Neuroscience seminars

Through Ask SAC sessions we aim to bridge the gap between our Scientific Advisory Committe and our budding neuroscientists! After completing her Masters in Neuroscience from the University of Manchester, UK and a professional stint at Pfizer, Ritwika joined Reservoir to make a difference in neurology. She develops creative strategies to assist the neurodiverse community and facilitate better healt support functions. Join us, to ask her anything and everything related to a career in neuroscience!

Dendrites are thin processes that extend from the cell body of neurons, the main computing units of the brain. The role of dendrites in complex brain functions has been investigated for several decades, yet their direct involvement in key behaviors such as for example sensory perception has only recently been established. In my presentation I will discuss how computational modelling has helped us illuminate dendritic function. I will present the main findings of a number of projects in lab dealing with dendritic nonlinearities in excitatory and inhibitory and their consequences on neuronal tuning and memory formation, the role of dendrites in solving nonlinear problems in human neurons and recent efforts to advance machine learning algorithms by adopting dendritic features.

Core body temperature is regulated to a setpoint between 36.1 to 37.8°C, with an average fluctuation of 0.5°C during a 24-hour day. Despite mechanistic safeguards, major temperature deviations (1-3°C) from the setpoint occur in the body and in turn the brain. For unknown reasons, in most mammals (humans included), these increases in brain temperature are benign. However, macro-fluctuations in brain temperature in some cases result in deleterious outcomes such as seizures. In this talk, I will describe a mechanism for circuit-level adaptive regulation of cortical activity during macro-fluctuations in brain temperature. I will also discuss how this mechanism can be applied towards the understanding of the pathology of Autism Spectrum Disorder.

External cues imbued with significance can enhance the motivational state of an organism, trigger related memories and influence future planning and goal directed behavior. At the same time, internal thought and imaginings can moderate and counteract the impact of external motivational cues. The neural underpinnings of imagination have been largely opaque, due to the inherent inaccessibility of mental actions. The talk will describe studies utilizing imagination and tracking how its neural correlates bidirectionally interact with external motivational cues. Stimulus-response associative learning is only one form of memory organization. A more comprehensive and efficient organizational principal is the cognitive map. In the last part of the talk we will examine this concept in the case of abstract memories and social space. Social encounters provide opportunities to become intimate or estranged from others and to gain or lose power over them. The locations of others on the axes of power and affiliation can serve as reference points for our own position in the social space. Research is beginning to uncover the spatial-like neural representation of these social coordinates. We will discuss recent and growing evidence on utilizing the principals of the cognitive map across multiple domains, providing a systematic way of organizing memories to navigate life.

One may think that Deep Learning technology works in ways that are similar to the human brain. This is not really true. Our best AI technology still does not mimic the brain sufficiently well to be a match in intelligence. I will describe seven differences on how our minds work in ways diametrically opposite to those of Deep Learning technology.

In this seminar, I will present new methods in magnetic resonance spectroscopy (MRS) we’ve been working on in the lab. The talk will be divided into two parts. In the first, I will talk about neurochemical changes we observe in glutamate and GABA during various paradigms, including simple motors tasks and reinforcement learning. In the second part, I’ll present a new approach to MRS that focuses on measuring the relaxation times (T1, T2) of metabolites, which reflect changes to specific cellular microenvironments. I will explain why these can be exciting markers for studying several in-vivo pathologies, and also present some preliminary data from a cohort of mild cognitive impairment (MCI) patients, showing changes that correlate to cognitive decline.

On April 22, 2021, Dr. Alan J Thompson of the University College London and the UCL Institute of Neurology, London, UK will deliver the Hughlings Jackson Lecture entitled, “Making Progress in Progressive MS – the Ultimate Challenge!” Established in 1935, the Hughlings Jackson Lecture is The Neuro’s premier scientific lecture. It honors the legacy of British neurologist John Hughlings Jackson (1835-1911) who pioneered the development of neurology as a medical specialty. Talk Abstract : The international focus on progressive MS, driven by the Progressive MS Alliance amongst others, together with recent encouraging results from clinical trials have raised the profile and emphasised the importance of understanding, treating and ultimately preventing progression in MS. Effective treatment for Progressive MS is now regarded as the single most important issue facing the MS community. There are several important challenges to developing new treatments for progressive MS. Fundamental to any development in treatment is a better understanding of the mechanisms of tissue injury underpinning progression which will in turn allow the identification of new targets against which treatments can be directed. There are additional complications in determining when progression actually starts, determining the impact of aging and defining the progressive clinical phenotypes – an area which has become increasingly complex in recent months. Evaluating potential new treatments in progressive MS also poses particular challenges including trial design and the selection of appropriate clinical and imaging outcomes - in particular, identifying an imaging biomarker for phase II trials of progressive MS. Despite these challenges, considerable progress is being made in developing new treatments targeting the innate immune system and exploring neuroprotective strategies. Further advances are being driven by a number of international networks, funded by the Progressive MS Alliance. Overall we are seeing encouraging progress as a result of co-ordinated global collaboration which offers real possibilities for truly effective treatment of progression.

