The combined development of new technologies for neuronal recordings and the development of novel sensors for recording both cellular activity and neurotransmitter binding has ushered in a new era for the field of neuroscience. Among these new technologies is fiber photometry, a technique wherein an implanted fiber optic is used to record signals from genetically encoded fluorescent sensors in bulk tissue. Fiber photometry has been widely adapted due to its costeffectiveness, ability to examine the activity of neurons with specific anatomical or genetic identities, and the ability to use these highly modular systems to record from one or more sensors or brain sites in both superficial and deep-brain structures. Despite these many benefits, one major hurdle for laboratories adopting this technique is the steep learning curve associated with the analysis of fiber photometry data. This has been further complicated by a lack of standardization in analysis pipelines. In the present communication, we present pMAT, a 'photometry modular analysis tool' that allows users to accomplish common analysis routines through the use of a graphical user interface. This tool can be deployed in MATLAB and edited by more advanced users, but is also available as an independently deployable, open-source application.
The combined development of new technologies for neuronal recordings and the development of novel sensors for recording both cellular activity and neurotransmitter binding has ushered in a new era for the field of neuroscience. Among these new technologies is fiber photometry, a technique wherein an implanted fiber optic is used to record signals from genetically encoded fluorescent sensors in bulk tissue. Fiber photometry has been widely adapted due to its cost-effectiveness, ability to examine the activity of neurons with specific anatomical or genetic identities, and the ability to use these highly modular systems to record from one or more sensors or brain sites in both superficial and deep-brain structures. Despite these many benefits, one major hurdle for laboratories adopting this technique is the steep learning curve associated with the analysis of fiber photometry data. This has been further complicated by a lack of standardization in analysis pipelines. In the present communication, we present pMAT, a ‘photometry modular analysis tool’ that allows users to accomplish common analysis routines through the use of a graphical user interface. This tool can be deployed in MATLAB and edited by more advanced users, but is also available as an independently deployable, open-source application.
Mu opioid receptor (MOR) agonists are potent analgesics, but also cause sedation, respiratory depression, and addiction risk. The epithalamic lateral habenula (LHb) signals aversive states including pain, and here we found that it is a potent site for MOR-agonist analgesia-like responses in rats. Importantly, LHb MOR activation is not reinforcing in the absence of noxious input. The LHb receives excitatory inputs from multiple sites including the ventral tegmental area, lateral hypothalamus, entopeduncular nucleus, and the lateral preoptic area of the hypothalamus (LPO). Here we report that LHb-projecting glutamatergic LPO neurons are excited by noxious stimulation and are preferentially inhibited by MOR selective agonists. Critically, optogenetic stimulation of LHb-projecting LPO neurons produces an aversive state that is relieved by LHb MOR activation, and optogenetic inhibition of LHb-projecting LPO neurons relieves the aversiveness of ongoing pain.
Mu opioid receptor (MOR) agonists are the most effective analgesics, but their use risks respiratory depression and addiction. The epithalamic lateral habenula (LHb) is a critical site that signals aversive states, often via indirect inhibition of reward circuitry, and MORs are highly expressed in the LHb. We found that the LHb is a potent site for MOR-agonist analgesia. Strikingly, LHb MOR activation generates negative reinforcement but is not rewarding in the absence of noxious input. While the LHb receives inputs from multiple sites, we found that inputs from the lateral preoptic area of the hypothalamus (LPO) are excited by noxious stimulation, express MOR mRNA, and are preferentially targeted by MOR selective agonists. Critically, optogenetic stimulation of LHb-projecting LPO neurons produces an aversive state relieved by LHb MOR activation. Therefore targeting this MOR sensitive forebrain circuit can relieve pain yet lower the risk of misuse by pain free individuals.
Susceptibility to stress has long been considered important for the development of substance use disorders. Nonetheless, behavioral and physiological responses to stress are highly variable, making it difficult to identify the individuals who are most likely to abuse drugs. In the present study, we employed a comprehensive battery of tests for negative valence behaviors and nociception to identify individuals predisposed to opioid seeking following oral opioid self‐administration. Furthermore, we examined how this profile was affected by a history of stress. We observed that mice receiving foot shock stress failed to exhibit a preference for sucrose, showed increased immobility in the forced swim task, and exhibited mechanical hypersensitivity when compared to controls. When considering these behaviors in light of future fentanyl‐seeking responses, we observed that heightened mechanical sensitivity corresponded to higher opioid preference in mice with a history of stress, but not controls. Moreover, we were surprised to discover that paradoxically high sucrose preferences predicted fentanyl preference in shock mice, while signs of anhedonia predicted fentanyl preference in controls. Taken together, these results indicate that stress can act as a physiological modulator, shifting profiles of opioid abuse susceptibility depending on an individual's history.
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