Browsing by Subject "Visual cortex"

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Neural correlates of behavior and stimulus sensitivity of individual neurons and population responses in the primary visual cortex
(2009-05) Palmer, Christopher Russell, 1975-; Seidemann, Eyal
The overall goals of this dissertation were 1) to understand the role that neurons in primate primary visual cortex (V1) play in the detection of small visual stimuli, and 2) to understand the quantitative relationship between the responses of individual neurons and neural population responses in V1. These goals were addressed in experiments with awake, behaving macaque monkeys using electrophysiological and imaging techniques. Initially, I employed ideal observer models to assess V1 neural detection sensitivity in a reaction-time visual detection task and found it to be comparable to the monkey's detection sensitivity. Using the same detection task, I found weak, but significant, correlations between V1 neural activity and the trial-by-trial behavior of monkeys (choice and reaction time). The conclusion of these studies is that the monkey's behavior in the detection task was likely mediated by large neural populations. Voltage-sensitive dye imaging (VSDI) is a powerful imaging technique that is well suited for assessing the link between the activity of large neural populations and behavior. VSDI measures changes in membrane potential over a cortical area of 1-2 cm² with high spatial and temporal resolutions. Using position tuning experiments with VSDI and electrophysiology, I described the relatively unknown quantitative relationships between spiking activity, the local field potential, and VSDI. These relationships were well captured by non-linear transfer functions. Lastly, these experiments also revealed important new findings about the representation of visual space by populations of neurons in V1. In particular, we resolved a long standing debate regarding the size of the cortical point image (CPI), the area of cortex activated by a single point stimulus. We found that the CPI is constant across eccentricity in parafoveal V1, suggesting that each point in space activates an approximately equivalent amount of cortical tissue. In conclusion, the results and analyses described in this dissertation contribute to our understanding of the role that neural populations in V1 play in mediating visual detection, reveal important properties of the representation of visual space by populations of neurons in V1, and provide the first analysis of the quantitative relationship between VSDI and electrophysiological signals.
A population gain control model of spatiotemporal responses in the visual cortex
(2009-08) Sit, Yiu Fai; Miikkulainen, Risto; Seidemann, Eyal
The mammalian brain is a complex computing system that contains billions of neurons and trillions of connections. Is there a general principle that governs the processing in such large neural populations? This dissertation attempts to address this question using computational modeling and quantitative analysis of direct physiological measurements of large neural populations in the monkey primary visual cortex (V1). First, the complete spatiotemporal dynamics of V1 responses over the entire region that is activated by small stationary stimuli are characterized quantitatively. The dynamics of the responses are found to be systematic but complex. Importantly, they are inconsistent with many popular computational models of neural processing. Second, a simple population gain control (PGC) model that can account for these complex response properties is proposed for the small stationary stimuli. The PGC model is then used to predict the responses to stimuli composed of two elements and stimuli that move at a constant speed. The predictions of the model are consistent with the measured responses in V1 for both stimuli. PGC is the first model that can account for the complete spatiotemporal dynamics of V1 population responses for different types of stimuli, suggesting that gain control is a general mechanism of neural processing.
Predictive Feedback Can Account for Biphasic Responses in the Lateral Geniculate Nucleus
(Public Library of Science, 2009-05-01) Jehee, Janneke F. M.; Ballard, Dana H.
Biphasic neural response properties, where the optimal stimulus for driving a neural response changes from one stimulus pattern to the opposite stimulus pattern over short periods of time, have been described in several visual areas, including lateral geniculate nucleus (LGN), primary visual cortex (V1), and middle temporal area (MT). We describe a hierarchical model of predictive coding and simulations that capture these temporal variations in neuronal response properties. We focus on the LGN-V1 circuit and find that after training on natural images the model exhibits the brain's LGN-V1 connectivity structure, in which the structure of V1 receptive fields is linked to the spatial alignment and properties of center-surround cells in the LGN. In addition, the spatio-temporal response profile of LGN model neurons is biphasic in structure, resembling the biphasic response structure of neurons in cat LGN. Moreover, the model displays a specific pattern of influence of feedback, where LGN receptive fields that are aligned over a simple cell receptive field zone of the same polarity decrease their responses while neurons of opposite polarity increase their responses with feedback. This phase-reversed pattern of influence was recently observed in neurophysiology. These results corroborate the idea that predictive feedback is a general coding strategy in the brain.
Studies of photoreceptor throughput to visual cortex
(2021-11-04) Rhim, Issac; Nauhaus, Ian; Huk, Alex; Priebe, Nicholas; Seidemann, Eyal
The work in this dissertation aims to (1) examine the presence of a functional map in the mouse visual cortex by measuring its variable cone M-opsin and S-opsin inputs, as predicted by the graded dorsoventral cone opsin expression in the retina (Rhim et al., 2017), (2) devise a method for measuring rod saturation and utilize it to characterize differential spatio-temporal tuning between rod-mediated and cone-mediated vision in V1 (Rhim et al., 2021), and (3) study the representation of color and form. We report that the dorsoventral cone opsin expression gradient in the retina is recapitulated in the mouse visual cortex, including primary visual cortex (V1) and higher visual areas (HVAs). This provides a first finding of a functional map in the mouse cortex, next to retinotopy map. Next, we exploit this feature in the mouse cortex to measure variable opsin inputs to the cortex to provide a model to estimate rod saturation. This is a much-needed foundation in mouse vision research, which will help future studies to differentially quantify inputs from the three photoreceptor opsins found in mice: rhodopsin, S-opsin, and M-opsin. We exemplify this by studying the spatio-temporal tuning of rod-mediated vs. cone-mediated vision in V1. Cone-mediated V1 responds to 2.5-fold higher temporal frequencies than rod-mediated V1, highlighting differences in rod vs. cone information throughput. Lastly, we study the mechanisms underlying spatio-chromatic processing in the cortex. We find that V1's spatial frequency (SF) tuning is more low-pass to color contrast than brightness (i.e., luminance) contrast. Furthermore, our data can be accounted by a random wiring model with rhodopsin and cone S-opsin inputs to single-opponent V1 neurons. While classic models of single-opponency require selective wiring for ON and OFF subfields from each photoreceptor class, we find this to be inconsistent with our data. This provides a new insight to mechanism underlying color vision.