The promise and perils of causal circuit manipulations

Human-derived monoclonal autoantibodies as interrogators of cellular proteotypes in the brain

A major aim of neuroscience is to identify and model the functional properties of neural cells whose dysfunction underlie neuropsychiatric illness. In this article, we propose that human-derived monoclonal autoantibodies (HD-mAbs) are well positioned to selectively target and manipulate neural subpopulations as defined by their protein expression; that is, cellular proteotypes. Recent technical advances allow for efficient cloning of autoantibodies from neuropsychiatric patients. These HD-mAbs can be introduced into animal models to gain biological and pathobiological insights about neural proteotypes of interest. Protein engineering can be used to modify, enhance, silence, or confer new functional properties to native HD-mAbs, thereby enhancing their versatility. Finally, we discuss the challenges and limitations confronting HD-mAbs as experimental research tools for neuroscience.

Motor cortical inactivation impairs corrective submovements in mice performing a hold-still center-out reach task

Holding still and aiming reaches to spatial targets may depend on distinct neural circuits. Using automated homecage training and a sensitive joystick, we trained freely moving mice to contact a joystick, hold their forelimb still, and then reach to rewarded target locations. Mice learned the task by initiating forelimb sequences with clearly resolved submillimeter-scale micromovements followed by millimeter-scale reaches to learned spatial targets. Hundreds of thousands of trajectories were decomposed into millions of kinematic submovements, while photoinhibition was used to test roles of motor cortical areas. Inactivation of both caudal and rostral forelimb areas preserved the ability to produce aimed reaches, but reduced reach speed. Inactivation specifically of contralateral caudal forelimb area (CFA) additionally impaired the ability to aim corrective submovements to remembered locations following target undershoots. Our findings show that motor cortical inactivations reduce the gain of forelimb movements but that inactivation specifically of contralateral CFA impairs corrective movements important for reaching a target location.NEW & NOTEWORTHY To test the role of different cortical areas in holding still and reaching to targets, this study combined home-cage training with optogenetic silencing as mice engaged in a learned center-out-reach task. Inactivation specifically of contralateral caudal forelimb area (CFA) impaired corrective movements necessary to reach spatial targets to earn reward.

Neuronal network dynamics in the posterodorsal amygdala: shaping reproductive hormone pulsatility

Normal reproductive function and fertility rely on the rhythmic secretion of gonadotropin-releasing hormone (GnRH), which is driven by the hypothalamic GnRH pulse generator. A key regulator of the GnRH pulse generator is the posterodorsal subnucleus of the medial amygdala (MePD), a brain region that is involved in processing external environmental cues, including the effect of stress. However, the neuronal pathways enabling the dynamic, stress-triggered modulation of GnRH secretion remain largely unknown. Here, we employ in silico modelling in order to explore the impact of dynamic inputs on GnRH pulse generator activity. We introduce and analyse a mathematical model representing MePD neuronal circuits composed of GABAergic and glutamatergic neuronal populations, integrating it with our GnRH pulse generator model. Our analysis dissects the influence of excitatory and inhibitory MePD projections' outputs on the GnRH pulse generator's activity and reveals a functionally relevant MePD glutamatergic projection to the GnRH pulse generator, which we probe with in vivo optogenetics. Our study sheds light on how MePD neuronal dynamics affect the GnRH pulse generator activity and offers insights into stress-related dysregulation.

Integrator dynamics in the cortico-basal ganglia loop underlie flexible motor timing

Flexible control of motor timing is crucial for behavior. Before volitional movement begins, the frontal cortex and striatum exhibit ramping spiking activity, with variable ramp slopes anticipating movement onsets. This activity in the cortico-basal ganglia loop may function as an adjustable 'timer,' triggering actions at the desired timing. However, because the frontal cortex and striatum share similar ramping dynamics and are both necessary for timing behaviors, distinguishing their individual roles in this timer function remains challenging. To address this, we conducted perturbation experiments combined with multi-regional electrophysiology in mice performing a flexible lick-timing task. Following transient silencing of the frontal cortex, cortical and striatal activity swiftly returned to pre-silencing levels and resumed ramping, leading to a shift in lick timing close to the silencing duration. Conversely, briefly inhibiting the striatum caused a gradual decrease in ramping activity in both regions, with ramping resuming from post-inhibition levels, shifting lick timing beyond the inhibition duration. Thus, inhibiting the frontal cortex and striatum effectively paused and rewound the timer, respectively. These findings suggest the striatum is a part of the network that temporally integrates input from the frontal cortex and generates ramping activity that regulates motor timing.

Topographical and cell type-specific connectivity of rostral and caudal forelimb corticospinal neuron populations

Corticospinal neurons (CSNs) synapse directly on spinal neurons, a diverse assortment of cells with unique structural and functional properties necessary for body movements. CSNs modulating forelimb behavior fractionate into caudal forelimb area (CFA) and rostral forelimb area (RFA) motor cortical populations. Despite their prominence, the full diversity of spinal neurons targeted by CFA and RFA CSNs is uncharted. Here, we use anatomical and RNA sequencing methods to show that CSNs synapse onto a remarkably selective group of spinal cell types, favoring inhibitory populations that regulate motoneuron activity and gate sensory feedback. CFA and RFA CSNs target similar spinal neuron types, with notable exceptions that suggest that these populations differ in how they influence behavior. Finally, axon collaterals of CFA and RFA CSNs target similar brain regions yet receive highly divergent inputs. These results detail the rules of CSN connectivity throughout the brain and spinal cord for two regions critical for forelimb behavior.

Recurrent Neural Circuits Overcome Partial Inactivation by Compensation and Re-learning

Technical advances in artificial manipulation of neural activity have precipitated a surge in studying the causal contribution of brain circuits to cognition and behavior. However, complexities of neural circuits challenge interpretation of experimental results, necessitating new theoretical frameworks for reasoning about causal effects. Here, we take a step in this direction, through the lens of recurrent neural networks trained to perform perceptual decisions. We show that understanding the dynamical system structure that underlies network solutions provides a precise account for the magnitude of behavioral effects due to perturbations. Our framework explains past empirical observations by clarifying the most sensitive features of behavior, and how complex circuits compensate and adapt to perturbations. In the process, we also identify strategies that can improve the interpretability of inactivation experiments.

