Circuit mechanisms encoding odors and driving aging-associated behavioral declines in Caenorhabditis elegans.

PubMed

Leinwand, Sarah G; Yang, Claire J; Bazopoulou, Daphne; Chronis, Nikos; Srinivasan, Jagan; Chalasani, Sreekanth H

2015-09-22

Chemosensory neurons extract information about chemical cues from the environment. How is the activity in these sensory neurons transformed into behavior? Using Caenorhabditis elegans, we map a novel sensory neuron circuit motif that encodes odor concentration. Primary neurons, AWC(ON) and AWA, directly detect the food odor benzaldehyde (BZ) and release insulin-like peptides and acetylcholine, respectively, which are required for odor-evoked responses in secondary neurons, ASEL and AWB. Consistently, both primary and secondary neurons are required for BZ attraction. Unexpectedly, this combinatorial code is altered in aged animals: odor-evoked activity in secondary, but not primary, olfactory neurons is reduced. Moreover, experimental manipulations increasing neurotransmission from primary neurons rescues aging-associated neuronal deficits. Finally, we correlate the odor responsiveness of aged animals with their lifespan. Together, these results show how odors are encoded by primary and secondary neurons and suggest reduced neurotransmission as a novel mechanism driving aging-associated sensory neural activity and behavioral declines.

Circuit mechanisms encoding odors and driving aging-associated behavioral declines in Caenorhabditis elegans

PubMed Central

Leinwand, Sarah G; Yang, Claire J; Bazopoulou, Daphne; Chronis, Nikos; Srinivasan, Jagan; Chalasani, Sreekanth H

2015-01-01

Chemosensory neurons extract information about chemical cues from the environment. How is the activity in these sensory neurons transformed into behavior? Using Caenorhabditis elegans, we map a novel sensory neuron circuit motif that encodes odor concentration. Primary neurons, AWCON and AWA, directly detect the food odor benzaldehyde (BZ) and release insulin-like peptides and acetylcholine, respectively, which are required for odor-evoked responses in secondary neurons, ASEL and AWB. Consistently, both primary and secondary neurons are required for BZ attraction. Unexpectedly, this combinatorial code is altered in aged animals: odor-evoked activity in secondary, but not primary, olfactory neurons is reduced. Moreover, experimental manipulations increasing neurotransmission from primary neurons rescues aging-associated neuronal deficits. Finally, we correlate the odor responsiveness of aged animals with their lifespan. Together, these results show how odors are encoded by primary and secondary neurons and suggest reduced neurotransmission as a novel mechanism driving aging-associated sensory neural activity and behavioral declines. DOI: http://dx.doi.org/10.7554/eLife.10181.001 PMID:26394000

Neuronal encoding of subjective value in dorsal and ventral anterior cingulate cortex

PubMed Central

Cai, Xinying; Padoa-Schioppa, Camillo

2012-01-01

We examined the activity of individual cells in the primate anterior cingulate cortex during an economic choice task. In the experiments, monkeys chose between different juices offered in variables amounts and subjective values were inferred from the animals’ choices. We analyzed neuronal firing rates in relation to a large number of behaviorally relevant variables. We report three main results. First, there were robust differences between the dorsal bank (ACCd) and the ventral bank (ACCv) of the cingulate sulcus. Specifically, neurons in ACCd but not in ACCv were modulated by the movement direction. Furthermore, neurons in ACCd were most active prior to movement initiation whereas neurons in ACCv were most active after juice delivery. Second, neurons in both areas encoded the identity and the subjective value of the juice chosen by the animal. In contrast, neither region encoded the value of individual offers. Third, the population of value-encoding neurons in both ACCd and ACCv underwent range adaptation. With respect to economic choice, it is interesting to compare these areas with the orbitofrontal cortex (OFC), previously examined. While neurons in OFC encoded both pre-decision and post-decision variables, neurons in ACCd and ACCv only encoded post-decision variables. Moreover, the encoding of chosen value in ACCd and ACCv trailed that found in OFC. These observations indicate that economic decisions (value comparisons) take place upstream of ACCd and ACCv. The coexistence of choice outcome and movement signals in ACCd suggests that this area constitutes a getaway through which the choice system informs motor systems. PMID:22423100

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.

The dependence of neuronal encoding efficiency on Hebbian plasticity and homeostatic regulation of neurotransmitter release

PubMed Central

Faghihi, Faramarz; Moustafa, Ahmed A.

2015-01-01

Synapses act as information filters by different molecular mechanisms including retrograde messenger that affect neuronal spiking activity. One of the well-known effects of retrograde messenger in presynaptic neurons is a change of the probability of neurotransmitter release. Hebbian learning describe a strengthening of a synapse between a presynaptic input onto a postsynaptic neuron when both pre- and postsynaptic neurons are coactive. In this work, a theory of homeostatic regulation of neurotransmitter release by retrograde messenger and Hebbian plasticity in neuronal encoding is presented. Encoding efficiency was measured for different synaptic conditions. In order to gain high encoding efficiency, the spiking pattern of a neuron should be dependent on the intensity of the input and show low levels of noise. In this work, we represent spiking trains as zeros and ones (corresponding to non-spike or spike in a time bin, respectively) as words with length equal to three. Then the frequency of each word (here eight words) is measured using spiking trains. These frequencies are used to measure neuronal efficiency in different conditions and for different parameter values. Results show that neurons that have synapses acting as band-pass filters show the highest efficiency to encode their input when both Hebbian mechanism and homeostatic regulation of neurotransmitter release exist in synapses. Specifically, the integration of homeostatic regulation of feedback inhibition with Hebbian mechanism and homeostatic regulation of neurotransmitter release in the synapses leads to even higher efficiency when high stimulus intensity is presented to the neurons. However, neurons with synapses acting as high-pass filters show no remarkable increase in encoding efficiency for all simulated synaptic plasticity mechanisms. This study demonstrates the importance of cooperation of Hebbian mechanism with regulation of neurotransmitter release induced by rapid diffused retrograde messenger in neurons with synapses as low and band-pass filters to obtain high encoding efficiency in different environmental and physiological conditions. PMID:25972786

Odor-evoked inhibition of olfactory sensory neurons drives olfactory perception in Drosophila.

PubMed

Cao, Li-Hui; Yang, Dong; Wu, Wei; Zeng, Xiankun; Jing, Bi-Yang; Li, Meng-Tong; Qin, Shanshan; Tang, Chao; Tu, Yuhai; Luo, Dong-Gen

2017-11-07

Inhibitory response occurs throughout the nervous system, including the peripheral olfactory system. While odor-evoked excitation in peripheral olfactory cells is known to encode odor information, the molecular mechanism and functional roles of odor-evoked inhibition remain largely unknown. Here, we examined Drosophila olfactory sensory neurons and found that inhibitory odors triggered outward receptor currents by reducing the constitutive activities of odorant receptors, inhibiting the basal spike firing in olfactory sensory neurons. Remarkably, this odor-evoked inhibition of olfactory sensory neurons elicited by itself a full range of olfactory behaviors from attraction to avoidance, as did odor-evoked olfactory sensory neuron excitation. These results indicated that peripheral inhibition is comparable to excitation in encoding sensory signals rather than merely regulating excitation. Furthermore, we demonstrated that a bidirectional code with both odor-evoked inhibition and excitation in single olfactory sensory neurons increases the odor-coding capacity, providing a means of efficient sensory encoding.

How Does the Sparse Memory “Engram” Neurons Encode the Memory of a Spatial–Temporal Event?

PubMed Central

Guan, Ji-Song; Jiang, Jun; Xie, Hong; Liu, Kai-Yuan

2016-01-01

Episodic memory in human brain is not a fixed 2-D picture but a highly dynamic movie serial, integrating information at both the temporal and the spatial domains. Recent studies in neuroscience reveal that memory storage and recall are closely related to the activities in discrete memory engram (trace) neurons within the dentate gyrus region of hippocampus and the layer 2/3 of neocortex. More strikingly, optogenetic reactivation of those memory trace neurons is able to trigger the recall of naturally encoded memory. It is still unknown how the discrete memory traces encode and reactivate the memory. Considering a particular memory normally represents a natural event, which consists of information at both the temporal and spatial domains, it is unknown how the discrete trace neurons could reconstitute such enriched information in the brain. Furthermore, as the optogenetic-stimuli induced recall of memory did not depend on firing pattern of the memory traces, it is most likely that the spatial activation pattern, but not the temporal activation pattern of the discrete memory trace neurons encodes the memory in the brain. How does the neural circuit convert the activities in the spatial domain into the temporal domain to reconstitute memory of a natural event? By reviewing the literature, here we present how the memory engram (trace) neurons are selected and consolidated in the brain. Then, we will discuss the main challenges in the memory trace theory. In the end, we will provide a plausible model of memory trace cell network, underlying the conversion of neural activities between the spatial domain and the temporal domain. We will also discuss on how the activation of sparse memory trace neurons might trigger the replay of neural activities in specific temporal patterns. PMID:27601979

How Does the Sparse Memory "Engram" Neurons Encode the Memory of a Spatial-Temporal Event?

PubMed

Guan, Ji-Song; Jiang, Jun; Xie, Hong; Liu, Kai-Yuan

2016-01-01

Episodic memory in human brain is not a fixed 2-D picture but a highly dynamic movie serial, integrating information at both the temporal and the spatial domains. Recent studies in neuroscience reveal that memory storage and recall are closely related to the activities in discrete memory engram (trace) neurons within the dentate gyrus region of hippocampus and the layer 2/3 of neocortex. More strikingly, optogenetic reactivation of those memory trace neurons is able to trigger the recall of naturally encoded memory. It is still unknown how the discrete memory traces encode and reactivate the memory. Considering a particular memory normally represents a natural event, which consists of information at both the temporal and spatial domains, it is unknown how the discrete trace neurons could reconstitute such enriched information in the brain. Furthermore, as the optogenetic-stimuli induced recall of memory did not depend on firing pattern of the memory traces, it is most likely that the spatial activation pattern, but not the temporal activation pattern of the discrete memory trace neurons encodes the memory in the brain. How does the neural circuit convert the activities in the spatial domain into the temporal domain to reconstitute memory of a natural event? By reviewing the literature, here we present how the memory engram (trace) neurons are selected and consolidated in the brain. Then, we will discuss the main challenges in the memory trace theory. In the end, we will provide a plausible model of memory trace cell network, underlying the conversion of neural activities between the spatial domain and the temporal domain. We will also discuss on how the activation of sparse memory trace neurons might trigger the replay of neural activities in specific temporal patterns.

Decoupling kinematics and mechanics reveals coding properties of trigeminal ganglion neurons in the rat vibrissal system

PubMed Central

Bush, Nicholas E; Schroeder, Christopher L; Hobbs, Jennifer A; Yang, Anne ET; Huet, Lucie A; Solla, Sara A; Hartmann, Mitra JZ

2016-01-01

Tactile information available to the rat vibrissal system begins as external forces that cause whisker deformations, which in turn excite mechanoreceptors in the follicle. Despite the fundamental mechanical origin of tactile information, primary sensory neurons in the trigeminal ganglion (Vg) have often been described as encoding the kinematics (geometry) of object contact. Here we aimed to determine the extent to which Vg neurons encode the kinematics vs. mechanics of contact. We used models of whisker bending to quantify mechanical signals (forces and moments) at the whisker base while simultaneously monitoring whisker kinematics and recording single Vg units in both anesthetized rats and awake, body restrained rats. We employed a novel manual stimulation technique to deflect whiskers in a way that decouples kinematics from mechanics, and used Generalized Linear Models (GLMs) to show that Vg neurons more directly encode mechanical signals when the whisker is deflected in this decoupled stimulus space. DOI: http://dx.doi.org/10.7554/eLife.13969.001 PMID:27348221

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.

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

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

Encoding of head direction by hippocampal place cells in bats.

PubMed

Rubin, Alon; Yartsev, Michael M; Ulanovsky, Nachum

2014-01-15

Most theories of navigation rely on the concept of a mental map and compass. Hippocampal place cells are neurons thought to be important for representing the mental map; these neurons become active when the animal traverses a specific location in the environment (the "place field"). Head-direction cells are found outside the hippocampus, and encode the animal's head orientation, thus implementing a neural compass. The prevailing view is that the activity of head-direction cells is not tuned to a single place, while place cells do not encode head direction. However, little work has been done to investigate in detail the possible head-directional tuning of hippocampal place cells across species. Here we addressed this by recording the activity of single neurons in the hippocampus of two evolutionarily distant bat species, Egyptian fruit bat and big brown bat, which crawled randomly in three different open-field arenas. We found that a large fraction of hippocampal neurons, in both bat species, showed conjunctive sensitivity to the animal's spatial position (place field) and to its head direction. We introduced analytical methods to demonstrate that the head-direction tuning was significant even after controlling for the behavioral coupling between position and head direction. Surprisingly, some hippocampal neurons preserved their head direction tuning even outside the neuron's place field, suggesting that "spontaneous" extra-field spikes are not noise, but in fact carry head-direction information. Overall, these findings suggest that bat hippocampal neurons can convey both map information and compass information.

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.

A Novel Nonparametric Approach for Neural Encoding and Decoding Models of Multimodal Receptive Fields.

