Quantitative Analysis of Rat Dorsal Root Ganglion Neurons Cultured on Microelectrode Arrays Based on Fluorescence Microscopy Image Processing.

PubMed

Mari, João Fernando; Saito, José Hiroki; Neves, Amanda Ferreira; Lotufo, Celina Monteiro da Cruz; Destro-Filho, João-Batista; Nicoletti, Maria do Carmo

2015-12-01

Microelectrode Arrays (MEA) are devices for long term electrophysiological recording of extracellular spontaneous or evocated activities on in vitro neuron culture. This work proposes and develops a framework for quantitative and morphological analysis of neuron cultures on MEAs, by processing their corresponding images, acquired by fluorescence microscopy. The neurons are segmented from the fluorescence channel images using a combination of segmentation by thresholding, watershed transform, and object classification. The positioning of microelectrodes is obtained from the transmitted light channel images using the circular Hough transform. The proposed method was applied to images of dissociated culture of rat dorsal root ganglion (DRG) neuronal cells. The morphological and topological quantitative analysis carried out produced information regarding the state of culture, such as population count, neuron-to-neuron and neuron-to-microelectrode distances, soma morphologies, neuron sizes, neuron and microelectrode spatial distributions. Most of the analysis of microscopy images taken from neuronal cultures on MEA only consider simple qualitative analysis. Also, the proposed framework aims to standardize the image processing and to compute quantitative useful measures for integrated image-signal studies and further computational simulations. As results show, the implemented microelectrode identification method is robust and so are the implemented neuron segmentation and classification one (with a correct segmentation rate up to 84%). The quantitative information retrieved by the method is highly relevant to assist the integrated signal-image study of recorded electrophysiological signals as well as the physical aspects of the neuron culture on MEA. Although the experiments deal with DRG cell images, cortical and hippocampal cell images could also be processed with small adjustments in the image processing parameter estimation.

Spectral and Temporal Processing in Rat Posterior Auditory Cortex

PubMed Central

Pandya, Pritesh K.; Rathbun, Daniel L.; Moucha, Raluca; Engineer, Navzer D.; Kilgard, Michael P.

2009-01-01

The rat auditory cortex is divided anatomically into several areas, but little is known about the functional differences in information processing between these areas. To determine the filter properties of rat posterior auditory field (PAF) neurons, we compared neurophysiological responses to simple tones, frequency modulated (FM) sweeps, and amplitude modulated noise and tones with responses of primary auditory cortex (A1) neurons. PAF neurons have excitatory receptive fields that are on average 65% broader than A1 neurons. The broader receptive fields of PAF neurons result in responses to narrow and broadband inputs that are stronger than A1. In contrast to A1, we found little evidence for an orderly topographic gradient in PAF based on frequency. These neurons exhibit latencies that are twice as long as A1. In response to modulated tones and noise, PAF neurons adapt to repeated stimuli at significantly slower rates. Unlike A1, neurons in PAF rarely exhibit facilitation to rapidly repeated sounds. Neurons in PAF do not exhibit strong selectivity for rate or direction of narrowband one octave FM sweeps. These results indicate that PAF, like nonprimary visual fields, processes sensory information on larger spectral and longer temporal scales than primary cortex. PMID:17615251

Visual perception and imagery: a new molecular hypothesis.

PubMed

Bókkon, I

2009-05-01

Here, we put forward a redox molecular hypothesis about the natural biophysical substrate of visual perception and visual imagery. This hypothesis is based on the redox and bioluminescent processes of neuronal cells in retinotopically organized cytochrome oxidase-rich visual areas. Our hypothesis is in line with the functional roles of reactive oxygen and nitrogen species in living cells that are not part of haphazard process, but rather a very strict mechanism used in signaling pathways. We point out that there is a direct relationship between neuronal activity and the biophoton emission process in the brain. Electrical and biochemical processes in the brain represent sensory information from the external world. During encoding or retrieval of information, electrical signals of neurons can be converted into synchronized biophoton signals by bioluminescent radical and non-radical processes. Therefore, information in the brain appears not only as an electrical (chemical) signal but also as a regulated biophoton (weak optical) signal inside neurons. During visual perception, the topological distribution of photon stimuli on the retina is represented by electrical neuronal activity in retinotopically organized visual areas. These retinotopic electrical signals in visual neurons can be converted into synchronized biophoton signals by radical and non-radical processes in retinotopically organized mitochondria-rich areas. As a result, regulated bioluminescent biophotons can create intrinsic pictures (depictive representation) in retinotopically organized cytochrome oxidase-rich visual areas during visual imagery and visual perception. The long-term visual memory is interpreted as epigenetic information regulated by free radicals and redox processes. This hypothesis does not claim to solve the secret of consciousness, but proposes that the evolution of higher levels of complexity made the intrinsic picture representation of the external visual world possible by regulated redox and bioluminescent reactions in the visual system during visual perception and visual imagery.

The Chronotron: A Neuron That Learns to Fire Temporally Precise Spike Patterns

PubMed Central

Florian, Răzvan V.

2012-01-01

In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons), one that provides high memory capacity (E-learning), and one that has a higher biological plausibility (I-learning). With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm. PMID:22879876

Mapping sensory circuits by anterograde trans-synaptic transfer of recombinant rabies virus

PubMed Central

Zampieri, Niccolò; Jessell, Thomas M.; Murray, Andrew J.

2014-01-01

Summary Primary sensory neurons convey information from the external world to relay circuits within the central nervous system (CNS), but the identity and organization of the neurons that process incoming sensory information remains sketchy. Within the CNS viral tracing techniques that rely on retrograde trans-synaptic transfer provide a powerful tool for delineating circuit organization. Viral tracing of the circuits engaged by primary sensory neurons has, however, been hampered by the absence of a genetically tractable anterograde transfer system. In this study we demonstrate that rabies virus can infect sensory neurons in the somatosensory system, is subject to anterograde trans-synaptic transfer from primary sensory to spinal target neurons, and can delineate output connectivity with third-order neurons. Anterograde trans-synaptic transfer is a feature shared by other classes of primary sensory neurons, permitting the identification and potentially the manipulation of neural circuits processing sensory feedback within the mammalian CNS. PMID:24486087

From in silico astrocyte cell models to neuron-astrocyte network models: A review.

PubMed

Oschmann, Franziska; Berry, Hugues; Obermayer, Klaus; Lenk, Kerstin

2018-01-01

The idea that astrocytes may be active partners in synaptic information processing has recently emerged from abundant experimental reports. Because of their spatial proximity to neurons and their bidirectional communication with them, astrocytes are now considered as an important third element of the synapse. Astrocytes integrate and process synaptic information and by doing so generate cytosolic calcium signals that are believed to reflect neuronal transmitter release. Moreover, they regulate neuronal information transmission by releasing gliotransmitters into the synaptic cleft affecting both pre- and postsynaptic receptors. Concurrent with the first experimental reports of the astrocytic impact on neural network dynamics, computational models describing astrocytic functions have been developed. In this review, we give an overview over the published computational models of astrocytic functions, from single-cell dynamics to the tripartite synapse level and network models of astrocytes and neurons. Copyright © 2017 Elsevier Inc. All rights reserved.

Role of temporal processing stages by inferior temporal neurons in facial recognition.

PubMed

Sugase-Miyamoto, Yasuko; Matsumoto, Narihisa; Kawano, Kenji

2011-01-01

In this review, we focus on the role of temporal stages of encoded facial information in the visual system, which might enable the efficient determination of species, identity, and expression. Facial recognition is an important function of our brain and is known to be processed in the ventral visual pathway, where visual signals are processed through areas V1, V2, V4, and the inferior temporal (IT) cortex. In the IT cortex, neurons show selective responses to complex visual images such as faces, and at each stage along the pathway the stimulus selectivity of the neural responses becomes sharper, particularly in the later portion of the responses. In the IT cortex of the monkey, facial information is represented by different temporal stages of neural responses, as shown in our previous study: the initial transient response of face-responsive neurons represents information about global categories, i.e., human vs. monkey vs. simple shapes, whilst the later portion of these responses represents information about detailed facial categories, i.e., expression and/or identity. This suggests that the temporal stages of the neuronal firing pattern play an important role in the coding of visual stimuli, including faces. This type of coding may be a plausible mechanism underlying the temporal dynamics of recognition, including the process of detection/categorization followed by the identification of objects. Recent single-unit studies in monkeys have also provided evidence consistent with the important role of the temporal stages of encoded facial information. For example, view-invariant facial identity information is represented in the response at a later period within a region of face-selective neurons. Consistent with these findings, temporally modulated neural activity has also been observed in human studies. These results suggest a close correlation between the temporal processing stages of facial information by IT neurons and the temporal dynamics of face recognition.

Role of Temporal Processing Stages by Inferior Temporal Neurons in Facial Recognition

PubMed Central

Sugase-Miyamoto, Yasuko; Matsumoto, Narihisa; Kawano, Kenji

2011-01-01

In this review, we focus on the role of temporal stages of encoded facial information in the visual system, which might enable the efficient determination of species, identity, and expression. Facial recognition is an important function of our brain and is known to be processed in the ventral visual pathway, where visual signals are processed through areas V1, V2, V4, and the inferior temporal (IT) cortex. In the IT cortex, neurons show selective responses to complex visual images such as faces, and at each stage along the pathway the stimulus selectivity of the neural responses becomes sharper, particularly in the later portion of the responses. In the IT cortex of the monkey, facial information is represented by different temporal stages of neural responses, as shown in our previous study: the initial transient response of face-responsive neurons represents information about global categories, i.e., human vs. monkey vs. simple shapes, whilst the later portion of these responses represents information about detailed facial categories, i.e., expression and/or identity. This suggests that the temporal stages of the neuronal firing pattern play an important role in the coding of visual stimuli, including faces. This type of coding may be a plausible mechanism underlying the temporal dynamics of recognition, including the process of detection/categorization followed by the identification of objects. Recent single-unit studies in monkeys have also provided evidence consistent with the important role of the temporal stages of encoded facial information. For example, view-invariant facial identity information is represented in the response at a later period within a region of face-selective neurons. Consistent with these findings, temporally modulated neural activity has also been observed in human studies. These results suggest a close correlation between the temporal processing stages of facial information by IT neurons and the temporal dynamics of face recognition. PMID:21734904

Modeling of inter-neuronal coupling medium and its impact on neuronal synchronization

PubMed Central

Iqbal, Muhammad; Hong, Keum-Shik

2017-01-01

In this paper, modeling of the coupling medium between two neurons, the effects of the model parameters on the synchronization of those neurons, and compensation of coupling strength deficiency in synchronization are studied. Our study exploits the inter-neuronal coupling medium and investigates its intrinsic properties in order to get insight into neuronal-information transmittance and, there from, brain-information processing. A novel electrical model of the coupling medium that represents a well-known RLC circuit attributable to the coupling medium’s intrinsic resistive, inductive, and capacitive properties is derived. Surprisingly, the integration of such properties reveals the existence of a natural three-term control strategy, referred to in the literature as the proportional integral derivative (PID) controller, which can be responsible for synchronization between two neurons. Consequently, brain-information processing can rely on a large number of PID controllers based on the coupling medium properties responsible for the coherent behavior of neurons in a neural network. Herein, the effects of the coupling model (or natural PID controller) parameters are studied and, further, a supervisory mechanism is proposed that follows a learning and adaptation policy based on the particle swarm optimization algorithm for compensation of the coupling strength deficiency. PMID:28486505

Thalamocortical Connections Drive Intracortical Activation of Functional Columns in the Mislaminated Reeler Somatosensory Cortex

PubMed Central

Wagener, Robin J.; Witte, Mirko; Guy, Julien; Mingo-Moreno, Nieves; Kügler, Sebastian; Staiger, Jochen F.

2016-01-01

Neuronal wiring is key to proper neural information processing. Tactile information from the rodent's whiskers reaches the cortex via distinct anatomical pathways. The lemniscal pathway relays whisking and touch information from the ventral posteromedial thalamic nucleus to layer IV of the primary somatosensory “barrel” cortex. The disorganized neocortex of the reeler mouse is a model system that should severely compromise the ingrowth of thalamocortical axons (TCAs) into the cortex. Moreover, it could disrupt intracortical wiring. We found that neuronal intermingling within the reeler barrel cortex substantially exceeded previous descriptions, leading to the loss of layers. However, viral tracing revealed that TCAs still specifically targeted transgenically labeled spiny layer IV neurons. Slice electrophysiology and optogenetics proved that these connections represent functional synapses. In addition, we assessed intracortical activation via immediate-early-gene expression resulting from a behavioral exploration task. The cellular composition of activated neuronal ensembles suggests extensive similarities in intracolumnar information processing in the wild-type and reeler brains. We conclude that extensive ectopic positioning of neuronal partners can be compensated for by cell-autonomous mechanisms that allow for the establishment of proper connectivity. Thus, genetic neuronal fate seems to be of greater importance for correct cortical wiring than radial neuronal position. PMID:26564256

Otolith-Canal Convergence In Vestibular Nuclei Neurons

NASA Technical Reports Server (NTRS)

Dickman, J. David; Si, Xiao-Hong

2002-01-01

The current final report covers the period from June 1, 1999 to May 31, 2002. The primary objective of the investigation was to determine how information regarding head movements and head position relative to gravity is received and processed by central vestibular nuclei neurons in the brainstem. Specialized receptors in the vestibular labyrinths of the inner ear function to detect angular and linear accelerations of the head, with receptors located in the semicircular canals transducing rotational head movements and receptors located in the otolith organs transducing changes in head position relative to gravity or linear accelerations of the head. The information from these different receptors is then transmitted to central vestibular nuclei neurons which process the input signals, then project the appropriate output information to the eye, head, and body musculature motor neurons to control compensatory reflexes. Although a number of studies have reported on the responsiveness of vestibular nuclei neurons, it has not yet been possible to determine precisely how these cells combine the information from the different angular and linear acceleration receptors into a correct neural output signal. In the present project, rotational and linear motion stimuli were separately delivered while recording responses from vestibular nuclei neurons that were characterized according to direct input from the labyrinth and eye movement sensitivity. Responses from neurons receiving convergent input from the semicircular canals and otolith organs were quantified and compared to non-convergent neurons.

Impaired neurogenesis of the dentate gyrus is associated with pattern separation deficits: A computational study.

PubMed

Faghihi, Faramarz; Moustafa, Ahmed A

2016-09-01

The separation of input patterns received from the entorhinal cortex (EC) by the dentate gyrus (DG) is a well-known critical step of information processing in the hippocampus. Although the role of interneurons in separation pattern efficiency of the DG has been theoretically known, the balance of neurogenesis of excitatory neurons and interneurons as well as its potential role in information processing in the DG is not fully understood. In this work, we study separation efficiency of the DG for different rates of neurogenesis of interneurons and excitatory neurons using a novel computational model in which we assume an increase in the synaptic efficacy between excitatory neurons and interneurons and then its decay over time. Information processing in the EC and DG was simulated as information flow in a two layer feed-forward neural network. The neurogenesis rate was modeled as the percentage of new born neurons added to the neuronal population in each time bin. The results show an important role of an optimal neurogenesis rate of interneurons and excitatory neurons in the DG in efficient separation of inputs from the EC in pattern separation tasks. The model predicts that any deviation of the optimal values of neurogenesis rates leads to different decreased levels of the separation deficits of the DG which influences its function to encode memory.

Study on algorithm of process neural network for soft sensing in sewage disposal system

NASA Astrophysics Data System (ADS)

Liu, Zaiwen; Xue, Hong; Wang, Xiaoyi; Yang, Bin; Lu, Siying

2006-11-01

A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Process neural network with the structure of three layers in which hidden layer is process neuron and input and output are common neurons for soft sensing is discussed. The intelligent soft sensing based on PNN may be used to fulfill measurement of the effluent BOD (Biochemical Oxygen Demand) from sewage disposal system, and a good training result of soft sensing was obtained by the method.

Distinct populations of neurons respond to emotional valence and arousal in the human subthalamic nucleus.

PubMed

Sieger, Tomáš; Serranová, Tereza; Růžička, Filip; Vostatek, Pavel; Wild, Jiří; Štastná, Daniela; Bonnet, Cecilia; Novák, Daniel; Růžička, Evžen; Urgošík, Dušan; Jech, Robert

2015-03-10

Both animal studies and studies using deep brain stimulation in humans have demonstrated the involvement of the subthalamic nucleus (STN) in motivational and emotional processes; however, participation of this nucleus in processing human emotion has not been investigated directly at the single-neuron level. We analyzed the relationship between the neuronal firing from intraoperative microrecordings from the STN during affective picture presentation in patients with Parkinson's disease (PD) and the affective ratings of emotional valence and arousal performed subsequently. We observed that 17% of neurons responded to emotional valence and arousal of visual stimuli according to individual ratings. The activity of some neurons was related to emotional valence, whereas different neurons responded to arousal. In addition, 14% of neurons responded to visual stimuli. Our results suggest the existence of neurons involved in processing or transmission of visual and emotional information in the human STN, and provide evidence of separate processing of the affective dimensions of valence and arousal at the level of single neurons as well.

Spike count, spike timing and temporal information in the cortex of awake, freely moving rats

PubMed Central

Scaglione, Alessandro; Foffani, Guglielmo; Moxon, Karen A.

2014-01-01

Objective Sensory processing of peripheral information is not stationary but is, in general, a dynamic process related to the behavioral state of the animal. Yet the link between the state of the behavior and the encoding properties of neurons is unclear. This report investigates the impact of the behavioral state on the encoding mechanisms used by cortical neurons for both detection and discrimination of somatosensory stimuli in awake, freely moving, rats. Approach Neuronal activity was recorded from the primary somatosensory cortex of five rats under two different behavioral states (quiet vs. whisking) while electrical stimulation of increasing stimulus strength was delivered to the mystacial pad. Information theoretical measures were then used to measure the contribution of different encoding mechanisms to the information carried by neurons in response to the whisker stimulation. Main Results We found that the behavioral state of the animal modulated the total amount of information conveyed by neurons and that the timing of individual spikes increased the information compared to the total count of spikes alone. However, the temporal information, i.e. information exclusively related to when the spikes occur, was not modulated by behavioral state. Significance We conclude that information about somatosensory stimuli is modulated by the behavior of the animal and this modulation is mainly expressed in the spike count while the temporal information is more robust to changes in behavioral state. PMID:25024291

Neurons in Anterior Cingulate Cortex Multiplex Information about Reward and Action

PubMed Central

Hayden, Benjamin Y.; Platt, Michael L.

2010-01-01

The dorsal anterior cingulate cortex (dACC) is thought to play a critical role in forming associations between rewards and actions. Currently available physiological data, however, remain inconclusive regarding the question of whether dACC neurons carry information linking particular actions to reward or, instead, encode abstract reward information independent of specific actions. Here we show that firing rates of a majority of dACC neurons in a population studied in an eight-option variably rewarded choice task were sensitive to both saccade direction and reward value. Furthermore, the influences of reward and saccade direction on neuronal activity were roughly equal in magnitude over the range of rewards tested and were statistically independent. Our results indicate that dACC neurons multiplex information about both reward and action, endorsing the idea that this area links motivational outcomes to behavior and undermining the notion that its neurons solely contribute to reward processing in the abstract. PMID:20203193

Temporal Precision of Neuronal Information in a Rapid Perceptual Judgment

PubMed Central

Ghose, Geoffrey M.; Harrison, Ian T.

2009-01-01

In many situations, such as pedestrians crossing a busy street or prey evading predators, rapid decisions based on limited perceptual information are critical for survival. The brevity of these perceptual judgments constrains how neuronal signals are integrated or pooled over time because the underlying sequence of processes, from sensation to perceptual evaluation to motor planning and execution, all occur within several hundred milliseconds. Because most previous physiological studies of these processes have relied on tasks requiring considerably longer temporal integration, the neuronal basis of such rapid decisions remains largely unexplored. In this study, we examine the temporal precision of neuronal activity associated with a rapid perceptual judgment. We find that the activity of individual neurons over tens of milliseconds can reliably convey information about sensory events and was well correlated with the animals' judgments. There was a strong correlation between sensory reliability and the correlation with behavioral choice, suggesting that rapid decisions were preferentially based on the most reliable sensory signals. We also find that a simple model in which the responses of a small number of individual neurons (<5) are summed can completely explain behavioral performance. These results suggest that neuronal circuits are sufficiently precise to allow for cognitive decisions to be based on small numbers of action potentials from highly reliable neurons. PMID:19109454

Temporal precision of neuronal information in a rapid perceptual judgment.

PubMed

Ghose, Geoffrey M; Harrison, Ian T

2009-03-01

In many situations, such as pedestrians crossing a busy street or prey evading predators, rapid decisions based on limited perceptual information are critical for survival. The brevity of these perceptual judgments constrains how neuronal signals are integrated or pooled over time because the underlying sequence of processes, from sensation to perceptual evaluation to motor planning and execution, all occur within several hundred milliseconds. Because most previous physiological studies of these processes have relied on tasks requiring considerably longer temporal integration, the neuronal basis of such rapid decisions remains largely unexplored. In this study, we examine the temporal precision of neuronal activity associated with a rapid perceptual judgment. We find that the activity of individual neurons over tens of milliseconds can reliably convey information about sensory events and was well correlated with the animals' judgments. There was a strong correlation between sensory reliability and the correlation with behavioral choice, suggesting that rapid decisions were preferentially based on the most reliable sensory signals. We also find that a simple model in which the responses of a small number of individual neurons (<5) are summed can completely explain behavioral performance. These results suggest that neuronal circuits are sufficiently precise to allow for cognitive decisions to be based on small numbers of action potentials from highly reliable neurons.

Neural mechanisms of vocal imitation: The role of sleep replay in shaping mirror neurons.

PubMed

Giret, Nicolas; Edeline, Jean-Marc; Del Negro, Catherine

2017-06-01

Learning by imitation involves not only perceiving another individual's action to copy it, but also the formation of a memory trace in order to gradually establish a correspondence between the sensory and motor codes, which represent this action through sensorimotor experience. Memory and sensorimotor processes are closely intertwined. Mirror neurons, which fire both when the same action is performed or perceived, have received considerable attention in the context of imitation. An influential view of memory processes considers that the consolidation of newly acquired information or skills involves an active offline reprocessing of memories during sleep within the neuronal networks that were initially used for encoding. Here, we review the recent advances in the field of mirror neurons and offline processes in the songbird. We further propose a theoretical framework that could establish the neurobiological foundations of sensorimotor learning by imitation. We propose that the reactivation of neuronal assemblies during offline periods contributes to the integration of sensory feedback information and the establishment of sensorimotor mirroring activity at the neuronal level. Copyright © 2017 Elsevier Ltd. All rights reserved.

Differences in reward processing between putative cell types in primate prefrontal cortex

PubMed Central

Fan, Hongwei; Wang, Rubin; Sakagami, Masamichi

2017-01-01

Single-unit studies in monkeys have demonstrated that neurons in the prefrontal cortex predict the reward type, reward amount or reward availability associated with a stimulus. To examine contributions of pyramidal cells and interneurons in reward processing, single-unit activity was extracellularly recorded in prefrontal cortices of four monkeys performing a reward prediction task. Based on their shapes of spike waveforms, prefrontal neurons were classified into broad-spike and narrow-spike units that represented putative pyramidal cells and interneurons, respectively. We mainly observed that narrow-spike neurons showed higher firing rates but less bursty discharges than did broad-spike neurons. Both narrow-spike and broad-spike cells selectively responded to the stimulus, reward and their interaction, and the proportions of each type of selective neurons were similar between the two cell classes. Moreover, the two types of cells displayed equal reliability of reward or stimulus discrimination. Furthermore, we found that broad-spike and narrow-spike cells showed distinct mechanisms for encoding reward or stimulus information. Broad-spike neurons raised their firing rate relative to the baseline rate to represent the preferred reward or stimulus information, whereas narrow-spike neurons inhibited their firing rate lower than the baseline rate to encode the non-preferred reward or stimulus information. Our results suggest that narrow-spike and broad-spike cells were equally involved in reward and stimulus processing in the prefrontal cortex. They utilized a binary strategy to complementarily represent reward or stimulus information, which was consistent with the task structure in which the monkeys were required to remember two reward conditions and two visual stimuli. PMID:29261734

Differences in reward processing between putative cell types in primate prefrontal cortex.

PubMed

Fan, Hongwei; Pan, Xiaochuan; Wang, Rubin; Sakagami, Masamichi

2017-01-01

Single-unit studies in monkeys have demonstrated that neurons in the prefrontal cortex predict the reward type, reward amount or reward availability associated with a stimulus. To examine contributions of pyramidal cells and interneurons in reward processing, single-unit activity was extracellularly recorded in prefrontal cortices of four monkeys performing a reward prediction task. Based on their shapes of spike waveforms, prefrontal neurons were classified into broad-spike and narrow-spike units that represented putative pyramidal cells and interneurons, respectively. We mainly observed that narrow-spike neurons showed higher firing rates but less bursty discharges than did broad-spike neurons. Both narrow-spike and broad-spike cells selectively responded to the stimulus, reward and their interaction, and the proportions of each type of selective neurons were similar between the two cell classes. Moreover, the two types of cells displayed equal reliability of reward or stimulus discrimination. Furthermore, we found that broad-spike and narrow-spike cells showed distinct mechanisms for encoding reward or stimulus information. Broad-spike neurons raised their firing rate relative to the baseline rate to represent the preferred reward or stimulus information, whereas narrow-spike neurons inhibited their firing rate lower than the baseline rate to encode the non-preferred reward or stimulus information. Our results suggest that narrow-spike and broad-spike cells were equally involved in reward and stimulus processing in the prefrontal cortex. They utilized a binary strategy to complementarily represent reward or stimulus information, which was consistent with the task structure in which the monkeys were required to remember two reward conditions and two visual stimuli.

The neuronal encoding of information in the brain.

PubMed

Rolls, Edmund T; Treves, Alessandro

2011-11-01

We describe the results of quantitative information theoretic analyses of neural encoding, particularly in the primate visual, olfactory, taste, hippocampal, and orbitofrontal cortex. Most of the information turns out to be encoded by the firing rates of the neurons, that is by the number of spikes in a short time window. This has been shown to be a robust code, for the firing rate representations of different neurons are close to independent for small populations of neurons. Moreover, the information can be read fast from such encoding, in as little as 20 ms. In quantitative information theoretic studies, only a little additional information is available in temporal encoding involving stimulus-dependent synchronization of different neurons, or the timing of spikes within the spike train of a single neuron. Feature binding appears to be solved by feature combination neurons rather than by temporal synchrony. The code is sparse distributed, with the spike firing rate distributions close to exponential or gamma. A feature of the code is that it can be read by neurons that take a synaptically weighted sum of their inputs. This dot product decoding is biologically plausible. Understanding the neural code is fundamental to understanding not only how the cortex represents, but also processes, information. Copyright © 2011 Elsevier Ltd. All rights reserved.

Redundant information encoding in primary motor cortex during natural and prosthetic motor control.

PubMed

So, Kelvin; Ganguly, Karunesh; Jimenez, Jessica; Gastpar, Michael C; Carmena, Jose M

2012-06-01

Redundant encoding of information facilitates reliable distributed information processing. To explore this hypothesis in the motor system, we applied concepts from information theory to quantify the redundancy of movement-related information encoded in the macaque primary motor cortex (M1) during natural and neuroprosthetic control. Two macaque monkeys were trained to perform a delay center-out reaching task controlling a computer cursor under natural arm movement (manual control, 'MC'), and using a brain-machine interface (BMI) via volitional control of neural ensemble activity (brain control, 'BC'). During MC, we found neurons in contralateral M1 to contain higher and more redundant information about target direction than ipsilateral M1 neurons, consistent with the laterality of movement control. During BC, we found that the M1 neurons directly incorporated into the BMI ('direct' neurons) contained the highest and most redundant target information compared to neurons that were not incorporated into the BMI ('indirect' neurons). This effect was even more significant when comparing to M1 neurons of the opposite hemisphere. Interestingly, when we retrained the BMI to use ipsilateral M1 activity, we found that these neurons were more redundant and contained higher information than contralateral M1 neurons, even though ensembles from this hemisphere were previously less redundant during natural arm movement. These results indicate that ensembles most associated to movement contain highest redundancy and information encoding, which suggests a role for redundancy in proficient natural and prosthetic motor control.

Mutual information and redundancy in spontaneous communication between cortical neurons.

PubMed

Szczepanski, J; Arnold, M; Wajnryb, E; Amigó, J M; Sanchez-Vives, M V

2011-03-01

An important question in neural information processing is how neurons cooperate to transmit information. To study this question, we resort to the concept of redundancy in the information transmitted by a group of neurons and, at the same time, we introduce a novel concept for measuring cooperation between pairs of neurons called relative mutual information (RMI). Specifically, we studied these two parameters for spike trains generated by neighboring neurons from the primary visual cortex in the awake, freely moving rat. The spike trains studied here were spontaneously generated in the cortical network, in the absence of visual stimulation. Under these conditions, our analysis revealed that while the value of RMI oscillated slightly around an average value, the redundancy exhibited a behavior characterized by a higher variability. We conjecture that this combination of approximately constant RMI and greater variable redundancy makes information transmission more resistant to noise disturbances. Furthermore, the redundancy values suggest that neurons can cooperate in a flexible way during information transmission. This mostly occurs via a leading neuron with higher transmission rate or, less frequently, through the information rate of the whole group being higher than the sum of the individual information rates-in other words in a synergetic manner. The proposed method applies not only to the stationary, but also to locally stationary neural signals.

Signal processing in local neuronal circuits based on activity-dependent noise and competition

NASA Astrophysics Data System (ADS)

Volman, Vladislav; Levine, Herbert

2009-09-01

We study the characteristics of weak signal detection by a recurrent neuronal network with plastic synaptic coupling. It is shown that in the presence of an asynchronous component in synaptic transmission, the network acquires selectivity with respect to the frequency of weak periodic stimuli. For nonperiodic frequency-modulated stimuli, the response is quantified by the mutual information between input (signal) and output (network's activity) and is optimized by synaptic depression. Introducing correlations in signal structure resulted in the decrease in input-output mutual information. Our results suggest that in neural systems with plastic connectivity, information is not merely carried passively by the signal; rather, the information content of the signal itself might determine the mode of its processing by a local neuronal circuit.

Integrative properties and transfer function of cortical neurons initiating absence seizures in a rat genetic model

PubMed Central

Williams, Mark S.; Altwegg‐Boussac, Tristan; Chavez, Mario; Lecas, Sarah; Mahon, Séverine

2016-01-01

Key points Absence seizures are accompanied by spike‐and‐wave discharges in cortical electroencephalograms. These complex paroxysmal activities, affecting the thalamocortical networks, profoundly alter cognitive performances and preclude conscious perception.Here, using a well‐recognized genetic model of absence epilepsy, we investigated in vivo how information processing was impaired in the ictogenic neurons, i.e. the population of cortical neurons responsible for seizure initiation.In between seizures, ictogenic neurons were more prone to generate bursting activity and their firing response to weak depolarizing events was considerably facilitated compared to control neurons.In the course of seizures, information processing became unstable in ictogenic cells, alternating between an increased and a decreased responsiveness to excitatory inputs, depending on the spike and wave patterns.The state‐dependent modulation in the excitability of ictogenic neurons affects their inter‐seizure transfer function and their time‐to‐time responsiveness to incoming inputs during absences. Abstract Epileptic seizures result from aberrant cellular and/or synaptic properties that can alter the capacity of neurons to integrate and relay information. During absence seizures, spike‐and‐wave discharges (SWDs) interfere with incoming sensory inputs and preclude conscious experience. The Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well‐established animal model of absence epilepsy, allows exploration of the cellular basis of this impaired information processing. Here, by combining in vivo electrocorticographic and intracellular recordings from GAERS and control animals, we investigated how the pro‐ictogenic properties of seizure‐initiating cortical neurons modify their integrative properties and input–output operation during inter‐ictal periods and during the spike (S‐) and wave (W‐) cortical patterns alternating during seizures. In addition to a sustained depolarization and an excessive firing rate in between seizures, ictogenic neurons exhibited a pronounced hyperpolarization‐activated depolarization compared to homotypic control neurons. Firing frequency versus injected current relations indicated an increased sensitivity of GAERS cells to weak excitatory inputs, without modifications in the trial‐to‐trial variability of current‐induced firing. During SWDs, the W‐component resulted in paradoxical effects in ictogenic neurons, associating an increased membrane input resistance with a reduction in the current‐evoked firing responses. Conversely, the collapse of cell membrane resistance during the S‐component was accompanied by an elevated current‐evoked firing relative to W‐sequences, which remained, however, lower compared to inter‐ictal periods. These findings show a dynamic modulation of ictogenic neurons’ intrinsic properties that may alter inter‐seizure cortical function and participate in compromising information processing in cortical networks during absences. PMID:27311433

Energy-efficient neural information processing in individual neurons and neuronal networks.

PubMed

Yu, Lianchun; Yu, Yuguo

2017-11-01

Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A role for the anterior insular cortex in the global neuronal workspace model of consciousness.

PubMed

Michel, Matthias

2017-03-01

According to the global neuronal workspace model of consciousness, consciousness results from the global broadcast of information throughout the brain. The global neuronal workspace is mainly constituted by a fronto-parietal network. The anterior insular cortex is part of this global neuronal workspace, but the function of this region has not yet been defined within the global neuronal workspace model of consciousness. In this review, I hypothesize that the anterior insular cortex implements a cross-modal priority map, the function of which is to determine priorities for the processing of information and subsequent entrance in the global neuronal workspace. Copyright © 2017 Elsevier Inc. All rights reserved.

A Mechanism for Graded, Dynamically Routable Current Propagation in Pulse-Gated Synfire Chains and Implications for Information Coding

PubMed Central

Sornborger, Andrew T.; Wang, Zhuo; Tao, Louis

2015-01-01

Neural oscillations can enhance feature recognition [1], modulate interactions between neurons [2], and improve learning and memory [3]. Numerical studies have shown that coherent spiking can give rise to windows in time during which information transfer can be enhanced in neuronal networks [4–6]. Unanswered questions are: 1) What is the transfer mechanism? And 2) how well can a transfer be executed? Here, we present a pulse-based mechanism by which a graded current amplitude may be exactly propagated from one neuronal population to another. The mechanism relies on the downstream gating of mean synaptic current amplitude from one population of neurons to another via a pulse. Because transfer is pulse-based, information may be dynamically routed through a neural circuit with fixed connectivity. We demonstrate the transfer mechanism in a realistic network of spiking neurons and show that it is robust to noise in the form of pulse timing inaccuracies, random synaptic strengths and finite size effects. We also show that the mechanism is structurally robust in that it may be implemented using biologically realistic pulses. The transfer mechanism may be used as a building block for fast, complex information processing in neural circuits. We show that the mechanism naturally leads to a framework wherein neural information coding and processing can be considered as a product of linear maps under the active control of a pulse generator. Distinct control and processing components combine to form the basis for the binding, propagation, and processing of dynamically routed information within neural pathways. Using our framework, we construct example neural circuits to 1) maintain a short-term memory, 2) compute time-windowed Fourier transforms, and 3) perform spatial rotations. We postulate that such circuits, with automatic and stereotyped control and processing of information, are the neural correlates of Crick and Koch’s zombie modes. PMID:26227067

Contribution of amygdalar and lateral hypothalamic neurons to visual information processing of food and nonfood in monkey.

PubMed

Ono, T; Tamura, R; Nishijo, H; Nakamura, K; Tabuchi, E

1989-02-01

Visual information processing was investigated in the inferotemporal cortical (ITCx)-amygdalar (AM)-lateral hypothalamic (LHA) axis which contributes to food-nonfood discrimination. Neuronal activity was recorded from monkey AM and LHA during discrimination of sensory stimuli including sight of food or nonfood. The task had four phases: control, visual, bar press, and ingestion. Of 710 AM neurons tested, 220 (31.0%) responded during visual phase: 48 to only visual stimulation, 13 (1.9%) to visual plus oral sensory stimulation, 142 (20.0%) to multimodal stimulation and 17 (2.4%) to one affectively significant item. Of 669 LHA neurons tested, 106 (15.8%) responded in the visual phase. Of 80 visual-related neurons tested systematically, 33 (41.2%) responded selectively to the sight of any object predicting the availability of reward, and 47 (58.8%) responded nondifferentially to both food and nonfood. Many of AM neuron responses were graded according to the degree of affective significance of sensory stimuli (sensory-affective association), but responses of LHA food responsive neurons did not depend on the kind of reward indicated by the sensory stimuli (stimulus-reinforcement association). Some AM and LHA food responses were modulated by extinction or reversal. Dynamic information processing in ITCx-AM-LHA axis was investigated by reversible deficits of bilateral ITCx or AM by cooling. ITCx cooling suppressed discrimination by vision responding AM neurons (8/17). AM cooling suppressed LHA responses to food (9/22). We suggest deep AM-LHA involvement in food-nonfood discrimination based on AM sensory-affective association and LHA stimulus-reinforcement association.

Neurons responsive to face-view in the primate ventrolateral prefrontal cortex.

PubMed

Romanski, L M; Diehl, M M

2011-08-25

Studies have indicated that temporal and prefrontal brain regions process face and vocal information. Face-selective and vocalization-responsive neurons have been demonstrated in the ventrolateral prefrontal cortex (VLPFC) and some prefrontal cells preferentially respond to combinations of face and corresponding vocalizations. These studies suggest VLPFC in nonhuman primates may play a role in communication that is similar to the role of inferior frontal regions in human language processing. If VLPFC is involved in communication, information about a speaker's face including identity, face-view, gaze, and emotional expression might be encoded by prefrontal neurons. In the following study, we examined the effect of face-view in ventrolateral prefrontal neurons by testing cells with auditory, visual, and a set of human and monkey faces rotated through 0°, 30°, 60°, 90°, and -30°. Prefrontal neurons responded selectively to either the identity of the face presented (human or monkey) or to the specific view of the face/head, or to both identity and face-view. Neurons which were affected by the identity of the face most often showed an increase in firing in the second part of the stimulus period. Neurons that were selective for face-view typically preferred forward face-view stimuli (0° and 30° rotation). The neurons which were selective for forward face-view were also auditory responsive compared to other neurons which responded to other views or were unselective which were not auditory responsive. Our analysis showed that the human forward face (0°) was decoded better and also contained the most information relative to other face-views. Our findings confirm a role for VLPFC in the processing and integration of face and vocalization information and add to the growing body of evidence that the primate ventrolateral prefrontal cortex plays a prominent role in social communication and is an important model in understanding the cellular mechanisms of communication. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

Neurons responsive to face-view in the Primate Ventrolateral Prefrontal Cortex

PubMed Central

Romanski, Lizabeth M.; Diehl, Maria M.

2011-01-01

Studies have indicated that temporal and prefrontal brain regions process face and vocal information. Face-selective and vocalization-responsive neurons have been demonstrated in the ventrolateral prefrontal cortex (VLPFC) and some prefrontal cells preferentially respond to combinations of face and corresponding vocalizations. These studies suggest VLPFC in non-human primates may play a role in communication that is similar to the role of inferior frontal regions in human language processing. If VLPFC is involved in communication, information about a speaker's face including identity, face-view, gaze and emotional expression might be encoded by prefrontal neurons. In the following study, we examined the effect of face-view in ventrolateral prefrontal neurons by testing cells with auditory, visual, and a set of human and monkey faces rotated through 0°, 30°, 60°, 90°, and −30°. Prefrontal neurons responded selectively to either the identity of the face presented (human or monkey) or to the specific view of the face/head, or to both identity and face-view. Neurons which were affected by the identity of the face most often showed an increase in firing in the second part of the stimulus period. Neurons that were selective for face-view typically preferred forward face-view stimuli (0° and 30° rotation). The neurons which were selective for forward face-view were also auditory responsive compared to other neurons which responded to other views or were unselective which were not auditory responsive. Our analysis showed that the human forward face (0°) was decoded better and also contained the most information relative to other face-views. Our findings confirm a role for VLPFC in the processing and integration of face and vocalization information and add to the growing body of evidence that the primate ventrolateral prefrontal cortex plays a prominent role in social communication and is an important model in understanding the cellular mechanisms of communication. PMID:21605632

Computational implications of activity-dependent neuronal processes

NASA Astrophysics Data System (ADS)

Goldman, Mark Steven

Synapses, the connections between neurons, often fail to transmit a large percentage of the action potentials that they receive. I describe several models of synaptic transmission at a single stochastic synapse with an activity-dependent probability of transmission and demonstrate how synaptic transmission failures may increase the efficiency with which a synapse transmits information. Spike trains in the visual cortex of freely viewing monkeys have positive auto correlations that are indicative of a redundant representation of the information they contain. I show how a synapse with activity-dependent transmission failures modeled after those occurring in visual cortical synapses can remove this redundancy by transmitting a decorrelated subset of the spike trains it receives. I suggest that redundancy reduction at individual synapses saves synaptic resources while increasing the sensitivity of the postsynaptic neuron to information arriving along many inputs. For a neuron receiving input from many decorrelating synapses, my analysis leads to a prediction of the number of visual inputs to a neuron and the cross-correlations between these inputs and suggests that the time scale of synaptic dynamics observed in sensory areas corresponds to a fundamental time scale for processing sensory information. Systems with activity-dependent changes in their parameters, or plasticity, often display a wide variability in their individual components that belies the stability of their function, Motivated by experiments demonstrating that identified neurons with stereotyped function can have a large variability in the densities of their ion channels, or ionic conductances, I build a conductance-based model of a single neuron. The neuron's firing activity is relatively insensitive to changes in certain combinations of conductances, but markedly sensitive to changes in other combinations. Using a combined modeling and experimental approach, I show that neuromodulators and regulatory processes target sensitive combinations of conductances. I suggest that the variability observed in conductance measurements occurs along insensitive combinations of conductances and could result from homeostatic processes that allow the neuron's conductances to drift without triggering activity- dependent feedback mechanisms. These results together suggest that plastic systems may have a high degree of flexibility and variability in their components without a loss of robustness in their response properties.

Distinct populations of neurons respond to emotional valence and arousal in the human subthalamic nucleus

PubMed Central

Sieger, Tomáš; Serranová, Tereza; Růžička, Filip; Vostatek, Pavel; Wild, Jiří; Šťastná, Daniela; Bonnet, Cecilia; Novák, Daniel; Růžička, Evžen; Urgošík, Dušan; Jech, Robert

2015-01-01

Both animal studies and studies using deep brain stimulation in humans have demonstrated the involvement of the subthalamic nucleus (STN) in motivational and emotional processes; however, participation of this nucleus in processing human emotion has not been investigated directly at the single-neuron level. We analyzed the relationship between the neuronal firing from intraoperative microrecordings from the STN during affective picture presentation in patients with Parkinson’s disease (PD) and the affective ratings of emotional valence and arousal performed subsequently. We observed that 17% of neurons responded to emotional valence and arousal of visual stimuli according to individual ratings. The activity of some neurons was related to emotional valence, whereas different neurons responded to arousal. In addition, 14% of neurons responded to visual stimuli. Our results suggest the existence of neurons involved in processing or transmission of visual and emotional information in the human STN, and provide evidence of separate processing of the affective dimensions of valence and arousal at the level of single neurons as well. PMID:25713375

Neuronal avalanches of a self-organized neural network with active-neuron-dominant structure.

PubMed

Li, Xiumin; Small, Michael

2012-06-01

Neuronal avalanche is a spontaneous neuronal activity which obeys a power-law distribution of population event sizes with an exponent of -3/2. It has been observed in the superficial layers of cortex both in vivo and in vitro. In this paper, we analyze the information transmission of a novel self-organized neural network with active-neuron-dominant structure. Neuronal avalanches can be observed in this network with appropriate input intensity. We find that the process of network learning via spike-timing dependent plasticity dramatically increases the complexity of network structure, which is finally self-organized to be active-neuron-dominant connectivity. Both the entropy of activity patterns and the complexity of their resulting post-synaptic inputs are maximized when the network dynamics are propagated as neuronal avalanches. This emergent topology is beneficial for information transmission with high efficiency and also could be responsible for the large information capacity of this network compared with alternative archetypal networks with different neural connectivity.

Large-Scale Fluorescence Calcium-Imaging Methods for Studies of Long-Term Memory in Behaving Mammals

PubMed Central

Jercog, Pablo; Rogerson, Thomas; Schnitzer, Mark J.

2016-01-01

During long-term memory formation, cellular and molecular processes reshape how individual neurons respond to specific patterns of synaptic input. It remains poorly understood how such changes impact information processing across networks of mammalian neurons. To observe how networks encode, store, and retrieve information, neuroscientists must track the dynamics of large ensembles of individual cells in behaving animals, over timescales commensurate with long-term memory. Fluorescence Ca2+-imaging techniques can monitor hundreds of neurons in behaving mice, opening exciting avenues for studies of learning and memory at the network level. Genetically encoded Ca2+ indicators allow neurons to be targeted by genetic type or connectivity. Chronic animal preparations permit repeated imaging of neural Ca2+ dynamics over multiple weeks. Together, these capabilities should enable unprecedented analyses of how ensemble neural codes evolve throughout memory processing and provide new insights into how memories are organized in the brain. PMID:27048190

Common inputs in subthreshold membrane potential: The role of quiescent states in neuronal activity

NASA Astrophysics Data System (ADS)

Montangie, Lisandro; Montani, Fernando

2018-06-01

Experiments in certain regions of the cerebral cortex suggest that the spiking activity of neuronal populations is regulated by common non-Gaussian inputs across neurons. We model these deviations from random-walk processes with q -Gaussian distributions into simple threshold neurons, and investigate the scaling properties in large neural populations. We show that deviations from the Gaussian statistics provide a natural framework to regulate population statistics such as sparsity, entropy, and specific heat. This type of description allows us to provide an adequate strategy to explain the information encoding in the case of low neuronal activity and its possible implications on information transmission.

Updated energy budgets for neural computation in the neocortex and cerebellum

PubMed Central

Howarth, Clare; Gleeson, Padraig; Attwell, David

2012-01-01

The brain's energy supply determines its information processing power, and generates functional imaging signals. The energy use on the different subcellular processes underlying neural information processing has been estimated previously for the grey matter of the cerebral and cerebellar cortex. However, these estimates need reevaluating following recent work demonstrating that action potentials in mammalian neurons are much more energy efficient than was previously thought. Using this new knowledge, this paper provides revised estimates for the energy expenditure on neural computation in a simple model for the cerebral cortex and a detailed model of the cerebellar cortex. In cerebral cortex, most signaling energy (50%) is used on postsynaptic glutamate receptors, 21% is used on action potentials, 20% on resting potentials, 5% on presynaptic transmitter release, and 4% on transmitter recycling. In the cerebellar cortex, excitatory neurons use 75% and inhibitory neurons 25% of the signaling energy, and most energy is used on information processing by non-principal neurons: Purkinje cells use only 15% of the signaling energy. The majority of cerebellar signaling energy use is on the maintenance of resting potentials (54%) and postsynaptic receptors (22%), while action potentials account for only 17% of the signaling energy use. PMID:22434069

Responses of prefrontal multisensory neurons to mismatching faces and vocalizations.

PubMed

Diehl, Maria M; Romanski, Lizabeth M

2014-08-20

Social communication relies on the integration of auditory and visual information, which are present in faces and vocalizations. Evidence suggests that the integration of information from multiple sources enhances perception compared with the processing of a unimodal stimulus. Our previous studies demonstrated that single neurons in the ventrolateral prefrontal cortex (VLPFC) of the rhesus monkey (Macaca mulatta) respond to and integrate conspecific vocalizations and their accompanying facial gestures. We were therefore interested in how VLPFC neurons respond differentially to matching (congruent) and mismatching (incongruent) faces and vocalizations. We recorded VLPFC neurons during the presentation of movies with congruent or incongruent species-specific facial gestures and vocalizations as well as their unimodal components. Recordings showed that while many VLPFC units are multisensory and respond to faces, vocalizations, or their combination, a subset of neurons showed a significant change in neuronal activity in response to incongruent versus congruent vocalization movies. Among these neurons, we typically observed incongruent suppression during the early stimulus period and incongruent enhancement during the late stimulus period. Incongruent-responsive VLPFC neurons were both bimodal and nonlinear multisensory, fostering their ability to respond to changes in either modality of a face-vocalization stimulus. These results demonstrate that ventral prefrontal neurons respond to changes in either modality of an audiovisual stimulus, which is important in identity processing and for the integration of multisensory communication information. Copyright © 2014 the authors 0270-6474/14/3411233-11$15.00/0.

High-Degree Neurons Feed Cortical Computations

PubMed Central

Timme, Nicholas M.; Ito, Shinya; Shimono, Masanori; Yeh, Fang-Chin; Litke, Alan M.; Beggs, John M.

2016-01-01

Recent work has shown that functional connectivity among cortical neurons is highly varied, with a small percentage of neurons having many more connections than others. Also, recent theoretical developments now make it possible to quantify how neurons modify information from the connections they receive. Therefore, it is now possible to investigate how information modification, or computation, depends on the number of connections a neuron receives (in-degree) or sends out (out-degree). To do this, we recorded the simultaneous spiking activity of hundreds of neurons in cortico-hippocampal slice cultures using a high-density 512-electrode array. This preparation and recording method combination produced large numbers of neurons recorded at temporal and spatial resolutions that are not currently available in any in vivo recording system. We utilized transfer entropy (a well-established method for detecting linear and nonlinear interactions in time series) and the partial information decomposition (a powerful, recently developed tool for dissecting multivariate information processing into distinct parts) to quantify computation between neurons where information flows converged. We found that computations did not occur equally in all neurons throughout the networks. Surprisingly, neurons that computed large amounts of information tended to receive connections from high out-degree neurons. However, the in-degree of a neuron was not related to the amount of information it computed. To gain insight into these findings, we developed a simple feedforward network model. We found that a degree-modified Hebbian wiring rule best reproduced the pattern of computation and degree correlation results seen in the real data. Interestingly, this rule also maximized signal propagation in the presence of network-wide correlations, suggesting a mechanism by which cortex could deal with common random background input. These are the first results to show that the extent to which a neuron modifies incoming information streams depends on its topological location in the surrounding functional network. PMID:27159884

Long-term memory, neurogenesis, and signal novelty.

PubMed

Sokolov, E N; Nezlina, N I

2004-10-01

According to our suggested hypothesis, long-term memory is a collection of "gnostic units," selectively tuned to past events. The formation of long-term memory occurs with the involvement of constantly appearing new neurons which differentiate from stem cells during the process of neurogenesis, in particular in adults. Conversion of precursor neurons into "gnostic units" selective in relation to ongoing events, supplemented by the involvement of hippocampal "novelty neurons," which increase the flow of information needing to be fixed in long-term memory. "Gnostic units" form before the informational processes occurring in the ventral ("what?") and dorsal ("where?") systems. Formation of new "gnostic units" selectively tuned to a particular event results from the combination of excitation of the detector for stimulus characteristics and the novelty signal generated by "novelty neurons" in the hippocampus.

Prefrontal Neuronal Responses during Audiovisual Mnemonic Processing

PubMed Central

Hwang, Jaewon

2015-01-01

During communication we combine auditory and visual information. Neurophysiological research in nonhuman primates has shown that single neurons in ventrolateral prefrontal cortex (VLPFC) exhibit multisensory responses to faces and vocalizations presented simultaneously. However, whether VLPFC is also involved in maintaining those communication stimuli in working memory or combining stored information across different modalities is unknown, although its human homolog, the inferior frontal gyrus, is known to be important in integrating verbal information from auditory and visual working memory. To address this question, we recorded from VLPFC while rhesus macaques (Macaca mulatta) performed an audiovisual working memory task. Unlike traditional match-to-sample/nonmatch-to-sample paradigms, which use unimodal memoranda, our nonmatch-to-sample task used dynamic movies consisting of both facial gestures and the accompanying vocalizations. For the nonmatch conditions, a change in the auditory component (vocalization), the visual component (face), or both components was detected. Our results show that VLPFC neurons are activated by stimulus and task factors: while some neurons simply responded to a particular face or a vocalization regardless of the task period, others exhibited activity patterns typically related to working memory such as sustained delay activity and match enhancement/suppression. In addition, we found neurons that detected the component change during the nonmatch period. Interestingly, some of these neurons were sensitive to the change of both components and therefore combined information from auditory and visual working memory. These results suggest that VLPFC is not only involved in the perceptual processing of faces and vocalizations but also in their mnemonic processing. PMID:25609614

Spectrotemporal Processing in Spectral Tuning Modules of Cat Primary Auditory Cortex

PubMed Central

Atencio, Craig A.; Schreiner, Christoph E.

2012-01-01

Spectral integration properties show topographical order in cat primary auditory cortex (AI). Along the iso-frequency domain, regions with predominantly narrowly tuned (NT) neurons are segregated from regions with more broadly tuned (BT) neurons, forming distinct processing modules. Despite their prominent spatial segregation, spectrotemporal processing has not been compared for these regions. We identified these NT and BT regions with broad-band ripple stimuli and characterized processing differences between them using both spectrotemporal receptive fields (STRFs) and nonlinear stimulus/firing rate transformations. The durations of STRF excitatory and inhibitory subfields were shorter and the best temporal modulation frequencies were higher for BT neurons than for NT neurons. For NT neurons, the bandwidth of excitatory and inhibitory subfields was matched, whereas for BT neurons it was not. Phase locking and feature selectivity were higher for NT neurons. Properties of the nonlinearities showed only slight differences across the bandwidth modules. These results indicate fundamental differences in spectrotemporal preferences - and thus distinct physiological functions - for neurons in BT and NT spectral integration modules. However, some global processing aspects, such as spectrotemporal interactions and nonlinear input/output behavior, appear to be similar for both neuronal subgroups. The findings suggest that spectral integration modules in AI differ in what specific stimulus aspects are processed, but they are similar in the manner in which stimulus information is processed. PMID:22384036

Auditory connections and functions of prefrontal cortex

PubMed Central

Plakke, Bethany; Romanski, Lizabeth M.

2014-01-01

The functional auditory system extends from the ears to the frontal lobes with successively more complex functions occurring as one ascends the hierarchy of the nervous system. Several areas of the frontal lobe receive afferents from both early and late auditory processing regions within the temporal lobe. Afferents from the early part of the cortical auditory system, the auditory belt cortex, which are presumed to carry information regarding auditory features of sounds, project to only a few prefrontal regions and are most dense in the ventrolateral prefrontal cortex (VLPFC). In contrast, projections from the parabelt and the rostral superior temporal gyrus (STG) most likely convey more complex information and target a larger, widespread region of the prefrontal cortex. Neuronal responses reflect these anatomical projections as some prefrontal neurons exhibit responses to features in acoustic stimuli, while other neurons display task-related responses. For example, recording studies in non-human primates indicate that VLPFC is responsive to complex sounds including vocalizations and that VLPFC neurons in area 12/47 respond to sounds with similar acoustic morphology. In contrast, neuronal responses during auditory working memory involve a wider region of the prefrontal cortex. In humans, the frontal lobe is involved in auditory detection, discrimination, and working memory. Past research suggests that dorsal and ventral subregions of the prefrontal cortex process different types of information with dorsal cortex processing spatial/visual information and ventral cortex processing non-spatial/auditory information. While this is apparent in the non-human primate and in some neuroimaging studies, most research in humans indicates that specific task conditions, stimuli or previous experience may bias the recruitment of specific prefrontal regions, suggesting a more flexible role for the frontal lobe during auditory cognition. PMID:25100931

Challenges of microtome‐based serial block‐face scanning electron microscopy in neuroscience

PubMed Central

WANNER, A. A.; KIRSCHMANN, M. A.

2015-01-01

Summary Serial block‐face scanning electron microscopy (SBEM) is becoming increasingly popular for a wide range of applications in many disciplines from biology to material sciences. This review focuses on applications for circuit reconstruction in neuroscience, which is one of the major driving forces advancing SBEM. Neuronal circuit reconstruction poses exceptional challenges to volume EM in terms of resolution, field of view, acquisition time and sample preparation. Mapping the connections between neurons in the brain is crucial for understanding information flow and information processing in the brain. However, information on the connectivity between hundreds or even thousands of neurons densely packed in neuronal microcircuits is still largely missing. Volume EM techniques such as serial section TEM, automated tape‐collecting ultramicrotome, focused ion‐beam scanning electron microscopy and SBEM (microtome serial block‐face scanning electron microscopy) are the techniques that provide sufficient resolution to resolve ultrastructural details such as synapses and provides sufficient field of view for dense reconstruction of neuronal circuits. While volume EM techniques are advancing, they are generating large data sets on the terabyte scale that require new image processing workflows and analysis tools. In this review, we present the recent advances in SBEM for circuit reconstruction in neuroscience and an overview of existing image processing and analysis pipelines. PMID:25907464

Adaptive Neurons For Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1990-01-01

Training time decreases dramatically. In improved mathematical model of neural-network processor, temperature of neurons (in addition to connection strengths, also called weights, of synapses) varied during supervised-learning phase of operation according to mathematical formalism and not heuristic rule. Evidence that biological neural networks also process information at neuronal level.

Preserving information in neural transmission.

PubMed

Sincich, Lawrence C; Horton, Jonathan C; Sharpee, Tatyana O

2009-05-13

Along most neural pathways, the spike trains transmitted from one neuron to the next are altered. In the process, neurons can either achieve a more efficient stimulus representation, or extract some biologically important stimulus parameter, or succeed at both. We recorded the inputs from single retinal ganglion cells and the outputs from connected lateral geniculate neurons in the macaque to examine how visual signals are relayed from retina to cortex. We found that geniculate neurons re-encoded multiple temporal stimulus features to yield output spikes that carried more information about stimuli than was available in each input spike. The coding transformation of some relay neurons occurred with no decrement in information rate, despite output spike rates that averaged half the input spike rates. This preservation of transmitted information was achieved by the short-term summation of inputs that geniculate neurons require to spike. A reduced model of the retinal and geniculate visual responses, based on two stimulus features and their associated nonlinearities, could account for >85% of the total information available in the spike trains and the preserved information transmission. These results apply to neurons operating on a single time-varying input, suggesting that synaptic temporal integration can alter the temporal receptive field properties to create a more efficient representation of visual signals in the thalamus than the retina.

Network inference from functional experimental data (Conference Presentation)

NASA Astrophysics Data System (ADS)

Desrosiers, Patrick; Labrecque, Simon; Tremblay, Maxime; Bélanger, Mathieu; De Dorlodot, Bertrand; Côté, Daniel C.

2016-03-01

Functional connectivity maps of neuronal networks are critical tools to understand how neurons form circuits, how information is encoded and processed by neurons, how memory is shaped, and how these basic processes are altered under pathological conditions. Current light microscopy allows to observe calcium or electrical activity of thousands of neurons simultaneously, yet assessing comprehensive connectivity maps directly from such data remains a non-trivial analytical task. There exist simple statistical methods, such as cross-correlation and Granger causality, but they only detect linear interactions between neurons. Other more involved inference methods inspired by information theory, such as mutual information and transfer entropy, identify more accurately connections between neurons but also require more computational resources. We carried out a comparative study of common connectivity inference methods. The relative accuracy and computational cost of each method was determined via simulated fluorescence traces generated with realistic computational models of interacting neurons in networks of different topologies (clustered or non-clustered) and sizes (10-1000 neurons). To bridge the computational and experimental works, we observed the intracellular calcium activity of live hippocampal neuronal cultures infected with the fluorescent calcium marker GCaMP6f. The spontaneous activity of the networks, consisting of 50-100 neurons per field of view, was recorded from 20 to 50 Hz on a microscope controlled by a homemade software. We implemented all connectivity inference methods in the software, which rapidly loads calcium fluorescence movies, segments the images, extracts the fluorescence traces, and assesses the functional connections (with strengths and directions) between each pair of neurons. We used this software to assess, in real time, the functional connectivity from real calcium imaging data in basal conditions, under plasticity protocols, and epileptic conditions.

Otolith-Canal Convergence in Vestibular Nuclei Neurons

NASA Technical Reports Server (NTRS)

Dickman, J. David

1996-01-01

During manned spaceflight, acute vestibular disturbances often occur, leading to physical duress and a loss of performance. Vestibular adaptation to the weightless environment follows within two to three days yet the mechanisms responsible for the disturbance and subsequent adaptation are still unknown In order to understand vestibular system function in space and normal earth conditions the basic physiological mechanisms of vestibular information co coding must be determined. Information processing regarding head movement and head position with respect to gravity takes place in the vestibular nuclei neurons that receive signals From the semicircular canals and otolith organs in the vestibular labyrinth. These neurons must synthesize the information into a coded output signal that provides for the head and eye movement reflexes as well as the conscious perception of the body in three-dimensional space The current investigation will for the first time. determine how the vestibular nuclei neurons quantitatively synthesize afferent information from the different linear and angular acceleration receptors in the vestibular labyrinths into an integrated output signal. During the second year of funding, progress on the current project has been focused on the anatomical orientation of semicircular canals and the spatial orientation of the innervating afferent responses. This information is necessary in order to understand how vestibular nuclei neurons process the incoming afferent spatial signals particularly with the convergent otolith afferent signals that are also spatially distributed Since information from the vestibular nuclei is presented to different brain regions associated with differing reflexive and sensory functions it is important to understand the computational mechanisms used by vestibular neurons to produce the appropriate output signal.

Novel encoding and updating of positional, or directional, spatial cues are processed by distinct hippocampal subfields: Evidence for parallel information processing and the "what" stream.

PubMed

Hoang, Thu-Huong; Aliane, Verena; Manahan-Vaughan, Denise

2018-05-01

The specific roles of hippocampal subfields in spatial information processing and encoding are, as yet, unclear. The parallel map theory postulates that whereas the CA1 processes discrete environmental features (positional cues used to generate a "sketch map"), the dentate gyrus (DG) processes large navigation-relevant landmarks (directional cues used to generate a "bearing map"). Additionally, the two-streams hypothesis suggests that hippocampal subfields engage in differentiated processing of information from the "where" and the "what" streams. We investigated these hypotheses by analyzing the effect of exploration of discrete "positional" features and large "directional" spatial landmarks on hippocampal neuronal activity in rats. As an indicator of neuronal activity we measured the mRNA induction of the immediate early genes (IEGs), Arc and Homer1a. We observed an increase of this IEG mRNA in CA1 neurons of the distal neuronal compartment and in proximal CA3, after novel spatial exploration of discrete positional cues, whereas novel exploration of directional cues led to increases in IEG mRNA in the lower blade of the DG and in proximal CA3. Strikingly, the CA1 did not respond to directional cues and the DG did not respond to positional cues. Our data provide evidence for both the parallel map theory and the two-streams hypothesis and suggest a precise compartmentalization of the encoding and processing of "what" and "where" information occurs within the hippocampal subfields. © 2018 The Authors. Hippocampus Published by Wiley Periodicals, Inc.

The Emergence of Single Neurons in Clinical Neurology

PubMed Central

Cash, Sydney S.; Hochberg, Leigh R.

2015-01-01

Summary Single neuron actions and interactions are the sine qua non of brain function, and nearly all diseases and injuries of the central nervous system trace their clinical sequelae to neuronal dysfunction or failure. Remarkably, discussion of neuronal activity is largely absent in clinical neuroscience. Advances in neurotechnology and computational capabilities, accompanied by shifts in theoretical frameworks, have led to renewed interest in the information represented by single neurons. Using direct interfaces with the nervous system, millisecond-scale information will soon be extracted from single neurons in clinical environments, supporting personalized treatment of neurologic and psychiatric disease. In this review we focus on single neuronal activity in restoring communication and motor control in patients suffering from devastating neurological injuries. We also explore the single neuron's role in epilepsy and movement disorders, surgical anesthesia, and in cognitive processes disrupted in neurodegenerative and neuropsychiatric disease. Finally, we speculate on how technological advances will revolutionize neurotherapeutics. PMID:25856488

The emergence of single neurons in clinical neurology.

PubMed

Cash, Sydney S; Hochberg, Leigh R

2015-04-08

Single neuron actions and interactions are the sine qua non of brain function, and nearly all diseases and injuries of the CNS trace their clinical sequelae to neuronal dysfunction or failure. Remarkably, discussion of neuronal activity is largely absent in clinical neuroscience. Advances in neurotechnology and computational capabilities, accompanied by shifts in theoretical frameworks, have led to renewed interest in the information represented by single neurons. Using direct interfaces with the nervous system, millisecond-scale information will soon be extracted from single neurons in clinical environments, supporting personalized treatment of neurologic and psychiatric disease. In this Perspective, we focus on single-neuronal activity in restoring communication and motor control in patients suffering from devastating neurological injuries. We also explore the single neuron's role in epilepsy and movement disorders, surgical anesthesia, and in cognitive processes disrupted in neurodegenerative and neuropsychiatric disease. Finally, we speculate on how technological advances will revolutionize neurotherapeutics. Copyright © 2015 Elsevier Inc. All rights reserved.

A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker.

PubMed

Leibfried, Felix; Braun, Daniel A

2015-08-01

Rate distortion theory describes how to communicate relevant information most efficiently over a channel with limited capacity. One of the many applications of rate distortion theory is bounded rational decision making, where decision makers are modeled as information channels that transform sensory input into motor output under the constraint that their channel capacity is limited. Such a bounded rational decision maker can be thought to optimize an objective function that trades off the decision maker's utility or cumulative reward against the information processing cost measured by the mutual information between sensory input and motor output. In this study, we interpret a spiking neuron as a bounded rational decision maker that aims to maximize its expected reward under the computational constraint that the mutual information between the neuron's input and output is upper bounded. This abstract computational constraint translates into a penalization of the deviation between the neuron's instantaneous and average firing behavior. We derive a synaptic weight update rule for such a rate distortion optimizing neuron and show in simulations that the neuron efficiently extracts reward-relevant information from the input by trading off its synaptic strengths against the collected reward.

Statistics of natural scenes and cortical color processing.

PubMed

Cecchi, Guillermo A; Rao, A Ravishankar; Xiao, Youping; Kaplan, Ehud

2010-09-01

We investigate the spatial correlations of orientation and color information in natural images. We find that the correlation of orientation information falls off rapidly with increasing distance, while color information is more highly correlated over longer distances. We show that orientation and color information are statistically independent in natural images and that the spatial correlation of jointly encoded orientation and color information decays faster than that of color alone. Our findings suggest that: (a) orientation and color information should be processed in separate channels and (b) the organization of cortical color and orientation selectivity at low spatial frequencies is a reflection of the cortical adaptation to the statistical structure of the visual world. These findings are in agreement with biological observations, as form and color are thought to be represented by different classes of neurons in the primary visual cortex, and the receptive fields of color-selective neurons are larger than those of orientation-selective neurons. The agreement between our findings and biological observations supports the ecological theory of perception.

Novelty-Sensitive Dopaminergic Neurons in the Human Substantia Nigra Predict Success of Declarative Memory Formation.

PubMed

Kamiński, Jan; Mamelak, Adam N; Birch, Kurtis; Mosher, Clayton P; Tagliati, Michele; Rutishauser, Ueli

2018-05-07

The encoding of information into long-term declarative memory is facilitated by dopamine. This process depends on hippocampal novelty signals, but it remains unknown how midbrain dopaminergic neurons are modulated by declarative-memory-based information. We recorded individual substantia nigra (SN) neurons and cortical field potentials in human patients performing a recognition memory task. We found that 25% of SN neurons were modulated by stimulus novelty. Extracellular waveform shape and anatomical location indicated that these memory-selective neurons were putatively dopaminergic. The responses of memory-selective neurons appeared 527 ms after stimulus onset, changed after a single trial, and were indicative of recognition accuracy. SN neurons phase locked to frontal cortical theta-frequency oscillations, and the extent of this coordination predicted successful memory formation. These data reveal that dopaminergic neurons in the human SN are modulated by memory signals and demonstrate a progression of information flow in the hippocampal-basal ganglia-frontal cortex loop for memory encoding. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Local Circuits of V1 Layer 4B Neurons Projecting to V2 Thick Stripes Define Distinct Cell Classes and Avoid Cytochrome Oxidase Blobs

PubMed Central

Yarch, Jeff; Federer, Frederick

2017-01-01

Decades of anatomical studies on the primate primary visual cortex (V1) have led to a detailed diagram of V1 intrinsic circuitry, but this diagram lacks information about the output targets of V1 cells. Understanding how V1 local processing relates to downstream processing requires identification of neuronal populations defined by their output targets. In primates, V1 layers (L)2/3 and 4B send segregated projections to distinct cytochrome oxidase (CO) stripes in area V2: neurons in CO blob columns project to thin stripes while neurons outside blob columns project to thick and pale stripes, suggesting functional specialization of V1-to-V2 CO streams. However, the conventional diagram of V1 shows all L4B neurons, regardless of their soma location in blob or interblob columns, as projecting selectively to CO blobs in L2/3, suggesting convergence of blob/interblob information in L2/3 blobs and, possibly, some V2 stripes. However, it is unclear whether all L4B projection neurons show similar local circuitries. Using viral-mediated circuit tracing, we have identified the local circuits of L4B neurons projecting to V2 thick stripes in macaque. Consistent with previous studies, we found the somata of this L4B subpopulation to reside predominantly outside blob columns; however, unlike previous descriptions of local L4B circuits, these cells consistently projected outside CO blob columns in all layers. Thus, the local circuits of these L4B output neurons, just like their extrinsic projections to V2, preserve CO streams. Moreover, the intra-V1 laminar patterns of axonal projections identify two distinct neuron classes within this L4B subpopulation, including a rare novel neuron type, suggestive of two functionally specialized output channels. SIGNIFICANCE STATEMENT Conventional diagrams of primate primary visual cortex (V1) depict neuronal connections within and between different V1 layers, but lack information about the cells' downstream targets. This information is critical to understanding how local processing in V1 relates to downstream processing. We have identified the local circuits of a population of cells in V1 layer (L)4B that project to area V2. These cells' local circuits differ from classical descriptions of L4B circuits in both the laminar and functional compartments targeted by their axons, and identify two neuron classes. Our results demonstrate that both local intra-V1 and extrinsic V1-to-V2 connections of L4B neurons preserve CO-stream segregation, suggesting that across-stream integration occurs downstream of V1, and that output targets dictate local V1 circuitry. PMID:28077720

Computing by physical interaction in neurons.

PubMed

Aur, Dorian; Jog, Mandar; Poznanski, Roman R

2011-12-01

The electrodynamics of action potentials represents the fundamental level where information is integrated and processed in neurons. The Hodgkin-Huxley model cannot explain the non-stereotyped spatial charge density dynamics that occur during action potential propagation. Revealed in experiments as spike directivity, the non-uniform charge density dynamics within neurons carry meaningful information and suggest that fragments of information regarding our memories are endogenously stored in structural patterns at a molecular level and are revealed only during spiking activity. The main conceptual idea is that under the influence of electric fields, efficient computation by interaction occurs between charge densities embedded within molecular structures and the transient developed flow of electrical charges. This process of computation underlying electrical interactions and molecular mechanisms at the subcellular level is dissimilar from spiking neuron models that are completely devoid of physical interactions. Computation by interaction describes a more powerful continuous model of computation than the one that consists of discrete steps as represented in Turing machines.

Study on Electro-polymerization Nano-micro Wiring System Imitating Axonal Growth of Artificial Neurons towards Machine Learning

NASA Astrophysics Data System (ADS)

Dang, Nguyen Tuan; Akai-Kasada, Megumi; Asai, Tetsuya; Saito, Akira; Kuwahara, Yuji; Hokkaido University Collaboration

2015-03-01

Machine learning using the artificial neuron network research is supposed to be the best way to understand how the human brain trains itself to process information. In this study, we have successfully developed the programs using supervised machine learning algorithm. However, these supervised learning processes for the neuron network required the very strong computing configuration. Derivation from the necessity of increasing in computing ability and in reduction of power consumption, accelerator circuits become critical. To develop such accelerator circuits using supervised machine learning algorithm, conducting polymer micro/nanowires growing process was realized and applied as a synaptic weigh controller. In this work, high conductivity Polypyrrole (PPy) and Poly (3, 4 - ethylenedioxythiophene) PEDOT wires were potentiostatically grown crosslinking the designated electrodes, which were prefabricated by lithography, when appropriate square wave AC voltage and appropriate frequency were applied. Micro/nanowire growing process emulated the neurotransmitter release process of synapses inside a biological neuron and wire's resistance variation during the growing process was preferred to as the variation of synaptic weigh in machine learning algorithm. In a cooperation with Graduate School of Information Science and Technology, Hokkaido University.

Remediation of information processing following traumatic brain injury: a community-based rehabilitation approach.

PubMed

Ashley, Mark J; Ashley, Jessica; Kreber, Lisa

2012-01-01

Traumatic brain injury (TBI) results in disruption of information processing via damage to primary, secondary, and tertiary cortical regions, as well as, subcortical pathways supporting information flow within and between cortical structures. TBI predominantly affects the anterior frontal poles, anterior temporal poles, white matter tracts and medial temporal structures. Fundamental information processing skills such as attention, perceptual processing, categorization and cognitive distance are concentrated within these same regions and are frequently disrupted following injury. Information processing skills improve in accordance with the extent to which residual frontal and temporal neurons can be encouraged to recruit and bias neuronal networks or the degree to which the functional connectivity of neural networks can be re-established and result in re-emergence or regeneration of specific cognitive skills. Higher-order cognitive processes, i.e., memory, reasoning, problem solving and other executive functions, are dependent upon the integrity of attention, perceptual processing, categorization, and cognitive distance. A therapeutic construct for treatment of attention, perceptual processing, categorization and cognitive distance deficits is presented along with an interventional model for encouragement of re-emergence or regeneration of these fundamental information processing skills.

Brain Embodiment of Syntax and Grammar: Discrete Combinatorial Mechanisms Spelt Out in Neuronal Circuits

ERIC Educational Resources Information Center

Pulvermuller, Friedemann

2010-01-01

Neuroscience has greatly improved our understanding of the brain basis of abstract lexical and semantic processes. The neuronal devices underlying words and concepts are distributed neuronal assemblies reaching into sensory and motor systems of the cortex and, at the cognitive level, information binding in such widely dispersed circuits is…

Basic mathematical rules are encoded by primate prefrontal cortex neurons

PubMed Central

Bongard, Sylvia; Nieder, Andreas

2010-01-01

Mathematics is based on highly abstract principles, or rules, of how to structure, process, and evaluate numerical information. If and how mathematical rules can be represented by single neurons, however, has remained elusive. We therefore recorded the activity of individual prefrontal cortex (PFC) neurons in rhesus monkeys required to switch flexibly between “greater than” and “less than” rules. The monkeys performed this task with different numerical quantities and generalized to set sizes that had not been presented previously, indicating that they had learned an abstract mathematical principle. The most prevalent activity recorded from randomly selected PFC neurons reflected the mathematical rules; purely sensory- and memory-related activity was almost absent. These data show that single PFC neurons have the capacity to represent flexible operations on most abstract numerical quantities. Our findings support PFC network models implementing specific “rule-coding” units that control the flow of information between segregated input, memory, and output layers. We speculate that these neuronal circuits in the monkey lateral PFC could readily have been adopted in the course of primate evolution for syntactic processing of numbers in formalized mathematical systems. PMID:20133872

The molecular basis of memory. Part 2: chemistry of the tripartite mechanism.

PubMed

Marx, Gerard; Gilon, Chaim

2013-06-19

We propose a tripartite mechanism to describe the processing of cognitive information (cog-info), comprising the (1) neuron, (2) surrounding neural extracellular matrix (nECM), and (3) numerous "trace" metals distributed therein. The neuron is encased in a polyanionic nECM lattice doped with metals (>10), wherein it processes (computes) and stores cog-info. Each [nECM:metal] complex is the molecular correlate of a cognitive unit of information (cuinfo), similar to a computer "bit". These are induced/sensed by the neuron via surface iontophoretic and electroelastic (piezoelectric) sensors. The generic cuinfo are used by neurons to biochemically encode and store cog-info in a rapid, energy efficient, but computationally expansive manner. Here, we describe chemical reactions involved in various processes that underline the tripartite mechanism. In addition, we present novel iconographic representations of various types of cuinfo resulting from"tagging" and cross-linking reactions, essential for the indexing cuinfo for organized retrieval and storage of memory.