Integrating across behaviors and timescales to understand the neural control of movement

The nervous system evolved to enable navigation throughout the environment in the pursuit of resources. Evolutionarily newer structures allowed increasingly complex adaptations but necessarily added redundancy. A dominant view of movement neuroscientists is that there is a one-to-one mapping between brain region and function. However, recent experimental data is hard to reconcile with the most conservative interpretation of this framework, suggesting a degree of functional redundancy during the performance of well-learned, constrained behaviors. This apparent redundancy likely stems from the bidirectional interactions between the various cortical and subcortical structures involved in motor control. We posit that these bidirectional connections enable flexible interactions across structures that change depending upon behavioral demands, such as during acquisition, execution or adaptation of a skill. Observing the system across both multiple actions and behavioral timescales can help isolate the functional contributions of individual structures, leading to an integrated understanding of the neural control of movement.

The influence of cortical activity on perception depends on behavioral state and sensory context

The mechanistic link between neural circuit activity and behavior remains unclear. While manipulating cortical activity can bias certain behaviors and elicit artificial percepts, some tasks can still be solved when cortex is silenced or removed. Here, mice were trained to perform a visual detection task during which we selectively targeted groups of visually responsive and co-tuned neurons in L2/3 of primary visual cortex (V1) for two-photon photostimulation. The influence of photostimulation was conditional on two key factors: the behavioral state of the animal and the contrast of the visual stimulus. The detection of low-contrast stimuli was enhanced by photostimulation, while the detection of high-contrast stimuli was suppressed, but crucially, only when mice were highly engaged in the task. When mice were less engaged, our manipulations of cortical activity had no effect on behavior. The behavioral changes were linked to specific changes in neuronal activity. The responses of non-photostimulated neurons in the local network were also conditional on two factors: their functional similarity to the photostimulated neurons and the contrast of the visual stimulus. Functionally similar neurons were increasingly suppressed by photostimulation with increasing visual stimulus contrast, correlating with the change in behavior. Our results show that the influence of cortical activity on perception is not fixed, but dynamically and contextually modulated by behavioral state, ongoing activity and the routing of information through specific circuits.

Direct contribution of the sensory cortex to the judgment of stimulus duration

Decision making frequently depends on monitoring the duration of sensory events. To determine whether, and how, the perception of elapsed time derives from the neuronal representation of the stimulus itself, we recorded and optogenetically modulated vibrissal somatosensory cortical activity as male rats judged vibration duration. Perceived duration was dilated by optogenetic excitation. A second set of rats judged vibration intensity; here, optogenetic excitation amplified the intensity percept, demonstrating sensory cortex to be the common gateway both to time and to stimulus feature processing. A model beginning with the membrane currents evoked by vibrissal and optogenetic drive and culminating in the representation of perceived time successfully replicated rats' choices. Time perception is thus as deeply intermeshed within the sensory processing pathway as is the sense of touch itself, suggesting that the experience of time may be further investigated with the toolbox of sensory coding.

Causation in neuroscience: keeping mechanism meaningful

A fundamental goal of research in neuroscience is to uncover the causal structure of the brain. This focus on causation makes sense, because causal information can provide explanations of brain function and identify reliable targets with which to understand cognitive function and prevent or change neurological conditions and psychiatric disorders. In this research, one of the most frequently used causal concepts is 'mechanism' - this is seen in the literature and language of the field, in grant and funding inquiries that specify what research is supported, and in journal guidelines on which contributions are considered for publication. In these contexts, mechanisms are commonly tied to expressions of the main aims of the field and cited as the 'fundamental', 'foundational' and/or 'basic' unit for understanding the brain. Despite its common usage and perceived importance, mechanism is used in different ways that are rarely distinguished. Given that this concept is defined in different ways throughout the field - and that there is often no clarification of which definition is intended - there remains a marked ambiguity about the fundamental goals, orientation and principles of the field. Here we provide an overview of causation and mechanism from the perspectives of neuroscience and philosophy of science, in order to address these challenges.

Downstream network transformations dissociate neural activity from causal functional contributions

Neuroscientists rely on distributed spatio-temporal patterns of neural activity to understand how neural units contribute to cognitive functions and behavior. However, the extent to which neural activity reliably indicates a unit's causal contribution to the behavior is not well understood. To address this issue, we provide a systematic multi-site perturbation framework that captures time-varying causal contributions of elements to a collectively produced outcome. Applying our framework to intuitive toy examples and artificial neural networks revealed that recorded activity patterns of neural elements may not be generally informative of their causal contribution due to activity transformations within a network. Overall, our findings emphasize the limitations of inferring causal mechanisms from neural activities and offer a rigorous lesioning framework for elucidating causal neural contributions.

The Basal Ganglia and Mesencephalic Locomotor Region Connectivity Matrix

Although classically considered a relay station for basal ganglia (BG) output, the anatomy, connectivity, and function of the mesencephalic locomotor region (MLR) were redefined during the last two decades. In striking opposition to what was initially thought, MLR and BG are actually reciprocally and intimately interconnected. New viral-based, optogenetic, and mapping technologies revealed that cholinergic, glutamatergic, and GABAergic neurons coexist in this structure, which, in addition to extending descending projections, send long-range ascending fibers to the BG. These MLR projections to the BG convey motor and non-motor information to specific synaptic targets throughout different nuclei. Moreover, MLR efferent fibers originate from precise neuronal subpopulations located in particular MLR subregions, defining independent anatomo-functional subcircuits involved in particular aspects of animal behavior such as fast locomotion, explorative locomotion, posture, forelimb- related movements, speed, reinforcement, among others. In this review, we revised the literature produced during the last decade linking MLR and BG. We conclude that the classic framework considering the MLR as a homogeneous output structure passively receiving input from the BG needs to be revisited. We propose instead that the multiple subcircuits embedded in this region should be taken as independent entities that convey relevant and specific ascending information to the BG and, thus, actively participate in the execution and tuning of behavior.

Topographical and cell type-specific connectivity of rostral and caudal forelimb corticospinal neuron populations

Corticospinal neurons (CSNs) synapse directly on spinal neurons, a diverse group of neurons with unique structural and functional properties necessary for body movements. CSNs modulating forelimb behavior fractionate into caudal forelimb area (CFA) and rostral forelimb area (RFA) motor cortical populations. Despite their prominence, no studies have mapped the diversity of spinal cell types targeted by CSNs, let alone compare CFA and RFA populations. Here we use anatomical and RNA-sequencing methods to show that CSNs synapse onto a remarkably selective group of spinal cell types, favoring inhibitory populations that regulate motoneuron activity and gate sensory feedback. CFA and RFA CSNs target similar spinal cell types, with notable exceptions that suggest these populations differ in how they influence behavior. Finally, axon collaterals of CFA and RFA CSNs target similar brain regions yet receive surprisingly divergent inputs. These results detail the rules of CSN connectivity throughout the brain and spinal cord for two regions critical for forelimb behavior.

