A polysynaptic feedback circuit in rat visual cortex

Cellular mechanisms of cooperative context-sensitive predictive inference

We argue that prediction success maximization is a basic objective of cognition and cortex, that it is compatible with but distinct from prediction error minimization, that neither objective requires subtractive coding, that there is clear neurobiological evidence for the amplification of predicted signals, and that we are unconvinced by evidence proposed in support of subtractive coding. We outline recent discoveries showing that pyramidal cells on which our cognitive capabilities depend usually transmit information about input to their basal dendrites and amplify that transmission when input to their distal apical dendrites provides a context that agrees with the feedforward basal input in that both are depolarizing, i.e., both are excitatory rather than inhibitory. Though these intracellular discoveries require a level of technical expertise that is beyond the current abilities of most neuroscience labs, they are not controversial and acclaimed as groundbreaking. We note that this cellular cooperative context-sensitivity greatly enhances the cognitive capabilities of the mammalian neocortex, and that much remains to be discovered concerning its evolution, development, and pathology.

Top-down influence of areas 21a and 7 differently affects the surround suppression of V1 neurons in cats

Surround suppression (SS) is a phenomenon whereby a neuron's response to stimuli in its central receptive field (cRF) is suppressed by stimuli extending to its surround receptive field (sRF). Recent evidence show that top-down influence contributed to SS in the primary visual cortex (V1). However, how the top-down influence from different high-level cortical areas affects SS in V1 has not been comparatively observed. The present study applied transcranial direct current stimulation (tDCS) to modulate the neural activity in area 21a (A21a) and area 7 (A7) of cats and examined the changes in the cRF and sRF of V1 neurons. We found that anode-tDCS at A21a reduced V1 neurons' cRF size and increased their response to visual stimuli in cRF, causing an improved SS strength. By contrast, anode-tDCS at A7 increased V1 neurons' sRF size and response to stimuli in cRF, also enhancing the SS. Modeling analysis based on DoG function indicated that the increased SS of V1 neurons after anode-tDCS at A21a could be explained by a center-only mechanism, whereas the improved SS after anode-tDCS at A7 might be mediated through a combined center and surround mechanism. In conclusion, A21a and A7 may affect the SS of V1 neurons through different mechanisms.

Enriched environment exposure during development positively impacts the structure and function of the visual cortex in mice

Optimal conditions of development have been of interest for decades, since genetics alone cannot fully explain how an individual matures. In the present study, we used optical brain imaging to investigate whether a relatively simple enrichment can positively influence the development of the visual cortex of mice. The enrichment paradigm was composed of larger cages housing multiple mice that contained several toys, hiding places, nesting material and a spinning wheel that were moved or replaced at regular intervals. We compared C57BL/6N adult mice (> P60) that had been raised either in an enriched environment (EE; n = 16) or a standard (ST; n = 12) environment from 1 week before birth to adulthood, encompassing all cortical developmental stages. Here, we report significant beneficial changes on the structure and function of the visual cortex following environmental enrichment throughout the lifespan. More specifically, retinotopic mapping through intrinsic signal optical imaging revealed that the size of the primary visual cortex was greater in mice reared in an EE compared to controls. In addition, the visual field coverage of EE mice was wider. Finally, the organization of the cortical representation of the visual field (as determined by cortical magnification) versus its eccentricity also differed between the two groups. We did not observe any significant differences between females and males within each group. Taken together, these data demonstrate specific benefits of an EE throughout development on the visual cortex, which suggests adaptation to their environmental realities.

Suppression of top-down influence decreases both behavioral and V1 neuronal response sensitivity to stimulus orientations in cats

How top-down influence affects behavioral detection of visual signals and neuronal response sensitivity in the primary visual cortex (V1) remains poorly understood. This study examined both behavioral performance in stimulus orientation identification and neuronal response sensitivity to stimulus orientations in the V1 of cat before and after top-down influence of area 7 (A7) was modulated by non-invasive transcranial direct current stimulation (tDCS). Our results showed that cathode (c) but not sham (s) tDCS in A7 significantly increased the behavioral threshold in identifying stimulus orientation difference, which effect recovered after the tDCS effect vanished. Consistently, c-tDCS but not s-tDCS in A7 significantly decreased the response selectivity bias of V1 neurons for stimulus orientations, which effect could recover after withdrawal of the tDCS effect. Further analysis showed that c-tDCS induced reduction of V1 neurons in response selectivity was not resulted from alterations of neuronal preferred orientation, nor of spontaneous activity. Instead, c-tDCS in A7 significantly lowered the visually-evoked response, especially the maximum response of V1 neurons, which caused a decrease in response selectivity and signal-to-noise ratio. By contrast, s-tDCS exerted no significant effect on the responses of V1 neurons. These results indicate that top-down influence of A7 may enhance behavioral identification of stimulus orientations by increasing neuronal visually-evoked response and response selectivity in the V1.

Alternative strategy for driving voltage-oscillator in neocortex of rats

Information integration in the brain requires functional connectivity between local neural networks. Here, we investigated the interregional coupling mechanism from the viewpoint of oscillations using optical recording methods. Low-frequency electrical stimulation of rat neocortical slices in a caffeine-containing medium induced oscillatory activity between the primary visual cortex (Oc1) and medial secondary visual cortex (Oc2M), in which the oscillation generator was located in the Oc2M and was triggered by a feedforward signal. During to-and-fro oscillatory activity, neural excitation was marked in layer II/III. When the upper layer was disrupted between Oc1 and Oc2M, feedforward signals could propagate through the deep layer and switch on the oscillator in the Oc2M. When the lower layer was disrupted between Oc1 and Oc2M, feedforward signals could propagate through the upper layer and switch on the oscillator in the Oc2M. In the backward direction, neither the upper layer cut nor the lower layer cut disrupted the propagation of the oscillations. In all cases, the horizontal and vertical pathways were used as needed. Fluctuations in the oscillatory waveforms of the local field potential at the upper and lower layers in the Oc2M were reversed, suggesting that the oscillation originated between the two layers. Thus, the neocortex may work as a safety device for interregional communications in an alternative way to drive voltage oscillators in the neocortex.

Effects of top-down influence suppression on behavioral and V1 neuronal contrast sensitivity functions in cats

To explore the relative contributions of higher-order and primary visual cortex (V1) to visual perception, we compared cats' behavioral and V1 neuronal contrast sensitivity functions (CSF) and threshold versus external noise contrast (TvC) functions before and after top-down influence of area 7 (A7) was modulated with transcranial direct current stimulation (tDCS). We found that suppressing top-down influence of A7 with cathode-tDCS, but not sham-tDCS, reduced behavioral and neuronal contrast sensitivity in the same range of spatial frequencies and increased behavioral and neuronal contrast thresholds in the same range of external noise levels. The neuronal CSF and TvC functions were highly correlated with their behavioral counterparts both before and after the top-down suppression. Analysis of TvC functions using the Perceptual Template Model (PTM) indicated that top-down influence of A7 increased both behavioral and V1 neuronal contrast sensitivity by reducing internal additive noise and the impact of external noise.

