Update blog/2023-year-in-review.md

Co-authored-by: Robert Gemma <[email protected]>

blog/2023-year-in-review.md

@@ -95,7 +95,7 @@ Alongside supporting Oscar for high-performance computing needs, CCVers provided
 In 2023, we supported 60 projects and collaborations throughout Brown. The following are some highlights from those projects.
 
 - We launched our first mobile applications: [**SOMA**](https://somatheapp.com/), an app focused on pain management, and [**MAPPS**](https://www.mappsproject.com/), an app designed to explore social interactions and their influence on disease transmission patterns.
-- [**Honeycomb**](https://brown-ccv.github.io/honeycomb-docs/), a template for reproducible psychological tasks for clinic, laboratory, and home use has undergone a significant upgrade and has released version 3.2.6.
+- [**Honeycomb**](https://brown-ccv.github.io/honeycomb-docs/) released versions 3.1 and 3.2 which better align the repository with [jsPsych](https://www.jspsych.org/7.3/) best practices.
 - [**Hierarchical Sequential Sampling Modeling (HSSM)**](https://lnccbrown.github.io/HSSM/) —a contemporary Python toolbox integrating cutting-edge likelihood approximation methods within the Python Bayesian ecosystem—was released on the Python Package Index (PyPI) in late June.
 - We developed and released two packages in Julia, a rising programming language in the data science space. [IceFlowTracker.jl](https://github.com/WilhelmusLab/IceFloeTracker.jl) was created in collaboration with the [Wilhelmus Lab](https://wilhelmuslab.me/) for tracking ice floes using moderate resolution imaging spectroradiometer (MODIS) data. [Chamber.jl](https://github.com/brown-ccv/Chamber.jl/tree/master) is a Julia package for simulating the eruption of a volcano using a model for the frequency of eruptions of upper crustal magma chambers based on Degruyter and Huber (2014).
 - We developed and released a versatile utility script to streamline data exports to Oscar, led two XNAT Workshops for the neuroimaging community, and contributed to the MNE-BIDS open-source project. Furthermore, we enhanced the xnat2bids pipeline to accommodate EEG and Physiological data, highlighting our collective commitment to optimizing neuroimaging workflows and fostering open-source collaboration.