Haploinsufficiency of the Parkinson's disease gene synaptojanin1 is associated with abnormal responses to psychomotor stimulants and mesolimbic dopamine signaling.

The synaptojanin-1 (SYNJ1) gene is known to be important for dopamine-related disorders. Recent evidence has demonstrated that Synj1 deficient mice (Synj1 +/-) have impairments in dopaminergic synaptic vesicular recycling. However, less is known about how Synj1 deficits affect the mesolimbic system, reward processing, and motivated behavior. To examine the role of the Synj1 gene in motivated behavior, we subjected male and female Synj1 +/- and Synj1 +/+ mice to a battery of behavioral tests evaluating hedonic responses, effortful responding, and responses to psychomotor stimulants. We observed that Synj1 +/- mice exhibit few differences in reward processing and motivated behavior, with normal hedonic responses and motivated responding for sucrose. However, male but not female Synj1 +/- demonstrated an attenuated conditioned place preference for cocaine that could not be attributed to deficits in spatial memory. To further understand the dopamine signaling underlying the attenuated response to cocaine in these mutant mice, we recorded nucleus accumbens dopamine in response to cocaine and observed that Synj1 +/- male and female mice took longer to reach peak dopamine release following experimenter-administered cocaine. However, female mice also showed slower decay in accumbens dopamine that appear to be linked to differences in cocaine-induced DAT responses. These findings demonstrate that SYNJ1 deficiencies result in abnormal mesolimbic DA signaling which has not previously been demonstrated. Our work also highlights the need to develop targeted therapeutics capable of restoring deficits in DAT function, which may be effective for reversing the pathologies associated with Synj1 mutations.

pMAT: An open-source software suite for the analysis of fiber photometry data.

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.