CATEGORIES AND CONCEPTS
CATEGORIES AND CONCEPTS PSY 341K
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This 73 page Class Notes was uploaded by Marco Wolf on Monday September 7, 2015. The Class Notes belongs to PSY 341K at University of Texas at Austin taught by Staff in Fall. Since its upload, it has received 48 views. For similar materials see /class/181803/psy-341k-university-of-texas-at-austin in Psychlogy at University of Texas at Austin.
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Date Created: 09/07/15
Physics of Sound When a tree falls in a forest with no one around does it produce a sound m Properties of vibrating systems Free and forced vibrations Resonance and frequency response Sound waves in air Frequency wavelength and velocity of a sound wave Simple and complex sound waves Periodic and aperiodic sound waves Fourier analysis and sound spectra Sound pressure and intensity The decibel dB scale The acoustics of speech production Speech spectrograms Displacement Scale LLiIHIIi Mass Sp ng low Friction Supporting Surface Rigid Point of Attachment A simple spring mass oscillator Sound is created by motions and vibrations of objects in the environment The nature of those motions is determined by the forces impinging on the objects and their resonance characteristics Properties of Vibrating Systems m displacement momentary distance from reslpuinl B cycle one complete oscillation amplitude maximum displacemenp average displacement frequency number of cycles per secund hut in Hz perind number of seconds per cycle phase portion of a cycle thruugh which a waveform has advanced relative to some arbitrary reference point What is the relation between frequency 0 and period T F1T T1If HHHH EQTR o 5 80 Q 3959 00 5 at Time SINEWAVE I I T l circle of mpgion amplitudc I i I gt noycs honzomally I l l k 1 II In tlmc l39 g m TIME 0 lsec 259 I point in uniform circular LJ motion at one revolution pm second sinewave trace of Ptojccttd Point on cyclc1 scc cqucncyzlllz 11 mn nmn MM H I 110 second a b c u i u u l I i I x i i i 5 6 7 YIME IN SECONDS Dixpluczmml 0 um vibratng mm mm m wilhimt damping a m m b lightly 4mm x mm hmin damped Imagine increasing the friction in the simple springmass oscillator Resonance l Lightly dmped Highly damped PM of forced vibrations I I I I I I I I I I I I I I I I I I 45 45 47 48 49 50 51 52 53 54 55 Frequency of driving force Hz Resonance curves for lightly damped and highly damped systems Forced vibrations and resonance curves Imagine tapping the block in the spring mass oscillator at different tapping frequencies FTequencyVVavekngthand Velocity of Sound Waves Wavelength the spatial extent of one cycle of a simple waveform Compare this to period If we know the frequency f and the wavelength A of a simple waveform what is its velocity c fkc Appy this formula to explain Helium speech Uniform pressu loudspeaker stationary I I L gt High pressure as loudspeaker moves toward thread Low pressure as loudspeaker moves away from thr a VHWHH I lHHHWHHH HHHHIHHHII Pressure 3 8 a 1 Pressure Period P gt amplitude A Time Periodic waveforms Periodic waveforms 8525 ms Periodic waveforms Trons ent donols Hue at ewmples m ano wr sou ur nprriodic gtigna Ape riodic waveforms 10m 1mm Fanrig 2 March main May 1m 1111 punm39xxian n a mmiomaqm I lunl39dpu t 1 Gmble I VVVV AAAA vvvvvv A Pure tone Square wave Train of pulses Single pulse While noise Shon tone Amplitude WAVEFORM iiiii O 40 40 Amplitude o o o O lllil o SPECTRUM 0 5000 10000 Sound energy Relative energy Time msac a 40 30 20 10 n 7 I l I l 0 400 800 1200 1600 2000 2400 2800 3200 3500 4000 Frequency Hz Fundamental b Sound Pressure and Inwnsily Sound pressure p form per square centimeter ldyllEscmz Intensity 1 power per square centimeter Wattscull l kp2 Smalle l audihle sound 2 1 10quot dynescnr39 l0 Wat39scml A problem Belween a just audihle sound and a sound at Ihe pain threshold sound pressures vary by u ratiu ul 110000000 and intensities vary by a ratio of l 1000000000000001 More convenient m use scales based on logarithms Decibels MESH 20 log plp 1 log LIn where p is the sound pressure and II is the intensity of the sound of interest and p and loane the sound pressure and intensity ofajust audible sound 0 Threshold 01 heanng 10 Novmal breathing 20 Leaves rustling in a breeze 30 Empty movie house 40 Residential neighborhood at night 50 Quiet restauvank 60 Twoperson conversauon 70 Busy Ira xc 