scholarly journals Randomly connected networks generate emergent selectivity and predict decoding properties of large populations of neurons

2019 ◽  
Author(s):  
Audrey Sederberg ◽  
Ilya Nemenman
Keyword(s):  
Cortical Neurons ◽  
Posterior Parietal Cortex ◽  
Neural Circuit ◽  
Functional Organization ◽  
Alternative Hypothesis ◽  
Random Network ◽  
Single Cells ◽  
Emergent Properties ◽  
Alternative Mechanism ◽  
Large Populations

AbstractAdvances in neural recording methods enable sampling from populations of thousands of neurons during the performance of behavioral tasks, raising the question of how recorded activity relates to the theoretical models of computations underlying performance. In the context of decision making in rodents, patterns of functional connectivity between choice-selective cortical neurons, as well as broadly distributed choice information in both excitatory and inhibitory populations, were recently reported [1]. The straightforward interpretation of these data suggests a mechanism relying on specific patterns of anatomical connectivity to achieve selective pools of inhibitory as well as excitatory neurons. We investigate an alternative mechanism for the emergence of these experimental observations using a computational approach. We find that a randomly connected network of excitatory and inhibitory neurons generates single-cell selectivity, patterns of pairwise correlations, and indistinguishable excitatory and inhibitory readout weight distributions, as observed in recorded neural populations. Further, we make the readily verifiable experimental predictions that, for this type of evidence accumulation task, there are no anatomically defined sub-populations of neurons representing choice, and that choice preference of a particular neuron changes with the details of the task. This work suggests that distributed stimulus selectivity and patterns of functional organization in population codes could be emergent properties of randomly connected networks.Author summaryWhat can we learn about neural circuit organization and function from recordings of large populations of neurons? For example, in population recordings in the posterior parietal cortex of mice performing an evidence integration task, particular patterns of selectivity and correlations between cells were observed. One hypothesis for an underlying mechanism generating these patterns is that they follow from intricate rules of connectivity between specific neurons, but this raises the question of how such intricate patterns arise during learning or development. An alternative hypothesis, which we explore here, is that such patterns emerge from networks with broad spectra of eigenvalues, which is a generic property of certain random networks. We find that a random network model matches many features of experimental recordings, from single cells to populations. We suggest that such emergent selectivity could be an important principle in brain areas, in which a broad distribution of selectivity is observed.

scholarly journals Functional organization of human posterior parietal cortex: grasping- and reaching-related activations relative to topographically organized cortex

2013 ◽  
Vol 109 (12) ◽  
pp. 2897-2908 ◽  
Author(s):  
Christina S. Konen ◽  
Ryan E. B. Mruczek ◽  
Jessica L. Montoya ◽  
Sabine Kastner
Keyword(s):  
Neural Networks ◽  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Functional Organization ◽  
Macaque Monkey ◽  
Superior Parietal Lobule ◽  
Movement Type ◽  
The Neural Networks ◽  
Posterior Parietal ◽  
The Relationship

The act of reaching to grasp an object requires the coordination between transporting the arm and shaping the hand. Neurophysiological, neuroimaging, neuroanatomic, and neuropsychological studies in macaque monkeys and humans suggest that the neural networks underlying grasping and reaching acts are at least partially separable within the posterior parietal cortex (PPC). To better understand how these neural networks have evolved in primates, we characterized the relationship between grasping- and reaching-related responses and topographically organized areas of the human intraparietal sulcus (IPS) using functional MRI. Grasping-specific activation was localized to the left anterior IPS, partially overlapping with the most anterior topographic regions and extending into the postcentral sulcus. Reaching-specific activation was localized to the left precuneus and superior parietal lobule, partially overlapping with the medial aspects of the more posterior topographic regions. Although the majority of activity within the topographic regions of the IPS was nonspecific with respect to movement type, we found evidence for a functional gradient of specificity for reaching and grasping movements spanning posterior-medial to anterior-lateral PPC. In contrast to the macaque monkey, grasp- and reach-specific activations were largely located outside of the human IPS.

scholarly journals The Development of Single-Cell Metabolism and Its Role in Studying Cancer Emergent Properties

2022 ◽  
Vol 11 ◽  
Author(s):  
Dingju Wei ◽  
Meng Xu ◽  
Zhihua Wang ◽  
Jingjing Tong
Keyword(s):  
Tumor Cell ◽  
Single Cell ◽  
Immune Escape ◽  
Cell Metabolism ◽  
Single Cells ◽  
Metabolic Reprogramming ◽  
Biological Information ◽  
Emergent Properties ◽  
Anti Cancer ◽  
Cell Metabolomics

