Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session D03: Information Processing in sensory and motor systemsFocus Recordings Available
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Sponsoring Units: DBIO Chair: Luca Mazzucato, University of Oregon Room: McCormick Place W-176A |
Monday, March 14, 2022 3:00PM - 3:12PM |
D03.00001: Differential robustness of neural networks in a regenerative brain Samuel Bray, Bo Wang, Livia Wyss, Chew Chai While we often consider the complexity of information processing in a nervous system, the robustness and resilience of the signaling network is critically important following brain injury and subsequent plastic remodeling. These concerns are especially relevant in the flatworm Schmidtea Mediterranea, a planarian which regularly regrows an entire brain and central nervous system during fissioning asexual reproduction. Here, we develop a platform to continuously measure planarian behavior throughout neural regeneration. We demonstrate that planaria are capable of information processing including signal integration, short term memory, and latent arousal states. Surprisingly, sensitization (a form of short-term memory), is retained even after brain amputation, whereas other memory like habituation do not return until late neural development . To understand the asynchronous return of function, we performed a genetic knockdown screen and found that sensitization and arousal require relatively long-range diffusive neuropeptide signals, while suppression of activity depends on locally-acting synaptic monoamines. Our results show that longer range peptidergic transmission creates a signaling network more robust to structural perturbations than the traditional synaptic connectome. |
Monday, March 14, 2022 3:12PM - 3:24PM Withdrawn |
D03.00002: Dynamic switch between ON and OFF responses in an olfactory receptor neuron Mahmut Demir, Srinivas Gorur-Shandilya, Thierry Emonet It has been shown that sensory neurons are either activated or inhibited by stimuli. Here we demonstrate existence of a third response modality in the Drosophila olfactory receptor neuron (ORN) ab2A, whose polarity is inverted from excitatory to inhibitory when stimulated with a single odorant of a certain type. ab2A increases its spike rate in response to an initial increase in odor intensity, exhibiting an “on” response. However, further increases/decreases in stimulus intensity elicit a decrease/increase in the spike rate, reminiscent of “off” responses. This on/off polarity inversion is dose-dependent and modulates olfactory behavior. It is broadly observed across several odorants and with other drosophilids. Furthermore, ab2A can compute whether an odor is a mixture of inverting and non-inverting odorants, as well as whether an inverting odor is received as a background or foreground cue. Polarity inversion does not require electrical coupling with neighboring neurons, does not rely on extracellular molecular mechanisms, and is not a result of membrane depolarization. Inversion is observed at the level of signal transduction, upstream of action potential generation. Moreover, it is qualitatively recapitulated by a biophysical model with two binding sites, suggesting it might take place at the level of the receptor. Together, these results establish polarity inversion as an important property of ORNs, and provide a quantitative framework for future studies of this new dimension in odor coding and neural computation. |
Monday, March 14, 2022 3:24PM - 3:36PM |
D03.00003: Deep Learning Diagnostic Analysis of the kinematic movement data recorded from individuals with Neurodevelopmental Disorders Khoshrav Doctor, Di Wu, Aditya Phadnis, Martin H Plawecki, John Nurnberger Jr., Jorge V Jose We have used Deep Learning ML techniques to analyze the kinematic movement patterns of individuals with Neurodevelopmental disorders (NDD). We studied individuals with Autism Spectrum Disorder (ASD), Attention Deficit Hyperactive Disorder (ADHD), comorbid ASD and ADHD (ASD+ADHD) vs Typically Developing (TD). Motor deficits have previously been identified in subjects with NDDs. We used XSENS high definition motor sensors, (www.xsens.com), to measure the angular velocity, angular acceleration and jerk, as well as the linear acceleration and linear jerk. The subjects carried out a reaching task. The reaching task consisted in moving the subjects’ arms towards touch screen targets appearing intermittently on the monitor. We implemented a supervised deep neural network to predict NDD conditions based on the raw kinematic sensors data, without any preconceived assumptions about the data. We assumed that the sensors raw kinematic data would contain such NDD classification information that is unravelled when