scholarly journals Experience-Dependent Plasticity in S1 Caused by Noncoincident Inputs

2005 ◽  
Vol 94 (3) ◽  
pp. 2239-2250 ◽  
Author(s):  
David T. Blake ◽  
Fabrizio Strata ◽  
Richard Kempter ◽  
Michael M. Merzenich
Keyword(s):  
Time Window ◽  
Cortical Excitability ◽  
Receptive Fields ◽  
Stimulus Onset ◽  
Spike Timing ◽  
Interval Length ◽  
Response Latencies ◽  
Dependent Plasticity ◽  
Cortical Implants ◽  
Somatic Sensory Cortex

Prior work has shown that coincident inputs became corepresented in somatic sensory cortex. In this study, the hypothesis that the corepresentation of digits required synchronous inputs was tested, and the daily development of two-digit receptive fields was observed with cortical implants. Two adult primates detected temporal differences in tap pairs delivered to two adjacent digits. With stimulus onset asynchronies of ≥100 ms, representations changed to include two-digit receptive fields across the first 4 wk of training. In addition, receptive fields at sites responsive to the taps enlarged more than twofold, and receptive fields at sites not responsive to the taps had no significant areal change. Further training did not increase the expression of two-digit receptive fields. Cortical responses to the taps were not dependent on the interval length. Stimuli preceding a hit, miss, false positives, and true negatives differed in the ongoing cortical rate from 50 to 100 ms after the stimulus but did not differ in the initial, principal, response to the taps. Response latencies to the emergent responses averaged 4.3 ms longer than old responses, which occurs if plasticity is cortical in origin. New response correlations developed in parallel with the new receptive fields. These data show corepresentation can be caused by presentation of stimuli across a longer time window than predicted by spike-timing–dependent plasticity and suggest that increased cortical excitability accompanies new task learning.

scholarly journals Response Properties of Whisker-Related Neurons in Rat Second Somatosensory Cortex

2004 ◽  
Vol 92 (4) ◽  
pp. 2083-2092 ◽  
Author(s):  
Ernest E. Kwegyir-Afful ◽  
Asaf Keller
Keyword(s):  
Somatosensory Cortex ◽  
Receptive Fields ◽  
Stimulus Onset ◽  
Similar Response ◽  
Activity Levels ◽  
Response Latencies ◽  
Response Properties ◽  
Fast Spiking ◽  
Evoked Activity ◽  
Lemniscal System

In addition to a primary somatosensory cortex (SI), the cerebral cortex of all mammals contains a second somatosensory area (SII); however, the functions of SII are largely unknown. Our aim was to explore the functions of SII by comparing response properties of whisker-related neurons in this area with their counterparts in the SI. We obtained extracellular unit recordings from narcotized rats, in response to whisker deflections evoked by a piezoelectric device, and compared response properties of SI barrel (layer IV) neurons with those of SII (layers II to VI) neurons. Neurons in both cortical areas have similar response latencies and spontaneous activity levels. However, SI and SII neurons differ in several significant properties. The receptive fields of SII neurons are at least five times as large as those of barrel neurons, and they respond equally strongly to several principal whiskers. The response magnitude of SII neurons is significantly smaller than that of neurons in SI, and SII neurons are more selective for the angle of whisker deflection. Furthermore, whereas in SI fast-spiking (inhibitory) and regular-spiking (excitatory) units have different spontaneous and evoked activity levels and differ in their responses to stimulus onset and offset, SII neurons do not show significant differences in these properties. The response properties of SII neurons suggest that they are driven by thalamic inputs that are part of the paralemniscal system. Thus whisker-related inputs are processed in parallel by a lemniscal system involving SI and a paralemniscal system that processes complimentary aspects of somatosensation.

scholarly journals Response Properties of Whisker-Associated Trigeminothalamic Neurons in Rat Nucleus Principalis

2003 ◽  
Vol 89 (1) ◽  
pp. 40-56 ◽  
Author(s):  
Brandon S. Minnery ◽  
Daniel J. Simons
Keyword(s):  
Receptive Fields ◽  
Stimulus Onset ◽  
Response Latencies ◽  
Primary Afferent ◽  
Medial Nucleus ◽  
Afferent Fibers ◽  
Highly Sensitive ◽  
Primary Afferent Fibers ◽  
Stimulus Features ◽  
Nucleus Principalis

