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15 Pages

### neurohw3

Course: NBIO 136, Spring 2006
School: Brandeis
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Word Count: 1813

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V1 1. 0.04 0.02 0 0.02 0.04 0.06 0.08 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 T, Frequency = 37 * 2 spikes per second or 74 hz Period = 1/frequency = 1/74 0.04 0.02 0 0.02 0.04 0.06 0.08 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 T, V2 Frequency = 37 * 2 spikes per second or 74 hz Period = 1/frequency = 1/74 The same as neuron 1 b/c it is the same model with the...

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V1 1. 0.04 0.02 0 0.02 0.04 0.06 0.08 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 T, Frequency = 37 * 2 spikes per second or 74 hz Period = 1/frequency = 1/74 0.04 0.02 0 0.02 0.04 0.06 0.08 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 T, V2 Frequency = 37 * 2 spikes per second or 74 hz Period = 1/frequency = 1/74 The same as neuron 1 b/c it is the same model with the same starting conditions and without coupling 2. 0.1 0 0.1 0.4 0.2 0 0.1 0 0.1 0.4 0.2 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Tsyn = 1ms From top to bottom: (t, V1), (t, syn1), (t, V2), (t, syn2) 0.1 0 0.1 1 0.5 0 0.1 0 0.1 1 0.5 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Tsyn = 10ms From top to bottom: (t, V1), (t, syn1), (t, V2), (t, syn2) If tsyn is low than the syn values effectively spike just after a spike in the neuron occurs and rapidly fall back to zero. However if the tsyn is large enough (here 10ms) the fall back to zero is not fast enough to reach zero before another spike occurs, pushing the syn value up further and further with each spike, until a new high syn average steady state value is achieved. As syn increases the size of the kicks decrease until they equal the decrease caused by natural exponential decay, there the syn oscillates closely around a new high average value. 3. For -60 mV, -60 mV see above graphs, the oscillations are in phase with each other. 0.1 0.05 0 0.05 0.1 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.8 0.6 0.4 0.2 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 For -60mV (in blue) and -40mV (in red) Top of both graphs is t, v and bottom is t, syn The -40mV neuron lags behind the -60mV neuron in both the voltage and syn values. It is slightly negatively out of phase because it started at a higher voltage, which meant current had to be applied longer until it reached the spiking threshold. 0.031 0.03 0.029 0.028 0.027 0.162 0.164 0.166 0.168 0.17 0.172 0.79 0.785 0.78 0.775 0.222 0.224 0.226 0.228 0.23 0.232 0.1 0.05 0 0.05 0.1 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.8 0.6 0.4 0.2 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 For -60mV (in blue) and -80mV (in red) The Opposite effect occurs because the voltage is now lower requiring less current to be applied, however the overall phase shift (laterally) is reduced because once the neuron starting spiking the starting voltage quickly becomes less important. Top of both graphs is t, v and bottom is t, syn 4. 