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Top-down suppression lowers both behavioral and V1 neuronal CSF functions

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Top-down suppression raises both behavioral and V1 neuronal TvC functions

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The neuronal CSFs and TvCs are highly correlated with their behavioral counterparts

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Top-down influence lowers internal additive noise and impact of external noise in V1

Stimulus-dependent representational drift in primary visual cortex

To produce consistent sensory perception, neurons must maintain stable representations of sensory input. However, neurons in many regions exhibit progressive drift across days. Longitudinal studies have found stable responses to artificial stimuli across sessions in visual areas, but it is unclear whether this stability extends to naturalistic stimuli. We performed chronic 2-photon imaging of mouse V1 populations to directly compare the representational stability of artificial versus naturalistic visual stimuli over weeks. Responses to gratings were highly stable across sessions. However, neural responses to naturalistic movies exhibited progressive representational drift across sessions. Differential drift was present across cortical layers, in inhibitory interneurons, and could not be explained by differential response strength or higher order stimulus statistics. However, representational drift was accompanied by similar differential changes in local population correlation structure. These results suggest representational stability in V1 is stimulus-dependent and may relate to differences in preexisting circuit architecture of co-tuned neurons.

Suppression of top-down influence decreases neuronal excitability and contrast sensitivity in the V1 cortex of cat

How top-down influence affects neuronal activity and information encoding in the primary visual cortex (V1) remains elusive. This study examined changes of neuronal excitability and contrast sensitivity in cat V1 cortex after top-down influence of area 7 (A7) was modulated by transcranial direct current stimulation (tDCS). The neuronal excitability in V1 cortex was evaluated by visually evoked field potentials (VEPs), and contrast sensitivity (CS) was assessed by the inverse of threshold contrast of neurons in response to visual stimuli at different performance accuracy. We found that the amplitude of VEPs in V1 cortex lowered after top-down influence suppression with cathode-tDCS in A7, whereas VEPs in V1 did not change after sham-tDCS in A7 and nonvisual cortical area 5 (A5) or cathode-tDCS in A5 and lesioned A7. Moreover, the mean CS of V1 neurons decreased after cathode-tDCS but not sham-tDCS in A7, which could recover after tDCS effect vanished. Comparisons of neuronal contrast-response functions showed that cathode-tDCS increased the stimulus contrast required to generate the half-maximum response, with a weakly-correlated reduction in maximum response but not baseline response. Therefore, top-down influence of A7 enhanced neuronal excitability in V1 cortex and improved neuronal contrast sensitivity by both contrast gain and response gain.

Cortical and Subcortical Circuits for Cross-Modal Plasticity Induced by Loss of Vision

Cortical areas are highly interconnected both via cortical and subcortical pathways, and primary sensory cortices are not isolated from this general structure. In primary sensory cortical areas, these pre-existing functional connections serve to provide contextual information for sensory processing and can mediate adaptation when a sensory modality is lost. Cross-modal plasticity in broad terms refers to widespread plasticity across the brain in response to losing a sensory modality, and largely involves two distinct changes: cross-modal recruitment and compensatory plasticity. The former involves recruitment of the deprived sensory area, which includes the deprived primary sensory cortex, for processing the remaining senses. Compensatory plasticity refers to plasticity in the remaining sensory areas, including the spared primary sensory cortices, to enhance the processing of its own sensory inputs. Here, we will summarize potential cellular plasticity mechanisms involved in cross-modal recruitment and compensatory plasticity, and review cortical and subcortical circuits to the primary sensory cortices which can mediate cross-modal plasticity upon loss of vision.

Untangling the cortico-thalamo-cortical loop: cellular pieces of a knotty circuit puzzle

Functions of the neocortex depend on its bidirectional communication with the thalamus, via cortico-thalamo-cortical (CTC) loops. Recent work dissecting the synaptic connectivity in these loops is generating a clearer picture of their cellular organization. Here, we review findings across sensory, motor and cognitive areas, focusing on patterns of cell type-specific synaptic connections between the major types of cortical and thalamic neurons. We outline simple and complex CTC loops, and note features of these loops that appear to be general versus specialized. CTC loops are tightly interlinked with local cortical and corticocortical (CC) circuits, forming extended chains of loops that are probably critical for communication across hierarchically organized cerebral networks. Such CTC-CC loop chains appear to constitute a modular unit of organization, serving as scaffolding for area-specific structural and functional modifications. Inhibitory neurons and circuits are embedded throughout CTC loops, shaping the flow of excitation. We consider recent findings in the context of established CTC and CC circuit models, and highlight current efforts to pinpoint cell type-specific mechanisms in CTC loops involved in consciousness and perception. As pieces of the connectivity puzzle fall increasingly into place, this knowledge can guide further efforts to understand structure-function relationships in CTC loops.

Laminar-specific cortico-cortical loops in mouse visual cortex

Many theories propose recurrent interactions across the cortical hierarchy, but it is unclear if cortical circuits are selectively wired to implement looped computations. Using subcellular channelrhodopsin-2-assisted circuit mapping in mouse visual cortex, we compared feedforward (FF) or feedback (FB) cortico-cortical (CC) synaptic input to cells projecting back to the input source (looped neurons) with cells projecting to a different cortical or subcortical area. FF and FB afferents showed similar cell-type selectivity, making stronger connections with looped neurons than with other projection types in layer (L)5 and L6, but not in L2/3, resulting in selective modulation of activity in looped neurons. In most cases, stronger connections in looped L5 neurons were located on their apical tufts, but not on their perisomatic dendrites. Our results reveal that CC connections are selectively wired to form monosynaptic excitatory loops and support a differential role of supragranular and infragranular neurons in hierarchical recurrent computations.

Characterization of Feedback Neurons in the High-Level Visual Cortical Areas That Project Directly to the Primary Visual Cortex in the Cat

Previous studies indicate that top-down influence plays a critical role in visual information processing and perceptual detection. However, the substrate that carries top-down influence remains poorly understood. Using a combined technique of retrograde neuronal tracing and immunofluorescent double labeling, we characterized the distribution and cell type of feedback neurons in cat's high-level visual cortical areas that send direct connections to the primary visual cortex (V1: area 17). Our results showed: (1) the high-level visual cortex of area 21a at the ventral stream and PMLS area at the dorsal stream have a similar proportion of feedback neurons back projecting to the V1 area, (2) the distribution of feedback neurons in the higher-order visual area 21a and PMLS was significantly denser than in the intermediate visual cortex of area 19 and 18, (3) feedback neurons in all observed high-level visual cortex were found in layer II-III, IV, V, and VI, with a higher proportion in layer II-III, V, and VI than in layer IV, and (4) most feedback neurons were CaMKII-positive excitatory neurons, and few of them were identified as inhibitory GABAergic neurons. These results may argue against the segregation of ventral and dorsal streams during visual information processing, and support "reverse hierarchy theory" or interactive model proposing that recurrent connections between V1 and higher-order visual areas constitute the functional circuits that mediate visual perception. Also, the corticocortical feedback neurons from high-level visual cortical areas to the V1 area are mostly excitatory in nature.

