The effect of age on alpha rhythms in the human brain derived from source localized resting-state electroencephalography.

With increasing age, peak alpha frequency (PAF) is slowed, and alpha power is reduced during resting-states with eyes closed. These age-related changes are evident across the whole scalp but remained unclear at the source level. The purpose of this study was to determine whether age impacts the power and frequency of the dominant alpha rhythm equally across source generators or whether the impact of age varies across sources. A total of 28 young adults and 26 elderly adults were recruited. High-density EEG was recorded for 10 mins with eyes closed. Single dipoles for each independent component were localized and clustered based on their anatomical label, resulting in 36 clusters. Meta-analyses were then conducted to assess effect sizes for PAF and power at PAF for all 36 clusters. Subgroup analyses were then implemented for frontal, sensorimotor, parietal, temporal, and occipital regions. The results of the meta-analyses showed that the elderly group exhibited slower PAF and less power at PAF compared to the young group. Subgroup analyses revealed age effects on PAF in parietal (g = 0.38), temporal (g = 0.65), and occipital regions (g = 1.04), with the largest effects observed in occipital regions. For power at PAF, age effects were observed in sensorimotor (g = 0.84) and parietal regions (g = 0.80), with the sensorimotor region showing the largest effect. Our findings show that age-related slowing and attenuation of the alpha rhythm manifests differentially across cortical regions, with sensorimotor and occipital regions most susceptible to age effects.

Brain anatomy and dynamics: A commentary on "Does the brain behave like a (complex) network? I. Dynamics" by Papo and Buldú (2024).

Papo and Buldú [1] ask whether the brain truly acts as a network, or whether it is a convenient coincidence that it can be described with the tools of complex network theory, and the emerging field of network neuroscience. After a broad ranging discussion of networkness they explore some of the ways in which the combination of brain structure and dynamics can indeed better be understood as realising a complex network that subserves brain function. To complement and bolster this perspective, which is informed largely from a physics viewpoint, we direct the reader to additional tools, approaches and insights available from applied mathematics that may further help address some of the many remaining open challenges in this field.

Diffusion MRI relates to plasma Aß42/40 in PET negative participants without dementia.

INTRODUCTION: Magnetic resonance imaging (MRI) biomarkers are needed for indexing early biological stages of Alzheimer's disease (AD), such as plasma amyloid-ß (Aß42/40) positivity in Aß positron emission tomography (PET) negative individuals. METHODS: Diffusion free-water (FW) MRI was acquired in individuals with normal cognition (NC) and mild cognitive impairment (MCI) with Aß plasma-/PET- (NC = 22, MCI = 60), plasma+/PET- (NC = 5, MCI = 20), and plasma+/PET+ (AD dementia = 21) biomarker status. Gray and white matter FW and fractional anisotropy (FAt) were compared cross-sectionally and the relationships between imaging, plasma and PET biomarkers were assessed. RESULTS: Plasma+/PET- demonstrated increased FW (24 regions) and decreased FAt (66 regions) compared to plasma-/PET-. FW (16 regions) and FAt (51 regions) were increased in plasma+/PET+ compared to plasma+/PET-. Composite brain FW correlated with plasma Aß42/40 and p-tau181. DISCUSSION: FW imaging changes distinguish plasma Aß42/40 positive and negative groups, independent of group differences in cognitive status, Aß PET status, and other plasma biomarkers (i.e., t-tau, p-tau181, glial fibrillary acidic protein, neurofilament light). HIGHLIGHTS: Plasma Aß42/40 positivity is associated with brain microstructure decline. Plasma+/PET- demonstrated increased FW in 24 total GM and WM regions. Plasma+/PET- demonstrated decreased FAt in 66 total GM and WM regions. Whole-brain FW correlated with plasma Aß42/40 and p-tau181 measures. Plasma+/PET- demonstrated decreased cortical volume and thickness.

Lower individual alpha frequency in individuals with chronic low back pain and fear of movement.