Degree Correlations Optimize Neuronal Network Sensitivity to Sub-Threshold Stimuli

PubMed Central

Schmeltzer, Christian; Kihara, Alexandre Hiroaki; Sokolov, Igor Michailovitsch; Rüdiger, Sten

2015-01-01

Information processing in the brain crucially depends on the topology of the neuronal connections. We investigate how the topology influences the response of a population of leaky integrate-and-fire neurons to a stimulus. We devise a method to calculate firing rates from a self-consistent system of equations taking into account the degree distribution and degree correlations in the network. We show that assortative degree correlations strongly improve the sensitivity for weak stimuli and propose that such networks possess an advantage in signal processing. We moreover find that there exists an optimum in assortativity at an intermediate level leading to a maximum in input/output mutual information. PMID:26115374

Neuronal Categorization and Discrimination of Social Behaviors in Primate Prefrontal Cortex

PubMed Central

Tsunada, Joji; Sawaguchi, Toshiyuki

2012-01-01

It has been implied that primates have an ability to categorize social behaviors between other individuals for the execution of adequate social-interactions. Since the lateral prefrontal cortex (LPFC) is involved in both the categorization and the processing of social information, the primate LPFC may be involved in the categorization of social behaviors. To test this hypothesis, we examined neuronal activity in the LPFC of monkeys during presentations of two types of movies of social behaviors (grooming, mounting) and movies of plural monkeys without any eye- or body-contacts between them (no-contacts movies). Although the monkeys were not required to categorize and discriminate the movies in this task, a subset of neurons sampled from the LPFC showed a significantly different activity during the presentation of a specific type of social behaviors in comparison with the others. These neurons categorized social behaviors at the population level and, at the individual neuron level, the majority of the neurons discriminated each movie within the same category of social behaviors. Our findings suggest that a fraction of LPFC neurons process categorical and discriminative information of social behaviors, thereby contributing to the adaptation to social environments. PMID:23285110

Cortical neurons of bats respond best to echoes from nearest targets when listening to natural biosonar multi-echo streams.

PubMed

Beetz, M Jerome; Hechavarría, Julio C; Kössl, Manfred

2016-10-27

Bats orientate in darkness by listening to echoes from their biosonar calls, a behaviour known as echolocation. Recent studies showed that cortical neurons respond in a highly selective manner when stimulated with natural echolocation sequences that contain echoes from single targets. However, it remains unknown how cortical neurons process echolocation sequences containing echo information from multiple objects. In the present study, we used echolocation sequences containing echoes from three, two or one object separated in the space depth as stimuli to study neuronal activity in the bat auditory cortex. Neuronal activity was recorded with multi-electrode arrays placed in the dorsal auditory cortex, where neurons tuned to target-distance are found. Our results show that target-distance encoding neurons are mostly selective to echoes coming from the closest object, and that the representation of echo information from distant objects is selectively suppressed. This suppression extends over a large part of the dorsal auditory cortex and may override possible parallel processing of multiple objects. The presented data suggest that global cortical suppression might establish a cortical "default mode" that allows selectively focusing on close obstacle even without active attention from the animals.

Cortical neurons of bats respond best to echoes from nearest targets when listening to natural biosonar multi-echo streams

PubMed Central

Beetz, M. Jerome; Hechavarría, Julio C.; Kössl, Manfred

2016-01-01

Bats orientate in darkness by listening to echoes from their biosonar calls, a behaviour known as echolocation. Recent studies showed that cortical neurons respond in a highly selective manner when stimulated with natural echolocation sequences that contain echoes from single targets. However, it remains unknown how cortical neurons process echolocation sequences containing echo information from multiple objects. In the present study, we used echolocation sequences containing echoes from three, two or one object separated in the space depth as stimuli to study neuronal activity in the bat auditory cortex. Neuronal activity was recorded with multi-electrode arrays placed in the dorsal auditory cortex, where neurons tuned to target-distance are found. Our results show that target-distance encoding neurons are mostly selective to echoes coming from the closest object, and that the representation of echo information from distant objects is selectively suppressed. This suppression extends over a large part of the dorsal auditory cortex and may override possible parallel processing of multiple objects. The presented data suggest that global cortical suppression might establish a cortical “default mode” that allows selectively focusing on close obstacle even without active attention from the animals. PMID:27786252

High Stimulus-Related Information in Barrel Cortex Inhibitory Interneurons

PubMed Central

Reyes-Puerta, Vicente; Kim, Suam; Sun, Jyh-Jang; Imbrosci, Barbara; Kilb, Werner; Luhmann, Heiko J.

2015-01-01

The manner in which populations of inhibitory (INH) and excitatory (EXC) neocortical neurons collectively encode stimulus-related information is a fundamental, yet still unresolved question. Here we address this question by simultaneously recording with large-scale multi-electrode arrays (of up to 128 channels) the activity of cell ensembles (of up to 74 neurons) distributed along all layers of 3–4 neighboring cortical columns in the anesthetized adult rat somatosensory barrel cortex in vivo. Using two different whisker stimulus modalities (location and frequency) we show that individual INH neurons – classified as such according to their distinct extracellular spike waveforms – discriminate better between restricted sets of stimuli (≤6 stimulus classes) than EXC neurons in granular and infra-granular layers. We also demonstrate that ensembles of INH cells jointly provide as much information about such stimuli as comparable ensembles containing the ~20% most informative EXC neurons, however presenting less information redundancy – a result which was consistent when applying both theoretical information measurements and linear discriminant analysis classifiers. These results suggest that a consortium of INH neurons dominates the information conveyed to the neocortical network, thereby efficiently processing incoming sensory activity. This conclusion extends our view on the role of the inhibitory system to orchestrate cortical activity. PMID:26098109

Temporal-pattern recognition by single neurons in a sensory pathway devoted to social communication behavior

PubMed Central

Carlson, Bruce A.

2010-01-01

Sensory systems often encode stimulus information into the temporal pattern of action potential activity. However, little is known about how the information contained within these patterns is extracted by postsynaptic neurons. Similar to temporal coding by sensory neurons, social information in mormyrid fish is encoded into the temporal patterning of an electric organ discharge (EOD). In the current study, sensitivity to temporal patterns of electrosensory stimuli was found to arise within the midbrain posterior exterolateral nucleus (ELp). Whole-cell patch recordings from ELp neurons in vivo revealed three patterns of interpulse interval (IPI) tuning: low-pass neurons tuned to long intervals, high-pass neurons tuned to short intervals and band-pass neurons tuned to intermediate intervals. Many neurons within each class also responded preferentially to either increasing or decreasing IPIs. Playback of electric signaling patterns recorded from freely behaving fish revealed that the IPI and direction tuning of ELp neurons resulted in selective responses to particular social communication displays characterized by distinct IPI patterns. The postsynaptic potential responses of many neurons indicated a combination of excitatory and inhibitory synaptic input, and the IPI tuning of ELp neurons was directly related to rate-dependent changes in the direction and amplitude of postsynaptic potentials. These results suggest that differences in the dynamics of short-term synaptic plasticity in excitatory and inhibitory pathways may tune central sensory neurons to particular temporal patterns of presynaptic activity. This may represent a general mechanism for the processing of behaviorally-relevant stimulus information encoded into temporal patterns of activity by sensory neurons. PMID:19641105

Temporal-pattern recognition by single neurons in a sensory pathway devoted to social communication behavior.

PubMed

Carlson, Bruce A

2009-07-29

Sensory systems often encode stimulus information into the temporal pattern of action potential activity. However, little is known about how the information contained within these patterns is extracted by postsynaptic neurons. Similar to temporal coding by sensory neurons, social information in mormyrid fish is encoded into the temporal patterning of an electric organ discharge. In the current study, sensitivity to temporal patterns of electrosensory stimuli was found to arise within the midbrain posterior exterolateral nucleus (ELp). Whole-cell patch recordings from ELp neurons in vivo revealed three patterns of interpulse interval (IPI) tuning: low-pass neurons tuned to long intervals, high-pass neurons tuned to short intervals, and bandpass neurons tuned to intermediate intervals. Many neurons within each class also responded preferentially to either increasing or decreasing IPIs. Playback of electric signaling patterns recorded from freely behaving fish revealed that the IPI and direction tuning of ELp neurons resulted in selective responses to particular social communication displays characterized by distinct IPI patterns. The postsynaptic potential responses of many neurons indicated a combination of excitatory and inhibitory synaptic input, and the IPI tuning of ELp neurons was directly related to rate-dependent changes in the direction and amplitude of postsynaptic potentials. These results suggest that differences in the dynamics of short-term synaptic plasticity in excitatory and inhibitory pathways may tune central sensory neurons to particular temporal patterns of presynaptic activity. This may represent a general mechanism for the processing of behaviorally relevant stimulus information encoded into temporal patterns of activity by sensory neurons.

Emergence of transformation-tolerant representations of visual objects in rat lateral extrastriate cortex

PubMed Central

Tafazoli, Sina; Safaai, Houman; De Franceschi, Gioia; Rosselli, Federica Bianca; Vanzella, Walter; Riggi, Margherita; Buffolo, Federica; Panzeri, Stefano; Zoccolan, Davide

2017-01-01

Rodents are emerging as increasingly popular models of visual functions. Yet, evidence that rodent visual cortex is capable of advanced visual processing, such as object recognition, is limited. Here we investigate how neurons located along the progression of extrastriate areas that, in the rat brain, run laterally to primary visual cortex, encode object information. We found a progressive functional specialization of neural responses along these areas, with: (1) a sharp reduction of the amount of low-level, energy-related visual information encoded by neuronal firing; and (2) a substantial increase in the ability of both single neurons and neuronal populations to support discrimination of visual objects under identity-preserving transformations (e.g., position and size changes). These findings strongly argue for the existence of a rat object-processing pathway, and point to the rodents as promising models to dissect the neuronal circuitry underlying transformation-tolerant recognition of visual objects. DOI: http://dx.doi.org/10.7554/eLife.22794.001 PMID:28395730

Processing of Natural Echolocation Sequences in the Inferior Colliculus of Seba’s Fruit Eating Bat, Carollia perspicillata

PubMed Central

Kordes, Sebastian; Kössl, Manfred

2017-01-01

Abstract For the purpose of orientation, echolocating bats emit highly repetitive and spatially directed sonar calls. Echoes arising from call reflections are used to create an acoustic image of the environment. The inferior colliculus (IC) represents an important auditory stage for initial processing of echolocation signals. The present study addresses the following questions: (1) how does the temporal context of an echolocation sequence mimicking an approach flight of an animal affect neuronal processing of distance information to echo delays? (2) how does the IC process complex echolocation sequences containing echo information from multiple objects (multiobject sequence)? Here, we conducted neurophysiological recordings from the IC of ketamine-anaesthetized bats of the species Carollia perspicillata and compared the results from the IC with the ones from the auditory cortex (AC). Neuronal responses to an echolocation sequence was suppressed when compared to the responses to temporally isolated and randomized segments of the sequence. The neuronal suppression was weaker in the IC than in the AC. In contrast to the cortex, the time course of the acoustic events is reflected by IC activity. In the IC, suppression sharpens the neuronal tuning to specific call-echo elements and increases the signal-to-noise ratio in the units’ responses. When presenting multiple-object sequences, despite collicular suppression, the neurons responded to each object-specific echo. The latter allows parallel processing of multiple echolocation streams at the IC level. Altogether, our data suggests that temporally-precise neuronal responses in the IC could allow fast and parallel processing of multiple acoustic streams. PMID:29242823

Processing of Natural Echolocation Sequences in the Inferior Colliculus of Seba's Fruit Eating Bat, Carollia perspicillata.

PubMed

Beetz, M Jerome; Kordes, Sebastian; García-Rosales, Francisco; Kössl, Manfred; Hechavarría, Julio C

2017-01-01

For the purpose of orientation, echolocating bats emit highly repetitive and spatially directed sonar calls. Echoes arising from call reflections are used to create an acoustic image of the environment. The inferior colliculus (IC) represents an important auditory stage for initial processing of echolocation signals. The present study addresses the following questions: (1) how does the temporal context of an echolocation sequence mimicking an approach flight of an animal affect neuronal processing of distance information to echo delays? (2) how does the IC process complex echolocation sequences containing echo information from multiple objects (multiobject sequence)? Here, we conducted neurophysiological recordings from the IC of ketamine-anaesthetized bats of the species Carollia perspicillata and compared the results from the IC with the ones from the auditory cortex (AC). Neuronal responses to an echolocation sequence was suppressed when compared to the responses to temporally isolated and randomized segments of the sequence. The neuronal suppression was weaker in the IC than in the AC. In contrast to the cortex, the time course of the acoustic events is reflected by IC activity. In the IC, suppression sharpens the neuronal tuning to specific call-echo elements and increases the signal-to-noise ratio in the units' responses. When presenting multiple-object sequences, despite collicular suppression, the neurons responded to each object-specific echo. The latter allows parallel processing of multiple echolocation streams at the IC level. Altogether, our data suggests that temporally-precise neuronal responses in the IC could allow fast and parallel processing of multiple acoustic streams.

A comprehensive wiring diagram of the protocerebral bridge for visual information processing in the Drosophila brain.

PubMed

Lin, Chih-Yung; Chuang, Chao-Chun; Hua, Tzu-En; Chen, Chun-Chao; Dickson, Barry J; Greenspan, Ralph J; Chiang, Ann-Shyn

2013-05-30

How the brain perceives sensory information and generates meaningful behavior depends critically on its underlying circuitry. The protocerebral bridge (PB) is a major part of the insect central complex (CX), a premotor center that may be analogous to the human basal ganglia. Here, by deconstructing hundreds of PB single neurons and reconstructing them into a common three-dimensional framework, we have constructed a comprehensive map of PB circuits with labeled polarity and predicted directions of information flow. Our analysis reveals a highly ordered information processing system that involves directed information flow among CX subunits through 194 distinct PB neuron types. Circuitry properties such as mirroring, convergence, divergence, tiling, reverberation, and parallel signal propagation were observed; their functional and evolutional significance is discussed. This layout of PB neuronal circuitry may provide guidelines for further investigations on transformation of sensory (e.g., visual) input into locomotor commands in fly brains. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

A neuromorphic circuit mimicking biological short-term memory.

PubMed

Barzegarjalali, Saeid; Parker, Alice C

2016-08-01

Research shows that the way we remember things for a few seconds is a different mechanism from the way we remember things for a longer time. Short-term memory is based on persistently firing neurons, whereas storing information for a longer time is based on strengthening the synapses or even forming new neural connections. Information about location and appearance of an object is segregated and processed by separate neurons. Furthermore neurons can continue firing using different mechanisms. Here, we have designed a biomimetic neuromorphic circuit that mimics short-term memory by firing neurons, using biological mechanisms to remember location and shape of an object. Our neuromorphic circuit has a hybrid architecture. Neurons are designed with CMOS 45nm technology and synapses are designed with carbon nanotubes (CNT).

An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites.

PubMed

Jadi, Monika P; Behabadi, Bardia F; Poleg-Polsky, Alon; Schiller, Jackie; Mel, Bartlett W

2014-05-01

In pursuit of the goal to understand and eventually reproduce the diverse functions of the brain, a key challenge lies in reverse engineering the peculiar biology-based "technology" that underlies the brain's remarkable ability to process and store information. The basic building block of the nervous system is the nerve cell, or "neuron," yet after more than 100 years of neurophysiological study and 60 years of modeling, the information processing functions of individual neurons, and the parameters that allow them to engage in so many different types of computation (sensory, motor, mnemonic, executive, etc.) remain poorly understood. In this paper, we review both historical and recent findings that have led to our current understanding of the analog spatial processing capabilities of dendrites, the major input structures of neurons, with a focus on the principal cell type of the neocortex and hippocampus, the pyramidal neuron (PN). We encapsulate our current understanding of PN dendritic integration in an abstract layered model whose spatially sensitive branch-subunits compute multidimensional sigmoidal functions. Unlike the 1-D sigmoids found in conventional neural network models, multidimensional sigmoids allow the cell to implement a rich spectrum of nonlinear modulation effects directly within their dendritic trees.

Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function.

PubMed

Reimann, Michael W; Nolte, Max; Scolamiero, Martina; Turner, Katharine; Perin, Rodrigo; Chindemi, Giuseppe; Dłotko, Paweł; Levi, Ran; Hess, Kathryn; Markram, Henry

2017-01-01

The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity. The synaptic network contains an abundance of cliques of neurons bound into cavities that guide the emergence of correlated activity. In response to stimuli, correlated activity binds synaptically connected neurons into functional cliques and cavities that evolve in a stereotypical sequence toward peak complexity. We propose that the brain processes stimuli by forming increasingly complex functional cliques and cavities.

Differential dynamics of spatial attention, position, and color coding within the parietofrontal network.

PubMed

Astrand, Elaine; Ibos, Guilhem; Duhamel, Jean-René; Ben Hamed, Suliann

2015-02-18

Despite an ever growing knowledge on how parietal and prefrontal neurons encode low-level spatial and color information or higher-level information, such as spatial attention, an understanding of how these cortical regions process neuronal information at the population level is still missing. A simple assumption would be that the function and temporal response profiles of these neuronal populations match that of its constituting individual cells. However, several recent studies suggest that this is not necessarily the case and that the single-cell approach overlooks dynamic changes in how information is distributed over the neuronal population. Here, we use a time-resolved population pattern analysis to explore how spatial position, spatial attention and color information are differentially encoded and maintained in the macaque monkey prefrontal (frontal eye fields) and parietal cortex (lateral intraparietal area). Overall, our work brings about three novel observations. First, we show that parietal and prefrontal populations operate in two distinct population regimens for the encoding of sensory and cognitive information: a stationary mode and a dynamic mode. Second, we show that the temporal dynamics of a heterogeneous neuronal population brings about complementary information to that of its functional subpopulations. Thus, both need to be investigated in parallel. Last, we show that identifying the neuronal configuration in which a neuronal population encodes given information can serve to reveal this same information in a different context. All together, this work challenges common views on neural coding in the parietofrontal network. Copyright © 2015 the authors 0270-6474/15/353174-16$15.00/0.

Processing and Integration of Contextual Information in Monkey Ventrolateral Prefrontal Neurons during Selection and Execution of Goal-Directed Manipulative Actions.

PubMed

Bruni, Stefania; Giorgetti, Valentina; Bonini, Luca; Fogassi, Leonardo

2015-08-26

The prefrontal cortex (PFC) is deemed to underlie the complexity, flexibility, and goal-directedness of primates' behavior. Most neurophysiological studies performed so far investigated PFC functions with arm-reaching or oculomotor tasks, thus leaving unclear whether, and to which extent, PFC neurons also play a role in goal-directed manipulative actions, such as those commonly used by primates during most of their daily activities. Here we trained two macaques to perform or withhold grasp-to-eat and grasp-to-place actions, depending on the combination of two subsequently presented cues: an auditory go/no-go cue (high/low tone) and a visually presented target (food/object). By varying the order of presentation of the two cues, we could segment and independently evaluate the processing and integration of contextual information allowing the monkey to make a decision on whether or not to act, and what action to perform. We recorded 403 task-related neurons from the ventrolateral prefrontal cortex (VLPFC): unimodal sensory-driven (37%), motor-related (21%), unimodal sensory-and-motor (23%), and multisensory (19%) neurons. Target and go/no-go selectivity characterized most of the recorded neurons, particularly those endowed with motor-related discharge. Interestingly, multisensory neurons appeared to encode a behavioral decision independently from the sensory modality of the stimulus allowing the monkey to make it: some of them reflected the decision to act or refraining from acting (56%), whereas others (44%) encoded the decision to perform (or withhold) a specific action (e.g., grasp-to-eat). Our findings indicate that VLPFC neurons play a role in the processing of contextual information underlying motor decision during goal-directed manipulative actions. We demonstrated that macaque ventrolateral prefrontal cortex (VLPFC) neurons show remarkable selectivity for different aspects of the contextual information allowing the monkey to select and execute goal-directed manipulative actions. Interestingly, a set of these neurons provide multimodal representations of the intended goal of a forthcoming action, encoding a behavioral decision (e.g., grasp-to-eat) independently from the sensory information allowing the monkey to make it. Our findings expand the available knowledge on prefrontal functions by showing that VLPFC neurons play a role in the selection and execution of goal-directed manipulative actions resembling those of common primates' foraging behaviors. On these bases, we propose that VLPFC may host an abstract "vocabulary" of the intended goals pursued by primates in their natural environment. Copyright © 2015 the authors 0270-6474/15/3511877-14$15.00/0.

A-type potassium channels differentially tune afferent pathways from rat solitary tract nucleus to caudal ventrolateral medulla or paraventricular hypothalamus

PubMed Central

Bailey, T W; Hermes, S M; Whittier, K L; Aicher, S A; Andresen, M C

2007-01-01

The solitary tract nucleus (NTS) conveys visceral information to diverse central networks involved in homeostatic regulation. Although afferent information content arriving at various CNS sites varies substantially, little is known about the contribution of processing within the NTS to these differences. Using retrograde dyes to identify specific NTS projection neurons, we recently reported that solitary tract (ST) afferents directly contact NTS neurons projecting to caudal ventrolateral medulla (CVLM) but largely only indirectly contact neurons projecting to the hypothalamic paraventricular nucleus (PVN). Since intrinsic properties impact information transmission, here we evaluated potassium channel expression and somatodendritic morphology of projection neurons and their relation to afferent information output directed to PVN or CVLM pathways. In slices, tracer-identified projection neurons were classified as directly or indirectly (polysynaptically) coupled to ST afferents by EPSC latency characteristics (directly coupled, jitter < 200 μs). In each neuron, voltage-dependent potassium currents (IK) were evaluated and, in representative neurons, biocytin-filled structures were quantified. Both CVLM- and PVN-projecting neurons had similar, tetraethylammonium-sensitive IK. However, only PVN-projecting NTS neurons displayed large transient, 4aminopyridine-sensitive, A-type currents (IKA). PVN-projecting neurons had larger cell bodies with more elaborate dendritic morphology than CVLM-projecting neurons. ST shocks faithfully (> 75%) triggered action potentials in CVLM-projecting neurons but spike output was uniformly low (< 20%) in PVN-projecting neurons. Pre-conditioning hyperpolarization removed IKA inactivation and attenuated ST-evoked spike generation along PVN but not CVLM pathways. Thus, multiple differences in structure, organization, synaptic transmission and ion channel expression tune the overall fidelity of afferent signals that reach these destinations. PMID:17510187

Motor-visual neurons and action recognition in social interactions.

PubMed

de la Rosa, Stephan; Bülthoff, Heinrich H

2014-04-01

Cook et al. suggest that motor-visual neurons originate from associative learning. This suggestion has interesting implications for the processing of socially relevant visual information in social interactions. Here, we discuss two aspects of the associative learning account that seem to have particular relevance for visual recognition of social information in social interactions - namely, context-specific and contingency based learning.

Speed of feedforward and recurrent processing in multilayer networks of integrate-and-fire neurons.

PubMed

Panzeri, S; Rolls, E T; Battaglia, F; Lavis, R

2001-11-01

The speed of processing in the visual cortical areas can be fast, with for example the latency of neuronal responses increasing by only approximately 10 ms per area in the ventral visual system sequence V1 to V2 to V4 to inferior temporal visual cortex. This has led to the suggestion that rapid visual processing can only be based on the feedforward connections between cortical areas. To test this idea, we investigated the dynamics of information retrieval in multiple layer networks using a four-stage feedforward network modelled with continuous dynamics with integrate-and-fire neurons, and associative synaptic connections between stages with a synaptic time constant of 10 ms. Through the implementation of continuous dynamics, we found latency differences in information retrieval of only 5 ms per layer when local excitation was absent and processing was purely feedforward. However, information latency differences increased significantly when non-associative local excitation was included. We also found that local recurrent excitation through associatively modified synapses can contribute significantly to processing in as little as 15 ms per layer, including the feedforward and local feedback processing. Moreover, and in contrast to purely feed-forward processing, the contribution of local recurrent feedback was useful and approximately this rapid even when retrieval was made difficult by noise. These findings suggest that cortical information processing can benefit from recurrent circuits when the allowed processing time per cortical area is at least 15 ms long.

Short-term memory in networks of dissociated cortical neurons.

PubMed

Dranias, Mark R; Ju, Han; Rajaram, Ezhilarasan; VanDongen, Antonius M J

2013-01-30

Short-term memory refers to the ability to store small amounts of stimulus-specific information for a short period of time. It is supported by both fading and hidden memory processes. Fading memory relies on recurrent activity patterns in a neuronal network, whereas hidden memory is encoded using synaptic mechanisms, such as facilitation, which persist even when neurons fall silent. We have used a novel computational and optogenetic approach to investigate whether these same memory processes hypothesized to support pattern recognition and short-term memory in vivo, exist in vitro. Electrophysiological activity was recorded from primary cultures of dissociated rat cortical neurons plated on multielectrode arrays. Cultures were transfected with ChannelRhodopsin-2 and optically stimulated using random dot stimuli. The pattern of neuronal activity resulting from this stimulation was analyzed using classification algorithms that enabled the identification of stimulus-specific memories. Fading memories for different stimuli, encoded in ongoing neural activity, persisted and could be distinguished from each other for as long as 1 s after stimulation was terminated. Hidden memories were detected by altered responses of neurons to additional stimulation, and this effect persisted longer than 1 s. Interestingly, network bursts seem to eliminate hidden memories. These results are similar to those that have been reported from similar experiments in vivo and demonstrate that mechanisms of information processing and short-term memory can be studied using cultured neuronal networks, thereby setting the stage for therapeutic applications using this platform.

Dendrites Enable a Robust Mechanism for Neuronal Stimulus Selectivity.

PubMed

Cazé, Romain D; Jarvis, Sarah; Foust, Amanda J; Schultz, Simon R

2017-09-01

Hearing, vision, touch: underlying all of these senses is stimulus selectivity, a robust information processing operation in which cortical neurons respond more to some stimuli than to others. Previous models assume that these neurons receive the highest weighted input from an ensemble encoding the preferred stimulus, but dendrites enable other possibilities. Nonlinear dendritic processing can produce stimulus selectivity based on the spatial distribution of synapses, even if the total preferred stimulus weight does not exceed that of nonpreferred stimuli. Using a multi-subunit nonlinear model, we demonstrate that stimulus selectivity can arise from the spatial distribution of synapses. We propose this as a general mechanism for information processing by neurons possessing dendritic trees. Moreover, we show that this implementation of stimulus selectivity increases the neuron's robustness to synaptic and dendritic failure. Importantly, our model can maintain stimulus selectivity for a larger range of loss of synapses or dendrites than an equivalent linear model. We then use a layer 2/3 biophysical neuron model to show that our implementation is consistent with two recent experimental observations: (1) one can observe a mixture of selectivities in dendrites that can differ from the somatic selectivity, and (2) hyperpolarization can broaden somatic tuning without affecting dendritic tuning. Our model predicts that an initially nonselective neuron can become selective when depolarized. In addition to motivating new experiments, the model's increased robustness to synapses and dendrites loss provides a starting point for fault-resistant neuromorphic chip development.

Color opponent receptive fields self-organize in a biophysical model of visual cortex via spike-timing dependent plasticity

PubMed Central

Eguchi, Akihiro; Neymotin, Samuel A.; Stringer, Simon M.

2014-01-01

Although many computational models have been proposed to explain orientation maps in primary visual cortex (V1), it is not yet known how similar clusters of color-selective neurons in macaque V1/V2 are connected and develop. In this work, we address the problem of understanding the cortical processing of color information with a possible mechanism of the development of the patchy distribution of color selectivity via computational modeling. Each color input is decomposed into a red, green, and blue representation and transmitted to the visual cortex via a simulated optic nerve in a luminance channel and red–green and blue–yellow opponent color channels. Our model of the early visual system consists of multiple topographically-arranged layers of excitatory and inhibitory neurons, with sparse intra-layer connectivity and feed-forward connectivity between layers. Layers are arranged based on anatomy of early visual pathways, and include a retina, lateral geniculate nucleus, and layered neocortex. Each neuron in the V1 output layer makes synaptic connections to neighboring neurons and receives the three types of signals in the different channels from the corresponding photoreceptor position. Synaptic weights are randomized and learned using spike-timing-dependent plasticity (STDP). After training with natural images, the neurons display heightened sensitivity to specific colors. Information-theoretic analysis reveals mutual information between particular stimuli and responses, and that the information reaches a maximum with fewer neurons in the higher layers, indicating that estimations of the input colors can be done using the output of fewer cells in the later stages of cortical processing. In addition, cells with similar color receptive fields form clusters. Analysis of spiking activity reveals increased firing synchrony between neurons when particular color inputs are presented or removed (ON-cell/OFF-cell). PMID:24659956

Neural dynamics and information representation in microcircuits of motor cortex.

PubMed

Tsubo, Yasuhiro; Isomura, Yoshikazu; Fukai, Tomoki

2013-01-01

The brain has to analyze and respond to external events that can change rapidly from time to time, suggesting that information processing by the brain may be essentially dynamic rather than static. The dynamical features of neural computation are of significant importance in motor cortex that governs the process of movement generation and learning. In this paper, we discuss these features based primarily on our recent findings on neural dynamics and information coding in the microcircuit of rat motor cortex. In fact, cortical neurons show a variety of dynamical behavior from rhythmic activity in various frequency bands to highly irregular spike firing. Of particular interest are the similarity and dissimilarity of the neuronal response properties in different layers of motor cortex. By conducting electrophysiological recordings in slice preparation, we report the phase response curves (PRCs) of neurons in different cortical layers to demonstrate their layer-dependent synchronization properties. We then study how motor cortex recruits task-related neurons in different layers for voluntary arm movements by simultaneous juxtacellular and multiunit recordings from behaving rats. The results suggest an interesting difference in the spectrum of functional activity between the superficial and deep layers. Furthermore, the task-related activities recorded from various layers exhibited power law distributions of inter-spike intervals (ISIs), in contrast to a general belief that ISIs obey Poisson or Gamma distributions in cortical neurons. We present a theoretical argument that this power law of in vivo neurons may represent the maximization of the entropy of firing rate with limited energy consumption of spike generation. Though further studies are required to fully clarify the functional implications of this coding principle, it may shed new light on information representations by neurons and circuits in motor cortex.

Understanding metal homeostasis in primary cultured neurons. Studies using single neuron subcellular and quantitative metallomics.

PubMed

Colvin, Robert A; Lai, Barry; Holmes, William R; Lee, Daewoo

2015-07-01

The purpose of this study was to demonstrate how single cell quantitative and subcellular metallomics inform us about both the spatial distribution and cellular mechanisms of metal buffering and homeostasis in primary cultured neurons from embryonic rat brain, which are often used as models of human disease involving metal dyshomeostasis. The present studies utilized synchrotron radiation X-ray fluorescence (SRXRF) and focused primarily on zinc and iron, two abundant metals in neurons that have been implicated in the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. Total single cell contents for calcium, iron, zinc, copper, manganese, and nickel were determined. Resting steady state zinc showed a diffuse distribution in both soma and processes, best defined by the mass profile of the neuron with an enrichment in the nucleus compared with the cytoplasm. Zinc buffering and homeostasis was studied using two modes of cellular zinc loading - transporter and ionophore (pyrithione) mediated. Single neuron zinc contents were shown to statistically significantly increase by either loading method - ionophore: 160 million to 7 billion; transporter 160 million to 280 million atoms per neuronal soma. The newly acquired and buffered zinc still showed a diffuse distribution. Soma and processes have about equal abilities to take up zinc via transporter mediated pathways. Copper levels are distributed diffusely as well, but are relatively higher in the processes relative to zinc levels. Prior studies have observed iron puncta in certain cell types, but others have not. In the present study, iron puncta were characterized in several primary neuronal types. The results show that iron puncta could be found in all neuronal types studied and can account for up to 50% of the total steady state content of iron in neuronal soma. Although other metals can be present in iron puncta, they are predominantly iron containing and do not appear to be associated with ferritin cages or transferrin receptor endosomes. The iron content and its distribution in puncta were similar in all neuron types studied including primary dopaminergic neurons. In summary, quantitative measurements of steady state metal levels in single primary cultured neurons made possible by SRXRF analyses provide unique information on the relative levels of each metal in neuronal soma and processes, subcellular location of zinc loads, and have confirmed and extended the characterization of heretofore poorly understood cytoplasmic iron puncta.

Modality distribution of sensory neurons in the feline caudate nucleus and the substantia nigra.

PubMed

Márkus, Zita; Eördegh, Gabriella; Paróczy, Zsuzsanna; Benedek, G; Nagy, A

2008-09-01

Despite extensive analysis of the motor functions of the basal ganglia and the fact that multisensory information processing appears critical for the execution of their behavioral action, little is known concerning the sensory functions of the caudate nucleus (CN) and the substantia nigra (SN). In the present study, we set out to describe the sensory modality distribution and to determine the proportions of multisensory units within the CN and the SN. The separate single sensory modality tests demonstrated that a majority of the neurons responded to only one modality, so that they seemed to be unimodal. In contrast with these findings, a large proportion of these neurons exhibited significant multisensory cross-modal interactions. Thus, these neurons should also be classified as multisensory. Our results suggest that a surprisingly high proportion of sensory neurons in the basal ganglia are multisensory, and demonstrate that an analysis without a consideration of multisensory cross-modal interactions may strongly underrepresent the number of multisensory units. We conclude that a majority of the sensory neurons in the CN and SN process multisensory information and only a minority of these units are clearly unimodal.

Reference frames for spatial frequency in face representation differ in the temporal visual cortex and amygdala.

PubMed

Inagaki, Mikio; Fujita, Ichiro

2011-07-13

Social communication in nonhuman primates and humans is strongly affected by facial information from other individuals. Many cortical and subcortical brain areas are known to be involved in processing facial information. However, how the neural representation of faces differs across different brain areas remains unclear. Here, we demonstrate that the reference frame for spatial frequency (SF) tuning of face-responsive neurons differs in the temporal visual cortex and amygdala in monkeys. Consistent with psychophysical properties for face recognition, temporal cortex neurons were tuned to image-based SFs (cycles/image) and showed viewing distance-invariant representation of face patterns. On the other hand, many amygdala neurons were influenced by retina-based SFs (cycles/degree), a characteristic that is useful for social distance computation. The two brain areas also differed in the luminance contrast sensitivity of face-responsive neurons; amygdala neurons sharply reduced their responses to low luminance contrast images, while temporal cortex neurons maintained the level of their responses. From these results, we conclude that different types of visual processing in the temporal visual cortex and the amygdala contribute to the construction of the neural representations of faces.

Memory formation orchestrates the wiring of adult-born hippocampal neurons into brain circuits.

PubMed

Petsophonsakul, Petnoi; Richetin, Kevin; Andraini, Trinovita; Roybon, Laurent; Rampon, Claire

2017-08-01

During memory formation, structural rearrangements of dendritic spines provide a mean to durably modulate synaptic connectivity within neuronal networks. New neurons generated throughout the adult life in the dentate gyrus of the hippocampus contribute to learning and memory. As these neurons become incorporated into the network, they generate huge numbers of new connections that modify hippocampal circuitry and functioning. However, it is yet unclear as to how the dynamic process of memory formation influences their synaptic integration into neuronal circuits. New memories are established according to a multistep process during which new information is first acquired and then consolidated to form a stable memory trace. Upon recall, memory is transiently destabilized and vulnerable to modification. Using contextual fear conditioning, we found that learning was associated with an acceleration of dendritic spines formation of adult-born neurons, and that spine connectivity becomes strengthened after memory consolidation. Moreover, we observed that afferent connectivity onto adult-born neurons is enhanced after memory retrieval, while extinction training induces a change of spine shapes. Together, these findings reveal that the neuronal activity supporting memory processes strongly influences the structural dendritic integration of adult-born neurons into pre-existing neuronal circuits. Such change of afferent connectivity is likely to impact the overall wiring of hippocampal network, and consequently, to regulate hippocampal function.

Time-Warp–Invariant Neuronal Processing

PubMed Central

Gütig, Robert; Sompolinsky, Haim

2009-01-01

Fluctuations in the temporal durations of sensory signals constitute a major source of variability within natural stimulus ensembles. The neuronal mechanisms through which sensory systems can stabilize perception against such fluctuations are largely unknown. An intriguing instantiation of such robustness occurs in human speech perception, which relies critically on temporal acoustic cues that are embedded in signals with highly variable duration. Across different instances of natural speech, auditory cues can undergo temporal warping that ranges from 2-fold compression to 2-fold dilation without significant perceptual impairment. Here, we report that time-warp–invariant neuronal processing can be subserved by the shunting action of synaptic conductances that automatically rescales the effective integration time of postsynaptic neurons. We propose a novel spike-based learning rule for synaptic conductances that adjusts the degree of synaptic shunting to the temporal processing requirements of a given task. Applying this general biophysical mechanism to the example of speech processing, we propose a neuronal network model for time-warp–invariant word discrimination and demonstrate its excellent performance on a standard benchmark speech-recognition task. Our results demonstrate the important functional role of synaptic conductances in spike-based neuronal information processing and learning. The biophysics of temporal integration at neuronal membranes can endow sensory pathways with powerful time-warp–invariant computational capabilities. PMID:19582146

[Long-term memory, neurogenesis and novelty signal].

PubMed

Sokolova, E N; Nezlina, N I

2003-01-01

In accordance with the advanced hypothesis the long-term memory is a collection of "gnostic units" selectively tuned to experienced events. The long-term memory is continuously supplemented by new neurons differentiated from stem cells during neurogenesis (particularly, in adults). The transformation of neuronal progenitors into event-selective gnostic units is accomplished with participation of hippocampal "novelty neurons" emphasizing information inputs to be stored in the long-term memory. The formation of the gnostic units is preceded by informational processes occurring in the ventral ("what?") and dorsal ("where?") systems. The formation of a new gnostic unit selectively tuned to a particular event is a result of combination of feature-detector excitation and novelty signal generated by hippocampal novelty neurons.

Delayed excitatory and inhibitory feedback shape neural information transmission

NASA Astrophysics Data System (ADS)

Chacron, Maurice J.; Longtin, André; Maler, Leonard

2005-11-01

Feedback circuitry with conduction and synaptic delays is ubiquitous in the nervous system. Yet the effects of delayed feedback on sensory processing of natural signals are poorly understood. This study explores the consequences of delayed excitatory and inhibitory feedback inputs on the processing of sensory information. We show, through numerical simulations and theory, that excitatory and inhibitory feedback can alter the firing frequency response of stochastic neurons in opposite ways by creating dynamical resonances, which in turn lead to information resonances (i.e., increased information transfer for specific ranges of input frequencies). The resonances are created at the expense of decreased information transfer in other frequency ranges. Using linear response theory for stochastically firing neurons, we explain how feedback signals shape the neural transfer function for a single neuron as a function of network size. We also find that balanced excitatory and inhibitory feedback can further enhance information tuning while maintaining a constant mean firing rate. Finally, we apply this theory to in vivo experimental data from weakly electric fish in which the feedback loop can be opened. We show that it qualitatively predicts the observed effects of inhibitory feedback. Our study of feedback excitation and inhibition reveals a possible mechanism by which optimal processing may be achieved over selected frequency ranges.

A critical period for experience-dependent remodeling of adult-born neuron connectivity.

PubMed

Bergami, Matteo; Masserdotti, Giacomo; Temprana, Silvio G; Motori, Elisa; Eriksson, Therese M; Göbel, Jana; Yang, Sung Min; Conzelmann, Karl-Klaus; Schinder, Alejandro F; Götz, Magdalena; Berninger, Benedikt

2015-02-18

Neurogenesis in the dentate gyrus (DG) of the adult hippocampus is a process regulated by experience. To understand whether experience also modifies the connectivity of new neurons, we systematically investigated changes in their innervation following environmental enrichment (EE). We found that EE exposure between 2-6 weeks following neuron birth, rather than merely increasing the number of new neurons, profoundly affected their pattern of monosynaptic inputs. Both local innervation by interneurons and to even greater degree long-distance innervation by cortical neurons were markedly enhanced. Furthermore, following EE, new neurons received inputs from CA3 and CA1 inhibitory neurons that were rarely observed under control conditions. While EE-induced changes in inhibitory innervation were largely transient, cortical innervation remained increased after returning animals to control conditions. Our findings demonstrate an unprecedented experience-dependent reorganization of connections impinging onto adult-born neurons, which is likely to have important impact on their contribution to hippocampal information processing. Copyright © 2015 Elsevier Inc. All rights reserved.

Surfing a spike wave down the ventral stream.

PubMed

VanRullen, Rufin; Thorpe, Simon J

2002-10-01

Numerous theories of neural processing, often motivated by experimental observations, have explored the computational properties of neural codes based on the absolute or relative timing of spikes in spike trains. Spiking neuron models and theories however, as well as their experimental counterparts, have generally been limited to the simulation or observation of isolated neurons, isolated spike trains, or reduced neural populations. Such theories would therefore seem inappropriate to capture the properties of a neural code relying on temporal spike patterns distributed across large neuronal populations. Here we report a range of computer simulations and theoretical considerations that were designed to explore the possibilities of one such code and its relevance for visual processing. In a unified framework where the relation between stimulus saliency and spike relative timing plays the central role, we describe how the ventral stream of the visual system could process natural input scenes and extract meaningful information, both rapidly and reliably. The first wave of spikes generated in the retina in response to a visual stimulation carries information explicitly in its spatio-temporal structure: the most salient information is represented by the first spikes over the population. This spike wave, propagating through a hierarchy of visual areas, is regenerated at each processing stage, where its temporal structure can be modified by (i). the selectivity of the cortical neurons, (ii). lateral interactions and (iii). top-down attentional influences from higher order cortical areas. The resulting model could account for the remarkable efficiency and rapidity of processing observed in the primate visual system.

Neuronal Representation of Social Information in the Medial Amygdala of Awake Behaving Mice.

PubMed

Li, Ying; Mathis, Alexander; Grewe, Benjamin F; Osterhout, Jessica A; Ahanonu, Biafra; Schnitzer, Mark J; Murthy, Venkatesh N; Dulac, Catherine

2017-11-16

The medial amygdala (MeA) plays a critical role in processing species- and sex-specific signals that trigger social and defensive behaviors. However, the principles by which this deep brain structure encodes social information is poorly understood. We used a miniature microscope to image the Ca 2+ dynamics of large neural ensembles in awake behaving mice and tracked the responses of MeA neurons over several months. These recordings revealed spatially intermingled subsets of MeA neurons with distinct temporal dynamics. The encoding of social information in the MeA differed between males and females and relied on information from both individual cells and neuronal populations. By performing long-term Ca 2+ imaging across different social contexts, we found that sexual experience triggers lasting and sex-specific changes in MeA activity, which, in males, involve signaling by oxytocin. These findings reveal basic principles underlying the brain's representation of social information and its modulation by intrinsic and extrinsic factors. Copyright © 2017 Elsevier Inc. All rights reserved.

Inactivation of basolateral amygdala specifically eliminates palatability-related information in cortical sensory responses.

PubMed

Piette, Caitlin E; Baez-Santiago, Madelyn A; Reid, Emily E; Katz, Donald B; Moran, Anan

2012-07-18

Evidence indirectly implicates the amygdala as the primary processor of emotional information used by cortex to drive appropriate behavioral responses to stimuli. Taste provides an ideal system with which to test this hypothesis directly, as neurons in both basolateral amygdala (BLA) and gustatory cortex (GC)-anatomically interconnected nodes of the gustatory system-code the emotional valence of taste stimuli (i.e., palatability), in firing rate responses that progress similarly through "epochs." The fact that palatability-related firing appears one epoch earlier in BLA than GC is broadly consistent with the hypothesis that such information may propagate from the former to the latter. Here, we provide evidence supporting this hypothesis, assaying taste responses in small GC single-neuron ensembles before, during, and after temporarily inactivating BLA in awake rats. BLA inactivation (BLAx) changed responses in 98% of taste-responsive GC neurons, altering the entirety of every taste response in many neurons. Most changes involved reductions in firing rate, but regardless of the direction of change, the effect of BLAx was epoch-specific: while firing rates were changed, the taste specificity of responses remained stable; information about taste palatability, however, which normally resides in the "Late" epoch, was reduced in magnitude across the entire GC sample and outright eliminated in most neurons. Only in the specific minority of neurons for which BLAx enhanced responses did palatability specificity survive undiminished. Our data therefore provide direct evidence that BLA is a necessary component of GC gustatory processing, and that cortical palatability processing in particular is, in part, a function of BLA activity.

Inactivation of basolateral amygdala specifically eliminates palatability-related information in cortical sensory responses

PubMed Central

Piette, Caitlin E.; Baez-Santiago, Madelyn A.; Reid, Emily E.; Katz, Donald B.; Moran, Anan

2012-01-01

Evidence indirectly implicates the amygdala as the primary processor of emotional information used by cortex to drive appropriate behavioral responses to stimuli. Taste provides an ideal system with which to test this hypothesis directly, as neurons in both basolateral amygdala (BLA) and gustatory cortex (GC)—anatomically interconnected nodes of the gustatory system—code the emotional valence of taste stimuli (i.e., palatability), in firing rate responses that progress similarly through “epochs.” The fact that palatability-related firing appears one epoch earlier in BLA than GC is broadly consistent with the hypothesis that such information may propagate from the former to the latter. Here, we provide evidence supporting this hypothesis, assaying taste responses in small GC single-neuron ensembles before, during and after temporarily inactivating BLA (BLAx) in awake rats. BLAx changed responses in 98% of taste-responsive GC neurons, altering the entirety of every taste response in many neurons. Most changes involved reductions in firing rate, but regardless of the direction of change, the effect of BLAx was epoch-specific: while firing rates were changed, the taste-specificity of responses remained stable; information about taste palatability, however, which normally resides in the “Late” epoch, was reduced in magnitude across the entire GC sample and outright eliminated in most neurons. Only in the specific minority of neurons for which BLAx enhanced responses did palatability-specificity survive undiminished. Our data therefore provide direct evidence that BLA is a necessary component of GC gustatory processing, and that cortical palatability processing in particular is, in part, a function of BLA activity. PMID:22815512

Self-Organized Information Processing in Neuronal Networks: Replacing Layers in Deep Networks by Dynamics

NASA Astrophysics Data System (ADS)

Kirst, Christoph

It is astonishing how the sub-parts of a brain co-act to produce coherent behavior. What are mechanism that coordinate information processing and communication and how can those be changed flexibly in order to cope with variable contexts? Here we show that when information is encoded in the deviations around a collective dynamical reference state of a recurrent network the propagation of these fluctuations is strongly dependent on precisely this underlying reference. Information here 'surfs' on top of the collective dynamics and switching between states enables fast and flexible rerouting of information. This in turn affects local processing and consequently changes in the global reference dynamics that re-regulate the distribution of information. This provides a generic mechanism for self-organized information processing as we demonstrate with an oscillatory Hopfield network that performs contextual pattern recognition. Deep neural networks have proven to be very successful recently. Here we show that generating information channels via collective reference dynamics can effectively compress a deep multi-layer architecture into a single layer making this mechanism a promising candidate for the organization of information processing in biological neuronal networks.

Quantum-like model of processing of information in the brain based on classical electromagnetic field.

PubMed

Khrennikov, Andrei

2011-09-01

We propose a model of quantum-like (QL) processing of mental information. This model is based on quantum information theory. However, in contrast to models of "quantum physical brain" reducing mental activity (at least at the highest level) to quantum physical phenomena in the brain, our model matches well with the basic neuronal paradigm of the cognitive science. QL information processing is based (surprisingly) on classical electromagnetic signals induced by joint activity of neurons. This novel approach to quantum information is based on representation of quantum mechanics as a version of classical signal theory which was recently elaborated by the author. The brain uses the QL representation (QLR) for working with abstract concepts; concrete images are described by classical information theory. Two processes, classical and QL, are performed parallely. Moreover, information is actively transmitted from one representation to another. A QL concept given in our model by a density operator can generate a variety of concrete images given by temporal realizations of the corresponding (Gaussian) random signal. This signal has the covariance operator coinciding with the density operator encoding the abstract concept under consideration. The presence of various temporal scales in the brain plays the crucial role in creation of QLR in the brain. Moreover, in our model electromagnetic noise produced by neurons is a source of superstrong QL correlations between processes in different spatial domains in the brain; the binding problem is solved on the QL level, but with the aid of the classical background fluctuations. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Dysregulation of neural calcium signaling in Alzheimer disease, bipolar disorder and schizophrenia

PubMed Central

Berridge, Michael J.

2013-01-01

Neurons have highly developed Ca2+ signaling systems responsible for regulating a large number of neural functions such as the control of brain rhythms, information processing and the changes in synaptic plasticity that underpin learning and memory. The tonic excitatory drive, which is activated by the ascending arousal system, is particularly important for processes such as sensory perception, cognition and consciousness. The Ca2+ signaling pathway is a key component of this arousal system that regulates the neuronal excitability responsible for controlling the neural brain rhythms required for information processing and cognition. Dysregulation of the Ca2+ signaling pathway responsible for many of these neuronal processes has been implicated in the development of some of the major neural diseases in man such as Alzheimer disease, bipolar disorder and schizophrenia. Various treatments, which are known to act by reducing the activity of Ca2+ signaling, have proved successful in alleviating the symptoms of some of these neural diseases. PMID:22895098

A Neural Correlate of Predicted and Actual Reward-Value Information in Monkey Pedunculopontine Tegmental and Dorsal Raphe Nucleus during Saccade Tasks

PubMed Central

Okada, Ken-ichi; Nakamura, Kae; Kobayashi, Yasushi

2011-01-01

Dopamine, acetylcholine, and serotonin, the main modulators of the central nervous system, have been proposed to play important roles in the execution of movement, control of several forms of attentional behavior, and reinforcement learning. While the response pattern of midbrain dopaminergic neurons and its specific role in reinforcement learning have been revealed, the role of the other neuromodulators remains rather elusive. Here, we review our recent studies using extracellular recording from neurons in the pedunculopontine tegmental nucleus, where many cholinergic neurons exist, and the dorsal raphe nucleus, where many serotonergic neurons exist, while monkeys performed eye movement tasks to obtain different reward values. The firing patterns of these neurons are often tonic throughout the task period, while dopaminergic neurons exhibited a phasic activity pattern to the task event. The different modulation patterns, together with the activity of dopaminergic neurons, reveal dynamic information processing between these different neuromodulator systems. PMID:22013541

Neuronal responses to face-like stimuli in the monkey pulvinar.

PubMed

Nguyen, Minh Nui; Hori, Etsuro; Matsumoto, Jumpei; Tran, Anh Hai; Ono, Taketoshi; Nishijo, Hisao

2013-01-01

The pulvinar nuclei appear to function as the subcortical visual pathway that bypasses the striate cortex, rapidly processing coarse facial information. We investigated responses from monkey pulvinar neurons during a delayed non-matching-to-sample task, in which monkeys were required to discriminate five categories of visual stimuli [photos of faces with different gaze directions, line drawings of faces, face-like patterns (three dark blobs on a bright oval), eye-like patterns and simple geometric patterns]. Of 401 neurons recorded, 165 neurons responded differentially to the visual stimuli. These visual responses were suppressed by scrambling the images. Although these neurons exhibited a broad response latency distribution, face-like patterns elicited responses with the shortest latencies (approximately 50 ms). Multidimensional scaling analysis indicated that the pulvinar neurons could specifically encode face-like patterns during the first 50-ms period after stimulus onset and classify the stimuli into one of the five different categories during the next 50-ms period. The amount of stimulus information conveyed by the pulvinar neurons and the number of stimulus-differentiating neurons were consistently higher during the second 50-ms period than during the first 50-ms period. These results suggest that responsiveness to face-like patterns during the first 50-ms period might be attributed to ascending inputs from the superior colliculus or the retina, while responsiveness to the five different stimulus categories during the second 50-ms period might be mediated by descending inputs from cortical regions. These findings provide neurophysiological evidence for pulvinar involvement in social cognition and, specifically, rapid coarse facial information processing. © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Rich-Club Organization in Effective Connectivity among Cortical Neurons.

PubMed

Nigam, Sunny; Shimono, Masanori; Ito, Shinya; Yeh, Fang-Chin; Timme, Nicholas; Myroshnychenko, Maxym; Lapish, Christopher C; Tosi, Zachary; Hottowy, Pawel; Smith, Wesley C; Masmanidis, Sotiris C; Litke, Alan M; Sporns, Olaf; Beggs, John M

2016-01-20

The performance of complex networks, like the brain, depends on how effectively their elements communicate. Despite the importance of communication, it is virtually unknown how information is transferred in local cortical networks, consisting of hundreds of closely spaced neurons. To address this, it is important to record simultaneously from hundreds of neurons at a spacing that matches typical axonal connection distances, and at a temporal resolution that matches synaptic delays. We used a 512-electrode array (60 μm spacing) to record spontaneous activity at 20 kHz from up to 500 neurons simultaneously in slice cultures of mouse somatosensory cortex for 1 h at a time. We applied a previously validated version of transfer entropy to quantify information transfer. Similar to in vivo reports, we found an approximately lognormal distribution of firing rates. Pairwise information transfer strengths also were nearly lognormally distributed, similar to reports of synaptic strengths. Some neurons transferred and received much more information than others, which is consistent with previous predictions. Neurons with the highest outgoing and incoming information transfer were more strongly connected to each other than chance, thus forming a "rich club." We found similar results in networks recorded in vivo from rodent cortex, suggesting the generality of these findings. A rich-club structure has been found previously in large-scale human brain networks and is thought to facilitate communication between cortical regions. The discovery of a small, but information-rich, subset of neurons within cortical regions suggests that this population will play a vital role in communication, learning, and memory. Significance statement: Many studies have focused on communication networks between cortical brain regions. In contrast, very few studies have examined communication networks within a cortical region. This is the first study to combine such a large number of neurons (several hundred at a time) with such high temporal resolution (so we can know the direction of communication between neurons) for mapping networks within cortex. We found that information was not transferred equally through all neurons. Instead, ∼70% of the information passed through only 20% of the neurons. Network models suggest that this highly concentrated pattern of information transfer would be both efficient and robust to damage. Therefore, this work may help in understanding how the cortex processes information and responds to neurodegenerative diseases. Copyright © 2016 Nigam et al.

Rich-Club Organization in Effective Connectivity among Cortical Neurons

PubMed Central

Shimono, Masanori; Ito, Shinya; Yeh, Fang-Chin; Timme, Nicholas; Myroshnychenko, Maxym; Lapish, Christopher C.; Tosi, Zachary; Hottowy, Pawel; Smith, Wesley C.; Masmanidis, Sotiris C.; Litke, Alan M.; Sporns, Olaf; Beggs, John M.

2016-01-01

The performance of complex networks, like the brain, depends on how effectively their elements communicate. Despite the importance of communication, it is virtually unknown how information is transferred in local cortical networks, consisting of hundreds of closely spaced neurons. To address this, it is important to record simultaneously from hundreds of neurons at a spacing that matches typical axonal connection distances, and at a temporal resolution that matches synaptic delays. We used a 512-electrode array (60 μm spacing) to record spontaneous activity at 20 kHz from up to 500 neurons simultaneously in slice cultures of mouse somatosensory cortex for 1 h at a time. We applied a previously validated version of transfer entropy to quantify information transfer. Similar to in vivo reports, we found an approximately lognormal distribution of firing rates. Pairwise information transfer strengths also were nearly lognormally distributed, similar to reports of synaptic strengths. Some neurons transferred and received much more information than others, which is consistent with previous predictions. Neurons with the highest outgoing and incoming information transfer were more strongly connected to each other than chance, thus forming a “rich club.” We found similar results in networks recorded in vivo from rodent cortex, suggesting the generality of these findings. A rich-club structure has been found previously in large-scale human brain networks and is thought to facilitate communication between cortical regions. The discovery of a small, but information-rich, subset of neurons within cortical regions suggests that this population will play a vital role in communication, learning, and memory. SIGNIFICANCE STATEMENT Many studies have focused on communication networks between cortical brain regions. In contrast, very few studies have examined communication networks within a cortical region. This is the first study to combine such a large number of neurons (several hundred at a time) with such high temporal resolution (so we can know the direction of communication between neurons) for mapping networks within cortex. We found that information was not transferred equally through all neurons. Instead, ∼70% of the information passed through only 20% of the neurons. Network models suggest that this highly concentrated pattern of information transfer would be both efficient and robust to damage. Therefore, this work may help in understanding how the cortex processes information and responds to neurodegenerative diseases. PMID:26791200

An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites

PubMed Central

JADI, MONIKA P.; BEHABADI, BARDIA F.; POLEG-POLSKY, ALON; SCHILLER, JACKIE; MEL, BARTLETT W.

2014-01-01

In pursuit of the goal to understand and eventually reproduce the diverse functions of the brain, a key challenge lies in reverse engineering the peculiar biology-based “technology” that underlies the brain’s remarkable ability to process and store information. The basic building block of the nervous system is the nerve cell, or “neuron,” yet after more than 100 years of neurophysiological study and 60 years of modeling, the information processing functions of individual neurons, and the parameters that allow them to engage in so many different types of computation (sensory, motor, mnemonic, executive, etc.) remain poorly understood. In this paper, we review both historical and recent findings that have led to our current understanding of the analog spatial processing capabilities of dendrites, the major input structures of neurons, with a focus on the principal cell type of the neocortex and hippocampus, the pyramidal neuron (PN). We encapsulate our current understanding of PN dendritic integration in an abstract layered model whose spatially sensitive branch-subunits compute multidimensional sigmoidal functions. Unlike the 1-D sigmoids found in conventional neural network models, multidimensional sigmoids allow the cell to implement a rich spectrum of nonlinear modulation effects directly within their dendritic trees. PMID:25554708

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks

PubMed Central

de Santos-Sierra, Daniel; Sanchez-Jimenez, Abel; Garcia-Vellisca, Mariano A.; Navas, Adrian; Villacorta-Atienza, Jose A.

2015-01-01

Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh–Rose neurons. PMID:26648863

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks.

PubMed

de Santos-Sierra, Daniel; Sanchez-Jimenez, Abel; Garcia-Vellisca, Mariano A; Navas, Adrian; Villacorta-Atienza, Jose A

2015-01-01

Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

NeuronMetrics: Software for Semi-Automated Processing of Cultured-Neuron Images

PubMed Central

Narro, Martha L.; Yang, Fan; Kraft, Robert; Wenk, Carola; Efrat, Alon; Restifo, Linda L.

2007-01-01

Using primary cell culture to screen for changes in neuronal morphology requires specialized analysis software. We developed NeuronMetrics™ for semi-automated, quantitative analysis of two-dimensional (2D) images of fluorescently labeled cultured neurons. It skeletonizes the neuron image using two complementary image-processing techniques, capturing fine terminal neurites with high fidelity. An algorithm was devised to span wide gaps in the skeleton. NeuronMetrics uses a novel strategy based on geometric features called faces to extract a branch-number estimate from complex arbors with numerous neurite-to-neurite contacts, without creating a precise, contact-free representation of the neurite arbor. It estimates total neurite length, branch number, primary neurite number, territory (the area of the convex polygon bounding the skeleton and cell body), and Polarity Index (a measure of neuronal polarity). These parameters provide fundamental information about the size and shape of neurite arbors, which are critical factors for neuronal function. NeuronMetrics streamlines optional manual tasks such as removing noise, isolating the largest primary neurite, and correcting length for self-fasciculating neurites. Numeric data are output in a single text file, readily imported into other applications for further analysis. Written as modules for ImageJ, NeuronMetrics provides practical analysis tools that are easy to use and support batch processing. Depending on the need for manual intervention, processing time for a batch of ~60 2D images is 1.0–2.5 hours, from a folder of images to a table of numeric data. NeuronMetrics’ output accelerates the quantitative detection of mutations and chemical compounds that alter neurite morphology in vitro, and will contribute to the use of cultured neurons for drug discovery. PMID:17270152

NeuronMetrics: software for semi-automated processing of cultured neuron images.

PubMed

Narro, Martha L; Yang, Fan; Kraft, Robert; Wenk, Carola; Efrat, Alon; Restifo, Linda L

2007-03-23

Using primary cell culture to screen for changes in neuronal morphology requires specialized analysis software. We developed NeuronMetrics for semi-automated, quantitative analysis of two-dimensional (2D) images of fluorescently labeled cultured neurons. It skeletonizes the neuron image using two complementary image-processing techniques, capturing fine terminal neurites with high fidelity. An algorithm was devised to span wide gaps in the skeleton. NeuronMetrics uses a novel strategy based on geometric features called faces to extract a branch number estimate from complex arbors with numerous neurite-to-neurite contacts, without creating a precise, contact-free representation of the neurite arbor. It estimates total neurite length, branch number, primary neurite number, territory (the area of the convex polygon bounding the skeleton and cell body), and Polarity Index (a measure of neuronal polarity). These parameters provide fundamental information about the size and shape of neurite arbors, which are critical factors for neuronal function. NeuronMetrics streamlines optional manual tasks such as removing noise, isolating the largest primary neurite, and correcting length for self-fasciculating neurites. Numeric data are output in a single text file, readily imported into other applications for further analysis. Written as modules for ImageJ, NeuronMetrics provides practical analysis tools that are easy to use and support batch processing. Depending on the need for manual intervention, processing time for a batch of approximately 60 2D images is 1.0-2.5 h, from a folder of images to a table of numeric data. NeuronMetrics' output accelerates the quantitative detection of mutations and chemical compounds that alter neurite morphology in vitro, and will contribute to the use of cultured neurons for drug discovery.

Electrophysiological models of neural processing.

PubMed

Nelson, Mark E

2011-01-01

The brain is an amazing information processing system that allows organisms to adaptively monitor and control complex dynamic interactions with their environment across multiple spatial and temporal scales. Mathematical modeling and computer simulation techniques have become essential tools in understanding diverse aspects of neural processing ranging from sub-millisecond temporal coding in the sound localization circuity of barn owls to long-term memory storage and retrieval in humans that can span decades. The processing capabilities of individual neurons lie at the core of these models, with the emphasis shifting upward and downward across different levels of biological organization depending on the nature of the questions being addressed. This review provides an introduction to the techniques for constructing biophysically based models of individual neurons and local networks. Topics include Hodgkin-Huxley-type models of macroscopic membrane currents, Markov models of individual ion-channel currents, compartmental models of neuronal morphology, and network models involving synaptic interactions among multiple neurons.

Synaptic plasticity, neural circuits, and the emerging role of altered short-term information processing in schizophrenia

PubMed Central

Crabtree, Gregg W.; Gogos, Joseph A.

2014-01-01

Synaptic plasticity alters the strength of information flow between presynaptic and postsynaptic neurons and thus modifies the likelihood that action potentials in a presynaptic neuron will lead to an action potential in a postsynaptic neuron. As such, synaptic plasticity and pathological changes in synaptic plasticity impact the synaptic computation which controls the information flow through the neural microcircuits responsible for the complex information processing necessary to drive adaptive behaviors. As current theories of neuropsychiatric disease suggest that distinct dysfunctions in neural circuit performance may critically underlie the unique symptoms of these diseases, pathological alterations in synaptic plasticity mechanisms may be fundamental to the disease process. Here we consider mechanisms of both short-term and long-term plasticity of synaptic transmission and their possible roles in information processing by neural microcircuits in both health and disease. As paradigms of neuropsychiatric diseases with strongly implicated risk genes, we discuss the findings in schizophrenia and autism and consider the alterations in synaptic plasticity and network function observed in both human studies and genetic mouse models of these diseases. Together these studies have begun to point toward a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders (ASDs) may be due to a combination of both short-term and long-term synaptic plasticity alterations. PMID:25505409

Dynamics of Phosphoinositide-Dependent Signaling in Sympathetic Neurons

PubMed Central

Kruse, Martin; Vivas, Oscar; Traynor-Kaplan, Alexis

2016-01-01

In neurons, loss of plasma membrane phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2] leads to a decrease in exocytosis and changes in electrical excitability. Restoration of PI(4,5)P2 levels after phospholipase C activation is therefore essential for a return to basal neuronal activity. However, the dynamics of phosphoinositide metabolism have not been analyzed in neurons. We measured dynamic changes of PI(4,5)P2, phosphatidylinositol 4-phosphate, diacylglycerol, inositol 1,4,5-trisphosphate, and Ca2+ upon muscarinic stimulation in sympathetic neurons from adult male Sprague-Dawley rats with electrophysiological and optical approaches. We used this kinetic information to develop a quantitative description of neuronal phosphoinositide metabolism. The measurements and analysis show and explain faster synthesis of PI(4,5)P2 in sympathetic neurons than in electrically nonexcitable tsA201 cells. They can be used to understand dynamic effects of receptor-mediated phospholipase C activation on excitability and other PI(4,5)P2-dependent processes in neurons. SIGNIFICANCE STATEMENT Phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2] is a minor phospholipid in the cytoplasmic leaflet of the plasma membrane. Depletion of PI(4,5)P2 via phospholipase C-mediated hydrolysis leads to a decrease in exocytosis and alters electrical excitability in neurons. Restoration of PI(4,5)P2 is essential for a return to basal neuronal activity. However, the dynamics of phosphoinositide metabolism have not been analyzed in neurons. We studied the dynamics of phosphoinositide metabolism in sympathetic neurons upon muscarinic stimulation and used the kinetic information to develop a quantitative description of neuronal phosphoinositide metabolism. The measurements and analysis show a several-fold faster synthesis of PI(4,5)P2 in sympathetic neurons than in an electrically nonexcitable cell line, and provide a framework for future studies of PI(4,5)P2-dependent processes in neurons. PMID:26818524

Large-scale two-photon imaging revealed super-sparse population codes in the V1 superficial layer of awake monkeys.

PubMed

Tang, Shiming; Zhang, Yimeng; Li, Zhihao; Li, Ming; Liu, Fang; Jiang, Hongfei; Lee, Tai Sing

2018-04-26

One general principle of sensory information processing is that the brain must optimize efficiency by reducing the number of neurons that process the same information. The sparseness of the sensory representations in a population of neurons reflects the efficiency of the neural code. Here, we employ large-scale two-photon calcium imaging to examine the responses of a large population of neurons within the superficial layers of area V1 with single-cell resolution, while simultaneously presenting a large set of natural visual stimuli, to provide the first direct measure of the population sparseness in awake primates. The results show that only 0.5% of neurons respond strongly to any given natural image - indicating a ten-fold increase in the inferred sparseness over previous measurements. These population activities are nevertheless necessary and sufficient to discriminate visual stimuli with high accuracy, suggesting that the neural code in the primary visual cortex is both super-sparse and highly efficient. © 2018, Tang et al.

Simulating spinal border cells and cerebellar granule cells under locomotion--a case study of spinocerebellar information processing.

PubMed

Spanne, Anton; Geborek, Pontus; Bengtsson, Fredrik; Jörntell, Henrik

2014-01-01

The spinocerebellar systems are essential for the brain in the performance of coordinated movements, but our knowledge about the spinocerebellar interactions is very limited. Recently, several crucial pieces of information have been acquired for the spinal border cell (SBC) component of the ventral spinocerebellar tract (VSCT), as well as the effects of SBC mossy fiber activation in granule cells of the cerebellar cortex. SBCs receive monosynaptic input from the reticulospinal tract (RST), which is an important driving system under locomotion, and disynaptic inhibition from Ib muscle afferents. The patterns of activity of RST neurons and Ib afferents under locomotion are known. The activity of VSCT neurons under fictive locomotion, i.e. without sensory feedback, is also known, but there is little information on how these neurons behave under actual locomotion and for cerebellar granule cells receiving SBC input this is completely unknown. But the available information makes it possible to simulate the interactions between the spinal and cerebellar neuronal circuitries with a relatively large set of biological constraints. Using a model of the various neuronal elements and the network they compose, we simulated the modulation of the SBCs and their target granule cells under locomotion and hence generated testable predictions of their general pattern of modulation under this condition. This particular system offers a unique opportunity to simulate these interactions with a limited number of assumptions, which helps making the model biologically plausible. Similar principles of information processing may be expected to apply to all spinocerebellar systems.

Optogenetic Activation of the Sensorimotor Cortex Reveals "Local Inhibitory and Global Excitatory" Inputs to the Basal Ganglia.

PubMed

Ozaki, Mitsunori; Sano, Hiromi; Sato, Shigeki; Ogura, Mitsuhiro; Mushiake, Hajime; Chiken, Satomi; Nakao, Naoyuki; Nambu, Atsushi

2017-12-01

To understand how information from different cortical areas is integrated and processed through the cortico-basal ganglia pathways, we used optogenetics to systematically stimulate the sensorimotor cortex and examined basal ganglia activity. We utilized Thy1-ChR2-YFP transgenic mice, in which channelrhodopsin 2 is robustly expressed in layer V pyramidal neurons. We applied light spots to the sensorimotor cortex in a grid pattern and examined neuronal responses in the globus pallidus (GP) and entopeduncular nucleus (EPN), which are the relay and output nuclei of the basal ganglia, respectively. Light stimulation typically induced a triphasic response composed of early excitation, inhibition, and late excitation in GP/EPN neurons. Other response patterns lacking 1 or 2 of the components were also observed. The distribution of the cortical sites whose stimulation induced a triphasic response was confined, whereas stimulation of the large surrounding areas induced early and late excitation without inhibition. Our results suggest that cortical inputs to the GP/EPN are organized in a "local inhibitory and global excitatory" manner. Such organization seems to be the neuronal basis for information processing through the cortico-basal ganglia pathways, that is, releasing and terminating necessary information at an appropriate timing, while simultaneously suppressing other unnecessary information. © The Author 2017. Published by Oxford University Press.

Cortical Neural Computation by Discrete Results Hypothesis

PubMed Central

Castejon, Carlos; Nuñez, Angel

2016-01-01

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called “Discrete Results” (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of “Discrete Results” is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel “Discrete Results” concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation. PMID:27807408

Cortical Neural Computation by Discrete Results Hypothesis.

PubMed

Castejon, Carlos; Nuñez, Angel

2016-01-01

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called "Discrete Results" (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of "Discrete Results" is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel "Discrete Results" concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation.

Multisensory integration in the basal ganglia.

PubMed

Nagy, Attila; Eördegh, Gabriella; Paróczy, Zsuzsanna; Márkus, Zita; Benedek, György

2006-08-01

Sensorimotor co-ordination in mammals is achieved predominantly via the activity of the basal ganglia. To investigate the underlying multisensory information processing, we recorded the neuronal responses in the caudate nucleus (CN) and substantia nigra (SN) of anaesthetized cats to visual, auditory or somatosensory stimulation alone and also to their combinations, i.e. multisensory stimuli. The main goal of the study was to ascertain whether multisensory information provides more information to the neurons than do the individual sensory components. A majority of the investigated SN and CN multisensory units exhibited significant cross-modal interactions. The multisensory response enhancements were either additive or superadditive; multisensory response depressions were also detected. CN and SN cells with facilitatory and inhibitory interactions were found in each multisensory combination. The strengths of the multisensory interactions did not differ in the two structures. A significant inverse correlation was found between the strengths of the best unimodal responses and the magnitudes of the multisensory response enhancements, i.e. the neurons with the weakest net unimodal responses exhibited the strongest enhancement effects. The onset latencies of the responses of the integrative CN and SN neurons to the multisensory stimuli were significantly shorter than those to the unimodal stimuli. These results provide evidence that the multisensory CN and SN neurons, similarly to those in the superior colliculus and related structures, have the ability to integrate multisensory information. Multisensory integration may help in the effective processing of sensory events and the changes in the environment during motor actions controlled by the basal ganglia.

An information theoretic model of information processing in the Drosophila olfactory system: the role of inhibitory neurons for system efficiency.

PubMed

Faghihi, Faramarz; Kolodziejski, Christoph; Fiala, André; Wörgötter, Florentin; Tetzlaff, Christian

2013-12-20

Fruit flies (Drosophila melanogaster) rely on their olfactory system to process environmental information. This information has to be transmitted without system-relevant loss by the olfactory system to deeper brain areas for learning. Here we study the role of several parameters of the fly's olfactory system and the environment and how they influence olfactory information transmission. We have designed an abstract model of the antennal lobe, the mushroom body and the inhibitory circuitry. Mutual information between the olfactory environment, simulated in terms of different odor concentrations, and a sub-population of intrinsic mushroom body neurons (Kenyon cells) was calculated to quantify the efficiency of information transmission. With this method we study, on the one hand, the effect of different connectivity rates between olfactory projection neurons and firing thresholds of Kenyon cells. On the other hand, we analyze the influence of inhibition on mutual information between environment and mushroom body. Our simulations show an expected linear relation between the connectivity rate between the antennal lobe and the mushroom body and firing threshold of the Kenyon cells to obtain maximum mutual information for both low and high odor concentrations. However, contradicting all-day experiences, high odor concentrations cause a drastic, and unrealistic, decrease in mutual information for all connectivity rates compared to low concentration. But when inhibition on the mushroom body is included, mutual information remains at high levels independent of other system parameters. This finding points to a pivotal role of inhibition in fly information processing without which the system efficiency will be substantially reduced.

Layer-specific input to distinct cell types in layer 6 of monkey primary visual cortex.

PubMed

Briggs, F; Callaway, E M

2001-05-15

Layer 6 of monkey V1 contains a physiologically and anatomically diverse population of excitatory pyramidal neurons. Distinctive arborization patterns of axons and dendrites within the functionally specialized cortical layers define eight types of layer 6 pyramidal neurons and suggest unique information processing roles for each cell type. To address how input sources contribute to cellular function, we examined the laminar sources of functional excitatory input onto individual layer 6 pyramidal neurons using scanning laser photostimulation. We find that excitatory input sources correlate with cell type. Class I neurons with axonal arbors selectively targeting magnocellular (M) recipient layer 4Calpha receive input from M-dominated layer 4B, whereas class I neurons whose axonal arbors target parvocellular (P) recipient layer 4Cbeta receive input from P-dominated layer 2/3. Surprisingly, these neuronal types do not differ significantly in the inputs they receive directly from layers 4Calpha or 4Cbeta. Class II cells, which lack dense axonal arbors within layer 4C, receive excitatory input from layers targeted by their local axons. Specifically, type IIA cells project axons to and receive input from the deep but not superficial layers. Type IIB neurons project to and receive input from the deepest and most superficial, but not middle layers. Type IIC neurons arborize throughout the cortical layers and tend to receive inputs from all cortical layers. These observations have implications for the functional roles of different layer 6 cell types in visual information processing.

Spatial Correlations in Natural Scenes Modulate Response Reliability in Mouse Visual Cortex

PubMed Central

Rikhye, Rajeev V.

2015-01-01

Intrinsic neuronal variability significantly limits information encoding in the primary visual cortex (V1). Certain stimuli can suppress this intertrial variability to increase the reliability of neuronal responses. In particular, responses to natural scenes, which have broadband spatiotemporal statistics, are more reliable than responses to stimuli such as gratings. However, very little is known about which stimulus statistics modulate reliable coding and how this occurs at the neural ensemble level. Here, we sought to elucidate the role that spatial correlations in natural scenes play in reliable coding. We developed a novel noise-masking method to systematically alter spatial correlations in natural movies, without altering their edge structure. Using high-speed two-photon calcium imaging in vivo, we found that responses in mouse V1 were much less reliable at both the single neuron and population level when spatial correlations were removed from the image. This change in reliability was due to a reorganization of between-neuron correlations. Strongly correlated neurons formed ensembles that reliably and accurately encoded visual stimuli, whereas reducing spatial correlations reduced the activation of these ensembles, leading to an unreliable code. Together with an ensemble-specific normalization model, these results suggest that the coordinated activation of specific subsets of neurons underlies the reliable coding of natural scenes. SIGNIFICANCE STATEMENT The natural environment is rich with information. To process this information with high fidelity, V1 neurons have to be robust to noise and, consequentially, must generate responses that are reliable from trial to trial. While several studies have hinted that both stimulus attributes and population coding may reduce noise, the details remain unclear. Specifically, what features of natural scenes are important and how do they modulate reliability? This study is the first to investigate the role of spatial correlations, which are a fundamental attribute of natural scenes, in shaping stimulus coding by V1 neurons. Our results provide new insights into how stimulus spatial correlations reorganize the correlated activation of specific ensembles of neurons to ensure accurate information processing in V1. PMID:26511254

How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks

PubMed Central

Rombouts, Jaldert O.; Bohte, Sander M.; Roelfsema, Pieter R.

