Transient and steady-state selection in the striatal microcircuit

Rethinking Movement Disorders

At present, clinical practice and research in movement disorders (MDs) focus on the "normalization" of altered movements. In this review, rather than concentrating on problems and burdens people with MDs undoubtedly have, we highlight their hidden potentials. Starting with current definitions of Parkinson's disease (PD), dystonia, chorea, and tics, we outline that solely conceiving these phenomena as signs of dysfunction falls short of their complex nature comprising both problems and potentials. Such potentials can be traced and understood in light of well-established cognitive neuroscience frameworks, particularly ideomotor principles, and their influential modern derivatives. Using these frameworks, the wealth of data on altered perception-action integration in the different MDs can be explained and systematized using the mechanism-oriented concept of perception-action binding. According to this concept, MDs can be understood as phenomena requiring and fostering flexible modifications of perception-action associations. Consequently, although conceived as being caught in a (trough) state of deficits, given their high flexibility, people with MDs also have high potential to switch to (adaptive) peak activity that can be conceptualized as hidden potentials. Currently, clinical practice and research in MDs are concerned with deficits and thus the "deep and wide troughs," whereas "scattered narrow peaks" reflecting hidden potentials are neglected. To better delineate and utilize the latter to alleviate the burden of affected people, and destigmatize their conditions, we suggest some measures, including computational modeling combined with neurophysiological methods and tailored treatment. © 2024 International Parkinson and Movement Disorder Society.

Effective Regulation of Auditory Processing by Parvalbumin Interneurons in the Tail of the Striatum

Parvalbumin (PV) interneurons in the auditory cortex (AC) play a crucial role in shaping auditory processing, including receptive field formation, temporal precision enhancement, and gain regulation. PV interneurons are also the primary inhibitory neurons in the tail of the striatum (TS), which is one of the major descending brain regions in the auditory nervous system. However, the specific roles of TS-PV interneurons in auditory processing remain elusive. In this study, morphological and slice recording experiments in both male and female mice revealed that TS-PV interneurons, compared with AC-PV interneurons, were present in fewer numbers but exhibited longer projection distances, which enabled them to provide sufficient inhibitory inputs to spiny projection neurons (SPNs). Furthermore, TS-PV interneurons received dense auditory input from both the AC and medial geniculate body (MGB), particularly from the MGB, which rendered their auditory responses comparable to those of AC-PV interneurons. Optogenetic manipulation experiments demonstrated that TS-PV interneurons were capable of bidirectionally regulating the auditory responses of SPNs. Our findings suggest that PV interneurons can effectively modulate auditory processing in the TS and may play a critical role in auditory-related behaviors.

Gamma-Aminobutyric Acid and Glutamate Concentrations in the Striatum and Anterior Cingulate Cortex Not Found to Be Associated with Cognitive Flexibility

Behavioral flexibility and goal-directed behavior heavily depend on fronto-striatal networks. Within these circuits, gamma-aminobutyric acid (GABA) and glutamate play an important role in (motor) response inhibition, but it has remained largely unclear whether they are also relevant for cognitive inhibition. We hence investigated the functional role of these transmitters for cognitive inhibition during cognitive flexibility. Healthy young adults performed two paradigms assessing different aspects of cognitive flexibility. Magnetic resonance spectroscopy (MRS) was used to quantify GABA+ and total glutamate/glutamine (Glx) levels in the striatum and anterior cingulate cortex (ACC) referenced to N-acetylaspartate (NAA). We observed typical task switching and backward inhibition effects, but striatal and ACC concentrations of GABA+/NAA and Glx/NAA were not associated with cognitive flexibility in a functionally relevant manner. The assumption of null effects was underpinned by Bayesian testing. These findings suggest that behavioral and cognitive inhibition are functionally distinct faculties, that depend on (at least partly) different brain structures and neurotransmitter systems. While previous studies consistently demonstrated that motor response inhibition is modulated by ACC and striatal GABA levels, our results suggest that the functionally distinct cognitive inhibition required for successful switching is not, or at least to a much lesser degree, modulated by these factors.