ABSTRACT: Significant progress has been made in linking measures of individual alpha frequency (IAF) and pain. A lower IAF has been associated with chronic neuropathic pain and with an increased sensitivity to pain in healthy young adults. However, the translation of these findings to chronic low back pain (cLBP) are sparse and inconsistent. To address this limitation, we assessed IAFs in a cohort of 70 individuals with cLBP, implemented 3 different IAF calculations, and separated cLBP subjects based on psychological variables. We hypothesized that a higher fear movement in cLBP is associated with a lower IAF at rest. A total of 10 minutes of resting data were collected from 128 electroencephalography channels. Our results offer 3 novel contributions to the literature. First, the high fear group had a significantly lower peak alpha frequency. The high fear group also reported higher pain and higher disability. Second, we calculated individual alpha frequency using 3 different but established methods; the effect of fear on individual alpha frequency was robust across all methods. Third, fear of movement, pain intensity, and disability highly correlated with each other and together significantly predicted IAF. Our findings are the first to show that individuals with cLBP and high fear have a lower peak alpha frequency.

The effect of chronic low back pain on postural control during quiet standing: A meta-analysis.

Low back pain (LBP) has been associated with altered body sway during quiet standing, but the pattern of results is inconsistent. The purpose of this meta-analysis is to examine the effects of vision (eyes open, eyes closed) and changing the support surface (foam surface, firm surface) on postural sway during quiet standing in individuals with chronic LBP (cLBP). Five electronic databases were searched on March 27th, 2022. Of 2,856, 16 studies (n = 663) were included. Across all conditions, we found a positive and medium effect size (g = 0.77 [0.50, 1.04]) that represented greater body sway in individuals with cLBP. Subgroup analyses revealed medium effects during eyes open conditions (firm surface: g = 0.60 [0.33, 0.87]; foam surface: g = 0.68 [0.38, 0.97]), and large effects during eyes closed conditions (firm surface: g = 0.97 [0.60, 1.35]; foam surface: g = 0.89 [0.28, 1.51]). We quantified effects of self-reported pain and found a moderate effect during eyes closed plus firm surface conditions (Q = 3.28; p = 0.070). We conclude that cLBP is associated with increased postural sway, with largest effect sizes evident when vision is removed and when self-reported pain intensity is higher.

Association of longitudinal cognitive decline with diffusion MRI in Gray Matter, Amyloid, and Tau deposition.

Extracellular amyloid plaques in gray matter are the earliest pathological marker for Alzheimer's disease (AD), followed by abnormal tau protein accumulation. The link between diffusion changes in gray matter, amyloid and tau pathology, and cognitive decline is not well understood. We first performed cross-sectional analyses on T1-weighted imaging, diffusion MRI, and amyloid and tau PETs from the ADNI 2/3 database. We evaluated cortical volume, free-water, fractional anisotropy (FA), and amyloid and tau SUVRs in 171 cognitively normal, 103 MCI, and 44 AD individuals. When the 3 groups were combined, increasing amyloid burden was associated with reduced extracellular free-water in the entorhinal cortex and hippocampus in those with amyloid-negative status whereas increasing tau burden was associated with increased extracellular free-water regardless of amyloid status. Next, we found that for the MCI subjects, diffusion measures (free-water, FA) alone predicted MMSE score 2 years later with a high r-square value (87%), as compared to tau SUVRs (27%), T1 volume (36%), and amyloid SUVRs (75%). Diffusion measures represent a potent non-invasive marker for predicting cognitive decline.

Structure-function clustering in weighted brain networks.

