• 検索結果がありません。

ベクトル加算演算と広視野運動知覚

N/A
N/A
Protected

Academic year: 2021

シェア "ベクトル加算演算と広視野運動知覚"

Copied!
8
0
0

読み込み中.... (全文を見る)

全文

(1)

࣋ࢡࢺࣝຍ⟬₇⟬࡜ᗈど㔝㐠ື▱ぬ

Linear Integration Properties of the Perception of Motion Aftereffect

Caused by Wide-field Transparent Visual Flow

ᵽ⏣ᰤ᥹㸪

ᶓᇼႛ♸㸪

┦ཎጾ

Eiki Hida Kyousuke Yokobori Takeshi Aihara ⋢ᕝ኱ᏛᕤᏛ㒊ࢯࣇࢺ࢙࢘࢔ࢧ࢖࢚ࣥࢫᏛ⛉

 ᮾி㒔⏫⏣ᕷ⋢ᕝᏛᅬ㸴㸫㸯㸫㸯 Faculty of Engineering, Tamagawa University

6-1-1 Tamagawagakuen, Machida-shi, Tokyo 194-8610

Abstract

We investigated motion integration properties of the perception of motion aftereffect caused by wide-field transparent visual flow. Adapting stimulus composed of random dot patterns was presented to human observers to examine both direction and duration of motion aftereffect(MAE). For unidirectional motion, perceived duration of MAE depended on the speed of adapting stimulus. Transparent visual stimulus in the multiple directions induced motion aftereffect with unidirectional percept. Perceived direction depended on the speed of coherent motion in the transparent visual flow. Direction of motion aftereffect suggested linear integration mechanism of transparent flows by weighted summation of each coherent motion in the visual stimulus.

Keywords: Wide-field Visual Flow, Transparent Motion, Multiple directions, Motion Aftereffect, Integration of Motion, Vector Summation

1. ࡣࡌࡵ࡟

ࢃࢀࢃࢀࡀ᪥ᖖ⤒㦂ࡍࡿどぬ㐠ື࡟ࡣ, እ⏺ ࡟Ꮡᅾࡍࡿ≀యࡢ㐠ື࡛࠶ࡿᒁᡤ㐠ື࡜⮬ᕫࡢ ⛣ື࡞࡝࡟కࡗ࡚⏕ࡎࡿᗈど㔝㐠ື࡜ࡀ࠶ࡿ㸯㸧 ࡇࡢ࠺ࡕᗈど㔝㐠ືࡣ㸪3 ḟඖ✵㛫ୖ࡟ᒎ㛤ࡍࡿ እ⏺ࢆᢕᥱࡋ㸪⮬㌟ࡢ㐠ື᪉ྥࢆṇࡋࡃㄆ㆑ࡋ ࡚⮬ᕫ㐠ືࡢไᚚࢆ⾜࠺ࡓࡵ࡟ࡣᚲせ୙ྍḞ࡛ ࡶࡢ࡛࠶ࡿ㸯㸧 ║ࡢ᭱ෆᒙ࡟Ꮡᅾࡍࡿ⥙⭷࡟ᫎࡋฟࡉࢀࡓእ ⏺ࡢᫎീ࠿ࡽ㸪࡝ࡢࡼ࠺࡞㐣⛬ࢆ⤒࡚ᗈど㔝㐠 ື᝟ሗࡀ᳨ฟࡉࢀࡿ࠿࡟ࡘ࠸࡚ࡣ㸪ࡑࡢ୺せ࡞ ⬻ෆ᝟ሗฎ⌮⤒㊰ࡀ▱ࡽࢀ࡚࠸ࡿ㸬ࡍ࡞ࢃࡕ㸪 ⥙⭷࡛㟁Ẽಙྕ࡟ኚ᥮ࡉࢀࡓどぬ᝟ሗࡣ㸪ᚋ㢌 ⴥࡢV1 㔝࡬࡜ᢞᑕࡉࢀࡿ㸬ࡇࡇ࡛㐠ື᝟ሗࡢ᭱ ึࡢ㐠ື᳨ฟࡀ࡞ࡉࢀࡓ࠶࡜㸪どぬ㐃ྜ㔝࡟఩ ⨨ࡍࡿMT 㔝࡛ᒁᡤ㐠ືࡢ᳨ฟ2㸧㸪⥆࠸࡚MST 㔝࡟࠾࠸࡚ࡣᗈど㔝㐠ືࡢ᝟ሗ᳨ฟࡀ࡞ࡉࢀࡿ 2㸪3㸪4㸧㸬ࡍ࡞ࢃࡕ㸪ᗈど㔝㐠ື᝟ሗࡀᢳฟࡉࢀࡿ

(2)

ࡓࡵ࡟ࡣ㸪ఱẁ㝵࡟ࡶࢃࡓࡿ᝟ሗࡢ⤫ྜࡀᚲ㡲 ࡜࡞ࡿ4㸧㸬ࡋ࠿ࡋ㸪㐠ື᝟ሗࡢ⤫ྜࡣMT 㔝࠿ ࡽMST 㔝࡟⮳ࡿẁ㝵࡛ࡢ᝟ሗฎ⌮࡛⤊⤖ࡋࡓ ࢃࡅ࡛ࡣ࡞࠸㸬ࡓ࡜࠼ࡤ㸪ど㔝ୖ࡟ከᩘࡢᗈど 㔝㐠ືࡀᏑᅾࡍࡿሙྜ࡟ࡣఱࡽ࠿ࡢ᝟ሗ⤫ྜࡀ ᚲせ࡛࠶ࡿࡀ5,6㸧㸪࡝ࡢࡼ࠺࡞ᛶ㉁ࡢ᝟ሗ⤫ྜ࡛ ࠶ࡿࡢ࠿࡟ࡘ࠸࡚ࡣ࠸ࡲࡔ᫂ࡽ࠿࡟࡞ࡗ࡚࠸࡞ ࠸㸬 ᮏ◊✲࡛ࡣ㸪ᗈど㔝㐠ື᝟ሗࡢ⤫ྜࡢᛶ㉁࡟ࡘ ࠸࡚㸪ࣄࢺࢆᑐ㇟࡜ࡋࡓᚰ⌮≀⌮Ꮫⓗᐇ㦂࡟ࡼ ࡾㄪ࡭࡚࠸ࡁࡓ࠸㸬ࡑࡢࡓࡵ࡟㸪᝟ሗ⤫ྜࡢ≉ ᛶࢆゎᯒࡍࡿࡢ࡟㐺ࡋ࡚࠸ࡿ㐠ືṧຠ▱ぬ࡟╔ ┠ࡋࡓ㸬  㐠ືṧຠ࡜ࡣ㸪୍ᐃ᪉ྥࡢ㐠ື่⃭ࢆ୍ᐃ᫬ 㛫ぢ⥆ࡅࡓ࠶࡜㟼Ṇࣃࢱ࣮ࣥ࡟┠ࢆ⛣ࡋࡓ࡜ࡁ㸪 㟼Ṇࡋ࡚࠸ࡿࡶࡢࡀࡺࡗࡃࡾ࡜ືࡃࡼ࠺࡟ぢ࠼ ࡿ▱ぬ⌧㇟࡛࠶ࡿ6,7,8,9㸧㸦ᅗ㸯㸧㸬ࡇࡢࡼ࠺࡟▱ ぬ≉ᛶ࡟ኚ໬ࢆࡶࡓࡽࡍ㐠ື่⃭ࢆ㡰ᛂ่⃭࡜ ࿧ࡪ㸬2 ࡘࡢ୪㐍㐠ືࣃࢱ࣮ࣥࡀ␗࡞ࡿ᪉ྥ࡟㐠 ືࡍࡿࡼ࠺࡞㡰ᛂ่⃭㸦㔜␚㐠ື่⃭㸧ࢆ୚࠼ ࡓ᫬ࡢ㐠ືṧຠࡢ▱ぬ᪉ྥࡣ㸪2 ࡘࡢ୪㐍㐠ືࡢ ࣋ࢡࢺࣝຍ⟬᪉ྥࡢ㏫᪉ྥ࡛࠶ࡿࡇ࡜ࡀ▱ࡽࢀ ࡚࠸ࡿ6,7,9,10,11㸧㸬ࡋࡓࡀࡗ࡚㸪㐠ືṧຠࡢ᪉ྥࡣ㸪 ࿊♧ࡉࢀࡓ」ᩘࡢ㐠ືࣃࢱ࣮ࣥࡢ᝟ሗࡀ⤫ྜࡉ ࢀࡓ⤖ᯝࢆ♧ࡍࡇ࡜࡟࡞ࡿ㸬