Metabolic reprogramming is one of the hallmarks of malignant tumors, which provides energy and material basis for tumor rapid proliferation, immune escape, as well as extensive invasion and metastasis. Blocking the energy and material supply of tumor cells is one of the strategies to treat tumor, however tumor cell metabolic heterogeneity prevents metabolic-based anti-cancer treatment. Therefore, searching for the key metabolic factors that regulate cell cancerous change and tumor recurrence has become a major challenge. Emerging technology––single-cell metabolomics is different from the traditional metabolomics that obtains average information of a group of cells. Single-cell metabolomics identifies the metabolites of single cells in different states by mass spectrometry, and captures the molecular biological information of the energy and substances synthesized in single cells, which provides more detailed information for tumor treatment metabolic target screening. This review will combine the current research status of tumor cell metabolism with the advantages of single-cell metabolomics technology, and explore the role of single-cell sequencing technology in searching key factors regulating tumor metabolism. The addition of single-cell technology will accelerate the development of metabolism-based anti-cancer strategies, which may greatly improve the prognostic survival rate of cancer patients.

scholarly journals Subthreshold membrane potential dynamics of posterior parietal cortical neurons coupled with hippocampal ripples

2021 ◽  
Author(s):  
Y. Sato ◽  
H. Mizuno ◽  
N. Matsumoto ◽  
Y. Ikegaya
Keyword(s):  
Local Field ◽  
Cortical Neurons ◽  
Posterior Parietal Cortex ◽  
Pyramidal Cells ◽  
Membrane Potentials ◽  
High Frequency Oscillations ◽  
Neocortical Neurons ◽  
Field Activity ◽  
Posterior Parietal ◽  
Post Hoc

AbstractDuring behavioral states of immobility, sleep, and anesthesia, the hippocampus generates high-frequency oscillations called ripples. Ripples occur simultaneously with synchronous neuronal activity in the neocortex, known as slow waves, and contribute to memory consolidation. During these ripples, various neocortical regions exhibit modulations in spike rates and local field activity irrespective of whether they receive direct synaptic inputs from the hippocampus. However, little is known about the subthreshold dynamics of the membrane potentials of neocortical neurons during ripples. We patch-clamped layer 2/3 pyramidal cells in the posterior parietal cortex (PPC), a neocortical region that is involved in allocentric spatial representation of behavioral exploration and sequential series of relevant action potentials during ripples. We simultaneously monitored the membrane potentials of post hoc-identified PPC neurons and the local field potentials of the hippocampus in anesthetized mice. More than 50% of the recorded PPC neurons exhibited significant depolarizations and/or hyperpolarizations during ripples. Histological inspections of the recorded neurons revealed that the ripple-modulated PPC neurons were distributed in the PPC in a spatially non-biased fashion. These results suggest that hippocampal ripples are widely but selectively associated with the subthreshold dynamics of the membrane potentials of PPC neurons even though there is no monosynaptic connectivity between the hippocampus and the PPC.

scholarly journals Transcranial Alternating Current Stimulation (tACS) Entrains Alpha Oscillations by Preferential Phase Synchronization of Fast-Spiking Cortical Neurons to Stimulation Waveform

2019 ◽  
Author(s):  
Ehsan Negahbani ◽  
Iain M. Stitt ◽  
Marshall Davey ◽  
Thien T. Doan ◽  
Moritz Dannhauer ◽  
...  
Keyword(s):  
Electric Field ◽  
Electric Fields ◽  
Cortical Neurons ◽  
Posterior Parietal Cortex ◽  
Phase Synchronization ◽  
Alternating Current ◽  
Arnold Tongue ◽  
Transcranial Alternating Current Stimulation ◽  
Neuronal Oscillators

SummaryModeling studies predict that transcranial alternating current stimulation (tACS) entrains brain oscillations, yet direct examination has been lacking or potentially contaminated by stimulation artefact. Here we first demonstrate how the posterior parietal cortex drives primary visual cortex and thalamic LP in the alpha-band in head-fixed awake ferrets. The spike-field synchrony is maximum within alpha frequency, and more prominent for narrow-spiking neurons than broad-spiking ones. Guided by a validated model of electric field distribution, we produced electric fields comparable to those in humans and primates (< 0.5 mV/mm). We found evidence to support the model-driven predictions of how tACS entrains neural oscillations as explained by the triangular Arnold tongue pattern. In agreement with the stronger spike-field coupling of narrow-spiking cells, tACS more strongly entrained this cell population. Our findings provide the firstin vivoevidence of how tACS with electric field amplitudes used in human studies entrains neuronal oscillators.

scholarly journals Cortical plasticity following stripe rearing in the marsupialMonodelphis domestica: neural response properties of V1

