Functional consequences of correlated excitatory and inhibitory conductances in cortical networks
- Jens Kremkow, Laurent U. Perrinet, Guillaume S. Masson, Ad Aertsen. Functional consequences of correlated excitatory and inhibitory conductances in cortical networks, URL . Journal of Computational Neuroscience, 28(3):579-94, 2010 abstractNeurons in the neocortex receive a large number of excitatory and inhibitory synaptic inputs. Excitation and inhibition dynamically balance each other, with inhibition lagging excitation by only few milliseconds. To characterize the functional consequences of such correlated excitation and inhibition, we studied models in which this correlation structure is induced by feedforward inhibition (FFI). Simple circuits show that an effective FFI changes the integrative behavior of neurons such that only synchronous inputs can elicit spikes, causing the responses to be sparse and precise. Further, effective FFI increases the selectivity for propagation of synchrony through a feedforward network, thereby increasing the stability to background activity. Last, we show that recurrent random networks with effective inhibition are more likely to exhibit dynamical network activity states as have been observed in vivo. Thus, when a feedforward signal path is embedded in such recurrent network, the stabilizing effect of effective inhibition creates an suitable substrate for signal propagation. In conclusion, correlated excitation and inhibition support the notion that synchronous spiking may be important for cortical processing..
Figure 3: Conditions for signal propagation through a feedforward network with correlated inhibition. (A): Model of a feedforward network with correlated inhibition induced by FFI. (B), Signal propagation of a synchronous input through the network when each group projects only onto the RS population of the following group. Due to the instability of the ground-state of purely excitatory feedforward networks (Tetzlaff et al., 2002), transient random fluctuations in the asynchronous background ac- tivity may occasionally induce spontaneously propagating synchrony, as can be observed here some 50 ms before the stimulus onset. (C), Propagation of an asynchronous input through the same network. The asynchronous input induced elevated firing rates in the first groups. However, the activity rapidly synchro- nized over subsequent groups. (D), Propagation of synchronous input was hardly affected by correlated inhibition, induced by including the FS neurons in the target population of the successive group. E, FFI in the feedforward network prevented asynchronous inputs from inducing synchronous activity in subsequent groups.
- Vernon B. Mountcastle, A. L. Berman, P. W. Davies. Topographic organization and modality representation in first somatic area of cat's cerebral cortex by method of single unit analysis. American Journal of Physiology, 183:464, 1955 abstract
- Vernon B. Mountcastle. Modality and topographic properties of single neurons of cat's somatic sensory cortex. Journal of Neurophysiology, 20(4):408--434, 1957 abstract
- Vernon B. Mountcastle, P. W. Davies, A. L. Berman. Response properties of neurons of cat's somatic sensory cortex to peripheral stimuli. Journal of Neurophysiology, 20:374---407, 1957 abstract
- Terrence J. Sejnowski. Strong covariance with nonlinearly interacting neurons. Journal of Mathematical biology, 4:303-321, 1977 abstract
- Vernon B. Mountcastle. An organizing principle for cerebral function. The unit module and the distributed system.. In The mindful brain, pages 7--50. Cambridge: MIT Press, 1978 abstract
- Ad M. Aertsen, JW Smolders, PI Johannesma. Neural representation of the acoustic biotope: on the existence of stimulus-event relations for sensory neurons. Biological Cybernetics, 32(3):175-85, 1979 abstract
- Moshe Abeles. Corticonics: neural circuits of the cerebral cortex. Cambridge: Cambridge University Press, 1980.
- Moshe Abeles. Local cortical circuits: an electrophysiological study. Springer-Verlag, 1982.
- Izumi Ohzawa, G. Sclar, R. D. Freeman. Contrast gain control in the cat visual cortex. Nature, 298(5871), 1982 abstract
- Thomas D. Albright. Direction and orientation selectivity of neurons in visual area MT of the macaque. Journal of Neurophysiology, 52:1106--30, 1984 abstract
- Ad M. Aertsen, G. L. Gerstein, M. K. Habib, G. Palm. Dynamics of neuronal firing correlation: modulation of "effective connectivity".. Journal of Neurophysiology, 61(5):900--917, 1989 abstract1. We reexamine the possibilities for analyzing and interpreting the time course of correlation in spike trains simultaneously and separably recorded from two neurons. 2. We develop procedures to quantify and properly normalize the classical joint peristimulus time scatter diagram. These allow separation of the "raw" correlation into components caused by direct stimulus modulations of the single-neuron firing rates and those caused by various types of interaction between the two neurons. 3. A newly developed significance test ("surprise") is applied to evaluate such inferences. 4. Application of the new procedures to simulated spike trains allowed the recovery of the known circuitry. In particular, it proved possible to recover fast stimulus-locked modulations of "effective connectivity," even if they were masked by strong direct stimulus modulations of individual firing rates. These procedures thus present a clearly superior alternative to the commonly used "shift predictor." 5. Adopting a model-based approach, we generalize the classical measures for quantifying a direct interneuronal connection ("efficacy" and "contribution") to include possible stimulus-locked time variations. 6. Application of the new procedures to real spike trains from several different preparations showed that fast stimulus-locked modulations of "effective connectivity" also occur for real neurons..
- Yves Burnod. An adaptive neural network: the cerebral cortex. Masson, 1989.
- G. Sclar, J.H.R. Maunsell, P. Lennie. Coding of image contrast in central visual pathways of the macaque monkey. Vision Research, 30:1--10, 1990 abstract
- D.J. Felleman, David C. van Essen. Distributed hierarchical processing in the primate cerebral cortex.. Cerebral Cortex, 1:1-47, 1991 abstract
- David C. van Essen, Charles H. Anderson, D J Felleman. Information processing in the primate visual system: an integrated systems perspective. Science, 255(5043):419--23, 1992 abstractThe primate visual system contains dozens of distinct areas in the cerebral cortex and several major subcortical structures. These subdivisions are extensively interconnected in a distributed hierarchical network that contains several intertwined processing streams. A number of strategies are used for efficient information processing within this hierarchy. These include linear and nonlinear filtering, passage through information bottlenecks, and coordinated use of multiple types of information. In addition, dynamic regulation of information flow within and between visual areas may provide the computational flexibility needed for the visual system to perform a broad spectrum of tasks accurately and at high resolution..
- Moshe Abeles, H. Bergman, E. Margalit, E. Vaadia. Spatiotemporal firing patterns in the frontal cortex of behaving monkeys. Journal of Neurophysiology, 70(4):1629--38, 1993 abstract
- William Softky, Christof Koch. Cortical cells should fire regularly, but do not. Neural Computation, 4:643-646, 1993 abstract
- William Softky, Christof Koch. The highly irregular firing of cortical cells is inconsistence with temporal integration of random EPSPs. Journal of Neuroscience, 13:334--50, 1993 abstract
- W. J. Freeman, J. M. Barrie. Chaotic Oscillations and the Genesis of Meaning in Cerebral Cortex. In Temporal Coding in the Brain, pages 13-37. Springer-Verlag, Berlin Heidelberg, 1994 abstract
- Zachary F. Mainen, Terrence J. Sejnowski. Reliability of spike timing in neocortical neurons.. Science, 268(5216):1503--06, 1995 abstractIt is not known whether the variability of neural activity in the cerebral cortex carries information or reflects noisy underlying mechanisms. In an examination of the reliability of spike generation using recordings from neurons in rat neocortical slices, the precision of spike timing was found to depend on stimulus transients. Constant stimuli led to imprecise spike trains, whereas stimuli with fluctuations resembling synaptic activity produced spike trains with timing reproducible to less than 1 millisecond. These data suggest a low intrinsic noise level in spike generation, which could allow cortical neurons to accurately transform synaptic input into spike sequences, supporting a possible role for spike timing in the processing of cortical information by the neocortex..
