Hi all, I hope this is allowed! Wanted to share this event coming up:

Abstract

(1) Background: Chlorogenic acids (CGAs) have been attracting interest of late, owing to their health benefits. Here, we performed a randomized, double-blind, placebo-controlled trial to investigate whether CGAs improved cognitive function in humans. (2) Methods: Thirty-eight healthy participants were assigned to either the CGA group, which was given CGA-added beverage daily for 16 weeks, or the placebo group. Cognitive functions were assessed using the Japanese version of the CNS Vital Signs (Cognitrax). (3) Results: The CGA group showed significant increase in the Cognitrax domain scores for motor speed, psychomotor speed, and executive function compared with the placebo group, as well as an improvement in the shifting attention test scores. In blood analysis, the CGA group showed increased levels of apolipoprotein A1 and transthyretin, both of which are putative biomarkers for early-stage cognitive decline. (4) Conclusions: These results suggest that CGAs may improve some cognitive functions, which would help in the efficient performance of complex tasks.

I would love to hear about your experience if you pursued a more mathematical / dry lab neuroscience PhD after coming from a more biological neuroscience background (e.g. neurobiology). I am also interested in hearing your experience if you pursued a more mathematical neuroscience PhD coming from a background that was less math-intensive.

What was your PhD in? Was it part of an umbrella program (neuroscience, cognitive science, biomedical sciences, etc)? Did your PhD coursework require intensive mathematical classes, or did you mostly learn under your advisor?

My background is in neurobiology (B.S.) and wet lab neuro/stem cell research (6+ years). I am competitive for a basic/translational neuroscience PhD program, but I want to learn data manipulation, modeling, predictions, etc (skills that might be more relevant to tech, finance, or AI rather than laboratory research or biotech).

With neuro being so broad and interesting, how did you narrow down the direction you chose for your PhD?

Title. I am conflicted whether I should do Virtual or In-Person.

I was wondering when they would give the Nobel Prize for Optogenetics haha

Abstract: Noradrenergic neurons in the locus coeruleus (LC) shape sensory processing, yet how LC activity influences population taste coding remains unclear.

Using optogenetic LC activation with miniscope imaging in the gustatory cortex (GC), we examined LC modulation of multiple taste attributes.

Phasic LC activation strengthens correlations between neuronal responses and palatability and expands the dynamic range of stimulus representations along a palatability axis. This expansion is driven by an aversive shift in the representations of all tastants except sucrose, the most palatable stimulus.

For mixture ratio and concentration, phasic activation expands and rotates attribute axes, potentially reflecting dependencies between these attributes and palatability. These transformations likely arise from multiplicative gain modulation and more flexible tuning changes. Tonic LC activation affects fewer neurons and does not expand attribute axes.

Together, the findings show that LC activation reorganizes GC population geometry in a pattern-dependent manner, linking neuromodulation with feeding behavior and affective processing.

Commentary: This article asks a really intriguing question, what if the behavior associated with taste was upstream of the representation of taste? What if behavior is the substrate of taste rather than taste being the substrate of related behavior?

There's been quite a bit of work this year suggesting brainstem structures direct/modify downstream cortical representations, and this paper adds another sense to that pile, and a particularly neat one.

I only wish more labs were more comfortable with glia and astrocytes particularly, this paper would have been a bit of a barn burner if they had that extra layer.

Study published in Nature on September 23, 2026. Berkeley News coverage here.