A multi-region recurrent circuit for evidence accumulation in rats.

Decision-making based on noisy evidence requires accumulating evidence and categorizing it to form a choice. Here we evaluate a proposed feedforward and modular mapping of this process in rats: evidence accumulated in anterodorsal striatum (ADS) is categorized in prefrontal cortex (frontal orienting fields, FOF). Contrary to this, we show that both regions appear to be indistinguishable in their encoding/decoding of accumulator value and communicate this information bidirectionally. Consistent with a role for FOF in accumulation, silencing FOF to ADS projections impacted behavior throughout the accumulation period, even while nonselective FOF silencing did not. We synthesize these findings into a multi-region recurrent neural network trained with a novel approach. In-silico experiments reveal that multiple scales of recurrence in the cortico-striatal circuit rescue computation upon nonselective FOF perturbations. These results suggest that ADS and FOF accumulate evidence in a recurrent and distributed manner, yielding redundant representations and robustness to certain perturbations.

Trial-history biases in evidence accumulation can give rise to apparent lapses in decision-making.

Trial history biases and lapses are two of the most common suboptimalities observed during perceptual decision-making. These suboptimalities are routinely assumed to arise from distinct processes. However, previous work has suggested that they covary in their prevalence and that their proposed neural substrates overlap. Here we demonstrate that during decision-making, history biases and apparent lapses can both arise from a common cognitive process that is optimal under mistaken beliefs that the world is changing i.e. nonstationary. This corresponds to an accumulation-to-bound model with history-dependent updates to the initial state of the accumulator. We test our model's predictions about the relative prevalence of history biases and lapses, and show that they are robustly borne out in two distinct decision-making datasets of male rats, including data from a novel reaction time task. Our model improves the ability to precisely predict decision-making dynamics within and across trials, by positing a process through which agents can generate quasi-stochastic choices.

Transitions in dynamical regime and neural mode underlie perceptual decision-making.

Perceptual decision-making is the process by which an animal uses sensory stimuli to choose an action or mental proposition. This process is thought to be mediated by neurons organized as attractor networks 1,2 . However, whether attractor dynamics underlie decision behavior and the complex neuronal responses remains unclear. Here we use an unsupervised, deep learning-based method to discover decision-related dynamics from the simultaneous activity of neurons in frontal cortex and striatum of rats while they accumulate pulsatile auditory evidence. We show that contrary to prevailing hypotheses, attractors play a role only after a transition from a regime in the dynamics that is strongly driven by inputs to one dominated by the intrinsic dynamics. The initial regime mediates evidence accumulation, and the subsequent intrinsic-dominant regime subserves decision commitment. This regime transition is coupled to a rapid reorganization in the representation of the decision process in the neural population (a change in the "neural mode" along which the process develops). A simplified model approximating the coupled transition in the dynamics and neural mode allows inferring, from each trial's neural activity, the internal decision commitment time in that trial, and captures diverse and complex single-neuron temporal profiles, such as ramping and stepping 3-5 . It also captures trial-averaged curved trajectories 6-8 , and reveals distinctions between brain regions. Our results show that the formation of a perceptual choice involves a rapid, coordinated transition in both the dynamical regime and the neural mode of the decision process, and suggest pairing deep learning and parsimonious models as a promising approach for understanding complex data.

Trial-history biases in evidence accumulation can give rise to apparent lapses.

Trial history biases and lapses are two of the most common suboptimalities observed during perceptual decision-making. These suboptimalities are routinely assumed to arise from distinct processes. However, several hints in the literature suggest that they covary in their prevalence and that their proposed neural substrates overlap - what could underlie these links? Here we demonstrate that history biases and apparent lapses can both arise from a common cognitive process that is normative under misbeliefs about non-stationarity in the world. This corresponds to an accumulation-to-bound model with history-dependent updates to the initial state of the accumulator. We test our model's predictions about the relative prevalence of history biases and lapses, and show that they are robustly borne out in two distinct rat decision-making datasets, including data from a novel reaction time task. Our model improves the ability to precisely predict decision-making dynamics within and across trials, by positing a process through which agents can generate quasi-stochastic choices.

Collicular circuits for flexible sensorimotor routing.

Context-based sensorimotor routing is a hallmark of executive control. Pharmacological inactivations in rats have implicated the midbrain superior colliculus (SC) in this process. But what specific role is this, and what circuit mechanisms support it? Here we report a subset of rat SC neurons that instantiate a specific link between the representations of context and motor choice. Moreover, these neurons encode animals' choice far earlier than other neurons in the SC or in the frontal cortex, suggesting that their neural dynamics lead choice computation. Optogenetic inactivations revealed that SC activity during context encoding is necessary for choice behavior, even while that choice behavior is robust to inactivations during choice formation. Searches for SC circuit models matching our experimental results identified key circuit predictions while revealing some a priori expected features as unnecessary. Our results reveal circuit mechanisms within the SC that implement response inhibition and context-based vector inversion during executive control.

