Adaptive Coincidence Detection and Dynamic Gain Control in Visual Cortical Neurons In Vivo

Azouz, Rony; Gray, Charles M.

doi:10.1016/s0896-6273(02)01186-8

Cited by 264 publications

(280 citation statements)

References 54 publications

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“…Synaptic unreliability might argue against the preservation of information on this temporal scale (2), but the mere fact that the synchronous activity is found on this, or even finer, time scales (38) proves this is not an obstacle for a coding system that is based on synchrony (40). Synaptic unreliability is overcome through coincident inputs (6), temporal integration and synaptic facilitation (12,19), oscillations (7), and activity-dependent changes in integration times (21,38,(41)(42)(43). These mechanisms can maintain and propagate synchrony throughout the visual hierarchy to form new synchronized assemblies at the perceptual level (4-7).…”

Section: Resultsmentioning

confidence: 99%

Cooperative synchronized assemblies enhance orientation discrimination

Samonds

Allison

Brown

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

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There is no clear link between the broad tuning of single neurons and the fine behavioral capabilities of orientation discrimination. We recorded from populations of cells in the cat visual cortex (area 17) to examine whether the joint activity of cells can support finer discrimination than found in individual responses. Analysis of joint firing yields a substantial advantage (i.e., cooperation) in fineangle discrimination. This cooperation increases to more considerable levels as the population of an assembly is increased. The cooperation in a population of six cells provides encoding of orientation with an information advantage that is at least 2-fold in terms of requiring either fewer cells or less time than independent coding. This cooperation suggests that correlated or synchronized activity can increase information.T raditionally, research in sensory cortex has sought to link sensory information with changes in the impulse rate of single neurons (1), under the presumption that the rate code is the primary signaling modality. The principle of a rate code has also been applied to a population of cells (2, 3), but concerns still arise about the ambiguities of rates, and the ability of a rate code to account for perceptual phenomena such as association, generalization, hyperacuity, and contextual modulation has been debated (2-8). Alternative theories of cortical function (4-8) require a reliable means of preserving the temporal information of impulses in a cortical network of unreliable synapses. Information-theoretic methods demonstrate the existence of links between the temporal structure of neural responses and sensory input (9-11), and mechanisms capable of generating predictable temporal patterns (e.g., bursts and oscillations) by means of intrinsic cellular properties and network interactions have been well documented (12)(13)(14). However, temporal information is relevant only when an appropriate decoding mechanism exists (15). Synchronization between neural assemblies provides one such mechanism for encoding, and possibly decoding, temporal structure because synchrony is dependent on temporal patterns (17)(18)(19) and is correlated with the orientation (17-19) and coherence (17,18,20) of visual stimuli.We have previously shown (21) that the orientation selectivity of dependency (a numeric measure reflecting synchrony) between two cells is on average 35.5% narrower than the selectivity of their individual rate tuning. Similar results have been documented with other methods (19,22). We also measured positive synergy (i.e., cooperation; information available only in the joint activity of the cells) among pairs of cells, at least for discriminating fine differences in orientation (21). The average bin width (4.6 ms) and discharge history (total time of 9.2 ms) of this analysis suggested that the cooperation results from correlated (or synchronous) activity. Traditionally, correlation among cells has been considered a limitation in the information capacity of population coding (23). However, because correl...

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Section: Resultsmentioning

confidence: 99%

Cooperative synchronized assemblies enhance orientation discrimination

Samonds

Allison

Brown

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

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“…This focusing will increase the impact of that spiking activity onto postsynaptic target neurons, because the latter act as coincidence detectors (1,4,6,28,29). When those target neurons get entrained to the input rhythm, they will undergo correlated excitability fluctuations and this will likely further increase the impact of the most gamma-locked spikes.…”

Section: Discussionmentioning

confidence: 99%

“…This tight coordination between excitation and inhibition generates steep membrane potential slopes at particular phases of the gamma cycle. Those fast membrane depolarizations are crucial in triggering postsynaptic spikes (1,28) and thereby crucial in closing a reverberant cortical loop. It is important to note that the tight coordination of excitation and inhibition quenches noisy slow fluctuations in synaptic input (35) and thereby reduces the noise in the cell's output and most likely also the noise correlation among neighboring cells.…”

Section: Discussionmentioning

confidence: 99%

Orientation selectivity and noise correlation in awake monkey area V1 are modulated by the gamma cycle

