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NeuroImage Apr 2018Brain regions are often topographically connected: nearby locations within one brain area connect with nearby locations in another area. Mapping these connection... (Review)
Review
Brain regions are often topographically connected: nearby locations within one brain area connect with nearby locations in another area. Mapping these connection topographies, or 'connectopies' in short, is crucial for understanding how information is processed in the brain. Here, we propose principled, fully data-driven methods for mapping connectopies using functional magnetic resonance imaging (fMRI) data acquired at rest by combining spectral embedding of voxel-wise connectivity 'fingerprints' with a novel approach to spatial statistical inference. We apply the approach in human primary motor and visual cortex, and show that it can trace biologically plausible, overlapping connectopies in individual subjects that follow these regions' somatotopic and retinotopic maps. As a generic mechanism to perform inference over connectopies, the new spatial statistics approach enables rigorous statistical testing of hypotheses regarding the fine-grained spatial profile of functional connectivity and whether that profile is different between subjects or between experimental conditions. The combined framework offers a fundamental alternative to existing approaches to investigating functional connectivity in the brain, from voxel- or seed-pair wise characterizations of functional association, towards a full, multivariate characterization of spatial topography.
Topics: Connectome; Data Interpretation, Statistical; Humans; Magnetic Resonance Imaging; Motor Cortex; Visual Cortex
PubMed: 28666880
DOI: 10.1016/j.neuroimage.2017.06.075 -
Cerebral Cortex (New York, N.Y. : 1991) Jun 2022Deciphering the physiological patterns of motor network connectivity is a prerequisite to elucidate aberrant oscillatory transformations and elaborate robust...
Deciphering the physiological patterns of motor network connectivity is a prerequisite to elucidate aberrant oscillatory transformations and elaborate robust translational models of movement disorders. In the proposed translational approach, we studied the connectivity between premotor (PMC) and primary motor cortex (M1) by recording high-density electroencephalography in humans and between caudal (CFA) and rostral forelimb (RFA) areas by recording multi-site extracellular activity in mice to obtain spectral power, functional and effective connectivity. We identified a significantly higher spectral power in β- and γ-bands in M1compared to PMC and similarly in mice CFA layers (L) 2/3 and 5 compared to RFA. We found a strong functional β-band connectivity between PMC and M1 in humans and between CFA L6 and RFA L5 in mice. We observed that in both humans and mice the direction of information flow mediated by β- and γ-band oscillations was predominantly from PMC toward M1 and from RFA to CFA, respectively. Combining spectral power, functional and effective connectivity, we revealed clear similarities between human PMC-M1 connections and mice RFA-CFA network. We propose that reciprocal connectivity of mice RFA-CFA circuitry presents a suitable model for analysis of motor control and physiological PMC-M1 functioning or pathological transformations within this network.
Topics: Animals; Electroencephalography; Forelimb; Mice; Motor Cortex; Neural Pathways
PubMed: 34689188
DOI: 10.1093/cercor/bhab369 -
Trends in Neurosciences Mar 2017In rodents, the medial aspect of the secondary motor cortex (M2) is known by other names, including medial agranular cortex (AGm), medial precentral cortex (PrCm), and... (Review)
Review
In rodents, the medial aspect of the secondary motor cortex (M2) is known by other names, including medial agranular cortex (AGm), medial precentral cortex (PrCm), and frontal orienting field (FOF). As a subdivision of the medial prefrontal cortex (mPFC), M2 can be defined by a distinct set of afferent and efferent connections, microstimulation responses, and lesion outcomes. However, the behavioral role of M2 remains mysterious. Here, we focus on evidence from rodent studies, highlighting recent findings of early and context-dependent choice-related activity in M2 during voluntary behavior. Based on the current understanding, we suggest that a major function for M2 is to flexibly map antecedent signals such as sensory cues to motor actions, thereby enabling adaptive choice behavior.
Topics: Animals; Frontal Lobe; Humans; Motor Activity; Motor Cortex; Neural Pathways; Perception; Rodentia
PubMed: 28012708
DOI: 10.1016/j.tins.2016.11.006 -
Nature Human Behaviour Apr 2024The most prominent characteristic of motor cortex is its activation during movement execution, but it is also active when we simply imagine movements in the absence of...