Black-box and surrogate optimization for tuning spiking neural models of striatum plasticity

The basal ganglia (BG) is a brain structure that has long been proposed to play an essential role in action selection, and theoretical models of spiking neurons have tried to explain how the BG solves this problem. A recently proposed functional and biologically inspired network model of the striatum (an important nucleus of the BG) is based on spike-timing-dependent eligibility (STDE) and captured important experimental features of this nucleus. The model can recognize complex input patterns and consistently choose rewarded actions to respond to such sensory inputs. However, model tuning is challenging due to two main reasons. The first is the expert knowledge required, resulting in tedious and potentially biased trial-and-error procedures. The second is the computational cost of assessing model configurations (approximately 1.78 h per evaluation). This study addresses the model tuning problem through numerical optimization. Considering the cost of assessing solutions, the selected methods stand out due to their low requirements for solution evaluations and compatibility with high-performance computing. They are the SurrogateOpt solver of Matlab and the RBFOpt library, both based on radial basis function approximations, and DIRECT-GL, an enhanced version of the widespread black-box optimizer DIRECT. Besides, a parallel random search serves as a baseline reference of the outcome of opting for sophisticated methods. SurrogateOpt turns out to be the best option for tuning this kind of model. It outperforms, on average, the quality of the configuration found by an expert and works significantly faster and autonomously. RBFOpt and the random search share the second position, but their average results are below the option found by hand. Finally, DIRECT-GL follows this line becoming the worst-performing method.

Differential Dopamine Receptor-Dependent Sensitivity Improves the Switch Between Hard and Soft Selection in a Model of the Basal Ganglia

The problem of selecting one action from a set of different possible actions, simply referred to as the problem of action selection, is a ubiquitous challenge in the animal world. For vertebrates, the basal ganglia (BG) are widely thought to implement the core computation to solve this problem, as its anatomy and physiology are well suited to this end. However, the BG still display physiological features whose role in achieving efficient action selection remains unclear. In particular, it is known that the two types of dopaminergic receptors (D1 and D2) present in the BG give rise to mechanistically different responses. The overall effect will be a difference in sensitivity to dopamine, which may have ramifications for action selection. However, which receptor type leads to a stronger response is unclear due to the complexity of the intracellular mechanisms involved. In this study, we use an existing, high-level computational model of the BG, which assumes that dopamine contributes to action selection by enabling a switch between different selection regimes, to predict which of D1 or D2 has the greater sensitivity. Thus, we ask, Assuming dopamine enables a switch between action selection regimes in the BG, what functional sensitivity values would result in improved action selection computation? To do this, we quantitatively assessed the model's capacity to perform action selection as we parametrically manipulated the sensitivity weights of D1 and D2. We show that differential (rather than equal) D1 and D2 sensitivity to dopaminergic input improves the switch between selection regimes during the action selection computation in our model. Specifically, greater D2 sensitivity compared to D1 led to these improvements.

Making decisions in the dark basement of the brain: A look back at the GPR model of action selection and the basal ganglia

How does your brain decide what you will do next? Over the past few decades compelling evidence has emerged that the basal ganglia, a collection of nuclei in the fore- and mid-brain of all vertebrates, are vital to action selection. Gurney, Prescott, and Redgrave published an influential computational account of this idea in Biological Cybernetics in 2001. Here we take a look back at this pair of papers, outlining the "GPR" model contained therein, the context of that model's development, and the influence it has had over the past twenty years. Tracing its lineage into models and theories still emerging now, we are encouraged that the GPR model is that rare thing, a computational model of a brain circuit whose advances were directly built on by others.

Lower-level associations in Gilles de la Tourette syndrome: Convergence between hyperbinding of stimulus and response features and procedural hyperfunctioning theories

Gilles de la Tourette syndrome (GTS) can be characterized by enhanced cognitive functions related to creating, modifying and maintaining connections between stimuli and responses (S-R links). Specifically, two areas, procedural sequence learning and, as a novel finding, also event file binding, show converging evidence of hyperfunctioning in GTS. In this review, we describe how these two enhanced functions can be considered as cognitive mechanisms behind habitual behaviour, such as tics in GTS. Moreover, the presence of both procedural sequence learning and event file binding hyperfunctioning in the same disorder can be treated as evidence for their functional connections, even beyond GTS. Importantly though, we argue that hyperfunctioning of event file binding and procedural learning are not interchangeable: they have different time scales, different sensitivities to potential impairment in action sequencing and distinguishable contributions to the cognitive profile of GTS. An integrated theoretical account of hyperbinding and hyperlearning in GTS allows to formulate predictions for the emergence, activation and long-term persistence of tics in GTS.