㸰㸬┠ⓗ

 ᮏ◊✲࡛ࡣ㸪ど㔝ୖ࡟」ᩘࡢᗈど㔝㐠ື่⃭ ࡀ㔜␚ࡍࡿ࡜ࡁ㸪࡝ࡢࡼ࠺࡞㐠ື᝟ሗࡢ⤫ྜࡀ Ꮡᅾࡍࡿ࠿ࢆ㸪ࣄࢺࡢ㐠ືṧຠ▱ぬ≉ᛶࢆゎᯒ ࡍࡿࡇ࡜࡟ࡼࡾ⪃ᐹࡋࡓ㸬≉࡟㸪␗࡞ࡿࢫࣆ࣮ ࢻ࡜᪉ྥࢆ᭷ࡍࡿ⊂❧ࡋࡓ୪㐍㐠ື࠿ࡽ࡞ࡿ㔜 ␚㐠ື่⃭ࣃࢱ࣮ࣥ࡟ᑐࡋ࡚㸪ྛࣃࢱ࣮ࣥࡢ㐠 ື᪉ྥࡀ࣋ࢡࢺࣝຍ⟬ⓗ࡟⤫ྜࡉࢀ࡚࠸ࡿࡢ࠿ ྰ࠿࡟ࡘ࠸࡚ヲ⣽࡟᳨ウࡍࡿࡇ࡜࡟ࡋࡓ㸬ࡑࡋ ࡚㸪ᗈど㔝㐠ື᝟ሗࡀ⬻ෆ࡛࡝ࡢࡼ࠺࡟᝟ሗ⾲ ⌧ࡉࢀ࡚࠸ࡿ࠿࡟ࡘ࠸࡚ࡶ⪃ᐹࡋࡓ㸬 㸱 㸱㸬ᐇ㦂᪉ἲ ௨ୗ࡟♧ࡍᐇ㦂ࡣ㸪ᡂே⏨ᛶ4 ྡࡢ⿕㦂⪅ࢆ ᑐ㇟࡜ࡋࡓ㸬ᐇ㦂࡟౑⏝ࡉࢀࡿ㡰ᛂ่⃭࠾ࡼࡧ ࢸࢫࢺ่⃭࡟㛵ࡋ࡚ࡣ㸪VisualC ࡜ OpenGL ࢆ⏝ ࠸࡚సᡂࡋ㸪ࡑࢀࡽࡢ่⃭ࣃࢱ࣮ࣥࢆ⿕㦂⪅ࡢ ๓㠃࡟㓄⨨ࡋࡓࢹ࢕ࢫࣉ࣮ࣞ࡟࿊♧ࡋࡓ㸬่⃭ ࣃࢱ࣮ࣥࡢど㔝ゅࡣ67r™52r࡜ࡋࡓ㸬 ᐇ㦂㸯㸸㸯᪉ྥᗈど㔝㐠ື่⃭࡟ࡼࡿ㐠ືṧຠ ࡢࢫࣆ࣮ࢻ౫Ꮡᛶ 㡰ᛂ่⃭ࣃࢱ࣮ࣥࡣ୍᪉ྥ࡟୪㐍㐠ືࡍࡿࣛ ࣥࢲ࣒ࢻࢵࢺࣃࢱ࣮ࣥ࡜ࡋࡓ㸦ᅗ㸯㸧㸬⏬㠃ෆࡢ ࢻࢵࢺᩘࡣ100 ಶ࡜ࡋ㸪㡰ᛂ่⃭ࡢࢫࣆ࣮ࢻࡣ 4.0r/sec ࠿ࡽ 48.0r/sec ࡲ࡛ 5 ẁ㝵࡟タᐃࡋࡓ㸬 30 ⛊㛫㡰ᛂ่⃭ࣃࢱ࣮ࣥࢆ࿊♧ࡋࡓࡢࡕࢸࢫ ࢺ่⃭ࣃࢱ࣮ࣥ㸦㟼Ṇࣃࢱ࣮ࣥ㸧ࢆ࿊♧ࡋ㸪⿕ 㦂⪅ࡣ▱ぬࡉࢀࡓ㐠ືṧຠࡢᣢ⥆᫬㛫࡜㐠ື᪉ ྥࢆᅇ⟅ࡋࡓ㸬 ᅗ㸯 㐠ືṧຠࡢㄝ᫂ᅗ

㐠ື่⃭࿊♧㻌㻌

㟼Ṇ㻌

㐠ືṧຠ▱ぬ㻌

(3)

