scholarly journals Author response: Mechanisms underlying sharpening of visual response dynamics with familiarity

2019 ◽  
Author(s):  
Sukbin Lim
2015 ◽  
Author(s):  
Nicolás Peláez ◽  
Arnau Gavalda-Miralles ◽  
Bao Wang ◽  
Heliodoro Tejedor Navarro ◽  
Herman Gudjonson ◽  
...  

2020 ◽  
Author(s):  
Paul B Dieterle ◽  
Jiseon Min ◽  
Daniel Irimia ◽  
Ariel Amir

2020 ◽  
Author(s):  
Michaël E Belloy ◽  
Jacob Billings ◽  
Anzar Abbas ◽  
Amrit Kashyap ◽  
Wen-Ju Pan ◽  
...  

Abstract How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional magnetic resonance imaging to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) are the most prominent component of mouse resting brain dynamics. These QPPs captured the temporal alignment of anticorrelation between the default mode (DMN)- and task-positive (TPN)-like networks, with global brain fluctuations, and activity in neuromodulatory nuclei of the reticular formation. Specifically, the phase of QPPs prior to stimulation could significantly stratify subsequent visual response magnitude, suggesting QPPs relate to brain state fluctuations. This is the first observation in mice that dynamics of the DMN- and TPN-like networks, and particularly their anticorrelation, capture a brain state dynamic that affects sensory processing. Interestingly, QPPs also displayed transient onset response properties during visual stimulation, which covaried with deactivations in the reticular formation. We conclude that QPPs appear to capture a brain state fluctuation that may be orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.


2020 ◽  
Author(s):  
Rolando Ruiz-Vega ◽  
Chi-Fen Chen ◽  
Emaad Razzak ◽  
Priya Vasudeva ◽  
Tatiana B Krasieva ◽  
...  

2020 ◽  
Author(s):  
Jennifer L Fribourgh ◽  
Ashutosh Srivastava ◽  
Colby R Sandate ◽  
Alicia K Michael ◽  
Peter L Hsu ◽  
...  

2017 ◽  
Author(s):  
Autumn P Pomreinke ◽  
Gary H Soh ◽  
Katherine W Rogers ◽  
Jennifer K Bergmann ◽  
Alexander J Bläßle ◽  
...  

2017 ◽  
Author(s):  
Alexander Chien ◽  
Sheng Min Shih ◽  
Raqual Bower ◽  
Douglas Tritschler ◽  
Mary E Porter ◽  
...  

Author(s):  
Yaara Y Columbus-Shenkar ◽  
Maria Y Sachkova ◽  
Jason Macrander ◽  
Arie Fridrich ◽  
Vengamanaidu Modepalli ◽  
...  

2018 ◽  
Author(s):  
Sarah Adio ◽  
Heena Sharma ◽  
Tamara Senyushkina ◽  
Prajwal Karki ◽  
Cristina Maracci ◽  
...  

2019 ◽  
Author(s):  
Caterina Trainito ◽  
Constantin von Nicolai ◽  
Earl K. Miller ◽  
Markus Siegel

SummaryUnderstanding the function of different neuronal cell types is key to understanding brain function. However, cell type diversity is typically overlooked in electrophysiological studies in awake behaving animals. Here, we show that four functionally distinct cell classes can be robustly identified from extracellular recordings in several cortical regions of awake behaving monkeys. We recorded extracellular spiking activity from dorsolateral prefrontal cortex (dlPFC), the frontal eye field (FEF), and the lateral intraparietal area of macaque monkeys during a visuomotor decision-making task. We employed unsupervised clustering of spike waveforms, which robustly dissociated four distinct cell classes across all three brain regions. The four cell classes were functionally distinct. They showed different baseline firing statistics, visual response dynamics, and coding of visual information. While cell class-specific baseline statistics were consistent across brain regions, response dynamics and information coding were regionally specific. Our results identify four waveform-based cell classes in primate cortex. This opens a new window to dissect and study the cell-type specific function of cortical circuits.


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