On the functional role of striatal and anterior cingulate GABA+ in stimulus-response binding

Successful response selection relies on constantly updating stimulus-response associations. The Theory of Event Coding (TEC) proposes that perception and action are conjointly coded in event files, for which fronto-striatal networks seem to play an important role. However, the exact neurobiochemical mechanism behind event file coding has remained unknown. We investigated the functional relevance of the striatal and anterior cingulate (ACC) GABAergic system using magnetic resonance spectroscopy (MRS). Specifically, the striatal and ACC concentrations of GABA+ referenced against N-acetylaspartate (NAA) were assessed in 35 young healthy males, who subsequently performed a standard event file task. As predicted by the TEC, the participants' responses were modulated by pre-established stimulus response bindings in event files. GABA+/NAA concentrations in the striatum and ACC were not correlated with the overall event binding effect. However, higher GABA+/NAA concentrations in the ACC were correlated with stronger event file binding processes in the early phase of the task. This association disappeared by the end of the task. Taken together, our findings show that striatal GABA+ levels does not seem to modulate event file binding, while ACC GABA+ seem to improve event file binding, but only as long as the participants have not yet gathered sufficient task experience. To the best of our knowledge, this is the first study providing direct evidence for the role of striatal and ACC GABA+ in stimulus-response bindings and thus insights into the brain structure-specific neurobiological aspects of the TEC.

A Basal Ganglia Computational Model to Explain the Paradoxical Sensorial Improvement in the Presence of Huntington's Disease

The basal ganglia (BG) represent a critical center of the nervous system for sensorial discrimination. Although it is known that Huntington's disease (HD) affects this brain area, it still remains unclear how HD patients achieve paradoxical improvement in sensorial discrimination tasks. This paper presents a computational model of the BG including the main nuclei and the typical firing properties of their neurons. The BG model has been embedded within an auditory signal detection task. We have emulated the effect that the altered levels of dopamine and the degree of HD affectation have in information processing at different layers of the BG, and how these aspects shape transient and steady states differently throughout the selection task. By extracting the independent components of the BG activity at different populations, it is evidenced that early and medium stages of HD affectation may enhance transient activity in the striatum and the substantia nigra pars reticulata. These results represent a possible explanation for the paradoxical improvement that HD patients present in discrimination task performance. Thus, this paper provides a novel understanding on how the fast dynamics of the BG network at different layers interact and enable transient states to emerge throughout the successive neuron populations.

A literature review on the neurophysiological underpinnings and cognitive effects of transcutaneous vagus nerve stimulation: challenges and future directions

Brain stimulation approaches are important to gain causal mechanistic insights into the relevance of functional brain regions and/or neurophysiological systems for human cognitive functions. In recent years, transcutaneous vagus nerve stimulation (tVNS) has attracted considerable popularity. It is a noninvasive brain stimulation technique based on the stimulation of the vagus nerve. The stimulation of this nerve activates subcortical nuclei, such as the locus coeruleus and the nucleus of the solitary tract, and from there, the activation propagates to the cortex. Since tVNS is a novel stimulation technique, this literature review outlines a brief historical background of tVNS, before detailing underlying neurophysiological mechanisms of action, stimulation parameters, cognitive effects of tVNS on healthy humans, and, lastly, current challenges and future directions of tVNS research in cognitive functions. Although more research is needed, we conclude that tVNS, by increasing norepineprine (NE) and gamma-aminobutyric acid (GABA) levels, affects NE- and GABA-related cognitive performance. The review provides detailed background information how to use tVNS as a neuromodulatory tool in cognitive neuroscience and outlines important future leads of research on tVNS.

