A critical time window for dopamine actions on the structural plasticity of dendritic spines

Frontal eye field neurons selectively signal the reward value of prior actions

The consequences of individual actions are typically unknown until well after they are executed. This fact necessitates a mechanism that bridges delays between specific actions and reward outcomes. We looked for the presence of such a mechanism in the post-movement activity of neurons in the frontal eye field (FEF), a visuomotor area in prefrontal cortex. Monkeys performed an oculomotor gamble task in which they made eye movements to different locations associated with dynamically varying reward outcomes. Behavioral data showed that monkeys tracked reward history and made choices according to their own risk preferences. Consistent with previous studies, we observed that the activity of FEF neurons is correlated with the expected reward value of different eye movements before a target appears. Moreover, we observed that the activity of FEF neurons continued to signal the direction of eye movements, the expected reward value, and their interaction well after the movements were completed and when targets were no longer within the neuronal response field. In addition, this post-movement information was also observed in local field potentials, particularly in low-frequency bands. These results show that neural signals of prior actions and expected reward value persist across delays between those actions and their experienced outcomes. These memory traces may serve a role in reward-based learning in which subjects need to learn actions predicting delayed reward.

Distributional Reinforcement Learning in the Brain

Learning about rewards and punishments is critical for survival. Classical studies have demonstrated an impressive correspondence between the firing of dopamine neurons in the mammalian midbrain and the reward prediction errors of reinforcement learning algorithms, which express the difference between actual reward and predicted mean reward. However, it may be advantageous to learn not only the mean but also the complete distribution of potential rewards. Recent advances in machine learning have revealed a biologically plausible set of algorithms for reconstructing this reward distribution from experience. Here, we review the mathematical foundations of these algorithms as well as initial evidence for their neurobiological implementation. We conclude by highlighting outstanding questions regarding the circuit computation and behavioral readout of these distributional codes.

Active maintenance of eligibility trace in rodent prefrontal cortex

Even though persistent neural activity has been proposed as a mechanism for maintaining eligibility trace, direct empirical evidence for active maintenance of eligibility trace has been lacking. We recorded neuronal activity in the medial prefrontal cortex (mPFC) in rats performing a dynamic foraging task in which a choice must be remembered until its outcome on the timescale of seconds for correct credit assignment. We found that mPFC neurons maintain significant choice signals during the time period between action selection and choice outcome. We also found that neural signals for choice, outcome, and action value converge in the mPFC when choice outcome was revealed. Our results indicate that the mPFC maintains choice signals necessary for temporal credit assignment in the form of persistent neural activity in our task. They also suggest that the mPFC might update action value by combining actively maintained eligibility trace with action value and outcome signals.

A systems-neuroscience model of phasic dopamine

We describe a neurobiologically informed computational model of phasic dopamine signaling to account for a wide range of findings, including many considered inconsistent with the simple reward prediction error (RPE) formalism. The central feature of this PVLV framework is a distinction between a primary value (PV) system for anticipating primary rewards (Unconditioned Stimuli [USs]), and a learned value (LV) system for learning about stimuli associated with such rewards (CSs). The LV system represents the amygdala, which drives phasic bursting in midbrain dopamine areas, while the PV system represents the ventral striatum, which drives shunting inhibition of dopamine for expected USs (via direct inhibitory projections) and phasic pausing for expected USs (via the lateral habenula). Our model accounts for data supporting the separability of these systems, including individual differences in CS-based (sign-tracking) versus US-based learning (goal-tracking). Both systems use competing opponent-processing pathways representing evidence for and against specific USs, which can explain data dissociating the processes involved in acquisition versus extinction conditioning. Further, opponent processing proved critical in accounting for the full range of conditioned inhibition phenomena, and the closely related paradigm of second-order conditioning. Finally, we show how additional separable pathways representing aversive USs, largely mirroring those for appetitive USs, also have important differences from the positive valence case, allowing the model to account for several important phenomena in aversive conditioning. Overall, accounting for all of these phenomena strongly constrains the model, thus providing a well-validated framework for understanding phasic dopamine signaling. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Preclinical evidence in support of repurposing sub-anesthetic ketamine as a treatment for L-DOPA-induced dyskinesia

Parkinson's disease (PD) is the second most common neurodegenerative disease. Pharmacotherapy with L-DOPA remains the gold-standard therapy for PD, but is often limited by the development of the common side effect of L-DOPA-induced dyskinesia (LID), which can become debilitating. The only effective treatment for disabling dyskinesia is surgical therapy (neuromodulation or lesioning), therefore effective pharmacological treatment of LID is a critical unmet need. Here, we show that sub-anesthetic doses of ketamine attenuate the development of LID in a rodent model, while also having acute anti-parkinsonian activity. The long-term anti-dyskinetic effect is mediated by brain-derived neurotrophic factor-release in the striatum, followed by activation of ERK1/2 and mTOR pathway signaling. This ultimately leads to morphological changes in dendritic spines on striatal medium spiny neurons that correlate with the behavioral effects, specifically a reduction in the density of mushroom spines, a dendritic spine phenotype that shows a high correlation with LID. These molecular and cellular changes match those occurring in hippocampus and cortex after effective sub-anesthetic ketamine treatment in preclinical models of depression, and point to common mechanisms underlying the therapeutic efficacy of ketamine for these two disorders. These preclinical mechanistic studies complement current ongoing clinical testing of sub-anesthetic ketamine for the treatment of LID by our group, and provide further evidence in support of repurposing ketamine to treat individuals with PD. Given its clinically proven therapeutic benefit for both treatment-resistant depression and several pain states, very common co-morbidities in PD, sub-anesthetic ketamine could provide multiple therapeutic benefits for PD in the future.

Geometry and the Organizational Principle of Spine Synapses along a Dendrite

Precise information on synapse organization in a dendrite is crucial to understanding the mechanisms underlying voltage integration and the variability in the strength of synaptic inputs across dendrites of different complex morphologies. Here, we used focused ion beam/scanning electron microscope (FIB/SEM) to image the dendritic spines of mice in the hippocampal CA1 region, CA3 region, somatosensory cortex, striatum, and cerebellum (CB). Our results show that the spine geometry and dimensions differ across neuronal cell types. Despite this difference, dendritic spines were organized in an orchestrated manner such that the postsynaptic density (PSD) area per unit length of dendrite scaled positively with the dendritic diameter in CA1 proximal stratum radiatum (PSR), cortex, and CB. The ratio of the PSD area to neck length was kept relatively uniform across dendrites of different diameters in CA1 PSR. Computer simulation suggests that a similar level of synaptic strength across different dendrites in CA1 PSR enables the effective transfer of synaptic inputs from the dendrites toward soma. Excitatory postsynaptic potentials (EPSPs), evoked at single spines by glutamate uncaging and recorded at the soma, show that the neck length is more influential than head width in regulating the EPSP magnitude at the soma. Our study describes thorough morphologic features and the organizational principles of dendritic spines in different brain regions.

