Bulletin of the American Physical Society
APS March Meeting 2018
Volume 63, Number 1
Monday–Friday, March 5–9, 2018; Los Angeles, California
Session C42: Emergent Dynamics in Neural SystemsInvited
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Sponsoring Units: DBIO Chair: Emanuela Del Gado, Georgetown Univ Room: LACC 502B |
Monday, March 5, 2018 2:30PM - 3:06PM |
C42.00001: How manipulating the excitatory-inhibitory balance within in vitro neuronal networks with dopamine impacts network dynamics Invited Speaker: Rhonda Dzakpasu Neuronal oscillations take place within both cortical and hippocampal circuits and particular frequencies have been associated with cognitive processes such as working memory and attention. These oscillations manifest due to the synchronized activity within neural populations and the underlying neural spiking and bursting between individual cells is modulated by changes in intrinsic membrane excitability and synaptic transmission. The effects of dopamine - a neuromodulator known to impact learning, memory and attention - on synchronized activity has been widely studied in neural regions such as prefrontal cortex and striatum but fewer studies have investigated how dopamine impacts membrane excitability and network dynamics within the hippocampus, the neural region involved in spatial working memory. We use a 64-channel microelectrode array system to record extracellular action potential activity to study how dopamine modulates neuronal network activity from cultured hippocampal neurons. We find that while application of dopamine increases network and synchronized activity, the increase is short-lived with a return to basal levels. However, we show that upon an extended incubation with dopamine followed by application of glutamate, an excitatory neurotransmitter, network activity is increased over a longer timescale than with dopamine alone and we identify the receptor subtype that might play a role in this activity. |
Monday, March 5, 2018 3:06PM - 3:42PM |
C42.00002: Correlations in the brain Invited Speaker: Lucilla De Arcangelis Neuronal avalanches are a novel mode of spontaneous brain activity, experimentally found in vitro and in vivo, which exhibits a robust scaling behaviour. They suggest that the brain operates close to a critical point, as evidenced by the absence of a characteristic size in the phenomenon. The temporal organization of neuronal avalanches can be characterized by the distribution of waiting times between successive events. Experimental measurements in the rat cortex in vitro exhibit a non-monotonic behavior, not usually found in other natural processes. Numerical simulations provide evidence that this behavior is a consequence of the alternation between states of high and low activity, leading to a dynamic balance between excitation and inhibition. During these different states, both the single neuron behavior and the network excitability level, keeping memory of past activity, are tuned by homeostatic mechanisms. Moreover, by systematically removing smaller avalanches from the experimental time series we evidence the characteristic periodicity of θ and β/γ oscillations, which derive from the temporal organization of avalanches of different sizes: Large avalanches occur at low frequency triggering cascades of smaller avalanches, which occur at higher frequency.This behavior is also detected at a larger scale, i.e., on fMRI and MEG data from resting patients. Indeed, by monitoring temporal correlations we confirm that the system is able to self-regulate the activity level tuning the size of successive events according to their temporal distance. |
Monday, March 5, 2018 3:42PM - 4:18PM |
C42.00003: The statistical mechanics of hallucinations and the evolution of the visual cortex Invited Speaker: Nigel Goldenfeld In the normal state of vision, neural excitation patterns are driven by external stimuli. However, accepted models of the visual cortex bear formal similarities to statistical mechanical models describing spatially-extended ecosystems with activation and inhibition. As such, they are subject to fluctuation-induced Turing instabilities, which generically give rise to spatial patterns of neural excitation that would be perceived as hallucinations, masking the true external stimuli. Organisms operating under such conditions would not survive --- for example, they would be easy victims of predators. How is this devastating failure mode finessed by the visual cortex? We analyze the phase diagram of the visual cortex model as a function of its long-range connectivity, and show that the neuronal connections in the visual cortex have evolved precisely the global architecture necessary to mitigate the failure mode: sparse long-range inhibition. These results imply that sparse long-range inhibition plays a previously unrecognized role in stabilizing the normal vision state, and in addition, accounts for the observed regularity of geometric visual hallucinations. |
Monday, March 5, 2018 4:18PM - 4:54PM |
C42.00004: Does the cortex truly operate at criticality? Invited Speaker: John Beggs
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Monday, March 5, 2018 4:54PM - 5:30PM |
C42.00005: How neural emergent dynamics creates the perception of abstract space-time Invited Speaker: Mayank R. Mehta All animals move in space, as a function of time, hence they must have a very clear perception of space and time. How are space-time represented in the brain? What are the environmental and biophysical mechanisms by which the mental maps of space-time are constructed? Pioneering research done over the last three decades has answered the first question, resulting in the Nobel Prize in 2014. They found that a brain circuit called the hippocampus contains neurons that are activated as a function of the precise location of the subject in space. Hence, these neurons are termed “place cells”. Further, they recently discovered that a connected circuit, the entorhinal cortex, contains neurons that fire at the vertices of a triangular lattice that tiles the entire environment explored by the subject, and these neurons are called “grid cells”. The challenge now is to understand the emergent mechanisms by which these fascinating mental maps of space emerge, and their role in encoding time. There are two key difficulties in tackling this challenge. First, it has not possible to precisely measure and manipulate the multisensory stimuli that create space-time perception. Second, the experimental and analytical techniques to measure and decipher the neural emergent dynamics have been lacking. I will describe accomplishments and opportunities, both experimental and analytical, in tackling these challenges. In particular, I will discuss the novel, multisensory virtual reality approaches and tools to measure neural signals with high spatio-temporal precision. |
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