Acute Alcohol Effects on Response Inhibition Depend on Response Automatization, but not on GABA or Glutamate Levels in the ACC and Striatum

Alcohol increases GABAergic signaling and decreases glutamatergic signaling in the brain. Variations in these neurotransmitter levels may modulate/predict executive functioning. Matching this, strong impairments of response inhibition are one of the most consistently reported cognitive/behavioral effects of acute alcohol intoxication. However, it has never been investigated whether baseline differences in these neurotransmitters allow to predict how much alcohol intoxication impairs response inhibition, and whether this is reflected in neurophysiological measures of cognitive control. We used MR spectroscopy to assess baseline (i.e., sober) GABA and glutamate levels in the anterior cingulate cortex (ACC) and striatum in n = 30 healthy young males, who were subsequently tested once sober and once intoxicated (1.01 permille). Inhibition was assessed with the sustained attention to response task (SART). This paradigm also allows to examine the effect of different degrees of response automatization, which is a known modulator for response inhibition, but does not seem to be substantially impaired during acute intoxication. As a neurophysiological correlate of response inhibition and control, we quantified EEG-derived theta band power and located its source using beamforming analyses. We found that alcohol-induced response inhibition deficits only occurred in the case of response automatization. This was reflected by decreased theta band activity in the left supplementary motor area (SMA), which may reflect modulations in the encoding of a surprise signal in response to inhibition cues. However, we did not find that differences in baseline (i.e., sober) GABA or glutamate levels significantly modulated differences in the size of alcohol-induced inhibition deficits.

Predictive coding and adaptive behavior in patients with genetically determined cerebellar ataxia--A neurophysiology study

Genetically determined cerebellar ataxias (CA) are a heterogeneous group of disorders with progressive decline of cerebellar functions. The cerebellum influences internal forward models that play a role in cognitive control, but whether these processes are dysfunctional in CA is unclear. Here, we examined sensory predictive coding processes and response adaptation in CA and healthy controls (HC) using behavioral tests with concomitant EEG recordings. N = 23 patients and N = 29 age- and sex-matched HC were studied. Sensory prediction coding was tested with an auditory distraction paradigm and error-related behavioral adaptation with a visual flanker task. As neurophysiological markers we studied different event-related potentials: the P3a for orientation of attention; the N2 and the error-related negativity (ERN) for cognitive adaptation processes/consequences of response errors; error-related positivity (Pe) for error-awareness; the mismatch negativity (MMN) for sensory predictive coding; and reorientation negativity (RON) for reorientation after unexpected events. Overall reaction times were slower in patients compared to HC, but error rates did not differ. Both in patients and HC, P3a amplitudes were larger in distraction trials, but the P3a amplitude was smaller in patients compared to HC. The MMN as well as behavioral and EEG-correlates of response adaptation (ERN/N2) did not differ between groups, while the Pe was attenuated in patients. During sensory predictive coding, RON amplitudes were significantly larger in HC compared to patients. In HC, but not in patients, RON amplitudes were also larger in deviant compared to frequent trials. Processes generating internal forward models are largely intact in genetically determined CA, whereas updating of mental models and error awareness are disturbed in these patients.

Differential changes to D1 and D2 medium spiny neurons in the 12-month-old Q175+/- mouse model of Huntington's Disease

Huntington's Disease (HD) is an autosomal dominant, progressive neurodegenerative disorder caused by deleterious expansion of CAG repeats in the Huntingtin gene and production of neurotoxic mutant Huntingtin protein (mHTT). The key pathological feature of HD is a profound degeneration of the striatum and a loss of cortical volume. The initial loss of indirect pathway (D2) medium spiny neuron (MSN) projections in early stages of HD, followed by a loss of direct pathway (D1) projections in advanced stages has important implications for the trajectory of motor and cognitive dysfunction in HD, but is not yet understood. Mouse models of HD have yielded important information on the effects and mechanisms of mHTT toxicity; however, whether these models recapitulate differential vulnerability of D1 vs. D2 MSNs is unknown. Here, we employed 12-month-old Q175+/- x D2-eGFP mice to examine the detailed structural and functional properties of D1 vs. D2 MSNs. While both D1 and D2 MSNs exhibited increased input resistance, depolarized resting membrane potentials and action potential threshold, only D1 MSNs showed reduced rheobase, action potential amplitude and frequency of spontaneous excitatory postsynaptic currents. Furthermore, D1 but not D2 MSNs showed marked proliferative changes to their dendritic arbors and reductions in spine density. Immunohistochemical assessment showed no loss of glutamatergic afferent inputs from cortical and subcortical sources onto identified D1 and D2 MSNs. Computational models constrained by empirical data predict that the increased dendritic complexity in Q175+/- D1 MSNs likely leads to greater dendritic filtering and attenuation of signals propagating to the soma from the dendrites. Together these findings reveal that, by twelve months, D1 and D2 MSNs exhibit distinctive responses to the presence of mHTT in this important mouse model of HD. This further highlights the need to incorporate findings from D1 and D2 MSNs independently in the context of HD models.