2015-01-01

Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions. PMID:25742003

A Background of a Volatile Plant Compound Alters Neural and Behavioral Responses to the Sex Pheromone Blend in a Moth.

PubMed

Dupuy, Fabienne; Rouyar, Angéla; Deisig, Nina; Bourgeois, Thomas; Limousin, Denis; Wycke, Marie-Anne; Anton, Sylvia; Renou, Michel

2017-01-01

Recognition of intra-specific olfactory signals within a complex environment of plant-related volatiles is crucial for reproduction in male moths. Sex pheromone information is detected by specific olfactory receptor neurons (Phe-ORNs), highly abundant on the male antenna. The information is then transmitted to the pheromone processing macroglomerular complex (MGC) within the primary olfactory center, the antennal lobe, where it is processed by local interneurons and projection neurons. Ultimately a behavioral response, orientation toward the pheromone source, is elicited. Volatile plant compounds (VPCs) are detected by other functional types of olfactory receptor neurons (ORNs) projecting in another area of the antennal lobe. However, Phe-ORNs also respond to some VPCs. Female-produced sex pheromones are emitted within a rich environment of VPCs, some of which have been shown to interfere with the detection and processing of sex pheromone information. As interference between the different odor sources might depend on the spatial and temporal features of the two types of stimuli, we investigated here behavioral and neuronal responses to a brief sex pheromone blend pulse in a VPC background as compared to a control background in the male noctuid moth Agrotis ipsilon . We observed male orientation behavior in a wind tunnel and recorded responses of Phe-ORNs and MGC neurons to a brief sex pheromone pulse within a background of individual VPCs. We also recorded the global input signal to the MGC using in vivo calcium imaging with the same stimulation protocol. We found that VPCs eliciting a response in Phe-ORNs and MGC neurons masked responses to the pheromone and decreased the contrast between background odor and the sex pheromone at both levels, whereas α-pinene did not interfere with first order processing. The calcium signal produced in response to a VPC background was tonic, lasting longer than the VPC stimulus duration, and masked entirely the pheromone response. One percent heptanal and linalool, in addition to the masking effect, caused a clear delay in responses of MGC neurons to the sex pheromone. Upwind flight toward the pheromone in a wind tunnel was also delayed but otherwise not altered by different doses of heptanal.

The application of the multi-alternative approach in active neural network models

NASA Astrophysics Data System (ADS)

Podvalny, S.; Vasiljev, E.

2017-02-01

The article refers to the construction of intelligent systems based artificial neuron networks are used. We discuss the basic properties of the non-compliance of artificial neuron networks and their biological prototypes. It is shown here that the main reason for these discrepancies is the structural immutability of the neuron network models in the learning process, that is, their passivity. Based on the modern understanding of the biological nervous system as a structured ensemble of nerve cells, it is proposed to abandon the attempts to simulate its work at the level of the elementary neurons functioning processes and proceed to the reproduction of the information structure of data storage and processing on the basis of the general enough evolutionary principles of multialternativity, i.e. the multi-level structural model, diversity and modularity. The implementation method of these principles is offered, using the faceted memory organization in the neuron network with the rearranging active structure. An example of the implementation of the active facet-type neuron network in the intellectual decision-making system in the conditions of critical events development in the electrical distribution system.

Spontaneous processing of abstract categorical information in the ventrolateral prefrontal cortex

PubMed Central

Cohen, Yale E; Hauser, Marc D; Russ, Brian E

2006-01-01

In various aspects of linguistic analysis and human cognition, some forms of observed variation are ignored in the service of handling more abstract categories. In the absence of training, rhesus discriminate between different types of vocalizations based on the information conveyed as opposed to their acoustic morphologies. We hypothesized that neurons in the ventrolateral prefrontal cortex (vPFC), an area involved in auditory-object processing, might be involved in this spontaneous categorization. To test this hypothesis, we recorded vPFC activity while rhesus listened to vocalizations conveying information about food and non-food events. Results showed between, but not within category discrimination. That is, vPFC neurons discriminated between vocalizations associated with food versus non-food events but not within the class of food calls associated with differences in quality. These results indicate that the vPFC plays a significant role in spontaneously processing abstract categorical information. PMID:17148378

Cell-intrinsic mechanisms of temperature compensation in a grasshopper sensory receptor neuron

PubMed Central

Roemschied, Frederic A; Eberhard, Monika JB; Schleimer, Jan-Hendrik; Ronacher, Bernhard; Schreiber, Susanne

2014-01-01

Changes in temperature affect biochemical reaction rates and, consequently, neural processing. The nervous systems of poikilothermic animals must have evolved mechanisms enabling them to retain their functionality under varying temperatures. Auditory receptor neurons of grasshoppers respond to sound in a surprisingly temperature-compensated manner: firing rates depend moderately on temperature, with average Q10 values around 1.5. Analysis of conductance-based neuron models reveals that temperature compensation of spike generation can be achieved solely relying on cell-intrinsic processes and despite a strong dependence of ion conductances on temperature. Remarkably, this type of temperature compensation need not come at an additional metabolic cost of spike generation. Firing rate-based information transfer is likely to increase with temperature and we derive predictions for an optimal temperature dependence of the tympanal transduction process fostering temperature compensation. The example of auditory receptor neurons demonstrates how neurons may exploit single-cell mechanisms to cope with multiple constraints in parallel. DOI: http://dx.doi.org/10.7554/eLife.02078.001 PMID:24843016

Attention Increases Spike Count Correlations between Visual Cortical Areas.

PubMed

Ruff, Douglas A; Cohen, Marlene R

2016-07-13

Visual attention, which improves perception of attended locations or objects, has long been known to affect many aspects of the responses of neuronal populations in visual cortex. There are two nonmutually exclusive hypotheses concerning the neuronal mechanisms that underlie these perceptual improvements. The first hypothesis, that attention improves the information encoded by a population of neurons in a particular cortical area, has considerable physiological support. The second hypothesis is that attention improves perception by selectively communicating relevant visual information. This idea has been tested primarily by measuring interactions between neurons on very short timescales, which are mathematically nearly independent of neuronal interactions on longer timescales. We tested the hypothesis that attention changes the way visual information is communicated between cortical areas on longer timescales by recording simultaneously from neurons in primary visual cortex (V1) and the middle temporal area (MT) in rhesus monkeys. We used two independent and complementary approaches. Our correlative experiment showed that attention increases the trial-to-trial response variability that is shared between the two areas. In our causal experiment, we electrically microstimulated V1 and found that attention increased the effect of stimulation on MT responses. Together, our results suggest that attention affects both the way visual stimuli are encoded within a cortical area and the extent to which visual information is communicated between areas on behaviorally relevant timescales. Visual attention dramatically improves the perception of attended stimuli. Attention has long been thought to act by selecting relevant visual information for further processing. It has been hypothesized that this selection is accomplished by increasing communication between neurons that encode attended information in different cortical areas. We recorded simultaneously from neurons in primary visual cortex and the middle temporal area while rhesus monkeys performed an attention task. We found that attention increased shared variability between neurons in the two areas and that attention increased the effect of microstimulation in V1 on the firing rates of MT neurons. Our results provide support for the hypothesis that attention increases communication between neurons in different brain areas on behaviorally relevant timescales. Copyright © 2016 the authors 0270-6474/16/367523-12$15.00/0.

Attention Increases Spike Count Correlations between Visual Cortical Areas

PubMed Central

Cohen, Marlene R.

2016-01-01

Visual attention, which improves perception of attended locations or objects, has long been known to affect many aspects of the responses of neuronal populations in visual cortex. There are two nonmutually exclusive hypotheses concerning the neuronal mechanisms that underlie these perceptual improvements. The first hypothesis, that attention improves the information encoded by a population of neurons in a particular cortical area, has considerable physiological support. The second hypothesis is that attention improves perception by selectively communicating relevant visual information. This idea has been tested primarily by measuring interactions between neurons on very short timescales, which are mathematically nearly independent of neuronal interactions on longer timescales. We tested the hypothesis that attention changes the way visual information is communicated between cortical areas on longer timescales by recording simultaneously from neurons in primary visual cortex (V1) and the middle temporal area (MT) in rhesus monkeys. We used two independent and complementary approaches. Our correlative experiment showed that attention increases the trial-to-trial response variability that is shared between the two areas. In our causal experiment, we electrically microstimulated V1 and found that attention increased the effect of stimulation on MT responses. Together, our results suggest that attention affects both the way visual stimuli are encoded within a cortical area and the extent to which visual information is communicated between areas on behaviorally relevant timescales. SIGNIFICANCE STATEMENT Visual attention dramatically improves the perception of attended stimuli. Attention has long been thought to act by selecting relevant visual information for further processing. It has been hypothesized that this selection is accomplished by increasing communication between neurons that encode attended information in different cortical areas. We recorded simultaneously from neurons in primary visual cortex and the middle temporal area while rhesus monkeys performed an attention task. We found that attention increased shared variability between neurons in the two areas and that attention increased the effect of microstimulation in V1 on the firing rates of MT neurons. Our results provide support for the hypothesis that attention increases communication between neurons in different brain areas on behaviorally relevant timescales. PMID:27413161

Suprathreshold stochastic resonance in neural processing tuned by correlation.

PubMed

Durrant, Simon; Kang, Yanmei; Stocks, Nigel; Feng, Jianfeng

2011-07-01

Suprathreshold stochastic resonance (SSR) is examined in the context of integrate-and-fire neurons, with an emphasis on the role of correlation in the neuronal firing. We employed a model based on a network of spiking neurons which received synaptic inputs modeled by Poisson processes stimulated by a stepped input signal. The smoothed ensemble firing rate provided an output signal, and the mutual information between this signal and the input was calculated for networks with different noise levels and different numbers of neurons. It was found that an SSR effect was present in this context. We then examined a more biophysically plausible scenario where the noise was not controlled directly, but instead was tuned by the correlation between the inputs. The SSR effect remained present in this scenario with nonzero noise providing improved information transmission, and it was found that negative correlation between the inputs was optimal. Finally, an examination of SSR in the context of this model revealed its connection with more traditional stochastic resonance and showed a trade-off between supratheshold and subthreshold components. We discuss these results in the context of existing empirical evidence concerning correlations in neuronal firing.

Suprathreshold stochastic resonance in neural processing tuned by correlation

NASA Astrophysics Data System (ADS)

Durrant, Simon; Kang, Yanmei; Stocks, Nigel; Feng, Jianfeng

2011-07-01

Suprathreshold stochastic resonance (SSR) is examined in the context of integrate-and-fire neurons, with an emphasis on the role of correlation in the neuronal firing. We employed a model based on a network of spiking neurons which received synaptic inputs modeled by Poisson processes stimulated by a stepped input signal. The smoothed ensemble firing rate provided an output signal, and the mutual information between this signal and the input was calculated for networks with different noise levels and different numbers of neurons. It was found that an SSR effect was present in this context. We then examined a more biophysically plausible scenario where the noise was not controlled directly, but instead was tuned by the correlation between the inputs. The SSR effect remained present in this scenario with nonzero noise providing improved information transmission, and it was found that negative correlation between the inputs was optimal. Finally, an examination of SSR in the context of this model revealed its connection with more traditional stochastic resonance and showed a trade-off between supratheshold and subthreshold components. We discuss these results in the context of existing empirical evidence concerning correlations in neuronal firing.

NeuroRhythmics: software for analyzing time-series measurements of saltatory movements in neuronal processes.

PubMed

Kerlin, Aaron M; Lindsley, Tara A

2008-08-15

Time-lapse imaging of living neurons both in vivo and in vitro has revealed that the growth of axons and dendrites is highly dynamic and characterized by alternating periods of extension and retraction. These growth dynamics are associated with important features of neuronal development and are differentially affected by experimental treatments, but the underlying cellular mechanisms are poorly understood. NeuroRhythmics was developed to semi-automate specific quantitative tasks involved in analysis of two-dimensional time-series images of processes that exhibit saltatory elongation. This software provides detailed information on periods of growth and nongrowth that it identifies by transitions in elongation (i.e. initiation time, average rate, duration) and information regarding the overall pattern of saltatory growth (i.e. time of pattern onset, frequency of transitions, relative time spent in a state of growth vs. nongrowth). Plots and numeric output are readily imported into other applications. The user has the option to specify criteria for identifying transitions in growth behavior, which extends the potential application of the software to neurons of different types or developmental stage and to other time-series phenomena that exhibit saltatory dynamics. NeuroRhythmics will facilitate mechanistic studies of periodic axonal and dendritic growth in neurons.

Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

PubMed Central

Nessler, Bernhard; Pfeiffer, Michael; Buesing, Lars; Maass, Wolfgang

2013-01-01

The principles by which networks of neurons compute, and how spike-timing dependent plasticity (STDP) of synaptic weights generates and maintains their computational function, are unknown. Preceding work has shown that soft winner-take-all (WTA) circuits, where pyramidal neurons inhibit each other via interneurons, are a common motif of cortical microcircuits. We show through theoretical analysis and computer simulations that Bayesian computation is induced in these network motifs through STDP in combination with activity-dependent changes in the excitability of neurons. The fundamental components of this emergent Bayesian computation are priors that result from adaptation of neuronal excitability and implicit generative models for hidden causes that are created in the synaptic weights through STDP. In fact, a surprising result is that STDP is able to approximate a powerful principle for fitting such implicit generative models to high-dimensional spike inputs: Expectation Maximization. Our results suggest that the experimentally observed spontaneous activity and trial-to-trial variability of cortical neurons are essential features of their information processing capability, since their functional role is to represent probability distributions rather than static neural codes. Furthermore it suggests networks of Bayesian computation modules as a new model for distributed information processing in the cortex. PMID:23633941

Dynamic Information Encoding With Dynamic Synapses in Neural Adaptation

PubMed Central

Li, Luozheng; Mi, Yuanyuan; Zhang, Wenhao; Wang, Da-Hui; Wu, Si

2018-01-01

Adaptation refers to the general phenomenon that the neural system dynamically adjusts its response property according to the statistics of external inputs. In response to an invariant stimulation, neuronal firing rates first increase dramatically and then decrease gradually to a low level close to the background activity. This prompts a question: during the adaptation, how does the neural system encode the repeated stimulation with attenuated firing rates? It has been suggested that the neural system may employ a dynamical encoding strategy during the adaptation, the information of stimulus is mainly encoded by the strong independent spiking of neurons at the early stage of the adaptation; while the weak but synchronized activity of neurons encodes the stimulus information at the later stage of the adaptation. The previous study demonstrated that short-term facilitation (STF) of electrical synapses, which increases the synchronization between neurons, can provide a mechanism to realize dynamical encoding. In the present study, we further explore whether short-term plasticity (STP) of chemical synapses, an interaction form more common than electrical synapse in the cortex, can support dynamical encoding. We build a large-size network with chemical synapses between neurons. Notably, facilitation of chemical synapses only enhances pair-wise correlations between neurons mildly, but its effect on increasing synchronization of the network can be significant, and hence it can serve as a mechanism to convey the stimulus information. To read-out the stimulus information, we consider that a downstream neuron receives balanced excitatory and inhibitory inputs from the network, so that the downstream neuron only responds to synchronized firings of the network. Therefore, the response of the downstream neuron indicates the presence of the repeated stimulation. Overall, our study demonstrates that STP of chemical synapse can serve as a mechanism to realize dynamical neural encoding. We believe that our study shed lights on the mechanism underlying the efficient neural information processing via adaptation. PMID:29636675

Sensory integration: neuronal filters for polarized light patterns.

PubMed

Krapp, Holger G

2014-09-22

Animal and human behaviour relies on local sensory signals that are often ambiguous. A new study shows how tuning neuronal responses to celestial cues helps locust navigation, demonstrating a common principle of sensory information processing: the use of matched filters. Copyright © 2014 Elsevier Ltd. All rights reserved.

Neuronal modelling of baroreflex response to orthostatic stress

NASA Astrophysics Data System (ADS)

Samin, Azfar

The accelerations experienced in aerial combat can cause pilot loss of consciousness (GLOC) due to a critical reduction in cerebral blood circulation. The development of smart protective equipment requires understanding of how the brain processes blood pressure (BP) information in response to acceleration. We present a biologically plausible model of the Baroreflex to investigate the neural correlates of short-term BP control under acceleration or orthostatic stress. The neuronal network model, which employs an integrate-and-fire representation of a biological neuron, comprises the sensory, motor, and the central neural processing areas that form the Baroreflex. Our modelling strategy is to test hypotheses relating to the encoding mechanisms of multiple sensory inputs to the nucleus tractus solitarius (NTS), the site of central neural processing. The goal is to run simulations and reproduce model responses that are consistent with the variety of available experimental data. Model construction and connectivity are inspired by the available anatomical and neurophysiological evidence that points to a barotopic organization in the NTS, and the presence of frequency-dependent synaptic depression, which provides a mechanism for generating non-linear local responses in NTS neurons that result in quantifiable dynamic global baroreflex responses. The entire physiological range of BP and rate of change of BP variables is encoded in a palisade of NTS neurons in that the spike responses approximate Gaussian 'tuning' curves. An adapting weighted-average decoding scheme computes the motor responses and a compensatory signal regulates the heart rate (HR). Model simulations suggest that: (1) the NTS neurons can encode the hydrostatic pressure difference between two vertically separated sensory receptor regions at +Gz, and use changes in that difference for the regulation of HR; (2) even though NTS neurons do not fire with a cardiac rhythm seen in the afferents, pulse-rhythmic activity is regained downstream provided the input phase information in preserved centrally; (3) frequency-dependent synaptic depression, which causes temporal variations in synaptic strength due to changes in input frequency, is a possible mechanism of non-linear dynamic baroreflex gain control. Synaptic depression enables the NTS neuron to encode dBP/dt but to lose information about the steady state firing of the afferents.

Information processing in dendrites I. Input pattern generalisation.

PubMed

Gurney, K N

2001-10-01

In this paper and its companion, we address the question as to whether there are any general principles underlying information processing in the dendritic trees of biological neurons. In order to address this question, we make two assumptions. First, the key architectural feature of dendrites responsible for many of their information processing abilities is the existence of independent sub-units performing local non-linear processing. Second, any general functional principles operate at a level of abstraction in which neurons are modelled by Boolean functions. To accommodate these assumptions, we therefore define a Boolean model neuron-the multi-cube unit (MCU)-which instantiates the notion of the discrete functional sub-unit. We then use this model unit to explore two aspects of neural functionality: generalisation (in this paper) and processing complexity (in its companion). Generalisation is dealt with from a geometric viewpoint and is quantified using a new metric-the set of order parameters. These parameters are computed for threshold logic units (TLUs), a class of random Boolean functions, and MCUs. Our interpretation of the order parameters is consistent with our knowledge of generalisation in TLUs and with the lack of generalisation in randomly chosen functions. Crucially, the order parameters for MCUs imply that these functions possess a range of generalisation behaviour. We argue that this supports the general thesis that dendrites facilitate input pattern generalisation despite any local non-linear processing within functionally isolated sub-units.

Preferential Representation of Past Outcome Information and Future Choice Behavior by Putative Inhibitory Interneurons Rather Than Putative Pyramidal Neurons in the Primate Dorsal Anterior Cingulate Cortex.

PubMed

Kawai, Takashi; Yamada, Hiroshi; Sato, Nobuya; Takada, Masahiko; Matsumoto, Masayuki

2018-05-02

The dorsal anterior cingulate cortex (dACC) plays crucial roles in monitoring the outcome of a choice and adjusting a subsequent choice behavior based on the outcome information. In the present study, we investigated how different types of dACC neurons, that is, putative pyramidal neurons and putative inhibitory interneurons, contribute to these processes. We analyzed single-unit database obtained from the dACC in monkeys performing a reversal learning task. The monkey was required to adjust choice behavior from past outcome experiences. Depending on their action potential waveforms, the recorded neurons were classified into putative pyramidal neurons and putative inhibitory interneurons. We found that these neurons do not equally contribute to outcome monitoring and behavioral adjustment. Although both neuron types evenly responded to the current outcome, a larger proportion of putative inhibitory interneurons than putative pyramidal neurons stored the information about the past outcome. The putative inhibitory interneurons further represented choice-related signals more frequently, such as whether the monkey would shift the last choice to an alternative at the next choice opportunity. Our findings suggest that putative inhibitory interneurons, which are thought not to project to brain areas outside the dACC, preferentially transmit signals that would adjust choice behavior based on past outcome experiences.

Conversion of Phase Information into a Spike-Count Code by Bursting Neurons

PubMed Central

Samengo, Inés; Montemurro, Marcelo A.

2010-01-01

Single neurons in the cerebral cortex are immersed in a fluctuating electric field, the local field potential (LFP), which mainly originates from synchronous synaptic input into the local neural neighborhood. As shown by recent studies in visual and auditory cortices, the angular phase of the LFP at the time of spike generation adds significant extra information about the external world, beyond the one contained in the firing rate alone. However, no biologically plausible mechanism has yet been suggested that allows downstream neurons to infer the phase of the LFP at the soma of their pre-synaptic afferents. Therefore, so far there is no evidence that the nervous system can process phase information. Here we study a model of a bursting pyramidal neuron, driven by a time-dependent stimulus. We show that the number of spikes per burst varies systematically with the phase of the fluctuating input at the time of burst onset. The mapping between input phase and number of spikes per burst is a robust response feature for a broad range of stimulus statistics. Our results suggest that cortical bursting neurons could play a crucial role in translating LFP phase information into an easily decodable spike count code. PMID:20300632

Cortical network architecture for context processing in primate brain

PubMed Central

Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka

2015-01-01

Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition. DOI: http://dx.doi.org/10.7554/eLife.06121.001 PMID:26416139

Chaos in neurons and its application: perspective of chaos engineering.

PubMed

Hirata, Yoshito; Oku, Makito; Aihara, Kazuyuki

2012-12-01

We review our recent work on chaos in neurons and its application to neural networks from perspective of chaos engineering. Especially, we analyze a dataset of a squid giant axon by newly combining our previous work of identifying Devaney's chaos with surrogate data analysis, and show that an axon can behave chaotically. Based on this knowledge, we use a chaotic neuron model to investigate possible information processing in the brain.

Specific Contributions of Ventromedial, Anterior Cingulate, and Lateral Prefrontal Cortex for Attentional Selection and Stimulus Valuation

PubMed Central

Kaping, Daniel; Vinck, Martin; Hutchison, R. Matthew; Everling, Stefan; Womelsdorf, Thilo

2011-01-01

Attentional control ensures that neuronal processes prioritize the most relevant stimulus in a given environment. Controlling which stimulus is attended thus originates from neurons encoding the relevance of stimuli, i.e. their expected value, in hand with neurons encoding contextual information about stimulus locations, features, and rules that guide the conditional allocation of attention. Here, we examined how these distinct processes are encoded and integrated in macaque prefrontal cortex (PFC) by mapping their functional topographies at the time of attentional stimulus selection. We find confined clusters of neurons in ventromedial PFC (vmPFC) that predominantly convey stimulus valuation information during attention shifts. These valuation signals were topographically largely separated from neurons predicting the stimulus location to which attention covertly shifted, and which were evident across the complete medial-to-lateral extent of the PFC, encompassing anterior cingulate cortex (ACC), and lateral PFC (LPFC). LPFC responses showed particularly early-onset selectivity and primarily facilitated attention shifts to contralateral targets. Spatial selectivity within ACC was delayed and heterogeneous, with similar proportions of facilitated and suppressed responses during contralateral attention shifts. The integration of spatial and valuation signals about attentional target stimuli was observed in a confined cluster of neurons at the intersection of vmPFC, ACC, and LPFC. These results suggest that valuation processes reflecting stimulus-specific outcome predictions are recruited during covert attentional control. Value predictions and the spatial identification of attentional targets were conveyed by largely separate neuronal populations, but were integrated locally at the intersection of three major prefrontal areas, which may constitute a functional hub within the larger attentional control network. PMID:22215982

Basic Gravitational Reflexes in the Larval Frog

NASA Technical Reports Server (NTRS)

Cochran, Stephen L.

1996-01-01

This investigation was designed to determine how a primitive vertebrate, the bullfrog tadpole, is able to sense and process gravitational stimuli. Because of the phylogenetic similarities of the vestibular systems in all vertebrates, the understanding of the gravitational reflexes in this relatively simple vertebrate should elucidate a skeletal framework on a elementary level, upon which the more elaborate reflexes of higher vertebrates may be constructed. The purpose of this study was to understand how the nervous system of the larval amphibian processes gravitational information. This study involved predominantly electrophysiological investigations of the isolated, alert (forebrain removed) bullfrog tadpole head. The focus of these experiments is threefold: (1) to understand from whole extraocular nerve recordings the signals sent to the eye following static gravitational tilt of the head; (2) to localize neuronal centers responsible for generating these signals through reversible pharmacological ablation of these centers; and (3) to record intracellularly from neurons within these centers in order to determine the single neuron's role in the overall processing of the center. This study has provided information on the mechanisms by which a primitive vertebrate processes gravitational reflexes.

Probing the function of neuronal populations: combining micromirror-based optogenetic photostimulation with voltage-sensitive dye imaging

PubMed Central

Tsuda, Sachiko; Kee, Michelle Z.L.; Cunha, Catarina; Kim, Jinsook; Yan, Ping; Loew, Leslie M.; Augustine, George J.

2013-01-01

Recent advances in our understanding of brain function have come from using light to either control or image neuronal activity. Here we describe an approach that combines both techniques: a micromirror array is used to photostimulate populations of presynaptic neurons expressing channelrhodopsin-2, while a red-shifted voltage-sensitive dye allows optical detection of resulting postsynaptic activity. Such technology allowed us to control the activity of cerebellar interneurons while simultaneously recording inhibitory responses in multiple Purkinje neurons, their postsynaptic targets. This approach should substantially accelerate our understanding of information processing by populations of neurons within brain circuits. PMID:23254260

Multimodal Integration After Unilateral Labyrinthine Lesion: Single Vestibular Nuclei Neuron Responses and Implications for Postural Compensation

PubMed Central

Sadeghi, Soroush G.; Minor, Lloyd B.

2011-01-01

Plasticity in neuronal responses is necessary for compensation following brain lesions and adaptation to new conditions and motor learning. In a previous study, we showed that compensatory changes in the vestibuloocular reflex (VOR) following unilateral vestibular loss were characterized by dynamic reweighting of inputs from vestibular and extravestibular modalities at the level of single neurons that constitute the first central stage of VOR signal processing. Here, we studied another class of neurons, i.e., the vestibular-only neurons, in the vestibular nuclei that mediate vestibulospinal reflexes and provide information for higher brain areas. We investigated changes in the relative contribution of vestibular, neck proprioceptive, and efference copy signals in the response of these neurons during compensation after contralateral vestibular loss in Macaca mulata monkeys. We show that the time course of recovery of vestibular sensitivity of neurons corresponds with that of lower extremity muscle and tendon reflexes reported in previous studies. More important, we found that information from neck proprioceptors, which did not influence neuronal responses before the lesion, were unmasked after lesion. Such inputs influenced the early stages of the compensation process evidenced by faster and more substantial recovery of the resting discharge in proprioceptive-sensitive neurons. Interestingly, unlike our previous study of VOR interneurons, the improvement in the sensitivity of the two groups of neurons did not show any difference in the early or late stages after lesion. Finally, neuronal responses during active head movements were not different before and after lesion and were attenuated relative to passive movements over the course of recovery, similar to that observed in control conditions. Comparison of compensatory changes observed in the vestibuloocular and vestibulospinal pathways provides evidence for similarities and differences between the two classes of neurons that mediate these pathways at the functional and cellular levels. PMID:21148096

Multimodal integration after unilateral labyrinthine lesion: single vestibular nuclei neuron responses and implications for postural compensation.

PubMed

Sadeghi, Soroush G; Minor, Lloyd B; Cullen, Kathleen E

2011-02-01

Plasticity in neuronal responses is necessary for compensation following brain lesions and adaptation to new conditions and motor learning. In a previous study, we showed that compensatory changes in the vestibuloocular reflex (VOR) following unilateral vestibular loss were characterized by dynamic reweighting of inputs from vestibular and extravestibular modalities at the level of single neurons that constitute the first central stage of VOR signal processing. Here, we studied another class of neurons, i.e., the vestibular-only neurons, in the vestibular nuclei that mediate vestibulospinal reflexes and provide information for higher brain areas. We investigated changes in the relative contribution of vestibular, neck proprioceptive, and efference copy signals in the response of these neurons during compensation after contralateral vestibular loss in Macaca mulata monkeys. We show that the time course of recovery of vestibular sensitivity of neurons corresponds with that of lower extremity muscle and tendon reflexes reported in previous studies. More important, we found that information from neck proprioceptors, which did not influence neuronal responses before the lesion, were unmasked after lesion. Such inputs influenced the early stages of the compensation process evidenced by faster and more substantial recovery of the resting discharge in proprioceptive-sensitive neurons. Interestingly, unlike our previous study of VOR interneurons, the improvement in the sensitivity of the two groups of neurons did not show any difference in the early or late stages after lesion. Finally, neuronal responses during active head movements were not different before and after lesion and were attenuated relative to passive movements over the course of recovery, similar to that observed in control conditions. Comparison of compensatory changes observed in the vestibuloocular and vestibulospinal pathways provides evidence for similarities and differences between the two classes of neurons that mediate these pathways at the functional and cellular levels.

A Virtual Reality Visualization Tool for Neuron Tracing

PubMed Central

Usher, Will; Klacansky, Pavol; Federer, Frederick; Bremer, Peer-Timo; Knoll, Aaron; Angelucci, Alessandra; Pascucci, Valerio

2017-01-01

Tracing neurons in large-scale microscopy data is crucial to establishing a wiring diagram of the brain, which is needed to understand how neural circuits in the brain process information and generate behavior. Automatic techniques often fail for large and complex datasets, and connectomics researchers may spend weeks or months manually tracing neurons using 2D image stacks. We present a design study of a new virtual reality (VR) system, developed in collaboration with trained neuroanatomists, to trace neurons in microscope scans of the visual cortex of primates. We hypothesize that using consumer-grade VR technology to interact with neurons directly in 3D will help neuroscientists better resolve complex cases and enable them to trace neurons faster and with less physical and mental strain. We discuss both the design process and technical challenges in developing an interactive system to navigate and manipulate terabyte-sized image volumes in VR. Using a number of different datasets, we demonstrate that, compared to widely used commercial software, consumer-grade VR presents a promising alternative for scientists. PMID:28866520

Functional model of biological neural networks.

PubMed

Lo, James Ting-Ho

2010-12-01

A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.

A Virtual Reality Visualization Tool for Neuron Tracing.

PubMed

Usher, Will; Klacansky, Pavol; Federer, Frederick; Bremer, Peer-Timo; Knoll, Aaron; Yarch, Jeff; Angelucci, Alessandra; Pascucci, Valerio

2018-01-01

Tracing neurons in large-scale microscopy data is crucial to establishing a wiring diagram of the brain, which is needed to understand how neural circuits in the brain process information and generate behavior. Automatic techniques often fail for large and complex datasets, and connectomics researchers may spend weeks or months manually tracing neurons using 2D image stacks. We present a design study of a new virtual reality (VR) system, developed in collaboration with trained neuroanatomists, to trace neurons in microscope scans of the visual cortex of primates. We hypothesize that using consumer-grade VR technology to interact with neurons directly in 3D will help neuroscientists better resolve complex cases and enable them to trace neurons faster and with less physical and mental strain. We discuss both the design process and technical challenges in developing an interactive system to navigate and manipulate terabyte-sized image volumes in VR. Using a number of different datasets, we demonstrate that, compared to widely used commercial software, consumer-grade VR presents a promising alternative for scientists.

EGR-1 Expression in Catecholamine-synthesizing Neurons Reflects Auditory Learning and Correlates with Responses in Auditory Processing Areas.

PubMed

Dai, Jennifer B; Chen, Yining; Sakata, Jon T

2018-05-21

Distinguishing between familiar and unfamiliar individuals is an important task that shapes the expression of social behavior. As such, identifying the neural populations involved in processing and learning the sensory attributes of individuals is important for understanding mechanisms of behavior. Catecholamine-synthesizing neurons have been implicated in sensory processing, but relatively little is known about their contribution to auditory learning and processing across various vertebrate taxa. Here we investigated the extent to which immediate early gene expression in catecholaminergic circuitry reflects information about the familiarity of social signals and predicts immediate early gene expression in sensory processing areas in songbirds. We found that male zebra finches readily learned to differentiate between familiar and unfamiliar acoustic signals ('songs') and that playback of familiar songs led to fewer catecholaminergic neurons in the locus coeruleus (but not in the ventral tegmental area, substantia nigra, or periaqueductal gray) expressing the immediate early gene, EGR-1, than playback of unfamiliar songs. The pattern of EGR-1 expression in the locus coeruleus was similar to that observed in two auditory processing areas implicated in auditory learning and memory, namely the caudomedial nidopallium (NCM) and the caudal medial mesopallium (CMM), suggesting a contribution of catecholamines to sensory processing. Consistent with this, the pattern of catecholaminergic innervation onto auditory neurons co-varied with the degree to which song playback affected the relative intensity of EGR-1 expression. Together, our data support the contention that catecholamines like norepinephrine contribute to social recognition and the processing of social information. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Neurient: An Algorithm for Automatic Tracing of Confluent Neuronal Images to Determine Alignment

PubMed Central

Mitchel, J.A.; Martin, I.S.

2013-01-01

A goal of neural tissue engineering is the development and evaluation of materials that guide neuronal growth and alignment. However, the methods available to quantitatively evaluate the response of neurons to guidance materials are limited and/or expensive, and may require manual tracing to be performed by the researcher. We have developed an open source, automated Matlab-based algorithm, building on previously published methods, to trace and quantify alignment of fluorescent images of neurons in culture. The algorithm is divided into three phases, including computation of a lookup table which contains directional information for each image, location of a set of seed points which may lie along neurite centerlines, and tracing neurites starting with each seed point and indexing into the lookup table. This method was used to obtain quantitative alignment data for complex images of densely cultured neurons. Complete automation of tracing allows for unsupervised processing of large numbers of images. Following image processing with our algorithm, available metrics to quantify neurite alignment include angular histograms, percent of neurite segments in a given direction, and mean neurite angle. The alignment information obtained from traced images can be used to compare the response of neurons to a range of conditions. This tracing algorithm is freely available to the scientific community under the name Neurient, and its implementation in Matlab allows a wide range of researchers to use a standardized, open source method to quantitatively evaluate the alignment of dense neuronal cultures. PMID:23384629

Neural representation of cost-benefit selections in rat anterior cingulate cortex in self-paced decision making.

PubMed

Wang, Shuai; Shi, Yi; Li, Bao-Ming

2017-03-01

The anterior cingulate cortex (ACC) is crucial for decision making which involves the processing of cost-benefit information. Our previous study has shown that ACC is essential for self-paced decision making. However, it is unclear how ACC neurons represent cost-benefit selections during the decision-making process. In the present study, we trained rats on the same "Do More Get More" (DMGM) task as in our previous work. In each trial, the animals stand upright and perform a sustained nosepoke of their own will to earn a water reward, with the amount of reward positively correlated to the duration of the nosepoke (i.e., longer nosepokes earn larger rewards). We then recorded ACC neuronal activity on well-trained rats while they were performing the DMGM task. Our results show that (1) approximately 3/5 ACC neurons (296/496, 59.7%) exhibited changes in firing frequency that were temporally locked with the main events of the DMGM task; (2) about 1/5 ACC neurons (101/496, 20.4%) or 1/3 of the event-modulated neurons (101/296, 34.1%) showed differential firing rate changes for different cost-benefit selections; and (3) many ACC neurons exhibited linear encoding of the cost-benefit selections in the DMGM task events. These results suggest that ACC neurons are engaged in encoding cost-benefit information, thus represent the selections in self-paced decision making. Copyright © 2016 Elsevier Inc. All rights reserved.

Characterisation of rebound depolarisation in mice deep dorsal horn neurons in vitro.

PubMed

Rivera-Arconada, Ivan; Lopez-Garcia, Jose A

2015-09-01

Spinal dorsal horn neurons constitute the first relay for pain processing and participate in the processing of other sensory, motor and autonomic information. At the cellular level, intrinsic excitability is a factor contributing to network function. In turn, excitability is set by the array of ionic conductance expressed by neurons. Here, we set out to characterise rebound depolarisation following hyperpolarisation, a feature frequently described in dorsal horn neurons but never addressed in depth. To this end, an in vitro preparation of the spinal cord from mice pups was used combined with whole-cell recordings in current and voltage clamp modes. Results show the expression of H- and/or T-type currents in a significant proportion of dorsal horn neurons. The expression of these currents determines the presence of rebound behaviour at the end of hyperpolarising pulses. T-type calcium currents were associated to high-amplitude rebounds usually involving high-frequency action potential firing. H-currents were associated to low-amplitude rebounds less prone to elicit firing or firing at lower frequencies. For a large proportion of neurons expressing both currents, the H-current constitutes a mechanism to ensure a faster response after hyperpolarisations, adjusting the latency of the rebound firing. We conclude that rebound depolarisation and firing are intrinsic factors to many dorsal horn neurons that may constitute a mechanism to integrate somatosensory information in the spinal cord, allowing for a rapid switch from inhibited-to-excited states.

Human embryonic stem cell-derived neurons adopt and regulate the activity of an established neural network

PubMed Central

Weick, Jason P.; Liu, Yan; Zhang, Su-Chun

2011-01-01

Whether hESC-derived neurons can fully integrate with and functionally regulate an existing neural network remains unknown. Here, we demonstrate that hESC-derived neurons receive unitary postsynaptic currents both in vitro and in vivo and adopt the rhythmic firing behavior of mouse cortical networks via synaptic integration. Optical stimulation of hESC-derived neurons expressing Channelrhodopsin-2 elicited both inhibitory and excitatory postsynaptic currents and triggered network bursting in mouse neurons. Furthermore, light stimulation of hESC-derived neurons transplanted to the hippocampus of adult mice triggered postsynaptic currents in host pyramidal neurons in acute slice preparations. Thus, hESC-derived neurons can participate in and modulate neural network activity through functional synaptic integration, suggesting they are capable of contributing to neural network information processing both in vitro and in vivo. PMID:22106298

Controlling Synfire Chain by Inhibitory Synaptic Input

NASA Astrophysics Data System (ADS)

Shinozaki, Takashi; Câteau, Hideyuki; Urakubo, Hidetoshi; Okada, Masato

2007-04-01

The propagation of highly synchronous firings across neuronal networks, called the synfire chain, has been actively studied both theoretically and experimentally. The temporal accuracy and remarkable stability of the propagation have been repeatedly examined in previous studies. However, for such a mode of signal transduction to play a major role in processing information in the brain, the propagation should also be controlled dynamically and flexibly. Here, we show that inhibitory but not excitatory input can bidirectionally modulate the propagation, i.e., enhance or suppress the synchronous firings depending on the timing of the input. Our simulations based on the Hodgkin-Huxley neuron model demonstrate this bidirectional modulation and suggest that it should be achieved with any biologically inspired modeling. Our finding may help describe a concrete scenario of how multiple synfire chains lying in a neuronal network are appropriately controlled to perform significant information processing.

Temporal tuning in the bat auditory cortex is sharper when studied with natural echolocation sequences.

PubMed

Beetz, M Jerome; Hechavarría, Julio C; Kössl, Manfred

2016-06-30

Precise temporal coding is necessary for proper acoustic analysis. However, at cortical level, forward suppression appears to limit the ability of neurons to extract temporal information from natural sound sequences. Here we studied how temporal processing can be maintained in the bats' cortex in the presence of suppression evoked by natural echolocation streams that are relevant to the bats' behavior. We show that cortical neurons tuned to target-distance actually profit from forward suppression induced by natural echolocation sequences. These neurons can more precisely extract target distance information when they are stimulated with natural echolocation sequences than during stimulation with isolated call-echo pairs. We conclude that forward suppression does for time domain tuning what lateral inhibition does for selectivity forms such as auditory frequency tuning and visual orientation tuning. When talking about cortical processing, suppression should be seen as a mechanistic tool rather than a limiting element.

Temporal structure of neuronal population oscillations with empirical model decomposition

NASA Astrophysics Data System (ADS)

Li, Xiaoli

2006-08-01

Frequency analysis of neuronal oscillation is very important for understanding the neural information processing and mechanism of disorder in the brain. This Letter addresses a new method to analyze the neuronal population oscillations with empirical mode decomposition (EMD). Following EMD of neuronal oscillation, a series of intrinsic mode functions (IMFs) are obtained, then Hilbert transform of IMFs can be used to extract the instantaneous time frequency structure of neuronal oscillation. The method is applied to analyze the neuronal oscillation in the hippocampus of epileptic rats in vivo, the results show the neuronal oscillations have different descriptions during the pre-ictal, seizure onset and ictal periods of the epileptic EEG at the different frequency band. This new method is very helpful to provide a view for the temporal structure of neural oscillation.

a-Band Oscillations in Intracellular Membrane Potentials of Dentate Gyrus Neurons in Awake Rodents

ERIC Educational Resources Information Center

Anderson, Ross W.; Strowbridge, Ben W.

2014-01-01

The hippocampus and dentate gyrus play critical roles in processing declarative memories and spatial information. Dentate granule cells, the first relay in the trisynaptic circuit through the hippocampus, exhibit low spontaneous firing rates even during locomotion. Using intracellular recordings from dentate neurons in awake mice operating a…

Advanced Computing Architectures for Cognitive Processing

DTIC Science & Technology

2009-07-01

Evolution ................................................................................. 20  Figure 9: Logic diagram smart block-based neuron...48  Figure 21: Naive Grid Potential Kernel...processing would be helpful for Air Force systems acquisition. Specific cognitive processing approaches addressed herein include global information grid

Temporal characteristics of gustatory responses in rat parabrachial neurons vary by stimulus and chemosensitive neuron type.

PubMed

Geran, Laura; Travers, Susan

2013-01-01

It has been demonstrated that temporal features of spike trains can increase the amount of information available for gustatory processing. However, the nature of these temporal characteristics and their relationship to different taste qualities and neuron types are not well-defined. The present study analyzed the time course of taste responses from parabrachial (PBN) neurons elicited by multiple applications of "sweet" (sucrose), "salty" (NaCl), "sour" (citric acid), and "bitter" (quinine and cycloheximide) stimuli in an acute preparation. Time course varied significantly by taste stimulus and best-stimulus classification. Across neurons, the ensemble code for the three electrolytes was similar initially but quinine diverged from NaCl and acid during the second 500 ms of stimulation and all four qualities became distinct just after 1s. This temporal evolution was reflected in significantly broader tuning during the initial response. Metric space analyses of quality discrimination by individual neurons showed that increases in information (H) afforded by temporal factors was usually explained by differences in rate envelope, which had a greater impact during the initial 2s (22.5% increase in H) compared to the later response (9.5%). Moreover, timing had a differential impact according to cell type, with between-quality discrimination in neurons activated maximally by NaCl or citric acid most affected. Timing was also found to dramatically improve within-quality discrimination (80% increase in H) in neurons that responded optimally to bitter stimuli (B-best). Spikes from B-best neurons were also more likely to occur in bursts. These findings suggest that among PBN taste neurons, time-dependent increases in mutual information can arise from stimulus- and neuron-specific differences in response envelope during the initial dynamic period. A stable rate code predominates in later epochs.

Temporal Characteristics of Gustatory Responses in Rat Parabrachial Neurons Vary by Stimulus and Chemosensitive Neuron Type

PubMed Central

Geran, Laura; Travers, Susan

2013-01-01

It has been demonstrated that temporal features of spike trains can increase the amount of information available for gustatory processing. However, the nature of these temporal characteristics and their relationship to different taste qualities and neuron types are not well-defined. The present study analyzed the time course of taste responses from parabrachial (PBN) neurons elicited by multiple applications of “sweet” (sucrose), “salty” (NaCl), “sour” (citric acid), and “bitter” (quinine and cycloheximide) stimuli in an acute preparation. Time course varied significantly by taste stimulus and best-stimulus classification. Across neurons, the ensemble code for the three electrolytes was similar initially but quinine diverged from NaCl and acid during the second 500ms of stimulation and all four qualities became distinct just after 1s. This temporal evolution was reflected in significantly broader tuning during the initial response. Metric space analyses of quality discrimination by individual neurons showed that increases in information (H) afforded by temporal factors was usually explained by differences in rate envelope, which had a greater impact during the initial 2s (22.5% increase in H) compared to the later response (9.5%). Moreover, timing had a differential impact according to cell type, with between-quality discrimination in neurons activated maximally by NaCl or citric acid most affected. Timing was also found to dramatically improve within-quality discrimination (80% increase in H) in neurons that responded optimally to bitter stimuli (B-best). Spikes from B-best neurons were also more likely to occur in bursts. These findings suggest that among PBN taste neurons, time-dependent increases in mutual information can arise from stimulus- and neuron-specific differences in response envelope during the initial dynamic period. A stable rate code predominates in later epochs. PMID:24124597

The power of projectomes: genetic mosaic labeling in the larval zebrafish brain reveals organizing principles of sensory circuits.

PubMed

Robles, Estuardo

2017-09-01

In no vertebrate species do we possess an accurate, comprehensive tally of neuron types in the brain. This is in no small part due to the vast diversity of neuronal types that comprise complex vertebrate nervous systems. A fundamental goal of neuroscience is to construct comprehensive catalogs of cell types defined by structure, connectivity, and physiological response properties. This type of information will be invaluable for generating models of how assemblies of neurons encode and distribute sensory information and correspondingly alter behavior. This review summarizes recent efforts in the larval zebrafish to construct sensory projectomes, comprehensive analyses of axonal morphologies in sensory axon tracts. Focusing on the olfactory and optic tract, these studies revealed principles of sensory information processing in the olfactory and visual systems that could not have been directly quantified by other methods. In essence, these studies reconstructed the optic and olfactory tract in a virtual manner, providing insights into patterns of neuronal growth that underlie the formation of sensory axon tracts. Quantitative analysis of neuronal diversity revealed organizing principles that determine information flow through sensory systems in the zebrafish that are likely to be conserved across vertebrate species. The generation of comprehensive cell type classifications based on structural, physiological, and molecular features will lead to testable hypotheses on the functional role of individual sensory neuron subtypes in controlling specific sensory-evoked behaviors.

[Cognitive Functions in the Prefrontal Association Cortex; Transitive Inference and the Lateral Prefrontal Cortex].

PubMed

Tanaka, Shingo; Oguchi, Mineki; Sakagami, Masamichi

2016-11-01

To behave appropriately in a complex and uncertain world, the brain makes use of several distinct learning systems. One such system is called the "model-free process", via which conditioning allows the association between a stimulus or response and a given reward to be learned. Another system is called the "model-based process". Via this process, the state transition between a stimulus and a response is learned so that the brain is able to plan actions prior to their execution. Several studies have tried to relate the difference between model-based and model-free processes to the difference in functions of the lateral prefrontal cortex (LPFC) and the striatum. Here, we describe a series of studies that demonstrate the ability of LPFC neurons to categorize visual stimuli by their associated behavioral responses and to generate abstract information. If LPFC neurons utilize abstract code to associate a stimulus with a reward, they should be able to infer similar relationships between other stimuli of the same category and their rewards without direct experience of these stimulus-reward contingencies. We propose that this ability of LPFC neurons to utilize abstract information can contribute to the model-based learning process.

Cell Class-Dependent Intracortical Connectivity and Output Dynamics of Layer 6 Projection Neurons of the Rat Primary Visual Cortex.

PubMed

Cotel, Florence; Fletcher, Lee N; Kalita-de Croft, Simon; Apergis-Schoute, John; Williams, Stephen R

2018-07-01

Neocortical information processing is powerfully influenced by the activity of layer 6 projection neurons through control of local intracortical and subcortical circuitry. Morphologically distinct classes of layer 6 projection neuron have been identified in the mammalian visual cortex, which exhibit contrasting receptive field properties, but little information is available on their functional specificity. To address this we combined anatomical tracing techniques with high-resolution patch-clamp recording to identify morphological and functional distinct classes of layer 6 projection neurons in the rat primary visual cortex, which innervated separable subcortical territories. Multisite whole-cell recordings in brain slices revealed that corticoclaustral and corticothalamic layer 6 projection neurons exhibited similar somatically recorded electrophysiological properties. These classes of layer 6 projection neurons were sparsely and reciprocally synaptically interconnected, but could be differentiated by cell-class, but not target-cell-dependent rules of use-dependent depression and facilitation of unitary excitatory synaptic output. Corticoclaustral and corticothalamic layer 6 projection neurons were differentially innervated by columnar excitatory circuitry, with corticoclaustral, but not corticothalamic, neurons powerfully driven by layer 4 pyramidal neurons, and long-range pathways conveyed in neocortical layer 1. Our results therefore reveal projection target-specific, functionally distinct, streams of layer 6 output in the rodent neocortex.

Nonvisual influences on visual-information processing in the superior colliculus.

PubMed

Stein, B E; Jiang, W; Wallace, M T; Stanford, T R

2001-01-01

Although visually responsive neurons predominate in the deep layers of the superior colliculus (SC), the majority of them also receive sensory inputs from nonvisual sources (i.e. auditory and/or somatosensory). Most of these 'multisensory' neurons are able to synthesize their cross-modal inputs and, as a consequence, their responses to visual stimuli can be profoundly enhanced or depressed in the presence of a nonvisual cue. Whether response enhancement or response depression is produced by this multisensory interaction is predictable based on several factors. These include: the organization of a neuron's visual and nonvisual receptive fields; the relative spatial relationships of the different stimuli (to their respective receptive fields and to one another); and whether or not the neuron is innervated by a select population of cortical neurons. The response enhancement or depression of SC neurons via multisensory integration has significant survival value via its profound impact on overt attentive/orientation behaviors. Nevertheless, these multisensory processes are not present at birth, and require an extensive period of postnatal maturation. It seems likely that the sensory experiences obtained during this period play an important role in crafting the processes underlying these multisensory interactions.

Thalamic neuron models encode stimulus information by burst-size modulation

PubMed Central

Elijah, Daniel H.; Samengo, Inés; Montemurro, Marcelo A.

2015-01-01

Thalamic neurons have been long assumed to fire in tonic mode during perceptive states, and in burst mode during sleep and unconsciousness. However, recent evidence suggests that bursts may also be relevant in the encoding of sensory information. Here, we explore the neural code of such thalamic bursts. In order to assess whether the burst code is generic or whether it depends on the detailed properties of each bursting neuron, we analyzed two neuron models incorporating different levels of biological detail. One of the models contained no information of the biophysical processes entailed in spike generation, and described neuron activity at a phenomenological level. The second model represented the evolution of the individual ionic conductances involved in spiking and bursting, and required a large number of parameters. We analyzed the models' input selectivity using reverse correlation methods and information theory. We found that n-spike bursts from both models transmit information by modulating their spike count in response to changes to instantaneous input features, such as slope, phase, amplitude, etc. The stimulus feature that is most efficiently encoded by bursts, however, need not coincide with one of such classical features. We therefore searched for the optimal feature among all those that could be expressed as a linear transformation of the time-dependent input current. We found that bursting neurons transmitted 6 times more information about such more general features. The relevant events in the stimulus were located in a time window spanning ~100 ms before and ~20 ms after burst onset. Most importantly, the neural code employed by the simple and the biologically realistic models was largely the same, implying that the simple thalamic neuron model contains the essential ingredients that account for the computational properties of the thalamic burst code. Thus, our results suggest the n-spike burst code is a general property of thalamic neurons. PMID:26441623

Thalamic neuron models encode stimulus information by burst-size modulation.

PubMed

Elijah, Daniel H; Samengo, Inés; Montemurro, Marcelo A

2015-01-01

Thalamic neurons have been long assumed to fire in tonic mode during perceptive states, and in burst mode during sleep and unconsciousness. However, recent evidence suggests that bursts may also be relevant in the encoding of sensory information. Here, we explore the neural code of such thalamic bursts. In order to assess whether the burst code is generic or whether it depends on the detailed properties of each bursting neuron, we analyzed two neuron models incorporating different levels of biological detail. One of the models contained no information of the biophysical processes entailed in spike generation, and described neuron activity at a phenomenological level. The second model represented the evolution of the individual ionic conductances involved in spiking and bursting, and required a large number of parameters. We analyzed the models' input selectivity using reverse correlation methods and information theory. We found that n-spike bursts from both models transmit information by modulating their spike count in response to changes to instantaneous input features, such as slope, phase, amplitude, etc. The stimulus feature that is most efficiently encoded by bursts, however, need not coincide with one of such classical features. We therefore searched for the optimal feature among all those that could be expressed as a linear transformation of the time-dependent input current. We found that bursting neurons transmitted 6 times more information about such more general features. The relevant events in the stimulus were located in a time window spanning ~100 ms before and ~20 ms after burst onset. Most importantly, the neural code employed by the simple and the biologically realistic models was largely the same, implying that the simple thalamic neuron model contains the essential ingredients that account for the computational properties of the thalamic burst code. Thus, our results suggest the n-spike burst code is a general property of thalamic neurons.

Frequency-specific corticofugal modulation of the dorsal cochlear nucleus in mice.

PubMed

Kong, Lingzhi; Xiong, Colin; Li, Liang; Yan, Jun

2014-01-01

The primary auditory cortex (AI) modulates the sound information processing in the lemniscal subcortical nuclei, including the anteroventral cochlear nucleus (AVCN), in a frequency-specific manner. The dorsal cochlear nucleus (DCN) is a non-lemniscal subcortical nucleus but it is tonotopically organized like the AVCN. However, it remains unclear how the AI modulates the sound information processing in the DCN. This study examined the impact of focal electrical stimulation of AI on the auditory responses of the DCN neurons in mice. We found that the electrical stimulation induced significant changes in the best frequency (BF) of DCN neurons. The changes in the BFs were highly specific to the BF differences between the stimulated AI neurons and the recorded DCN neurons. The DCN BFs shifted higher when the AI BFs were higher than the DCN BFs and the DCN BFs shifted lower when the AI BFs were lower than the DCN BFs. The DCN BFs showed no change when the AI and DCN BFs were similar. Moreover, the BF shifts were linearly correlated to the BF differences. Thus, our data suggest that corticofugal modulation of the DCN is also highly specific to frequency information, similar to the corticofugal modulation of the AVCN. The frequency-specificity of corticofugal modulation does not appear limited to the lemniscal ascending pathway.

Distinct Thalamic Reticular Cell Types Differentially Modulate Normal and Pathological Cortical Rhythms.

PubMed

Clemente-Perez, Alexandra; Makinson, Stefanie Ritter; Higashikubo, Bryan; Brovarney, Scott; Cho, Frances S; Urry, Alexander; Holden, Stephanie S; Wimer, Matthew; Dávid, Csaba; Fenno, Lief E; Acsády, László; Deisseroth, Karl; Paz, Jeanne T

2017-06-06

Integrative brain functions depend on widely distributed, rhythmically coordinated computations. Through its long-ranging connections with cortex and most senses, the thalamus orchestrates the flow of cognitive and sensory information. Essential in this process, the nucleus reticularis thalami (nRT) gates different information streams through its extensive inhibition onto other thalamic nuclei, however, we lack an understanding of how different inhibitory neuron subpopulations in nRT function as gatekeepers. We dissociated the connectivity, physiology, and circuit functions of neurons within rodent nRT, based on parvalbumin (PV) and somatostatin (SOM) expression, and validated the existence of such populations in human nRT. We found that PV, but not SOM, cells are rhythmogenic, and that PV and SOM neurons are connected to and modulate distinct thalamocortical circuits. Notably, PV, but not SOM, neurons modulate somatosensory behavior and disrupt seizures. These results provide a conceptual framework for how nRT may gate incoming information to modulate brain-wide rhythms. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

What and where information in the caudate tail guides saccades to visual objects

PubMed Central

Yamamoto, Shinya; Monosov, Ilya E.; Yasuda, Masaharu; Hikosaka, Okihide

2012-01-01

We understand the world by making saccadic eye movements to various objects. However, it is unclear how a saccade can be aimed at a particular object, because two kinds of visual information, what the object is and where it is, are processed separately in the dorsal and ventral visual cortical pathways. Here we provide evidence suggesting that a basal ganglia circuit through the tail of the monkey caudate nucleus (CDt) guides such object-directed saccades. First, many CDt neurons responded to visual objects depending on where and what the objects were. Second, electrical stimulation in the CDt induced saccades whose directions matched the preferred directions of neurons at the stimulation site. Third, many CDt neurons increased their activity before saccades directed to the neurons’ preferred objects and directions in a free-viewing condition. Our results suggest that CDt neurons receive both ‘what’ and ‘where’ information and guide saccades to visual objects. PMID:22875934

Cell-Type-Specific Modulation of Sensory Responses in Olfactory Bulb Circuits by Serotonergic Projections from the Raphe Nuclei

PubMed Central

Brunert, Daniela; Tsuno, Yusuke; Rothermel, Markus; Shipley, Michael T.

2016-01-01

Serotonergic neurons in the brainstem raphe nuclei densely innervate the olfactory bulb (OB), where they can modulate the initial representation and processing of olfactory information. Serotonergic modulation of sensory responses among defined OB cell types is poorly characterized in vivo. Here, we used cell-type-specific expression of optical reporters to visualize how raphe stimulation alters sensory responses in two classes of GABAergic neurons of the mouse OB glomerular layer, periglomerular (PG) and short axon (SA) cells, as well as mitral/tufted (MT) cells carrying OB output to piriform cortex. In PG and SA cells, brief (1–4 s) raphe stimulation elicited a large increase in the magnitude of responses linked to inhalation of ambient air, as well as modest increases in the magnitude of odorant-evoked responses. Near-identical effects were observed when the optical reporter of glutamatergic transmission iGluSnFR was expressed in PG and SA cells, suggesting enhanced excitatory input to these neurons. In contrast, in MT cells imaged from the dorsal OB, raphe stimulation elicited a strong increase in resting GCaMP fluorescence with only a slight enhancement of inhalation-linked responses to odorant. Finally, optogenetically stimulating raphe serotonergic afferents in the OB had heterogeneous effects on presumptive MT cells recorded extracellularly, with an overall modest increase in resting and odorant-evoked responses during serotonergic afferent stimulation. These results suggest that serotonergic afferents from raphe dynamically modulate olfactory processing through distinct effects on multiple OB targets, and may alter the degree to which OB output is shaped by inhibition during behavior. SIGNIFICANCE STATEMENT Modulation of the circuits that process sensory information can profoundly impact how information about the external world is represented and perceived. This study investigates how the serotonergic system modulates the initial processing of olfactory information by the olfactory bulb, an obligatory relay between sensory neurons and cortex. We find that serotonergic projections from the raphe nuclei to the olfactory bulb dramatically enhance the responses of two classes of inhibitory interneurons to sensory input, that this effect is mediated by increased glutamatergic drive onto these neurons, and that serotonergic afferent activation alters the responses of olfactory bulb output neurons in vivo. These results elucidate pathways by which neuromodulatory systems can dynamically regulate brain circuits during behavior. PMID:27335411

A biophysical signature of network affiliation and sensory processing in mitral cells

PubMed Central

Angelo, Kamilla; Rancz, Ede A.; Pimentel, Diogo; Hundahl, Christian; Hannibal, Jens; Fleischmann, Alexander; Pichler, Bruno; Margrie, Troy W.

2012-01-01

One defining characteristic of the mammalian brain is its neuronal diversity1. For a given region, substructure or layer and even cell type2, variability in neuronal morphology and connectivity2-5 persists. While it is well established that such cellular properties vary considerably according to neuronal type, the significant biophysical diversity of neurons of the same morphological class is typically averaged out and ignored. Here we show that the amplitude of hyperpolarization-evoked membrane potential sag recorded in olfactory bulb mitral cells is an emergent, homotypic property of local networks and sensory information processing. Simultaneous whole-cell recordings from pairs of cells reveal that the amount of hyperpolarization-evoked sag potential and current6 is stereotypic for mitral cells belonging to the same glomerular circuit. This is corroborated by a mosaic, glomerulus-based pattern of expression of the HCN2 subunit of the hyperpolarization-activated current (Ih) channel. Furthermore, inter-glomerular differences in both membrane potential sag and HCN2 protein are diminished when sensory input to glomeruli is genetically and globally altered so only one type of odorant receptor is universally expressed7. We therefore suggest that population diversity in the intrinsic profile of mitral cells reflect functional adaptations of distinct local circuits dedicated to processing subtly different odor-related information. PMID:22820253

Probing the function of neuronal populations: combining micromirror-based optogenetic photostimulation with voltage-sensitive dye imaging.

PubMed

Tsuda, Sachiko; Kee, Michelle Z L; Cunha, Catarina; Kim, Jinsook; Yan, Ping; Loew, Leslie M; Augustine, George J

2013-01-01

Recent advances in our understanding of brain function have come from using light to either control or image neuronal activity. Here we describe an approach that combines both techniques: a micromirror array is used to photostimulate populations of presynaptic neurons expressing channelrhodopsin-2, while a red-shifted voltage-sensitive dye allows optical detection of resulting postsynaptic activity. Such technology allowed us to control the activity of cerebellar interneurons while simultaneously recording inhibitory responses in multiple Purkinje neurons, their postsynaptic targets. This approach should substantially accelerate our understanding of information processing by populations of neurons within brain circuits. Copyright © 2013 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Three-dimensional reconstruction of brain-wide wiring networks in Drosophila at single-cell resolution.

PubMed

Chiang, Ann-Shyn; Lin, Chih-Yung; Chuang, Chao-Chun; Chang, Hsiu-Ming; Hsieh, Chang-Huain; Yeh, Chang-Wei; Shih, Chi-Tin; Wu, Jian-Jheng; Wang, Guo-Tzau; Chen, Yung-Chang; Wu, Cheng-Chi; Chen, Guan-Yu; Ching, Yu-Tai; Lee, Ping-Chang; Lin, Chih-Yang; Lin, Hui-Hao; Wu, Chia-Chou; Hsu, Hao-Wei; Huang, Yun-Ann; Chen, Jing-Yi; Chiang, Hsin-Jung; Lu, Chun-Fang; Ni, Ru-Fen; Yeh, Chao-Yuan; Hwang, Jenn-Kang

2011-01-11

Animal behavior is governed by the activity of interconnected brain circuits. Comprehensive brain wiring maps are thus needed in order to formulate hypotheses about information flow and also to guide genetic manipulations aimed at understanding how genes and circuits orchestrate complex behaviors. To assemble this map, we deconstructed the adult Drosophila brain into approximately 16,000 single neurons and reconstructed them into a common standardized framework to produce a virtual fly brain. We have constructed a mesoscopic map and found that it consists of 41 local processing units (LPUs), six hubs, and 58 tracts covering the whole Drosophila brain. Despite individual local variation, the architecture of the Drosophila brain shows invariance for both the aggregation of local neurons (LNs) within specific LPUs and for the connectivity of projection neurons (PNs) between the same set of LPUs. An open-access image database, named FlyCircuit, has been constructed for online data archiving, mining, analysis, and three-dimensional visualization of all single neurons, brain-wide LPUs, their wiring diagrams, and neural tracts. We found that the Drosophila brain is assembled from families of multiple LPUs and their interconnections. This provides an essential first step in the analysis of information processing within and between neurons in a complete brain. Copyright © 2011 Elsevier Ltd. All rights reserved.

Persistent neural activity in auditory cortex is related to auditory working memory in humans and nonhuman primates

PubMed Central

Huang, Ying; Matysiak, Artur; Heil, Peter; König, Reinhard; Brosch, Michael

2016-01-01

Working memory is the cognitive capacity of short-term storage of information for goal-directed behaviors. Where and how this capacity is implemented in the brain are unresolved questions. We show that auditory cortex stores information by persistent changes of neural activity. We separated activity related to working memory from activity related to other mental processes by having humans and monkeys perform different tasks with varying working memory demands on the same sound sequences. Working memory was reflected in the spiking activity of individual neurons in auditory cortex and in the activity of neuronal populations, that is, in local field potentials and magnetic fields. Our results provide direct support for the idea that temporary storage of information recruits the same brain areas that also process the information. Because similar activity was observed in the two species, the cellular bases of some auditory working memory processes in humans can be studied in monkeys. DOI: http://dx.doi.org/10.7554/eLife.15441.001 PMID:27438411

Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation and Completion of Episodic Information.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aimone, James Bradley; Bernard, Michael Lewis; Vineyard, Craig Michael

2014-10-01

Adult neurogenesis in the hippocampus region of the brain is a neurobiological process that is believed to contribute to the brain's advanced abilities in complex pattern recognition and cognition. Here, we describe how realistic scale simulations of the neurogenesis process can offer both a unique perspective on the biological relevance of this process and confer computational insights that are suggestive of novel machine learning techniques. First, supercomputer based scaling studies of the neurogenesis process demonstrate how a small fraction of adult-born neurons have a uniquely larger impact in biologically realistic scaled networks. Second, we describe a novel technical approach bymore » which the information content of ensembles of neurons can be estimated. Finally, we illustrate several examples of broader algorithmic impact of neurogenesis, including both extending existing machine learning approaches and novel approaches for intelligent sensing.« less

Naftidrofuryl affects neurite regeneration by injured adult auditory neurons.

PubMed

Lefebvre, P P; Staecker, H; Moonen, G; van de Water, T R

1993-07-01

Afferent auditory neurons are essential for the transmission of auditory information from Corti's organ to the central auditory pathway. Auditory neurons are very sensitive to acute insult and have a limited ability to regenerate injured neuronal processes. Therefore, these neurons appear to be a limiting factor in restoration of hearing function following an injury to the peripheral auditory receptor. In a previous study nerve growth factor (NGF) was shown to stimulate neurite repair but not survival of injured auditory neurons. In this study, we have demonstrated a neuritogenesis promoting effect of naftidrofuryl in an vitro model for injury to adult auditory neurons, i.e. dissociated cell cultures of adult rat spiral ganglia. Conversely, naftidrofuryl did not have any demonstrable survival promoting effect on these in vitro preparations of injured auditory neurons. The potential uses of this drug as a therapeutic agent in acute diseases of the inner ear are discussed in the light of these observations.

Closed-form expressions of some stochastic adapting equations for nonlinear adaptive activation function neurons.

PubMed

Fiori, Simone

2003-12-01

In recent work, we introduced nonlinear adaptive activation function (FAN) artificial neuron models, which learn their activation functions in an unsupervised way by information-theoretic adapting rules. We also applied networks of these neurons to some blind signal processing problems, such as independent component analysis and blind deconvolution. The aim of this letter is to study some fundamental aspects of FAN units' learning by investigating the properties of the associated learning differential equation systems.

Structural synaptic plasticity in the hippocampus induced by spatial experience and its implications in information processing.

PubMed

Carasatorre, M; Ramírez-Amaya, V; Díaz Cintra, S

2016-10-01

Long-lasting memory formation requires that groups of neurons processing new information develop the ability to reproduce the patterns of neural activity acquired by experience. Changes in synaptic efficiency let neurons organise to form ensembles that repeat certain activity patterns again and again. Among other changes in synaptic plasticity, structural modifications tend to be long-lasting which suggests that they underlie long-term memory. There is a large body of evidence supporting that experience promotes changes in the synaptic structure, particularly in the hippocampus. Structural changes to the hippocampus may be functionally implicated in stabilising acquired memories and encoding new information. Copyright © 2012 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Face inversion decreased information about facial identity and expression in face-responsive neurons in macaque area TE.

PubMed

Sugase-Miyamoto, Yasuko; Matsumoto, Narihisa; Ohyama, Kaoru; Kawano, Kenji

2014-09-10

To investigate the effect of face inversion and thatcherization (eye inversion) on temporal processing stages of facial information, single neuron activities in the temporal cortex (area TE) of two rhesus monkeys were recorded. Test stimuli were colored pictures of monkey faces (four with four different expressions), human faces (three with four different expressions), and geometric shapes. Modifications were made in each face-picture, and its four variations were used as stimuli: upright original, inverted original, upright thatcherized, and inverted thatcherized faces. A total of 119 neurons responded to at least one of the upright original facial stimuli. A majority of the neurons (71%) showed activity modulations depending on upright and inverted presentations, and a lesser number of neurons (13%) showed activity modulations depending on original and thatcherized face conditions. In the case of face inversion, information about the fine category (facial identity and expression) decreased, whereas information about the global category (monkey vs human vs shape) was retained for both the original and thatcherized faces. Principal component analysis on the neuronal population responses revealed that the global categorization occurred regardless of the face inversion and that the inverted faces were represented near the upright faces in the principal component analysis space. By contrast, the face inversion decreased the ability to represent human facial identity and monkey facial expression. Thus, the neuronal population represented inverted faces as faces but failed to represent the identity and expression of the inverted faces, indicating that the neuronal representation in area TE cause the perceptual effect of face inversion. Copyright © 2014 the authors 0270-6474/14/3412457-13$15.00/0.

μ-Opioid Receptor-Mediated Inhibition of Intercalated Neurons and Effect on Synaptic Transmission to the Central Amygdala.

PubMed

Blaesse, Peter; Goedecke, Lena; Bazelot, Michaël; Capogna, Marco; Pape, Hans-Christian; Jüngling, Kay

2015-05-13

The amygdala is a key region for the processing of information underlying fear, anxiety, and fear extinction. Within the local neuronal networks of the amygdala, a population of inhibitory, intercalated neurons (ITCs) modulates the flow of information among various nuclei of amygdala, including the basal nucleus (BA) and the centromedial nucleus (CeM) of the amygdala. These ITCs have been shown to be important during fear extinction and are target of a variety of neurotransmitters and neuropeptides. Here we provide evidence that the activation of μ-opioid receptors (MORs) by the specific agonist DAMGO ([D-Ala2,N-Me-Phe4,Gly5-ol]-Enkephalin) hyperpolarizes medially located ITCs (mITCs) in acute brain slices of mice. Moreover, we use whole-cell patch-clamp recordings in combination with local electrical stimulation or glutamate uncaging to analyze the effect of MOR activation on local microcircuits. We show that the GABAergic transmission between mITCs and CeM neurons is attenuated by DAMGO, whereas the glutamatergic transmission on CeM neurons and mITCs is unaffected. Furthermore, MOR activation induced by theta burst stimulation in BA suppresses plastic changes of feedforward inhibitory transmission onto CeM neurons as revealed by the MOR antagonist CTAP d-Phe-Cys-Tyr-d-Trp-Arg-Thr-Pen-Thr-NH2. In summary, the mITCs constitute a target for the opioid system, and therefore, the activation of MOR in ITCs might play a central role in the modulation of the information processing between the basolateral complex of the amygdala and central nuclei of the amygdala. Copyright © 2015 Blaesse, Goedecke et al.

Dopamine-dependent non-linear correlation between subthalamic rhythms in Parkinson's disease.

PubMed

Marceglia, S; Foffani, G; Bianchi, A M; Baselli, G; Tamma, F; Egidi, M; Priori, A

2006-03-15

The basic information architecture in the basal ganglia circuit is under debate. Whereas anatomical studies quantify extensive convergence/divergence patterns in the circuit, suggesting an information sharing scheme, neurophysiological studies report an absence of linear correlation between single neurones in normal animals, suggesting a segregated parallel processing scheme. In 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated monkeys and in parkinsonian patients single neurones become linearly correlated, thus leading to a loss of segregation between neurones. Here we propose a possible integrative solution to this debate, by extending the concept of functional segregation from the cellular level to the network level. To this end, we recorded local field potentials (LFPs) from electrodes implanted for deep brain stimulation (DBS) in the subthalamic nucleus (STN) of parkinsonian patients. By applying bispectral analysis, we found that in the absence of dopamine stimulation STN LFP rhythms became non-linearly correlated, thus leading to a loss of segregation between rhythms. Non-linear correlation was particularly consistent between the low-beta rhythm (13-20 Hz) and the high-beta rhythm (20-35 Hz). Levodopa administration significantly decreased these non-linear correlations, therefore increasing segregation between rhythms. These results suggest that the extensive convergence/divergence in the basal ganglia circuit is physiologically necessary to sustain LFP rhythms distributed in large ensembles of neurones, but is not sufficient to induce correlated firing between neurone pairs. Conversely, loss of dopamine generates pathological linear correlation between neurone pairs, alters the patterns within LFP rhythms, and induces non-linear correlation between LFP rhythms operating at different frequencies. The pathophysiology of information processing in the human basal ganglia therefore involves not only activities of individual rhythms, but also interactions between rhythms.

Dopamine-dependent non-linear correlation between subthalamic rhythms in Parkinson's disease

PubMed Central

Marceglia, S; Foffani, G; Bianchi, A M; Baselli, G; Tamma, F; Egidi, M; Priori, A

2006-01-01

The basic information architecture in the basal ganglia circuit is under debate. Whereas anatomical studies quantify extensive convergence/divergence patterns in the circuit, suggesting an information sharing scheme, neurophysiological studies report an absence of linear correlation between single neurones in normal animals, suggesting a segregated parallel processing scheme. In 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated monkeys and in parkinsonian patients single neurones become linearly correlated, thus leading to a loss of segregation between neurones. Here we propose a possible integrative solution to this debate, by extending the concept of functional segregation from the cellular level to the network level. To this end, we recorded local field potentials (LFPs) from electrodes implanted for deep brain stimulation (DBS) in the subthalamic nucleus (STN) of parkinsonian patients. By applying bispectral analysis, we found that in the absence of dopamine stimulation STN LFP rhythms became non-linearly correlated, thus leading to a loss of segregation between rhythms. Non-linear correlation was particularly consistent between the low-beta rhythm (13–20 Hz) and the high-beta rhythm (20–35 Hz). Levodopa administration significantly decreased these non-linear correlations, therefore increasing segregation between rhythms. These results suggest that the extensive convergence/divergence in the basal ganglia circuit is physiologically necessary to sustain LFP rhythms distributed in large ensembles of neurones, but is not sufficient to induce correlated firing between neurone pairs. Conversely, loss of dopamine generates pathological linear correlation between neurone pairs, alters the patterns within LFP rhythms, and induces non-linear correlation between LFP rhythms operating at different frequencies. The pathophysiology of information processing in the human basal ganglia therefore involves not only activities of individual rhythms, but also interactions between rhythms. PMID:16410285

Neurons selective to the number of visual items in the corvid songbird endbrain

PubMed Central

Ditz, Helen M.; Nieder, Andreas

2015-01-01

It is unknown whether anatomical specializations in the endbrains of different vertebrates determine the neuronal code to represent numerical quantity. Therefore, we recorded single-neuron activity from the endbrain of crows trained to judge the number of items in displays. Many neurons were tuned for numerosities irrespective of the physical appearance of the items, and their activity correlated with performance outcome. Comparison of both behavioral and neuronal representations of numerosity revealed that the data are best described by a logarithmically compressed scaling of numerical information, as postulated by the Weber–Fechner law. The behavioral and neuronal numerosity representations in the crow reflect surprisingly well those found in the primate association cortex. This finding suggests that distantly related vertebrates with independently developed endbrains adopted similar neuronal solutions to process quantity. PMID:26056278

Face processing in different brain areas, and critical band masking.

PubMed

Rolls, Edmund T

2008-09-01

Neurophysiological evidence is described showing that some neurons in the macaque inferior temporal visual cortex have responses that are invariant with respect to the position, size, view, and spatial frequency of faces and objects, and that these neurons show rapid processing and rapid learning. Critical band spatial frequency masking is shown to be a property of these face-selective neurons and of the human visual perception of faces. Which face or object is present is encoded using a distributed representation in which each neuron conveys independent information in its firing rate, with little information evident in the relative time of firing of different neurons. This ensemble encoding has the advantages of maximizing the information in the representation useful for discrimination between stimuli using a simple weighted sum of the neuronal firing by the receiving neurons, generalization, and graceful degradation. These invariant representations are ideally suited to provide the inputs to brain regions such as the orbitofrontal cortex and amygdala that learn the reinforcement associations of an individual's face, for then the learning, and the appropriate social and emotional responses generalize to other views of the same face. A theory is described of how such invariant representations may be produced by self-organizing learning in a hierarchically organized set of visual cortical areas with convergent connectivity. The theory utilizes either temporal or spatial continuity with an associative synaptic modification rule. Another population of neurons in the cortex in the superior temporal sulcus encodes other aspects of faces such as face expression, eye-gaze, face view, and whether the head is moving. These neurons thus provide important additional inputs to parts of the brain such as the orbitofrontal cortex and amygdala that are involved in social communication and emotional behaviour. Outputs of these systems reach the amygdala, in which face-selective neurons are found, and also the orbitofrontal cortex, in which some neurons are tuned to face identity and others to face expression. In humans, activation of the orbitofrontal cortex is found when a change of face expression acts as a social signal that behaviour should change; and damage to the human orbitofrontal and pregenual cingulate cortex can impair face and voice expression identification, and also the reversal of emotional behaviour that normally occurs when reinforcers are reversed.