- DC Somers, SB Nelson, M Sur. An emergent model of orientation selectivity in cat visual cortical simple cells, URL . Journal of Neuroscience, 15(8):5448--65, 1995 abstract
- José-Ma\ nuel Alonso, W. Martin Usrey, R. Clay Reid. Precisely correlated firing in cells of the lateral geniculate nucleus. Nature, 383(6603):815--9, 1996 abstractSimple cells within layer IV of the cat primary visual cortex are selective for lines of a specific orientation.It has been proposed that their receptive-field properties are established by the pattern of connections that they receive from the lateral geniculate nucleus (LGN) of the thalamus [1-5]. Thalamic inputs, however, represent only a small proportion of the synapses made onto simple cells [6-8], and others have argued that corticocortical connections are likely to be important in shaping simple-cell response properties [9-11]. Here we describe a mechanism that might be involved in selectively strengthening the effect of thalamic inputs. We show that neighbouring geniculate neurons with overlapping receptive fields of the same type (on-centre or off-centre) often fire spikes that are synchronized to within 1 milli-second. Moreover, these neurons often project to a common cortical target neuron where synchronous spikes are more effective in evoking a postsynaptic response. We propose that precisely correlated firing within a group of geniculate neurons could serve to reinforce the thalamic input to cortical simple cells..
- Vernon B. Mountcastle. The columnar organization of the neocortex. Brain, 120 ( Pt 4):701--22, 1997 abstractThe modular organization of nervous systems is a widely documented principle of design for both vertebrate and invertebrate brains of which the columnar organization of the neocortex is an example. The classical cytoarchitectural areas of the neocortex are composed of smaller units, local neural circuits repeated iteratively within each area. Modules may vary in cell type and number, in internal and external connectivity, and in mode of neuronal processing between different large entities; within any single large entity they have a basic similarity of internal design and operation. Modules are most commonly grouped into entities by sets of dominating external connections. This unifying factor is most obvious for the heterotypical sensory and motor areas of the neocortex. Columnar defining factors in homotypical areas are generated, in part, within the cortex itself. The set of all modules composing such an entity may be fractionated into different modular subsets by different extrinsic connections. Linkages between them and subsets in other large entities form distributed systems. The neighborhood relations between connected subsets of modules in different entities result in nested distributed systems that serve distributed functions. A cortical area defined in classical cytoarchitectural terms may belong to more than one and sometimes to several distributed systems. Columns in cytoarchitectural areas located at some distance from one another, but with some common properties, may be linked by long-range, intracortical connections..
- Roland J Baddeley, Larry F. Abbott, M. Booth, F. Sengpiel, T. Freeman, E. Wakeman, E. Rolls. Responses of neurons in primary and inferior temporal visual cortices to natural scenes. In Proc. Roy. Soc.(Lond.), 1997 abstract
- Matteo Carandini, David J. Heeger, J. Anthony Movshon. Linearity and normalization in simple cells of the macaque primary visual cortex. Journal of Neuroscience, 17(21):8621---44, 1997 abstract
- P. Fries, P. R. Roelfsema, A. K. Engel, P. Konig, Wolf Singer. Synchronization of oscillatory responses in visual cortex correlates with perception in interocular rivalry. Proceedings of the National Academy of Sciences USA, 94(23):12699-704, 1997 abstract
- Alexa Riehle, Sonja Grün, Markus Diesmann, Ad M. Aertsen. Spike synchronization and rate modulation differentially involved in motor control. Science, 278:1950--3, 1997 abstract
- Kamal Sen, J. A. Varela, Sacha B. Nelson. Synaptic Depression and Cortical Gain Control. Science, 275:220-222, 1997 abstract
- Haim Sompolinsky, Robert M Shapley. New perspectives on the mechanisms for orientation selectivity. Current Opinion in Neurobiology, 7(4):514--22, 1997 abstractSince the discovery of orientation selectivity by Hubel and Wiesel, the mechanisms responsible for this remarkable operation in the visual cortex have been controversial. Experimental studies over the past year have highlighted the contribution of feedforward thalamo-cortical afferents, as proposed originally by Hubel and Wiesel, but they have also indicated that this contribution alone is insufficient to account for the sharp orientation tuning observed in the visual cortex. Recent advances in understanding the functional architecture of local cortical circuitry have led to new proposals for the involvement of intracortical recurrent excitation and inhibition in orientation selectivity. Establishing how these two mechanisms work together remains an important experimental and theoretical challenge..
- Vernon B. Mountcastle. Perceptual neuroscience: the cerebral cortex. 1998.
- DC Somers, EV Todorov, AG Siapas, LJ Toth, DS Kim, M Sur. A local circuit approach to understanding integration of long-range inputs in primary visual cortex, URL . Cerebral Cortex, 8(3):204--17, 1998 abstractIntegration of inputs by cortical neurons provides the basis for the complex information processing performed in the cerebral cortex. Here, we have examined how primary visual cortical neurons integrate classical and nonclassical receptive field inputs. The effect of nonclassical receptive field stimuli and, correspondingly, of long-range intracortical inputs is known to be context-dependent: the same long-range stimulus can either facilitate or suppress responses, depending on the level of local activation. By constructing a large-scale model of primary visual cortex, we demonstrate that this effect can be understood in terms of the local cortical circuitry. Each receptive field position contributes both excitatory and inhibitory inputs; however, the inhibitory inputs have greater influence when overall receptive field drive is greater. This mechanism also explains contrast-dependent modulations within the classical receptive field, which similarly switch between excitatory and inhibitory. In order to simplify analysis and to explain the fundamental mechanisms of the model, self-contained modules that capture nonlinear local circuit interactions are constructed. This work supports the notion that receptive field integration is the result of local processing within small groups of neurons rather than in single neurons..
- M.P. Sceniak, Dario L. Ringach, M.J. Hawken, S. Shapley. Contrast's effect on spatial summation by macaque V1 neurons. Nature Neuroscience, 2:753--9, 1999 abstract
- S. Deiss, Rodney Douglas, A. Whatley. A pulse-coded communications infrastucture for neuromorphic systems. pages 159-77. abstract
- Alexander D. Protopapas, Michael Vanier, James M. Bower. Simulating Large Networks of Neurons. pages 461-498. abstract
- John Rinzel, Bard Ermentrout. Analysis of Neural Excitability and Oscillations. pages 251-292. abstract
- Shun-ichi Amari. A Statistical Neural Field Approach to Orientation Selectivity. Neurocomputing, 1999 abstract
- Lyle J. Borg-Graham. Interpretations of Data and Mechanisms for Hippocampal Pyramidal Cell Models. In Cerebral Cortex, P. S. Ulinski, E. G. Jones and A. Peters, New York: Plenum Press, 1999 abstract
- Matteo Carandini, David J. Heeger, J. Anthony Movshon. Linearity and Gain Control in V1 Simple Cells. In Cortical models, Plenum Press, New York, 1999 abstract
- M Diesmann, M O Gewaltig, Ad M. Aertsen. Stable propagation of synchronous spiking in cortical neural networks.. Nature, 402(6761), 1999 abstractThe classical view of neural coding has emphasized the importance of information carried by the rate at which neurons discharge action potentials. More recent proposals that information may be carried by precise spike timing have been challenged by the assumption that these neurons operate in a noisy fashion--presumably reflecting fluctuations in synaptic input and, thus, incapable of transmitting signals with millisecond fidelity. Here we show that precisely synchronized action potentials can propagate within a model of cortical network activity that recapitulates many of the features of biological systems. An attractor, yielding a stable spiking precision in the (sub)millisecond range, governs the dynamics of synchronization. Our results indicate that a combinatorial neural code, based on rapid associations of groups of neurons co-ordinating their activity at the single spike level, is possible within a cortical-like network..
