Transatlantic Systems Neuro

Nearly every aspect of life involves decisions between options that differ in both their expected rewards and the potential costs (such as delay to reward delivery or risk of harm) that accompany those rewards. The ability to choose adaptively when faced with such decisions is critical for well-being and overall quality of life. In neuropsychiatric conditions such as substance use disorders, however, decision making is often compromised, which can prolong and exacerbate their severity and co-morbidities. In this seminar, Dr. Setlow will discuss research in rodent models investigating behavioral and biological mechanisms of cost-benefit decision making. In particular, he will focus on factors (including sex) that contribute to differences in cost-benefit decision making across the population, how variability in decision making is related to substance use, and how substance use can produce long-lasting changes in decision preference.

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.

Working memory is the sketchpad of consciousness, the fundamental mechanism the brain uses to gain volitional control over its thoughts and actions. For the past 50 years, working memory has been thought to rely on cortical neurons that fire continuous impulses that keep thoughts “online”. However, new work from our lab has revealed more complex dynamics. The impulses fire sparsely and interact with brain rhythms of different frequencies. Higher frequency gamma (>35 Hz) rhythms help carry the contents of working memory while lower frequency alpha/beta (~8-30 Hz) rhythms act as control signals that gate access to and clear out working memory. In other words, a rhythmic dance between brain rhythms may underlie your ability to control your own thoughts.

The hippocampus and the amygdala are two structures required for emotional memory. While the hippocampus encodes the contextual part of the memory, the amygdala processes its emotional valence. During Non-REM sleep, the hippocampus displays high frequency oscillations called “ripples”. Our early work shows that the suppression of ripples during sleep impairs performance on a spatial task, underlying their crucial role in memory consolidation. We more recently showed that the joint amygdala-hippocampus activity linked to aversive learning is reinstated during the following Non-REM sleep epochs, specifically during ripples. This mechanism potentially sustains the consolidation of aversive associative memories during Non REM sleep. On the other hand, REM sleep is associated with regular 8 Hz theta oscillations, and is believed to play a role in emotional processing. A crucial, initial step in understanding this role is to unravel sleep dynamics related to REM sleep in the hippocampus-amygdala network

Although animals can estimate numerical quantities, true counting and arithmetic abilities are unique to humans and are inextricably linked to symbolic competence. However, our unprecedented numerical skills are deeply rooted in our neuronal heritage as primates and vertebrates. I argue that numerical competence in humans is the result of three neural constraints. First, I propose that the neuronal mechanisms of quantity estimation are part of our evolutionary heritage and can be witnessed across primate and vertebrate phylogeny. Second, I suggest that a basic understanding of number, what numerical quantity means, is innately wired into the brain and gives rise to an intuitive number sense, or number instinct. Third and finally, I argue that symbolic counting and arithmetic in humans is rooted in an evolutionarily and ontogenetically primeval neural system for non-symbolic number representations. These three neural constraints jointly determine the basic processing of number concepts in the human mind.

Stereopsis – deriving information about distance by comparing views from two eyes – is widespread in vertebrates but so far known in only class of invertebrates, the praying mantids. Understanding stereopsis which has evolved independently in such a different nervous system promises to shed light on the constraints governing any stereo system. Behavioral experiments indicate that insect stereopsis is functionally very different from that studied in vertebrates. Vertebrate stereopsis depends on matching up the pattern of contrast in the two eyes; it works in static scenes, and may have evolved in order to break camouflage rather than to detect distances. Insect stereopsis matches up regions of the image where the luminance is changing; it is insensitive to the detailed pattern of contrast and operates to detect the distance to a moving target. Work from my lab has revealed a network of neurons within the mantis brain which are tuned to binocular disparity, including some that project to early visual areas. This is in contrast to previous theories which postulated that disparity was computed only at a single, late stage, where visual information is passed down to motor neurons. Thus, despite their very different properties, the underlying neural mechanisms supporting vertebrate and insect stereopsis may be computationally more similar than has been assumed.

Psychotic disorders are devastating conditions without any mechanistic treatment available. One major hurdle in the biological study of psychosis is the challenge of rigorously probing this condition in pre-clinical animal models. The goal of our research is to develop and exploit innovative frameworks for the study of psychosis in mice. In our present work, where we developed a cross-species computational psychiatry approach to probe hallucination-like perception. This enabled us to directly relate human and mouse behavior, and to demonstrate and dissect the causal role of striatal dopamine in hallucination-like perception. Our results suggest a neural circuit mechanism for the long-standing dopamine hypothesis of psychosis, and provide a new translational framework for the biological study of psychosis. This opens up exciting possibilities for advancing the biological understanding of psychosis and to identify mechanistic treatment targets.