ᐇ㦂2㸸2 ᪉ྥᗈど㔝㔜␚㐠ື่⃭࡟ࡼࡿ㐠ືṧ ຠ≉ᛶ 㡰ᛂ่⃭ࣃࢱ࣮ࣥࡣ2 ⩌ࡢ⊂❧ࡋࡓ୪㐍㐠ື ࠿ࡽ࡞ࡿ㔜␚่⃭ࣃࢱ࣮࡛ࣥ࠶ࡿ㸦ᅗ2㸧㸬่⃭ ࣃࢱ࣮ࣥࡢࢻࢵࢺᩘࡣྛ㐠ື⩌࡟ࡘ࠸࡚100 ಶ ࡎࡘ࡜ࡋࡓ㸬ྛ㐠ື⩌ࡢࢫࣆ࣮ࢻࡣ8.0r/sec ࡜ 32.0r/sec ࡢ࠺ࡕ࡝ࡕࡽ࠿ࢆ㑅ᢥࡋ㸪2 ⩌ࡢࢫࣆ ࣮ࢻࡀྠ୍ࡢሙྜ࡜㸪୍᪉ࡀ㏿ࡃ௚᪉ࡀ㐜࠸ሙ ྜ࡜ࢆタᐃࡋࡓ㸬ࡲࡓ㸪㔜␚่⃭ࢆᵓᡂࡍࡿ୪ 㐍㐠ືࡢ᪉ྥࡣྑ᪉ྥ࡜ୖ᪉ྥ࡟ᐃࡵࡓ㸬 ⿕㦂⪅࡟ࡣ30 ⛊㛫㡰ᛂ่⃭ࢆ୚࠼ࡓᚋ㸪㟼 Ṇࣃࢱ࣮ࣥࢆ࿊♧ࡋ࡚▱ぬࡉࢀࡓ㐠ືṧຠࡢ᪉ ྥ࡜ᣢ⥆᫬㛫ࢆᅇ⟅ࡋ࡚ࡶࡽࡗࡓ㸬 ᐇ㦂3㸸3 ᪉ྥ㔜␚ᗈど㔝㐠ື่⃭࡟ࡼࡿ㐠ືṧ ຠ≉ᛶ 㡰ᛂ่⃭ࣃࢱ࣮ࣥࡣ3 ⩌ࡢ⊂❧ࡋࡓ୪㐍㐠ື ࠿ࡽ࡞ࡿ㔜␚㐠ືࣃࢱ࣮࡛ࣥ࠶ࡿ㸦ᅗ3㸧㸬่⃭ ࣃࢱ࣮ࣥࢆᵓᡂࡍࡿࢻࢵࢺᩘࡣྛ㐠ື⩌࡟ࡘࡁ 100 ಶࡎࡘ࡜ࡋࡓ㸬ྛ㐠ື⩌ࡢࢫࣆ࣮ࢻࡣᐇ㦂 2 ࡜ྠᵝ㸪8.0r/sec ࡜ 32.0r/sec ࡢ࠺ࡕࡢ࡝ࡕࡽ ࠿ࢆ㑅ᢥࡋࡓ㸬ࡲࡓ㸪3 ⩌ࡢ୪㐍㐠ືࡢ㐠ື᪉ྥ ࡟ࡘ࠸࡚ࡣ㸪ᅗ3 ࡟♧ࡍ 3 ✀㢮ࡢ⤌ࡳྜࢃࡏ࡜ ࡋࡓ㸬ᐇ㦂㸯࡜ྠᵝ࡟㸪⿕㦂⪅࡟ࡣ30 ⛊㛫㡰ᛂ ่⃭ࢆ୚࠼ࡓᚋ㸪㟼Ṇࣃࢱ࣮ࣥࢆ࿊♧ࡋ࡚▱ぬ ࡉࢀࡓ㐠ືṧຠࡢ᪉ྥ࡜ᣢ⥆᫬㛫ࢆᅇ⟅ࡋ࡚ࡶ ࡽࡗࡓ㸬 ᐇ㦂4㸸ࢥࣄ࣮ࣞࣥࢺ್ࡢ␗࡞ࡿ 3 ᪉ྥ㔜␚ᗈど 㔝㐠ື่⃭࡟ࡼࡿ㐠ືṧຠ≉ᛶ  㡰ᛂ่⃭ࢆᵓᡂࡍࡿ3 ⩌ࡢ୪㐍㐠ືࡢ࠺ࡕ㸪 ࡦ࡜ࡘࡢ୪㐍㐠ືࡢࢥࣄ࣮ࣞࣥࢺ್ࢆ0.1 ࠿ࡽ 0.8 ࡲ࡛ 8 ẁ㝵࡟タᐃࡋࡓ㸬ࢥࣄ࣮ࣞࣥࢺ್࡜ࡣ ୍ᐃ᪉ྥ࡟㐠ືࡍࡿ୪㐍㐠ືࡢ୰୍࡛ᐃ᪉ྥ࡟ 㐠ືࡍࡿࢻࢵࢺࡢ๭ྜࢆ♧ࡍ㸬ࡓ࡜࠼ࡤ㸪ࣃࢱ ࣮ࣥࢆᵓᡂࡍࡿࢻࢵࢺᩘࡀ100 ಶ࠶ࡾ㸪ࡇࡢࣃ ࢱ࣮ࣥࡢࢥࣄ࣮ࣞࣥࢺ್ࡀ0.5 ࡢሙྜ࡟ࡣ㸪100 ಶࡢࢻࢵࢺࡢ࠺ࡕ50 ಶࡀ୍ᐃ᪉ྥ࡬㐠ືࡍࡿࡀ㸪 ௚ࡢ50 ಶࡣࡑࢀࡒࢀࡀ௚ࡢࢻࢵࢺ࡜ࡣ⊂❧࡟ࣛ ࣥࢲ࣒࡞᪉ྥ࡬࡜㐠ືࡍࡿࡇ࡜ࢆ࠶ࡽࢃࡋ࡚࠸ ࡿ㸬ࡋࡓࡀࡗ࡚㸪୪㐍㐠ືࣃࢱ࣮ࣥࡢࢥࣄ࣮ࣞ ࣥࢺ್ࡀ኱ࡁ࠸࡯࡝୍ᐃ᪉ྥ࡬ࡢ㐠ືᡂศࡀከ ࠸ࡓࡵ㸪⿕㦂⪅࡟ࡣࡼࡾᙉ࠸㐠ື▱ぬࢆࡶࡓࡽ ࡍࡇ࡜࡟࡞ࡿ㸬  㡰ᛂ่⃭ࢆᵓᡂࡍࡿ௚ࡢ2 ⩌ࡢ୪㐍㐠ື࡟ࡘ ࠸࡚ࡣࡍ࡭࡚ࡢࢻࢵࢺࡀ୍ᐃ᪉ྥ࡬ືࡃ㸪ࡍ࡞ ࢃࡕࢥࣄ࣮ࣞࣥࢺ್ࡀ1.0 ࡢ୪㐍㐠ື࡜ࡋࡓ㸬 ᅗ2 2 ᪉ྥ㔜␚㐠ືࡢㄝ᫂ᅗ

3 ᐇ㦂࡟౑⏝ࡋࡓ㐠ືࣃࢱ࣮ࣥ

ࣃࢱ࣮ࣥ $㻌 ࣃࢱ࣮ࣥ %㻌 ࣃࢱ࣮ࣥ &㻌

(4)

