Biology subjects

Winke, N.

Publications and source records attributed to Winke, N..

3 recordsLinked to original sources

bioRxiv2023

The geometry of appetitive-aversive value representations in medial prefrontal networks

The value of rewards and punishments - namely, how good or bad they are perceived - guides approach or avoidance behaviors. Valence refers to the negative or positive "sign" of the state elicited by an event, whereas salience refers to the amount of attention an event attracts, disregarding its valence. While identifying these signals conveys critical information for understanding circuits involved in emotional processing, they are often confounded due to their underlying correlation. Moreover, whereas the study of the neural basis of value coding has been intensively investigated in the appetitive domain, the neural substrates for how aversive values are established for different threat intensities and guide defensive behavior have yet to be discovered. The dorsomedial prefrontal cortex (dmPFC) is a key region in the control of defensive actions, although how different aversive values are encoded at the neuronal level within this region and drive defensive behaviors remains unknown. Here, we developed an instrumental approach/avoidance task in mice that, by matching motivational salience levels elicited by cues predicting rewards or punishments, allows univocally disentangling the presence of either salience, valence, or value coding from brain signals. We performed freely moving large neuronal population calcium imaging in the dmPFC of mice performing our task, conducting appetitive/aversive outcome devaluation/revaluation behavioral tests. We found that, while a similar fraction of single neurons decoded valence and value information, and only a minor fraction decoded salience, value coding was observed at the neuronal population level. Moreover, different value representations of the same valence lay within similar subspaces of the neural state space while values of opposed valence were encoded in orthogonal subspaces, unveiling how the brain stores associative appetitive and aversive information in medial prefrontal networks.

neuroscience↗

bioRxiv2022

Pyfiber: an open source python library that facilitates the merge of operant behavior and fiber photometry- focus on intravenous self-administration

BackgroundAdvances in in vivo fluorescent imaging have exploded with the recent developments of genetically encoded calcium indicators (GECIs) and fluorescent biosensors. Their use with a bulk imaging technique such as fiber photometry (FP) can be highly beneficial in identifying neuronal signatures in behavioral neuroscience experiments. Popularity of FP has grown rapidly. Initially applied to classical conditioning, its integration into operant behavior paradigms is progressing. However, in operant behavior, protocols can be complex including numerous scheduled events, while behavioral responses can occur in diverse and non-predictable manners. To optimize data processing and analysis, there is a need for a flexible tool to extract and relate behavioral and fiber photometry data occurring over operant sessions. New MethodApplied to cocaine intravenous self-administration (using Imetronic polymodal apparati) and FP recordings in the prelimbic cortex (using Doric Lenses photometry system) in the rat, we established Pyfiber, an outline and open source data analysis python library that facilitates the merge of fiber photometry (using Doric Lenses) with operant behavior (using Imetronic). It allows relating activity changes within a neuronal population to the various behavioral responses and events occurring during operant behavior. ResultsWe show some of the possibilities and benefits of the analytical tool Pyfiber, which helps to: 1. Extract the different types of events that occur in an operant session, 2. Extract and process the fiber photometry signals, 3. Select events of interest and align them to the corresponding fiber photometry signals, 4. Apply the most appropriate type of FP signal normalization and signal analysis according to the studied type of event or behavioral response, 5. Run data extraction and analysis on multiple individuals and sessions at the same time, 6. Collect results in an easily readable format for statistical analysis. From our data and through the use of Pyfiber, we show that we can successfully record and easily analyze calcium transients surrounding events occurring during a cocaine self-administration paradigm in the rat. Comparison with Existing Method(s)While other analytical tools can be used for streamlined fiber photometry analysis, they are either too rigid and specific or too flexible, requiring extensive coding to properly fit the data sets. Additionally, current tools do not permit easy exploration of multiple types of events in parallel- something that is possible with Pyfiber. ConclusionsThis work established an open source resource that facilitates the pairing of fiber photometry recordings (using Doric Lenses photometry system) with operant behavior (using Imetronic polymodal apparati), setting a solid foundation in analyzing the relationship between different dimensions of operant behavior with fluorescent signals from brain regions of interest.

neuroscience↗

bioRxiv2022

Brainstem somatostatin-expressing cells control the emotional regulation of pain behavior

In threatening situations, animals exhibit a broad range of behavioral and autonomic responses. As such, a crucial adaptive response is the inhibition of pain, which facilitates relevant defensive behaviors that promote survival. Whereas the structures and mechanisms involved in fear and pain behaviors are well documented, little is known about the precise neuronal mechanisms mediating the emotional regulation of endogenous pain-suppression. Here, we used a combination of behavioral, anatomical, optogenetic, and electrophysiological approaches to investigate, in male mice, the role of somatostatin-expressing cells in the ventrolateral periaqueductal gray matter (SST+ vlPAG cells) in the control of analgesia induced during defensive states. Our data indicate that optogenetic inhibition of SST+ vlPAG cells promotes analgesia irrespective of animal defensive state. In contrast, optogenetic activation of long-range SST+ vlPAG cells that project to the rostral ventromedial medulla (RVM) abolishes the analgesia mediated by fear behavior. Together, these results identify a novel circuit mechanism composed of long-range SST+ vlPAG cells projecting to the RVM that regulate analgesia elicited during defensive states.

neuroscience↗