Functional networks, which typically describe patterns of activity taking place across the cerebral cortex, are widely studied in neuroscience. The dynamical features of these networks, and in particular their deviation from the relatively static structural network, are thought to be key to higher brain function. The interactions between such structural networks and emergent function, and the multimodal neuroimaging approaches and common analysis according to frequency band motivate a multilayer network approach. However, many such investigations rely on arbitrary threshold choices that convert dense, weighted networks to sparse, binary structures. Here, we generalise a measure of multiplex clustering to describe weighted multiplexes with arbitrarily-many layers. Moreover, we extend a recently-developed measure of structure-function clustering (that describes the disparity between anatomical connectivity and functional networks) to the weighted case. To demonstrate its utility we combine human connectome data with simulated neural activity and bifurcation analysis. Our results indicate that this new measure can extract neurologically relevant features not readily apparent in analogous single-layer analyses. In particular, we are able to deduce dynamical regimes under which multistable patterns of neural activity emerge. Importantly, these findings suggest a role for brain operation just beyond criticality to promote cognitive flexibility.

Neurophysiology of movement inhibition during full body reaching.

Our current understanding of response inhibition comes from go/no-go studies that draw conclusions based on the overt movement of single limbs (i.e., a single finger pushing a button). In general, go/no-go paradigms have found that an individual's ability to correctly inhibit the motor system is indicative of a healthy central nervous system. However, measuring inhibition by an overt behavioral response may lack the sensitivity to conclude whether the motor system is completely inhibited. Therefore, our goal was to use behavioral and neurophysiological measures to investigate inhibition of the motor system during a full-body reaching task. When directly comparing neurophysiological and behavioral measures, we found that neurophysiological measures were associated with a greater number of errors during no-go trials and faster onset times during go trials. Further analyses revealed a negative correlation between errors and onset times, such that the muscles that activated the earliest during go trials also had the greatest number of errors during no-go trials. Together, our observations show that the absence of an overt behavioral response does not always translate to total inhibition of the motor system.

Advanced diffusion imaging to track progression in Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy.

Advanced diffusion imaging which accounts for complex tissue properties, such as crossing fibers and extracellular fluid, may detect longitudinal changes in widespread pathology in atypical Parkinsonian syndromes. We implemented fixel-based analysis, Neurite Orientation and Density Imaging (NODDI), and free-water imaging in Parkinson's disease (PD), multiple system atrophy (MSAp), progressive supranuclear palsy (PSP), and controls longitudinally over one year. Further, we used these three advanced diffusion imaging techniques to investigate longitudinal progression-related effects in key white matter tracts and gray matter regions in PD and two common atypical Parkinsonian disorders. Fixel-based analysis and free-water imaging revealed longitudinal declines in a greater number of descending sensorimotor tracts in MSAp and PSP compared to PD. In contrast, only the primary motor descending sensorimotor tract had progressive decline over one year, measured by fiber density (FD), in PD compared to that in controls. PSP was characterized by longitudinal impairment in multiple transcallosal tracts (primary motor, dorsal and ventral premotor, pre-supplementary motor, and supplementary motor area) as measured by FD, whereas there were no transcallosal tracts with longitudinal FD impairment in MSAp and PD. In addition, free-water (FW) and FW-corrected fractional anisotropy (FAt) in gray matter regions showed longitudinal changes over one year in regions that have previously shown cross-sectional impairment in MSAp (putamen) and PSP (substantia nigra, putamen, subthalamic nucleus, red nucleus, and pedunculopontine nucleus). NODDI did not detect any longitudinal white matter tract progression effects and there were few effects in gray matter regions across Parkinsonian disorders. All three imaging methods were associated with change in clinical disease severity across all three Parkinsonian syndromes. These results identify novel extra-nigral and extra-striatal longitudinal progression effects in atypical Parkinsonian disorders through the application of multiple diffusion methods that are related to clinical disease progression. Moreover, the findings suggest that fixel-based analysis and free-water imaging are both particularly sensitive to these longitudinal changes in atypical Parkinsonian disorders.

Low Risk for Persistent Back Pain Disability Is Characterized by Lower Pain Sensitivity and Higher Physical Performance.

