MBI Videos
Workshop 6: Sensory Systems and Coding
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Tatyana Sharpee -
Andrea BarreiroMechanisms for higher-order correlations in microcircuits. -
Kresimir JosicPopulations of neurons jointly drive behavior. Thus, understanding how population activity is coordinated is a key challenge. Novel recording techniques allow for the simultaneous recording from many cells revealing the joint activity of neuronal population during sensory, motor, and cognitive tasks. This has prompted widespread measurement of pairwise correlations. However, the magnitude, the interpretation, and the underlying neural mechanisms of such neural correlations are being vigorously debated. I will start by reviewing our current understanding of the biological mechanisms that control the correlation between the spiking activity of cortical neurons. In particular, I will discuss the potential pitfalls in simple mechanistic explanations of modulations in the coherence in network activity.
In the second part of the talk I will discuss the role of correlations in neural coding. I will first examine the role of coupling between the neurons of the Vertical System (VS) in the lobula plate of the fly. These 20 non-spiking neurons code for the azimuth of the axis of rotation of the fly during flight. The electrical coupling between the cells is relatively large, and the activity of VS cells is strongly correlated. I will discuss the potential role this coupling plays in the processing of optical flow information. I will end with a comment on the impact of noise correlation in models used in psychophysics.
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Mark WillisInteractions of sensor structure, and environmental and locomotory context determine odor plume tracking behavior. -
Remus OsanThe size and complexity of neural data is increasing at a dramatic pace due to rapid advances in experimental technologies. As a result, the data analysis techniques are shifting their focus from single-units to neural populations. We use projection methods, such as Principal Component Analysis PCA and Multiple Discriminant Analysis MDA, to facilitate the understanding and monitoring of the dynamics of neural populations recorded in the hippocampus and olfactory bulb. For the hippocampal date, we examine representation of startle episodes, in order to differentiate between somato-sensory and memory components of the hippocampal representations. For the olfactory data, we focus on how dynamics of odor responses in the olfactory receptor neurons of awake rats are shaped by the temporal features of the active odor sniffing. Our analyses indicate that the dynamics of neural representations depend non-linearly on odor identity and concentration, as well as breathing rhythms of the rats. These results include work done with graduate students Jun Xia and Jie Zhang. -
Charles SchroederNeuronal oscillations reflecting synchronous, rhythmic fluctuation of neuron ensembles between high and low excitability states, dominate ambient activity in the sensory pathways. Because excitability determines the probability that neurons will respond to input, a top-down process like attention can use oscillations as "instruments" to amplify or suppress the brain's representation of external events. That is, by tuning the frequency and phase of its rhythms to those of behaviorally and/or cognitively-relevant event streams, the brain can use its rhythms to parse event streams and to form internal representations of them. In doing this, the brain is making temporal predictions. I will discuss findings from parallel experiments in humans and non-human primates that outline specific structural and functional components of this temporal prediction mechanism. I will also discuss its possible generalization across temporal scales. Finally, I will discuss motor system contributions to sensory systems' dynamics.
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Daniel ButtsIn addition to visual information from thalamus, neurons in primary visual cortex (V1) receive inputs from other V1 neurons, as well as from higher cortical areas. This “non-classical� input to V1 neurons, which can be inferred in part from the local field potential, can modulate the “classical� feed-forward responses of V1 neurons to visual stimuli. Using multielectrode recordings in awake primate, we can characterize this modulation in a variety of stimulus contexts. Because this network activity is by definition shared, it can serve to coordinate single neuron responses across a given region of cortex. Such network modulation plays a clear role during natural viewing, where saccadic eye movements result in stereotyped network activity. Thus these network influences to V1 neuron activity, which likely represent both coordinated processing within V1 and top-down influences, play a fundamental role in natural visual processing.