Womelsdorf

Lima²,

Vinck³

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

119

120

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Gamma-band synchronization adjusts the timing of excitatory and inhibitory inputs to a neuron. Neurons in the visual cortex are selective for stimulus orientation because of dynamic interactions between excitatory and inhibitory inputs. We hypothesized that these interactions and hence also orientation selectivity vary during the gamma cycle. We determined for each spike its phase relative to the gamma cycle. As a function of gamma phase, we then determined spike rates and their orientation selectivity. Orientation selectivity was modulated by gamma phase. The firing rate of spiking activity that occurred close to a neuron's mean gamma phase of firing was most orientation selective. This stimulus-selective signal could best be conveyed to postsynaptic neurons if it were not corrupted by noise correlations. Noise correlations between firing rates were modulated by gamma phase such that they were not statistically detectable for the spiking activity occurring close to a neuron's mean gamma phase of firing. Thus, gamma-band synchronization produces spiking activity that carries maximal stimulus selectivity and minimal noise correlation in its firing rate, and at the same time synchronizes this spiking activity for maximal impact on postsynaptic targets. oscillation | primary visual cortex | neuronal coding | neuronal tuning | information theory R hythmic neuronal synchronization has been described in numerous brain systems, species, and under many different conditions. A prominent proposal is that rhythmically synchronized spikes have an enhanced impact on target neurons. This consequence of synchronization might stem from direct feedforward triggering of coincidence detection mechanisms, from the entrainment of target neurons, or from both mechanisms in conjunction (1-4). This proposal has been detailed in several computational studies (5, 6) and has received substantial experimental support (7-11).Here, we ask a complementary, yet central question: Does the rhythmically synchronized spiking activity, besides its enhanced impact, also carry an enhanced representation of, e.g., a sensory stimulus in its firing rate? One of the best-studied cases of neuronal stimulus selectivity is the orientation selectivity of neurons in primary visual cortex. We recorded from several sites in awake monkey primary visual cortex while it was stimulated with patches of drifting grating that varied in orientation. Those stimuli induced strong gamma-band synchronization. We sorted spikes based on the phase in the gamma cycle at which they occurred, and we tested whether orientation selectivity varied as a function of phase in the gamma cycle.Stimulus-selective neuronal responses signal a stimulus to postsynaptic target neurons most effectively when they are not corrupted by so-called correlated noise. The term "noise" is often used to denote variance in neuronal activity that is not explained by variance in the sensory stimulus. This so-called noise might well be fully determined, just by brain processes that are not determined by the...

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“…Spike generation has been shown to be dependent on the temporal microstructure of membrane potential fluctuations. High frequency fluctuations in membrane potential lead to higher firing rates, whereas spike rates are lower for the same mean membrane potential without rapid fluctuations [5,6,71,72]. Furthermore, the membrane potential contains more high frequency fluctuations in response to the preferred orientation than in response to non-preferred orientations [6,72].…”

Section: Mechanisms Regulating Spike Tuning Near Pinwheel Centersmentioning

confidence: 99%

“…High frequency fluctuations in membrane potential lead to higher firing rates, whereas spike rates are lower for the same mean membrane potential without rapid fluctuations [5,6,71,72]. Furthermore, the membrane potential contains more high frequency fluctuations in response to the preferred orientation than in response to non-preferred orientations [6,72]. In fact, the tuning curve of high frequency components of the membrane potential are more similar to the firing rate tuning curves than are the tuning curves of other slower components of the subthreshold response.…”

Section: Mechanisms Regulating Spike Tuning Near Pinwheel Centersmentioning

confidence: 99%

Local networks in visual cortex and their influence on neuronal responses and dynamics

Schummers¹,

Mariño²,

Sur³

2004

Journal of Physiology-Paris

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Networks of neurons in the cerebral cortex generate complex outputs that are not simply predicted by their inputs. These emergent responses underlie the function of the cortex. Understanding how cortical networks carry out such transformations requires a description of the responses of individual neurons and of their networks at multiple levels of analysis. We focus on orientation selectivity in primary visual cortex as a model system to understand cortical network computations. Recent experiments in our laboratory and others provide significant insight into how cortical networks generate and maintain orientation selectivity. We first review evidence for the diversity of orientation tuning characteristics in visual cortex. We then describe experiments that combine optical imaging of orientation maps with intracellular and extracellular recordings from individual neurons at known locations in the orientation map. The data indicate that excitatory and inhibitory synaptic inputs are summed across the cortex in a manner that is consistent with simple rules of integration of local inputs. These rules arise from known anatomical projection patterns in visual cortex. We propose that the generation and plasticity of orientation tuning is strongly influenced by local cortical networks-the diversity of these properties arises in part from the diversity of neighbourhood features that derive from the orientation map.

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Adaptive Coincidence Detection and Dynamic Gain Control in Visual Cortical Neurons In Vivo

Cited by 264 publications

References 54 publications

Cooperative synchronized assemblies enhance orientation discrimination

Cooperative synchronized assemblies enhance orientation discrimination

Orientation selectivity and noise correlation in awake monkey area V1 are modulated by the gamma cycle

Local networks in visual cortex and their influence on neuronal responses and dynamics

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