OBJECTIVE: The STarT Back Tool (SBT) predicts risk for persistent low back pain (LBP)-related disability based on psychological distress levels. Other non-psychological factors associated with LBP, such as pain sensitivity and physical performance, may further characterize SBT-risk subgroups. The purpose of this study was to determine whether a low-risk SBT subgroup demonstrated lower pain sensitivity and/or higher physical performance compared with a medium-/high-risk SBT subgroup. METHODS: In this cross-sectional, secondary analysis, adults with LBP (N = 76) completed SBT and demographics (age, sex, race, chronicity) questionnaires. Participants underwent pain sensitivity (local and remote pressure pain thresholds, temporal summation, conditioned pain modulation) and physical performance (Back Performance Scale, walking speed, obstacle negotiation, Timed "Up & Go" [TUG], TUG Cognitive) testing. Independent samples t tests determined low- versus medium-/high-risk SBT subgroup differences. A follow-up discriminant function analysis was also conducted. RESULTS: The medium-/high-risk subgroup demonstrated a lower proportion of participants with acute pain. The low-risk subgroup demonstrated lower pain sensitivity (higher local pressure pain thresholds and higher conditioned pain modulation) and higher physical performance (superior Back Performance Scale scores, faster walking speeds, faster obstacle approach and crossing speeds, and faster TUG completion). Discriminant function analysis results supported the 2-subgroup classification and indicated strong to moderate relationships with obstacle crossing speed, chronicity, and conditioned pain modulation. CONCLUSION: Lower pain sensitivity and higher physical performance characterized the low-risk SBT subgroup and may represent additional LBP prognostic factors associated with persistent disability. Longitudinal studies are needed to confirm whether these factors can enhance SBT prediction accuracy and further direct treatment priorities. IMPACT: Sensory and physical factors contribute to SBT risk classification, suggesting additional, non-psychological factors are indicative of favorable LBP outcomes. Findings highlight the need for assessment of multiple factors to improve LBP clinical prediction. LAY SUMMARY: People at low risk for back pain disability have less sensitivity to pain and better physical performance. By measuring these factors, physical therapists could guide treatment and improve outcomes for people with back pain.

Recalling fearful memories modifies approach and avoidance behavior based on spatial context.

Motor responses are more efficient when there is a match (or congruency) between the motivational properties of an emotional state and the distance altering characteristics of the movement being executed to the emotion-eliciting stimulus. However, the role of spatial context in shaping motivational orientations to approach and avoid, particularly during whole-body movement tasks, remains less understood. We sought to narrow this knowledge gap by investigating whether an emotion (fear) relived from a previous experience affected movement initiation based on whether motor responses were implicitly coded as approach (i.e., incongruent) or avoidance (i.e., congruent) as per the location of the imagined threat stimulus. Participants (N = 29) completed a tone-initiated forward gait initiation task after recalling a previous fearful experience in which the stimulus from their memory was located either in front (incongruent) or behind (congruent) them. Facilitation versus inhibition of motor responses was indexed by reaction time (RT), displacement and velocity of postural movements prior to stepping, and step kinematics. Analyses revealed that participants initiating forward gait after recalling a fearful experience in which the fearful stimulus was congruent to the movement direction expedited RTs, greater displacement and velocity of anticipatory postural responses, and greater step length and velocity. Results provide support for the theoretical position that motivational orientations to approach and avoid are contextualized based on affective congruency, which includes the spatial orientation of real or imagined emotional stimuli. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Mean-Field Models for EEG/MEG: From Oscillations to Waves.

Neural mass models have been used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. Here we consider a simple spiking neuron network model that has recently been shown to admit an exact mean-field description for both synaptic and gap-junction interactions. The mean-field model takes a similar form to a standard neural mass model, with an additional dynamical equation to describe the evolution of within-population synchrony. As well as reviewing the origins of this next generation mass model we discuss its extension to describe an idealised spatially extended planar cortex. To emphasise the usefulness of this model for EEG/MEG modelling we show how it can be used to uncover the role of local gap-junction coupling in shaping large scale synaptic waves.