 ୖグࡢࡼ࠺࡞㡰ᛂ่⃭ࢆ30 ⛊㛫⿕㦂⪅࡟࿊♧ ࡋࡓ㸬ࡑࡢᚋ࡛㟼Ṇࣃࢱ࣮ࣥࢆ࿊♧ࡋ࡚▱ぬࡉ ࢀࡿ㐠ືṧຠࡢ᪉ྥ࡜ᣢ⥆᫬㛫ࢆㄪ࡭ࡓ㸬

㸲㸬ᐇ㦂⤖ᯝ࡜⪃ᐹ

ᐇ㦂1㸸1 ᪉ྥᗈど㔝㐠ື่⃭࡟ࡼࡿ㐠ືṧຠࡢ ࢫࣆ࣮ࢻ౫Ꮡᛶ 1 ᪉ྥࡢᗈど㔝㐠ື่⃭㸦㡰ᛂ่⃭㸧࡟ࡼࡿ㐠 ືṧຠࡢ᪉ྥࡣ㸪㡰ᛂ่⃭ࡢ㏫᪉ྥ࡛࠶ࡗࡓ㸬 ࡲࡓ㸪㐠ືṧຠࡢᣢ⥆᫬㛫ࡣ㡰ᛂ่⃭ࡢࢫࣆ࣮ ࢻ࡟ࡼࡗ࡚␗࡞ࡿ࡞ࡿࡇ࡜ࡀุ᫂ࡋࡓ㸬ࡑࡢ⤖ ᯝࢆᅗ㸲࡟♧ࡍ㸬ࢢࣛࣇࡣ⿕㦂⪅4 ྡࡢᖹᆒ್ ࡛♧ࡋ࡚࠶ࡿ㸬㡰ᛂ่⃭ࢫࣆ࣮ࢻࡀ4.0r/sec ࡢ ࡜ࡁ࡟ࡣ㸪ᣢ⥆᫬㛫ࡣ5.5 ⛊࡛࠶ࡿࡀ㸪㡰ᛂ่⃭ ࡢࢫࣆ࣮ࢻࡀ8.0r/sec ࡛ࡣ㸪ᣢ⥆᫬㛫ࡣ 7.0 ⛊ ࡟ቑຍࡋࡓ㸬ࢫࣆ࣮ࢻࢆ16r/sec ࡲ࡛ୖࡆࡿ࡜㸪 ᣢ⥆᫬㛫ࡣ4.4 ⛊ࡲ࡛ῶᑡࡋ㸪ࡉࡽ࡟ࢫࣆ࣮ࢻࢆ ୖࡆࡓሙྜ࡟ࡣ㸪ᣢ⥆᫬㛫ࡣᚎࠎ࡟ῶᑡࡍࡿഴ ྥ࡟࠶ࡗࡓ㸬ࡍ࡞ࢃࡕ㸪㐠ືṧຠࡢᣢ⥆᫬㛫ࡣ 8.0r/sec ࡢ㡰ᛂ่⃭࡛᭱኱್ࢆ♧ࡋࡓ㸬 㐠ືṧຠࡢᣢ⥆᫬㛫ࡀ㛗࠸ࡢࡣ㸪㡰ᛂ่⃭ࡀ ࡼࡾᙉ࠸ṧຠຠᯝࢆ୚࠼ࡓ࠿ࡽࡔ࡜ゎ㔘࡛ࡁࡿ㸬 ࡋࡓࡀࡗ࡚㸪ᅗ4 ࡟♧ࡍ⤖ᯝࡣ㸪㐜ࡃືࡃࣃࢱ ࣮ࣥࡢ᪉ࡀࡼࡾᙉ࠸㐠ືṧຠࢆࡶࡓࡽࡍࡇ࡜ࢆ ♧ࡋ࡚࠸ࡿ㸬࡞ࡐ㐜࠸㐠ືࣃࢱ࣮ࣥࡢ᪉ࡀࡼࡾ ᙉ࠸㐠ືṧຠࢆ⏕ࡎࡿࡢ࠿࡟ࡘ࠸࡚㸪ḟࡢ⌮⏤ ࡀ⪃࠼ࡽࢀࡿ㸬ࡍ࡞ࢃࡕ㸪㐠ືṧຠࡣᴟࡵ࡚ࡺ ࡗࡃࡾࡋࡓ㐠ື▱ぬ࡛࠶ࡾ㸪ࡇࡢࡼ࠺࡞㐠ືឤ ぬࡣ㐜࠸ࢫࣆ࣮ࢻࢆ᭱㐺ࢫࣆ࣮ࢻ࡜ࡋ࡚࠸ࡿ᪉ ྥ㑅ᢥᛶ⣽⬊ࡀᢸࡗ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿ㸬ࡋࡓ ࡀࡗ࡚㸪㐜࠸㡰ᛂ่⃭ࡣ㐜࠸㐠ືࢆࢥ࣮ࢹ࢕ࣥ ࢢࡍࡿ⣽⬊ࡢឤᗘࢆࡼࡾపୗࡉࡏࡿࡀࡓࡵ࡟㸪 㐜࠸㡰ᛂ่⃭࡟ࡼࡿ㐠ືṧຠ᫬㛫ࡣ㸪ࡼࡾ㛗ࡃ ࡞ࡿࡢ࡛ࡣ࡞࠸࠿࡜⪃࠼ࡽࢀࡿ㸬 ௨ୗࡢᐇ㦂࡛ࡣ㸪ࡇࡢࡼ࠺࡞㐠ືṧຠࡢ㡰ᛂ ่⃭ࢫࣆ࣮ࢻ౫Ꮡᛶࢆ⪃៖ࡋ࡞ࡀࡽ㡰ᛂ่⃭ࢆ 㑅ᢥࡋࡓ㸬 ᐇ㦂2㸸2 ᪉ྥᗈど㔝㔜␚㐠ື่⃭࡟ࡼࡿ㐠ືṧ ຠ≉ᛶ ᭱ึ࡟㸪2 ᪉ྥ㔜␚㐠ືࢆᵓᡂࡍࡿ୪㐍㐠ືࡢ ࢫࣆ࣮ࢻࡀྠ୍ࡢሙྜࢆ᳨ウࡋࡓ㸬ࡍ࡞ࢃࡕ㸪 ୪㐍㐠ືࡢࢫࣆ࣮ࢻࡢ⤌ࡳྜࢃࡏ࡜ࡋ࡚ࡣ㸪୧ ୪㐍㐠ື࡜ࡶ࡟8.0r/sec ࡢሙྜ࡜ 16.0r/sec ࡢ ሙྜ࡟ࡘ࠸࡚ᐇ㦂ࢆ⾜ࡗࡓ㸬⤖ᯝࢆᅗ5 ࡟♧ࡍ㸬 ࡇࡢᅗ࡛ࡣ㸪ྑ᪉ྥ࡬ࡢ୪㐍㐠ື㸦ࢫࣆ࣮ࢻ 8.0r/sec㸧࡜ୖ᪉ྥ࡬ࡢ୪㐍㐠ື㸦ࢫࣆ࣮ࢻ 8.0r ᅗ4 㡰ᛂ่⃭㏿ᗘ࡜㐠ືṧຠᣢ⥆᫬㛫

㡰ᛂ่⃭㻌

㐠ືṧຠ㻌

ᅗ5 2 ᪉ྥ㔜␚㐠ື่⃭࡜㐠ືṧຠ

(5)