80 Vacuum cleans Baglnnlng of danger 90 Water at loot of Niagaia Falls We 100 Subway train Prolonged exposure can cause 120 Propeller plane at Iakeo hearlng loss 130 Machinegun fire close range Threshold 140 Jezal takeolf onequot 160 Wind unnel mainlqu m 2 i u u 39 quot m d hummuutmmdlm umlummnlmmy m ounnznmmun nmmalwbc MW Humuldlnkm mu lhmlllnmaf ulkr mmmmm aIuweuvmuunmeummm 1 u um mumum dalmw lxhwwdJhnadl d l39aIIh nlwwdlamtu mmwlnnmdmvm huwvc 2 minim mmmmormmmmmwmmumw mar1mm m FREQUENCY IN KHz TIME M34 0 e 39F 1 El 5 psktrama v 1 sp itSIll t A speech spectrogram a spectrum of speech in timequot Human Elephant u 95 Illlllll I IIIIIIH I 10 100 1000 10000 100000 Frequency Hz of keys Low A 275 Middle C 261 High C 4186 I I I II I I 1000 4000 Frequencv Hz H7 M17775 inns quoth 2thj gj L39 V L C r 9 r xyheostggsur j K E 1117 EIZQRQ I L le w u W A The sounds reolw mere of the moment earrecieves Whatyour 5 brain perceives N 1 Z 7quot392 w 51 Le 2 M W Sound source u V J I l 1 Direct paths Indirect paths to ear o prk ma Prhmry visual Lawn genicuhtc body Opm nduuum Dunc nerve Dunc chiasma 0pm tract Lamral geliiculaIQ J Superior collmulus Optic radlation Sriale conex Visual pathway from retina t0 striate cortex The right Visual eld projects to the left hemisphere and the left Visual eld projects to the right hemisphere P zone lt AU X Xi ugh M zone N AX LGN layers The lateral geniculate nucleus LGN is divided into layers The upper layers P layers receive projections from the midget ganlion cells in the retina The lower M layers receive projections from the parasol ganglion cells The smaller K layers receive input from ganglion cells coding responses from the blue S cones Green layers receive projections from the contralateral eye brown from the ipsilateral eye Rodieck R W 1998 The First Steps in Seeing Sunderland Sinauer Contrast Spatial frequency High Low High Low B C D 30 2 E gt a s 5 IE In l0 V39 a a o 5 a 3 U E o s U l Control 1 10 P M Sparlal frequency Temporal lrequency ame alone Hz cyclesdegree o Palone D M alone Control Effects on Visual performance of lesions in the P and M layers of the LGN Merigan W H and J H R Maunsell 1993 How parallel are the primate visual pathways Annual Review of Neuroscience 16 369402 Visual areas in the visual cortex of the macaque monkey Felleman D J and D C Van Essen 1991 Distributed hierarchical processing in the primate cerebral cortex Cerebral Cortex 1 1 7 Micro electrode Micro electrode rv vortex 0pm mu Micro el ectrode ch gcniculnlc body Op adnnons Single unit electrophysiology A Field mapped with spots B Receptive C Importance of orientation eld of bar of light w uj Light i H i 94 69 Diffuse illiunination l g1 0 39l 2 3 0 1 2 3 Time s Time s Receptive eld properties ofa simple cell The cell is orientation selective and positionphase selective Hubel D H and T N Wiesel 1962 Receptive elds binocular interaction and functional architecture in the cat s visual cortex Journal of Physiology London 160 106154 Hubel D H and T N Wiesel 1968 Receptive elds and functional architecture of monkey striate cortex Journal of Physiology London 195 215243 Response Properties ofV1 Neurons Simple cells 1 Low spontaneous activity quiet when not stimulated 2 Receptive fields are elongated not circular and are also divided into excitatory and inhibitory regions 3 The and regions do not form a center and a surround but form alternating stripes rectangular regions edge detectors slit detectors ine detectors 4 They are position or phase selective 5 They are orientation selective 6 They are size selective 7 They are often direction selective 8 They are often disparity selective I W4 I lh I lmt k W I lm W4 gal 4b I ll IWl Iquot 4 L1JI U l 2 3 4 1 2 3 4 Time s Time 5 Receptive properties of a complex cell The gray square shows the location of the classical receptive eld The cell is orientation selective but not positionphase selective Hubel D H and T N Wiesel 1962 Receptive elds binocular interaction and functional architecture in the cat s visual corteX Journal of Physiology London 160 106154 Hubel D H and T N Wiesel 1968 Receptive elds and functional architecture of monkey striate cortex Journal of Physiology London 195 215243 Response Properties ofV1 Neurons Coleex cells 1 Low spontaneous activity quiet when not stimulated 2 Receptive fields are elongated not circular 3 Do not form a center and a surround ratherthey behave like edge detectors slit detectors