For spatial orientation, heading information can be processed in two different frames of reference, a self-centered egocentric or a viewpoint allocentric frame of reference. Using the most efficient frame of reference is in particular important if an animal migrates over large distances, as it the case for the monarch butterfly (Danaus plexippus). These butterflies employ a sun compass to travel over more than 4,000 kilometers to their destination in central Mexico. We developed tetrode recordings from the heading-direction network of tethered flying monarch butterflies that were allowed to orient with respect to a sun stimulus. We show that the neurons switch their frame of reference depending on the animal’s locomotion state. In quiescence, the heading-direction cells encode a sun bearing in an egocentric reference frame, while during active flight, the heading-direction is encoded within an allocentric reference frame. By switching to an allocentric frame of reference during flight, monarch butterflies convert the sun to a global compass cue for long-distance navigation, an ideal strategy for maintaining a migratory heading.

Working memory (WM) is a fundamental human cognitive capacity that allows us to maintain and manipulate information stored for a short period of time in an active form. Thanks to a unique opportunity to record activity of neurons in humans during epilepsy monitoring we could test neuronal mechanisms of this cognitive capacity. We showed that firing rate of image selective neurons in Medial Temporal Lobe persists through maintenance periods of working memory task. This activity was behaviorally relevant and formed attractors in its state-space. Furthermore, we showed that firing rate of those neurons phase lock to ongoing slow-frequency oscillations. The properties of phase locking are dependent on memory content and load. During high memory loads, the phase of the oscillatory activity to which neurons phase lock provides information about memory content not available in the firing rate of the neurons.

Jonathan Whitlock is an associate professor of neuroscience at the Kavli Institute for Systems Neuroscience in Trondheim, Norway. His group combines high-density single-unit recordings with silicone probes and sub-millimeter 3D tracking to study the cortical representation of pose and movement in freely behaving rats. The lecture will introduce his group’s work on neural tuning to pose and movement parietal and motor areas, and will include more recent findings from primary visual, auditory and somatosensory areas

Our work concerns the general problem of adaptive behaviour in response to predatory threats, and of the neural mechanisms underlying a choice between strategies. When faced with a threat, an animal must decide whether to freeze, reducing its chances of being noticed, or to flee to the safety of a refuge. Animals from fish to primates choose between these two alternatives when confronted by an attacking predator, a choice that largely depends on the context in which the threat occurs. Recent work has made strides identifying the pre-motor circuits, and their inputs, which control freezing behaviour in rodents, but how contextual information is integrated to guide this choice is still far from understood. The social environment is a potent contextual modulator of defensive behaviours of animals in a group. Indeed, anti-predation strategies are believed to be a major driving force for the evolution of sociality. We recently found that fruit flies in response to visual looming stimuli, simulating a large object on collision course, make rapid freeze/flee choices accompanied by lasting changes in the fly’s internal state, reflected in altered cardiac activity. In this talk, I will discuss our work on how flies process contextual cues, focusing on the social environment, to guide their behavioural response to a threat. We have identified a social safety cue, resumption of activity, and visual projection neurons involved in processing this cue. Given the knowledge regarding sensory detection of looming threats and descending neuron involved in the expression of freezing, we are now in a unique position to understand how information about a threat is integrated with cues from the social environment to guide the choice of whether to freeze.

We study the larval stages of the marine annelid Platynereis dumerilii, a powerful experimental system for neural circuits. With serial electron microscopy, we have reconstructed the entire nervous and effector systems of a Platynereis larva. We use neurogenetics, activity imaging, and behavioural experiments to understand circuit activity and how the nervous system controls behaviour and physiology. Platynereis is one of very few systems where these different approaches can be combined to study an entire nervous system. I will talk about circuits for the whole-body coordination of locomotor cilia and a hydrodynamic startle response for predator avoidance.