/sec㸧ࡀ⏬㠃ୖ࡟㔜␚ࡋ࡚࠸ࡿ㸬ࡇࢀࡽࡢ㐠ື࣋ ࢡࢺࣝࢆຍ⟬ࡋࡓࡶࡢࡀᅗ㸳ୗࡢⓑᢤࡁ࣋ࢡࢺ ࡛ࣝ࠶ࡿࡀ㸪㐠ືṧຠࡢ᪉ྥࡣⓑᢤࡁ࣋ࢡࢺࣝ ࡢ㏫᪉ྥ࡛࠶ࡗࡓ㸦⅊Ⰽ࣋ࢡࢺࣝ㸧㸬୧୪㐍㐠ື ࡢࢫࣆ࣮ࢻࡀ16.0rࡢሙྜ࡟ࡶ㸪㏿ᗘ࣋ࢡࢺࣝ ࢆຍ⟬ࡍࡿ࡜ྑୖ45r᪉ྥ࡜࡞ࡿࡀ㸪㐠ືṧຠ ࡢ᪉ྥࡣᕥୗ45r᪉ྥ㸪ࡍ࡞ࢃࡕ㸪ຍ⟬࣋ࢡࢺ ࣝࡢ㏫᪉ྥ࡟࠶ࡽࢃࢀࡓ㸬 ࡇࢀࡽࡢ⤖ᯝࡣ㸪2 ࡘࡢ୪㐍㐠ືࡢࢫࣆ࣮ࢻࡀ ྠ୍ࡢሙྜ࡟ࡣ㸪2 ࡘࡢ୪㐍㐠ືࡀྠ᫬࡟࿊♧ࡉ ࢀࡓ࡜ࡁ㸪୧㐠ືࡢ࣋ࢡࢺࣝຍ⟬⤫ྜࡀ࠾ࡇ࡞ ࢃࢀࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿ㸬 ࡘࡂ࡟㸪୍᪉ࡀ16.0r/sec㸪௚᪉ࡣ 32.0r/sec ࡛㐠ືࡍࡿ୪㐍㐠ືࡢ㐠ືṧຠࡢ⤖ᯝࡣ㸪ᅗ6 ࡢࡼ࠺࡞࣋ࢡࢺࣝᅗ࡜࡞ࡗࡓ㸬ᅗ୰㸪2 ࡘࡢ୪㐍 㐠ື࣋ࢡࢺࣝࡣ㯮࣋ࢡࢺ࡛ࣝ㸪ࡑࢀࡽࡢຍ⟬࣋ ࢡࢺࣝࡣⓑᢤࡁ࣋ࢡࢺ࡛ࣝ⾲♧ࡉࢀ࡚࠸ࡿ㸬ࡇ ࡢ࡜ࡁ⅊Ⰽ࣋ࢡࢺ࡛ࣝ⾲♧ࡉࢀࡿ㐠ືṧຠࡢ᪉ ྥࡣ㸪ຍ⟬࣋ࢡࢺࣝࡢ㏫᪉ྥ࡟⏕ࡌࡓ㸬ࡋࡓࡀ ࡗ࡚ࠊ㐠ືṧຠᣢ⥆᫬㛫ࡀ࡯ࡰྠ୍ࡢሙྜ࡟ࡣ㸪 㸰ࡘࡢ୪㐍㐠ື࡟ᑐࡋ࡚ࢫࣆ࣮ࢻ᝟ሗࡶྵࡵࡓ ࣋ࢡࢺࣝ⤫ྜฎ⌮ࡀ⾜ࢃࢀࡿ࡜⪃࠼ࡽࢀࡿ㸬 ࡉࡽ࡟㸪୍᪉ࡢࢫࣆ࣮ࢻࡀ8.0r/sec㸪௚᪉ࡀ 16.0r/sec ࡢሙྜࢆ᳨ウࡋࡓ㸬ࡇࡢ᮲௳ࡣ㸪୪㐍 㐠ືࡢࢫࣆ࣮ࢻẚ࡜ࡋ࡚ࡣඛ࡯࡝࡜ྠᵝ1:2 ࡛ ࠶ࡿࡀ㸪ᅗ4 ࡟♧ࡍࡼ࠺࡟㸪8.0r/sec ࡢ୪㐍㐠 ືࡣ16.0rࡢ୪㐍㐠ືࡼࡾࡶ 1.5 ಸ࡯࡝㐠ືṧ ຠᣢ⥆᫬㛫ࡀ㛗࠸㸬ࡇࡢሙྜ࡟ࡶඛ࡯࡝࡜ྠᵝ㸪 ᅗ6 ࡢࡼ࠺࡞࣋ࢡࢺࣝຍ⟬ࡀᡂ❧ࡍࡿ࠿ࢆ᳨ウ ࡋࡓ㸬⿕㦂⪅4 ྡ࡜ࡶ࡟࡯ࡰྠᵝࡢ⤖ᯝ࡜࡞ࡗ ࡓࡀ㸪ᅗ7 ࡣࡑࡢ୰ࡢ௦⾲౛ࢆ♧ࡋࡓࡶࡢ࡛࠶ ࡿ㸬ᅗ୰㸪ⓑᢤࡁ࣋ࢡࢺࣝࡣ㸰ࡘࡢ୪㐍㐠ື࣋ ࢡࢺࣝࢆຍ⟬ࡋࡓࡶࡢ࡛࠶ࡿࡀ㸪㐠ືṧຠࡢ᪉ ྥ㸦⅊Ⰽ࣋ࢡࢺࣝ㸧ࡣୗྥࡁ࡟㏆࠸250r᪉ྥ࡜ ࡞ࡗࡓ㸬ࡇࡢ᪉ྥࡣຍ⟬᪉ྥࡢ㏫᪉ྥ࠿ࡽࡣ኱ ࡁࡃእࢀ࡚࠸ࡿ㸬ࡑࢀ࡛ࡣ㸪▱ぬࡉࢀࡓ㐠ືṧ ຠࡢ᪉ྥࡣ㸪2 ࡘࡢ㐠ື࣋ࢡࢺࣝࢆ࡝ࡢࡼ࠺࡟⤫ ྜࡍࢀࡤᚓࡽࢀࡿࡢ࡛࠶ࢁ࠺࠿㸬 ࡇࡇ࡛㐠ືṧຠᣢ⥆᫬㛫ࡢ㛗࠸㐠ື่⃭ࡢ᪉ ࡀ㐠ືṧຠ࡟ᑐࡍࡿᐤ୚ࡀ኱ࡁ࠸࡜⪃࠼㸪ࡑࡢ 㐠ື࣋ࢡࢺࣝࡢ㛗ࡉࢆㄪᩚࡋ㸦㔜ࡳ࡙ࡅࢆ⾜࠸㸧㸪 ᐇ㝿ࡼࡾࡶ㛗࠸࣋ࢡࢺ࡛ࣝ⾲♧ࡍࡿ㸬ࡇࡢ࣋ࢡ ࢺࣝ࡜௚᪉ࡢ࣋ࢡࢺࣝ࡜ࢆຍ⟬ࡋ㸪ࡑࡢ㏫᪉ྥ ࢆㄪ࡭ࡿ࡜㸪࡯ࡰᐇ㝿ࡢ㐠ືṧຠࡢ᪉ྥ࡜୍⮴ ࡋࡓ㸬௨ୖࡢ⪃ᐹࡼࡾ㸪୪㐍㐠ື࣋ࢡࢺࣝࢆ㐠 ື᪉ྥ࡜ࢫࣆ࣮ࢻࢆ࠶ࡽࢃࡍࡶࡢ࡜ᤊ࠼ࡿࡢ࡛ ࡣ࡞ࡃ㸪㐠ືṧຠࡢᣢ⥆᫬㛫ࡢ㛗ࡉࢆ㐠ືṧຠ ࡬ࡢᐤ୚ࡢ኱ࡁࡉ࡜⪃࠼㸪ࡑࢀࢆ࣋ࢡࢺࣝࡢ㛗 ࡉ࡜ゎ㔘ࡍࡿ㸬ࡑ࠺ࡍࢀࡤ㸪2 ᪉ྥ㔜␚่⃭࡟ࡼ ࡿ㐠ືṧຠࡢ᪉ྥࡣ㸪㔜ࡳ࡙ࡅࢆ࠾ࡇ࡞ࡗࡓ2 ࡘࡢ୪㐍㐠ື࣋ࢡࢺࣝࡢ⤫ྜ᪉ྥࡢ㏫᪉ྥ࡟࠶ ࡽࢃࢀࡿ࡜⪃࠼ࡿࡇ࡜ࡀ࡛ࡁࡿ㸬 ᅗ6 2 ᪉ྥ㔜␚่⃭࡜㐠ືṧຠ

rVHF㻌

rVHF㻌

ձ㻌

ղ㻌

ᅗ7 2 ᪉ྥ㔜␚่⃭࡜㐠ືṧຠ

rVHF㻌

rVHF㻌

ձ㻌

ղ㻌

(6)