Visuomotor brain network activation and functional connectivity among individuals with autism spectrum disorder.

Sensorimotor abnormalities are common in autism spectrum disorder (ASD) and predictive of functional outcomes, though their neural underpinnings remain poorly understood. Using functional magnetic resonance imaging, we examined both brain activation and functional connectivity during visuomotor behavior in 27 individuals with ASD and 30 typically developing (TD) controls (ages 9-35 years). Participants maintained a constant grip force while receiving visual feedback at three different visual gain levels. Relative to controls, ASD participants showed increased force variability, especially at high gain, and reduced entropy. Brain activation was greater in individuals with ASD than controls in supplementary motor area, bilateral superior parietal lobules, and contralateral middle frontal gyrus at high gain. During motor action, functional connectivity was reduced between parietal-premotor and parietal-putamen in individuals with ASD compared to controls. Individuals with ASD also showed greater age-associated increases in functional connectivity between cerebellum and visual, motor, and prefrontal cortical areas relative to controls. These results indicate that visuomotor deficits in ASD are associated with atypical activation and functional connectivity of posterior parietal, premotor, and striatal circuits involved in translating sensory feedback information into precision motor behaviors, and that functional connectivity of cerebellar-cortical sensorimotor and nonsensorimotor networks show delayed maturation.

Association of Cognitive Impairment With Free Water in the Nucleus Basalis of Meynert and Locus Coeruleus to Transentorhinal Cortex Tract.

BACKGROUND AND OBJECTIVES: The goal of this work was to determine the relationship between diffusion microstructure and early changes in Alzheimer disease (AD) severity as assessed by clinical diagnosis, cognitive performance, dementia severity, and plasma concentrations of neurofilament light chain. METHODS: Diffusion MRI scans were collected on cognitively normal participants (CN) and patients with early mild cognitive impairment (EMCI), late mild cognitive impairment, and AD. Free water (FW) and FW-corrected fractional anisotropy were calculated in the locus coeruleus to transentorhinal cortex tract, 4 magnocellular regions of the basal forebrain (e.g., nucleus basalis of Meynert), entorhinal cortex, and hippocampus. All patients underwent a battery of cognitive assessments; neurofilament light chain levels were measured in plasma samples. RESULTS: FW was significantly higher in patients with EMCI compared to CN in the locus coeruleus to transentorhinal cortex tract, nucleus basalis of Meynert, and hippocampus (mean Cohen d = 0.54; p fdr < 0.05). FW was significantly higher in those with AD compared to CN in all the examined regions (mean Cohen d = 1.41; p fdr < 0.01). In addition, FW in the hippocampus, entorhinal cortex, nucleus basalis of Meynert, and locus coeruleus to transentorhinal cortex tract positively correlated with all 5 cognitive impairment metrics and neurofilament light chain levels (mean r 2 = 0.10; p fdr < 0.05). DISCUSSION: These results show that higher FW is associated with greater clinical diagnosis severity, cognitive impairment, and neurofilament light chain. They also suggest that FW elevation occurs in the locus coeruleus to transentorhinal cortex tract, nucleus basalis of Meynert, and hippocampus in the transition from CN to EMCI, while other basal forebrain regions and the entorhinal cortex are not affected until a later stage of AD. FW is a clinically relevant and noninvasive early marker of structural changes related to cognitive impairment.

Unraveling somatotopic organization in the human brain using machine learning and adaptive supervoxel-based parcellations.