PubMed

Agarwal, Rahul; Chen, Zhe; Kloosterman, Fabian; Wilson, Matthew A; Sarma, Sridevi V

2016-07-01

Pyramidal neurons recorded from the rat hippocampus and entorhinal cortex, such as place and grid cells, have diverse receptive fields, which are either unimodal or multimodal. Spiking activity from these cells encodes information about the spatial position of a freely foraging rat. At fine timescales, a neuron's spike activity also depends significantly on its own spike history. However, due to limitations of current parametric modeling approaches, it remains a challenge to estimate complex, multimodal neuronal receptive fields while incorporating spike history dependence. Furthermore, efforts to decode the rat's trajectory in one- or two-dimensional space from hippocampal ensemble spiking activity have mainly focused on spike history-independent neuronal encoding models. In this letter, we address these two important issues by extending a recently introduced nonparametric neural encoding framework that allows modeling both complex spatial receptive fields and spike history dependencies. Using this extended nonparametric approach, we develop novel algorithms for decoding a rat's trajectory based on recordings of hippocampal place cells and entorhinal grid cells. Results show that both encoding and decoding models derived from our new method performed significantly better than state-of-the-art encoding and decoding models on 6 minutes of test data. In addition, our model's performance remains invariant to the apparent modality of the neuron's receptive field.

Dynamical information encoding in neural adaptation.

PubMed

Luozheng Li; Wenhao Zhang; Yuanyuan Mi; Dahui Wang; Xiaohan Lin; Si Wu

2016-08-01

Adaptation refers to the general phenomenon that a neural system dynamically adjusts its response property according to the statistics of external inputs. In response to a prolonged constant stimulation, neuronal firing rates always first increase dramatically at the onset of the stimulation; and afterwards, they decrease rapidly to a low level close to background activity. This attenuation of neural activity seems to be contradictory to our experience that we can still sense the stimulus after the neural system is adapted. Thus, it prompts a question: where is the stimulus information encoded during the adaptation? Here, we investigate a computational model in which the neural system employs a dynamical encoding strategy during the neural adaptation: at the early stage of the adaptation, the stimulus information is mainly encoded in the strong independent firings; and as time goes on, the information is shifted into the weak but concerted responses of neurons. We find that short-term plasticity, a general feature of synapses, provides a natural mechanism to achieve this goal. Furthermore, we demonstrate that with balanced excitatory and inhibitory inputs, this correlation-based information can be read out efficiently. The implications of this study on our understanding of neural information encoding are discussed.

Coding of auditory temporal and pitch information by hippocampal individual cells and cell assemblies in the rat.

PubMed

Sakurai, Y

2002-01-01

This study reports how hippocampal individual cells and cell assemblies cooperate for neural coding of pitch and temporal information in memory processes for auditory stimuli. Each rat performed two tasks, one requiring discrimination of auditory pitch (high or low) and the other requiring discrimination of their duration (long or short). Some CA1 and CA3 complex-spike neurons showed task-related differential activity between the high and low tones in only the pitch-discrimination task. However, without exception, neurons which showed task-related differential activity between the long and short tones in the duration-discrimination task were always task-related neurons in the pitch-discrimination task. These results suggest that temporal information (long or short), in contrast to pitch information (high or low), cannot be coded independently by specific neurons. The results also indicate that the two different behavioral tasks cannot be fully differentiated by the task-related single neurons alone and suggest a model of cell-assembly coding of the tasks. Cross-correlation analysis among activities of simultaneously recorded multiple neurons supported the suggested cell-assembly model.Considering those results, this study concludes that dual coding by hippocampal single neurons and cell assemblies is working in memory processing of pitch and temporal information of auditory stimuli. The single neurons encode both auditory pitches and their temporal lengths and the cell assemblies encode types of tasks (contexts or situations) in which the pitch and the temporal information are processed.

Influence of local objects on hippocampal representations: landmark vectors and memory

PubMed Central

Deshmukh, Sachin S.; Knierim, James J.

2013-01-01

The hippocampus is thought to represent nonspatial information in the context of spatial information. An animal can derive both spatial information as well as nonspatial information from the objects (landmarks) it encounters as it moves around in an environment. Here, we demonstrate correlates of both object-derived spatial as well as nonspatial information in the hippocampus of rats foraging in the presence of objects. We describe a new form of CA1 place cells, called landmark-vector cells, that encode spatial locations as a vector relationship to local landmarks. Such landmark vector relationships can be dynamically encoded. Of the 26 CA1 neurons that developed new fields in the course of a day’s recording sessions, in 8 cases the new fields were located at a similar distance and direction from a landmark as the initial field was located relative to a different landmark. We also demonstrate object-location memory in the hippocampus. When objects were removed from an environment or moved to new locations, a small number of neurons in CA1 and CA3 increased firing at the locations where the objects used to be. In some neurons, this increase occurred only in one location, indicating object +place conjunctive memory; in other neurons the increase in firing was seen at multiple locations where an object used to be. Taken together, these results demonstrate that the spatially restricted firing of hippocampal neurons encode multiple types of information regarding the relationship between an animal’s location and the location of objects in its environment. PMID:23447419

Encoding of Reward and Space During a Working Memory Task in the Orbitofrontal Cortex and Anterior Cingulate Sulcus

PubMed Central

Kennerley, Steven W.

2009-01-01

Several lines of research indicate that emotional and motivational information may be useful in guiding the allocation of attentional resources. Two areas of the frontal lobe that are particularly implicated in the encoding of motivational information are the orbital prefrontal cortex (PFo) and the dorsomedial region of prefrontal cortex, specifically the anterior cingulate sulcus (PFcs). However, it remains unclear whether these areas use this information to influence spatial attention. We used single-unit neurophysiology to examine whether, at the level of individual neurons, there was evidence for integration between reward information and spatial attention. We trained two subjects to perform a task that required them to attend to a spatial location across a delay under different expectancies of reward for correct performance. We balanced the order of presentation of spatial and reward information so we could assess the neuronal encoding of the two pieces of information independently and conjointly. We found little evidence for encoding of the spatial location in either PFo or PFcs. In contrast, both areas encoded the expected reward. Furthermore, PFo consistently encoded reward more quickly than PFcs, although reward encoding was subsequently more prevalent and stronger in PFcs. These results suggest a differential contribution of PFo and PFcs to reward encoding, with PFo potentially more important for initially determining the value of rewards predicted by sensory stimuli. They also suggest that neither PFo nor PFcs play a direct role in the control of spatial attention. PMID:19776363

A systematic approach to selecting task relevant neurons.

PubMed

Kahn, Kevin; Saxena, Shreya; Eskandar, Emad; Thakor, Nitish; Schieber, Marc; Gale, John T; Averbeck, Bruno; Eden, Uri; Sarma, Sridevi V

2015-04-30

Since task related neurons cannot be specifically targeted during surgery, a critical decision to make is to select which neurons are task-related when performing data analysis. Including neurons unrelated to the task degrade decoding accuracy and confound neurophysiological results. Traditionally, task-related neurons are selected as those with significant changes in firing rate when a stimulus is applied. However, this assumes that neurons' encoding of stimuli are dominated by their firing rate with little regard to temporal dynamics. This paper proposes a systematic approach for neuron selection, which uses a likelihood ratio test to capture the contribution of stimulus to spiking activity while taking into account task-irrelevant intrinsic dynamics that affect firing rates. This approach is denoted as the model deterioration excluding stimulus (MDES) test. MDES is compared to firing rate selection in four case studies: a simulation, a decoding example, and two neurophysiology examples. The MDES rankings in the simulation match closely with ideal rankings, while firing rate rankings are skewed by task-irrelevant parameters. For decoding, 95% accuracy is achieved using the top 8 MDES-ranked neurons, while the top 12 firing-rate ranked neurons are needed. In the neurophysiological examples, MDES matches published results when firing rates do encode salient stimulus information, and uncovers oscillatory modulations in task-related neurons that are not captured when neurons are selected using firing rates. These case studies illustrate the importance of accounting for intrinsic dynamics when selecting task-related neurons and following the MDES approach accomplishes that. MDES selects neurons that encode task-related information irrespective of these intrinsic dynamics which can bias firing rate based selection. Copyright © 2015 Elsevier B.V. All rights reserved.

Critical and maximally informative encoding between neural populations in the retina

PubMed Central

Kastner, David B.; Baccus, Stephen A.; Sharpee, Tatyana O.

2015-01-01

Computation in the brain involves multiple types of neurons, yet the organizing principles for how these neurons work together remain unclear. Information theory has offered explanations for how different types of neurons can maximize the transmitted information by encoding different stimulus features. However, recent experiments indicate that separate neuronal types exist that encode the same filtered version of the stimulus, but then the different cell types signal the presence of that stimulus feature with different thresholds. Here we show that the emergence of these neuronal types can be quantitatively described by the theory of transitions between different phases of matter. The two key parameters that control the separation of neurons into subclasses are the mean and standard deviation (SD) of noise affecting neural responses. The average noise across the neural population plays the role of temperature in the classic theory of phase transitions, whereas the SD is equivalent to pressure or magnetic field, in the case of liquid–gas and magnetic transitions, respectively. Our results account for properties of two recently discovered types of salamander Off retinal ganglion cells, as well as the absence of multiple types of On cells. We further show that, across visual stimulus contrasts, retinal circuits continued to operate near the critical point whose quantitative characteristics matched those expected near a liquid–gas critical point and described by the nearest-neighbor Ising model in three dimensions. By operating near a critical point, neural circuits can maximize information transmission in a given environment while retaining the ability to quickly adapt to a new environment. PMID:25675497

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

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

Encoding of Olfactory Information with Oscillating Neural Assemblies

NASA Astrophysics Data System (ADS)

Laurent, Gilles; Davidowitz, Hananel

1994-09-01

In the brain, fast oscillations of local field potentials, which are thought to arise from the coherent and rhythmic activity of large numbers of neurons, were observed first in the olfactory system and have since been described in many neocortical areas. The importance of these oscillations in information coding, however, is controversial. Here, local field potential and intracellular recordings were obtained from the antennal lobe and mushroom body of the locust Schistocerca americana. Different odors evoked coherent oscillations in different, but usually overlapping, ensembles of neurons. The phase of firing of individual neurons relative to the population was not dependent on the odor. The components of a coherently oscillating ensemble of neurons changed over the duration of a single exposure to an odor. It is thus proposed that odors are encoded by specific but dynamic assemblies of coherently oscillating neurons. Such distributed and temporal representation of complex sensory signals may facilitate combinatorial coding and associative learning in these, and possibly other, sensory networks.

How Animals Understand the Meaning of Indefinite Information from Environments?

NASA Astrophysics Data System (ADS)

Shimizu, H.; Yamaguchi, Y.

Animals, including human beings, have ability to understand the meaning of indefinite information from environments. Thanks to this ability the animals have flexibility in their behaviors for the environmental changes. Staring from a hypothesis that understanding of the input (Shannonian) information is based on the self-organization of a neuronal representation, that is, a spatio-temporal pattern constituted of coherent activities of neurons encoding a ``figure'', being separated from the ``background'' encoded by incoherent activities, the conditions necessary for the understanding of indefinite information were discussed. The crucial conditions revealed are that the neuronal system is incomplete or indefinite in a sense that its rules for the self-organization of the neuronal activities are completed only after the input of the environmental information and that it has an additional system named "self-specific to relevantly self-organize dynamical ``constraints'' or ``boundary conditions'' for the self-organization of the representation. For the simultaneous self-organizations of the relevant constraints and the representation, a global circulation of activities must be self-organized between these two kinds of neuronal systems. Moreover, for the performance of these functions, a specific kind of synergetic elements, ``holon elements'', are also necessary. By means of a neuronal model, the visual perception of indefinite input signals is demonstrated. The results obtained are consistent with those recently observed in the visual cortex of cats.

Encoding of reward expectation by monkey anterior insular neurons

PubMed Central

Mizuhiki, Takashi; Richmond, Barry J.

2012-01-01

The insula, a cortical brain region that is known to encode information about autonomic, visceral, and olfactory functions, has recently been shown to encode information during reward-seeking tasks in both single neuronal recording and functional magnetic resonance imaging studies. To examine the reward-related activation, we recorded from 170 single neurons in anterior insula of 2 monkeys during a multitrial reward schedule task, where the monkeys had to complete a schedule of 1, 2, 3, or 4 trials to earn a reward. In one block of trials a visual cue indicated whether a reward would or would not be delivered in the current trial after the monkey successfully detected that a red spot turned green, and in other blocks the visual cue was random with respect to reward delivery. Over one-quarter of 131 responsive neurons were activated when the current trial would (certain or uncertain) be rewarded if performed correctly. These same neurons failed to respond in trials that were certain, as indicated by the cue, to be unrewarded. Another group of neurons responded when the reward was delivered, similar to results reported previously. The dynamics of population activity in anterior insula also showed strong signals related to knowing when a reward is coming. The most parsimonious explanation is that this activity codes for a type of expected outcome, where the expectation encompasses both certain and uncertain rewards. PMID:22402653

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.

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

Metrics for comparing neuronal tree shapes based on persistent homology.

PubMed

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A; Mitra, Partha; Wang, Yusu

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities-Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework.

Metrics for comparing neuronal tree shapes based on persistent homology

PubMed Central

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A.; Mitra, Partha

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities—Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework. PMID:28809960

A neural mechanism for background information-gated learning based on axonal-dendritic overlaps.

