scholarly journals Of maps and grids

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
Matteo Grasso ◽  
Andrew M Haun ◽  
Giulio Tononi

Abstract Neuroscience has made remarkable advances in accounting for how the brain performs its various functions. Consciousness, too, is usually approached in functional terms: the goal is to understand how the brain represents information, accesses that information, and acts on it. While useful for prediction, this functional, information-processing approach leaves out the subjective structure of experience: it does not account for how experience feels. Here, we consider a simple model of how a “grid-like” network meant to resemble posterior cortical areas can represent spatial information and act on it to perform a simple “fixation” function. Using standard neuroscience tools, we show how the model represents topographically the retinal position of a stimulus and triggers eye muscles to fixate or follow it. Encoding, decoding, and tuning functions of model units illustrate the working of the model in a way that fully explains what the model does. However, these functional properties have nothing to say about the fact that a human fixating a stimulus would also “see” it—experience it at a location in space. Using the tools of Integrated Information Theory, we then show how the subjective properties of experienced space—its extendedness—can be accounted for in objective, neuroscientific terms by the “cause-effect structure” specified by the grid-like cortical area. By contrast, a “map-like” network without lateral connections, meant to resemble a pretectal circuit, is functionally equivalent to the grid-like system with respect to representation, action, and fixation but cannot account for the phenomenal properties of space.

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Yael Mandelblat-Cerf ◽  
Liora Las ◽  
Natalia Denisenko ◽  
Michale S Fee

Many learned motor behaviors are acquired by comparing ongoing behavior with an internal representation of correct performance, rather than using an explicit external reward. For example, juvenile songbirds learn to sing by comparing their song with the memory of a tutor song. At present, the brain regions subserving song evaluation are not known. In this study, we report several findings suggesting that song evaluation involves an avian 'cortical' area previously shown to project to the dopaminergic midbrain and other downstream targets. We find that this ventral portion of the intermediate arcopallium (AIV) receives inputs from auditory cortical areas, and that lesions of AIV result in significant deficits in vocal learning. Additionally, AIV neurons exhibit fast responses to disruptive auditory feedback presented during singing, but not during nonsinging periods. Our findings suggest that auditory cortical areas may guide learning by transmitting song evaluation signals to the dopaminergic midbrain and/or other subcortical targets.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuka Inamochi ◽  
Kenji Fueki ◽  
Nobuo Usui ◽  
Masato Taira ◽  
Noriyuki Wakabayashi

AbstractSuccessful adaptation to wearing dentures with palatal coverage may be associated with cortical activity changes related to tongue motor control. The purpose was to investigate the brain activity changes during tongue movement in response to a new oral environment. Twenty-eight fully dentate subjects (mean age: 28.6-years-old) who had no experience with removable dentures wore experimental palatal plates for 7 days. We measured tongue motor dexterity, difficulty with tongue movement, and brain activity using functional magnetic resonance imaging during tongue movement at pre-insertion (Day 0), as well as immediately (Day 1), 3 days (Day 3), and 7 days (Day 7) post-insertion. Difficulty with tongue movement was significantly higher on Day 1 than on Days 0, 3, and 7. In the subtraction analysis of brain activity across each day, activations in the angular gyrus and right precuneus on Day 1 were significantly higher than on Day 7. Tongue motor impairment induced activation of the angular gyrus, which was associated with monitoring of the tongue’s spatial information, as well as the activation of the precuneus, which was associated with constructing the tongue motor imagery. As the tongue regained the smoothness in its motor functions, the activation of the angular gyrus and precuneus decreased.


1989 ◽  
Vol 1 (4) ◽  
pp. 317-326 ◽  
Author(s):  
Sabrina J. Goodman ◽  
Richard A. Andersen

Microstimulation of many saccadic centers in the brain produces eye movements that are not consistent with either a strictly retinal or strictly head-centered coordinate coding of eye movements. Rather, stimulation produces some features of both types of coordinate coding. Recently we demonstrated a neural network model that was trained to localize the position of visual stimuli in head-centered coordinates at the output using inputs of eye and retinal position similar to those converging on area 7a of the posterior parietal cortex of monkeys (Zipser & Andersen 1988; Andersen & Zipser 1988). Here we show that microstimulation of this trained network, achieved by fully activating single units in the middle layer, produces “saccades” that are very much like the saccades produced by stimulating the brain. The activity of the middle-layer units can be considered to code the desired location of the eyes in head-centered coordinates; however, stimulation of these units does not produce the saccades predicted by a classical head-centered coordinate coding because the location in space appears to be coded in a distributed fashion among a population of units rather than explicitly at the level of single cells.