0.02 0.015 0.01 0.005 0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.11 0.37 0.36 0.35 0.34 0.33 0.32 0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.11 0.1 0.05 0 0.05 0.1 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.4 0.3 0.2 0.1 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Neuron 1 is in blue and starts at -60 mV, 2 is in red and starts at -75mV. Top of both graphs is t, v and bottom is t, syn When fast excitatory coupling occurs the neurons push each other to fire at the same time and overcome any phase shifting introduced by the initial starting voltages. However the maximum peak on each spike reached by a neuron oscillates between the 2 as evidenced in the graph. 5. 0.1 0.05 0 0.05 0.1 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 0.4 0.3 0.2 0.1 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 Neuron 1 is in blue and starts at -60 mV, 2 is in red and starts at -75mV. Top of both graphs is t, v and bottom is t, syn When slower excitatory coupling occurs the neurons still fire together and the syn graph resembles that of the fast coupling graph. However since the neurons spike together and drive syn upward, they also oppose the decay back down (by external current) to the spiking threshold. Thus the spike is very fast once the threshold is reached, but the frequency of spiking is decreased due to slow decay of the syn which tries to keep the neurons at higher voltages until syn exponentially decays to zero. 6. 0.1 0.05 0 0.05 0.1 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.5 0.4 0.3 0.2 0.1 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Neuron 1 is in blue and starts at -60 mV, 2 is in red and starts at -75mV. Top of both graphs is t, v and bottom is t, syn When inhibitory coupling occurs the first neuron to spike (here the blue one) gains control over the entire system (until escape or release occurs). Since this model does not include the random escape factors and since the applied current occurs over the entire timeframe (no release) the first neuron to fire (here neuron 1) spikes for the entire time and prevents neuron 2 from ever spiking. Neuron 1 spikes at 74 hz because the inhibitory coupling is strong enough that neuron 1 acts as though neuron 2 were not even coupled. The intermediate tsyn (5ms) generates an syn1 graph that is between the two different patterns seen, it is large enough to oscillate around an average value but smaller than the average value for tsyn = 1ms. Code % This model is the Hodgkin-Huxley model of Homework 2. clear dt = 0.00001; tmax=0.5; i c l amp_ f l ag = 1 ; i f th i s i s 1 , run under cu r ren t c lamp cond i t i ons % vc lamp_ f l ag = 0 ; othe rw i se th i s shou ld be 1 , f o r vo l tage c lamp cond i t i ons % i s ta r t = 0 .5 ;t ime app l i ed cu r ren