PubMed

Mainetti, Matteo; Ascoli, Giorgio A

2015-03-01

Experiencing certain events triggers the acquisition of new memories. Although necessary, however, actual experience is not sufficient for memory formation. One-trial learning is also gated by knowledge of appropriate background information to make sense of the experienced occurrence. Strong neurobiological evidence suggests that long-term memory storage involves formation of new synapses. On the short time scale, this form of structural plasticity requires that the axon of the pre-synaptic neuron be physically proximal to the dendrite of the post-synaptic neuron. We surmise that such "axonal-dendritic overlap" (ADO) constitutes the neural correlate of background information-gated (BIG) learning. The hypothesis is based on a fundamental neuroanatomical constraint: an axon must pass close to the dendrites that are near other neurons it contacts. The topographic organization of the mammalian cortex ensures that nearby neurons encode related information. Using neural network simulations, we demonstrate that ADO is a suitable mechanism for BIG learning. We model knowledge as associations between terms, concepts or indivisible units of thought via directed graphs. The simplest instantiation encodes each concept by single neurons. Results are then generalized to cell assemblies. The proposed mechanism results in learning real associations better than spurious co-occurrences, providing definitive cognitive advantages.

A Neural Mechanism for Background Information-Gated Learning Based on Axonal-Dendritic Overlaps

PubMed Central

Mainetti, Matteo; Ascoli, Giorgio A.

2015-01-01

Experiencing certain events triggers the acquisition of new memories. Although necessary, however, actual experience is not sufficient for memory formation. One-trial learning is also gated by knowledge of appropriate background information to make sense of the experienced occurrence. Strong neurobiological evidence suggests that long-term memory storage involves formation of new synapses. On the short time scale, this form of structural plasticity requires that the axon of the pre-synaptic neuron be physically proximal to the dendrite of the post-synaptic neuron. We surmise that such “axonal-dendritic overlap” (ADO) constitutes the neural correlate of background information-gated (BIG) learning. The hypothesis is based on a fundamental neuroanatomical constraint: an axon must pass close to the dendrites that are near other neurons it contacts. The topographic organization of the mammalian cortex ensures that nearby neurons encode related information. Using neural network simulations, we demonstrate that ADO is a suitable mechanism for BIG learning. We model knowledge as associations between terms, concepts or indivisible units of thought via directed graphs. The simplest instantiation encodes each concept by single neurons. Results are then generalized to cell assemblies. The proposed mechanism results in learning real associations better than spurious co-occurrences, providing definitive cognitive advantages. PMID:25767887

Computational modeling of the neural representation of object shape in the primate ventral visual system

PubMed Central

Eguchi, Akihiro; Mender, Bedeho M. W.; Evans, Benjamin D.; Humphreys, Glyn W.; Stringer, Simon M.

2015-01-01

Neurons in successive stages of the primate ventral visual pathway encode the spatial structure of visual objects. In this paper, we investigate through computer simulation how these cell firing properties may develop through unsupervised visually-guided learning. Individual neurons in the model are shown to exploit statistical regularity and temporal continuity of the visual inputs during training to learn firing properties that are similar to neurons in V4 and TEO. Neurons in V4 encode the conformation of boundary contour elements at a particular position within an object regardless of the location of the object on the retina, while neurons in TEO integrate information from multiple boundary contour elements. This representation goes beyond mere object recognition, in which neurons simply respond to the presence of a whole object, but provides an essential foundation from which the brain is subsequently able to recognize the whole object. PMID:26300766

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

The Influence of Mexican Hat Recurrent Connectivity on Noise Correlations and Stimulus Encoding

PubMed Central

Meyer, Robert; Ladenbauer, Josef; Obermayer, Klaus

2017-01-01

Noise correlations are a common feature of neural responses and have been observed in many cortical areas across different species. These correlations can influence information processing by enhancing or diminishing the quality of the neural code, but the origin of these correlations is still a matter of controversy. In this computational study we explore the hypothesis that noise correlations are the result of local recurrent excitatory and inhibitory connections. We simulated two-dimensional networks of adaptive spiking neurons with local connection patterns following Gaussian kernels. Noise correlations decay with distance between neurons but are only observed if the range of excitatory connections is smaller than the range of inhibitory connections (“Mexican hat” connectivity) and if the connection strengths are sufficiently strong. These correlations arise from a moving blob-like structure of evoked activity, which is absent if inhibitory interactions have a smaller range (“inverse Mexican hat” connectivity). Spatially structured external inputs fixate these blobs to certain locations and thus effectively reduce noise correlations. We further investigated the influence of these network configurations on stimulus encoding. On the one hand, the observed correlations diminish information about a stimulus encoded by a network. On the other hand, correlated activity allows for more precise encoding of stimulus information if the decoder has only access to a limited amount of neurons. PMID:28539881

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.

Spiking, Bursting, and Population Dynamics in a Network of Growth Transform Neurons.

PubMed

Gangopadhyay, Ahana; Chakrabartty, Shantanu

2018-06-01

This paper investigates the dynamical properties of a network of neurons, each of which implements an asynchronous mapping based on polynomial growth transforms. In the first part of this paper, we present a geometric approach for visualizing the dynamics of the network where each of the neurons traverses a trajectory in a dual optimization space, whereas the network itself traverses a trajectory in an equivalent primal optimization space. We show that as the network learns to solve basic classification tasks, different choices of primal-dual mapping produce unique but interpretable neural dynamics like noise shaping, spiking, and bursting. While the proposed framework is general enough, in this paper, we demonstrate its use for designing support vector machines (SVMs) that exhibit noise-shaping properties similar to those of modulators, and for designing SVMs that learn to encode information using spikes and bursts. It is demonstrated that the emergent switching, spiking, and burst dynamics produced by each neuron encodes its respective margin of separation from a classification hyperplane whose parameters are encoded by the network population dynamics. We believe that the proposed growth transform neuron model and the underlying geometric framework could serve as an important tool to connect well-established machine learning algorithms like SVMs to neuromorphic principles like spiking, bursting, population encoding, and noise shaping.

Neurons in the barrel cortex turn into processing whisker and odor signals: a cellular mechanism for the storage and retrieval of associative signals

PubMed Central

Wang, Dangui; Zhao, Jun; Gao, Zilong; Chen, Na; Wen, Bo; Lu, Wei; Lei, Zhuofan; Chen, Changfeng; Liu, Yahui; Feng, Jing; Wang, Jin-Hui

2015-01-01

Associative learning and memory are essential to logical thinking and cognition. How the neurons are recruited as associative memory cells to encode multiple input signals for their associated storage and distinguishable retrieval remains unclear. We studied this issue in the barrel cortex by in vivo two-photon calcium imaging, electrophysiology, and neural tracing in our mouse model that the simultaneous whisker and olfaction stimulations led to odorant-induced whisker motion. After this cross-modal reflex arose, the barrel and piriform cortices connected. More than 40% of barrel cortical neurons became to encode odor signal alongside whisker signal. Some of these neurons expressed distinct activity patterns in response to acquired odor signal and innate whisker signal, and others encoded similar pattern in response to these signals. In the meantime, certain barrel cortical astrocytes encoded odorant and whisker signals. After associative learning, the neurons and astrocytes in the sensory cortices are able to store the newly learnt signal (cross-modal memory) besides the innate signal (native-modal memory). Such associative memory cells distinguish the differences of these signals by programming different codes and signify the historical associations of these signals by similar codes in information retrievals. PMID:26347609

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.

Open source tools for the information theoretic analysis of neural data.

PubMed

Ince, Robin A A; Mazzoni, Alberto; Petersen, Rasmus S; Panzeri, Stefano

2010-01-01

The recent and rapid development of open source software tools for the analysis of neurophysiological datasets consisting of simultaneous multiple recordings of spikes, field potentials and other neural signals holds the promise for a significant advance in the standardization, transparency, quality, reproducibility and variety of techniques used to analyze neurophysiological data and for the integration of information obtained at different spatial and temporal scales. In this review we focus on recent advances in open source toolboxes for the information theoretic analysis of neural responses. We also present examples of their use to investigate the role of spike timing precision, correlations across neurons, and field potential fluctuations in the encoding of sensory information. These information toolboxes, available both in MATLAB and Python programming environments, hold the potential to enlarge the domain of application of information theory to neuroscience and to lead to new discoveries about how neurons encode and transmit information.

Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment

PubMed Central

Legenstein, Robert; Maass, Wolfgang

2014-01-01

It has recently been shown that networks of spiking neurons with noise can emulate simple forms of probabilistic inference through “neural sampling”, i.e., by treating spikes as samples from a probability distribution of network states that is encoded in the network. Deficiencies of the existing model are its reliance on single neurons for sampling from each random variable, and the resulting limitation in representing quickly varying probabilistic information. We show that both deficiencies can be overcome by moving to a biologically more realistic encoding of each salient random variable through the stochastic firing activity of an ensemble of neurons. The resulting model demonstrates that networks of spiking neurons with noise can easily track and carry out basic computational operations on rapidly varying probability distributions, such as the odds of getting rewarded for a specific behavior. We demonstrate the viability of this new approach towards neural coding and computation, which makes use of the inherent parallelism of generic neural circuits, by showing that this model can explain experimentally observed firing activity of cortical neurons for a variety of tasks that require rapid temporal integration of sensory information. PMID:25340749

Autonomous encoding of irrelevant goals and outcomes by prefrontal cortex neurons.

PubMed

Genovesio, Aldo; Tsujimoto, Satoshi; Navarra, Giulia; Falcone, Rossella; Wise, Steven P

2014-01-29

Two rhesus monkeys performed a distance discrimination task in which they reported whether a red square or a blue circle had appeared farther from a fixed reference point. Because a new pair of distances was chosen randomly on each trial, and because the monkeys had no opportunity to correct errors, no information from the previous trial was relevant to a current one. Nevertheless, many prefrontal cortex neurons encoded the outcome of the previous trial on current trials. A smaller, intermingled population of cells encoded the spatial goal on the previous trial or the features of the chosen stimuli, such as color or shape. The coding of previous outcomes and goals began at various times during a current trial, and it was selective in that prefrontal cells did not encode other information from the previous trial. The monitoring of previous goals and outcomes often contributes to problem solving, and it can support exploratory behavior. The present results show that such monitoring occurs autonomously and selectively, even when irrelevant to the task at hand.

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.

Coding of vocalizations by single neurons in ventrolateral prefrontal cortex.

PubMed

Plakke, Bethany; Diltz, Mark D; Romanski, Lizabeth M

2013-11-01

Neuronal activity in single prefrontal neurons has been correlated with behavioral responses, rules, task variables and stimulus features. In the non-human primate, neurons recorded in ventrolateral prefrontal cortex (VLPFC) have been found to respond to species-specific vocalizations. Previous studies have found multisensory neurons which respond to simultaneously presented faces and vocalizations in this region. Behavioral data suggests that face and vocal information are inextricably linked in animals and humans and therefore may also be tightly linked in the coding of communication calls in prefrontal neurons. In this study we therefore examined the role of VLPFC in encoding vocalization call type information. Specifically, we examined previously recorded single unit responses from the VLPFC in awake, behaving rhesus macaques in response to 3 types of species-specific vocalizations made by 3 individual callers. Analysis of responses by vocalization call type and caller identity showed that ∼19% of cells had a main effect of call type with fewer cells encoding caller. Classification performance of VLPFC neurons was ∼42% averaged across the population. When assessed at discrete time bins, classification performance reached 70 percent for coos in the first 300 ms and remained above chance for the duration of the response period, though performance was lower for other call types. In light of the sub-optimal classification performance of the majority of VLPFC neurons when only vocal information is present, and the recent evidence that most VLPFC neurons are multisensory, the potential enhancement of classification with the addition of accompanying face information is discussed and additional studies recommended. Behavioral and neuronal evidence has shown a considerable benefit in recognition and memory performance when faces and voices are presented simultaneously. In the natural environment both facial and vocalization information is present simultaneously and neural systems no doubt evolved to integrate multisensory stimuli during recognition. This article is part of a Special Issue entitled "Communication Sounds and the Brain: New Directions and Perspectives". Copyright © 2013 Elsevier B.V. All rights reserved.

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

Double dissociation of value computations in orbitofrontal and anterior cingulate neurons

PubMed Central

Kennerley, Steven W.; Behrens, Timothy E. J.; Wallis, Jonathan D.

2011-01-01

Damage to prefrontal cortex (PFC) impairs decision-making, but the underlying value computations that might cause such impairments remain unclear. Here we report that value computations are doubly dissociable within PFC neurons. While many PFC neurons encoded chosen value, they used opponent encoding schemes such that averaging the neuronal population eliminated value coding. However, a special population of neurons in anterior cingulate cortex (ACC) - but not orbitofrontal cortex (OFC) - multiplex chosen value across decision parameters using a unified encoding scheme, and encoded reward prediction errors. In contrast, neurons in OFC - but not ACC - encoded chosen value relative to the recent history of choice values. Together, these results suggest complementary valuation processes across PFC areas: OFC neurons dynamically evaluate current choices relative to recent choice values, while ACC neurons encode choice predictions and prediction errors using a common valuation currency reflecting the integration of multiple decision parameters. PMID:22037498

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

A neural coding scheme reproducing foraging trajectories

NASA Astrophysics Data System (ADS)

Gutiérrez, Esther D.; Cabrera, Juan Luis

2015-12-01

The movement of many animals may follow Lévy patterns. The underlying generating neuronal dynamics of such a behavior is unknown. In this paper we show that a novel discovery of multifractality in winnerless competition (WLC) systems reveals a potential encoding mechanism that is translatable into two dimensional superdiffusive Lévy movements. The validity of our approach is tested on a conductance based neuronal model showing WLC and through the extraction of Lévy flights inducing fractals from recordings of rat hippocampus during open field foraging. Further insights are gained analyzing mice motor cortex neurons and non motor cell signals. The proposed mechanism provides a plausible explanation for the neuro-dynamical fundamentals of spatial searching patterns observed in animals (including humans) and illustrates an until now unknown way to encode information in neuronal temporal series.