Dopamine and Addiction

Addiction is commonly identified with habitual nonmedical self-administration of drugs. It is usually defined by characteristics of intoxication or by characteristics of withdrawal symptoms. Such addictions can also be defined in terms of the brain mechanisms they activate; most addictive drugs cause elevations in extracellular levels of the neurotransmitter dopamine. Animals unable to synthesize or use dopamine lack the conditioned reflexes discussed by Pavlov or the appetitive behavior discussed by Craig; they have only unconditioned consummatory reflexes. Burst discharges (phasic firing) of dopamine-containing neurons are necessary to establish long-term memories associating predictive stimuli with rewards and punishers. Independent discharges of dopamine neurons (tonic or pacemaker firing) determine the motivation to respond to such cues. As a result of habitual intake of addictive drugs, dopamine receptors expressed in the brain are decreased, thereby reducing interest in activities not already stamped in by habitual rewards.

Cortical circuits for transforming whisker sensation into goal-directed licking

Animals can learn to use sensory stimuli to generate motor actions in order to obtain rewards. However, the precise neuronal circuits driving learning and execution of a specific goal-directed sensory-to-motor transformation remain to be elucidated. Here, we review progress in understanding the contribution of cortical neuronal circuits to a task in which head-restrained water-restricted mice learn to lick a reward spout in response to whisker deflection. We first examine 'innate' pathways for whisker sensory processing and licking motor control, and then discuss how these might become linked through reward-based learning, perhaps enabled by cholinergic-gated and dopaminergic-gated plasticity. The aim is to uncover the synaptically connected neuronal pathways that mediate reward-based learning and execution of a well-defined sensory-to-motor transformation.

An ultrasensitive biosensor for high-resolution kinase activity imaging in awake mice

Protein kinases control nearly every facet of cellular function. These key signaling nodes integrate diverse pathway inputs to regulate complex physiological processes, and aberrant kinase signaling is linked to numerous pathologies. While fluorescent protein-based biosensors have revolutionized the study of kinase signaling by allowing direct, spatiotemporally precise kinase activity measurements in living cells, powerful new molecular tools capable of robustly tracking kinase activity dynamics across diverse experimental contexts are needed to fully dissect the role of kinase signaling in physiology and disease. Here, we report the development of an ultrasensitive, second-generation excitation-ratiometric protein kinase A (PKA) activity reporter (ExRai-AKAR2), obtained via high-throughput linker library screening, that enables sensitive and rapid monitoring of live-cell PKA activity across multiple fluorescence detection modalities, including plate reading, cell sorting and one- or two-photon imaging. Notably, in vivo visual cortex imaging in awake mice reveals highly dynamic neuronal PKA activity rapidly recruited by forced locomotion.

A role for the medial temporal lobes in category learning

Despite much research, the role of the medial temporal lobes (MTL) in category learning is unclear. Two unstructured categorization experiments explored conditions that might recruit MTL category learning and memory systems—namely, whether the stimulus display includes one or two stimuli, and whether category membership depends on configural properties of the stimulus features. The results supported three conclusions. First, in agreement with prior research, learning with single stimulus displays depended on striatal-mediated procedural learning. Second, and most important, learning with pair displays was mediated by MTL declarative memory systems. Third, the use of stimuli in which category membership depends on configural properties of the stimulus features made MTL learning slightly more likely. Overall, the results suggested that the MTL are most likely to mediate learning when the participant must decide which of two configural stimuli belongs to a selected category.

Functional Dissection of Basal Ganglia Inhibitory Inputs onto Substantia Nigra Dopaminergic Neurons

Substantia nigra (SNc) dopaminergic neurons respond to aversive stimuli with inhibitory pauses in firing followed by transient rebound activation. We tested integration of inhibitory synaptic inputs onto SNc neurons from genetically defined populations in dorsal striatum (striosome and matrix) and external globus pallidus (GPe; parvalbumin- and Lhx6-positive), and examined their contribution to pause-rebound firing. Activation of striosome projections, which target "dendron bouquets" in the pars reticulata (SNr), consistently quiets firing and relief from striosome inhibition triggers rebound activity. Striosomal inhibitory postsynaptic currents (IPSCs) display a prominent GABA-B receptor-mediated component that strengthens the impact of SNr dendrite synapses on somatic excitability and enables rebounding. By contrast, GPe projections activate GABA-A receptors on the soma and proximal dendrites but do not result in rebounding. Lastly, optical mapping shows that dorsal striatum selectively inhibits the ventral population of SNc neurons, which are intrinsically capable of rebounding. Therefore, we define a distinct striatonigral circuit for generating dopamine rebound.

Context-Dependent Multiplexing by Individual VTA Dopamine Neurons

Dopamine (DA) neurons of the VTA track cues and rewards to generate a reward prediction error signal during Pavlovian conditioning. Here we explored how these neurons respond to a self-paced, operant task in freely moving mice. The animal could trigger a reward-predicting cue by remaining in a specific location of an operant box for a brief time before moving to a spout for reward collection. VTA DA neurons were identified using DAT-Cre male mice that carried an optrode with minimal impact on the behavioral task. In vivo single-unit recordings revealed transient fast spiking responses to the cue and reward in correct trials, while for incorrect ones the activity paused, reflecting positive and negative error signals of a reward prediction. In parallel, a majority of VTA DA neurons simultaneously encoded multiple actions (e.g., movement velocity, acceleration, distance to goal, and licking) in sustained slow firing modulation. Applying a GLM, we show that such multiplexed encoding of rewarding and motor variables by individual DA neurons was only apparent while the mouse was engaged in the task. Downstream targets may exploit such goal-directed multiplexing of VTA DA neurons to adjust actions to optimize the task's outcome.SIGNIFICANCE STATEMENT VTA DA neurons code for multiple functions, including the reward prediction error but also motivation and locomotion. Here we show that about half of the recorded VTA DA neurons perform multiplexing: they exploit the phasic and tonic activity modes to encode, respectively, the cue/reward responses and motor parameters, most prominently when the mouse engages in a self-paced operand task. VTA non-DA neurons, by contrast, encode motor parameters regardless of task engagement.