In addition to the well-established somatotopy in the pre- and post-central gyrus, there is now strong evidence that somatotopic organization is evident across other regions in the sensorimotor network. This raises several experimental questions: To what extent is activity in the sensorimotor network effector-dependent and effector-independent? How important is the sensorimotor cortex when predicting the motor effector? Is there redundancy in the distributed somatotopically organized network such that removing one region has little impact on classification accuracy? To answer these questions, we developed a novel experimental approach. fMRI data were collected while human subjects performed a precisely controlled force generation task separately with their hand, foot, and mouth. We used a simple linear iterative clustering (SLIC) algorithm to segment whole-brain beta coefficient maps to build an adaptive brain parcellation and then classified effectors using extreme gradient boosting (XGBoost) based on parcellations at various spatial resolutions. This allowed us to understand how data-driven adaptive brain parcellation granularity altered classification accuracy. Results revealed effector-dependent activity in regions of the post-central gyrus, precentral gyrus, and paracentral lobule. SMA, regions of the inferior and superior parietal lobule, and cerebellum each contained effector-dependent and effector-independent representations. Machine learning analyses showed that increasing the spatial resolution of the data-driven model increased classification accuracy, which reached 94% with 1755 supervoxels. Our SLIC-based supervoxel parcellation outperformed classification analyses using established brain templates and random simulations. Occlusion experiments further demonstrated redundancy across the sensorimotor network when classifying effectors. Our observations extend our understanding of effector-dependent and effector-independent organization within the human brain and provide new insight into the functional neuroanatomy required to predict the motor effector used in a motor control task.

A dynamic neural field model of continuous input integration.

The ability of neural systems to turn transient inputs into persistent changes in activity is thought to be a fundamental requirement for higher cognitive functions. In continuous attractor networks frequently used to model working memory or decision making tasks, the persistent activity settles to a stable pattern with the stereotyped shape of a "bump" independent of integration time or input strength. Here, we investigate a new bump attractor model in which the bump width and amplitude not only reflect qualitative and quantitative characteristics of a preceding input but also the continuous integration of evidence over longer timescales. The model is formalized by two coupled dynamic field equations of Amari-type which combine recurrent interactions mediated by a Mexican-hat connectivity with local feedback mechanisms that balance excitation and inhibition. We analyze the existence, stability and bifurcation structure of single and multi-bump solutions and discuss the relevance of their input dependence to modeling cognitive functions. We then systematically compare the pattern formation process of the two-field model with the classical Amari model. The results reveal that the balanced local feedback mechanisms facilitate the encoding and maintenance of multi-item memories. The existence of stable subthreshold bumps suggests that different to the Amari model, the suppression effect of neighboring bumps in the range of lateral competition may not lead to a complete loss of information. Moreover, bumps with larger amplitude are less vulnerable to noise-induced drifts and distance-dependent interaction effects resulting in more faithful memory representations over time.

Pain differences in neurite orientation dispersion and density imaging measures among community-dwelling older adults.

Neurite orientation dispersion and density imaging (NODDI) is a technique providing more detailed information on the microstructural bases of white matter. Given the previously reported white matter contributions to chronic pain, the present study aims to investigate pain-specific differences in NODDI measures across white matter tracts in a sample of community-dwelling older adults with (n = 29) and without (n = 18) chronic musculoskeletal pain. We further aimed to investigate associations between NODDI measures and clinical and experimental pain measures. As part of the Nepal study, a subset of older adults (>60 years old), underwent multiple laboratory sessions providing self-reported and experimental pain measures and a diffusion weighted neuroimaging sequence. Older adults with chronic musculoskeletal pain had a lower neurite density with less geometric complexity across a number of white matter tracts compared to older pain-free controls (corrected p's < 0.05). Lower neurite density was associated with greater self-reported pain intensity and anatomical pain sites, as well as greater experimental pain sensitivity (p's < 0.05). There were also significant pain-by-sex differences in neurite density and geometric complexity across multiple white matter tracts mainly around the hippocampus (corrected p's < 0.05). Finally, there were no pain differences with respect to extra-cellular water diffusion (corrected p's > 0.05). Our study demonstrates less geometric complexity in neurite density and architecture in chronic musculoskeletal pain, partly in a sex-dependent manner. An increased understanding of neurobiological mechanisms such as those measured by NODDI may contribute to the potential targeting of interventions in our older population suffering from chronic pain.

