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Psych119F Wk 9 Notes

by: Marissa Mayeda

Psych119F Wk 9 Notes Psychology 119F

Marissa Mayeda
GPA 3.3
Neural Basis of Behavior

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Neural Basis of Behavior
Class Notes
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This 36 page Class Notes was uploaded by Marissa Mayeda on Wednesday March 4, 2015. The Class Notes belongs to Psychology 119F at University of California - Los Angeles taught by Blair in Winter2015. Since its upload, it has received 94 views. For similar materials see Neural Basis of Behavior in Psychlogy at University of California - Los Angeles.

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Date Created: 03/04/15
Midterm 2 in class Wed Mar 11 Office hours after class on Monday March 9 Review session on Tuesday March 10 in Franz 2258A from 46 pm No office hours will be held after the exam on Wednesday or on Friday March 13 Written Final Exam Thursday March 19 spatial pegged 7 gt spatialfrequency d1I I r x I I I I I I 39 I I I I I I lullhi 39III39I39 I uIIIIIIIIIII H E I I I 1 I i I I 39 I 39 I I data from HaftingI Fyhn Bonnevie Moser amp Moser 2008 E I Supplementary Figure 5 FE I I I I I 4 I HE E II I I I I I II 5 quot I I E II I II IJ39 I I 39I I II 39 I I39IIquotI II 3939 III 39i39 I I I Iquot I III I II 39 39 I II39IIIIII I I 39III39 39I II E I II 39 II LI III IIIII39 I r II I I39I I I I 39 39 j I 39 39II I39I I I 39IIIII I III 39I I I I II I IIII I I II I I I I I I quotI IIII III I II I I E EI IIIII I IIIle II I 39II III I II I39 II III I I39 II EL I I IIII39II II39 III I II39I39III EH 11 II39 II Il39 III I JIII I I I I III I i I III I I I I I I D I I I39 I I I I I I I Position x Hacking the ring attractor What if we make some modifications to this circuit such as feeding velocity inputs from the utricle instead of from the semicircular canals linear speed move bump around the ring bump speed a und ring increase with rat running speed INHIBITORY UTRICLE RING EXCITATORY RING INHIBITORY RING like odometer in your car faster car moves faster odometer moves ampIl larger period smaller frequency Each grid cell bursts at a a Z dv frequency In Hz which IS equal to 360 the number of grid fields traversed A i 270 r per second Burst freq o 360 a 6 2 180 d 3 90 shallower for bigger spacing 8 0 lambda distance per second because makes 360 Angular frequency of the bump 0 varies linearly with velocity v at a slope determined by the spatial frequency d1 M of the periodic length interval Cyclical versus linear position or distance This odometer is like a clock with six hands that measures distance on six different spatial scales Adding just one new dial to the odometer multiplies the number of distances we can represent by a factor of ten Could the brain contain systems for measuring distance that work like this Different grid cells have different spatial periods or quotvertex spacings and thus A different spatial frequencies I firing rate IS the same as expected but pattern is diff fire bursts of spikes at 7Hz II 700 0 degrees s gridcells mid MEC grid cells 3 j dorsal MEC 0 0 V distance s M 72 7L3 Grid cells with different vertex spacings can be thought to reside in different ring attractors which are like different wheels on the odometer f grid cells dorsal MEC 0 degrees s M K2 7amp3 V distance s l midMEC I grid cells 360 27a 180 90 12 2 7zr dzv 0 M x2 x3 r 1 grid cells ventral MEC 1 The bump circulates m in rings with a smaller vertex spacing L which corresponds to a higher spatial frequency d and a steeper slope of the line relating v to a e 3 this is the correct diagram one from last lecture is incorrect Ring attractor model of grid cells 1 The remapping problem Grid cells with the same vertex spacing appear to maintain identical adjacency relations with one another in all environments so there is no remapping problem to worry about 2 The temporal coding problem Like place cells grid cells also burst rhythmically at the theta frequency and exhibit phase precession against the local LFPthe attractor model still does not inherently account for this 3 The unbounded domain problem By using several rings each composed from grid cells with a different spacing just like the different wheels of the odometer we can uniquely encode a VAST number of locations enough to cover the surface of the earth many time over so the unbounded domain problem is less of an issue each time rat passes through either one of grid fields see phase precession occurs over and over again Phase precession in grid cells bursts per second different firing rate because multiple spikes in burst burst at 7Hz firing rate and burst freq are not the same but both measure in Hz d gt T Ral wvn 1W 139 w 30 2O 1O 0 