Pathway specific interventions reveal the multiple roles of ventral hippocampus projections in cognitive functions

Since the 1950s study of Scoville and Milner on the case H.M., the hippocampus has attracted neuroscientists' attention. The hippocampus has been traditionally divided into dorsal and ventral parts, each of which projects to different brain structures and mediates various functions. Despite a predominant interest in its dorsal part in animal models, especially regarding episodic-like and spatial cognition, recent data highlight the role of the ventral hippocampus (vHPC), as the main hippocampal output, in cognitive processes. Here, we review recent studies conducted in rodents that have used advanced in vivo functional techniques to specifically monitor and manipulate vHPC efferent pathways and delineate the roles of these specific projections in learning and memory processes. Results highlight that vHPC projections to basal amygdala are implicated in emotional memory, to nucleus accumbens in social memory and instrumental actions and to prefrontal cortex in all the above as well as in object-based memory. Some of these hippocampal projections also modulate feeding and anxiety-like behaviours providing further evidence that the "one pathway-one function" view is outdated and future directions are proposed to better understand the role of hippocampal pathways and shed further light on its connectivity and function.

Heterogeneous off-target impact of ion-channel deletion on intrinsic properties of hippocampal model neurons that self-regulate calcium

How do neurons that implement cell-autonomous self-regulation of calcium react to knockout of individual ion-channel conductances? To address this question, we used a heterogeneous population of 78 conductance-based models of hippocampal pyramidal neurons that maintained cell-autonomous calcium homeostasis while receiving theta-frequency inputs. At calcium steady-state, we individually deleted each of the 11 active ion-channel conductances from each model. We measured the acute impact of deleting each conductance (one at a time) by comparing intrinsic electrophysiological properties before and immediately after channel deletion. The acute impact of deleting individual conductances on physiological properties (including calcium homeostasis) was heterogeneous, depending on the property, the specific model, and the deleted channel. The underlying many-to-many mapping between ion channels and properties pointed to ion-channel degeneracy. Next, we allowed the other conductances (barring the deleted conductance) to evolve towards achieving calcium homeostasis during theta-frequency activity. When calcium homeostasis was perturbed by ion-channel deletion, post-knockout plasticity in other conductances ensured resilience of calcium homeostasis to ion-channel deletion. These results demonstrate degeneracy in calcium homeostasis, as calcium homeostasis in knockout models was implemented in the absence of a channel that was earlier involved in the homeostatic process. Importantly, in reacquiring homeostasis, ion-channel conductances and physiological properties underwent heterogenous plasticity (dependent on the model, the property, and the deleted channel), even introducing changes in properties that were not directly connected to the deleted channel. Together, post-knockout plasticity geared towards maintaining homeostasis introduced heterogenous off-target effects on several channels and properties, suggesting that extreme caution be exercised in interpreting experimental outcomes involving channel knockouts.

Visuo-vestibular heading perception: a model system to study multi-sensory decision making

Integrating noisy signals across time as well as sensory modalities, a process named multi-sensory decision making (MSDM), is an essential strategy for making more accurate and sensitive decisions in complex environments. Although this field is just emerging, recent extraordinary works from different perspectives, including computational theory, psychophysical behaviour and neurophysiology, begin to shed new light onto MSDM. In the current review, we focus on MSDM by using a model system of visuo-vestibular heading. Combining well-controlled behavioural paradigms on virtual-reality systems, single-unit recordings, causal manipulations and computational theory based on spiking activity, recent progress reveals that vestibular signals contain complex temporal dynamics in many brain regions, including unisensory, multi-sensory and sensory-motor association areas. This challenges the brain for cue integration across time and sensory modality such as optic flow which mainly contains a motion velocity signal. In addition, new evidence from the higher-level decision-related areas, mostly in the posterior and frontal/prefrontal regions, helps revise our conventional thought on how signals from different sensory modalities may be processed, converged, and moment-by-moment accumulated through neural circuits for forming a unified, optimal perceptual decision. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Propagation of activity through the cortical hierarchy and perception are determined by neural variability

Brains are composed of anatomically and functionally distinct regions performing specialized tasks, but regions do not operate in isolation. Orchestration of complex behaviors requires communication between brain regions, but how neural dynamics are organized to facilitate reliable transmission is not well understood. Here we studied this process directly by generating neural activity that propagates between brain regions and drives behavior, assessing how neural populations in sensory cortex cooperate to transmit information. We achieved this by imaging two densely interconnected regions-the primary and secondary somatosensory cortex (S1 and S2)-in mice while performing two-photon photostimulation of S1 neurons and assigning behavioral salience to the photostimulation. We found that the probability of perception is determined not only by the strength of the photostimulation but also by the variability of S1 neural activity. Therefore, maximizing the signal-to-noise ratio of the stimulus representation in cortex relative to the noise or variability is critical to facilitate activity propagation and perception.

Mechanosensory Control of Locomotion in Animals and Robots: Moving Forward

While animals swim, crawl, walk, and fly with apparent ease, building robots capable of robust locomotion remains a significant challenge. In this review, we draw attention to mechanosensation-the sensing of mechanical forces generated within and outside the body-as a key sense that enables robust locomotion in animals. We discuss differences between mechanosensation in animals and current robots with respect to (1) the encoding properties and distribution of mechanosensors and (2) the integration and regulation of mechanosensory feedback. We argue that robotics would benefit greatly from a detailed understanding of these aspects in animals. To that end, we highlight promising experimental and engineering approaches to study mechanosensation, emphasizing the mutual benefits for biologists and engineers that emerge from moving forward together.

