Bulletin of the American Physical Society
APS March Meeting 2018
Volume 63, Number 1
Monday–Friday, March 5–9, 2018; Los Angeles, California
Session S06: Neural Control of BehaviorFocus
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Sponsoring Units: DBIO Chair: Gordon Berman, Emory Univ Room: LACC 153A |
Thursday, March 8, 2018 11:15AM - 11:51AM |
S06.00001: The brain outside the lab: Exploring the neural basis of long-term, naturalistic human behaviors Invited Speaker: Bing Brunton Much of our knowledge about neural computation in humans has been informed by data collected through carefully controlled experiments in laboratory settings, but understanding the brain in action requires exploration of large, naturalistic neural data recorded outside structured tasks. I will talk about our work analyzing neural processing in long-term brain recordings acquired in a task-free, naturalistic setting. Our data set consists of large-scale human intracranial brain recordings (ECoG) augmented with video, audio and depth camera recordings, all simultaneously and continuously monitoring a subject over several days to weeks. Importantly, unlike the majority of previous neural data used to train neural decoders, here the subjects are not instructed to perform specific tasks but are simply behaving as they wish in their hospital rooms. Motivated by the size of the dataset and substantial variety between individual subjects, our scalable computational approach circumvents tedious manual annotation and fine tuning of parameters. I will talk about data-driven models we developed to explore this long-term, naturalistic data using perspectives from dynamical systems, unsupervised clustering, and multimodal deep neural networks. |
Thursday, March 8, 2018 11:51AM - 12:03PM |
S06.00002: Modelling the Dynamics of Phase-Amplitude-Coupling During Prairie Vole Social Bond Formation Itai Pinkoviezky, Ahmed Roman, Elizabeth Amadei, Robert Liu, Gordon Berman Forming and maintaining social interactions is key to many species' survival and fitness. An extreme example of social behavior is pair bonding in prairie voles (M. ochrogaster), where male and a female voles form a strong social attachment after mating. Recent experiments showed the importance of coupling between regions of the brain’s reward system in the formation of pair bonding, finding that the amplitude of the high frequency activity is modulated by the phase of low frequency inputs – known as phase-amplitude coupling (PAC). In cases where the input decreased with time, the voles tended to form stronger bonds, suggesting habit formation. To shed light on these findings we developed a model of the relevant circuit as an inhibitory network of leaky integrate-and-fire neurons driven by oscillatory input. We calculate the non-linear response of the network within a self-consistent mean-field theory. Our results confirm that the network exhibits PAC between the input and higher frequency activity, showing how the network can compensate for a reduction in the oscillatory input by increasing both the DC input component and the inhibition level. Finally, we predict how changing the physiological variables of the network may alter the behavior of the animal. |
Thursday, March 8, 2018 12:03PM - 12:15PM |
S06.00003: Neural Connectome, Optimal Signaling, and Behavior in C. elegans nematode: connecting data to theory. Jan Karbowski, Franciszek Rakowski Neural connectomes, i.e. neural connectivity maps, are important for uncovering the design principles of nervous systems, and there has been a huge interest in neuroscience in determining connectomes of different species. Up to now, C. elegans worm is the only animal with the known connectome. However, can such maps really contribute to our understanding of animal behavior? I will argue that a detailed connectome is not sufficient to understand network dynamics, which in turn are related to animal's behavior. What is additionally necessary, is the type of synaptic signaling mediated by connections (i.e. whether excitation or inhibition). But the determination of signaling maps is challenging even for relatively small neural circuits in C. elegans due to "astronomical numbers" of possible synaptic patterns. I will discuss a powerful and fast parallel computational technique that in combination with behavioral data of C. elegans enables us to find optimal synaptic signaling for network controlling locomotion in these worms. This signaling map can be used to create realistic models of well studied behaviors of C. elegans, such as chemotaxis or thermotaxis. |
Thursday, March 8, 2018 12:15PM - 12:27PM |