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.

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.

Behavioral and Single-Neuron Sensitivity to Millisecond Variations in Temporally Patterned Communication Signals

PubMed Central

Baker, Christa A.; Ma, Lisa; Casareale, Chelsea R.

2016-01-01

In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8–12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. SIGNIFICANCE STATEMENT The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals. PMID:27559179

Behavioral and Single-Neuron Sensitivity to Millisecond Variations in Temporally Patterned Communication Signals.

PubMed

Baker, Christa A; Ma, Lisa; Casareale, Chelsea R; Carlson, Bruce A

2016-08-24

In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8-12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals. Copyright © 2016 the authors 0270-6474/16/368985-16$15.00/0.

The Vestibular System Implements a Linear–Nonlinear Transformation In Order to Encode Self-Motion

PubMed Central

Massot, Corentin; Schneider, Adam D.; Chacron, Maurice J.; Cullen, Kathleen E.

2012-01-01

Although it is well established that the neural code representing the world changes at each stage of a sensory pathway, the transformations that mediate these changes are not well understood. Here we show that self-motion (i.e. vestibular) sensory information encoded by VIIIth nerve afferents is integrated nonlinearly by post-synaptic central vestibular neurons. This response nonlinearity was characterized by a strong (∼50%) attenuation in neuronal sensitivity to low frequency stimuli when presented concurrently with high frequency stimuli. Using computational methods, we further demonstrate that a static boosting nonlinearity in the input-output relationship of central vestibular neurons accounts for this unexpected result. Specifically, when low and high frequency stimuli are presented concurrently, this boosting nonlinearity causes an intensity-dependent bias in the output firing rate, thereby attenuating neuronal sensitivities. We suggest that nonlinear integration of afferent input extends the coding range of central vestibular neurons and enables them to better extract the high frequency features of self-motion when embedded with low frequency motion during natural movements. These findings challenge the traditional notion that the vestibular system uses a linear rate code to transmit information and have important consequences for understanding how the representation of sensory information changes across sensory pathways. PMID:22911113

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.

Modeling task-specific neuronal ensembles improves decoding of grasp

NASA Astrophysics Data System (ADS)

Smith, Ryan J.; Soares, Alcimar B.; Rouse, Adam G.; Schieber, Marc H.; Thakor, Nitish V.

2018-06-01

Objective. Dexterous movement involves the activation and coordination of networks of neuronal populations across multiple cortical regions. Attempts to model firing of individual neurons commonly treat the firing rate as directly modulating with motor behavior. However, motor behavior may additionally be associated with modulations in the activity and functional connectivity of neurons in a broader ensemble. Accounting for variations in neural ensemble connectivity may provide additional information about the behavior being performed. Approach. In this study, we examined neural ensemble activity in primary motor cortex (M1) and premotor cortex (PM) of two male rhesus monkeys during performance of a center-out reach, grasp and manipulate task. We constructed point process encoding models of neuronal firing that incorporated task-specific variations in the baseline firing rate as well as variations in functional connectivity with the neural ensemble. Models were evaluated both in terms of their encoding capabilities and their ability to properly classify the grasp being performed. Main results. Task-specific ensemble models correctly predicted the performed grasp with over 95% accuracy and were shown to outperform models of neuronal activity that assume only a variable baseline firing rate. Task-specific ensemble models exhibited superior decoding performance in 82% of units in both monkeys (p  <  0.01). Inclusion of ensemble activity also broadly improved the ability of models to describe observed spiking. Encoding performance of task-specific ensemble models, measured by spike timing predictability, improved upon baseline models in 62% of units. Significance. These results suggest that additional discriminative information about motor behavior found in the variations in functional connectivity of neuronal ensembles located in motor-related cortical regions is relevant to decode complex tasks such as grasping objects, and may serve the basis for more reliable and accurate neural prosthesis.

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

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.

Encoding properties of haltere neurons enable motion feature detection in a biological gyroscope

PubMed Central

Fox, Jessica L.; Fairhall, Adrienne L.; Daniel, Thomas L.

2010-01-01

The halteres of dipteran insects are essential sensory organs for flight control. They are believed to detect Coriolis and other inertial forces associated with body rotation during flight. Flies use this information for rapid flight control. We show that the primary afferent neurons of the haltere’s mechanoreceptors respond selectively with high temporal precision to multiple stimulus features. Although we are able to identify many stimulus features contributing to the response using principal component analysis, predictive models using only two features, common across the cell population, capture most of the cells’ encoding activity. However, different sensitivity to these two features permits each cell to respond to sinusoidal stimuli with a different preferred phase. This feature similarity, combined with diverse phase encoding, allows the haltere to transmit information at a high rate about numerous inertial forces, including Coriolis forces. PMID:20133721

Extracellular voltage threshold settings can be tuned for optimal encoding of movement and stimulus parameters

NASA Astrophysics Data System (ADS)

Oby, Emily R.; Perel, Sagi; Sadtler, Patrick T.; Ruff, Douglas A.; Mischel, Jessica L.; Montez, David F.; Cohen, Marlene R.; Batista, Aaron P.; Chase, Steven M.

2016-06-01

Objective. A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain-computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1). Approach. We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings. Main Results. The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography. Significance. How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent, and thus enhance BCI control. Further, by sweeping the detection threshold, one can gain insights into the topographic organization of the nearby neural tissue.

Extracellular voltage threshold settings can be tuned for optimal encoding of movement and stimulus parameters

PubMed Central

Oby, Emily R; Perel, Sagi; Sadtler, Patrick T; Ruff, Douglas A; Mischel, Jessica L; Montez, David F; Cohen, Marlene R; Batista, Aaron P; Chase, Steven M

2018-01-01

Objective A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain–computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1). Approach We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings. Main Results The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography. Significance How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent, and thus enhance BCI control. Further, by sweeping the detection threshold, one can gain insights into the topographic organization of the nearby neural tissue. PMID:27097901

Extracellular voltage threshold settings can be tuned for optimal encoding of movement and stimulus parameters.

PubMed

Oby, Emily R; Perel, Sagi; Sadtler, Patrick T; Ruff, Douglas A; Mischel, Jessica L; Montez, David F; Cohen, Marlene R; Batista, Aaron P; Chase, Steven M

2016-06-01

A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain-computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1). We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings. The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography. How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent, and thus enhance BCI control. Further, by sweeping the detection threshold, one can gain insights into the topographic organization of the nearby neural tissue.

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.

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.

Hemispheric encoding/retrieval asymmetry in episodic memory: positron emission tomography findings.

PubMed Central

Tulving, E; Kapur, S; Craik, F I; Moscovitch, M; Houle, S

1994-01-01

Data are reviewed from positron emission tomography studies of encoding and retrieval processes in episodic memory. These data suggest a hemispheric encoding/retrieval asymmetry model of prefrontal involvement in encoding and retrieval of episodic memory. According to this model, the left and right prefrontal lobes are part of an extensive neuronal network that subserves episodic remembering, but the two prefrontal hemispheres play different roles. Left prefrontal cortical regions are differentially more involved in retrieval of information from semantic memory and in simultaneously encoding novel aspects of the retrieved information into episodic memory. Right prefrontal cortical regions, on the other hand, are differentially more involved in episodic memory retrieval. PMID:8134342

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.

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

A neural coding scheme reproducing foraging trajectories

PubMed Central

Gutiérrez, Esther D.; Cabrera, Juan Luis

2015-01-01

The movement of many animals may follow Lévy patterns. The underlying generating neuronal dynamics of such a behavior is unknown. In this paper we show that a novel discovery of multifractality in winnerless competition (WLC) systems reveals a potential encoding mechanism that is translatable into two dimensional superdiffusive Lévy movements. The validity of our approach is tested on a conductance based neuronal model showing WLC and through the extraction of Lévy flights inducing fractals from recordings of rat hippocampus during open field foraging. Further insights are gained analyzing mice motor cortex neurons and non motor cell signals. The proposed mechanism provides a plausible explanation for the neuro-dynamical fundamentals of spatial searching patterns observed in animals (including humans) and illustrates an until now unknown way to encode information in neuronal temporal series. PMID:26648311

Dopamine neurons share common response function for reward prediction error

PubMed Central

Eshel, Neir; Tian, Ju; Bukwich, Michael; Uchida, Naoshige

2016-01-01

Dopamine neurons are thought to signal reward prediction error, or the difference between actual and predicted reward. How dopamine neurons jointly encode this information, however, remains unclear. One possibility is that different neurons specialize in different aspects of prediction error; another is that each neuron calculates prediction error in the same way. We recorded from optogenetically-identified dopamine neurons in the lateral ventral tegmental area (VTA) while mice performed classical conditioning tasks. Our tasks allowed us to determine the full prediction error functions of dopamine neurons and compare them to each other. We found striking homogeneity among individual dopamine neurons: their responses to both unexpected and expected rewards followed the same function, just scaled up or down. As a result, we could describe both individual and population responses using just two parameters. Such uniformity ensures robust information coding, allowing each dopamine neuron to contribute fully to the prediction error signal. PMID:26854803

Refractory Sampling Links Efficiency and Costs of Sensory Encoding to Stimulus Statistics

PubMed Central

Song, Zhuoyi

2014-01-01

Sensory neurons integrate information about the world, adapting their sampling to its changes. However, little is understood mechanistically how this primary encoding process, which ultimately limits perception, depends upon stimulus statistics. Here, we analyze this open question systematically by using intracellular recordings from fly (Drosophila melanogaster and Coenosia attenuata) photoreceptors and corresponding stochastic simulations from biophysically realistic photoreceptor models. Recordings show that photoreceptors can sample more information from naturalistic light intensity time series (NS) than from Gaussian white-noise (GWN), shuffled-NS or Gaussian-1/f stimuli; integrating larger responses with higher signal-to-noise ratio and encoding efficiency to large bursty contrast changes. Simulations reveal how a photoreceptor's information capture depends critically upon the stochastic refractoriness of its 30,000 sampling units (microvilli). In daylight, refractoriness sacrifices sensitivity to enhance intensity changes in neural image representations, with more and faster microvilli improving encoding. But for GWN and other stimuli, which lack longer dark contrasts of real-world intensity changes that reduce microvilli refractoriness, these performance gains are submaximal and energetically costly. These results provide mechanistic reasons why information sampling is more efficient for natural/naturalistic stimulation and novel insight into the operation, design, and evolution of signaling and code in sensory neurons. PMID:24849356

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

PubMed Central

Resnik, Andrey; Celikel, Tansu; Englitz, Bernhard

2016-01-01

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information. PMID:27304526

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding.

PubMed

Huang, Chao; Resnik, Andrey; Celikel, Tansu; Englitz, Bernhard

2016-06-01

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.

Ensemble codes involving hippocampal neurons are at risk during delayed performance tests.

PubMed

Hampson, R E; Deadwyler, S A

1996-11-26

Multielectrode recording techniques were used to record ensemble activity from 10 to 16 simultaneously active CA1 and CA3 neurons in the rat hippocampus during performance of a spatial delayed-nonmatch-to-sample task. Extracted sources of variance were used to assess the nature of two different types of errors that accounted for 30% of total trials. The two types of errors included ensemble "miscodes" of sample phase information and errors associated with delay-dependent corruption or disappearance of sample information at the time of the nonmatch response. Statistical assessment of trial sequences and associated "strength" of hippocampal ensemble codes revealed that miscoded error trials always followed delay-dependent error trials in which encoding was "weak," indicating that the two types of errors were "linked." It was determined that the occurrence of weakly encoded, delay-dependent error trials initiated an ensemble encoding "strategy" that increased the chances of being correct on the next trial and avoided the occurrence of further delay-dependent errors. Unexpectedly, the strategy involved "strongly" encoding response position information from the prior (delay-dependent) error trial and carrying it forward to the sample phase of the next trial. This produced a miscode type error on trials in which the "carried over" information obliterated encoding of the sample phase response on the next trial. Application of this strategy, irrespective of outcome, was sufficient to reorient the animal to the proper between trial sequence of response contingencies (nonmatch-to-sample) and boost performance to 73% correct on subsequent trials. The capacity for ensemble analyses of strength of information encoding combined with statistical assessment of trial sequences therefore provided unique insight into the "dynamic" nature of the role hippocampus plays in delay type memory tasks.

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

Engram formation in psychiatric disorders.

PubMed

Gebicke-Haerter, Peter J

2014-01-01

Environmental factors substantially influence beginning and progression of mental illness, reinforcing or reducing the consequences of genetic vulnerability. Often initiated by early traumatic events, "engrams" or memories are formed that may give rise to a slow and subtle progression of psychiatric disorders. The large delay between beginning and time of onset (diagnosis) may be explained by efficient compensatory mechanisms observed in brain metabolism that use optional pathways in highly redundant molecular interactions. To this end, research has to deal with mechanisms of learning and long-term memory formation, which involves (a) epigenetic changes, (b) altered neuronal activities, and (c) changes in neuron-glia communication. On the epigenetic level, apparently DNA-methylations are more stable than histone modifications, although both closely interact. Neuronal activities basically deliver digital information, which clearly can serve as basis for memory formation (LTP). However, research in this respect has long time neglected the importance of glia. They are more actively involved in the control of neuronal activities than thought before. They can both reinforce and inhibit neuronal activities by transducing neuronal information from frequency-encoded to amplitude and frequency-modulated calcium wave patterns spreading in the glial syncytium by use of gap junctions. In this way, they serve integrative functions. In conclusion, we are dealing with two concepts of encoding information that mutually control each other and synergize: a digital (neuronal) and a wave-like (glial) computing, forming neuron-glia functional units with inbuilt feedback loops to maintain balance of excitation and inhibition. To better understand mental illness, we have to gain more insight into the dynamics of adverse environmental impact on those cellular and molecular systems. This report summarizes existing knowledge and draws some outline about further research in molecular psychiatry.

