Two-Photon Imaging of Neural Activity in Awake, Head-Restrained Mice

Author(s):  
Martin Wienisch ◽  
David G. Blauvelt ◽  
Tomokazu F. Sato ◽  
Venkatesh N. Murthy
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Min Chen ◽  
Hongjun Tian ◽  
Guoyong Huang ◽  
Tao Fang ◽  
Xiaodong Lin ◽  
...  

AbstractBrain pathological features during manic/hypomanic and depressive episodes in the same patients with bipolar disorder (BPD) have not been described precisely. The study aimed to investigate depressive and manic-phase-specific brain neural activity patterns of BPD in the same murine model to provide information guiding investigation of the mechanism of phase switching and tailored prevention and treatment for patients with BPD. In vivo two-photon imaging was used to observe brain activity alterations in the depressive and manic phases in the same murine model of BPD. Two-photon imaging showed significantly reduced Ca2+ activity in temporal cortex pyramidal neurons in the depression phase in mice exposed to chronic unpredictable mild stress (CUMS), but not in the manic phase in mice exposed to CUMS and ketamine. Total integrated calcium values correlated significantly with immobility times. Brain Ca2+ hypoactivity was observed in the depression and manic phases in the same mice exposed to CUMS and ketamine relative to naïve controls. The novel object recognition preference ratio correlated negatively with the immobility time in the depression phase and the total distance traveled in the manic phase. With recognition of its limitations, this study revealed brain neural activity impairment indicating that intrinsic emotional network disturbance is a mechanism of BPD and that brain neural activity is associated with cognitive impairment in the depressive and manic phases of this disorder. These findings are consistent with those from macro-imaging studies of patients with BPD. The observed correlation of brain neural activity with the severity of depressive, but not manic, symptoms need to be investigated further.


2018 ◽  
Author(s):  
Simon Musall ◽  
Matthew T. Kaufman ◽  
Ashley L. Juavinett ◽  
Steven Gluf ◽  
Anne K. Churchland

When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks focus on cognitive computations and specific task-related movements. We wondered whether task-performing animals explore a broader movement landscape, and how this impacts neural activity. We characterized movements using video and other sensors and measured neural activity using widefield and two-photon imaging. Cortex-wide activity was dominated by movements, especially uninstructed movements, reflecting unknown priorities of the animal. Some uninstructed movements were aligned to trial events. Accounting for them revealed that neurons with similar trial-averaged activity often reflected utterly different combinations of cognitive and movement variables. Other movements occurred idiosyncratically, accounting for trial-by-trial fluctuations that are often considered “noise”. This held true for extracellular Neuropixels recordings in cortical and subcortical areas. Our observations argue that animals execute expert decisions while performing richly varied, uninstructed movements that profoundly shape neural activity.


2018 ◽  
Author(s):  
Luke E. Rogerson ◽  
Zhijian Zhao ◽  
Katrin Franke ◽  
Philipp Berens ◽  
Thomas Euler

AbstractVariability, stochastic or otherwise, is a central feature of neural circuits. Yet the means by which variation and uncertainty are derived from noisy observations of neural activity is often unprincipled, with too much weight placed on numerical convenience at the cost of statistical rigour. For two-photon imaging data, composed of fundamentally probabilistic streams of photon detections, the problem is particularly acute. Here, we present a complete statistical pipeline for the inference and analysis of neural activity using Gaussian Process Regression, applied to two-photon recordings of light-driven activity in ex vivo mouse retina. We demonstrate the flexibility and extensibility of these models, considering cases with non-stationary statistics, driven by complex parametric stimuli, in signal discrimination, hierarchical clustering and inference tasks. Sparse approximation methods allow these models to be fitted rapidly, permitting them to actively guiding the design of light stimulation in the midst of ongoing two-photon experiments.


Author(s):  
David J. Margolis ◽  
Henry Lütcke ◽  
Fritjof Helmchen ◽  
Bruno Weber ◽  
Florent Haiss

2014 ◽  
Vol 2014 (7) ◽  
pp. pdb.top081810-pdb.top081810 ◽  
Author(s):  
D. Dombeck ◽  
D. Tank

2016 ◽  
Vol 271 ◽  
pp. 55-64 ◽  
Author(s):  
Thom P. Santisakultarm ◽  
Calvin J. Kersbergen ◽  
Daryl K. Bandy ◽  
David C. Ide ◽  
Sang-Ho Choi ◽  
...  

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