Dendritic Spine Plasticity: Function and Mechanisms

Dendritic spines are small protrusions studding neuronal dendrites, first described in 1888 by Ramón y Cajal using his famous Golgi stainings. Around 50 years later the advance of electron microscopy (EM) confirmed Cajal's intuition that spines constitute the postsynaptic site of most excitatory synapses in the mammalian brain. The finding that spine density decreases between young and adult ages in fixed tissues suggested that spines are dynamic. It is only a decade ago that two-photon microscopy (TPM) has unambiguously proven the dynamic nature of spines, through the repeated imaging of single spines in live animals. Spine dynamics comprise formation, disappearance, and stabilization of spines and are modulated by neuronal activity and developmental age. Here, we review several emerging concepts in the field that start to answer the following key questions: What are the external signals triggering spine dynamics and the molecular mechanisms involved? What is, in return, the role of spine dynamics in circuit-rewiring, learning, and neuropsychiatric disorders?

Developmental Changes in Dendritic Spine Morphology in the Striatum and Their Alteration in an A53T α-Synuclein Transgenic Mouse Model of Parkinson's Disease

The aging process is accompanied by various neurophysiological changes, and the severity of neurodegenerative disorders such as Parkinson’s disease (PD) increases with aging. However, the precise neuroanatomical changes that accompany the aging process in both normal and pathologic conditions remain unknown. This is in part because there is a lack of high-resolution imaging tool that has the capacity to image a desired volume of neurons in a high-throughput and automated manner. In the present study, focused ion beam/scanning electron microscopy (FIB/SEM) was used to image striatal neuropil in both wild-type (WT) mice and an A53T bacterial artificial chromosome (BAC) human α-synuclein (A53T-BAC-SNCA) transgenic (Tg) mouse model of PD, at 1, 3, 6, and 22 months of age. We demonstrated that spine density gradually decreases, and average spine head volume gradually increases with age in WT mice, suggesting a homeostatic balance between spine head volume and spine density. However, this inverse relationship between spine head volume and spine density was not observed in A53T-BAC-SNCA Tg mice. Taken together, our data suggest that PD is accompanied by an abnormality in the mechanisms that control synapse growth and maturity.

Useful Caged Compounds for Cell Physiology

Light has been instrumental in the study of living cells since its use helped in their discovery in the late 17th century. Further, combining chemical technology with light microscopy was an essential part of the Nobel Prize for Physiology in 1906. Such landmark scientific findings involved passive observation of cells. However, over the past 50 years, a "second use" of light has emerged in cell physiology, namely one of rational control. The seminal method for this emerged in late 1970s with the invention of caged compounds. This was the point when "caged compounds" were defined as optical probes in which the active functionality of a physiological signaling molecule was blocked with a photochemical protecting group. Caged compounds are analogous to prodrugs; in both, the activity of the effector is latent. However, caged compounds, unlike prodrugs, use a trigger that confers the power of full temporal and spatial manipulation of the effects of release of its latent biological cargo. Light is distinct because it is bio-orthogonal, passes through living tissue (even into the cell interior), and initiates rapid release of the "caged" biomolecule. Further, because light can be directed to broad areas or focused to small points, caged compounds offer an array of timing scenarios for physiologists to dissect virtually any type of cellular process.The collaborative interaction between chemists and physiologists plays a fundamental role in the development of caged compounds. First, the physiologists must define the problem to be addressed; then, with the help of chemists, decide if a caged compound would be useful. For this, structure-activity relationships of the potential optical probe and receptor must be determined. If rational targets seem feasible, synthetic organic chemistry is used to make the caged compound. The crucial property of prephotolysis bio-inertness relies on physiological or biochemical assays. Second, detailed optical characterization of the caged compound requires the skill of photochemists because the rate and efficiency of uncaging are also crucial properties for a useful caged compound. Often, these studies reveal limitations in the caged compound which has been developed; thus, chemists and physiologists use their abilities for iterative development of even more powerful optical probes. A similar dynamic will be familiar to scientists in the pharmaceutical industry. Therefore, caged compound development provides an excellent training framework for (young) chemists both intellectually and professionally. In this Account, I draw on my long experience in the field of making useful caged compounds for cell physiology by showing how each probe I have developed has been defined by an important physiological problem. Fundamental to this process has been my initial training by the pioneers in aromatic photochemistry, Derek Bryce-Smith and Andrew Gilbert. I discuss making a range of "caged calcium" probes, ones which went on to be the most widely used of all caged compounds. Then, I describe the development of caged neurotransmitters for two-photon uncaging microscopy. Finally, I survey recent work on making new photochemical protecting groups for wavelength orthogonal, two-color, and ultraefficient two-photon uncaging.

Directly to the Point: Dopamine Persistently Enhances Excitability of Direct Pathway Striatal Neurons

In this issue of Neuron, Lahiri and Bevan (2020) investigate the effects of dopamine release on striatal projection neurons. Using perforated patch recordings and optogenetics, they show that dopamine release persistently enhances the intrinsic excitability of direct pathway striatal neurons.

Signaling models for dopamine-dependent temporal contiguity in striatal synaptic plasticity

Animals remember temporal links between their actions and subsequent rewards. We previously discovered a synaptic mechanism underlying such reward learning in D1 receptor (D1R)-expressing spiny projection neurons (D1 SPN) of the striatum. Dopamine (DA) bursts promote dendritic spine enlargement in a time window of only a few seconds after paired pre- and post-synaptic spiking (pre-post pairing), which is termed as reinforcement plasticity (RP). The previous study has also identified underlying signaling pathways; however, it still remains unclear how the signaling dynamics results in RP. In the present study, we first developed a computational model of signaling dynamics of D1 SPNs. The D1 RP model successfully reproduced experimentally observed protein kinase A (PKA) activity, including its critical time window. In this model, adenylate cyclase type 1 (AC1) in the spines/thin dendrites played a pivotal role as a coincidence detector against pre-post pairing and DA burst. In particular, pre-post pairing (Ca2+ signal) stimulated AC1 with a delay, and the Ca2+-stimulated AC1 was activated by the DA burst for the asymmetric time window. Moreover, the smallness of the spines/thin dendrites is crucial to the short time window for the PKA activity. We then developed a RP model for D2 SPNs, which also predicted the critical time window for RP that depended on the timing of pre-post pairing and phasic DA dip. AC1 worked for the coincidence detector in the D2 RP model as well. We further simulated the signaling pathway leading to Ca2+/calmodulin-dependent protein kinase II (CaMKII) activation and clarified the role of the downstream molecules of AC1 as the integrators that turn transient input signals into persistent spine enlargement. Finally, we discuss how such timing windows guide animals' reward learning.