60 4o 201 3quot 0 720quot Lap number Firing rate Hz Theta phase deg 480 240 1 8 quot J I Position cm Like place cells grid cells in entorhinal cortex often show phase precession against the locally recorded EEG theta rhythm Phase precession is more common in grid cells recorded from cortical layer ll than in otherlayers The ring attractor model of grid cells does not provide us with an obvious explanation for phase precession Hacking the ring attractoragain What if we make some modifications to this circuit such as eliminating the bottom inhibitory ring How will the circuit behave now INHIBITORY RING excitatory cells also excite inhibitory cells get walls of inhibition EXCITATORY here only get wall on RING one side allow bump to only move in one direction INHIBITORY RING A ring oscillator CPG With a constantly circulating bump the ring attractor becomes a ring oscillator that could drive rhythmic behaviors like the locust wingbeat cycle ELEVATOR MUSCLES DEPRESSOR MUSCLES Theta cells Rate histogram of a theta cell Compare the firing rate maps of a theta cell place cell and grid cell All burst rhythmically at about 79 Hz but the theta cell lacks spatial tuning Theta cell Place cell Grid cell lll l ill l l i39lli l f il l tl lllilll tile H E j lllt jHL Ring oscillator model of theta CPG A ring oscillator circuit can easily simulate theta cells if the activity bump circulates at the theta frequency of about 8 Hz 0 Each cell in the ring bursts on its own phase of the theta cycle Theta cell spikes lllll II a III llll Illl II lllll Illll Ill Illl llll Theta Frequency Hz 9 N 5 0 9 00 9 03 I 0quot 3 Speed dependence of theta frequency From Jeewajee et al 2008 Hippocampus 1821175 10 20 30 40 Running Speed cms theta freq between 4 and 12 Hz but usually 69 Hz 0 A number of studies have shown that the frequency of theta rhythm in both EEG and singleunit recordings tends to increase slightly with the rat s running speed 0 How can the ring oscillator model account for this dependence of burst frequency on running speed Shift of yintercept The main difference between grid From Jeewajee et al 2008 Hippocampus 1821175 9392 360 Hillim E 270 gas a 180 E86 iii L 90 cells and theta cells is their y intercept 2nd 227 V is slope spatial frequency should say 390 not 2 AW P lIl cgt 10 20 30 40 Running Speed cms running speed zero bump speed zero Speedmodulated theta CPG frequency is some constant plus what it was before if lambda a Q 27rd v UTRICLE W36 1 1 3 o2m A m w tr 2 ollso no 3 8 o If we imagine that the theta ring oscillator receives an excitatory driving input that encodes LINEAR velocity then the theta frequency will increase with running speed from a nonzero baseline When the rat sits still two bumps MOVE in different theta rings but AT THE SAME SPEED or angular frequency so that that they are not moving with respect to EACH OTHER bumps moving at same frequency so not moving with respect to each other exists a reference frame in which bumps are stayin s glltvlv lglEJra tTisgtay ggp U Vl It depends upon what reference frame we measure their position in g I RING 2 J theta cells 875 With respect to the neurons in the rings the bumps are moving But with respect to one another they are not moving So there exists a reference frame in which the bumps are 0 M 7 2 7L3 0 M 7 2 7 3 still when the rat is still V distance s 00 N Um Theta Freq Hz When the rat moves the two bumps AT DIFFERENT SPEEDS or angular frequencies so that that now they are moving with respect to EACH OTHER when rat starts moving frequencies are different YVVWVWVYVWW If running speed modulates the bump frequency with DIFFERENT SLOPES IN EACH RING then the bump frequencies will only be equal when running speed is zero The faster the rat runs the greater the difference between the bumps speeds and thus the faster the move with respect to each other RING 1 theta cells 1 V distance s 0 M x2 x3 Beat interference Sinusoidal tones that differ in frequency or pitch by just one cycle per second 1 Hz are very hard to tell apart from each other 2ms 1996 ms 1Hz is very small difference in frequency 500 Hz 501 Beat interference l x 501500 1 Hz envelop NW N Wm M WWW quot I Oscillatory interference models of grid cells Burgess amp O Keefe 2005 Burgess et al 2005 Giocomo et al 2007 Hasselmo et al 2007 constructively interfere when peaks a iihlme5 5e 08 move in and out of phase beat freq is time for one bump to go 360 degb t period f I SecCycle 2 1 around with respect to other bump I I W WWI IlllI W W I I v f2f1 beat spacing cmcycle Converting a time code into a lace codesound familiar as rat walks across tracks peaks are when t ey are in phase time code for rat s position WVWWVYWW VWWVYVWWWWMYYWW RING 2 1 r theta cells 1 ell The two theta rings store a TIME CODE