Inhibitory Plasticity Balances Excitation And Inhibition-Books Pdf

Inhibitory Plasticity Balances Excitation and Inhibition
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Fig 1 Inhibitory synaptic plas A B C, ticity balances excitation and Stimulus In 8 100. inhibition A Feedforward inhi In 1 60, bition Excitatory input reaches a. target region through both direct EX Ex 1 20, excitation and indirect disynaptic 20. inhibition B Feedforward inhi Ex 8 80 40 0 40 80, bition for a single postsynaptic Spike Timing ms. cell Eight groups of 100 excit BEFORE, atory and 25 inhibitory synapses D Inh E 100 Ex Inh F.
Mem Curr nA, Av Curr pA, each deliver spikes to a single Net 0 5 100 700. 0 5 0 25 60, postsynaptic cell Spiking prob S5, Ave inh cond pS. Firing Rate Hz, abilities are homogeneous with 0 5. in the groups but vary in time 1 5 S3 500, simulating eight separate color Spikes 1 2 3 4 5 6 7 8. coded signal channels that reach 50, DURING 300, the cell simultaneously through 100.
Av Curr pA, Mem Curr nA, excitatory and inhibitory synaps 1 5. es C Spike timing dependent 0 5 60, Downloaded from www sciencemag org on January 18 2012. learning rule Near coincident pre 0 5, and postsynaptic spikes poten 1 5 0 25 0 5 0 2 4 6. tiate inhibitory synapses marked Spikes 1 2 3 4 5 6 7 8 Time min. with in A and B whereas, every presynaptic spike causes AFTER G Simulation. Output Rate Hz, Mem Curr nA, synaptic depression D Total ex 1 5 100 Prediction.
Av Curr pA, citatory black inhibitory gray 0 5, and net green membrane cur 60 5 5. rents before during and after 20, inhibitory synaptic plasticity 1 5. Spikes 0 0, The resulting spikes are indi 0 25 0 5 1 2 3 4 5 6 7 8 0 5 10 0 10 20 30. cated as dots underneath each Time s Signal no 0 Hz Input Rate Hz. current plot E Excitatory and, inhibitory membrane currents black and white symbols respectively evoked nals dotted lines and indicate the times at which the top middle. by each signal channel averaged over 4 s before during and after inhibitory and bottom graphs of D and E were recorded G Average firing rate of the. synaptic plasticity top middle and bottom respectively F Temporal evo postsynaptic neuron after learning plotted for different values of target firing. lution of the postsynaptic firing rate solid line and the average synaptic rate r0 left and different input rates right The dashed lines in both graphs. weights of the inhibitory synapses associated with three representative sig show the analytical predictions. with reversal potentials V E 0 mV and V I synapses were set to nonzero strengths the post er because detailed balance requires a correlation. 80 mV and time constants tE 5 ms and tI synaptic neuron fired at high rates when the in between excitatory and inhibitory synaptic in. 10 ms for excitation and inhibition respective hibitory synapses were weak at the beginning of puts the balance deteriorated when the delay be. ly see supporting online material SOM The a simulation Fig 1 D and E top and F The tween excitation and inhibition increased to values. strength of the inhibitory synapses was initially resulting high number of pairs of pre and post larger than the autocorrelation time of the input. weak but could change according to a spike synaptic spikes led to relatively indiscriminate signals and the coincidence time of the Hebbian. timing dependent plasticity rule in which near strengthening of all inhibitory synapses Fig 1 D learning rule but global balance still persisted. coincident pre and postsynaptic spikes induce and E middle until excitatory and inhibitory fig S2. potentiation of the synapse 17 19 Additional membrane currents became approximately ba To investigate how the state of the balance. ly every presynaptic spike leads to synaptic lanced and the postsynaptic firing rate was dra affects the neuron s response properties we pres. depression 17 18 Fig 1C This learning rule matically reduced Fig 1F In this globally ented a fixed stimulus sequence to the neuron. can be summarized as balanced state only unbalanced excitatory sig Fig 2A and compared the spiking response. nals led to coincident pairs of pre and postsynaptic over 50 trials to the input rates of each signal. Dw h pre post r0 pre 1 spikes consequently