2021 ◽  
Vol 33 (5) ◽  
pp. 1372-1401
Author(s):  
Xi Liu ◽  
Xiang Shen ◽  
Shuhang Chen ◽  
Xiang Zhang ◽  
Yifan Huang ◽  
...  

Abstract Motor brain machine interfaces (BMIs) interpret neural activities from motor-related cortical areas in the brain into movement commands to control a prosthesis. As the subject adapts to control the neural prosthesis, the medial prefrontal cortex (mPFC), upstream of the primary motor cortex (M1), is heavily involved in reward-guided motor learning. Thus, considering mPFC and M1 functionality within a hierarchical structure could potentially improve the effectiveness of BMI decoding while subjects are learning. The commonly used Kalman decoding method with only one simple state model may not be able to represent the multiple brain states that evolve over time as well as along the neural pathway. In addition, the performance of Kalman decoders degenerates in heavy-tailed nongaussian noise, which is usually generated due to the nonlinear neural system or influences of movement-related noise in online neural recording. In this letter, we propose a hierarchical model to represent the brain states from multiple cortical areas that evolve along the neural pathway. We then introduce correntropy theory into the hierarchical structure to address the heavy-tailed noise existing in neural recordings. We test the proposed algorithm on in vivo recordings collected from the mPFC and M1 of two rats when the subjects were learning to perform a lever-pressing task. Compared with the classic Kalman filter, our results demonstrate better movement decoding performance due to the hierarchical structure that integrates the past failed trial information over multisite recording and the combination with correntropy criterion to deal with noisy heavy-tailed neural recordings.


Development ◽  
1997 ◽  
Vol 124 (24) ◽  
pp. 4959-4970 ◽  
Author(s):  
S. Tole ◽  
C. Christian ◽  
E.A. Grove

Studies of the specification of distinct areas in the developing cerebral cortex have until now focused mainly on neocortex. We demonstrate that the hippocampus, an archicortical structure, offers an elegant, alternative system in which to explore cortical area specification. Individual hippocampal areas, called CA fields, display striking molecular differences in maturity. We use these distinct patterns of gene expression as markers of CA field identity, and show that the two major hippocampal fields, CA1 and CA3, are specified early in hippocampal development, during the period of neurogenesis. Two field-specific markers display consistent patterns of expression from the embryo to the adult. Presumptive CA1 and CA3 fields (Pca1, Pca3) can therefore be identified between embryonic days 14.5 and 15.5 in the mouse, a week before the fields are morphologically distinct. No other individual cortical areas have been detected by gene expression as early in development. Indeed, other features that distinguish between the CA fields appear after birth, indicating that mature CA field identity is acquired over at least 3 weeks. To determine if Pca1 and Pca3 are already specified to acquire mature CA field identities, the embryonic fields were isolated from further potential specification cues by maintaining them in slice culture. CA field development proceeds in slices of the entire embryonic hippocampus. More strikingly, slices restricted to Pca1 or Pca3 alone also develop appropriate mature features of CA1 or CA3. Pca1 and Pca3 are therefore able to develop complex characteristics of mature CA field identity autonomously, that is, without contact or innervation from other fields or other parts of the brain. Because Pca1 and Pca3 can be identified before major afferents grow into the hippocampus, innervation may also be unnecessary for the initial division of the hippocampus into separate fields. Providing a clue to the source of the true specifying signals, the earliest field markers appear first at the poles of the hippocampus, then progress inwards. General hippocampal development does not follow this pronounced pattern. We suggest that the sources of signals that specify hippocampal field identity lie close to the hippocampal poles, and that the signals operate first on cells at the poles, then move inwards.