ᐇ㦂3㸸3 ᪉ྥ㔜␚ᗈど㔝㐠ື่⃭࡟ࡼࡿ㐠ືṧ ຠ≉ᛶ  ᐇ㦂࡟⏝࠸ࡓ3 ᪉ྥ㔜␚㐠ື่⃭ࡢ᪉ྥࡢ⤌ ࡳྜࢃࡏࡣ㸪ᅗ3 ࡢࣃࢱ࣮ࣥ A㸪ࣃࢱ࣮ࣥ B㸪 ࠾ࡼࡧࣃࢱ࣮ࣥC ࡜ࡋࡓ㸬  ࣃࢱ࣮ࣥA ࢆᵓᡂࡍࡿ୪㐍㐠ືࡢࢫࣆ࣮ࢻࡀ ྠ୍ࡢሙྜࡣ㸪࡝ࡢࢫࣆ࣮ࢻࢆ⏝࠸࡚ࡶ㐠ືṧ ຠࡣ࠶ࡽࢃࢀ࡞࠿ࡗࡓ㸬ࣃࢱ࣮ࣥA ࡛ࡣ 3 ᪉ྥ ࡑࢀࡒࢀࡢࢫࣆ࣮ࢻࡀྠ୍㸪ࡍ࡞ࢃࡕ㸪࣋ࢡࢺ ࣝࡢ㛗ࡉࡀྠ୍ࡢሙྜ࡟ࡣ㸪3 ࡘࡢ࣋ࢡࢺࣝࢆຍ ⟬ࡍࢀࡤࢮࣟ࡟࡞ࡿ㸬ࡋࡓࡀࡗ࡚㸪㐠ືṧຠࡀ ▱ぬࡉࢀ࡞࠸ࡢࡣ㸪㔜␚่⃭ࢆᵓᡂࡍࡿ3 ࡘࡢ 㐠ື᝟ሗࢆṇ☜࡟࣋ࢡࢺࣝຍ⟬⤫ྜࡋ࡚࠸ࡿ࠿ ࡽ࡛ࡣ࡞࠸࠿࡜⪃࠼ࡽࢀࡿ㸬  ḟ࡟㸪ࣃࢱ࣮ࣥA ࡟࠾࠸࡚㸪୪㐍㐠ື߇ࡢࢫ ࣆ࣮ࢻࢆ8r/sec㸪୪㐍㐠ືղ࡜୪㐍㐠ືճࡢࢫ ࣆ࣮ࢻࢆ40r/sec ࡜ࡋࡓ᫬ࡢ㐠ືṧຠࡢ᪉ྥࡣ㸪 ᅗ8 ࡢ⅊Ⰽ࣋ࢡࢺ࡛ࣝ♧ࡍ᪉ྥ࡜࡞ࡗࡓ㸬ࡍ࡞ ࢃࡕ㸪㐠ືṧຠࡣ㐜࠸ࢫࣆ࣮ࢻ࡛ືࡃ୪㐍㐠ື ߇ࡢ㏫᪉ྥ࡟࠶ࡽࢃࢀࡓ㸬ࡇࡢ⤖ᯝࡣ㸪ᅗ8 ᕥ ࡟♧ࡍ㏿ᗘ࣋ࢡࢺࣝຍ⟬ᅗ࠿ࡽࡣ෌⌧࡛ࡁ࡞࠸㸬 ࡋ࠿ࡋ㸪୪㐍㐠ື߇ࡢ㐠ືṧຠ᫬㛫ࡀ㛗࠸ࡇ࡜ ࢆ⪃៖ࡋ࡚୪㐍㐠ື߇ࡢ࣋ࢡࢺࣝ࡟㔜ࡳ௜ࡅࢆ ࠾ࡇ࡞࠸㸪෌ᗘ3 ࡘࡢ࣋ࢡࢺࣝࢆຍ⟬ࡋ࡚ࡳࡿ ࡜㸪㐠ືṧຠ࣋ࢡࢺࣝࡢ㏫࣋ࢡࢺࣝ࡜࡞ࡿࡇ࡜ ࡀࢃ࠿ࡗࡓ㸦ᅗ8 ྑ㸧㸬ࡍ࡞ࢃࡕ㸪3 ᪉ྥࡢ୪㐍 㐠ື࡟ᑐࡋ࡚ࡶ2 ᪉ྥ㔜␚୪㐍㐠ືࡢ࡜ࡁ࡜ྠ ᵝ㸪ከ᪉ྥ୪㐍㐠ື᝟ሗࡢ࣋ࢡࢺࣝຍ⟬⤫ྜࡀ ࠾ࡇ࡞ࢃࢀࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿ㸬  ḟ࡟ࣃࢱ࣮ࣥB ࡟ࡘ࠸࡚ࡶ㸪࣋ࢡࢺࣝຍ⟬⤫ ྜࡀᡂ❧ࡋ࡚࠸ࡿ࠿ࢆㄪ࡭ࡓ㸬ࣃࢱ࣮ࣥB ࡢ 3 ࡘࡢ୪㐍㐠ືࡢࢫࣆ࣮ࢻࡣྠ୍࡜ࡋ㸪㐠ື᪉ྥ ࡣᅗ9 ࡟♧ࡍ᪉ྥ࡜ࡋࡓ㸬ࡇࡢ࡜ࡁ㸪㐠ືṧຠ ࡢ᪉ྥࡣ࡯ࡰᕥୗ225rࡢ᪉ྥ࡛࠶ࡗࡓ㸦ᅗ 9 ࡢ⅊Ⰽ࣋ࢡࢺࣝ㸧㸬㔜␚㐠ືࢆᵓᡂࡍࡿ3 ࡘࡢ୪ 㐍㐠ື࣋ࢡࢺࣝ㸦኱ࡁࡉ

v

v

㸧ࢆຍ⟬ࡍࡿ࡜࣋ࢡ ࢺࣝࡢ㛗ࡉࡣ

( 2 1) v



v

࡜࡞ࡾ㸪࣋ࢡࢺࣝࡢ᪉ ྥࡣ45r᪉ྥ࡜࡞ࡿ㸬ࡇࡢ࣋ࢡࢺࣝࡢ㏫࣋ࢡࢺ ࣝ᪉ྥࡣᕥୗ225r᪉ྥ࡛࠶ࡾ㐠ືṧຠࡢ᪉ྥ ࡜୍⮴ࡍࡿ㸬ࡋࡓࡀࡗ࡚㸪ࣃࢱ࣮ࣥB ࡟ࡘ࠸࡚ ࡶ࣋ࢡࢺࣝຍ⟬ࡀᡂ❧ࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿ㸬  ᭱ᚋ࡟ࣃࢱ࣮ࣥC ࡟ࡘ࠸࡚ㄪ࡭ࡓࡀ㸪ண᝿㏻ ࡾ㸪㐠ືṧຠࡢ᪉ྥࡣ୪㐍㐠ືղࡢ㏫᪉ྥ࡛࠶ ࡗࡓ㸬ࣃࢱ࣮ࣥC ࡛ࡣ୪㐍㐠ື߇࡜୪㐍㐠ືճ ࡣ஫࠸࡟㏫᪉ྥ࡟㐠ືࡍࡿࡓࡵ㸪㐠ື࣋ࢡࢺࣝ ࢆຍ⟬ࡍࢀࡤࢮࣟ࡜࡞ࡿ㸬ࡋࡓࡀࡗ࡚㸪㐠ືṧ ຠ࡟ᐤ୚ࡍࡿࡢࡣ୪㐍㐠ືղ࡜࡞ࡿࡓࡵ㸪㐠ື ṧຠࡢ᪉ྥࡣ㸪୪㐍㐠ືղࡢ㏫᪉ྥ࡜࡞ࡿ㸬 ᅗ8 3 ᪉ྥ㔜␚㐠ື࡜㐠ືṧຠ

㏿ᗘ࣋ࢡࢺࣝ ᐇ㝿ࡢ⤖ᯝ



㔜ࡳ௜ࡅࡋࡓ࣋ࢡࢺࣝ 㐠ືṧຠ᪉ྥ㸦⅊Ⰽ࣋ࢡࢺࣝ㸧 ᅗ9 3 ᪉ྥ㔜␚㐠ື࡜㐠ືṧຠ

(7)