- Yves Frégnac, Daniel E Shulz. Activity-dependent regulation of receptive field properties of cat area 17 by supervised Hebbian learning.. Journal of Neurobiology, 41(1):69--82, 1999 abstractMost algorithms currently used to model synaptic plasticity in self-organizing cortical networks suppose that the change in synaptic efficacy is governed by the same structuring factor, i.e., the temporal correlation of activity between pre- and postsynaptic neurons. Functional predictions generated by such algorithms have been tested electrophysiologically in the visual cortex of anesthetized and paralyzed cats. Supervised learning procedures were applied at the cellular level to change receptive field (RF) properties during the time of recording of an individual functionally identified cell. The protocols were devised as cellular analogs of the plasticity of RF properties, which is normally expressed during a critical period of postnatal development. We summarize here evidence demonstrating that changes in covariance between afferent input and postsynaptic response imposed during extracellular and intracellular conditioning can acutely induce selective long-lasting up- and down-regulations of visual responses. The functional properties that could be modified in 40% of cells submitted to differential pairing protocols include ocular dominance, orientation selectivity and orientation preference, interocular orientation disparity, and the relative dominance of ON and OFF responses. Since changes in RF properties can be induced in the adult as well, our findings also suggest that similar activity-dependent processes may occur during development and during active phases of learning under the supervision of behavioral attention or contextual signals. Such potential for plasticity in primary visual cortical neurons suggests the existence of a hidden connectivity expressing a wider functional competence than the one revealed at the spiking level. In particular, in the spatial domain the sensory synaptic integration field is larger than the classical discharge field. It can be shaped by supervised learning and its subthreshold extent can be unmasked by the pharmacological blockade of intracortical inhibition..
- K. Kawano. Ocular tracking: behavior and neurophysiology. Current Opinion in Neurobiology, 9:467--73, 1999 abstract
- E. Rodriguez, N. George, J.-P. Lachaux, J. Martinerie, B. Renault, F. Varela. Perception's shadow: long-distance gamma band synchronization of human brain activity. Nature, 397:430-3, 1999 abstract
- . Methods in neuronal modeling: from synapses to networks. The MIT Press, Cambridge, MA, Cambridge, Massachusetts, 1999.
- David Ferster, Kenneth D. Miller. Neural Mechanisms of Orientation Selectivity in the Visual Cortex. Annual Review of Neuroscience, 23:441---71, 2000 abstract
- J Xing, David J. Heeger. Center-surround interactions in foveal and peripheral vision, URL . Vision Research, 40(22):3065--72, 2000 abstractThe perceived contrast of a central stimulus can be decreased (surround suppression) or increased (surround facilitation) by the presence of surround stimuli. In this report we examined center-surround interactions in foveal and peripheral vision using contrast-matching tasks. We found that: (1) surround suppression became markedly stronger as the center-surround stimulus was moved toward the periphery; (2) surround facilitation diminished in the periphery; and (3) the suppression in the periphery was less orientation- and frequency-specific than that in the fovea, so that significant suppression was induced even when the central and surround gratings had very different orientations and spatial frequencies. The different center-surround interactions in the fovea and periphery can not be accounted for by cortical magnification, suggesting that center-surround interactions in the fovea and periphery are incommensurable and play different functional roles in human image processing..
- T Z Lauritzen, Anton E. Krukowski, Kenneth D. Miller. Local correlation-based circuitry can account for responses to multi-grating stimuli in a model of cat V1.. Journal of Neurophysiology, 86(4):1803--1815, 2001 abstractIn cortical simple cells of cat striate cortex, the response to a visual stimulus of the preferred orientation is partially suppressed by simultaneous presentation of a stimulus at the orthogonal orientation, an effect known as "cross-orientation inhibition." It has been argued that this is due to the presence of inhibitory connections between cells tuned for different orientations, but intracellular studies suggest that simple cells receive inhibitory input primarily from cells with similar orientation tuning. Furthermore, response suppression can be elicited by a variety of nonpreferred stimuli at all orientations. Here we study a model circuit that was presented previously to address many aspects of simple cell orientation tuning, which is based on local intracortical connectivity between cells of similar orientation tuning. We show that this model circuit can account for many aspects of cross-orientation inhibition and, more generally, of response suppression by nonpreferred stimuli and of other nonlinear properties of responses to stimulation with multiple gratings..
- Arnaud Delorme, Laurent U. Perrinet, Simon J. Thorpe, Manuel Samuelides. Network of integrate-and-fire neurons using Rank Order Coding B: spike timing dependant plasticity and emergence of orientation selectivity, URL . Neurocomputing, 38--40(1--4):539--45, 2001 abstract
- P. Fries, S. Neuenschwander, A. K. Engel, R. Goebel, Wolf Singer. Rapid feature selective neuronal synchronization through correlated latency shifting.. Nature Neuroscience, 4:194-200, 2001 abstract
- Emilio Salinas, Terrence J. Sejnowski. Correlated neuronal activity and the flow of neural information. Nature Reviews Neuroscience, 2:539-554, 2001 abstract
- Odelia Schwartz, Eero P. Simoncelli. Natural Signal Statistics and Sensory Gain Control. Nature Neuroscience, 4(8):819--25, 2001 abstract
- F. Varela, J.-P. Lachaux, E. Rodriguez, J. Martinerie. The brainweb: phase synchronization and large-scale integration.. Nature Reviews Neuroscience, 2(4):229-39, 2001 abstract
- D. J. Wielaard, M. Shelley, D. McLaughlin, Robert M Shapley. How simple cells are made in a nonlinear network model of the visual cortex.. Journal of Neuroscience, 21(14):5203--11, 2001 abstractSimple cells in the striate cortex respond to visual stimuli in an approximately linear manner, although the LGN input to the striate cortex, and the cortical network itself, are highly nonlinear. Although simple cells are vital for visual perception, there has been no satisfactory explanation of how they are produced in the cortex. To examine this question, we have developed a large-scale neuronal network model of layer 4Calpha in V1 of the macaque cortex that is based on, and constrained by, realistic cortical anatomy and physiology. This paper has two aims: (1) to show that neurons in the model respond like simple cells. (2) To identify how the model generates this linearized response in a nonlinear network. Each neuron in the model receives nonlinear excitation from the lateral geniculate nucleus (LGN). The cells of the model receive strong (nonlinear) lateral inhibition from other neurons in the model cortex. Mathematical analysis of the dependence of membrane potential on synaptic conductances, and computer simulations, reveal that the nonlinearity of corticocortical inhibition cancels the nonlinear excitatory input from the LGN. This interaction produces linearized responses that agree with both extracellular and intracellular measurements. The model correctly accounts for experimental results about the time course of simple cell responses and also generates testable predictions about variation in linearity with position in the cortex, and the effect on the linearity of signal summation, caused by unbalancing the relative strengths of excitation and inhibition pharmacologically or with extrinsic current..
- David Hansel, C van Vreeswijk. How noise contributes to contrast invariance of orientation tuning in cat visual cortex.. Journal of Neuroscience, 22(12):5118--5128, 2002 abstractThe width of the orientation tuning curves of the spike response of neurons in V1 is invariant to contrast. This property constrains the possible mechanisms underlying orientation selectivity. It has been suggested that noise circumvents the iceberg effect that would prevent contrast invariance in the purely feedforward mechanism. Here we investigate systematically how noise contributes to the contrast invariance of orientation tuning curves in V1. We study three models of increasing complexity: a simple threshold-linear firing rate model, a leaky integrate-and-fire model, and a conductance-based model. We show that the noise transmutes the threshold nonlinearity of the input-output relationships into an approximate power law without a threshold within some firing rate range. This implies that, under certain conditions which are derived here, the tuning of the neuron output is approximately contrast invariant. In particular we show that this mechanism for contrast invariance requires that the neuron firing rate must not be too large and that increasing or lowering the contrast too much destroys this invariance. We also show that if this mechanism operates in V1, the spike response, R, and average voltage response V of the neurons in V1 should vary with the contrast, C, according to R(C)gamma proportional to V(C)gamma. The exponent gamma can be estimated from the amount by which the spike tuning curve is sharpened with respect to the voltage tuning curves of the neurons. This prediction does not depend on the specifics of the model and can be tested experimentally..