Shape perception enhances perceived contrast: evidence for excitatory predictive feedback?

Predictive coding theory suggests that predictable responses are “explained away” (i.e., reduced) by feedback. Experimental evidence for feedback inhibition, however, is inconsistent: most neuroimaging studies show reduced activity by predictive feedback, while neurophysiology indicates that most inter-areal cortical feedback is excitatory and targets excitatory neurons. In this study, we asked subjects to judge the luminance of two gray disks containing stimulus outlines: one enabling predictive feedback (a 3D-shape) and one impeding it (random-lines). These outlines were comparable to those used in past neuroimaging studies. All 14 subjects consistently perceived the disk with a 3D-shape stimulus brighter; thus, predictive feedback enhanced perceived contrast. Since early visual cortex activity at the population level has been shown to have a monotonic relationship with subjective contrast perception, we speculate that the perceived contrast enhancement could reflect an increase in neuronal activity. In other words, predictive feedback may have had an excitatory influence on neuronal responses. Control experiments ruled out attention bias, local feature differences and response bias as alternate explanations.

A review of predictive coding algorithms

Predictive coding is a leading theory of how the brain performs probabilistic inference. However, there are a number of distinct algorithms which are described by the term "predictive coding". This article provides a concise review of these different predictive coding algorithms, highlighting their similarities and differences. Five algorithms are covered: linear predictive coding which has a long and influential history in the signal processing literature; the first neuroscience-related application of predictive coding to explaining the function of the retina; and three versions of predictive coding that have been proposed to model cortical function. While all these algorithms aim to fit a generative model to sensory data, they differ in the type of generative model they employ, in the process used to optimise the fit between the model and sensory data, and in the way that they are related to neurobiology.

Hierarchical Novelty-Familiarity Representation in the Visual System by Modular Predictive Coding

Predictive coding has been previously introduced as a hierarchical coding framework for the visual system. At each level, activity predicted by the higher level is dynamically subtracted from the input, while the difference in activity continuously propagates further. Here we introduce modular predictive coding as a feedforward hierarchy of prediction modules without back-projections from higher to lower levels. Within each level, recurrent dynamics optimally segregates the input into novelty and familiarity components. Although the anatomical feedforward connectivity passes through the novelty-representing neurons, it is nevertheless the familiarity information which is propagated to higher levels. This modularity results in a twofold advantage compared to the original predictive coding scheme: the familiarity-novelty representation forms quickly, and at each level the full representational power is exploited for an optimized readout. As we show, natural images are successfully compressed and can be reconstructed by the familiarity neurons at each level. Missing information on different spatial scales is identified by novelty neurons and complements the familiarity representation. Furthermore, by virtue of the recurrent connectivity within each level, non-classical receptive field properties still emerge. Hence, modular predictive coding is a biologically realistic metaphor for the visual system that dynamically extracts novelty at various scales while propagating the familiarity information.

Neural Mechanisms of Cortical Motion Computation Based on a Neuromorphic Sensory System

The visual cortex analyzes motion information along hierarchically arranged visual areas that interact through bidirectional interconnections. This work suggests a bio-inspired visual model focusing on the interactions of the cortical areas in which a new mechanism of feedforward and feedback processing are introduced. The model uses a neuromorphic vision sensor (silicon retina) that simulates the spike-generation functionality of the biological retina. Our model takes into account two main model visual areas, namely V1 and MT, with different feature selectivities. The initial motion is estimated in model area V1 using spatiotemporal filters to locally detect the direction of motion. Here, we adapt the filtering scheme originally suggested by Adelson and Bergen to make it consistent with the spike representation of the DVS. The responses of area V1 are weighted and pooled by area MT cells which are selective to different velocities, i.e. direction and speed. Such feature selectivity is here derived from compositions of activities in the spatio-temporal domain and integrating over larger space-time regions (receptive fields). In order to account for the bidirectional coupling of cortical areas we match properties of the feature selectivity in both areas for feedback processing. For such linkage we integrate the responses over different speeds along a particular preferred direction. Normalization of activities is carried out over the spatial as well as the feature domains to balance the activities of individual neurons in model areas V1 and MT. Our model was tested using different stimuli that moved in different directions. The results reveal that the error margin between the estimated motion and synthetic ground truth is decreased in area MT comparing with the initial estimation of area V1. In addition, the modulated V1 cell activations shows an enhancement of the initial motion estimation that is steered by feedback signals from MT cells.

Physiology of layer 5 pyramidal neurons in mouse primary visual cortex: coincidence detection through bursting

L5 pyramidal neurons are the only neocortical cell type with dendrites reaching all six layers of cortex, casting them as one of the main integrators in the cortical column. What is the nature and mode of computation performed in mouse primary visual cortex (V1) given the physiology of L5 pyramidal neurons? First, we experimentally establish active properties of the dendrites of L5 pyramidal neurons of mouse V1 using patch-clamp recordings. Using a detailed multi-compartmental model, we show this physiological setup to be well suited for coincidence detection between basal and apical tuft inputs by controlling the frequency of spike output. We further show how direct inhibition of calcium channels in the dendrites modulates such coincidence detection. To establish the singe-cell computation that this biophysics supports, we show that the combination of frequency-modulation of somatic output by tuft input and (simulated) calcium-channel blockage functionally acts as a composite sigmoidal function. Finally, we explore how this computation provides a mechanism whereby dendritic spiking contributes to orientation tuning in pyramidal neurons.

Neurons in the brain have elaborate dendritic morphologies, hosting a variety of nonlinear channels that give way to single cell computation. In this study, we perform patch clamp recordings in the apical dendrites to establish the spatial distribution of nonlinear channels and the signals they support in the dendrites of layer 5 pyramidal neurons of the mouse primary visual cortex. Using this data, we create a detailed single cell model and simulate synaptic input. We then summarize the results of the simulations using a simple abstracted model, that ultimately describes the computation layer 5 pyramidal neurons perform on synaptic input. We find that this computation is a form of nonlinear frequency-modulation that works in a dendritic-spike dependent manner. Finally, we show how this computation allows dendritic spikes to contribute to the orientation tuning of pyramidal neurons in the visual cortex.