ᐇ㦂4㸸ࢥࣄ࣮ࣞࣥࢺ್ࡢ␗࡞ࡿ 3 ᪉ྥ㔜␚ᗈど 㔝㐠ື่⃭࡟ࡼࡿ㐠ືṧຠ≉ᛶ ᐇ㦂3 ࡟࠾࠸࡚㸪ࣃࢱ࣮ࣥ A ࢆᵓᡂࡍࡿ୪㐍 㐠ືࡢࢫࣆ࣮ࢻࡀྠ୍ࡢሙྜ࡟ࡣ㸪㐠ືṧຠࡣ ⏕ࡌ࡞࠿ࡗࡓ㸬ࡑࡢ⌮⏤ࡣ㸪3 ࡘࡢ୪㐍㐠ື࣋ࢡ ࢺࣝࢆຍ⟬ࡍࡿ࡜ࢮࣟ࡟࡞ࡿ࠿ࡽ࡛࠶ࡗࡓ㸬ࡶ ࡋ㸪3 ࡘࡢ୪㐍㐠ືࡀ࣋ࢡࢺࣝຍ⟬⤫ྜࡉࢀࡿࡢ ࡛࠶ࢀࡤ㸪3 ᪉ྥ୪㐍㐠ືࡢ࠺ࡕࡢ 1 ࡘࡀ௚ࡢ 2 ࡘࡢ㐠ືࡼࡾࡶ㐠ືᡂศ㔞ࡀᑡ࡞࠸ሙྜ࡟ࡣ㸪 㐠ືᡂศ㔞ࡢᑡ࡞࠸㐠ືࡣ㸪࣋ࢡࢺࣝࡢ኱ࡁࡉ ࡀ௚ࡢ2 ࡘࡼࡾᑠࡉࡃ࡞ࡿ࡜⪃࠼ࡽࢀࡿ㸬ࡋࡓ ࡀࡗ࡚㸪3 ࡘࡢ㐠ື࣋ࢡࢺࣝࢆຍ⟬ࡋ࡚ࡶࢮࣟ࡟ ࡣ࡞ࡽࡎ㸪ࡑࡢࡓࡵ࡟㸪㐠ືᡂศ㔞ࡢᑠࡉ࠸㐠 ື᪉ྥ࡬ࡢ㐠ືṧຠࡀ▱ぬࡉࢀࡿ࡜ண ࡉࢀࡿ㸬 ᐇ㦂4 ࡛ࡣ㸪ࡇࡢண ࢆ᳨ドࡍࡿࡓࡵ࡟㸪ࣃ ࢱ࣮ࣥA ࢆᵓᡂࡍࡿ୪㐍㐠ືࡢ࠺ࡕ㸪୪㐍㐠ື ղ࡜ճࡣࢥࣄ࣮ࣞࣥࢺ್ࡀ1.0㸪ࡍ࡞ࢃࡕ㸪ࡍ࡭ ࡚ࡢࢻࢵࢺࡀ୍ᐃ᪉ྥ࡬࡜㐠ືࡍࡿࡀ㸪୪㐍㐠 ື߇ࡢࢥࣄ࣮ࣞࣥࢺ್ࡣ㸪0.1 ࠿ࡽ 1.0 ࡲ࡛ẁ㝵 ⓗ࡟࠿࠼࡚࠸ࡗࡓ㸬ࡲࡓ㸪3 ࡘࡢ୪㐍㐠ືࡢࢫࣆ ࣮ࢻࡣࡍ࡭࡚48r/sec ࡜ࡋࡓ㸬 ࡇࡢ࡜ࡁ࡟▱ぬࡉࢀࡓ㐠ືṧຠࡢᣢ⥆᫬㛫ࢆ ᅗ10 ࡟♧ࡍ㸬୪㐍㐠ື߇ࡢࢥࣄ࣮ࣞࣥࢺ್ࡀ 0.1㸪 ࡍ࡞ࢃࡕ㸪100 ಶࡢࢻࢵࢺࡢ࠺ࡕ 10 ಶࡢࡳࡀྑ ᪉ྥ࡟⛣ືࡍࡿሙྜ࡟ࡣ㸪2.6 ⛊ࡢ㐠ືṧຠᣢ⥆ ᫬㛫ࢆ♧ࡋࡓࡀ㸪୪㐍㐠ື߇ࡢࢥࣄ࣮ࣞࣥࢺ್ ࢆ኱ࡁࡃࡋ୍࡚ᐃ᪉ྥ࡬ࡢ㐠ືᡂศ㔞ࢆቑࡸࡍ ࡜㐠ືṧຠᣢ᫬㛫ࡣῶᑡࡋ㸪ࢥࣄ࣮ࣞࣥࢺ1.0㸪 ࡍ࡞ࢃࡕ㸪3 ࡘࡢ୪㐍㐠ືࢆᵓᡂࡍࡿࡑࢀࡒࢀࡢ ࢻࢵࢺࡀࡍ࡭࡚୚࠼ࡽࢀࡓ᪉ྥ࡬࡜୪㐍㐠ືࡍ ࡿሙྜ࡟ࡣ㸪ண ࡝࠾ࡾ㐠ືṧຠࡣ▱ぬࡉࢀ࡞ ࡃ࡞ࡗࡓ㸬  ḟ࡟㸪ྠᵝࡢᐇ㦂ࢆࣃࢱ࣮ࣥB㸦ᅗ 3㸧࡟ᑐࡋ ࡚⾜ࡗࡓ㸬ࡇࡢࣃࢱ࣮ࣥࡣ㸪ࣃࢱ࣮ࣥA ࡜ࡣ␗ ࡞ࡾ㸪3 ࡘࡢ୪㐍㐠ືࡀࢥࣄ࣮ࣞࣥࢺ್ 1.0 ࡛࠶ ࡗ࡚ࡶ㸪㐠ືṧຠࡀ⏕ࡎࡿ㸦ᅗ9㸧㸬ࡋࡓࡀࡗ࡚㸪 ࣃࢱ࣮ࣥB ࡢ୪㐍㐠ືղ࡟࠾ࡅࡿࢥࣄ࣮ࣞࣥࢺ ್ࢆẁ㝵ⓗ࡟ቑຍࡉࡏ࡚᭱኱್1.0 ࡜ࡋ࡚ࡶ㐠 ືṧຠࡀṧࡿ࡜⪃࠼ࡽࢀࡿ㸬ࡇࡢண ࢆ☜ㄆࡍ ࡿࡓࡵ࡟㸪㐠ືṧຠ୪㐍㐠ືղࡢࢥࣄ࣮ࣞࣥࢺ ್ࢆ0.1 ࠿ࡽ 1.0 ࡲ࡛ẁ㝵ⓗ࡟࠿࠼࡚࠸ࡗࡓ㸬ࡲ ࡓ㸪3 ࡘࡢ୪㐍㐠ືࡢࢫࣆ࣮ࢻࡣ 48r/sec ࡜ࡋ ࡓ㸬ᅗ11 ࡟♧ࡍ⤖ᯝࢆぢࡿ࡜㸪ࣃࢱ࣮ࣥ A ࡢ࡜ ࡁ࡜ྠᵝ㸪୪㐍㐠ືղࡢࢥࣄ࣮ࣞࣥࢺ್ࡀቑຍ ࡍࡿ࡟ࡘࢀ࡚㐠ືṧຠᣢ⥆᫬㛫ࡣ▷ࡃ࡞ࡗ࡚࠸ ࡃࡀ㸪ࢥࣄ࣮ࣞࣥࢺ್1.0㸪ࡍ࡞ࢃࡕ㸪୪㐍㐠ື ղࡢࢻࢵࢺࡀࡍ࡭࡚ྠ୍᪉ྥ࡟ື࠸࡚ࡶ0.8 ⛊ ⛬ᗘࡢ㐠ືṧຠࡀ▱ぬࡉࢀࡓ㸬ࡋࡓࡀࡗ࡚㸪ࣃ ࢱ࣮ࣥB ࢆ⏝࠸ࡓᐇ㦂⤖ᯝࡶ 3 ࡘࡢ୪㐍㐠ືࡀ ࣋ࢡࢺࣝຍ⟬⤫ྜࡉࢀࡿࡇ࡜ࢆᨭᣢࡋ࡚࠸ࡿ㸬  ௒ᅇࡢ◊✲⤖ᯝࡣ㸪ࢫࣆ࣮ࢻ࡜㐠ື᪉ྥࡢ␗ ࡞ࡿ୪㐍㐠ືࡀᏑᅾࡍࡿ࡜ࡁ㸪ྛ㐠ືࢆ࠶ࡽࢃ ᅗ10 ୪㐍㐠ືࡢ㐠ືᡂศ㔞࡜ 㐠ືṧຠᣢ⥆᫬㛫 ᅗ11 ୪㐍㐠ືࡢ㐠ືᡂศ㔞࡜ 㐠ືṧຠᣢ⥆᫬㛫