The Representation of Information about Faces in the Temporal and Frontal Lobes

ERIC Educational Resources Information Center

Rolls, Edmund T.

2007-01-01

Neurophysiological evidence is described showing that some neurons in the macaque inferior temporal visual cortex have responses that are invariant with respect to the position, size and view of faces and objects, and that these neurons show rapid processing and rapid learning. Which face or object is present is encoded using a distributed…

Stanislas Dehaene's Les Neurones de la Lecture

ERIC Educational Resources Information Center

Battro, Antonio M.

2008-01-01

Stanislas Dehaene has published a remarkable book on the neurons of reading. It is a comprehensive description of the main issues related to the "paradox of reading": how humans process linguistic information using the visual brain path while the brain has not evolved in the short period of time since the invention of writing. The article presents…

Neuronal coding of implicit emotion categories in the subcallosal cortex in patients with depression.

PubMed

Laxton, Adrian W; Neimat, Joseph S; Davis, Karen D; Womelsdorf, Thilo; Hutchison, William D; Dostrovsky, Jonathan O; Hamani, Clement; Mayberg, Helen S; Lozano, Andres M

2013-11-15

The subcallosal cingulate and adjacent ventromedial prefrontal cortex (collectively referred to here as the subcallosal cortex or SCC) have been identified as key brain areas in emotional processing. The SCC's role in affective valuation as well as severe mood and motivational disturbances, such as major depression, has been largely inferred from measures of neuronal population activity using functional neuroimaging. On the basis of imaging studies, it is unclear whether the SCC predominantly processes 1) negatively valenced affective content, 2) affective arousal, or 3) category-specific affective information. To clarify these putative functional roles of the SCC, we measured single neuron activity in the SCC of 15 human subjects undergoing deep brain stimulation for depression while they viewed emotionally evocative images grouped into categories that varied in emotional valence (pleasantness) and arousal. We found that the majority of responsive neurons were modulated by specific emotion categories, rather than by valence or arousal alone. Moreover, although these emotion-category-specific neurons responded to both positive and negative emotion categories, a significant majority were selective for negatively valenced emotional content. These findings reveal that single SCC neuron activity reflects the automatic valuational processing and implicit emotion categorization of visual stimuli. Furthermore, because of the predominance of neuronal signals in SCC conveying negative affective valuations and the increased activity in this region among depressed people, the effectiveness of depression therapies that alter SCC neuronal activity may relate to the down-regulation of a previously negative emotional processing bias. © 2013 Society of Biological Psychiatry.

Layer-specific excitation/inhibition balances during neuronal synchronization in the visual cortex.

PubMed

Adesnik, Hillel

2018-05-01

Understanding the balance between synaptic excitation and inhibition in cortical circuits in the brain, and how this contributes to cortical rhythms, is fundamental to explaining information processing in the cortex. This study used cortical layer-specific optogenetic activation in mouse cortex to show that excitatory neurons in any cortical layer can drive powerful gamma rhythms, while inhibition balances excitation. The net impact of this is to keep activity within each layer in check, but simultaneously to promote the propagation of activity to downstream layers. The data show that rhythm-generating circuits exist in all principle layers of the cortex, and provide layer-specific balances of excitation and inhibition that affect the flow of information across the layers. Rhythmic activity can synchronize neural ensembles within and across cortical layers. While gamma band rhythmicity has been observed in all layers, the laminar sources and functional impacts of neuronal synchronization in the cortex remain incompletely understood. Here, layer-specific optogenetic stimulation demonstrates that populations of excitatory neurons in any cortical layer of the mouse's primary visual cortex are sufficient to powerfully entrain neuronal oscillations in the gamma band. Within each layer, inhibition balances excitation and keeps activity in check. Across layers, translaminar output overcomes inhibition and drives downstream firing. These data establish that rhythm-generating circuits exist in all principle layers of the cortex, but provide layer-specific balances of excitation and inhibition that may dynamically shape the flow of information through cortical circuits. These data might help explain how excitation/inhibition (E/I) balances across cortical layers shape information processing, and shed light on the diverse nature and functional impacts of cortical gamma rhythms. © 2018 The Authors. The Journal of Physiology © 2018 The Physiological Society.

Contribution of LFP dynamics to single-neuron spiking variability in motor cortex during movement execution

PubMed Central

Rule, Michael E.; Vargas-Irwin, Carlos; Donoghue, John P.; Truccolo, Wilson

2015-01-01

Understanding the sources of variability in single-neuron spiking responses is an important open problem for the theory of neural coding. This variability is thought to result primarily from spontaneous collective dynamics in neuronal networks. Here, we investigate how well collective dynamics reflected in motor cortex local field potentials (LFPs) can account for spiking variability during motor behavior. Neural activity was recorded via microelectrode arrays implanted in ventral and dorsal premotor and primary motor cortices of non-human primates performing naturalistic 3-D reaching and grasping actions. Point process models were used to quantify how well LFP features accounted for spiking variability not explained by the measured 3-D reach and grasp kinematics. LFP features included the instantaneous magnitude, phase and analytic-signal components of narrow band-pass filtered (δ,θ,α,β) LFPs, and analytic signal and amplitude envelope features in higher-frequency bands. Multiband LFP features predicted single-neuron spiking (1ms resolution) with substantial accuracy as assessed via ROC analysis. Notably, however, models including both LFP and kinematics features displayed marginal improvement over kinematics-only models. Furthermore, the small predictive information added by LFP features to kinematic models was redundant to information available in fast-timescale (<100 ms) spiking history. Overall, information in multiband LFP features, although predictive of single-neuron spiking during movement execution, was redundant to information available in movement parameters and spiking history. Our findings suggest that, during movement execution, collective dynamics reflected in motor cortex LFPs primarily relate to sensorimotor processes directly controlling movement output, adding little explanatory power to variability not accounted by movement parameters. PMID:26157365

Surface dynamics of voltage-gated ion channels.

PubMed

Heine, Martin; Ciuraszkiewicz, Anna; Voigt, Andreas; Heck, Jennifer; Bikbaev, Arthur

2016-07-03

Neurons encode information in fast changes of the membrane potential, and thus electrical membrane properties are critically important for the integration and processing of synaptic inputs by a neuron. These electrical properties are largely determined by ion channels embedded in the membrane. The distribution of most ion channels in the membrane is not spatially uniform: they undergo activity-driven changes in the range of minutes to days. Even in the range of milliseconds, the composition and topology of ion channels are not static but engage in highly dynamic processes including stochastic or activity-dependent transient association of the pore-forming and auxiliary subunits, lateral diffusion, as well as clustering of different channels. In this review we briefly discuss the potential impact of mobile sodium, calcium and potassium ion channels and the functional significance of this for individual neurons and neuronal networks.

Surface dynamics of voltage-gated ion channels

PubMed Central

Heine, Martin; Ciuraszkiewicz, Anna; Voigt, Andreas; Heck, Jennifer; Bikbaev, Arthur

2016-01-01

ABSTRACT Neurons encode information in fast changes of the membrane potential, and thus electrical membrane properties are critically important for the integration and processing of synaptic inputs by a neuron. These electrical properties are largely determined by ion channels embedded in the membrane. The distribution of most ion channels in the membrane is not spatially uniform: they undergo activity-driven changes in the range of minutes to days. Even in the range of milliseconds, the composition and topology of ion channels are not static but engage in highly dynamic processes including stochastic or activity-dependent transient association of the pore-forming and auxiliary subunits, lateral diffusion, as well as clustering of different channels. In this review we briefly discuss the potential impact of mobile sodium, calcium and potassium ion channels and the functional significance of this for individual neurons and neuronal networks. PMID:26891382

Postnatal Ablation of Synaptic Retinoic Acid Signaling Impairs Cortical Information Processing and Sensory Discrimination in Mice.

PubMed

Park, Esther; Tjia, Michelle; Zuo, Yi; Chen, Lu

2018-06-06

Retinoic acid (RA) and its receptors (RARs) are well established essential transcriptional regulators during embryonic development. Recent findings in cultured neurons identified an independent and critical post-transcriptional role of RA and RARα in the homeostatic regulation of excitatory and inhibitory synaptic transmission in mature neurons. However, the functional relevance of synaptic RA signaling in vivo has not been established. Here, using somatosensory cortex as a model system and the RARα conditional knock-out mouse as a tool, we applied multiple genetic manipulations to delete RARα postnatally in specific populations of cortical neurons, and asked whether synaptic RA signaling observed in cultured neurons is involved in cortical information processing in vivo Indeed, conditional ablation of RARα in mice via a CaMKIIα-Cre or a layer 5-Cre driver line or via somatosensory cortex-specific viral expression of Cre-recombinase impaired whisker-dependent texture discrimination, suggesting a critical requirement of RARα expression in L5 pyramidal neurons of somatosensory cortex for normal tactile sensory processing. Transcranial two-photon imaging revealed a significant increase in dendritic spine elimination on apical dendrites of somatosensory cortical layer 5 pyramidal neurons in these mice. Interestingly, the enhancement of spine elimination is whisker experience-dependent as whisker trimming rescued the spine elimination phenotype. Additionally, experiencing an enriched environment improved texture discrimination in RARα-deficient mice and reduced excessive spine pruning. Thus, RA signaling is essential for normal experience-dependent cortical circuit remodeling and sensory processing. SIGNIFICANCE STATEMENT The importance of synaptic RA signaling has been demonstrated in in vitro studies. However, whether RA signaling mediated by RARα contributes to neural circuit functions in vivo remains largely unknown. In this study, using a RARα conditional knock-out mouse, we performed multiple regional/cell-type-specific manipulation of RARα expression in the postnatal brain, and show that RARα signaling contributes to normal whisker-dependent texture discrimination as well as regulating spine dynamics of apical dendrites from layer (L5) pyramidal neurons in S1. Deletion of RARα in excitatory neurons in the forebrain induces elevated spine elimination and impaired sensory discrimination. Our study provides novel insights into the role of RARα signaling in cortical processing and experience-dependent spine maturation. Copyright © 2018 the authors 0270-6474/18/385277-12$15.00/0.

Cellular complexity in subcortical white matter: a distributed control circuit?

PubMed

Colombo, Jorge A

2018-03-01

The subcortical white matter (SWM) has been traditionally considered as a site for passive-neutral-information transfer through cerebral cortex association and projection fibers. Yet, the presence of subcortical neuronal and glial "interstitial" cells expressing immunolabelled neurotransmitters/neuromodulators and synaptic vesicular proteins, and recent immunohistochemical and electrophysiological observations on the rat visual cortex as well as interactive regulation of myelinating processes support the possibility that SWM nests subcortical, regionally variable, distributed neuronal-glial circuits, that could influence information transfer. Their hypothetical involvement in regulating the timing and signal transfer probability at the SWM axonal components ought to be considered and experimentally analysed. Thus, the "interstitial" neuronal cells-associated with local glial cells-traditionally considered to be vestigial and functionally inert under normal conditions, they may well turn to be critical in regulating information transfer at the SWM.

Sub-millisecond closed-loop feedback stimulation between arbitrary sets of individual neurons

PubMed Central

Müller, Jan; Bakkum, Douglas J.; Hierlemann, Andreas

2012-01-01

We present a system to artificially correlate the spike timing between sets of arbitrary neurons that were interfaced to a complementary metal–oxide–semiconductor (CMOS) high-density microelectrode array (MEA). The system features a novel reprogrammable and flexible event engine unit to detect arbitrary spatio-temporal patterns of recorded action potentials and is capable of delivering sub-millisecond closed-loop feedback of electrical stimulation upon trigger events in real-time. The relative timing between action potentials of individual neurons as well as the temporal pattern among multiple neurons, or neuronal assemblies, is considered an important factor governing memory and learning in the brain. Artificially changing timings between arbitrary sets of spiking neurons with our system could provide a “knob” to tune information processing in the network. PMID:23335887

A structural and a functional aspect of stable information processing by the brain

PubMed Central

2007-01-01

Brain is an expert in producing the same output from a particular set of inputs, even from a very noisy environment. In this article a model of neural circuit in the brain has been proposed which is composed of cyclic sub-circuits. A big loop has been defined to be consisting of a feed forward path from the sensory neurons to the highest processing area of the brain and feed back paths from that region back up to close to the same sensory neurons. It has been mathematically shown how some smaller cycles can amplify signal. A big loop processes information by contrast and amplify principle. How a pair of presynaptic and postsynaptic neurons can be identified by an exact synchronization detection method has also been mentioned. It has been assumed that the spike train coming out of a firing neuron encodes all the information produced by it as output. It is possible to extract this information over a period of time by Fourier transforms. The Fourier coefficients arranged in a vector form will uniquely represent the neural spike train over a period of time. The information emanating out of all the neurons in a given neural circuit over a period of time can be represented by a collection of points in a multidimensional vector space. This cluster of points represents the functional or behavioral form of the neural circuit. It has been proposed that a particular cluster of vectors as the representation of a new behavior is chosen by the brain interactively with respect to the memory stored in that circuit and the amount of emotion involved. It has been proposed that in this situation a Coulomb force like expression governs the dynamics of functioning of the circuit and stability of the system is reached at the minimum of all the minima of a potential function derived from the force like expression. The calculations have been done with respect to a pseudometric defined in a multidimensional vector space. PMID:19003500

Cortico-Cortical interactions between and within three cortical auditory areas specialized for time-domain signal processing

PubMed Central

Tang, Jie; Suga, Nobuo

2009-01-01

In auditory cortex of the mustached bat, the FF (F means frequency modulation), dorsal fringe (DF) and ventral fringe (VF) areas consist of “combination-sensitive” neurons tuned to the pair of an emitted biosonar pulse and its echo with a specific delay (best delay: BD). The DF and VF areas are hierarchically at a higher level than the FF area. Focal electric stimulation of the FF area evokes “centrifugal” BD shifts of DF neurons, i.e., shifts away from the BD of the stimulated FF neurons, whereas stimulation of the DF neurons evokes “centripetal” BD shifts of FF neurons, i.e., shifts toward the BD of the stimulated DF neurons. In our current studies, we found that the feed forward projection from FF neurons evokes centrifugal BD shifts of VF neurons, that the feedback projection from VF neurons evokes centripetal BD shifts of FF neurons, that the contralateral projection from DF neurons evokes centripetal BD shifts of DF neurons, and that the centripetal BD shifts evoked by the DF and VF neurons are 2.5 times larger than the centrifugal BD shifts evoked by the FF neurons. The centrifugal BD shifts shape the selective neural representation of a specific target-distance, whereas the centripetal BD shifts expand the representation of the selected specific target-distance to focus on the processing of the target information at a specific distance. The centrifugal and centripetal BD shifts evoked by the feed forward and feedback projections promote finer analysis of a target at shorter distances. PMID:19494145

Graph-based unsupervised segmentation algorithm for cultured neuronal networks' structure characterization and modeling.

PubMed

de Santos-Sierra, Daniel; Sendiña-Nadal, Irene; Leyva, Inmaculada; Almendral, Juan A; Ayali, Amir; Anava, Sarit; Sánchez-Ávila, Carmen; Boccaletti, Stefano

2015-06-01

Large scale phase-contrast images taken at high resolution through the life of a cultured neuronal network are analyzed by a graph-based unsupervised segmentation algorithm with a very low computational cost, scaling linearly with the image size. The processing automatically retrieves the whole network structure, an object whose mathematical representation is a matrix in which nodes are identified neurons or neurons' clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocytochemistry techniques, our non invasive measures entitle us to perform a longitudinal analysis during the maturation of a single culture. Such an analysis furnishes the way of individuating the main physical processes underlying the self-organization of the neurons' ensemble into a complex network, and drives the formulation of a phenomenological model yet able to describe qualitatively the overall scenario observed during the culture growth. © 2014 International Society for Advancement of Cytometry.

M-type potassium conductance controls the emergence of neural phase codes: a combined experimental and neuron modelling study

PubMed Central

Kwag, Jeehyun; Jang, Hyun Jae; Kim, Mincheol; Lee, Sujeong

2014-01-01

Rate and phase codes are believed to be important in neural information processing. Hippocampal place cells provide a good example where both coding schemes coexist during spatial information processing. Spike rate increases in the place field, whereas spike phase precesses relative to the ongoing theta oscillation. However, what intrinsic mechanism allows for a single neuron to generate spike output patterns that contain both neural codes is unknown. Using dynamic clamp, we simulate an in vivo-like subthreshold dynamics of place cells to in vitro CA1 pyramidal neurons to establish an in vitro model of spike phase precession. Using this in vitro model, we show that membrane potential oscillation (MPO) dynamics is important in the emergence of spike phase codes: blocking the slowly activating, non-inactivating K+ current (IM), which is known to control subthreshold MPO, disrupts MPO and abolishes spike phase precession. We verify the importance of adaptive IM in the generation of phase codes using both an adaptive integrate-and-fire and a Hodgkin–Huxley (HH) neuron model. Especially, using the HH model, we further show that it is the perisomatically located IM with slow activation kinetics that is crucial for the generation of phase codes. These results suggest an important functional role of IM in single neuron computation, where IM serves as an intrinsic mechanism allowing for dual rate and phase coding in single neurons. PMID:25100320

The Role of Astrocytes in the Generation, Migration, and Integration of New Neurons in the Adult Olfactory Bulb

PubMed Central

Gengatharan, Archana; Bammann, Rodrigo R.; Saghatelyan, Armen

2016-01-01

In mammals, new neurons in the adult olfactory bulb originate from a pool of neural stem cells in the subventricular zone of the lateral ventricles. Adult-born cells play an important role in odor information processing by adjusting the neuronal network to changing environmental conditions. Olfactory bulb neurogenesis is supported by several non-neuronal cells. In this review, we focus on the role of astroglial cells in the generation, migration, integration, and survival of new neurons in the adult forebrain. In the subventricular zone, neural stem cells with astrocytic properties display regional and temporal specificity when generating different neuronal subtypes. Non-neurogenic astrocytes contribute to the establishment and maintenance of the neurogenic niche. Neuroblast chains migrate through the rostral migratory stream ensheathed by astrocytic processes. Astrocytes play an important regulatory role in neuroblast migration and also assist in the development of a vasculature scaffold in the migratory stream that is essential for neuroblast migration in the postnatal brain. In the olfactory bulb, astrocytes help to modulate the network through a complex release of cytokines, regulate blood flow, and provide metabolic support, which may promote the integration and survival of new neurons. Astrocytes thus play a pivotal role in various processes of adult olfactory bulb neurogenesis, and it is likely that many other functions of these glial cells will emerge in the near future. PMID:27092050

Robustness of cortical and subcortical processing in the presence of natural masking sounds.

PubMed

Beetz, M Jerome; García-Rosales, Francisco; Kössl, Manfred; Hechavarría, Julio C

2018-05-01

Processing of ethologically relevant stimuli could be interfered by non-relevant stimuli. Animals have behavioral adaptations to reduce signal interference. It is largely unexplored whether the behavioral adaptations facilitate neuronal processing of relevant stimuli. Here, we characterize behavioral adaptations in the presence of biotic noise in the echolocating bat Carollia perspicillata and we show that the behavioral adaptations could facilitate neuronal processing of biosonar information. According to the echolocation behavior, bats need to extract their own signals in the presence of vocalizations from conspecifics. With playback experiments, we demonstrate that C. perspicillata increases the sensory acquisition rate by emitting groups of echolocation calls when flying in noisy environments. Our neurophysiological results from the auditory midbrain and cortex show that the high sensory acquisition rate does not vastly increase neuronal suppression and that the response to an echolocation sequence is partially preserved in the presence of biosonar signals from conspecifics.

Neuronal Entropy-Rate Feature of Entopeduncular Nucleus in Rat Model of Parkinson's Disease.

PubMed

Darbin, Olivier; Jin, Xingxing; Von Wrangel, Christof; Schwabe, Kerstin; Nambu, Atsushi; Naritoku, Dean K; Krauss, Joachim K; Alam, Mesbah

2016-03-01

The function of the nigro-striatal pathway on neuronal entropy in the basal ganglia (BG) output nucleus, i.e. the entopeduncular nucleus (EPN) was investigated in the unilaterally 6-hyroxydopamine (6-OHDA)-lesioned rat model of Parkinson's disease (PD). In both control subjects and subjects with 6-OHDA lesion of dopamine (DA) the nigro-striatal pathway, a histological hallmark for parkinsonism, neuronal entropy in EPN was maximal in neurons with firing rates ranging between 15 and 25 Hz. In 6-OHDA lesioned rats, neuronal entropy in the EPN was specifically higher in neurons with firing rates above 25 Hz. Our data establishes that the nigro-striatal pathway controls neuronal entropy in motor circuitry and that the parkinsonian condition is associated with abnormal relationship between firing rate and neuronal entropy in BG output nuclei. The neuronal firing rates and entropy relationship provide putative relevant electrophysiological information to investigate the sensory-motor processing in normal condition and conditions such as movement disorders.

RELATIONSHIP BETWEEN ENTROPY OF SPIKE TIMING AND FIRING RATE IN ENTOPEDUNCULAR NUCLEUS NEURONS IN ANESTHETIZED RATS: FUNCTION OF THE NIGRO-STRIATAL PATHWAY

PubMed Central

Darbin, Olivier; Jin, Xingxing; von Wrangel, Christof; Schwabe, Kerstin; Nambu, Atsushi; Naritoku, Dean K; Krauss, Joachim K.; Alam, Mesbah

2016-01-01

The function of the nigro-striatal pathway on neuronal entropy in the basal ganglia (BG) output nucleus (entopeduncular nucleus, EPN) was investigated in the unilaterally 6-hyroxydopamine (6-OHDA)-lesioned rat model of Parkinson’s disease (PD). In both control subjects and subjects with 6-OHDA lesion of the nigro-striatal pathway, a histological hallmark for parkinsonism, neuronal entropy in EPN was maximal in neurons with firing rates ranging between 15Hz and 25 Hz. In 6-OHDA lesioned rats, neuronal entropy in the EPN was specifically higher in neurons with firing rates above 25Hz. Our data establishes that nigro-striatal pathway controls neuronal entropy in motor circuitry and that the parkinsonian condition is associated with abnormal relationship between firing rate and neuronal entropy in BG output nuclei. The neuronal firing rates and entropy relationship provide putative relevant electrophysiological information to investigate the sensory-motor processing in normal condition and conditions with movement disorders. PMID:26711712

Computational exploration of neuron and neural network models in neurobiology.

PubMed

Prinz, Astrid A

2007-01-01

The electrical activity of individual neurons and neuronal networks is shaped by the complex interplay of a large number of non-linear processes, including the voltage-dependent gating of ion channels and the activation of synaptic receptors. These complex dynamics make it difficult to understand how individual neuron or network parameters-such as the number of ion channels of a given type in a neuron's membrane or the strength of a particular synapse-influence neural system function. Systematic exploration of cellular or network model parameter spaces by computational brute force can overcome this difficulty and generate comprehensive data sets that contain information about neuron or network behavior for many different combinations of parameters. Searching such data sets for parameter combinations that produce functional neuron or network output provides insights into how narrowly different neural system parameters have to be tuned to produce a desired behavior. This chapter describes the construction and analysis of databases of neuron or neuronal network models and describes some of the advantages and downsides of such exploration methods.

Synchronization in neural nets

NASA Technical Reports Server (NTRS)

Vidal, Jacques J.; Haggerty, John

1988-01-01

The paper presents an artificial neural network concept (the Synchronizable Oscillator Networks) where the instants of individual firings in the form of point processes constitute the only form of information transmitted between joining neurons. In the model, neurons fire spontaneously and regularly in the absence of perturbation. When interaction is present, the scheduled firings are advanced or delayed by the firing of neighboring neurons. Networks of such neurons become global oscillators which exhibit multiple synchronizing attractors. From arbitrary initial states, energy minimization learning procedures can make the network converge to oscillatory modes that satisfy multi-dimensional constraints. Such networks can directly represent routing and scheduling problems that consist of ordering sequences of events.

Monkey primary somatosensory cortical activity during the early reaction time period differs with cues that guide movements

PubMed Central

Liu, Yu; Denton, John M.; Nelson, Randall J.

2009-01-01

Vibration-related neurons in monkey primary somatosensory cortex (SI) discharge rhythmically when vibratory stimuli are presented. It remains unclear how functional information carried by vibratory inputs is coded in rhythmic neuronal activity. In the present study, we compared neuronal activity during wrist movements in response to two sets of cues. In the first, movements were guided by vibratory cue only (VIB trials). In the second, movements were guided by simultaneous presentation of both vibratory and visual cues (COM trials). SI neurons were recorded extracellularly during both wrist extensions and flexions. Neuronal activity during the instructed delay period (IDP) and the early reaction time period (RTP) were analyzed. A total of 96 cases from 48 neurons (each neuron contributed two cases, one each for extension and flexion) showed significant vibration entrainment during the early RTPs, as determined by circular statistics (Rayleigh test). Of these, 50 cases had cutaneous (CUTA) and 46 had deep (DEEP) receptive fields. The CUTA neurons showed lower firing rates during the IDPs and greater firing rate changes during the early RTPs when compared with the DEEP neurons. The CUTA neurons also demonstrated decreases in activity entrainment during VIB trials when compared with COM trials. For the DEEP neurons, the difference of entrainment between VIB and COM trials was not statistically significant. The results suggest that somatic vibratory input is coded by both the firing rate and the activity entrainment of the CUTA neurons in SI. The results also suggest that when vibratory inputs are required for successful task completion, the activity of the CUTA neurons increases but the entrainment degrades. The DEEP neurons may be tuned before movement initiation for processing information encoded by proprioceptive afferents. PMID:18288475

Monkey primary somatosensory cortical activity during the early reaction time period differs with cues that guide movements.

PubMed

Liu, Yu; Denton, John M; Nelson, Randall J

2008-05-01

Vibration-related neurons in monkey primary somatosensory cortex (SI) discharge rhythmically when vibratory stimuli are presented. It remains unclear how functional information carried by vibratory inputs is coded in rhythmic neuronal activity. In the present study, we compared neuronal activity during wrist movements in response to two sets of cues. In the first, movements were guided by vibratory cue only (VIB trials). In the second, movements were guided by simultaneous presentation of both vibratory and visual cues (COM trials). SI neurons were recorded extracellularly during both wrist extensions and flexions. Neuronal activity during the instructed delay period (IDP) and the early reaction time period (RTP) were analyzed. A total of 96 cases from 48 neurons (each neuron contributed two cases, one each for extension and flexion) showed significant vibration entrainment during the early RTPs, as determined by circular statistics (Rayleigh test). Of these, 50 cases had cutaneous (CUTA) and 46 had deep (DEEP) receptive fields. The CUTA neurons showed lower firing rates during the IDPs and greater firing rate changes during the early RTPs when compared with the DEEP neurons. The CUTA neurons also demonstrated decreases in activity entrainment during VIB trials when compared with COM trials. For the DEEP neurons, the difference of entrainment between VIB and COM trials was not statistically significant. The results suggest that somatic vibratory input is coded by both the firing rate and the activity entrainment of the CUTA neurons in SI. The results also suggest that when vibratory inputs are required for successful task completion, the activity of the CUTA neurons increases but the entrainment degrades. The DEEP neurons may be tuned before movement initiation for processing information encoded by proprioceptive afferents.

State Dependency of Chemosensory Coding in the Gustatory Thalamus (VPMpc) of Alert Rats

PubMed Central

Liu, Haixin

2015-01-01

The parvicellular portion of the ventroposteromedial nucleus (VPMpc) is the part of the thalamus that processes gustatory information. Anatomical evidence shows that the VPMpc receives ascending gustatory inputs from the parabrachial nucleus (PbN) in the brainstem and sends projections to the gustatory cortex (GC). Although taste processing in PbN and GC has been the subject of intense investigation in behaving rodents, much less is known on how VPMpc neurons encode gustatory information. Here we present results from single-unit recordings in the VPMpc of alert rats receiving multiple tastants. Thalamic neurons respond to taste with time-varying modulations of firing rates, consistent with those observed in GC and PbN. These responses encode taste quality as well as palatability. Comparing responses to tastants either passively delivered, or self-administered after a cue, unveiled the effects of general expectation on taste processing in VPMpc. General expectation led to an improvement of taste coding by modulating response dynamics, and single neuron ability to encode multiple tastants. Our results demonstrate that the time course of taste coding as well as single neurons' ability to encode for multiple qualities are not fixed but rather can be altered by the state of the animal. Together, the data presented here provide the first description that taste coding in VPMpc is dynamic and state-dependent. SIGNIFICANCE STATEMENT Over the past years, a great deal of attention has been devoted to understanding taste coding in the brainstem and cortex of alert rodents. Thanks to this research, we now know that taste coding is dynamic, distributed, and context-dependent. Alas, virtually nothing is known on how the gustatory thalamus (VPMpc) processes gustatory information in behaving rats. This manuscript investigates taste processing in the VPMpc of behaving rats. Our results show that thalamic neurons encode taste and palatability with time-varying patterns of activity and that thalamic coding of taste is modulated by general expectation. Our data will appeal not only to researchers interested in taste, but also to a broader audience of sensory and systems neuroscientists interested in the thalamocortical system. PMID:26609147

Glucose sensing by GABAergic neurons in the mouse nucleus tractus solitarii

PubMed Central

Boychuk, Carie R.; Gyarmati, Peter; Xu, Hong

2015-01-01

Changes in blood glucose concentration alter autonomic function in a manner consistent with altered neural activity in brain regions controlling digestive processes, including neurons in the brain stem nucleus tractus solitarii (NTS), which process viscerosensory information. With whole cell or on-cell patch-clamp recordings, responses to elevating glucose concentration from 2.5 to 15 mM were assessed in identified GABAergic NTS neurons in slices from transgenic mice that express EGFP in a subset of GABA neurons. Single-cell real-time RT-PCR was also performed to detect glutamic acid decarboxylase (GAD67) in recorded neurons. In most identified GABA neurons (73%), elevating glucose concentration from 2.5 to 15 mM resulted in either increased (40%) or decreased (33%) neuronal excitability, reflected by altered membrane potential and/or action potential firing. Effects on membrane potential were maintained when action potentials or fast synaptic inputs were blocked, suggesting direct glucose sensing by GABA neurons. Glucose-inhibited GABA neurons were found predominantly in the lateral NTS, whereas glucose-excited cells were mainly in the medial NTS, suggesting regional segregation of responses. Responses were prevented in the presence of glucosamine, a glucokinase (GCK) inhibitor. Depolarizing responses were prevented when KATP channel activity was blocked with tolbutamide. Whereas effects on synaptic input to identified GABAergic neurons were variable in GABA neurons, elevating glucose increased glutamate release subsequent to stimulation of tractus solitarius in unlabeled, unidentified neurons. These results indicate that GABAergic NTS neurons act as GCK-dependent glucose sensors in the vagal complex, providing a means of modulating central autonomic signals when glucose is elevated. PMID:26084907

Possible Effects of Synaptic Imbalances on Oligodendrocyte–Axonic Interactions in Schizophrenia: A Hypothetical Model

PubMed Central

Mitterauer, Bernhard J.; Kofler-Westergren, Birgitta

2011-01-01

A model of glial–neuronal interactions is proposed that could be explanatory for the demyelination identified in brains with schizophrenia. It is based on two hypotheses: (1) that glia–neuron systems are functionally viable and important for normal brain function, and (2) that disruption of this postulated function disturbs the glial categorization function, as shown by formal analysis. According to this model, in schizophrenia receptors on astrocytes in glial–neuronal synaptic units are not functional, loosing their modulatory influence on synaptic neurotransmission. Hence, an unconstrained neurotransmission flux occurs that hyperactivates the axon and floods the cognate receptors of neurotransmitters on oligodendrocytes. The excess of neurotransmitters may have a toxic effect on oligodendrocytes and myelin, causing demyelination. In parallel, an increasing impairment of axons may disconnect neuronal networks. It is formally shown how oligodendrocytes normally categorize axonic information processing via their processes. Demyelination decomposes the oligodendrocyte–axonic system making it incapable to generate categories of information. This incoherence may be responsible for symptoms of disorganization in schizophrenia, such as thought disorder, inappropriate affect and incommunicable motor behavior. In parallel, the loss of oligodendrocytes affects gap junctions in the panglial syncytium, presumably responsible for memory impairment in schizophrenia. PMID:21647404

Development and modulation of intrinsic membrane properties control the temporal precision of auditory brain stem neurons.

PubMed

Franzen, Delwen L; Gleiss, Sarah A; Berger, Christina; Kümpfbeck, Franziska S; Ammer, Julian J; Felmy, Felix

2015-01-15

Passive and active membrane properties determine the voltage responses of neurons. Within the auditory brain stem, refinements in these intrinsic properties during late postnatal development usually generate short integration times and precise action-potential generation. This developmentally acquired temporal precision is crucial for auditory signal processing. How the interactions of these intrinsic properties develop in concert to enable auditory neurons to transfer information with high temporal precision has not yet been elucidated in detail. Here, we show how the developmental interaction of intrinsic membrane parameters generates high firing precision. We performed in vitro recordings from neurons of postnatal days 9-28 in the ventral nucleus of the lateral lemniscus of Mongolian gerbils, an auditory brain stem structure that converts excitatory to inhibitory information with high temporal precision. During this developmental period, the input resistance and capacitance decrease, and action potentials acquire faster kinetics and enhanced precision. Depending on the stimulation time course, the input resistance and capacitance contribute differentially to action-potential thresholds. The decrease in input resistance, however, is sufficient to explain the enhanced action-potential precision. Alterations in passive membrane properties also interact with a developmental change in potassium currents to generate the emergence of the mature firing pattern, characteristic of coincidence-detector neurons. Cholinergic receptor-mediated depolarizations further modulate this intrinsic excitability profile by eliciting changes in the threshold and firing pattern, irrespective of the developmental stage. Thus our findings reveal how intrinsic membrane properties interact developmentally to promote temporally precise information processing. Copyright © 2015 the American Physiological Society.

Cognitive Consilience: Primate Non-Primary Neuroanatomical Circuits Underlying Cognition

PubMed Central

Solari, Soren Van Hout; Stoner, Rich

2011-01-01

Interactions between the cerebral cortex, thalamus, and basal ganglia form the basis of cognitive information processing in the mammalian brain. Understanding the principles of neuroanatomical organization in these structures is critical to understanding the functions they perform and ultimately how the human brain works. We have manually distilled and synthesized hundreds of primate neuroanatomy facts into a single interactive visualization. The resulting picture represents the fundamental neuroanatomical blueprint upon which cognitive functions must be implemented. Within this framework we hypothesize and detail 7 functional circuits corresponding to psychological perspectives on the brain: consolidated long-term declarative memory, short-term declarative memory, working memory/information processing, behavioral memory selection, behavioral memory output, cognitive control, and cortical information flow regulation. Each circuit is described in terms of distinguishable neuronal groups including the cerebral isocortex (9 pyramidal neuronal groups), parahippocampal gyrus and hippocampus, thalamus (4 neuronal groups), basal ganglia (7 neuronal groups), metencephalon, basal forebrain, and other subcortical nuclei. We focus on neuroanatomy related to primate non-primary cortical systems to elucidate the basis underlying the distinct homotypical cognitive architecture. To display the breadth of this review, we introduce a novel method of integrating and presenting data in multiple independent visualizations: an interactive website (http://www.frontiersin.org/files/cognitiveconsilience/index.html) and standalone iPhone and iPad applications. With these tools we present a unique, annotated view of neuroanatomical consilience (integration of knowledge). PMID:22194717

Individual Neurons Confined to Distinct Antennal-Lobe Tracts in the Heliothine Moth: Morphological Characteristics and Global Projection Patterns

PubMed Central

Ian, Elena; Zhao, Xin C.; Lande, Andreas; Berg, Bente G.

2016-01-01

To explore fundamental principles characterizing chemosensory information processing, we have identified antennal-lobe projection neurons in the heliothine moth, including several neuron types not previously described. Generally, odor information is conveyed from the primary olfactory center of the moth brain, the antennal lobe, to higher brain centers via projection neuron axons passing along several parallel pathways, of which the medial, mediolateral, and lateral antennal-lobe tract are considered the classical ones. Recent data have revealed the projections of the individual tracts more in detail demonstrating three main target regions in the protocerebrum; the calyces are innervated mainly by the medial tract, the superior intermediate protocerebrum by the lateral tract exclusively, and the lateral horn by all tracts. In the present study, we have identified, via iontophoretic intracellular staining combined with confocal microscopy, individual projection neurons confined to the tracts mentioned above, plus two additional ones. Further, using the visualization software AMIRA, we reconstructed the stained neurons and registered the models into a standard brain atlas, which allowed us to compare the termination areas of individual projection neurons both across and within distinct tracts. The data demonstrate a morphological diversity of the projection neurons within distinct tracts. Comparison of the output areas of the neurons confined to the three main tracts in the lateral horn showed overlapping terminal regions for the medial and mediolateral tracts; the lateral tract neurons, on the contrary, targeted mostly other output areas in the protocerebrum. PMID:27822181

Laminar Organization of Attentional Modulation in Macaque Visual Area V4.

PubMed

Nandy, Anirvan S; Nassi, Jonathan J; Reynolds, John H

2017-01-04

Attention is critical to perception, serving to select behaviorally relevant information for privileged processing. To understand the neural mechanisms of attention, we must discern how attentional modulation varies by cell type and across cortical layers. Here, we test whether attention acts non-selectively across cortical layers or whether it engages the laminar circuit in specific and selective ways. We find layer- and cell-class-specific differences in several different forms of attentional modulation in area V4. Broad-spiking neurons in the superficial layers exhibit attention-mediated increases in firing rate and decreases in variability. Spike count correlations are highest in the input layer and attention serves to reduce these correlations. Superficial and input layer neurons exhibit attention-dependent decreases in low-frequency (<10 Hz) coherence, but deep layer neurons exhibit increases in coherence in the beta and gamma frequency ranges. Our study provides a template for attention-mediated laminar information processing that might be applicable across sensory modalities. Copyright © 2017 Elsevier Inc. All rights reserved.

Correlated activity supports efficient cortical processing

PubMed Central

Hung, Chou P.; Cui, Ding; Chen, Yueh-peng; Lin, Chia-pei; Levine, Matthew R.

2015-01-01

Visual recognition is a computational challenge that is thought to occur via efficient coding. An important concept is sparseness, a measure of coding efficiency. The prevailing view is that sparseness supports efficiency by minimizing redundancy and correlations in spiking populations. Yet, we recently reported that “choristers”, neurons that behave more similarly (have correlated stimulus preferences and spontaneous coincident spiking), carry more generalizable object information than uncorrelated neurons (“soloists”) in macaque inferior temporal (IT) cortex. The rarity of choristers (as low as 6% of IT neurons) indicates that they were likely missed in previous studies. Here, we report that correlation strength is distinct from sparseness (choristers are not simply broadly tuned neurons), that choristers are located in non-granular output layers, and that correlated activity predicts human visual search efficiency. These counterintuitive results suggest that a redundant correlational structure supports efficient processing and behavior. PMID:25610392

Rational modulation of neuronal processing with applied electric fields.

PubMed

Bikson, Marom; Radman, Thomas; Datta, Abhishek

2006-01-01

Traditional approaches to electrical stimulation, using trains of supra-threshold pulses to trigger action potentials, may be replaced or augmented by using 'rational' sub-threshold stimulation protocols that incorporate knowledge of single neuron geometry, inhomogeneous tissue properties, and nervous system information coding. Sub-threshold stimulation, at intensities (well) below those sufficient to trigger action potentials, may none-the-less exert a profound effect on brain function through modulation of concomitant neuronal activity. For example, small DC fields may coherently polarize a network of neurons and thus modulate the simultaneous processing of afferent synaptic input as well as resulting changes in synaptic plasticity. Through 'activity-dependent plasticity', sub-threshold fields may allow specific targeting of pathological networks and are thus particularly suitable to overcome the poor anatomical focus of noninvasive (transcranial) electrical stimulation. Additional approaches to improve targeting in transcranial stimulation using novel electrode configurations are also introduced.

Switching modes in corticogenesis: mechanisms of neuronal subtype transitions and integration in the cerebral cortex

PubMed Central

Toma, Kenichi; Hanashima, Carina

2015-01-01

Information processing in the cerebral cortex requires the activation of diverse neurons across layers and columns, which are established through the coordinated production of distinct neuronal subtypes and their placement along the three-dimensional axis. Over recent years, our knowledge of the regulatory mechanisms of the specification and integration of neuronal subtypes in the cerebral cortex has progressed rapidly. In this review, we address how the unique cytoarchitecture of the neocortex is established from a limited number of progenitors featuring neuronal identity transitions during development. We further illuminate the molecular mechanisms of the subtype-specific integration of these neurons into the cerebral cortex along the radial and tangential axis, and we discuss these key features to exemplify how neocortical circuit formation accomplishes economical connectivity while maintaining plasticity and evolvability to adapt to environmental changes. PMID:26321900

In vitro thermosensitivity of the midline thalamus

NASA Technical Reports Server (NTRS)

Travis, Kathleen A.; Bockholt, H. Jeremy; Zardetto-Smith, Andrea M.

1995-01-01

This study compared the thermosensitivity and spontaneous activity of thatamic midline neurons with those of neurons in areas widely regarded to be involved in thermoregulation (preoptic/anterior hypothalamus and posterior hypothalamus). In vitro single unit recordings were made from neurons within the thalamic midline nuclei, the preoptic/anterior hypothalamus and posterior hypothalamus prior to and during a temperature change 3-7 C above and below 37 C. There were no significant differences in the degree of thermosensitivity or the proportion of thermosensitive neurons in the three areas. In each area examined, the thermosensitive neurons had a spontaneous activity which was significantly greater than that of the temperature-insensitive neurons. The results suggest that structures of the midline thalamus may play a role similar to that of the preoptic/anterior hypothalamus and posterior hypothalamus in the processing of temperature related information.

Drivers from the deep: the contribution of collicular input to thalamocortical processing.

PubMed

Wurtz, Robert H; Sommer, Marc A; Cavanaugh, James

2005-01-01

A traditional view of the thalamus is that it is a relay station which receives sensory input and conveys this information to cortex. This sensory input determines most of the properties of first order thalamic neurons, and so is said to drive, rather than modulate, these neurons. This holds as a rule for first order thalamic nuclei, but in contrast, higher order thalamic nuclei receive much of their driver input back from cerebral cortex. In addition, higher order thalamic neurons receive inputs from subcortical movement-related centers. In the terminology popularized from studies of the sensory system, can we consider these ascending motor inputs to thalamus from subcortical structures to be modulators, subtly influencing the activity of their target neurons, or drivers, dictating the activity of their target neurons? This chapter summarizes relevant evidence from neuronal recording, inactivation, and stimulation of pathways projecting from the superior colliculus through thalamus to cerebral cortex. The study concludes that many inputs to the higher order nuclei of the thalamus from subcortical oculomotor areas - from the superior colliculus and probably other midbrain and pontine regions - should be regarded as motor drivers analogous to the sensory drivers at the first order thalamic nuclei. These motor drivers at the thalamus are viewed as being at the top of a series of feedback loops that provide information on impending actions, just as sensory drivers provide information about the external environment.

Feedforward motor information enhances somatosensory responses and sharpens angular tuning of rat S1 barrel cortex neurons.

PubMed

Khateb, Mohamed; Schiller, Jackie; Schiller, Yitzhak

2017-01-06

The primary vibrissae motor cortex (vM1) is responsible for generating whisking movements. In parallel, vM1 also sends information directly to the sensory barrel cortex (vS1). In this study, we investigated the effects of vM1 activation on processing of vibrissae sensory information in vS1 of the rat. To dissociate the vibrissae sensory-motor loop, we optogenetically activated vM1 and independently passively stimulated principal vibrissae. Optogenetic activation of vM1 supra-linearly amplified the response of vS1 neurons to passive vibrissa stimulation in all cortical layers measured. Maximal amplification occurred when onset of vM1 optogenetic activation preceded vibrissa stimulation by 20 ms. In addition to amplification, vM1 activation also sharpened angular tuning of vS1 neurons in all cortical layers measured. Our findings indicated that in addition to output motor signals, vM1 also sends preparatory signals to vS1 that serve to amplify and sharpen the response of neurons in the barrel cortex to incoming sensory input signals.

Supralinear and Supramodal Integration of Visual and Tactile Signals in Rats: Psychophysics and Neuronal Mechanisms.

PubMed

Nikbakht, Nader; Tafreshiha, Azadeh; Zoccolan, Davide; Diamond, Mathew E

2018-02-07

To better understand how object recognition can be triggered independently of the sensory channel through which information is acquired, we devised a task in which rats judged the orientation of a raised, black and white grating. They learned to recognize two categories of orientation: 0° ± 45° ("horizontal") and 90° ± 45° ("vertical"). Each trial required a visual (V), a tactile (T), or a visual-tactile (VT) discrimination; VT performance was better than that predicted by optimal linear combination of V and T signals, indicating synergy between sensory channels. We examined posterior parietal cortex (PPC) and uncovered key neuronal correlates of the behavioral findings: PPC carried both graded information about object orientation and categorical information about the rat's upcoming choice; single neurons exhibited identical responses under the three modality conditions. Finally, a linear classifier of neuronal population firing replicated the behavioral findings. Taken together, these findings suggest that PPC is involved in the supramodal processing of shape. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Encoding of Spatio-Temporal Input Characteristics by a CA1 Pyramidal Neuron Model

PubMed Central

Pissadaki, Eleftheria Kyriaki; Sidiropoulou, Kyriaki; Reczko, Martin; Poirazi, Panayiota

2010-01-01

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code. PMID:21187899

Effects of Morphology Constraint on Electrophysiological Properties of Cortical Neurons

NASA Astrophysics Data System (ADS)

Zhu, Geng; Du, Liping; Jin, Lei; Offenhäusser, Andreas

2016-04-01

There is growing interest in engineering nerve cells in vitro to control architecture and connectivity of cultured neuronal networks or to build neuronal networks with predictable computational function. Pattern technologies, such as micro-contact printing, have been developed to design ordered neuronal networks. However, electrophysiological characteristics of the single patterned neuron haven’t been reported. Here, micro-contact printing, using polyolefine polymer (POP) stamps with high resolution, was employed to grow cortical neurons in a designed structure. The results demonstrated that the morphology of patterned neurons was well constrained, and the number of dendrites was decreased to be about 2. Our electrophysiological results showed that alterations of dendritic morphology affected firing patterns of neurons and neural excitability. When stimulated by current, though both patterned and un-patterned neurons presented regular spiking, the dynamics and strength of the response were different. The un-patterned neurons exhibited a monotonically increasing firing frequency in response to injected current, while the patterned neurons first exhibited frequency increase and then a slow decrease. Our findings indicate that the decrease in dendritic complexity of cortical neurons will influence their electrophysiological characteristics and alter their information processing activity, which could be considered when designing neuronal circuitries.

Voltage Imaging of Waking Mouse Cortex Reveals Emergence of Critical Neuronal Dynamics

PubMed Central

Scott, Gregory; Fagerholm, Erik D.; Mutoh, Hiroki; Leech, Robert; Sharp, David J.; Shew, Woodrow L.

2014-01-01

Complex cognitive processes require neuronal activity to be coordinated across multiple scales, ranging from local microcircuits to cortex-wide networks. However, multiscale cortical dynamics are not well understood because few experimental approaches have provided sufficient support for hypotheses involving multiscale interactions. To address these limitations, we used, in experiments involving mice, genetically encoded voltage indicator imaging, which measures cortex-wide electrical activity at high spatiotemporal resolution. Here we show that, as mice recovered from anesthesia, scale-invariant spatiotemporal patterns of neuronal activity gradually emerge. We show for the first time that this scale-invariant activity spans four orders of magnitude in awake mice. In contrast, we found that the cortical dynamics of anesthetized mice were not scale invariant. Our results bridge empirical evidence from disparate scales and support theoretical predictions that the awake cortex operates in a dynamical regime known as criticality. The criticality hypothesis predicts that small-scale cortical dynamics are governed by the same principles as those governing larger-scale dynamics. Importantly, these scale-invariant principles also optimize certain aspects of information processing. Our results suggest that during the emergence from anesthesia, criticality arises as information processing demands increase. We expect that, as measurement tools advance toward larger scales and greater resolution, the multiscale framework offered by criticality will continue to provide quantitative predictions and insight on how neurons, microcircuits, and large-scale networks are dynamically coordinated in the brain. PMID:25505314

Noise shaping in populations of coupled model neurons.

PubMed

Mar, D J; Chow, C C; Gerstner, W; Adams, R W; Collins, J J

1999-08-31

Biological information-processing systems, such as populations of sensory and motor neurons, may use correlations between the firings of individual elements to obtain lower noise levels and a systemwide performance improvement in the dynamic range or the signal-to-noise ratio. Here, we implement such correlations in networks of coupled integrate-and-fire neurons using inhibitory coupling and demonstrate that this can improve the system dynamic range and the signal-to-noise ratio in a population rate code. The improvement can surpass that expected for simple averaging of uncorrelated elements. A theory that predicts the resulting power spectrum is developed in terms of a stochastic point-process model in which the instantaneous population firing rate is modulated by the coupling between elements.

A recurrent neural model for proto-object based contour integration and figure-ground segregation.

PubMed

Hu, Brian; Niebur, Ernst

2017-12-01

Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects ("proto-objects") based on the integration of local feature information. Grouping neurons receive input from an organized set of local feature neurons, and project modulatory feedback to those same neurons. Additionally, inhibition at both the local feature level and the object representation level biases the interpretation of the visual scene in agreement with principles from Gestalt psychology. Our model explains several sets of neurophysiological results (Zhou et al. Journal of Neuroscience, 20(17), 6594-6611 2000; Qiu et al. Nature Neuroscience, 10(11), 1492-1499 2007; Chen et al. Neuron, 82(3), 682-694 2014), and makes testable predictions about the influence of neuronal feedback and attentional selection on neural responses across different visual areas. Our model also provides a framework for understanding how object-based attention is able to select both objects and the features associated with them.

Isoflurane modulates neuronal excitability of the nucleus reticularis thalami in vitro.

PubMed

Joksovic, Pavle M; Todorovic, Slobodan M

2010-06-01

The thalamus has a key function in processing sensory information, sleep, and cognition. We examined the effects of a common volatile anesthetic, isoflurane, on modulation of neuronal excitability in reticular thalamic nucleus (nRT) in intact brain slices from immature rats. In current-clamp recordings, isoflurane (300-600 micromol/L) consistently depolarized membrane potential, decreased input resistance, and inhibited both rebound burst firing and tonic spike firing modes of nRT neurons. The isoflurane-induced depolarization persisted not only in the presence of tetrodotoxin, but after replacement of Ca(2+) with Ba(2+) ions in external solution; it was abolished by partial replacement of extracellular Na(+) ions with N-methyl-D-glucamine. In voltage-clamp recordings, we found that isoflurane slowed recovery from inactivation of T-type Ca(2+) current. Thus, at clinically relevant concentrations, isoflurane inhibits neuronal excitability of nRT neurons in developing brain via multiple ion channels. Inhibition of the neuronal excitability of thalamic cells may contribute to impairment of sensory information transfer in the thalamocortical network by general anesthetics. The findings may be important for understanding cellular mechanisms of anesthesia, such as loss of consciousness and potentially damaging consequences of general anesthetics on developing mammalian brains.

Representational geometry: integrating cognition, computation, and the brain

PubMed Central

Kriegeskorte, Nikolaus; Kievit, Rogier A.

2013-01-01

The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure. PMID:23876494

Orientation-selective aVLSI spiking neurons.

PubMed

Liu, S C; Kramer, J; Indiveri, G; Delbrück, T; Burg, T; Douglas, R

2001-01-01

We describe a programmable multi-chip VLSI neuronal system that can be used for exploring spike-based information processing models. The system consists of a silicon retina, a PIC microcontroller, and a transceiver chip whose integrate-and-fire neurons are connected in a soft winner-take-all architecture. The circuit on this multi-neuron chip approximates a cortical microcircuit. The neurons can be configured for different computational properties by the virtual connections of a selected set of pixels on the silicon retina. The virtual wiring between the different chips is effected by an event-driven communication protocol that uses asynchronous digital pulses, similar to spikes in a neuronal system. We used the multi-chip spike-based system to synthesize orientation-tuned neurons using both a feedforward model and a feedback model. The performance of our analog hardware spiking model matched the experimental observations and digital simulations of continuous-valued neurons. The multi-chip VLSI system has advantages over computer neuronal models in that it is real-time, and the computational time does not scale with the size of the neuronal network.

When are new hippocampal neurons, born in the adult brain, integrated into the network that processes spatial information?

PubMed

Sandoval, C Jimena; Martínez-Claros, Marisela; Bello-Medina, Paola C; Pérez, Oswaldo; Ramírez-Amaya, Víctor

2011-03-09

Adult-born neurons in the dentate gyrus (DG) functionally integrate into the behaviorally relevant hippocampal networks, showing a specific Arc-expression response to spatial exploration when mature. However, it is not clear when, during the 4- to 6-week interval that is critical for survival and maturation of these neurons, this specific response develops. Therefore, we characterized Arc expression after spatial exploration or cage control conditions in adult-born neurons from rats that were injected with BrdU on one day and were sacrificed 1, 7, 15, 30, and 45 days post-BrdU injection (PBI). Triple immunostaining for NeuN, Arc, and BrdU was analyzed through the different DG layers. Arc protein expression in BrdU-positive cells was observed from day 1 to day 15 PBI but was not related to behavioral stimulation. The specific Arc-expression response to spatial exploration was observed from day 30 and 45 in about 5% of the BrdU-positive cell population. Most of the BrdU-positive neurons expressing Arc in response to spatial exploration (∼90%) were located in DG layer 1, and no Arc expression was observed in cells located in the subgranular zone (SGZ). Using the current data and that obtained previously, we propose a mathematical model suggesting that new neurons are unlikely to respond to exploration by expressing Arc after they are 301 days old, and also that in a 7-month-old rat the majority (60%) of the neurons that respond to exploration must have been born during adulthood; thus, suggesting that adult neurogenesis in the DG is highly relevant for spatial information processing.

When Are New Hippocampal Neurons, Born in the Adult Brain, Integrated into the Network That Processes Spatial Information?

PubMed Central

Sandoval, C. Jimena; Pérez, Oswaldo; Ramírez-Amaya, Víctor

2011-01-01

Adult-born neurons in the dentate gyrus (DG) functionally integrate into the behaviorally relevant hippocampal networks, showing a specific Arc-expression response to spatial exploration when mature. However, it is not clear when, during the 4- to 6-week interval that is critical for survival and maturation of these neurons, this specific response develops. Therefore, we characterized Arc expression after spatial exploration or cage control conditions in adult-born neurons from rats that were injected with BrdU on one day and were sacrificed 1, 7, 15, 30, and 45 days post-BrdU injection (PBI). Triple immunostaining for NeuN, Arc, and BrdU was analyzed through the different DG layers. Arc protein expression in BrdU-positive cells was observed from day 1 to day 15 PBI but was not related to behavioral stimulation. The specific Arc-expression response to spatial exploration was observed from day 30 and 45 in about 5% of the BrdU-positive cell population. Most of the BrdU-positive neurons expressing Arc in response to spatial exploration (∼90%) were located in DG layer 1, and no Arc expression was observed in cells located in the subgranular zone (SGZ). Using the current data and that obtained previously, we propose a mathematical model suggesting that new neurons are unlikely to respond to exploration by expressing Arc after they are 301 days old, and also that in a 7-month-old rat the majority (60%) of the neurons that respond to exploration must have been born during adulthood; thus, suggesting that adult neurogenesis in the DG is highly relevant for spatial information processing. PMID:21408012

Extracting Behaviorally Relevant Traits from Natural Stimuli: Benefits of Combinatorial Representations at the Accessory Olfactory Bulb

PubMed Central

Kahan, Anat; Ben-Shaul, Yoram

2016-01-01

For many animals, chemosensation is essential for guiding social behavior. However, because multiple factors can modulate levels of individual chemical cues, deriving information about other individuals via natural chemical stimuli involves considerable challenges. How social information is extracted despite these sources of variability is poorly understood. The vomeronasal system provides an excellent opportunity to study this topic due to its role in detecting socially relevant traits. Here, we focus on two such traits: a female mouse’s strain and reproductive state. In particular, we measure stimulus-induced neuronal activity in the accessory olfactory bulb (AOB) in response to various dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus female mice from two different strains. We first show that all tested secretions provide information about a female’s receptivity and genotype. Next, we investigate how these traits can be decoded from neuronal activity despite multiple sources of variability. We show that individual neurons are limited in their capacity to allow trait classification across multiple sources of variability. However, simple linear classifiers sampling neuronal activity from small neuronal ensembles can provide a substantial improvement over that attained with individual units. Furthermore, we show that some traits are more efficiently detected than others, and that particular secretions may be optimized for conveying information about specific traits. Across all tested stimulus sources, discrimination between strains is more accurate than discrimination of receptivity, and detection of receptivity is more accurate with vaginal secretions than with urine. Our findings highlight the challenges of chemosensory processing of natural stimuli, and suggest that downstream readout stages decode multiple behaviorally relevant traits by sampling information from distinct but overlapping populations of AOB neurons. PMID:26938460

Extracting Behaviorally Relevant Traits from Natural Stimuli: Benefits of Combinatorial Representations at the Accessory Olfactory Bulb.

PubMed

Kahan, Anat; Ben-Shaul, Yoram

2016-03-01

For many animals, chemosensation is essential for guiding social behavior. However, because multiple factors can modulate levels of individual chemical cues, deriving information about other individuals via natural chemical stimuli involves considerable challenges. How social information is extracted despite these sources of variability is poorly understood. The vomeronasal system provides an excellent opportunity to study this topic due to its role in detecting socially relevant traits. Here, we focus on two such traits: a female mouse's strain and reproductive state. In particular, we measure stimulus-induced neuronal activity in the accessory olfactory bulb (AOB) in response to various dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus female mice from two different strains. We first show that all tested secretions provide information about a female's receptivity and genotype. Next, we investigate how these traits can be decoded from neuronal activity despite multiple sources of variability. We show that individual neurons are limited in their capacity to allow trait classification across multiple sources of variability. However, simple linear classifiers sampling neuronal activity from small neuronal ensembles can provide a substantial improvement over that attained with individual units. Furthermore, we show that some traits are more efficiently detected than others, and that particular secretions may be optimized for conveying information about specific traits. Across all tested stimulus sources, discrimination between strains is more accurate than discrimination of receptivity, and detection of receptivity is more accurate with vaginal secretions than with urine. Our findings highlight the challenges of chemosensory processing of natural stimuli, and suggest that downstream readout stages decode multiple behaviorally relevant traits by sampling information from distinct but overlapping populations of AOB neurons.

The functional significance of newly born neurons integrated into olfactory bulb circuits.

PubMed

Sakamoto, Masayuki; Kageyama, Ryoichiro; Imayoshi, Itaru

2014-01-01

The olfactory bulb (OB) is the first central processing center for olfactory information connecting with higher areas in the brain, and this neuronal circuitry mediates a variety of odor-evoked behavioral responses. In the adult mammalian brain, continuous neurogenesis occurs in two restricted regions, the subventricular zone (SVZ) of the lateral ventricle and the hippocampal dentate gyrus. New neurons born in the SVZ migrate through the rostral migratory stream and are integrated into the neuronal circuits of the OB throughout life. The significance of this continuous supply of new neurons in the OB has been implicated in plasticity and memory regulation. Two decades of huge investigation in adult neurogenesis revealed the biological importance of integration of new neurons into the olfactory circuits. In this review, we highlight the recent findings about the physiological functions of newly generated neurons in rodent OB circuits and then discuss the contribution of neurogenesis in the brain function. Finally, we introduce cutting edge technologies to monitor and manipulate the activity of new neurons.

The functional significance of newly born neurons integrated into olfactory bulb circuits

PubMed Central

Sakamoto, Masayuki; Kageyama, Ryoichiro; Imayoshi, Itaru

2014-01-01

The olfactory bulb (OB) is the first central processing center for olfactory information connecting with higher areas in the brain, and this neuronal circuitry mediates a variety of odor-evoked behavioral responses. In the adult mammalian brain, continuous neurogenesis occurs in two restricted regions, the subventricular zone (SVZ) of the lateral ventricle and the hippocampal dentate gyrus. New neurons born in the SVZ migrate through the rostral migratory stream and are integrated into the neuronal circuits of the OB throughout life. The significance of this continuous supply of new neurons in the OB has been implicated in plasticity and memory regulation. Two decades of huge investigation in adult neurogenesis revealed the biological importance of integration of new neurons into the olfactory circuits. In this review, we highlight the recent findings about the physiological functions of newly generated neurons in rodent OB circuits and then discuss the contribution of neurogenesis in the brain function. Finally, we introduce cutting edge technologies to monitor and manipulate the activity of new neurons. PMID:24904263

Predicted contextual modulation varies with distance from pinwheel centers in the orientation preference map

PubMed Central

Okamoto, Tsuyoshi; Ikezoe, Koji; Tamura, Hiroshi; Watanabe, Masataka; Aihara, Kazuyuki; Fujita, Ichiro

2011-01-01

In the primary visual cortex (V1) of some mammals, columns of neurons with the full range of orientation preferences converge at the center of a pinwheel-like arrangement, the ‘pinwheel center' (PWC). Because a neuron receives abundant inputs from nearby neurons, the neuron's position on the cortical map likely has a significant impact on its responses to the layout of orientations inside and outside its classical receptive field (CRF). To understand the positional specificity of responses, we constructed a computational model based on orientation preference maps in monkey V1 and hypothetical neuronal connections. The model simulations showed that neurons near PWCs displayed weaker but detectable orientation selectivity within their CRFs, and strongly reduced contextual modulation from extra-CRF stimuli, than neurons distant from PWCs. We suggest that neurons near PWCs robustly extract local orientation within their CRF embedded in visual scenes, and that contextual information is processed in regions distant from PWCs. PMID:22355631

Changes in basal ganglia processing of cortical input following magnetic stimulation in Parkinsonism.

PubMed

Tischler, Hadass; Moran, Anan; Belelovsky, Katya; Bronfeld, Maya; Korngreen, Alon; Bar-Gad, Izhar

2012-12-01

Parkinsonism is associated with major changes in neuronal activity throughout the cortico-basal ganglia loop. Current measures quantify changes in baseline neuronal and network activity but do not capture alterations in information propagation throughout the system. Here, we applied a novel non-invasive magnetic stimulation approach using a custom-made mini-coil that enabled us to study transmission of neuronal activity throughout the cortico-basal ganglia loop in both normal and parkinsonian primates. By magnetically perturbing cortical activity while simultaneously recording neuronal responses along the cortico-basal ganglia loop, we were able to directly investigate modifications in descending cortical activity transmission. We found that in both the normal and parkinsonian states, cortical neurons displayed similar multi-phase firing rate modulations in response to magnetic stimulation. However, in the basal ganglia, large synaptically driven stereotypic neuronal modulation was present in the parkinsonian state that was mostly absent in the normal state. The stimulation-induced neuronal activity pattern highlights the change in information propagation along the cortico-basal ganglia loop. Our findings thus point to the role of abnormal dynamic activity transmission rather than changes in baseline activity as a major component in parkinsonian pathophysiology. Moreover, our results hint that the application of transcranial magnetic stimulation (TMS) in human patients of different disorders may result in different neuronal effects than the one induced in normal subjects. Copyright © 2012 Elsevier Inc. All rights reserved.

Closed-Loop Estimation of Retinal Network Sensitivity by Local Empirical Linearization

PubMed Central

2018-01-01

Abstract Understanding how sensory systems process information depends crucially on identifying which features of the stimulus drive the response of sensory neurons, and which ones leave their response invariant. This task is made difficult by the many nonlinearities that shape sensory processing. Here, we present a novel perturbative approach to understand information processing by sensory neurons, where we linearize their collective response locally in stimulus space. We added small perturbations to reference stimuli and tested if they triggered visible changes in the responses, adapting their amplitude according to the previous responses with closed-loop experiments. We developed a local linear model that accurately predicts the sensitivity of the neural responses to these perturbations. Applying this approach to the rat retina, we estimated the optimal performance of a neural decoder and showed that the nonlinear sensitivity of the retina is consistent with an efficient encoding of stimulus information. Our approach can be used to characterize experimentally the sensitivity of neural systems to external stimuli locally, quantify experimentally the capacity of neural networks to encode sensory information, and relate their activity to behavior. PMID:29379871

Learning about Expectation Violation from Prediction Error Paradigms – A Meta-Analysis on Brain Processes Following a Prediction Error

PubMed Central

D’Astolfo, Lisa; Rief, Winfried

2017-01-01

Modifying patients’ expectations by exposing them to expectation violation situations (thus maximizing the difference between the expected and the actual situational outcome) is proposed to be a crucial mechanism for therapeutic success for a variety of different mental disorders. However, clinical observations suggest that patients often maintain their expectations regardless of experiences contradicting their expectations. It remains unclear which information processing mechanisms lead to modification or persistence of patients’ expectations. Insight in the processing could be provided by Neuroimaging studies investigating prediction error (PE, i.e., neuronal reactions to non-expected stimuli). Two methods are often used to investigate the PE: (1) paradigms, in which participants passively observe PEs (”passive” paradigms) and (2) paradigms, which encourage a behavioral adaptation following a PE (“active” paradigms). These paradigms are similar to the methods used to induce expectation violations in clinical settings: (1) the confrontation with an expectation violation situation and (2) an enhanced confrontation in which the patient actively challenges his expectation. We used this similarity to gain insight in the different neuronal processing of the two PE paradigms. We performed a meta-analysis contrasting neuronal activity of PE paradigms encouraging a behavioral adaptation following a PE and paradigms enforcing passiveness following a PE. We found more neuronal activity in the striatum, the insula and the fusiform gyrus in studies encouraging behavioral adaptation following a PE. Due to the involvement of reward assessment and avoidance learning associated with the striatum and the insula we propose that the deliberate execution of action alternatives following a PE is associated with the integration of new information into previously existing expectations, therefore leading to an expectation change. While further research is needed to directly assess expectations of participants, this study provides new insights into the information processing mechanisms following an expectation violation. PMID:28804467

Learning about Expectation Violation from Prediction Error Paradigms - A Meta-Analysis on Brain Processes Following a Prediction Error.

PubMed

D'Astolfo, Lisa; Rief, Winfried

2017-01-01

Modifying patients' expectations by exposing them to expectation violation situations (thus maximizing the difference between the expected and the actual situational outcome) is proposed to be a crucial mechanism for therapeutic success for a variety of different mental disorders. However, clinical observations suggest that patients often maintain their expectations regardless of experiences contradicting their expectations. It remains unclear which information processing mechanisms lead to modification or persistence of patients' expectations. Insight in the processing could be provided by Neuroimaging studies investigating prediction error (PE, i.e., neuronal reactions to non-expected stimuli). Two methods are often used to investigate the PE: (1) paradigms, in which participants passively observe PEs ("passive" paradigms) and (2) paradigms, which encourage a behavioral adaptation following a PE ("active" paradigms). These paradigms are similar to the methods used to induce expectation violations in clinical settings: (1) the confrontation with an expectation violation situation and (2) an enhanced confrontation in which the patient actively challenges his expectation. We used this similarity to gain insight in the different neuronal processing of the two PE paradigms. We performed a meta-analysis contrasting neuronal activity of PE paradigms encouraging a behavioral adaptation following a PE and paradigms enforcing passiveness following a PE. We found more neuronal activity in the striatum, the insula and the fusiform gyrus in studies encouraging behavioral adaptation following a PE. Due to the involvement of reward assessment and avoidance learning associated with the striatum and the insula we propose that the deliberate execution of action alternatives following a PE is associated with the integration of new information into previously existing expectations, therefore leading to an expectation change. While further research is needed to directly assess expectations of participants, this study provides new insights into the information processing mechanisms following an expectation violation.

Alterations of cortical GABA neurons and network oscillations in schizophrenia.

PubMed

Gonzalez-Burgos, Guillermo; Hashimoto, Takanori; Lewis, David A

2010-08-01

The hypothesis that alterations of cortical inhibitory gamma-aminobutyric acid (GABA) neurons are a central element in the pathology of schizophrenia has emerged from a series of postmortem studies. How such abnormalities may contribute to the clinical features of schizophrenia has been substantially informed by a convergence with basic neuroscience studies revealing complex details of GABA neuron function in the healthy brain. Importantly, activity of the parvalbumin-containing class of GABA neurons has been linked to the production of cortical network oscillations. Furthermore, growing knowledge supports the concept that gamma band oscillations (30-80 Hz) are an essential mechanism for cortical information transmission and processing. Herein we review recent studies further indicating that inhibition from parvalbumin-positive GABA neurons is necessary to produce gamma oscillations in cortical circuits; provide an update on postmortem studies documenting that deficits in the expression of glutamic acid decarboxylase67, which accounts for most GABA synthesis in the cortex, are widely observed in schizophrenia; and describe studies using novel, noninvasive approaches directly assessing potential relations between alterations in GABA, oscillations, and cognitive function in schizophrenia.

[How we smell and what it means to us: basic principles of the sense of smell].

PubMed

Manzini, I; Frasnelli, J; Croy, I

2014-12-01

The origins of the sense of smell lie in the perception of environmental molecules and go back to unicellular organisms such as bacteria. Odors transmit a multitude of information about the chemical composition of our environment. The sense of smell helps people and animals with orientation in space, warns of potential threats, influences the choice of sexual partners, regulates food intake and influences feelings and social behavior in general. The perception of odors begins in sensory neurons residing in the olfactory epithelium that express G protein-coupled receptors, the so-called olfactory receptors. The binding of odor molecules to olfactory receptors initiates a signal transduction cascade that converts olfactory stimuli into electrical signals. These signals are then transmitted to the olfactory bulb, the first relay center in the olfactory pathway, via the axons of the sensory neurons. The olfactory information is processed in the bulb and then transferred to higher olfactory centers via axons of mitral cells, the bulbar projection neurons. This review describes the mechanisms involved in peripheral detection of odorants, outlines the further processing of olfactory information in higher olfactory centers and finally gives an overview of the overall significance of the ability to smell.

Auditory fovea and Doppler shift compensation: adaptations for flutter detection in echolocating bats using CF-FM signals.

PubMed

Schnitzler, Hans-Ulrich; Denzinger, Annette

2011-05-01

Rhythmical modulations in insect echoes caused by the moving wings of fluttering insects are behaviourally relevant information for bats emitting CF-FM signals with a high duty cycle. Transmitter and receiver of the echolocation system in flutter detecting foragers are especially adapted for the processing of flutter information. The adaptations of the transmitter are indicated by a flutter induced increase in duty cycle, and by Doppler shift compensation (DSC) that keeps the carrier frequency of the insect echoes near a reference frequency. An adaptation of the receiver is the auditory fovea on the basilar membrane, a highly expanded frequency representation centred to the reference frequency. The afferent projections from the fovea lead to foveal areas with an overrepresentation of sharply tuned neurons with best frequencies near the reference frequency throughout the entire auditory pathway. These foveal neurons are very sensitive to stimuli with natural and simulated flutter information. The frequency range of the foveal areas with their flutter processing neurons overlaps exactly with the frequency range where DS compensating bats most likely receive echoes from fluttering insects. This tight match indicates that auditory fovea and DSC are adaptations for the detection and evaluation of insects flying in clutter.

Visual adaptation and novelty responses in the superior colliculus

PubMed Central

Boehnke, Susan E.; Berg, David J.; Marino, Robert M.; Baldi, Pierre F.; Itti, Laurent; Munoz, Douglas P.

2011-01-01

The brain's ability to ignore repeating, often redundant, information while enhancing novel information processing is paramount to survival. When stimuli are repeatedly presented, the response of visually-sensitive neurons decreases in magnitude, i.e. neurons adapt or habituate, although the mechanism is not yet known. We monitored activity of visual neurons in the superior colliculus (SC) of rhesus monkeys who actively fixated while repeated visual events were presented. We dissociated adaptation from habituation as mechanisms of the response decrement by using a Bayesian model of adaptation, and by employing a paradigm including rare trials that included an oddball stimulus that was either brighter or dimmer. If the mechanism is adaptation, response recovery should be seen only for the brighter stimulus; if habituation, response recovery (‘dishabituation’) should be seen for both the brighter and dimmer stimulus. We observed a reduction in the magnitude of the initial transient response and an increase in response onset latency with stimulus repetition for all visually responsive neurons in the SC. Response decrement was successfully captured by the adaptation model which also predicted the effects of presentation rate and rare luminance changes. However, in a subset of neurons with sustained activity to visual stimuli, a novelty signal akin to dishabituation was observed late in the visual response profile to both brighter and dimmer stimuli and was not captured by the model. This suggests that SC neurons integrate both rapidly discounted information about repeating stimuli and novelty information about oddball events, to support efficient selection in a cluttered dynamic world. PMID:21864319

Enhanced neurite outgrowth of PC-12 cells on graphene-monolayer-coated substrates as biomimetic cues

NASA Astrophysics Data System (ADS)

Lee, Jong Ho; Shin, Yong Cheol; Jin, Oh Seong; Han, Dong-Wook; Kang, Seok Hee; Hong, Suck Won; Kim, Jong Man

2012-11-01

Neurons are electrically excitable cells that transmit and process information in the nervous system. Recently, the differentiation of human neural stem cells to neurons has been shown to be enhanced on graphene substrates, and differentiated neurons have been shown to be able to still carry electrical signals when stimulated by graphene electrodes. Graphene films grown by using chemical vapor deposition were transferred onto glass coverslips by using the scooping method and were then coated with fetal bovine serum for a neuronal cell culture. The graphene substrates as biomimetic cues have been shown to enhance the neurite outgrowth of PC-12 cells. Our findings suggest that graphene has a unique surface property that can promote neuronal cells, which should open tremendous opportunities in neuroscience, neural engineering and regenerative medicine.

Molecular neurobiology of Drosophila taste

PubMed Central

Freeman, Erica Gene; Dahanukar, Anupama

2015-01-01

Drosophila is a powerful model in which to study the molecular and cellular basis of taste coding. Flies sense tastants via populations of taste neurons that are activated by compounds of distinct categories. The past few years have borne witness to studies that define the properties of taste neurons, identifying functionally distinct classes of sweet and bitter taste neurons that express unique subsets of gustatory receptor (Gr) genes, as well as water, salt, and pheromone sensing neurons that express members of the pickpocket (ppk) or ionotropic receptor (Ir) families. There has also been significant progress in terms of understanding how tastant information is processed and conveyed to higher brain centers, and modulated by prior dietary experience or starvation. PMID:26102453

Plasticity of Neuron-Glial Transmission: Equipping Glia for Long-Term Integration of Network Activity.

PubMed

Croft, Wayne; Dobson, Katharine L; Bellamy, Tomas C

2015-01-01

The capacity of synaptic networks to express activity-dependent changes in strength and connectivity is essential for learning and memory processes. In recent years, glial cells (most notably astrocytes) have been recognized as active participants in the modulation of synaptic transmission and synaptic plasticity, implicating these electrically nonexcitable cells in information processing in the brain. While the concept of bidirectional communication between neurons and glia and the mechanisms by which gliotransmission can modulate neuronal function are well established, less attention has been focussed on the computational potential of neuron-glial transmission itself. In particular, whether neuron-glial transmission is itself subject to activity-dependent plasticity and what the computational properties of such plasticity might be has not been explored in detail. In this review, we summarize current examples of plasticity in neuron-glial transmission, in many brain regions and neurotransmitter pathways. We argue that induction of glial plasticity typically requires repetitive neuronal firing over long time periods (minutes-hours) rather than the short-lived, stereotyped trigger typical of canonical long-term potentiation. We speculate that this equips glia with a mechanism for monitoring average firing rates in the synaptic network, which is suited to the longer term roles proposed for astrocytes in neurophysiology.