Reinforcement learning approaches to hippocampus-dependent flexible spatial navigation.

Humans and non-human animals show great flexibility in spatial navigation, including the ability to return to specific locations based on as few as one single experience. To study spatial navigation in the laboratory, watermaze tasks, in which rats have to find a hidden platform in a pool of cloudy water surrounded by spatial cues, have long been used. Analogous tasks have been developed for human participants using virtual environments. Spatial learning in the watermaze is facilitated by the hippocampus. In particular, rapid, one-trial, allocentric place learning, as measured in the delayed-matching-to-place variant of the watermaze task, which requires rodents to learn repeatedly new locations in a familiar environment, is hippocampal dependent. In this article, we review some computational principles, embedded within a reinforcement learning framework, that utilise hippocampal spatial representations for navigation in watermaze tasks. We consider which key elements underlie their efficacy, and discuss their limitations in accounting for hippocampus-dependent navigation, both in terms of behavioural performance (i.e. how well do they reproduce behavioural measures of rapid place learning) and neurobiological realism (i.e. how well do they map to neurobiological substrates involved in rapid place learning). We discuss how an actor-critic architecture, enabling simultaneous assessment of the value of the current location and of the optimal direction to follow, can reproduce one-trial place learning performance as shown on watermaze and virtual delayed-matching-to-place tasks by rats and humans, respectively, if complemented with map-like place representations. The contribution of actor-critic mechanisms to delayed-matching-to-place performance is consistent with neurobiological findings implicating the striatum and hippocampo-striatal interaction in delayed-matching-to-place performance, given that the striatum has been associated with actor-critic mechanisms. Moreover, we illustrate that hierarchical computations embedded within an actor-critic architecture may help to account for aspects of flexible spatial navigation. The hierarchical reinforcement learning approach separates trajectory control via a temporal-difference error from goal selection via a goal prediction error and may account for flexible, trial-specific, navigation to familiar goal locations, as required in some arm-maze place memory tasks, although it does not capture one-trial learning of new goal locations, as observed in open field, including watermaze and virtual, delayed-matching-to-place tasks. Future models of one-shot learning of new goal locations, as observed on delayed-matching-to-place tasks, should incorporate hippocampal plasticity mechanisms that integrate new goal information with allocentric place representation, as such mechanisms are supported by substantial empirical evidence.

Functional imaging of the brainstem during visually-guided motor control reveals visuomotor regions in the pons and midbrain.

Integrating visual information for motor output is an essential process of visually-guided motor control. The brainstem is known to be a major center involved in the integration of sensory information for motor output, however, limitations of functional imaging in humans have impaired our knowledge about the individual roles of sub-nuclei within the brainstem. Thus, the bulk of our knowledge surrounding the function of the brainstem is based on anatomical and behavioral studies in non-human primates, cats, and rodents, despite studies demonstrating differences in the organization of visuomotor processing between mammals. fMRI studies in humans have examined activity related to visually-guided motor tasks, however, few have done so while controlling for both force without visual feedback activity and visual stimuli without force activity. Of the studies that have controlled for both conditions, none have reported brainstem activity. Here, we employed a novel fMRI paradigm focused on the brainstem and cerebellum to systematically investigate the hypothesis that the pons and midbrain are critical for the integration of visual information for motor control. Visuomotor activity during visually-guided pinch-grip force was measured while controlling for force without visual feedback activity and visual stimuli without force activity in healthy adults. Using physiological noise correction and multiple task repetitions, we demonstrated that visuomotor activity occurs in the inferior portion of the basilar pons and the midbrain. These findings provide direct evidence in humans that the pons and midbrain support the integration of visual information for motor control. We also determined the effect of physiological noise and task repetitions on the visuomotor signal that will be useful in future studies of neurodegenerative diseases affecting the brainstem.