Visual cortex

Arno Onken examines transformer models for predicting responses in the retina and visual cortex. These models learn complex neural-response patterns from large datasets and can transfer learned representations between settings, but fitting and interpreting them differs from linear–nonlinear and convolutional approaches. The talk discusses the opportunities and difficulties this creates for understanding sensory processing. It includes ViV1T, a transformer trained on natural movies that revealed previously uncharacterised response properties in mouse primary visual cortex. The work illustrates

Current machine learning systems consume vastly more energy than biological brains. Neuromorphic systems aim to overcome this difference by mimicking the brain’s information coding via discrete voltage spikes. However, it remains unclear how both artificial and natural networks of spiking neurons can learn energy-efficient information processing strategies. Here we propose Predictive Coding Light (PCL), a recurrent hierarchical spiking neural network for unsupervised representation learning. In contrast to previous predictive coding approaches, PCL does not transmit prediction errors to higher

Functional connectomics reveals general wiring rule in mouse visual cortex

Visual restoration after decades of blindness is now becoming possible by means of retinal and cortical prostheses, as well as emerging stem cell and gene therapeutic approaches. After restoring visual perception, however, a key question remains. Are there optimal means and methods for retraining the visual cortex to process visual inputs, and for learning or relearning to “see”? Up to this point, it has been largely assumed that if the sensory loss is visual, then the rehabilitation focus should also be primarily visual. However, the other senses play a key role in visual rehabilitation due t

Visual perception emerges from intricate interactions among neuronal populations across the brain's sensory processing hierarchy. Neuronal correlations in the visual cortex can be modulated by both external visual stimuli and internal states. Recent studies emphasize the role of communication subspaces as a population-level routing mechanism that serve as “channels” for transmitting information, facilitating coordinated activity across brain areas (e.g., V1-V2) or between cortical layers (e.g., input-superficial). It is however not known if this co-ordinated activity has directed or shared ori

…responses to multiple stimuli in visual cortex. Neurons in the visual cortex exhibit highly heterogeneous degrees of normalization. Past work has proposed several hypotheses of the functions of normalization in both biological and artificial neural network. For example, normalization can maximize sensitivity in retina neurons, reduce redundancy in sensory cortex, and accelerate and stabilize the learning process in deep neural networks. However, the mechanism underlying the neuronal heterogeneity of normalization and

Recurrent neural networks (RNNs) have increasingly been employed to model cortical function, but conventional architectures lack biological realism. Notably, they often ignore two key biological principles: i) Dale’s Law, which constrains neurons to either be strictly excitatory or inhibitory, and ii) Sparse, structured connectivity motifs observed in the brain. Incorporating these constraints however poses challenges, as they often affect model performance negatively. Our work presents a novel approach that integrates Dale’s backpropagation, a sign-constrained training method, with topologica

Healthy cerebral cortex function requires complex neuronal population activity with a diverse repertoire of timescales, from fleeting response to sensory input ($\sim$10-100 ms), to execution of complex body movements ($\sim 100-1000 ms$), to even longer timescales of working memory ($\sim 1-10 s$). How does cortex generate such a broad range of timescales? How is the timescale repertoire tuned in response to shifting behavioral demands? One potential explanation is that cortex operates close to criticality, i.e., close to a boundary between two different dynamical regimes. At criticality, flu

…as primates and carnivores, the mature visual cortex is characterized by iterated clusters of similarly responding neurons, or modules, and provides an excellent model system for exploring the mechanisms underlying the development of functional network organization. The sequence of early events that leads to the initial emergence of modular network structure remains unknown. Interestingly during this period of ear

…a general computational motif in the cortex. Arguments support that in the visual cortex, DN acts as a canonical computation in generative models, which delivers contextual effects and contributes to shaping response variability. Deep generative models (DGMs) have recently been adopted by neuroscience from machine vision to embrace nonlinear computations in the visual cortex. Yet, it remains unclear whether DGMs effectively integrate DN as a core computational element. We inv

…Reconstruction of visual input from human fMRI data has garnered significant attention in recent years. Comparatively less focus has been directed towards vision reconstruction from single-cell recordings, despite its potential to provide a more direct measure of the information represented by the brain. Here, we achieve high-quality reconstructions of videos presented to mice, from the activity of neurons in their visual cortex. With our method of video

Visual attention enhances the neural representation of salient stimuli within the visual cortex. Although it is generally thought that this enhancement is driven by glutamatergic feedback from frontal cortical areas, cortically released neuromodulators are also believed to play a major uncharacterized role. Here we report the unexpected observation that dorsal raphe (DR) derived serotonin (5HT) controls visual attention. We adopted a behavioral model that captured how mice allocated attention to cued and uncued visual features. Simultaneous photometry recordings showed that DR activity decreas

