Aging and neurodegeneration are associated with changes in brain tissue at the molecular level, affecting its organization, density, and composition. These changes can be detected using quantitative MRI (qMRI), which provides physical measures that are sensitive to structural alterations. However, a major challenge in brain research is to relate physical estimates to their underlying biological sources. In this talk, I will discuss the community's efforts to use qMRI to identify biological processes that underlie changes in brain tissue. Specifically, I will highlight approaches for differentiating between changes in the concentration and composition of myelin and iron during aging. By exploring the molecular landscape of the aging and neurodegenerative brain using qMRI, we aim to gain a better understanding of these processes and potentially provide new metrics for evaluating them.

How information is processed within the brain is a key question in systems neuroscience. We address the issue in spiking neuronal networks of freely moving mice. I will describe our recent findings and conclusions pertaining to three specific information processing steps: transmission, representation, and storage. First, using feedforward optogenetic injection of white noise input to a small group of adjacent neocortical excitatory cells, we find that spike transmission to a postsynaptic cell exhibits error correction, improved precision, and temporal coding. The results are consistent with a nonlinear coincidence detection model in the postsynaptic neuron. Second, by triggering input on animal kinematics, we create an artificial place field in an otherwise-silent pyramidal cell. In hippocampal region CA1 but not in the neocortex, artificial fields exhibit synthetic phase precession that persists for a full cycle. The local conversion of an induced rate code into an emerging phase code is compatible with a dual-oscillator interference model. Third, by triggering input on spontaneous spiking, we impose self-terminating spike patterns in a group of presynaptic excitatory neurons and a postsynaptic cell. The precise timing of all pre- and postsynaptic spikes has a more substantial impact on long-lasting effective connectivity than that of individual cell pairs, revealing an unexpected plasticity mechanism. We conclude that intrinsic properties of single neurons support millisecond-timescale operations, and that cortical networks are organized in functional modules which we refer to as “converging assemblies”.

Sensory processing is fundamental for animal adaptation and survival, linking them to their environments. Understanding the nervous system's integration of sensory information is crucial for comprehending behavior and cognition. This process involves integrating external cues across modalities, along with internal states, cognitive processes, and motor control, leading to complex behaviors and a nuanced understanding of the world. To facilitate research on these processes, we aimed to identify natural behaviors that produce both auditory and somatosensory stimuli, steering clear of artificial stimulus sources. We discovered that whisking, previously considered a unimodal behavior associated solely with tactile sensations, also produces sounds with distinctive acoustic features within the auditory frequency range of mice. We explored the auditory neuronal representation of sounds generated by whisking and their implications for behavioral performance.  We demonstrate that sounds produced by whisking elicit diverse neuronal responses in the auditory cortex, encoding the object's identity and the mouse's whisking state, even in the absence of tactile sensations. Furthermore, we show that mice are capable of completing behavioral tasks relying solely on auditory cues generated by whisking against objects.

For centuries, consciousness was considered to be outside the reach of scientific investigation. Yet in recent decades, more and more studies have tried to probe the neural correlates of conscious experience, and several neuronally-inspired theories for consciousness have emerged. In this talk, I will focus on four leading theories of consciousness: Global Neuronal Workspace (GNW), integrated Information Theory (IIT), Recurrent Processing Theory (RPT) and Higher Order Theory (HOT). I will first shortly present the guiding principles of these theories. Then, I will provide a bird's-eye view of the field, using the results of a large-scale quantitative and analytic review we conducted, examining all studies that either empirically tested these theories or interpreted their findings with respect to at least one of them. Finally, I will describe the first results of the Cogitate consortium - an adversarial collaboration aimed at testing GNW and IIT.