(8)

ࡍ㐠ື࣋ࢡࢺࣝ࡟ᑐࡋ࡚㸪㐠ືṧຠ࡟ཬࡰࡍ኱ ࡁࡉ࡛㔜ࡳࢆ௜ࡅࡓᚋ㸪ྛ㐠ື࣋ࢡࢺࣝࢆຍ⟬ ࡋ㸪ࡑࡢ㏫᪉ྥࢆồࡵࢀࡤ㐠ືṧຠࡢ᪉ྥ࡜࡞ ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿ㸬ࡇࡢࡇ࡜ࡣ㸪ᗈど㔝㐠ື ᝟ሗࡢ᳨ฟ࡟㔜せ࡞ᙺ๭ࢆᯝࡓࡋ࡚࠸ࡿMST 㔝࡟࠾࠸࡚㸪᪉ྥ㑅ᢥᛶ⣽⬊࡟ࡼࡿ᪉ྥ᝟ሗࡢ ⾲⌧6㸧ࡔࡅ࡛ࡣ࡞ࡃ㸪ࢫࣆ࣮ࢻ㑅ᢥᛶࢆᣢࡘ⣽ ⬊ࡢࢫࣆ࣮ࢻ᝟ሗࡢ⾲⌧12㸧ࡶ㐠ືṧຠㄆ▱࡟⏝ ࠸ࡽࢀ࡚࠸ࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿ㸬

5㸬

㸬࠾ࢃࡾ࡟

ᮏ◊✲࡛ࡣ㸪ࢸࢫࢺ่⃭࡜ࡋ࡚㟼Ṇ่⃭ࢆ⏝ ࠸࡚㐠ືṧຠ≉ᛶࢆㄪ࡭ࡓ㸬ࢸࢫࢺ่⃭࡜ࡋ࡚ ࢲ࢖ࢼ࣑ࢵࢡࣛࣥࢲ࣒ࣃࢱ࣮ࣥ࡜࿧ࡤࢀࡿࡍ࡭ ࡚ࡢࢻࢵࢺࡀࣛࣥࢲ࣒࡞᪉ྥ࡟ືࡃࣃࢱ࣮ࣥ౑ ⏝ࡋࡓ࡜ࡁ࡟ࡣ㸪௒ᅇ࡜ࡣ␗࡞ࡿ᪉ྥ࡬ࡢ㐠ື ṧຠ▱ぬࡀ⪃࠼ࡽࢀࡿ11,13㸧㸬ࢸࢫࢺࣃࢱ࣮ࣥ࡟ ౫Ꮡࡋࡓᗈど㔝㐠ືṧຠ▱ぬࡀ㸪MST 㔝࡟࠾ࡅ ࡿᗈど㔝㐠ື᝟ሗ⾲⌧࡜࡝ࡢࡼ࠺࡟㛵㐃ࡋ࡚࠸ ࡿ࠿ࢆ᳨ウࡍࡿࡢࡀ௒ᚋࡢㄢ㢟࡛࠶ࡿ㸬 ཧ ཧ⪃ᩥ⊩

1㸧Smith, A.T. and Snowden, R.J. Visual Detection of Motion, Academic Press (1994)

2㸧Rodman H.R. and Albright T.D. Single-unit analysis of pattern-motion selective properties in the middle temporal visual area(MT). Exp. Brain Res. 75(1989) ,53-64

3㸧Zeki, S.M. Uniformity and diversity of structure and function of rhesus monkey prestriate visual cortex., J. Physiol., 277 (1978), 273-290

4㸧Saito, H.A.,Yukie, M., Tanaka, K., Hikosaka, K., Fukada., Y., and Iwai., E., Integration of

direction signals of image motion in the superior temporal sulcus of the macaque monkey., J. Neurophysiol. 6(1986) ,145-157.

5㸧Treue, S. Hol., K., and Rauber H.-J., Seeing

multiple directions of motion-physiology and psychophysics., Nature Neuroscience 3 (2000), 270-276

6㸧Saito, H.A., Hida, E., Amari, S. Ohno H., and Hashimoto., N., Neural population

representation hypothesis of visual flow and its illusory aftereffect in the brain:psychophysics, neurophysiology and computational approaches., Cogn. Neurodyn. 6(2012), 169-183

7㸧Mather, G., The Motion Aftereffect: A Modern Perspective, MIT Press (1998)

8㸧Sutherland, N.S., Figural aftereffects and apparent size. Q. J. Exp. Psychol. 13 ( 1961 ), 222-228 9㸧Mather, G., Pavan, A., Campana, G.,and Casco,C.,

The motion aftereffect reloaded, Trends in Cognitive Science, 12( 2008), 481-487 10㸧De Grind, W.A. Movement Aftereffect of

bi-vectorial transparent motion. Vision Res. 39,(1994), 349-358

11㸧Verstraten, F.A.J. , van der Smagt, M.J., Fredericksen, R.E., and van de Grind., W.A., Integration of after adaptation to transparent motion: Static and dynamic test patterns result in different aftereffect directions. Vision Res. 34(1999), 803-810

12㸧Pribe, N.J., Cassanello, C.R., and Lisberger, S.G., The neural representation of speed in macaque area MT/V5. J/ Neurosci. 23(2003),5650-5661 13㸧Alais, D., Verstraten, F.A.J .and Burr, D.C.

The motion aftereffect of transparent motion: Two temporal channels account for perceived direction., Vision Res. 45(2005) ,403-412

2016 年3月 17 日原稿受付,2016 年3月 30 日採録決定 Received, March 17, 2016; accepted, March 30, 2016

参照

関連したドキュメント

We then prove the con- vergence of finite dimensional distributions and tightness results in section 3 for the non-degenerate case and section 4 for the degenerate case (when the

An easy-to-use procedure is presented for improving the ε-constraint method for computing the efficient frontier of the portfolio selection problem endowed with additional cardinality

If condition (2) holds then no line intersects all the segments AB, BC, DE, EA (if such line exists then it also intersects the segment CD by condition (2) which is impossible due

It is suggested by our method that most of the quadratic algebras for all St¨ ackel equivalence classes of 3D second order quantum superintegrable systems on conformally flat

In Section 3, we show that the clique- width is unbounded in any superfactorial class of graphs, and in Section 4, we prove that the clique-width is bounded in any hereditary

The following proposition gives strong bounds on the probability of finding particles which are, at given times, close to the level of the maximum, but not localized....

Next, we prove bounds for the dimensions of p-adic MLV-spaces in Section 3, assuming results in Section 4, and make a conjecture about a special element in the motivic Galois group

Transirico, “Second order elliptic equations in weighted Sobolev spaces on unbounded domains,” Rendiconti della Accademia Nazionale delle Scienze detta dei XL.. Memorie di