The whole prefrontal cortex is premotor cortex

Modulation of dorsal premotor cortex differentially influences visuomotor adaptation in young and older adults

The communication between dorsal premotor cortex (PMd) and primary motor cortex (M1) is important for visuomotor adaptation, but it is unclear how this relationship changes with advancing age. The present study recruited 21 young and 23 older participants for two experimental sessions during which intermittent theta burst stimulation (iTBS) or sham was applied over PMd. We assessed the effects of PMd iTBS on M1 excitability using motor evoked potentials (MEP) recorded from right first dorsal interosseous when single-pulse transcranial magnetic stimulation (TMS) was applied with posterior-anterior (PA) or anterior-posterior (AP) currents; and adaptation by quantifying error recorded during a visuomotor adaptation task (VAT). PMd iTBS potentiated PA (P < 0.0001) and AP (P < 0.0001) MEP amplitude in both young and older adults. PMd iTBS increased error in young adults during adaptation (P = 0.026), but had no effect in older adults (P = 0.388). Although PMd iTBS potentiated M1 excitability in both young and older adults, the intervention attenuated visuomotor adaptation specifically in young adults.

Sensing, feeling and regulating: investigating the association of focal brain damage with voluntary respiratory and motor control

Breathing is a complex, vital function that can be modulated to influence physical and mental well-being. However, the role of cortical and subcortical brain regions in voluntary control of human respiration is underexplored. Here we investigated the influence of damage to human frontal, temporal or limbic regions on the sensation and regulation of breathing patterns. Participants performed a respiratory regulation task across regular and irregular frequencies ranging from 6 to 60 breaths per minute (bpm), with a counterbalanced hand motor control task. Interoceptive and affective states induced by each condition were assessed via questionnaire, and autonomic signals were indexed via skin conductance. Participants with focal lesions to the bilateral frontal lobe, right insula/basal ganglia and left medial temporal lobe showed reduced performance relative to individually matched healthy comparisons during the breathing and motor tasks. They also reported significantly higher anxiety during the 60 bpm regular and irregular breathing trials, with anxiety correlating with difficulty in rapid breathing specifically within this group. This study demonstrates that damage to frontal, temporal or limbic regions is associated with abnormal voluntary respiratory and motor regulation and tachypnoea-related anxiety, highlighting the role of the forebrain in affective and motor responses during breathing. This article is part of the theme issue 'Sensing and feeling: an integrative approach to sensory processing and emotional experience'.

Beta: bursts of cognition

Beta oscillations are linked to the control of goal-directed processing of sensory information and the timing of motor output. Recent evidence demonstrates they are not sustained but organized into intermittent high-power bursts mediating timely functional inhibition. This implies there is a considerable moment-to-moment variation in the neural dynamics supporting cognition. Beta bursts thus offer new opportunities for studying how sensory inputs are selectively processed, reshaped by inhibitory cognitive operations and ultimately result in motor actions. Recent method advances reveal diversity in beta bursts that provide deeper insights into their function and the underlying neural circuit activity motifs. We propose that brain-wide, spatiotemporal patterns of beta bursting reflect various cognitive operations and that their dynamics reveal nonlinear aspects of cortical processing.

A prefrontal motor circuit initiates persistent movement

Persistence reinforces continuous action, which benefits animals in many aspects. Diverse external or internal signals may trigger animals to start a persistent movement. However, it is unclear how the brain decides to persist with current actions by selecting specific information. Using single-unit extracellular recordings and opto-tagging in awake mice, we demonstrated that a group of dorsal mPFC (dmPFC) motor cortex projecting (MP) neurons initiate a persistent movement by selectively encoding contextual information rather than natural valence. Inactivation of dmPFC MP neurons impairs the initiation and reduces neuronal activity in the insular and motor cortex. After the persistent movement is initiated, the dmPFC MP neurons are not required to maintain it. Finally, a computational model suggests that a successive sensory stimulus acts as an input signal for the dmPFC MP neurons to initiate a persistent movement. These results reveal a neural initiation mechanism on the persistent movement.

Exploring the impact of biological alterations in the superior thalamic radiations on exploratory eye movements in attenuated psychosis syndrome

Introduction

Aberrant fixation and scan paths in visual searches have been repeatedly reported in schizophrenia. The frontal eye fields (FEF) and thalamus may be responsible for fixation and scan paths. These two regions are connected by superior thalamic radiation (STR) in humans. Studies have reported reduced fixation numbers and shortened scan path lengths in individuals with attenuated psychosis syndrome (APS) and schizophrenia. In this study, we hypothesized that STRs in the white matter fiber bundles of impairments underlie abnormalities in fixation and scan path length in individuals with APS.

Methods

Twenty-one individuals with APS and 30 healthy controls participated in this study. All participants underwent diffusion tensor imaging, and fractional anisotropy (FA) values of the left and right STR were analyzed using the novel method TractSeg. The number of eye fixations (NEF), total eye scanning length (TESL), and mean eye scanning length (MESL), derived using the exploratory eye movement (EEM) test, were adopted to evaluate the fixation and scan path length. We compared the FA values of the bilateral STR and EEM parameters between the APS and healthy control groups. We investigated the correlation between bilateral STR and EEM parameters in the APS and healthy control groups.

