Multiplexed and flexible neural coding in sensory, parietal, and frontal cortices during goal-directed virtual navigation

We do not understand how neural nodes operate within the recurrent action-perception loops that characterize naturalistic self-environment interactions, nor how brain networks reconfigure during changing computational demands. Here, we record local field potentials (LFPs) and spiking activity simultaneously from the dorsomedial superior temporal area (MSTd), parietal area 7a, and dorsolateral prefrontal cortex (dlPFC) as monkeys navigate in virtual reality to “catch fireflies”. This task requires animals to actively sample from a closed-loop visual environment while concurrently computing latent variables: the evolving distance and angle to a memorized firefly. We observed mixed selectivity in all areas, with even a traditionally sensory area (MSTd) tracking latent variables. Strikingly, global encoding profiles and unit-to-unit coupling suggested a functional subnetwork between MSTd and dlPFC, and not between these areas and 7a, as anatomy would suggest. When sensory evidence was rendered scarce, lateral connectivity through neuron-to-neuron coupling within MSTd strengthened but its pattern remained fixed, while neuronal coupling adaptively remapped within 7a and dlPFC. The larger the remapping in 7a/dlPFC and the greater the stability within MSTd, the less was behavior impacted by loss of sensory evidence. These results highlight the distributed nature of neural coding during closed-loop action-perception naturalistic behaviors and suggest internal models may be housed in the pattern of fine-grain lateral connectivity within parietal and frontal cortices.

Emergence of Lie Symmetries in Functional Architectures Learned by CNNs

In this paper we study the spontaneous development of symmetries in the early layers of a Convolutional Neural Network (CNN) during learning on natural images. Our architecture is built in such a way to mimic some properties of the early stages of biological visual systems. In particular, it contains a pre-filtering step ℓ0 defined in analogy with the Lateral Geniculate Nucleus (LGN). Moreover, the first convolutional layer is equipped with lateral connections defined as a propagation driven by a learned connectivity kernel, in analogy with the horizontal connectivity of the primary visual cortex (V1). We first show that the ℓ0 filter evolves during the training to reach a radially symmetric pattern well approximated by a Laplacian of Gaussian (LoG), which is a well-known model of the receptive profiles of LGN cells. In line with previous works on CNNs, the learned convolutional filters in the first layer can be approximated by Gabor functions, in agreement with well-established models for the receptive profiles of V1 simple cells. Here, we focus on the geometric properties of the learned lateral connectivity kernel of this layer, showing the emergence of orientation selectivity w.r.t. the tuning of the learned filters. We also examine the short-range connectivity and association fields induced by this connectivity kernel, and show qualitative and quantitative comparisons with known group-based models of V1 horizontal connections. These geometric properties arise spontaneously during the training of the CNN architecture, analogously to the emergence of symmetries in visual systems thanks to brain plasticity driven by external stimuli.

Flexible neural coding in sensory, parietal, and frontal cortices during goal-directed virtual navigation

We do not understand how neural nodes operate within the recurrent action-perception loops that characterize naturalistic self-environment interactions, nor how brain networks reconfigure during changing computational demands. Here, we record local field potentials (LFPs) and spiking activity simultaneously from the dorsomedial superior temporal area (MSTd), parietal area 7a, and dorsolateral prefrontal cortex (dlPFC) as monkeys navigate in virtual reality to catch fireflies. This task requires animals to actively sample from a closed-loop visual environment while concurrently computing latent variables: the evolving distance and angle to a memorized firefly. We observed mixed selectivity in all areas, with even a traditionally sensory area (MSTd) tracking latent variables. Strikingly, global encoding profiles and unit-to-unit coupling suggested a functional subnetwork between MSTd and dlPFC, and not between these are 7a, as anatomy would suggest. When sensory evidence was rendered scarce, lateral connectivity through neuron-to-neuron coupling within MSTd strengthened but its pattern remains fixed, while neuronal coupling adaptively remapped within 7a and dlPFC. The larger the remapping in 7a/dlPFC and the greater the stability within MSTd, the less was behavior impacted by loss of sensory evidence. These results highlight the distributed nature of neural coding during closed-loop action-perception naturalistic behaviors and suggest internal models may be housed in the pattern of fine-grain lateral connectivity within parietal and frontal cortices.

Grid Cells Lose Coherence in Realistic Environments

Spatial cognition in naturalistic environments, for freely moving animals, may pose quite different constraints from that studied in artificial laboratory settings. Hippocampal place cells indeed look quite different, but almost nothing is known about entorhinal cortex grid cells, in the wild. Simulating our self-organizing adaptation model of grid cell pattern formation, we consider a virtual rat randomly exploring a virtual burrow, with feedforward connectivity from place to grid units and recurrent connectivity between grid units. The virtual burrow was based on those observed by John B. Calhoun, including several chambers and tunnels. Our results indicate that lateral connectivity between grid units may enhance their “gridness” within a limited strength range, but the overall effect of the irregular geometry is to disable long-range and obstruct short-range order. What appears as a smooth continuous attractor in a flat box, kept rigid by recurrent connections, turns into an incoherent motley of unit clusters, flexible or outright unstable.