Interchangeable Role of Motor Cortex and Reafference for the Stable Execution of an Orofacial Action

Animals interact with their environment through mechanically active, mobile sensors. The efficient use of these sensory organs implies the ability to track their position; otherwise, perceptual stability or prehension would be profoundly impeded. The nervous system may keep track of the position of a sensorimotor organ via two complementary feedback mechanisms-peripheral reafference (external, sensory feedback) and efference copy (internal feedback). Yet, the potential contributions of these mechanisms remain largely unexplored. By training male rats to place one of their vibrissae within a predetermined angular range without contact, a task that depends on knowledge of vibrissa position relative to their face, we found that peripheral reafference is not required. The presence of motor cortex is not required either, except in the absence of peripheral reafference to maintain motor stability. Finally, the red nucleus, which receives descending inputs from motor cortex and cerebellum and projects to facial motoneurons, is critically involved in the execution of the vibrissa positioning task. All told, our results point toward the existence of an internal model that requires either peripheral reafference or motor cortex to optimally drive voluntary motion.SIGNIFICANCE STATEMENT How does an animal know where a mechanically active, mobile sensor lies relative to its body? We address this basic question in sensorimotor integration using the motion of the vibrissae in rats. We show that rats can learn to reliably position their vibrissae in the absence of sensory feedback or in the absence of motor cortex. Yet, when both sensory feedback and motor cortex are absent, motor precision is degraded. This suggests the existence of an internal model able to operate in closed- and open-loop modes, requiring either motor cortex or sensory feedback to maintain motor stability.

When Neural Activity Fails to Reveal Causal Contributions

Neuroscientists rely on distributed spatio-temporal patterns of neural activity to understand how neural units contribute to cognitive functions and behavior. However, the extent to which neural activity reliably indicates a unit's causal contribution to the behavior is not well understood. To address this issue, we provide a systematic multi-site perturbation framework that captures time-varying causal contributions of elements to a collectively produced outcome. Applying our framework to intuitive toy examples and artificial neuronal networks revealed that recorded activity patterns of neural elements may not be generally informative of their causal contribution due to activity transformations within a network. Overall, our findings emphasize the limitations of inferring causal mechanisms from neural activities and offer a rigorous lesioning framework for elucidating causal neural contributions.

Temporal lobe perceptual predictions for speech are instantiated in motor cortex and reconciled by inferior frontal cortex

Humans use predictions to improve speech perception, especially in noisy environments. Here we use 7-T functional MRI (fMRI) to decode brain representations of written phonological predictions and degraded speech signals in healthy humans and people with selective frontal neurodegeneration (non-fluent variant primary progressive aphasia [nfvPPA]). Multivariate analyses of item-specific patterns of neural activation indicate dissimilar representations of verified and violated predictions in left inferior frontal gyrus, suggestive of processing by distinct neural populations. In contrast, precentral gyrus represents a combination of phonological information and weighted prediction error. In the presence of intact temporal cortex, frontal neurodegeneration results in inflexible predictions. This manifests neurally as a failure to suppress incorrect predictions in anterior superior temporal gyrus and reduced stability of phonological representations in precentral gyrus. We propose a tripartite speech perception network in which inferior frontal gyrus supports prediction reconciliation in echoic memory, and precentral gyrus invokes a motor model to instantiate and refine perceptual predictions for speech.

Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3

Recurrent connectivity between excitatory neurons and the strength of feedback from inhibitory neurons are critical determinants of the dynamics and computational properties of neuronal circuits. Toward a better understanding of these circuit properties in regions CA1 and CA3 of the hippocampus, we performed optogenetic manipulations combined with large-scale unit recordings in rats under anesthesia and in quiet waking, using photoinhibition and photoexcitation with different light-sensitive opsins. In both regions, we saw striking paradoxical responses: subsets of cells increased firing during photoinhibition, while other cells decreased firing during photoexcitation. These paradoxical responses were more prominent in CA3 than in CA1, but, notably, CA1 interneurons showed increased firing in response to photoinhibition of CA3. These observations were recapitulated in simulations where we modeled both CA1 and CA3 as inhibition-stabilized networks in which strong recurrent excitation is balanced by feedback inhibition. To directly test the inhibition-stabilized model, we performed large-scale photoinhibition directed at (GAD-Cre) inhibitory cells and found that interneurons in both regions increased firing when photoinhibited, as predicted. Our results highlight the often-paradoxical circuit dynamics that are evidenced during optogenetic manipulations and indicate that, contrary to long-standing dogma, both CA1 and CA3 hippocampal regions display strongly recurrent excitation, which is stabilized through inhibition.

Neural Mechanisms That Make Perceptual Decisions Flexible

Neural mechanisms of perceptual decision making have been extensively studied in experimental settings that mimic stable environments with repeating stimuli, fixed rules, and payoffs. In contrast, we live in an ever-changing environment and have varying goals and behavioral demands. To accommodate variability, our brain flexibly adjusts decision-making processes depending on context. Here, we review a growing body of research that explores the neural mechanisms underlying this flexibility. We highlight diverse forms of context dependency in decision making implemented through a variety of neural computations. Context-dependent neural activity is observed in a distributed network of brain structures, including posterior parietal, sensory, motor, and subcortical regions, as well as the prefrontal areas classically implicated in cognitive control. We propose that investigating the distributed network underlying flexible decisions is key to advancing our understanding and discuss a path forward for experimental and theoretical investigations.

Multi-area recordings and optogenetics in the awake, behaving marmoset

The common marmoset has emerged as a key model in neuroscience. Marmosets are small in size, show great potential for genetic modification and exhibit complex behaviors. Thus, it is necessary to develop technology that enables monitoring and manipulation of the underlying neural circuits. Here, we describe a novel approach to record and optogenetically manipulate neural activity in awake, behaving marmosets. Our design utilizes a light-weight, 3D printed titanium chamber that can house several high-density silicon probes for semi-chronic recordings, while enabling simultaneous optogenetic stimulation. We demonstrate the application of our method in male marmosets by recording multi- and single-unit data from areas V1 and V6 with 192 channels simultaneously, and show that optogenetic activation of excitatory neurons in area V6 can influence behavior in a detection task. This method may enable future studies to investigate the neural basis of perception and behavior in the marmoset.