- Frances S. Chance, Larry F. Abbott, Alex D. Reyes. Gain Modulation from Background Synaptic Input. Neuron, :Vol. 35, 773--782, August 15, 2002 abstract
- James R. Cavanaugh, Wyeth Bair, J. Anthony Movshon. Nature and interaction of signals from the receptive field center and surround in macaque V1 neurons, URL . Journal of Neurophysiology, 88(5):2530--46, 2002 abstract
- P. Fries, J. H. Schroder, P. R. Roelfsema, Wolf Singer, A. K. Engel. Oscillatory neuronal synchronization in primary visual cortex as a correlate of stimulus selection. Journal of Neuroscience, 22(9):3739-54, 2002 abstract
- Sébastien Georges, Peggy Seriès, Yves Frégnac, Jean Lorenceau. Orientation dependent modulation of apparent speed: psychophysical evidence.. Vision Research, 42(25):2757--72, 2002 abstractWe report several experiments showing that a Gabor patch moving in apparent motion sequences appears much faster when its orientation is aligned with the motion path than when it is at an angle to it. This effect is very large and peaks at high speeds (64 degrees /s), decreases for higher and lower speeds and disappears at low speeds (4 degrees /s). This speed bias decreases as the angle between the motion axis and the orientation of the Gabor patch increases, but remains high for curvilinear paths, provided that element orientation is kept tangential to the motion trajectory. It is not accounted for by decision strategies relying on the overall length and duration of the motion sequence or the gap size (or spatial jump) between successive frames. We propose a simple explanation, thoroughly developed as a computational model in a companion paper (Seri\`es, Georges, Lorenceau & Fr\'egnac: "Orientation dependent modulation of apparent speed: a model based on the dynamics of feedforward and horizontal connectivity in V1 cortex", this issue), according to which long-range horizontal connections in V1 elicit differential latency modulations in response to apparent motion sequences, whose read-out at an MT stage results in a perceptual speed bias. The consequences of these findings are discussed..
- Dario L. Ringach, Robert M Shapley, M.J. Hawken. Orientation selectivity in macaque V1: diversity and laminar dependence., URL . Journal of Neuroscience, 22(13):5639-51, 2002 abstract
- Adam M Sillito, Helen E Jones. Corticothalamic interactions in the transfer of visual information.. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 357(1428):1739--52, 2002 abstractThalamic function does not stand apart, as a discrete processing step, from the cortical circuitry. The thalamus receives extensive feedback from the cortex and this influences the firing pattern, synchronization and sensory response mode of relay cells. A crucial question concerns the extent to which the feedback simply controls the state and transmission mode of relay cells and the extent to which the feedback participates in the specific processing of sensory information. Using examples from experiments examining the influence of feedback from the visual cortex to the lateral geniculate nucleus (LGN), we argue that thalamic mechanisms are selectively focused by visually driven feedback to optimize the thalamic contribution to segmentation and global integration. This involves effects on both the temporal and spatial parameters characterizing the responses of LGN cells and includes, for example, motion-driven feedback effects from MT (middle temporal visual area) relayed via layer 6 of V1 (primary visual cortex)..
- Kenneth D. Miller. Understanding layer 4 of the cortical circuit: a model based on cat V1.. Cerebral Cortex, 13(1):73--82, 2003 abstractThis paper reviews theoretical and experimental results on the processing of layer 4, the input-recipient layer, of cat primary visual cortex (V1). A wide range of experimental data can be understood from a model in which response tuning of layer 4 cells is largely determined by a local interplay of feedforward excitation (from thalamus) and feedforward inhibition (from layer 4 inhibitory interneurons driven by thalamus). Feedforward inhibition dominates excitation, inherits its tuning from the thalamic input and sharpens the tuning of excitatory cells. At least a strong component of the feedforward inhibition received by a cell is spatially opponent to the excitation it receives, meaning that inhibition is driven by dark in regions of the visual field in which excitation is driven by light, and vice versa. The idea of opponent inhibition can be generalized to mean inhibition driven by input patterns that are strongly anti-correlated with the patterns that excite a cell. This paper argues that dominant feedforward opponent inhibition may be a general principle of cortical layer 4. This leads to the suggestion that the properties that show columnar organization--invariance across the vertical depth of cortex--may be properties that are shared by 'opposite' (anticorrelated) stimulus pairs. This contrasts with the more common idea that a column represents a set of cells that all share similar stimulus preferences..
- Wyeth Bair, James R. Cavanaugh, J. Anthony Movshon. Time course and time-distance relationships for surround suppression in macaque V1 neurons. Journal of Neuroscience, 23(20):7690 ---701, 2003 abstract
- Arnaud Delorme, Simon J. Thorpe. Early cortical orientation selectivity: How fast shunting inhibition decodes the order of spike latencies. Journal of Computational Neuroscience, 15:357--65, 2003 abstract
- Stephen Grossberg. How does the cerebral cortex work? Development, Learning, Attention, and 3-D Vision by Laminar Circuits of Visual Cortex. Behavioral and Cognitive Neuroscience Reviews, 2(1):47--76, 2003 abstractThe organization of neocortex into layers is one of its most salient anatomical features. These layers include circuits that form functional columns in cortical maps. A major unsolved problem concerns how bottom-up, top-down, and horizontal interactions are organized within cortical layers to generate adaptive behaviors. This article models how these interactions help visual cortex to realize: (i) the binding process whereby cortex groups distributed data into coherent object representations; (ii) the attentional process whereby cortex selectively processes important events; and (iii) the developmental and learning processes whereby cortex shapes its circuits to match environmental constraints. New computational ideas about feedback systems suggest how neocortex develops and learns in a stable way, and why top-down attention requires converging bottom-up inputs to fully activate cortical cells, whereas perceptual groupings do not..
- Darragh Smyth, Ben Willmore, Gary E Baker, Ian D Thompson, David J Tolhurst. The receptive-field organization of simple cells in primary visual cortex of ferrets under natural scene stimulation.. Journal of Neuroscience, 23(11):4746--59, 2003 abstractThe responses of simple cells in primary visual cortex to sinusoidal gratings can primarily be predicted from their spatial receptive fields, as mapped using spots or bars. Although this quasilinearity is well documented, it is not clear whether it holds for complex natural stimuli. We recorded from simple cells in the primary visual cortex of anesthetized ferrets while stimulating with flashed digitized photographs of natural scenes. We applied standard reverse-correlation methods to quantify the average natural stimulus that invokes a neuronal response. Although these maps cannot be the receptive fields, we find that they still predict the preferred orientation of grating for each cell very well (r = 0.91); they do not predict the spatial-frequency tuning. Using a novel application of the linear reconstruction method called regularized pseudoinverse, we were able to recover high-resolution receptive-field maps from the responses to a relatively small number of natural scenes. These receptive-field maps not only predict the optimum orientation of each cell (r = 0.96) but also the spatial-frequency optimum (r = 0.89); the maps also predict the tuning bandwidths of many cells. Therefore, our first conclusion is that the tuning preferences of the cells are primarily linear and constant across stimulus type. However, when we used these maps to predict the actual responses of the cells to natural scenes, we did find evidence of expansive output nonlinearity and nonlinear influences from outside the classical receptive fields, orientation tuning, and spatial-frequency tuning..
