Synergistic activity between primary visual neurons

Abstract : Cortical microcircuitry plays a pivotal role in encoding sensory information reaching the cortex. However, the fundamental knowledge concerning the mechanisms that govern feature-encoding by these sub-networks is still sparse. Here, we show through multi electrode recordings in V1 of conventionally prepared anesthetized cats, that an avalanche of synergistic neural activity occurs between functionally connected neurons in a cell assembly in response to the presented stimulus. The results specifically show that once the reference neuron spikes in a connected neuron-pair, it facilitates the response of its companion (target) neuron for 50 ms and, thereafter, the excitability of the target neuron declines. On the other hand, the functionally unconnected neurons do not facilitate each other’s activity within the 50 ms time-window. The added excitation (facilitation) of connected neurons is almost four times the responsiveness of unconnected neurons. This suggests that connectedness confers the added excitability to neurons; consequently leading to feature-encoding within the emergent 50 ms-period. Furthermore, the facilitation significantly decreases as a function of orientation selectivity spread

Modulation of functional connectivity following visual adaptation: homeostasis in V1

Abstract: Sensory neurons exhibit remarkable adaptability in acquiring new optimal selectivity to unfamiliar features when a new stimulus becomes prevalent in the environment. In conventionally prepared adult anesthetized cats, we used visual adaptation to change the preferred orientation selectivity in V1 neurons. Cortical circuits are dominated by complex and intricate connections between neurons. Cross-correlation of cellular spike-trains discloses the putative functional connection between two neurons. We sought to investigate changes in these links following a twelve minute uninterrupted application of a specific, usually non-preferred, orientation. We report that visual adaptation, mimicking training, modulates the magnitude of cross-correlograms suggesting that the strength of inter-neuronal relationships is modified. While individual cell-pairs exhibit changes in their response correlation strength, the average correlation of the recorded cell cluster remains unchanged. Hence, visual adaptation induces plastic changes that impact the connectivity between neurons

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

The function of connectomes in encoding sensory stimuli

The enormous number of neurons and the massive sum of connecting fibers linking them make the neural processes of encoding sensory signals extraordinarily complex, and this challenge is far from being elucidated. Simply stated, for the present paper, the question is — how does the brain encode complex images? Our proposal argues that modulation of strengths of functional relationships between firing neurons in relation to an input results in the formation of stimulus-salient functional connectomes. This type of connection/coupling strength is computed by performing cross correlograms (CCG) of spike trains between simultaneously firing cells. Significantly, the strength is dependent upon stimuli characteristics, inferring that cells may join or leave particular ensembles, thus creating signature emergent connectomes for different images, thereby, allowing their discrimination. We observed in an ensemble that functionally connected cells exhibited synergistic excitatory activity, increased coherence, and augmented gamma oscillations within a window-of-opportunity contrasting with unconnected neighboring neuronal companions. We suggest that investigating and revealing such stimulus-salient emergent connectomes is a realistic and promising pursuit toward answering how the brain processes complex images