Results

NEF, TESL, MESL, and the FA values of the left STR were significantly reduced in individuals with APS compared to healthy controls. The left STR FA value in the APS group was significantly positively correlated with the MESL (r = 0.567, p = 0.007). In addition, the right STR FA value of the APS group was significantly correlated with the TESL (r = 0.587, p = 0.005) and MESL (r = 0.756, p = 0.7×10-4).

Discussion

These results demonstrate that biological changes in the STR, which connects the thalamus and FEF, underlie abnormalities in fixation and scanning. Recently, aberrations in the thalamus-frontal connection have been shown to underlie the emergence of psychotic symptoms. STR impairment may be a part of the biological basis of APS in individuals with subthreshold psychotic symptoms.

Formalising the role of behaviour in neuroscience

We develop a mathematical approach to formally proving that certain neural computations and representations exist based on patterns observed in an organism's behaviour. To illustrate, we provide a simple set of conditions under which an ant's ability to determine how far it is from its nest would logically imply neural structures isomorphic to the natural numbersℕ $$ \mathrm{\mathbb{N}} $$ . We generalise these results to arbitrary behaviours and representations and show what mathematical characterisation of neural computation and representation is simplest while being maximally predictive of behaviour. We develop this framework in detail using a path integration example, where an organism's ability to search for its nest in the correct location implies representational structures isomorphic to two-dimensional coordinates under addition. We also study a system for processinga n b n $$ {a}^n{b}^n $$ strings common in comparative work. Our approach provides an objective way to determine what theory of a physical system is best, addressing a fundamental challenge in neuroscientific inference. These results motivate considering which neurobiological structures have the requisite formal structure and are otherwise physically plausible given relevant physical considerations such as generalisability, information density, thermodynamic stability and energetic cost.

Insula uses overlapping codes for emotion in self and others

In daily life, we must recognize others' emotions so we can respond appropriately. This ability may rely, at least in part, on neural responses similar to those associated with our own emotions. We hypothesized that the insula, a cortical region near the junction of the temporal, parietal, and frontal lobes, may play a key role in this process. We recorded local field potential (LFP) activity in human neurosurgical patients performing two tasks, one focused on identifying their own emotional response and one on identifying facial emotional responses in others. We found matching patterns of gamma- and high-gamma band activity for the two tasks in the insula. Three other regions (MTL, ACC, and OFC) clearly encoded both self- and other-emotions, but used orthogonal activity patterns to do so. These results support the hypothesis that the insula plays a particularly important role in mediating between experienced vs. observed emotions.

Toward a neuroscience of natural behavior

One of the most exciting new developments in systems neuroscience is the progress being made toward neurophysiological experiments that move beyond simplified laboratory settings and address the richness of natural behavior. This is enabled by technological advances such as wireless recording in freely moving animals, automated quantification of behavior, and new methods for analyzing large data sets. Beyond new empirical methods and data, however, there is also a need for new theories and concepts to interpret that data. Such theories need to address the particular challenges of natural behavior, which often differ significantly from the scenarios studied in traditional laboratory settings. Here, we discuss some strategies for developing such novel theories and concepts and some example hypotheses being proposed.

Atypical characteristic changes of surface morphology and structural covariance network in developmental dyslexia

BACKGROUND

Developmental dyslexia (DD) is a neurodevelopmental disorder that is characterized by difficulties with all aspects of information acquisition in the written word, including slow and inaccurate word recognition. The neural basis behind DD has not been fully elucidated.

METHOD

The study included 22 typically developing (TD) children, 16 children with isolated spelling disorder (SpD), and 20 children with DD. The cortical thickness, folding index, and mean curvature of Broca's area, including the triangular part of the left inferior frontal gyrus (IFGtriang) and the opercular part of the left inferior frontal gyrus, were assessed to explore the differences of surface morphology among the TD, SpD, and DD groups. Furthermore, the structural covariance network (SCN) of the triangular part of the left inferior frontal gyrus was analyzed to explore the changes of structural connectivity in the SpD and DD groups.

RESULTS

The DD group showed higher curvature and cortical folding of the left IFGtriang than the TD group and SpD group. In addition, compared with the TD group and the SpD group, the structural connectivity between the left IFGtriang and the left middle-frontal gyrus and the right mid-orbital frontal gyrus was increased in the DD group, and the structural connectivity between the left IFGtriang and the right precuneus and anterior cingulate was decreased in the DD group.

CONCLUSION

DD had atypical structural connectivity in brain regions related to visual attention, memory and which might impact the information input and integration needed for reading and spelling.

