÚ¸ Ú‡ÍÓ„Ó Ó·˙flÒÌÂ-ÌËfl ÔÓ‰Ú‚Âʉ‡ÂÚÒfl ÚÂÏ, ˜ÚÓ ‚ ˝ÍÒÔÂËÏÂÌÚ‡ı Ò ÍÓθˆ‡ÏË ã‡Ì‰Óθڇ Ú‡ÍËı „ÓËÁÓÌڇθÌÓ-‚Â-ÚË͇θÌ˚ı ‡Á΢ËÈ Ì ӷ̇ÛÊÂÌÓ [6]. ç‡Ï Ô‰ÒÚ‡‚ÎflÂÚÒfl ËÌÚÂÂÒÌ˚Ï Ë Á̇˜Ë-Ï˚Ï ÚÓÚ Ù‡ÍÚ, ˜ÚÓ Û ÔÓÎÓ‚ËÌ˚ ËÒÔ˚ÚÛÂÏ˚ı ÔÓ „ÓËÁÓÌڇθÌÓÏÛ „‡‰ËÂÌÚÛ ê300 ÔÓfl‚ËÎÒfl ˝ÙÙÂÍÚ Î‡ÚÂ‡Î¸ÌÓ„Ó ÚÓÏÓÊÂÌËfl [7]. ì˜Ë-Ú˚‚‡fl, ˜ÚÓ ÔÓ‰Ò‚ÂÚ͇ ÍÓÎÓÌÓÍ Ë fl‰Ó‚ ·ÛÍ‚ ÔÓËÁ‚Ӊ˷Ҹ ‚ ÒÎÛ˜‡ÈÌÓÏ ÔÓfl‰ÍÂ, ˝ÚÓÚ ˝Ù-ÙÂÍÚ ÌÂθÁfl Ó·˙flÒÌËÚ¸ fl‚ÎÂÌËÂÏ ‚ÂÏÂÌÌó„Ó ÍÓÌÚ‡ÒÚ‡. éÒÚ‡ÂÚÒfl Ô‰ÔÓÎÓÊËÚ¸, ˜ÚÓ ‚ ÛÒÎÓ-‚Ëflı ̇¯Ëı ÓÔ˚ÚÓ‚ ‚ ÌÂÍÓÂÏ ÓÚ‰ÂΠÁËÚÂθ-ÌÓÈ ÍÓ˚ ÒÓı‡ÌflÂÚÒfl ÒΉ ·ÛÍ‚ÂÌÁËÚÂθ-ÌÓÈ Ï‡ÚË-ˆ˚, Á̇˜ËÏ˚È ˝ÎÂÏÂÌÚ ÍÓÚÓÓ„Ó (ÒΉ ‚˚·‡Ì-ÌÓÈ ·ÛÍ‚˚) ÚÓÏÓÁËÚ ÒÓÒ‰ÌË ˝ÎÂÏÂÌÚ˚. Ç ˝ÚÓÈ Ò‚flÁË ÔÓÎÓÊËÚÂθ̇fl Ò‚flÁ¸ ÏÂÊ‰Û ÔÎÓ˘‡-‰¸˛ ‚ÓÎÌ˚ ê300 Ë ÓÒÚÓÚÓÈ Ì‡ÒÚÓÈÍË Ì‡ Á̇-˜ËÏÛ˛ ·ÛÍ‚Û ÒÚ‡ÌÓ‚ËÚÒfl ÔÓÌflÚÌÓÈ, Ú‡Í Í‡Í Ú‡-ÍÛ˛ Ò‚flÁ¸ ÏÓÊÂÚ Ó·ÂÒÔ˜ËÚ¸ ÚÓθÍÓ Ó·ÓÒÚÂ-ÌË ̇ÒÚÓÈÍË ·ÓÍÓ‚˚Ï ÚÓÏÓÊÂÓ·ÓÒÚÂ-ÌËÂÏ. ç‡ ËÒ. 5, · ÒıÂχÚ˘ÂÒÍË ÔÓ͇Á‡ÌÓ, Í‡Í ÏÓÊÂÚ ËÁ-ÏÂÌËÚ¸Òfl ¯ËË̇ ̇ÒÚÓÈÍË ÔË ‡ÁÌÓÈ ‡Ï-ÔÎËÚۉ Ò˄̇· ‚ ÒËÒÚÂÏ ·ÂÁ ÚÓÏÓÊÂÌËfl (1 Ë 2) Ë ÔË Â„Ó ‚ÓÁÌËÍÌÓ‚ÂÌËË ‚ ÒÎÛ˜‡Â ·Óθ-¯ÂÈ ‡ÏÔÎËÚÛ‰˚ Ò˄̇· (4). ÅÂÁ ÚÓÏÓÊÂÌËfl Ò‚flÁ¸ ¯ËËÌ˚ ̇ÒÚÓÈÍË Ë ÔÎÓ˘‡‰Ë ‚ÓÎÌ˚ ê300 ‰ÓÎÊ̇ ·˚· ·˚ ÒÚ‡Ú¸ ÔÓÎÓÊËÚÂθÌÓÈ, ‡ ÚÓÏÓÊÂÌË ӷÓÒÚflÂÚ Ì‡ÒÚÓÈÍÛ, ÛÏÂ̸¯‡fl  ¯ËËÌÛ. ÇõÇéÑõ 1. èÎÓ˘‡‰¸ ÔÓ‰ ‚ÓÎÌÓÈ ê300 ÁËÚÂθÌÓ„Ó ‚˚Á‚‡ÌÌÓ„Ó ÔÓÚÂ̈ˇ· ÏÓÁ„‡ ˜ÂÎÓ‚Â͇ ̇ ÍÓ-ÓÚÍÛ˛ ÔÓ‰Ò‚ÂÚÍÛ ‚ ·ÛÍ‚ÂÌÌÓÈ Ï‡Úˈ ÒÚÓη-ˆ‡ ËÎË fl‰‡ ·ÛÍ‚, ÒÓ‰Âʇ˘Â„Ó Á̇˜ËÏÛ˛ (Á‡-‰ÛχÌÌÛ˛) ·ÛÍ‚Û, ‰ÓÒÚÓ‚ÂÌÓ ‚˚¯Â, ˜ÂÏ ‰Îfl β·Ó„Ó ÒÚÓηˆ‡ ËÎË fl‰‡ Ò ÌÂÁ̇˜ËÏ˚ÏË ·ÛÍ-‚‡ÏË. ùÚÓ ‚ÂÌÓ ‰Îfl β·Ó„Ó ÔÓÎÓÊÂÌËfl ·ÛÍ‚˚ ̇ χÚˈÂ. 2. èË Û‰‡ÎÂÌËË ÓÚ Á̇˜ËÏÓ„Ó ÒÚËÏÛ· ÔÎÓ-˘‡‰¸ ÔÓ‰ ‚ÓÎÌÓÈ ê300 Û·˚‚‡ÂÚ: ‚ 2 ‡Á‡ ̇ ‡Ò-ÒÚÓflÌËË ÓÍÓÎÓ 0.8 „‡‰, ˜ÚÓ ·ÎËÁÍÓ Í ‡ÒÒÚÓfl-Ì˲ ÏÂÊ‰Û ÒÓÒ‰ÌËÏË fl‰‡ÏË ËÎË ÍÓÎÓÌ͇ÏË. ÑÓÒÚÓ‚ÂÌ˚ı ‡Á΢ËÈ ‚ „ÓËÁÓÌڇθÌÓÏ Ë ‚ÂÚË͇θÌÓÏ „‡‰ËÂÌÚ‡ı ̇ÒÚÓÈÍË Ì‡ Á̇˜Ë-ÏÛ˛ ·ÛÍ‚Û Ì ӷ̇ÛÊÂÌÓ. 3. ÑÎfl „ÓËÁÓÌڇθÌÓ„Ó ÔÓÒÚ‡ÌÒÚ‚ÂÌÌÓ„Ó „‡‰ËÂÌÚ‡ ê300 ӷ̇ÛÊÂÌ ˝ÙÙÂÍÚ ·ÓÍÓ‚Ó„Ó ÚÓÏÓÊÂÌËfl, ÍÓÚÓ˚È Ì ‚˚‡ÊÂÌ ‚ ‚ÂÚË-͇θÌÓÏ „‡‰ËÂÌÚÂ.

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