Anatomy of hierarchy: feedforward and feedback pathways in macaque visual cortex

The laminar location of the cell bodies and terminals of interareal connections determines the hierarchical structural organization of the cortex and has been intensively studied. However, we still have only a rudimentary understanding of the connectional principles of feedforward (FF) and feedback (FB) pathways. Quantitative analysis of retrograde tracers was used to extend the notion that the laminar distribution of neurons interconnecting visual areas provides an index of hierarchical distance (percentage of supragranular labeled neurons [SLN]). We show that: 1) SLN values constrain models of cortical hierarchy, revealing previously unsuspected areal relations; 2) SLN reflects the operation of a combinatorial distance rule acting differentially on sets of connections between areas; 3) Supragranular layers contain highly segregated bottom-up and top-down streams, both of which exhibit point-to-point connectivity. This contrasts with the infragranular layers, which contain diffuse bottom-up and top-down streams; 4) Cell filling of the parent neurons of FF and FB pathways provides further evidence of compartmentalization; 5) FF pathways have higher weights, cross fewer hierarchical levels, and are less numerous than FB pathways. Taken together, the present results suggest that cortical hierarchies are built from supra- and infragranular counterstreams. This compartmentalized dual counterstream organization allows point-to-point connectivity in both bottom-up and top-down directions.

Cortico-cortical projections in mouse visual cortex are functionally target specific

Neurons in primary sensory cortex have diverse response properties, whereas higher cortical areas are specialized. Specific connectivity may be important for areal specialization, particularly in the mouse, where neighboring neurons are functionally diverse. To examine whether higher visual areas receive functionally specific input from primary visual cortex (V1), we used two-photon calcium imaging to measure responses of axons from V1 arborizing in three areas with distinct spatial and temporal frequency preferences. We found that visual preferences of presynaptic boutons in each area were distinct and matched the average preferences of recipient neurons. This specificity could not be explained by organization within V1 and instead was due to both a greater density and greater response amplitude of functionally matched boutons. Projections from a single layer (layer 5) and from secondary visual cortex were also matched to their target areas. Thus, transmission of specific information to downstream targets may be a general feature of cortico-cortical communication.

Canonical microcircuits for predictive coding

This Perspective considers the influential notion of a canonical (cortical) microcircuit in light of recent theories about neuronal processing. Specifically, we conciliate quantitative studies of microcircuitry and the functional logic of neuronal computations. We revisit the established idea that message passing among hierarchical cortical areas implements a form of Bayesian inference-paying careful attention to the implications for intrinsic connections among neuronal populations. By deriving canonical forms for these computations, one can associate specific neuronal populations with specific computational roles. This analysis discloses a remarkable correspondence between the microcircuitry of the cortical column and the connectivity implied by predictive coding. Furthermore, it provides some intuitive insights into the functional asymmetries between feedforward and feedback connections and the characteristic frequencies over which they operate.

Cholinergic control of cortical network interactions enables feedback-mediated attentional modulation

Attention increases our ability to detect behaviorally relevant stimuli. At the neuronal level this is supported by increased firing rates of neurons representing the attended object. In primary visual cortex an attention-mediated activity increase depends on the presence of the neuromodulator acetylcholine. Using a spiking network model of visual cortex we have investigated how acetylcholine interacts with biased feedback to enable attentional processing. Although acetylcholine affects cortical processing in a multitude of manners, we restricted our analysis to four of its main established actions. These were (i) a reduction in firing rate adaptation by reduction in M-currents (muscarinic), (ii) an increase in thalamocortical synaptic efficacy by nicotinic presynaptic receptors, (iii) a reduction in lateral interactions by muscarinic presynaptic receptors, and (iv) an increase in inhibitory drive by muscarinic receptors located on inhibitory interneurons. We found that acetylcholine contributes to feedback-mediated attentional modulation, mostly by reducing intracortical interactions and also to some extent by increasing the inhibitory drive. These findings help explain why acetylcholine is necessary for top-down-driven attentional modulation, and suggest a close interdependence of cholinergic and feedback drive in mediating cognitive function.

Indirect pathway between the primary auditory and visual cortices through layer V pyramidal neurons in V2L in mouse and the effects of bilateral enucleation

Visual cortical areas are activated by auditory stimuli in blind mice. Direct heteromodal cortical connections have been shown between the primary auditory cortex (A1) and primary visual cortex (V1), and between A1 and secondary visual cortex (V2). Auditory afferents to V2 terminate in close proximity to neurons that project to V1, and potentially constitute an effective indirect pathway between A1 and V1. In this study, we injected a retrograde adenoviral vector that expresses enhanced green fluorescent protein under a synapsin promotor in V1 and biotinylated dextran amine as an anterograde tracer in A1 to determine: (i) whether A1 axon terminals establish synaptic contacts onto the lateral part of V2 (V2L) neurons that project to V1; and (ii) if this indirect cortical pathway is altered by a neonatal enucleation in mice. Complete dendritic arbors of layer V pyramidal neurons were reconstructed in 3D, and putative contacts between pre-synaptic auditory inputs and postsynaptic visual neurons were analysed using a laser-scanning confocal microscope. Putative synaptic contacts were classified as high-confidence and low-confidence contacts, and charted onto dendritic trees. As all reconstructed layer V pyramidal neurons received auditory inputs by these criteria, we conclude that V2L acts as an important relay between A1 and V1. Auditory inputs are preferentially located onto lower branch order dendrites in enucleated mice. Also, V2L neurons are subject to morphological reorganizations in both apical and basal dendrites after the loss of vision. The A1-V2L-V1 pathway could be involved in multisensory processing and contribute to the auditory activation of the occipital cortex in the blind rodent.

Fast and robust image segmentation by small-world neural oscillator networks

Inspired by the temporal correlation theory of brain functions, researchers have presented a number of neural oscillator networks to implement visual scene segmentation problems. Recently, it is shown that many biological neural networks are typical small-world networks. In this paper, we propose and investigate two small-world models derived from the well-known LEGION (locally excitatory and globally inhibitory oscillator network) model. To form a small-world network, we add a proper proportion of unidirectional shortcuts (random long-range connections) to the original LEGION model. With local connections and shortcuts, the neural oscillators can not only communicate with neighbors but also exchange phase information with remote partners. Model 1 introduces excitatory shortcuts to enhance the synchronization within an oscillator group representing the same object. Model 2 goes further to replace the global inhibitor with a sparse set of inhibitory shortcuts. Simulation results indicate that the proposed small-world models could achieve synchronization faster than the original LEGION model and are more likely to bind disconnected image regions belonging together. In addition, we argue that these two models are more biologically plausible.

Descending projections from extrastriate visual cortex modulate responses of cells in primary auditory cortex

Primary sensory cortical responses are modulated by the presence or expectation of related sensory information in other modalities, but the sources of multimodal information and the cellular locus of this integration are unclear. We investigated the modulation of neural responses in the murine primary auditory cortical area Au1 by extrastriate visual cortex (V2). Projections from V2 to Au1 terminated in a classical descending/modulatory pattern, with highest density in layers 1, 2, 5, and 6. In brain slices, whole-cell recordings revealed long latency responses to stimulation in V2L that could modulate responses to subsequent white matter (WM) stimuli at latencies of 5-20 ms. Calcium responses imaged in Au1 cell populations showed that preceding WM with V2L stimulation modulated WM responses, with both summation and suppression observed. Modulation of WM responses was most evident for near-threshold WM stimuli. These data indicate that corticocortical projections from V2 contribute to multimodal integration in primary auditory cortex.