or line detectors 4 They are not selective to position or phase 5 They are orientation selective 6 They are size selective 7 They are often direction selective 8 They are often disparity selective Excitation Simple cortical cell Model ofneural circuit for simple cells Model ofneural circuit for complex cells Pia mater Proiemions slellaie cell Superior colliculus Lateral geniculate nucleus Left eye afferent from High eye alferent from lateral geniculate nucleus Iareral geniculale nucleus White matter Layers of the striate cortex also known as primary Visual cortex area 17 in cat and V1 in monkey slnate cortex LGN retinas lTHdgEl Fgiant small a cam paras bislramied kinase Zlypes Stypes epsilon gamma pathways 01 gangllon cells to LGN and smale cortex Current estimates of projection pathways for ganglion cells in the retina of primates macaques and humans Rodieck R W 1998 The First Steps in Seeing Sunderland Sinauer CorKical pegs Ocular 1 I r dominance concerned w lh co 0 Layers Surfao To higher m conical regions IV Primary visual conex area 17 v Tu superiorcohicums v To Ialetal geniculate r nucleus While mzner Ovienlation co umns Laugral genlculale nucleus 61C 5H MC ill 2 1C Jig The columnar structure of primary Visual cortex There are ocular dominance and orientation columns Each complete set of columns all orientations and both eyes de ne a hypercolumn Blasdel G G 1992 Differential imaging of ocular dominance and orientation selectivity in monkey striate corteX Journal of Neuoscience 12 31153138 HI 0 Quantitative characterization of cortical cell response properties using linear and nonlinear systems analysis One common approach is to measure the responses with sine wave gratings Measured Responses amp Descriptive Functions E CONTRAST SPATIAL FREQUENCV TEMPORAL FREQUENCY 1o 12 T T T Q T T T T T T 2 A 39 c Ill 7 I 7 7 7 7 39 7 2 a 4 5 E E 6 I I a T g 1 u T T o T T u a W 7 7 392 39 o 5 2 2 7 E 3 a 3 r 7 u T o T T T g T u so u 5 1n 0 15 30 c m u cpd w 1H1 quot SPATIAL POSITION ORIENTATION DIRECTION OF MOTION 33 1 T T T 15 T T 10 T T T 9 a a m 2 a 5 7 9 n w 7 a E E E E u T T T u T T E g 2 7 3 7 7 g ill a T T T T 8 U 8 U 180 350 80 I an min e deg Examples of tuning characteristics of neurons in primary Visual cortex of the macaque monkey Geisler W S and D G Albrecht 1997 Visual cortex neurons in monkeys and cats Detection discrimination and identi cation Visual Neuroscience 14 897919 20 OBW degrees I Devaiois Yund amp Hepier1982 01 0 1 020 2030 3040 4050 5060 6070 7080 8090 90180 gt180 o CELLS 015 1530 3045 4560 6075 7590 90105 Opeak degrees 105120 120135 135150 150165 165180 I Biakemore et ai 1981 o CELLS n o n Histograms for Orientation Tuning o CELLS o CELLS Histograms for Contrast Response 510 1 m N 2025 1015 1520 c50 contrast 3035 II II I 0 3540 gt40 I swap Maunsetr amp Lenme 1990 Atbrecht amp Hamttton 1982 21 RESPONSE spks LOGVLOG LINEARUNEAR RESPONSE spks 40 CONTRAST 3 11 1n CONTRAST Wu 1 camcax Call Rod Photoyecenlo RESPONSE nELmvs RESPONSE mu man m w commsr w PHOTONS Comparison of contrast response functions of cortical neurons and intensity response functions in the photoreceptors Geisler W S and D G Albrecht 2000 Spatial vision Seeing K K De Valois New York Academic Press 79128 24 szwoctaves o CELLS 2224 gt24 Deva o s A brecht amp ThoreH 1982 ThoreH Deva o s amp A brecht 1984 o CELLS Histograms for Spatial Frequency Tuning superior oblique superior reclus r medial reams 397 superior oblique I superior recfus aleral recurs lmfemr DblQue rnferror reclus The human visual system implements an elegant comprise between the competing goals of maximizing eld of view maximizing spatial resolution and minimizing neural resources It encodes a large eld of view using a retina with variable spatial resolution and then when necessary uses highspeed eye movements to direct the highestresolution region of the retina the fovea at speci c points in the visual scene This diagram shows the eye muscles controlling eye movements There are two basic kinds of eye movements saccades and smooth pursuit 25 Response Properties of V1 Neurons 1Selective to orientation size position direction of motion etc 2 Tuning functions vary across cells but they are smooth with characteristic shapes 3 Tuning functions are invariant in shape with contrast 4 Contrast response functions saturate often at low contrasts 5 Sensitivity and tuning are controlled by fast contrast normalization and slow contrast