An approach for long-term, multi-probe Neuropixels recordings in unrestrained rats.

The use of Neuropixels probes for chronic neural recordings is in its infancy and initial studies leave questions about long-term stability and probe reusability unaddressed. Here, we demonstrate a new approach for chronic Neuropixels recordings over a period of months in freely moving rats. Our approach allows multiple probes per rat and multiple cycles of probe reuse. We found that hundreds of units could be recorded for multiple months, but that yields depended systematically on anatomical position. Explanted probes displayed a small increase in noise compared to unimplanted probes, but this was insufficient to impair future single-unit recordings. We conclude that cost-effective, multi-region, and multi-probe Neuropixels recordings can be carried out with high yields over multiple months in rats or other similarly sized animals. Our methods and observations may facilitate the standardization of chronic recording from Neuropixels probes in freely moving animals.

More than Just a "Motor": Recent Surprises from the Frontal Cortex.

Motor and premotor cortices are crucial for the control of movements. However, we still know little about how these areas contribute to higher-order motor control, such as deciding which movements to make and when to make them. Here we focus on rodent studies and review recent findings, which suggest that-in addition to motor control-neurons in motor cortices play a role in sensory integration, behavioral strategizing, working memory, and decision-making. We suggest that these seemingly disparate functions may subserve an evolutionarily conserved role in sensorimotor cognition and that further study of rodent motor cortices could make a major contribution to our understanding of the evolution and function of the mammalian frontal cortex.

Posterior parietal cortex represents sensory history and mediates its effects on behaviour.

Many models of cognition and of neural computations posit the use and estimation of prior stimulus statistics: it has long been known that working memory and perception are strongly impacted by previous sensory experience, even when that sensory history is not relevant to the current task at hand. Nevertheless, the neural mechanisms and regions of the brain that are necessary for computing and using such prior experience are unknown. Here we report that the posterior parietal cortex (PPC) is a critical locus for the representation and use of prior stimulus information. We trained rats in an auditory parametric working memory task, and found that they displayed substantial and readily quantifiable behavioural effects of sensory-stimulus history, similar to those observed in humans and monkeys. Earlier proposals that the PPC supports working memory predict that optogenetic silencing of this region would impair behaviour in our working memory task. Contrary to this prediction, we found that silencing the PPC significantly improved performance. Quantitative analyses of behaviour revealed that this improvement was due to the selective reduction of the effects of prior sensory stimuli. Electrophysiological recordings showed that PPC neurons carried far more information about the sensory stimuli of previous trials than about the stimuli of the current trial. Furthermore, for a given rat, the more information about previous trial sensory history in the neural firing rates of the PPC, the greater the behavioural effect of sensory history, suggesting a tight link between behaviour and PPC representations of stimulus history. Our results indicate that the PPC is a central component in the processing of sensory-stimulus history, and could enable further neurobiological investigation of long-standing questions regarding how perception and working memory are affected by prior sensory information.

Rat Prefrontal Cortex Inactivations during Decision Making Are Explained by Bistable Attractor Dynamics.

Two-node attractor networks are flexible models for neural activity during decision making. Depending on the network configuration, these networks can model distinct aspects of decisions including evidence integration, evidence categorization, and decision memory. Here, we use attractor networks to model recent causal perturbations of the frontal orienting fields (FOF) in rat cortex during a perceptual decision-making task (Erlich, Brunton, Duan, Hanks, & Brody, 2015 ). We focus on a striking feature of the perturbation results. Pharmacological silencing of the FOF resulted in a stimulus-independent bias. We fit several models to test whether integration, categorization, or decision memory could account for this bias and found that only the memory configuration successfully accounts for it. This memory model naturally accounts for optogenetic perturbations of FOF in the same task and correctly predicts a memory-duration-dependent deficit caused by silencing FOF in a different task. Our results provide mechanistic support for a "postcategorization" memory role of the FOF in upcoming choices.

Cortical and Subcortical Contributions to Short-Term Memory for Orienting Movements.

Neural activity in frontal cortical areas has been causally linked to short-term memory (STM), but whether this activity is necessary for forming, maintaining, or reading out STM remains unclear. In rats performing a memory-guided orienting task, the frontal orienting fields in cortex (FOF) are considered critical for STM maintenance, and during each trial display a monotonically increasing neural encoding for STM. Here, we transiently inactivated either the FOF or the superior colliculus and found that the resulting impairments in memory-guided orienting performance followed a monotonically decreasing time course, surprisingly opposite to the neural encoding. A dynamical attractor model in which STM relies equally on cortical and subcortical regions reconciled the encoding and inactivation data. We confirmed key predictions of the model, including a time-dependent relationship between trial difficulty and perturbability, and substantial, supralinear, impairment following simultaneous inactivation of the FOF and superior colliculus during memory maintenance.