Columnar Lesions in Barrel Cortex Persistently Degrade Object Location Discrimination Performance

Primary sensory cortices display functional topography, suggesting that even small cortical volumes may underpin perception of specific stimuli. Traditional loss-of-function approaches have a relatively large radius of effect (>1 mm), and few studies track recovery following loss-of-function perturbations. Consequently, the behavioral necessity of smaller cortical volumes remains unclear. In the mouse primary vibrissal somatosensory cortex (vS1), "barrels" with a radius of ∼150 μm receive input predominantly from a single whisker, partitioning vS1 into a topographic map of well defined columns. Here, we train animals implanted with a cranial window over vS1 to perform single-whisker perceptual tasks. We then use high-power laser exposure centered on the barrel representing the spared whisker to produce lesions with a typical volume of one to two barrels. These columnar-scale lesions impair performance in an object location discrimination task for multiple days without disrupting vibrissal kinematics. Animals with degraded location discrimination performance can immediately perform a whisker touch detection task with high accuracy. Animals trained de novo on both simple and complex whisker touch detection tasks showed no permanent behavioral deficits following columnar-scale lesions. Thus, columnar-scale lesions permanently degrade performance in object location discrimination tasks.

Neuronal circuitry for recognition memory of object and place in rodent models

Rats and mice are used for studying neuronal circuits underlying recognition memory due to their ability to spontaneously remember the occurrence of an object, its place and an association of the object and place in a particular environment. A joint employment of lesions, pharmacological interventions, optogenetics and chemogenetics is constantly expanding our knowledge of the neural basis for recognition memory of object, place, and their association. In this review, we summarize current studies on recognition memory in rodents with a focus on the novel object preference, novel location preference and object-in-place paradigms. The evidence suggests that the medial prefrontal cortex- and hippocampus-connected circuits contribute to recognition memory for object and place. Under certain conditions, the striatum, medial septum, amygdala, locus coeruleus and cerebellum are also involved. We propose that the neuronal circuitry for recognition memory of object and place is hierarchically connected and constructed by different cortical (perirhinal, entorhinal and retrosplenial cortices), thalamic (nucleus reuniens, mediodorsal and anterior thalamic nuclei) and primeval (hypothalamus and interpeduncular nucleus) modules interacting with the medial prefrontal cortex and hippocampus.

A call for more clarity around causality in neuroscience

In neuroscience, the term 'causality' is used to refer to different concepts, leading to confusion. Here we illustrate some of those variations, and we suggest names for them. We then introduce four ways to enhance clarity around causality in neuroscience.

The emergence and influence of internal states

Animal behavior is shaped by a variety of "internal states"-partially hidden variables that profoundly shape perception, cognition, and action. The neural basis of internal states, such as fear, arousal, hunger, motivation, aggression, and many others, is a prominent focus of research efforts across animal phyla. Internal states can be inferred from changes in behavior, physiology, and neural dynamics and are characterized by properties such as pleiotropy, persistence, scalability, generalizability, and valence. To date, it remains unclear how internal states and their properties are generated by nervous systems. Here, we review recent progress, which has been driven by advances in behavioral quantification, cellular manipulations, and neural population recordings. We synthesize research implicating defined subsets of state-inducing cell types, widespread changes in neural activity, and neuromodulation in the formation and updating of internal states. In addition to highlighting the significance of these findings, our review advocates for new approaches to clarify the underpinnings of internal brain states across the animal kingdom.

Neural Algorithms and Circuits for Motor Planning

The brain plans and executes volitional movements. The underlying patterns of neural population activity have been explored in the context of movements of the eyes, limbs, tongue, and head in nonhuman primates and rodents. How do networks of neurons produce the slow neural dynamics that prepare specific movements and the fast dynamics that ultimately initiate these movements? Recent work exploits rapid and calibrated perturbations of neural activity to test specific dynamical systems models that are capable of producing the observed neural activity. These joint experimental and computational studies show that cortical dynamics during motor planning reflect fixed points of neural activity (attractors). Subcortical control signals reshape and move attractors over multiple timescales, causing commitment to specific actions and rapid transitions to movement execution. Experiments in rodents are beginning to reveal how these algorithms are implemented at the level of brain-wide neural circuits.

Recentering neuroscience on behavior: The interface between brain and environment is a privileged level of control of neural activity

Despite the huge and constant progress in the molecular and cellular neuroscience fields, our capability to understand brain alterations and treat mental illness is still limited. Therefore, a paradigm shift able to overcome such limitation is warranted. Behavior and the associated mental states are the interface between the central nervous system and the living environment. Since, in any system, the interface is a key regulator of system organization, behavior is proposed here as a unique and privileged level of control and orchestration of brain structure and activity. This view has relevant scientific and clinical implications. First, the study of behavior represents a singular starting point for the investigation of neural activity in an integrated and comprehensive fashion. Second, behavioral changes, accomplished through psychotherapy or environmental interventions, are expected to have the highest impact to specifically reorganize the complexity of the human mind and thus achieve a solid and long-lasting improvement in mental health.

Advantages, Pitfalls, and Developments of All Optical Interrogation Strategies of Microcircuits in vivo

The holy grail for every neurophysiologist is to conclude a causal relationship between an elementary behaviour and the function of a specific brain area or circuit. Our effort to map elementary behaviours to specific brain loci and to further manipulate neural activity while observing the alterations in behaviour is in essence the goal for neuroscientists. Recent advancements in the area of experimental brain imaging in the form of longer wavelength near infrared (NIR) pulsed lasers with the development of highly efficient optogenetic actuators and reporters of neural activity, has endowed us with unprecedented resolution in spatiotemporal precision both in imaging neural activity as well as manipulating it with multiphoton microscopy. This readily available toolbox has introduced a so called all-optical physiology and interrogation of circuits and has opened new horizons when it comes to precisely, fast and non-invasively map and manipulate anatomically, molecularly or functionally identified mesoscopic brain circuits. The purpose of this review is to describe the advantages and possible pitfalls of all-optical approaches in system neuroscience, where by all-optical we mean use of multiphoton microscopy to image the functional response of neuron(s) in the network so to attain flexible choice of the cells to be also optogenetically photostimulated by holography, in absence of electrophysiology. Spatio-temporal constraints will be compared toward the classical reference of electrophysiology methods. When appropriate, in relation to current limitations of current optical approaches, we will make reference to latest works aimed to overcome these limitations, in order to highlight the most recent developments. We will also provide examples of types of experiments uniquely approachable all-optically. Finally, although mechanically non-invasive, all-optical electrophysiology exhibits potential off-target effects which can ambiguate and complicate the interpretation of the results. In summary, this review is an effort to exemplify how an all-optical experiment can be designed, conducted and interpreted from the point of view of the integrative neurophysiologist.