Feed-forward segmentation of figure-ground and assignment of border-ownership.

PubMed

Supèr, Hans; Romeo, August; Keil, Matthias

2010-05-19

Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.

Feed-Forward Segmentation of Figure-Ground and Assignment of Border-Ownership

PubMed Central

Supèr, Hans; Romeo, August; Keil, Matthias

2010-01-01

Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment. PMID:20502718

Glycinergic Input to the Mouse Basal Forebrain Cholinergic Neurons

PubMed Central

Bardóczi, Zsuzsanna; Pál, Balázs; Kőszeghy, Áron; Wilheim, Tamás; Záborszky, László; Liposits, Zsolt

2017-01-01

The basal forebrain (BF) receives afferents from brainstem ascending pathways, which has been implicated first by Moruzzi and Magoun (1949) to induce forebrain activation and cortical arousal/waking behavior; however, it is very little known about how brainstem inhibitory inputs affect cholinergic functions. In the current study, glycine, a major inhibitory neurotransmitter of brainstem neurons, and gliotransmitter of local glial cells, was tested for potential interaction with BF cholinergic (BFC) neurons in male mice. In the BF, glycine receptor α subunit-immunoreactive (IR) sites were localized in choline acetyltransferase (ChAT)-IR neurons. The effect of glycine on BFC neurons was demonstrated by bicuculline-resistant, strychnine-sensitive spontaneous IPSCs (sIPSCs; 0.81 ± 0.25 × 10−1 Hz) recorded in whole-cell conditions. Potential neuronal as well as glial sources of glycine were indicated in the extracellular space of cholinergic neurons by glycine transporter type 1 (GLYT1)- and GLYT2-IR processes found in apposition to ChAT-IR cells. Ultrastructural analyses identified synapses of GLYT2-positive axon terminals on ChAT-IR neurons, as well as GLYT1-positive astroglial processes, which were localized in the vicinity of synapses of ChAT-IR neurons. The brainstem raphe magnus was determined to be a major source of glycinergic axons traced retrogradely from the BF. Our results indicate a direct effect of glycine on BFC neurons. Furthermore, the presence of high levels of plasma membrane glycine transporters in the vicinity of cholinergic neurons suggests a tight control of extracellular glycine in the BF. SIGNIFICANCE STATEMENT Basal forebrain cholinergic (BFC) neurons receive various activating inputs from specific brainstem areas and channel this information to the cortex via multiple projections. So far, very little is known about inhibitory brainstem afferents to the BF. The current study established glycine as a major regulator of BFC neurons by (1) identifying glycinergic neurons in the brainstem projecting to the BF, (2) showing glycine receptor α subunit-immunoreactive (IR) sites in choline acetyltransferase (ChAT)-IR neurons, (3) demonstrating glycine transporter type 2 (GLYT2)-positive axon terminals synapsing on ChAT-IR neurons, and (4) localizing GLYT1-positive astroglial processes in the vicinity of synapses of ChAT-IR neurons. The effect of glycine on BFC neurons was demonstrated by bicuculline-resistant, strychnine-sensitive spontaneous IPSCs recorded in whole-cell conditions. PMID:28874448

Pheromone detection by mammalian vomeronasal neurons.

PubMed

Zufall, Frank; Kelliher, Kevin R; Leinders-Zufall, Trese

2002-08-01

The vomeronasal organ (VNO) of mammals plays an essential role in the perception of chemical stimuli of social nature including pheromone-like signals but direct evidence for the transduction of pheromones by vomeronasal sensory neurons has been lacking. The recent development of electrophysiological and optical imaging methods using confocal microscopy has enabled researchers to systematically analyze sensory responses in large populations of mouse vomeronasal neurons. These experiments revealed that vomeronasal neurons are surprisingly sensitive and highly discriminative detectors of volatile, urinary metabolites that have pheromonal activity in recipient mice. Functional mapping studies of pheromone receptor activation have uncovered the basic principles of sensory processing by vomeronasal neurons and revealed striking differences in the neural mechanisms by which chemosensory information is detected by receptor neurons in the VNO and the main olfactory epithelium. These advances offer the opportunity to decipher the logic of mammalian pheromonal communication. Copyright 2002 Wiley-Liss, Inc.

Transformation of binaural response properties in the ascending auditory pathway: influence of time-varying interaural phase disparity.

PubMed

Spitzer, M W; Semple, M N

1998-12-01

Transformation of binaural response properties in the ascending auditory pathway: influence of time-varying interaural phase disparity. J. Neurophysiol. 80: 3062-3076, 1998. Previous studies demonstrated that tuning of inferior colliculus (IC) neurons to interaural phase disparity (IPD) is often profoundly influenced by temporal variation of IPD, which simulates the binaural cue produced by a moving sound source. To determine whether sensitivity to simulated motion arises in IC or at an earlier stage of binaural processing we compared responses in IC with those of two major IPD-sensitive neuronal classes in the superior olivary complex (SOC), neurons whose discharges were phase locked (PL) to tonal stimuli and those that were nonphase locked (NPL). Time-varying IPD stimuli consisted of binaural beats, generated by presenting tones of slightly different frequencies to the two ears, and interaural phase modulation (IPM), generated by presenting a pure tone to one ear and a phase modulated tone to the other. IC neurons and NPL-SOC neurons were more sharply tuned to time-varying than to static IPD, whereas PL-SOC neurons were essentially uninfluenced by the mode of stimulus presentation. Preferred IPD was generally similar in responses to static and time-varying IPD for all unit populations. A few IC neurons were highly influenced by the direction and rate of simulated motion, but the major effect for most IC neurons and all SOC neurons was a linear shift of preferred IPD at high rates-attributable to response latency. Most IC and NPL-SOC neurons were strongly influenced by IPM stimuli simulating motion through restricted ranges of azimuth; simulated motion through partially overlapping azimuthal ranges elicited discharge profiles that were highly discontiguous, indicating that the response associated with a particular IPD is dependent on preceding portions of the stimulus. In contrast, PL-SOC responses tracked instantaneous IPD throughout the trajectory of simulated motion, resulting in highly contiguous discharge profiles for overlapping stimuli. This finding indicates that responses of PL-SOC units to time-varying IPD reflect only instantaneous IPD with no additional influence of dynamic stimulus attributes. Thus the neuronal representation of auditory spatial information undergoes a major transformation as interaural delay is initially processed in the SOC and subsequently reprocessed in IC. The finding that motion sensitivity in IC emerges from motion-insensitive input suggests that information about change of position is crucial to spatial processing at higher levels of the auditory system.

Analysis of fault-tolerant neurocontrol architectures

NASA Technical Reports Server (NTRS)

Troudet, T.; Merrill, W.

1992-01-01

The fault-tolerance of analog parallel distributed implementations of a multivariable aircraft neurocontroller is analyzed by simulating weight and neuron failures in a simplified scheme of analog processing based on the functional architecture of the ETANN chip (Electrically Trainable Artificial Neural Network). The neural information processing is found to be only partially distributed throughout the set of weights of the neurocontroller synthesized with the backpropagation algorithm. Although the degree of distribution of the neural processing, and consequently the fault-tolerance of the neurocontroller, could be enhanced using Locally Distributed Weight and Neuron Approaches, a satisfactory level of fault-tolerance could only be obtained by retraining the degrated VLSI neurocontroller. The possibility of maintaining neurocontrol performance and stability in the presence of single weight of neuron failures was demonstrated through an automated retraining procedure of the neurocontroller based on a pre-programmed choice and sequence of the training parameters.

Cusps enable line attractors for neural computation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiao, Zhuocheng; Zhang, Jiwei; Sornborger, Andrew T.

Here, line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next. To understand how pulse-gating manifests itself in a high-dimensional, nonlinear, feedforward integrate-and-fire network, we use a Fokker-Planck approach to analyzemore » system dynamics. We make a connection between pulse-gated propagation in the Fokker-Planck and population-averaged mean-field (firing rate) models, and then identify an approximate line attractor in state space as the essential structure underlying graded information propagation. An analysis of the line attractor shows that it consists of three fixed points: a central saddle with an unstable manifold along the line and stable manifolds orthogonal to the line, which is surrounded on either side by stable fixed points. Along the manifold defined by the fixed points, slow dynamics give rise to a ghost. We show that this line attractor arises at a cusp catastrophe, where a fold bifurcation develops as a function of synaptic noise; and that the ghost dynamics near the fold of the cusp underly the robustness of the line attractor. Understanding the dynamical aspects of this cusp catastrophe allows us to show how line attractors can persist in biologically realistic neuronal networks and how the interplay of pulse gating, synaptic coupling, and neuronal stochasticity can be used to enable attracting one-dimensional manifolds and, thus, dynamically control the processing of graded information.« less

Altered Intrinsic Pyramidal Neuron Properties and Pathway-Specific Synaptic Dysfunction Underlie Aberrant Hippocampal Network Function in a Mouse Model of Tauopathy

PubMed Central

Booth, Clair A.; Witton, Jonathan; Nowacki, Jakub; Tsaneva-Atanasova, Krasimira; Jones, Matthew W.; Randall, Andrew D.

2016-01-01

The formation and deposition of tau protein aggregates is proposed to contribute to cognitive impairments in dementia by disrupting neuronal function in brain regions, including the hippocampus. We used a battery of in vivo and in vitro electrophysiological recordings in the rTg4510 transgenic mouse model, which overexpresses a mutant form of human tau protein, to investigate the effects of tau pathology on hippocampal neuronal function in area CA1 of 7- to 8-month-old mice, an age point at which rTg4510 animals exhibit advanced tau pathology and progressive neurodegeneration. In vitro recordings revealed shifted theta-frequency resonance properties of CA1 pyramidal neurons, deficits in synaptic transmission at Schaffer collateral synapses, and blunted plasticity and imbalanced inhibition at temporoammonic synapses. These changes were associated with aberrant CA1 network oscillations, pyramidal neuron bursting, and spatial information coding in vivo. Our findings relate tauopathy-associated changes in cellular neurophysiology to altered behavior-dependent network function. SIGNIFICANCE STATEMENT Dementia is characterized by the loss of learning and memory ability. The deposition of tau protein aggregates in the brain is a pathological hallmark of dementia; and the hippocampus, a brain structure known to be critical in processing learning and memory, is one of the first and most heavily affected regions. Our results show that, in area CA1 of hippocampus, a region involved in spatial learning and memory, tau pathology is associated with specific disturbances in synaptic, cellular, and network-level function, culminating in the aberrant encoding of spatial information and spatial memory impairment. These studies identify several novel ways in which hippocampal information processing may be disrupted in dementia, which may provide targets for future therapeutic intervention. PMID:26758828

AER image filtering

NASA Astrophysics Data System (ADS)

Gómez-Rodríguez, F.; Linares-Barranco, A.; Paz, R.; Miró-Amarante, L.; Jiménez, G.; Civit, A.

2007-05-01

Address Event Representation (AER) is an emergent neuromorphic interchip communication protocol that allows real-time virtual massive connectivity among huge number of neurons located on different chips.[1] By exploiting high speed digital communication circuits (with nano-seconds timing), synaptic neural connections can be time multiplexed, while neural activity signals (with mili-seconds timings) are sampled at low frequencies. Neurons generate "events" according to their activity levels. That is, more active neurons generate more events per unit time and access the interchip communication channel more frequently than neurons with low activity. In Neuromorphic system development, AER brings some advantages to develop real-time image processing system: (1) AER represents the information like time continuous stream not like a frame; (2) AER sends the most important information first (although this depends on the sender); (3) AER allows to process information as soon as it is received. When AER is used in artificial vision field, each pixel is considered like a neuron, so pixel's intensity is represented like a sequence of events; modifying the number and the frequency of these events, it is possible to make some image filtering. In this paper we present four image filters using AER: (a) Noise addition and suppression, (b) brightness modification, (c) single moving object tracking and (d) geometrical transformations (rotation, translation, reduction and magnification). For testing and debugging, we use USB-AER board developed by Robotic and Technology of Computers Applied to Rehabilitation (RTCAR) research group. This board is based on an FPGA, devoted to manage the AER functionality. This board also includes a micro-controlled for USB communication, 2 Mbytes RAM and 2 AER ports (one for input and one for output).

Cusps enable line attractors for neural computation

NASA Astrophysics Data System (ADS)

Xiao, Zhuocheng; Zhang, Jiwei; Sornborger, Andrew T.; Tao, Louis

2017-11-01

Line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next. To understand how pulse-gating manifests itself in a high-dimensional, nonlinear, feedforward integrate-and-fire network, we use a Fokker-Planck approach to analyze system dynamics. We make a connection between pulse-gated propagation in the Fokker-Planck and population-averaged mean-field (firing rate) models, and then identify an approximate line attractor in state space as the essential structure underlying graded information propagation. An analysis of the line attractor shows that it consists of three fixed points: a central saddle with an unstable manifold along the line and stable manifolds orthogonal to the line, which is surrounded on either side by stable fixed points. Along the manifold defined by the fixed points, slow dynamics give rise to a ghost. We show that this line attractor arises at a cusp catastrophe, where a fold bifurcation develops as a function of synaptic noise; and that the ghost dynamics near the fold of the cusp underly the robustness of the line attractor. Understanding the dynamical aspects of this cusp catastrophe allows us to show how line attractors can persist in biologically realistic neuronal networks and how the interplay of pulse gating, synaptic coupling, and neuronal stochasticity can be used to enable attracting one-dimensional manifolds and, thus, dynamically control the processing of graded information.

Transition between Functional Regimes in an Integrate-And-Fire Network Model of the Thalamus

PubMed Central

Barardi, Alessandro; Mazzoni, Alberto

2016-01-01

The thalamus is a key brain element in the processing of sensory information. During the sleep and awake states, this brain area is characterized by the presence of two distinct dynamical regimes: in the sleep state activity is dominated by spindle oscillations (7 − 15 Hz) weakly affected by external stimuli, while in the awake state the activity is primarily driven by external stimuli. Here we develop a simple and computationally efficient model of the thalamus that exhibits two dynamical regimes with different information-processing capabilities, and study the transition between them. The network model includes glutamatergic thalamocortical (TC) relay neurons and GABAergic reticular (RE) neurons described by adaptive integrate-and-fire models in which spikes are induced by either depolarization or hyperpolarization rebound. We found a range of connectivity conditions under which the thalamic network composed by these neurons displays the two aforementioned dynamical regimes. Our results show that TC-RE loops generate spindle-like oscillations and that a minimum level of clustering (i.e. local connectivity density) in the RE-RE connections is necessary for the coexistence of the two regimes. We also observe that the transition between the two regimes occurs when the external excitatory input on TC neurons (mimicking sensory stimulation) is large enough to cause a significant fraction of them to switch from hyperpolarization-rebound-driven firing to depolarization-driven firing. Overall, our model gives a novel and clear description of the role that the two types of neurons and their connectivity play in the dynamical regimes observed in the thalamus, and in the transition between them. These results pave the way for the development of efficient models of the transmission of sensory information from periphery to cortex. PMID:27598260

Cusps enable line attractors for neural computation

DOE PAGES

Xiao, Zhuocheng; Zhang, Jiwei; Sornborger, Andrew T.; ...

2017-11-07

Here, line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next. To understand how pulse-gating manifests itself in a high-dimensional, nonlinear, feedforward integrate-and-fire network, we use a Fokker-Planck approach to analyzemore » system dynamics. We make a connection between pulse-gated propagation in the Fokker-Planck and population-averaged mean-field (firing rate) models, and then identify an approximate line attractor in state space as the essential structure underlying graded information propagation. An analysis of the line attractor shows that it consists of three fixed points: a central saddle with an unstable manifold along the line and stable manifolds orthogonal to the line, which is surrounded on either side by stable fixed points. Along the manifold defined by the fixed points, slow dynamics give rise to a ghost. We show that this line attractor arises at a cusp catastrophe, where a fold bifurcation develops as a function of synaptic noise; and that the ghost dynamics near the fold of the cusp underly the robustness of the line attractor. Understanding the dynamical aspects of this cusp catastrophe allows us to show how line attractors can persist in biologically realistic neuronal networks and how the interplay of pulse gating, synaptic coupling, and neuronal stochasticity can be used to enable attracting one-dimensional manifolds and, thus, dynamically control the processing of graded information.« less

Altered Intrinsic Pyramidal Neuron Properties and Pathway-Specific Synaptic Dysfunction Underlie Aberrant Hippocampal Network Function in a Mouse Model of Tauopathy.

PubMed

Booth, Clair A; Witton, Jonathan; Nowacki, Jakub; Tsaneva-Atanasova, Krasimira; Jones, Matthew W; Randall, Andrew D; Brown, Jonathan T

2016-01-13

The formation and deposition of tau protein aggregates is proposed to contribute to cognitive impairments in dementia by disrupting neuronal function in brain regions, including the hippocampus. We used a battery of in vivo and in vitro electrophysiological recordings in the rTg4510 transgenic mouse model, which overexpresses a mutant form of human tau protein, to investigate the effects of tau pathology on hippocampal neuronal function in area CA1 of 7- to 8-month-old mice, an age point at which rTg4510 animals exhibit advanced tau pathology and progressive neurodegeneration. In vitro recordings revealed shifted theta-frequency resonance properties of CA1 pyramidal neurons, deficits in synaptic transmission at Schaffer collateral synapses, and blunted plasticity and imbalanced inhibition at temporoammonic synapses. These changes were associated with aberrant CA1 network oscillations, pyramidal neuron bursting, and spatial information coding in vivo. Our findings relate tauopathy-associated changes in cellular neurophysiology to altered behavior-dependent network function. Dementia is characterized by the loss of learning and memory ability. The deposition of tau protein aggregates in the brain is a pathological hallmark of dementia; and the hippocampus, a brain structure known to be critical in processing learning and memory, is one of the first and most heavily affected regions. Our results show that, in area CA1 of hippocampus, a region involved in spatial learning and memory, tau pathology is associated with specific disturbances in synaptic, cellular, and network-level function, culminating in the aberrant encoding of spatial information and spatial memory impairment. These studies identify several novel ways in which hippocampal information processing may be disrupted in dementia, which may provide targets for future therapeutic intervention. Copyright © 2016 Booth, Witton et al.

A behavioral task with more opportunities for memory acquisition promotes the survival of new neurons in the adult dentate gyrus.

PubMed

Aasebø, Ida E J; Kasture, Ameya Sanjay; Passeggeri, Marzia; Tashiro, Ayumu

2018-05-09

It has been suggested that the dentate gyrus, particularly its new neurons generated via adult neurogenesis, is involved in memory acquisition and recall. Here, we trained rats in two types of Morris water maze tasks that are differentially associated with these two memory processes, and examined whether new neurons are differently affected by the two tasks performed during the second week of neuronal birth. Our results indicate that the task involving more opportunities to acquire new information better supports the survival of new neurons. Further, we assessed whether the two tasks differentially induce the expression of an immediate early gene, Zif268, which is known to be induced by neuronal activation. While the two tasks differentially induce Zif268 expression in the dentate gyrus, the proportions of new neurons activated were similar between the two tasks. Thus, we conclude that while the two tasks differentially activate the dentate gyrus, the task involving more opportunities for memory acquisition during the second week of the birth of new neurons better promotes the survival of the new neurons.

Analytical Calculation of Mutual Information between Weakly Coupled Poisson-Spiking Neurons in Models of Dynamically Gated Communication.

PubMed

Cannon, Jonathan

2017-01-01

Mutual information is a commonly used measure of communication between neurons, but little theory exists describing the relationship between mutual information and the parameters of the underlying neuronal interaction. Such a theory could help us understand how specific physiological changes affect the capacity of neurons to synaptically communicate, and, in particular, they could help us characterize the mechanisms by which neuronal dynamics gate the flow of information in the brain. Here we study a pair of linear-nonlinear-Poisson neurons coupled by a weak synapse. We derive an analytical expression describing the mutual information between their spike trains in terms of synapse strength, neuronal activation function, the time course of postsynaptic currents, and the time course of the background input received by the two neurons. This expression allows mutual information calculations that would otherwise be computationally intractable. We use this expression to analytically explore the interaction of excitation, information transmission, and the convexity of the activation function. Then, using this expression to quantify mutual information in simulations, we illustrate the information-gating effects of neural oscillations and oscillatory coherence, which may either increase or decrease the mutual information across the synapse depending on parameters. Finally, we show analytically that our results can quantitatively describe the selection of one information pathway over another when multiple sending neurons project weakly to a single receiving neuron.

Synchronous Spike Patterns in Macaque Motor Cortex during an Instructed-Delay Reach-to-Grasp Task

PubMed Central

Torre, Emiliano; Quaglio, Pietro; Denker, Michael; Brochier, Thomas; Riehle, Alexa

2016-01-01

The computational role of spike time synchronization at millisecond precision among neurons in the cerebral cortex is hotly debated. Studies performed on data of limited size provided experimental evidence that low-order correlations occur in relation to behavior. Advances in electrophysiological technology to record from hundreds of neurons simultaneously provide the opportunity to observe coordinated spiking activity of larger populations of cells. We recently published a method that combines data mining and statistical evaluation to search for significant patterns of synchronous spikes in massively parallel spike trains (Torre et al., 2013). The method solves the computational and multiple testing problems raised by the high dimensionality of the data. In the current study, we used our method on simultaneous recordings from two macaque monkeys engaged in an instructed-delay reach-to-grasp task to determine the emergence of spike synchronization in relation to behavior. We found a multitude of synchronous spike patterns aligned in both monkeys along a preferential mediolateral orientation in brain space. The occurrence of the patterns is highly specific to behavior, indicating that different behaviors are associated with the synchronization of different groups of neurons (“cell assemblies”). However, pooled patterns that overlap in neuronal composition exhibit no specificity, suggesting that exclusive cell assemblies become active during different behaviors, but can recruit partly identical neurons. These findings are consistent across multiple recording sessions analyzed across the two monkeys. SIGNIFICANCE STATEMENT Neurons in the brain communicate via electrical impulses called spikes. How spikes are coordinated to process information is still largely unknown. Synchronous spikes are effective in triggering a spike emission in receiving neurons and have been shown to occur in relation to behavior in a number of studies on simultaneous recordings of few neurons. We recently published a method to extend this type of investigation to larger data. Here, we apply it to simultaneous recordings of hundreds of neurons from the motor cortex of macaque monkeys performing a motor task. Our analysis reveals groups of neurons selectively synchronizing their activity in relation to behavior, which sheds new light on the role of synchrony in information processing in the cerebral cortex. PMID:27511007

Synchronous Spike Patterns in Macaque Motor Cortex during an Instructed-Delay Reach-to-Grasp Task.

PubMed

Torre, Emiliano; Quaglio, Pietro; Denker, Michael; Brochier, Thomas; Riehle, Alexa; Grün, Sonja

2016-08-10

The computational role of spike time synchronization at millisecond precision among neurons in the cerebral cortex is hotly debated. Studies performed on data of limited size provided experimental evidence that low-order correlations occur in relation to behavior. Advances in electrophysiological technology to record from hundreds of neurons simultaneously provide the opportunity to observe coordinated spiking activity of larger populations of cells. We recently published a method that combines data mining and statistical evaluation to search for significant patterns of synchronous spikes in massively parallel spike trains (Torre et al., 2013). The method solves the computational and multiple testing problems raised by the high dimensionality of the data. In the current study, we used our method on simultaneous recordings from two macaque monkeys engaged in an instructed-delay reach-to-grasp task to determine the emergence of spike synchronization in relation to behavior. We found a multitude of synchronous spike patterns aligned in both monkeys along a preferential mediolateral orientation in brain space. The occurrence of the patterns is highly specific to behavior, indicating that different behaviors are associated with the synchronization of different groups of neurons ("cell assemblies"). However, pooled patterns that overlap in neuronal composition exhibit no specificity, suggesting that exclusive cell assemblies become active during different behaviors, but can recruit partly identical neurons. These findings are consistent across multiple recording sessions analyzed across the two monkeys. Neurons in the brain communicate via electrical impulses called spikes. How spikes are coordinated to process information is still largely unknown. Synchronous spikes are effective in triggering a spike emission in receiving neurons and have been shown to occur in relation to behavior in a number of studies on simultaneous recordings of few neurons. We recently published a method to extend this type of investigation to larger data. Here, we apply it to simultaneous recordings of hundreds of neurons from the motor cortex of macaque monkeys performing a motor task. Our analysis reveals groups of neurons selectively synchronizing their activity in relation to behavior, which sheds new light on the role of synchrony in information processing in the cerebral cortex. Copyright © 2016 Torre, et al.

Network dynamics underlying the formation of sparse, informative representations in the hippocampus.

PubMed

Karlsson, Mattias P; Frank, Loren M

2008-12-24

During development, activity-dependent processes increase the specificity of neural responses to stimuli, but the role that this type of process plays in adult plasticity is unclear. We examined the dynamics of hippocampal activity as animals learned about new environments to understand how neural selectivity changes with experience. Hippocampal principal neurons fire when the animal is located in a particular subregion of its environment, and in any given environment the hippocampal representation is sparse: less than half of the neurons in areas CA1 and CA3 are active whereas the rest are essentially silent. Here we show that different dynamics govern the evolution of this sparsity in CA1 and upstream area CA3. CA1, but not CA3, produces twice as many spikes in novel compared with familiar environments. This high rate firing continues during sharp wave ripple events in a subsequent rest period. The overall CA1 population rate declines and the number of active cells decreases as the environment becomes familiar and task performance improves, but the decline in rate is not uniform across neurons. Instead, the activity of cells with initial peak spatial rates above approximately 12 Hz is enhanced, whereas the activity of cells with lower initial peak rates is suppressed. The result of these changes is that the active CA1 population comes to consist of a relatively small group of cells with strong spatial tuning. This process is not evident in CA3, indicating that a region-specific and long timescale process operates in CA1 to create a sparse, spatially informative population of neurons.

Early sensitivity for eyes within faces: a new neuronal account of holistic and featural processing

PubMed Central

Nemrodov, Dan; Anderson, Thomas; Preston, Frank F.; Itier, Roxane J.

2017-01-01

Eyes are central to face processing however their role in early face encoding as reflected by the N170 ERP component is unclear. Using eye tracking to enforce fixation on specific facial features, we found that the N170 was larger for fixation on the eyes compared to fixation on the forehead, nasion, nose or mouth, which all yielded similar amplitudes. This eye sensitivity was seen in both upright and inverted faces and was lost in eyeless faces, demonstrating it was due to the presence of eyes at fovea. Upright eyeless faces elicited largest N170 at nose fixation. Importantly, the N170 face inversion effect (FIE) was strongly attenuated in eyeless faces when fixation was on the eyes but was less attenuated for nose fixation and was normal when fixation was on the mouth. These results suggest the impact of eye removal on the N170 FIE is a function of the angular distance between the fixated feature and the eye location. We propose the Lateral Inhibition, Face Template and Eye Detector based (LIFTED) model which accounts for all the present N170 results including the FIE and its interaction with eye removal. Although eyes elicit the largest N170 response, reflecting the activity of an eye detector, the processing of upright faces is holistic and entails an inhibitory mechanism from neurons coding parafoveal information onto neurons coding foveal information. The LIFTED model provides a neuronal account of holistic and featural processing involved in upright and inverted faces and offers precise predictions for further testing. PMID:24768932

Cognitive processing in the primary visual cortex: from perception to memory.

PubMed

Supèr, Hans

2002-01-01

The primary visual cortex is the first cortical area of the visual system that receives information from the external visual world. Based on the receptive field characteristics of the neurons in this area, it has been assumed that the primary visual cortex is a pure sensory area extracting basic elements of the visual scene. This information is then subsequently further processed upstream in the higher-order visual areas and provides us with perception and storage of the visual environment. However, recent findings show that such neural implementations are observed in the primary visual cortex. These neural correlates are expressed by the modulated activity of the late response of a neuron to a stimulus, and most likely depend on recurrent interactions between several areas of the visual system. This favors the concept of a distributed nature of visual processing in perceptual organization.

Neuromorphic photonic networks using silicon photonic weight banks.

PubMed

Tait, Alexander N; de Lima, Thomas Ferreira; Zhou, Ellen; Wu, Allie X; Nahmias, Mitchell A; Shastri, Bhavin J; Prucnal, Paul R

2017-08-07

Photonic systems for high-performance information processing have attracted renewed interest. Neuromorphic silicon photonics has the potential to integrate processing functions that vastly exceed the capabilities of electronics. We report first observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks. A mathematical isomorphism between the silicon photonic circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis. Exploiting this isomorphism, a simulated 24-node silicon photonic neural network is programmed using "neural compiler" to solve a differential system emulation task. A 294-fold acceleration against a conventional benchmark is predicted. We also propose and derive power consumption analysis for modulator-class neurons that, as opposed to laser-class neurons, are compatible with silicon photonic platforms. At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.

A plausible neural circuit for decision making and its formation based on reinforcement learning.

PubMed

Wei, Hui; Dai, Dawei; Bu, Yijie

2017-06-01

A human's, or lower insects', behavior is dominated by its nervous system. Each stable behavior has its own inner steps and control rules, and is regulated by a neural circuit. Understanding how the brain influences perception, thought, and behavior is a central mandate of neuroscience. The phototactic flight of insects is a widely observed deterministic behavior. Since its movement is not stochastic, the behavior should be dominated by a neural circuit. Based on the basic firing characteristics of biological neurons and the neural circuit's constitution, we designed a plausible neural circuit for this phototactic behavior from logic perspective. The circuit's output layer, which generates a stable spike firing rate to encode flight commands, controls the insect's angular velocity when flying. The firing pattern and connection type of excitatory and inhibitory neurons are considered in this computational model. We simulated the circuit's information processing using a distributed PC array, and used the real-time average firing rate of output neuron clusters to drive a flying behavior simulation. In this paper, we also explored how a correct neural decision circuit is generated from network flow view through a bee's behavior experiment based on the reward and punishment feedback mechanism. The significance of this study: firstly, we designed a neural circuit to achieve the behavioral logic rules by strictly following the electrophysiological characteristics of biological neurons and anatomical facts. Secondly, our circuit's generality permits the design and implementation of behavioral logic rules based on the most general information processing and activity mode of biological neurons. Thirdly, through computer simulation, we achieved new understanding about the cooperative condition upon which multi-neurons achieve some behavioral control. Fourthly, this study aims in understanding the information encoding mechanism and how neural circuits achieve behavior control. Finally, this study also helps establish a transitional bridge between the microscopic activity of the nervous system and macroscopic animal behavior.

Goal-seeking neural net for recall and recognition

NASA Astrophysics Data System (ADS)

Omidvar, Omid M.

1990-07-01

Neural networks have been used to mimic cognitive processes which take place in animal brains. The learning capability inherent in neural networks makes them suitable candidates for adaptive tasks such as recall and recognition. The synaptic reinforcements create a proper condition for adaptation, which results in memorization, formation of perception, and higher order information processing activities. In this research a model of a goal seeking neural network is studied and the operation of the network with regard to recall and recognition is analyzed. In these analyses recall is defined as retrieval of stored information where little or no matching is involved. On the other hand recognition is recall with matching; therefore it involves memorizing a piece of information with complete presentation. This research takes the generalized view of reinforcement in which all the signals are potential reinforcers. The neuronal response is considered to be the source of the reinforcement. This local approach to adaptation leads to the goal seeking nature of the neurons as network components. In the proposed model all the synaptic strengths are reinforced in parallel while the reinforcement among the layers is done in a distributed fashion and pipeline mode from the last layer inward. A model of complex neuron with varying threshold is developed to account for inhibitory and excitatory behavior of real neuron. A goal seeking model of a neural network is presented. This network is utilized to perform recall and recognition tasks. The performance of the model with regard to the assigned tasks is presented.

Retrograde monosynaptic tracing reveals the temporal evolution of inputs onto new neurons in the adult dentate gyrus and olfactory bulb

PubMed Central

Deshpande, Aditi; Bergami, Matteo; Ghanem, Alexander; Conzelmann, Karl-Klaus; Lepier, Alexandra; Götz, Magdalena; Berninger, Benedikt

2013-01-01

Identifying the connectome of adult-generated neurons is essential for understanding how the preexisting circuitry is refined by neurogenesis. Changes in the pattern of connectivity are likely to control the differentiation process of newly generated neurons and exert an important influence on their unique capacity to contribute to information processing. Using a monosynaptic rabies virus-based tracing technique, we studied the evolving presynaptic connectivity of adult-generated neurons in the dentate gyrus (DG) of the hippocampus and olfactory bulb (OB) during the first weeks of their life. In both neurogenic zones, adult-generated neurons first receive local connections from multiple types of GABAergic interneurons before long-range projections become established, such as those originating from cortical areas. Interestingly, despite fundamental similarities in the overall pattern of evolution of presynaptic connectivity, there were notable differences with regard to the development of cortical projections: although DG granule neuron input originating from the entorhinal cortex could be traced starting only from 3 to 5 wk on, newly generated neurons in the OB received input from the anterior olfactory nucleus and piriform cortex already by the second week. This early glutamatergic input onto newly generated interneurons in the OB was matched in time by the equally early innervations of DG granule neurons by glutamatergic mossy cells. The development of connectivity revealed by our study may suggest common principles for incorporating newly generated neurons into a preexisting circuit. PMID:23487772

The graphical brain: Belief propagation and active inference

PubMed Central

Friston, Karl J.; Parr, Thomas; de Vries, Bert

2018-01-01

This paper considers functional integration in the brain from a computational perspective. We ask what sort of neuronal message passing is mandated by active inference—and what implications this has for context-sensitive connectivity at microscopic and macroscopic levels. In particular, we formulate neuronal processing as belief propagation under deep generative models. Crucially, these models can entertain both discrete and continuous states, leading to distinct schemes for belief updating that play out on the same (neuronal) architecture. Technically, we use Forney (normal) factor graphs to elucidate the requisite message passing in terms of its form and scheduling. To accommodate mixed generative models (of discrete and continuous states), one also has to consider link nodes or factors that enable discrete and continuous representations to talk to each other. When mapping the implicit computational architecture onto neuronal connectivity, several interesting features emerge. For example, Bayesian model averaging and comparison, which link discrete and continuous states, may be implemented in thalamocortical loops. These and other considerations speak to a computational connectome that is inherently state dependent and self-organizing in ways that yield to a principled (variational) account. We conclude with simulations of reading that illustrate the implicit neuronal message passing, with a special focus on how discrete (semantic) representations inform, and are informed by, continuous (visual) sampling of the sensorium. Author Summary This paper considers functional integration in the brain from a computational perspective. We ask what sort of neuronal message passing is mandated by active inference—and what implications this has for context-sensitive connectivity at microscopic and macroscopic levels. In particular, we formulate neuronal processing as belief propagation under deep generative models that can entertain both discrete and continuous states. This leads to distinct schemes for belief updating that play out on the same (neuronal) architecture. Technically, we use Forney (normal) factor graphs to characterize the requisite message passing, and link this formal characterization to canonical microcircuits and extrinsic connectivity in the brain. PMID:29417960

The Neural Representation of Goal-Directed Actions and Outcomes in the Ventral Striatum's Olfactory Tubercle

PubMed Central

Gadziola, Marie A.

2016-01-01

The ventral striatum is critical for evaluating reward information and the initiation of goal-directed behaviors. The many cellular, afferent, and efferent similarities between the ventral striatum's nucleus accumbens and olfactory tubercle (OT) suggests the distributed involvement of neurons within the ventral striatopallidal complex in motivated behaviors. Although the nucleus accumbens has an established role in representing goal-directed actions and their outcomes, it is not known whether this function is localized within the nucleus accumbens or distributed also within the OT. Answering such a fundamental question will expand our understanding of the neural mechanisms underlying motivated behaviors. Here we address whether the OT encodes natural reinforcers and serves as a substrate for motivational information processing. In recordings from mice engaged in a novel water-motivated instrumental task, we report that OT neurons modulate their firing rate during initiation and progression of the instrumental licking behavior, with some activity being internally generated and preceding the first lick. We further found that as motivational drive decreases throughout a session, the activity of OT neurons is enhanced earlier relative to the behavioral action. Additionally, OT neurons discriminate the types and magnitudes of fluid reinforcers. Together, these data suggest that the processing of reward information and the orchestration of goal-directed behaviors is a global principle of the ventral striatum and have important implications for understanding the neural systems subserving addiction and mood disorders. SIGNIFICANCE STATEMENT Goal-directed behaviors are widespread among animals and underlie complex behaviors ranging from food intake, social behavior, and even pathological conditions, such as gambling and drug addiction. The ventral striatum is a neural system critical for evaluating reward information and the initiation of goal-directed behaviors. Here we show that neurons in the olfactory tubercle subregion of the ventral striatum robustly encode the onset and progression of motivated behaviors, and discriminate the type and magnitude of a reward. Our findings are novel in showing that olfactory tubercle neurons participate in such coding schemes and are in accordance with the principle that ventral striatum substructures may cooperate to guide motivated behaviors. PMID:26758844

NeuronRead, an open source semi-automated tool for morphometric analysis of phase contrast and fluorescence neuronal images.

PubMed

Dias, Roberto A; Gonçalves, Bruno P; da Rocha, Joana F; da Cruz E Silva, Odete A B; da Silva, Augusto M F; Vieira, Sandra I

2017-12-01

Neurons are specialized cells of the Central Nervous System whose function is intricately related to the neuritic network they develop to transmit information. Morphological evaluation of this network and other neuronal structures is required to establish relationships between neuronal morphology and function, and may allow monitoring physiological and pathophysiologic alterations. Fluorescence-based microphotographs are the most widely used in cellular bioimaging, but phase contrast (PhC) microphotographs are easier to obtain, more affordable, and do not require invasive, complicated and disruptive techniques. Despite the various freeware tools available for fluorescence-based images analysis, few exist that can tackle the more elusive and harder-to-analyze PhC images. To surpass this, an interactive semi-automated image processing workflow was developed to easily extract relevant information (e.g. total neuritic length, average cell body area) from both PhC and fluorescence neuronal images. This workflow, named 'NeuronRead', was developed in the form of an ImageJ macro. Its robustness and adaptability were tested and validated on rat cortical primary neurons under control and differentiation inhibitory conditions. Validation included a comparison to manual determinations and to a golden standard freeware tool for fluorescence image analysis. NeuronRead was subsequently applied to PhC images of neurons at distinct differentiation days and exposed or not to DAPT, a pharmacological inhibitor of the γ-secretase enzyme, which cleaves the well-known Alzheimer's amyloid precursor protein (APP) and the Notch receptor. Data obtained confirms a neuritogenic regulatory role for γ-secretase products and validates NeuronRead as a time- and cost-effective useful monitoring tool. Copyright © 2017. Published by Elsevier Inc.

Processing and Analysis of Multichannel Extracellular Neuronal Signals: State-of-the-Art and Challenges

PubMed Central

Mahmud, Mufti; Vassanelli, Stefano

2016-01-01

In recent years multichannel neuronal signal acquisition systems have allowed scientists to focus on research questions which were otherwise impossible. They act as a powerful means to study brain (dys)functions in in-vivo and in in-vitro animal models. Typically, each session of electrophysiological experiments with multichannel data acquisition systems generate large amount of raw data. For example, a 128 channel signal acquisition system with 16 bits A/D conversion and 20 kHz sampling rate will generate approximately 17 GB data per hour (uncompressed). This poses an important and challenging problem of inferring conclusions from the large amounts of acquired data. Thus, automated signal processing and analysis tools are becoming a key component in neuroscience research, facilitating extraction of relevant information from neuronal recordings in a reasonable time. The purpose of this review is to introduce the reader to the current state-of-the-art of open-source packages for (semi)automated processing and analysis of multichannel extracellular neuronal signals (i.e., neuronal spikes, local field potentials, electroencephalogram, etc.), and the existing Neuroinformatics infrastructure for tool and data sharing. The review is concluded by pinpointing some major challenges that are being faced, which include the development of novel benchmarking techniques, cloud-based distributed processing and analysis tools, as well as defining novel means to share and standardize data. PMID:27313507

Optimality in mono- and multisensory map formation.

PubMed

Bürck, Moritz; Friedel, Paul; Sichert, Andreas B; Vossen, Christine; van Hemmen, J Leo

2010-07-01

In the struggle for survival in a complex and dynamic environment, nature has developed a multitude of sophisticated sensory systems. In order to exploit the information provided by these sensory systems, higher vertebrates reconstruct the spatio-temporal environment from each of the sensory systems they have at their disposal. That is, for each modality the animal computes a neuronal representation of the outside world, a monosensory neuronal map. Here we present a universal framework that allows to calculate the specific layout of the involved neuronal network by means of a general mathematical principle, viz., stochastic optimality. In order to illustrate the use of this theoretical framework, we provide a step-by-step tutorial of how to apply our model. In so doing, we present a spatial and a temporal example of optimal stimulus reconstruction which underline the advantages of our approach. That is, given a known physical signal transmission and rudimental knowledge of the detection process, our approach allows to estimate the possible performance and to predict neuronal properties of biological sensory systems. Finally, information from different sensory modalities has to be integrated so as to gain a unified perception of reality for further processing, e.g., for distinct motor commands. We briefly discuss concepts of multimodal interaction and how a multimodal space can evolve by alignment of monosensory maps.

Chemosensory Information Processing between Keratinocytes and Trigeminal Neurons

PubMed Central

Sondersorg, Anna Christina; Busse, Daniela; Kyereme, Jessica; Rothermel, Markus; Neufang, Gitta; Gisselmann, Günter; Hatt, Hanns; Conrad, Heike

2014-01-01

Trigeminal fibers terminate within the facial mucosa and skin and transmit tactile, proprioceptive, chemical, and nociceptive sensations. Trigeminal sensations can arise from the direct stimulation of intraepithelial free nerve endings or indirectly through information transmission from adjacent cells at the peripheral innervation area. For mechanical and thermal cues, communication processes between skin cells and somatosensory neurons have already been suggested. High concentrations of most odors typically provoke trigeminal sensations in vivo but surprisingly fail to activate trigeminal neuron monocultures. This fact favors the hypothesis that epithelial cells may participate in chemodetection and subsequently transmit signals to neighboring trigeminal fibers. Keratinocytes, the major cell type of the epidermis, express various receptors that enable reactions to multiple environmental stimuli. Here, using a co-culture approach, we show for the first time that exposure to the odorant chemicals induces a chemical communication between human HaCaT keratinocytes and mouse trigeminal neurons. Moreover, a supernatant analysis of stimulated keratinocytes and subsequent blocking experiments with pyrodoxalphosphate-6-azophenyl-2′,4′-disulfonate revealed that ATP serves as the mediating transmitter molecule released from skin cells after odor stimulation. We show that the ATP release resulting from Javanol® stimulation of keratinocytes was mediated by pannexins. Consequently, keratinocytes act as chemosensors linking the environment and the trigeminal system via ATP signaling. PMID:24790106

Towards the understanding of network information processing in biology

NASA Astrophysics Data System (ADS)

Singh, Vijay

Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.

Birds have primate-like numbers of neurons in the forebrain

PubMed Central

Olkowicz, Seweryn; Kocourek, Martin; Lučan, Radek K.; Porteš, Michal; Fitch, W. Tecumseh; Herculano-Houzel, Suzana; Němec, Pavel

2016-01-01

Some birds achieve primate-like levels of cognition, even though their brains tend to be much smaller in absolute size. This poses a fundamental problem in comparative and computational neuroscience, because small brains are expected to have a lower information-processing capacity. Using the isotropic fractionator to determine numbers of neurons in specific brain regions, here we show that the brains of parrots and songbirds contain on average twice as many neurons as primate brains of the same mass, indicating that avian brains have higher neuron packing densities than mammalian brains. Additionally, corvids and parrots have much higher proportions of brain neurons located in the pallial telencephalon compared with primates or other mammals and birds. Thus, large-brained parrots and corvids have forebrain neuron counts equal to or greater than primates with much larger brains. We suggest that the large numbers of neurons concentrated in high densities in the telencephalon substantially contribute to the neural basis of avian intelligence. PMID:27298365

Experience-related reorganization of giant synapses in the lateral complex: Potential role in plasticity of the sky-compass pathway in the desert ant Cataglyphis fortis.

PubMed

Schmitt, Franziska; Stieb, Sara Mae; Wehner, Rüdiger; Rössler, Wolfgang

2016-04-01

Cataglyphis desert ants undergo an age-related polyethism from interior workers to relatively short-lived foragers with remarkable visual navigation capabilities, predominantly achieved by path integration using a polarized skylight-based sun compass and a stride-integrating odometer. Behavioral and physiological experiments revealed that the polarization (POL) pattern is processed via specialized UV-photoreceptors in the dorsal rim area of the compound eye and POL sensitive optic lobe neurons. Further information about the neuronal substrate for processing of POL information in the ant brain has remained elusive. This work focuses on the lateral complex (LX), known as an important relay station in the insect sky-compass pathway. Neuroanatomical results in Cataglyphis fortis show that LX giant synapses (GS) connect large presynaptic terminals from anterior optic tubercle neurons with postsynaptic GABAergic profiles of tangential neurons innervating the ellipsoid body of the central complex. At the ultrastructural level, the cup-shaped presynaptic structures comprise many active zones contacting numerous small postsynaptic profiles. Three-dimensional quantification demonstrated a significantly higher number of GS (∼ 13%) in foragers compared with interior workers. Light exposure, as opposed to age, was necessary and sufficient to trigger a similar increase in GS numbers. Furthermore, the increase in GS numbers was sensitive to the exclusion of UV light. As previous experiments have demonstrated the importance of the UV spectrum for sky-compass navigation in Cataglyphis, we conclude that plasticity in LX GS may reflect processes involved in the initial calibration of sky-compass neuronal circuits during orientation walks preceding active foraging. © 2015 Wiley Periodicals, Inc.

Representational geometry: integrating cognition, computation, and the brain.

PubMed

Kriegeskorte, Nikolaus; Kievit, Rogier A

2013-08-01

The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure. Copyright © 2013 Elsevier Ltd. All rights reserved.

Parallel processing in the honeybee olfactory pathway: structure, function, and evolution.

PubMed

Rössler, Wolfgang; Brill, Martin F

2013-11-01

Animals face highly complex and dynamic olfactory stimuli in their natural environments, which require fast and reliable olfactory processing. Parallel processing is a common principle of sensory systems supporting this task, for example in visual and auditory systems, but its role in olfaction remained unclear. Studies in the honeybee focused on a dual olfactory pathway. Two sets of projection neurons connect glomeruli in two antennal-lobe hemilobes via lateral and medial tracts in opposite sequence with the mushroom bodies and lateral horn. Comparative studies suggest that this dual-tract circuit represents a unique adaptation in Hymenoptera. Imaging studies indicate that glomeruli in both hemilobes receive redundant sensory input. Recent simultaneous multi-unit recordings from projection neurons of both tracts revealed widely overlapping response profiles strongly indicating parallel olfactory processing. Whereas lateral-tract neurons respond fast with broad (generalistic) profiles, medial-tract neurons are odorant specific and respond slower. In analogy to "what-" and "where" subsystems in visual pathways, this suggests two parallel olfactory subsystems providing "what-" (quality) and "when" (temporal) information. Temporal response properties may support across-tract coincidence coding in higher centers. Parallel olfactory processing likely enhances perception of complex odorant mixtures to decode the diverse and dynamic olfactory world of a social insect.

The representation of information about faces in the temporal and frontal lobes.

PubMed

Rolls, Edmund T

2007-01-07

Neurophysiological evidence is described showing that some neurons in the macaque inferior temporal visual cortex have responses that are invariant with respect to the position, size and view of faces and objects, and that these neurons show rapid processing and rapid learning. Which face or object is present is encoded using a distributed representation in which each neuron conveys independent information in its firing rate, with little information evident in the relative time of firing of different neurons. This ensemble encoding has the advantages of maximising the information in the representation useful for discrimination between stimuli using a simple weighted sum of the neuronal firing by the receiving neurons, generalisation and graceful degradation. These invariant representations are ideally suited to provide the inputs to brain regions such as the orbitofrontal cortex and amygdala that learn the reinforcement associations of an individual's face, for then the learning, and the appropriate social and emotional responses, generalise to other views of the same face. A theory is described of how such invariant representations may be produced in a hierarchically organised set of visual cortical areas with convergent connectivity. The theory proposes that neurons in these visual areas use a modified Hebb synaptic modification rule with a short-term memory trace to capture whatever can be captured at each stage that is invariant about objects as the objects change in retinal view, position, size and rotation. Another population of neurons in the cortex in the superior temporal sulcus encodes other aspects of faces such as face expression, eye gaze, face view and whether the head is moving. These neurons thus provide important additional inputs to parts of the brain such as the orbitofrontal cortex and amygdala that are involved in social communication and emotional behaviour. Outputs of these systems reach the amygdala, in which face-selective neurons are found, and also the orbitofrontal cortex, in which some neurons are tuned to face identity and others to face expression. In humans, activation of the orbitofrontal cortex is found when a change of face expression acts as a social signal that behaviour should change; and damage to the orbitofrontal cortex can impair face and voice expression identification, and also the reversal of emotional behaviour that normally occurs when reinforcers are reversed.

Parallel processing via a dual olfactory pathway in the honeybee.

PubMed

Brill, Martin F; Rosenbaum, Tobias; Reus, Isabelle; Kleineidam, Christoph J; Nawrot, Martin P; Rössler, Wolfgang

2013-02-06

In their natural environment, animals face complex and highly dynamic olfactory input. Thus vertebrates as well as invertebrates require fast and reliable processing of olfactory information. Parallel processing has been shown to improve processing speed and power in other sensory systems and is characterized by extraction of different stimulus parameters along parallel sensory information streams. Honeybees possess an elaborate olfactory system with unique neuronal architecture: a dual olfactory pathway comprising a medial projection-neuron (PN) antennal lobe (AL) protocerebral output tract (m-APT) and a lateral PN AL output tract (l-APT) connecting the olfactory lobes with higher-order brain centers. We asked whether this neuronal architecture serves parallel processing and employed a novel technique for simultaneous multiunit recordings from both tracts. The results revealed response profiles from a high number of PNs of both tracts to floral, pheromonal, and biologically relevant odor mixtures tested over multiple trials. PNs from both tracts responded to all tested odors, but with different characteristics indicating parallel processing of similar odors. Both PN tracts were activated by widely overlapping response profiles, which is a requirement for parallel processing. The l-APT PNs had broad response profiles suggesting generalized coding properties, whereas the responses of m-APT PNs were comparatively weaker and less frequent, indicating higher odor specificity. Comparison of response latencies within and across tracts revealed odor-dependent latencies. We suggest that parallel processing via the honeybee dual olfactory pathway provides enhanced odor processing capabilities serving sophisticated odor perception and olfactory demands associated with a complex olfactory world of this social insect.

Information Compression, Multiple Alignment, and the Representation and Processing of Knowledge in the Brain

PubMed Central

Wolff, J. Gerard

2016-01-01

The SP theory of intelligence, with its realization in the SP computer model, aims to simplify and integrate observations and concepts across artificial intelligence, mainstream computing, mathematics, and human perception and cognition, with information compression as a unifying theme. This paper describes how abstract structures and processes in the theory may be realized in terms of neurons, their interconnections, and the transmission of signals between neurons. This part of the SP theory—SP-neural—is a tentative and partial model for the representation and processing of knowledge in the brain. Empirical support for the SP theory—outlined in the paper—provides indirect support for SP-neural. In the abstract part of the SP theory (SP-abstract), all kinds of knowledge are represented with patterns, where a pattern is an array of atomic symbols in one or two dimensions. In SP-neural, the concept of a “pattern” is realized as an array of neurons called a pattern assembly, similar to Hebb's concept of a “cell assembly” but with important differences. Central to the processing of information in SP-abstract is information compression via the matching and unification of patterns (ICMUP) and, more specifically, information compression via the powerful concept of multiple alignment, borrowed and adapted from bioinformatics. Processes such as pattern recognition, reasoning and problem solving are achieved via the building of multiple alignments, while unsupervised learning is achieved by creating patterns from sensory information and also by creating patterns from multiple alignments in which there is a partial match between one pattern and another. It is envisaged that, in SP-neural, short-lived neural structures equivalent to multiple alignments will be created via an inter-play of excitatory and inhibitory neural signals. It is also envisaged that unsupervised learning will be achieved by the creation of pattern assemblies from sensory information and from the neural equivalents of multiple alignments, much as in the non-neural SP theory—and significantly different from the “Hebbian” kinds of learning which are widely used in the kinds of artificial neural network that are popular in computer science. The paper discusses several associated issues, with relevant empirical evidence. PMID:27857695

Information Compression, Multiple Alignment, and the Representation and Processing of Knowledge in the Brain.

PubMed

Wolff, J Gerard

2016-01-01

The SP theory of intelligence , with its realization in the SP computer model , aims to simplify and integrate observations and concepts across artificial intelligence, mainstream computing, mathematics, and human perception and cognition, with information compression as a unifying theme. This paper describes how abstract structures and processes in the theory may be realized in terms of neurons, their interconnections, and the transmission of signals between neurons. This part of the SP theory- SP-neural -is a tentative and partial model for the representation and processing of knowledge in the brain. Empirical support for the SP theory-outlined in the paper-provides indirect support for SP-neural. In the abstract part of the SP theory (SP-abstract), all kinds of knowledge are represented with patterns , where a pattern is an array of atomic symbols in one or two dimensions. In SP-neural, the concept of a "pattern" is realized as an array of neurons called a pattern assembly , similar to Hebb's concept of a "cell assembly" but with important differences. Central to the processing of information in SP-abstract is information compression via the matching and unification of patterns (ICMUP) and, more specifically, information compression via the powerful concept of multiple alignment , borrowed and adapted from bioinformatics. Processes such as pattern recognition, reasoning and problem solving are achieved via the building of multiple alignments, while unsupervised learning is achieved by creating patterns from sensory information and also by creating patterns from multiple alignments in which there is a partial match between one pattern and another. It is envisaged that, in SP-neural, short-lived neural structures equivalent to multiple alignments will be created via an inter-play of excitatory and inhibitory neural signals. It is also envisaged that unsupervised learning will be achieved by the creation of pattern assemblies from sensory information and from the neural equivalents of multiple alignments, much as in the non-neural SP theory-and significantly different from the "Hebbian" kinds of learning which are widely used in the kinds of artificial neural network that are popular in computer science. The paper discusses several associated issues, with relevant empirical evidence.

Automatic spike sorting using tuning information.

PubMed

Ventura, Valérie

2009-09-01

Current spike sorting methods focus on clustering neurons' characteristic spike waveforms. The resulting spike-sorted data are typically used to estimate how covariates of interest modulate the firing rates of neurons. However, when these covariates do modulate the firing rates, they provide information about spikes' identities, which thus far have been ignored for the purpose of spike sorting. This letter describes a novel approach to spike sorting, which incorporates both waveform information and tuning information obtained from the modulation of firing rates. Because it efficiently uses all the available information, this spike sorter yields lower spike misclassification rates than traditional automatic spike sorters. This theoretical result is verified empirically on several examples. The proposed method does not require additional assumptions; only its implementation is different. It essentially consists of performing spike sorting and tuning estimation simultaneously rather than sequentially, as is currently done. We used an expectation-maximization maximum likelihood algorithm to implement the new spike sorter. We present the general form of this algorithm and provide a detailed implementable version under the assumptions that neurons are independent and spike according to Poisson processes. Finally, we uncover a systematic flaw of spike sorting based on waveform information only.

Neural plasticity and its initiating conditions in tinnitus.

PubMed

Roberts, L E

2018-03-01

Deafferentation caused by cochlear pathology (which can be hidden from the audiogram) activates forms of neural plasticity in auditory pathways, generating tinnitus and its associated conditions including hyperacusis. This article discusses tinnitus mechanisms and suggests how these mechanisms may relate to those involved in normal auditory information processing. Research findings from animal models of tinnitus and from electromagnetic imaging of tinnitus patients are reviewed which pertain to the role of deafferentation and neural plasticity in tinnitus and hyperacusis. Auditory neurons compensate for deafferentation by increasing their input/output functions (gain) at multiple levels of the auditory system. Forms of homeostatic plasticity are believed to be responsible for this neural change, which increases the spontaneous and driven activity of neurons in central auditory structures in animals expressing behavioral evidence of tinnitus. Another tinnitus correlate, increased neural synchrony among the affected neurons, is forged by spike-timing-dependent neural plasticity in auditory pathways. Slow oscillations generated by bursting thalamic neurons verified in tinnitus animals appear to modulate neural plasticity in the cortex, integrating tinnitus neural activity with information in brain regions supporting memory, emotion, and consciousness which exhibit increased metabolic activity in tinnitus patients. The latter process may be induced by transient auditory events in normal processing but it persists in tinnitus, driven by phantom signals from the auditory pathway. Several tinnitus therapies attempt to suppress tinnitus through plasticity, but repeated sessions will likely be needed to prevent tinnitus activity from returning owing to deafferentation as its initiating condition.

Static and dynamic views of visual cortical organization.

PubMed

Casagrande, Vivien A; Xu, Xiangmin; Sáry, Gyula

2002-01-01

Without the aid of modern techniques Cajal speculated that cells in the visual cortex were connected in circuits. From Cajal's time until fairly recently, the flow of information within the cells and circuits of visual cortex has been described as progressing from input to output, from sensation to action. In this chapter we argue that a paradigm shift in our concept of the visual cortical neuron is under way. The most important change in our view concerns the neuron's functional role. Visual cortical neurons do not have static functional signatures but instead function dynamically depending on the ongoing activity of the networks to which they belong. These networks are not merely top-down or bottom-up unidirectional transmission lines, but rather represent machinery that uses recurrent information and is dynamic and highly adaptable. With the advancement of technology for analyzing the conversations of multiple neurons at many levels in the visual system and higher resolution imaging, we predict that the paradigm shift will progress to the point where neurons are no longer viewed as independent processing units but as members of subsets of networks where their role is mapped in space-time coordinates in relationship to the other neuronal members. This view moves us far from Cajal's original views of the neuron. Nevertheless, we believe that understanding the basic morphology and wiring of networks will continue to contribute to our overall understanding of the visual cortex.

Polarization-sensitive descending neurons in the locust: connecting the brain to thoracic ganglia.

PubMed

Träger, Ulrike; Homberg, Uwe

2011-02-09

Many animal species, in particular insects, exploit the E-vector pattern of the blue sky for sun compass navigation. Like other insects, locusts detect dorsal polarized light via photoreceptors in a specialized dorsal rim area of the compound eye. Polarized light information is transmitted through several processing stages to the central complex, a brain area involved in the control of goal-directed orientation behavior. To investigate how polarized light information is transmitted to thoracic motor circuits, we studied the responses of locust descending neurons to polarized light. Three sets of polarization-sensitive descending neurons were characterized through intracellular recordings from axonal fibers in the neck connectives combined with single-cell dye injections. Two descending neurons from the brain, one with ipsilaterally and the second with contralaterally descending axon, are likely to bridge the gap between polarization-sensitive neurons in the brain and thoracic motor centers. In both neurons, E-vector tuning changed linearly with daytime, suggesting that they signal time-compensated spatial directions, an important prerequisite for navigation using celestial signals. The third type connects the suboesophageal ganglion with the prothoracic ganglion. It showed no evidence for time compensation in E-vector tuning and might play a role in flight stabilization and control of head movements.

Active dendrites: colorful wings of the mysterious butterflies.

PubMed

Johnston, Daniel; Narayanan, Rishikesh

2008-06-01

Santiago Ramón y Cajal had referred to neurons as the 'mysterious butterflies of the soul.' Wings of these butterflies--their dendrites--were traditionally considered as passive integrators of synaptic information. Owing to a growing body of experimental evidence, it is now widely accepted that these wings are colorful, endowed with a plethora of active conductances, with each family of these butterflies made of distinct hues and shades. Furthermore, rapidly evolving recent literature also provides direct and indirect demonstrations for activity-dependent plasticity of these active conductances, pointing toward chameleonic adaptability in these hues. These experimental findings firmly establish the immense computational power of a single neuron, and thus constitute a turning point toward the understanding of various aspects of neuronal information processing. In this brief historical perspective, we track important milestones in the chameleonic transmogrification of these mysterious butterflies.

Reinforcement Learning of Two-Joint Virtual Arm Reaching in a Computer Model of Sensorimotor Cortex

PubMed Central

Neymotin, Samuel A.; Chadderdon, George L.; Kerr, Cliff C.; Francis, Joseph T.; Lytton, William W.

2014-01-01

Neocortical mechanisms of learning sensorimotor control involve a complex series of interactions at multiple levels, from synaptic mechanisms to cellular dynamics to network connectomics. We developed a model of sensory and motor neocortex consisting of 704 spiking model neurons. Sensory and motor populations included excitatory cells and two types of interneurons. Neurons were interconnected with AMPA/NMDA and GABAA synapses. We trained our model using spike-timing-dependent reinforcement learning to control a two-joint virtual arm to reach to a fixed target. For each of 125 trained networks, we used 200 training sessions, each involving 15 s reaches to the target from 16 starting positions. Learning altered network dynamics, with enhancements to neuronal synchrony and behaviorally relevant information flow between neurons. After learning, networks demonstrated retention of behaviorally relevant memories by using proprioceptive information to perform reach-to-target from multiple starting positions. Networks dynamically controlled which joint rotations to use to reach a target, depending on current arm position. Learning-dependent network reorganization was evident in both sensory and motor populations: learned synaptic weights showed target-specific patterning optimized for particular reach movements. Our model embodies an integrative hypothesis of sensorimotor cortical learning that could be used to interpret future electrophysiological data recorded in vivo from sensorimotor learning experiments. We used our model to make the following predictions: learning enhances synchrony in neuronal populations and behaviorally relevant information flow across neuronal populations, enhanced sensory processing aids task-relevant motor performance and the relative ease of a particular movement in vivo depends on the amount of sensory information required to complete the movement. PMID:24047323

Fast Coding of Orientation in Primary Visual Cortex

PubMed Central

Shriki, Oren; Kohn, Adam; Shamir, Maoz

2012-01-01

Understanding how populations of neurons encode sensory information is a major goal of systems neuroscience. Attempts to answer this question have focused on responses measured over several hundred milliseconds, a duration much longer than that frequently used by animals to make decisions about the environment. How reliably sensory information is encoded on briefer time scales, and how best to extract this information, is unknown. Although it has been proposed that neuronal response latency provides a major cue for fast decisions in the visual system, this hypothesis has not been tested systematically and in a quantitative manner. Here we use a simple ‘race to threshold’ readout mechanism to quantify the information content of spike time latency of primary visual (V1) cortical cells to stimulus orientation. We find that many V1 cells show pronounced tuning of their spike latency to stimulus orientation and that almost as much information can be extracted from spike latencies as from firing rates measured over much longer durations. To extract this information, stimulus onset must be estimated accurately. We show that the responses of cells with weak tuning of spike latency can provide a reliable onset detector. We find that spike latency information can be pooled from a large neuronal population, provided that the decision threshold is scaled linearly with the population size, yielding a processing time of the order of a few tens of milliseconds. Our results provide a novel mechanism for extracting information from neuronal populations over the very brief time scales in which behavioral judgments must sometimes be made. PMID:22719237

Excitatory signal flow and connectivity in a cortical column: focus on barrel cortex.

PubMed

Lübke, Joachim; Feldmeyer, Dirk

2007-07-01

A basic feature of the neocortex is its organization in functional, vertically oriented columns, recurring modules of signal processing and a system of transcolumnar long-range horizontal connections. These columns, together with their network of neurons, present in all sensory cortices, are the cellular substrate for sensory perception in the brain. Cortical columns contain thousands of neurons and span all cortical layers. They receive input from other cortical areas and subcortical brain regions and in turn their neurons provide output to various areas of the brain. The modular concept presumes that the neuronal network in a cortical column performs basic signal transformations, which are then integrated with the activity in other networks and more extended brain areas. To understand how sensory signals from the periphery are transformed into electrical activity in the neocortex it is essential to elucidate the spatial-temporal dynamics of cortical signal processing and the underlying neuronal 'microcircuits'. In the last decade the 'barrel' field in the rodent somatosensory cortex, which processes sensory information arriving from the mysticial vibrissae, has become a quite attractive model system because here the columnar structure is clearly visible. In the neocortex and in particular the barrel cortex, numerous neuronal connections within or between cortical layers have been studied both at the functional and structural level. Besides similarities, clear differences with respect to both physiology and morphology of synaptic transmission and connectivity were found. It is therefore necessary to investigate each neuronal connection individually, in order to develop a realistic model of neuronal connectivity and organization of a cortical column. This review attempts to summarize recent advances in the study of individual microcircuits and their functional relevance within the framework of a cortical column, with emphasis on excitatory signal flow.

Developmental Experience Alters Information Coding in Auditory Midbrain and Forebrain Neurons

PubMed Central

Woolley, Sarah M. N.; Hauber, Mark E.; Theunissen, Frederic E.

2010-01-01

In songbirds, species identity and developmental experience shape vocal behavior and behavioral responses to vocalizations. The interaction of species identity and developmental experience may also shape the coding properties of sensory neurons. We tested whether responses of auditory midbrain and forebrain neurons to songs differed between species and between groups of conspecific birds with different developmental exposure to song. We also compared responses of individual neurons to conspecific and heterospecific songs. Zebra and Bengalese finches that were raised and tutored by conspecific birds, and zebra finches that were cross-tutored by Bengalese finches were studied. Single-unit responses to zebra and Bengalese finch songs were recorded and analyzed by calculating mutual information, response reliability, mean spike rate, fluctuations in time-varying spike rate, distributions of time-varying spike rates, and neural discrimination of individual songs. Mutual information quantifies a response’s capacity to encode information about a stimulus. In midbrain and forebrain neurons, mutual information was significantly higher in normal zebra finch neurons than in Bengalese finch and cross-tutored zebra finch neurons, but not between Bengalese finch and cross-tutored zebra finch neurons. Information rate differences were largely due to spike rate differences. Mutual information did not differ between responses to conspecific and heterospecific songs. Therefore, neurons from normal zebra finches encoded more information about songs than did neurons from other birds, but conspecific and heterospecific songs were encoded equally. Neural discrimination of songs and mutual information were highly correlated. Results demonstrate that developmental exposure to vocalizations shapes the information coding properties of songbird auditory neurons. PMID:20039264

Prior activity of olfactory receptor neurons is required for proper sensory processing and behavior in Drosophila larvae.

PubMed

Utashiro, Nao; Williams, Claire R; Parrish, Jay Z; Emoto, Kazuo

2018-06-05

Animal responses to their environment rely on activation of sensory neurons by external stimuli. In many sensory systems, however, neurons display basal activity prior to the external stimuli. This prior activity is thought to modulate neural functions, yet its impact on animal behavior remains elusive. Here, we reveal a potential role for prior activity in olfactory receptor neurons (ORNs) in shaping larval olfactory behavior. We show that prior activity in larval ORNs is mediated by the olfactory receptor complex (OR complex). Mutations of Orco, an odorant co-receptor required for OR complex function, cause reduced attractive behavior in response to optogenetic activation of ORNs. Calcium imaging reveals that Orco mutant ORNs fully respond to optogenetic stimulation but exhibit altered temporal patterns of neural responses. These findings together suggest a critical role for prior activity in information processing upon ORN activation in Drosophila larvae, which in turn contributes to olfactory behavior control.

SNAP-25 requirement for dendritic growth of hippocampal neurons.

PubMed

Grosse, G; Grosse, J; Tapp, R; Kuchinke, J; Gorsleben, M; Fetter, I; Höhne-Zell, B; Gratzl, M; Bergmann, M

1999-06-01

Structure and dimension of the dendritic arbor are important determinants of information processing by the nerve cell, but mechanisms and molecules involved in dendritic growth are essentially unknown. We investigated early mechanisms of dendritic growth using mouse fetal hippocampal neurons in primary culture, which form processes during the first week in vitro. We detected a key component of regulated exocytosis, SNAP-25 (synaptosomal associated protein of 25 kDa), in axons and axonal terminals as well as in dendrites identified by the occurrence of the dendritic markers transferrin receptor and MAP2. Selective inactivation of SNAP-25 by botulinum neurotoxin A (BoNTA) resulted in inhibition of axonal growth and of vesicle recycling in axonal terminals. In addition, dendritic growth of hippocampal pyramidal and granule neurons was significantly inhibited by BoNTA. In contrast, cleavage of synaptobrevin by tetanus toxin had an effect on neither axonal nor dendritic growth. Our observations indicate that SNAP-25, but not synaptobrevin, is involved in constitutive axonal growth and dendrite formation by hippocampal neurons.

Neuroregulatory and neuroendocrine GnRH pathways in the hypothalamus and forebrain of the baboon.

PubMed

Marshall, P E; Goldsmith, P C

1980-07-14

The distribution of neurons containing gonadotropin-releasing hormone (GnRH) in the baboon hypothalamus and forebrain was studied immunocytochemically by light and electron microscopy. GnRH was present in the perikarya, axonal and dendritic processes of immunoreactive neurons. Three populations of GnRH neurons could be distinguished. Most of the GnRH neurons which are assumed to directly influence the anterior pituitary were in the medial basal hypothalamus. Other cells that projected to the median eminence were found scattered throughout the hypothalamus. A second, larger population of neurons apparently was not involved with control of the anterior pituitary. These neurons were generally found within afferent and efferent pathways of the hypothalamus and forebrain, and may receive external information affecting reproduction. A few neurons projecting to the median eminence were also observed sending collaterals to other brain areas. Thus, in addition to their neuroendocrine role, these cells possibly have neuroregulatory functions. The inference is made that these bifunctional neurons, together with the widely observed GnRH-GnRH cellular interactions may help to synchronize ovulation and sexual behavior.

Axonal Conduction Delays, Brain State, and Corticogeniculate Communication

PubMed Central

2017-01-01

Thalamocortical conduction times are short, but layer 6 corticothalamic axons display an enormous range of conduction times, some exceeding 40–50 ms. Here, we investigate (1) how axonal conduction times of corticogeniculate (CG) neurons are related to the visual information conveyed to the thalamus, and (2) how alert versus nonalert awake brain states affect visual processing across the spectrum of CG conduction times. In awake female Dutch-Belted rabbits, we found 58% of CG neurons to be visually responsive, and 42% to be unresponsive. All responsive CG neurons had simple, orientation-selective receptive fields, and generated sustained responses to stationary stimuli. CG axonal conduction times were strongly related to modulated firing rates (F1 values) generated by drifting grating stimuli, and their associated interspike interval distributions, suggesting a continuum of visual responsiveness spanning the spectrum of axonal conduction times. CG conduction times were also significantly related to visual response latency, contrast sensitivity (C-50 values), directional selectivity, and optimal stimulus velocity. Increasing alertness did not cause visually unresponsive CG neurons to become responsive and did not change the response linearity (F1/F0 ratios) of visually responsive CG neurons. However, for visually responsive CG neurons, increased alertness nearly doubled the modulated response amplitude to optimal visual stimulation (F1 values), significantly shortened response latency, and dramatically increased response reliability. These effects of alertness were uniform across the broad spectrum of CG axonal conduction times. SIGNIFICANCE STATEMENT Corticothalamic neurons of layer 6 send a dense feedback projection to thalamic nuclei that provide input to sensory neocortex. While sensory information reaches the cortex after brief thalamocortical axonal delays, corticothalamic axons can exhibit conduction delays of <2 ms to 40–50 ms. Here, in the corticogeniculate visual system of awake rabbits, we investigate the functional significance of this axonal diversity, and the effects of shifting alert/nonalert brain states on corticogeniculate processing. We show that axonal conduction times are strongly related to multiple visual response properties, suggesting a continuum of visual responsiveness spanning the spectrum of corticogeniculate axonal conduction times. We also show that transitions between awake brain states powerfully affect corticogeniculate processing, in some ways more strongly than in layer 4. PMID:28559382

Neural correlates of motor learning in the vestibulo-ocular reflex: dynamic regulation of multimodal integration in the macaque vestibular system

PubMed Central

Sadeghi, Soroush G.; Minor, Lloyd B.; Cullen, Kathleen E.

2010-01-01

Motor learning is required for the reacquisition of skills that have been compromised as a result of brain lesion or disease, as well as for the acquisition of new skills. Behaviors with well-characterized anatomy and physiology are required to yield significant insight into changes that occur in the brain during motor learning. The vestibulo-ocular-reflex (VOR) is well suited to establish connections between neurons, neural circuits, and motor performance during learning. Here we examined the linkage between neuronal and behavioural VOR responses in alert behaving monkeys (macaca mulatta) during the impressive recovery that occurs after unilateral vestibular loss. We show, for the first time, that motor learning is characterized by the dynamic reweighting of inputs from different modalities (i.e., vestibular versus extra-vestibular) at the level of the single neurons which constitute the first central stage of vestibular processing. Specifically, two types of information, which did not influence neuronal responses prior to the lesion, had an important role during compensation. First, unmasked neck proprioceptive inputs played a critical role in the early stages of this process demonstrated by faster and more substantial recovery of vestibular responses in proprioceptive sensitive neurons. Second, neuronal and VOR responses were significantly enhanced during active relative to passive head motion later in the compensation process (>3 weeks). Taken together, our findings provide evidence linking the dynamic regulation of multimodal integration at the level of single neurons and behavioural recovery, suggesting a role for homeostatic mechanisms in VOR motor learning. PMID:20668199

Information and Efficiency in the Nervous System—A Synthesis

PubMed Central

Sengupta, Biswa; Stemmler, Martin B.; Friston, Karl J.

2013-01-01

In systems biology, questions concerning the molecular and cellular makeup of an organism are of utmost importance, especially when trying to understand how unreliable components—like genetic circuits, biochemical cascades, and ion channels, among others—enable reliable and adaptive behaviour. The repertoire and speed of biological computations are limited by thermodynamic or metabolic constraints: an example can be found in neurons, where fluctuations in biophysical states limit the information they can encode—with almost 20–60% of the total energy allocated for the brain used for signalling purposes, either via action potentials or by synaptic transmission. Here, we consider the imperatives for neurons to optimise computational and metabolic efficiency, wherein benefits and costs trade-off against each other in the context of self-organised and adaptive behaviour. In particular, we try to link information theoretic (variational) and thermodynamic (Helmholtz) free-energy formulations of neuronal processing and show how they are related in a fundamental way through a complexity minimisation lemma. PMID:23935475

Basic Investigations of Dynamic Travel Time Estimation Model for Traffic Signals Control Using Information from Optical Beacons

NASA Astrophysics Data System (ADS)

Okutani, Iwao; Mitsui, Tatsuro; Nakada, Yusuke

In this paper put forward are neuron-type models, i.e., neural network model, wavelet neuron model and three layered wavelet neuron model(WV3), for estimating traveling time between signalized intersections in order to facilitate adaptive setting of traffic signal parameters such as green time and offset. Model validation tests using simulated data reveal that compared to other models, WV3 model works very fast in learning process and can produce more accurate estimates of travel time. Also, it is exhibited that up-link information obtainable from optical beacons, i.e., travel time observed during the former cycle time in this case, makes a crucial input variable to the models in that there isn't any substantial difference between the change of estimated and simulated travel time with the change of green time or offset when up-link information is employed as input while there appears big discrepancy between them when not employed.

A 4-fJ/Spike Artificial Neuron in 65 nm CMOS Technology

PubMed Central

Sourikopoulos, Ilias; Hedayat, Sara; Loyez, Christophe; Danneville, François; Hoel, Virginie; Mercier, Eric; Cappy, Alain

2017-01-01

As Moore's law reaches its end, traditional computing technology based on the Von Neumann architecture is facing fundamental limits. Among them is poor energy efficiency. This situation motivates the investigation of different processing information paradigms, such as the use of spiking neural networks (SNNs), which also introduce cognitive characteristics. As applications at very high scale are addressed, the energy dissipation needs to be minimized. This effort starts from the neuron cell. In this context, this paper presents the design of an original artificial neuron, in standard 65 nm CMOS technology with optimized energy efficiency. The neuron circuit response is designed as an approximation of the Morris-Lecar theoretical model. In order to implement the non-linear gating variables, which control the ionic channel currents, transistors operating in deep subthreshold are employed. Two different circuit variants describing the neuron model equations have been developed. The first one features spike characteristics, which correlate well with a biological neuron model. The second one is a simplification of the first, designed to exhibit higher spiking frequencies, targeting large scale bio-inspired information processing applications. The most important feature of the fabricated circuits is the energy efficiency of a few femtojoules per spike, which improves prior state-of-the-art by two to three orders of magnitude. This performance is achieved by minimizing two key parameters: the supply voltage and the related membrane capacitance. Meanwhile, the obtained standby power at a resting output does not exceed tens of picowatts. The two variants were sized to 200 and 35 μm2 with the latter reaching a spiking output frequency of 26 kHz. This performance level could address various contexts, such as highly integrated neuro-processors for robotics, neuroscience or medical applications. PMID:28360831

Micro-level dynamics of the online information propagation: A user behavior model based on noisy spiking neurons.