t s ta r t s % i l eng th=0 .5 ; % l eng th o f app l i ed cu r ren t pu l se I e=120e -9 ; % magn i tude o f app l i ed cu r ren t pu l se %Ie = 0.78e-7; % threshold for constant spiking with no A-current vs ta r t = 0 .25 ; t ime to s tep vo l tage % v leng th = 0 .5 % l eng th o f vo l tage s tep ; V0 = - 0 .080 ; % i n i t i a l vo l tage be fo re s tep Ve = - 0 .040 ; % va lue o f votage s tepped to V_L = - 0 .0544 ; % l eak reve rsa l potent i a l E_Na = 0 .050 ; % reve rsa l f o r sod ium channe l s E_K = - 0 .077 ; % reve rsa l f o r potass ium channe l s E_A = - 0 .075 ; % reve rsa l f o r A-t ype potass ium channe l s g_L = 3e -6 ; % spec i f i c l eak conduc tance g_Na = 1 .2e - 3 ;% spec i f i c sod ium conduc tance g_K = 3 .6e - 4 ; % spec i f i c potass ium conduc tance %g_A = 4.77e-4; % specific A-tpe potassium conductance g_A = 0 .0 ; % i f g_A i s ze ro i t sw i t ches o f f the A-cu r ren t gsyn = 2e -3 ;%coup l i ng conduc tance t syn = 5e -3 ; ime cons tan t f o r exponent i a l decay %t cm = 10e -9 ; % spec i f i c m mbrane capac i tance e tau = cm/g_L ; % m mbrane t ime cons tan t e esyn = -0.075; sigma = 100e-6; t=0 :d t : tmax ; % t ime vec to r nspikewidth = round(tsyn*10/dt); Vspike = 0.0; i f ( i c l amp_ f l ag i . e . i f i n cu r ren t - c lamp mode %) V(1 ) = V_L% se t the i n i t i t a i l va lue o f vo l tage ; end %neuron 1 n1=ze ros ( s i ze ( t ) )% n : potass ium ac t i va t i on gat ing var i ab le ; n1(1 ) = 0 .0 ; % s ta r t o f f at ze ro m =zeros (s i ze ( t ) ) ; m: sod ium ac t i va t i on gat ing var i ab le 1 % m 1(1) = 0 .0 ; % s ta r t o f f at ze ro h1=ze ros ( s i ze ( t ) )% h : sod im i nac t i va t i on gat ing var i ab le ; h1(1 ) = 0 .0 ; % s ta r t o f f at ze ro a1=ze ros ( s i ze ( t ) )% A-cu r ren t ac t i va t i on gat ing var i ab le ; a1(1 ) = 0 .0 ; % s ta r t o f f at ze ro b1=ze ros ( s i ze ( t ) )% A-cu r ren t i nac t i va t i on gat ing var i ab le ; b1(1 ) = 0 .0 ; % s ta r t o f f at ze ro V1=zeros ( s i ze ( t )%;vo l tage vec to r ) sp i kes1 = ze ros ( s i ze (%)wi l l conta in se t o f sp i ke t imes t ); sp i ke1now = 0 ; % var i ab le to say i f code i s i n midd le o f a sp i ke lastspike1 = 0; s1 = zeros(size(t)); %neuron 2 n2=ze ros ( s i ze ( t ) )% n : potass ium ac t i va t i on gat ing var i ab le ; n2(1 ) = 0 .0 ; % s ta r t o f f at ze ro m =zeros (s i ze ( t ) ) ; m: sod ium ac t i va t i on gat ing var i ab le 2 % m 2(1) = 0 .0 ; % s ta r t o f f at ze ro h2=ze ros ( s i ze ( t ) )% h : sod im i nac t i va t i on gat ing var i ab le ; h2(1 ) = 0 .0 ; % s ta r t o f f at ze ro a2=ze ros ( s i ze ( t ) )% A-cu r ren t ac t i va t i on gat ing var i ab le ; a2(1 ) = 0 .0 ; % s ta r t o f f at ze ro b2=ze ros ( s i ze ( t ) )% A-cu r ren t i nac t i va t i on gat ing var i ab le ; b2(1 ) = 0 .0 ; % s ta r t o f f at ze ro V2=zeros ( s i ze ( t )%;vo l tage vec to r ) sp i kes2 = ze ros ( s i ze (%)wi l l conta in se t o f sp i ke t imes t ); sp i ke2now = 0 ; % var i ab le to say i f code i s i n midd le o f a sp i ke lastspike2 = 0; s2 = zeros(size(t)); Vapp=ze ros ( s i ze ( t )%;App l i ed vo l tage , re levant i n vo l tage - c lamp mode ) i f ( vc lamp_ f l ag ) f o r i = 1 : round(vs ta r t /d t ) % % make V0 be fo re pu l se Vapp(i) = V0; end f o r i= round(vs ta r t /d t )+1 : round( (vs ta r t+v length )make Ve f o r dura t i on o f % /d t ) vo l tage pu l se Vapp(i) = Ve; end f o r i= round( (vs ta r t+v length ) /d t ) : l eng th (Vapp) V0 f o l l ow ing pu l se % make Vapp(i) = V0; end end I t o t1=ze ros ( s i ze ( t ) ) n case we want to p lo t and l ook at the to ta l cu r ren t % i; Itot2=zeros(size(t)); V1(1) = -.060; V2(1) = -.075; f o r i = 2 : l eng th ( t )now see how th ings change th rough t ime %; Iapp(i) = Ie; il1 = g_L*(V_L-V1(i-1)); il2 = g_L*(V_L-V2(i-1)); V m1 = V1( i - 1)*1000 conver t s vo l tages to m as needed i n the equat i ons on %; V p .224 o f Dayan /Abbot t Vm2 = V2(i-1) *1000; % Sod ium and potass ium gat ing var i ab les are de f i ned by the % vo l tage - dependent t rans i t i on ra tes between s ta tes , l abe led a lpha and % beta . Wr i t ten out f rom Dayan /Abbot t , un i t s are 1 /ms . am1 = -0.1*(Vm1+40)/(exp(-0.1*(Vm1+40))-1); bm1 = 4*exp(-(Vm1+65)/18); ah1 = 0.07*exp(-0.05*(Vm1+65)); bh1 = 1/(1+exp(-0.1*(Vm1+35))); an1 = -0.01*(Vm1+55)/(exp(-0.1*(Vm1+55))-1); bn1 = 0.125*exp(-(Vm1+65)/80); am2 = -0.1*(Vm2+40)/(exp(-0.1*(Vm2+40))-1); bm2 = 4*exp(-(Vm2+65)/18); ah2 = 0.07*exp(-0.05*(Vm2+65)); bh2 = 1/(1+exp(-0.1*(Vm2+35))); an2 = -0.01*(Vm2+55)/(exp(-0.1*(Vm2+55))-1); bn2 = 0.125*exp(-(Vm2+65)/80); % From the a lpha and beta f o r each gat ing var i ab le we f i nd the s teady % s ta te va lues ( _ i n f ) and the t ime cons tan ts ( tau_ ) f o r each m,h and n . taum1 = 1e -3 / (am1+b m1) ; % t ime cons tan t conver ted f rom ms to sec minf1 = am1/(am1+bm1); tauh1 = 1e -3 / (ah1+bh1) ;% t ime cons tan t conver ted f rom ms to sec hinf1 = ah1/(ah1+bh1); taun1 = 1e -3 / (an1+bn1) ;% t ime cons tan t conver ted f rom ms to sec ninf1 = an1/(an1+bn1); taum2 = 1e -3 / (am2+b m2) ; % t ime cons tan t conver ted f rom ms to sec minf2 = am2/(am2+bm2); tauh2 = 1e -3 / (ah2+bh2) ;% t ime cons tan t conver ted f rom ms to sec hinf2 = ah2/(ah2+bh2); taun2 = 1e -3 / (an2+bn2) ;% t ime cons tan t conver ted f rom ms to sec ninf2 = an2/(an2+bn2); m i ) = m i - 1) + (m in f1 - m i - 1) ) *d t / taum1; 1( 1( 1( % Update m h1( i ) = h1( i - 1) + (h in f1 - h1( i - 1) ) *d%/ Update h t tauh1 ; n1( i ) = n1( i - 1) + (n in f1 - n1( i - 1) ) *d%/ Update n t taun1 ; m i ) = m i - 1) + (m in f2 - m i - 1) ) *d t / taum2; 2( 2( 2( % Update m h2( i ) = h2( i - 1) + (h in f2 - h2( i - 1) ) *d%/ Update h t tauh2 ; n2( i ) = n2( i - 1) + (n in f2 - n2( i - 1) ) *d%/ Update n t taun2 ; I _Na1 = g_Na*m1( i ) *m1( i ) *m1( i ) *h1 ( i ) * (E_Na -V1( i -ta l) ;sod ium cu r ren t % to 1) I _K1 = g_K*n1( i ) *n1 ( i ) *n1 ( i ) *n1 ( i ) * (E_K- V1( i - 1) ) ; % to ta l