Control over a mixture of policies determines change of mind topology during continuous choice

Behavior is naturally organized into categorically distinct states with corresponding patterns of neural activity; how does the brain control those states? We propose that states are regulated by specific neural processes that implement meta-control that can blend simpler control processes. To test this hypothesis, we recorded from neurons in the dorsal anterior cingulate cortex (dACC) and dorsal premotor cortex (PMd) while macaques performed a continuous pursuit task with two moving prey that followed evasive strategies. We used a novel control theoretic approach to infer subjects' moment-to-moment latent control variables, which in turn dictated their blend of distinct identifiable control processes. We identified low-dimensional subspaces in neuronal responses that reflected the current strategy, the value of the pursued target, and the relative value of the two targets. The top two principal components of activity tracked changes of mind in abstract and change-type-specific formats, respectively. These results indicate that control of behavioral state reflects the interaction of brain processes found in dorsal prefrontal regions that implement a mixture over low-level control policies.

A prefrontal motor circuit initiates persistent movement

Persistence reinforces continuous action, which benefits animals in many aspects. Diverse information may trigger animals to start a persistent movement. However, it is unclear how the brain decides to persist with current actions by selecting specific information. Using single-unit extracellular recordings and opto-tagging in awake mice, we demonstrated that a group of dorsal mPFC (dmPFC) motor cortex projecting (MP) neurons initiate a persistent movement selectively encoding contextual information rather than natural valence. Inactivation of dmPFC MP neurons impairs the initiation and reduces neuronal activity in the insular and motor cortex. Finally, a computational model suggests that a successive sensory stimulus acts as an input signal for the dmPFC MP neurons to initiate a persistent movement. These results reveal a neural initiation mechanism on the persistent movement.

Sensing, Feeling, and Regulating: Investigating the Association of Focal Brain Damage with Voluntary Respiratory and Motor Control

Breathing is a complex, vital function that can be modulated to influence physical and mental well-being. However, the role of cortical and subcortical brain regions in voluntary control of human respiration is underexplored. Here we investigated the influence of damage to human frontal, temporal, or limbic regions on the sensation and regulation of breathing patterns. Participants performed a respiratory regulation task across regular and irregular frequencies ranging from 6 to 60 breaths per minute (bpm), with a counterbalanced hand motor control task. Interoceptive and affective states induced by each condition were assessed via questionnaire and autonomic signals were indexed via skin conductance. Participants with focal lesions to the bilateral frontal lobe, right insula/basal ganglia, and left medial temporal lobe showed reduced performance than individually matched healthy comparisons during the breathing and motor tasks. They also reported significantly higher anxiety during the 60-bpm regular and irregular breathing trials, with anxiety correlating with difficulty in rapid breathing specifically within this group. This study demonstrates that damage to frontal, temporal, or limbic regions is associated with abnormal voluntary respiratory and motor regulation and tachypnea-related anxiety, highlighting the role of the forebrain in affective and motor responses during breathing.

Highlights

Impaired human respiratory regulation is associated with cortical/subcortical brain lesionsFrontolimbic/temporal regions contribute to rhythmic breathing and hand motor controlFrontolimbic/temporal damage is associated with anxiety during tachypnea/irregular breathingThe human forebrain is vital for affective and interoceptive experiences during breathing.

Variation in brain connectivity during motor imagery and motor execution in stroke patients based on electroencephalography

Objective

The objective of this study was to analyze the changes in connectivity between motor imagery (MI) and motor execution (ME) in the premotor area (PMA) and primary motor cortex (MA) of the brain, aiming to explore suitable forms of treatment and potential therapeutic targets.

Methods

Twenty-three inpatients with stroke were selected, and 21 right-handed healthy individuals were recruited. EEG signal during hand MI and ME (synergy and isolated movements) was recorded. Correlations between functional brain areas during MI and ME were compared.

Results

PMA and MA were significantly and positively correlated during hand MI in all participants. The power spectral density (PSD) values of PMA EEG signals were greater than those of MA during MI and ME in both groups. The functional connectivity correlation was higher in the stroke group than in healthy people during MI, especially during left-handed MI. During ME, functional connectivity correlation in the brain was more enhanced during synergy movements than during isolated movements. The regions with abnormal functional connectivity were in the 18th lead of the left PMA area.

Conclusion

Left-handed MI may be crucial in MI therapy, and the 18th lead may serve as a target for non-invasive neuromodulation to promote further recovery of limb function in patients with stroke. This may provide support for the EEG theory of neuromodulation therapy for hemiplegic patients.

Sequential neuronal processing of number values, abstract decision, and action in the primate prefrontal cortex

Decision-making requires processing of sensory information, comparing the gathered evidence to make a judgment, and performing the action to communicate it. How neuronal representations transform during this cascade of representations remains a matter of debate. Here, we studied the succession of neuronal representations in the primate prefrontal cortex (PFC). We trained monkeys to judge whether a pair of sequentially presented displays had the same number of items. We used a combination of single neuron and population-level analyses and discovered a sequential transformation of represented information with trial progression. While numerical values were initially represented with high precision and in conjunction with detailed information such as order, the decision was encoded in a low-dimensional subspace of neural activity. This decision encoding was invariant to both retrospective numerical values and prospective motor plans, representing only the binary judgment of "same number" versus "different number," thus facilitating the generalization of decisions to novel number pairs. We conclude that this transformation of neuronal codes within the prefrontal cortex supports cognitive flexibility and generalizability of decisions to new conditions.