Computational Characteristics of the Striatal Dopamine System Described by Reinforcement Learning With Fast Generalization

Generalization is the ability to apply past experience to similar but non-identical situations. It not only affects stimulus-outcome relationships, as observed in conditioning experiments, but may also be essential for adaptive behaviors, which involve the interaction between individuals and their environment. Computational modeling could potentially clarify the effect of generalization on adaptive behaviors and how this effect emerges from the underlying computation. Recent neurobiological observation indicated that the striatal dopamine system achieves generalization and subsequent discrimination by updating the corticostriatal synaptic connections in differential response to reward and punishment. In this study, we analyzed how computational characteristics in this neurobiological system affects adaptive behaviors. We proposed a novel reinforcement learning model with multilayer neural networks in which the synaptic weights of only the last layer are updated according to the prediction error. We set fixed connections between the input and hidden layers to maintain the similarity of inputs in the hidden-layer representation. This network enabled fast generalization of reward and punishment learning, and thereby facilitated safe and efficient exploration of spatial navigation tasks. Notably, it demonstrated a quick reward approach and efficient punishment aversion in the early learning phase, compared to algorithms that do not show generalization. However, disturbance of the network that causes noisy generalization and impaired discrimination induced maladaptive valuation. These results suggested the advantage and potential drawback of computation by the striatal dopamine system with regard to adaptive behaviors.

A solution to the learning dilemma for recurrent networks of spiking neurons

Recurrently connected networks of spiking neurons underlie the astounding information processing capabilities of the brain. Yet in spite of extensive research, how they can learn through synaptic plasticity to carry out complex network computations remains unclear. We argue that two pieces of this puzzle were provided by experimental data from neuroscience. A mathematical result tells us how these pieces need to be combined to enable biologically plausible online network learning through gradient descent, in particular deep reinforcement learning. This learning method-called e-prop-approaches the performance of backpropagation through time (BPTT), the best-known method for training recurrent neural networks in machine learning. In addition, it suggests a method for powerful on-chip learning in energy-efficient spike-based hardware for artificial intelligence.

Dopamine D1 Receptors Regulate Spines in Striatal Direct-Pathway and Indirect-Pathway Neurons

BACKGROUND

Dopamine transmission is involved in the maintenance of the structural plasticity of direct-pathway and indirect-pathway striatal projection neurons (d-SPNs and i-SPNs, respectively). The lack of dopamine in Parkinson's disease produces synaptic remodeling in both types of SPNs, reducing the length of the dendritic arbor and spine density and increasing the intrinsic excitability. Meanwhile, the elevation of dopamine levels by levodopa recovers these alterations selectively in i-SPNs. However, little is known about the specific role of the D1 receptor (D1R) in these alterations.

METHODS

To explore the specific role of D1R in the synaptic remodeling of SPNs, we used knockout D1R mice (D1R^-/- ) and wild-type mice crossed with drd2-enhanced green fluorescent protein (eGFP) to identify d-SPNs and i-SPNs. Corticostriatal slices were used for reconstruction of the dendritic arbors after Lucifer yellow intracellular injection and for whole-cell recordings in naïve and parkinsonian mice treated with saline or levodopa.

RESULTS

The genetic inactivation of D1R reduces the length of the dendritic tree and the spine density in all SPNs, although more so in d-SPNs, which also increases their spiking. In parkinsonian D1R^-/- mice, the spine density decreases in i-SPNs, and this spine loss recovers after chronic levodopa.

CONCLUSIONS

D1R is essential for the maintenance of spine plasticity in d-SPNs but also affects i-SPNs, indicating an important crosstalk between these 2 types of neurons. © 2020 International Parkinson and Movement Disorder Society.

Synaptotagmin-1 is the Ca2+ sensor for fast striatal dopamine release

Dopamine powerfully controls neural circuits through neuromodulation. In the vertebrate striatum, dopamine adjusts cellular functions to regulate behaviors across broad time scales, but how the dopamine secretory system is built to support fast and slow neuromodulation is not known. Here, we set out to identify Ca²⁺-triggering mechanisms for dopamine release. We find that synchronous dopamine secretion is abolished in acute brain slices of conditional knockout mice in which Synaptotagmin-1 is removed from dopamine neurons. This indicates that Synaptotagmin-1 is the Ca²⁺ sensor for fast dopamine release. Remarkably, dopamine release induced by strong depolarization and asynchronous release during stimulus trains are unaffected by Synaptotagmin-1 knockout. Microdialysis further reveals that these modes and action potential-independent release provide significant amounts of extracellular dopamine in vivo. We propose that the molecular machinery for dopamine secretion has evolved to support fast and slow signaling modes, with fast release requiring the Ca²⁺ sensor Synaptotagmin-1.

Dopamine D2-Like Receptors Modulate Intrinsic Properties and Synaptic Transmission of Parvalbumin Interneurons in the Mouse Primary Motor Cortex

Dopamine (DA) plays a crucial role in the control of motor and higher cognitive functions such as learning, working memory, and decision making. The primary motor cortex (M1), which is essential for motor control and the acquisition of motor skills, receives dopaminergic inputs in its superficial and deep layers from the midbrain. However, the precise action of DA and DA receptor subtypes on the cortical microcircuits of M1 remains poorly understood. The aim of this work was to investigate in mice how DA, through the activation of D2-like receptors (D2Rs), modulates the cellular and synaptic activity of M1 parvalbumin-expressing interneurons (PVINs) which are crucial to regulate the spike output of pyramidal neurons (PNs). By combining immunofluorescence, ex vivo electrophysiology, pharmacology and optogenetics approaches, we show that D2R activation increases neuronal excitability of PVINs and GABAergic synaptic transmission between PVINs and PNs in Layer V of M1. Our data reveal how cortical DA modulates M1 microcircuitry, which could be important in the acquisition of motor skills.

