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4 Janelia Publications

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    06/26/19 | High-dimensional geometry of population responses in visual cortex.
    Stringer C, Pachitariu M, Steinmetz NA, Carandini M, Harris KD
    Nature. 2019 Jun 26;571(7765):361-65. doi: 10.1038/s41586-019-1346-5

    A neuronal population encodes information most efficiently when its activity is uncorrelated and high-dimensional, and most robustly when its activity is correlated and lower-dimensional. Here, we analyzed the correlation structure of natural image coding, in large visual cortical populations recorded from awake mice. Evoked population activity was high dimensional, with correlations obeying an unexpected power-law: the n-th principal component variance scaled as 1/n. This was not inherited from the 1/f spectrum of natural images, because it persisted after stimulus whitening. We proved mathematically that the variance spectrum must decay at least this fast if a population code is smooth, i.e. if small changes in input cannot dominate population activity. The theory also predicts larger power-law exponents for lower-dimensional stimulus ensembles, which we validated experimentally. These results suggest that coding smoothness represents a fundamental constraint governing correlations in neural population codes.

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    04/19/19 | Spontaneous behaviors drive multidimensional, brain-wide population activity.
    Stringer C, Pachitariu M, Steinmetz NA, Reddy CB, Carandini M, Harris KD
    Science. 2019 Apr 18;364(6437):255. doi: 10.1101/306019

    Sensory cortices are active in the absence of external sensory stimuli. To understand the nature of this ongoing activity, we used two-photon calcium imaging to record from over 10,000 neurons in the visual cortex of mice awake in darkness while monitoring their behavior videographically. Ongoing population activity was multidimensional, exhibiting at least 100 significant dimensions, some of which were related to the spontaneous behaviors of the mice. The largest single dimension was correlated with the running speed and pupil area, while a 16-dimensional summary of orofacial behaviors could predict ~45% of the explainable neural variance. Electrophysiological recordings with 8 simultaneous Neuropixels probes revealed a similar encoding of high-dimensional orofacial behaviors across multiple forebrain regions. Representation of motor variables continued uninterrupted during visual stimulus presentation, occupying dimensions nearly orthogonal to the stimulus responses. Our results show that a multidimensional representation of motor state is encoded across the forebrain, and is integrated with visual input by neuronal populations in primary visual cortex.

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    04/04/19 | Thirst regulates motivated behavior through modulation of brainwide neural population dynamics.
    Allen WE, Chen MZ, Pichamoorthy N, Tien RH, Pachitariu M, Luo L, Deisseroth K
    Science. 2019 Apr 04;364(6437):253. doi: 10.1126/science.aav3932

    Physiological needs produce motivational drives, such as thirst and hunger, that regulate behaviors essential to survival. Hypothalamic neurons sense these needs and must coordinate relevant brainwide neuronal activity to produce the appropriate behavior. We studied dynamics from ~24,000 neurons in 34 brain regions during thirst-motivated choice behavior, as mice consumed water and became sated. Water-predicting sensory cues elicited activity that rapidly spread throughout the brain of thirsty animals. These dynamics were gated by a brainwide mode of population activity that encoded motivational state. Focal optogenetic activation of hypothalamic thirst-sensing neurons, after satiation, returned global activity to the pre-satiation state. Thus, motivational states specify initial conditions determining how a brainwide dynamical system transforms sensory input into behavioral output.

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    04/01/19 | Computational processing of neural recordings from calcium imaging data.
    Stringer C, Pachitariu M
    Current Opinion in Neurobiology. 2019 Apr ;55:22-31. doi: 10.1016/j.conb.2018.11.005

    Electrophysiology has long been the workhorse of neuroscience, allowing scientists to record with millisecond precision the action potentials generated by neurons in vivo. Recently, calcium imaging of fluorescent indicators has emerged as a powerful alternative. This technique has its own strengths and weaknesses and unique data processing problems and interpretation confounds. Here we review the computational methods that convert raw calcium movies to estimates of single neuron spike times with minimal human supervision. By computationally addressing the weaknesses of calcium imaging, these methods hold the promise of significantly improving data quality. We also introduce a new metric to evaluate the output of these processing pipelines, which is based on the cluster isolation distance routinely used in electrophysiology.

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