- Kukjin Kang, Robert M Shapley, Haim Sompolinsky. Information tuning of populations of neurons in primary visual cortex, URL . Journal of Neuroscience, 24(15):3726--35, 2004 abstractNeurons in macaque primary visual cortex (V1) show a diversity of orientation tuning properties, exhibiting a broad distribution of tuning width, baseline activity, peak response, and circular variance (CV). Here, we studied how the different tuning features affect the performance of these cells in discriminating between stimuli with different orientations. Previous studies of the orientation discrimination power of neurons in V1 focused on resolving two nearby orientations close to the psychophysical threshold of orientation discrimination. Here, we developed a theoretical framework, the information tuning curve, that measures the discrimination power of cells as a function of the orientation difference, deltatheta, of the two stimuli. This tuning curve also represents the mutual information between the neuronal responses and the stimulus orientation. We studied theoretically the dependence of the information tuning curve on the orientation tuning width, baseline, and peak responses. Of main interest is the finding that narrow orientation tuning is not necessarily optimal for all angular discrimination tasks. Instead, the optimal tuning width depends linearly on deltatheta. We applied our theory to study the discrimination performance of a population of 490 neurons in macaque V1. We found that a significant fraction of the neuronal population exhibits favorable tuning properties for large deltatheta. We also studied how the discrimination capability of neurons is distributed and compared several other measures of the orientation tuning such as CV with Chernoff distances for normalized tuning curves..
- Peggy Seriès, Peter E Latham, Alexandre Pouget. Tuning curve sharpening for orientation selectivity: coding efficiency and the impact of correlations., URL . Nature Neuroscience, 7(10):1129--1135, 2004 abstractSeveral studies have shown that the information conveyed by bell-shaped tuning curves increases as their width decreases, leading to the notion that sharpening of tuning curves improves population codes. This notion, however, is based on assumptions that the noise distribution is independent among neurons and independent of the tuning curve width. Here we reexamine these assumptions in networks of spiking neurons by using orientation selectivity as an example. We compare two principal classes of model: one in which the tuning curves are sharpened through cortical lateral interactions, and one in which they are not. We report that sharpening through lateral interactions does not improve population codes but, on the contrary, leads to a severe loss of information. In addition, the sharpening models generate complicated codes that rely extensively on pairwise correlations. Our study generates several experimental predictions that can be used to distinguish between these two classes of model..
- Rony Azouz. Dynamic Spatiotemporal Synaptic Integration in Cortical Neurons: Neuronal Gain, Revisited. Journal of Neurophysiology, :94: 2785--2796, 2005 abstract
- Wyeth Bair. Visual receptive field organization. Current Opinion in Neurobiology, 15(4):459--64, 2005 abstractIncreasingly systematic approaches to quantifying receptive fields in primary visual cortex, combined with inspired ideas about functional circuitry, non-linearities, and visual stimuli, are bringing new interest to classical problems. This includes the distinction and hierarchy between simple and complex cells, the mechanisms underlying the receptive field surround, and debates about optimal stimuli for mapping receptive fields. An important new problem arises from recent observations of stimulus-dependent spatial and temporal summation in primary visual cortex. It appears that the receptive field can no longer be considered unique, and we might have to relinquish this cherished notion as the embodiment of neuronal function in primary visual cortex..
- V Bonin, Valerio Mante, Matteo Carandini. The suppressive field of neurons in lateral geniculate nucleus, URL . Journal of Neuroscience, 25(47):10844--56, 2005 abstractThe responses of neurons in lateral geniculate nucleus (LGN) exhibit powerful suppressive phenomena such as contrast saturation, size tuning, and masking. These phenomena cannot be explained by the classical center-surround receptive field and have been ascribed to a variety of mechanisms, including feedback from cortex. We asked whether these phenomena might all be explained by a single mechanism, contrast gain control, which is inherited from retina and possibly strengthened in thalamus. We formalized an intuitive model of retinal contrast gain control that explicitly predicts gain as a function of local contrast. In the model, the output of the receptive field is divided by the output of a suppressive field, which computes the local root-mean-square contrast. The model provides good fits to LGN responses to a variety of stimuli; with a single set of parameters, it captures saturation, size tuning, and masking. It also correctly predicts that responses to small stimuli grow proportionally with contrast: were it not for the suppressive field, LGN responses would be linear. We characterized the suppressive field and found that it is similar in size to the surround of the classical receptive field (which is eight times larger than commonly estimated), it is not selective for stimulus orientation, and it responds to a wide range of frequencies, including very low spatial frequencies and high temporal frequencies. The latter property is hardly consistent with feedback from cortex. These measurements thoroughly describe the visual properties of contrast gain control in LGN and provide a parsimonious explanation for disparate suppressive phenomena..
- Matteo Carandini, Jonathan B. Demb, Valerio Mante, David J. Tolhurst, Yang Dan, Bruno A. Olshausen, Jack L. Gallant, Nicole C. Rust. Do we know what the early visual system does?, URL . Journal of Neuroscience, 25(46):10577--97, 2005 abstract
- Adam Kohn, Matthew A. Smith. Stimulus Dependence of Neuronal Correlation in Primary Visual Cortex of the Macaque, URL . Journal of Neuroscience, 25(14):3661--73, 2005 abstract
- Jens Kremkow. Dynamics of structured networks - Networks with 3-compartment model neurons.. Technical report, Dept. Neurobiology \& Biophysics, Fac. Biology, Albert-Ludwigs University Freiburg., 2005.
- Jim Wielaard, Paul Sajda. Extraclassical receptive field phenomena \& short-range connectivity in V1., URL . 2005 abstract
- V Bonin, Valerio Mante, Matteo Carandini. The statistical computation underlying contrast gain control, URL . Journal of Neuroscience, 26(23):6346-6353, 2006 abstractIn the early visual system, a contrast gain control mechanism sets the gain of responses based on the locally prevalent contrast. The measure of contrast used by this adaptation mechanism is commonly assumed to be the standard deviation of light intensities relative to the mean (root-mean-square contrast). A number of alternatives, however, are possible. For example, the measure of contrast might depend on the absolute deviations relative to the mean, or on the prevalence of the darkest or lightest intensities. We investigated the statistical computation underlying this measure of contrast in the cat's lateral geniculate nucleus, which relays signals from retina to cortex. Borrowing a method from psychophysics, we recorded responses to white noise stimuli whose distribution of intensities was precisely varied. We varied the standard deviation, skewness, and kurtosis of the distribution of intensities while keeping the mean luminance constant. We found that gain strongly depends on the standard deviation of the distribution. At constant standard deviation, moreover, gain is invariant to changes in skewness or kurtosis. These findings held for both ON and OFF cells, indicating that the measure of contrast is independent of the range of stimulus intensities signaled by the cells. These results confirm the long-held assumption that contrast gain control computes root-mean-square contrast. They also show that contrast gain control senses the full distribution of intensities and leaves unvaried the relative responses of the different cell types. The advantages to visual processing of this remarkably specific computation are not entirely known..
- Julia Biederlack, Miguel Castelo-Branco, Sergio Neuenschwander, Diek W. Wheeler, Wolf Singer, Danko Nikoli\'c. Brightness Induction: Rate Enhancement and Neuronal Synchronization as Complementary Codes. Neuron, 52:1073--83, 2006 abstractIn cat visual cortex, we investigated with parallel recordingsfrom multiple units the neuronal correlatesof perceived brightness. The perceived brightness ofa center grating was changed by varying the orientationor the relative spatial phase of a surrounding grating.Brightness enhancement by orientation contrastis associated with an increase of discharge rates ofresponses to the center grating but not with changesin spike synchronization. In contrast, if brightnessenhancement is induced by phase offset, dischargerates are unchanged but synchronization increasesbetween neurons responding to the center grating.The changes in synchronization correlate well withchanges in perceived brightness that were assessedin parallel in human subjects using the same stimuli.These results indicate that in cerebral cortex themodulation of synchronicity of responses is usedas a mechanism complementary to rate changes toenhance the saliency of neuronal responses..