Monkeys (Macaca mulatta) learn two-choice discriminations under displaced reinforcement

To explain animal learning, researchers invoke a dominant associative construct. In contrast, researchers freely acknowledge humans' explicit-declarative learning capacity. Here, we stretched animals' learning performance toward the explicit pole of cognition. We tested four macaques (Macaca mulatta) in new discrimination-learning paradigms. Monkeys learned a series of two-choice discrimination tasks. But immediate reinforcement was denied. Instead, reinforcement was lagged-monkeys received feedback for trial N only after seeing and responding to the N + 1-trial stimulus. Theory suggests that lagged reinforcement will eliminate a dominant form of implicit discrimination learning. Yet monkeys still learned successfully. Thus, monkeys may have alternative learning algorithms usable when reinforcement is displaced and reinforcement learning undermined. This learning may, as in humans, take a more explicit form. This and related methods that disable associative learning-fostering a possible transition to explicit cognition-could have empirical utility and theoretical significance within comparative psychology. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Striatal Kir2 K+ channel inhibition mediates the antidyskinetic effects of amantadine

Levodopa-induced dyskinesia (LID) poses a significant health care challenge for Parkinson's disease (PD) patients. Amantadine is currently the only drug proven to alleviate LID. Although its efficacy in treating LID is widely assumed to be mediated by blockade of N-methyl-D-aspartate (NMDA) glutamate receptors, our experiments demonstrate that at therapeutically relevant concentrations, amantadine preferentially blocks inward-rectifying K+ channel type 2 (Kir2) channels in striatal spiny projection neurons (SPNs) - not NMDA receptors. In so doing, amantadine enhances dendritic integration of excitatory synaptic potentials in SPNs and enhances - not antagonizes - the induction of long-term potentiation (LTP) at excitatory, axospinous synapses. Taken together, our studies suggest that the alleviation of LID in PD patients is mediated by diminishing the disparity in the excitability of direct- and indirect-pathway SPNs in the on state, rather than by disrupting LTP induction. This insight points to a pharmacological approach that could be used to effectively ameliorate LID and improve the quality of life for PD patients.

Dopaminergic Transmission Rapidly and Persistently Enhances Excitability of D1 Receptor-Expressing Striatal Projection Neurons

Substantia nigra dopamine neurons have been implicated in the initiation and invigoration of movement, presumably through their modulation of striatal projection neuron (SPN) activity. However, the impact of native dopaminergic transmission on SPN excitability has not been directly demonstrated. Using perforated patch-clamp recording, we found that optogenetic stimulation of nigrostriatal dopamine axons rapidly and persistently elevated the excitability of D1 receptor-expressing SPNs (D1-SPNs). The evoked firing of D1-SPNs increased within hundreds of milliseconds of stimulation and remained elevated for ≥ 10 min. Consistent with the negative modulation of depolarization- and Ca2+-activated K+ currents, dopaminergic transmission accelerated subthreshold depolarization in response to current injection, reduced the latency to fire, and transiently diminished action potential afterhyperpolarization. Persistent modulation was protein kinase A dependent and associated with a reduction in action potential threshold. Together, these data demonstrate that dopaminergic transmission potently increases D1-SPN excitability with a time course that could support subsecond and sustained behavioral control.

Methodological approaches to understand the molecular mechanism of structural plasticity of dendritic spines

Dendritic spines are tiny protrusions emanating from the neuronal dendrites, typically housing single excitatory postsynapses. Structural plasticity of dendritic spines is considered to be essential for synaptic functional plasticity and also reorganization of neural circuits during learning and memory. Structural plasticity of spines is mediated by complex biochemical signaling with various spatial and temporal scales. A variety of methods based on pharmacological, genetic, molecular, imaging and optical approaches has been developed and applied to dissect the complex signal transduction pathways. In this review, we overview both conventional and new methodological approaches to identify, monitor and manipulate key molecules for structural plasticity of dendritic spines, ultimately aiming to understand the molecular mechanism of learning and memory in behaving animals.

Carbon Monoxide, a Retrograde Messenger Generated in Postsynaptic Mushroom Body Neurons, Evokes Noncanonical Dopamine Release

Dopaminergic neurons innervate extensive areas of the brain and release dopamine (DA) onto a wide range of target neurons. However, DA release is also precisely regulated. In Drosophila melanogaster brain explant preparations, DA is released specifically onto α3/α'3 compartments of mushroom body (MB) neurons that have been coincidentally activated by cholinergic and glutamatergic inputs. The mechanism for this precise release has been unclear. Here we found that coincidentally activated MB neurons generate carbon monoxide (CO), which functions as a retrograde signal evoking local DA release from presynaptic terminals. CO production depends on activity of heme oxygenase in postsynaptic MB neurons, and CO-evoked DA release requires Ca²⁺ efflux through ryanodine receptors in DA terminals. CO is only produced in MB areas receiving coincident activation, and removal of CO using scavengers blocks DA release. We propose that DA neurons use two distinct modes of transmission to produce global and local DA signaling.SIGNIFICANCE STATEMENT Dopamine (DA) is needed for various higher brain functions, including memory formation. However, DA neurons form extensive synaptic connections, while memory formation requires highly specific and localized DA release. Here we identify a mechanism through which DA release from presynaptic terminals is controlled by postsynaptic activity. Postsynaptic neurons activated by cholinergic and glutamatergic inputs generate carbon monoxide, which acts as a retrograde messenger inducing presynaptic DA release. Released DA is required for memory-associated plasticity. Our work identifies a novel mechanism that restricts DA release to the specific postsynaptic sites that require DA during memory formation.

Targeting the cholinergic system in Parkinson's disease

Motor control in the striatum is an orchestra played by various neuronal populations. Loss of harmony due to dopamine deficiency is considered the primary pathological cause of the symptoms of Parkinson’s disease (PD). Recent progress in experimental approaches has enabled us to examine the striatal circuitry in a much more comprehensive manner, not only reshaping our understanding of striatal functions in movement regulation but also leading to new opportunities for the development of therapeutic strategies for treating PD. In addition to dopaminergic innervation, giant aspiny cholinergic interneurons (ChIs) within the striatum have long been recognized as a critical node for balancing dopamine signaling and regulating movement. With the roles of ChIs in motor control further uncovered and more specific manipulations available, striatal ChIs and their corresponding receptors are emerging as new promising therapeutic targets for PD. This review summarizes recent progress in functional studies of striatal circuitry and discusses the translational implications of these new findings for the treatment of PD.