A single functional model accounts for the distinct properties of suppression in cortical area V1

Cross-orientation suppression and surround suppression have been extensively studied in primary visual cortex (V1). These two forms of suppression have some distinct properties which has led to the suggestion that they are generated by different underlying mechanisms. Furthermore, it has been suggested that mechanisms other than intracortical inhibition may be central to both forms of suppression. A simple computational model (PC/BC), in which intracortical inhibition is fundamental, is shown to simulate the distinct properties of cross-orientation and surround suppression. The same model has previously been shown to account for a large range of V1 response properties including orientation-tuning, spatial and temporal frequency tuning, facilitation and inhibition by flankers and textured surrounds as well as a range of other experimental results on cross-orientation suppression and surround suppression. The current results thus provide additional support for the PC/BC model of V1 and for the proposal that the diverse range of response properties observed in V1 neurons have a single computational explanation. Furthermore, these results demonstrate that current neurophysiological evidence is insufficient to discount intracortical inhibition as a central mechanism underlying both forms of suppression.

Evaluation of inputs to rat primary auditory cortex from the suprageniculate nucleus and extrastriate visual cortex

Evidence indicates that visual stimuli influence cells in the primary auditory cortex. To evaluate potential sources of this visual input and how they enter into the circuitry of the auditory cortex, we examined axonal terminations in the primary auditory cortex from nonprimary extrastriate visual cortex (V2M, V2L) and from the multimodal thalamic suprageniculate nucleus (SG). Gross biocytin/biotinylated dextran amine (BDA) injections into the SG or extrastriate cortex labeled inputs terminating primarily in superficial and deep layers. SG projects primarily to layers I, V, and VI while V2M and V2L project primarily to layers I and VI, with V2L also targeting layers II/III. Layer I inputs differ in that SG terminals are concentrated superficially, V2L are deeper, and V2M are equally distributed throughout. Individual axonal reconstructions document that single axons can 1) innervate multiple layers; 2) run considerable distances in layer I; and 3) run preferentially in the dorsoventral direction similar to isofrequency axes. At the electron microscopic level, SG and V2M terminals 1) are the same size regardless of layer; 2) are non-gamma-aminobutyric acid (GABA)ergic; 3) are smaller than ventral medial geniculate terminals synapsing in layer IV; 4) make asymmetric synapses onto dendrites/spines that 5) are non-GABAergic and 6) are slightly larger in layer I. Thus, both areas provide a substantial feedback-like input with differences that may indicate potentially different roles.

Receptive-field properties of V1 and V2 neurons in mice and macaque monkeys

We report the results of extracellular single-unit recording experiments where we quantitatively analyzed the receptive-field (RF) properties of neurons in V1 and an adjacent extrastriate visual area (V2L) of anesthetized mice with emphasis on the RF center-surround organization. We compared the results with the RF center-surround organization of V1 and V2 neurons in macaque monkeys. If species differences in spatial scale are taken into consideration, mouse V1 and V2L neurons had remarkably fine stimulus selectivity, and the majority of response properties in V2L were not different from those in V1. The RF center-surround organization of mouse V1 neurons was qualitatively similar to that for macaque monkeys (i.e., the RF center is surrounded by extended suppressive regions). However, unlike in monkey V2, a significant proportion of cortical neurons, largely complex cells in V2L, did not exhibit quantifiable RF surround suppression. Simple cells had smaller RF centers than complex cells, and the prevalence and strength of surround suppression were greater in simple cells than in complex cells. These findings, particularly on the RF center-surround organization of visual cortical neurons, give new insights into the principles governing cortical circuits in the mouse visual cortex and should provide further impetus for the use of mice in studies on the genetic and molecular basis of RF development and synaptic plasticity.

Organization and morphology of thalamocortical neurons of mouse ventral lateral thalamus

The ventral lateral nucleus of the thalamus (VL) serves as a central integrative center for motor control, receiving inputs from the cerebellum, striatum, and cortex and projecting to the primary motor cortex. We aimed to determine the somatotopy and morphological features of the thalamocortical neurons within mouse VL. Retrograde tracing studies revealed that whisker-related VL neurons were found relatively anterior and medial to those labeled following injection of retrograde tracer into hindpaw motor areas. Simultaneous injections of fluorescent microspheres in both cortical regions did not result in double-labeled neurons in VL. Quantitative analysis of dendritic and somatic morphologies did not reveal any differences between hindpaw and whisker thalamocortical neurons within VL. The morphology of the thalamocortical neurons within mouse VL is similar to those in other mammals and suggests that mouse can be used as a model system for studying thalamocortical transformations within the motor system as well as plasticity following sensory deprivation or enrichment.

Cortical circuitry implementing graphical models

In this letter, we develop and simulate a large-scale network of spiking neurons that approximates the inference computations performed by graphical models. Unlike previous related schemes, which used sum and product operations in either the log or linear domains, the current model uses an inference scheme based on the sum and maximization operations in the log domain. Simulations show that using these operations, a large-scale circuit, which combines populations of spiking neurons as basic building blocks, is capable of finding close approximations to the full mathematical computations performed by graphical models within a few hundred milliseconds. The circuit is general in the sense that it can be wired for any graph structure, it supports multistate variables, and it uses standard leaky integrate-and-fire neuronal units. Following previous work, which proposed relations between graphical models and the large-scale cortical anatomy, we focus on the cortical microcircuitry and propose how anatomical and physiological aspects of the local circuitry may map onto elements of the graphical model implementation. We discuss in particular the roles of three major types of inhibitory neurons (small fast-spiking basket cells, large layer 2/3 basket cells, and double-bouquet neurons), subpopulations of strongly interconnected neurons with their unique connectivity patterns in different cortical layers, and the possible role of minicolumns in the realization of the population-based maximum operation.

Adaptive gain modulation in V1 explains contextual modifications during bisection learning

The neuronal processing of visual stimuli in primary visual cortex (V1) can be modified by perceptual training. Training in bisection discrimination, for instance, changes the contextual interactions in V1 elicited by parallel lines. Before training, two parallel lines inhibit their individual V1-responses. After bisection training, inhibition turns into non-symmetric excitation while performing the bisection task. Yet, the receptive field of the V1 neurons evaluated by a single line does not change during task performance. We present a model of recurrent processing in V1 where the neuronal gain can be modulated by a global attentional signal. Perceptual learning mainly consists in strengthening this attentional signal, leading to a more effective gain modulation. The model reproduces both the psychophysical results on bisection learning and the modified contextual interactions observed in V1 during task performance. It makes several predictions, for instance that imagery training should improve the performance, or that a slight stimulus wiggling can strongly affect the representation in V1 while performing the task. We conclude that strengthening a top-down induced gain increase can explain perceptual learning, and that this top-down signal can modify lateral interactions within V1, without significantly changing the classical receptive field of V1 neurons.