for the rat s position in very much the same way that the barn owl s left amp right nucleus magnocellularis store a time code for azimuth The grid cells convert the time code into a place code very much like the nucleus laminaris computes a place code for azimuth Do grid cells and place cells derive their locationspecific firing by detecting synchrony among theta cells grid cells come from theta cells grid cell fire when 2 theta oscillator 25 cms 20 cm cells fire in synchrony so happens Ia Grid cell data from Haftlng et al 2008 e i E L 4 5 5 5 g 2W quot 339 5 E E 5 1 I Ildlalil39 Il39lquot 39Ilquotquot3939H I39 Hi m Hun in m vvquot 39 V V l v 1 v 11 a i 5 i i 39 C9 place cell only fire if many theta oscillators fire in synchrony less common so sparse code Place cell data from Foster amp Wilson 2008 l O Firing Rate Hz 5 O l l Position Ascending theta pathways target entorhinal cortex where grid cells are found and hippocampus where place cells are found origin of theta rhythm p 7 b I 13 if drug injected into medial septum 39quot quot Entorhinal Cortex Hippooampus A ten quot Mi 39 f 39 quotquot 39 39 The I 39 a w MOIate histogram of a theta cell Vme f Elm E n i Hill Spatial aloecte39y eulocmrelalion D r 21l39zat1blz Spazid autocorrddticn T39Jjettory r quot Baseline Sub Medial Septum rr 1247 p gm 1 0 E 9 a a I 1 Rate 39neo g39mross 219 sampled W 412541 p 37 m LII z s 12H grooms 071 l t x r K f Inactivation 39r39 02 125 rd39icss 4222 36 Hour Recovery n 374 p 51 1 39r Liaix 910 24 Hour Recovery 039 1311731 ick7 391 2Dl 1 a tilz grdwcss 045 Reprinted from Brandon et al 2011 Theta inputs to grid and place cells can be quotturned of by infusing drugs into the medial septum This temporarily inactivates the projection from medial septum to entorhinal cortex When this is done grid cells in the entorhinal cortex are severely disrupted Brandon et al 2011 Koenig et al 2011 Inactivating medial septum reduces place cell firing rates but spares spatial tuning T E Iidt f inie 3 Ear HIFFEEEHWF UE lELlLE rat 3513 v53 ll39ll j a5lquot ti ratf w TITLE 39 I it t t u I a ME It l3 Before inactivation inact reCOVerV Reprinted from Koenig et al 2011 The grid cell model is supported by the data but the place cell model is not 25 cms 20 cm Grid cell data from Hafting et al 2008 a E L 4 z a 2 i E it I H i I H 93 a 5m 3 3 E E 1 I Il I39IIIJIIEIIII39L ll I I lllll llll 39llll39 llllquotlllll grid ail Place cell data from Foster amp Wilson 2008 0 A 20 8 V EN 8 2 9quot 5 10 gt 0quot A E 39quotVVVVVV39 39VVVV39V39V LL 0 u place POSItIO cell Place cells in hippocampus of crawling bats Each cell fires at one or two preferred locations Different cells have different preferred locations evenly distributed throughout the environment 270 cm 2 Place cell recording in flying bats Example of bat flight trajectory Bat flies in a room containing an artficial tree at the center He flies around the tree to receive rewards from baited branches Bat wears a headstage homing electrodes and wireless transmitters 3D place cells in bats Top view XY Side view YZ Front view XZ Location specificity is preserved in cross sections through all angles 3D path plots and firing rate maps show that this hippocampal neuron fires in a specific 3D location As in rats different place cells prefer to fire in different locations K 10 Hz J 6H2 I l l III L t 1 1 7 p I t A Bat 1 n 10 place cells Ten place cells recorded from the same bat had different preferred firing N locations Hippocampal theta is transient in bats d LFP theta rhythm d E I b f WANNA appears on y In re 339 1s 39 4 25Hz bouts lasting 1 second M ax e There IS no promInent Min theta peak in the LFP power spectrum during S39eep Behav sleep or behavior 481420 4814 20 Frequency Hz Grid cells in MEC of crawling bats Adjacent cells had similar spacing amp orientation but differing spatial phase Dorsoventral gradient of spacings Some grid cells were directionally modulated others not Firing rates were modulated by running speed 9 0quot C 0 I 1 39 0 U C 39 0 j 395 o o 0 ct Entorhinal theta is transient in bats c Entorhinal theta also occurs in brief bouts jk Grid cell firing is present even when theta is absent suggesting that theta is not required for grid cell firing Full writlam Maul It Full With ui Ellhm EEEEJHDI EEH lmut 4 ulnly gl Illt sessilenu HEJIIEZIIIL r r tan 1161 156 crnlyr Do place and grid cells without theta in bats disprove oscillatory interference models Possible explanations Theta is present in bats but for some reason is not being observed Oscillatory interference occurs at a different frequency in bats not theta frequency The oscillatory interference frequency is not constant in bats but instead changes with time 1 Hz 8 Hz 2 Hz etc


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