Does Corticothalamic Feedback Control Cortical Velocity Tuning?

The thalamus is the major gate to the cortex and its contribution to cortical receptive field properties is well established. Cortical feedback to the thalamus is, in turn, the anatomically dominant input to relay cells, yet its influence on thalamic processing has been difficult to interpret. For an understanding of complex sensory processing, detailed concepts of the corticothalamic interplay need yet to be established. To study corticogeniculate processing in a model, we draw on various physiological and anatomical data concerning the intrinsic dynamics of geniculate relay neurons, the cortical influence on relay modes, lagged and nonlagged neurons, and the structure of visual cortical receptive fields. In extensive computer simulations we elaborate the novel hypothesis that the visual cortex controls via feedback the temporal response properties of geniculate relay cells in a way that alters the tuning of cortical cells for speed

Does Corticothalamic Feedback Control Cortical Velocity Tuning?

The thalamus is the major gate to the cortex and its contribution to cortical receptive field properties is well established. Cortical feedback to the thalamus is, in turn, the anatomically dominant input to relay cells, yet its influence on thalamic processing has been difficult to interpret. For an understanding of complex sensory processing, detailed concepts of the corticothalamic interplay need yet to be established. To study corticogeniculate processing in a model, we draw on various physiological and anatomical data concerning the intrinsic dynamics of geniculate relay neurons, the cortical influence on relay modes, lagged and nonlagged neurons, and the structure of visual cortical receptive fields. In extensive computer simulations we elaborate the novel hypothesis that the visual cortex controls via feedback the temporal response properties of geniculate relay cells in a way that alters the tuning of cortical cells for speed.Comment: 31 pages, 7 figure

A Theoretical Analysis of the Influence of Fixational Instability on the Development of Thalamocortical Connectivity

Under natural viewing conditions, the physiological inotability of visual fixation keeps the projection of the stimulus on the retina in constant motion. After eye opening, chronic exposure to a constantly moving retinal image might influence the experience-dependent refinement of cell response characteristics. The results of previous modeling studies have suggested a contribution of fixational instability in the Hebbian maturation of the receptive fields of V1 simple cells (Rucci, Edelman, & Wray, 2000; Rucci & Casile, 2004). This paper presents a mathematieal explanation of our previous computational results. Using quasi-linear models of LGN units and V1 simple cells, we derive analytical expressions for the second-order statistics of thalamocortical activity before and after eye opening. We show that in the presence of natural stimulation, fixational instability introduces a spatially uncorrelated signal in the retinal input, whieh strongly influences the structure of correlated activity in the model

Gating Input to Visual Cortex by Feedback to LGN

Anatomical studies have documented massive back-projections from higher to lower visual cortices and to the lateral geniculate nucleus (LGN). The large number of synapses from these sources suggest that they should have a profound influence on the information carried by feed-forward inputs to these cells. However, the functional role of these connections is unclear. In order to explore the role of the feedback connections, we have recorded spike trains from electrodes placed in LGN in the macaque monkey under sufenta anesthesia, and have compared LGN cells' activity with and without suppression by cooling of feedback from primary visual cortex (V1). Normally, magno and parvo LGN cells show a wide range over which their responses are proportional to stimulus contrast. Inactivation of V1 feedback causes LGN cells to become more nonlinear and less sensitive to high contrast than during normal conditions. Responses during V1 inactivation have a similar shape to those of retinal ganglion cells. We have also tested the properties of the so-called extended surround as they relate to cortical activity and to influences on responses to LGN stimulation. A model of this data suggests an interpretation in terms of two fnuctional components of feedback: a contrast-dependent component which dominates at high input contrast, and a constant baseline level of inhibitory feedback. We also show that the influence of the extended surround on the classical center mechanism is more complicated than a simple integration model.National Institutes of Health (EY-05156); Office of Naval Research (N00014-95-1-409

Temporal Dynamics of Binocular Display Processing with Corticogeniculate Interactions

A neural model of binocular vision is developed to simulate psychophysical and neurobiological data concerning the dynamics of binocular disparity processing. The model shows how feedforward and feedback interactions among LGN ON and OFF cells and cortical simple, complex, and hypercomplex cells can simulate binocular summation, the Pulfrich effect, and the fusion of delayed anticorrelated stereograms. Model retinal ON and OFF cells are linked by an opponent process capable of generating antagonistic rebounds from OFF cells after offset of an ON cell input. Spatially displaced ON and OFF cells excite simple cells. Opposite polarity simple cells compete before their half-wave rectified outputs excite complex cells. Complex cells binocularly match like-polarity simple cell outputs before pooling half-wave rectified signals frorn opposite polarities. Competitive feedback among complex cells leads to sharpening of disparity selectivity and normalizes cell activity. Slow inhibitory interneurons help to reset complex cells after input offset. The Pulfrich effect occurs because the delayed input from the one eye fuses with the present input from the other eye to create a disparity. Binocular summation occurs for stimuli of brief duration or of low contrast because competitive normalization takes time, and cannot occur for very brief or weak stimuli. At brief SOAs, anticorrelatecd stereograms can be fused because the rebound mechanism ensures that the present image to one eye can fuse with the afterimage from a previous image to the other eye. Corticogeniculate feedback embodies a matching process that enhances the speed and temporal accuracy of complex cell disparity tuning. Model mechanisms interact to control the stable development of sharp disparity tuning.Air Force Office of Scientific Research (F19620-92-J-0499, F49620-92-J-0334, F49620-92-J-0225); Office of Naval Research (N00014-95-1-0409, N00014-95-l-0657, N00014-92-J-1015, N00014-91-J-4100

Modeling the Possible Influences of Eye Movements on the Refinement of Cortical Direction Selectivity

The second-order statistics of neural activity was examined in a model of the cat LGN and V1 during free-viewing of natural images. In the model, the specific patterns of thalamocortical activity required for a Bebbian maturation of direction-selective cells in VI were found during the periods of visual fixation, when small eye movements occurred, but not when natural images were examined in the absence of fixational eye movements. In addition, simulations of stroboscopic reming that replicated the abnormal pattern of eye movements observed in kittens chronically exposed to stroboscopic illumination produced results consistent with the reported loss of direction selectivity and preservation of orientation selectivity. These results suggest the involvement of the oculomotor activity of visual fixation in the maturation of cortical direction selectivity

Linking Visual Cortical Development to Visual Perception

Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (IRI-97-20333); Office of Naval Research (N00014-95-1-0657

Towards building a more complex view of the lateral geniculate nucleus: Recent advances in understanding its role

The lateral geniculate nucleus (LGN) has often been treated in the past as a linear filter that adds little to retinal processing of visual inputs. Here we review anatomical, neurophysiological, brain imaging, and modeling studies that have in recent years built up a much more complex view of LGN . These include effects related to nonlinear dendritic processing, cortical feedback, synchrony and oscillations across LGN populations, as well as involvement of LGN in higher level cognitive processing. Although recent studies have provided valuable insights into early visual processing including the role of LGN, a unified model of LGN responses to real-world objects has not yet been developed. In the light of recent data, we suggest that the role of LGN deserves more careful consideration in developing models of high-level visual processing