Distinct relationships of parietal and prefrontal cortices to evidence accumulation.

Gradual accumulation of evidence is thought to be fundamental for decision-making, and its neural correlates have been found in several brain regions. Here we develop a generalizable method to measure tuning curves that specify the relationship between neural responses and mentally accumulated evidence, and apply it to distinguish the encoding of decision variables in posterior parietal cortex and prefrontal cortex (frontal orienting fields, FOF). We recorded the firing rates of neurons in posterior parietal cortex and FOF from rats performing a perceptual decision-making task. Classical analyses uncovered correlates of accumulating evidence, similar to previous observations in primates and also similar across the two regions. However, tuning curve assays revealed that while the posterior parietal cortex encodes a graded value of the accumulating evidence, the FOF has a more categorical encoding that indicates, throughout the trial, the decision provisionally favoured by the evidence accumulated so far. Contrary to current views, this suggests that premotor activity in the frontal cortex does not have a role in the accumulation process, but instead has a more categorical function, such as transforming accumulated evidence into a discrete choice. To probe causally the role of FOF activity, we optogenetically silenced it during different time points of the trial. Consistent with a role in committing to a categorical choice at the end of the evidence accumulation process, but not consistent with a role during the accumulation itself, a behavioural effect was observed only when FOF silencing occurred at the end of the perceptual stimulus. Our results place important constraints on the circuit logic of brain regions involved in decision-making.

Experience-dependent modification of a central amygdala fear circuit.

The amygdala is essential for fear learning and expression. The central amygdala (CeA), once viewed as a passive relay between the amygdala complex and downstream fear effectors, has emerged as an active participant in fear conditioning. However, the mechanism by which CeA contributes to the learning and expression of fear is unclear. We found that fear conditioning in mice induced robust plasticity of excitatory synapses onto inhibitory neurons in the lateral subdivision of the CeA (CeL). This experience-dependent plasticity was cell specific, bidirectional and expressed presynaptically by inputs from the lateral amygdala. In particular, preventing synaptic potentiation onto somatostatin-positive neurons impaired fear memory formation. Furthermore, activation of these neurons was necessary for fear memory recall and was sufficient to drive fear responses. Our findings support a model in which fear conditioning-induced synaptic modifications in CeL favor the activation of somatostatin-positive neurons, which inhibit CeL output, thereby disinhibiting the medial subdivision of CeA and releasing fear expression.

Semi-automated atlas-based analysis of brain histological sections.

Quantifying the location and/or number of features in a histological section of the brain currently requires one to first, manually register a corresponding section from a tissue atlas onto the experimental section and second, count the features. No automated method exists for the first process (registering), and most automated methods for the second process (feature counting) operate reliably only in a high signal-to-noise regime. To reduce experimenter bias and inconsistencies and increase the speed of these analyses, we developed Atlas Fitter, a semi-automated, open-source MatLab-based software package that assists in rapidly registering atlas panels onto histological sections. We also developed CellCounter, a novel fully automated cell counting algorithm that is designed to operate on images with non-uniform background intensities and low signal-to-noise ratios.

Human performance on the temporal bisection task.

The perception and processing of temporal information are tasks the brain must continuously perform. These include measuring the duration of stimuli, storing duration information in memory, recalling such memories, and comparing two durations. How the brain accomplishes these tasks, however, is still open for debate. The temporal bisection task, which requires subjects to compare temporal stimuli to durations held in memory, is perfectly suited to address these questions. Here we perform a meta-analysis of human performance on the temporal bisection task collected from 148 experiments spread across 18 independent studies. With this expanded data set we are able to show that human performance on this task contains a number of significant peculiarities, which in total no single model yet proposed has been able to explain. Here we present a simple 2-step decision model that is capable of explaining all the idiosyncrasies seen in the data.

Roles of stargazin and phosphorylation in the control of AMPA receptor subcellular distribution.

