Biology subjects

Kaufman, M.

Publications and source records attributed to Kaufman, M..

3 recordsLinked to original sources

bioRxiv2018

Dynamics of social representation in the mouse prefrontal cortex

The prefrontal cortex (PFC) plays an important role in regulating social functions in mammals, and impairments in this region have been linked with social dysfunction in psychiatric disorders. Yet little is known of how the PFC encodes social information and of how social representations may be altered in such disorders. Here, we show that neurons in the medial PFC (mPFC) of freely behaving mice preferentially respond to socially-relevant sensory cues. Population activity patterns in the mPFC differed considerably between social and nonsocial stimuli and underwent experience-dependent refinement. In Cntnap2 knockout mice, a genetic model of autism, both the categorization of sensory stimuli and the refinement of social representations were impaired. Noise levels in spontaneous population activity were higher in Cntnap2 mice, and correlated strongly with the degree to which social representations were disrupted. Our findings elucidate the encoding of social sensory cues in the mPFC, and provide an important link between altered prefrontal dynamics and autism-associated social dysfunction.

neuroscience↗

bioRxiv2017

Accurate estimation of neural population dynamics without spike sorting

A central goal of systems neuroscience is to relate an organisms neural activity to behavior. Neural population analysis often begins by reducing the dimensionality of the data to focus on the patterns most relevant to a given task. A major practical hurdle to data analysis is spike sorting, and this problem is growing rapidly as the number of neurons measured increases. Here, we investigate whether spike sorting is necessary to estimate neural dynamics. The theory of random projections suggests that we can accurately estimate the geometry of low-dimensional manifolds from a small number of linear projections of the data. We re-analyzed data from three previous studies and found that neural dynamics and scientific conclusions are quite similar using multi-unit threshold crossings in place of sorted neurons. This finding unlocks existing data for new analyses and informs the design and use of new electrode arrays for laboratory and clinical use.

neuroscience↗

bioRxiv2017

OnACID: Online Analysis of Calcium Imaging Data in Real Time

Optical imaging methods using calcium indicators are critical for monitoring the activity of large neuronal populations in vivo. Imaging experiments typically generate a large amount of data that needs to be processed to extract the activity of the imaged neuronal sources. While deriving such processing algorithms is an active area of research, most existing methods require the processing of large amounts of data at a time, rendering them vulnerable to the volume of the recorded data, and preventing realtime experimental interrogation. Here we introduce OnACID, an Online framework for the Analysis of streaming Calcium Imaging Data, including i) motion artifact correction, ii) neuronal source extraction, and iii) activity denoising and deconvolution. Our approach combines and extends previous work on online dictionary learning and calcium imaging data analysis, to deliver an automated pipeline that can discover and track the activity of hundreds of cells in real time, thereby enabling new types of closed-loop experiments. We apply our algorithm on two large scale experimental datasets, benchmark its performance on manually annotated data, and show that it outperforms a popular offline approach.

neuroscience↗