Panksepp, J., and Yovell, Y. (2014). Preclinical Modeling of Primal Emotional Affects (SEEKING, PANIC and PLAY): Gateways to the Development of New Treatments for Depression. Psychopathology 47, 383–393. doi: 10.1159/000366208

Applications | Action Circuits

Breton, Y.-A., Marcus, J. C., and Shizgal, P. (2009). Rattus Psychologicus: construction of preferences by self-stimulating rats. Behav. Brain Res. 202, 77–91. doi: 10.1016/j.bbr.2009.03.019 Alcaro, A., Huber, R., and Panksepp, J. (2007). Behavioral functions of the mesolimbic dopaminergic system: An affective neuroethological perspective. Brain Res. Rev. 56, 283–321. doi: 10.1016/j.brainresrev.2007.07.014

Depression: Symptoms, Proposed Mechanisms, and Interventions

Extension of the quantitative approach to rewarding effects produced by specific optogenetic activation of midbrain dopamine neurons has led to a new view of the circuitry underlying intracranial self-stimulation ( Trujillo-Pisanty et al., 2020). On that view, parallel processing channels convey to the behavioral final-common path signals arising in non-dopaminergic MFB fibers and in the ascending projections of midbrain dopamine neurons. We summarize that new view below and explore its potential implications for explaining the relief of treatment-resistant depression by MFB stimulation. Before doing so, we situate the study of intracranial self-stimulation within the context of animal models of depression, we review aspects of depression germane to the question of how MFB stimulation provides relief, and we discuss how research on the effects of such stimulation in rodents could provide insight into the mechanism underlying the antidepressant effect in humans. Animal Models of Depression The maximum firing frequency of human dopamine neurons has yet to be determined, as far as we know. That said, the pulse frequency employed in the deep-brain stimulation of the human MFB, 130 Hz, is well above the maximum firing frequency that dopaminergic neurons can sustain in the rodent ( Tsai et al., 2009; Witten et al., 2011; Covey and Cheer, 2019). The Centrality of the Dopamine Neurons? van der Meer, M., Kurth-Nelson, Z., and Redish, A. D. (2012). Information Processing in Decision-Making Systems. Neuroscientist 18, 342–359. doi: 10.1177/1073858411435128 Yizhar, O., Fenno, L. E., Davidson, T. J., Mogri, M., and Deisseroth, K. (2011). Optogenetics in neural systems. Neuron 71, 9–34. doi: 10.1016/j.neuron.2011.06.004 Once the trajectories of the axons of interest have been traced, optogenetic methods ( Yizhar et al., 2011) can render the neurons that give rise to particular MFB components optically excitable, thereby making it possible to determine whether driving these cells produces rewarding and/or motivating effects. Identification of the terminal fields of the MFB-projecting neurons, coupled with optogenetic silencing methods ( Yizhar et al., 2011; Wiegert et al., 2017) provide complementary means for assessing the necessity of these neurons for the rewarding effect of MFB stimulation. By recording the activity of these neurons in response to rewarding MFB stimulation, it can be determined whether the properties of their axons correspond to the psychophysically derived portrait of the fibers subserving MFB self-stimulation (e.g., Rompré and Shizgal, 1986; Shizgal et al., 1989; Murray and Shizgal, 1996b; Cossette et al., 2016). Implications for Research on the Antidepressant Effect of Deep-Brain Stimulation Stimulation Parameters

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Witten, I. B., Steinberg, E. E., Davidson, T. J., Yizhar, O., Ramakrishnan, C., Stuber, G. D., et al. (2011). Recombinase-driver rat lines: tools, techniques, and optogenetic application to dopamine-mediated reinforcement. Neuron 72, 721–733. doi: 10.1016/j.neuron.2011.10.028 Berry, M.J. II, Brivanlou, I.H., Jordan, T.A., and Meister, M. (1999). Anticipation of moving stimuli by the retina. Nature 398, 334–338. Wise, R. A. (1978). Catecholamine theories of reward: a critical review. Brain Res. 152, 215–247. doi: 10.1016/0006-8993(78)90253-6 Jacobson, N. S., Dobson, K. S., Truax, P. A., Addis, M. E., Koerner, K., Gollan, J. K., et al. (1996). A component analysis of cognitive - Behavioral treatment for depression. J. Consult. Clin. Psychol. 64, 295–304. doi: 10.1037/0022-006X.64.2.295Tsai, H.-C., Zhang, F., Adamantidis, A., Stuber, G. D., Bonci, A., de Lecea, L., et al. (2009). Phasic firing in dopaminergic neurons is sufficient for behavioral conditioning. Science 324, 1080–1084. doi: 10.1126/science.1168878 Kumar, P., Goer, F., Murray, L., Dillon, D. G., Beltzer, M. L., Cohen, A. L., et al. (2018). Impaired reward prediction error encoding and striatal-midbrain connectivity in depression. Neuropsychopharmacology 43, 1581–1588. doi: 10.1038/s41386-018-0032-x Kringelbach, M. L., Jenkinson, N., Owen, S. L. F., and Aziz, T. Z. (2007). Translational principles of deep brain stimulation. Nat. Rev. Neurosci. 8, 623–635. doi: 10.1038/nrn2196 Gao, R., Asano, S. M., Upadhyayula, S., Pisarev, I., Milkie, D. E., Liu, T.-L., et al. (2019). Cortical column and whole-brain imaging with molecular contrast and nanoscale resolution. Science 363:eaau8302. doi: 10.1126/science.aau8302