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Stephanie JonesLow frequency neocortical rhythms are among the most prominent activity measured in human brain imaging signals such as electro- and magneto-encephalography (EEG/MEG). Elucidating the role that these dynamics play in perception, cognition and action is a key challenge of modern neuroscience. We have recently combined human brain imaging, computational neural modeling, and electrophysiological recordings in rodents to explore the functional relevance and mechanistic underpinnings of rhythms in primary somatosensory cortex (SI), containing Alpha (7-14Hz) and Beta (15-29Hz) components. In this talk, I will review our findings showing this rhythm impacts tactile detection, changes with healthy aging and practice, and is modulated with attention. Constrained by the human imaging data, our biophysically principled computational modeling work has led to a novel prediction on the origin of this rhythm predicting that it emerges from the combination of two stochastic ~10 Hz thalamic drives to the granular/infragranular and supragranular cortical layers. Relative Alpha/Beta expression depends on the strength and delay between the thalamic drives. This model is able to accurately reproduce numerous key features of the human rhythm and proposes a specific mechanistic link between the Beta component of the rhythm and sensory perception. Further, initial electrophysiological recordings in rodents support out hypotheses and suggest a role for non-lemniscal pallidal thalamus in coordinating Beta rhythmicity, with relevance to understanding disrupt Beta in Parkinson's Disease.
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Jonathan PillowBarlow's "efficient coding hypothesis" asserts that neurons should maximize the information they convey about stimuli. This idea has provided a guiding theoretical framework for the study of coding in neural systems, and has sparked a great many studies of decorrelation and efficiency in early sensory areas. A more recent theory, the "Bayesian brain hypothesis", asserts that neural responses encode posterior distributions in order to support Bayesian inference.
However, these two theories have not yet been formally connected. In this talk, I will introduce a Bayesian theory of efficient coding, which has Barlow's framework as a special case. I will argue that there is nothing privileged about information-maximizing codes: they are ideal when one wishes minimize entropy, but they can be substantially suboptimal in other cases. Moreover, codes optimized for information transfer may differ strongly from codes optimized for other loss functions. Bayesian efficient coding substantially enlarges the family of normatively optimal codes and provides a general framework for understanding the principles of sensory encoding. I will derive Bayesian efficient codes for a few simple examples and show an application to neural data.
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Stephen BaccusPrinciples of Biological Design -
Stephanie PalmerSensory prediction in the natural world -
David GolombWe study why whiskers of land mammals are approximately conical by considering a tapered whisker under contact with an object. We convert the Euler-Bernoulli quasi-static equation into a boundary-value equation and analyze it using dynamical system theory. The equation has two solutions, one stable and one unstable, that coalesce in a saddle-node bifurcation. Beyond the bifurcation, the whisker slips-off. Slip-off does not occur for cylindrical hairs for realistic parameters. We suggest that slip-off events code radial distances of objects far from the whisker base. Experimental results show that conical whiskers can sweep pass textures in a series of stick-slip events, but cylindrical hairs are stuck. -
Fabrizio GabbianiUnderstanding how the brain processes sensory information in real-time to generate meaningful behaviors is one of the outstanding contemporary challenges of neuroscience. Visually guided collision avoidance behaviors are nearly universal in animals endowed with spatial vision and offer a favorable opportunity to address this question. This talk will summarize the current understanding of their generation at the level of neural networks, single neurons and their ion channels. The focus will be on a model system that has proven particularly suitable for this purpose, the locust brain, but will also tie the results learned in this preparation to studies carried out in a wide range of other species.
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Hermann RieckeThe olfactory bulb exhibits substantial turn-over of the dominant interneuron population, even in adult animals. It is observed that with neurogenesis suppressed the animals' capacity for perceptual learning is impaired. We have developed a simple network model in which the connectivity adapts to the odor environment through the experimentally observed dependence of the survival of the interneurons on their activity. Due to the reciprocity of the connections between the principal neurons and the interneurons this restructuring of the network allows it to reduce the correlation of the representations of similar stimuli.