Engram formation in psychiatric disorders

PubMed Central

Gebicke-Haerter, Peter J.

2014-01-01

Environmental factors substantially influence beginning and progression of mental illness, reinforcing or reducing the consequences of genetic vulnerability. Often initiated by early traumatic events, “engrams” or memories are formed that may give rise to a slow and subtle progression of psychiatric disorders. The large delay between beginning and time of onset (diagnosis) may be explained by efficient compensatory mechanisms observed in brain metabolism that use optional pathways in highly redundant molecular interactions. To this end, research has to deal with mechanisms of learning and long-term memory formation, which involves (a) epigenetic changes, (b) altered neuronal activities, and (c) changes in neuron-glia communication. On the epigenetic level, apparently DNA-methylations are more stable than histone modifications, although both closely interact. Neuronal activities basically deliver digital information, which clearly can serve as basis for memory formation (LTP). However, research in this respect has long time neglected the importance of glia. They are more actively involved in the control of neuronal activities than thought before. They can both reinforce and inhibit neuronal activities by transducing neuronal information from frequency-encoded to amplitude and frequency-modulated calcium wave patterns spreading in the glial syncytium by use of gap junctions. In this way, they serve integrative functions. In conclusion, we are dealing with two concepts of encoding information that mutually control each other and synergize: a digital (neuronal) and a wave-like (glial) computing, forming neuron-glia functional units with inbuilt feedback loops to maintain balance of excitation and inhibition. To better understand mental illness, we have to gain more insight into the dynamics of adverse environmental impact on those cellular and molecular systems. This report summarizes existing knowledge and draws some outline about further research in molecular psychiatry. PMID:24904262

UniEnt: uniform entropy model for the dynamics of a neuronal population

NASA Astrophysics Data System (ADS)

Hernandez Lahme, Damian; Nemenman, Ilya

Sensory information and motor responses are encoded in the brain in a collective spiking activity of a large number of neurons. Understanding the neural code requires inferring statistical properties of such collective dynamics from multicellular neurophysiological recordings. Questions of whether synchronous activity or silence of multiple neurons carries information about the stimuli or the motor responses are especially interesting. Unfortunately, detection of such high order statistical interactions from data is especially challenging due to the exponentially large dimensionality of the state space of neural collectives. Here we present UniEnt, a method for the inference of strengths of multivariate neural interaction patterns. The method is based on the Bayesian prior that makes no assumptions (uniform a priori expectations) about the value of the entropy of the observed multivariate neural activity, in contrast to popular approaches that maximize this entropy. We then study previously published multi-electrode recordings data from salamander retina, exposing the relevance of higher order neural interaction patterns for information encoding in this system. This work was supported in part by Grants JSMF/220020321 and NSF/IOS/1208126.

Massively parallel neural circuits for stereoscopic color vision: encoding, decoding and identification.

PubMed

Lazar, Aurel A; Slutskiy, Yevgeniy B; Zhou, Yiyin

2015-03-01

Past work demonstrated how monochromatic visual stimuli could be faithfully encoded and decoded under Nyquist-type rate conditions. Color visual stimuli were then traditionally encoded and decoded in multiple separate monochromatic channels. The brain, however, appears to mix information about color channels at the earliest stages of the visual system, including the retina itself. If information about color is mixed and encoded by a common pool of neurons, how can colors be demixed and perceived? We present Color Video Time Encoding Machines (Color Video TEMs) for encoding color visual stimuli that take into account a variety of color representations within a single neural circuit. We then derive a Color Video Time Decoding Machine (Color Video TDM) algorithm for color demixing and reconstruction of color visual scenes from spikes produced by a population of visual neurons. In addition, we formulate Color Video Channel Identification Machines (Color Video CIMs) for functionally identifying color visual processing performed by a spiking neural circuit. Furthermore, we derive a duality between TDMs and CIMs that unifies the two and leads to a general theory of neural information representation for stereoscopic color vision. We provide examples demonstrating that a massively parallel color visual neural circuit can be first identified with arbitrary precision and its spike trains can be subsequently used to reconstruct the encoded stimuli. We argue that evaluation of the functional identification methodology can be effectively and intuitively performed in the stimulus space. In this space, a signal reconstructed from spike trains generated by the identified neural circuit can be compared to the original stimulus. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Optimal sparse approximation with integrate and fire neurons.

PubMed

Shapero, Samuel; Zhu, Mengchen; Hasler, Jennifer; Rozell, Christopher

2014-08-01

Sparse approximation is a hypothesized coding strategy where a population of sensory neurons (e.g. V1) encodes a stimulus using as few active neurons as possible. We present the Spiking LCA (locally competitive algorithm), a rate encoded Spiking Neural Network (SNN) of integrate and fire neurons that calculate sparse approximations. The Spiking LCA is designed to be equivalent to the nonspiking LCA, an analog dynamical system that converges on a ℓ(1)-norm sparse approximations exponentially. We show that the firing rate of the Spiking LCA converges on the same solution as the analog LCA, with an error inversely proportional to the sampling time. We simulate in NEURON a network of 128 neuron pairs that encode 8 × 8 pixel image patches, demonstrating that the network converges to nearly optimal encodings within 20 ms of biological time. We also show that when using more biophysically realistic parameters in the neurons, the gain function encourages additional ℓ(0)-norm sparsity in the encoding, relative both to ideal neurons and digital solvers.

Decoding spike timing: the differential reverse correlation method

PubMed Central

Tkačik, Gašper; Magnasco, Marcelo O.

2009-01-01

It is widely acknowledged that detailed timing of action potentials is used to encode information, for example in auditory pathways; however the computational tools required to analyze encoding through timing are still in their infancy. We present a simple example of encoding, based on a recent model of time-frequency analysis, in which units fire action potentials when a certain condition is met, but the timing of the action potential depends also on other features of the stimulus. We show that, as a result, spike-triggered averages are smoothed so much they do not represent the true features of the encoding. Inspired by this example, we present a simple method, differential reverse correlations, that can separate an analysis of what causes a neuron to spike, and what controls its timing. We analyze with this method the leaky integrate-and-fire neuron and show the method accurately reconstructs the model's kernel. PMID:18597928

Video time encoding machines.

PubMed

Lazar, Aurel A; Pnevmatikakis, Eftychios A

2011-03-01

We investigate architectures for time encoding and time decoding of visual stimuli such as natural and synthetic video streams (movies, animation). The architecture for time encoding is akin to models of the early visual system. It consists of a bank of filters in cascade with single-input multi-output neural circuits. Neuron firing is based on either a threshold-and-fire or an integrate-and-fire spiking mechanism with feedback. We show that analog information is represented by the neural circuits as projections on a set of band-limited functions determined by the spike sequence. Under Nyquist-type and frame conditions, the encoded signal can be recovered from these projections with arbitrary precision. For the video time encoding machine architecture, we demonstrate that band-limited video streams of finite energy can be faithfully recovered from the spike trains and provide a stable algorithm for perfect recovery. The key condition for recovery calls for the number of neurons in the population to be above a threshold value.

Video Time Encoding Machines

PubMed Central

Lazar, Aurel A.; Pnevmatikakis, Eftychios A.

2013-01-01

We investigate architectures for time encoding and time decoding of visual stimuli such as natural and synthetic video streams (movies, animation). The architecture for time encoding is akin to models of the early visual system. It consists of a bank of filters in cascade with single-input multi-output neural circuits. Neuron firing is based on either a threshold-and-fire or an integrate-and-fire spiking mechanism with feedback. We show that analog information is represented by the neural circuits as projections on a set of band-limited functions determined by the spike sequence. Under Nyquist-type and frame conditions, the encoded signal can be recovered from these projections with arbitrary precision. For the video time encoding machine architecture, we demonstrate that band-limited video streams of finite energy can be faithfully recovered from the spike trains and provide a stable algorithm for perfect recovery. The key condition for recovery calls for the number of neurons in the population to be above a threshold value. PMID:21296708

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…

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

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

Decoding stimulus features in primate somatosensory cortex during perceptual categorization

PubMed Central

Alvarez, Manuel; Zainos, Antonio; Romo, Ranulfo

2015-01-01

Neurons of the primary somatosensory cortex (S1) respond as functions of frequency or amplitude of a vibrotactile stimulus. However, whether S1 neurons encode both frequency and amplitude of the vibrotactile stimulus or whether each sensory feature is encoded by separate populations of S1 neurons is not known, To further address these questions, we recorded S1 neurons while trained monkeys categorized only one sensory feature of the vibrotactile stimulus: frequency, amplitude, or duration. The results suggest a hierarchical encoding scheme in S1: from neurons that encode all sensory features of the vibrotactile stimulus to neurons that encode only one sensory feature. We hypothesize that the dynamic representation of each sensory feature in S1 might serve for further downstream processing that leads to the monkey’s psychophysical behavior observed in these tasks. PMID:25825711

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

Information recall using relative spike timing in a spiking neural network.

PubMed

Sterne, Philip

2012-08-01

We present a neural network that is capable of completing and correcting a spiking pattern given only a partial, noisy version. It operates in continuous time and represents information using the relative timing of individual spikes. The network is capable of correcting and recalling multiple patterns simultaneously. We analyze the network's performance in terms of information recall. We explore two measures of the capacity of the network: one that values the accurate recall of individual spike times and another that values only the presence or absence of complete patterns. Both measures of information are found to scale linearly in both the number of neurons and the period of the patterns, suggesting these are natural measures of network information. We show a smooth transition from encodings that provide precise spike times to flexible encodings that can encode many scenes. This makes it plausible that many diverse tasks could be learned with such an encoding.

Naturalistic stimulation changes the dynamic response of action potential encoding in a mechanoreceptor

PubMed Central

Pfeiffer, Keram; French, Andrew S.

2015-01-01

Naturalistic signals were created from vibrations made by locusts walking on a Sansevieria plant. Both naturalistic and Gaussian noise signals were used to mechanically stimulate VS-3 slit-sense mechanoreceptor neurons of the spider, Cupiennius salei, with stimulus amplitudes adjusted to give similar firing rates for either stimulus. Intracellular microelectrodes recorded action potentials, receptor potential, and receptor current, using current clamp and voltage clamp. Frequency response analysis showed that naturalistic stimulation contained relatively more power at low frequencies, and caused increased neuronal sensitivity to higher frequencies. In contrast, varying the amplitude of Gaussian stimulation did not change neuronal dynamics. Naturalistic stimulation contained less entropy than Gaussian, but signal entropy was higher than stimulus in the resultant receptor current, indicating addition of uncorrelated noise during transduction. The presence of added noise was supported by measuring linear information capacity in the receptor current. Total entropy and information capacity in action potentials produced by either stimulus were much lower than in earlier stages, and limited to the maximum entropy of binary signals. We conclude that the dynamics of action potential encoding in VS-3 neurons are sensitive to the form of stimulation, but entropy and information capacity of action potentials are limited by firing rate. PMID:26578975

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

Executive control processes underlying multi-item working memory

PubMed Central

Lara, Antonio H.; Wallis, Jonathan D.

2014-01-01

A dominant view of prefrontal cortex (PFC) function is that it stores task-relevant information in working memory. To examine this and determine how it applies when multiple pieces of information must be stored, we trained two macaque monkeys to perform a multi-item color change-detection task and recorded activity of neurons in PFC. Few neurons encoded the color of the items. Instead, the predominant encoding was spatial: a static signal reflecting the item's position and a dynamic signal reflecting the animal's covert attention. These findings challenge the notion that PFC stores task-relevant information. Instead, we suggest that the contribution of PFC is in controlling the allocation of resources to support working memory. In support of this, we found that increased power in the alpha and theta bands of PFC local field potentials, which are thought to reflect long-range communication with other brain areas, was correlated with more precise color representations. PMID:24747574

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.

Multimodal Encoding of Goal-Directed Actions in Monkey Ventral Premotor Grasping Neurons.