- Stephen D. Van Hooser, J. Alexander Heimel, Sooyoung Chung, Sacha B. Nelson. Lack of Patchy Horizontal Connectivity in Primary Visual Cortex of a Mammal without Orientation Maps. Journal of Neuroscience, 26(29):7680 --7692, 2006 abstractIn the cerebral cortex of mammals, horizontal connections link cells up to several millimeters apart. In primary visual cortex (V1) of mammals with orientation maps, horizontal connections ramify in periodic patches across the cortical surface, connecting cells with similar orientation preferences. Rodents have orientation-selective cells but lack orientation maps, raising questions about relationships of horizontal connections to functional maps and receptive field properties. To address these questions, we studied anatomy of horizontal connections and characterized horizontal functional interactions in V1 of the gray squirrel, a highly visual rodent. Long-range intrinsic connections in squirrel V1 extended 1--2 mm but were not patchy or periodic. This result suggests that periodic and patchy connectivity is not a universal organizing principle of cortex, and the existence of patchy and periodic connectivity and functional maps may be linked. In multielectrode and intracellular recordings, we found evidence of unselective local interactions among cells, similar to pinwheel centers of carnivores. These data suggest that, in mammals with and without orientation maps, local connections link near neighbors without regard to orientation selectivity. In single-unit recordings, we found length-summing and end-stopped cells that were similar to those in other mammals. Length-summing cell surrounds were orientation selective, whereas surrounds of end-stopped cells were not. Receptive field response classes are quite similar across mammals, and therefore patchy and columnar connectivity may not be essential for these properties..
- Wei Wang, Helen E Jones, Ian M Andolina, Thomas E Salt, Adam M Sillito. Functional alignment of feedback effects from visual cortex to thalamus.. Nature Neuroscience, 9(10):1330--1336, 2006 abstractFollowing from the classical work of Hubel and Wiesel, it has been recognized that the orientation and the on- and off-zones of receptive fields of layer 4 simple cells in the visual cortex are linked to the spatial alignment and properties of the cells in the visual thalamus that relay the retinal input. Here we present evidence showing that the orientation and the on- and off-zones of receptive fields of layer 6 simple cells in cat visual cortex that provide feedback to the thalamus are similarly linked to the alignment and properties of the receptive fields of the thalamic cells they contact. However, the pattern of influence linked to on- and off-zones is phase-reversed. This has important functional implications..
- A. Angelucci, P. C. Bressloff. Abstract Contribution of feedforward, lateral and feedback connections to the classical receptive field center and extra-classical receptive field surround of primate V1 neurons.. Progress in Brain Research, 154:93--120, 2006 abstract
- L.M. Martinez. The generation of receptive-field structure in cat primary visual cortex. Progress in Brain Research, 154:73--90, 2006 abstract
- Alexandre Reynaud, Frédéric Barthélemy, Ivo Vanzetta, Guillaume S. Masson, Frédéric Chavane. Input-output transformation in the visuo-oculomotor loop: comparison of real-time optical imaging recording in V1 to the ocular following response to center-surround stimulation.. In FENS, 2006 abstractWith human oculomotor recordings, we have previously given evidence for an orientation selective suppressive effect of the surround on the contrast gain control of local stimuli (Barth\'elemy et al 2005). To determine the role of V1 horizontal connectivity in this phenomenon, we compared, in awake behaving monkeys, V1 population activity recorded with voltage-sensitive dye optical imaging with the oculomotor response. Local drifting gratings at various contrasts evoked very similar responses between both recordings. When a surround counter-phased grating is added, the response at the cortical representation of the central region showed an additional offset and a reduction of the amplitude modulation to the different contrasts. This additional offset is most probably due to subthreshold activation by horizontal propagation from the surround representation (Bringuier et al 1999). If we take into account the subthreshold response to surround-only stimulation, optical activity becomes quite analogous to oculomotor response: both recordings showed identical linearization of the contrast tuning curve and a contrast gain reduction in presence of a surround. However, the orientation of the surround stimulus does not affect V1 activity at the representation of the central stimulus although oculomotor response does (at least in human). Studying input and output of the visuo-oculomotor loop allowed us to extrapolate the role of extrastriate visual areas in oculomotor response. At this point, these results may suggest that horizontal connectivity of V1 influences contrast perception but orientation selective suppression occurs in upper level areas..
- Jim Wielaard, Paul Sajda. Extraclassical receptive field phenomena \& short-range connectivity in V1, URL . Cerebral Cortex, 2006 abstract
- Jim Wielaard, Paul Sajda. Circuitry and the Classification of Simple and Complex Cells in V1.. Journal of Neurophysiology, 96:2739-2749, 2006 abstract
- Daniel A. Butts, Chong Weng, Jianzhong Jin, Chun-I Yeh, Nick A. Lesica, José-Ma\ nuel Alonso, Garrett B. Stanley. Temporal precision in the neural code and the time scales of natural vision. Nature, 449(7158):92--5, 2007 abstractThe timing of action potentials relative to sensory stimuli can be precise down to milliseconds in the visual system, even though the relevant time scales of natural vision are much slower. The existence of such precision contributes to a fundamental debate over the basis of the neural code and, specifically, what time scales are important for neural computation. Using recordings in the anesthetized cat, we demonstrate that the temporal precision of LGN spike trains depends on the frequency content of the visual stimulus, and such ``relative'' precision'' is maintained both in spatially uniform noise stimuli and naturalistic movies. Using information-theoretic techniques, we demonstrate a clear role of relative prevision and show that the experimentally observed temporal structure in the neuronal responses adjusts in order to accurately represent the more slowly changing visual world. The existence of relative precision links visual neuron function on slow time scales to temporal structure in the response at faster time scales, and suggests a straightforward functional role of fine-time-scale features of neuronal spike trains..
- Yoav Banitt, Kevan A. C. Martin, Idan Segev. A Biologically Realistic Model of Contrast Invariant Orientation Tuning by Thalamocortical Synaptic Depression, URL . Journal of Neuroscience, 27(38):10230-10239, 2007 abstractSimple cells in layer 4 of the primary visual cortex of the cat show contrast-invariant orientation tuning, in which the amplitude of the peak response is proportional to the stimulus contrast but the width of the tuning curve hardly changes with contrast. This study uses a detailed model of spiny stellate cells (SSCs) from cat area 17 to explain this property. The model integrates our experimental data, including morphological and intrinsic membrane properties and the number and spatial distribution of four major synaptic input sources of the SSC: the dorsal lateral geniculate nucleus (dLGN) and three cortical sources. The model also includes synaptic properties of these inputs. The cortical input served as sources of background activity, and visual stimuli was modeled as sinusoidal grating. For all contrasts, strong synaptic depression of the dLGN feedforward afferents compresses the firing rates in response to orthogonal stimuli, keeping these rates at practically the same low level. However, at preferred orientations, despite synaptic depression, firing rate changes as a function of contrast. Thus, when embedded in an active network, strong synaptic depression can explain contrast-invariant orientation tuning of simple cells. This is true also when the dLGN inputs are partially depressed as a result of their spontaneous activity and to some extent also when parameters were fitted to a more moderate level of synaptic depression. The model response is in close agreement with experimental results, in terms of both output spikes and membrane voltage (amplitude and fluctuations), with reasonable exceptions given that recurrent connections were not incorporated..
- Jessica A Cardin, Larry A Palmer, Diego Contreras. Stimulus feature selectivity in excitatory and inhibitory neurons in primary visual cortex.. Journal of Neuroscience, 27(39):10333--10344, 2007 abstractAlthough several lines of evidence suggest that stimulus selectivity in somatosensory and visual cortices is critically dependent on unselective inhibition, particularly in the thalamorecipient layer 4, no comprehensive comparison of the responses of excitatory and inhibitory cells has been conducted. Here, we recorded intracellularly from a large population of regular spiking (RS; presumed excitatory) and fast spiking (FS; presumed inhibitory) cells in layers 2-6 of primary visual cortex. In layer 4, where selectivity for orientation and spatial frequency first emerges, we found no untuned FS cells. Instead, the tuning of the spike output of layer 4 FS cells was significantly but moderately broader than that of RS cells. However, the tuning of the underlying synaptic responses was not different, indicating that the difference in spike-output selectivity resulted from differences in the transformation of synaptic input into firing rate. Layer 4 FS cells exhibited significantly lower input resistance and faster time constants than layer 4 RS cells, leading to larger and faster membrane potential (V(m)) fluctuations. FS cell V(m) fluctuations were more broadly tuned than those of RS cells and matched spike-output tuning, suggesting that the broader spike tuning of these cells was driven by visually evoked synaptic noise. These differences were not observed outside of layer 4. Thus, cell type-specific differences in stimulus feature selectivity at the first level of cortical sensory processing may arise as a result of distinct biophysical properties that determine the dynamics of synaptic integration..