Cortical Synchrony as a Mechanism of Collinear Facilitation and Suppression in Early Visual Cortex

Stimulus-induced oscillations and synchrony among neuronal populations in visual cortex are well-established phenomena. Their functional role in cognition are, however, not well-understood. Recent studies have suggested that neural synchrony may underlie perceptual grouping as stimulus-frequency relationships and stimulus-dependent lateral connectivity profiles can determine the success or failure of synchronization among neuronal groups encoding different stimulus elements. We suggest that the same mechanism accounts for collinear facilitation and suppression effects where the detectability of a target Gabor stimulus is improved or diminished by the presence of collinear flanking Gabor stimuli. We propose a model of oscillators which represent three neuronal populations in visual cortex with distinct receptive fields reflecting the target and two flankers, respectively, and whose connectivity is determined by the collinearity of the presented Gabor stimuli. Our model simulations confirm that neuronal synchrony can indeed explain known collinear facilitation and suppression effects for attended and unattended stimuli.

Impact assessment of structural barriers and flow regulation on the Ganga River morphology and ecology

<p>The Ganga-Brahmaputra river system in the Himalayan Foreland supports diverse aquatic fauna. Decades of flow regulation through dams and barrages have affected their habitat suitability. To evaluate the impacts of large barrages on the morphology and habitat ecology we studied two different reaches (middle and lower) of the Ganga River. These reaches are the habitat of the endangered Ganga River dolphin (<em>Platanista gangetica</em>). In a reach in the middle Ganga between Bijnor and Narora barrage, a reported rise in dolphin population has been documented. In contrast, near the Farakka barrage in the lower reach of the Ganga River, a significant decline in the dolphin population has been observed.</p><p>We use Corona and time-series Landsat satellite images along with flow discharge data to assess the morphological and ecological impact of the barrages. In middle Ganga, the dolphin habitat is isolated between the Bijnor and Narora barrage where the minimum flow is available throughout the year for the dolphins to thrive.  On the other hand, in the lower Ganga, contrasting impacts are observed in the proximity (upstream/downstream) of the Farakka barrage. In the downstream, reduction in water (by one-third in the pre-monsoon discharge) and sediment discharge has decoupled the channel belt to its floodplain resulting in a loss of lateral connectivity. The presence of minimum flow between the Bijnor and Narora barrage has aided the dolphin population rise while the loss of lateral connectivity and excess siltation at the Farakka barrage has made the river reach unsuitable for habitation.   </p>

Vegetation and Geomorphic Connectivity in Mountain Fluvial Systems

Rivers are complex biophysical systems, constantly adjusting to a suite of changing governing conditions, including vegetation cover within their basins. This review seeks to: (i) highlight the crucial role that vegetation’s influence on the efficiency of clastic material fluxes (geomorphic connectivity) plays in defining mountain fluvial landscape’s behavior; and (ii) identify key challenges which hinder progress in the understanding of this subject. To this end, a selective literature review is carried out to illustrate the pervasiveness of the plants’ effects on geomorphic fluxes within channel networks (longitudinal connectivity), as well as between channels and the broader landscape (lateral connectivity). Taken together, the reviewed evidence lends support to the thesis that vegetation-connectivity linkages play a central role in regulating geomorphic behavior of mountain fluvial systems. The manuscript is concluded by a brief discussion of the need for the integration of mechanistic research into the local feedbacks between plants and sediment fluxes with basin-scale research that considers emergent phenomena.

On the potential role of lateral connectivity in retinal anticipation

We analyse the potential effects of lateral connectivity (amacrine cells and gap junctions) on motion anticipation in the retina. Our main result is that lateral connectivity can—under conditions analysed in the paper—trigger a wave of activity enhancing the anticipation mechanism provided by local gain control (Berry et al. in Nature 398(6725):334–338, 1999; Chen et al. in J. Neurosci. 33(1):120–132, 2013). We illustrate these predictions by two examples studied in the experimental literature: differential motion sensitive cells (Baccus and Meister in Neuron 36(5):909–919, 2002) and direction sensitive cells where direction sensitivity is inherited from asymmetry in gap junctions connectivity (Trenholm et al. in Nat. Neurosci. 16:154–156, 2013). We finally present reconstructions of retinal responses to 2D visual inputs to assess the ability of our model to anticipate motion in the case of three different 2D stimuli.