Human lesions and animal studies link the claustrum to perception, salience, sleep and pain

The claustrum is the most densely interconnected region in the human brain. Despite the accumulating data from clinical and experimental studies, the functional role of the claustrum remains unknown. Here, we systematically review claustrum lesion studies and discuss their functional implications. Claustral lesions are associated with an array of signs and symptoms, including changes in cognitive, perceptual and motor abilities; electrical activity; mental state; and sleep. The wide range of symptoms observed following claustral lesions do not provide compelling evidence to support prominent current theories of claustrum function such as multisensory integration or salience computation. Conversely, the lesions studies support the hypothesis that the claustrum regulates cortical excitability. We argue that the claustrum is connected to, or part of, multiple brain networks that perform both fundamental and higher cognitive functions. As a multifunctional node in numerous networks, this may explain the manifold effects of claustrum damage on brain and behaviour.

The geometry of robustness in spiking neural networks

Neural systems are remarkably robust against various perturbations, a phenomenon that still requires a clear explanation. Here, we graphically illustrate how neural networks can become robust. We study spiking networks that generate low-dimensional representations, and we show that the neurons’ subthreshold voltages are confined to a convex region in a lower-dimensional voltage subspace, which we call a 'bounding box'. Any changes in network parameters (such as number of neurons, dimensionality of inputs, firing thresholds, synaptic weights, or transmission delays) can all be understood as deformations of this bounding box. Using these insights, we show that functionality is preserved as long as perturbations do not destroy the integrity of the bounding box. We suggest that the principles underlying robustness in these networks — low-dimensional representations, heterogeneity of tuning, and precise negative feedback — may be key to understanding the robustness of neural systems at the circuit level.

Functional Organisation of the Mouse Superior Colliculus

The superior colliculus (SC) is a highly conserved area of the mammalian midbrain that is widely implicated in the organisation and control of behaviour. SC receives input from a large number of brain areas, and provides outputs to a large number of areas. The convergence and divergence of anatomical connections with different areas and systems provides challenges for understanding how SC contributes to behaviour. Recent work in mouse has provided large anatomical datasets, and a wealth of new data from experiments that identify and manipulate different cells within SC, and their inputs and outputs, during simple behaviours. These data offer an opportunity to better understand the roles that SC plays in these behaviours. However, some of the observations appear, at first sight, to be contradictory. Here we review this recent work and hypothesise a simple framework which can capture the observations, that requires only a small change to previous models. Specifically, the functional organisation of SC can be explained by supposing that three largely distinct circuits support three largely distinct classes of simple behaviours-arrest, turning towards, and the triggering of escape or capture. These behaviours are hypothesised to be supported by the optic, intermediate and deep layers, respectively.

Causal Evidence for the Multiple Demand Network in Change Detection: Auditory Mismatch Magnetoencephalography across Focal Neurodegenerative Diseases

The multiple demand (MD) system is a network of fronto-parietal brain regions active during the organization and control of diverse cognitive operations. It has been argued that this activation may be a nonspecific signal of task difficulty. However, here we provide convergent evidence for a causal role for the MD network in the "simple task" of automatic auditory change detection, through the impairment of top-down control mechanisms. We employ independent structure-function mapping, dynamic causal modeling (DCM), and frequency-resolved functional connectivity analyses of MRI and magnetoencephalography (MEG) from 75 mixed-sex human patients across four neurodegenerative syndromes [behavioral variant fronto-temporal dementia (bvFTD), nonfluent variant primary progressive aphasia (nfvPPA), posterior cortical atrophy (PCA), and Alzheimer's disease mild cognitive impairment with positive amyloid imaging (ADMCI)] and 48 age-matched controls. We show that atrophy of any MD node is sufficient to impair auditory neurophysiological response to change in frequency, location, intensity, continuity, or duration. There was no similar association with atrophy of the cingulo-opercular, salience or language networks, or with global atrophy. MD regions displayed increased functional but decreased effective connectivity as a function of neurodegeneration, suggesting partially effective compensation. Overall, we show that damage to any of the nodes of the MD network is sufficient to impair top-down control of sensation, providing a common mechanism for impaired change detection across dementia syndromes.SIGNIFICANCE STATEMENT Previous evidence for fronto-parietal networks controlling perception is largely associative and may be confounded by task difficulty. Here, we use a preattentive measure of automatic auditory change detection [mismatch negativity (MMN) magnetoencephalography (MEG)] to show that neurodegeneration in any frontal or parietal multiple demand (MD) node impairs primary auditory cortex (A1) neurophysiological response to change through top-down mechanisms. This explains why the impaired ability to respond to change is a core feature across dementias, and other conditions driven by brain network dysfunction, such as schizophrenia. It validates theoretical frameworks in which neurodegenerating networks upregulate connectivity as partially effective compensation. The significance extends beyond network science and dementia, in its construct validation of dynamic causal modeling (DCM), and human confirmation of frequency-resolved analyses of animal neurodegeneration models.

The Spino-Parabrachial Pathway for Itch

Itch-induced scratching is an evolutionarily conserved behavioral response that protects organisms from potential parasites/irritants in their immediate vicinity. How the exposure to a pruritogen is translated to the perception of itch and how that perception drives scratching directed towards the site of exposure remains poorly understood. In this review, we focus on the recent findings that shed light on the neural pathways in the brain that underlie itch-induced scratching. We compare the molecularly defined itch pathways with the known pain circuits as they have anatomical and functional overlap. We review the roles played by the neurons in the spinoparabrachial pathway-comprising of the neurons in the spinal cord and the parabrachial nucleus (PBN), which acts as a hub for transmitting itch information across the brain. Lastly, we deliberate on scratching as a behavioral measure of the intensity of itch and its implication in unraveling the underlying supraspinal mechanisms. In summary, we provide a resource on the recent advances and discuss a path forward on our understanding of the neural circuits for itch.

Rapid odor processing by layer 2 subcircuits in lateral entorhinal cortex

Olfactory information is encoded in lateral entorhinal cortex (LEC) by two classes of layer 2 (L2) principal neurons: fan and pyramidal cells. However, the functional properties of L2 cells and how they contribute to odor coding are unclear. Here, we show in awake mice that L2 cells respond to odors early during single sniffs and that LEC is essential for rapid discrimination of both odor identity and intensity. Population analyses of L2 ensembles reveal that rate coding distinguishes odor identity, but firing rates are only weakly concentration dependent and changes in spike timing can represent odor intensity. L2 principal cells differ in afferent olfactory input and connectivity with inhibitory circuits and the relative timing of pyramidal and fan cell spikes provides a temporal code for odor intensity. Downstream, intensity is encoded purely by spike timing in hippocampal CA1. Together, these results reveal the unique processing of odor information by LEC subcircuits and highlight the importance of temporal coding in higher olfactory areas.