using the AI Deep Learning techniques. We generated training sets with, typically, 75% of the full NDD and TD data sets measured with the sensors to train a neural network. Each of the output neurons were trained to represent a different NDD condition. We showed that the network was not overfitting through the accuracy on the held out set that was never used to train the network. Given the small size of the datasets, we applied K-Fold Cross Validation to train the network. The final accuracy on the held out set was 71.4%. This shows that DL is indeed able to correctly identify the diagnostics of most of the remaining NDD subjects without any a priori information about their cognitive abilities. It also clearly separates the NDDs from the TDs. This remarkable DL motor predictive power could be used as an early step in diagnosing the NDD conditions for potential treatments. |
Monday, March 14, 2022 3:36PM - 3:48PM |
D03.00004: Hebbian learning of orientation-selective receptive fields with monotonic fall-off of input correlations Bettina Hein, Francesco Fumarola, Kenneth D Miller Orientation-selective receptive fields (OSRFs) are shaped by specific feedforward connectivity from thalamus to V1 [Reid 1995]. Previous modeling found that OSRFs will develop from a "Mexican-hat" input correlation pattern between same-type (ON-ON, OFF-OFF) and opposite-type (ON-OFF) correlations [Miller 1994]. However, experimental work suggests a monotonic fall-off of this correlation difference. |
Monday, March 14, 2022 3:48PM - 4:24PM |
D03.00005: TBA Invited Speaker: Agostina Palmigiano
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Monday, March 14, 2022 4:24PM - 4:36PM |
D03.00006: A spiking network model of prefrontal cortex activity during strategic behavior Tianshu Li, Giancarlo La Camera The ability to adjust behavior according to context is essential to survival. In turn, this may require the ability to respond to identical stimuli with different behaviors. In the task analyzed here (Genovesio et al, Neuron 47:307–320, 2005), macaque monkeys must select a response based on an instruction stimulus and previous behavior. Depending on past trial type and behavior, the same instruction stimulus may require different responses. Specifically, if the instruction stimulus is the same as the previous trial, the same response is required (repeat-stay strategy); otherwise, a new response is required among the remaining two possible answers (change-shift strategy). If the latter response is not the required one, a second-chance change-shift trial is offered, and the monkey must select the remaining available response. We have preliminary evidence that prefrontal neural activity is metastable in this task, raising the question of how metastable neural dynamics are linked to the ability to produce strategic behavior. Here, we analyze under what conditions a metastable network of spiking neurons can exhibit strategic behavior. We found that a hierarchical metastable network can solve tasks with first-order contextual dependency (e.g., in change-shift trials), while additional mechanisms are required for higher-order dependency (e.g., in second-chance shift trials). |
Monday, March 14, 2022 4:36PM - 4:48PM |
D03.00007: Chemosensory diversity is invariant to background stimuli in chemotactic E. coli Jeremy P Moore, Keita Kamino, Thomas Shimizu, Thierry Emonet Non-genetic phenotypic diversity allows populations to hedge their bets when future conditions are uncertain. Could such diversity play a role in how chemotactic bacteria navigate complex chemical environments? Bacteria sense chemical attractants with highly cooperative arrays of receptors that modulate the activity of a kinase controlling flagellar rotation. Previous work from our lab demonstrated that variation in the degree of receptor cooperativity in a population of cells leads to variation in sensitivity to chemoattractant. But upon adaptation to a background stimulus, this variation is significantly reduced, effectively switching the population from a bet-hedging strategy to one where every cell is sensitive to the signal. Here, we explored how sensitivity to one stimulus varies in the presence of different background stimuli. We found that perfect adaptation to a chemoattractant that binds one receptor, does not affect the distribution of sensitivities to signals that bind other receptors. However, if the background chemoattractant binds the same receptor at the same site as the foreground, the mean sensitivity decreases, but the degree of cell-to-cell variability in sensitivity to the foreground remains unchanged. Thus, isogenic populations can switch between bet-hedging and exploitation independently for multiple signals. |
Monday, March 14, 2022 4:48PM - 5:00PM |