potass ium cu r ren t ig1= gsyn *s2(i-1) * (esyn - V1(i-1)); Itot1(i-1) = il1+I_Na1+I_K1+Iapp(i-1) + ig1; I _Na2 = g_Na*m2( i ) *m2( i ) *m2( i ) *h2 ( i ) * (E_Na -V2( i -ta l) ;sod ium cu r ren t % to 1) I _K2 = g_K*n2( i ) *n2 ( i ) *n2 ( i ) *n2 ( i ) * (E_K- V2( i - 1) ) ; % to ta l potass ium cu r ren t ig2=gsyn *s1(i-1) * (esyn - V2(i-1)); I t o t2 ( i - 1) = i l 2+ I _Na2+I_K2+Iapp( i - % to ta l ;cu r ren t i s sum o f l eak + ac t i ve 1) +ig2 channe l s + app l i ed cu r ren t + coup led V1( i ) = V1( i - 1) + I t o t1 ( i - 1)*d t / cm ; % +sigma*randn(1 ) *sq r t (d t ) / tau ; the me mbrane potent i a l , V. V2( i ) = V2( i - 1) + I t o t2 ( i - 1)*d t / cm ; % +sigma*randn(1 ) *sq r t (d t ) / tau ; the me mbrane potent i a l , V. % Update % Update i f ( vc lamp_ f l ag ) % i f we are us ing vo l tage c lamp V1( i ) = Vapp( i i)gno re the vo l tage i n tegra t i on and se t V to be the app l i ed %; vo l tage V2(i) = Vapp(i); end % Now check f o r sp i kes and update synapt i c gat ing var i ab les %s1( i ) = s1 ( i - 1) * exp ( - 1* (d t / t syn ) ) ; %cons tans t decay %s2( i ) = s2 ( i - 1) * exp ( - 1* (d t / t syn ) ) ; i f ( V1( i ) > Vsp i ke ) && ( sp i ke1now = 0f ) V1 i s at a sp i k ing l eve l , but the =i % sp i ke i s not a l ready detec ted sp i ke1now = 1 ; % detec t th i s sp i ke sp i kes1 ( i ) = 1 ; % reco rd th i s sp i ke t ime f o r j = 0 :nsp i kew id th % f o r many synapt i c t ime cons tan ts i n the f u tu re i f i+ j < l eng th ( s1 ) = % so l ong as we are s t i l l i n s i de the to ta l s imu la t i on t ime s1 ( i+ j ) = s1 ( i+ j ) + dt* j / t syn*exp ( - dt* j / t syn ) ;tance f rom % ex t ra conduc th i s sp i ke end end end i f ( V1( i ) < Vsp i ke - 0 .010 ) % once the sp i ke i s over sp i ke1now = 0 ; % se t th i s to ze ro so we are ready f o r the nex t sp i ke . end % Now do the same f o r sp i kes f rom neuron 2 . i f ( V2( i ) > Vsp i ke ) && ( sp i ke2now = 0 ) = spike2now = 1; spikes2(i) = 1; f o r j = 0 :nsp i kew id th i f i+ j < l eng th ( s2 ) = s2(i+j) = s2(i+j) + dt*j/tsyn*exp(-dt*j/tsyn); end end end i f ( V2( i ) < Vsp i ke - 0 .010 ) spike2now = 0; end end
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BIO NOTES 9/2 Energy Transfer (CH. 5) plants use oxygen to make sugars to store energy from sunlight; plants make CO2 also but not enough to keep them alive (both photosynth. and cell respiration) chloroplasts convert sun energy to chem. energy m
UNC - BIOL - 101L
LAB NOTESCell Structures Chlorophyta (most complex green algae representative) spherical colony = 500 to 50,000 cells cells on outside of colony are biflagellate; interconnected Paramecium Protozoans=animal-like protists; Ciliophora by cytoplasm
UNC - BIOL - 101
interp haseBIO NOTES Mitosis -cell division, helps you grow; reproduction in some organisms -purpose of mitosis: to maintain chromosome # -most frequent cell division in lining of digestive system A. G1 1st growth phase a. synthesis and growth b.