S06.00004: What Can We Learn About Neurodevelopment by Studying the Kinematics of Simple Body Motions? Di Wu, Jorge Jose, John Nurnberger, Elizabeth Torres To understand how the nervous system develops people often study the brain directly. Here we posit that one can learn about neurodevelopment by studying the kinematic of simple body movements. We perform simple motions, like reaching or walking, everyday. Maturation of these motions are realized through a complex learning process at each milestone stage in our neurodevelopment. We conjectured that a detailed examination of such motion outputs may uncover some important biological information about typical neurodevelopment as well as the deviations in neurological disorders, like Autism Spectrum Disorder (ASD). To extract the potential physiological information, we examined the continuous motion outputs at millisecond time scales, introducing new mathematical metrics to assess possible hidden motion smoothness properties. Applying our metrics to reaching and natural walking motions showed that our metrics are capable of providing effective neurodevelopment assessments in both typical individuals and individuals with ASD. Our results show a surprising connection with several classical clinical psychiatric scores, like IQ etc., in the ASD cohort, providing a potential connection between motion performance and cognitive abilities in neurological disorders. |
Thursday, March 8, 2018 12:27PM - 12:39PM |
S06.00005: Neuromechanical Control and Passive Interaction Leads to Collisional Diffraction of a Sand Snake Perrin Schiebel, Jennifer Rieser, Alex Hubbard, Lillian Chen, Daniel Goldman Snakes coordinate the interaction of their flexible trunks with heterogeneity to generate propulsion. We hypothesized the snake C. occipitalis controls for its stereotyped travelling wave of body bending, specialized for movement on the sand substrate of their desert habitat [Schiebel et al SICB 2016], by targeting a pattern of muscle activation. We found C. occipitalis traversing a model multi-component terrain—a spatially uniform sand-mimic substrate and a single row of rigid posts perpendicular to the snakes’ initial trajectory—was re-oriented by the array into preferred directions of either ~0° (continuing straight) or ±21±9°. Since the shape changes of the snake were small during interaction, we posited that the motor program was largely preserved upon contact. We developed a model with a similar travelling wave. Following insights by Astley et al [SICB 2016] based on muscle activation patterns measured by Jayne [1988], we assumed external forces on the body were resisted only where active muscles would be lengthened. Thus posts were accommodated by changing curvature so that active muscles would shorten further, mimicking shape changes due to external forces. The model captured the collisional diffraction pattern, suggesting scattering is a result of passive dynamics. |
Thursday, March 8, 2018 12:39PM - 12:51PM |
S06.00006: Decoding human behavior from complex neural interactions Josuan Calderon, Yating Yang, Cory Inman, Jon Willie, Gordon Berman The brain is a complex system with intricate neural dynamics generated by interactions. How these interactions ultimately control an animal’s behavior, however, remains unresolved. This mapping is particularly mysterious for behaviors involving the coordination of multiple body parts over time scales longer than tens of milliseconds. Here we use electrocorticography (ECoG) data recorded from multiple patients to create a 2D representation of the stereotyped states of neural activity, based on embedding theorems in nonlinear state-space reconstruction. This method captures structured interactions underlying brain-wide dynamics that may be missed by conventional correlation-based analysis. Videos are used to decode human activities in an unsupervised manner. We discover patterns in the neural map that can be matched to behaviorally salient categories such as movement, speech, and rest. The transition of states is projected back to the neural map itself. Optimal predictive representations that best describe the hierarchical relationship between states over the multiple time scales are found in these transitions. These measurements are in agreement with theories from ethology and cognitive psychology, pointing towards general principles of the neural control of behavior. |
Thursday, March 8, 2018 12:51PM - 1:03PM |
S06.00007: Recording neural activity in unrestrained animals with 3D tracking two photon microscopy Doycho Karagyozov, Mirna Mihovilovic Skanata, Amanda Lesar, Marc Gershow Optical recordings of neural activity in behaving animals can reveal the neural correlates of decision making, but such recordings are compromised by brain motion that often accompanies behavior. Two-photon point scanning microscopy is especially sensitive to motion artifacts, and to date, two-photon recording of activity has required rigid mechanical coupling between the brain and microscope. To overcome these difficulties, we developed a two-photon tracking microscope capable of tracking neurons moving with velocities of 3 mm/s and accelerations of 1 m/s2 both in-plane and axially. We maintained continuous focus on targeted neurons allowing high-bandwidth measurements with modest excitation power. We recorded from motor- and inter- neurons in unrestrained freely behaving fruit fly larvae, correlating neural activity with stimulus presentation and behavioral outputs. Our technique can be extended to stabilize recordings in a variety of moving substrates. |