Synapse plasticity in motor, sensory, and limbo-prefrontal cortex areas as measured by degrading axon terminals in an environment model of gerbils (Meriones unguiculatus)

Still little is known about naturally occurring synaptogenesis in the adult neocortex and related impacts of epigenetic influences. We therefore investigated (pre)synaptic plasticity in various cortices of adult rodents, visualized by secondary lysosome accumulations (LA) in remodeling axon terminals. Twenty-two male gerbils from either enriched (ER) or impoverished rearing (IR) were used for quantification of silver-stained LA. ER-animals showed rather low LA densities in most primary fields, whereas barrel and secondary/associative cortices exhibited higher densities and layer-specific differences. In IR-animals, these differences were evened out or even inverted. Basic plastic capacities might be linked with remodeling of local intrinsic circuits in the context of cortical map adaptation in both IR- and ER-animals. Frequently described disturbances due to IR in multiple corticocortical and extracortical afferent systems, including the mesocortical dopamine projection, might have led to maladaptations in the plastic capacities of prefronto-limbic areas, as indicated by different LA densities in IR- compared with ER-animals.

fMRI reveals that non-local processing in ventral retinotopic cortex underlies perceptual grouping by temporal synchrony

When spatially separated objects appear and disappear in a synchronous manner, they perceptually group into a single global object that itself appears and disappears. We employed functional magnetic resonance imaging (fMRI) to identify brain regions involved in this type of perceptual grouping. Subjects viewed four chromatically-defined disks (one per visual quadrant) that flashed on and off. We contrasted %BOLD signal changes between blocks of synchronously flashing disks (Grouping) with blocks of asynchronously flashing disks (no-Grouping).

RESULTS

A region of interest analysis revealed %BOLD signal change in the Grouping condition was significantly greater than in the no-Grouping condition within retinotopic areas V2, V3, and V4v. Within a single quadrant of the visual field, the spatio-temporal information present in the image was identical across the two stimulus conditions. As such, the two conditions could not be distinguished from each other on the basis of the rate or pattern of flashing within a single visual quadrant. The observed results must therefore arise through nonlocal interactions between or within these retinotopic areas, or arise from outside these retinotopic areas. Furthermore, when V2 and V3 were split into ventral and dorsal sub-ROIs, ventral retinotopic areas V2v and V3v preferentially differentiated between the two conditions whereas the corresponding dorsal areas V2d and V3d did not. In contrast, within hMT+, %BOLD signal was significantly greater in the no-Grouping condition.

CONCLUSION

Nonlocal processing within, between, or to ventral retinotopic cortex at least as early as V2v, and including V3v, and V4v, underlies perceptual grouping via temporal synchrony.

Dendritic excitability and synaptic plasticity

Most synaptic inputs are made onto the dendritic tree. Recent work has shown that dendrites play an active role in transforming synaptic input into neuronal output and in defining the relationships between active synapses. In this review, we discuss how these dendritic properties influence the rules governing the induction of synaptic plasticity. We argue that the location of synapses in the dendritic tree, and the type of dendritic excitability associated with each synapse, play decisive roles in determining the plastic properties of that synapse. Furthermore, since the electrical properties of the dendritic tree are not static, but can be altered by neuromodulators and by synaptic activity itself, we discuss how learning rules may be dynamically shaped by tuning dendritic function. We conclude by describing how this reciprocal relationship between plasticity of dendritic excitability and synaptic plasticity has changed our view of information processing and memory storage in neuronal networks.

Modeling the top-down influences on the lateral interactions in the visual cortex

Attention modulates the amount of excitatory and inhibitory lateral interactions in the visual cortex. A recurrent neural network is proposed to account for modulatory influence of top-down signals. In the model, two types of inhibitions are distinguished: dendritic and lateral inhibitions. Dendritic inhibition regulates the amount of impact that surrounding cells may exert on a target cell via the dendrites of excitatory neurons and the dendrites of subpopulation of inhibitory neurons mediating lateral inhibition. Attention increases the amount of dendritic inhibition and prevents contextual interactions, while it has no effect on the target cell when there is no surround input. Computer simulations showed that the proposed model is able to exhibit properties of attentional gating. In the condition of focused attention, neural activity in the presence of surrounding stimuli is restored to the level as when the target stimulus is presented alone. Moreover, the model is able to show contrast gain and response gain on the contrast sensitivity function depending on the strength of the dendritic inhibition.

Perceptual learning via modification of cortical top-down signals

The primary visual cortex (V1) is pre-wired to facilitate the extraction of behaviorally important visual features. Collinear edge detectors in V1, for instance, mutually enhance each other to improve the perception of lines against a noisy background. The same pre-wiring that facilitates line extraction, however, is detrimental when subjects have to discriminate the brightness of different line segments. How is it possible to improve in one task by unsupervised practicing, without getting worse in the other task? The classical view of perceptual learning is that practicing modulates the feedforward input stream through synaptic modifications onto or within V1. However, any rewiring of V1 would deteriorate other perceptual abilities different from the trained one. We propose a general neuronal model showing that perceptual learning can modulate top-down input to V1 in a task-specific way while feedforward and lateral pathways remain intact. Consistent with biological data, the model explains how context-dependent brightness discrimination is improved by a top-down recruitment of recurrent inhibition and a top-down induced increase of the neuronal gain within V1. Both the top-down modulation of inhibition and of neuronal gain are suggested to be universal features of cortical microcircuits which enable perceptual learning.

Functional role of the secondary visual cortex in multisensory facilitation in rats

Recent studies reveal that multisensory convergence can occur in early sensory cortical areas. However, the behavioral importance of the multisensory integration in such early cortical areas is unknown. Here, we used c-Fos immunohistochemistry to explore neuronal populations specifically activated during the facilitation of reaction time induced by the temporally congruent audiovisual stimuli in rats. Our newly developed analytical method for c-Fos mapping revealed a pronounced up-regulation of c-Fos expression particularly in layer 4 of the lateral secondary visual area (V2L). A local injection of a GABA A receptor agonist, muscimol, into V2L completely suppressed the audiovisual facilitation of reaction time without affecting responses to unimodal stimuli. Such a selective suppression was not found following the injection of muscimol into the primary auditory and visual areas. To examine whether or not the rats might have shown the facilitated responses because of increment of stimulus intensity caused by the two modal stimuli, the behavioral facilitation induced by the high-intensity unimodal stimuli was tested by the injection of muscimol into V2L, which turned out not to affect the facilitation. These results suggest that V2L, an early visual area, is critically involved in the multisensory facilitation of reaction time induced by the combination of auditory and visual stimuli.