Birdsong emerges when a set of highly interconnected brain areas manage to generate a complex output. The similarities between birdsong production and human speech have positioned songbirds as unique animal models for studying learning and production of this complex motor skill. In this work, we developed a low dimensional model for a neural network in which the variables were the average activities of different neural populations within the nuclei of the song system. This neural network is active during production, perception and learning of birdsong. We performed electrophysiological experiments to record neural activity from one of these nuclei and found that the low dimensional model could reproduce the neural dynamics observed during the experiments. Also, this model could reproduce the respiratory motor patterns used to generate song. We showed that sparse activity in one of the neural nuclei could drive a more complex activity downstream in the neural network. This interdisciplinary work shows how low dimensional neural models can be a valuable tool for studying the emergence of complex motor tasks

The hippocampus lies at the centre of a network of brain regions thought to support spatial and episodic memory. Place cells - the principal cell of the hippocampus, represent information about an animal’s spatial location. Yet, during rest and awake quiescence place cells spontaneously recapitulate past trajectories (‘replay’). Replay has been hypothesised to support systems consolidation – the stabilisation of new memories via maturation of complementary cortical memory traces. Indeed, in recent work we found place and grid cells, from the deep medial entorhinal cortex (dMEC, the principal cortical output region of the hippocampus), replayed coherently during rest periods. Importantly, dMEC grid cells lagged place cells by ~11ms; suggesting the coordination may reflect consolidation. Moreover, preliminary data shows that the dMEC-hippocampal coordination strengthens as an animal becomes familiar with a task and that it may be led by directionally modulated cells. Finally, on-going work, in my recently established lab, shows replay may represent the mechanism underlying the maturation of episodic/spatial memory in pre-weanling pups. Together, these results indicate replay may play a central role in ensuring the permanency of memories.

Sensory representations are typically thought as neuronal activity patterns that encode physical attributes of the outside world. However, increasing evidence is showing that as animals learned the association between a sensory stimulus and its behavioral relevance, stimulus representation in sensory cortical areas can change. In this seminar I will present recent experiments from our lab showing that the activity in the olfactory piriform cortex (PC) of mice encodes not only odor information, but also non-olfactory variables associated with the behavioral task. By developing an associative olfactory learning task, in which animals learn to associate a particular context with an odor and a reward, we were able to record the activity of multiple neurons as the animal runs in a virtual reality corridor. By analyzing the population activity dynamics using Principal Components Analysis, we find different population trajectories evolving through time that can discriminate aspects of different trial types. By using Generalized Linear Models we further dissected the contribution of different sensory and non-sensory variables to the modulation of PC activity. Interestingly, the experiments show that variables related to both sensory and non-sensory aspects of the task (e.g., odor, context, reward, licking, sniffing rate and running speed) differently modulate PC activity, suggesting that the PC adapt odor processing depending on experience and behavior.

To make judgments, brain must be able to infer the state of the world based on often incomplete and ambiguous evidence. To probe neural circuits that perform the computations underlying such judgments, we developed a behavioral task for mice that required them to detect sustained increases in the speed of a continuously varying visual stimulus. In this talk, I will present evidence that the responses of secondary motor cortex to stimulus fluctuations in this task are consistent with updates of the animal’s state of belief that the change has occurred. These results establish a framework for mechanistic inquiries into neural circuits underlying inference during perceptual decision-making.

Investigations of the neurophysiological processes underlying animal behaviors are almost exclusively done inside the laboratory, typically using few animal models born and reared under artificially stabilized conditions. Yet, animals living in the wild have to cope with much complex and variable environments. Thus, while the laboratory provides the technical possibilities for physiological research, the field offers a more realistic perspective about the animal´s behavioral abilities. We study neural circuits underlying the visually guided prey and predator behaviors in a semiterrestrial crab. By combining lab and field experiments we have, for example, found that the level of predation risk experienced by the animals in the wild affects the responsiveness of identified neurons involved in the animal escape response. Using this and other results from my lab I will illustrate and discuss the importance of complementing lab with field studies in wild animals for understanding the neural mechanisms subserving behavior.

Both computational and experimental results in single neurons and small networks demonstrate that very similar network function can result from quite disparate sets of neuronal and network parameters. Using the crustacean stomatogastric nervous system, we study the influence of these differences in underlying structure on differential resilience of individuals to a variety of environmental perturbations, including changes in temperature, pH, potassium concentration and neuromodulation. We show that neurons with many different kinds of ion channels can smoothly move through different mechanisms in generating their activity patterns, thus extending their dynamic range.

Paramecium is a unicellular organism that swims in fresh water using cilia. When it is stimulated (mechanically, chemically, optically, thermally, etc), it often swims backward then turns and swims forward again: this is called the avoiding reaction. This reaction is triggered by a calcium-based action potential. For this reason, it enjoyed a period of glory in the 1970s as a model organism for neuroscience. I will describe the behavior and electrophysiology of this “swimming neuron”, then I will present our ongoing attempts at developing an integrative quantitative model of Paramecium.