PubMed

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

2017-01-01

Visuo-motor neurons of the ventral premotor area F5 encode "pragmatic" representations of object in terms of the potential motor acts (e.g., precision grip) afforded by it. Likewise, objects with identical pragmatic features (e.g., small spheres) but different behavioral value (e.g., edible or inedible) convey different "semantic" information and thus afford different goal-directed behaviors (e.g., grasp-to-eat or grasp-to-place). However, whether F5 neurons can extract distinct behavioral affordances from objects with similar pragmatic features is unknown. We recorded 134 F5 visuo-motor neurons in 2 macaques during a contextually cued go/no-go task in which the monkey grasped, or refrained from grasping, a previously presented edible or inedible target to eat it or placing it, respectively. Sixty-nine visuo-motor neurons showed motor selectivity for the target (35 food and 34 object), and about half of them (N = 35) exhibited congruent visual preference. Interestingly, when the monkey grasped in complete darkness and could identify the target only based on haptic feedback, visuo-motor neurons lost their precontact selectivity, but most of them (80%) showed it again 60 ms after hand-target contact. These findings suggest that F5 neurons possess a multimodal access to semantic information on objects, which are transformed into motor representations of the potential goal-directed actions afforded by them. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

Traumatic Brain Injury and Neuronal Functionality Changes in Sensory Cortex

PubMed Central

Carron, Simone F.; Alwis, Dasuni S.; Rajan, Ramesh

2016-01-01

Traumatic brain injury (TBI), caused by direct blows to the head or inertial forces during relative head-brain movement, can result in long-lasting cognitive and motor deficits which can be particularly consequential when they occur in young people with a long life ahead. Much is known of the molecular and anatomical changes produced in TBI but much less is known of the consequences of these changes to neuronal functionality, especially in the cortex. Given that much of our interior and exterior lives are dependent on responsiveness to information from and about the world around us, we have hypothesized that a significant contributor to the cognitive and motor deficits seen after TBI could be changes in sensory processing. To explore this hypothesis, and to develop a model test system of the changes in neuronal functionality caused by TBI, we have examined neuronal encoding of simple and complex sensory input in the rat’s exploratory and discriminative tactile system, the large face macrovibrissae, which feeds to the so-called “barrel cortex” of somatosensory cortex. In this review we describe the short-term and long-term changes in the barrel cortex encoding of whisker motion modeling naturalistic whisker movement undertaken by rats engaged in a variety of tasks. We demonstrate that the most common form of TBI results in persistent neuronal hyperexcitation specifically in the upper cortical layers, likely due to changes in inhibition. We describe the types of cortical inhibitory neurons and their roles and how selective effects on some of these could produce the particular forms of neuronal encoding changes described in TBI, and then generalize to compare the effects on inhibition seen in other forms of brain injury. From these findings we make specific predictions as to how non-invasive extra-cranial electrophysiology can be used to provide the high-precision information needed to monitor and understand the temporal evolution of changes in neuronal functionality in humans suffering TBI. Such detailed understanding of the specific changes in an individual patient’s cortex can allow for treatment to be tailored to the neuronal changes in that particular patient’s brain in TBI, a precision that is currently unavailable with any technique. PMID:27313514

Encoding of Natural Sounds at Multiple Spectral and Temporal Resolutions in the Human Auditory Cortex

PubMed Central

Santoro, Roberta; Moerel, Michelle; De Martino, Federico; Goebel, Rainer; Ugurbil, Kamil; Yacoub, Essa; Formisano, Elia

2014-01-01

Functional neuroimaging research provides detailed observations of the response patterns that natural sounds (e.g. human voices and speech, animal cries, environmental sounds) evoke in the human brain. The computational and representational mechanisms underlying these observations, however, remain largely unknown. Here we combine high spatial resolution (3 and 7 Tesla) functional magnetic resonance imaging (fMRI) with computational modeling to reveal how natural sounds are represented in the human brain. We compare competing models of sound representations and select the model that most accurately predicts fMRI response patterns to natural sounds. Our results show that the cortical encoding of natural sounds entails the formation of multiple representations of sound spectrograms with different degrees of spectral and temporal resolution. The cortex derives these multi-resolution representations through frequency-specific neural processing channels and through the combined analysis of the spectral and temporal modulations in the spectrogram. Furthermore, our findings suggest that a spectral-temporal resolution trade-off may govern the modulation tuning of neuronal populations throughout the auditory cortex. Specifically, our fMRI results suggest that neuronal populations in posterior/dorsal auditory regions preferably encode coarse spectral information with high temporal precision. Vice-versa, neuronal populations in anterior/ventral auditory regions preferably encode fine-grained spectral information with low temporal precision. We propose that such a multi-resolution analysis may be crucially relevant for flexible and behaviorally-relevant sound processing and may constitute one of the computational underpinnings of functional specialization in auditory cortex. PMID:24391486

Stimulus encoding and feature extraction by multiple sensory neurons.

PubMed

Krahe, Rüdiger; Kreiman, Gabriel; Gabbiani, Fabrizio; Koch, Christof; Metzner, Walter

2002-03-15

Neighboring cells in topographical sensory maps may transmit similar information to the next higher level of processing. How information transmission by groups of nearby neurons compares with the performance of single cells is a very important question for understanding the functioning of the nervous system. To tackle this problem, we quantified stimulus-encoding and feature extraction performance by pairs of simultaneously recorded electrosensory pyramidal cells in the hindbrain of weakly electric fish. These cells constitute the output neurons of the first central nervous stage of electrosensory processing. Using random amplitude modulations (RAMs) of a mimic of the fish's own electric field within behaviorally relevant frequency bands, we found that pyramidal cells with overlapping receptive fields exhibit strong stimulus-induced correlations. To quantify the encoding of the RAM time course, we estimated the stimuli from simultaneously recorded spike trains and found significant improvements over single spike trains. The quality of stimulus reconstruction, however, was still inferior to the one measured for single primary sensory afferents. In an analysis of feature extraction, we found that spikes of pyramidal cell pairs coinciding within a time window of a few milliseconds performed significantly better at detecting upstrokes and downstrokes of the stimulus compared with isolated spikes and even spike bursts of single cells. Coincident spikes can thus be considered "distributed bursts." Our results suggest that stimulus encoding by primary sensory afferents is transformed into feature extraction at the next processing stage. There, stimulus-induced coincident activity can improve the extraction of behaviorally relevant features from the stimulus.

Adaptation can explain evidence for encoding of probabilistic information in macaque inferior temporal cortex.

PubMed

Vinken, Kasper; Vogels, Rufin

2017-11-20

In predictive coding theory, the brain is conceptualized as a prediction machine that constantly constructs and updates expectations of the sensory environment [1]. In the context of this theory, Bell et al.[2] recently studied the effect of the probability of task-relevant stimuli on the activity of macaque inferior temporal (IT) neurons and observed a reduced population response to expected faces in face-selective neurons. They concluded that "IT neurons encode long-term, latent probabilistic information about stimulus occurrence", supporting predictive coding. They manipulated expectation by the frequency of face versus fruit stimuli in blocks of trials. With such a design, stimulus repetition is confounded with expectation. As previous studies showed that IT neurons decrease their response with repetition [3], such adaptation (or repetition suppression), instead of expectation suppression as assumed by the authors, could explain their effects. The authors attempted to control for this alternative interpretation with a multiple regression approach. Here we show by using simulation that adaptation can still masquerade as expectation effects reported in [2]. Further, the results from the regression model used for most analyses cannot be trusted, because the model is not uniquely defined. Copyright © 2017 Elsevier Ltd. All rights reserved.

High-Dimensional Brain: A Tool for Encoding and Rapid Learning of Memories by Single Neurons.

PubMed

Tyukin, Ivan; Gorban, Alexander N; Calvo, Carlos; Makarova, Julia; Makarov, Valeri A

2018-03-19

Codifying memories is one of the fundamental problems of modern Neuroscience. The functional mechanisms behind this phenomenon remain largely unknown. Experimental evidence suggests that some of the memory functions are performed by stratified brain structures such as the hippocampus. In this particular case, single neurons in the CA1 region receive a highly multidimensional input from the CA3 area, which is a hub for information processing. We thus assess the implication of the abundance of neuronal signalling routes converging onto single cells on the information processing. We show that single neurons can selectively detect and learn arbitrary information items, given that they operate in high dimensions. The argument is based on stochastic separation theorems and the concentration of measure phenomena. We demonstrate that a simple enough functional neuronal model is capable of explaining: (i) the extreme selectivity of single neurons to the information content, (ii) simultaneous separation of several uncorrelated stimuli or informational items from a large set, and (iii) dynamic learning of new items by associating them with already "known" ones. These results constitute a basis for organization of complex memories in ensembles of single neurons. Moreover, they show that no a priori assumptions on the structural organization of neuronal ensembles are necessary for explaining basic concepts of static and dynamic memories.

Bayesian decoding using unsorted spikes in the rat hippocampus

PubMed Central

Layton, Stuart P.; Chen, Zhe; Wilson, Matthew A.

2013-01-01

A fundamental task in neuroscience is to understand how neural ensembles represent information. Population decoding is a useful tool to extract information from neuronal populations based on the ensemble spiking activity. We propose a novel Bayesian decoding paradigm to decode unsorted spikes in the rat hippocampus. Our approach uses a direct mapping between spike waveform features and covariates of interest and avoids accumulation of spike sorting errors. Our decoding paradigm is nonparametric, encoding model-free for representing stimuli, and extracts information from all available spikes and their waveform features. We apply the proposed Bayesian decoding algorithm to a position reconstruction task for freely behaving rats based on tetrode recordings of rat hippocampal neuronal activity. Our detailed decoding analyses demonstrate that our approach is efficient and better utilizes the available information in the nonsortable hash than the standard sorting-based decoding algorithm. Our approach can be adapted to an online encoding/decoding framework for applications that require real-time decoding, such as brain-machine interfaces. PMID:24089403

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.

Neurones associated with saccade metrics in the monkey central mesencephalic reticular formation

PubMed Central

Cromer, Jason A; Waitzman, David M

2006-01-01

Neurones in the central mesencephalic reticular formation (cMRF) begin to discharge prior to saccades. These long lead burst neurones interact with major oculomotor centres including the superior colliculus (SC) and the paramedian pontine reticular formation (PPRF). Three different functions have been proposed for neurones in the cMRF: (1) to carry eye velocity signals that provide efference copy information to the SC (feedback), (2) to provide duration signals from the omnipause neurones to the SC (feedback), or (3) to participate in the transformation from the spatial encoding of a target selection signal in the SC into the temporal pattern of discharge used to drive the excitatory burst neurones in the pons (feed-forward). According to each respective proposal, specific predictions about cMRF neuronal discharge have been formulated. Individual neurones should: (1) encode instantaneous eye velocity, (2) burst specifically in relation to saccade duration but not to other saccade metrics, or (3) have a spectrum of weak to strong correlations to saccade dynamics. To determine if cMRF neurones could subserve these multiple oculomotor roles, we examined neuronal activity in relation to a variety of saccade metrics including amplitude, velocity and duration. We found separate groups of cMRF neurones that have the characteristics predicted by each of the proposed models. We also identified a number of subgroups for which no specific model prediction had previously been established. We found that we could accurately predict the neuronal firing pattern during one type of saccade behaviour (visually guided) using the activity during an alternative behaviour with different saccade metrics (memory guided saccades). We suggest that this evidence of a close relationship of cMRF neuronal discharge to individual saccade metrics supports the hypothesis that the cMRF participates in multiple saccade control pathways carrying saccade amplitude, velocity and duration information within the brainstem. PMID:16308353

Neuronal population coding of perceived and memorized visual features in the lateral prefrontal cortex

PubMed Central

Mendoza-Halliday, Diego; Martinez-Trujillo, Julio C.

2017-01-01

The primate lateral prefrontal cortex (LPFC) encodes visual stimulus features while they are perceived and while they are maintained in working memory. However, it remains unclear whether perceived and memorized features are encoded by the same or different neurons and population activity patterns. Here we record LPFC neuronal activity while monkeys perceive the motion direction of a stimulus that remains visually available, or memorize the direction if the stimulus disappears. We find neurons with a wide variety of combinations of coding strength for perceived and memorized directions: some neurons encode both to similar degrees while others preferentially or exclusively encode either one. Reading out the combined activity of all neurons, a machine-learning algorithm reliably decode the motion direction and determine whether it is perceived or memorized. Our results indicate that a functionally diverse population of LPFC neurons provides a substrate for discriminating between perceptual and mnemonic representations of visual features. PMID:28569756

Millisecond-Scale Motor Encoding in a Cortical Vocal Area

NASA Astrophysics Data System (ADS)

Nemenman, Ilya; Tang, Claire; Chehayeb, Diala; Srivastava, Kyle; Sober, Samuel

2015-03-01

Studies of motor control have almost universally examined firing rates to investigate how the brain shapes behavior. In principle, however, neurons could encode information through the precise temporal patterning of their spike trains as well as (or instead of) through their firing rates. Although the importance of spike timing has been demonstrated in sensory systems, it is largely unknown whether timing differences in motor areas could affect behavior. We tested the hypothesis that significant information about trial-by-trial variations in behavior is represented by spike timing in the songbird vocal motor system. We found that neurons in motor cortex convey information via spike timing far more often than via spike rate and that the amount of information conveyed at the millisecond timescale greatly exceeds the information available from spike counts. These results demonstrate that information can be represented by spike timing in motor circuits and suggest that timing variations evoke differences in behavior. This work was supported in part by the National Institutes of Health, National Science Foundation, and James S. McDonnell Foundation

Sensor fusion in identified visual interneurons.

PubMed

Parsons, Matthew M; Krapp, Holger G; Laughlin, Simon B

2010-04-13

Animal locomotion often depends upon stabilization reflexes that use sensory feedback to maintain trajectories and orientation. Such stabilizing reflexes are critically important for the blowfly, whose aerodynamic instability permits outstanding maneuverability but increases the demands placed on flight control. Flies use several sensory systems to drive reflex responses, and recent studies have provided access to the circuitry responsible for combining and employing these sensory inputs. We report that lobula plate VS neurons combine inputs from two optical sensors, the ocelli and the compound eyes. Both systems deliver essential information on in-flight rotations, but our neuronal recordings reveal that the ocelli encode this information in three axes, whereas the compound eyes encode in nine. The difference in dimensionality is reconciled by tuning each VS neuron to the ocellar axis closest to its compound eye axis. We suggest that this simple projection combines the speed of the ocelli with the accuracy of the compound eyes without compromising either. Our findings also support the suggestion that the coordinates of sensory information processing are aligned with axes controlling the natural modes of the fly's flight to improve the efficiency with which sensory signals are transformed into appropriate motor commands.

