Neuron participation in a synchrony-encoding assembly

BACKGROUND: Synchronization of action potentials between neurons is considered to be an encoding process that allows the grouping of various and multiple features of an image leading to a coherent perception. How this coding neuronal assembly is configured is debated. We have previously shown that the magnitude of synchronization between excited neurons is stimulus-dependent. In the present investigation we compare the levels of synchronization between synchronizing individual neurons and the synchronizing pool of cells to which they belong. RESULTS: Even though neurons belonged to their respective pools, some cells synchronized for all presented stimuli while others were rather selective and only a few stimulating conditions produced a significant synchronization. In addition the experiments show that one synchronizing pair rarely replicates the level of synchrony between corresponding groups of units. But when synchronizing clusters of neurons increase in number, the correlation (measured as a coefficient of determination) between unit synchronization and the synchronization between the entire pools of cells to which individual neurons belong improves. CONCLUSION: These results prompt the hypothesis that random or spontaneous synchronization becomes progressively less important, whereas coincident spikes related to encoding properties of targets gain significance because a particular configuration of an image biases the excitatory inputs in favor of connections driven by the applied features of the stimulus

Adaptive behavior of neighboring neurons during adaptation-induced plasticity of orientation tuning in V1

<p>Abstract</p> <p>Background</p> <p>Sensory neurons display transient changes of their response properties following prolonged exposure to an appropriate stimulus (adaptation). In adult cat primary visual cortex, orientation-selective neurons shift their preferred orientation after being adapted to a non-preferred orientation. The direction of those shifts, towards (attractive) or away (repulsive) from the adapter depends mostly on adaptation duration. How the adaptive behavior of a neuron is related to that of its neighbors remains unclear.</p> <p>Results</p> <p>Here we show that in most cases (75%), cells shift their preferred orientation in the same direction as their neighbors. We also found that cells shifting preferred orientation differently from their neighbors (25%) display three interesting properties: (i) larger variance of absolute shift amplitude, (ii) wider tuning bandwidth and (iii) larger range of preferred orientations among the cluster of cells. Several response properties of V1 neurons depend on their location within the cortical orientation map. Our results suggest that recording sites with both attractive and repulsive shifts following adaptation may be located in close proximity to iso-orientation domain boundaries or pinwheel centers. Indeed, those regions have a more diverse orientation distribution of local inputs that could account for the three properties above. On the other hand, sites with all cells shifting their preferred orientation in the same direction could be located within iso-orientation domains.</p> <p>Conclusions</p> <p>Our results suggest that the direction and amplitude of orientation preference shifts in V1 depend on location within the orientation map. This anisotropy of adaptation-induced plasticity, comparable to that of the visual cortex itself, could have important implications for our understanding of visual adaptation at the psychophysical level.</p

A flexible bio-inspired hierarchical model for analyzing musical timbre

A flexible and multipurpose bio-inspired hierarchical model for analyzing musical timbre is presented in this paper. Inspired by findings in the fields of neuroscience, computational neuroscience, and psychoacoustics, not only does the model extract spectral and temporal characteristics of a signal, but it also analyzes amplitude modulations on different timescales. It uses a cochlear filter bank to resolve the spectral components of a sound, lateral inhibition to enhance spectral resolution, and a modulation filter bank to extract the global temporal envelope and roughness of the sound from amplitude modulations. The model was evaluated in three applications. First, it was used to simulate subjective data from two roughness experiments. Second, it was used for musical instrument classification using the k-NN algorithm and a Bayesian network. Third, it was applied to find the features that characterize sounds whose timbres were labeled in an audiovisual experiment. The successful application of the proposed model in these diverse tasks revealed its potential in capturing timbral information

High noise correlation between the functionally connected neurons in emergent V1 microcircuits