Cortical region interactions and the functional role of apical dendrites

The basal and distal apical dendrites of pyramidal cells occupy distinct cortical layers and are targeted by axons originating in different cortical regions. Hence, apical and basal dendrites receive information from distinct sources. Physiological evidence suggests that this anatomically observed segregation of input sources may have functional significance. This possibility has been explored in various connectionist models that employ neurons with functionally distinct apical and basal compartments. A neuron in which separate sets of inputs can be integrated independently has the potential to operate in a variety of ways not possible for the conventional neuron model, in which all inputs are treated equally. This article thus considers how functionally distinct apical and basal dendrites can contribute to the information-processing capacities of single neurons and, in particular, how information from different cortical regions could have disparate effects on neural activity and learning.

Experience-dependent formation of activity propagation patterns at the somatosensory S1 and S2 boundary in rat cortical slices

Somatosensory information is serially processed by the primary (S1) and secondary (S2) cortices, which can be identified in fresh cortical slices. We visualized activity propagation between S1 and S2 in rat cortical slices using flavoprotein fluorescence imaging. When S1 was stimulated, fluorescence responses extended into S2, while responses hardly propagated to S1 following S2 stimulation. The dominant activity propagation pattern from S1 to S2 was not affected by antagonists of glutamate or GABA(A) receptors. Ca(2+) imaging and electrophysiological recordings confirmed the anisotropic activity propagation pattern. This pattern could be formed as a result of serial information processing in S1 and S2. To test this hypothesis, activity propagation was investigated in cortical slices prepared 2 weeks or 3 days after trimming contralateral whiskers that provide massive inputs to S1. Supragranular activities in the barrel cortex were clearly suppressed. Furthermore, activities elicited in the rostral small vibrissae/mouth area of S1 near the border between S1 and S2 spread into the adjacent barrel cortex rather than into S2. Behavioral effects of whisker trimming were evaluated using a test, in which rats chose one of two bridges that had a wall on the right or left side only. Immediately after hemilateral whisker trimming, rats preferred to use the bridge with a wall close to the intact side. However, this preference disappeared 3 days after trimming. Modified activities observed in cortical slices after whisker trimming might be mechanisms for this behavioral compensation. These findings suggest experience-dependent formation of activity propagation patterns in the somatosensory cortex.

The sensorimotor slice

The reciprocal connections between primary motor cortex (M1) and primary somatosensory cortex (S1) are hypothesized to play a role in an animal's ability to update its motor plan in response to changes in the sensory periphery. These interactions provide the sensory cortex with anticipatory knowledge of motor plans. In the mouse neocortex there are representations of the body surface within both M1 and S1. Utilizing physiologically targeted micro injections of biotinylated dextran amine into either the whisker representation of M1 (wM1) or S1 (wS1) we characterized the axonal pathways connecting these two areas. We then used this data to determine a plane of section that contained both whisker M1 and whisker S1 and maintained the axonal pathway between these two areas. In vitro physiological studies demonstrated that excitatory synaptic connections are maintained in this novel plane of section. The sensorimotor slice is an ideal preparation to study inter-areal cortical connectivity.

Functional local connections with differential activity-dependence and critical periods surrounding the primary auditory cortex in rat cerebral slices

Sensory information is processed in neural networks connecting the primary sensory cortices with surrounding higher areas. Here, we investigated the properties of local connections between the primary auditory cortex (area 41) and surrounding areas (areas 20, 36, 18a and 39) in rat cerebral slices. Neural activities elicited by repetitive electrical stimulation were visualized using the activity-dependent changes in endogenous fluorescence derived from mitochondrial flavoproteins, which mostly reflect activities produced by polysynaptic glutamatergic transmission. Polysynaptic feedforward propagation was dominant compared with the corresponding polysynaptic feedback propagation between the primary (area 41) and secondary (areas 20 and 36) auditory cortices, while such a tendency was less clear in other pathways. Long inter-areal (>1 mm) propagation with the same dominancy was observed after layer V stimulation between areas 41 and 20, and was not affected by cutting the underlying white matter. Activity-dependent changes in neural activities induced by low-frequency stimulation in the presence of 1 microM bicuculline were investigated using Ca2+ imaging. Significant potentiation of the polysynaptic Ca2+ activities was only observed in polysynaptic feedforward pathways from the primary to secondary auditory cortices. Experience-dependence of the connections between areas 41 and 20 was investigated using flavoprotein fluorescence imaging. The activities from areas 41 to 20 were reduced by cochlear lesions produced at P12 but not at P28, while the activities from areas 20 to 41 were reduced by the lesions at P28, suggesting the critical period for the polysynaptic feedforward connection was before P28, while for the polysynaptic feedback connection was after P28.

A model of surround suppression through cortical feedback

Surround suppression occurs when a visual stimulus outside a neuron's classical receptive field causes a reduction in firing rate. It has become clear that several mechanisms are working together to induce center-surround effects such as surround suppression. While several models exist that rely on lateral connections within V1 to explain surround suppression, few have been proposed that show how cortical feedback might play a role. In this work, we propose a theory in which reductions in excitatory feedback contribute to a neuron's suppressed firing rate. We also provide a computational model that incorporates this idea.

Pattern reversal visual evoked responses of V1/V2 and V5/MT as revealed by MEG combined with probabilistic cytoarchitectonic maps

Pattern reversal stimulation provides an established tool for assessing the integrity of the visual pathway and for studying early visual processing. Numerous magnetoencephalographic (MEG) and electroencephalographic (EEG) studies have revealed a three-phasic waveform of the averaged pattern reversal visual evoked potential/magnetic field, with components N75(m), P100(m), and N145(m). However, the anatomical assignment of these components to distinct cortical generators is still a matter of debate, which has inter alia connected with considerable interindividual variations of the human striate and extrastriate cortex. The anatomical variability can be compensated for by means of probabilistic cytoarchitectonic maps, which are three-dimensional maps obtained by an observer-independent statistical mapping in a sample of ten postmortem brains. Transformed onto a subject's brain under consideration, these maps provide the probability with which a given voxel of the subject's brain belongs to a particular cytoarchitectonic area. We optimize the spatial selectivity of the probability maps for V1 and V2 with a probability threshold which optimizes the self- vs. cross-overlap in the population of postmortem brains used for deriving the probabilistic cytoarchitectonic maps. For the first time, we use probabilistic cytoarchitectonic maps of visual cortical areas in order to anatomically identify active cortical generators underlying pattern reversal visual evoked magnetic fields as revealed by MEG. The generators are determined with magnetic field tomography (MFT), which reconstructs the current source density in each voxel. In all seven subjects, our approach reveals generators in V1/V2 (with a greater overlap with V1) and in V5 unilaterally (right V5 in three subjects, left V5 in four subjects) and consistent time courses of their stimulus-locked activations, with three peak activations in V1/V2 (contributing to C1m/N75m, P100m, and N145m) and two peak activations in V5 (contributing to P100m and N145m). The reverberating V1/V2 and V5 activations demonstrate the effect of recurrent activation mechanisms including V1 and extrastriate areas and/or corticofugal feedback loops. Our results demonstrate that the combined investigation of MEG signals with MFT and probabilistic cytoarchitectonic maps significantly improves the anatomical identification of active brain areas.