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

Distributed Representation of Visual Objects by Single Neurons in the Human Brain

PubMed Central

Valdez, André B.; Papesh, Megan H.; Treiman, David M.; Smith, Kris A.; Goldinger, Stephen D.

2015-01-01

It remains unclear how single neurons in the human brain represent whole-object visual stimuli. While recordings in both human and nonhuman primates have shown distributed representations of objects (many neurons encoding multiple objects), recordings of single neurons in the human medial temporal lobe, taken as subjects' discriminated objects during multiple presentations, have shown gnostic representations (single neurons encoding one object). Because some studies suggest that repeated viewing may enhance neural selectivity for objects, we had human subjects discriminate objects in a single, more naturalistic viewing session. We found that, across 432 well isolated neurons recorded in the hippocampus and amygdala, the average fraction of objects encoded was 26%. We also found that more neurons encoded several objects versus only one object in the hippocampus (28 vs 18%, p < 0.001) and in the amygdala (30 vs 19%, p < 0.001). Thus, during realistic viewing experiences, typical neurons in the human medial temporal lobe code for a considerable range of objects, across multiple semantic categories. PMID:25834044

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

Encoding of social signals in all three electrosensory pathways of Eigenmannia virescens.

PubMed

Stöckl, Anna; Sinz, Fabian; Benda, Jan; Grewe, Jan

2014-11-01

Extracting complementary features in parallel pathways is a widely used strategy for a robust representation of sensory signals. Weakly electric fish offer the rare opportunity to study complementary encoding of social signals in all of its electrosensory pathways. Electrosensory information is conveyed in three parallel pathways: two receptor types of the tuberous (active) system and one receptor type of the ampullary (passive) system. Modulations of the fish's own electric field are sensed by these receptors and used in navigation, prey detection, and communication. We studied the neuronal representation of electric communication signals (called chirps) in the ampullary and the two tuberous pathways of Eigenmannia virescens. We first characterized different kinds of chirps observed in behavioral experiments. Since Eigenmannia chirps simultaneously drive all three types of receptors, we studied their responses in in vivo electrophysiological recordings. Our results demonstrate that different electroreceptor types encode different aspects of the stimuli and each appears best suited to convey information about a certain chirp type. A decoding analysis of single neurons and small populations shows that this specialization leads to a complementary representation of information in the tuberous and ampullary receptors. This suggests that a potential readout mechanism should combine information provided by the parallel processing streams to improve chirp detectability. Copyright © 2014 the American Physiological Society.

A shared neural ensemble links distinct contextual memories encoded close in time

NASA Astrophysics Data System (ADS)

Cai, Denise J.; Aharoni, Daniel; Shuman, Tristan; Shobe, Justin; Biane, Jeremy; Song, Weilin; Wei, Brandon; Veshkini, Michael; La-Vu, Mimi; Lou, Jerry; Flores, Sergio E.; Kim, Isaac; Sano, Yoshitake; Zhou, Miou; Baumgaertel, Karsten; Lavi, Ayal; Kamata, Masakazu; Tuszynski, Mark; Mayford, Mark; Golshani, Peyman; Silva, Alcino J.

2016-06-01

Recent studies suggest that a shared neural ensemble may link distinct memories encoded close in time. According to the memory allocation hypothesis, learning triggers a temporary increase in neuronal excitability that biases the representation of a subsequent memory to the neuronal ensemble encoding the first memory, such that recall of one memory increases the likelihood of recalling the other memory. Here we show in mice that the overlap between the hippocampal CA1 ensembles activated by two distinct contexts acquired within a day is higher than when they are separated by a week. Several findings indicate that this overlap of neuronal ensembles links two contextual memories. First, fear paired with one context is transferred to a neutral context when the two contexts are acquired within a day but not across a week. Second, the first memory strengthens the second memory within a day but not across a week. Older mice, known to have lower CA1 excitability, do not show the overlap between ensembles, the transfer of fear between contexts, or the strengthening of the second memory. Finally, in aged mice, increasing cellular excitability and activating a common ensemble of CA1 neurons during two distinct context exposures rescued the deficit in linking memories. Taken together, these findings demonstrate that contextual memories encoded close in time are linked by directing storage into overlapping ensembles. Alteration of these processes by ageing could affect the temporal structure of memories, thus impairing efficient recall of related information.

Metaplasticity contributes to memory formation in the hippocampus.

PubMed

Crestani, Ana P; Krueger, Jamie N; Barragan, Eden V; Nakazawa, Yuki; Nemes, Sonya E; Quillfeldt, Jorge A; Gray, John A; Wiltgen, Brian J

2018-05-16

Prior learning can modify the plasticity mechanisms that are used to encode new information. For example, NMDA receptor (NMDAR) activation is typically required for new spatial and contextual learning in the hippocampus. However, once animals have acquired this information, they can learn new tasks even if NMDARs are blocked. This finding suggests that behavioral training alters cellular plasticity mechanisms such that NMDARs are not required for subsequent learning. The mechanisms that mediate this change are currently unknown. To address this issue, we tested the idea that changes in intrinsic excitability (induced by learning) facilitate the encoding of new memories via metabotropic glutamate receptor (mGluR) activation. Consistent with this hypothesis, hippocampal neurons exhibited increases in intrinsic excitability after learning that lasted for several days. This increase was selective and only observed in neurons that were activated by the learning event. When animals were trained on a new task during this period, excitable neurons were reactivated and memory formation required the activation of mGluRs instead of NMDARs. These data suggest that increases in intrinsic excitability may serve as a metaplastic mechanism for memory formation.

Decoding sound level in the marmoset primary auditory cortex.

PubMed

Sun, Wensheng; Marongelli, Ellisha N; Watkins, Paul V; Barbour, Dennis L

2017-10-01

Neurons that respond favorably to a particular sound level have been observed throughout the central auditory system, becoming steadily more common at higher processing areas. One theory about the role of these level-tuned or nonmonotonic neurons is the level-invariant encoding of sounds. To investigate this theory, we simulated various subpopulations of neurons by drawing from real primary auditory cortex (A1) neuron responses and surveyed their performance in forming different sound level representations. Pure nonmonotonic subpopulations did not provide the best level-invariant decoding; instead, mixtures of monotonic and nonmonotonic neurons provided the most accurate decoding. For level-fidelity decoding, the inclusion of nonmonotonic neurons slightly improved or did not change decoding accuracy until they constituted a high proportion. These results indicate that nonmonotonic neurons fill an encoding role complementary to, rather than alternate to, monotonic neurons. NEW & NOTEWORTHY Neurons with nonmonotonic rate-level functions are unique to the central auditory system. These level-tuned neurons have been proposed to account for invariant sound perception across sound levels. Through systematic simulations based on real neuron responses, this study shows that neuron populations perform sound encoding optimally when containing both monotonic and nonmonotonic neurons. The results indicate that instead of working independently, nonmonotonic neurons complement the function of monotonic neurons in different sound-encoding contexts. Copyright © 2017 the American Physiological Society.

Characteristics of fast-spiking neurons in the striatum of behaving monkeys.

PubMed

Yamada, Hiroshi; Inokawa, Hitoshi; Hori, Yukiko; Pan, Xiaochuan; Matsuzaki, Ryuichi; Nakamura, Kae; Samejima, Kazuyuki; Shidara, Munetaka; Kimura, Minoru; Sakagami, Masamichi; Minamimoto, Takafumi

2016-04-01

Inhibitory interneurons are the fundamental constituents of neural circuits that organize network outputs. The striatum as part of the basal ganglia is involved in reward-directed behaviors. However, the role of the inhibitory interneurons in this process remains unclear, especially in behaving monkeys. We recorded the striatal single neuron activity while monkeys performed reward-directed hand or eye movements. Presumed parvalbumin-containing GABAergic interneurons (fast-spiking neurons, FSNs) were identified based on narrow spike shapes in three independent experiments, though they were a small population (4.2%, 42/997). We found that FSNs are characterized by high-frequency and less-bursty discharges, which are distinct from the basic firing properties of the presumed projection neurons (phasically active neurons, PANs). Besides, the encoded information regarding actions and outcomes was similar between FSNs and PANs in terms of proportion of neurons, but the discharge selectivity was higher in PANs than that of FSNs. The coding of actions and outcomes in FSNs and PANs was consistently observed under various behavioral contexts in distinct parts of the striatum (caudate nucleus, putamen, and anterior striatum). Our results suggest that FSNs may enhance the discharge selectivity of postsynaptic output neurons (PANs) in encoding crucial variables for a reward-directed behavior. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Locomotion Enhances Neural Encoding of Visual Stimuli in Mouse V1

PubMed Central

2017-01-01

Neurons in mouse primary visual cortex (V1) are selective for particular properties of visual stimuli. Locomotion causes a change in cortical state that leaves their selectivity unchanged but strengthens their responses. Both locomotion and the change in cortical state are thought to be initiated by projections from the mesencephalic locomotor region, the latter through a disinhibitory circuit in V1. By recording simultaneously from a large number of single neurons in alert mice viewing moving gratings, we investigated the relationship between locomotion and the information contained within the neural population. We found that locomotion improved encoding of visual stimuli in V1 by two mechanisms. First, locomotion-induced increases in firing rates enhanced the mutual information between visual stimuli and single neuron responses over a fixed window of time. Second, stimulus discriminability was improved, even for fixed population firing rates, because of a decrease in noise correlations across the population. These two mechanisms contributed differently to improvements in discriminability across cortical layers, with changes in firing rates most important in the upper layers and changes in noise correlations most important in layer V. Together, these changes resulted in a threefold to fivefold reduction in the time needed to precisely encode grating direction and orientation. These results support the hypothesis that cortical state shifts during locomotion to accommodate an increased load on the visual system when mice are moving. SIGNIFICANCE STATEMENT This paper contains three novel findings about the representation of information in neurons within the primary visual cortex of the mouse. First, we show that locomotion reduces by at least a factor of 3 the time needed for information to accumulate in the visual cortex that allows the distinction of different visual stimuli. Second, we show that the effect of locomotion is to increase information in cells of all layers of the visual cortex. Third, we show that the means by which information is enhanced by locomotion differs between the upper layers, where the major effect is the increasing of firing rates, and in layer V, where the major effect is the reduction in noise correlations. PMID:28264980

Dynamic state estimation based on Poisson spike trains—towards a theory of optimal encoding

NASA Astrophysics Data System (ADS)

Susemihl, Alex; Meir, Ron; Opper, Manfred

2013-03-01

Neurons in the nervous system convey information to higher brain regions by the generation of spike trains. An important question in the field of computational neuroscience is how these sensory neurons encode environmental information in a way which may be simply analyzed by subsequent systems. Many aspects of the form and function of the nervous system have been understood using the concepts of optimal population coding. Most studies, however, have neglected the aspect of temporal coding. Here we address this shortcoming through a filtering theory of inhomogeneous Poisson processes. We derive exact relations for the minimal mean squared error of the optimal Bayesian filter and, by optimizing the encoder, obtain optimal codes for populations of neurons. We also show that a class of non-Markovian, smooth stimuli are amenable to the same treatment, and provide results for the filtering and prediction error which hold for a general class of stochastic processes. This sets a sound mathematical framework for a population coding theory that takes temporal aspects into account. It also formalizes a number of studies which discussed temporal aspects of coding using time-window paradigms, by stating them in terms of correlation times and firing rates. We propose that this kind of analysis allows for a systematic study of temporal coding and will bring further insights into the nature of the neural code.

Explicit Encoding of Multimodal Percepts by Single Neurons in the Human Brain

PubMed Central

Quiroga, Rodrigo Quian; Kraskov, Alexander; Koch, Christof; Fried, Itzhak

2010-01-01

Summary Different pictures of Marilyn Monroe can evoke the same percept, even if greatly modified as in Andy Warhol’s famous portraits. But how does the brain recognize highly variable pictures as the same percept? Various studies have provided insights into how visual information is processed along the “ventral pathway,” via both single-cell recordings in monkeys [1, 2] and functional imaging in humans [3, 4]. Interestingly, in humans, the same “concept” of Marilyn Monroe can be evoked with other stimulus modalities, for instance by hearing or reading her name. Brain imaging studies have identified cortical areas selective to voices [5, 6] and visual word forms [7, 8]. However, how visual, text, and sound information can elicit a unique percept is still largely unknown. By using presentations of pictures and of spoken and written names, we show that (1) single neurons in the human medial temporal lobe (MTL) respond selectively to representations of the same individual across different sensory modalities; (2) the degree of multimodal invariance increases along the hierarchical structure within the MTL; and (3) such neuronal representations can be generated within less than a day or two. These results demonstrate that single neurons can encode percepts in an explicit, selective, and invariant manner, even if evoked by different sensory modalities. PMID:19631538

Imaging Voltage in Genetically Defined Neuronal Subpopulations with a Cre Recombinase-Targeted Hybrid Voltage Sensor.