Neocortical-hippocampal interactions during off-line periods such as slow-wave sleep are implicated in memory processing. In particular, recent memory traces are replayed in hippocampus during some sharp-wave ripple (SWR) events, and these replay events are positively correlated with neocortical memory trace reactivation. A prevalent model is that SWR arise ‘spontaneously’ in CA3 and propagate recent memory ‘indices’ outward to the neocortex to enable memory consolidation there; however, the spatiotemporal distribution of neocortical activation relative to SWR is incompletely understood. We used wide-field optical imaging to study voltage and glutamate release transients in dorsal neocortex in relation to CA1 multiunit activity (MUA) and SWR of sleeping and urethane anesthetized mice. Modulation of voltage and glutamate release signals in relation to SWRs varied across superficial neocortical regions, and it was largest in posteromedial regions surrounding retrosplenial cortex (RSC), which receives strong hippocampal output connections. Activity tended to spread sequentially from more medial towards more lateral regions. Contrary to the unidirectional hypothesis, activation exhibited a continuum of timing relative to SWRs, varying from neocortex leading to neocortex lagging the SWRs (± ~250 msec). The timing continuum was correlated with the skewness of peri-SWR hippocampal MUA and with a tendency for some SWR to occur in clusters. Thus, contrary to the model in which SWRs arise spontaneously in hippocampus, neocortical activation often precedes SWRs and may thus constitute a trigger event in which neocortical information seeds associative reactivation of hippocampal ‘indices’.

The hippocampal formation has been implicated in both cognitive functions as well as the sensing and control of endocrine states. To identify a candidate activity pattern which may link such disparate functions, we simultaneously measured electrophysiological activity from the hippocampus and interstitial glucose concentrations in the body of freely behaving rats. We found that clusters of sharp wave-ripples (SPW-Rs) recorded from both dorsal and ventral hippocampus reliably predicted a decrease in peripheral glucose concentrations within ~10 minutes. This correlation was less dependent on circadian, ultradian, and meal-triggered fluctuations, it could be mimicked with optogenetically induced ripples, and was attenuated by pharmacogenetically suppressing activity of the lateral septum, the major conduit between the hippocampus and subcortical structures. Our findings demonstrate that a novel function of the SPW-R is to modulate peripheral glucose homeostasis and offer a mechanism for the link between sleep disruption and blood glucose dysregulation seen in type 2 diabetes and obesity.

Genetic mutations of the SCN1A gene, the voltage gated sodium channel NaV1.1, cause well-defined epilepsies, including the severe developmental and epileptic encephalopathy Dravet syndrome and genetic epilepsy with febrile seizures plus (GEFS+), as well as a severe form of migraine with aura, familial hemiplegic migraine (FHM). More recently, they have been identified in an extremely severe early infantile encephalopathy. Functional studies and animal models have contributed to disclose pathological mechanisms, which can be often linked to a straightforward loss- vs gain- of channel function. However, although this simple dichotomy is pertinent and useful, detailed pathological mechanisms in neuronal circuits can be more complex, sometimes because of unexpected homeostatic or pathologic responses. I will compare pathological mechanisms of epilepsy and migraine mutations studied with cellular, animal and computational models, highlighting a novel homeostatic response implemented by CCK-positive GABAergic neurons in a mouse model of Dravet syndrome, which may be boosted in therapeutic approaches.

Protein quality control is essential for maintenance of a healthy and functional proteome that can attend the multiplicity of cellular functions. Failure of the systems that contribute to protein homeostasis, the so called proteostasis networks, have been identified in the pathogenesis of multiple neurodegenerative disorders and demonstrated to contribute to disease onset and progression. We are interested in autophagy, one of the components of the proteostasis network, and in the interplay of wo selective types of autophagy, chaperone-mediated autophagy (CMA) and endosomal microautophagy (eMI), with neurodegeneration. We have recently found that pathogenic proteins involved in common neurodegenerative conditions such as tauopathies or Parkinson’s disease, can exert a toxic effect in both types of selective types of autophagy compromising their functioning. We have now used mouse models with compromised CMA that support increased propagation of proteins such as tau and alpha-synuclein and an exacerbation of disease phenotype with aging. Conversely, genetic or chemical upregulation of CMA in this context of proteotoxicity slow down disease progression by facilitating effective intracellular removal of pathogenic proteins. Our findings highlight CMA and eMI as potential novel therapeutic targets against neurodegeneration.

When listening to music, we typically lock onto and move to a beat (1-6 Hz). Behavioral studies on such synchronization (Repp 2005) abound, yet the neural mechanisms remain poorly understood. Some models hypothesize an array of self-sustaining entrainable neural oscillators that resonate when forced with rhythmic stimuli (Large et al. 2010). In contrast, our formulation focuses on event time estimation and plasticity: a neuronal beat generator that adapts its intrinsic frequency and phase to match the extermal rhythm. The model quickly learns new rhythms, within a few cycles as found in human behavior. When the stimulus is removed the beat generator continues to produce the learned rhythm in accordance with a synchronization continuation task.

The subdivision benefit refers to the positive effect of subdividing a beat on sensorimotor synchronization. We recorded electroencephalograms of musicians and non-musicians to study how they listened or finger-tapped to a beat, subdivided into four distinct subdivisions. Musicians showed more consistent tapping responses than non-musicians, and enhanced neural entrainment during the tapping task than in the listening task. In both groups, there was a neural enhancement of the beat frequency and its first harmonic (related to duplets) after listening to the four subdivisions. Furthermore, non-musicians tapped more consistently to the beat of duplets than other subdivisions. Altogether, this suggests a neural and behavioral advantage for binary subdivisions, that can be modulated with formal training in music.

Pain is a major clinical problem affecting 1 in 5 people in the world. There are unresolved questions that urgently require answers to treat pain effectively, a crucial one being how the feeling of pain arises from brain activity. Computational models of pain consider how the brain processes noxious information and allow mapping neural circuits and networks to cognition and behaviour. To date, they have generally have assumed two largely independent processes: perceptual and/or predictive inference, typically modelled as an approximate Bayesian process, and action control, typically modelled as a reinforcement learning process. However, inference and control are intertwined in complex ways, challenging the clarity of this distinction. I will discuss how they may comprise a parallel hierarchical architecture that combines pain inference, information-seeking, and adaptive value-based control. Finally, I will discuss whether and how these learning processes might contribute to chronic pain.