PubMed

Lymperopoulos, Ilias N; Ioannou, George D

2016-10-01

We develop and validate a model of the micro-level dynamics underlying the formation of macro-level information propagation patterns in online social networks. In particular, we address the dynamics at the level of the mechanism regulating a user's participation in an online information propagation process. We demonstrate that this mechanism can be realistically described by the dynamics of noisy spiking neurons driven by endogenous and exogenous, deterministic and stochastic stimuli representing the influence modulating one's intention to be an information spreader. Depending on the dynamically changing influence characteristics, time-varying propagation patterns emerge reflecting the temporal structure, strength, and signal-to-noise ratio characteristics of the stimulation driving the online users' information sharing activity. The proposed model constitutes an overarching, novel, and flexible approach to the modeling of the micro-level mechanisms whereby information propagates in online social networks. As such, it can be used for a comprehensive understanding of the online transmission of information, a process integral to the sociocultural evolution of modern societies. The proposed model is highly adaptable and suitable for the study of the propagation patterns of behavior, opinions, and innovations among others. Copyright © 2016 Elsevier Ltd. All rights reserved.

Training of Attentional Filtering, but Not of Memory Storage, Enhances Working Memory Efficiency by Strengthening the Neuronal Gatekeeper Network.

PubMed

Schmicker, Marlen; Schwefel, Melanie; Vellage, Anne-Katrin; Müller, Notger G

2016-04-01

Memory training (MT) in older adults with memory deficits often leads to frustration and, therefore, is usually not recommended. Here, we pursued an alternative approach and looked for transfer effects of 1-week attentional filter training (FT) on working memory performance and its neuronal correlates in young healthy humans. The FT effects were compared with pure MT, which lacked the necessity to filter out irrelevant information. Before and after training, all participants performed an fMRI experiment that included a combined task in which stimuli had to be both filtered based on color and stored in memory. We found that training induced processing changes by biasing either filtering or storage. FT induced larger transfer effects on the untrained cognitive function than MT. FT increased neuronal activity in frontal parts of the neuronal gatekeeper network, which is proposed to hinder irrelevant information from being unnecessarily stored in memory. MT decreased neuronal activity in the BG part of the gatekeeper network but enhanced activity in the parietal storage node. We take these findings as evidence that FT renders working memory more efficient by strengthening the BG-prefrontal gatekeeper network. MT, on the other hand, simply stimulates storage of any kind of information. These findings illustrate a tight connection between working memory and attention, and they may open up new avenues for ameliorating memory deficits in patients with cognitive impairments.

The central amygdala controls learning in the lateral amygdala

PubMed Central

Yu, Kai; Ahrens, Sandra; Zhang, Xian; Schiff, Hillary; Ramakrishnan, Charu; Fenno, Lief; Deisseroth, Karl; Zhao, Fei; Luo, Min-Hua; Gong, Ling; He, Miao; Zhou, Pengcheng; Paninski, Liam; Li, Bo

2018-01-01

Experience-driven synaptic plasticity in the lateral amygdala (LA) is thought to underlie the formation of associations between sensory stimuli and an ensuing threat. However, how the central amygdala (CeA) participates in such learning process remains unclear. Here we show that PKC-δ-expressing CeA neurons are essential for the synaptic plasticity underlying learning in the LA, as they convey information about unconditioned stimulus to LA neurons during fear conditioning. PMID:29184202

Contextual signals in visual cortex.

PubMed

Khan, Adil G; Hofer, Sonja B

2018-06-05

Vision is an active process. What we perceive strongly depends on our actions, intentions and expectations. During visual processing, these internal signals therefore need to be integrated with the visual information from the retina. The mechanisms of how this is achieved by the visual system are still poorly understood. Advances in recording and manipulating neuronal activity in specific cell types and axonal projections together with tools for circuit tracing are beginning to shed light on the neuronal circuit mechanisms of how internal, contextual signals shape sensory representations. Here we review recent work, primarily in mice, that has advanced our understanding of these processes, focusing on contextual signals related to locomotion, behavioural relevance and predictions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Role of Ongoing, Intrinsic Activity of Neuronal Populations for Quantitative Neuroimaging of Functional Magnetic Resonance Imaging–Based Networks

PubMed Central

Herman, Peter; Sanganahalli, Basavaraju G.; Coman, Daniel; Blumenfeld, Hal; Rothman, Douglas L.

2011-01-01

Abstract A primary objective in neuroscience is to determine how neuronal populations process information within networks. In humans and animal models, functional magnetic resonance imaging (fMRI) is gaining increasing popularity for network mapping. Although neuroimaging with fMRI—conducted with or without tasks—is actively discovering new brain networks, current fMRI data analysis schemes disregard the importance of the total neuronal activity in a region. In task fMRI experiments, the baseline is differenced away to disclose areas of small evoked changes in the blood oxygenation level-dependent (BOLD) signal. In resting-state fMRI experiments, the spotlight is on regions revealed by correlations of tiny fluctuations in the baseline (or spontaneous) BOLD signal. Interpretation of fMRI-based networks is obscured further, because the BOLD signal indirectly reflects neuronal activity, and difference/correlation maps are thresholded. Since the small changes of BOLD signal typically observed in cognitive fMRI experiments represent a minimal fraction of the total energy/activity in a given area, the relevance of fMRI-based networks is uncertain, because the majority of neuronal energy/activity is ignored. Thus, another alternative for quantitative neuroimaging of fMRI-based networks is a perspective in which the activity of a neuronal population is accounted for by the demanded oxidative energy (CMRO2). In this article, we argue that network mapping can be improved by including neuronal energy/activity of both the information about baseline and small differences/fluctuations of BOLD signal. Thus, total energy/activity information can be obtained through use of calibrated fMRI to quantify differences of ΔCMRO2 and through resting-state positron emission tomography/magnetic resonance spectroscopy measurements for average CMRO2. PMID:22433047

Double-Labeled Metabolic Maps of Memory.

ERIC Educational Resources Information Center

John, E. R.; And Others

1986-01-01

Reviews a study which sought to obtain a quantitative metabolic map of the neurons mediating a specific memory. Research results support notions of cooperative processes in which nonrandom behavior of high ensembles of neural elements mediates the integration and processing of information and the retrieval of memory. (ML)

Establishment of high reciprocal connectivity between clonal cortical neurons is regulated by the Dnmt3b DNA methyltransferase and clustered protocadherins.

PubMed

Tarusawa, Etsuko; Sanbo, Makoto; Okayama, Atsushi; Miyashita, Toshio; Kitsukawa, Takashi; Hirayama, Teruyoshi; Hirabayashi, Takahiro; Hasegawa, Sonoko; Kaneko, Ryosuke; Toyoda, Shunsuke; Kobayashi, Toshihiro; Kato-Itoh, Megumi; Nakauchi, Hiromitsu; Hirabayashi, Masumi; Yagi, Takeshi; Yoshimura, Yumiko

2016-12-02

The specificity of synaptic connections is fundamental for proper neural circuit function. Specific neuronal connections that underlie information processing in the sensory cortex are initially established without sensory experiences to a considerable extent, and then the connections are individually refined through sensory experiences. Excitatory neurons arising from the same single progenitor cell are preferentially connected in the postnatal cortex, suggesting that cell lineage contributes to the initial wiring of neurons. However, the postnatal developmental process of lineage-dependent connection specificity is not known, nor how clonal neurons, which are derived from the same neural stem cell, are stamped with the identity of their common neural stem cell and guided to form synaptic connections. We show that cortical excitatory neurons that arise from the same neural stem cell and reside within the same layer preferentially establish reciprocal synaptic connections in the mouse barrel cortex. We observed a transient increase in synaptic connections between clonal but not nonclonal neuron pairs during postnatal development, followed by selective stabilization of the reciprocal connections between clonal neuron pairs. Furthermore, we demonstrate that selective stabilization of the reciprocal connections between clonal neuron pairs is impaired by the deficiency of DNA methyltransferase 3b (Dnmt3b), which determines DNA-methylation patterns of genes in stem cells during early corticogenesis. Dnmt3b regulates the postnatal expression of clustered protocadherin (cPcdh) isoforms, a family of adhesion molecules. We found that cPcdh deficiency in clonal neuron pairs impairs the whole process of the formation and stabilization of connections to establish lineage-specific connection reciprocity. Our results demonstrate that local, reciprocal neural connections are selectively formed and retained between clonal neurons in layer 4 of the barrel cortex during postnatal development, and that Dnmt3b and cPcdhs are required for the establishment of lineage-specific reciprocal connections. These findings indicate that lineage-specific connection reciprocity is predetermined by Dnmt3b during embryonic development, and that the cPcdhs contribute to postnatal cortical neuron identification to guide lineage-dependent synaptic connections in the neocortex.

Noradrenaline and acetylcholine responsiveness of glucose-monitoring and glucose-insensitive neurons in the mediodorsal prefrontal cortex.

PubMed

Nagy, Bernadett; Szabó, István; Csetényi, Bettina; Hormay, Edina; Papp, Szilárd; Keresztes, Dóra; Karádi, Zoltán

2014-01-16

The mediodorsal prefrontal cortex (mdPFC), as part of the forebrain glucose-monitoring (GM) system, plays important role in several regulatory processes to control the internal state of the organism and to initiate behavioral outputs accordingly. Little is known, however, about the neurochemical sensitivity of neurons located in this area. Substantial evidence indicates that the locus ceruleus - noradrenaline (NA) projection system and the nucleus basalis magnocellularis - cholinergic projection system regulate behavioral state and state dependent processing of sensory information, various cognitive functions already associated with the mdPFC. The main goal of the present study was to examine noradrenergic and cholinergic responsiveness of glucose-monitoring and glucose-insensitive (GIS) neurons in the mediodorsal prefrontal cortex. One fifth of the neurons tested changed in firing rate to microelectrophoretically applied NA. Responsiveness of the GM cells to this catecholamine proved to be significantly higher than that of the GIS units. Microiontophoretic application of acetylcholine (Ach) resulted in activity changes (predominantly facilitation) of more than 40% of the mdPFC neurons. Proportion of Ach sensitive units among the GM and the GIS neurons was found to be similar. The glucose-monitoring neurons of the mdPFC and their distinct NA and remarkable Ach sensitivity are suggested to be of particular significance in prefrontal control of adaptive behaviors. © 2013 Published by Elsevier B.V.

Octopus Cells in the Posteroventral Cochlear Nucleus Provide the Main Excitatory Input to the Superior Paraolivary Nucleus

PubMed Central

Felix II, Richard A.; Gourévitch, Boris; Gómez-Álvarez, Marcelo; Leijon, Sara C. M.; Saldaña, Enrique; Magnusson, Anna K.

2017-01-01

Auditory streaming enables perception and interpretation of complex acoustic environments that contain competing sound sources. At early stages of central processing, sounds are segregated into separate streams representing attributes that later merge into acoustic objects. Streaming of temporal cues is critical for perceiving vocal communication, such as human speech, but our understanding of circuits that underlie this process is lacking, particularly at subcortical levels. The superior paraolivary nucleus (SPON), a prominent group of inhibitory neurons in the mammalian brainstem, has been implicated in processing temporal information needed for the segmentation of ongoing complex sounds into discrete events. The SPON requires temporally precise and robust excitatory input(s) to convey information about the steep rise in sound amplitude that marks the onset of voiced sound elements. Unfortunately, the sources of excitation to the SPON and the impact of these inputs on the behavior of SPON neurons have yet to be resolved. Using anatomical tract tracing and immunohistochemistry, we identified octopus cells in the contralateral cochlear nucleus (CN) as the primary source of excitatory input to the SPON. Cluster analysis of miniature excitatory events also indicated that the majority of SPON neurons receive one type of excitatory input. Precise octopus cell-driven onset spiking coupled with transient offset spiking make SPON responses well-suited to signal transitions in sound energy contained in vocalizations. Targets of octopus cell projections, including the SPON, are strongly implicated in the processing of temporal sound features, which suggests a common pathway that conveys information critical for perception of complex natural sounds. PMID:28620283

Spiking Neurons for Analysis of Patterns

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance

2008-01-01

Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological neurons). These features enable the neurons to adapt their responses to high-rate inputs from sensors, and to adapt their firing thresholds to mitigate noise or effects of potential sensor failure. The mathematical derivation of the SVM starts from a prior model, known in the art as the point soma model, which captures all of the salient properties of neuronal response while keeping the computational cost low. The point-soma latency time is modified to be an exponentially decaying function of the strength of the applied potential. Choosing computational efficiency over biological fidelity, the dendrites surrounding a neuron are represented by simplified compartmental submodels and there are no dendritic spines. Updates to the dendritic potential, calcium-ion concentrations and conductances, and potassium-ion conductances are done by use of equations similar to those of the point soma. Diffusion processes in dendrites are modeled by averaging among nearest-neighbor compartments. Inputs to each of the dendritic compartments come from sensors. Alternatively or in addition, when an affected neuron is part of a pool, inputs can come from other spiking neurons. At present, SVM neural networks are implemented by computational simulation, using algorithms that encode the SVM and its submodels. However, it should be possible to implement these neural networks in hardware: The differential equations for the dendritic and cellular processes in the SVM model of spiking neurons map to equivalent circuits that can be implemented directly in analog very-large-scale integrated (VLSI) circuits.

Multiplicative and additive modulation of neuronal tuning with population activity affects encoded information

PubMed Central

Arandia-Romero, Iñigo; Tanabe, Seiji; Drugowitsch, Jan; Kohn, Adam; Moreno-Bote, Rubén

2016-01-01

Numerous studies have shown that neuronal responses are modulated by stimulus properties, and also by the state of the local network. However, little is known about how activity fluctuations of neuronal populations modulate the sensory tuning of cells and affect their encoded information. We found that fluctuations in ongoing and stimulus-evoked population activity in primate visual cortex modulate the tuning of neurons in a multiplicative and additive manner. While distributed on a continuum, neurons with stronger multiplicative effects tended to have less additive modulation, and vice versa. The information encoded by multiplicatively-modulated neurons increased with greater population activity, while that of additively-modulated neurons decreased. These effects offset each other, so that population activity had little effect on total information. Our results thus suggest that intrinsic activity fluctuations may act as a `traffic light' that determines which subset of neurons are most informative. PMID:26924437

Hyperconnectivity and slow synapses during early development of medial prefrontal cortex in a mouse model for mental retardation and autism.

PubMed

Testa-Silva, Guilherme; Loebel, Alex; Giugliano, Michele; de Kock, Christiaan P J; Mansvelder, Huibert D; Meredith, Rhiannon M

2012-06-01

Neuronal theories of neurodevelopmental disorders (NDDs) of autism and mental retardation propose that abnormal connectivity underlies deficits in attentional processing. We tested this theory by studying unitary synaptic connections between layer 5 pyramidal neurons within medial prefrontal cortex (mPFC) networks in the Fmr1-KO mouse model for mental retardation and autism. In line with predictions from neurocognitive theory, we found that neighboring pyramidal neurons were hyperconnected during a critical period in early mPFC development. Surprisingly, excitatory synaptic connections between Fmr1-KO pyramidal neurons were significantly slower and failed to recover from short-term depression as quickly as wild type (WT) synapses. By 4-5 weeks of mPFC development, connectivity rates were identical for both KO and WT pyramidal neurons and synapse dynamics changed from depressing to facilitating responses with similar properties in both groups. We propose that the early alteration in connectivity and synaptic recovery are tightly linked: using a network model, we show that slower synapses are essential to counterbalance hyperconnectivity in order to maintain a dynamic range of excitatory activity. However, the slow synaptic time constants induce decreased responsiveness to low-frequency stimulation, which may explain deficits in integration and early information processing in attentional neuronal networks in NDDs.

Hyperconnectivity and Slow Synapses during Early Development of Medial Prefrontal Cortex in a Mouse Model for Mental Retardation and Autism

PubMed Central

Testa-Silva, Guilherme; Loebel, Alex; Giugliano, Michele; de Kock, Christiaan P.J.; Mansvelder, Huibert D.; Meredith, Rhiannon M.

2013-01-01

Neuronal theories of neurodevelopmental disorders (NDDs) of autism and mental retardation propose that abnormal connectivity underlies deficits in attentional processing. We tested this theory by studying unitary synaptic connections between layer 5 pyramidal neurons within medial prefrontal cortex (mPFC) networks in the Fmr1-KO mouse model for mental retardation and autism. In line with predictions from neurocognitive theory, we found that neighboring pyramidal neurons were hyperconnected during a critical period in early mPFC development. Surprisingly, excitatory synaptic connections between Fmr1-KO pyramidal neurons were significantly slower and failed to recover from short-term depression as quickly as wild type (WT) synapses. By 4--5 weeks of mPFC development, connectivity rates were identical for both KO and WT pyramidal neurons and synapse dynamics changed from depressing to facilitating responses with similar properties in both groups. We propose that the early alteration in connectivity and synaptic recovery are tightly linked: using a network model, we show that slower synapses are essential to counterbalance hyperconnectivity in order to maintain a dynamic range of excitatory activity. However, the slow synaptic time constants induce decreased responsiveness to low-frequency stimulation, which may explain deficits in integration and early information processing in attentional neuronal networks in NDDs. PMID:21856714

Genetic control of adult neurogenesis: interplay of differentiation, proliferation and survival modulates new neurons function, and memory circuits

PubMed Central

Tirone, Felice; Farioli-Vecchioli, Stefano; Micheli, Laura; Ceccarelli, Manuela; Leonardi, Luca

2013-01-01

Within the hippocampal circuitry, the basic function of the dentate gyrus is to transform the memory input coming from the enthorinal cortex into sparse and categorized outputs to CA3, in this way separating related memory information. New neurons generated in the dentate gyrus during adulthood appear to facilitate this process, allowing a better separation between closely spaced memories (pattern separation). The evidence underlying this model has been gathered essentially by ablating the newly adult-generated neurons. This approach, however, does not allow monitoring of the integration of new neurons into memory circuits and is likely to set in motion compensatory circuits, possibly leading to an underestimation of the role of new neurons. Here we review the background of the basic function of the hippocampus and of the known properties of new adult-generated neurons. In this context, we analyze the cognitive performance in mouse models generated by us and others, with modified expression of the genes Btg2 (PC3/Tis21), Btg1, Pten, BMP4, etc., where new neurons underwent a change in their differentiation rate or a partial decrease of their proliferation or survival rate rather than ablation. The effects of these modifications are equal or greater than full ablation, suggesting that the architecture of circuits, as it unfolds from the interaction between existing and new neurons, can have a greater functional impact than the sheer number of new neurons. We propose a model which attempts to measure and correlate the set of cellular changes in the process of neurogenesis with the memory function. PMID:23734097

Whisker row deprivation affects the flow of sensory information through rat barrel cortex.

PubMed

Jacob, Vincent; Mitani, Akinori; Toyoizumi, Taro; Fox, Kevin

2017-01-01

Whisker trimming causes substantial reorganization of neuronal response properties in barrel cortex. However, little is known about experience-dependent rerouting of sensory processing following sensory deprivation. To address this, we performed in vivo intracellular recordings from layers 2/3 (L2/3), layer 4 (L4), layer 5 regular-spiking (L5RS), and L5 intrinsically bursting (L5IB) neurons and measured their multiwhisker receptive field at the level of spiking activity, membrane potential, and synaptic conductance before and after sensory deprivation. We used Chernoff information to quantify the "sensory information" contained in the firing patterns of cells in response to spared and deprived whisker stimulation. In the control condition, information for flanking-row and same-row whiskers decreased in the order L4, L2/3, L5IB, L5RS. However, after whisker-row deprivation, spared flanking-row whisker information was reordered to L4, L5RS, L5IB, L2/3. Sensory information from the trimmed whiskers was reduced and delayed in L2/3 and L5IB neurons, whereas sensory information from spared whiskers was increased and advanced in L4 and L5RS neurons. Sensory information from spared whiskers was increased in L5IB neurons without a latency change. L5RS cells exhibited the largest changes in sensory information content through an atypical plasticity combining a significant decrease in spontaneous activity and an increase in a short-latency excitatory conductance. Sensory cortical plasticity is usually quantified by changes in evoked firing rate. In this study we quantified plasticity by changes in sensory detection performance using Chernoff information and receiver operating characteristic analysis. We found that whisker deprivation causes a change in information flow within the cortical layers and that layer 5 regular-spiking cells, despite showing only a small potentiation of short-latency input, show the greatest increase in information content for the spared input partly by decreasing their spontaneous activity. Copyright © 2017 the American Physiological Society.

Short-term synaptic plasticity and heterogeneity in neural systems

NASA Astrophysics Data System (ADS)

Mejias, J. F.; Kappen, H. J.; Longtin, A.; Torres, J. J.

2013-01-01

We review some recent results on neural dynamics and information processing which arise when considering several biophysical factors of interest, in particular, short-term synaptic plasticity and neural heterogeneity. The inclusion of short-term synaptic plasticity leads to enhanced long-term memory capacities, a higher robustness of memory to noise, and irregularity in the duration of the so-called up cortical states. On the other hand, considering some level of neural heterogeneity in neuron models allows neural systems to optimize information transmission in rate coding and temporal coding, two strategies commonly used by neurons to codify information in many brain areas. In all these studies, analytical approximations can be made to explain the underlying dynamics of these neural systems.

Computing the Energy Cost of the Information Transmitted by Model Biological Neurons

NASA Astrophysics Data System (ADS)

Torrealdea, F. J.; Sarasola, C.; d'Anjou, A.; Moujahid, A.

2009-08-01

We assign an energy function to a Hindmarsh-Rose model of a neuron and use it to compute values of average energy consumption during its signalling activity. We also compute values of information entropy of an isolated neuron and of mutual information between two electrically coupled neurons. We find that for the isolated neuron the chaotic signaling regime is the one with the biggest ratio of information entropy to energy consumption. We also find that in the case of electrically coupled neurons there are values of the coupling strength at which the mutual information to energy consumption ratio is maximum, that is, that transmitting at that coupling conditions is energetically less expensive.

Mutual information against correlations in binary communication channels.

PubMed

Pregowska, Agnieszka; Szczepanski, Janusz; Wajnryb, Eligiusz

2015-05-19

Explaining how the brain processing is so fast remains an open problem (van Hemmen JL, Sejnowski T., 2004). Thus, the analysis of neural transmission (Shannon CE, Weaver W., 1963) processes basically focuses on searching for effective encoding and decoding schemes. According to the Shannon fundamental theorem, mutual information plays a crucial role in characterizing the efficiency of communication channels. It is well known that this efficiency is determined by the channel capacity that is already the maximal mutual information between input and output signals. On the other hand, intuitively speaking, when input and output signals are more correlated, the transmission should be more efficient. A natural question arises about the relation between mutual information and correlation. We analyze the relation between these quantities using the binary representation of signals, which is the most common approach taken in studying neuronal processes of the brain. We present binary communication channels for which mutual information and correlation coefficients behave differently both quantitatively and qualitatively. Despite this difference in behavior, we show that the noncorrelation of binary signals implies their independence, in contrast to the case for general types of signals. Our research shows that the mutual information cannot be replaced by sheer correlations. Our results indicate that neuronal encoding has more complicated nature which cannot be captured by straightforward correlations between input and output signals once the mutual information takes into account the structure and patterns of the signals.

Cochlea-inspired sensing node for compressive sensing

NASA Astrophysics Data System (ADS)

Peckens, Courtney A.; Lynch, Jerome P.

2013-04-01

While sensing technologies for structural monitoring applications have made significant advances over the last several decades, there is still room for improvement in terms of computational efficiency, as well as overall energy consumption. The biological nervous system can offer a potential solution to address these current deficiencies. The nervous system is capable of sensing and aggregating information about the external environment through very crude processing units known as neurons. Neurons effectively communicate in an extremely condensed format by encoding information into binary electrical spike trains, thereby reducing the amount of raw information sent throughout a neural network. Due to its unique signal processing capabilities, the mammalian cochlea and its interaction with the biological nervous system is of particular interest for devising compressive sensing strategies for dynamic engineered systems. The cochlea uses a novel method of place theory and frequency decomposition, thereby allowing for rapid signal processing within the nervous system. In this study, a low-power sensing node is proposed that draws inspiration from the mechanisms employed by the cochlea and the biological nervous system. As such, the sensor is able to perceive and transmit a compressed representation of the external stimulus with minimal distortion. Each sensor represents a basic building block, with function similar to the neuron, and can form a network with other sensors, thus enabling a system that can convey input stimulus in an extremely condensed format. The proposed sensor is validated through a structural monitoring application of a single degree of freedom structure excited by seismic ground motion.

Neural changes associated with appetite information processing in schizophrenic patients after 16 weeks of olanzapine treatment

PubMed Central

Stip, E; Lungu, O V; Anselmo, K; Letourneau, G; Mendrek, A; Stip, B; Lipp, O; Lalonde, P; Bentaleb, L A

2012-01-01

There is evidence that some atypical antipsychotics, including olanzapine, can produce unwanted metabolic side effects, weight gain and diabetes. However, neuronal correlates of change related to food information processing have not been investigated with these medications. We studied the effect of a pharmacological manipulation with an antipsychotic known to cause weight gain on metabolites, cognitive tasks and neural correlates related to food regulation. We used functional magnetic resonance imaging in conjunction with a task requiring visual processing of appetitive stimuli in schizophrenic patients and healthy controls before and after 16 weeks of antipsychotic medication with olanzapine. In patients, the psychological and neuronal changes associated following the treatment correlated with appetite control measures and metabolite levels in fasting blood samples. After 16 weeks of olanzapine treatment, the patients gained weight, increased their waist circumference, had fewer positive schizophrenia symptoms, a reduced ghrelin plasma concentration and an increased concentration of triglycerides, insulin and leptin. In premotor area, somatosensory cortices as well as bilaterally in the fusiform gyri, the olanzapine treatment increased the neural activity related to appetitive information in schizophrenic patients to similar levels relative to healthy individuals. However, a higher increase in sensitivity to appetitive stimuli after the treatment was observed in insular cortices, amygdala and cerebellum in schizophrenic patients as compared with healthy controls. Furthermore, these changes in neuronal activity correlated with changes in some metabolites and cognitive measurements related to appetite regulation. PMID:22714121

Regulation of neuronal communication by G protein-coupled receptors.

PubMed

Huang, Yunhong; Thathiah, Amantha

2015-06-22

Neuronal communication plays an essential role in the propagation of information in the brain and requires a precisely orchestrated connectivity between neurons. Synaptic transmission is the mechanism through which neurons communicate with each other. It is a strictly regulated process which involves membrane depolarization, the cellular exocytosis machinery, neurotransmitter release from synaptic vesicles into the synaptic cleft, and the interaction between ion channels, G protein-coupled receptors (GPCRs), and downstream effector molecules. The focus of this review is to explore the role of GPCRs and G protein-signaling in neurotransmission, to highlight the function of GPCRs, which are localized in both presynaptic and postsynaptic membrane terminals, in regulation of intrasynaptic and intersynaptic communication, and to discuss the involvement of astrocytic GPCRs in the regulation of neuronal communication. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Neuronal basis of covert spatial attention in the frontal eye field.

PubMed

Thompson, Kirk G; Biscoe, Keri L; Sato, Takashi R

2005-10-12

The influential "premotor theory of attention" proposes that developing oculomotor commands mediate covert visual spatial attention. A likely source of this attentional bias is the frontal eye field (FEF), an area of the frontal cortex involved in converting visual information into saccade commands. We investigated the link between FEF activity and covert spatial attention by recording from FEF visual and saccade-related neurons in monkeys performing covert visual search tasks without eye movements. Here we show that the source of attention signals in the FEF is enhanced activity of visually responsive neurons. At the time attention is allocated to the visual search target, nonvisually responsive saccade-related movement neurons are inhibited. Therefore, in the FEF, spatial attention signals are independent of explicit saccade command signals. We propose that spatially selective activity in FEF visually responsive neurons corresponds to the mental spotlight of attention via modulation of ongoing visual processing.

Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing

PubMed Central

da Rocha, Armando Freitas; Foz, Flávia Benevides; Pereira, Alfredo

2015-01-01

Recent studies on language processing indicate that language cognition is better understood if assumed to be supported by a distributed intelligent processing system enrolling neurons located all over the cortex, in contrast to reductionism that proposes to localize cognitive functions to specific cortical structures. Here, brain activity was recorded using electroencephalogram while volunteers were listening or reading small texts and had to select pictures that translate meaning of these texts. Several techniques for EEG analysis were used to show this distributed character of neuronal enrollment associated with the comprehension of oral and written descriptive texts. Low Resolution Tomography identified the many different sets (s i) of neurons activated in several distinct cortical areas by text understanding. Linear correlation was used to calculate the information H(e i) provided by each electrode of the 10/20 system about the identified s i. H(e i) Principal Component Analysis (PCA) was used to study the temporal and spatial activation of these sources s i. This analysis evidenced 4 different patterns of H(e i) covariation that are generated by neurons located at different cortical locations. These results clearly show that the distributed character of language processing is clearly evidenced by combining available EEG technologies. PMID:26713089

A common neural code for social and monetary rewards in the human striatum

PubMed Central

Wake, Stephanie J

2017-01-01

Abstract Although managing social information and decision making on the basis of reward is critical for survival, it remains uncertain whether differing reward type is processed in a uniform manner. Previously, we demonstrated that monetary reward and the social reward of good reputation activated the same striatal regions including the caudate nucleus and putamen. However, it remains unclear whether overlapping activations reflect activities of identical neuronal populations or two overlapping but functionally independent neuronal populations. Here, we re-analyzed the original data and addressed this question using multivariate-pattern-analysis and found evidence that in the left caudate nucleus and bilateral nucleus accumbens, social vs monetary reward were represented similarly. The findings suggest that social and monetary rewards are processed by the same population of neurons within these regions of the striatum. Additional findings demonstrated similar neural patterns when participants experience high social reward compared to viewing others receiving low social reward (potentially inducing schadenfreude). This is possibly an early indication that the same population of neurons may be responsible for processing two different types of social reward (good reputation and schadenfreude). These findings provide a supplementary perspective to previous research, helping to further elucidate the mechanisms behind social vs non-social reward processing. PMID:28985408

A common neural code for social and monetary rewards in the human striatum.

PubMed

Wake, Stephanie J; Izuma, Keise

2017-10-01

Although managing social information and decision making on the basis of reward is critical for survival, it remains uncertain whether differing reward type is processed in a uniform manner. Previously, we demonstrated that monetary reward and the social reward of good reputation activated the same striatal regions including the caudate nucleus and putamen. However, it remains unclear whether overlapping activations reflect activities of identical neuronal populations or two overlapping but functionally independent neuronal populations. Here, we re-analyzed the original data and addressed this question using multivariate-pattern-analysis and found evidence that in the left caudate nucleus and bilateral nucleus accumbens, social vs monetary reward were represented similarly. The findings suggest that social and monetary rewards are processed by the same population of neurons within these regions of the striatum. Additional findings demonstrated similar neural patterns when participants experience high social reward compared to viewing others receiving low social reward (potentially inducing schadenfreude). This is possibly an early indication that the same population of neurons may be responsible for processing two different types of social reward (good reputation and schadenfreude). These findings provide a supplementary perspective to previous research, helping to further elucidate the mechanisms behind social vs non-social reward processing. © The Author (2017). Published by Oxford University Press.

Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing.

PubMed

Rocha, Armando Freitas da; Foz, Flávia Benevides; Pereira, Alfredo

2015-01-01

Recent studies on language processing indicate that language cognition is better understood if assumed to be supported by a distributed intelligent processing system enrolling neurons located all over the cortex, in contrast to reductionism that proposes to localize cognitive functions to specific cortical structures. Here, brain activity was recorded using electroencephalogram while volunteers were listening or reading small texts and had to select pictures that translate meaning of these texts. Several techniques for EEG analysis were used to show this distributed character of neuronal enrollment associated with the comprehension of oral and written descriptive texts. Low Resolution Tomography identified the many different sets (s i ) of neurons activated in several distinct cortical areas by text understanding. Linear correlation was used to calculate the information H(e i ) provided by each electrode of the 10/20 system about the identified s i . H(e i ) Principal Component Analysis (PCA) was used to study the temporal and spatial activation of these sources s i . This analysis evidenced 4 different patterns of H(e i ) covariation that are generated by neurons located at different cortical locations. These results clearly show that the distributed character of language processing is clearly evidenced by combining available EEG technologies.

Texture coarseness responsive neurons and their mapping in layer 2–3 of the rat barrel cortex in vivo

PubMed Central

Garion, Liora; Dubin, Uri; Rubin, Yoav; Khateb, Mohamed; Schiller, Yitzhak; Azouz, Rony; Schiller, Jackie

2014-01-01

Texture discrimination is a fundamental function of somatosensory systems, yet the manner by which texture is coded and spatially represented in the barrel cortex are largely unknown. Using in vivo two-photon calcium imaging in the rat barrel cortex during artificial whisking against different surface coarseness or controlled passive whisker vibrations simulating different coarseness, we show that layer 2–3 neurons within barrel boundaries differentially respond to specific texture coarsenesses, while only a minority of neurons responded monotonically with increased or decreased surface coarseness. Neurons with similar preferred texture coarseness were spatially clustered. Multi-contact single unit recordings showed a vertical columnar organization of texture coarseness preference in layer 2–3. These findings indicate that layer 2–3 neurons perform high hierarchical processing of tactile information, with surface coarseness embodied by distinct neuronal subpopulations that are spatially mapped onto the barrel cortex. DOI: http://dx.doi.org/10.7554/eLife.03405.001 PMID:25233151

A microprobe for parallel optical and electrical recordings from single neurons in vivo.

PubMed

LeChasseur, Yoan; Dufour, Suzie; Lavertu, Guillaume; Bories, Cyril; Deschênes, Martin; Vallée, Réal; De Koninck, Yves

2011-04-01

Recording electrical activity from identified neurons in intact tissue is key to understanding their role in information processing. Recent fluorescence labeling techniques have opened new possibilities to combine electrophysiological recording with optical detection of individual neurons deep in brain tissue. For this purpose we developed dual-core fiberoptics-based microprobes, with an optical core to locally excite and collect fluorescence, and an electrolyte-filled hollow core for extracellular single unit electrophysiology. This design provides microprobes with tips < 10 μm, enabling analyses with single-cell optical resolution. We demonstrate combined electrical and optical detection of single fluorescent neurons in rats and mice. We combined electrical recordings and optical Ca²(+) measurements from single thalamic relay neurons in rats, and achieved detection and activation of single channelrhodopsin-expressing neurons in Thy1::ChR2-YFP transgenic mice. The microprobe expands possibilities for in vivo electrophysiological recording, providing parallel access to single-cell optical monitoring and control.

Stimulus-related activity during conditional associations in monkey perirhinal cortex neurons depends on upcoming reward outcome.

PubMed

Ohyama, Kaoru; Sugase-Miyamoto, Yasuko; Matsumoto, Narihisa; Shidara, Munetaka; Sato, Chikara

2012-11-28

Acquiring the significance of events based on reward-related information is critical for animals to survive and to conduct social activities. The importance of the perirhinal cortex for reward-related information processing has been suggested. To examine whether or not neurons in this cortex represent reward information flexibly when a visual stimulus indicates either a rewarded or unrewarded outcome, neuronal activity in the macaque perirhinal cortex was examined using a conditional-association cued-reward task. The task design allowed us to study how the neuronal responses depended on the animal's prediction of whether it would or would not be rewarded. Two visual stimuli, a color stimulus as Cue1 followed by a pattern stimulus as Cue2, were sequentially presented. Each pattern stimulus was conditionally associated with both rewarded and unrewarded outcomes depending on the preceding color stimulus. We found an activity depending upon the two reward conditions during Cue2, i.e., pattern stimulus presentation. The response appeared after the response dependent upon the image identity of Cue2. The response delineating a specific cue sequence also appeared between the responses dependent upon the identity of Cue2 and reward conditions. Thus, when Cue1 sets the context for whether or not Cue2 indicates a reward, this region represents the meaning of Cue2, i.e., the reward conditions, independent of the identity of Cue2. These results suggest that neurons in the perirhinal cortex do more than associate a single stimulus with a reward to achieve flexible representations of reward information.

The dorsal raphe modulates sensory responsiveness during arousal in zebrafish

PubMed Central

Yokogawa, Tohei; Hannan, Markus C.; Burgess, Harold A.

2012-01-01

During waking behavior animals adapt their state of arousal in response to environmental pressures. Sensory processing is regulated in aroused states and several lines of evidence imply that this is mediated at least partly by the serotonergic system. However there is little information directly showing that serotonergic function is required for state-dependent modulation of sensory processing. Here we find that zebrafish larvae can maintain a short-term state of arousal during which neurons in the dorsal raphe modulate sensory responsiveness to behaviorally relevant visual cues. Following a brief exposure to water flow, larvae show elevated activity and heightened sensitivity to perceived motion. Calcium imaging of neuronal activity after flow revealed increased activity in serotonergic neurons of the dorsal raphe. Genetic ablation of these neurons abolished the increase in visual sensitivity during arousal without affecting baseline visual function or locomotor activity. We traced projections from the dorsal raphe to a major visual area, the optic tectum. Laser ablation of the tectum demonstrated that this structure, like the dorsal raphe, is required for improved visual sensitivity during arousal. These findings reveal that serotonergic neurons of the dorsal raphe have a state-dependent role in matching sensory responsiveness to behavioral context. PMID:23100441

Where the thoughts dwell: the physiology of neuronal-glial "diffuse neural net".

PubMed

Verkhratsky, Alexei; Parpura, Vladimir; Rodríguez, José J

2011-01-07

The mechanisms underlying the production of thoughts by exceedingly complex cellular networks that construct the human brain constitute the most challenging problem of natural sciences. Our understanding of the brain function is very much shaped by the neuronal doctrine that assumes that neuronal networks represent the only substrate for cognition. These neuronal networks however are embedded into much larger and probably more complex network formed by neuroglia. The latter, although being electrically silent, employ many different mechanisms for intercellular signalling. It appears that astrocytes can control synaptic networks and in such a capacity they may represent an integral component of the computational power of the brain rather than being just brain "connective tissue". The fundamental question of whether neuroglia is involved in cognition and information processing remains, however, open. Indeed, a remarkable increase in the number of glial cells that distinguishes the human brain can be simply a result of exceedingly high specialisation of the neuronal networks, which delegated all matters of survival and maintenance to the neuroglia. At the same time potential power of analogue processing offered by internally connected glial networks may represent the alternative mechanism involved in cognition. Copyright © 2010 Elsevier B.V. All rights reserved.

A Spiking Neural Network System for Robust Sequence Recognition.

PubMed

Yu, Qiang; Yan, Rui; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2016-03-01

This paper proposes a biologically plausible network architecture with spiking neurons for sequence recognition. This architecture is a unified and consistent system with functional parts of sensory encoding, learning, and decoding. This is the first systematic model attempting to reveal the neural mechanisms considering both the upstream and the downstream neurons together. The whole system is a consistent temporal framework, where the precise timing of spikes is employed for information processing and cognitive computing. Experimental results show that the system is competent to perform the sequence recognition, being robust to noisy sensory inputs and invariant to changes in the intervals between input stimuli within a certain range. The classification ability of the temporal learning rule used in the system is investigated through two benchmark tasks that outperform the other two widely used learning rules for classification. The results also demonstrate the computational power of spiking neurons over perceptrons for processing spatiotemporal patterns. In summary, the system provides a general way with spiking neurons to encode external stimuli into spatiotemporal spikes, to learn the encoded spike patterns with temporal learning rules, and to decode the sequence order with downstream neurons. The system structure would be beneficial for developments in both hardware and software.

Control of Phasic Firing by a Background Leak Current in Avian Forebrain Auditory Neurons

PubMed Central

Dagostin, André A.; Lovell, Peter V.; Hilscher, Markus M.; Mello, Claudio V.; Leão, Ricardo M.

2015-01-01

Central neurons express a variety of neuronal types and ion channels that promote firing heterogeneity among their distinct neuronal populations. Action potential (AP) phasic firing, produced by low-threshold voltage-activated potassium currents (VAKCs), is commonly observed in mammalian brainstem neurons involved in the processing of temporal properties of the acoustic information. The avian caudomedial nidopallium (NCM) is an auditory area analogous to portions of the mammalian auditory cortex that is involved in the perceptual discrimination and memorization of birdsong and shows complex responses to auditory stimuli We performed in vitro whole-cell patch-clamp recordings in brain slices from adult zebra finches (Taeniopygia guttata) and observed that half of NCM neurons fire APs phasically in response to membrane depolarizations, while the rest fire transiently or tonically. Phasic neurons fired APs faster and with more temporal precision than tonic and transient neurons. These neurons had similar membrane resting potentials, but phasic neurons had lower membrane input resistance and time constant. Surprisingly phasic neurons did not express low-threshold VAKCs, which curtailed firing in phasic mammalian brainstem neurons, having similar VAKCs to other NCM neurons. The phasic firing was determined not by VAKCs, but by the potassium background leak conductances, which was more prominently expressed in phasic neurons, a result corroborated by pharmacological, dynamic-clamp, and modeling experiments. These results reveal a new role for leak currents in generating firing diversity in central neurons. PMID:26696830

Neuroelectric Tuning of Cortical Oscillations by Apical Dendrites in Loop Circuits

PubMed Central

LaBerge, David; Kasevich, Ray S.

2017-01-01

Bundles of relatively long apical dendrites dominate the neurons that make up the thickness of the cerebral cortex. It is proposed that a major function of the apical dendrite is to produce sustained oscillations at a specific frequency that can serve as a common timing unit for the processing of information in circuits connected to that apical dendrite. Many layer 5 and 6 pyramidal neurons are connected to thalamic neurons in loop circuits. A model of the apical dendrites of these pyramidal neurons has been used to simulate the electric activity of the apical dendrite. The results of that simulation demonstrated that subthreshold electric pulses in these apical dendrites can be tuned to specific frequencies and also can be fine-tuned to narrow bandwidths of less than one Hertz (1 Hz). Synchronous pulse outputs from the circuit loops containing apical dendrites can tune subthreshold membrane oscillations of neurons they contact. When the pulse outputs are finely tuned, they function as a local “clock,” which enables the contacted neurons to synchronously communicate with each other. Thus, a shared tuning frequency can select neurons for membership in a circuit. Unlike layer 6 apical dendrites, layer 5 apical dendrites can produce burst firing in many of their neurons, which increases the amplitude of signals in the neurons they contact. This difference in amplitude of signals serves as basis of selecting a sub-circuit for specialized processing (e.g., sustained attention) within the typically larger layer 6-based circuit. After examining the sustaining of oscillations in loop circuits and the processing of spikes in network circuits, we propose that cortical functioning can be globally viewed as two systems: a loop system and a network system. The loop system oscillations influence the network system’s timing and amplitude of pulse signals, both of which can select circuits that are momentarily dominant in cortical activity. PMID:28659768

Neuroelectric Tuning of Cortical Oscillations by Apical Dendrites in Loop Circuits.

PubMed

LaBerge, David; Kasevich, Ray S

2017-01-01

Bundles of relatively long apical dendrites dominate the neurons that make up the thickness of the cerebral cortex. It is proposed that a major function of the apical dendrite is to produce sustained oscillations at a specific frequency that can serve as a common timing unit for the processing of information in circuits connected to that apical dendrite. Many layer 5 and 6 pyramidal neurons are connected to thalamic neurons in loop circuits. A model of the apical dendrites of these pyramidal neurons has been used to simulate the electric activity of the apical dendrite. The results of that simulation demonstrated that subthreshold electric pulses in these apical dendrites can be tuned to specific frequencies and also can be fine-tuned to narrow bandwidths of less than one Hertz (1 Hz). Synchronous pulse outputs from the circuit loops containing apical dendrites can tune subthreshold membrane oscillations of neurons they contact. When the pulse outputs are finely tuned, they function as a local "clock," which enables the contacted neurons to synchronously communicate with each other. Thus, a shared tuning frequency can select neurons for membership in a circuit. Unlike layer 6 apical dendrites, layer 5 apical dendrites can produce burst firing in many of their neurons, which increases the amplitude of signals in the neurons they contact. This difference in amplitude of signals serves as basis of selecting a sub-circuit for specialized processing (e.g., sustained attention) within the typically larger layer 6-based circuit. After examining the sustaining of oscillations in loop circuits and the processing of spikes in network circuits, we propose that cortical functioning can be globally viewed as two systems: a loop system and a network system. The loop system oscillations influence the network system's timing and amplitude of pulse signals, both of which can select circuits that are momentarily dominant in cortical activity.

Neuronal Representation of Ultraviolet Visual Stimuli in Mouse Primary Visual Cortex

PubMed Central

Tan, Zhongchao; Sun, Wenzhi; Chen, Tsai-Wen; Kim, Douglas; Ji, Na

2015-01-01

The mouse has become an important model for understanding the neural basis of visual perception. Although it has long been known that mouse lens transmits ultraviolet (UV) light and mouse opsins have absorption in the UV band, little is known about how UV visual information is processed in the mouse brain. Using a custom UV stimulation system and in vivo calcium imaging, we characterized the feature selectivity of layer 2/3 neurons in mouse primary visual cortex (V1). In adult mice, a comparable percentage of the neuronal population responds to UV and visible stimuli, with similar pattern selectivity and receptive field properties. In young mice, the orientation selectivity for UV stimuli increased steadily during development, but not direction selectivity. Our results suggest that, by expanding the spectral window through which the mouse can acquire visual information, UV sensitivity provides an important component for mouse vision. PMID:26219604

A gustatory second-order neuron that connects sucrose-sensitive primary neurons and a distinct region of the gnathal ganglion in the Drosophila brain

PubMed Central

Miyazaki, Takaaki; Lin, Tzu-Yang; Ito, Kei; Lee, Chi-Hon; Stopfer, Mark

2016-01-01

Although the gustatory system provides animals with sensory cues important for food choice and other critical behaviors, little is known about neural circuitry immediately following gustatory sensory neurons (GSNs). Here, we identify and characterize a bilateral pair of gustatory second-order neurons in Drosophila. Previous studies identified GSNs that relay taste information to distinct subregions of the primary gustatory center (PGC) in the gnathal ganglia (GNG). To identify candidate gustatory second-order neurons (G2Ns) we screened ~5,000 GAL4 driver strains for lines that label neural fibers innervating the PGC. We then combined GRASP (GFP reconstitution across synaptic partners) with presynaptic labeling to visualize potential synaptic contacts between the dendrites of the candidate G2Ns and the axonal terminals of Gr5a-expressing GSNs, which are known to respond to sucrose. Results of the GRASP analysis, followed by a single cell analysis by FLPout recombination, revealed a pair of neurons that contact Gr5a axon terminals in both brain hemispheres, and send axonal arborizations to a distinct region outside the PGC but within the GNG. To characterize the input and output branches, respectively, we expressed fluorescence-tagged acetylcholine receptor subunit (Dα7) and active-zone marker (Brp) in the G2Ns. We found that G2N input sites overlaid GRASP-labeled synaptic contacts to Gr5a neurons, while presynaptic sites were broadly distributed throughout the neurons’ arborizations. GRASP analysis and further tests with the Syb-GRASP method suggested that the identified G2Ns receive synaptic inputs from Gr5a-expressing GSNs, but not Gr66a-expressing GSNs, which respond to caffeine. The identified G2Ns relay information from Gr5a-expressing GSNs to distinct regions in the GNG, and are distinct from other, recently identified gustatory projection neurons, which relay information about sugars to a brain region called the antennal mechanosensory and motor center (AMMC). Our findings suggest unexpected complexity for taste information processing in the first relay of the gustatory system. PMID:26004543

A gustatory second-order neuron that connects sucrose-sensitive primary neurons and a distinct region of the gnathal ganglion in the Drosophila brain.

PubMed

Miyazaki, Takaaki; Lin, Tzu-Yang; Ito, Kei; Lee, Chi-Hon; Stopfer, Mark

2015-01-01

Although the gustatory system provides animals with sensory cues important for food choice and other critical behaviors, little is known about neural circuitry immediately following gustatory sensory neurons (GSNs). Here, we identify and characterize a bilateral pair of gustatory second-order neurons (G2Ns) in Drosophila. Previous studies identified GSNs that relay taste information to distinct subregions of the primary gustatory center (PGC) in the gnathal ganglia (GNG). To identify candidate G2Ns, we screened ∼5,000 GAL4 driver strains for lines that label neural fibers innervating the PGC. We then combined GRASP (GFP reconstitution across synaptic partners) with presynaptic labeling to visualize potential synaptic contacts between the dendrites of the candidate G2Ns and the axonal terminals of Gr5a-expressing GSNs, which are known to respond to sucrose. Results of the GRASP analysis, followed by a single-cell analysis by FLP-out recombination, revealed a pair of neurons that contact Gr5a axon terminals in both brain hemispheres and send axonal arborizations to a distinct region outside the PGC but within the GNG. To characterize the input and output branches, respectively, we expressed fluorescence-tagged acetylcholine receptor subunit (Dα7) and active-zone marker (Brp) in the G2Ns. We found that G2N input sites overlaid GRASP-labeled synaptic contacts to Gr5a neurons, while presynaptic sites were broadly distributed throughout the neurons' arborizations. GRASP analysis and further tests with the Syb-GRASP method suggested that the identified G2Ns receive synaptic inputs from Gr5a-expressing GSNs, but not Gr66a-expressing GSNs, which respond to caffeine. The identified G2Ns relay information from Gr5a-expressing GSNs to distinct regions in the GNG, and are distinct from other, recently identified gustatory projection neurons, which relay information about sugars to a brain region called the antennal mechanosensory and motor center (AMMC). Our findings suggest unexpected complexity for taste information processing in the first relay of the gustatory system.

A simplified computational memory model from information processing.

PubMed

Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

2016-11-23

This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view.

Differential Contributions of Ventral and Dorsal Striatum to Early and Late Phases of Cognitive Set Reconfiguration

PubMed Central

Sleezer, Brianna J.; Hayden, Benjamin Y.

2017-01-01

Flexible decision-making, a defining feature of human cognition, is typically thought of as a canonical pFC function. Recent work suggests that the striatum may participate as well; however, its role in this process is not well understood. We recorded activity of neurons in both the ventral (VS) and dorsal (DS) striatum while rhesus macaques performed a version of the Wisconsin Card Sorting Test, a classic test of flexibility. Our version of the task involved a trial-and-error phase before monkeys could identify the correct rule on each block. We observed changes in firing rate in both regions when monkeys switched rules. Specifically, VS neurons demonstrated switch-related activity early in the trial-and-error period when the rule needed to be updated, and a portion of these neurons signaled information about the switch context (i.e., whether the switch was intradimensional or extradimensional). Neurons in both VS and DS demonstrated switch-related activity at the end of the trial-and-error period, immediately before the rule was fully established and maintained, but these signals did not carry any information about switch context. We also observed associative learning signals (i.e., specific responses to options associated with rewards in the presentation period before choice) that followed the same pattern as switch signals (early in VS, later in DS). Taken together, these results endorse the idea that the striatum participates directly in cognitive set reconfiguration and suggest that single neurons in the striatum may contribute to a functional handoff from the VS to the DS during reconfiguration processes. PMID:27417204

The cyclic nucleotide gated channel subunit CNG-1 instructs behavioral outputs in Caenorhabditis elegans by coincidence detection of nutritional status and olfactory input.

PubMed

He, Chao; Altshuler-Keylin, Svetlana; Daniel, David; L'Etoile, Noelle D; O'Halloran, Damien

2016-10-06

In mammals, olfactory subsystems have been shown to express seven-transmembrane G-protein-coupled receptors (GPCRs) in a one-receptor-one-neuron pattern, whereas in Caenorhabditis elegans, olfactory sensory neurons express multiple G-protein coupled odorant receptors per olfactory sensory neuron. In both mammalian and C. elegans olfactory sensory neurons (OSNs), the process of olfactory adaptation begins within the OSN; this process of negative feedback within the mammalian OSN has been well described in mammals and enables activated OSNs to desensitize their response cell autonomously while attending to odors detected by separate OSNs. However, the mechanism that enables C. elegans to adapt to one odor and attend to another odor sensed by the same olfactory sensory neuron remains unclear. We found that the cyclic nucleotide gated channel subunit CNG-1 is required to promote cross adaptation responses between distinct olfactory cues. This change in sensitivity to a pair of odorants after persistent stimulation by just one of these odors is modulated by the internal nutritional state of the animal, and we find that this response is maintained across a diverse range of food sources for C. elegans. We also reveal that CNG-1 integrates food related cues for exploratory motor output, revealing that CNG-1 functions in multiple capacities to link nutritional information with behavioral output. Our data describes a novel model whereby CNG channels can integrate the coincidence detection of appetitive and olfactory information to set olfactory preferences and instruct behavioral outputs. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Millisecond-timescale local network coding in the rat primary somatosensory cortex.

PubMed

Eldawlatly, Seif; Oweiss, Karim G

2011-01-01

Correlation among neocortical neurons is thought to play an indispensable role in mediating sensory processing of external stimuli. The role of temporal precision in this correlation has been hypothesized to enhance information flow along sensory pathways. Its role in mediating the integration of information at the output of these pathways, however, remains poorly understood. Here, we examined spike timing correlation between simultaneously recorded layer V neurons within and across columns of the primary somatosensory cortex of anesthetized rats during unilateral whisker stimulation. We used bayesian statistics and information theory to quantify the causal influence between the recorded cells with millisecond precision. For each stimulated whisker, we inferred stable, whisker-specific, dynamic bayesian networks over many repeated trials, with network similarity of 83.3±6% within whisker, compared to only 50.3±18% across whiskers. These networks further provided information about whisker identity that was approximately 6 times higher than what was provided by the latency to first spike and 13 times higher than what was provided by the spike count of individual neurons examined separately. Furthermore, prediction of individual neurons' precise firing conditioned on knowledge of putative pre-synaptic cell firing was 3 times higher than predictions conditioned on stimulus onset alone. Taken together, these results suggest the presence of a temporally precise network coding mechanism that integrates information across neighboring columns within layer V about vibrissa position and whisking kinetics to mediate whisker movement by motor areas innervated by layer V.

Processing of Intraoral Olfactory and Gustatory Signals in the Gustatory Cortex of Awake Rats

PubMed Central

Fontanini, Alfredo

2017-01-01

The integration of gustatory and olfactory information is essential to the perception of flavor. Human neuroimaging experiments have pointed to the gustatory cortex (GC) as one of the areas involved in mediating flavor perception. Although GC's involvement in encoding the chemical identity and hedonic value of taste stimuli is well studied, it is unknown how single GC neurons process olfactory stimuli emanating from the mouth. In this study, we relied on multielectrode recordings to investigate how single GC neurons respond to intraorally delivered tastants and tasteless odorants dissolved in water and whether/how these two modalities converge in the same neurons. We found that GC neurons could either be unimodal, responding exclusively to taste (taste-only) or odor (odor-only), or bimodal, responding to both gustatory and olfactory stimuli. Odor responses were confirmed to result from retronasal olfaction: monitoring respiration revealed that exhalation preceded odor-evoked activity and reversible inactivation of olfactory receptors in the nasal epithelium significantly reduced responses to intraoral odorants but not to tastants. Analysis of bimodal neurons revealed that they encode palatability significantly better than the unimodal taste-only group. Bimodal neurons exhibited similar responses to palatable tastants and odorants dissolved in water. This result suggested that odorized water could be palatable. This interpretation was further supported with a brief access task, where rats avoided consuming aversive taste stimuli and consumed the palatable tastants and dissolved odorants. These results demonstrate the convergence of the chemosensory components of flavor onto single GC neurons and provide evidence for the integration of flavor with palatability coding. SIGNIFICANCE STATEMENT Food perception and choice depend upon the concurrent processing of olfactory and gustatory signals from the mouth. The primary gustatory cortex has been proposed to integrate chemosensory stimuli; however, no study has examined the single-unit responses to intraoral odorant presentation. Here we found that neurons in gustatory cortex can respond either exclusively to tastants, exclusively to odorants, or to both (bimodal). Several differences exist between these groups' responses; notably, bimodal neurons code palatability significantly better than unimodal neurons. This group of neurons might represent a substrate for how odorants gain the quality of tastants. PMID:28077705

The metabolic response to excitotoxicity - lessons from single-cell imaging.

PubMed

Connolly, Niamh M C; Prehn, Jochen H M

2015-04-01

Excitotoxicity is a pathological process implicated in neuronal death during ischaemia, traumatic brain injuries and neurodegenerative diseases. Excitotoxicity is caused by excess levels of glutamate and over-activation of NMDA or calcium-permeable AMPA receptors on neuronal membranes, leading to ionic influx, energetic stress and potential neuronal death. The metabolic response of neurons to excitotoxicity is complex and plays a key role in the ability of the neuron to adapt and recover from such an insult. Single-cell imaging is a powerful experimental technique that can be used to study the neuronal metabolic response to excitotoxicity in vitro and, increasingly, in vivo. Here, we review some of the knowledge of the neuronal metabolic response to excitotoxicity gained from in vitro single-cell imaging, including calcium and ATP dynamics and their effects on mitochondrial function, along with the contribution of glucose metabolism, oxidative stress and additional neuroprotective signalling mechanisms. Future work will combine knowledge gained from single-cell imaging with data from biochemical and computational techniques to garner holistic information about the metabolic response to excitotoxicity at the whole brain level and transfer this knowledge to a clinical setting.

Cellular Scaling Rules for Primate Spinal Cords

PubMed Central

Burish, Mark J.; Peebles, J. Klint; Baldwin, Mary K.; Tavares, Luciano; Kaas, Jon H.; Herculano-Houzel, Suzana

2010-01-01

The spinal cord can be considered a major sensorimotor interface between the body and the brain. How does the spinal cord scale with body and brain mass, and how are its numbers of neurons related to the number of neurons in the brain across species of different body and brain sizes? Here we determine the cellular composition of the spinal cord in eight primate species and find that its number of neurons varies as a linear function of cord length, and accompanies body mass raised to an exponent close to 1/3. This relationship suggests that the extension, mass and number of neurons that compose the spinal cord are related to body length, rather than to body mass or surface. Moreover, we show that although brain mass increases linearly with cord mass, the number of neurons in the brain increases with the number of neurons in the spinal cord raised to the power of 1.7. This faster addition of neurons to the brain than to the spinal cord is consistent with current views on how larger brains add complexity to the processing of environmental and somatic information. PMID:20926855

Talking back: Development of the olivocochlear efferent system.

PubMed

Frank, Michelle M; Goodrich, Lisa V

2018-06-26

Developing sensory systems must coordinate the growth of neural circuitry spanning from receptors in the peripheral nervous system (PNS) to multilayered networks within the central nervous system (CNS). This breadth presents particular challenges, as nascent processes must navigate across the CNS-PNS boundary and coalesce into a tightly intermingled wiring pattern, thereby enabling reliable integration from the PNS to the CNS and back. In the auditory system, feedforward spiral ganglion neurons (SGNs) from the periphery collect sound information via tonotopically organized connections in the cochlea and transmit this information to the brainstem for processing via the VIII cranial nerve. In turn, feedback olivocochlear neurons (OCNs) housed in the auditory brainstem send projections into the periphery, also through the VIII nerve. OCNs are motor neuron-like efferent cells that influence auditory processing within the cochlea and protect against noise damage in adult animals. These aligned feedforward and feedback systems develop in parallel, with SGN central axons reaching the developing auditory brainstem around the same time that the OCN axons extend out toward the developing inner ear. Recent findings have begun to unravel the genetic and molecular mechanisms that guide OCN development, from their origins in a generic pool of motor neuron precursors to their specialized roles as modulators of cochlear activity. One recurrent theme is the importance of efferent-afferent interactions, as afferent SGNs guide OCNs to their final locations within the sensory epithelium, and efferent OCNs shape the activity of the developing auditory system. This article is categorized under: Nervous System Development > Vertebrates: Regional Development. © 2018 Wiley Periodicals, Inc.

Tiger moths and the threat of bats: decision-making based on the activity of a single sensory neuron.

PubMed

Ratcliffe, John M; Fullard, James H; Arthur, Benjamin J; Hoy, Ronald R

2009-06-23

Echolocating bats and eared moths are a model system of predator-prey interaction within an almost exclusively auditory world. Through selective pressures from aerial-hawking bats, noctuoid moths have evolved simple ears that contain one to two auditory neurons and function to detect bat echolocation calls and initiate defensive flight behaviours. Among these moths, some chemically defended and mimetic tiger moths also produce ultrasonic clicks in response to bat echolocation calls; these defensive signals are effective warning signals and may interfere with bats' ability to process echoic information. Here, we demonstrate that the activity of a single auditory neuron (the A1 cell) provides sufficient information for the toxic dogbane tiger moth, Cycnia tenera, to decide when to initiate defensive sound production in the face of bats. Thus, despite previous suggestions to the contrary, these moths' only other auditory neuron, the less sensitive A2 cell, is not necessary for initiating sound production. However, we found a positive linear relationship between combined A1 and A2 activity and the number of clicks the dogbane tiger moth produces.

The importance of metadata to assess information content in digital reconstructions of neuronal morphology.

PubMed

Parekh, Ruchi; Armañanzas, Rubén; Ascoli, Giorgio A

2015-04-01

Digital reconstructions of axonal and dendritic arbors provide a powerful representation of neuronal morphology in formats amenable to quantitative analysis, computational modeling, and data mining. Reconstructed files, however, require adequate metadata to identify the appropriate animal species, developmental stage, brain region, and neuron type. Moreover, experimental details about tissue processing, neurite visualization and microscopic imaging are essential to assess the information content of digital morphologies. Typical morphological reconstructions only partially capture the underlying biological reality. Tracings are often limited to certain domains (e.g., dendrites and not axons), may be incomplete due to tissue sectioning, imperfect staining, and limited imaging resolution, or can disregard aspects irrelevant to their specific scientific focus (such as branch thickness or depth). Gauging these factors is critical in subsequent data reuse and comparison. NeuroMorpho.Org is a central repository of reconstructions from many laboratories and experimental conditions. Here, we introduce substantial additions to the existing metadata annotation aimed to describe the completeness of the reconstructed neurons in NeuroMorpho.Org. These expanded metadata form a suitable basis for effective description of neuromorphological data.

Predictive Suppression of Cortical Excitability and Its Deficit in Schizophrenia

PubMed Central

Schroeder, Charles E.; Leitman, David I.

2013-01-01

Recent neuroscience advances suggest that when interacting with our environment, along with previous experience, we use contextual cues and regularities to form predictions that guide our perceptions and actions. The goal of such active “predictive sensing” is to selectively enhance the processing and representation of behaviorally relevant information in an efficient manner. Since a hallmark of schizophrenia is impaired information selection, we tested whether this deficiency stems from dysfunctional predictive sensing by measuring the degree to which neuronal activity predicts relevant events. In healthy subjects, we established that these mechanisms are engaged in an effort-dependent manner and that, based on a correspondence between human scalp and intracranial nonhuman primate recordings, their main role is a predictive suppression of excitability in task-irrelevant regions. In contrast, schizophrenia patients displayed a reduced alignment of neuronal activity to attended stimuli, which correlated with their behavioral performance deficits and clinical symptoms. These results support the relevance of predictive sensing for normal and aberrant brain function, and highlight the importance of neuronal mechanisms that mold internal ongoing neuronal activity to model key features of the external environment. PMID:23843536

Enhanced Excitatory Connectivity and Disturbed Sound Processing in the Auditory Brainstem of Fragile X Mice.

PubMed

Garcia-Pino, Elisabet; Gessele, Nikodemus; Koch, Ursula

2017-08-02

Hypersensitivity to sounds is one of the prevalent symptoms in individuals with Fragile X syndrome (FXS). It manifests behaviorally early during development and is often used as a landmark for treatment efficacy. However, the physiological mechanisms and circuit-level alterations underlying this aberrant behavior remain poorly understood. Using the mouse model of FXS ( Fmr1 KO ), we demonstrate that functional maturation of auditory brainstem synapses is impaired in FXS. Fmr1 KO mice showed a greatly enhanced excitatory synaptic input strength in neurons of the lateral superior olive (LSO), a prominent auditory brainstem nucleus, which integrates ipsilateral excitation and contralateral inhibition to compute interaural level differences. Conversely, the glycinergic, inhibitory input properties remained unaffected. The enhanced excitation was the result of an increased number of cochlear nucleus fibers converging onto one LSO neuron, without changing individual synapse properties. Concomitantly, immunolabeling of excitatory ending markers revealed an increase in the immunolabeled area, supporting abnormally elevated excitatory input numbers. Intrinsic firing properties were only slightly enhanced. In line with the disturbed development of LSO circuitry, auditory processing was also affected in adult Fmr1 KO mice as shown with single-unit recordings of LSO neurons. These processing deficits manifested as an increase in firing rate, a broadening of the frequency response area, and a shift in the interaural level difference function of LSO neurons. Our results suggest that this aberrant synaptic development of auditory brainstem circuits might be a major underlying cause of the auditory processing deficits in FXS. SIGNIFICANCE STATEMENT Fragile X Syndrome (FXS) is the most common inheritable form of intellectual impairment, including autism. A core symptom of FXS is extreme sensitivity to loud sounds. This is one reason why individuals with FXS tend to avoid social interactions, contributing to their isolation. Here, a mouse model of FXS was used to investigate the auditory brainstem where basic sound information is first processed. Loss of the Fragile X mental retardation protein leads to excessive excitatory compared with inhibitory inputs in neurons extracting information about sound levels. Functionally, this elevated excitation results in increased firing rates, and abnormal coding of frequency and binaural sound localization cues. Imbalanced early-stage sound level processing could partially explain the auditory processing deficits in FXS. Copyright © 2017 the authors 0270-6474/17/377403-17$15.00/0.

Somato-Motor Haptic Processing in Posterior Inner Perisylvian Region (SII/pIC) of the Macaque Monkey

PubMed Central

Ishida, Hiroaki; Fornia, Luca; Grandi, Laura Clara; Umiltà, Maria Alessandra; Gallese, Vittorio

2013-01-01

The posterior inner perisylvian region including the secondary somatosensory cortex (area SII) and the adjacent region of posterior insular cortex (pIC) has been implicated in haptic processing by integrating somato-motor information during hand-manipulation, both in humans and in non-human primates. However, motor-related properties during hand-manipulation are still largely unknown. To investigate a motor-related activity in the hand region of SII/pIC, two macaque monkeys were trained to perform a hand-manipulation task, requiring 3 different grip types (precision grip, finger exploration, side grip) both in light and in dark conditions. Our results showed that 70% (n = 33/48) of task related neurons within SII/pIC were only activated during monkeys’ active hand-manipulation. Of those 33 neurons, 15 (45%) began to discharge before hand-target contact, while the remaining neurons were tonically active after contact. Thirty-percent (n = 15/48) of studied neurons responded to both passive somatosensory stimulation and to the motor task. A consistent percentage of task-related neurons in SII/pIC was selectively activated during finger exploration (FE) and precision grasping (PG) execution, suggesting they play a pivotal role in control skilled finger movements. Furthermore, hand-manipulation-related neurons also responded when visual feedback was absent in the dark. Altogether, our results suggest that somato-motor neurons in SII/pIC likely contribute to haptic processing from the initial to the final phase of grasping and object manipulation. Such motor-related activity could also provide the somato-motor binding principle enabling the translation of diachronic somatosensory inputs into a coherent image of the explored object. PMID:23936121

It takes two-coincidence coding within the dual olfactory pathway of the honeybee.

PubMed

Brill, Martin F; Meyer, Anneke; Rössler, Wolfgang

2015-01-01

To rapidly process biologically relevant stimuli, sensory systems have developed a broad variety of coding mechanisms like parallel processing and coincidence detection. Parallel processing (e.g., in the visual system), increases both computational capacity and processing speed by simultaneously coding different aspects of the same stimulus. Coincidence detection is an efficient way to integrate information from different sources. Coincidence has been shown to promote associative learning and memory or stimulus feature detection (e.g., in auditory delay lines). Within the dual olfactory pathway of the honeybee both of these mechanisms might be implemented by uniglomerular projection neurons (PNs) that transfer information from the primary olfactory centers, the antennal lobe (AL), to a multimodal integration center, the mushroom body (MB). PNs from anatomically distinct tracts respond to the same stimulus space, but have different physiological properties, characteristics that are prerequisites for parallel processing of different stimulus aspects. However, the PN pathways also display mirror-imaged like anatomical trajectories that resemble neuronal coincidence detectors as known from auditory delay lines. To investigate temporal processing of olfactory information, we recorded PN odor responses simultaneously from both tracts and measured coincident activity of PNs within and between tracts. Our results show that coincidence levels are different within each of the two tracts. Coincidence also occurs between tracts, but to a minor extent compared to coincidence within tracts. Taken together our findings support the relevance of spike timing in coding of olfactory information (temporal code).

High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels†

PubMed Central

Müller, Jan; Ballini, Marco; Livi, Paolo; Chen, Yihui; Radivojevic, Milos; Shadmani, Amir; Viswam, Vijay; Jones, Ian L.; Fiscella, Michele; Diggelmann, Roland; Stettler, Alexander; Frey, Urs; Bakkum, Douglas J.; Hierlemann, Andreas

2017-01-01

Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 μm) within a large overall sensing area (3.85 × 2.10 mm2). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons. PMID:25973786

Manipulating neural activity in physiologically classified neurons: triumphs and challenges

PubMed Central

Gore, Felicity; Schwartz, Edmund C.; Salzman, C. Daniel

2015-01-01

Understanding brain function requires knowing both how neural activity encodes information and how this activity generates appropriate responses. Electrophysiological, imaging and immediate early gene immunostaining studies have been instrumental in identifying and characterizing neurons that respond to different sensory stimuli, events and motor actions. Here we highlight approaches that have manipulated the activity of physiologically classified neurons to determine their role in the generation of behavioural responses. Previous experiments have often exploited the functional architecture observed in many cortical areas, where clusters of neurons share response properties. However, many brain structures do not exhibit such functional architecture. Instead, neurons with different response properties are anatomically intermingled. Emerging genetic approaches have enabled the identification and manipulation of neurons that respond to specific stimuli despite the lack of discernable anatomical organization. These approaches have advanced understanding of the circuits mediating sensory perception, learning and memory, and the generation of behavioural responses by providing causal evidence linking neural response properties to appropriate behavioural output. However, significant challenges remain for understanding cognitive processes that are probably mediated by neurons with more complex physiological response properties. Currently available strategies may prove inadequate for determining how activity in these neurons is causally related to cognitive behaviour. PMID:26240431

High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels.

PubMed

Müller, Jan; Ballini, Marco; Livi, Paolo; Chen, Yihui; Radivojevic, Milos; Shadmani, Amir; Viswam, Vijay; Jones, Ian L; Fiscella, Michele; Diggelmann, Roland; Stettler, Alexander; Frey, Urs; Bakkum, Douglas J; Hierlemann, Andreas

2015-07-07

Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 μm) within a large overall sensing area (3.85 × 2.10 mm(2)). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons.

Auditory responses in the amygdala to social vocalizations

NASA Astrophysics Data System (ADS)

Gadziola, Marie A.

The underlying goal of this dissertation is to understand how the amygdala, a brain region involved in establishing the emotional significance of sensory input, contributes to the processing of complex sounds. The general hypothesis is that communication calls of big brown bats (Eptesicus fuscus) transmit relevant information about social context that is reflected in the activity of amygdalar neurons. The first specific aim analyzed social vocalizations emitted under a variety of behavioral contexts, and related vocalizations to an objective measure of internal physiological state by monitoring the heart rate of vocalizing bats. These experiments revealed a complex acoustic communication system among big brown bats in which acoustic cues and call structure signal the emotional state of a sender. The second specific aim characterized the responsiveness of single neurons in the basolateral amygdala to a range of social syllables. Neurons typically respond to the majority of tested syllables, but effectively discriminate among vocalizations by varying the response duration. This novel coding strategy underscores the importance of persistent firing in the general functioning of the amygdala. The third specific aim examined the influence of acoustic context by characterizing both the behavioral and neurophysiological responses to natural vocal sequences. Vocal sequences differentially modify the internal affective state of a listening bat, with lower aggression vocalizations evoking the greatest change in heart rate. Amygdalar neurons employ two different coding strategies: low background neurons respond selectively to very few stimuli, whereas high background neurons respond broadly to stimuli but demonstrate variation in response magnitude and timing. Neurons appear to discriminate the valence of stimuli, with aggression sequences evoking robust population-level responses across all sound levels. Further, vocal sequences show improved discrimination among stimuli compared to isolated syllables, and this improved discrimination is expressed in part by the timing of action potentials. Taken together, these data support the hypothesis that big brown bat social vocalizations transmit relevant information about the social context that is encoded within the discharge pattern of amygdalar neurons ultimately responsible for coordinating appropriate social behaviors. I further propose that vocalization-evoked amygdalar activity will have significant impact on subsequent sensory processing and plasticity.

Coding of position by simultaneously recorded sensory neurones in the cat dorsal root ganglion

PubMed Central

Stein, R B; Weber, D J; Aoyagi, Y; Prochazka, A; Wagenaar, J B M; Shoham, S; Normann, R A

2004-01-01

Muscle, cutaneous and joint afferents continuously signal information about the position and movement of individual joints. How does the nervous system extract more global information, for example about the position of the foot in space? To study this question we used microelectrode arrays to record impulses simultaneously from up to 100 discriminable nerve cells in the L6 and L7 dorsal root ganglia (DRG) of the anaesthetized cat. When the hindlimb was displaced passively with a random trajectory, the firing rate of the neurones could be predicted from a linear sum of positions and velocities in Cartesian (x, y), polar or joint angular coordinates. The process could also be reversed to predict the kinematics of the limb from the firing rates of the neurones with an accuracy of 1–2 cm. Predictions of position and velocity could be combined to give an improved fit to limb position. Decoders trained using random movements successfully predicted cyclic movements and movements in which the limb was displaced from a central point to various positions in the periphery. A small number of highly informative neurones (6–8) could account for over 80% of the variance in position and a similar result was obtained in a realistic limb model. In conclusion, this work illustrates how populations of sensory receptors may encode a sense of limb position and how the firing of even a small number of neurones can be used to decode the position of the limb in space. PMID:15331686

Oscillatory integration windows in neurons

PubMed Central

Gupta, Nitin; Singh, Swikriti Saran; Stopfer, Mark

2016-01-01

Oscillatory synchrony among neurons occurs in many species and brain areas, and has been proposed to help neural circuits process information. One hypothesis states that oscillatory input creates cyclic integration windows: specific times in each oscillatory cycle when postsynaptic neurons become especially responsive to inputs. With paired local field potential (LFP) and intracellular recordings and controlled stimulus manipulations we directly test this idea in the locust olfactory system. We find that inputs arriving in Kenyon cells (KCs) sum most effectively in a preferred window of the oscillation cycle. With a computational model, we show that the non-uniform structure of noise in the membrane potential helps mediate this process. Further experiments performed in vivo demonstrate that integration windows can form in the absence of inhibition and at a broad range of oscillation frequencies. Our results reveal how a fundamental coincidence-detection mechanism in a neural circuit functions to decode temporally organized spiking. PMID:27976720

Multisite two-photon imaging of neurons on multielectrode arrays

NASA Astrophysics Data System (ADS)

Potter, Steve M.; Lukina, Natalia; Longmuir, Kenneth J.; Wu, Yan

2001-04-01

We wish to understand how neural systems store, recall, and process information. We are using cultured networks of cortical neurons grown on microelectrode arrays as a model system for studying the emergent properties of ensembles of living neurons. We have developed a 2-way communication interface between the cultured network and a computer- generated animal, the Neurally Controlled Animat. Neural activity is used to control the behavior of the Animat, and 2- photon time-lapse imaging is carried out in order to observe the morphological changes that might underlie changes in neural processing. The 2-photon microscope is ideal for repeated imaging over hours or days, with submicron resolution and little photodamage. We have designed a computer-controlled microscope stage that allows imaging several locations in sequence, in order to collect more image data. For the latest progress, see: http://www.caltech.edu/~pinelab/PotterGroup.htm.

