Neuroscience seminars

Dysregulation of protein synthesis both globally and locally in neurons and astrocytes is a key feature of neurodegenerative diseases. Aberrant signalling through the Unfolded Protein Response (UPR) and related Integrated Stress Response (ISR) have become major targets for neuroprotection in these disorders. In addition, other homeostatic mechanisms and stress responses, including the cold shock response, appear to regulate local translation and RNA splicing to control synapse maintenance and regeneration and can also be targeted therapeutically for neuroprotection. We have defined the role of UPR/ISR and the cold-shock response in neurodegenerative disorders and have developed translational strategies targeting them for new treatments for dementia.

Brain-computer interfaces (BCIs) have afforded paralysed users “mental control” of computer cursors and robots, and even of electrical stimulators that reanimate their own limbs. Most existing BCIs map the activity of hundreds of motor cortical neurons recorded with implanted electrodes into control signals to drive these devices. Despite these impressive advances, the field is facing a number of challenges that need to be overcome in order for BCIs to become widely used during daily living. In this talk, I will focus on two such challenges: 1) having BCIs that allow performing a broad range of actions; and 2) having BCIs whose performance is robust over long time periods. I will present recent studies from our group in which we apply neuroscientific findings to address both issues. This research is based on an emerging view about how the brain works. Our proposal is that brain function is not based on the independent modulation of the activity of single neurons, but rather on specific population-wide activity patters —which mathematically define a “neural manifold”. I will provide evidence in favour of such a neural manifold view of brain function, and illustrate how advances in systems neuroscience may be critical for the clinical success of BCIs.

In this talk I will discuss our recent findings that sensory signals from the brain adjust the physiology and behavior of the nematode C. elegans, enabling this animal to deal with the lethal threat of hydrogen peroxide. Hydrogen peroxide (H2O2) is the most common chemical threat in the microbial battlefield. Prevention and repair of the damage that hydrogen peroxide inflicts on macromolecules are critical for health and survival. In the first part of the talk, I will discuss our findings that C. elegans represses their own H2O2 defenses in response to sensory perception of Escherichia coli, the nematode’s food source, because E. coli can deplete H2O2 from the local environment and thereby protect the nematodes. Thus, the E. coli self-defense mechanisms create a public good, an environment safe from the threat of H2O2, that benefits C. elegans. In the second part of the talk, I will discuss how the modulation of C. elegans’ sensory perception by the interplay of hydrogen peroxide and bacteria adjusts the nematode’s behavior to improve the nematode’s chances of finding a niche that provides both food and protection from hydrogen peroxide.

Survival is predicated on the ability of an organism to respond to stress. The reliability of this response is ensured by a synaptic architecture that is relatively inflexible (i.e. hard-wired). Our work has shown that in naive animals, synapses on CRH neurons in the paraventricular nucleus of the hypothalamus are very reluctant to modification. If animals are stressed, however, these synapses become willing to learn. This seminar will focus on mechanisms linking acute stress to metaplastic changes at glutamate synapses, and also show how stress, and these synaptic changes can be transmitted from one individual to another.

This talk will focus on the generative modelling of resting state time series or endogenous neuronal activity. I will survey developments in modelling distributed neuronal fluctuations – spectral dynamic causal modelling (DCM) for functional MRI – and how this modelling rests upon functional connectivity. The dynamics of brain connectivity has recently attracted a lot of attention among brain mappers. I will also show a novel method to identify dynamic effective connectivity using spectral DCM. Further, I will summarise the development of the next generation of DCMs towards large-scale, whole-brain schemes which are computationally inexpensive, to the other extreme of the development using more sophisticated and biophysically detailed generative models based on the canonical microcircuits.

The digital kickoff of NeurotechRI will take place on the 26th from 13:00 to 16:00 (CET). Come and join us as we discuss our plans for the Graduate School and our research and innovation roadmap! The programme can be downloaded here. Don’t miss out on our Board of Governors presentation of the project and the synergies with NeurotechEU, meet with our keynote speakers from the European Research Executive Agency: Mr Stijn Delaure (DG R&I, Unit A3 “R&I Actors and Research Careers”) and Ms Marta Truco Calbet (DG R&I, Unit C.4 "Reforming European R&I and Research Infrastructures''). Last but not least, the day will finish with a roundtable discussion organised by our students society. The roundtable will be an open space and an opportunity for all students to discuss their needs in education. Registration is open: www.crowdcast.io/e/neurotechri-kickoff

The interaction between spontaneously and externally evoked neuronal activity is fundamental for a functional brain. Increasing evidence suggests that bursts of high-power oscillations in the 15-30 Hz beta-band represent activation of resting state networks and can mask perception of external cues. Yet demonstration of the effect of beta power modulation on perception in real-time is missing, and little is known about the underlying mechanism. In this talk I will present the methods we developed to fill this gap together with our recent results. We used a closed-loop stimulus-intensity adjustment system based on online burst-occupancy analyses in rats involved in a forepaw vibrotactile detection task. We found that the masking influence of burst-occupancy on perception can be counterbalanced in real-time by adjusting the vibration amplitude. Offline analysis of firing-rates and local field potentials across cortical layers and frequency bands confirmed that beta-power in the somatosensory cortex anticorrelated with sensory evoked responses. Mechanistically, bursts in all bands were accompanied by transient synchronization of cell assemblies, but only beta-bursts were followed by a reduction of firing-rate. Our closed loop approach reveals that spontaneous beta-bursts reflect a dynamic state that competes with external stimuli.

