POPULATION CODING IN LAMINAR CORTICAL CIRCUITS

One of the fundamental questions in neuroscience is to understand how encoding of sensory inputs is distributed across neuronal networks in cerebral cortex to influence sensory processing and behavioral performance. The fact that the structure of neuronal networks is organized according to cortical layers raises the possibility that sensory information could be processed differently in distinct layers. The goal of my thesis research is to understand how laminar circuits encode information in their population activity, how the properties of the population code adapt to changes in visual input, and how population coding influences behavioral performance. To this end, we performed a series of novel experiments to investigate how sensory information in the primary visual cortex (V1) emerges across laminar cortical circuits. First, it is commonly known that the amount of information encoded by cortical circuits depends critically on whether or not nearby neurons exhibit correlations. We examined correlated variability in V1 circuits from a laminar-specific perspective and observed that cells in the input layer, which have only local projections, encode incoming stimuli optimally by exhibiting low correlated variability. In contrast, output layers, which send projections to other cortical and subcortical areas, encode information suboptimally by exhibiting large correlations. These results argue that neuronal populations in different cortical layers play different roles in network computations. Secondly, a fundamental feature of cortical neurons is their ability to adapt to changes in incoming stimuli. Understanding how adaptation emerges across cortical layers to influence information processing is vital for understanding efficient sensory coding. We examined the effects of adaptation, on the time-scale of a visual fixation, on network synchronization across laminar circuits. Specific to the superficial layers, we observed an increase in gamma-band (30-80 Hz) synchronization after adaptation that was correlated with an improvement in neuronal orientation discrimination performance. Thus, synchronization enhances sensory coding to optimize network processing across laminar circuits. Finally, we tested the hypothesis that individual neurons and local populations synchronize their activity in real-time to communicate information about incoming stimuli, and that the degree of synchronization influences behavioral performance. These analyses assessed for the first time the relationship between changes in laminar cortical networks involved in stimulus processing and behavioral performance.

Functional and motor neuronal analysis of defensive siphon responses in {\it Aplysia californica}

One of the central goals of neuroscience research is to determine how networks of neurons control and modify behavior. One of the most influential model systems for this kind of analysis is the siphon and gill withdrawal reflex of the marine mollusc A. californica. In response to tactile stimulation, the siphon displays 3 different responses: (1) a posterior pointing and leveling (flaring) of the siphon in response to tail stimulation (the siphon T response), (2) constriction and anterior pointing to head stimulation (the siphon H response) and (3) constriction and withdrawal between the animal's parapodia (the siphon S response). The siphon S response is pseudoconditioned by a noxious tail stimulus to resemble the siphon T response. Behavioral and combined behavioral/intracellular studies were conducted to determine the motor neuronal control of these behaviors and to search for mechanisms of siphon response transformation following pseudoconditioning. The present studies have found that the flaring component of pseudoconditioned siphon S responses occurs during mantle pumping (MP) triggered by noxious tail stimulation. Siphon stimulation also triggers MP, as recorded in neurons of the Interneuron II pattern generator which commands MP. The 4 LF$\rm\sb{SB}$ siphon motor neurons (SMNs) were found necessary and sufficient for the siphon T response, while SMNs RD$\rm\sb S$ and LD$\rm\sb{S1}$ were found necessary and sufficient for the siphon H response. Following pseudoconditioning, there is an increase in the number of evoked spikes to the test stimulus for the LF$\rm\sb{SB}$ cells and a decreased number for RD$\rm\sb S.$ Siphon flaring occurring during the pseudoconditioned response correlates with increased LF$\rm\sb{SB}$ activity during triggered MP cycles. This suggests that psuedoconditioning is in part due to reconfiguration of the motor outputs of the Interneuron II network. These results suggest that these defensive responses are controlled and patterned by a well-defined, finite set of motor neurons and interneurons (Interneuron II) that are dedicated to specific behavioral functions, but also have parallel distributed properties. ^

Diversity of neuronal connexins in the mammalian retina

Many neurons in the mammalian retina are electrically coupled by intercellular channels or gap junctions, which are assembled from a family of proteins called connexins. Numerous studies indicate that gap junctions differ in properties such as conductance and tracer permeability. For example, A-type horizontal cell gap junctions are permeable to Lucifer Yellow, but B-type horizontal cell gap junctions are not. This suggests the two cell types express different connexins. My hypothesis is that multiple neuronal connexins are expressed in the mammalian retina in a cell type specific manner. Immunohistochemical techniques and confocal microscopy were used to localize certain connexins within well-defined neuronal circuits. The results of this study can be summarized as follows: AII amacrine cells, which receive direct input from rod bipolar cells, are well-coupled to neighboring AIIs. In addition, AII amacrine cells also form gap junctions with ON cone bipolar cells. This is a complex heterocellular network. In both rabbit and primate retina, connexin36 occurs at dendritic crossings in the AII matrix as well as between AIIs and ON cone bipolar cells. Coupling in the AII network is thought to reduce noise in the rod pathway while AII/bipolar gap junctions are required for the transmission of rod signals to ON ganglion cells. In the outer plexiform layer, connexin36 forms gap junctions between cones and between rods and cones via cone telodendria. Cone to cone coupling is thought to reduce noise and is partly color selective. Rod to cone coupling forms an alternative rod pathway thought to operate at intermediate light intensity. A-type horizontal cells in the rabbit retina are strongly coupled via massive low resistance gap junctions composed from Cx50. Coupling dramatically extends the receptive field of horizontal cells and the modulation of coupling is thought to change the strength of the feedback signal from horizontal cells to cones. Finally, there are other coupled networks, such as B-type horizontal cells and S1/S2 amacrine cells, which do not use either connexin36 or Cx50. These results confirm the hypothesis that multiple neuronal connexins are expressed in the mammalian retina and these connexins are localized to particular retinal circuits. ^