Thursday, March 8, 2018 1:03PM - 1:15PM |
S06.00008: Uncovering the Neural Basis of Flight Control in Fruit Flies Samuel Whitehead, Troy Shirangi, Theodore Lindsay, Saumya Sahai, Erica Ehrhardt, Tsevi Beatus, Nilay Yapici, Michael Dickinson, David Stern, Itai Cohen Rapidly-diverging aerodynamic instabilities require that flapping insects make subtle, millisecond-timescale adjustments to their wing motion to stay on course. Remarkably, fruit flies accomplish this feat using only 12 steering muscles to modulate the kinematics of each wing. Previous studies showed these stabilization reflexes can be modeled by a proportional-integral (PI) controller, but the implementation of this control by the wing muscles is poorly understood. Here, we leverage genetic tools for probing the fly nervous system and behavioral modeling to uncover the role of the first basalar (b1) muscle—a prominent member of the fly’s steering muscles—in the flight stabilization reflex. We selectively reduced the activity of the b1 muscle by silencing its motor neuron, and tested the control reflex of freely-flying flies. We find a surprisingly specific result: inhibiting b1 activity only affected the controller’s dependence on angular displacement, but not angular velocity, and this effect is specific to only one of the fly’s three rotational axes. What emerges from these and other studies is an organizational principal that dedicates different muscles to specific aspects of flight control. |
Thursday, March 8, 2018 1:15PM - 1:27PM |
S06.00009: Reliable targeting method for in vivo photo-stimulation of neurons Samira Aghayee, Daniel Winkowski, Patrick Kanold, Wolfgang Losert Recent advances in optical neuroscience have provided powerful tools to explore neuronal circuitry of the brain in novel ways. In vivo calcium imaging allows for monitoring the activity of tens to hundreds of neurons in real time. Simultaneous photo-stimulation of target neurons can be achieved using an integrated holographic stimulation beam path. However, the persistent jitter in awake behaving animals hinders our ability to accurately read out neural activity or to reliably target neurons for photo-stimulation. Real time capable tracking-based motion correction (Aghayee et al, 2017) corrects for the jitter and therefore allows for a valid read out of neural activity essential for identification of target neurons. We show that motion compensation can be used to estimate the real-time position of neurons more accurately as opposed to using the average position. In addition, we address the optical accessibility and off-target illumination problem in holographic microscopy by introducing a simple optical configuration that reduces speckles and yields more uniform intensity across target points. |
Thursday, March 8, 2018 1:27PM - 1:39PM |
S06.00010: Abstract Withdrawn
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Thursday, March 8, 2018 1:39PM - 2:15PM |
S06.00011: Cerebellar circuit mechanisms for coordinated locomotion in mice Invited Speaker: Megan Carey Smooth and efficient walking requires the coordination of movement across the body and depends critically on an intact cerebellum. We aim to understand how neural circuit mechanisms within the cerebellum contribute to specific aspects of coordinated locomotion. To this end, we have developed an automated, markerless 3D tracking system (LocoMouse) and used it to establish a quantitative framework for locomotor coordination in freely walking mice. In this talk I will describe our work combining these high resolution behavioral measurements with perturbations of the underlying neural circuits in order to probe the neural basis for locomotor coordination. Analyzing the behavior of mice with cerebellar defects has revealed specific features of locomotor coordination that suggest that cerebellar ataxia results from an inability to predict the consequences of movements across the body. In current experiments we are testing this idea by investigating neural circuit mechanisms of locomotor learning, in which mice learn to adapt their locomotor patterns to achieve a more symmetrical gait while walking on a split-belt treadmill. This approach is providing insight into how the highly stereotyped cellular architecture of the cerebellum supports a wide variety of behaviors, from relatively simple forms of learning to complex feats of coordination. |
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