Multisensory integration in early vestibular processing in mice: the encoding of passive vs. active motion

PubMed Central

Medrea, Ioana

2013-01-01

The mouse has become an important model system for studying the cellular basis of learning and coding of heading by the vestibular system. Here we recorded from single neurons in the vestibular nuclei to understand how vestibular pathways encode self-motion under natural conditions, during which proprioceptive and motor-related signals as well as vestibular inputs provide feedback about an animal's movement through the world. We recorded neuronal responses in alert behaving mice focusing on a group of neurons, termed vestibular-only cells, that are known to control posture and project to higher-order centers. We found that the majority (70%, n = 21/30) of neurons were bimodal, in that they responded robustly to passive stimulation of proprioceptors as well as passive stimulation of the vestibular system. Additionally, the linear summation of a given neuron's vestibular and neck sensitivities predicted well its responses when both stimuli were applied simultaneously. In contrast, neuronal responses were suppressed when the same motion was actively generated, with the one striking exception that the activity of bimodal neurons similarly and robustly encoded head on body position in all conditions. Our results show that proprioceptive and motor-related signals are combined with vestibular information at the first central stage of vestibular processing in mice. We suggest that these results have important implications for understanding the multisensory integration underlying accurate postural control and the neural representation of directional heading in the head direction cell network of mice. PMID:24089394

Coding and decoding with dendrites.

PubMed

Papoutsi, Athanasia; Kastellakis, George; Psarrou, Maria; Anastasakis, Stelios; Poirazi, Panayiota

2014-02-01

Since the discovery of complex, voltage dependent mechanisms in the dendrites of multiple neuron types, great effort has been devoted in search of a direct link between dendritic properties and specific neuronal functions. Over the last few years, new experimental techniques have allowed the visualization and probing of dendritic anatomy, plasticity and integrative schemes with unprecedented detail. This vast amount of information has caused a paradigm shift in the study of memory, one of the most important pursuits in Neuroscience, and calls for the development of novel theories and models that will unify the available data according to some basic principles. Traditional models of memory considered neural cells as the fundamental processing units in the brain. Recent studies however are proposing new theories in which memory is not only formed by modifying the synaptic connections between neurons, but also by modifications of intrinsic and anatomical dendritic properties as well as fine tuning of the wiring diagram. In this review paper we present previous studies along with recent findings from our group that support a key role of dendrites in information processing, including the encoding and decoding of new memories, both at the single cell and the network level. Copyright © 2013 Elsevier Ltd. All rights reserved.

Information transmission and detection thresholds in the vestibular nuclei: single neurons vs. population encoding

PubMed Central

Massot, Corentin; Chacron, Maurice J.

2011-01-01

Understanding how sensory neurons transmit information about relevant stimuli remains a major goal in neuroscience. Of particular relevance are the roles of neural variability and spike timing in neural coding. Peripheral vestibular afferents display differential variability that is correlated with the importance of spike timing; regular afferents display little variability and use a timing code to transmit information about sensory input. Irregular afferents, conversely, display greater variability and instead use a rate code. We studied how central neurons within the vestibular nuclei integrate information from both afferent classes by recording from a group of neurons termed vestibular only (VO) that are known to make contributions to vestibulospinal reflexes and project to higher-order centers. We found that, although individual central neurons had sensitivities that were greater than or equal to those of individual afferents, they transmitted less information. In addition, their velocity detection thresholds were significantly greater than those of individual afferents. This is because VO neurons display greater variability, which is detrimental to information transmission and signal detection. Combining activities from multiple VO neurons increased information transmission. However, the information rates were still much lower than those of equivalent afferent populations. Furthermore, combining responses from multiple VO neurons led to lower velocity detection threshold values approaching those measured from behavior (∼2.5 vs. 0.5–1°/s). Our results suggest that the detailed time course of vestibular stimuli encoded by afferents is not transmitted by VO neurons. Instead, they suggest that higher vestibular pathways must integrate information from central vestibular neuron populations to give rise to behaviorally observed detection thresholds. PMID:21307329

A fast BK-type KCa current acts as a postsynaptic modulator of temporal selectivity for communication signals.

PubMed

Kohashi, Tsunehiko; Carlson, Bruce A

2014-01-01

Temporal patterns of spiking often convey behaviorally relevant information. Various synaptic mechanisms and intrinsic membrane properties can influence neuronal selectivity to temporal patterns of input. However, little is known about how synaptic mechanisms and intrinsic properties together determine the temporal selectivity of neuronal output. We tackled this question by recording from midbrain electrosensory neurons in mormyrid fish, in which the processing of temporal intervals between communication signals can be studied in a reduced in vitro preparation. Mormyrids communicate by varying interpulse intervals (IPIs) between electric pulses. Within the midbrain posterior exterolateral nucleus (ELp), the temporal patterns of afferent spike trains are filtered to establish single-neuron IPI tuning. We performed whole-cell recording from ELp neurons in a whole-brain preparation and examined the relationship between intrinsic excitability and IPI tuning. We found that spike frequency adaptation of ELp neurons was highly variable. Postsynaptic potentials (PSPs) of strongly adapting (phasic) neurons were more sharply tuned to IPIs than weakly adapting (tonic) neurons. Further, the synaptic filtering of IPIs by tonic neurons was more faithfully converted into variation in spiking output, particularly at short IPIs. Pharmacological manipulation under current- and voltage-clamp revealed that tonic firing is mediated by a fast, large-conductance Ca(2+)-activated K(+) (KCa) current (BK) that speeds up action potential repolarization. These results suggest that BK currents can shape the temporal filtering of sensory inputs by modifying both synaptic responses and PSP-to-spike conversion. Slow SK-type KCa currents have previously been implicated in temporal processing. Thus, both fast and slow KCa currents can fine-tune temporal selectivity.

Laterodorsal Nucleus of the Thalamus: A Processor of Somatosensory Inputs

PubMed Central

BEZDUDNAYA, TATIANA; KELLER, ASAF

2009-01-01

The laterodorsal (LD) nucleus of the thalamus has been considered a “higher order” nucleus that provides inputs to limbic cortical areas. Although its functions are largely unknown, it is often considered to be involved in spatial learning and memory. Here we provide evidence that LD is part of a hitherto unknown pathway for processing somatosensory information. Juxtacellular and extracellular recordings from LD neurons reveal that they respond to vibrissa stimulation with short latency (median = 7 ms) and large magnitude responses (median = 1.2 spikes/stimulus). Most neurons (62%) had large receptive fields, responding to six and more individual vibrissae. Electrical stimulation of the trigeminal nucleus interpolaris (SpVi) evoked short latency responses (median = 3.8 ms) in vibrissa-responsive LD neurons. Labeling produced by anterograde and retrograde neuroanatomical tracers confirmed that LD neurons receive direct inputs from SpVi. Electrophysiological and neuroanatomical analyses revealed also that LD projects upon the cingulate and retrosplenial cortex, but has only sparse projections to the barrel cortex. These findings suggest that LD is part of a novel processing stream involved in spatial orientation and learning related to somatosensory cues. PMID:18273888

Common key-signals in learning and neurodegeneration: focus on excito-amino acids, beta-amyloid peptides and alpha-synuclein.

PubMed

Agnati, L F; Leo, G; Genedani, S; Piron, L; Rivera, A; Guidolin, D; Fuxe, K

2009-08-01

In this paper a hypothesis that some special signals ("key-signals" excito-amino acids, beta-amyloid peptides and alpha-synuclein) are not only involved in information handling by the neuronal circuits, but also trigger out substantial structural and/or functional changes in the Central Nervous System (CNS) is introduced. This forces the neuronal circuits to move from one stable state towards a new state, but in doing so these signals became potentially dangerous. Several mechanisms are put in action to protect neurons and glial cells from these potentially harmful signals. However, in agreement with the Red Queen Theory of Ageing (Agnati et al. in Acta Physiol Scand 145:301-309, 1992), it is proposed that during ageing these neuroprotective processes become less effective while, in the meantime, a shortage of brain plasticity occurs together with an increased need of plasticity for repairing the wear and tear of the CNS. The paper presents findings supporting the concept that such key-signals in instances such as ageing may favour neurodegenerative processes in an attempt of maximizing neuronal plasticity.

Visual pattern recognition based on spatio-temporal patterns of retinal ganglion cells’ activities

PubMed Central

Jing, Wei; Liu, Wen-Zhong; Gong, Xin-Wei; Gong, Hai-Qing

2010-01-01

Neural information is processed based on integrated activities of relevant neurons. Concerted population activity is one of the important ways for retinal ganglion cells to efficiently organize and process visual information. In the present study, the spike activities of bullfrog retinal ganglion cells in response to three different visual patterns (checker-board, vertical gratings and horizontal gratings) were recorded using multi-electrode arrays. A measurement of subsequence distribution discrepancy (MSDD) was applied to identify the spatio-temporal patterns of retinal ganglion cells’ activities in response to different stimulation patterns. The results show that the population activity patterns were different in response to different stimulation patterns, such difference in activity pattern was consistently detectable even when visual adaptation occurred during repeated experimental trials. Therefore, the stimulus pattern can be reliably discriminated according to the spatio-temporal pattern of the neuronal activities calculated using the MSDD algorithm. PMID:21886670

Temporal Interactions between Cortical Rhythms

PubMed Central

Roopun, Anita K.; Kramer, Mark A.; Carracedo, Lucy M.; Kaiser, Marcus; Davies, Ceri H.; Traub, Roger D.; Kopell, Nancy J.; Whittington, Miles A.

2008-01-01

Multiple local neuronal circuits support different, discrete frequencies of network rhythm in neocortex. Relationships between different frequencies correspond to mechanisms designed to minimise interference, couple activity via stable phase interactions, and control the amplitude of one frequency relative to the phase of another. These mechanisms are proposed to form a framework for spectral information processing. Individual local circuits can also transform their frequency through changes in intrinsic neuronal properties and interactions with other oscillating microcircuits. Here we discuss a frequency transformation in which activity in two co-active local circuits may combine sequentially to generate a third frequency whose period is the concatenation sum of the original two. With such an interaction, the intrinsic periodicity in each component local circuit is preserved – alternate, single periods of each original rhythm form one period of a new frequency – suggesting a robust mechanism for combining information processed on multiple concurrent spatiotemporal scales. PMID:19225587

Effects of channel blocking on information transmission and energy efficiency in squid giant axons.

PubMed

Liu, Yujiang; Yue, Yuan; Yu, Yuguo; Liu, Liwei; Yu, Lianchun

2018-04-01

Action potentials are the information carriers of neural systems. The generation of action potentials involves the cooperative opening and closing of sodium and potassium channels. This process is metabolically expensive because the ions flowing through open channels need to be restored to maintain concentration gradients of these ions. Toxins like tetraethylammonium can block working ion channels, thus affecting the function and energy cost of neurons. In this paper, by computer simulation of the Hodgkin-Huxley neuron model, we studied the effects of channel blocking with toxins on the information transmission and energy efficiency in squid giant axons. We found that gradually blocking sodium channels will sequentially maximize the information transmission and energy efficiency of the axons, whereas moderate blocking of potassium channels will have little impact on the information transmission and will decrease the energy efficiency. Heavy blocking of potassium channels will cause self-sustained oscillation of membrane potentials. Simultaneously blocking sodium and potassium channels with the same ratio increases both information transmission and energy efficiency. Our results are in line with previous studies suggesting that information processing capacity and energy efficiency can be maximized by regulating the number of active ion channels, and this indicates a viable avenue for future experimentation.

Visual Stimuli Evoked Action Potentials Trigger Rapidly Propagating Dendritic Calcium Transients in the Frog Optic Tectum Layer 6 Neurons.

PubMed

Svirskis, Gytis; Baranauskas, Gytis; Svirskiene, Natasa; Tkatch, Tatiana

2015-01-01

The superior colliculus in mammals or the optic tectum in amphibians is a major visual information processing center responsible for generation of orientating responses such as saccades in monkeys or prey catching avoidance behavior in frogs. The conserved structure function of the superior colliculus the optic tectum across distant species such as frogs, birds monkeys permits to draw rather general conclusions after studying a single species. We chose the frog optic tectum because we are able to perform whole-cell voltage-clamp recordings fluorescence imaging of tectal neurons while they respond to a visual stimulus. In the optic tectum of amphibians most visual information is processed by pear-shaped neurons possessing long dendritic branches, which receive the majority of synapses originating from the retinal ganglion cells. Since the first step of the retinal input integration is performed on these dendrites, it is important to know whether this integration is enhanced by active dendritic properties. We demonstrate that rapid calcium transients coinciding with the visual stimulus evoked action potentials in the somatic recordings can be readily detected up to the fine branches of these dendrites. These transients were blocked by calcium channel blockers nifedipine CdCl2 indicating that calcium entered dendrites via voltage-activated L-type calcium channels. The high speed of calcium transient propagation, >300 μm in <10 ms, is consistent with the notion that action potentials, actively propagating along dendrites, open voltage-gated L-type calcium channels causing rapid calcium concentration transients in the dendrites. We conclude that such activation by somatic action potentials of the dendritic voltage gated calcium channels in the close vicinity to the synapses formed by axons of the retinal ganglion cells may facilitate visual information processing in the principal neurons of the frog optic tectum.

Burst Firing is a Neural Code in an Insect Auditory System

PubMed Central

Eyherabide, Hugo G.; Rokem, Ariel; Herz, Andreas V. M.; Samengo, Inés

2008-01-01

Various classes of neurons alternate between high-frequency discharges and silent intervals. This phenomenon is called burst firing. To analyze burst activity in an insect system, grasshopper auditory receptor neurons were recorded in vivo for several distinct stimulus types. The experimental data show that both burst probability and burst characteristics are strongly influenced by temporal modulations of the acoustic stimulus. The tendency to burst, hence, is not only determined by cell-intrinsic processes, but also by their interaction with the stimulus time course. We study this interaction quantitatively and observe that bursts containing a certain number of spikes occur shortly after stimulus deflections of specific intensity and duration. Our findings suggest a sparse neural code where information about the stimulus is represented by the number of spikes per burst, irrespective of the detailed interspike-interval structure within a burst. This compact representation cannot be interpreted as a firing-rate code. An information-theoretical analysis reveals that the number of spikes per burst reliably conveys information about the amplitude and duration of sound transients, whereas their time of occurrence is reflected by the burst onset time. The investigated neurons encode almost half of the total transmitted information in burst activity. PMID:18946533

Noise in any frequency range can enhance information transmission in a sensory neuron

NASA Astrophysics Data System (ADS)

Levin, Jacob E.

1997-05-01

The effect of noise on the neural encoding of broadband signals was investigated in the cricket cercal system, a mechanosensory system sensitive to small near-field air particle disturbances. Known air current stimuli were presented to the cricket through audio speakers in a controlled environment in a variety of background noise conditions. Spike trains from the second layer of neuronal processing, the primary sensory interneurons, were recorded with intracellular Electrodes and the performance of these neurons characterized with the tools of information theory. SNR, mutual information rates, and other measures of encoding accuracy were calculated for single frequency, narrowband, and broadband signals over the entire amplitude sensitivity range of the cells, in the presence of uncorrelated noise background also spanning the cells' frequency and amplitude sensitivity range. Significant enhancements of transmitted information through the addition of external noise were observed regardless of the frequency range of either the signal or noise waveforms, provided both were within the operating range of the cell. Considerable improvements in signal encoding were observed for almost an entire order of magnitude of near-threshold signal amplitudes. This included sinusoidal signals embedded in broadband white noise, broadband signals in broadband noise, and even broadband signals presented with narrowband noise in a completely non-overlapping frequency range. The noise related increases in mutual information rate for broadband signals were as high as 150%, and up to 600% increases in SNR were observed for sinusoidal signals. Additionally, it was shown that the amount of information about the signal carried, on average, by each spike was INCREASED for small signals when presented with noise—implying that added input noise can, in certain situations, actually improve the accuracy of the encoding process itself.

All-memristive neuromorphic computing with level-tuned neurons

NASA Astrophysics Data System (ADS)

Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

2016-09-01

In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

All-memristive neuromorphic computing with level-tuned neurons.

PubMed

Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

2016-09-02

In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

Olivary subthreshold oscillations and burst activity revisited

PubMed Central

Bazzigaluppi, Paolo; De Gruijl, Jornt R.; van der Giessen, Ruben S.; Khosrovani, Sara; De Zeeuw, Chris I.; de Jeu, Marcel T. G.

2012-01-01

The inferior olive (IO) forms one of the major gateways for information that travels to the cerebellar cortex. Olivary neurons process sensory and motor signals that are subsequently relayed to Purkinje cells. The intrinsic subthreshold membrane potential oscillations of the olivary neurons are thought to be important for gating this flow of information. In vitro studies have revealed that the phase of the subthreshold oscillation determines the size of the olivary burst and may gate the information flow or encode the temporal state of the olivary network. Here, we investigated whether the same phenomenon occurred in murine olivary cells in an intact olivocerebellar system using the in vivo whole-cell recording technique. Our in vivo findings revealed that the number of wavelets within the olivary burst did not encode the timing of the spike relative to the phase of the oscillation but was related to the amplitude of the oscillation. Manipulating the oscillation amplitude by applying Harmaline confirmed the inverse relationship between the amplitude of oscillation and the number of wavelets within the olivary burst. Furthermore, we demonstrated that electrotonic coupling between olivary neurons affect this modulation of the olivary burst size. Based on these results, we suggest that the olivary burst size might reflect the “expectancy” of a spike to occur rather than the spike timing, and that this process requires the presence of gap junction coupling. PMID:23189043

Computational Model of Primary Visual Cortex Combining Visual Attention for Action Recognition

PubMed Central

Shu, Na; Gao, Zhiyong; Chen, Xiangan; Liu, Haihua

2015-01-01

Humans can easily understand other people’s actions through visual systems, while computers cannot. Therefore, a new bio-inspired computational model is proposed in this paper aiming for automatic action recognition. The model focuses on dynamic properties of neurons and neural networks in the primary visual cortex (V1), and simulates the procedure of information processing in V1, which consists of visual perception, visual attention and representation of human action. In our model, a family of the three-dimensional spatial-temporal correlative Gabor filters is used to model the dynamic properties of the classical receptive field of V1 simple cell tuned to different speeds and orientations in time for detection of spatiotemporal information from video sequences. Based on the inhibitory effect of stimuli outside the classical receptive field caused by lateral connections of spiking neuron networks in V1, we propose surround suppressive operator to further process spatiotemporal information. Visual attention model based on perceptual grouping is integrated into our model to filter and group different regions. Moreover, in order to represent the human action, we consider the characteristic of the neural code: mean motion map based on analysis of spike trains generated by spiking neurons. The experimental evaluation on some publicly available action datasets and comparison with the state-of-the-art approaches demonstrate the superior performance of the proposed model. PMID:26132270

A simplified computational memory model from information processing

PubMed Central

Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

2016-01-01

This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view. PMID:27876847

Functional Imaging of Retinal Photoreceptors and Inner Neurons Using Stimulus-Evoked Intrinsic Optical Signals

PubMed Central

Yao, Xin-Cheng; Li, Yi-Chao

2013-01-01

Retinal development is a dynamic process both anatomically and functionally. High-resolution imaging and dynamic monitoring of photoreceptors and inner neurons can provide important information regarding the structure and function of the developing retina. In this chapter, we describe intrinsic optical signal (IOS) imaging as a high spatiotemporal resolution method for functional study of living retinal tissues. IOS imaging is based on near infrared (NIR) light detection of stimulus-evoked transient change of inherent optical characteristics of the cells. With no requirement for exogenous biomarkers, IOS imaging is totally noninvasive for functional mapping of stimulus-evoked spatiotemporal dynamics of the photoreceptors and inner retinal neurons. PMID:22688714

Back to Pupillometry: How Cortical Network State Fluctuations Tracked by Pupil Dynamics Could Explain Neural Signal Variability in Human Cognitive Neuroscience

PubMed Central

2017-01-01

Abstract The mammalian thalamocortical system generates intrinsic activity reflecting different states of excitability, arising from changes in the membrane potentials of underlying neuronal networks. Fluctuations between these states occur spontaneously, regularly, and frequently throughout awake periods and influence stimulus encoding, information processing, and neuronal and behavioral responses. Changes of pupil size have recently been identified as a reliable marker of underlying neuronal membrane potential and thus can encode associated network state changes in rodent cortex. This suggests that pupillometry, a ubiquitous measure of pupil dilation in cognitive neuroscience, could be used as an index for network state fluctuations also for human brain signals. Considering this variable may explain task-independent variance in neuronal and behavioral signals that were previously disregarded as noise. PMID:29379876

Channel noise-induced temporal coherence transitions and synchronization transitions in adaptive neuronal networks with time delay

NASA Astrophysics Data System (ADS)

Gong, Yubing; Xie, Huijuan

2017-09-01

Using spike-timing-dependent plasticity (STDP), we study the effect of channel noise on temporal coherence and synchronization of adaptive scale-free Hodgkin-Huxley neuronal networks with time delay. It is found that the spiking regularity and spatial synchronization of the neurons intermittently increase and decrease as channel noise intensity is varied, exhibiting transitions of temporal coherence and synchronization. Moreover, this phenomenon depends on time delay, STDP, and network average degree. As time delay increases, the phenomenon is weakened, however, there are optimal STDP and network average degree by which the phenomenon becomes strongest. These results show that channel noise can intermittently enhance the temporal coherence and synchronization of the delayed adaptive neuronal networks. These findings provide a new insight into channel noise for the information processing and transmission in neural systems.

Retinoid-Related Orphan Receptor β and Transcriptional Control of Neuronal Differentiation.

PubMed

Liu, Hong; Aramaki, Michihiko; Fu, Yulong; Forrest, Douglas

2017-01-01

The ability to generate neuronal diversity is central to the function of the nervous system. Here we discuss the key neurodevelopmental roles of retinoid-related orphan receptor β (RORβ) encoded by the Rorb (Nr1f2) gene. Recent studies have reported loss of function of the human RORB gene in cases of familial epilepsy and intellectual disability. Principal sites of expression of the Rorb gene in model species include sensory organs, the spinal cord, and brain regions that process sensory and circadian information. Genetic analyses in mice have indicated functions in circadian behavior, vision, and, at the cellular level, the differentiation of specific neuronal cell types. Studies in the retina and sensory areas of the cerebral cortex suggest that this orphan nuclear receptor acts at decisive steps in transcriptional hierarchies that determine neuronal diversity. 2017 Published by Elsevier Inc.

The Mechanism for Processing Random-Dot Motion at Various Speeds in Early Visual Cortices

PubMed Central

An, Xu; Gong, Hongliang; McLoughlin, Niall; Yang, Yupeng; Wang, Wei

2014-01-01

All moving objects generate sequential retinotopic activations representing a series of discrete locations in space and time (motion trajectory). How direction-selective neurons in mammalian early visual cortices process motion trajectory remains to be clarified. Using single-cell recording and optical imaging of intrinsic signals along with mathematical simulation, we studied response properties of cat visual areas 17 and 18 to random dots moving at various speeds. We found that, the motion trajectory at low speed was encoded primarily as a direction signal by groups of neurons preferring that motion direction. Above certain transition speeds, the motion trajectory is perceived as a spatial orientation representing the motion axis of the moving dots. In both areas studied, above these speeds, other groups of direction-selective neurons with perpendicular direction preferences were activated to encode the motion trajectory as motion-axis information. This applied to both simple and complex neurons. The average transition speed for switching between encoding motion direction and axis was about 31°/s in area 18 and 15°/s in area 17. A spatio-temporal energy model predicted the transition speeds accurately in both areas, but not the direction-selective indexes to random-dot stimuli in area 18. In addition, above transition speeds, the change of direction preferences of population responses recorded by optical imaging can be revealed using vector maximum but not vector summation method. Together, this combined processing of motion direction and axis by neurons with orthogonal direction preferences associated with speed may serve as a common principle of early visual motion processing. PMID:24682033

Amyloid precursor protein expression and processing are differentially regulated during cortical neuron differentiation.

PubMed

Bergström, Petra; Agholme, Lotta; Nazir, Faisal Hayat; Satir, Tugce Munise; Toombs, Jamie; Wellington, Henrietta; Strandberg, Joakim; Bontell, Thomas Olsson; Kvartsberg, Hlin; Holmström, Maria; Boreström, Cecilia; Simonsson, Stina; Kunath, Tilo; Lindahl, Anders; Blennow, Kaj; Hanse, Eric; Portelius, Erik; Wray, Selina; Zetterberg, Henrik

2016-07-07

Amyloid precursor protein (APP) and its cleavage product amyloid β (Aβ) have been thoroughly studied in Alzheimer's disease. However, APP also appears to be important for neuronal development. Differentiation of induced pluripotent stem cells (iPSCs) towards cortical neurons enables in vitro mechanistic studies on human neuronal development. Here, we investigated expression and proteolytic processing of APP during differentiation of human iPSCs towards cortical neurons over a 100-day period. APP expression remained stable during neuronal differentiation, whereas APP processing changed. α-Cleaved soluble APP (sAPPα) was secreted early during differentiation, from neuronal progenitors, while β-cleaved soluble APP (sAPPβ) was first secreted after deep-layer neurons had formed. Short Aβ peptides, including Aβ1-15/16, peaked during the progenitor stage, while processing shifted towards longer peptides, such as Aβ1-40/42, when post-mitotic neurons appeared. This indicates that APP processing is regulated throughout differentiation of cortical neurons and that amyloidogenic APP processing, as reflected by Aβ1-40/42, is associated with mature neuronal phenotypes.

Axonal Conduction Delays, Brain State, and Corticogeniculate Communication.

PubMed

Stoelzel, Carl R; Bereshpolova, Yulia; Alonso, Jose-Manuel; Swadlow, Harvey A

2017-06-28

Thalamocortical conduction times are short, but layer 6 corticothalamic axons display an enormous range of conduction times, some exceeding 40-50 ms. Here, we investigate (1) how axonal conduction times of corticogeniculate (CG) neurons are related to the visual information conveyed to the thalamus, and (2) how alert versus nonalert awake brain states affect visual processing across the spectrum of CG conduction times. In awake female Dutch-Belted rabbits, we found 58% of CG neurons to be visually responsive, and 42% to be unresponsive. All responsive CG neurons had simple, orientation-selective receptive fields, and generated sustained responses to stationary stimuli. CG axonal conduction times were strongly related to modulated firing rates (F1 values) generated by drifting grating stimuli, and their associated interspike interval distributions, suggesting a continuum of visual responsiveness spanning the spectrum of axonal conduction times. CG conduction times were also significantly related to visual response latency, contrast sensitivity (C-50 values), directional selectivity, and optimal stimulus velocity. Increasing alertness did not cause visually unresponsive CG neurons to become responsive and did not change the response linearity (F1/F0 ratios) of visually responsive CG neurons. However, for visually responsive CG neurons, increased alertness nearly doubled the modulated response amplitude to optimal visual stimulation (F1 values), significantly shortened response latency, and dramatically increased response reliability. These effects of alertness were uniform across the broad spectrum of CG axonal conduction times. SIGNIFICANCE STATEMENT Corticothalamic neurons of layer 6 send a dense feedback projection to thalamic nuclei that provide input to sensory neocortex. While sensory information reaches the cortex after brief thalamocortical axonal delays, corticothalamic axons can exhibit conduction delays of <2 ms to 40-50 ms. Here, in the corticogeniculate visual system of awake rabbits, we investigate the functional significance of this axonal diversity, and the effects of shifting alert/nonalert brain states on corticogeniculate processing. We show that axonal conduction times are strongly related to multiple visual response properties, suggesting a continuum of visual responsiveness spanning the spectrum of corticogeniculate axonal conduction times. We also show that transitions between awake brain states powerfully affect corticogeniculate processing, in some ways more strongly than in layer 4. Copyright © 2017 the authors 0270-6474/17/376342-17$15.00/0.

The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields

PubMed Central

Deco, Gustavo; Jirsa, Viktor K.; Robinson, Peter A.; Breakspear, Michael; Friston, Karl

2008-01-01

The cortex is a complex system, characterized by its dynamics and architecture, which underlie many functions such as action, perception, learning, language, and cognition. Its structural architecture has been studied for more than a hundred years; however, its dynamics have been addressed much less thoroughly. In this paper, we review and integrate, in a unifying framework, a variety of computational approaches that have been used to characterize the dynamics of the cortex, as evidenced at different levels of measurement. Computational models at different space–time scales help us understand the fundamental mechanisms that underpin neural processes and relate these processes to neuroscience data. Modeling at the single neuron level is necessary because this is the level at which information is exchanged between the computing elements of the brain; the neurons. Mesoscopic models tell us how neural elements interact to yield emergent behavior at the level of microcolumns and cortical columns. Macroscopic models can inform us about whole brain dynamics and interactions between large-scale neural systems such as cortical regions, the thalamus, and brain stem. Each level of description relates uniquely to neuroscience data, from single-unit recordings, through local field potentials to functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and magnetoencephalogram (MEG). Models of the cortex can establish which types of large-scale neuronal networks can perform computations and characterize their emergent properties. Mean-field and related formulations of dynamics also play an essential and complementary role as forward models that can be inverted given empirical data. This makes dynamic models critical in integrating theory and experiments. We argue that elaborating principled and informed models is a prerequisite for grounding empirical neuroscience in a cogent theoretical framework, commensurate with the achievements in the physical sciences. PMID:18769680

Interactions between superficial and deep dorsal horn spinal cord neurons in the processing of nociceptive information.

PubMed

Petitjean, Hugues; Rodeau, Jean-Luc; Schlichter, Rémy

2012-12-01

In acute rat spinal cord slices, the application of capsaicin (5 μm, 90 s), an agonist of transient receptor potential vanilloid 1 receptors expressed by a subset of nociceptors that project to laminae I-II of the spinal cord dorsal horn, induced an increase in the frequency of spontaneous excitatory and spontaneous inhibitory postsynaptic currents in about half of the neurons in laminae II, III-IV and V. In the presence of tetrodotoxin, which blocks action potential generation and polysynaptic transmission, capsaicin increased the frequency of miniature excitatory postsynaptic currents in only 30% of lamina II neurons and had no effect on the frequency of miniature excitatory postsynaptic currents in laminae III-V or on the frequency of miniature inhibitory postsynaptic currents in laminae II-V. When the communication between lamina V and more superficial laminae was interrupted by performing a mechanical section between laminae IV and V, capsaicin induced an increase in spontaneous excitatory postsynaptic current frequency in laminae II-IV and an increase in spontaneous inhibitory postsynaptic current frequency in lamina II that were similar to those observed in intact slices. However, in laminae III-IV of transected slices, the increase in spontaneous inhibitory postsynaptic current frequency was virtually abolished. Our results indicate that nociceptive information conveyed by transient receptor potential vanilloid 1-expressing nociceptors is transmitted from lamina II to deeper laminae essentially by an excitatory pathway and that deep laminae exert a 'feedback' control over neurons in laminae III-IV by increasing inhibitory synaptic transmission in these laminae. Moreover, we provide evidence that laminae III-IV might play an important role in the processing of nociceptive information in the dorsal horn. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Spatiotemporal Coding of Individual Chemicals by the Gustatory System

PubMed Central

Reiter, Sam; Campillo Rodriguez, Chelsey; Sun, Kui

2015-01-01

Four of the five major sensory systems (vision, olfaction, somatosensation, and audition) are thought to use different but partially overlapping sets of neurons to form unique representations of vast numbers of stimuli. The only exception is gustation, which is thought to represent only small numbers of basic taste categories. However, using new methods for delivering tastant chemicals and making electrophysiological recordings from the tractable gustatory system of the moth Manduca sexta, we found chemical-specific information is as follows: (1) initially encoded in the population of gustatory receptor neurons as broadly distributed spatiotemporal patterns of activity; (2) dramatically integrated and temporally transformed as it propagates to monosynaptically connected second-order neurons; and (3) observed in tastant-specific behavior. Our results are consistent with an emerging view of the gustatory system: rather than constructing basic taste categories, it uses a spatiotemporal population code to generate unique neural representations of individual tastant chemicals. SIGNIFICANCE STATEMENT Our results provide a new view of taste processing. Using a new, relatively simple model system and a new set of techniques to deliver taste stimuli and to examine gustatory receptor neurons and their immediate followers, we found no evidence for labeled line connectivity, or basic taste categories such as sweet, salty, bitter, and sour. Rather, individual tastant chemicals are represented as patterns of spiking activity distributed across populations of receptor neurons. These representations are transformed substantially as multiple types of receptor neurons converge upon follower neurons, leading to a combinatorial coding format that uniquely, rapidly, and efficiently represents individual taste chemicals. Finally, we found that the information content of these neurons can drive tastant-specific behavior. PMID:26338341

Spatiotemporal Coding of Individual Chemicals by the Gustatory System.

PubMed

Reiter, Sam; Campillo Rodriguez, Chelsey; Sun, Kui; Stopfer, Mark

2015-09-02

Four of the five major sensory systems (vision, olfaction, somatosensation, and audition) are thought to use different but partially overlapping sets of neurons to form unique representations of vast numbers of stimuli. The only exception is gustation, which is thought to represent only small numbers of basic taste categories. However, using new methods for delivering tastant chemicals and making electrophysiological recordings from the tractable gustatory system of the moth Manduca sexta, we found chemical-specific information is as follows: (1) initially encoded in the population of gustatory receptor neurons as broadly distributed spatiotemporal patterns of activity; (2) dramatically integrated and temporally transformed as it propagates to monosynaptically connected second-order neurons; and (3) observed in tastant-specific behavior. Our results are consistent with an emerging view of the gustatory system: rather than constructing basic taste categories, it uses a spatiotemporal population code to generate unique neural representations of individual tastant chemicals. Our results provide a new view of taste processing. Using a new, relatively simple model system and a new set of techniques to deliver taste stimuli and to examine gustatory receptor neurons and their immediate followers, we found no evidence for labeled line connectivity, or basic taste categories such as sweet, salty, bitter, and sour. Rather, individual tastant chemicals are represented as patterns of spiking activity distributed across populations of receptor neurons. These representations are transformed substantially as multiple types of receptor neurons converge upon follower neurons, leading to a combinatorial coding format that uniquely, rapidly, and efficiently represents individual taste chemicals. Finally, we found that the information content of these neurons can drive tastant-specific behavior. Copyright © 2015 the authors 0270-6474/15/3512309-13$15.00/0.

Loss of Balance between Striatal Feedforward Inhibition and Corticostriatal Excitation Leads to Tremor.

PubMed

Oran, Yael; Bar-Gad, Izhar

2018-02-14

Fast-spiking interneurons (FSIs) exert powerful inhibitory control over the striatum and are hypothesized to balance the massive excitatory cortical and thalamic input to this structure. We recorded neuronal activity in the dorsolateral striatum and globus pallidus (GP) concurrently with the detailed movement kinematics of freely behaving female rats before and after selective inhibition of FSI activity using IEM-1460 microinjections. The inhibition led to the appearance of episodic rest tremor in the body part that depended on the somatotopic location of the injection within the striatum. The tremor was accompanied by coherent oscillations in the local field potential (LFP). Individual neuron activity patterns became oscillatory and coherent in the tremor frequency. Striatal neurons, but not GP neurons, displayed additional temporal, nonoscillatory correlations. The subsequent reduction in the corticostriatal input following muscimol injection to the corresponding somatotopic location in the primary motor cortex led to disruption of the tremor and a reduction of the LFP oscillations and individual neuron's phase-locked activity. The breakdown of the normal balance of excitation and inhibition in the striatum has been shown previously to be related to different motor abnormalities. Our results further indicate that the balance between excitatory corticostriatal input and feedforward FSI inhibition is sufficient to break down the striatal decorrelation process and generate oscillations resulting in rest tremor typical of multiple basal ganglia disorders. SIGNIFICANCE STATEMENT Fast-spiking interneurons (FSIs) play a key role in normal striatal processing by exerting powerful inhibitory control over the network. FSI malfunctions have been associated with abnormal processing of information within the striatum that leads to multiple movement disorders. Here, we study the changes in neuronal activity and movement kinematics following selective inhibition of these neurons. The injections led to the appearance of episodic rest tremor, accompanied by coherent oscillations in neuronal activity, which was reversed following corticostriatal inhibition. These results suggest that the balance between corticostriatal excitation and feedforward FSI inhibition is crucial for maintaining the striatal decorrelation process, and that its breakdown leads to the formation of oscillations resulting in rest tremor typical of multiple basal ganglia disorders. Copyright © 2018 the authors 0270-6474/18/381699-12$15.00/0.

Neuron-Like Networks Between Ribosomal Proteins Within the Ribosome

NASA Astrophysics Data System (ADS)

Poirot, Olivier; Timsit, Youri

2016-05-01

From brain to the World Wide Web, information-processing networks share common scale invariant properties. Here, we reveal the existence of neural-like networks at a molecular scale within the ribosome. We show that with their extensions, ribosomal proteins form complex assortative interaction networks through which they communicate through tiny interfaces. The analysis of the crystal structures of 50S eubacterial particles reveals that most of these interfaces involve key phylogenetically conserved residues. The systematic observation of interactions between basic and aromatic amino acids at the interfaces and along the extension provides new structural insights that may contribute to decipher the molecular mechanisms of signal transmission within or between the ribosomal proteins. Similar to neurons interacting through “molecular synapses”, ribosomal proteins form a network that suggest an analogy with a simple molecular brain in which the “sensory-proteins” innervate the functional ribosomal sites, while the “inter-proteins” interconnect them into circuits suitable to process the information flow that circulates during protein synthesis. It is likely that these circuits have evolved to coordinate both the complex macromolecular motions and the binding of the multiple factors during translation. This opens new perspectives on nanoscale information transfer and processing.

Vasculo-Neuronal Coupling: Retrograde Vascular Communication to Brain Neurons.

PubMed

Kim, Ki Jung; Ramiro Diaz, Juan; Iddings, Jennifer A; Filosa, Jessica A

2016-12-14

Continuous cerebral blood flow is essential for neuronal survival, but whether vascular tone influences resting neuronal function is not known. Using a multidisciplinary approach in both rat and mice brain slices, we determined whether flow/pressure-evoked increases or decreases in parenchymal arteriole vascular tone, which result in arteriole constriction and dilation, respectively, altered resting cortical pyramidal neuron activity. We present evidence for intercellular communication in the brain involving a flow of information from vessel to astrocyte to neuron, a direction opposite to that of classic neurovascular coupling and referred to here as vasculo-neuronal coupling (VNC). Flow/pressure increases within parenchymal arterioles increased vascular tone and simultaneously decreased resting pyramidal neuron firing activity. On the other hand, flow/pressure decreases evoke parenchymal arteriole dilation and increased resting pyramidal neuron firing activity. In GLAST-CreERT2; R26-lsl-GCaMP3 mice, we demonstrate that increased parenchymal arteriole tone significantly increased intracellular calcium in perivascular astrocyte processes, the onset of astrocyte calcium changes preceded the inhibition of cortical pyramidal neuronal firing activity. During increases in parenchymal arteriole tone, the pyramidal neuron response was unaffected by blockers of nitric oxide, GABA A , glutamate, or ecto-ATPase. However, VNC was abrogated by TRPV4 channel, GABA B , as well as an adenosine A 1 receptor blocker. Differently to pyramidal neuron responses, increases in flow/pressure within parenchymal arterioles increased the firing activity of a subtype of interneuron. Together, these data suggest that VNC is a complex constitutive active process that enables neurons to efficiently adjust their resting activity according to brain perfusion levels, thus safeguarding cellular homeostasis by preventing mismatches between energy supply and demand. We present evidence for vessel-to-neuron communication in the brain slice defined here as vasculo-neuronal coupling. We showed that, in response to increases in parenchymal arteriole tone, astrocyte intracellular Ca 2+ increased and cortical neuronal activity decreased. On the other hand, decreasing parenchymal arteriole tone increased resting cortical pyramidal neuron activity. Vasculo-neuronal coupling was partly mediated by TRPV4 channels as genetic ablation, or pharmacological blockade impaired increased flow/pressure-evoked neuronal inhibition. Increased flow/pressure-evoked neuronal inhibition was blocked in the presence of adenosine A1 receptor and GABA B receptor blockade. Results provide evidence for the concept of vasculo-neuronal coupling and highlight the importance of understanding the interplay between basal CBF and resting neuronal activity. Copyright © 2016 the authors 0270-6474/16/3612624-16$15.00/0.

Temporal integration at consecutive processing stages in the auditory pathway of the grasshopper.

PubMed

Wirtssohn, Sarah; Ronacher, Bernhard

2015-04-01

Temporal integration in the auditory system of locusts was quantified by presenting single clicks and click pairs while performing intracellular recordings. Auditory neurons were studied at three processing stages, which form a feed-forward network in the metathoracic ganglion. Receptor neurons and most first-order interneurons ("local neurons") encode the signal envelope, while second-order interneurons ("ascending neurons") tend to extract more complex, behaviorally relevant sound features. In different neuron types of the auditory pathway we found three response types: no significant temporal integration (some ascending neurons), leaky energy integration (receptor neurons and some local neurons), and facilitatory processes (some local and ascending neurons). The receptor neurons integrated input over very short time windows (<2 ms). Temporal integration on longer time scales was found at subsequent processing stages, indicative of within-neuron computations and network activity. These different strategies, realized at separate processing stages and in parallel neuronal pathways within one processing stage, could enable the grasshopper's auditory system to evaluate longer time windows and thus to implement temporal filters, while at the same time maintaining a high temporal resolution. Copyright © 2015 the American Physiological Society.

Temporal Processing in the Visual Cortex of the Awake and Anesthetized Rat.

PubMed

Aasebø, Ida E J; Lepperød, Mikkel E; Stavrinou, Maria; Nøkkevangen, Sandra; Einevoll, Gaute; Hafting, Torkel; Fyhn, Marianne

2017-01-01

The activity pattern and temporal dynamics within and between neuron ensembles are essential features of information processing and believed to be profoundly affected by anesthesia. Much of our general understanding of sensory information processing, including computational models aimed at mathematically simulating sensory information processing, rely on parameters derived from recordings conducted on animals under anesthesia. Due to the high variety of neuronal subtypes in the brain, population-based estimates of the impact of anesthesia may conceal unit- or ensemble-specific effects of the transition between states. Using chronically implanted tetrodes into primary visual cortex (V1) of rats, we conducted extracellular recordings of single units and followed the same cell ensembles in the awake and anesthetized states. We found that the transition from wakefulness to anesthesia involves unpredictable changes in temporal response characteristics. The latency of single-unit responses to visual stimulation was delayed in anesthesia, with large individual variations between units. Pair-wise correlations between units increased under anesthesia, indicating more synchronized activity. Further, the units within an ensemble show reproducible temporal activity patterns in response to visual stimuli that is changed between states, suggesting state-dependent sequences of activity. The current dataset, with recordings from the same neural ensembles across states, is well suited for validating and testing computational network models. This can lead to testable predictions, bring a deeper understanding of the experimental findings and improve models of neural information processing. Here, we exemplify such a workflow using a Brunel network model.

Temporal Processing in the Visual Cortex of the Awake and Anesthetized Rat

PubMed Central

Aasebø, Ida E. J.; Stavrinou, Maria; Nøkkevangen, Sandra; Einevoll, Gaute

2017-01-01

Abstract The activity pattern and temporal dynamics within and between neuron ensembles are essential features of information processing and believed to be profoundly affected by anesthesia. Much of our general understanding of sensory information processing, including computational models aimed at mathematically simulating sensory information processing, rely on parameters derived from recordings conducted on animals under anesthesia. Due to the high variety of neuronal subtypes in the brain, population-based estimates of the impact of anesthesia may conceal unit- or ensemble-specific effects of the transition between states. Using chronically implanted tetrodes into primary visual cortex (V1) of rats, we conducted extracellular recordings of single units and followed the same cell ensembles in the awake and anesthetized states. We found that the transition from wakefulness to anesthesia involves unpredictable changes in temporal response characteristics. The latency of single-unit responses to visual stimulation was delayed in anesthesia, with large individual variations between units. Pair-wise correlations between units increased under anesthesia, indicating more synchronized activity. Further, the units within an ensemble show reproducible temporal activity patterns in response to visual stimuli that is changed between states, suggesting state-dependent sequences of activity. The current dataset, with recordings from the same neural ensembles across states, is well suited for validating and testing computational network models. This can lead to testable predictions, bring a deeper understanding of the experimental findings and improve models of neural information processing. Here, we exemplify such a workflow using a Brunel network model. PMID:28791331

Different cortical projections from three subdivisions of the rat lateral posterior thalamic nucleus: a single-neuron tracing study with viral vectors.

PubMed

Nakamura, Hisashi; Hioki, Hiroyuki; Furuta, Takahiro; Kaneko, Takeshi

2015-05-01

The lateral posterior thalamic nucleus (LP) is one of the components of the extrageniculate pathway in the rat visual system, and is cytoarchitecturally divided into three subdivisions--lateral (LPl), rostromedial (LPrm), and caudomedial (LPcm) portions. To clarify the differences in the dendritic fields and axonal arborisations among the three subdivisions, we applied a single-neuron labeling technique with viral vectors to LP neurons. The proximal dendrites of LPl neurons were more numerous than those of LPrm and LPcm neurons, and LPrm neurons tended to have wider dendritic fields than LPl neurons. We then analysed the axonal arborisations of LP neurons by reconstructing the axon fibers in the cortex. The LPl, LPrm and LPcm were different from one another in terms of the projection targets--the main target cortical regions of LPl and LPrm neurons were the secondary and primary visual areas, whereas those of LPcm neurons were the postrhinal and temporal association areas. Furthermore, the principal target cortical layers of LPl neurons in the visual areas were middle layers, but that of LPrm neurons was layer 1. This indicates that LPl and LPrm neurons can be categorised into the core and matrix types of thalamic neurons, respectively, in the visual areas. In addition, LPl neurons formed multiple axonal clusters within the visual areas, whereas the fibers of LPrm neurons were widely and diffusely distributed. It is therefore presumed that these two types of neurons play different roles in visual information processing by dual thalamocortical innervation of the visual areas. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Dynamic synchronization of ongoing neuronal activity across spinal segments regulates sensory information flow

PubMed Central

Contreras-Hernández, E; Chávez, D; Rudomin, P

2015-01-01

Previous studies on the correlation between spontaneous cord dorsum potentials recorded in the lumbar spinal segments of anaesthetized cats suggested the operation of a population of dorsal horn neurones that modulates, in a differential manner, transmission along pathways mediating Ib non-reciprocal postsynaptic inhibition and pathways mediating primary afferent depolarization and presynaptic inhibition. In order to gain further insight into the possible neuronal mechanisms that underlie this process, we have measured changes in the correlation between the spontaneous activity of individual dorsal horn neurones and the cord dorsum potentials associated with intermittent activation of these inhibitory pathways. We found that high levels of neuronal synchronization within the dorsal horn are associated with states of incremented activity along the pathways mediating presynaptic inhibition relative to pathways mediating Ib postsynaptic inhibition. It is suggested that ongoing changes in the patterns of functional connectivity within a distributed ensemble of dorsal horn neurones play a relevant role in the state-dependent modulation of impulse transmission along inhibitory pathways, among them those involved in the central control of sensory information. This feature would allow the same neuronal network to be involved in different functional tasks. Key points We have examined, in the spinal cord of the anaesthetized cat, the relationship between ongoing correlated fluctuations of dorsal horn neuronal activity and state-dependent activation of inhibitory reflex pathways. We found that high levels of synchronization between the spontaneous activity of dorsal horn neurones occur in association with the preferential activation of spinal pathways leading to primary afferent depolarization and presynaptic inhibition relative to activation of pathways mediating Ib postsynaptic inhibition. It is suggested that changes in synchronization of ongoing activity within a distributed network of dorsal horn neurones play a relevant role in the configuration of structured (non-random) patterns of functional connectivity that shape the interaction of sensory inputs with spinal reflex pathways subserving different functional tasks. PMID:25653206

Neural coding of syntactic structure in learned vocalizations in the songbird.

PubMed

Fujimoto, Hisataka; Hasegawa, Taku; Watanabe, Dai

2011-07-06

Although vocal signals including human languages are composed of a finite number of acoustic elements, complex and diverse vocal patterns can be created from combinations of these elements, linked together by syntactic rules. To enable such syntactic vocal behaviors, neural systems must extract the sequence patterns from auditory information and establish syntactic rules to generate motor commands for vocal organs. However, the neural basis of syntactic processing of learned vocal signals remains largely unknown. Here we report that the basal ganglia projecting premotor neurons (HVC(X) neurons) in Bengalese finches represent syntactic rules that generate variable song sequences. When vocalizing an alternative transition segment between song elements called syllables, sparse burst spikes of HVC(X) neurons code the identity of a specific syllable type or a specific transition direction among the alternative trajectories. When vocalizing a variable repetition sequence of the same syllable, HVC(X) neurons not only signal the initiation and termination of the repetition sequence but also indicate the progress and state-of-completeness of the repetition. These different types of syntactic information are frequently integrated within the activity of single HVC(X) neurons, suggesting that syntactic attributes of the individual neurons are not programmed as a basic cellular subtype in advance but acquired in the course of vocal learning and maturation. Furthermore, some auditory-vocal mirroring type HVC(X) neurons display transition selectivity in the auditory phase, much as they do in the vocal phase, suggesting that these songbirds may extract syntactic rules from auditory experience and apply them to form their own vocal behaviors.

Consequences of converting graded to action potentials upon neural information coding and energy efficiency.

PubMed

Sengupta, Biswa; Laughlin, Simon Barry; Niven, Jeremy Edward

2014-01-01

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na(+) and K(+) channels, with generator potential and graded potential models lacking voltage-gated Na(+) channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na(+) channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a 'footprint' in the generator potential that obscures incoming signals. These three processes reduce information rates by ∼50% in generator potentials, to ∼3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation.

Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency

PubMed Central

Sengupta, Biswa; Laughlin, Simon Barry; Niven, Jeremy Edward

2014-01-01

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ∼50% in generator potentials, to ∼3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation. PMID:24465197

A fish on the hunt, observed neuron by neuron

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2010-01-01

This three-dimensional microscopy image reveals an output neuron of the optic tectum lighting up in response to visual information from the retina. The scientists used this state-of-the-art imaging technology to learn how neurons in the optic tectum take visual information and convert it into an output that drives action. More information: http://newscenter.lbl.gov/feature-stories/2010/10/29/zebrafish-vision/

Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series.

PubMed

Zeldenrust, Fleur; de Knecht, Sicco; Wadman, Wytse J; Denève, Sophie; Gutkin, Boris

2017-01-01

Understanding the relation between (sensory) stimuli and the activity of neurons (i.e., "the neural code") lies at heart of understanding the computational properties of the brain. However, quantifying the information between a stimulus and a spike train has proven to be challenging. We propose a new ( in vitro ) method to measure how much information a single neuron transfers from the input it receives to its output spike train. The input is generated by an artificial neural network that responds to a randomly appearing and disappearing "sensory stimulus": the hidden state. The sum of this network activity is injected as current input into the neuron under investigation. The mutual information between the hidden state on the one hand and spike trains of the artificial network or the recorded spike train on the other hand can easily be estimated due to the binary shape of the hidden state. The characteristics of the input current, such as the time constant as a result of the (dis)appearance rate of the hidden state or the amplitude of the input current (the firing frequency of the neurons in the artificial network), can independently be varied. As an example, we apply this method to pyramidal neurons in the CA1 of mouse hippocampi and compare the recorded spike trains to the optimal response of the "Bayesian neuron" (BN). We conclude that like in the BN, information transfer in hippocampal pyramidal cells is non-linear and amplifying: the information loss between the artificial input and the output spike train is high if the input to the neuron (the firing of the artificial network) is not very informative about the hidden state. If the input to the neuron does contain a lot of information about the hidden state, the information loss is low. Moreover, neurons increase their firing rates in case the (dis)appearance rate is high, so that the (relative) amount of transferred information stays constant.

Single-unit analysis of somatosensory processing in the core auditory cortex of hearing ferrets.

PubMed

Meredith, M Alex; Allman, Brian L

2015-03-01

The recent findings in several species that the primary auditory cortex processes non-auditory information have largely overlooked the possibility of somatosensory effects. Therefore, the present investigation examined the core auditory cortices (anterior auditory field and primary auditory cortex) for tactile responsivity. Multiple single-unit recordings from anesthetised ferret cortex yielded histologically verified neurons (n = 311) tested with electronically controlled auditory, visual and tactile stimuli, and their combinations. Of the auditory neurons tested, a small proportion (17%) was influenced by visual cues, but a somewhat larger number (23%) was affected by tactile stimulation. Tactile effects rarely occurred alone and spiking responses were observed in bimodal auditory-tactile neurons. However, the broadest tactile effect that was observed, which occurred in all neuron types, was that of suppression of the response to a concurrent auditory cue. The presence of tactile effects in the core auditory cortices was supported by a substantial anatomical projection from the rostral suprasylvian sulcal somatosensory area. Collectively, these results demonstrate that crossmodal effects in the auditory cortex are not exclusively visual and that somatosensation plays a significant role in modulation of acoustic processing, and indicate that crossmodal plasticity following deafness may unmask these existing non-auditory functions. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Noise reduction of coincidence detector output by the inferior colliculus of the barn owl.

PubMed

Christianson, G Björn; Peña, José Luis

2006-05-31

A recurring theme in theoretical work is that integration over populations of similarly tuned neurons can reduce neural noise. However, there are relatively few demonstrations of an explicit noise reduction mechanism in a neural network. Here we demonstrate that the brainstem of the barn owl includes a stage of processing apparently devoted to increasing the signal-to-noise ratio in the encoding of the interaural time difference (ITD), one of two primary binaural cues used to compute the position of a sound source in space. In the barn owl, the ITD is processed in a dedicated neural pathway that terminates at the core of the inferior colliculus (ICcc). The actual locus of the computation of the ITD is before ICcc in the nucleus laminaris (NL), and ICcc receives no inputs carrying information that did not originate in NL. Unlike in NL, the rate-ITD functions of ICcc neurons require as little as a single stimulus presentation per ITD to show coherent ITD tuning. ICcc neurons also displayed a greater dynamic range with a maximal difference in ITD response rates approximately double that seen in NL. These results indicate that ICcc neurons perform a computation functionally analogous to averaging across a population of similarly tuned NL neurons.

Mixed input to olfactory glomeruli from two subsets of ciliated sensory neurons does not impede relay neuron specificity in the crucian carp.

PubMed

Hansson, Kenth-Arne; Døving, Kjell B; Skjeldal, Frode M

2015-10-01

The consensus view of olfactory processing is that the axons of receptor-specific primary olfactory sensory neurons (OSNs) converge to a small subset of glomeruli, thus preserving the odour identity before the olfactory information is processed in higher brain centres. In the present study, we show that two different subsets of ciliated OSNs with different odorant specificities converge to the same glomeruli. In order to stain different ciliated OSNs in the crucian carp Carassius carassius we used two different chemical odorants, a bile salt and a purported alarm substance, together with fluorescent dextrans. The dye is transported within the axons and stains glomeruli in the olfactory bulb. Interestingly, the axons from the ciliated OSNs co-converge to the same glomeruli. Despite intermingled innervation of glomeruli, axons and terminal fields from the two different subsets of ciliated OSNs remained mono-coloured. By 4-6 days after staining, the dye was transported trans-synaptically to separately stained axons of relay neurons. These findings demonstrate that specificity of the primary neurons is retained in the olfactory pathways despite mixed innervation of the olfactory glomeruli. The results are discussed in relation to the emerging concepts about non-mammalian glomeruli. © 2015. Published by The Company of Biologists Ltd.

Control of Abnormal Synchronization in Neurological Disorders

PubMed Central

Popovych, Oleksandr V.; Tass, Peter A.

2014-01-01

In the nervous system, synchronization processes play an important role, e.g., in the context of information processing and motor control. However, pathological, excessive synchronization may strongly impair brain function and is a hallmark of several neurological disorders. This focused review addresses the question of how an abnormal neuronal synchronization can specifically be counteracted by invasive and non-invasive brain stimulation as, for instance, by deep brain stimulation for the treatment of Parkinson’s disease, or by acoustic stimulation for the treatment of tinnitus. On the example of coordinated reset (CR) neuromodulation, we illustrate how insights into the dynamics of complex systems contribute to successful model-based approaches, which use methods from synergetics, non-linear dynamics, and statistical physics, for the development of novel therapies for normalization of brain function and synaptic connectivity. Based on the intrinsic multistability of the neuronal populations induced by spike timing-dependent plasticity (STDP), CR neuromodulation utilizes the mutual interdependence between synaptic connectivity and dynamics of the neuronal networks in order to restore more physiological patterns of connectivity via desynchronization of neuronal activity. The very goal is to shift the neuronal population by stimulation from an abnormally coupled and synchronized state to a desynchronized regime with normalized synaptic connectivity, which significantly outlasts the stimulation cessation, so that long-lasting therapeutic effects can be achieved. PMID:25566174

Superconducting Optoelectronic Circuits for Neuromorphic Computing

NASA Astrophysics Data System (ADS)

Shainline, Jeffrey M.; Buckley, Sonia M.; Mirin, Richard P.; Nam, Sae Woo

2017-03-01

Neural networks have proven effective for solving many difficult computational problems, yet implementing complex neural networks in software is computationally expensive. To explore the limits of information processing, it is necessary to implement new hardware platforms with large numbers of neurons, each with a large number of connections to other neurons. Here we propose a hybrid semiconductor-superconductor hardware platform for the implementation of neural networks and large-scale neuromorphic computing. The platform combines semiconducting few-photon light-emitting diodes with superconducting-nanowire single-photon detectors to behave as spiking neurons. These processing units are connected via a network of optical waveguides, and variable weights of connection can be implemented using several approaches. The use of light as a signaling mechanism overcomes fanout and parasitic constraints on electrical signals while simultaneously introducing physical degrees of freedom which can be employed for computation. The use of supercurrents achieves the low power density (1 mW /cm2 at 20-MHz firing rate) necessary to scale to systems with enormous entropy. Estimates comparing the proposed hardware platform to a human brain show that with the same number of neurons (1 011) and 700 independent connections per neuron, the hardware presented here may achieve an order of magnitude improvement in synaptic events per second per watt.

A neuronal reward inequity signal in primate striatum

PubMed Central

van Coeverden, Charlotte R.; Schultz, Wolfram

2015-01-01

Primates are social animals, and their survival depends on social interactions with others. Especially important for social interactions and welfare is the observation of rewards obtained by other individuals and the comparison with own reward. The fundamental social decision variable for the comparison process is reward inequity, defined by an asymmetric reward distribution among individuals. An important brain structure for coding reward inequity may be the striatum, a component of the basal ganglia involved in goal-directed behavior. Two rhesus monkeys were seated opposite each other and contacted a touch-sensitive table placed between them to obtain specific magnitudes of reward that were equally or unequally distributed among them. Response times in one of the animals demonstrated differential behavioral sensitivity to reward inequity. A group of neurons in the striatum showed distinct signals reflecting disadvantageous and advantageous reward inequity. These neuronal signals occurred irrespective of, or in conjunction with, own reward coding. These data demonstrate that striatal neurons of macaque monkeys sense the differences between other's and own reward. The neuronal activities are likely to contribute crucial reward information to neuronal mechanisms involved in social interactions. PMID:26378202

Active immunization against vasoactive intestinal polypeptide decreases neuronal recruitment and inhibits reproduction in zebra finches.

PubMed

Vistoropsky, Yulia; Heiblum, Rachel; Smorodinsky, Nechama-Ina; Barnea, Anat

2016-08-15

Neurogenesis and neuronal recruitment occur in adult brains of many vertebrates, and the hypothesis is that these phenomena contribute to the brain plasticity that enables organisms to adjust to environmental changes. In mammals, vasoactive intestinal polypeptide (VIP) is known to have many neuroprotective properties, but in the avian brain, although widely distributed, its role in neuronal recruitment is not yet understood. In the present study we actively immunized adult zebra finches against VIP conjugated to KLH and compared neuronal recruitment in their brains, with brains of control birds, which were immunized against KLH. We looked at two forebrain regions: the nidopallium caudale (NC), which plays a role in vocal communication, and the hippocampus (HC), which is involved in the processing of spatial information. Our data demonstrate that active immunization against VIP reduces neuronal recruitment, inhibits reproduction, and induces molting, with no change in plasma prolactin levels. Thus, our observations suggest that VIP has a direct positive role in neuronal recruitment and reproduction in birds. J. Comp. Neurol. 524:2516-2528, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Model-based analysis of pattern motion processing in mouse primary visual cortex

PubMed Central

Muir, Dylan R.; Roth, Morgane M.; Helmchen, Fritjof; Kampa, Björn M.

2015-01-01

Neurons in sensory areas of neocortex exhibit responses tuned to specific features of the environment. In visual cortex, information about features such as edges or textures with particular orientations must be integrated to recognize a visual scene or object. Connectivity studies in rodent cortex have revealed that neurons make specific connections within sub-networks sharing common input tuning. In principle, this sub-network architecture enables local cortical circuits to integrate sensory information. However, whether feature integration indeed occurs locally in rodent primary sensory areas has not been examined directly. We studied local integration of sensory features in primary visual cortex (V1) of the mouse by presenting drifting grating and plaid stimuli, while recording the activity of neuronal populations with two-photon calcium imaging. Using a Bayesian model-based analysis framework, we classified single-cell responses as being selective for either individual grating components or for moving plaid patterns. Rather than relying on trial-averaged responses, our model-based framework takes into account single-trial responses and can easily be extended to consider any number of arbitrary predictive models. Our analysis method was able to successfully classify significantly more responses than traditional partial correlation (PC) analysis, and provides a rigorous statistical framework to rank any number of models and reject poorly performing models. We also found a large proportion of cells that respond strongly to only one stimulus class. In addition, a quarter of selectively responding neurons had more complex responses that could not be explained by any simple integration model. Our results show that a broad range of pattern integration processes already take place at the level of V1. This diversity of integration is consistent with processing of visual inputs by local sub-networks within V1 that are tuned to combinations of sensory features. PMID:26300738

A digital pixel cell for address event representation image convolution processing

NASA Astrophysics Data System (ADS)

Camunas-Mesa, Luis; Acosta-Jimenez, Antonio; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabe

2005-06-01

Address Event Representation (AER) is an emergent neuromorphic interchip communication protocol that allows for real-time virtual massive connectivity between huge number of neurons located on different chips. By exploiting high speed digital communication circuits (with nano-seconds timings), synaptic neural connections can be time multiplexed, while neural activity signals (with mili-seconds timings) are sampled at low frequencies. Also, neurons generate events according to their information levels. Neurons with more information (activity, derivative of activities, contrast, motion, edges,...) generate more events per unit time, and access the interchip communication channel more frequently, while neurons with low activity consume less communication bandwidth. AER technology has been used and reported for the implementation of various type of image sensors or retinae: luminance with local agc, contrast retinae, motion retinae,... Also, there has been a proposal for realizing programmable kernel image convolution chips. Such convolution chips would contain an array of pixels that perform weighted addition of events. Once a pixel has added sufficient event contributions to reach a fixed threshold, the pixel fires an event, which is then routed out of the chip for further processing. Such convolution chips have been proposed to be implemented using pulsed current mode mixed analog and digital circuit techniques. In this paper we present a fully digital pixel implementation to perform the weighted additions and fire the events. This way, for a given technology, there is a fully digital implementation reference against which compare the mixed signal implementations. We have designed, implemented and tested a fully digital AER convolution pixel. This pixel will be used to implement a full AER convolution chip for programmable kernel image convolution processing.

Advancing interconnect density for spiking neural network hardware implementations using traffic-aware adaptive network-on-chip routers.

PubMed

Carrillo, Snaider; Harkin, Jim; McDaid, Liam; Pande, Sandeep; Cawley, Seamus; McGinley, Brian; Morgan, Fearghal

2012-09-01

The brain is highly efficient in how it processes information and tolerates faults. Arguably, the basic processing units are neurons and synapses that are interconnected in a complex pattern. Computer scientists and engineers aim to harness this efficiency and build artificial neural systems that can emulate the key information processing principles of the brain. However, existing approaches cannot provide the dense interconnect for the billions of neurons and synapses that are required. Recently a reconfigurable and biologically inspired paradigm based on network-on-chip (NoC) and spiking neural networks (SNNs) has been proposed as a new method of realising an efficient, robust computing platform. However, the use of the NoC as an interconnection fabric for large-scale SNNs demands a good trade-off between scalability, throughput, neuron/synapse ratio and power consumption. This paper presents a novel traffic-aware, adaptive NoC router, which forms part of a proposed embedded mixed-signal SNN architecture called EMBRACE (EMulating Biologically-inspiRed ArChitectures in hardwarE). The proposed adaptive NoC router provides the inter-neuron connectivity for EMBRACE, maintaining router communication and avoiding dropped router packets by adapting to router traffic congestion. Results are presented on throughput, power and area performance analysis of the adaptive router using a 90 nm CMOS technology which outperforms existing NoCs in this domain. The adaptive behaviour of the router is also verified on a Stratix II FPGA implementation of a 4 × 2 router array with real-time traffic congestion. The presented results demonstrate the feasibility of using the proposed adaptive NoC router within the EMBRACE architecture to realise large-scale SNNs on embedded hardware. Copyright © 2012 Elsevier Ltd. All rights reserved.

Stimfit: quantifying electrophysiological data with Python

PubMed Central

Guzman, Segundo J.; Schlögl, Alois; Schmidt-Hieber, Christoph

2013-01-01

Intracellular electrophysiological recordings provide crucial insights into elementary neuronal signals such as action potentials and synaptic currents. Analyzing and interpreting these signals is essential for a quantitative understanding of neuronal information processing, and requires both fast data visualization and ready access to complex analysis routines. To achieve this goal, we have developed Stimfit, a free software package for cellular neurophysiology with a Python scripting interface and a built-in Python shell. The program supports most standard file formats for cellular neurophysiology and other biomedical signals through the Biosig library. To quantify and interpret the activity of single neurons and communication between neurons, the program includes algorithms to characterize the kinetics of presynaptic action potentials and postsynaptic currents, estimate latencies between pre- and postsynaptic events, and detect spontaneously occurring events. We validate and benchmark these algorithms, give estimation errors, and provide sample use cases, showing that Stimfit represents an efficient, accessible and extensible way to accurately analyze and interpret neuronal signals. PMID:24600389

THREE-DIMENSIONAL RANDOM ACCESS MULTIPHOTON MICROSCOPY FOR FAST FUNCTIONAL IMAGING OF NEURONAL ACTIVITY

PubMed Central

Reddy, Gaddum Duemani; Kelleher, Keith; Fink, Rudy; Saggau, Peter

2009-01-01

The dynamic ability of neuronal dendrites to shape and integrate synaptic responses is the hallmark of information processing in the brain. Effectively studying this phenomenon requires concurrent measurements at multiple sites on live neurons. Significant progress has been made by optical imaging systems which combine confocal and multiphoton microscopy with inertia-free laser scanning. However, all systems developed to date restrict fast imaging to two dimensions. This severely limits the extent to which neurons can be studied, since they represent complex three-dimensional (3D) structures. Here we present a novel imaging system that utilizes a unique arrangement of acousto-optic deflectors to steer a focused ultra-fast laser beam to arbitrary locations in 3D space without moving the objective lens. As we demonstrate, this highly versatile random-access multiphoton microscope supports functional imaging of complex 3D cellular structures such as neuronal dendrites or neural populations at acquisition rates on the order of tens of kilohertz. PMID:18432198

Spike-Threshold Adaptation Predicted by Membrane Potential Dynamics In Vivo

PubMed Central

Fontaine, Bertrand; Peña, José Luis; Brette, Romain

2014-01-01

Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo. PMID:24722397

Maternal Immune Activation Alters Nonspatial Information Processing in the Hippocampus of the Adult Offspring

PubMed Central

Ito, Hiroshi T.; Smith, Stephen E. P.; Hsiao, Elaine; Patterson, Paul H.

2010-01-01

The observation that maternal infection increases the risk for schizophrenia in the offspring suggests that the maternal immune system plays a key role in the etiology of schizophrenia. In a mouse model, maternal immune activation (MIA) by injection of poly(I:C) yields adult offspring that display abnormalities in a variety of behaviors relevant to schizophrenia. As abnormalities in the hippocampus are a consistent observation in schizophrenia patients, we examined synaptic properties in hippocampal slices prepared from the offspring of poly(I:C)- and saline-treated mothers. Compared to controls, CA1 pyramidal neurons from adult offspring of MIA mothers display reduced frequency and increased amplitude of miniature excitatory postsynaptic currents. In addition, the specific component of the temporoammonic pathway that mediates object-related information displays increased sensitivity to dopamine. To assess hippocampal network function in vivo, we used expression of the immediate early gene, c-Fos, as a surrogate measure of neuronal activity. Compared to controls, the offspring of poly(I:C)-treated mothers display a distinct c-Fos expression pattern in area CA1 following novel object, but not novel location, exposure. Thus, the offspring of MIA mothers may have an abnormality in modality-specific information processing. Indeed, the MIA offspring display enhanced discrimination in a novel object recognition, but not in an object location, task. Thus, analysis of object and spatial information processing at both synaptic and behavioral levels reveals a largely selective abnormality in object information processing in this mouse model. Our results suggest that altered processing of object-related information may be part of the pathogenesis of schizophrenia-like cognitive behaviors. PMID:20227486

Maternal immune activation alters nonspatial information processing in the hippocampus of the adult offspring.

PubMed

Ito, Hiroshi T; Smith, Stephen E P; Hsiao, Elaine; Patterson, Paul H

2010-08-01

The observation that maternal infection increases the risk for schizophrenia in the offspring suggests that the maternal immune system plays a key role in the etiology of schizophrenia. In a mouse model, maternal immune activation (MIA) by injection of poly(I:C) yields adult offspring that display abnormalities in a variety of behaviors relevant to schizophrenia. As abnormalities in the hippocampus are a consistent observation in schizophrenia patients, we examined synaptic properties in hippocampal slices prepared from the offspring of poly(I:C)- and saline-treated mothers. Compared to controls, CA1 pyramidal neurons from adult offspring of MIA mothers display reduced frequency and increased amplitude of miniature excitatory postsynaptic currents. In addition, the specific component of the temporoammonic pathway that mediates object-related information displays increased sensitivity to dopamine. To assess hippocampal network function in vivo, we used expression of the immediate-early gene, c-Fos, as a surrogate measure of neuronal activity. Compared to controls, the offspring of poly(I:C)-treated mothers display a distinct c-Fos expression pattern in area CA1 following novel object, but not novel location, exposure. Thus, the offspring of MIA mothers may have an abnormality in modality-specific information processing. Indeed, the MIA offspring display enhanced discrimination in a novel object recognition, but not in an object location, task. Thus, analysis of object and spatial information processing at both synaptic and behavioral levels reveals a largely selective abnormality in object information processing in this mouse model. Our results suggest that altered processing of object-related information may be part of the pathogenesis of schizophrenia-like cognitive behaviors. Copyright 2010 Elsevier Inc. All rights reserved.

The relationship between nernst equilibrium variability and the multifractality of interspike intervals in the hippocampus.

PubMed

Meier, Stephen R; Lancaster, Jarrett L; Fetterhoff, Dustin; Kraft, Robert A; Hampson, Robert E; Starobin, Joseph M

2017-04-01

Spatiotemporal patterns of action potentials are considered to be closely related to information processing in the brain. Auto-generating neurons contributing to these processing tasks are known to cause multifractal behavior in the inter-spike intervals of the output action potentials. In this paper we define a novel relationship between this multifractality and the adaptive Nernst equilibrium in hippocampal neurons. Using this relationship we are able to differentiate between various drugs at varying dosages. Conventional methods limit their ability to account for cellular charge depletion by not including these adaptive Nernst equilibria. Our results provide a new theoretical approach for measuring the effects which drugs have on single-cell dynamics.

Response of Electrical Activity in an Improved Neuron Model under Electromagnetic Radiation and Noise

PubMed Central

Zhan, Feibiao; Liu, Shenquan

2017-01-01

Electrical activities are ubiquitous neuronal bioelectric phenomena, which have many different modes to encode the expression of biological information, and constitute the whole process of signal propagation between neurons. Therefore, we focus on the electrical activities of neurons, which is also causing widespread concern among neuroscientists. In this paper, we mainly investigate the electrical activities of the Morris-Lecar (M-L) model with electromagnetic radiation or Gaussian white noise, which can restore the authenticity of neurons in realistic neural network. First, we explore dynamical response of the whole system with electromagnetic induction (EMI) and Gaussian white noise. We find that there are slight differences in the discharge behaviors via comparing the response of original system with that of improved system, and electromagnetic induction can transform bursting or spiking state to quiescent state and vice versa. Furthermore, we research bursting transition mode and the corresponding periodic solution mechanism for the isolated neuron model with electromagnetic induction by using one-parameter and bi-parameters bifurcation analysis. Finally, we analyze the effects of Gaussian white noise on the original system and coupled system, which is conducive to understand the actual discharge properties of realistic neurons. PMID:29209192

Response of Electrical Activity in an Improved Neuron Model under Electromagnetic Radiation and Noise.

PubMed

Zhan, Feibiao; Liu, Shenquan

2017-01-01

Electrical activities are ubiquitous neuronal bioelectric phenomena, which have many different modes to encode the expression of biological information, and constitute the whole process of signal propagation between neurons. Therefore, we focus on the electrical activities of neurons, which is also causing widespread concern among neuroscientists. In this paper, we mainly investigate the electrical activities of the Morris-Lecar (M-L) model with electromagnetic radiation or Gaussian white noise, which can restore the authenticity of neurons in realistic neural network. First, we explore dynamical response of the whole system with electromagnetic induction (EMI) and Gaussian white noise. We find that there are slight differences in the discharge behaviors via comparing the response of original system with that of improved system, and electromagnetic induction can transform bursting or spiking state to quiescent state and vice versa. Furthermore, we research bursting transition mode and the corresponding periodic solution mechanism for the isolated neuron model with electromagnetic induction by using one-parameter and bi-parameters bifurcation analysis. Finally, we analyze the effects of Gaussian white noise on the original system and coupled system, which is conducive to understand the actual discharge properties of realistic neurons.

A Rotational Motion Perception Neural Network Based on Asymmetric Spatiotemporal Visual Information Processing.

PubMed

Hu, Bin; Yue, Shigang; Zhang, Zhuhong

All complex motion patterns can be decomposed into several elements, including translation, expansion/contraction, and rotational motion. In biological vision systems, scientists have found that specific types of visual neurons have specific preferences to each of the three motion elements. There are computational models on translation and expansion/contraction perceptions; however, little has been done in the past to create computational models for rotational motion perception. To fill this gap, we proposed a neural network that utilizes a specific spatiotemporal arrangement of asymmetric lateral inhibited direction selective neural networks (DSNNs) for rotational motion perception. The proposed neural network consists of two parts-presynaptic and postsynaptic parts. In the presynaptic part, there are a number of lateral inhibited DSNNs to extract directional visual cues. In the postsynaptic part, similar to the arrangement of the directional columns in the cerebral cortex, these direction selective neurons are arranged in a cyclic order to perceive rotational motion cues. In the postsynaptic network, the delayed excitation from each direction selective neuron is multiplied by the gathered excitation from this neuron and its unilateral counterparts depending on which rotation, clockwise (cw) or counter-cw (ccw), to perceive. Systematic experiments under various conditions and settings have been carried out and validated the robustness and reliability of the proposed neural network in detecting cw or ccw rotational motion. This research is a critical step further toward dynamic visual information processing.All complex motion patterns can be decomposed into several elements, including translation, expansion/contraction, and rotational motion. In biological vision systems, scientists have found that specific types of visual neurons have specific preferences to each of the three motion elements. There are computational models on translation and expansion/contraction perceptions; however, little has been done in the past to create computational models for rotational motion perception. To fill this gap, we proposed a neural network that utilizes a specific spatiotemporal arrangement of asymmetric lateral inhibited direction selective neural networks (DSNNs) for rotational motion perception. The proposed neural network consists of two parts-presynaptic and postsynaptic parts. In the presynaptic part, there are a number of lateral inhibited DSNNs to extract directional visual cues. In the postsynaptic part, similar to the arrangement of the directional columns in the cerebral cortex, these direction selective neurons are arranged in a cyclic order to perceive rotational motion cues. In the postsynaptic network, the delayed excitation from each direction selective neuron is multiplied by the gathered excitation from this neuron and its unilateral counterparts depending on which rotation, clockwise (cw) or counter-cw (ccw), to perceive. Systematic experiments under various conditions and settings have been carried out and validated the robustness and reliability of the proposed neural network in detecting cw or ccw rotational motion. This research is a critical step further toward dynamic visual information processing.