Ramping dynamics and theta oscillations reflect dissociable signatures during rule-guided human behavior

Contextual cues and prior evidence guide human goal-directed behavior. The neurophysiological mechanisms that implement contextual priors to guide subsequent actions in the human brain remain unclear. Using intracranial electroencephalography (iEEG), we demonstrate that increasing uncertainty introduces a shift from a purely oscillatory to a mixed processing regime with an additional ramping component. Oscillatory and ramping dynamics reflect dissociable signatures, which likely differentially contribute to the encoding and transfer of different cognitive variables in a cue-guided motor task. The results support the idea that prefrontal activity encodes rules and ensuing actions in distinct coding subspaces, while theta oscillations synchronize the prefrontal-motor network, possibly to guide action execution. Collectively, our results reveal how two key features of large-scale neural population activity, namely continuous ramping dynamics and oscillatory synchrony, jointly support rule-guided human behavior.

Dissociating the Contributions of Frontal Eye Field Activity to Spatial Working Memory and Motor Preparation

Neurons within dorsolateral prefrontal cortex (PFC) of primates are characterized by robust persistent spiking activity exhibited during the delay period of working memory tasks. This includes the frontal eye field (FEF) where nearly half of the neurons are active when spatial locations are held in working memory. Past evidence has established the FEF's contribution to the planning and triggering of saccadic eye movements as well as to the control of visual spatial attention. However, it remains unclear whether persistent delay activity reflects a similar dual role in movement planning and visuospatial working memory. We trained male monkeys to alternate between different forms of a spatial working memory task which could dissociate remembered stimulus locations from planned eye movements. We tested the effects of inactivation of FEF sites on behavioral performance in the different tasks. Consistent with previous studies, FEF inactivation impaired the execution of memory-guided saccades (MGSs), and impaired performance when remembered locations matched the planned eye movement. In contrast, memory performance was largely unaffected when the remembered location was dissociated from the correct eye movement response. Overall, the inactivation effects demonstrated clear deficits in eye movements, regardless of task type, but little or no evidence of a deficit in spatial working memory. Thus, our results indicate that persistent delay activity in the FEF contributes primarily to the preparation of eye movements and not to spatial working memory.SIGNIFICANCE STATEMENT Many frontal eye field (FEF) neurons exhibit spatially tuned persistent spiking activity during the delay period of working memory tasks. However, the role of the FEF in spatial working memory remains unresolved. We tested the effects of inactivation of FEF sites on behavioral performance in different forms of a spatial working memory task, one of which dissociated the remembered stimulus locations from planned eye movements. We found that FEF inactivation produced clear deficits in eye movements, regardless of task type, but no deficit in spatial working memory when dissociated from those movements.

A goal-centric outlook on learning

Goals play a central role in human cognition. However, computational theories of learning and decision-making often take goals as given. Here, we review key empirical findings showing that goals shape the representations of inputs, responses, and outcomes, such that setting a goal crucially influences the central aspects of any learning process: states, actions, and rewards. We thus argue that studying goal selection is essential to advance our understanding of learning. By following existing literature in framing goal selection within a hierarchy of decision-making problems, we synthesize important findings on the principles underlying goal value attribution and exploration strategies. Ultimately, we propose that a goal-centric perspective will help develop more complete accounts of learning in both biological and artificial agents.

Investigation of altered spontaneous brain activity in patients with bronchial asthma using the percent amplitude of fluctuation method: a resting-state functional MRI study

Purpose

To explore the regions of aberrant spontaneous brain activity in asthma patients and their potential impacts using the Percent amplitude of fluctuation (PerAF) analysis method.

Patients and methods

In this study, a total of 31 bronchial asthma (BA) patients were ultimately included, comprising 17 males and 14 females. Subsequently, 31 healthy control subjects (HCS) were recruited, consisting of 17 males and 14 females, and they were matched with the BA group based on age, sex, and educational status. The PerAF analysis technique was employed to study the differences in spontaneous brain activity between the two groups. The SPM12 toolkit was used to carry out a two sample t-test on the collected fMRI data, in order to examine the differences in PerAF values between the asthma patients and the healthy controls. We employed the Montreal Cognitive Assessment (MoCA) scale and the Hamilton Depression Scale (HAMD) to evaluate the cognitive and emotional states of the two groups. Pearson correlation analysis was utilized to ascertain the relationship between changes in the PerAF values within specific brain regions and cognitive as well as emotional conditions.

Results

Compared with the healthy control group, areas of the brain with reduced PerAF in asthma patients included the inferior cerebellum, fusiform gyrus, right inferior orbital frontal gyrus, left middle orbital frontal gyrus, left/right middle frontal gyrus (MFG), dorsal lateral superior frontal gyrus (SFGdl), left superior temporal gyrus (STG), precuneus, right inferior parietal lobule (IPL), and left/right angular gyrus. BA patients exhibit mild cognitive impairments and a propensity for emotional disturbances. Furthermore, the perAF values of the SFGdl region are significantly positively correlated with the results of the MoCA cognitive assessment, while negatively correlated with the HAMD evaluation.