- A. Peter Bannister, Alex M. Thomson. Dynamic Properties of Excitatory Synaptic Connections Involving Layer 4 Pyramidal Cells in Adult Rat and Cat Neocortex. Cerebral Cortex, 17:2190--2203, 2007 abstract
- Jens Kremkow, Arvind Kumar, Stefan Rotter, Ad M. Aertsen. Emergence of population synchrony in a layered network of the cat visual cortex. Neurocomputing, 70(10-12):2069-2073, 2007 abstractRecently, a quantitative wiring diagram for the local neuronal network of cat visual cortex was described [T. Binzegger, R.J. Douglas, K.A.C. Martin, A quantitative map of the circuit of the cat primary visual cortex, J. Neurosci. 39 (24) (2004) 8441--8453.] giving the first complete estimate of synaptic connectivity among various types of neurons in different cortical layers. Here we numerically studied the activity dynamics of the resulting heterogeneous layered network of spiking integrate-and-fire neurons, connected with conductance-based synapses. The layered network exhibited, among other states, an interesting asynchronous activity with intermittent population-wide synchronizations. These population bursts (PB) were initiated by a network hot spot, and then spread into the other parts of the network. The cause of this PB is the correlation amplifying nature of recurrent connections, which becomes significant in densely coupled networks. The hot spot was located in layer 2/3, the part of the network with the highest number of excitatory recurrent connections. We conclude that in structured networks, regions with a high degree of recurrence and many out-going fibres may be a source for population-wide synchronization..
- Ian M Andolina, Helen E Jones, Wei Wang, Adam M Sillito. Corticothalamic feedback enhances stimulus response precision in the visual system.. Proceedings of the National Academy of Sciences USA, 104(5):1685--90, 2007 abstractThere is a tightly coupled bidirectional interaction between visual cortex and visual thalamus [lateral geniculate nucleus (LGN)]. Using drifting sinusoidal grating stimuli, we compared the response of cells in the LGN with and without feedback from the visual cortex. Raster plots revealed a striking difference in the response pattern of cells with and without feedback. This difference was reflected in the results from computing vector sum plots and the ratio of zero harmonic to the fundamental harmonic of the fast Fourier transform (FFT) for these responses. The variability of responses assessed by using the Fano factor was also different for the two groups, with the cells without feedback showing higher variability. We examined the covariance of these measures between pairs of simultaneously recorded cells with and without feedback, and they were much more strongly positively correlated with feedback. We constructed orientation tuning curves from the central 5 ms in the raw cross-correlograms of the outputs of pairs of LGN cells, and these curves revealed much sharper tuning with feedback. We discuss the significance of these data for cortical function and suggest that the precision in stimulus-linked firing in the LGN appears as an emergent factor from the corticothalamic interaction..
- Jens Kremkow, Laurent U. Perrinet, Arvind Kumar, Ad M. Aertsen, Guillaume S. Masson. Synchrony in thalamic inputs enhances propagation of activity through cortical layers, URL . In Sixteenth Annual Computational Neuroscience Meeting: CNS*2007, Toronto, Canada. 7--12 July 2007, 2007 abstractSensory input enters the cortex via the thalamocortical (TC) projection, where it elicits large postsynaptic potentials in layer 4 neurons . Interestingly, the TC connections account for only ~15% of synapses onto these neurons. It has been therefore controversially discussed how thalamic input can drive the cortex. Strong TC synapses have been one suggestion to ensure the strength of the TC projection ("strong-synapse model"). Another possibility is that the excitation from single thalamic fibers are weak but get amplified by recurrent excitatory feedback in layer 4 ("amplifier model"). Bruno and Sakmann  recently provided new evidence that individual TC synapses in vivo are weak and only produce small excitatory postsynaptic potentials. However, they suggested that thalamic input can activate the cortex due to the synchronous firing and that cortical amplification is not required. This would support the "synchrony model" proposed by correlation analysis . Here, we studied the effect of correlation in the TC input, with weak synapses, to the responses of a layered cortical network model. The connectivity of the layered network was taken from Binzegger et al. 2004 . The network was simulated using NEST  with the Python interface PyNN  to enable interoperability with different simulators. The sensory input to layer 4 was modelled by a simple retino-geniculate model of the transformation of light into spike trains , which was implemented by leaky integrate-and-fire model neurons. We found that introducing correlation into TC inputs enhanced the likelihood to produce responses in layer 4 and improved the activity propagation across layers. In addition, we compared the response of the cortical network to different noise conditions and obtained contrast response functions which were in accordance with neurophysiological observations. This Work is supported by the 6th RFP of the EU (grant no. 15879-FACETS) and by the BMBF grant 01GQ0420 to the BCCN Freiburg. 1. Chung S, Ferster D: Strength and orientation tuning of the thalamic input to simple cells revealed by electrically evoked cortical suppression. Neuron 1998, 20:1177-1189. 2. Bruno M, Sakmann B: Cortex is driven by weak but synchronously active thalamocortical synpases. Science 2006, 312:1622-1627. 3. Alonso JM, Usrey WM, Reid RC: Precisely correlated firing in cells of the lateral geniculate nucleus. Nature 1996, 383:815-819. 4. Binzegger T, Douglas RJ, Martin KAC: A quantitative map of the circuit of the cat primary visual cortex. J Neurosci 2004, 24:8441-8453. 5. NEST http://www.nest-initiative.org 6. PyNN http://pynn.gforge.inria.fr 7. Gazeres N, Borg-Graham LJ, Fr\'egnac Y: A phenomenological model of visually evoked spike trains in cat geniculate nonlagged X-cells. Vis Neurosci 1998, 15:1157-1174..
- Alexandre Reynaud, Frédéric Barthélemy, Ivo Vanzetta, Guillaume S. Masson, Frédéric Chavane. Input-output transformation in the visuo-oculomotor loop: comparison of real-time optical imaging recording in V1 to the ocular following response to center-surround stimulation. Italian Archives of Biology, 145:251--62, 2007 abstractWith human oculomotor recordings, we have previously given evidence for an orientation selective suppressive effect of the surround on the contrast gain control of local stimuli (Barth\'elemy et al 2005). To determine the role of V1 horizontal connectivity in this phenomenon, we compared, in awake behaving monkeys, V1 population activity recorded with voltage-sensitive dye optical imaging with the oculomotor response. Local drifting gratings at various contrasts evoked very similar responses between both recordings. When a surround counter-phased grating is added, the response at the cortical representation of the central region showed an additional offset and a reduction of the amplitude modulation to the different contrasts. This additional offset is most probably due to subthreshold activation by horizontal propagation from the surround representation (Bringuier et al 1999). If we take into account the subthreshold response to surround-only stimulation, optical activity becomes quite analogous to oculomotor response: both recordings showed identical linearization of the contrast tuning curve and a contrast gain reduction in presence of a surround. However, the orientation of the surround stimulus does not affect V1 activity at the representation of the central stimulus although oculomotor response does (at least in human). Studying input and output of the visuo-oculomotor loop allowed us to extrapolate the role of extrastriate visual areas in oculomotor response. At this point, these results may suggest that horizontal connectivity of V1 influences contrast perception but orientation selective suppression occurs in upper level areas..