strengthening underpowered In the globally balanced state Fig 2B top in. inhibitory synapses Those inhibitory synapses that which inhibitory synapses were distributed so. where w denotes the change in synaptic effi were stronger than their excitatory counterparts that excitation and inhibition were balanced only. cacy pre and post are the pre and postsynaptic kept the postsynaptic side unresponsive and on average across all channels the peristimulus. activity h is the learning rate and r0 is a con were thus weakened because of sole presynaptic time histogram PSTH faithfully reproduced the. stant that acts as a target rate for the postsynaptic firing until they allowed postsynaptic spiking firing rates of the preferred signals The other non. neuron see SOM Sec 2 for a mathematical again Over time this led to a precise detailed preferred input signals evoked more inhibition. analysis balance of excitatory and inhibitory synaptic than excitation and thus had no impact on the cell s. Whereas inhibitory synapses were plastic the weights for each channel Fig 1 D and E bot firing behavior An additional steplike input rate. efficacies of the excitatory model synapses were tom In agreement with the mathematical anal protocol in which 100 ms long pulses of various. fixed at the beginning of a simulation and left ysis the postsynaptic firing rate was determined step sizes Fig 2C were presented to one channel. unchanged unless otherwise noted Analogous to mainly by the depression factor r0 but not by the at a time revealed that spiking responses are. frequency or orientation tuned sensory neurons average input firing rate to the postsynaptic neu largely insensitive to stimulus intensity and indeed. excitatory synapses were tuned to have a pre ron Fig 1G The mechanism was robust to narrowly tuned to the preferred stimulus giving. ferred signal Fig 1E Because all excitatory plausible delays of several milliseconds Howev rise to an all or none response Fig 2 D and E. 1570 16 DECEMBER 2011 VOL 334 SCIENCE www sciencemag org. A 100 pS C D Phasic Resp E Tonic Resp, Fire Rate Hz.
Input step Hz, Global Balance, 6 30 10Hz 30, 7 25 5Hz 25. 1 sec 20 20, B Global Balance, Cross Correlation 1. 12345678 12345678, 0 4 non preferred preferred, F S3 S5 G H. Detailed Balance, Input step Hz, 12345678 35, Detailed Balance 30 30. 0 8 100 ms, 12345678 0 15 15, Signal no 12345678 12345678 12345678.
Signal no Signal no Signal no, Fig 2 Inhibitory synaptic plasticity sparsifies and democratizes receptive C Schematic of a step stimulus delivered with large and small step sizes. fields A A fixed sequence of eight stimuli of varying firing rates is fed solid and dotted black lines respectively Sample PSTHs for nonpreferred. repetitively into a postsynaptic cell Excitatory synapses are strength tuned red and preferred blue stimuli to both step sizes are shown for a globally. Downloaded from www sciencemag org on January 18 2012. by signal group see conductance graph on the right so that signal five balanced cell D and E Iso response contour lines of the postsynaptic cell. marked also by dashed lines is the preferred signal B Postsynaptic spikes in the globally balanced regime during the onset phasic 0 to 50 ms D. over 50 trials with globally or detailed balanced inhibitory synapses top and and tonic 50 to 100 ms E parts of the response F Sample responses for. bottom graphs respectively as indicated by the schematics on the left nonpreferred red and preferred blue stimuli to both step stimuli as in. compare with Fig 1E The normalized and squared cross correlation co C G and H Iso response contour lines as in D and E for a detailed. efficients between each input signal and the PSTH are also shown right balanced cell. BEFORE AFTER 3 0 with experimental results 5 7 8 23 24 and. A B E Experiment confirm earlier theoretical studies arguing that. EXPERIMENT, Normalized current, Cell 3 sharp tuning is not a necessary feature for a sparse. Normalized current, 1 0 30 min, 1 0 sensory representation 25 26 The sparsity of the. response to each signal was a direct consequence, 0 5 0 5 1 5. of the detailed balance of correlated excitatory and. inhibitory synapses as described above not of the, 0 0 0 0 specificity of the tuning curve.