Closed-loop neuromodulation for studying spontaneous activity and causality

Having established that spontaneous brain activity follows meaningful coactivation patterns and correlates with behavior, researchers have turned their attention to understanding its function and behavioral significance. We suggest closed-loop neuromodulation as a neural perturbation tool uniquely well suited for this task. Closed-loop neuromodulation has primarily been viewed as an interventionist tool to teach subjects to directly control their own brain activity. We examine an alternative operant conditioning model of closed-loop neuromodulation which, through implicit feedback, can manipulate spontaneous activity at the network level, without violating the spontaneous or endogenous nature of the signal, thereby providing a direct test of network causality.

Application of optogenetics and in vivo imaging approaches for elucidating the neurobiology of addiction

The neurobiology of addiction has been an intense topic of investigation for more than 50 years. Over this time, technological innovation in methods for studying brain function rapidly progressed, leading to increasingly sophisticated experimental approaches. To understand how specific brain regions, cell types, and circuits are affected by drugs of abuse and drive behaviors characteristic of addiction, it is necessary both to observe and manipulate neural activity in addiction-related behavioral paradigms. In pursuit of this goal, there have been several key technological advancements in in vivo imaging and neural circuit modulation in recent years, which have shed light on the cellular and circuit mechanisms of addiction. Here we discuss some of these key technologies, including circuit modulation with optogenetics, in vivo imaging with miniaturized single-photon microscopy (miniscope) and fiber photometry, and how the application of these technologies has garnered novel insights into the neurobiology of addiction.

Cholinergic modulation of hierarchical inhibitory control over cortical resting state dynamics: Local circuit modeling of schizophrenia-related hypofrontality

Nicotinic acetylcholine receptors (nAChRs) modulate the cholinergic drive to a hierarchy of inhibitory neurons in the superficial layers of the PFC, critical to cognitive processes. It has been shown that genetic deletions of the various types of nAChRs impact the properties of ultra-slow transitions between high and low PFC activity states in mice during quiet wakefulness. The impact characteristics depend on specific interneuron populations expressing the manipulated receptor subtype. In addition, recent data indicate that a genetic mutation of the α5 nAChR subunit, located on vasoactive intestinal polypeptide (VIP) inhibitory neurons, the rs16969968 single nucleotide polymorphism (α5 SNP), plays a key role in the hypofrontality observed in schizophrenia patients carrying the SNP. Data also indicate that chronic nicotine application to α5 SNP mice relieves the hypofrontality. We developed a computational model to show that the activity patterns recorded in the genetically modified mice can be explained by changes in the dynamics of the local PFC circuit. Notably, our model shows that these altered PFC circuit dynamics are due to changes in the stability structure of the activity states. We identify how this stability structure is differentially modulated by cholinergic inputs to the parvalbumin (PV), somatostatin (SOM) or the VIP inhibitory populations. Our model uncovers that a change in amplitude, but not duration of the high activity states can account for the lowered pyramidal (PYR) population firing rates recorded in α5 SNP mice. We demonstrate how nicotine-induced desensitization and upregulation of the β2 nAChRs located on SOM interneurons, as opposed to the activation of α5 nAChRs located on VIP interneurons, is sufficient to explain the nicotine-induced activity normalization in α5 SNP mice. The model further implies that subsequent nicotine withdrawal may exacerbate the hypofrontality over and beyond one caused by the SNP mutation.

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Prefrontal cortex shows ultra-slow alterations between low and high activity states at rest. This activity is characteristically decreased in schizophrenia patients.

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Model identifies local circuit origin of hypofrontality associated with schizophrenia and a5 nicotinic receptor malfunction.

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Decrease in PFC VIP-interneuron excitability drives decrease in high-activity-state stability and overall hypofrontality.

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Model shows desensitization/upregulation of SOM-expressed β2-NAChRs drive nicotine-induced renormalization of PFC activity.

What can we learn from inactivation studies? Lessons from auditory cortex

Inactivation experiments in auditory cortex (AC) produce widely varying results that complicate interpretations regarding the precise role of AC in auditory perception and ensuing behaviour. The advent of optogenetic methods in neuroscience offers previously unachievable insight into the mechanisms transforming brain activity into behaviour. With a view to aiding the design and interpretation of future studies in and outside AC, here we discuss the methodological challenges faced in manipulating neural activity. While considering AC’s role in auditory behaviour through the prism of inactivation experiments, we consider the factors that confound the interpretation of the effects of inactivation on behaviour, including the species, the type of inactivation, the behavioural task employed, and the exact location of the inactivation.

Wide variation in the outcome of auditory cortex inactivation has been an impediment to clear conclusions regarding the roles of the auditory cortex in behaviour.

Inactivation methods differ in their efficacy and specificity. The likelihood of observing a behavioural deficit is additionally influenced by factors such as the species being used, task design and reward.

A synthesis of previous results suggests that auditory cortex involvement is critical for tasks that require integrating across multiple stimulus features, and less likely to be critical for simple feature discriminations.

New methods of neural silencing provide opportunities for spatially and temporally precise manipulation of activity, allowing perturbation of individual subfields and specific circuits.

Using focal cooling to link neural dynamics and behavior

Establishing a causal link between neural function and behavioral output has remained a challenging problem. Commonly used perturbation techniques enable unprecedented control over intrinsic activity patterns and can effectively identify crucial circuit elements important for specific behaviors. However, these approaches may severely disrupt activity, precluding an investigation into the behavioral relevance of moment-to-moment neural dynamics within a specified brain region. Here we discuss the application of mild focal cooling to slow down intrinsic neural circuit activity while preserving its overall structure. Using network modeling and examples from multiple species, we highlight the power and versatility of focal cooling for understanding how neural dynamics control behavior and argue for its wider adoption within the systems neuroscience community.