Abstract : Neural correlations (noise correlations and cross-correlograms) are widely studied to infer functional connectivity between neurons. High noise correlations (Rsc) between neurons have been reported to increase the encoding accuracy of a neuronal population; however, low noise correlations have also been documented to play a critical role in cortical microcircuits. Therefore, the role of noise correlations in neural encoding is highly debated. To this aim, through multi-electrodes, we recorded neuronal ensembles in the primary visual cortex of anesthetized cats. By computing cross-correlograms (CCGs), we divulged the functional network (microcircuit) between neurons within an ensemble in relation to a specific orientation. We show that functionally connected neurons systematically exhibit higher noise correlations than functionally unconnected neurons in a microcircuit that is activated in response to a particular orientation. Furthermore, the mean strength of noise correlations for the connected neurons increases steeply than the unconnected neurons as a function of the resolution-window used to calculate noise correlations. We suggest that, neurons that display high noise correlations in emergent microcircuits feature functional connections which are inevitable for information encoding in the primary visual cortex

Electrophysiological and firing properties of neurons: categorizing soloists and choristers in primary visual cortex

Abstract: Visual processing in the cortex involves various aspects of neuronal properties such as morphological, electrophysiological and molecular. In particular, the neural firing pattern is an important indicator of dynamic circuitry within a neuronal population. Indeed, in microcircuits, neurons act as soloists or choristers wherein the characteristical activity of a ‘soloist’ differs from the firing pattern of a ‘chorister’. Both cell types correlate their respective firing rate with the global populational activity in a unique way. In the present study, we sought to examine the relationship between the spike shape (thin spike neurons and broad spike neurons) of cortical neurons recorded from V1, their firing levels and their propensity to act as soloists or choristers. We found that thin spike neurons, which exhibited higher levels of firing, generally correlate their activity with the neuronal population (choristers). On the other hand, broad spike neurons showed lower levels of firing and demonstrated weak correlations with the assembly (soloists). A major consequence of the present study is: estimating the correlation of neural spike trains with their neighboring population is a predictive indicator of spike waveforms and firing level. Indeed, we found a continuum distribution of coupling strength ranging from weak correlation-strength (attributed to low-firing neurons) to high correlation-strength (attributed to high-firing neurons). The tendency to exhibit high- or low-firing is conducive to the spike shape of neurons. Our results offer new insights into visual processing by showing how high-firing rate neurons (mostly thin spike neurons) could modulate the neuronal responses within cell-assemblies

Summation of connectivity strengths in the visual cortex reveals stability of neuronal microcircuits after plasticity

Abstract : Background: Within sensory systems, neurons are continuously affected by environmental stimulation. Recently, we showed that, on cell-pair basis, visual adaptation modulates the connectivity strength between similarly tuned neurons to orientation and we suggested that, on a larger scale, the connectivity strength between neurons forming sub-networks could be maintained after adaptation-induced-plasticity. In the present paper, based on the summation of the connectivity strengths, we sought to examine how, within cell-assemblies, functional connectivity is regulated during an exposure-based adaptation. Results: Using intrinsic optical imaging combined with electrophysiological recordings following the reconfiguration of the maps of the primary visual cortex by long stimulus exposure, we found that within functionally connected cells, the summed connectivity strengths remain almost equal although connections among individual pairs are modified. Neuronal selectivity appears to be strongly associated with neuronal connectivity in a “homeodynamic” manner which maintains the stability of cortical functional relationships after experience-dependent plasticity. Conclusions: Our results support the “homeostatic plasticity concept” giving new perspectives on how the summation in visual cortex leads to the stability within labile neuronal ensembles, depending on the newly acquired properties by neurons

Multisensory integration: is medial prefornetal cortex signaling relevant for the treatment of higher-order visual dysfunctions?

In the mammalian brain, information processing in sensory modalities and global mechanisms of multisensory integration facilitate perception. Emerging experimental evidence suggests that the contribution of multisensory integration to sensory perception is far more complex than previously expected. Here we revise how associative areas such as the prefrontal cortex, which receive and integrate inputs from diverse sensory modalities, can affect information processing in unisensory systems via processes of down-stream signaling. We focus our attention on the influence of the medial prefrontal cortex on the processing of information in the visual system and whether this phenomenon can be clinically used to treat higher-order visual dysfunctions. We propose that non-invasive and multisensory stimulation strategies such as environmental enrichment and/or attention-related tasks could be of clinical relevance to fight cerebral visual impairment