Dopamine Modulates the Efficiency of Sensory Evidence Accumulation During Perceptual Decision Making

BACKGROUND

Perceptual decision making is the process through which available sensory information is gathered and processed to guide our choices. However, the neuropsychopharmacological basis of this important cognitive function is largely elusive. Yet, theoretical considerations suggest that the dopaminergic system may play an important role.

METHODS

In a double-blind, randomized, placebo-controlled study design, we examined the effect of methylphenidate in 2 dosages (0.25 mg/kg and 0.5 mg/kg body weight) in separate groups of healthy young adults. We used a moving dots task in which the coherency of the direction of moving dots stimuli was manipulated in 3 levels (5%, 15%, and 35%). Drift diffusion modelling was applied to behavioral data to capture subprocesses of perceptual decision making.

RESULTS

The findings show that only the drift rate (v), reflecting the efficiency of sensory evidence accumulation, but not the decision criterion threshold (a) or the duration of nondecisional processes (Ter), is affected by methylphenidate vs placebo administration. Compared with placebo, administering 0.25 mg/kg methylphenidate increased v, but only in the 35% coherence condition. Administering 0.5 mg/kg methylphenidate did not induce modulations.

CONCLUSIONS

The data suggest that dopamine selectively modulates the efficacy of evidence accumulation during perceptual decision making. This modulation depends on 2 factors: (1) the degree to which the dopaminergic system is modulated using methylphenidate (i.e., methylphenidate dosage) and (2) the signal-to-noise ratio of the visual information. Dopamine affects sensory evidence accumulation only when dopamine concentration is not shifted beyond an optimal level and the incoming information is less noisy.

Basal Ganglia Neuromodulation Over Multiple Temporal and Structural Scales-Simulations of Direct Pathway MSNs Investigate the Fast Onset of Dopaminergic Effects and Predict the Role of Kv4.2

The basal ganglia are involved in the motivational and habitual control of motor and cognitive behaviors. Striatum, the largest basal ganglia input stage, integrates cortical and thalamic inputs in functionally segregated cortico-basal ganglia-thalamic loops, and in addition the basal ganglia output nuclei control targets in the brainstem. Striatal function depends on the balance between the direct pathway medium spiny neurons (D1-MSNs) that express D1 dopamine receptors and the indirect pathway MSNs that express D2 dopamine receptors. The striatal microstructure is also divided into striosomes and matrix compartments, based on the differential expression of several proteins. Dopaminergic afferents from the midbrain and local cholinergic interneurons play crucial roles for basal ganglia function, and striatal signaling via the striosomes in turn regulates the midbrain dopaminergic system directly and via the lateral habenula. Consequently, abnormal functions of the basal ganglia neuromodulatory system underlie many neurological and psychiatric disorders. Neuromodulation acts on multiple structural levels, ranging from the subcellular level to behavior, both in health and disease. For example, neuromodulation affects membrane excitability and controls synaptic plasticity and thus learning in the basal ganglia. However, it is not clear on what time scales these different effects are implemented. Phosphorylation of ion channels and the resulting membrane effects are typically studied over minutes while it has been shown that neuromodulation can affect behavior within a few hundred milliseconds. So how do these seemingly contradictory effects fit together? Here we first briefly review neuromodulation of the basal ganglia, with a focus on dopamine. We furthermore use biophysically detailed multi-compartmental models to integrate experimental data regarding dopaminergic effects on individual membrane conductances with the aim to explain the resulting cellular level dopaminergic effects. In particular we predict dopaminergic effects on Kv4.2 in D1-MSNs. Finally, we also explore dynamical aspects of the onset of neuromodulation effects in multi-scale computational models combining biochemical signaling cascades and multi-compartmental neuron models.