Paired Associative Stimulation Fails to Induce Plasticity in Freely Behaving Intact Rats

Paired associative stimulation (PAS) has been explored in humans as a noninvasive tool to drive plasticity and promote recovery after neurologic insult. A more thorough understanding of PAS-induced plasticity is needed to fully harness it as a clinical tool. Here, we tested the efficacy of PAS with multiple interstimulus intervals in an awake rat model to study the principles of associative plasticity. Using chronically implanted electrodes in motor cortex and forelimb, we explored PAS parameters to effectively drive plasticity. We assessed changes in corticomotor excitability using a closed-loop, EMG-controlled cortical stimulation paradigm. We tested 11 PAS intervals, chosen to force the coincidence of neuronal activity in the motor cortex and spinal cord of rats with timings relevant to the principles of Hebbian spike timing-dependent plasticity. However, despite a relatively large number of stimulus pairings (300), none of the tested intervals reliably changed corticospinal excitability relative to control conditions. Our results question PAS effectiveness under these conditions.

Dopamine D2 receptors in discrimination learning and spine enlargement

Dopamine D2 receptors (D2Rs) are densely expressed in the striatum and have been linked to neuropsychiatric disorders such as schizophrenia^1,2. High-affinity binding of dopamine suggests that D2Rs detect transient reductions in dopamine concentration (the dopamine dip) during punishment learning^3-5. However, the nature and cellular basis of D2R-dependent behaviour are unclear. Here we show that tone reward conditioning induces marked stimulus generalization in a manner that depends on dopamine D1 receptors (D1Rs) in the nucleus accumbens (NAc) of mice, and that discrimination learning refines the conditioning using a dopamine dip. In NAc slices, a narrow dopamine dip (as short as 0.4 s) was detected by D2Rs to disinhibit adenosine A_2A receptor (A_2AR)-mediated enlargement of dendritic spines in D2R-expressing spiny projection neurons (D2-SPNs). Plasticity-related signalling by Ca²⁺/calmodulin-dependent protein kinase II and A_2ARs in the NAc was required for discrimination learning. By contrast, extinction learning did not involve dopamine dips or D2-SPNs. Treatment with methamphetamine, which dysregulates dopamine signalling, impaired discrimination learning and spine enlargement, and these impairments were reversed by a D2R antagonist. Our data show that D2Rs refine the generalized reward learning mediated by D1Rs.

Optical control of neuronal ion channels and receptors

Light-controllable tools provide powerful means to manipulate and interrogate brain function with relatively low invasiveness and high spatiotemporal precision. Although optogenetic approaches permit neuronal excitation or inhibition at the network level, other technologies, such as optopharmacology (also known as photopharmacology) have emerged that provide molecular-level control by endowing light sensitivity to endogenous biomolecules. In this Review, we discuss the challenges and opportunities of photocontrolling native neuronal signalling pathways, focusing on ion channels and neurotransmitter receptors. We describe existing strategies for rendering receptors and channels light sensitive and provide an overview of the neuroscientific insights gained from such approaches. At the crossroads of chemistry, protein engineering and neuroscience, optopharmacology offers great potential for understanding the molecular basis of brain function and behaviour, with promises for future therapeutics.

Synaptic Plasticity Forms and Functions

Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long been considered an important component of learning and memory. Computational and engineering work corroborate the power of learning through the directed adjustment of connection weights. Here we review the fundamental elements of four broadly categorized forms of synaptic plasticity and discuss their functional capabilities and limitations. Although standard, correlation-based, Hebbian synaptic plasticity has been the primary focus of neuroscientists for decades, it is inherently limited. Three-factor plasticity rules supplement Hebbian forms with neuromodulation and eligibility traces, while true supervised types go even further by adding objectives and instructive signals. Finally, a recently discovered hippocampal form of synaptic plasticity combines the above elements, while leaving behind the primary Hebbian requirement. We suggest that the effort to determine the neural basis of adaptive behavior could benefit from renewed experimental and theoretical investigation of more powerful directed types of synaptic plasticity.

Transient and sustained effects of dopamine and serotonin signaling in motivation-related behavior

Pharmacological studies of antidepressants and atypical antipsychotics have suggested a role of dopamine and serotonin signaling in depression. However, depressive symptoms and treatment effects are difficult to explain based simply on brain-wide decrease or increase in the concentrations of these molecules. Recent animal studies using advanced neuronal manipulation and observation techniques have revealed detailed dopamine and serotonin dynamics that regulate diverse aspects of motivation-related behavior. Dopamine and serotonin transiently modulate moment-to-moment behavior at timescales ranging from sub-second to minutes and also produce persistent effects, such as reward-related learning and stress responses that last longer than several days. Transient and sustained effects often exhibit specific roles depending on the projection sites, where distinct synaptic and cellular mechanisms are required to process the neurotransmitters for each transient and sustained timescale. Therefore, it appears that specific aspects of motivation-related behavior are regulated by distinct synaptic and cellular mechanisms in specific brain regions that underlie the transient and sustained effects of dopamine and serotonin signaling. Recent clinical studies have implied that subjects with depressive symptoms show impaired transient and sustained signaling functions; moreover, they exhibit heterogeneity in depressive symptoms and neuronal dysfunction. Depressive symptoms may be explained by the dysfunction of each transient and sustained signaling mechanism, and distinct patterns of impairment in the relevant mechanisms may explain the heterogeneity of symptoms. Thus, detailed understanding of dopamine and serotonin signaling may provide new insight into depressive symptoms.

Temporally restricted dopaminergic control of reward-conditioned movements

Midbrain dopamine (DA) neurons encode both reward- and movement-related events and are implicated in disorders of reward processing as well as movement. Consequently, disentangling the contribution of DA neurons in reinforcing versus generating movements is challenging and has led to lasting controversy. In this study, we dissociated these functions by parametrically varying the timing of optogenetic manipulations in a Pavlovian conditioning task and examining the influence on anticipatory licking before reward delivery. Inhibiting both ventral tegmental area and substantia nigra pars compacta DA neurons in the post-reward period had a significantly greater behavioral effect than inhibition in the pre-reward period of the task. Furthermore, the contribution of DA neurons to behavior decreased linearly as a function of elapsed time after reward. Together, the results indicate a temporally restricted role of DA neurons primarily related to reinforcing stimulus-reward associations and suggest that directly generating movements is a comparatively less important function.