A leg to stand on: computational models of proprioception

Dexterous motor control requires feedback from proprioceptors, internal mechanosensory neurons that sense the body's position and movement. An outstanding question in neuroscience is how diverse proprioceptive feedback signals contribute to flexible motor control. Genetic tools now enable targeted recording and perturbation of proprioceptive neurons in behaving animals; however, these experiments can be challenging to interpret, due to the tight coupling of proprioception and motor control. Here, we argue that understanding the role of proprioceptive feedback in controlling behavior will be aided by the development of multiscale models of sensorimotor loops. We review current phenomenological and structural models for proprioceptor encoding and discuss how they may be integrated with existing models of posture, movement, and body state estimation.

Mechanisms of Network Interactions for Flexible Cortico-Basal Ganglia-Mediated Action Control

In humans, finely tuned γ synchronization (60-90 Hz) rapidly appears at movement onset in a motor control network involving primary motor cortex, the basal ganglia and motor thalamus. Yet the functional consequences of brief movement-related synchronization are still unclear. Distinct synchronization phenomena have also been linked to different forms of motor inhibition, including relaxing antagonist muscles, rapid movement interruption and stabilizing network dynamics for sustained contractions. Here, I will introduce detailed hypotheses about how intrasite and intersite synchronization could interact with firing rate changes in different parts of the network to enable flexible action control. The here proposed cause-and-effect relationships shine a spotlight on potential key mechanisms of cortico-basal ganglia-thalamo-cortical (CBGTC) communication. Confirming or revising these hypotheses will be critical in understanding the neuronal basis of flexible movement initiation, invigoration and inhibition. Ultimately, the study of more complex cognitive phenomena will also become more tractable once we understand the neuronal mechanisms underlying behavioral readouts.

Shaping therapeutic trajectories in mental health: Instructive vs. permissive causality

We are currently facing the challenge of improving treatments for psychiatric disorders such as major depression. Notably, antidepressants have an incomplete efficacy, mostly due to our limited knowledge of their action. Here we present a theoretical framework that considers the distinction between instructive and permissive causality, which allows formalizing and disentangling the effects exerted by different therapeutic strategies commonly used in psychiatry. Instructive causality implies that an action determines a specific effect while permissive causality allows an action to take effect or not. We posit that therapeutic strategies able to improve the quality of the living environment or the ability to face it, including changes in lifestyle and psychotherapeutic interventions, rely mainly on instructive causality and thus shape the individual's ability to face the psychopathology and build resilience. By contrast, pharmacological treatments, such as selective serotonin reuptake inhibitors, act primarily through a permissive causality: they boost neural plasticity, i.e. the ability of the brain to change itself, and therefore allow for instructive interventions to produce beneficial effects or not. The combination of an instructive and a permissive action represents the most promising approach since the quality of the living environment can shape the path leading to mental health while drug treatment can increase the likelihood of achieving such a goal.

Higher baseline interleukin-1β and TNF-α hamper antidepressant response in major depressive disorder

Raised pro-inflammatory immune/inflammatory setpoints, leading to an increased production of peripheral cytokines, have been associated with Major Depressive Disorder (MDD) and with failure to respond to first-line antidepressant drugs. However, the usefulness of these biomarkers in clinical psychopharmacology has been questioned because single findings did not translate into the clinical practice, where patients are prescribed treatments upon clinical need. We studied a panel of 27 inflammatory biomarkers in a sample of 108 inpatients with MDD, treated with antidepressant monotherapy for 4 weeks upon clinical need in a specialized hospital setting, and assessed the predictive effect of baseline peripheral measures of inflammation on antidepressing efficacy (response rates and time-lagged pattern of decrease of depression severity) using a machine-learning approach with elastic net penalized regression, and multivariate analyses in the context of the general linear model. When considering both categorical and continuous measures of response, baseline levels of IL-1β predicted non-response to antidepressants, with the predicted probability to respond being highly dispersed at low levels of IL-1β, and stratifying toward non-response when IL-1β is high. Significant negative effects were also detected for TNF-α, while IL-12 weakly predicted response. These findings support the usefulness of inflammatory biomarkers in the clinical psychopharmacology of depression, and add to ongoing research efforts aiming at defining reliable cutoff values to identify depressed patients in clinical settings with high inflammation, and low probability to respond.

Distributed processing of side-choice biases

Psychophysics describes how variations in stimulus strength lead to changes in perceptual performance. Yet, the contribution of non-sensory information processing to perceptual decision making is still not fully understood. For instance, in two-alternative forced-choice tasks, observers can exhibit tendencies to choose more one alternative over another, with no apparent goal or function. Such choice biases are highly prevalent in mice and, in free-choice tasks, they are insensitive to changes in stimulus discriminability. Thus, a reasonable proposal is that these side-choice biases could derive from functional asymmetries in sensory processing, decision making, or both. Here, we explored how different circuits participate in the production of choice biases in adult mice. We found that the magnitude of the changes in biased choice behavior depended on the inactivated region. Indeed, contralateral, but not ipsilateral, inactivations of the primary visual and posterior parietal cortices reduced the probability of mice choosing their preferred side. In contrast, ipsilateral inactivations of the subtantia nigra pars reticulata and of the frontal orienting fields, reduced and increased the probabilities of mice choosing their preferred side, respectively. These results demonstrate that internal circuit processing contributes to side-choice behavior and illustrates how distinct brain regions could participate in producing normal to aberrant levels of choice variability.

Values encoded in orbitofrontal cortex are causally related to economic choices

In the eighteenth century, Daniel Bernoulli, Adam Smith and Jeremy Bentham proposed that economic choices rely on the computation and comparison of subjective values1. This hypothesis continues to inform modern economic theory2 and research in behavioural economics3, but behavioural measures are ultimately not sufficient to verify the proposal4. Consistent with the hypothesis, when agents make choices, neurons in the orbitofrontal cortex (OFC) encode the subjective value of offered and chosen goods5. Value-encoding cells integrate multiple dimensions6-9, variability in the activity of each cell group correlates with variability in choices10,11 and the population dynamics suggests the formation of a decision12. However, it is unclear whether these neural processes are causally related to choices. More generally, the evidence linking economic choices to value signals in the brain13-15 remains correlational16. Here we show that neuronal activity in the OFC is causal to economic choices. We conducted two experiments using electrical stimulation in rhesus monkeys (Macaca mulatta). Low-current stimulation increased the subjective value of individual offers and thus predictably biased choices. Conversely, high-current stimulation disrupted both the computation and the comparison of subjective values, and thus increased choice variability. These results demonstrate a causal chain linking subjective values encoded in OFC to valuation and choice.