Conclusion

Through the application of PerAF analysis methods, we discovered that several brain regions in asthma patients that control the amplitude of respiration, vision, memory, language, attention, and emotional control display abnormal changes in intrinsic brain activity. This helps characterize the neural mechanisms behind cognitive, sensory, and motor function impairments in asthma patients, providing valuable insights for potential therapeutic targets and disease management strategies.

Perceptual control or action-selection? Comment on: a perceptual control theory of emotional action

The Perceptual Control Theory of Emotional Action provides a compelling view of the synergy between action and perception in the context of emotion. In this invited response, we outline three suggestions to further clarify and concretesise the theory in the hope that it can provide a solid basis for the theoretical, empirical, and clinical fields of emotion and emotion regulation. First, we emphasise the importance of concretesising these ideas in a way that is biologically plausible and testable in terms of its neuronal implementation, which has not been addressed in the main manuscript. Secondly, we highlight the challenges for this account to effectively describe core symptoms in emotional disorders, an essential step if the theory aims to foster the development of better-tuned neurocognitively grounded interventions. Finally, we take a leap on what action-oriented accounts of emotion can mean for the field of emotion regulation.

Emotion regulation from an action-control perspective

Despite increasing interest in emotional processes in cognitive science, theories on emotion regulation have remained rather isolated, predominantly focused on cognitive regulation strategies such as reappraisal. However, recent neurocognitive evidence suggests that early emotion regulation may involve sensorimotor control in addition to other emotion-regulation processes. We propose an action-oriented view of emotion regulation, in which feedforward predictions develop from action-selection mechanisms. Those can account for acute emotional-action control as well as more abstract instances of emotion regulation such as cognitive reappraisal. We argue the latter occurs in absence of overt motor output, yet in the presence of full-blown autonomic, visceral, and subjective changes. This provides an integrated framework with testable neuro-computational predictions and concrete starting points for intervention to improve emotion control in affective disorders.

Effectiveness of motor and prefrontal cortical areas for brain-controlled functional electrical stimulation neuromodulation

Objective. Brain-computer interface (BCI)-controlled functional electrical stimulation (FES) could excite the central nervous system to enhance upper limb motor recovery. Our current study assessed the effectiveness of motor and prefrontal cortical activity-based BCI-FES to help elucidate the underlying neuromodulation mechanisms of this neurorehabilitation approach.Approach. The primary motor cortex (M1) and prefrontal cortex (PFC) BCI-FES interventions were performed for 25 min on separate days with twelve non-disabled participants. During the interventions, a single electrode from the contralateral M1 or PFC was used to detect event-related desynchronization (ERD) in the calibrated frequency range. If the BCI system detected ERD within 15 s of motor imagery, FES activated wrist extensor muscles. Otherwise, if the BCI system did not detect ERD within 15 s, a subsequent trial was initiated without FES. To evaluate neuromodulation effects, corticospinal excitability was assessed using single-pulse transcranial magnetic stimulation, and cortical excitability was assessed by motor imagery ERD and resting-state functional connectivity before, immediately, 30 min, and 60 min after each intervention.Main results. M1 and PFC BCI-FES interventions had similar success rates of approximately 80%, while the M1 intervention was faster in detecting ERD activity. Consequently, only the M1 intervention effectively elicited corticospinal excitability changes for at least 60 min around the targeted cortical area in the M1, suggesting a degree of spatial localization. However, cortical excitability measures did not indicate changes after either M1 or PFC BCI-FES.Significance. Neural mechanisms underlying the effectiveness of BCI-FES neuromodulation may be attributed to the M1 direct corticospinal projections and/or the closer timing between ERD detection and FES, which likely enhanced Hebbian-like plasticity by synchronizing cortical activation detected by the BCI system with the sensory nerve activation and movement related reafference elicited by FES.

Hierarchical action encoding in prefrontal cortex of freely moving macaques

Our natural behavioral repertoires include coordinated actions of characteristic types. To better understand how neural activity relates to the expression of actions and action switches, we studied macaques performing a freely moving foraging task in an open environment. We developed a novel analysis pipeline that can identify meaningful units of behavior, corresponding to recognizable actions such as sitting, walking, jumping, and climbing. On the basis of transition probabilities between these actions, we found that behavior is organized in a modular and hierarchical fashion. We found that, after regressing out many potential confounders, actions are associated with specific patterns of firing in each of six prefrontal brain regions and that, overall, encoding of action category is progressively stronger in more dorsal and more caudal prefrontal regions. Together, these results establish a link between selection of units of primate behavior on one hand and neuronal activity in prefrontal regions on the other.

