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Wessel, R.

Publications and source records attributed to Wessel, R..

4 recordsLinked to original sources

Visual Response Properties In The Three Layer Turtle Visual Cortex

Turtle dorsal cortex provides us with unique insights into cortical processing. It is known to share many features with the mammalian hippocampus and olfactory cortex as well as geniculo-cortical areas in stem amniotes from which mammals evolved. To this end, we have used data from extracellular recordings from microelectrode arrays to study spatial and temporal patterns of responses to visual stimuli as seen in both local field potential and action potentials. We discovered surprisingly large receptive fields, responsiveness to a broad range of stimuli, and high correlation between distant neural ensembles across recording array. Moreover, we found significant response variability regarding latency and strength in the presence of adaptation to both ongoing and visually evoked activity.

neuroscience

Network activity influences the subthreshold and spiking visual responses of pyramidal neurons in a three-layer cortex

A primary goal of systems neuroscience is to understand cortical function, which typically involves studying spontaneous and sensory-evoked cortical activity. Mounting evidence suggests a strong and complex relationship between the ongoing and evoked state. To date, most work in this area has been based on spiking in populations of neurons. While advantageous in many respects, this approach is limited in scope; it records the activities of a minority of neurons, and gives no direct indication of the underlying subthreshold dynamics. Membrane potential recordings can fill these gaps in our understanding, but are difficult to obtain in vivo. Here, we record subthreshold cortical visual responses in the ex vivo turtle eye-attached whole-brain preparation, which is ideally-suited to such a study. In the absence of visual stimulation, the network is \"synchronous\"; neurons display network-mediated transitions between low- and high-conductance membrane potential states. The prevalence of these slow-wave transitions varies across turtles and recording sessions. Visual stimulation evokes similar high-conductance states, which are on average larger and less reliable when the ongoing state is more synchronous. Responses are muted when immediately preceded by large, spontaneous high-conductance events. Evoked spiking is sparse, highly variable across trials, and mediated by concerted synaptic inputs that are in general only very weakly correlated with inputs to nearby neurons. Together, these results highlight the multiplexed influence of the cortical network on the spontaneous and sensory-evoked activity of individual cortical neurons.

neuroscience

Response variability and population coupling of cortical synaptic inputs are strongly influenced by network properties

The highly variable spiking of a cortical neuron is \"coupled\" to that of other neurons in the network. This has implications for sensory coding, and appears to represent a fundamental property of cortical sensory processing. To date, most studies of population coupling have focused on recorded spiking activity, an approach that suffers from several confounding issues. Moreover, the contributions of various network properties to population coupling are largely unexplored. To this end, we recorded the membrane potential (V) and the nearby LFP in the visual cortex of the turtle ex vivo wholebrain preparation during ongoing and visually-evoked activity. We used an algorithm to infer the excitatory conductance (g) from V, and calculated the g-LFP coupling. We found that g-LFP coupling was highly variable across neurons, and increased following visual stimulation before relaxing to intermediate values. To investigate the role of the network, we implemented a driven small-world network of leaky integrate-and-fire neurons. This model reproduces the large across-trial response variability and g-LFP coupling dynamic, and suggests crucial roles for anatomical and emergent network properties.

neuroscience

Adaptation modulates correlated response variability in visual cortex

Cortical sensory responses are highly variable across stimulus presentations. This variability can be correlated across neurons (due to some combination of dense intracortical connectivity, cortical activity level, and cortical state), with fundamental implications for population coding. Yet the interpretation of correlated response variability (or \"noise correlation\") has remained fraught with difficulty, in part because of the restriction to extracellular neuronal spike recordings. Here, we measured response variability and its correlation at the most microscopic level of electrical neural activity, the membrane potential, by obtaining dual whole-cell recordings from pairs of cortical pyramidal neurons during visual processing. We found that during visual stimulation, correlated variability adapts towards an intermediate level and that this correlation dynamic is mediated by intracortical mechanisms. A model network with external inputs, synaptic depression, and structure reproduced the observed dynamics of correlated variability. These results establish that intracortical adaptation self-organizes cortical circuits towards a balanced regime at which network coordination maintains an intermediate level.

neuroscience