Understanding how the subcellular fate of newly synthesized AMPA receptors (AMPARs) is controlled is important for elucidating the mechanisms of neuronal function. We examined the effect of increased synthesis of AMPAR subunits on their subcellular distribution in rat hippocampal neurons. Virally expressed AMPAR subunits (GluR1 or GluR2) accumulated in cell bodies and replaced endogenous dendritic AMPAR with little effect on total dendritic amounts and caused no change in synaptic transmission. Coexpressing stargazin (STG) or mimicking GluR1 phosphorylation enhanced dendritic GluR1 levels by protecting GluR1 from lysosomal degradation. However, STG interaction or GluR1 phosphorylation did not increase surface or synaptic GluR1 levels. Unlike GluR1, STG did not protect GluR2 from lysosomal degradation or increase dendritic GluR2 levels. In general, AMPAR surface levels, and not intracellular amounts, correlated strongly with synaptic levels. Our results suggest that AMPAR surface expression, but not its intracellular production or accumulation, is critical for regulating synaptic transmission.

GluR1 links structural and functional plasticity at excitatory synapses.

Long-term potentiation (LTP), a cellular model of learning and memory, produces both an enhancement of synaptic function and an increase in the size of the associated dendritic spine. Synaptic insertion of AMPA receptors is known to play an important role in mediating the increase in synaptic strength during LTP, whereas the role of AMPA receptor trafficking in structural changes remains unexplored. Here, we examine how the cell maintains the correlation between spine size and synapse strength during LTP. We found that cells exploit an elegant solution by linking both processes to a single molecule: the AMPA-type glutamate receptor subunit 1 (GluR1). Synaptic insertion of GluR1 is required to permit a stable increase in spine size, both in hippocampal slice cultures and in vivo. Synaptic insertion of GluR1 is not sufficient to drive structural plasticity. Although crucial to the expression of LTP, the ion channel function of GluR1 is not required for the LTP-driven spine size enhancement. Remarkably, a recombinant cytosolic C-terminal fragment (C-tail) of GluR1 is driven to the postsynaptic density after an LTP stimulus, and the synaptic incorporation of this isolated GluR1 C-tail is sufficient to permit spine enlargement even when postsynaptic exocytosis of endogenous GluR1 is blocked. We conclude that during plasticity, synaptic insertion of GluR1 has two functions: the established role of increasing synaptic strength via its ligand-gated ion channel, and a novel role through the structurally stabilizing effect of its C terminus that permits an increase in spine size.

A robust automated method to analyze rodent motion during fear conditioning.

A central question in the study of LTP has been to determine what role it plays in memory formation and storage. One valuable form of learning for addressing this issue is associative fear conditioning. In this paradigm an animal learns to associate a tone and shock, such that subsequent presentation of a tone evokes a fear response (freezing behavior). Recent studies indicate that overlapping cellular processes underlie fear conditioning and LTP. The fear response has generally been scored manually which is both labor-intensive and subject to potential artifacts such as inconsistent or biased results. Here we describe a simple automated method that provides unbiased and rapid analysis of animal motion. We show that measured motion, in units termed significant motion pixels (SMPs), is both linear and robust over a wide range of animal speeds and detection thresholds and scores freezing in a quantitatively similar manner to trained human observers. By comparing the frequency distribution of motion during baseline periods and to the response to fox urine (which causes unconditioned fear), we suggest that freezing and non-freezing are distinct behaviors. Finally, we show how this algorithm can be applied to a fear conditioning paradigm yielding information on long and short-term associative memory as well as habituation. This automated analysis of fear conditioning will permit a more rapid and accurate assessment of the role of LTP in memory.

Glutamate receptor exocytosis and spine enlargement during chemically induced long-term potentiation.

The changes in synaptic morphology and receptor content that underlie neural plasticity are poorly understood. Here, we use a pH-sensitive green fluorescent protein to tag recombinant glutamate receptors and monitor their dynamics onto dendritic spine surfaces. We show that chemically induced long-term potentiation (chemLTP) drives robust exocytosis of AMPA receptors. In contrast, the same stimulus produces a small reduction of NMDA receptors from the spine surface. chemLTP produces similar modification of small and large spines. Interestingly, during chemLTP induction, spines increase in volume before accumulation of AMPA receptors on their surface, indicating that distinct mechanisms underlie changes in morphology and receptor content.

High-throughput fluorescent tagging of full-length Arabidopsis gene products in planta.

We developed a high-throughput methodology, termed fluorescent tagging of full-length proteins (FTFLP), to analyze expression patterns and subcellular localization of Arabidopsis gene products in planta. Determination of these parameters is a logical first step in functional characterization of the approximately one-third of all known Arabidopsis genes that encode novel proteins of unknown function. Our FTFLP-based approach offers two significant advantages: first, it produces internally-tagged full-length proteins that are likely to exhibit native intracellular localization, and second, it yields information about the tissue specificity of gene expression by the use of native promoters. To demonstrate how FTFLP may be used for characterization of the Arabidopsis proteome, we tagged a series of known proteins with diverse subcellular targeting patterns as well as several proteins with unknown function and unassigned subcellular localization.