Information transfer

Slower (e.g., beta) and faster (e.g., gamma) oscillatory bursts have been linked to multiplexed communication between neural populations in different directions [1], respectively relaying, in a predictive coding interpretation, top-down expectations and bottom-up prediction error signals [2], which target and originate from distinct cortical layers with different dominant frequencies [3]. However, this oscillatory-multiplexed routing theory presents several challenges. Multiplexed routing might occur indeed without need for distinct frequencies of operation [4]. Furthermore, phasic enhancement

…evidence, but fail to explain the transfer of graded evidence between populations. This transfer supports the continuous representation of a decision when an anim

…These enable fast information transfer and facilitate hierarchical compositionality but have not yet been explored in artificial systems [3]. In this work, we present the Shallow Hierarchical Artificial Neural Network (SHANN), a novel brain-inspired architecture with shallow connections from the input to all the hierarchical processing layers. Like conventional deep networks, SHANNs can achieve high levels of abstraction in more hierarchical layers.

To date, our understanding of how the human brain retrieves, processes, and stores information remains limited. A specific challenge lies in unravelling how local plasticity mechanisms shape the transfer of information between neurons. Traditional approaches to studying local plasticity in vitro, such as patch clamp or calcium imaging, are often limited by low throughput or the ability to record only from a subset of neurons within intricate networks. In response to these challenges, we adopt a bottom-up approach to engineer low-density neuronal networks with defined architectures. Human induc

The perirhinal cortex (PER) integrates and transfers information from cortical areas to the hippocampus, which is crucial for memory-related tasks, particularly novel object recognition. However, how the PER gates information transfer is largely unknown. During learning and novelty-induced exploration, the locus coeruleus releases noradrenaline, a candidate for modulating synaptic plasticity within the PER. We explored the hypothesis that noradrenaline could transiently increase the excitability of the PER network, enhancing information transfer toward the hippocampus and ultimately leading to

…triggering hippocampal replay and information transfer to cortical sites. Critically, although SWRs are precisely coupled to the cardinal NREM sleep-related mesoscopic brain rhythms (i.e., cortical slow oscillations and thalamo-cortical spindles), evidence for a link between SWRs and directed information transfer is scarce. Here, we leveraged the rar

The neurobiological mechanisms of arousal and anesthesia remain poorly understood. Recent evidence highlights the key role of interactions between the cerebral cortex and the diffusely projecting matrix thalamic nuclei. Here, we interrogate these processes in a whole-brain corticothalamic neural mass model endowed with targeted and diffusely projecting thalamocortical nuclei inferred from empirical data. This model captures key features seen in propofol anesthesia, including diminished network integration, lowered state diversity, impaired susceptibility to perturbation, and decreased corticoc

Learning relies as much on synaptic weight modifications as it does on the timing of neural signaling. For instance, variability in axonal length and diameter may compromise spike-timing-dependent plasticity (STDP) by dispersing action potential timing, preventing synaptic potentiation and depression. Activity-dependent myelination (ADM), a form of brain plasticity relying on neuron-glia feedback, has been shown to normalize conduction times across different axons through adaptive, neuron-activity-dependent changes in axonal conduction velocity (CV). While historically seen as a mere compensat

…we need a deeper understanding of information transfer across cortical areas. There are two leading hypotheses for communication between cortical areas: 1) The communication through coherence (CTC) hypothesis posits that coherent oscillations between source and target populations of neurons are required for information propagation. 2) The information transmission via communication subspace (CS) hypothesis, recently introduced by Semedo et al., adv

…perception, we have to understand how information enters the brain, how it is transformed and how it is transferred. But, how do we measure information transfer in the brain? This presentation will start with a general introduction of what mutual information is and how to measure it in an experimental setup. Next, the talk will focus on how this can be used to develop brain models at different (spatial) levels, from the microscopic single neuron level to the macroscopic network and behavioural level. How can we incorporate the knowl

…ways of using the physics of information transfer first developed at Bell Labs for thinking about telephone communications to try to decipher the meaning of the regulatory features of genomes. Specifically, I will show how we have been able