2017 ◽  
Vol 117 (2) ◽  
pp. 566-581 ◽  
Author(s):  
James C. Dooley ◽  
Michaela S. Donaldson ◽  
Leah A. Krubitzer
Keyword(s):  
Visual System ◽  
Cortical Neurons ◽  
Functional Organization ◽  
Sensory Experience ◽  
Monodelphis Domestica ◽  
Visual Environment ◽  
Visual Response ◽  
Response Properties ◽  
Dependent Plasticity ◽  
Marsupial Species

The functional organization of the primary visual area (V1) and the importance of sensory experience in its normal development have been well documented in eutherian mammals. However, very few studies have investigated the response properties of V1 neurons in another large class of mammals, or whether sensory experience plays a role in shaping their response properties. Thus we reared opossums ( Monodelphis domestica) in normal and vertically striped cages until they reached adulthood. They were then anesthetized using urethane, and electrophysiological techniques were used to examine neuronal responses to different orientations, spatial and temporal frequencies, and contrast levels. For normal opossums, we observed responses to the temporal and spatial characteristics of the stimulus to be similar to those described in small, nocturnal, eutherian mammals such as rats and mice; neurons in V1 responded maximally to stimuli at 0.09 cycles per degree and 2.12 cycles per second. Unlike other eutherians, but similar to other marsupials investigated, only 40% of the neurons were orientation selective. In stripe-reared animals, neurons were significantly more likely to respond to vertical stimuli at a wider range of spatial frequencies, and were more sensitive to gratings at lower contrast values compared with normal animals. These results are the first to demonstrate experience-dependent plasticity in the visual system of a marsupial species. Thus the ability of cortical neurons to alter their properties based on the dynamics of the visual environment predates the emergence of eutherian mammals and was likely present in our earliest mammalian ancestors.NEW & NOTEWORTHY These results are the first description of visual response properties of the most commonly studied marsupial model organism, the short-tailed opossum ( Monodelphis domestica). Further, these results are the first to demonstrate experience-dependent plasticity in the visual system of a marsupial species. Thus the ability of cortical neurons to alter their properties based on the dynamics of the visual environment predates the emergence of eutherian mammals and was likely present in our earliest mammalian ancestors.

Microstimulation of a Neural-Network Model for Visually Guided Saccades

1989 ◽  
Vol 1 (4) ◽  
pp. 317-326 ◽  
Author(s):  
Sabrina J. Goodman ◽  
Richard A. Andersen
Keyword(s):  
Neural Network ◽  
Eye Movements ◽  
Network Model ◽  
Neural Network Model ◽  
Posterior Parietal Cortex ◽  
Single Cells ◽  
Middle Layer ◽  
Retinal Position ◽  
Area 7A ◽  
The Brain

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.

Tonotopic and functional organization in the auditory cortex of the big brown bat, Eptesicus fuscus

1993 ◽  
Vol 70 (5) ◽  
pp. 1988-2009 ◽  
Author(s):  
S. P. Dear ◽  
J. Fritz ◽  
T. Haresign ◽  
M. Ferragamo ◽  
J. A. Simmons
Keyword(s):  
Auditory Cortex ◽  
Surface Area ◽  
Cortical Neurons ◽  
Functional Organization ◽  
Primary Auditory Cortex ◽  
Target Range ◽  
Cortical Surface ◽  
Behavioral Experiments ◽  
Cortical Surface Area ◽  
Harmonic Ratio

1. In Eptesicus the auditory cortex, as defined by electrical activity recorded from microelectrodes in response to tone bursts, FM sweeps, and combinations of FM sweeps, encompasses an average cortical surface area of 5.7 mm2. This area is large with respect to the total cortical surface area and reflects the importance of auditory processing to this species of bat. 2. The predominant pattern of organization in response to tone bursts observed in each cortex is tonotopic, with three discernible divisions revealed by our data. However, although cortical best-frequency (BF) maps from most of the individual bats are similar, no two maps are identical. The largest division contains an average of 84% of the auditory cortical surface area, with BF tonotopically mapped from high to low along the anteroposterior axis and is part of the primary auditory cortex. The medium division encompasses an average of 13% of the auditory cortical surface area, with highly variable BF organization across bats. The third region is the smallest, with an average of only 3% of auditory cortical surface area and is located at the anterolateral edge of the cortex. This region is marked by a reversal of the tonotopic axis and a restriction in the range of BFs as compared with the larger, tonotopically organized division. 3. A population of cortical neurons was found (n = 39) in which each neuron exhibited two BF threshold minima (BF1 and BF2) in response to tone bursts. These neurons thus have multipeaked frequency threshold tuning curves. In Eptesicus the majority of multipeaked frequency-tuned neurons (n = 27) have threshold minima at frequencies that correspond to a harmonic ratio of three-to-one. In contrast, the majority of multipeaked neurons in cats have threshold minima at frequencies in a ratio of three-to-two. A three-to-one harmonic ratio corresponds to the "spectral notches" produced by interference between overlapping echoes from multiple reflective surfaces in complex sonar targets. Behavioral experiments have demonstrated the ability of Eptesicus to use spectral interference notches for perceiving target shape, and this subpopulation of multipeaked frequency-tuned neurons may be involved in coding of spectral notches. 4. The auditory cortex contains delay-tuned neurons that encode target range (n = 99). Most delay-tuned neurons respond poorly to tones or individual FM sweeps and require combinations of FM sweeps. They are combination sensitive and delay tuned.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Correct Laminar Positioning in the Neocortex Influences Proper Dendritic and Synaptic Development

