|Ph.D Student||Haroush Netta|
|Subject||Trial to Trial Variability in Synchronized Neural|
|Department||Department of Medicine||Supervisor||Professor Shimon Marom|
|Full Thesis text|
In this dissertation I bring observations and interpretations from different aspects of response variability in synchronized neural populations. All of the experimental observations reported here were obtained in random large-scale networks of cortical neurons, developing in-vitro on an array of extracellular electrodes.
In the first chapter, trial to trial variations in the synchronized responses of neural networks are explored over time scales of minutes. I show that sub-second measures of the individual synchronous response, namely -- its latency and decay duration, are related to minutes-scale network response dynamics. Network responsiveness is reflected as residency in, or shifting amongst, areas of the latency-decay plane. The different sensitivities of latency and decay durations to synaptic blockers imply that these two measures reflect aspects of inhibitory and excitatory activities. Taken together, the data suggest that trial to trial variations in the synchronized responses of neural networks might be related to effective excitation-inhibition ratio being a dynamic variable over time scales of minutes.
In the second chapter, I block the inhibitory sub-network, and investigate response variations in excitatory networks. Controlled disinhibition dramatically reduces variability across and within preparations, bringing networks to standard initial conditions, characterized by low latencies and reliable responses. In these standardized networks, the rate sensitivity of the population trial to trial variability is evaluated. I show the existence of a critical input rate, beyond which reliable responsiveness is replaced by intermittency. This transition seems to place networks at the border between excitable a non-excitable status, and show markers of criticality. Interestingly, this is almost an identical replication of the transition occurring in single cells, to the extent of a temporal and spatial stretch to the relevant scales. This equivalence further supports the parallelism between a recurrent synchronized network and the single neuron level.
In the third chapter, the investigation is extended to microscopic features of the population response. Properties of evoked activity propagation are characterized under disinhibition and the impacts of intact inhibition on trial to trial variability are derived. Inspired by its impact in the highly structured sensory envelope, inhibition is acknowledged as sharpening contrast between responses to different stimuli. Its contribution in deeper and less structured stations, however, is less clear. Here I take advantage of the random connectivity of the in-vitro networks, and attempt to disengage the impacts of the structural component from that of inhibition. I investigate the impact of disinhibition on response variability and separability of responses evoked from different spatial locations. I show that disinihibition quenches variability of responses evoked through any given spatial source. This reduced variability does not affect the capacity of networks to classify input sources based on firing rates. Nevertheless, classification based on spike time relations is sharpened under disinhibition. Interpreting these results from the perspective of the inhibitory contribution suggests that intact inhibition induces dispersion. From this perspective, I bring evidence in support of inhibition as interfering with an otherwise coherent, wave-like propagation of activity through excitatory neurons; thus demonstrating a non-literal lateral inhibition in random networks.