Unraveling the mechanisms of deep-brain stimulation of the internal capsule in a mouse model.

Deep-brain stimulation (DBS) is an effective treatment for patients suffering from otherwise therapy-resistant psychiatric disorders, including obsessive-compulsive disorder. Modulation of cortico-striatal circuits has been suggested as a mechanism of action. To gain mechanistic insight, we monitored neuronal activity in cortico-striatal regions in a mouse model for compulsive behavior, while systematically varying clinically-relevant parameters of internal-capsule DBS. DBS showed dose-dependent effects on both brain and behavior: An increasing, yet balanced, number of excited and inhibited neurons was recruited, scattered throughout cortico-striatal regions, while excessive grooming decreased. Such neuronal recruitment did not alter basic brain function such as resting-state activity, and only occurred in awake animals, indicating a dependency on network activity. In addition to these widespread effects, we observed specific involvement of the medial orbitofrontal cortex in therapeutic outcomes, which was corroborated by optogenetic stimulation. Together, our findings provide mechanistic insight into how DBS exerts its therapeutic effects on compulsive behaviors.

Nucleus accumbens dopamine tracks aversive stimulus duration and prediction but not value or prediction error.

There is active debate on the role of dopamine in processing aversive stimuli, where inferred roles range from no involvement at all, to signaling an aversive prediction error (APE). Here, we systematically investigate dopamine release in the nucleus accumbens core (NAC), which is closely linked to reward prediction errors, in rats exposed to white noise (WN, a versatile, underutilized, aversive stimulus) and its predictive cues. Both induced a negative dopamine ramp, followed by slow signal recovery upon stimulus cessation. In contrast to reward conditioning, this dopamine signal was unaffected by WN value, context valence, or probabilistic contingencies, and the WN dopamine response shifted only partially toward its predictive cue. However, unpredicted WN provoked slower post-stimulus signal recovery than predicted WN. Despite differing signal qualities, dopamine responses to simultaneous presentation of rewarding and aversive stimuli were additive. Together, our findings demonstrate that instead of an APE, NAC dopamine primarily tracks prediction and duration of aversive events.

SpecSeg is a versatile toolbox that segments neurons and neurites in chronic calcium imaging datasets based on low-frequency cross-spectral power.

Imaging calcium signals in neurons of animals using single- or multi-photon microscopy facilitates the study of coding in large neural populations. Such experiments produce massive datasets requiring powerful methods to extract responses from hundreds of neurons. We present SpecSeg, an open-source toolbox for (1) segmentation of regions of interest (ROIs) representing neuronal structures, (2) inspection and manual editing of ROIs, (3) neuropil correction and signal extraction, and (4) matching of ROIs in sequential recordings. ROI segmentation in SpecSeg is based on temporal cross-correlations of low-frequency components derived by Fourier analysis of each pixel with its neighbors. The approach is user-friendly, intuitive, and insightful and enables ROI detection around neurons or neurites. It works for single- (miniscope) and multi-photon microscopy data, eliminating the need for separate toolboxes. SpecSeg thus provides an efficient and versatile approach for analyzing calcium responses in neuronal structures imaged over prolonged periods of time.

Invasive and Non-invasive Neurostimulation for OCD.

It becomes increasingly clear that (non-)invasive neurostimulation is an effective treatment for obsessive-compulsive disorder (OCD). In this chapter we review the available evidence on techniques and targets, clinical results including a meta-analysis, mechanisms of action, and animal research. We focus on deep brain stimulation (DBS), but also cover non-invasive neurostimulation including transcranial magnetic stimulation (TMS). Data shows that most DBS studies target the ventral capsule/ventral striatum (VC/VS), with an overall 76% response rate in treatment-refractory OCD. Also TMS holds clinical promise. Increased insight in the normalizing effects of neurostimulation on cortico-striatal-thalamic-cortical (CSTC) loops - through neuroimaging and animal research - provides novel opportunities to further optimize treatment strategies. Advancing clinical implementation of neurostimulation techniques is essential to ameliorate the lives of the many treatment-refractory OCD patients.

Behavioral flexibility in a mouse model for obsessive-compulsive disorder: Impaired Pavlovian reversal learning in SAPAP3 mutants.