Semi-orthogonal subspaces for value mediate a tradeoff between binding and generalization

When choosing between options, we must associate their values with the action needed to select them. We hypothesize that the brain solves this binding problem through neural population subspaces. To test this hypothesis, we examined neuronal responses in five reward-sensitive regions in macaques performing a risky choice task with sequential offers. Surprisingly, in all areas, the neural population encoded the values of offers presented on the left and right in distinct subspaces. We show that the encoding we observe is sufficient to bind the values of the offers to their respective positions in space while preserving abstract value information, which may be important for rapid learning and generalization to novel contexts. Moreover, after both offers have been presented, all areas encode the value of the first and second offers in orthogonal subspaces. In this case as well, the orthogonalization provides binding. Our binding-by-subspace hypothesis makes two novel predictions borne out by the data. First, behavioral errors should correlate with putative spatial (but not temporal) misbinding in the neural representation. Second, the specific representational geometry that we observe across animals also indicates that behavioral errors should increase when offers have low or high values, compared to when they have medium values, even when controlling for value difference. Together, these results support the idea that the brain makes use of semi-orthogonal subspaces to bind features together.

Moving, fast and slow: behavioural insights into bradykinesia in Parkinson's disease

The debilitating symptoms of Parkinson's disease, including the hallmark slowness of movement, termed bradykinesia, were described more than 100 years ago. Despite significant advances in elucidating the genetic, molecular and neurobiological changes in Parkinson's disease, it remains conceptually unclear exactly why patients with Parkinson's disease move slowly. To address this, we summarize behavioural observations of movement slowness in Parkinson's disease and discuss these findings in a behavioural framework of optimal control. In this framework, agents optimize the time it takes to gather and harvest rewards by adapting their movement vigour according to the reward that is at stake and the effort that needs to be expended. Thus, slow movements can be favourable when the reward is deemed unappealing or the movement very costly. While reduced reward sensitivity, which makes patients less inclined to work for reward, has been reported in Parkinson's disease, this appears to be related mainly to motivational deficits (apathy) rather than bradykinesia. Increased effort sensitivity has been proposed to underlie movement slowness in Parkinson's disease. However, careful behavioural observations of bradykinesia are inconsistent with abnormal computations of effort costs due to accuracy constraints or movement energetic expenditure. These inconsistencies can be resolved when considering that a general disability to switch between stable and dynamic movement states can contribute to an abnormal composite effort cost related to movement in Parkinson's disease. This can account for paradoxical observations such as the abnormally slow relaxation of isometric contractions or difficulties in halting a movement in Parkinson's disease, both of which increase movement energy expenditure. A sound understanding of the abnormal behavioural computations mediating motor impairment in Parkinson's disease will be vital for linking them to their underlying neural dynamics in distributed brain networks and for grounding future experimental studies in well-defined behavioural frameworks.

Widespread coding of navigational variables in prefrontal cortex

To navigate effectively, we must represent information about our location in the environment. Traditional research highlights the role of the hippocampal complex in this process. Spurred by recent research highlighting the widespread cortical encoding of cognitive and motor variables previously thought to have localized function, we hypothesized that navigational variables would be likewise encoded widely, especially in the prefrontal cortex, which is associated with volitional behavior. We recorded neural activity from six prefrontal regions while macaques performed a foraging task in an open enclosure. In all regions, we found strong encoding of allocentric position, allocentric head direction, boundary distance, and linear and angular velocity. These encodings were not accounted for by distance, time to reward, or motor factors. The strength of coding of all variables increased along a ventral-to-dorsal gradient. Together, these results argue that encoding of navigational variables is not localized to the hippocampus and support the hypothesis that navigation is continuous with other forms of flexible cognition in the service of action.

Abstract Value Encoding in Neural Populations But Not Single Neurons

An important open question in neuroeconomics is how the brain represents the value of offers in a way that is both abstract (allowing for comparison) and concrete (preserving the details of the factors that influence value). Here, we examine neuronal responses to risky and safe options in five brain regions that putatively encode value in male macaques. Surprisingly, we find no detectable overlap in the neural codes used for risky and safe options, even when the options have identical subjective values (as revealed by preference) in any of the regions. Indeed, responses are weakly correlated and occupy distinct (semi-orthogonal) encoding subspaces. Notably, however, these subspaces are linked through a linear transform of their constituent encodings, a property that allows for comparison of dissimilar option types. This encoding scheme allows these regions to multiplex decision related processes: they can encode the detailed factors that influence offer value (here, risky and safety) but also directly compare dissimilar offer types. Together these results suggest a neuronal basis for the qualitatively different psychological properties of risky and safe options and highlight the power of population geometry to resolve outstanding problems in neural coding.SIGNIFICANCE STATEMENT To make economic choices, we must have some mechanism for comparing dissimilar offers. We propose that the brain uses distinct neural codes for risky and safe offers, but that these codes are linearly transformable. This encoding scheme has the dual advantage of allowing for comparison across offer types while preserving information about offer type, which in turn allows for flexibility in changing circumstances. We show that responses to risky and safe offers exhibit these predicted properties in five different reward-sensitive regions. Together, these results highlight the power of population coding principles for solving representation problems in economic choice.