The role of cortical oscillations in a spiking neural network model of the basal ganglia

Although brain oscillations involving the basal ganglia (BG) have been the target of extensive research, the main focus lies disproportionally on oscillations generated within the BG circuit rather than other sources, such as cortical areas. We remedy this here by investigating the influence of various cortical frequency bands on the intrinsic effective connectivity of the BG, as well as the role of the latter in regulating cortical behaviour. To do this, we construct a detailed neural model of the complete BG circuit based on fine-tuned spiking neurons, with both electrical and chemical synapses as well as short-term plasticity between structures. As a measure of effective connectivity, we estimate information transfer between nuclei by means of transfer entropy. Our model successfully reproduces firing and oscillatory behaviour found in both the healthy and Parkinsonian BG. We found that, indeed, effective connectivity changes dramatically for different cortical frequency bands and phase offsets, which are able to modulate (or even block) information flow in the three major BG pathways. In particular, alpha (8–12Hz) and beta (13–30Hz) oscillations activate the direct BG pathway, and favour the modulation of the indirect and hyper-direct pathways via the subthalamic nucleus—globus pallidus loop. In contrast, gamma (30–90Hz) frequencies block the information flow from the cortex completely through activation of the indirect pathway. Finally, below alpha, all pathways decay gradually and the system gives rise to spontaneous activity generated in the globus pallidus. Our results indicate the existence of a multimodal gating mechanism at the level of the BG that can be entirely controlled by cortical oscillations, and provide evidence for the hypothesis of cortically-entrained but locally-generated subthalamic beta activity. These two findings suggest new insights into the pathophysiology of specific BG disorders.

Generation of low-gamma oscillations in a GABAergic network model of the striatum

Striatal oscillations in the low-gamma frequency range have been consistently recorded in a number of experimental studies. However, whether these rhythms are locally generated in the striatum circuit, which is mainly composed of GABAergic neurons, remains an open question. GABAergic medium spiny projection neurons represent the great majority of striatal neurons, but they fire at very low rates. GABAergic fast-spiking interneurons typically show firing rates that are approximately 10 times higher than those of principal neurons, but they are a very small minority of the total neuronal population. In this study, based on physiological constraints we developed a computational network model of these neurons and dissected the oscillations. Simulations showed that the population of medium spiny projection neurons, and not the GABAergic fast-spiking interneurons, determines the frequency range of the oscillations. D2-type dopamine receptor-expressing neurons dominate the generation of low-gamma rhythms. Feedforward inputs from GABAergic fast-spiking interneurons promote the oscillations by strengthening the inhibitory interactions between medium spiny projection neurons. The promotion effect is independent of the degree of synchronization in the fast-spiking interneuron population but affected by the strength of their feedforward inputs to medium spiny projection neurons. Our results provide a theoretical explanation for how firing properties and connections of the three types of GABAergic neurons, which are susceptible to on-going behaviors, experience, and dopamine disruptions, sculpt striatal oscillations.

Striatal Neuropeptides Enhance Selection and Rejection of Sequential Actions

The striatum is the primary input nucleus for the basal ganglia, and receives glutamatergic afferents from the cortex. Under the hypothesis that basal ganglia perform action selection, these cortical afferents encode potential “action requests.” Previous studies have suggested the striatum may utilize a mutually inhibitory network of medium spiny neurons (MSNs) to filter these requests so that only those of high salience are selected. However, the mechanisms enabling the striatum to perform clean, rapid switching between distinct actions that form part of a learned action sequence are still poorly understood. Substance P (SP) and enkephalin are neuropeptides co-released with GABA in MSNs preferentially expressing D₁ or D₂ dopamine receptors respectively. SP has a facilitatory effect on subsequent glutamatergic inputs to target MSNs, while enkephalin has an inhibitory effect. Blocking the action of SP in the striatum is also known to affect behavioral transitions. We constructed phenomenological models of the effects of SP and enkephalin, and integrated these into a hybrid model of basal ganglia comprising a spiking striatal microcircuit and rate–coded populations representing other major structures. We demonstrated that diffuse neuropeptide connectivity enhanced the selection of unordered action requests, and that for true action sequences, where action semantics define a fixed structure, a patterning of the SP connectivity reflecting this ordering enhanced selection of actions presented in the correct sequential order and suppressed incorrect ordering. We also showed that selective pruning of SP connections allowed context–sensitive inhibition of specific undesirable requests that otherwise interfered with selection of an action group. Our model suggests that the interaction of SP and enkephalin enhances the contrast between selection and rejection of action requests, and that patterned SP connectivity in the striatum allows the “chunking” of actions and improves selection of sequences. Efficient execution of action sequences may therefore result from a combination of ordered cortical inputs and patterned neuropeptide connectivity within striatum.