The most prominent characteristic of motor cortex is its activation during movement execution, but it is also active when we simply imagine movements in the absence of actual motor output. Despite decades of behavioural and imaging studies, it is unknown how the specific activity patterns and temporal dynamics in motor cortex during covert motor imagery relate to those during motor execution. Here we recorded intracortical activity from the motor cortex of two people who retain some residual wrist function following incomplete spinal cord injury as they performed both actual and imagined isometric wrist extensions. We found that we could decompose the population activity into three orthogonal subspaces, where one was similarly active during both action and imagery, and the others were active only during a single task type-action or imagery. Although they inhabited orthogonal neural dimensions, the action-unique and imagery-unique subspaces contained a strikingly similar set of dynamic features. Our results suggest that during motor imagery, motor cortex maintains the same overall population dynamics as during execution by reorienting the components related to motor output and/or feedback into a unique, output-null imagery subspace.
Topics: Humans; Motor Cortex; Imagination; Male; Spinal Cord Injuries; Adult; Movement; Female; Wrist; Motor Activity; Middle Aged; Psychomotor Performance
PubMed: 38287177
DOI: 10.1038/s41562-023-01804-5 -
Current Opinion in Neurobiology Aug 2015The issue of coding of movement in the motor cortex has recently acquired special significance due to its fundamental importance in neuroprosthetic applications. The... (Review)
Review
The issue of coding of movement in the motor cortex has recently acquired special significance due to its fundamental importance in neuroprosthetic applications. The challenge of controlling a prosthetic arm by processed motor cortical activity has opened a new era of research in applied medicine but has also provided an 'acid test' for hypotheses regarding coding of movement in the motor cortex. The successful decoding of movement information from the activity of motor cortical cells using their directional tuning and population coding has propelled successful neuroprosthetic applications and, at the same time, asserted the utility of those early discoveries, dating back to the early 1980s.
Topics: Afferent Pathways; Hand Strength; Humans; Models, Biological; Motor Cortex; Movement; Neurons
PubMed: 25646932
DOI: 10.1016/j.conb.2015.01.012 -
Brain Structure & Function Dec 2023The cortex contains multiple motor areas, including the primary motor cortex (M1) and supplementary motor area (SMA). Many muscles are represented in both the M1 and... (Review)
Review
The cortex contains multiple motor areas, including the primary motor cortex (M1) and supplementary motor area (SMA). Many muscles are represented in both the M1 and SMA, but the reason for this dual representation remains unclear. Previous work has shown that the M1 and SMA representations of a specific human muscle can be differentiated according to their functional connectivity with different brain areas located outside of the motor cortex. It is our perspective that this differential functional connectivity may be the neural substrate that allows an individual muscle to be accessed by distinct neural processes, such as those implementing volitional vs. postural task control. Here, we review existing human and animal literature suggesting how muscles are represented in the M1 and SMA and how these brain regions have distinct functions. We also discuss potential studies to further elucidate the distinct roles of the SMA and M1 in normal and dysfunctional motor control.
Topics: Animals; Humans; Motor Cortex; Muscles; Neural Pathways; Brain Mapping
PubMed: 37709903
DOI: 10.1007/s00429-023-02703-1 -
Neuroscience and Biobehavioral Reviews Jul 2019Working memory is vital for basic functions in everyday life. During working memory, one holds a finite amount of information in mind until it is no longer required or... (Review)
Review
Working memory is vital for basic functions in everyday life. During working memory, one holds a finite amount of information in mind until it is no longer required or when resources to maintain this information are depleted. Convergence of neuroimaging data indicates that working memory is supported by the motor system, and in particular, by regions that are involved in motor planning and preparation, in the absence of overt movement. These "secondary motor" regions are physically located between primary motor and non-motor regions, within the frontal lobe, cerebellum, and basal ganglia, creating a functionally organized gradient. The contribution of secondary motor regions to working memory may be to generate internal motor traces that reinforce the representation of information held in mind. The primary aim of this review is to elucidate motor-cognitive interactions through the lens of working memory using the Sternberg paradigm as a model and to suggest origins of the motor-cognitive interface. In addition, we discuss the implications of the motor-cognitive relationship for clinical groups with motor network deficits.