Contribution of feedforward, lateral and feedback connections to the classical receptive field center and extra-classical receptive field surround of primate V1 neurons

A central question in visual neuroscience is what circuits generate the responses of neurons in the primary visual cortex (V1). V1 neurons respond best to oriented stimuli of optimal size within their receptive field (RF) center. This size tuning is contrast dependent, i.e. a neuron's optimal stimulus size measured at high contrast (the high-contrast summation RF, or hsRF) is smaller than when measured using low-contrast stimuli (the low-contrast summation RF, or lsRF). Responses to stimuli in the RF center are usually suppressed by iso-oriented stimuli in the extra-classical RF surround. Iso-orientation surround suppression is fast and long range, extending well beyond the size of V1 cells' lsRF. Geniculocortical feedforward (FF), V1 lateral and extrastriate feedback (FB) connections to V1 could all contribute to generating the RF center and surround of V1 neurons. Studies on the spatio-temporal properties and functional organization of these connections can help disclose their specific contributions to the responses of V1 cells. These studies, reviewed in this chapter, have shown that FF afferents to V1 integrate signals within the hsRF of V1 cells; V1 lateral connections are commensurate with the size of the lsRF and may, thus, underlie contrast-dependent changes in spatial summation, and modulatory effects arising from the surround region closer to the RF center (the "near" surround). The spatial and temporal properties of lateral connections cannot account for the dimensions and onset latency of modulation arising from more distant regions of the surround (the "far" surround). Inter-areal FB connections to V1, instead, are commensurate with the full spatial range of center and surround responses, and show fast conduction velocity consistent with the short onset latency of modulation arising from the "far" surround. We review data showing that a subset of FB connections terminate in a patchy fashion in V1, and show modular and orientation specificity, consistent with their proposed role in orientation-specific center-surround interactions. We propose specific mechanisms by which each connection type contributes to the RF center and surround of V1 neurons, and implement these hypotheses into a recurrent network model. We show physiological data in support of the model's predictions, revealing that modulation from the "far" surround is not always suppressive, but can be facilitatory under specific stimulus conditions.

Volatile anesthetics disrupt frontal-posterior recurrent information transfer at gamma frequencies in rat

We seek to understand neural correlates of anesthetic-induced unconsciousness. We hypothesize that cortical integration of sensory information may underlie conscious perception and may be disrupted by anesthetics. A critical role in frontal-posterior interactions has been proposed, and gamma (20-60 Hz) oscillations have also been assigned an essential role in consciousness. Here we investigated whether general anesthetics may interfere with the exchange of information encoded in gamma oscillations between frontal and posterior cortices. Bipolar electrodes for recording of event-related potentials (ERP) were chronically implanted in the primary visual cortex, parietal association and frontal association cortices of six rats. Sixty light flashes were presented every 5s, and ERPs were recorded at increasing concentrations of halothane or isoflurane (0-2%). Information exchange was estimated by transfer entropy, a novel measure of directional information transfer. Transfer entropy was calculated from 1-s wavelet-transformed ERPs. We found that (1) feedforward transfer entropy (FF-TE) and feedback transfer entropy (FB-TE) were balanced in conscious-sedated state; (2) anesthetics at concentrations producing unconsciousness augmented both FF-TE and FB-TE at 30 Hz but reduced them at 50 Hz; (3) reduction at 50 Hz was more pronounced for FB-TE, especially between frontal and posterior regions; (4) at high concentrations, both FF-TE and FB-TE at all frequencies were at or below conscious-sedated baseline. Our findings suggest that inhalational anesthetics preferentially impair frontal-posterior FB information transfer at high gamma frequencies consistent with the postulated role of frontal-posterior interactions in consciousness.

Experience-dependent development of feedforward and feedback circuits between lower and higher areas of mouse visual cortex

Using whole cell recordings, we studied excitatory and inhibitory postsynaptic currents (EPSCs, IPSCs) in feedforward (FF) and feedback (FB) circuits between areas V1 and LM (lateromedial) in developing mouse visual cortex. We found that in mice reared with normal visual experience, FF and FB synapses onto layer 2/3 pyramidal neurons develop equal but submaximal strengths whose EPSCs are increased by monocular lid suture. In contrast, the development and experience-dependence of FF- and FB-IPSCs is pathway-specific. The difference develops during the critical period by strengthening FF-IPSCs, while keeping FB-IPSC amplitudes constant. Monocular lid suture increases FB-IPSCs but does not affect FF-IPSCs.

Fos-tau-LacZ mice expose light-activated pathways in the visual system

We have employed fos-tau-LacZ (FTL) transgenic mice to examine functional activation in the visual areas of the nervous system. The FTL mice express the marker gene lacZ in neurons and their processes following many different stimuli, and allow the imaging of activation from the level of the entire brain surface through individual neurons and their projections. Analysis of FTL expression in the retinas of mice following diurnal exposure to light shows that bipolar cells, specific classes of amacrine cells, ganglion cells, and a dense network of processes in the inner plexiform layer are functionally activated. In animals deprived of light, there is almost no activity in the retina. In the lateral geniculate nucleus (LGN), light exposure appears responsible for FTL expression in dorsal nuclei, but not for expression in the ventral nuclei or the intergeniculate leaflet. In the superficial layers of the superior colliculus, FTL expression is highly dependent on light exposure. Similarly, light exposure is required for FTL expression in primary visual cortex (area 17), but some expression remains in area 18 of dark-adapted animals. Finally, using mice with one or both eyes missing, we have determined which parts of the visual system are dependent on the presence of a functional connectivity from the eye. These data demonstrate the usefulness of the FTL mice to map functional activation within the entire visual system. Furthermore, we can capture visual activation in a conscious animal. Our findings give an insight into the architecture of activity within the retina and throughout the visual system.

Comparing dynamic causal models

This article describes the use of Bayes factors for comparing dynamic causal models (DCMs). DCMs are used to make inferences about effective connectivity from functional magnetic resonance imaging (fMRI) data. These inferences, however, are contingent upon assumptions about model structure, that is, the connectivity pattern between the regions included in the model. Given the current lack of detailed knowledge on anatomical connectivity in the human brain, there are often considerable degrees of freedom when defining the connectional structure of DCMs. In addition, many plausible scientific hypotheses may exist about which connections are changed by experimental manipulation, and a formal procedure for directly comparing these competing hypotheses is highly desirable. In this article, we show how Bayes factors can be used to guide choices about model structure, both concerning the intrinsic connectivity pattern and the contextual modulation of individual connections. The combined use of Bayes factors and DCM thus allows one to evaluate competing scientific theories about the architecture of large-scale neural networks and the neuronal interactions that mediate perception and cognition.