Dysfunctions in striatal microstructure can enhance perceptual decision making through deficits in predictive coding

An important brain function is to predict upcoming events on the basis of extracted regularities of previous inputs. These predictive coding processes can disturb performance in concurrent perceptual decision-making and are known to depend on fronto-striatal circuits. However, it is unknown whether, and if so, to what extent striatal microstructural properties modulate these processes. We addressed this question in a human disease model of striosomal dysfunction, i.e. X-linked dystonia-parkinsonism (XDP), using high-density EEG recordings and source localization. The results show faster and more accurate perceptual decision-making performance during distraction in XDP patients compared to healthy controls. The electrophysiological data show that sensory memory and predictive coding processes reflected by the mismatch negativity related to lateral prefrontal brain regions were weakened in XDP patients and thus induced less cognitive conflict than in controls as reflected by the N2 event-related potential (ERP). Consequently, attentional shifting (P3a ERP) and reorientation processes (RON ERP) were less pronounced in the XDP group. Taken together, these results suggests that striosomal dysfunction is related to predictive coding deficits leading to a better performance in concomitant perceptual decision-making, probably because predictive coding does not interfere with perceptual decision-making processes. These effects may reflect striatal imbalances between the striosomes and the matrix compartment.

Feedback for reinforcement learning based brain-machine interfaces using confidence metrics

OBJECTIVE

For brain-machine interfaces (BMI) to be used in activities of daily living by paralyzed individuals, the BMI should be as autonomous as possible. One of the challenges is how the feedback is extracted and utilized in the BMI. Our long-term goal is to create autonomous BMIs that can utilize an evaluative feedback from the brain to update the decoding algorithm and use it intelligently in order to adapt the decoder. In this study, we show how to extract the necessary evaluative feedback from a biologically realistic (synthetic) source, use both the quantity and the quality of the feedback, and how that feedback information can be incorporated into a reinforcement learning (RL) controller architecture to maximize its performance.

APPROACH

Motivated by the perception-action-reward cycle (PARC) in the brain which links reward for cognitive decision making and goal-directed behavior, we used a reward-based RL architecture named Actor-Critic RL as the model. Instead of using an error signal towards building an autonomous BMI, we envision to use a reward signal from the nucleus accumbens (NAcc) which plays a key role in the linking of reward to motor behaviors. To deal with the complexity and non-stationarity of biological reward signals, we used a confidence metric which was used to indicate the degree of feedback accuracy. This confidence was added to the Actor's weight update equation in the RL controller architecture. If the confidence was high (>0.2), the BMI decoder used this feedback to update its parameters. However, when the confidence was low, the BMI decoder ignored the feedback and did not update its parameters. The range between high confidence and low confidence was termed as the 'ambiguous' region. When the feedback was within this region, the BMI decoder updated its weight at a lower rate than when fully confident, which was decided by the confidence. We used two biologically realistic models to generate synthetic data for MI (Izhikevich model) and NAcc (Humphries model) to validate proposed controller architecture.

MAIN RESULTS

In this work, we show how the overall performance of the BMI was improved by using a threshold close to the decision boundary to reject erroneous feedback. Additionally, we show the stability of the system improved when the feedback was used with a threshold.

SIGNIFICANCE

The result of this study is a step towards making BMIs autonomous. While our method is not fully autonomous, the results demonstrate that extensive training times necessary at the beginning of each BMI session can be significantly decreased. In our approach, decoder training time was only limited to 10 trials in the first BMI session. Subsequent sessions used previous session weights to initialize the decoder. We also present a method where the use of a threshold can be applied to any decoder with a feedback signal that is less than perfect so that erroneous feedback can be avoided and the stability of the system can be increased.