…In the mammalian neocortex, inhibitory neurons are diverse. They are characterized by a variety of cellular attributes that enable their specialized roles in regulating information processing. It is increasingly clear that the major subtype specification of inhibitory neurons is given by their molecular identity, defined by techniques such as gene expression profiling. However, the molecular class alone provides limited insight into the anatomical, physiological, and connectivity properties of

Introduction: Spontaneous activity in visual cortex is high-dimensional and state-dependent, yet its organizing principles are unclear (Stringer et al. Science 2019; Berkes et al. Science 2011). We combine large-scale imaging, modelling, and theory to ask: 1. Does spontaneous activity share the structure of evoked activity? 2. Is spontaneous activity organized spatially? Methods: We constructed a modified Light Beads Microscope (Demas et al. Nature Methods 2021) to image Ca2+ transients in excitatory neurons from large volumes. We developed an open-source, GPU-accelerated volumetric cell extra

Human perception is significantly influenced by sensory context. A classic demonstration is the tilt illusion, in which the perceived orientation of a center stimulus is altered by the orientation of a surround (Gibson \& Radner 1937). Previous research on the tilt illusion has primarily focused on how surround context alters the response characteristics of individual neurons (e.g., changes in gain and tuning curves), but connecting these observations at the level of single neurons to perceptual behavior remains challenging. More broadly, we still lack a functional and teleological account of

…the functional networks of the visual cortex at both the single-cell and population levels. Ou

…of two-photon calcium imaging from the visual cortex of mice (Cleppien et al., 2024+), we identified short temporal stripes of interest from the un

The brain computes internal representations by applying highly recurrent dynamics to feed-forward input. Such dynamics may be viewed as analogous to the inference step in latent variables models, where one usually follows the gradient of the latent posterior distribution until a stable state is reached. At the stable state, when this gradient has approximately zero norm, a parameter optimization step can be applied to slightly increase the likelihood of the current sample under the model. Here we suggest this procedure, which closely matches the expectation-maximization (EM) algorithm, can be

Detecting a specific object in a visual scene is a task that the human visual system performs every day. To perform this target-specific object detection, it is necessary to filter out all unwanted objects during the processing, so that only the specific object can be detected. For this purpose, attention-related mechanisms along the visual pathway have been proposed to allow focusing on the desired object. Beuth and Hamker (2015) [1], using a biologically inspired recurrent model simulating lower and higher layers of the visual cortex, the frontal eye field, and the prefrontal cortex, showed

The brain continuously receives vast amounts of information from the rest of the body and the environment, only a fraction of which can be consciously processed and stored in memory. It is believed that hippocampal sharp-wave ripples tag memories that are relevant and should be remembered (Yang et al 2024). However, this selection of relevant information must occur already during sensory processing to avoid overloading the system with irrelevant information. The hypothesis of this project is that short bursts of high gamma activity, referred to as cortical ripples to distinguish them from hipp

…We tested this theory in the visual cortex, which has a well-defined critical period for experience-dependent neuronal plasticity. During adolescence, visual experience modulated oligodendrocyte maturation in visual cortex. To determine whether oligodendrocyte maturation in turn regulates neuronal plasticity, we genetically blocked oligodendrocyte differentiation and

…mouse brain non-invasively and in the visual cortex of a non-human primate after craniotomy.An IcoPrime 4D-RCA probe (80+80 elements, 15 MHz, pitch 0.11 mm, Iconeus) was driven by an Iconeus One scanner. For the mouse experiment, the probe was mounted on a

…In the visual cortex, apical dendrites may receive contextual signals via top-down inputs and local inhibition. It is not known, however, what causal effects they play indriving or suppressing somatic activity, and how they shape a neuron’s visual tuning.We recorded activity of pyramidal neurons sparsely expressing GCaMP7s in layer 5 of visualcortex in awake mice before and after pruning their apical dendrites with two-photondendrotomy. Together with the neuron’s receptive field and orientation/d

Monocular deprivation-induced ocular dominance plasticity (MD-ODP) in the visual cortex is an established in vivo paradigm, in which inactivity-induced synaptic plasticity contributes to the functional reconfiguration of cortical networks. Bassoon (Bsn) is a presynaptic protein involved in the spatial and functional organisation of synaptic vesicle (SV) recycling. Here, we report a novel role for Bsn in the inactivity-induced functional reconfiguration of adult neocortical networks in vivo and in vitro. We subjected Bsn knock-out mice to MD and imaged visual stimulus-evoked intrinsic signals i