Nucleus principalis (PrV) of the brain stem trigeminal complex mediates the processing and transfer of low-threshold mechanoreceptor input en route to the ventroposterior medial nucleus of the thalamus (VPM). In rats, this includes tactile information relayed from the large facial whiskers via primary afferent fibers originating in the trigeminal ganglion (NV). Here we describe the responses of antidromically identified VPM-projecting PrV neurons ( n = 72) to controlled ramp-and-hold deflections of whiskers. For comparison, we also recorded the responses of 64 NV neurons under identical experimental and stimulus conditions. Both PrV and NV neurons responded transiently to stimulus onset (on) and offset (off), and the majority of both populations also displayed sustained, or tonic, responses throughout the plateau phase of the stimulus (75% of NV cells and 93% of PrV cells). Averageon and off response magnitudes were similar between the two populations. In both NV and PrV, cells were highly sensitive to the direction of whisker deflection. Directional tuning was slightly but significantly greater in NV, suggesting that PrV neurons integrate inputs from NV cells differing in their preferred directions. Receptive fields of PrV neurons were typically dominated by a “principal” whisker (PW), whose evoked responses were on average threefold larger than those elicited by any given adjacent whisker (AW; n = 197). However, of the 65 PrV cells for which data from at least two AWs were obtained, most (89%) displayed statistically significanton responses to deflections of one or more AWs. AW response latencies were 2.7 ± 3.8 (SD) ms longer than those of their corresponding PWs, with an inner quartile latency difference of 1–4 ms (±25% of median). The range in latency differences suggests that some adjacent whisker responses arise within PrV itself, whereas others have a longer, multi-synaptic origin, possibly via the spinal trigeminal nucleus. Overall, our findings reveal that the stimulus features encoded by primary afferent neurons are reflected in the responses of VPM-projecting PrV neurons, and that significant convergence of information from multiple whiskers occurs at the first synaptic station in the whisker-to-barrel pathway.

scholarly journals Single pairing spike-timing dependent plasticity in BiFeO3 memristors with a time window of 25 ms to 125 μs

2015 ◽  
Vol 9 ◽  
Author(s):  
Nan Du ◽  
Mahdi Kiani ◽  
Christian G. Mayr ◽  
Tiangui You ◽  
Danilo Bürger ◽  
...  
Keyword(s):  
Time Window ◽  
Spike Timing ◽  
Spike Timing Dependent Plasticity ◽  
Dependent Plasticity

scholarly journals Functional consequences of pre- and postsynaptic expression of synaptic plasticity

2016 ◽  
Author(s):  
Rui Ponte Costa ◽  
Beatriz E.P. Mizusaki ◽  
P. Jesper Sjöström ◽  
Mark C. W. van Rossum
Keyword(s):  
Synaptic Plasticity ◽  
Research Effort ◽  
Receptive Fields ◽  
Spike Timing ◽  
Response Latencies ◽  
Considerable Research ◽  
Open Questions ◽  
Hebbian Plasticity ◽  
Functional Consequences ◽  
Specific Locus

AbstractGrowing experimental evidence shows that both homeostatic and Hebbian synaptic plasticity can be expressed presynaptically as well as postsynaptically. In this review, we start by discussing this evidence and methods used to determine expression loci. Next, we discuss functional consequences of this diversity in pre- and postsynaptic expression of both homeostatic and Hebbian synaptic plasticity. In particular, we explore the functional consequences of a biologically tuned model of pre- and postsynaptically expressed spike-timing-dependent plasticity complemented with postsynaptic homeostatic control. The pre- and postsynaptic expression in this model predicts 1) more reliable receptive fields and sensory perception, 2) rapid recovery of forgotten information (memory savings) and 3) reduced response latencies, compared to a model with postsynaptic expression only. Finally we discuss open questions that will require a considerable research effort to better elucidate how the specific locus of expression of homeostatic and Hebbian plasticity alters synaptic and network computations.

scholarly journals Memory Retention and Spike-Timing-Dependent Plasticity

2009 ◽  
Vol 101 (6) ◽  
pp. 2775-2788 ◽  
Author(s):  
Guy Billings ◽  
Mark C. W. van Rossum
Keyword(s):  
Retention Time ◽  
Single Neuron ◽  
Receptive Fields ◽  
Learning Rule ◽  
Spike Timing ◽  
Memory Retention ◽  
Neuron Models ◽  
Spike Timing Dependent Plasticity ◽  
Dependent Plasticity ◽  
Dependent Learning

Memory systems should be plastic to allow for learning; however, they should also retain earlier memories. Here we explore how synaptic weights and memories are retained in models of single neurons and networks equipped with spike-timing-dependent plasticity. We show that for single neuron models, the precise learning rule has a strong effect on the memory retention time. In particular, a soft-bound, weight-dependent learning rule has a very short retention time as compared with a learning rule that is independent of the synaptic weights. Next, we explore how the retention time is reflected in receptive field stability in networks. As in the single neuron case, the weight-dependent learning rule yields less stable receptive fields than a weight-independent rule. However, receptive fields stabilize in the presence of sufficient lateral inhibition, demonstrating that plasticity in networks can be regulated by inhibition and suggesting a novel role for inhibition in neural circuits.

scholarly journals Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution

2007 ◽  
Vol 19 (3) ◽  
pp. 639-671 ◽  
Author(s):  
Taro Toyoizumi ◽  
Jean-Pascal Pfister ◽  
Kazuyuki Aihara ◽  
Wulfram Gerstner
Keyword(s):  
Optimality Criterion ◽  
Receptive Fields ◽  
Spike Timing ◽  
Postsynaptic Neuron ◽  
Spike Timing Dependent Plasticity ◽  
Basic Principles ◽  
Dependent Plasticity ◽  
The Mean ◽  
Synaptic Dynamics ◽  
The Stability