UNC - BIOL - 101
BIO NOTES Meiosis -1st slide: diploid; every gene has a partner -alleles = genes that occur at the same loci on homologous chromosomes -ovaries/testes = gonads, sperm/eggs = gametes (animals); anther &amp; ovary (plants) A. Meiosis I a. individual chrom
UNC - BIOL - 101
BIO NOTES Cell Respiration Energy from Glucose to ATP I. Oxygen Independent (in cytoplasm) a. Glycolysis (purpose: to make ATPs!) i. 6-C molecule glucose: C6H12O6 1. C-C-C-C-C-C 2. P-C-C-C-C-C-C-P 2 ATPs2 ADPs 2 ATP *ATPs made thru substrate phosphor
UNC - DRAM - 115
DRAMA 9/59/10 NOTES - Comedy komoidia = song of the revelers satyr play = short comic play to round out 3 tragic works at festival normative comedy = allows us to find humor, pokes gentle fun but not oriented toward any great change (ex: Everybody Lo
UNC - DRAM - 115
DRAMA 9/59/10 NOTES - Comedy komoidia = song of the revelers satyr play = short comic play to round out 3 tragic works at festival normative comedy = allows us to find humor, pokes gentle fun but not oriented toward any great change (ex: Everybody Lo
UNC - DRAM - 115
DRAMA 8/27 Notes Greek Drama City Dionysia festival in Athens (political celebration to parade its supremacy); began as events to worship Dionysus (half-mortal, mysterious to Greeks), but became more secular eventually Epic Poetry art of storytell
UNC - DRAM - 160
STAGECRAFT 8/26 NOTES Architecture (+History) *all speculation before written record; diff. viewpoints* Greek Theatre hillside w/ stage carved in, slanted seating = theatron playing space = orchestra skene = stage house (w/ doors, platforms, smal
Michigan State University - CJ - 110
CJ 110 Tests Test one: 1. In criminal justice process a(n) _ had to occur before a(n)_ can take place a. Trial; arraignment b. First appearance; booking c. Arrest; booking d. Sentence; arrest 2. Bail is usually set at the: a. First apperance before t
Michigan State University - CJ - 110
Criminal Justice Notes Monday Nov. 26th Final Examination December 11th, 3:00 5:00 Covers corrections, and all other sections No Class 12/3Sentencing Review Objectives A judge will rarely sentence a person on the spot. Pre-sentence evaluation:
Michigan State University - CJ - 110
CJ pt. 426/11/2007 14:52:00Sentencing Systems- After someone pleads guilty, or found guilty, sentencing date will be set. Probation dept. puts together history of person just convicted (time between found guilty and sentencing date) Punishment T
Michigan State University - CJ - 110
CJ Final Section I. Sentencing a. Sentencing Objectives two main sentencing objections dominating sentencing today is deterrence and incapacitation i. Retribution 1. Taking revenge. Eye for an eye 2. Just deserts (ex. Arizona Sheriff) a. Its 120 deg
Michigan State University - CJ - 110
CJ 110 notes 9/5/07 Criminal justice system should be an obstacle course to get through from the process of arrest to imprisonment/ sentencing Individual rights versus public order o Public safety Top priority: Top Concerns: CJ Process: Presumpt
Michigan State University - CJ - 110
CJ 110 Notes 9-12 Characteristics of Crime o Crime versus deviance Crime is a small subset of deviance (you must break a law) You can be deviant without being a criminal o The expansion of Law o Changes over time (priorities shift) o Seriousness v
Michigan State University - CJ - 110
CJ 110 10/15/07 Slide Notes I. Contemporary Policing a. Major Issues (Impact of science and technology) i. Why do we look at crime photos? ii. Why do we have an insatiable appetite for crime? iii. Major Issues of Science and Technology 1. The CSI Eff
Michigan State University - CJ - 110
CJ 110 Notes 10/17 I. Geographic Profiling a. Behavioral patterns and familiarity b. Offenders and geographic specific i. Social disorganization and routine activities the two main themes of geographic profiling 1. need motivated offender, vulnerabl
Michigan State University - CJ - 110
I. Fourth Amendment search and seizure of evidence a. What is a search? any violation of a persons expectation or privacy i. What is a seizure? exercise of control by a police officer ii. What is an unreasonable search? a search and seizure is fi
Michigan State University - CJ - 110
Courts I. Structure of Courts a. Functions of courts in society i. Dispute Resolution ii. Behavior Modification what sets societies norms by rewarding some behaviors and punishing others iii. Allocation of gains and losses courts responsibility to