Logic Circuit - an overview | ScienceDirect Topics

In a Bayesian, decision-theoretic account, depression entails pessimistic expectations about the value of future rewards and possible actions ( Huys et al., 2015), an observation well supported by evidence ( Cooper et al., 2021). As noted above, Panksepp emphasized the role of the SEEKING system in anticipation of positive outcomes rather than in ongoing hedonic experience, and he viewed hypoactivity of the system as a determinant of depression ( Panksepp and Yovell, 2014). That view seems well aligned with the notions of pessimistic expectations and decisional anhedonia. Huys et al. (2015) argue that alterations in model-based, rather than model-free, learning are the most likely route to pessimistic expectations. Definitive isolation of model-based learning in rodents from other forms of learning is not easy to achieve, but it has been demonstrated convincingly ( van der Meer et al., 2012; Redish, 2016; Miller et al., 2017). The experimental paradigms in question should be amenable to assessing the effect of MFB stimulation on reward expectations. Thomas, C., Ye, F. Q., Irfanoglu, M. O., Modi, P., Saleem, K. S., Leopold, D. A., et al. (2014). Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited. PNAS 111, 16574–16579. doi: 10.1073/pnas.1405672111 Panksepp, J. (2016). The cross-mammalian neurophenomenology of primal emotional affects: From animal feelings to human therapeutics. J. Comparat. Neurol. 524, 1624–1635. doi: 10.1002/cne.23969 Wise, R. A. (1980). Action of drugs of abuse on brain reward systems. Pharmacol. Biochem. Behav. 13(Suppl. 1), 213–223. Hernandez, G., Trujillo-Pisanty, I., Cossette, M.-P., Conover, K., and Shizgal, P. (2012). Role of dopamine tone in the pursuit of brain stimulation reward. J. Neurosci. 32, 11032–11041. doi: 10.1523/JNEUROSCI.1051-12.2012

Supplementary Material

VP and PS: conceptualization and writing. Both authors contributed to the article and approved the submitted version. Funding Adamantidis, A. R., Tsai, H.-C., Boutrel, B., Zhang, F., Stuber, G. D., Budygin, E. A., et al. (2011). Optogenetic Interrogation of Dopaminergic Modulation of the Multiple Phases of Reward-Seeking Behavior. J. Neurosci. 31, 10829–10835. doi: 10.1523/JNEUROSCI.2246-11.2011 Coenen, V., Hurwitz, T., Panksepp, J., Mädler, B., and Honey, C. (2009b). Medial forebrain bundle stimulation elicits psychotropic side effects in Subthalamic Nucleus Deep Brain Stimulation for PD – new insights through Diffusion Tensor Imaging. Akt Neurol. 36, s–0029–1238842. doi: 10.1055/s-0029-1238842 Takigawa, M., and Mogenson, G. J. (1977). A study of inputs to antidromically identified neurons of the locus coeruleus. Brain Res. 135, 217–230. doi: 10.1016/0006-8993(77)91027-7 Olds, M. E., and Olds, J. (1963). Approach-avoidance analysis of rat diencephalon. J. Comp. Neurol. 120, 259–295. doi: 10.1002/cne.901200206

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Discovery #Mindblown Action Circuitry Electronic Experiment Set lets children build their own experiments that are powered with real electricity!

Programmed devices are now part of our everyday lives; applications from tumble driers to trains, airliners to air conditioning. Our clients exist almost everywhere, in every market and in every industry sector. Not surprisingly therefore we have built strong links with organisations renowned for their demanding levels of service and quality. Amsterdam, J. D., Settle, R. G., Doty, R. L., Abelman, E., and Winokur, A. (1987). Taste and smell perception in depression. Biol. Psychiat. 22, 1481–1485. doi: 10.1016/0006-3223(87)90108-9 Redish, A. D. (2016). Vicarious trial and error. Nat. Rev. Neurosci. 17, 147–159. doi: 10.1038/nrn.2015.30 In agreement with the Freiburg group and Panksepp, we hold that research on MFB self-stimulation in rodents will continue to have translational implications. We hope that future research into this seminal phenomenon, coupled with allied experimental work in non-human primates and humans, will yield a fuller understanding, both of the psychological and neural mechanisms underlying the antidepressant effect of deep-brain stimulation, and of the neural foundations of reward and motivation. Data Availability Statement Yeomans, J. S. (1975). Quantitative measurement of neural post-stimulation excitability with behavioral methods. Physiol. Behav. 1975, 593–602.