Topics: Basal Ganglia; Cerebellum; Humans; Memory, Short-Term; Motor Cortex; Movement Disorders; Nerve Net
PubMed: 31039359
DOI: 10.1016/j.neubiorev.2019.04.017 -
Frontiers in Neural Circuits 2015When Hubel (1982) referred to layer 1 of primary visual cortex as "… a 'crowning mystery' to keep area-17 physiologists busy for years to come …" he could have been... (Review)
Review
When Hubel (1982) referred to layer 1 of primary visual cortex as "… a 'crowning mystery' to keep area-17 physiologists busy for years to come …" he could have been talking about any cortical area. In the 80's and 90's there were no methods to examine this neuropile on the surface of the cortex: a tangled web of axons and dendrites from a variety of different places with unknown specificities and doubtful connections to the cortical output neurons some hundreds of microns below. Recently, three changes have made the crowning enigma less of an impossible mission: the clear presence of neurons in layer 1 (L1), the active conduction of voltage along apical dendrites and optogenetic methods that might allow us to look at one source of input at a time. For all of those reasons alone, it seems it is time to take seriously the function of L1. The functional properties of this layer will need to wait for more experiments but already L1 cells are GAD67 positive, i.e., inhibitory! They could reverse the sign of the thalamic glutamate (GLU) input for the entire cortex. It is at least possible that in the near future normal activity of individual sources of L1 could be detected using genetic tools. We are at the outset of important times in the exploration of thalamic functions and perhaps the solution to the crowning enigma is within sight. Our review looks forward to that solution from the solid basis of the anatomy of the basal ganglia output to motor thalamus. We will focus on L1, its afferents, intrinsic neurons and its influence on responses of pyramidal neurons in layers 2/3 and 5. Since L1 is present in the whole cortex we will provide a general overview considering evidence mainly from the somatosensory (S1) cortex before focusing on motor cortex.
Topics: Animals; Basal Ganglia; Motor Cortex; Thalamus
PubMed: 26582979
DOI: 10.3389/fncir.2015.00071 -
Experimental Brain Research Aug 2020I-waves represent high-frequency (~ 600 Hz) repetitive discharge of corticospinal fibers elicited by single-pulse stimulation of motor cortex. First detected and...
I-waves represent high-frequency (~ 600 Hz) repetitive discharge of corticospinal fibers elicited by single-pulse stimulation of motor cortex. First detected and examined in animal preparations, this multiple discharge can also be recorded in humans from the corticospinal tract with epidural spinal electrodes. The exact underpinning neurophysiology of I-waves is still unclear, but there is converging evidence that they originate at the cortical level through synaptic input from specific excitatory interneuronal circuitries onto corticomotoneuronal cells, controlled by GABAAergic interneurons. In contrast, there is at present no supportive evidence for the alternative hypothesis that I-waves are generated by high-frequency oscillations of the membrane potential of corticomotoneuronal cells upon initial strong depolarization. Understanding I-wave physiology is essential for understanding how TMS activates the motor cortex.
Topics: Animals; Evoked Potentials, Motor; Humans; Interneurons; Membrane Potentials; Motor Cortex; Pyramidal Tracts; Transcranial Magnetic Stimulation
PubMed: 32185405
DOI: 10.1007/s00221-020-05764-4 -
ELife Sep 2022Neural plasticity allows us to learn skills and incorporate new experiences. What happens when our lived experiences fundamentally change, such as after a severe injury?...
Neural plasticity allows us to learn skills and incorporate new experiences. What happens when our lived experiences fundamentally change, such as after a severe injury? To address this question, we analyzed intracortical population activity in the posterior parietal cortex (PPC) of a tetraplegic adult as she controlled a virtual hand through a brain-computer interface (BCI). By attempting to move her fingers, she could accurately drive the corresponding virtual fingers. Neural activity during finger movements exhibited robust representational structure similar to fMRI recordings of able-bodied individuals' motor cortex, which is known to reflect able-bodied usage patterns. The finger representational structure was consistent throughout multiple sessions, even though the structure contributed to BCI decoding errors. Within individual BCI movements, the representational structure was dynamic, first resembling muscle activation patterns and then resembling the anticipated sensory consequences. Our results reveal that motor representations in PPC reflect able-bodied motor usage patterns even after paralysis, and BCIs can re-engage these stable representations to restore lost motor functions.
Topics: Adult; Brain-Computer Interfaces; Female; Fingers; Humans; Magnetic Resonance Imaging; Motor Cortex; Movement; Paralysis
PubMed: 36125116
DOI: 10.7554/eLife.74478