adaptation 6 Tuning is sharpened by an expansive response nonlinearity 7 Sensitivity is modulated by attention and task demands buttuning is not 26 I I I I I I 28 3 724 Zn A 2508 20 35 8 89 55 067 16 3 CD0 Dl 2 010 047 71 2 Em O 0 8 0 VIRl 708 E35 gt lt 02 704 0 l I I I I 010 20 30 4O 5O 60 70 Contrast Relationship between contrast response function measured with MRI in humans and the average contrast response function of single neurons measured in primary Visual cortex of the macaque monkey Heeger D J A Huk et al 2000 What does neuroimaging tell us about neural activity Nature Neuroscience 3 631633 See also fMRI Videos 27 12 cycles 0 deg Demonstration of orientation and spatial frequency masking This is the high contrast masker alone 12 cycles 0 deg 12 cycles 90 deg Here is the high contrast masker plus a low contrast target of the same spatial frequency oriented in the orthogonal direction 29 12 cycles 0 deg 12 cycles 5 deg Here is the high contrast masker plus a low contrast target of the same spatial frequency oriented 5 degrees from the masker 12 cycles 0 deg 48 cycles 5 deg Here is the high contrast masker plus a low contrast target of a higher spatial frequency oriented 5 degrees from the masker u a o I Relative Contrast Threshold 03 v 1 01 1 10 100 Contast 30 E 3 g Zcpd g 10 E a 4cpd g Scpd 139 8 d g p E 1 E m n 03 01 1 10 100 Contest u Contrast masking functions for different masker orientations and spatial frequencies Ross J and H D Speed 1991 Contrast adaptation and contrast masking in human Vision P I of the Roval SocietV of London Series B 246 6169 Foley J M 1994 Human luminance patternVision mechanisms Masking experiments require a new model Journal of the Optical Socie of America A 1117101719 32 2 E E 37 E 0 U Threshold elevation Spatial equ nCY CW Elfect of adaptation to a particular spatial frequency on the contrast sensitivity function Blakemore C B and F W CAmpbell 1969 On the existence of neurones in the human visual system selectively sensitive to the orientation and size of retinal images Journal of PhysiologyJ London 203 237260 33 Adapt Test Adapt Demonstration of the tilt aftereffect View the test Now track your eyes around the circle on the left for 20 sec and look back at the test Now track your eyes around the circle on the right for 20 sec and look back at the test Notice how the test orientation shifts from vertical 34 Test Adapt WWW ll Contour uriematinn Cells preferred orientation Cells39 response Cells39 response Perceived Orientation Helm II Contour orientation l CeHs39 preferred orientatan Percelved orientation An explanation of the tilt aftereffect in terms of the adaptation of orientation selective populations of neurons in the Visual cortex 35 Simultaneous brightness contrast Simultaneous contrast contrast Chubb C G Sperling et al 1989 Texture interactions determine perceived constrast Proc Natl Acad Sci 86 96319635 36 Threshold elevation log Contrast Test spatial hequency cpdb DemngLon amp Henmng 1989 A masking effect not easily explained by the properties of cortical neurons Dunn El uuuuuuuuu D D an nun nu uuuuuuuuu u uuuuuu u uuuuuuuuu uuuu D DD nu u u uu uuuu uuuu u uuuuuuun uuuuuuuuu uuuuuuuuu nu EDD DDDD nu uuuuuuu Texture segregation pattern Texture Element Pairs I E 5 39 39 I It 4i lt1 K I IIII II T 39u39u 5 I I El 0 u H I Possible elements for central and background region 39 1 5 l l n9 E 13 r2029 D I E 117 7 E lt 9 7 a D 7 e E n 57 r 3 m 37 r O I 1 1 1 1 1 1 1 3 5 7 9 11 13 15 PREDICTED RANK ORDER Predicted central region Visibility based on a model of ganglion cell responses or Vl cell responses The model does poorly 40 I39llIn n nnnn nnnnn nnnnn nnn nn nnnnn nnnnn uuuuu uuuuu uuuuu uuuuu uuuuu nnnnn nnnn n nnnnn nnnnn Example of texture pair that should be easy to segment 41 11an 11311131311113 3111 n 31111111113113 Jinn 11311131 nunnn t tag 1111133 nunnn 13111 313111 nn 311 131 un nn nnn mm 1131 nnttnnn 11 3111311 3111113131311 131 311 3131111 nunnn n 111 n 313111311111313131 ntt 3111 311111313131 tunnn nnn 313111113111 11313111 111131311 Example of a texture pair that should be harder to segment 42 The gray scale luminance is the same for the two squares in the checkerboard in fact it is exactly the same gray shown at the tails of the arrows Illustrates how perception may re ect the complex properties of the environment Figure by Edward Ted Adelson at MIT 43
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