Author(s):  
Shirley H. Wray

discusses the brain’s visual architecture for directing and controlling of eye movements:the striate, frontal and parietal cortical areas; and the eye movements themselves—saccades, smooth pursuit, and vergence. The susceptibility to disorders of these systems is illustrated in four detailed cases that follow disease progression from initial symptoms and signs to diagnosis and treatment. The case studies and video displays include a patient with Pick’s disease (frontotemporal dementia), another with Alzheimer’s dementia, and two examples of rare saccadic syndromes, one a patient with the slow saccade syndrome due to progressive supranuclear palsy and one with selective saccadic palsy following cardiac surgery.


2019 ◽  
Vol 30 (3) ◽  
pp. 952-968
Author(s):  
Christoph Pokorny ◽  
Matias J Ison ◽  
Arjun Rao ◽  
Robert Legenstein ◽  
Christos Papadimitriou ◽  
...  

Abstract Memory traces and associations between them are fundamental for cognitive brain function. Neuron recordings suggest that distributed assemblies of neurons in the brain serve as memory traces for spatial information, real-world items, and concepts. However, there is conflicting evidence regarding neural codes for associated memory traces. Some studies suggest the emergence of overlaps between assemblies during an association, while others suggest that the assemblies themselves remain largely unchanged and new assemblies emerge as neural codes for associated memory items. Here we study the emergence of neural codes for associated memory items in a generic computational model of recurrent networks of spiking neurons with a data-constrained rule for spike-timing-dependent plasticity. The model depends critically on 2 parameters, which control the excitability of neurons and the scale of initial synaptic weights. By modifying these 2 parameters, the model can reproduce both experimental data from the human brain on the fast formation of associations through emergent overlaps between assemblies, and rodent data where new neurons are recruited to encode the associated memories. Hence, our findings suggest that the brain can use both of these 2 neural codes for associations, and dynamically switch between them during consolidation.


2020 ◽  
Vol 117 (36) ◽  
pp. 22522-22531 ◽  
Author(s):  
Mehran Spitmaan ◽  
Hyojung Seo ◽  
Daeyeol Lee ◽  
Alireza Soltani

A long-lasting challenge in neuroscience has been to find a set of principles that could be used to organize the brain into distinct areas with specific functions. Recent studies have proposed the orderly progression in the time constants of neural dynamics as an organizational principle of cortical computations. However, relationships between these timescales and their dependence on response properties of individual neurons are unknown, making it impossible to determine how mechanisms underlying such a computational principle are related to other aspects of neural processing. Here, we developed a comprehensive method to simultaneously estimate multiple timescales in neuronal dynamics and integration of task-relevant signals along with selectivity to those signals. By applying our method to neural and behavioral data during a dynamic decision-making task, we found that most neurons exhibited multiple timescales in their response, which consistently increased from parietal to prefrontal and cingulate cortex. While predicting rates of behavioral adjustments, these timescales were not correlated across individual neurons in any cortical area, resulting in independent parallel hierarchies of timescales. Additionally, none of these timescales depended on selectivity to task-relevant signals. Our results not only suggest the existence of multiple canonical mechanisms for increasing timescales of neural dynamics across cortex but also point to additional mechanisms that allow decorrelation of these timescales to enable more flexibility.


2015 ◽  
Vol 114 (6) ◽  
pp. 3211-3219 ◽  
Author(s):  
J. J. Tramper ◽  
W. P. Medendorp

It is known that the brain uses multiple reference frames to code spatial information, including eye-centered and body-centered frames. When we move our body in space, these internal representations are no longer in register with external space, unless they are actively updated. Whether the brain updates multiple spatial representations in parallel, or whether it restricts its updating mechanisms to a single reference frame from which other representations are constructed, remains an open question. We developed an optimal integration model to simulate the updating of visual space across body motion in multiple or single reference frames. To test this model, we designed an experiment in which participants had to remember the location of a briefly presented target while being translated sideways. The behavioral responses were in agreement with a model that uses a combination of eye- and body-centered representations, weighted according to the reliability in which the target location is stored and updated in each reference frame. Our findings suggest that the brain simultaneously updates multiple spatial representations across body motion. Because both representations are kept in sync, they can be optimally combined to provide a more precise estimate of visual locations in space than based on single-frame updating mechanisms.


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