Effect of the heterogeneous neuron and information transmission delay on stochastic resonance of neuronal networks

NASA Astrophysics Data System (ADS)

Wang, Qingyun; Zhang, Honghui; Chen, Guanrong

2012-12-01

We study the effect of heterogeneous neuron and information transmission delay on stochastic resonance of scale-free neuronal networks. For this purpose, we introduce the heterogeneity to the specified neuron with the highest degree. It is shown that in the absence of delay, an intermediate noise level can optimally assist spike firings of collective neurons so as to achieve stochastic resonance on scale-free neuronal networks for small and intermediate αh, which plays a heterogeneous role. Maxima of stochastic resonance measure are enhanced as αh increases, which implies that the heterogeneity can improve stochastic resonance. However, as αh is beyond a certain large value, no obvious stochastic resonance can be observed. If the information transmission delay is introduced to neuronal networks, stochastic resonance is dramatically affected. In particular, the tuned information transmission delay can induce multiple stochastic resonance, which can be manifested as well-expressed maximum in the measure for stochastic resonance, appearing every multiple of one half of the subthreshold stimulus period. Furthermore, we can observe that stochastic resonance at odd multiple of one half of the subthreshold stimulus period is subharmonic, as opposed to the case of even multiple of one half of the subthreshold stimulus period. More interestingly, multiple stochastic resonance can also be improved by the suitable heterogeneous neuron. Presented results can provide good insights into the understanding of the heterogeneous neuron and information transmission delay on realistic neuronal networks.

Low-level mechanisms for processing odor information in the behaving animal.

PubMed

Wachowiak, Matt; Wesson, Daniel W; Pírez, Nicolás; Verhagen, Justus V; Carey, Ryan M

2009-07-01

Sensory processing is typically thought to act on representations of sensory stimuli that are relatively fixed at low levels in the nervous system and become increasingly complex and subject to modulation at higher levels. Here we present recent findings from our laboratory demonstrating that, in the olfactory system, odor representations in the behaving animal can be transformed at low levels--as early as the primary sensory neurons themselves--via a variety of mechanisms. First, changes in odor sampling behavior, such as sniffing, can dramatically and rapidly alter primary odor representations by changing the strength and temporal structure of sensory input to the olfactory bulb, effectively shaping which features of the olfactory landscape are emphasized and likely altering how information is processed by the olfactory bulb network. Second, neural substrates exist for presynaptically modulating the strength of sensory input to the bulb as a function of behavioral state. The systems most likely to be involved in this modulation--cholinergic and serotonergic centrifugal inputs to the bulb--are linked to attention and arousal effects in other brain areas. Together, sniffing behavior and presynaptic inhibition have the potential to mediate, or at least contribute to, sensory processing phenomena, such as figure-ground separation, intensity invariance, and context-dependent and attentional modulation of response properties. Thus, "high order" processing can occur even before sensory neurons transmit information to the brain.

Structural organization of parallel information processing within the tectofugal visual system of the pigeon.

PubMed

Hellmann, B; Güntürkün, O

2001-01-01

Visual information processing within the ascending tectofugal pathway to the forebrain undergoes essential rearrangements between the mesencephalic tectum opticum and the diencephalic nucleus rotundus of birds. The outer tectal layers constitute a two-dimensional map of the visual surrounding, whereas nucleus rotundus is characterized by functional domains in which different visual features such as movement, color, or luminance are processed in parallel. Morphologic correlates of this reorganization were investigated by means of focal injections of the neuronal tracer choleratoxin subunit B into different regions of the nuclei rotundus and triangularis of the pigeon. Dependent on the thalamic injection site, variations in the retrograde labeling pattern of ascending tectal efferents were observed. All rotundal projecting neurons were located within the deep tectal layer 13. Five different cell populations were distinguished that could be differentiated according to their dendritic ramifications within different retinorecipient laminae and their axons projecting to different subcomponents of the nucleus rotundus. Because retinorecipient tectal layers differ in their input from distinct classes of retinal ganglion cells, each tectorotundal cell type probably processes different aspects of the visual surrounding. Therefore, the differential input/output connections of the five tectorotundal cell groups might constitute the structural basis for spatially segregated parallel information processing of different stimulus aspects within the tectofugal visual system. Because two of five rotundal projecting cell groups additionally exhibited quantitative shifts along the dorsoventral extension of the tectum, data also indicate visual field-dependent alterations in information processing for particular visual features. Copyright 2001 Wiley-Liss, Inc.

Working Memory in the Service of Executive Control Functions.

PubMed

Mansouri, Farshad A; Rosa, Marcello G P; Atapour, Nafiseh

2015-01-01

Working memory is a type of short-term memory which has a crucial cognitive function that supports ongoing and upcoming behaviors, allowing storage of information across delay periods. The content of this memory may typically include tangible information about features such as the shape, color or texture of an object, and its location and motion relative to the body, as well as phonological information. The neural correlate of working memory has been found in different brain areas that are involved in organizing perceptual or motor functions. In particular, neuronal activity in prefrontal areas encodes task-related information corresponding to working memory across delay periods, and lesions in the prefrontal cortex severely affect the ability to retain this type of memory. Recent studies have further expanded the scope and possible role of working memory by showing that information of a more abstract nature (including a behavior-guiding rule, or the occurrence of a conflict in information processing) can also be maintained in short-term memory, and used for adjusting the allocation of executive control in dynamic environments. It has also been shown that neuronal activity in the prefrontal cortex encodes and maintains information about such abstract entities. These findings suggest that the prefrontal cortex plays crucial roles in the organization of goal-directed behavior by supporting many different mnemonic processes, which maintain a wide range of information required for the executive control of ongoing and upcoming behaviors.

A computational model of pattern separation efficiency in the dentate gyrus with implications in schizophrenia

PubMed Central

Faghihi, Faramarz; Moustafa, Ahmed A.

2015-01-01

Information processing in the hippocampus begins by transferring spiking activity of the entorhinal cortex (EC) into the dentate gyrus (DG). Activity pattern in the EC is separated by the DG such that it plays an important role in hippocampal functions including memory. The structural and physiological parameters of these neural networks enable the hippocampus to be efficient in encoding a large number of inputs that animals receive and process in their life time. The neural encoding capacity of the DG depends on its single neurons encoding and pattern separation efficiency. In this study, encoding by the DG is modeled such that single neurons and pattern separation efficiency are measured using simulations of different parameter values. For this purpose, a probabilistic model of single neurons efficiency is presented to study the role of structural and physiological parameters. Known neurons number of the EC and the DG is used to construct a neural network by electrophysiological features of granule cells of the DG. Separated inputs as activated neurons in the EC with different firing probabilities are presented into the DG. For different connectivity rates between the EC and DG, pattern separation efficiency of the DG is measured. The results show that in the absence of feedback inhibition on the DG neurons, the DG demonstrates low separation efficiency and high firing frequency. Feedback inhibition can increase separation efficiency while resulting in very low single neuron’s encoding efficiency in the DG and very low firing frequency of neurons in the DG (sparse spiking). This work presents a mechanistic explanation for experimental observations in the hippocampus, in combination with theoretical measures. Moreover, the model predicts a critical role for impaired inhibitory neurons in schizophrenia where deficiency in pattern separation of the DG has been observed. PMID:25859189

Decision-Related Activity in Macaque V2 for Fine Disparity Discrimination Is Not Compatible with Optimal Linear Readout

PubMed Central

Clery, Stephane; Cumming, Bruce G.

2017-01-01

Fine judgments of stereoscopic depth rely mainly on relative judgments of depth (relative binocular disparity) between objects, rather than judgments of the distance to where the eyes are fixating (absolute disparity). In macaques, visual area V2 is the earliest site in the visual processing hierarchy for which neurons selective for relative disparity have been observed (Thomas et al., 2002). Here, we found that, in macaques trained to perform a fine disparity discrimination task, disparity-selective neurons in V2 were highly selective for the task, and their activity correlated with the animals' perceptual decisions (unexplained by the stimulus). This may partially explain similar correlations reported in downstream areas. Although compatible with a perceptual role of these neurons for the task, the interpretation of such decision-related activity is complicated by the effects of interneuronal “noise” correlations between sensory neurons. Recent work has developed simple predictions to differentiate decoding schemes (Pitkow et al., 2015) without needing measures of noise correlations, and found that data from early sensory areas were compatible with optimal linear readout of populations with information-limiting correlations. In contrast, our data here deviated significantly from these predictions. We additionally tested this prediction for previously reported results of decision-related activity in V2 for a related task, coarse disparity discrimination (Nienborg and Cumming, 2006), thought to rely on absolute disparity. Although these data followed the predicted pattern, they violated the prediction quantitatively. This suggests that optimal linear decoding of sensory signals is not generally a good predictor of behavior in simple perceptual tasks. SIGNIFICANCE STATEMENT Activity in sensory neurons that correlates with an animal's decision is widely believed to provide insights into how the brain uses information from sensory neurons. Recent theoretical work developed simple predictions to differentiate decoding schemes, and found support for optimal linear readout of early sensory populations with information-limiting correlations. Here, we observed decision-related activity for neurons in visual area V2 of macaques performing fine disparity discrimination, as yet the earliest site for this task. These findings, and previously reported results from V2 in a different task, deviated from the predictions for optimal linear readout of a population with information-limiting correlations. Our results suggest that optimal linear decoding of early sensory information is not a general decoding strategy used by the brain. PMID:28100751

Processing of Intraoral Olfactory and Gustatory Signals in the Gustatory Cortex of Awake Rats.

PubMed

Samuelsen, Chad L; Fontanini, Alfredo

2017-01-11

The integration of gustatory and olfactory information is essential to the perception of flavor. Human neuroimaging experiments have pointed to the gustatory cortex (GC) as one of the areas involved in mediating flavor perception. Although GC's involvement in encoding the chemical identity and hedonic value of taste stimuli is well studied, it is unknown how single GC neurons process olfactory stimuli emanating from the mouth. In this study, we relied on multielectrode recordings to investigate how single GC neurons respond to intraorally delivered tastants and tasteless odorants dissolved in water and whether/how these two modalities converge in the same neurons. We found that GC neurons could either be unimodal, responding exclusively to taste (taste-only) or odor (odor-only), or bimodal, responding to both gustatory and olfactory stimuli. Odor responses were confirmed to result from retronasal olfaction: monitoring respiration revealed that exhalation preceded odor-evoked activity and reversible inactivation of olfactory receptors in the nasal epithelium significantly reduced responses to intraoral odorants but not to tastants. Analysis of bimodal neurons revealed that they encode palatability significantly better than the unimodal taste-only group. Bimodal neurons exhibited similar responses to palatable tastants and odorants dissolved in water. This result suggested that odorized water could be palatable. This interpretation was further supported with a brief access task, where rats avoided consuming aversive taste stimuli and consumed the palatable tastants and dissolved odorants. These results demonstrate the convergence of the chemosensory components of flavor onto single GC neurons and provide evidence for the integration of flavor with palatability coding. Food perception and choice depend upon the concurrent processing of olfactory and gustatory signals from the mouth. The primary gustatory cortex has been proposed to integrate chemosensory stimuli; however, no study has examined the single-unit responses to intraoral odorant presentation. Here we found that neurons in gustatory cortex can respond either exclusively to tastants, exclusively to odorants, or to both (bimodal). Several differences exist between these groups' responses; notably, bimodal neurons code palatability significantly better than unimodal neurons. This group of neurons might represent a substrate for how odorants gain the quality of tastants. Copyright © 2017 the authors 0270-6474/17/370244-14$15.00/0.

Temporal dynamics of 2D motion integration for ocular following in macaque monkeys.

PubMed

Barthélemy, Fréderic V; Fleuriet, Jérome; Masson, Guillaume S

2010-03-01

Several recent studies have shown that extracting pattern motion direction is a dynamical process where edge motion is first extracted and pattern-related information is encoded with a small time lag by MT neurons. A similar dynamics was found for human reflexive or voluntary tracking. Here, we bring an essential, but still missing, piece of information by documenting macaque ocular following responses to gratings, unikinetic plaids, and barber-poles. We found that ocular tracking was always initiated first in the grating motion direction with ultra-short latencies (approximately 55 ms). A second component was driven only 10-15 ms later, rotating tracking toward pattern motion direction. At the end the open-loop period, tracking direction was aligned with pattern motion direction (plaids) or the average of the line-ending motion directions (barber-poles). We characterized the dependency on contrast of each component. Both timing and direction of ocular following were quantitatively very consistent with the dynamics of neuronal responses reported by others. Overall, we found a remarkable consistency between neuronal dynamics and monkey behavior, advocating for a direct link between the neuronal solution of the aperture problem and primate perception and action.

Dscam2 mediates axonal tiling in the Drosophila visual system

PubMed Central

Millard, S. Sean; Flanagan, John J.; Pappu, Kartik S.; Wu, Wei; Zipursky, S. Lawrence

2009-01-01

Sensory processing centres in both the vertebrate and the invertebrate brain are often organized into reiterated columns, thus facilitating an internal topographic representation of the external world. Cells within each column are arranged in a stereotyped fashion and form precise patterns of synaptic connections within discrete layers. These connections are largely confined to a single column, thereby preserving the spatial information from the periphery. Other neurons integrate this information by connecting to multiple columns. Restricting axons to columns is conceptually similar to tiling. Axons and dendrites of neighbouring neurons of the same class use tiling to form complete, yet non-overlapping, receptive fields1-3. It is thought that, at the molecular level, cell-surface proteins mediate tiling through contact-dependent repulsive interactions1,2,4,5, but proteins serving this function have not yet been identified. Here we show that the immunoglobulin superfamily member Dscam2 restricts the connections formed by L1 lamina neurons to columns in the Drosophila visual system. Our data support a model in which Dscam2 homophilic interactions mediate repulsion between neurites of L1 cells in neighbouring columns. We propose that Dscam2 is a tiling receptor for L1 neurons. PMID:17554308

Human consciousness and its relationship to social neuroscience: A novel hypothesis

PubMed Central

Graziano, Michael S. A.; Kastner, Sabine

2011-01-01

A common modern view of consciousness is that it is an emergent property of the brain, perhaps caused by neuronal complexity, and perhaps with no adaptive value. Exactly what emerges, how it emerges, and from what specific neuronal process, is in debate. One possible explanation of consciousness, proposed here, is that it is a construct of the social perceptual machinery. Humans have specialized neuronal machinery that allows us to be socially intelligent. The primary role for this machinery is to construct models of other people’s minds thereby gaining some ability to predict the behavior of other individuals. In the present hypothesis, awareness is a perceptual reconstruction of attentional state; and the machinery that computes information about other people’s awareness is the same machinery that computes information about our own awareness. The present article brings together a variety of lines of evidence including experiments on the neural basis of social perception, on hemispatial neglect, on the out-of-body experience, on mirror neurons, and on the mechanisms of decision-making, to explore the possibility that awareness is a construct of the social machinery in the brain. PMID:22121395

The impact of orientation filtering on face-selective neurons in monkey inferior temporal cortex.

PubMed

Taubert, Jessica; Goffaux, Valerie; Van Belle, Goedele; Vanduffel, Wim; Vogels, Rufin

2016-02-16

Faces convey complex social signals to primates. These signals are tolerant of some image transformations (e.g. changes in size) but not others (e.g. picture-plane rotation). By filtering face stimuli for orientation content, studies of human behavior and brain responses have shown that face processing is tuned to selective orientation ranges. In the present study, for the first time, we recorded the responses of face-selective neurons in monkey inferior temporal (IT) cortex to intact and scrambled faces that were filtered to selectively preserve horizontal or vertical information. Guided by functional maps, we recorded neurons in the lateral middle patch (ML), the lateral anterior patch (AL), and an additional region located outside of the functionally defined face-patches (CONTROL). We found that neurons in ML preferred horizontal-passed faces over their vertical-passed counterparts. Neurons in AL, however, had a preference for vertical-passed faces, while neurons in CONTROL had no systematic preference. Importantly, orientation filtering did not modulate the firing rate of neurons to phase-scrambled face stimuli in any recording region. Together these results suggest that face-selective neurons found in the face-selective patches are differentially tuned to orientation content, with horizontal tuning in area ML and vertical tuning in area AL.

Mirror neurons: from origin to function.

PubMed

Cook, Richard; Bird, Geoffrey; Catmur, Caroline; Press, Clare; Heyes, Cecilia

2014-04-01

This article argues that mirror neurons originate in sensorimotor associative learning and therefore a new approach is needed to investigate their functions. Mirror neurons were discovered about 20 years ago in the monkey brain, and there is now evidence that they are also present in the human brain. The intriguing feature of many mirror neurons is that they fire not only when the animal is performing an action, such as grasping an object using a power grip, but also when the animal passively observes a similar action performed by another agent. It is widely believed that mirror neurons are a genetic adaptation for action understanding; that they were designed by evolution to fulfill a specific socio-cognitive function. In contrast, we argue that mirror neurons are forged by domain-general processes of associative learning in the course of individual development, and, although they may have psychological functions, they do not necessarily have a specific evolutionary purpose or adaptive function. The evidence supporting this view shows that (1) mirror neurons do not consistently encode action "goals"; (2) the contingency- and context-sensitive nature of associative learning explains the full range of mirror neuron properties; (3) human infants receive enough sensorimotor experience to support associative learning of mirror neurons ("wealth of the stimulus"); and (4) mirror neurons can be changed in radical ways by sensorimotor training. The associative account implies that reliable information about the function of mirror neurons can be obtained only by research based on developmental history, system-level theory, and careful experimentation.

The pronociceptive dorsal reticular nucleus contains mostly tonic neurons and shows a high prevalence of spontaneous activity in block preparation.

PubMed

Sousa, Mafalda; Szucs, Peter; Lima, Deolinda; Aguiar, Paulo

2014-04-01

Despite the importance and significant clinical impact of understanding information processing in the nociceptive system, the functional properties of neurons in many parts of this system are still unknown. In this work we performed whole cell patch-clamp recording in rat brain stem blocks to characterize the electrophysiological properties of neurons in the dorsal reticular nucleus (DRt), a region known to be involved in pronociceptive modulation. We also compared properties of DRt neurons with those in the adjacent parvicellular reticular nucleus and in neighboring regions outside the reticular formation. We found that neurons in the DRt and parvicellular reticular nucleus had similar electrophysiological properties and exhibited mostly toniclike firing patterns, whereas neurons outside the reticular formation showed a larger diversity of firing patterns. Interestingly, more than one-half of the neurons also showed spontaneous activity. While the general view of the reticular formation, being a loosely associated mesh of groups of neurons with diverse function, and earlier reports suggests more electrophysiological heterogeneity, we showed that this is indeed not the case. Our results indicate that functional difference of neurons in the reticular formation may mostly be determined by their connectivity profiles and not by their intrinsic electrophysiological properties. The dominance of tonic neurons in the DRt supports previous conclusions that these neurons encode stimulus intensity through their firing frequency, while the high prevalence of spontaneous activity most likely shapes nociceptive modulation by this brain stem region.

Object size determines the spatial spread of visual time

PubMed Central

McGraw, Paul V.; Roach, Neil W.; Whitaker, David

2016-01-01

A key question for temporal processing research is how the nervous system extracts event duration, despite a notable lack of neural structures dedicated to duration encoding. This is in stark contrast with the orderly arrangement of neurons tasked with spatial processing. In this study, we examine the linkage between the spatial and temporal domains. We use sensory adaptation techniques to generate after-effects where perceived duration is either compressed or expanded in the opposite direction to the adapting stimulus' duration. Our results indicate that these after-effects are broadly tuned, extending over an area approximately five times the size of the stimulus. This region is directly related to the size of the adapting stimulus—the larger the adapting stimulus the greater the spatial spread of the after-effect. We construct a simple model to test predictions based on overlapping adapted versus non-adapted neuronal populations and show that our effects cannot be explained by any single, fixed-scale neural filtering. Rather, our effects are best explained by a self-scaled mechanism underpinned by duration selective neurons that also pool spatial information across earlier stages of visual processing. PMID:27466452

Feeling form: the neural basis of haptic shape perception.

PubMed

Yau, Jeffrey M; Kim, Sung Soo; Thakur, Pramodsingh H; Bensmaia, Sliman J

2016-02-01

The tactile perception of the shape of objects critically guides our ability to interact with them. In this review, we describe how shape information is processed as it ascends the somatosensory neuraxis of primates. At the somatosensory periphery, spatial form is represented in the spatial patterns of activation evoked across populations of mechanoreceptive afferents. In the cerebral cortex, neurons respond selectively to particular spatial features, like orientation and curvature. While feature selectivity of neurons in the earlier processing stages can be understood in terms of linear receptive field models, higher order somatosensory neurons exhibit nonlinear response properties that result in tuning for more complex geometrical features. In fact, tactile shape processing bears remarkable analogies to its visual counterpart and the two may rely on shared neural circuitry. Furthermore, one of the unique aspects of primate somatosensation is that it contains a deformable sensory sheet. Because the relative positions of cutaneous mechanoreceptors depend on the conformation of the hand, the haptic perception of three-dimensional objects requires the integration of cutaneous and proprioceptive signals, an integration that is observed throughout somatosensory cortex. Copyright © 2016 the American Physiological Society.

A Class of Visual Neurons with Wide-Field Properties Is Required for Local Motion Detection.

PubMed

Fisher, Yvette E; Leong, Jonathan C S; Sporar, Katja; Ketkar, Madhura D; Gohl, Daryl M; Clandinin, Thomas R; Silies, Marion

2015-12-21

Visual motion cues are used by many animals to guide navigation across a wide range of environments. Long-standing theoretical models have made predictions about the computations that compare light signals across space and time to detect motion. Using connectomic and physiological approaches, candidate circuits that can implement various algorithmic steps have been proposed in the Drosophila visual system. These pathways connect photoreceptors, via interneurons in the lamina and the medulla, to direction-selective cells in the lobula and lobula plate. However, the functional architecture of these circuits remains incompletely understood. Here, we use a forward genetic approach to identify the medulla neuron Tm9 as critical for motion-evoked behavioral responses. Using in vivo calcium imaging combined with genetic silencing, we place Tm9 within motion-detecting circuitry. Tm9 receives functional inputs from the lamina neurons L3 and, unexpectedly, L1 and passes information onto the direction-selective T5 neuron. Whereas the morphology of Tm9 suggested that this cell would inform circuits about local points in space, we found that the Tm9 spatial receptive field is large. Thus, this circuit informs elementary motion detectors about a wide region of the visual scene. In addition, Tm9 exhibits sustained responses that provide a tonic signal about incoming light patterns. Silencing Tm9 dramatically reduces the response amplitude of T5 neurons under a broad range of different motion conditions. Thus, our data demonstrate that sustained and wide-field signals are essential for elementary motion processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integration of Canal and Otolith Inputs by Central Vestibular Neurons Is Subadditive for Both Active and Passive Self-Motion: Implication for Perception

PubMed Central

Carriot, Jerome; Jamali, Mohsen; Brooks, Jessica X.

2015-01-01

Traditionally, the neural encoding of vestibular information is studied by applying either passive rotations or translations in isolation. However, natural vestibular stimuli are typically more complex. During everyday life, our self-motion is generally not restricted to one dimension, but rather comprises both rotational and translational motion that will simultaneously stimulate receptors in the semicircular canals and otoliths. In addition, natural self-motion is the result of self-generated and externally generated movements. However, to date, it remains unknown how information about rotational and translational components of self-motion is integrated by vestibular pathways during active and/or passive motion. Accordingly, here, we compared the responses of neurons at the first central stage of vestibular processing to rotation, translation, and combined motion. Recordings were made in alert macaques from neurons in the vestibular nuclei involved in postural control and self-motion perception. In response to passive stimulation, neurons did not combine canal and otolith afferent information linearly. Instead, inputs were subadditively integrated with a weighting that was frequency dependent. Although canal inputs were more heavily weighted at low frequencies, the weighting of otolith input increased with frequency. In response to active stimulation, neuronal modulation was significantly attenuated (∼70%) relative to passive stimulation for rotations and translations and even more profoundly attenuated for combined motion due to subadditive input integration. Together, these findings provide insights into neural computations underlying the integration of semicircular canal and otolith inputs required for accurate posture and motor control, as well as perceptual stability, during everyday life. PMID:25716854

Spinal cord processing of cardiac nociception: are there sex differences between male and proestrous female rats?

PubMed

Little, Janine M; Qin, Chao; Farber, Jay P; Foreman, Robert D

2011-09-21

Sex differences in the characteristics of cardiac pain have been reported from clinical studies. For example, women experience chest pain less frequently than men. Women describe their chest pain as sharp and stabbing, while men have chest pain that is felt as a pressure or heaviness. Pain is also referred to the back more often in women than men. The mechanisms underlying sex differences in cardiac pain are unknown. One possible mechanism for the observed differences could be related to plasma estradiol. This study investigated the actions of estradiol on the activity of T(3) spinal neurons that process cardiosomatic information in male and female rats. Extracellular potentials of T(3) spinal neurons were recorded in response to mechanical somatic stimulation and noxious chemical cardiac stimulation in pentobarbital-anesthetized male and proestrous female rats. Fifty one percent and fifty percent of neurons responded to intrapericardial algogenic chemicals (0.2 ml) in male and female rats, respectively. Somatic fields were located by applying brush, pressure, and pinch to the upper body. Of those neurons receiving cardiac input, 54% in female and 55% in male rats also received somatic input. In both male and female rats, 81% of neurons responding to somatic stimuli had somatic fields located on the side of the upper body, while 19% of neurons had somatic fields located on the chest. These results indicate there are no significant differences in the responses of T(3) spinal neurons to cardiosomatic stimulation between male and proestrous female rats, despite differences in estradiol levels. Published by Elsevier B.V.

View-Invariant Visuomotor Processing in Computational Mirror Neuron System for Humanoid

PubMed Central

Dawood, Farhan; Loo, Chu Kiong

2016-01-01

Mirror neurons are visuo-motor neurons found in primates and thought to be significant for imitation learning. The proposition that mirror neurons result from associative learning while the neonate observes his own actions has received noteworthy empirical support. Self-exploration is regarded as a procedure by which infants become perceptually observant to their own body and engage in a perceptual communication with themselves. We assume that crude sense of self is the prerequisite for social interaction. However, the contribution of mirror neurons in encoding the perspective from which the motor acts of others are seen have not been addressed in relation to humanoid robots. In this paper we present a computational model for development of mirror neuron system for humanoid based on the hypothesis that infants acquire MNS by sensorimotor associative learning through self-exploration capable of sustaining early imitation skills. The purpose of our proposed model is to take into account the view-dependency of neurons as a probable outcome of the associative connectivity between motor and visual information. In our experiment, a humanoid robot stands in front of a mirror (represented through self-image using camera) in order to obtain the associative relationship between his own motor generated actions and his own visual body-image. In the learning process the network first forms mapping from each motor representation onto visual representation from the self-exploratory perspective. Afterwards, the representation of the motor commands is learned to be associated with all possible visual perspectives. The complete architecture was evaluated by simulation experiments performed on DARwIn-OP humanoid robot. PMID:26998923

View-Invariant Visuomotor Processing in Computational Mirror Neuron System for Humanoid.

PubMed

Dawood, Farhan; Loo, Chu Kiong

2016-01-01

Mirror neurons are visuo-motor neurons found in primates and thought to be significant for imitation learning. The proposition that mirror neurons result from associative learning while the neonate observes his own actions has received noteworthy empirical support. Self-exploration is regarded as a procedure by which infants become perceptually observant to their own body and engage in a perceptual communication with themselves. We assume that crude sense of self is the prerequisite for social interaction. However, the contribution of mirror neurons in encoding the perspective from which the motor acts of others are seen have not been addressed in relation to humanoid robots. In this paper we present a computational model for development of mirror neuron system for humanoid based on the hypothesis that infants acquire MNS by sensorimotor associative learning through self-exploration capable of sustaining early imitation skills. The purpose of our proposed model is to take into account the view-dependency of neurons as a probable outcome of the associative connectivity between motor and visual information. In our experiment, a humanoid robot stands in front of a mirror (represented through self-image using camera) in order to obtain the associative relationship between his own motor generated actions and his own visual body-image. In the learning process the network first forms mapping from each motor representation onto visual representation from the self-exploratory perspective. Afterwards, the representation of the motor commands is learned to be associated with all possible visual perspectives. The complete architecture was evaluated by simulation experiments performed on DARwIn-OP humanoid robot.

Off the beaten path: drug addiction and the pontine laterodorsal tegmentum.

PubMed

Kohlmeier, Kristi A

2013-01-01

Drug addiction is a multileveled behavior controlled by interactions among many diverse neuronal groups involving several neurotransmitter systems. The involvement of brainstem-sourced, cholinergic neurotransmission in the development of addiction and in the persistent physiological processes that drive this maladaptive behavior has not been widely investigated. The major cholinergic input to neurons in the midbrain which are instrumental in assessment of reward and assignment of salience to stimuli, including drugs of abuse, sources from acetylcholine- (ACh-) containing pontine neurons of the laterodorsal tegmentum (LDT). Excitatory LDT input, likely cholinergic, is critical in allowing behaviorally relevant neuronal firing patterns within midbrain reward circuitry. Via this control, the LDT is positioned to be importantly involved in development of compulsive, addictive patterns of behavior. The goal of this review is to present the anatomical, physiological, and behavioral evidence suggesting a role of the LDT in the neurobiology underlying addiction to drugs of abuse. Although focus is directed on the evidence supporting a vital participation of the cholinergic neurons of the LDT, data indicating a contribution of noncholinergic LDT neurons to processes underlying addiction are also reviewed. While sparse, available information of actions of drugs of abuse on LDT cells and the output of these neurons as well as their influence on addiction-related behavior are also presented. Taken together, data from studies presented in this review strongly support the position that the LDT is a major player in the neurobiology of drug addiction. Accordingly, the LDT may serve as a future treatment target for efficacious pharmaceutical combat of drug addiction.

Off the Beaten Path: Drug Addiction and the Pontine Laterodorsal Tegmentum

PubMed Central

2013-01-01

Drug addiction is a multileveled behavior controlled by interactions among many diverse neuronal groups involving several neurotransmitter systems. The involvement of brainstem-sourced, cholinergic neurotransmission in the development of addiction and in the persistent physiological processes that drive this maladaptive behavior has not been widely investigated. The major cholinergic input to neurons in the midbrain which are instrumental in assessment of reward and assignment of salience to stimuli, including drugs of abuse, sources from acetylcholine- (ACh-) containing pontine neurons of the laterodorsal tegmentum (LDT). Excitatory LDT input, likely cholinergic, is critical in allowing behaviorally relevant neuronal firing patterns within midbrain reward circuitry. Via this control, the LDT is positioned to be importantly involved in development of compulsive, addictive patterns of behavior. The goal of this review is to present the anatomical, physiological, and behavioral evidence suggesting a role of the LDT in the neurobiology underlying addiction to drugs of abuse. Although focus is directed on the evidence supporting a vital participation of the cholinergic neurons of the LDT, data indicating a contribution of noncholinergic LDT neurons to processes underlying addiction are also reviewed. While sparse, available information of actions of drugs of abuse on LDT cells and the output of these neurons as well as their influence on addiction-related behavior are also presented. Taken together, data from studies presented in this review strongly support the position that the LDT is a major player in the neurobiology of drug addiction. Accordingly, the LDT may serve as a future treatment target for efficacious pharmaceutical combat of drug addiction. PMID:24959564

Social information signaling by neurons in primate striatum.

PubMed

Klein, Jeffrey T; Platt, Michael L

2013-04-22

Social decisions depend on reliable information about others. Consequently, social primates are motivated to acquire information about the identity, social status, and reproductive quality of others. Neurophysiological and neuroimaging studies implicate the striatum in the motivational control of behavior. Neuroimaging studies specifically implicate the ventromedial striatum in signaling motivational aspects of social interaction. Despite this evidence, precisely how striatal neurons encode social information remains unknown. Therefore, we probed the activity of single striatal neurons in monkeys choosing between visual social information at the potential expense of fluid reward. We show for the first time that a population of neurons located primarily in medial striatum selectively signals social information. Surprisingly, representation of social information was unrelated to simultaneously expressed social preferences. A largely nonoverlapping population of neurons that was not restricted to the medial striatum signaled information about fluid reward. Our findings demonstrate that information about social context and nutritive reward are maintained largely independently in striatum, even when both influence decisions to execute a single action. Copyright © 2013 Elsevier Ltd. All rights reserved.

Influence of highly distinctive structural properties on the excitability of pyramidal neurons in monkey visual and prefrontal cortices

PubMed Central

Amatrudo, Joseph M.; Weaver, Christina M.; Crimins, Johanna L.; Hof, Patrick R.; Rosene, Douglas L.; Luebke, Jennifer I.

2012-01-01

Whole-cell patch-clamp recordings and high-resolution 3D morphometric analyses of layer 3 pyramidal neurons in in vitro slices of monkey primary visual cortex (V1) and dorsolateral granular prefrontal cortex (dlPFC) revealed that neurons in these two brain areas possess highly distinctive structural and functional properties. Area V1 pyramidal neurons are much smaller than dlPFC neurons, with significantly less extensive dendritic arbors and far fewer dendritic spines. Relative to dlPFC neurons, V1 neurons have a significantly higher input resistance, depolarized resting membrane potential and higher action potential (AP) firing rates. Most V1 neurons exhibit both phasic and regular-spiking tonic AP firing patterns, while dlPFC neurons exhibit only tonic firing. Spontaneous postsynaptic currents are lower in amplitude and have faster kinetics in V1 than in dlPFC neurons, but are no different in frequency. Three-dimensional reconstructions of V1 and dlPFC neurons were incorporated into computational models containing Hodgkin-Huxley and AMPA- and GABAA-receptor gated channels. Morphology alone largely accounted for observed passive physiological properties, but led to AP firing rates that differed more than observed empirically, and to synaptic responses that opposed empirical results. Accordingly, modeling predicts that active channel conductances differ between V1 and dlPFC neurons. The unique features of V1 and dlPFC neurons are likely fundamental determinants of area-specific network behavior. The compact electrotonic arbor and increased excitability of V1 neurons support the rapid signal integration required for early processing of visual information. The greater connectivity and dendritic complexity of dlPFC neurons likely support higher level cognitive functions including working memory and planning. PMID:23035077

Early Brain Damage and the Development of Motor Behavior in Children: Clues for Therapeutic Intervention?

PubMed Central

Hadders-Algra, Mijna

2001-01-01

The Neuronal Group Selection Theory (NGST) could offer new insights into the mechanisms directing motor disorders, such as cerebral palsy and developmental coordination disorder. According to NGST, normal motor development is characterized by two phases of variability. Variation is not at random but determined by criteria set by genetic information. Development starts with the phase of primary variability,during which variation in motor behavior is not geared to external conditions. At function-specific ages secondary variability starts, during which motor performance can be adapted to specific situations. In both forms, of variability, selection on the basis of afferent information plays a significant role. From the NGST point of view, children with pre- or perinatally acquired brain damage, such as children with cerebral palsy and part of the children with developmental coordination disorder, suffer from stereotyped motor behavior, produced by a limited repertoire or primary (sub)cortical neuronal networks. These children also have roblems in selecting the most efficient neuronal activity, due to deficits in the processing of sensory information. Therefore, NGST suggests that intervention in these children at early age should aim at an enlargement of the primary neuronal networks. With increasing age, the emphasis of intervention could shift to the provision of ample opportunities for active practice, which might form a compensation for the impaired selection. PMID:11530887

Neural population encoding and decoding of sound source location across sound level in the rabbit inferior colliculus

PubMed Central

Delgutte, Bertrand

2015-01-01

At lower levels of sensory processing, the representation of a stimulus feature in the response of a neural population can vary in complex ways across different stimulus intensities, potentially changing the amount of feature-relevant information in the response. How higher-level neural circuits could implement feature decoding computations that compensate for these intensity-dependent variations remains unclear. Here we focused on neurons in the inferior colliculus (IC) of unanesthetized rabbits, whose firing rates are sensitive to both the azimuthal position of a sound source and its sound level. We found that the azimuth tuning curves of an IC neuron at different sound levels tend to be linear transformations of each other. These transformations could either increase or decrease the mutual information between source azimuth and spike count with increasing level for individual neurons, yet population azimuthal information remained constant across the absolute sound levels tested (35, 50, and 65 dB SPL), as inferred from the performance of a maximum-likelihood neural population decoder. We harnessed evidence of level-dependent linear transformations to reduce the number of free parameters in the creation of an accurate cross-level population decoder of azimuth. Interestingly, this decoder predicts monotonic azimuth tuning curves, broadly sensitive to contralateral azimuths, in neurons at higher levels in the auditory pathway. PMID:26490292

Effects of perinatal undernutrition on the development of neurons in the rat insular cortex.

PubMed

Salas, Manuel; Torrero, Carmen; Rubio, Lorena; Regalado, Mirelta

2012-09-01

The insular cortex (IC) of the rat is a major area for the convergence and integration of olfactory, gustatory, and visual information, and at present it is unclear if perinatal undernutrition interferes with the structure and function of the IC neurons. Golgi-Cox-stained cells of the IC were studied in control and undernourished Wistar rats at 12, 20, and 30 days of age. Pregnant dams were undernourished by the reduction of a balanced diet during a part of the gestational period (G6-G18). After parturition (P1-P23) pups remained for 12 hours with a normal and 12 hours with a nipple-ligated dam. Undernutrition significantly reduced the number, and the arborization of the dendritic arbors, and the perimeter, and cross-sectional area of perikarya. The IC neuronal morphology appearances suggest a possible mechanism for the impairment in information processing of complex phenomena such as taste sensation and hedonic response.

Deconstructing brain-derived neurotrophic factor actions in adult brain circuits to bridge an existing informational gap in neuro-cell biology.

PubMed

Bowling, Heather; Bhattacharya, Aditi; Klann, Eric; Chao, Moses V

2016-03-01

Brain-derived neurotrophic factor (BDNF) plays an important role in neurodevelopment, synaptic plasticity, learning and memory, and in preventing neurodegeneration. Despite decades of investigations into downstream signaling cascades and changes in cellular processes, the mechanisms of how BDNF reshapes circuits in vivo remain unclear. This informational gap partly arises from the fact that the bulk of studies into the molecular actions of BDNF have been performed in dissociated neuronal cultures, while the majority of studies on synaptic plasticity, learning and memory were performed in acute brain slices or in vivo. A recent study by Bowling-Bhattacharya et al., measured the proteomic changes in acute adult hippocampal slices following treatment and reported changes in proteins of neuronal and non-neuronal origin that may in concert modulate synaptic release and secretion in the slice. In this paper, we place these findings into the context of existing literature and discuss how they impact our understanding of how BDNF can reshape the brain.

DL-ReSuMe: A Delay Learning-Based Remote Supervised Method for Spiking Neurons.

PubMed

Taherkhani, Aboozar; Belatreche, Ammar; Li, Yuhua; Maguire, Liam P

2015-12-01

Recent research has shown the potential capability of spiking neural networks (SNNs) to model complex information processing in the brain. There is biological evidence to prove the use of the precise timing of spikes for information coding. However, the exact learning mechanism in which the neuron is trained to fire at precise times remains an open problem. The majority of the existing learning methods for SNNs are based on weight adjustment. However, there is also biological evidence that the synaptic delay is not constant. In this paper, a learning method for spiking neurons, called delay learning remote supervised method (DL-ReSuMe), is proposed to merge the delay shift approach and ReSuMe-based weight adjustment to enhance the learning performance. DL-ReSuMe uses more biologically plausible properties, such as delay learning, and needs less weight adjustment than ReSuMe. Simulation results have shown that the proposed DL-ReSuMe approach achieves learning accuracy and learning speed improvements compared with ReSuMe.

Decoding a Decision Process in the Neuronal Population of Dorsal Premotor Cortex.

PubMed

Rossi-Pool, Román; Zainos, Antonio; Alvarez, Manuel; Zizumbo, Jerónimo; Vergara, José; Romo, Ranulfo

2017-12-20

When trained monkeys discriminate the temporal structure of two sequential vibrotactile stimuli, dorsal premotor cortex (DPC) showed high heterogeneity among its neuronal responses. Notably, DPC neurons coded stimulus patterns as broader categories and signaled them during working memory, comparison, and postponed decision periods. Here, we show that such population activity can be condensed into two major coding components: one that persistently represented in working memory both the first stimulus identity and the postponed informed choice and another that transiently coded the initial sensory information and the result of the comparison between the two stimuli. Additionally, we identified relevant signals that coded the timing of task events. These temporal and task-parameter readouts were shown to be strongly linked to the monkeys' behavior when contrasted to those obtained in a non-demanding cognitive control task and during error trials. These signals, hidden in the heterogeneity, were prominently represented by the DPC population response. Copyright © 2017 Elsevier Inc. All rights reserved.

Optical dissection of odor information processing in vivo using GCaMPs expressed in specified cell types of the olfactory bulb

PubMed Central

Wachowiak, Matt; Economo, Michael N.; Díaz-Quesada, Marta; Brunert, Daniela; Wesson, Daniel W.; White, John. A.; Rothermel, Markus

2013-01-01

Understanding central processing requires precise monitoring of neural activity across populations of identified neurons in the intact brain. Here we used recently-optimized variants of the genetically-encoded calcium sensor GCaMP (GCaMP3 and GCaMPG5G) to image activity among genetically- and anatomically-defined neuronal populations in the olfactory bulb (OB), including two types of GABA-ergic interneurons (periglomerular (PG) and short axon (SA) cells) and OB output neurons (mitral/tufted (MT) cells) projecting to piriform cortex. We first established that changes in neuronal spiking can be accurately related to GCaMP fluorescence changes via a simple quantitative relationship over a large dynamic range. We next used in vivo two-photon imaging from individual neurons and epifluorescence signals reflecting population-level activity to investigate the spatiotemporal representation of odorants across these neuron types in anesthetized and awake mice. Under anesthesia, individual PG and SA cells showed temporally simple responses and little spontaneous activity, while MT cells were spontaneously active and showed diverse temporal responses. At the population level, response patterns of PG, SA and MT cells were surprisingly similar to those imaged from sensory inputs, with shared odorant-specific topography across the dorsal OB and inhalation-coupled temporal dynamics. During wakefulness, PG and SA cell responses increased in magnitude but remained temporally simple while those of MT cells changed to complex spatiotemporal patterns reflecting restricted excitation and widespread inhibition. These results point to multiple circuit elements with distinct roles in transforming odor representations in the OB and provide a framework for further dissecting early olfactory processing using optical and genetic tools. PMID:23516293

Encoding of sound envelope transients in the auditory cortex of juvenile rats and adult rats.

PubMed

Lu, Qi; Jiang, Cuiping; Zhang, Jiping

2016-02-01

Accurate neural processing of time-varying sound amplitude and spectral information is vital for species-specific communication. During postnatal development, cortical processing of sound frequency undergoes progressive refinement; however, it is not clear whether cortical processing of sound envelope transients also undergoes age-related changes. We determined the dependence of neural response strength and first-spike latency on sound rise-fall time across sound levels in the primary auditory cortex (A1) of juvenile (P20-P30) rats and adult (8-10 weeks) rats. A1 neurons were categorized as "all-pass", "short-pass", or "mixed" ("all-pass" at high sound levels to "short-pass" at lower sound levels) based on the normalized response strength vs. rise-fall time functions across sound levels. The proportions of A1 neurons within each of the three categories in juvenile rats were similar to that in adult rats. In general, with increasing rise-fall time, the average response strength decreased and the average first-spike latency increased in A1 neurons of both groups. At a given sound level and rise-fall time, the average normalized neural response strength did not differ significantly between the two age groups. However, the A1 neurons in juvenile rats showed greater absolute response strength, longer first-spike latency compared to those in adult rats. In addition, at a constant sound level, the average first-spike latency of juvenile A1 neurons was more sensitive to changes in rise-fall time. Our results demonstrate the dependence of the responses of rat A1 neurons on sound rise-fall time, and suggest that the response latency exhibit some age-related changes in cortical representation of sound envelope rise time. Copyright © 2015 Elsevier Ltd. All rights reserved.

Information transfer with rate-modulated Poisson processes: a simple model for nonstationary stochastic resonance.

PubMed

Goychuk, I

2001-08-01

Stochastic resonance in a simple model of information transfer is studied for sensory neurons and ensembles of ion channels. An exact expression for the information gain is obtained for the Poisson process with the signal-modulated spiking rate. This result allows one to generalize the conventional stochastic resonance (SR) problem (with periodic input signal) to the arbitrary signals of finite duration (nonstationary SR). Moreover, in the case of a periodic signal, the rate of information gain is compared with the conventional signal-to-noise ratio. The paper establishes the general nonequivalence between both measures notwithstanding their apparent similarity in the limit of weak signals.

Differential encoding of factors influencing predicted reward value in monkey rostral anterior cingulate cortex.

PubMed

Toda, Koji; Sugase-Miyamoto, Yasuko; Mizuhiki, Takashi; Inaba, Kiyonori; Richmond, Barry J; Shidara, Munetaka

2012-01-01

The value of a predicted reward can be estimated based on the conjunction of both the intrinsic reward value and the length of time to obtain it. The question we addressed is how the two aspects, reward size and proximity to reward, influence the responses of neurons in rostral anterior cingulate cortex (rACC), a brain region thought to play an important role in reward processing. We recorded from single neurons while two monkeys performed a multi-trial reward schedule task. The monkeys performed 1-4 sequential color discrimination trials to obtain a reward of 1-3 liquid drops. There were two task conditions, a valid cue condition, where the number of trials and reward amount were associated with visual cues, and a random cue condition, where the cue was picked from the cue set at random. In the valid cue condition, the neuronal firing is strongly modulated by the predicted reward proximity during the trials. Information about the predicted reward amount is almost absent at those times. In substantial subpopulations, the neuronal responses decreased or increased gradually through schedule progress to the predicted outcome. These two gradually modulating signals could be used to calculate the effect of time on the perception of reward value. In the random cue condition, little information about the reward proximity or reward amount is encoded during the course of the trial before reward delivery, but when the reward is actually delivered the responses reflect both the reward proximity and reward amount. Our results suggest that the rACC neurons encode information about reward proximity and amount in a manner that is dependent on utility of reward information. The manner in which the information is represented could be used in the moment-to-moment calculation of the effect of time and amount on predicted outcome value.

Do we track what we see? Common versus independent processing for motion perception and smooth pursuit eye movements: a review.

PubMed

Spering, Miriam; Montagnini, Anna

2011-04-22

Many neurophysiological studies in monkeys have indicated that visual motion information for the guidance of perception and smooth pursuit eye movements is - at an early stage - processed in the same visual pathway in the brain, crucially involving the middle temporal area (MT). However, these studies left some questions unanswered: Are perception and pursuit driven by the same or independent neuronal signals within this pathway? Are the perceptual interpretation of visual motion information and the motor response to visual signals limited by the same source of neuronal noise? Here, we review psychophysical studies that were motivated by these questions and compared perception and pursuit behaviorally in healthy human observers. We further review studies that focused on the interaction between perception and pursuit. The majority of results point to similarities between perception and pursuit, but dissociations were also reported. We discuss recent developments in this research area and conclude with suggestions for common and separate principles for the guidance of perceptual and motor responses to visual motion information. Copyright © 2010 Elsevier Ltd. All rights reserved.

Efficient processing of fluorescence images using directional multiscale representations.

PubMed

Labate, D; Laezza, F; Negi, P; Ozcan, B; Papadakis, M

2014-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data.

Efficient processing of fluorescence images using directional multiscale representations

PubMed Central

Labate, D.; Laezza, F.; Negi, P.; Ozcan, B.; Papadakis, M.

2017-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data. PMID:28804225

A critical role for Piezo2 channels in the mechanotransduction of mouse proprioceptive neurons

PubMed Central

Florez-Paz, Danny; Bali, Kiran Kumar; Kuner, Rohini; Gomis, Ana

2016-01-01

Proprioceptors are responsible for the conscious sensation of limb position and movement, muscle tension or force, and balance. Recent evidence suggests that Piezo2 is a low threshold mechanosensory receptor in the peripheral nervous system, acting as a transducer for touch sensation and proprioception. Thus, we characterized proprioceptive neurons in the mesencephalic trigeminal nucleus that are involved in processing proprioceptive information from the face and oral cavity. This is a specific population of neurons that produce rapidly adapting mechanically-activated currents that are fully dependent on Piezo2. As such, we analyzed the deficits in balance and coordination caused by the selective deletion of the channel in proprioceptors (conditional knockout). The data clearly shows that Piezo2 fulfills a critical role in a defined homogeneous population of proprioceptor neurons that innervate the head muscles, demonstrating that this ion channel is essential for mammalian proprioceptive mechanotransduction. PMID:27184818

SINGLE NEURON ACTIVITY AND THETA MODULATION IN POSTRHINAL CORTEX DURING VISUAL OBJECT DISCRIMINATION

PubMed Central

Furtak, Sharon C.; Ahmed, Omar J.; Burwell, Rebecca D.

2012-01-01

Postrhinal cortex, the rodent homolog of the primate parahippocampal cortex, processes spatial and contextual information. Our hypothesis of postrhinal function is that it serves to encode context, in part, by forming representations that link objects to places. We recorded postrhinal neuronal activity and local field potentials (LFPs) in rats trained on a two-choice, visual discrimination task. As predicted, a large proportion of postrhinal neurons signaled object-location conjunctions. In addition, postrhinal LFPs exhibited strong oscillatory rhythms in the theta band, and many postrhinal neurons were phase locked to theta. Although correlated with running speed, theta power was lower than predicted by speed alone immediately before and after choice. However, theta power was significantly increased following incorrect decisions, suggesting a role in signaling error. These findings provide evidence that postrhinal cortex encodes representations that link objects to places and suggest that postrhinal theta modulation extends to cognitive as well as spatial functions. PMID:23217745

Cell Assembly Dynamics of Sparsely-Connected Inhibitory Networks: A Simple Model for the Collective Activity of Striatal Projection Neurons.

PubMed

Angulo-Garcia, David; Berke, Joshua D; Torcini, Alessandro

2016-02-01

Striatal projection neurons form a sparsely-connected inhibitory network, and this arrangement may be essential for the appropriate temporal organization of behavior. Here we show that a simplified, sparse inhibitory network of Leaky-Integrate-and-Fire neurons can reproduce some key features of striatal population activity, as observed in brain slices. In particular we develop a new metric to determine the conditions under which sparse inhibitory networks form anti-correlated cell assemblies with time-varying activity of individual cells. We find that under these conditions the network displays an input-specific sequence of cell assembly switching, that effectively discriminates similar inputs. Our results support the proposal that GABAergic connections between striatal projection neurons allow stimulus-selective, temporally-extended sequential activation of cell assemblies. Furthermore, we help to show how altered intrastriatal GABAergic signaling may produce aberrant network-level information processing in disorders such as Parkinson's and Huntington's diseases.

Random synaptic feedback weights support error backpropagation for deep learning

NASA Astrophysics Data System (ADS)

Lillicrap, Timothy P.; Cownden, Daniel; Tweed, Douglas B.; Akerman, Colin J.

2016-11-01

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning.

Selective and graded coding of reward-uncertainty by neurons in the primate anterodorsal septal region

PubMed Central

Monosov, Ilya E.; Hikosaka, Okihide

2014-01-01

Natural environments are uncertain. Uncertainty of emotional outcomes can induce anxiety and raise vigilance, promote and signal the opportunity for learning, modulate economic choice, and regulate risk seeking. Here we demonstrate that a subset of neurons in the anterodorsal region of the primate septum (ADS) are primarily devoted to processing uncertainty in a highly specific manner. Those neurons were selectively activated by visual cues indicating probabilistic delivery of reward (e.g. 25%, 50%, 75% reward) and did not respond to cues indicating certain outcomes (0% and 100% reward). The average ADS uncertainty response was graded with the magnitude of reward uncertainty, and selectively signaled uncertainty about rewards rather than punishments. The selective and graded information about reward uncertainty encoded by many neurons in the ADS may underlie uncertainty-modulation of value- and sensorimotor- related areas to regulate goal-directed behavior. PMID:23666181

Random synaptic feedback weights support error backpropagation for deep learning

PubMed Central

Lillicrap, Timothy P.; Cownden, Daniel; Tweed, Douglas B.; Akerman, Colin J.

2016-01-01

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning. PMID:27824044

Visually Evoked 3-5 Hz Membrane Potential Oscillations Reduce the Responsiveness of Visual Cortex Neurons in Awake Behaving Mice.

PubMed

Einstein, Michael C; Polack, Pierre-Olivier; Tran, Duy T; Golshani, Peyman

2017-05-17

Low-frequency membrane potential ( V m ) oscillations were once thought to only occur in sleeping and anesthetized states. Recently, low-frequency V m oscillations have been described in inactive awake animals, but it is unclear whether they shape sensory processing in neurons and whether they occur during active awake behavioral states. To answer these questions, we performed two-photon guided whole-cell V m recordings from primary visual cortex layer 2/3 excitatory and inhibitory neurons in awake mice during passive visual stimulation and performance of visual and auditory discrimination tasks. We recorded stereotyped 3-5 Hz V m oscillations where the V m baseline hyperpolarized as the V m underwent high amplitude rhythmic fluctuations lasting 1-2 s in duration. When 3-5 Hz V m oscillations coincided with visual cues, excitatory neuron responses to preferred cues were significantly reduced. Despite this disruption to sensory processing, visual cues were critical for evoking 3-5 Hz V m oscillations when animals performed discrimination tasks and passively viewed drifting grating stimuli. Using pupillometry and animal locomotive speed as indicators of arousal, we found that 3-5 Hz oscillations were not restricted to unaroused states and that they occurred equally in aroused and unaroused states. Therefore, low-frequency V m oscillations play a role in shaping sensory processing in visual cortical neurons, even during active wakefulness and decision making. SIGNIFICANCE STATEMENT A neuron's membrane potential ( V m ) strongly shapes how information is processed in sensory cortices of awake animals. Yet, very little is known about how low-frequency V m oscillations influence sensory processing and whether they occur in aroused awake animals. By performing two-photon guided whole-cell recordings from layer 2/3 excitatory and inhibitory neurons in the visual cortex of awake behaving animals, we found visually evoked stereotyped 3-5 Hz V m oscillations that disrupt excitatory responsiveness to visual stimuli. Moreover, these oscillations occurred when animals were in high and low arousal states as measured by animal speed and pupillometry. These findings show, for the first time, that low-frequency V m oscillations can significantly modulate sensory signal processing, even in awake active animals. Copyright © 2017 the authors 0270-6474/17/375084-15$15.00/0.

Homeobox gene distal-less is required for neuronal differentiation and neurite outgrowth in the Drosophila olfactory system

PubMed Central

Plavicki, Jessica; Mader, Sara; Pueschel, Eric; Peebles, Patrick; Boekhoff-Falk, Grace

2012-01-01

Vertebrate Dlx genes have been implicated in the differentiation of multiple neuronal subtypes, including cortical GABAergic interneurons, and mutations in Dlx genes have been linked to clinical conditions such as epilepsy and autism. Here we show that the single Drosophila Dlx homolog, distal-less, is required both to specify chemosensory neurons and to regulate the morphologies of their axons and dendrites. We establish that distal-less is necessary for development of the mushroom body, a brain region that processes olfactory information. These are important examples of distal-less function in an invertebrate nervous system and demonstrate that the Drosophila larval olfactory system is a powerful model in which to understand distal-less functions during neurogenesis. PMID:22307614

Brain Energetics During the Sleep-Wake Cycle

PubMed Central

DiNuzzo, Mauro; Nedergaard, Maiken

2017-01-01

Brain activity during wakefulness is associated with high metabolic rates that are believed to support information processing and memory encoding. In spite of loss of consciousness, sleep still carries a substantial energy cost. Experimental evidence supports a cerebral metabolic shift taking place during sleep that suppresses aerobic glycolysis, a hallmark of environment-oriented waking behavior and synaptic plasticity. Recent studies reveal that glial astrocytes respond to the reduction of wake-promoting neuromodulators by regulating volume, composition and glymphatic drainage of interstitial fluid. These events are accompanied by changes in neuronal discharge patterns, astrocyte-neuron interactions, synaptic transactions and underlying metabolic features. Internally-generated neuronal activity and network homeostasis are proposed to account for the high sleep-related energy demand. PMID:29024871

Convergence of limb, visceral, and vertical semicircular canal or otolith inputs onto vestibular nucleus neurons

NASA Technical Reports Server (NTRS)

Jian, B. J.; Shintani, T.; Emanuel, B. A.; Yates, B. J.

2002-01-01

The major goal of this study was to determine the patterns of convergence of non-labyrinthine inputs from the limbs and viscera onto vestibular nucleus neurons receiving signals from vertical semicircular canals or otolith organs. A secondary aim was to ascertain whether the effects of non-labyrinthine inputs on the activity of vestibular nucleus neurons is affected by bilateral peripheral vestibular lesions. The majority (72%) of vestibular nucleus neurons in labyrinth-intact animals whose firing was modulated by vertical rotations responded to electrical stimulation of limb and/or visceral nerves. The activity of even more vestibular nucleus neurons (93%) was affected by limb or visceral nerve stimulation in chronically labyrinthectomized preparations. Some neurons received non-labyrinthine inputs from a variety of peripheral sources, including antagonist muscles acting at the same joint, whereas others received inputs from more limited sources. There was no apparent relationship between the spatial and dynamic properties of a neuron's responses to tilts in vertical planes and the non-labyrinthine inputs that it received. These data suggest that non-labyrinthine inputs elicited during movement will modulate the processing of information by the central vestibular system, and may contribute to the recovery of spontaneous activity of vestibular nucleus neurons following peripheral vestibular lesions. Furthermore, some vestibular nucleus neurons with non-labyrinthine inputs may be activated only during particular behaviors that elicit a specific combination of limb and visceral inputs.

Muscarinic Acetylcholine Receptors in Macaque V1 Are Most Frequently Expressed by Parvalbumin-Immunoreactive Neurons

PubMed Central

Disney, Anita A.; Aoki, Chiye

2010-01-01

Acetylcholine (ACh) is believed to underlie mechanisms of arousal and attention in mammals. ACh also has a demonstrated functional effect in visual cortex that is both diverse and profound. We have reported previously that cholinergic modulation in V1 of the macaque monkey is strongly targeted toward GABAergic interneurons. Here we examine the localization of m1 and m2 muscarinic receptor subtypes across subpopulations of GABAergic interneurons—identified by their expression of the calcium-binding proteins parvalbumin, calbindin, and calretinin—using dual-immunofluorescence confocal microscopy in V1 of the macaque monkey. In doing so, we find that the vast majority (87%) of parvalbumin-immunoreactive neurons express m1-type muscarinic ACh receptors. m1 receptors are also expressed by 60% of calbindin-immunoreactive neurons and 40% of calretinin-immunoreactive neurons. m2 AChRs, on the other hand, are expressed by only 31% of parvalbumin neurons, 23% of calbindin neurons, and 25% of calretinin neurons. Parvalbumin-immunoreactive cells comprise ≈75% of the inhibitory neuronal population in V1 and included in this large subpopulation are neurons known to veto and regulate the synchrony of principal cell spiking. Through the expression of m1 ACh receptors on nearly all of these PV cells, the cholinergic system avails itself of powerful control of information flow through and processing within the network of principal cells in the cortical circuit. PMID:18265004

Role of Immediate-Early Genes in Synaptic Plasticity and Neuronal Ensembles Underlying the Memory Trace

PubMed Central

Minatohara, Keiichiro; Akiyoshi, Mika; Okuno, Hiroyuki

2016-01-01

In the brain, neuronal gene expression is dynamically changed in response to neuronal activity. In particular, the expression of immediate-early genes (IEGs) such as egr-1, c-fos, and Arc is rapidly and selectively upregulated in subsets of neurons in specific brain regions associated with learning and memory formation. IEG expression has therefore been widely used as a molecular marker for neuronal populations that undergo plastic changes underlying formation of long-term memory. In recent years, optogenetic and pharmacogenetic studies of neurons expressing c-fos or Arc have revealed that, during learning, IEG-positive neurons encode and store information that is required for memory recall, suggesting that they may be involved in formation of the memory trace. However, despite accumulating evidence for the role of IEGs in synaptic plasticity, the molecular and cellular mechanisms associated with this process remain unclear. In this review, we first summarize recent literature concerning the role of IEG-expressing neuronal ensembles in organizing the memory trace. We then focus on the physiological significance of IEGs, especially Arc, in synaptic plasticity, and describe our hypotheses about the importance of Arc expression in various types of input-specific circuit reorganization. Finally, we offer perspectives on Arc function that would unveil the role of IEG-expressing neurons in the formation of memory traces in the hippocampus and other brain areas. PMID:26778955

Development of layer 1 neurons in the mouse neocortex.

PubMed

Ma, Jian; Yao, Xing-Hua; Fu, Yinghui; Yu, Yong-Chun

2014-10-01

Layer 1 of the neocortex harbors a unique group of neurons that play crucial roles in synaptic integration and information processing. Although extensive studies have characterized the properties of layer 1 neurons in the mature neocortex, it remains unclear how these neurons progressively acquire their distinct morphological, neurochemical, and physiological traits. In this study, we systematically examined the dynamic development of Cajal-Retzius cells and γ-aminobutyric acid (GABA)-ergic interneurons in layer 1 during the first 2 postnatal weeks. Cajal-Retzius cells underwent morphological degeneration after birth and gradually disappeared from layer 1. The majority of GABAergic interneurons showed clear expression of at least 1 of the 6 distinct neurochemical markers, including Reelin, GABA-A receptor subunit delta (GABAARδ), neuropeptide Y, vasoactive intestinal peptide (VIP), calretinin, and somatostatin from postnatal day 8. Furthermore, according to firing pattern, layer 1 interneurons can be divided into 2 groups: late-spiking (LS) and burst-spiking (BS) neurons. LS neurons preferentially expressed GABAARδ, whereas BS neurons preferentially expressed VIP. Interestingly, both LS and BS neurons exhibited a rapid electrophysiological and morphological development during the first postnatal week. Our results provide new insights into the molecular, morphological, and functional developments of the neurons in layer 1 of the neocortex. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Convergence of limb, visceral, and vertical semicircular canal or otolith inputs onto vestibular nucleus neurons.

PubMed

Jian, B J; Shintani, T; Emanuel, B A; Yates, B J

2002-05-01

The major goal of this study was to determine the patterns of convergence of non-labyrinthine inputs from the limbs and viscera onto vestibular nucleus neurons receiving signals from vertical semicircular canals or otolith organs. A secondary aim was to ascertain whether the effects of non-labyrinthine inputs on the activity of vestibular nucleus neurons is affected by bilateral peripheral vestibular lesions. The majority (72%) of vestibular nucleus neurons in labyrinth-intact animals whose firing was modulated by vertical rotations responded to electrical stimulation of limb and/or visceral nerves. The activity of even more vestibular nucleus neurons (93%) was affected by limb or visceral nerve stimulation in chronically labyrinthectomized preparations. Some neurons received non-labyrinthine inputs from a variety of peripheral sources, including antagonist muscles acting at the same joint, whereas others received inputs from more limited sources. There was no apparent relationship between the spatial and dynamic properties of a neuron's responses to tilts in vertical planes and the non-labyrinthine inputs that it received. These data suggest that non-labyrinthine inputs elicited during movement will modulate the processing of information by the central vestibular system, and may contribute to the recovery of spontaneous activity of vestibular nucleus neurons following peripheral vestibular lesions. Furthermore, some vestibular nucleus neurons with non-labyrinthine inputs may be activated only during particular behaviors that elicit a specific combination of limb and visceral inputs.

Myocardial ischaemia and the cardiac nervous system.

PubMed

Armour, J A

1999-01-01

The intrinsic cardiac nervous system has been classically considered to contain only parasympathetic efferent postganglionic neurones which receive inputs from medullary parasympathetic efferent preganglionic neurones. In such a view, intrinsic cardiac ganglia act as simple relay stations of parasympathetic efferent neuronal input to the heart, the major autonomic control of the heart purported to reside solely in the brainstem and spinal cord. Data collected over the past two decades indicate that processing occurs within the mammalian intrinsic cardiac nervous system which involves afferent neurones, local circuit neurones (interconnecting neurones) as well as both sympathetic and parasympathetic efferent postganglionic neurones. As such, intrinsic cardiac ganglionic interactions represent the organ component of the hierarchy of intrathoracic nested feedback control loops which provide rapid and appropriate reflex coordination of efferent autonomic neuronal outflow to the heart. In such a concept, the intrinsic cardiac nervous system acts as a distributive processor, integrating parasympathetic and sympathetic efferent centrifugal information to the heart in addition to centripetal information arising from cardiac sensory neurites. A number of neurochemicals have been shown to influence the interneuronal interactions which occur within the intrathoracic cardiac nervous system. For instance, pharmacological interventions that modify beta-adrenergic or angiotensin II receptors affect cardiomyocyte function not only directly, but indirectly by influencing the capacity of intrathoracic neurones to regulate cardiomyocytes. Thus, current pharmacological management of heart disease may influence cardiomyocyte function directly as well as indirectly secondary to modifying the cardiac nervous system. This review presents a brief summary of developing concepts about the role of the cardiac nervous system in regulating the normal heart. In addition, it provides some tentative ideas concerning the importance of this nervous system in cardiac disease states with a view to stimulating further interest in neural control of the heart so that appropriate neurocardiological strategies can be devised for the management of heart disease.

Viral-genetic tracing of the input-output organization of a central noradrenaline circuit.

PubMed

Schwarz, Lindsay A; Miyamichi, Kazunari; Gao, Xiaojing J; Beier, Kevin T; Weissbourd, Brandon; DeLoach, Katherine E; Ren, Jing; Ibanes, Sandy; Malenka, Robert C; Kremer, Eric J; Luo, Liqun

2015-08-06

Deciphering how neural circuits are anatomically organized with regard to input and output is instrumental in understanding how the brain processes information. For example, locus coeruleus noradrenaline (also known as norepinephrine) (LC-NE) neurons receive input from and send output to broad regions of the brain and spinal cord, and regulate diverse functions including arousal, attention, mood and sensory gating. However, it is unclear how LC-NE neurons divide up their brain-wide projection patterns and whether different LC-NE neurons receive differential input. Here we developed a set of viral-genetic tools to quantitatively analyse the input-output relationship of neural circuits, and applied these tools to dissect the LC-NE circuit in mice. Rabies-virus-based input mapping indicated that LC-NE neurons receive convergent synaptic input from many regions previously identified as sending axons to the locus coeruleus, as well as from newly identified presynaptic partners, including cerebellar Purkinje cells. The 'tracing the relationship between input and output' method (or TRIO method) enables trans-synaptic input tracing from specific subsets of neurons based on their projection and cell type. We found that LC-NE neurons projecting to diverse output regions receive mostly similar input. Projection-based viral labelling revealed that LC-NE neurons projecting to one output region also project to all brain regions we examined. Thus, the LC-NE circuit overall integrates information from, and broadcasts to, many brain regions, consistent with its primary role in regulating brain states. At the same time, we uncovered several levels of specificity in certain LC-NE sub-circuits. These tools for mapping output architecture and input-output relationship are applicable to other neuronal circuits and organisms. More broadly, our viral-genetic approaches provide an efficient intersectional means to target neuronal populations based on cell type and projection pattern.

A temperature rise reduces trial-to-trial variability of locust auditory neuron responses.

PubMed

Eberhard, Monika J B; Schleimer, Jan-Hendrik; Schreiber, Susanne; Ronacher, Bernhard

2015-09-01

The neurophysiology of ectothermic animals, such as insects, is affected by environmental temperature, as their body temperature fluctuates with ambient conditions. Changes in temperature alter properties of neurons and, consequently, have an impact on the processing of information. Nevertheless, nervous system function is often maintained over a broad temperature range, exhibiting a surprising robustness to variations in temperature. A special problem arises for acoustically communicating insects, as in these animals mate recognition and mate localization typically rely on the decoding of fast amplitude modulations in calling and courtship songs. In the auditory periphery, however, temporal resolution is constrained by intrinsic neuronal noise. Such noise predominantly arises from the stochasticity of ion channel gating and potentially impairs the processing of sensory signals. On the basis of intracellular recordings of locust auditory neurons, we show that intrinsic neuronal variability on the level of spikes is reduced with increasing temperature. We use a detailed mathematical model including stochastic ion channel gating to shed light on the underlying biophysical mechanisms in auditory receptor neurons: because of a redistribution of channel-induced current noise toward higher frequencies and specifics of the temperature dependence of the membrane impedance, membrane potential noise is indeed reduced at higher temperatures. This finding holds under generic conditions and physiologically plausible assumptions on the temperature dependence of the channels' kinetics and peak conductances. We demonstrate that the identified mechanism also can explain the experimentally observed reduction of spike timing variability at higher temperatures. Copyright © 2015 the American Physiological Society.

The neuronal and molecular basis of quinine-dependent bitter taste signaling in Drosophila larvae

PubMed Central

Apostolopoulou, Anthi A.; Mazija, Lorena; Wüst, Alexander; Thum, Andreas S.

2014-01-01

The sensation of bitter substances can alert an animal that a specific type of food is harmful and should not be consumed. However, not all bitter compounds are equally toxic and some may even be beneficial in certain contexts. Thus, taste systems in general may have a broader range of functions than just in alerting the animal. In this study we investigate bitter sensing and processing in Drosophila larvae using quinine, a substance perceived by humans as bitter. We show that behavioral choice, feeding, survival, and associative olfactory learning are all directly affected by quinine. On the cellular level, we show that 12 gustatory sensory receptor neurons that express both GR66a and GR33a are required for quinine-dependent choice and feeding behavior. Interestingly, these neurons are not necessary for quinine-dependent survival or associative learning. On the molecular receptor gene level, the GR33a receptor, but not GR66a, is required for quinine-dependent choice behavior. A screen for gustatory sensory receptor neurons that trigger quinine-dependent choice behavior revealed that a single GR97a receptor gene expressing neuron located in the peripheral terminal sense organ is partially necessary and sufficient. For the first time, we show that the elementary chemosensory system of the Drosophila larva can serve as a simple model to understand the neuronal basis of taste information processing on the single cell level with respect to different behavioral outputs. PMID:24478653

A temperature rise reduces trial-to-trial variability of locust auditory neuron responses

PubMed Central

Schleimer, Jan-Hendrik; Schreiber, Susanne; Ronacher, Bernhard

2015-01-01

The neurophysiology of ectothermic animals, such as insects, is affected by environmental temperature, as their body temperature fluctuates with ambient conditions. Changes in temperature alter properties of neurons and, consequently, have an impact on the processing of information. Nevertheless, nervous system function is often maintained over a broad temperature range, exhibiting a surprising robustness to variations in temperature. A special problem arises for acoustically communicating insects, as in these animals mate recognition and mate localization typically rely on the decoding of fast amplitude modulations in calling and courtship songs. In the auditory periphery, however, temporal resolution is constrained by intrinsic neuronal noise. Such noise predominantly arises from the stochasticity of ion channel gating and potentially impairs the processing of sensory signals. On the basis of intracellular recordings of locust auditory neurons, we show that intrinsic neuronal variability on the level of spikes is reduced with increasing temperature. We use a detailed mathematical model including stochastic ion channel gating to shed light on the underlying biophysical mechanisms in auditory receptor neurons: because of a redistribution of channel-induced current noise toward higher frequencies and specifics of the temperature dependence of the membrane impedance, membrane potential noise is indeed reduced at higher temperatures. This finding holds under generic conditions and physiologically plausible assumptions on the temperature dependence of the channels' kinetics and peak conductances. We demonstrate that the identified mechanism also can explain the experimentally observed reduction of spike timing variability at higher temperatures. PMID:26041833

Primum Non Nocere: An Evolutionary Analysis of Whether Antidepressants Do More Harm than Good

PubMed Central

Andrews, Paul W.; Thomson, J. Anderson; Amstadter, Ananda; Neale, Michael C.

2012-01-01

Antidepressant medications are the first-line treatment for people meeting current diagnostic criteria for major depressive disorder. Most antidepressants are designed to perturb the mechanisms that regulate the neurotransmitter serotonin – an evolutionarily ancient biochemical found in plants, animals, and fungi. Many adaptive processes evolved to be regulated by serotonin, including emotion, development, neuronal growth and death, platelet activation and the clotting process, attention, electrolyte balance, and reproduction. It is a principle of evolutionary medicine that the disruption of evolved adaptations will degrade biological functioning. Because serotonin regulates many adaptive processes, antidepressants could have many adverse health effects. For instance, while antidepressants are modestly effective in reducing depressive symptoms, they increase the brain’s susceptibility to future episodes after they have been discontinued. Contrary to a widely held belief in psychiatry, studies that purport to show that antidepressants promote neurogenesis are flawed because they all use a method that cannot, by itself, distinguish between neurogenesis and neuronal death. In fact, antidepressants cause neuronal damage and mature neurons to revert to an immature state, both of which may explain why antidepressants also cause neurons to undergo apoptosis (programmed death). Antidepressants can also cause developmental problems, they have adverse effects on sexual and romantic life, and they increase the risk of hyponatremia (low sodium in the blood plasma), bleeding, stroke, and death in the elderly. Our review supports the conclusion that antidepressants generally do more harm than good by disrupting a number of adaptive processes regulated by serotonin. However, there may be specific conditions for which their use is warranted (e.g., cancer, recovery from stroke). We conclude that altered informed consent practices and greater caution in the prescription of antidepressants are warranted. PMID:22536191

Neuronal Adaptive Mechanisms Underlying Intelligent Information Processing

DTIC Science & Technology

1981-05-01

Physiol. 134: 451-470, 1956. J. Freud , S, Unpublished, untitled paper (1895) subsequently published in Freud , Sigmund - Standard Edition...of the Complete Psychological Works of Freud , edited by J. Strachey. New York, Macmillan 1: 281-287, 1964. Gallagher, J.P. and Shinnick-Gallagher

Distinct GABAergic targets of feedforward and feedback connections between lower and higher areas of rat visual cortex.

PubMed

Gonchar, Yuri; Burkhalter, Andreas

2003-11-26

Processing of visual information is performed in different cortical areas that are interconnected by feedforward (FF) and feedback (FB) pathways. Although FF and FB inputs are excitatory, their influences on pyramidal neurons also depend on the outputs of GABAergic neurons, which receive FF and FB inputs. Rat visual cortex contains at least three different families of GABAergic neurons that express parvalbumin (PV), calretinin (CR), and somatostatin (SOM) (Gonchar and Burkhalter, 1997). To examine whether pathway-specific inhibition (Shao and Burkhalter, 1996) is attributable to distinct connections with GABAergic neurons, we traced FF and FB inputs to PV, CR, and SOM neurons in layers 1-2/3 of area 17 and the secondary lateromedial area in rat visual cortex. We found that in layer 2/3 maximally 2% of FF and FB inputs go to CR and SOM neurons. This contrasts with 12-13% of FF and FB inputs onto layer 2/3 PV neurons. Unlike inputs to layer 2/3, connections to layer 1, which contains CR but lacks SOM and PV somata, are pathway-specific: 21% of FB inputs go to CR neurons, whereas FF inputs to layer 1 and its CR neurons are absent. These findings suggest that FF and FB influences on layer 2/3 pyramidal neurons mainly involve disynaptic connections via PV neurons that control the spike outputs to axons and proximal dendrites. Unlike FF input, FB input in addition makes a disynaptic link via CR neurons, which may influence the excitability of distal pyramidal cell dendrites in layer 1.