Obsessive-compulsive disorder (OCD) is characterized by obsessive thinking, compulsive behavior and anxiety, and is often accompanied by cognitive deficits. The neuropathology of OCD involves dysregulation of cortical-striatal circuits. Similar to OCD patients, SAPAP3 knockout mice 3 (SAPAP3-/- ) exhibit compulsive behavior (grooming), anxiety and dysregulated cortical-striatal function. However, it is unknown whether SAPAP3-/- display cognitive deficits and how these different behavioral traits relate to one another. SAPAP3-/- and wild-type (WT) littermates were trained in a Pavlovian conditioning task pairing visual cues with the delivery of sucrose solution. After mice learned to discriminate between a reward-predicting conditioned stimulus (CS+) and a non-reward stimulus (CS-), contingencies were reversed (CS+ became CS- and vice versa). Additionally, we assessed grooming, anxiety and general activity. SAPAP3-/- acquired Pavlovian approach behavior similarly to WT, albeit less vigorously and with a different strategy. However, unlike WT, SAPAP3-/- were unable to adapt their behavior after contingency reversal, exemplified by a lack of re-establishing CS+ approach behavior (sign tracking). Surprisingly, such behavioral inflexibility, decreased vigor, compulsive grooming and anxiety were unrelated. This study shows that SAPAP3-/- are capable of Pavlovian learning, but lack flexibility to adapt associated conditioned approach behavior. Thus, SAPAP3-/- not only display compulsive-like behavior and anxiety, but also cognitive deficits, confirming and extending the validity of SAPAP3-/- as a suitable model for the study of OCD. The observation that compulsive-like behavior, anxiety and behavioral inflexibility were unrelated suggests a non-causal relationship between these traits and may be of clinical relevance for the treatment of OCD.

Differential Effects of Deep Brain Stimulation of the Internal Capsule and the Striatum on Excessive Grooming in Sapap3 Mutant Mice.

BACKGROUND: Deep brain stimulation (DBS) is an effective treatment for patients with obsessive-compulsive disorder (OCD) that do not respond to conventional therapies. Although the precise mechanism of action of DBS remains unknown, modulation of activity in corticofugal fibers originating in the prefrontal cortex is thought to underlie its beneficial effects in OCD. METHODS: To gain more mechanistic insight into DBS in OCD, we used Sapap3 mutant mice. These mice display excessive self-grooming and increased anxiety, both of which are responsive to therapeutic drugs used in OCD patients. We selected two clinically relevant DBS targets through which activity in prefronto-corticofugal fibers may be modulated: the internal capsule (IC) and the dorsal part of the ventral striatum (dVS). RESULTS: IC-DBS robustly decreased excessive grooming, whereas dVS-DBS was on average less effective. Grooming was reduced rapidly after IC-DBS onset and reinstated upon DBS offset. Only IC-DBS was associated with increased locomotion. DBS in both targets induced c-Fos expression around the electrode tip and in different regions of the prefrontal cortex. This prefronto-cortical activation was more extensive after IC-DBS, but not associated with behavioral effects. Furthermore, we found that the decline in grooming cannot be attributed to altered locomotor activity and that anxiety, measured on the elevated plus maze, was not affected by DBS. CONCLUSIONS: DBS in both the IC and dVS reduces compulsive grooming in Sapap3 mutant mice. However, IC stimulation was more effective, but also produced motor activation, even though both DBS targets modulated activity in a similar set of prefrontal cortical fibers.

Automated classification of self-grooming in mice using open-source software.

BACKGROUND: Manual analysis of behavior is labor intensive and subject to inter-rater variability. Although considerable progress in automation of analysis has been made, complex behavior such as grooming still lacks satisfactory automated quantification. NEW METHOD: We trained a freely available, automated classifier, Janelia Automatic Animal Behavior Annotator (JAABA), to quantify self-grooming duration and number of bouts based on video recordings of SAPAP3 knockout mice (a mouse line that self-grooms excessively) and wild-type animals. RESULTS: We compared the JAABA classifier with human expert observers to test its ability to measure self-grooming in three scenarios: mice in an open field, mice on an elevated plus-maze, and tethered mice in an open field. In each scenario, the classifier identified both grooming and non-grooming with great accuracy and correlated highly with results obtained by human observers. Consistently, the JAABA classifier confirmed previous reports of excessive grooming in SAPAP3 knockout mice. COMPARISON WITH EXISTING METHODS: Thus far, manual analysis was regarded as the only valid quantification method for self-grooming. We demonstrate that the JAABA classifier is a valid and reliable scoring tool, more cost-efficient than manual scoring, easy to use, requires minimal effort, provides high throughput, and prevents inter-rater variability. CONCLUSION: We introduce the JAABA classifier as an efficient analysis tool for the assessment of rodent self-grooming with expert quality. In our "how-to" instructions, we provide all information necessary to implement behavioral classification with JAABA.