A judgment of the relative value of options is required for learning through affective responses. This kind of learning regards experiences as having a positive or negative valence (e.g., pleasure or fear, respectively).
Learning these valence-based responses1,2 has been linked to a cluster of neurons known as the striatum in the subcortical basal ganglia by several studies.
The striatum is a key part of the brain’s motivation and movement control system and has been associated with a range of neurological diseases, including Huntington’s disease (HD) and Parkinson’s disease.
The striatum is organized into neurochemically distinct compartments and is composed of multiple neuronal phenotypes and researchers are just beginning to unravel its complexity. The compartments are embedded in a larger surrounding matrix compartment and present as pockets of striosomes.
Striosomes mediate value-based learning vulnerable in age and a huntington's disease model
Well trained subjects have been used in studies that have implicated striosomes in cost-benefit conflict decision making and in reinforcement-related updating paradigms.
Because of this, it is not clear how striosomes will perform in the naïve process of learning decision making under potentially rewarding and costly outcomes.
A team of researchers from Stanford University, Harvard and the Massachusetts Institute of Technology has tracked the activity of striatal microcircuits interconnecting striosomes and has investigated the neurobiology of decision-making for valence-discrimination learning across healthy aging and in a murine model of HD.
It was found, in a study by Friedman et al., that learning signals in striosomes decline in neurodegenerative disorders and during aging but will scale according to subjective value.
There is evidence offered by this study to suggest a mechanistic cause in order to explain how motivation to maintain engagement and learn new tasks may be negatively correlated with age.
Mice were played two different tones in a series of experiments. In one experiment, the tone was coupled with a rewarding delivery of sucrose, while in the other, the tone was coupled with an aversive bright light.
Mice learned through daily training that decreased licking of a particular spout during one tone would result in receiving less averse light intensity while licking the spout when hearing the other tone would result in more reward.
Researchers observed that as mice learned the task, their striosome signals underwent selective modification; their amplitude increased while their frequency declined.
This same activity was not recorded in the matrix, suggesting that discrimination learning shapes ribosomal activity. It was revealed in subsequent experimentation that encoding discrimination levels during learning was primarily caused by striosomes.
This indicated that it was not matrix signal levels but striosomal signals that are sensitive to task engagement and therefore correspond to subjective value.
In order to investigate causality, the researchers employed chemogenetic methods.
In order to be able to modulate specific neuronal activity through the DREADDS ligans, clozapine-N-oxide (CNO), the researchers selectively expressed designer receptors exclusively activated by designer drugs (DREADDS) in striosomal and matrix neurons.
The stimulation of inhibitory DREADDS on striosomes caused mice to exhibit a decrease in task engagement and additionally reduced striosomal activity (as measured through Ca2+ transients).
The same effect was not observed when the same inhibitory manipulation was done in the matrix population. However, when excitatory DREADDS on striosomes were stimulated, greater task engagement was observed.
When excitatory matrix populations were stimulated, the same effect was not observed. Taking this evidence together, researchers demonstrated that it is not matrix populations but striosomal populations that drive task engagement.
The experiments outlined above were supported by TissueGnostics, a solution provider for Precision Medicine / Next-Generation Digital Pathology. This was done through their fully integrated, cutting-edge tissue cytometers.
To tag and characterize striatal compartments following the generation of mouse lines (Mash1/Dlx1 and D1/D2-GFP), straining was performed on tissue from the offspring.
The quadruple protein stains (VGLUT1/PV/MOR1) and triple protein stains (mHTT/GFP/PV and GFP/mCherry/MOR1) were captured used the TissueFAXS SL Q+ high-end confocal Slide Loader system (automatic acquisition of up to 120 slides) from TissueGnostics.
The TissueGnostics’ spinning disc confocal technology with slide autoloader made this particular system’s high thoroughput, tiled confocal imaging possible.
Initial imaging of the dorsal central striatum allowed researchers to trace and select regions of interest for acquisition.
Researchers were able to automatically calculate a maximum projection by using the extended focus option. Images were validated for focus quality following acquisition.
A high level of digital slide sharpness is ensured by TissueGnostics Slide Validator technology. Sharpness is evaluated during the scan process for each scanned field of view (FOV).
The FOV will be rescanned on-the-fly if the validation algorithm deems it insufficiently sharp.
The Tissue FAXS Whole Slide Scanning System was used to collect all images of staining conducted in the DREADD experiments.
This system is available through the TissueFAXS system, a whole slide imaging tissue cytometer with brightfield imaging capability and multichannel fluorescence.
The autofocus algorithm and motorized stage were used to achieve high-throughput, tiled epifluorescence imaging.
The researchers used the standard configuration (8 slide capacity) to produce a 2.5x preview scan of all slides, allowing them to trace and select regions of interest in the dorsal central striatum for acquisition in higher resolution.
As above, images were validated for focus quality once acquisition was finished.
The drawing of causal links between striosomal activity and not matrix activity, modulating task engagement through DREADDS by Friedman et al. was facilitated by TissueGnostics’ instruments.
The utility of TissueGnostics instruments and technology is demonstrated by this experiment. However, they also offer a broader range of products covering an ever wider variety of applications.
- Berridge, K.C. (2019) Affective valence in the brain: modules or modes? Nature Reviews Neuroscience, 20 (4): 225–234. doi:10.1117/12.2549369.Hyperspectral.
- Perosa, V., De Boer, L., Ziegler, G., et al. (2020) The Role of the Striatum in Learning to Orthogonalize Action and Valence: A Combined PET and 7 T MRI Aging Study. Cerebral Cortex, 00 (00): 1–12. doi:10.1093/cercor/bhz313.
TissueGnostics (TG) is an Austrian company focusing on integrated solutions for high content and/or high throughput scanning and analysis of biomedical, veterinary, natural sciences, and technical microscopy samples.
TG has been founded by scientists from the Vienna University Hospital (AKH) in 2003. It is now a globally active company with subsidiaries in the EU, the USA, and China, and customers in 30 countries.
TG scanning systems are currently based on versatile automated microscopy systems with or without image analysis capabilities. We strive to provide cutting-edge technology solutions, such as multispectral imaging and context-based image analysis as well as established features like Z-Stacking and Extended Focus. This is combined with a strong emphasis on automation, ease of use of all solutions, and the production of publication-ready data.
The TG systems offer integrated workflows, i.e. scan and analysis, for digital slides or images of tissue sections, Tissue Microarrays (TMA), cell culture monolayers, smears, and other samples on slides and oversized slides, in Microtiter plates, Petri dishes and specialized sample containers. TG also provides dedicated workflows for FISH, CISH, and other dot structures.
TG analysis software apart from being integrated into full systems is fully standalone capable and supports a wide variety of scanner image formats as well as digital images taken with any microscope.
TG also provides routine hematology scanning and analysis systems for peripheral blood, bone marrow, and body fluids.
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