D03.00008: Investigating the effects of arousal on auditory processing Evangelia Papadopoulos, Michael Wehr, Luca Mazzucato Animals’ behavioral states vary rapidly over time, and these changes can drastically affect stimulus processing and task performance in different cortical areas. However, the neural mechanisms driving state-dependent effects on sensory processing are unclear. Here, we first present preliminary data from auditory cortex suggesting that tone frequency may be best decoded from population activity during states of moderate arousal. To explain this finding, we then consider a spiking model of a cortical circuit in which cells are arranged in clusters. Stimuli are modeled as cluster-specific-inputs, and state-changes are modeled as perturbations of the baseline external current to the network. We show that perturbations that increase external input heterogeneity modulate stimulus decoding in a way that is consistent with the effect of arousal in auditory cortex, with intermediate perturbation strengths yielding the best performance. We also demonstrate that these variations in stimulus processing arise due to a perturbation-induced shift from a phase in which network activity switches between metastable attractors to a phase with only a single attractor. In this picture, we show that moderate perturbation strengths improve decoding by speeding up transitions between metastable states. |
Monday, March 14, 2022 5:00PM - 5:12PM |
D03.00009: Mobile defects born from an energy cascade shape the locomotive behavior of a headless animal Manu Prakash, Matthew S Bull The physics of behavior seeks simple descriptions of animal behavior. The field has advanced rapidly by using techniques in low dimensional dynamics distilled from computer vision. Yet, we still do not generally understand the rules which shape these emergent behavioral manifolds in the face of complicated neuro-construction --- even in the simplest of animals. In this work, we introduce a non-neuromuscular model system which is complex enough to teach us something new but also simple enough for us to understand. We discover manifolds underlying the governing dynamics shaped and stabilized by a physical mechanism: an active-elastic, inverse-energy cascade. We explore the formulation of the governing dynamics of a polarized active elastic sheet in terms of the normal modes of an elastic structure decorated by a polarized activity at every node. By incorporating a torque mediated coupling physics, we show that the power is pumped from the shortest length scale up to longer length scale modes via a combination of direct mode coupling and preferential dissipation of higher frequency modes. We use this result to motivate the study of organismal locomotion as an emergent simplicity governing organism-scale behavior. To master the low dimensional dynamics on this manifold, we present a zero-transients limit study of the dynamics of +1 or vortex-like defects in the ciliary field (which is experimentally supported for small organisms). We show, experimentally, numerically and analytically that these defects arise from this energy cascade to generate long-lived, stable modes of locomotive behavior. Using a geometric model, we show how the defect undergoes unbinding. We extend this framework as a tool for studying larger organisms with non-circular shape and introduce local activity modulation for defect steering. We expect this work to inform the foundations of organismal control of distributed actuation without muscles or neurons. |
Monday, March 14, 2022 5:12PM - 5:24PM |
D03.00010: Extracting multi-neuron and dendritic activities from a freely behaving Drosophila larva Rui Wu, Paul McNulty, Doycho P Karagyozov, Mirna M Skanata, Marc H Gershow We study the decision-making process in Drosophila larva by simultaneously recording behavior and neural activity in a freely moving larva. We have developed a two-photon microscope that can reliably track and record activity from single or two nearby neurons [1]. To expand to multi-neuron recording, we volumetrically scan the vicinity of the tracked neuron, obtaining calcium imaging recordings from all neuron cell bodies, axons, and dendrites in the local neural circuit. The brain of a freely behaving larva undergoes significant motion and deformation, which presents new challenges for image analysis and neural signal extraction. We have developed a new analysis pipeline in 3D, combining new and existing tools in image processing to overcome these challenges. Calcium images are registered for both rigid and non-rigid motion, then corrected for spatial and temporal intensity fluctuations caused by motion, and neural activities are extracted from the processed images using a region of interest (ROI)-based method. We use this pipeline to examine the A27h premotor neurons of freely moving larvae, extracting activities from both cell bodies and the surrounding dendritic network. |