We studied the hypothesis that synaptic dynamics is controlled by three basic principles: (1) synapses adapt their weights so that neurons can effectively transmit information, (2) homeostatic processes stabilize the mean firing rate of the postsynaptic neuron, and (3) weak synapses adapt more slowly than strong ones, while maintenance of strong synapses is costly. Our results show that a synaptic update rule derived from these principles shares features, with spike-timing-dependent plasticity, is sensitive to correlations in the input and is useful for synaptic memory. Moreover, input selectivity (sharply tuned receptive fields) of postsynaptic neurons develops only if stimuli with strong features are presented. Sharply tuned neurons can coexist with unselective ones, and the distribution of synaptic weights can be unimodal or bimodal. The formulation of synaptic dynamics through an optimality criterion provides a simple graphical argument for the stability of synapses, necessary for synaptic memory.

Pulvinar nuclei of the behaving rhesus monkey: visual responses and their modulation

1985 ◽  
Vol 54 (4) ◽  
pp. 867-886 ◽  
Author(s):  
S. E. Petersen ◽  
D. L. Robinson ◽  
W. Keys
Keyword(s):  
Discharge Rate ◽  
Receptive Fields ◽  
Stimulus Onset ◽  
Visual Response ◽  
Visual Responses ◽  
Response Latencies ◽  
Stimulus Movement ◽  
Selective Visual Attention ◽  
Retinotopic Organization ◽  
A Cell

We have examined the properties of neurons in three subdivisions of the pulvinar of alert, trained rhesus monkeys 1) an inferior, retinotopically mapped area (PI), 2) a lateral, retinotopically organized region (PL), and 3) a dorsomedial visual portion of the lateral pulvinar (Pdm), which has a crude retinotopic organization. We tested the neurons for visual responses to stationary and moving stimuli and for changes in these responses produced by behavioral manipulations. All areas contain cells sensitive to stimulus orientation as well as neurons selective for the direction of stimulus movement; however, the majority of cells in all three regions are either broadly tuned or nonselective for these attributes. Nearly all cells respond to stimulus onset, a significant number also give a response to stimulus termination, and rarely a cell gives only off responses. Nearly all cells increase their discharge rate to visual stimuli. Receptive fields in the two retinotopically mapped regions, PI and PL, have well-defined borders. The sizes of these receptive fields show a positive correlation with the eccentricity of the receptive fields. The receptive fields in the remaining region, Pdm, are frequently very large, but with these large fields excluded, show a similar correlation with eccentricity. All pulvinar cells tested (n = 20) were mapped in retinal coordinates; the receptive fields are positioned in relation to the retina. We found no cells with gaze-gated characteristics (2), nor cells mapped in a spatial coordinate system. The response latencies in PI and PL are shorter and less variable than the latencies in Pdm. Active use of a stimulus can produce an enhancement or attenuation of the visual response. Eye-movement modulation was found in all three subdivisions in about equal frequencies. Attentional modulation was common in Pdm and was rare in PI and PL. The modulation is spatially selective in Pdm and nonselective in PI for a small number of tested cells. These data demonstrate functional differences between Pdm and the other two areas and suggest that Pdm plays a role in selective visual attention, whereas PI and PL probably contribute to other aspects of visual perception.

scholarly journals Functional consequences of pre- and postsynaptic expression of synaptic plasticity

2017 ◽  
Vol 372 (1715) ◽  
pp. 20160153 ◽  
Author(s):  
Rui Ponte Costa ◽  
Beatriz E. P. Mizusaki ◽  
P. Jesper Sjöström ◽  
Mark C. W. van Rossum
Keyword(s):  
Synaptic Plasticity ◽  
Research Effort ◽  
Receptive Fields ◽  
Spike Timing ◽  
Homeostatic Plasticity ◽  
Response Latencies ◽  
Open Questions ◽  
Hebbian Plasticity ◽  
Functional Consequences ◽  
Specific Locus

Growing experimental evidence shows that both homeostatic and Hebbian synaptic plasticity can be expressed presynaptically as well as postsynaptically. In this review, we start by discussing this evidence and methods used to determine expression loci. Next, we discuss the functional consequences of this diversity in pre- and postsynaptic expression of both homeostatic and Hebbian synaptic plasticity. In particular, we explore the functional consequences of a biologically tuned model of pre- and postsynaptically expressed spike-timing-dependent plasticity complemented with postsynaptic homeostatic control. The pre- and postsynaptic expression in this model predicts (i) more reliable receptive fields and sensory perception, (ii) rapid recovery of forgotten information (memory savings), and (iii) reduced response latencies, compared with a model with postsynaptic expression only. Finally, we discuss open questions that will require a considerable research effort to better elucidate how the specific locus of expression of homeostatic and Hebbian plasticity alters synaptic and network computations. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.

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