0 5 1 2 4 8 16 32 0 5 1 2 4 8 16 32 1 0, Frequency kHz Frequency kHz The self organizing dynamics of inhibitory. 0 5 plasticity imply that the excitatory inhibitory ba. C D lance is maintained even in the presence of on. Av current pA, Av current pA, going excitatory plasticity Fig 3 Experiments. F 0 60 120 180, 20 7 in which a stimulus alters the frequency. 10 tuning of excitatory input currents to pyramidal. 20 20 5 neurons in rat primary auditory cortex point in. 0 a similar direction The disrupted cotuning of, 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 0 60 120 180. Stimulus no Stimulus no Time min excitatory and inhibitory input currents Fig. 3A prompts a compensatory response that sub, Fig 3 Temporal dynamics of inhibitory plasticity experiment and model Frequency tuned excitatory sequently changes the amplitude of the inhibitory.
and inhibitory membrane currents black and white symbols respectively as recorded from pyramidal input currents After 180 min the cell returns to a. cells in the primary auditory cortex of adult rat 7 A 30 min and B 180 min after a stimulus protocol cotuned state albeit with a different preferred. shifted the preferred frequency of the excitatory membrane currents from 16 to 4 kHz Similarly stimulus frequency Fig 3B When we disturbed the co. tuned input currents in a simulation C 30 min and D 180 min after manually changing the excitatory tuning of a simulated neuron in a similar way. tuning curve Solid and open arrowheads indicate the previous and the new preferred stimuli in all panels. Fig 3C inhibitory plasticity rebalanced the ex, E Summary plot of the ratios of excitatory and inhibitory current amplitudes of previously preferred. citatory input currents Fig 3 D and E and, stimuli and new preferred stimuli as indicated in A to D in the experiment open and solid symbols. respectively and simulations blue and red lines respectively F Firing rate of the simulated neuron stabilized the output firing rates of the postsyn. over the time of the simulation in E Error bars indicate SEM A B and E adapted from 7 with aptic neurons Fig 3F Quantitative agreement. permission with the rebalancing dynamics observed in the. experiment for both synaptic depression and, potentiation was achieved by adjusting h r0. In the detailed balanced state the response of each other and thus failed to evoke a reliable and the average firing rate of the inhibitory input. the cell was sparse Fig 2B bottom and rem postsynaptic response Seemingly indifferent to neurons. iniscent of experimental observations 16 20 22 the tuning of the excitatory synapses each signal The learning rule for inhibitory synapses does. across many sensory systems Spikes were caused contributed an equal part to the PSTH of the not rely on a feedforward structure to achieve low. primarily by transients in the input signals during output signal but the effect of the excitatory syn firing rates It simply matches excitatory and in. which the faster dynamics of the excitatory syn aptic weights was uncovered by the steplike input hibitory synapses that show correlated activity. apses momentarily overcame inhibition Sustained protocol Fig 2F The broad graded responses We therefore tested whether inhibitory plasticity. episodes of presynaptic firing on the other hand as opposed to all or none to preferred and non was able to stabilize the dynamics of recurrent. caused steady membrane currents that canceled preferred stimuli Fig 2 G and H were in accord networks In simulations of such networks 13. www sciencemag org SCIENCE VOL 334 16 DECEMBER 2011 1571. with plastic inhibitory synapses that were initially memory attractors can be for long term memory recordings of neuronal activity would thus not. weak Fig 4A the resulting high firing rates systems if only one of all stored memories can be reveal the presence of a synaptic memory trace. and subsequent increase in inhibitory synaptic active at a time and potentially remains active in this state. strengths caused by the plasticity rule indeed for long periods of time broadcasting the stored Retrieval of previously quiescent memory. produced globally balanced input currents that information into the network 29 items could be achieved by momentarily dis. led to a self organized AI network state Fig Inhibitory plasticity can solve some of these rupting the balance within a cell assembly for. 4B with firing rates between 3 and 15 Hz problems After two arbitrarily chosen groups of example through additional excitatory input It. We wondered whether it was possible to in excitatory neurons were turned into Hebbian as was sufficient to drive a small fraction of the. troduce associative memories to the stabilized semblies by strengthening the excitatory con cells of one assembly to reactivate all cells of that. network by strengthening specific excitatory nections within the groups fivefold the assemblies assembly Notably the recall was asynchronous. connections within dedicated groups of neurons temporarily fired at high rates and raised the and irregular as indicated by low correlations. First proposed by Hebb 27 such cell assem background firing rate across the network Fig between neurons and large variability of the in. Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks T P Vogels 1 H Sprekeler F Zenke 1 C Clopath 1 2 W Gerstner Cortical neurons receive balanced excitatory and inhibitory synaptic currents Such a balance could be established and maintained in an experience dep endent manner by synaptic plasticity at inhibitory synapses We show that

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