Ever since Bliss and Lømo discovered the phenomenon of long-term potentiation (LTP) in rabbit dentate gyrus in the 1960s, Hebb’s rule—neurons that fire together wire together—gained popularity to explain learning and memory. Accumulating evidence, however, suggests that neural activity is homeostatically regulated. Homeostatic mechanisms are mostly interpreted to stabilize network dynamics. However, recent theoretical work has shown that linking the activity of a neuron to its connectivity within the network provides a robust alternative implementation of Hebb’s rule, although entirely based on negative feedback. In this setting, both natural and artificial stimulation of neurons can robustly trigger network rewiring. We used computational models of plastic networks to simulate the complex temporal dynamics of network rewiring in response to external stimuli. In parallel, we performed optogenetic stimulation experiments in the mouse anterior cingulate cortex (ACC) and subsequently analyzed the temporal profile of morphological changes in the stimulated tissue. Our results suggest that the new theoretical framework combining neural activity homeostasis and structural plasticity provides a consistent explanation of our experimental observations.

The seminar will first outline the architecture of the human mind, specifying general and domain-specific mental processes. The place of causal reasoning and its relations with the other processes will be specified. Experimental, psychometric, developmental, and brain-based evidence will be summarized. The main message of the talk is that causal thought involves domain-specific core processes rooted in perception and served by special brain networks which capture interactions between objects. With development, causal reasoning is increasingly associated with a general abstraction system which generates general principles underlying inductive, analogical, and deductive reasoning and also heuristics for specifying causal relations. These associations are discussed in some detail. Possible implications for artificial intelligence and educational implications are also discussed.

Selection is the hallmark of attention: processing improves for attended items but is relatively impaired for unattended items. It is well known that visual spatial attention changes sensory signals and perception in this selective fashion. In the work I will present, we asked whether and how attentional selection happens across time. First, our experiments revealed that voluntary temporal attention (attention to specific points in time) is selective, resulting in perceptual tradeoffs across time. Second, we measured small eye movements called microsaccades and found that directing voluntary temporal attention increases the stability of the eyes in anticipation of an attended stimulus. Third, we developed a computational model of dynamic attention, which proposes specific mechanisms underlying temporal attention and its selectivity. Lastly, I will mention how we are testing predictions of the model with MEG. Altogether, this research shows how precisely timed voluntary attention helps manage inherent limits in visual processing across short time intervals, advancing our understanding of attention as a dynamic process.

How the brain creates a painful experience remains a mystery. Solving this mystery is crucial to understanding the fundamental biological processes that underlie the perception of body integrity, and to creating better, non-addictive pain treatments. My laboratory’s goal is to resolve the neural basis of pain. We aim to understand the mechanisms by which our nervous system produces and assembles the sensory-discriminative, affective-motivational, and cognitive-evaluative dimensions of pain to create this unique and critically important experience. To capture every component of the pain experience, we examine the entirety of the pain circuitry, from sensory and spinal ascending pathways to cortical/subcortical circuits and brainstem descending pain modulation systems, at the molecular, cellular, circuit and whole-animal levels. For these studies, we have invented novel behavioral paradigms to interrogate the affective and cognitive dimensions of pain in mice while simultaneously imaging and manipulating nociceptive circuits. My laboratory also investigates how opioids suppress pain. Remarkably, despite their medical and societal significance, how opium poppy alkaloids such as morphine produce profound analgesia remains largely unexplained. By identifying where and how opioids act in neural circuits, we not only establish the mechanisms of action of one of the oldest drugs known to humans, but also reveal the critical elements of the pain circuitry for developing of novel analgesics and bringing an end to the opioid epidemic.

Fiber photometry (FP) is an adaptable method for recording in vivo neural activity in freely behaving animals. It has become a popular tool in neuroscience due to its ease of use, low cost, the ability to combine FP with freely moving behavior, among other advantages. However, analysis of FP data can be a challenge for new users, especially those with a limited programming background. Here, we present Guided Photometry Analysis in Python (GuPPy), a free and open-source FP analysis tool. GuPPy is provided as a Jupyter notebook, a well-commented interactive development environment (IDE) designed to operate across platforms. GuPPy presents the user with a set of graphic user interfaces (GUIs) to load data and provide input parameters. Graphs produced by GuPPy can be exported into various image formats for integration into scientific figures. As an open-source tool, GuPPy can be modified by users with knowledge of Python to fit their specific needs.

In a famous philosophical paradox, Buridan's ass perishes because he is equally hungry and thirsty, and cannot make up his mind whether to first drink or eat. We are faced daily with the need to pick between alternatives that are equally attractive (or not) to us. What are the processes that allow us to avoid paralysis and to rapidly select between such equal options when there are no preferences or rational reasons to rely on? One solution that was offered is that although on a higher cognitive level there is symmetry between the alternatives, on a neuronal level the symmetry does not maintain. What is the nature of this asymmetry of the neuronal level? In this talk I will present experiments addressing this important phenomenon using measures of human behavior, EEG, EMG and large scale neural network modeling, and discuss mechanisms involved in the process of intention formation and execution, in the face of alternatives to choose from. Specifically, I will show results revealing the temporal dynamics of rapid intention formation and, moreover, ‘change of intention’ in a free choice picking scenario, in which the alternatives are on a par for the participant. The results suggest that even in arbitrary choices, endogenous or exogenous biases that are present in the neural system for selecting one or another option may be implicitly overruled; thus creating an implicit and non-conscious ‘change of mind’. Finally, the question is raised: in what way do such rapid implicit ‘changes of mind’ help retain one’s self-control and free-will behavior?