Dissociating the Contributions of Frontal Eye Field Activity to Spatial Working Memory and Motor Preparation

Neurons within dorsolateral prefrontal cortex of primates are characterized by robust persistent spiking activity exhibited during the delay period of working memory tasks. This includes the frontal eye field (FEF) where nearly half of the neurons are active when spatial locations are held in working memory. Past evidence has established the FEF's contribution to the planning and triggering of saccadic eye movements as well as to the control of visual spatial attention. However, it remains unclear if persistent delay activity reflects a similar dual role in movement planning and visuospatial working memory. We trained monkeys to alternate between different forms of a spatial working memory task which could dissociate remembered stimulus locations from planned eye movements. We tested the effects of inactivation of FEF sites on behavioral performance in the different tasks. Consistent with previous studies, FEF inactivation impaired the execution of memory-guided saccades, and impaired performance when remembered locations matched the planned eye movement. In contrast, memory performance was largely unaffected when the remembered location was dissociated from the correct eye movement response. Overall, the inactivation effects demonstrated clear deficits on eye movements, regardless of task type, but little or no evidence of a deficit in spatial working memory. Thus, our results indicate that persistent delay activity in the FEF contributes primarily to the preparation of eye movements and not to spatial working memory.

The Dangers of Cortical Brain Maps

The parcellation of the primate cerebral cortex into numbered regions, based on cytoarchitecture, has greatly helped neuroscientists in our quest to understand how the brain implements cognition. Nonetheless, these maps provide an unnecessarily constraining view of how we should do functional neuroanatomy. It is time to think more broadly. Doing so will help advance the goal of incorporating ideas about emergentist organization and interactional complexity into neuroscience.

Modular Brain, Entangled Argument

It has become a truism that the brain is a complex structure. One idea associated with complex systems is that of emergence, which is often characterized as the occurrence of a novel collective property that results from the interactions of individual parts, each of which alone do not have that property. Pessoa in his book argues, plausibly, that given that cognition is the most complex thing the brain does then it will need a new emergence-inflected science to understand it. His subsequent argument, however, does not follow, namely that this will take the form of distributed networks with identity-switching nodes that morph pluripotently from one computation to another. This is not true for whole organisms, which became more complex through compartmentalization and specialization. The brain did the same with hierarchically organized specialized areas.

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.

Non-conscious processing of fear faces: a function of the implicit self-concept of anxiety

BACKGROUND

Trait anxiety refers to a stable tendency to experience fears and worries across many situations. High trait anxiety is a vulnerability factor for the development of psychopathologies. Self-reported trait anxiety appears to be associated with an automatic processing advantage for threat-related information. Self-report measures assess aspects of the explicit self-concept of anxiety. Indirect measures can tap into the implicit self-concept of anxiety.

METHODS

We examined automatic brain responsiveness to non-conscious threat as a function of trait anxiety using functional magnetic resonance imaging. Besides a self-report instrument, we administered the Implicit Association Test (IAT) to assess anxiety. We used a gender-decision paradigm presenting brief (17 ms) and backward-masked facial expressions depicting disgust and fear.

RESULTS

Explicit trait anxiety was not associated with brain responsiveness to non-conscious threat. However, a relation of the implicit self-concept of anxiety with masked fear processing in the thalamus, precentral gyrus, and lateral prefrontal cortex was observed.

CONCLUSIONS

We provide evidence that a measure of the implicit self-concept of anxiety is a valuable predictor of automatic neural responses to threat in cortical and subcortical areas. Hence, implicit anxiety measures could be a useful addition to explicit instruments. Our data support the notion that the thalamus may constitute an important neural substrate in biased non-conscious processing in anxiety.

Adaptive control of synaptic plasticity integrates micro- and macroscopic network function

Synaptic plasticity configures interactions between neurons and is therefore likely to be a primary driver of behavioral learning and development. How this microscopic-macroscopic interaction occurs is poorly understood, as researchers frequently examine models within particular ranges of abstraction and scale. Computational neuroscience and machine learning models offer theoretically powerful analyses of plasticity in neural networks, but results are often siloed and only coarsely linked to biology. In this review, we examine connections between these areas, asking how network computations change as a function of diverse features of plasticity and vice versa. We review how plasticity can be controlled at synapses by calcium dynamics and neuromodulatory signals, the manifestation of these changes in networks, and their impacts in specialized circuits. We conclude that metaplasticity-defined broadly as the adaptive control of plasticity-forges connections across scales by governing what groups of synapses can and can't learn about, when, and to what ends. The metaplasticity we discuss acts by co-opting Hebbian mechanisms, shifting network properties, and routing activity within and across brain systems. Asking how these operations can go awry should also be useful for understanding pathology, which we address in the context of autism, schizophrenia and Parkinson's disease.