Wisconsin - HIST - 101
History 2052008-09-03The Making of the Islamic World: The Middle East 500-1500Islam as a religion born in the broad day life born in Arabia creates own political and social system almost from scratch Muhammad- lived with no unified poltic
Wisconsin - HIST - 101
History 2232008-09-03ADIG Tacitus Suetonius Collector of gossip Describe the same women, but live after 80-100 years after the incident they are reporting on Done in the form of writing Ancient historians are always concerned with morality (
Wisconsin - HIST - 101
History 223: Explorations in European History Roman Women (and Men)Instructor: Prof. M. Kleijwegt; office hours: WF: 11:00-12:00; office: Humanities 5219; email: mkleijwegt@wisc.edu Teaching Assistant: Casey Stark Lecture Hall: Humanities 1101, MWF
Wisconsin - HIST - 101
History 1602008-09-02Nation BordersWays in which we categorize people Race Citizens Political beliefsIntroduction- Key Terms and ConceptsNation or Nation-StatePolitical concept which refers to an administrative apparatus deemed to
Nova Southeastern University - ENG - 1140
Character Analysis King Lear- He is the ruler of Britain who is planning on dividing the kingdom for his three daughters. Lear commands his daughters to answer the question: Which of you shall we say doth love us most (I.i.) The daughter who proves t
Nova Southeastern University - ENG - 1140
LEAR In the meantime I'll get down to my real business.Hand me that map over there. I hereby announce that I've divided my kingdom into three parts, which I'm handing over to the younger generation so I can enjoy a little rest and peace of mind in my
Nova Southeastern University - ENG - 1140
Jennifer Thai 08/25/08 Per. 03-AP Literature Perseus Perseus, the son of Zeus and Danae, was destined to be the murderer of his grandfather, Acrisius, but proved to be a hero as well in many ways. He rid the Earth of a deadly Gorgon, saved the beauti
Nova Southeastern University - ENG - 1140
Parallelism: Shakespeare establishes two separate dysfunctional family dramas from the first sentence of his play, both following the parallel structure of corrupted children scheming against their blinded fathers. The first of the two arises between
Nova Southeastern University - ENG - 1140
Jennifer Thai 09/01/08 Per. 03-AP Lit.Rapunzel (Damsel In Distress) Rapunzel is the perfect example of the damsel in distress archetype because she is literally locked in a tower, with no way out, and waiting for someone to come and save her. This
William & Mary - ECON - 101
CHAPTER 1 First Principles 1. Individual Choice Individual choice is the decision by an individual of what to do, which necessarily involves a decision of what not to do. Why must we choose?2. How Individuals Make Choices Basic principles behind
William & Mary - ECON - 101
Chapter 4 Activity1. A recent study found that the demand and supply schedules for Frisbees are as follows: Price Per Frisbee 11 10 9 8 7 6 Quantity Demanded 1 2 4 6 8 10 Quantity Supplied 15 12 9 6 3 1a. What are the equilibium price and quantity
William & Mary - PSYC - 201
9/2/08 Psychology Notes Why do research: Goals of any science o Prediction or estimate the likelihood of a phenomenon occurring o Understanding how or why it occurs Adding a causal explanation to a prediction Theory a proposed account of why/ho
William & Mary - PSYC - 201
Neurons! Three types a. Sensory from external world to spinal cord and brain b. Motor movement (eating) (nom nom nom) c. Interneurons receive messages from sensory and other interneurons; send messages to other interneurons and motor neurons; mak
William & Mary - PHYS - 176
Astronomy 9/17/08 Doppler shift in lightWave = the observed wavelength (shifted) Wave-o is the emitted wavelength V is the radial velocity C is speed of light Redshift increase in wavelength Blueshift decrease in wavelength Dark energy? in order
LSU - ASTR - 1100
AstronomyandtheUniverse1. SolarSystemBodiesONLYforourSolarSystem! a. Planetslargeenoughtobecomesphericalunderitsowngravity,rotatearoundthesun,andhas clearedoutitsorbit(wehave8planets) i. Patternoftheplanetsisexplainedthroughphysics.Becauseofthis,we
LSU - ASTR - 1100
EclipsesandtheMotionoftheMoon1. LightSource a. Thesunisthelightsourceforoursolarsystem b. Theearthandmoonarespherical i. Halfoftheearthandmoonarealwayslit,andtheotherhalfareintheshadow 2. PhasesoftheMoon a. Thisisthepercentageoftheilluminatedsizewe