The development of motor control over sensory organs is a critical milestone, enabling active exploration and shaping of the sensory environment. Whether the onset of sensory organ motor control directly influences the development of corresponding sensory cortices remains unknown. Here, we confirm and exploit the late onset of whisking behavior in mice to address this question in the somatosensory system. Using ex vivo electrophysiology, we describe a transient increase in the intrinsic excitability of excitatory neurons in layer IV of the barrel cortex, which processes whisker input, immediately following the onset of active whisking on postnatal days 13 and 14. This increase in neuronal gain is specific to layer IV, independent of changes in synaptic strength, and requires prior sensory experience. Further, these effects are not expressed in inhibitory interneurons in barrel cortex. The transient increase in excitability is not evident in layer II/III of barrel cortex or in the visual cortex upon eye ope...

Fiber photometry is a neuroscience technique that can continuously monitor in vivo fluorescence to assess population neural activity or neuropeptide/transmitter release in freely behaving animals. Despite the widespread adoption of this technique, methods to statistically analyze data in an unbiased, objective, and easily adopted manner are lacking. Various pipelines for data analysis exist, but they are often system specific, are only for preprocessing data, and/or lack usability. Current post hoc statistical approaches involve inadvertently biased user-defined time-binned averages or area under the curve analysis. To date, no post hoc user-friendly tool with few assumptions for a standardized unbiased analysis exists, yet such a tool would improve reproducibility and statistical reliability for all users. Hence, we have developed a user-friendly post hoc statistical analysis package in Python that is easily downloaded and applied to data from any fiber photometry system. This Fiber Photometry Post Hoc An...

Comparative analyses of locomotor behavior and cellular electrical properties between wild-type and mutant Caenorhabditis elegans are crucial for exploring the gene basis of behaviors and the underlying cellular mechanisms. Although many tools have been developed by research labs and companies, their application is often hindered by implementation difficulties or lack of features specifically suited for C. elegans . Our system addresses these challenges with three key components: WormTracker , SleepTracker , and Action Potential (AP) Analyzer . WormTracker accurately quantifies a comprehensive set of locomotor and body bending metrics, incorporates user-identified dorsal and ventral orientation based on microscopic observation, continuously tracks the animal using a motorized stage, and seamlessly integrates external devices, such as a light source for optogenetic stimulation. SleepTracker detects and quantifies sleep-like behavior in freely moving animals. AP Analyzer assesses the resting membrane potenti...

Material below summarizes the article Functional Connectome Analyses Reveal the Human Olfactory Network Organization, published on May 29, 2020, in eNeuro and authored by T. Campbell Arnold, Yuqi You, Mingzhou Ding, Xi-Nian Zuo, Ivan de Araujo and Wen Li. Highlights Smell is borne out of a network of interconnected regions that are distributed across the brain. The larger odor processing network consists of three smaller subnetworks, which serve different functional purposes. Segregation of subnetworks helps to insulate the different functions and facilitates olfactory perception.

The following is an excerpt from a commentary in the Journal of Neuroscience, Recognizing Team Science Contributions in Academic Hiring, Promotion, and Tenure, that originated from two Neuroscience 2019 Professional Development workshops (watch them here and here). Read the full commentary here. The vision of a scientist as a lone investigator reaching an epiphany is a widely cherished narrative. Consistent with this ideal, single author papers were frequent 50 years ago, when the Society for Neuroscience started. However, the basic and translational questions and the public health challenges being addressed in current neuroscience research are increasingly interdisciplinary and multidimensional, and so the vast majority of significant studies require a team of investigators, working together collaboratively. This trend is evident in the increased number of authors per citation and the rapid expansion of collaborative grants. Unfortunately, academic culture has not yet caught up with the direction of the science. Hiring, promotions, and peer review tend to credit the first and last authors, with little consideration that the work required an entire team. At the 2019 SfN annual meeting, there were two workshops addressing team science. One workshop highlighted the challenges in team science for trainees, while the other focused on ways in which academic leaders could change our procedures to address the disconnect between overly narrow attention to individual first and last authorship in hiring, promotion, and tenure versus the collaborative nature of current research. This Commentary distills the ideas and recommendations brought forth by these workshops, to advocate for changes in academic recognition.

Since I was a child, I’ve had two passions: science and storytelling. For the vast majority of my career, I’ve pursued the former. I majored in neuroscience at Smith College and went on to earn my doctorate at Northwestern University. I recently completed my postdoctoral training at Columbia and will soon open my independent laboratory in the Department of Physiology and Membrane Biology at the University of California Davis. Sounds like a typical climb up the academic ladder, right? Yet despite this traditional career trajectory, my passion for storytelling was ever-present. After nearly a decade as a scientist, I decided to combine it with my longstanding commitment to science education as a children’s book writer. My debut science adventure series, The Magnificent Makers, was recently published by Random House Children’s Books. As I delved into the world of writing for kids, I discovered four key aspects of my scientific training that were directly applicable to my journey as an author.

The history of Artificial Intelligence (AI) is inextricably intertwined with the history of neuroscience. Since the early days of AI, scientists turned to the human brain as a source of guidance for the development of intelligent machines. Unsurprisingly, many pioneers of AI such as Warren McCulloch were trained in the sciences of the brain. Modern AI borrowed most of its vocabulary from neurology and psychology. For instance, computational models consisting of networks of interconnected units —one of the most common approaches to AI— are called Artificial Neural Networks (ANN). Each unit is called an “artificial neuron.” Several areas of research in AI are labelled through neuropsychological categories such as computer vision, machine learning, natural language processing etc. It’s not just a matter of terminology. ANNs, for example, are actually inspired by and based on the functioning of biological neural networks that constitute animal nervous systems.

People often ask me, “Can you have it all?” I don’t know if you can, but I’m certainly having a good time trying. Here’s how.

Fiber photometry is a neuroscience technique that can continuously monitor in vivo fluorescence to assess population neural activity or neuropeptide/transmitter release in freely behaving animals. Despite the widespread adoption of this technique, methods to statistically analyse data in an unbiased, objective, and easily adopted manner are lacking. Various pipelines for data analysis exist, but they are often system-specific, only for pre-processing data, and/or lack usability. Current post hoc statistical approaches involve inadvertently biased user-defined time-binned averages or area under the curve analysis. To date, no post-hoc user-friendly tool with few assumptions for a standardised unbiased analysis exists, yet such a tool would improve reproducibility and statistical reliability for all users. Hence, we have developed a user-friendly post hoc statistical analysis package in Python that is easily downloaded and applied to data from any fiber photometry system. This Fi ber Pho tometry P ost H oc A...

The development of motor control over sensory organs is a critical milestone, enabling active exploration and shaping of the sensory environment. Whether the onset of sensory organ motor control directly influences the development of corresponding sensory cortices remains unknown. Here, we confirm and exploit the late onset of whisking behavior in mice to address this question in the somatosensory system. Using ex vivo electrophysiology, we describe a transient increase in the intrinsic excitability of excitatory neurons in layer IV of the barrel cortex, which processes whisker input, immediately following the onset of active whisking on postnatal days 13 and 14. This increase in neuronal gain is specific to layer IV, independent of changes in synaptic strength, and requires prior sensory experience. Further, these effects are not expressed in inhibitory interneurons in barrel cortex. The transient increase in excitability is not evident in layer II/III of barrel cortex or in the visual cortex upon eye ope...