- X Wang, M Zhang, IS Cohen, ME Goldberg. The proprioceptive representation of eye position in monkey primary somatosensory cortex. Nature Neuroscience, 10(5):640--6, 2007 abstractThe cerebral cortex must have access to an eye position signal, as humans can report passive changes in eye position in total darkness, and visual responses in many cortical areas are modulated by eye position. The source of this signal is unknown. Here we demonstrate a representation of eye position in monkey primary somatosensory cortex, in the representation of the trigeminal nerve, near cells with a tactile representation of the contralateral brow. The neurons have eye position signals that increase monotonically with increasing orbital eccentricity from near the center of gaze, with directionally selectivity tuned in a Gaussian manner. All directions of eye position are represented in a single hemisphere. The signal is proprioceptive, because it can be obliterated by anesthetizing the contralateral orbit. It is not related to foveal or peripheral visual stimulation, and it represents the position of the eye in the head and not the angle of gaze in space..
- Jens Kremkow, Laurent U. Perrinet, Pierre Baudot, Manu Levy, Olivier Marre, Cyril Monier, Yves Frégnac, Guillaume S. Masson, Ad Aertsen. Control of the temporal interplay between excitation and inhibition by the statistics of visual input: a V1 network modelling study, URL . In Proceedings of the Society for Neuroscience conference, 2008 abstractIn the primary visual cortex (V1), single cell responses to simple visual stimuli (gratings) are usually dense but with a high trial-by-trial variability. In contrast, when exposed to full field natural scenes, the firing patterns of these neurons are sparse but highly reproducible over trials (Marre et al., 2005; Fr\'egnac et al., 2006). It is still not understood how these two classes of stimuli can elicit these two distinct firing behaviours. A common model for simple-cell computation in layer 4 is the ``push-pull'' circuitry (Troyer et al. 1998). It accounts for the observed anti-phase behaviour between excitatory and inhibitory conductances in response to a drifting grating (Anderson et al., 2000; Monier et al., 2008), creating a wide temporal integration window during which excitation is integrated without the shunting or opponent effect of inhibition and allowed to elicit multiple spikes. This is in contrast to recent results from intracellular recordings in vivo during presentation of natural scenes (Baudot et al., submitted). Here the excitatory and inhibitory conductances were highly correlated, with inhibition lagging excitation only by few milliseconds (~6 ms). This small lag creates a narrow temporal integration window such that only synchronized excitatory inputs can elicit a spike, similar to parallel observations in other cortical sensory areas (Wehr and Zador, 2003; Okun and Lampl, 2008). To investigate the cellular and network mechanisms underlying these two different correlation structures, we constructed a realistic model of the V1 network using spiking neurons with conductance based synapses. We calibrated our model to fit the irregular ongoing activity pattern as well as in vivo conductance measurements during drifting grating stimulation and then extracted predicted responses to natural scenes seen through eye-movements. Our simulations reproduced the above described experimental observation, together with anti-phase behaviour between excitation and inhibition during gratings and phase lagged activation during natural scenes. In conclusion, the same cortical network that shows dense and variable responses to gratings exhibits sparse and precise spiking to natural scenes. Work is under way to show to which extent this feature is specific for the feedforward vs recurrent nature of the modelled circuit..
- Jens Kremkow, Laurent U. Perrinet, Ad M. Aertsen, Guillaume S. Masson. Functional properties of feed-forward inhibition. abstract
- Jens Kremkow, Laurent U. Perrinet, Guillaume S. Masson, Ad Aertsen. Functional consequences of correlated excitation and inhibition on single neuron integration and signal propagation through synfire chains, URL . In Eighth Göttingen Meeting of the German Neuroscience Society, pages T26-6B. 2009 abstractNeurons receive a large number of excitatory and inhibitory synaptic inputs whose temporal interplay determines their spiking behavior. On average, excitation (Gexc) and inhibition (Ginh) balance each other, such that spikes are elicited by fluctuations . In addition, it has been shown in vivo that Gexc and Ginh are correlated, with Ginh lagging Gexc only by few milliseconds (6ms), creating a small temporal integration window [2,3]. This correlation structure could be induced by feed-forward inhibition (FFI), which has been shown to be present at many sites in the central nervous system. To characterize the functional consequences of the FFI, we first modeled a simple circuit using spiking neurons with conductance based synapses and studied the effect on the single neuron integration. We then coupled many of such circuits to construct a feed-forward network (synfire chain [4,5]) and investigated the effect of FFI on signal propagation along such feed-forward network. We found that the small temporal integration window, induced by the FFI, changes the integrative properties of the neuron. Only transient stimuli could produce a response when the FFI was active whereas without FFI the neuron responded to both steady and transient stimuli. Due to the increase in selectivity to transient inputs, the conditions of signal propagation through the feed-forward network changed as well. Whereas synchronous inputs could reliable propagate, high asynchronous input rates, which are known to induce synfire activity , failed to do so. In summary, the FFI increased the stability of the synfire chain. Supported by DFG SFB 780, EU-15879-FACETS, BMBF 01GQ0420 to BCCN Freiburg  Kumar A., Schrader S., Aertsen A. and Rotter S. (2008). The high-conductance state of cortical networks. Neural Computation, 20(1):1--43.  Okun M. and Lampl I. (2008). Instantaneous correlation of excitation and inhibition during ongoing and sensory- evoked activities. Nat Neurosci, 11(5):535--7.  Baudot P., Levy M., Marre O., Monier C. and Fr\'egnac (2008). submitted.  Abeles M. (1991). Corticonics: Neural circuits of the cerebral cortex. Cambridge, UK  Diesmann M., Gewaltig M-O and Aertsen A. (1999). Stable propagation of synchronous spiking in cortical neural networks. Nature, 402(6761):529--33.  Kumar A., Rotter S. and Aertsen A. (2008), Conditions for propagating synchronous spiking and asynchronous firing rates in a cortical network model. J Neurosci 28 (20), 5268--80. Preliminary Program.
- Fabian H. Sinz, Matthias Bethge. The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction. In Advances in Neural Information Processing Systems 21, pages 1521--1528. 2009 abstract
- Jens Kremkow. Correlating Excitation and Inhibition in Visual Cortical Circuits: Functional Consequences and Biological Feasibility. 2009 abstractThe primary visual cortex (V1) is one of the most studied cortical area in the brain. Together with the retina and the lateral geniculate nucleus (LGN) it forms the early visual system. Artificial stimuli (i.e. drifting gratings (DG)) have given insights into the neural basis of visual processing. However, recently researchers have started to use more complex natural visual stimuli (NI), arguing that the low dimensional artificial stimuli are not sufficient for a complete understanding of the visual system.For example, whereas the responses of V1 neurons to DG are dense but with variable spike timings, the neurons respond with only few but precise spikes to NI. Furthermore, linear receptive field models provide a good fit to responses during simple stimuli, however, they often fail during NI. To investigate the mechanisms behind the stimulus dependent responses of cortical neurons we have built a biophysical model of the early visual system.Our results show that during NI the LGN afferents show epochs of correlated activity, resulting in precise spike timings in V1. The sparseness of the responses to NI can be explained by correlated inhibitory conductance. We continue by investigating the origin of stimulus dependent nonlinear responses, by comparing models of different complexity. Our results suggest that adaptive processes shape the responses, depending on the temporal properties of the stimuli. Lastly we study the functional consequences of correlated excitatory and inhibitory condutances in more details in generic models.The presented work gives new perspectives on the processing of the early visual system, in particular on the importance of correlated conductances..
- Jens Kremkow, Laurent U. Perrinet, Guillaume S. Masson, Ad Aertsen. Functional consequences of correlated excitatory and inhibitory conductances in cortical networks. Journal of Computational Neuroscience, 28(3):579-94, 2010 abstract
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This work was supported by European integrated project FP6-015879, "FACETS".