Thalamic regulation of frontal interactions in human cognitive flexibility

Interactions across frontal cortex are critical for cognition. Animal studies suggest a role for mediodorsal thalamus (MD) in these interactions, but the computations performed and direct relevance to human decision making are unclear. Here, inspired by animal work, we extended a neural model of an executive frontal-MD network and trained it on a human decision-making task for which neuroimaging data were collected. Using a biologically-plausible learning rule, we found that the model MD thalamus compressed its cortical inputs (dorsolateral prefrontal cortex, dlPFC) underlying stimulus-response representations. Through direct feedback to dlPFC, this thalamic operation efficiently partitioned cortical activity patterns and enhanced task switching across different contingencies. To account for interactions with other frontal regions, we expanded the model to compute higher-order strategy signals outside dlPFC, and found that the MD offered a more efficient route for such signals to switch dlPFC activity patterns. Human fMRI data provided evidence that the MD engaged in feedback to dlPFC, and had a role in routing orbitofrontal cortex inputs when subjects switched behavioral strategy. Collectively, our findings contribute to the emerging evidence for thalamic regulation of frontal interactions in the human brain.

The expansion of frontal cortex during mammalian evolution suggested a prominent role in intelligent and adaptive behavior, overshadowing earlier parts of the brain. However, recent rodent studies have pointed to a role for the cognitive mediodorsal thalamus (MD) in sustaining and flexibly switching representations in the frontal cortex, but direct relevance to human decision-making are unclear. Here, inspired by animal work, we extended a neural model of an executive frontal-MD network and trained it on a human decision-making task for which human neuroimaging data were collected. We found that the model MD thalamus learned an abstract representation of its cortical inputs and provided direct feedback to frontal cortex leading to flexible computations and enhanced task switching. These abstract MD representations and ability to re-organize frontal computations created an efficient mechanism where MD can integrate input from other regions to select behavioral strategy dynamically. The model predicted an efficient route through the MD for frontal region interactions and we found consistent evidence in human neuroimaging data. Collectively, our findings contribute to the emerging evidence for thalamic regulation of frontal interactions in the human brain.

Hierarchical Reinforcement Learning, Sequential Behavior, and the Dorsal Frontostriatal System

To effectively behave within ever-changing environments, biological agents must learn and act at varying hierarchical levels such that a complex task may be broken down into more tractable subtasks. Hierarchical reinforcement learning (HRL) is a computational framework that provides an understanding of this process by combining sequential actions into one temporally extended unit called an option. However, there are still open questions within the HRL framework, including how options are formed and how HRL mechanisms might be realized within the brain. In this review, we propose that the existing human motor sequence literature can aid in understanding both of these questions. We give specific emphasis to visuomotor sequence learning tasks such as the discrete sequence production task and the M × N (M steps × N sets) task to understand how hierarchical learning and behavior manifest across sequential action tasks as well as how the dorsal cortical-subcortical circuitry could support this kind of behavior. This review highlights how motor chunks within a motor sequence can function as HRL options. Furthermore, we aim to merge findings from motor sequence literature with reinforcement learning perspectives to inform experimental design in each respective subfield.

The Promise of Behavioral Tracking Systems for Advancing Primate Animal Welfare

Simple Summary

Computerized tracking systems for primates and other animals are one of the great inventions of the 21st century. These systems have already revolutionized the study of primatology, psychology, neuroscience, and biomedicine. Less discussed is that they also promise to greatly enhance animal welfare. Their potential benefits include identifying and reducing pain, suffering, and distress in captive populations, improving laboratory animal welfare, and applying our understanding of animal behavior to increase the “natural” behaviors in captive and wild populations, especially those under threat. We are optimistic that these changes will greatly increase the welfare of primates, including those in laboratories, zoos, primate centers, and in the wild.

Abstract

Recent years have witnessed major advances in the ability of computerized systems to track the positions of animals as they move through large and unconstrained environments. These systems have so far been a great boon in the fields of primatology, psychology, neuroscience, and biomedicine. Here, we discuss the promise of these technologies for animal welfare. Their potential benefits include identifying and reducing pain, suffering, and distress in captive populations, improving laboratory animal welfare within the context of the three Rs of animal research (reduction, refinement, and replacement), and applying our understanding of animal behavior to increase the “natural” behaviors in captive and wild populations facing human impact challenges. We note that these benefits are often incidental to the designed purpose of these tracking systems, a reflection of the fact that animal welfare is not inimical to research progress, but instead, that the aligned interests between basic research and welfare hold great promise for improvements to animal well-being.

Neuroscience needs evolution

The nervous system is a product of evolution. That is, it was constructed through a long series of modifications, within the strong constraints of heredity, and continuously subjected to intense selection pressures. As a result, the organization and functions of the brain are shaped by its history. We believe that this fact, underappreciated in contemporary systems neuroscience, offers an invaluable aid for helping us resolve the brain's mysteries. Indeed, we think that the consideration of evolutionary history ought to take its place alongside other intellectual tools used to understand the brain, such as behavioural experiments, studies of anatomical structure and functional characterization based on recordings of neural activity. In this introduction, we argue for the importance of evolution by highlighting specific examples of ways that evolutionary theory can enhance neuroscience. The rest of the theme issue elaborates this point, emphasizing the conservative nature of neural evolution, the important consequences of specific transitions that occurred in our history, and the ways in which considerations of evolution can shed light on issues ranging from specific mechanisms to fundamental principles of brain organization.

This article is part of the theme issue ‘Systems neuroscience through the lens of evolutionary theory’.