2018 ◽  
Vol 28 (8) ◽  
pp. 2976-2990 ◽  
Author(s):  
Fanny Sandrine Martineau ◽  
Surajit Sahu ◽  
Vanessa Plantier ◽  
Emmanuelle Buhler ◽  
Fabienne Schaller ◽  
...  
Keyword(s):  
Neuronal Migration ◽  
Cortical Neurons ◽  
Neuronal Development ◽  
Synapse Formation ◽  
Functional Organization ◽  
Functional Integration ◽  
Proper Function ◽  
Cortical Circuits ◽  
Gabaergic Synapses ◽  
Dendrite Morphogenesis

Abstract The neocortex is a 6-layered laminated structure with a precise anatomical and functional organization ensuring proper function. Laminar positioning of cortical neurons, as determined by termination of neuronal migration, is a key determinant of their ability to assemble into functional circuits. However, the exact contribution of laminar placement to dendrite morphogenesis and synapse formation remains unclear. Here we manipulated the laminar position of cortical neurons by knocking down doublecortin (Dcx), a crucial effector of migration, and show that misplaced neurons fail to properly form dendrites, spines, and functional glutamatergic and GABAergic synapses. We further show that knocking down Dcx in properly positioned neurons induces similar but milder defects, suggesting that the laminar misplacement is the primary cause of altered neuronal development. Thus, the specific laminar environment of their fated layers is crucial for the maturation of cortical neurons, and influences their functional integration into developing cortical circuits.

Chaotic Balanced State in a Model of Cortical Circuits

1998 ◽  
Vol 10 (6) ◽  
pp. 1321-1371 ◽  
Author(s):  
C. van Vreeswijk ◽  
H. Sompolinsky
Keyword(s):  
Cortical Neurons ◽  
Initial Conditions ◽  
Single Cells ◽  
Network Size ◽  
Short Time Scale ◽  
Strong Nonlinearity ◽  
Large Network ◽  
Wide Range ◽  
The Mean

The nature and origin of the temporal irregularity in the electrical activity of cortical neurons in vivo are not well understood. We consider the hypothesis that this irregularity is due to a balance of excitatory and inhibitory currents into the cortical cells. We study a network model with excitatory and inhibitory populations of simple binary units. The internal feedback is mediated by relatively large synaptic strengths, so that the magnitude of the total excitatory and inhibitory feedback is much larger than the neuronal threshold. The connectivity is random and sparse. The mean number of connections per unit is large, though small compared to the total number of cells in the network. The network also receives a large, temporally regular input from external sources. We present an analytical solution of the mean-field theory of this model, which is exact in the limit of large network size. This theory reveals a new cooperative stationary state of large networks, which we term a balanced state. In this state, a balance between the excitatory and inhibitory inputs emerges dynamically for a wide range of parameters, resulting in a net input whose temporal fluctuations are of the same order as its mean. The internal synaptic inputs act as a strong negative feedback, which linearizes the population responses to the external drive despite the strong nonlinearity of the individual cells. This feedback also greatly stabilizes the system's state and enables it to track a time-dependent input on time scales much shorter than the time constant of a single cell. The spatiotemporal statistics of the balanced state are calculated. It is shown that the autocorrelations decay on a short time scale, yielding an approximate Poissonian temporal statistics. The activity levels of single cells are broadly distributed, and their distribution exhibits a skewed shape with a long power-law tail. The chaotic nature of the balanced state is revealed by showing that the evolution of the microscopic state of the network is extremely sensitive to small deviations in its initial conditions. The balanced state generated by the sparse, strong connections is an asynchronous chaotic state. It is accompanied by weak spatial cross-correlations, the strength of which vanishes in the limit of large network size. This is in contrast to the synchronized chaotic states exhibited by more conventional network models with high connectivity of weak synapses.

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