Marked differences in the number and type of synapses innervating the somata and primary dendrites of midbrain dopaminergic neurons, striatal cholinergic interneurons, and striatal spiny projection neurons in the rat

Elucidating the link between cellular activity and goal-directed behavior requires a fuller understanding of the mechanisms underlying burst firing in midbrain dopaminergic neurons and those that suppress activity during aversive or non-rewarding events. We have characterized the afferent synaptic connections onto these neurons in the rat substantia nigra pars compacta (SNpc) and ventral tegmental area (VTA), and compared these findings with cholinergic interneurons and spiny projection neurons in the striatum. We found that the average absolute number of synapses was three to three and one-half times greater onto the somata of dorsal striatal spiny projection neurons than onto the somata of dopaminergic neurons in the SNpc or dorsal striatal cholinergic interneurons. A similar comparison between populations of dopamine neurons revealed a two times greater number of somatic synapses on VTA dopaminergic neurons than SNpc dopaminergic neurons. The percentage of symmetrical, presumably inhibitory, synaptic inputs on somata was significantly higher on spiny projection neurons and cholinergic interneurons compared with SNpc dopaminergic neurons. Synaptic data on the primary dendrites yielded similar significant differences for the percentage of symmetrical synapses for VTA dopaminergic vs. striatal neurons. No differences in the absolute number or type of somatic synapses were evident for dopaminergic neurons in the SNpc of Wistar vs. Sprague-Dawley rat strains. These data from identified neurons are pivotal for interpreting their electrophysiological responses to afferent activity and for generating realistic computer models of neuronal networks of striatal and midbrain dopaminergic function.

Decision-making and action selection in insects: inspiration from vertebrate-based theories

Effective decision-making, one of the most crucial functions of the brain, entails the analysis of sensory information and the selection of appropriate behavior in response to stimuli. Here, we consider the current state of knowledge on the mechanisms of decision-making and action selection in the insect brain, with emphasis on the olfactory processing system. Theoretical and computational models of decision-making emphasize the importance of using inhibitory connections to couple evidence-accumulating pathways; this coupling allows for effective discrimination between competing alternatives and thus enables a decision maker to reach a stable unitary decision. Theory also shows that the coupling of pathways can be implemented using a variety of different mechanisms and vastly improves the performance of decision-making systems. The vertebrate basal ganglia appear to resolve stable action selection by being a point of convergence for multiple excitatory and inhibitory inputs such that only one possible response is selected and all other alternatives are suppressed. Similar principles appear to operate within the insect brain. The insect lateral protocerebrum (LP) serves as a point of convergence for multiple excitatory and inhibitory channels of olfactory information to effect stable decision and action selection, at least for olfactory information. The LP is a rather understudied region of the insect brain, yet this premotor region may be key to effective resolution of action section. We argue that it may be beneficial to use models developed to explore the operation of the vertebrate brain as inspiration when considering action selection in the invertebrate domain. Such an approach may facilitate the proposal of new hypotheses and furthermore frame experimental studies for how decision-making and action selection might be achieved in insects.

A perspective on neural and cognitive mechanisms of error commission

Behavioral adaptation and cognitive control are crucial for goal-reaching behaviors. Every creature is ubiquitously faced with choices between behavioral alternatives. Common sense suggests that errors are an important source of information in the regulation of such processes. Several theories exist regarding cognitive control and the processing of undesired outcomes. However, most of these models focus on the consequences of an error, and less attention has been paid to the mechanisms that underlie the commissioning of an error. In this article, we present an integrative review of neuro-cognitive models that detail the determinants of the occurrence of response errors. The factors that may determine the likelihood of committing errors are likely related to the stability of task-representations in prefrontal networks, attentional selection mechanisms and mechanisms of action selection in basal ganglia circuits. An important conclusion is that the likelihood of committing an error is not stable over time but rather changes depending on the interplay of different functional neuro-anatomical and neuro-biological systems. We describe factors that might determine the time-course of cognitive control and the need to adapt behavior following response errors. Finally, we outline the mechanisms that may proof useful for predicting the outcomes of cognitive control and the emergence of response errors in future research.