Dopamine Receptor Activation Modulates the Integrity of the Perisynaptic Extracellular Matrix at Excitatory Synapses

In the brain, Hebbian-type and homeostatic forms of plasticity are affected by neuromodulators like dopamine (DA). Modifications of the perisynaptic extracellular matrix (ECM), which control the functions and mobility of synaptic receptors as well as the diffusion of transmitters and neuromodulators in the extracellular space, are crucial for the manifestation of plasticity. Mechanistic links between synaptic activation and ECM modifications are largely unknown. Here, we report that neuromodulation via D1-type DA receptors can induce targeted ECM proteolysis specifically at excitatory synapses of rat cortical neurons via proteases ADAMTS-4 and -5. We showed that receptor activation induces increased proteolysis of brevican (BC) and aggrecan, two major constituents of the adult ECM both in vivo and in vitro. ADAMTS immunoreactivity was detected near synapses, and shRNA-mediated knockdown reduced BC cleavage. We have outlined a molecular scenario of how synaptic activity and neuromodulation are linked to ECM rearrangements via increased cAMP levels, NMDA receptor activation, and intracellular calcium signaling.

Internal Clocks, mGluR7 and Microtubules: A Primer for the Molecular Encoding of Target Durations in Cerebellar Purkinje Cells and Striatal Medium Spiny Neurons

The majority of studies in the field of timing and time perception have generally focused on sub- and supra-second time scales, specific behavioral processes, and/or discrete neuronal circuits. In an attempt to find common elements of interval timing from a broader perspective, we review the literature and highlight the need for cell and molecular studies that can delineate the neural mechanisms underlying temporal processing. Moreover, given the recent attention to the function of microtubule proteins and their potential contributions to learning and memory consolidation/re-consolidation, we propose that these proteins play key roles in coding temporal information in cerebellar Purkinje cells (PCs) and striatal medium spiny neurons (MSNs). The presence of microtubules at relevant neuronal sites, as well as their adaptability, dynamic structure, and longevity, makes them a suitable candidate for neural plasticity at both intra- and inter-cellular levels. As a consequence, microtubules appear capable of maintaining a temporal code or engram and thereby regulate the firing patterns of PCs and MSNs known to be involved in interval timing. This proposed mechanism would control the storage of temporal information triggered by postsynaptic activation of mGluR7. This, in turn, leads to alterations in microtubule dynamics through a "read-write" memory process involving alterations in microtubule dynamics and their hexagonal lattice structures involved in the molecular basis of temporal memory.

Neural reinforcement: re-entering and refining neural dynamics leading to desirable outcomes

How do organisms learn to do again, on-demand, a behavior that led to a desirable outcome? Dopamine-dependent cortico-striatal plasticity provides a framework for learning behavior's value, but it is less clear how it enables the brain to re-enter desired behaviors and refine them over time. Reinforcing behavior is achieved by re-entering and refining the neural patterns that produce it. We review studies using brain-machine interfaces which reveal that reinforcing cortical population activity requires cortico-basal ganglia circuits. Then, we propose a formal framework for how reinforcement in cortico-basal ganglia circuits acts on the neural dynamics of cortical populations. We propose two parallel mechanisms: i) fast reinforcement which selects the inputs that permit the re-entrance of the particular cortical population dynamics which naturally produced the desired behavior, and ii) slower reinforcement which leads to refinement of cortical population dynamics and more reliable production of neural trajectories driving skillful behavior on-demand.

Environmental enrichment shapes striatal spike-timing-dependent plasticity in vivo

Behavioural experience, such as environmental enrichment (EE), induces long-term effects on learning and memory. Learning can be assessed with the Hebbian paradigm, such as spike-timing-dependent plasticity (STDP), which relies on the timing of neuronal activity on either side of the synapse. Although EE is known to control neuronal excitability and consequently spike timing, whether EE shapes STDP remains unknown. Here, using in vivo long-duration intracellular recordings at the corticostriatal synapses we show that EE promotes asymmetric anti-Hebbian STDP, i.e. spike-timing-dependent-potentiation (tLTP) for post-pre pairings and spike-timing-dependent-depression (tLTD) for pre-post pairings, whereas animals grown in standard housing show mainly tLTD and a high failure rate of plasticity. Indeed, in adult rats grown in standard conditions, we observed unidirectional plasticity (mainly symmetric anti-Hebbian tLTD) within a large temporal window (~200 ms). However, rats grown for two months in EE displayed a bidirectional STDP (tLTP and tLTD depending on spike timing) in a more restricted temporal window (~100 ms) with low failure rate of plasticity. We also found that the effects of EE on STDP characteristics are influenced by the anaesthesia status: the deeper the anaesthesia, the higher the absence of plasticity. These findings establish a central role for EE and the anaesthetic regime in shaping in vivo, a synaptic Hebbian learning rule such as STDP.

Catecholaminergic modulation of meta-learning

The remarkable expedience of human learning is thought to be underpinned by meta-learning, whereby slow accumulative learning processes are rapidly adjusted to the current learning environment. To date, the neurobiological implementation of meta-learning remains unclear. A burgeoning literature argues for an important role for the catecholamines dopamine and noradrenaline in meta-learning. Here, we tested the hypothesis that enhancing catecholamine function modulates the ability to optimise a meta-learning parameter (learning rate) as a function of environmental volatility. 102 participants completed a task which required learning in stable phases, where the probability of reinforcement was constant, and volatile phases, where probabilities changed every 10-30 trials. The catecholamine transporter blocker methylphenidate enhanced participants' ability to adapt learning rate: Under methylphenidate, compared with placebo, participants exhibited higher learning rates in volatile relative to stable phases. Furthermore, this effect was significant only with respect to direct learning based on the participants' own experience, there was no significant effect on inferred-value learning where stimulus values had to be inferred. These data demonstrate a causal link between catecholaminergic modulation and the adjustment of the meta-learning parameter learning rate.

Single Synapse LTP: A Matter of Context?