Monday, March 14, 2022 5:24PM - 5:36PM |
D03.00011: An excitatory plasticity rule for the formation of neural clusters in populations of spiking neurons Xiaoyu Yang, Giancarlo La Camera Growing evidence suggests that metastable neural dynamics might be the substrate of important cortical computations. Metastable dynamics can be obtained in a spiking network model partitioned in clusters wherein each cluster of neurons has an average synaptic strength above a critical value. One crucial question is to understand how clusters, and hence metastable dynamics, can be formed by experience. Motivated by obtaining a minimal learning rule which relies only on local ingredients, we propose an excitatory plasticity rule combined with a homeostatic mechanism that keeps the neural activity close to a desired level. A synaptic weight change is triggered by the arrival of presynaptic spikes, while the polarity of change depends on the recent history of its synaptic inputs. This learning rule leads to stable and robust formation of clusters and metastability, which is then maintained in the face of endogenously generated ongoing activity. After training, the spiking network can be successfully retrained with a new set of stimuli. When neurons respond to multiple stimuli during training, the same learning rule leads to the formation of overlapping clusters, a necessary condition for storing an extensive number of memories. These results show how metastable neural dynamics can emerge from a biologically plausible plasticity rule without the need for non-local ingredients such as synaptic renormalization. |
Monday, March 14, 2022 5:36PM - 5:48PM |
D03.00012: Analyzing dynamics of calcium and actin in primary cortical rat astrocytes of differing cytoskeletal architectures Nicholas J Mennona, Wolfgang Losert, Sylvester J Gates, Kate M O'Neill Astrocytes are an important cell type and are responsible for managing information flow and homeostasis in the brain. Astrocytes perform these functions using slow calcium (Ca2+) waves to communicate with each other and with other neural cells. Additionally, the ways in which astrocytes interact with neurons are dependent upon the cytoskeletal architecture, which in turn is affected by overall cell morphology. The three main morphological phenotypes of astrocytes are (1) stellate, (2) polygonal, and (3) reactive. In terms of functional states, the phenotypes correspond to immature, mature, and injury prevention, respectively. These diverse phenotypes and their associated functional consequences demonstrate a need to robustly analyze the functional dynamics of each type. Chemically and mechanically, we induce these differing phenotypes in vitro and then study native and perturbed calcium and actin dynamics. We employ data analytic algorithms to demonstrate differences (or lack there of) in the dynamics of these different astrocyte phenotypes. The use of data analytics reveals feature spaces whereby more insight into the way in which astrocytes signal can be known. |
Monday, March 14, 2022 5:48PM - 6:00PM |
D03.00013: Controlled gating of MS channels in bacterial cells in vivo using a mechanical load renata garces, Octavio Albarran, Samantha Miller, Christoph F Schmidt The ability to sense mechanical stimuli is an essential characteristic of living systems. In higher organisms mechanotransduction mediates, for example, the senses of touch and hearing. The main molecular transducers of mechanical stimuli into downstream signals are believed to be mechanically activated ion channels. The understanding of the gating mechanism of such channels, however, is far from complete. In-plane lipid membrane tension and attachment to intra- and extracellular structures are the most likely mechanisms. Mechanosensory ion channels (Msc) were first discovered in prokaryotes. E coli expresses seven different types of Mscs in its inner membrane. Their key role is to prevent cell lysis during hypoosmotic shocks. To date, patch clamping of ‘in vitro’ model membranes have been the only way to measure single-channel activity. There is no in vivo data at single channel resolution, and therefore it remains unknown how Mscs function in their complex native environment. We here present a new experimental approach to characterize gating activity of Mscs in bacteria in vivo. We use atomic force microscope cantilevers functionalized with large beads to compress cells. We observe pressure dependent channel gating at single channel resolution |
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