The most commonly studied form of synaptic plasticity is long-term potentiation (LTP). Over the last 15 years, it has been possible to induce structural and functional LTP in dendritic spines using two-photon glutamate uncaging, allowing for studying the signaling mechanisms of LTP with single synapse resolution. In this review, we compare different stimulation methods to induce single synapse LTP and discuss how LTP is expressed. We summarize the underlying signaling mechanisms that have been studied with high spatiotemporal resolution. Finally, we discuss how LTP in a single synapse can be affected by excitatory and inhibitory synapses nearby. We argue that single synapse LTP is highly dependent on context: the choice of induction method, the history of the dendritic spine and the dendritic vicinity crucially affect signaling pathways and expression of single synapse LTP.

One-shot learning and behavioral eligibility traces in sequential decision making

In many daily tasks, we make multiple decisions before reaching a goal. In order to learn such sequences of decisions, a mechanism to link earlier actions to later reward is necessary. Reinforcement learning (RL) theory suggests two classes of algorithms solving this credit assignment problem: In classic temporal-difference learning, earlier actions receive reward information only after multiple repetitions of the task, whereas models with eligibility traces reinforce entire sequences of actions from a single experience (one-shot). Here, we show one-shot learning of sequences. We developed a novel paradigm to directly observe which actions and states along a multi-step sequence are reinforced after a single reward. By focusing our analysis on those states for which RL with and without eligibility trace make qualitatively distinct predictions, we find direct behavioral (choice probability) and physiological (pupil dilation) signatures of reinforcement learning with eligibility trace across multiple sensory modalities.

The role of the nucleus accumbens in learned approach behavior diminishes with training

Nucleus accumbens dopamine plays a key role in reward-directed approach. Past findings suggest that dopamine's role in the expression of learned behavior diminishes with extended training. However, little is known about the central substrates that mediate the shift to dopamine-independent reward approach. In the present study, rats approached and inserted the head into a reward compartment in response to a cue signaling food delivery. On days 4 and 5 of 28-trial-per-day sessions, D1 receptor antagonist R(+)-7-chloro-8-hydroxy-3-methyl-1-phenyl-2,3,4,5-tetrahydro-1H-3-benzazepine hydrochloride (SCH23390) infused to the NAc core reduced the probability and speed of cued approach. The disruptive effect of D1 receptor blockade was specific to the nucleus accumbens core and not seen with drug infusions to nearby dopamine target regions. In rats that received drug infusions after extended training (days 10 or 11), accumbens core D1 receptor blockade produced little effect on the expression of the same behavior. These results could have been due to a continued accumbens mediation of cued approach even after the behavior had become independent of accumbens D1 receptors. However, accumbens core ionotropic glutamate receptor blockade disrupted cued approach during early but not late stages of training, similar to the effects of D1 antagonist infusions. The results suggest that with extended training, a nucleus accumbens D1-dependent behavior becomes less dependent not only on nucleus accumbens D1 transmission but also on excitatory transmission in the nucleus accumbens. These findings fill an important gap in a growing literature on reorganization of striatal function over the course of training.

Inefficient neural system stabilization: a theory of spontaneous resolutions and recurrent relapses in psychosis

A striking feature of psychosis is its heterogeneity. Presentations of psychosis vary from transient symptoms with no functional consequence in the general population to a tenacious illness at the other extreme, with a wide range of variable trajectories in between. Even among patients with schizophrenia, who are diagnosed on the basis of persistent deterioration, marked variation is seen in response to treatment, frequency of relapses and degree of eventual recovery. Existing theoretical accounts of psychosis focus almost exclusively on how symptoms are initially formed, with much less emphasis on explaining their variable course. In this review, I present an account that links several existing notions of the biology of psychosis with the variant clinical trajectories. My aim is to incorporate perspectives of systems neuroscience in a staging framework to explain the individual variations in illness course that follow the onset of psychosis.

A deep learning framework for neuroscience

Systems neuroscience seeks explanations for how the brain implements a wide variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to design computational systems based on the tasks they will have to solve. In artificial neural networks, the three components specified by design are the objective functions, the learning rules and the architectures. With the growing success of deep learning, which utilizes brain-inspired architectures, these three designed components have increasingly become central to how we model, engineer and optimize complex artificial learning systems. Here we argue that a greater focus on these components would also benefit systems neuroscience. We give examples of how this optimization-based framework can drive theoretical and experimental progress in neuroscience. We contend that this principled perspective on systems neuroscience will help to generate more rapid progress.

Neuromodulators and Long-Term Synaptic Plasticity in Learning and Memory: A Steered-Glutamatergic Perspective

The molecular pathways underlying the induction and maintenance of long-term synaptic plasticity have been extensively investigated revealing various mechanisms by which neurons control their synaptic strength. The dynamic nature of neuronal connections combined with plasticity-mediated long-lasting structural and functional alterations provide valuable insights into neuronal encoding processes as molecular substrates of not only learning and memory but potentially other sensory, motor and behavioural functions that reflect previous experience. However, one key element receiving little attention in the study of synaptic plasticity is the role of neuromodulators, which are known to orchestrate neuronal activity on brain-wide, network and synaptic scales. We aim to review current evidence on the mechanisms by which certain modulators, namely dopamine, acetylcholine, noradrenaline and serotonin, control synaptic plasticity induction through corresponding metabotropic receptors in a pathway-specific manner. Lastly, we propose that neuromodulators control plasticity outcomes through steering glutamatergic transmission, thereby gating its induction and maintenance.

From cells to sensations: A window to the physics of mind

Principles of methods for studying particles and fields that cannot be sensed by third-person observers by routine methods can be used to understand the physics of first-person properties of mind. Accordingly, whenever a system exhibits disparate features at multiple levels, unique combination of constraints offered by them direct us towards a solution that will be the first principle of that system. Using this method, it was possible to arrive at a third-person observable solution-point of brain-mind interface. Examination of this location identified a set of unique features that can allow an associatively learned (cue) stimulus to spark hallucinations that form units of first-person internal (inner) sensations reminiscent of stimuli from the associatively learned second item in timescales of milliseconds. It allows us to peep into a virtual space of mind where different modifications and integrations of units of internal sensations generate their different net conformations ranging from perception to an inner sense of hidden relationships that form a hypothesis. Since sparking of inner sensations of the late arriving (when far away) or non-arriving (when hidden) features of items started providing survival advantage, the focus of evolution might have been to optimize this property. Hence, the circuity that generates it can be considered as the primary circuitry of the system. The solution provides several testable predictions. By taking readers through the process of deriving the solution and by explaining how it interconnects disparate findings, it is hoped that the factors determining the physics of mind will become evident.