PubMed

Bayguinov, Peter O; Ma, Yihe; Gao, Yu; Zhao, Xinyu; Jackson, Meyer B

2017-09-20

Genetically encoded voltage indicators create an opportunity to monitor electrical activity in defined sets of neurons as they participate in the complex patterns of coordinated electrical activity that underlie nervous system function. Taking full advantage of genetically encoded voltage indicators requires a generalized strategy for targeting the probe to genetically defined populations of cells. To this end, we have generated a mouse line with an optimized hybrid voltage sensor (hVOS) probe within a locus designed for efficient Cre recombinase-dependent expression. Crossing this mouse with Cre drivers generated double transgenics expressing hVOS probe in GABAergic, parvalbumin, and calretinin interneurons, as well as hilar mossy cells, new adult-born neurons, and recently active neurons. In each case, imaging in brain slices from male or female animals revealed electrically evoked optical signals from multiple individual neurons in single trials. These imaging experiments revealed action potentials, dynamic aspects of dendritic integration, and trial-to-trial fluctuations in response latency. The rapid time response of hVOS imaging revealed action potentials with high temporal fidelity, and enabled accurate measurements of spike half-widths characteristic of each cell type. Simultaneous recording of rapid voltage changes in multiple neurons with a common genetic signature offers a powerful approach to the study of neural circuit function and the investigation of how neural networks encode, process, and store information. SIGNIFICANCE STATEMENT Genetically encoded voltage indicators hold great promise in the study of neural circuitry, but realizing their full potential depends on targeting the sensor to distinct cell types. Here we present a new mouse line that expresses a hybrid optical voltage sensor under the control of Cre recombinase. Crossing this line with Cre drivers generated double-transgenic mice, which express this sensor in targeted cell types. In brain slices from these animals, single-trial hybrid optical voltage sensor recordings revealed voltage changes with submillisecond resolution in multiple neurons simultaneously. This imaging tool will allow for the study of the emergent properties of neural circuits and permit experimental tests of the roles of specific types of neurons in complex circuit activity. Copyright © 2017 the authors 0270-6474/17/379305-15$15.00/0.

Neurons within the trigeminal mesencephalic nucleus encode for the kinematic parameters of the whisker pad macrovibrissae.

PubMed

Mameli, Ombretta; Caria, Marcello A; Biagi, Francesca; Zedda, Marco; Farina, Vittorio

2017-05-01

It has been recently shown in rats that spontaneous movements of whisker pad macrovibrissae elicited evoked responses in the trigeminal mesencephalic nucleus (Me5). In the present study, electrophysiological and neuroanatomical experiments were performed in anesthetized rats to evaluate whether, besides the whisker displacement per se, the Me5 neurons are also involved in encoding the kinematic properties of macrovibrissae movements, and also whether, as reported for the trigeminal ganglion, even within the Me5 nucleus exists a neuroanatomical representation of the whisker pad macrovibrissae. Extracellular electrical activity of single Me5 neurons was recorded before, during, and after mechanical deflection of the ipsilateral whisker pad macrovibrissae in different directions, and with different velocities and amplitudes. In several groups of animals, single or multiple injections of the tracer Dil were performed into the whisker pad of one side, in close proximity to the vibrissae follicles, in order to label the peripheral terminals of the Me5 neurons innervating the macrovibrissae (whisking-neurons), and therefore, the respective perikaria within the nucleus. Results showed that: (1) the whisker pad macrovibrissae were represented in the medial-caudal part of the Me5 nucleus by a single cluster of cells whose number seemed to match that of the macrovibrissae; (2) macrovibrissae mechanical deflection elicited significant responses in the Me5 whisking-neurons, which were related to the direction, amplitude, and frequency of the applied deflection. The specific functional role of Me5 neurons involved in encoding proprioceptive information arising from the macrovibrissae movements is discussed within the framework of the whole trigeminal nuclei activities. © 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.

Distributed representation of visual objects by single neurons in the human brain.

PubMed

Valdez, André B; Papesh, Megan H; Treiman, David M; Smith, Kris A; Goldinger, Stephen D; Steinmetz, Peter N

2015-04-01

It remains unclear how single neurons in the human brain represent whole-object visual stimuli. While recordings in both human and nonhuman primates have shown distributed representations of objects (many neurons encoding multiple objects), recordings of single neurons in the human medial temporal lobe, taken as subjects' discriminated objects during multiple presentations, have shown gnostic representations (single neurons encoding one object). Because some studies suggest that repeated viewing may enhance neural selectivity for objects, we had human subjects discriminate objects in a single, more naturalistic viewing session. We found that, across 432 well isolated neurons recorded in the hippocampus and amygdala, the average fraction of objects encoded was 26%. We also found that more neurons encoded several objects versus only one object in the hippocampus (28 vs 18%, p < 0.001) and in the amygdala (30 vs 19%, p < 0.001). Thus, during realistic viewing experiences, typical neurons in the human medial temporal lobe code for a considerable range of objects, across multiple semantic categories. Copyright © 2015 the authors 0270-6474/15/355180-07$15.00/0.

The Role of Binocular Disparity in Stereoscopic Images of Objects in the Macaque Anterior Intraparietal Area

PubMed Central

Romero, Maria C.; Van Dromme, Ilse C. L.; Janssen, Peter

2013-01-01

Neurons in the macaque Anterior Intraparietal area (AIP) encode depth structure in random-dot stimuli defined by gradients of binocular disparity, but the importance of binocular disparity in real-world objects for AIP neurons is unknown. We investigated the effect of binocular disparity on the responses of AIP neurons to images of real-world objects during passive fixation. We presented stereoscopic images of natural and man-made objects in which the disparity information was congruent or incongruent with disparity gradients present in the real-world objects, and images of the same objects where such gradients were absent. Although more than half of the AIP neurons were significantly affected by binocular disparity, the great majority of AIP neurons remained image selective even in the absence of binocular disparity. AIP neurons tended to prefer stimuli in which the depth information derived from binocular disparity was congruent with the depth information signaled by monocular depth cues, indicating that these monocular depth cues have an influence upon AIP neurons. Finally, in contrast to neurons in the inferior temporal cortex, AIP neurons do not represent images of objects in terms of categories such as animate-inanimate, but utilize representations based upon simple shape features including aspect ratio. PMID:23408970

Congruent and Opposite Neurons as Partners in Multisensory Integration and Segregation

NASA Astrophysics Data System (ADS)

Zhang, Wen-Hao; Wong, K. Y. Michael; Wang, He; Wu, Si

Experiments revealed that where visual and vestibular cues are integrated to infer heading direction in the brain, there are two types of neurons with roughly the same number. Respectively, congruent and opposite cells respond similarly and oppositely to visual and vestibular cues. Congruent neurons are known to be responsible for cue integration, but the computational role of opposite neurons remains largely unknown. We propose that opposite neurons may serve to encode the disparity information between cues necessary for multisensory segregation. We build a computational model composed of two reciprocally coupled modules, each consisting of groups of congruent and opposite neurons. Our model reproduces the characteristics of congruent and opposite neurons, and demonstrates that in each module, congruent and opposite neurons can jointly achieve optimal multisensory information integration and segregation. This study sheds light on our understanding of how the brain implements optimal multisensory integration and segregation concurrently in a distributed manner. This work is supported by the Research Grants Council of Hong Kong (N _HKUST606/12, 605813, and 16322616) and National Basic Research Program of China (2014CB846101) and the Natural Science Foundation of China (31261160495).

Spiking computation and stochastic amplification in a neuron-like semiconductor microstructure

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

Samardak, A. S.; Laboratory of Thin Film Technologies, Far Eastern Federal University, Vladivostok 690950; Nogaret, A.

2011-05-15

We have demonstrated the proof of principle of a semiconductor neuron, which has dendrites, axon, and a soma and computes information encoded in electrical pulses in the same way as biological neurons. Electrical impulses applied to dendrites diffuse along microwires to the soma. The soma is the active part of the neuron, which regenerates input pulses above a voltage threshold and transmits them into the axon. Our concept of neuron is a major step forward because its spatial structure controls the timing of pulses, which arrive at the soma. Dendrites and axon act as transmission delay lines, which modify themore » information, coded in the timing of pulses. We have finally shown that noise enhances the detection sensitivity of the neuron by helping the transmission of weak periodic signals. A maximum enhancement of signal transmission was observed at an optimum noise level known as stochastic resonance. The experimental results are in excellent agreement with simulations of the FitzHugh-Nagumo model. Our neuron is therefore extremely well suited to providing feedback on the various mathematical approximations of neurons and building functional networks.« less

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

Luminance, Colour, Viewpoint and Border Enhanced Disparity Energy Model

PubMed Central

Martins, Jaime A.; Rodrigues, João M. F.; du Buf, Hans

2015-01-01

The visual cortex is able to extract disparity information through the use of binocular cells. This process is reflected by the Disparity Energy Model, which describes the role and functioning of simple and complex binocular neuron populations, and how they are able to extract disparity. This model uses explicit cell parameters to mathematically determine preferred cell disparities, like spatial frequencies, orientations, binocular phases and receptive field positions. However, the brain cannot access such explicit cell parameters; it must rely on cell responses. In this article, we implemented a trained binocular neuronal population, which encodes disparity information implicitly. This allows the population to learn how to decode disparities, in a similar way to how our visual system could have developed this ability during evolution. At the same time, responses of monocular simple and complex cells can also encode line and edge information, which is useful for refining disparities at object borders. The brain should then be able, starting from a low-level disparity draft, to integrate all information, including colour and viewpoint perspective, in order to propagate better estimates to higher cortical areas. PMID:26107954

Temporal coding of reward-guided choice in the posterior parietal cortex

PubMed Central

Hawellek, David J.; Wong, Yan T.; Pesaran, Bijan

2016-01-01

Making a decision involves computations across distributed cortical and subcortical networks. How such distributed processing is performed remains unclear. We test how the encoding of choice in a key decision-making node, the posterior parietal cortex (PPC), depends on the temporal structure of the surrounding population activity. We recorded spiking and local field potential (LFP) activity in the PPC while two rhesus macaques performed a decision-making task. We quantified the mutual information that neurons carried about an upcoming choice and its dependence on LFP activity. The spiking of PPC neurons was correlated with LFP phases at three distinct time scales in the theta, beta, and gamma frequency bands. Importantly, activity at these time scales encoded upcoming decisions differently. Choice information contained in neural firing varied with the phase of beta and gamma activity. For gamma activity, maximum choice information occurred at the same phase as the maximum spike count. However, for beta activity, choice information and spike count were greatest at different phases. In contrast, theta activity did not modulate the encoding properties of PPC units directly but was correlated with beta and gamma activity through cross-frequency coupling. We propose that the relative timing of local spiking and choice information reveals temporal reference frames for computations in either local or large-scale decision networks. Differences between the timing of task information and activity patterns may be a general signature of distributed processing across large-scale networks. PMID:27821752

Ankle joint movements are encoded by both cutaneous and muscle afferents in humans.

PubMed

Aimonetti, Jean-Marc; Roll, Jean-Pierre; Hospod, Valérie; Ribot-Ciscar, Edith

2012-08-01

We analyzed the cutaneous encoding of two-dimensional movements by investigating the coding of movement velocity for differently oriented straight-line movements and the coding of complex trajectories describing cursive letters. The cutaneous feedback was then compared with that of the underlying muscle afferents previously recorded during the same "writing-like" movements. The unitary activity of 43 type II cutaneous afferents was recorded in the common peroneal nerve in healthy subjects during imposed ankle movements. These movements consisted first of ramp-and-hold movements imposed at two different and close velocities in seven directions and secondly of "writing-like" movements. In both cases, the responses were analyzed using the neuronal population vector model. The results show that movement velocity encoding depended on the direction of the ongoing movement. Discriminating between two velocities therefore involved processing the activity of afferent populations located in the various skin areas surrounding the moving joint, as shown by the statistically significant difference observed in the amplitude of the sum vectors. Secondly, "writing-like" movements induced cutaneous neuronal patterns of activity, which were reproducible and specific to each trajectory. Lastly, the "cutaneous neuronal trajectories," built by adding the sum vectors tip-to-tail, nearly matched both the movement trajectories and the "muscle neuronal trajectories," built from previously recorded muscle afferents. It was concluded that type II cutaneous and the underlying muscle afferents show similar encoding properties of two-dimensional movement parameters. This similarity is discussed in relation to a central gating process that would for instance increase the gain of cutaneous inputs when muscle information is altered by the fusimotor drive.

Information transmission in hippocampal CA1 neuron models in the presence of poisson shot noise: the case of periodic sub-threshold spike trains.

PubMed

Kawaguchi, Minato; Mino, Hiroyuki; Durand, Dominique M

2006-01-01

This article presents an analysis of the information transmission of periodic sub-threshold spike trains in a hippocampal CA1 neuron model in the presence of a homogeneous Poisson shot noise. In the computer simulation, periodic sub-threshold spike trains were presented repeatedly to the midpoint of the main apical branch, while the homogeneous Poisson shot noise was applied to the mid-point of a basal dendrite in the CA1 neuron model consisting of the soma with one sodium, one calcium, and five potassium channels. From spike firing times recorded at the soma, the inter spike intervals were generated and then the probability, p(T), of the inter-spike interval histogram corresponding to the spike interval, r, of the periodic input spike trains was estimated to obtain an index of information transmission. In the present article, it is shown that at a specific amplitude of the homogeneous Poisson shot noise, p(T) was found to be maximized, as well as the possibility to encode the periodic sub-threshold spike trains became greater. It was implied that setting the amplitude of the homogeneous Poisson shot noise to the specific values which maximize the information transmission might contribute to efficiently encoding the periodic sub-threshold spike trains by utilizing the stochastic resonance.

Spatial attention improves the quality of population codes in human visual cortex.

PubMed

Saproo, Sameer; Serences, John T

2010-08-01

Selective attention enables sensory input from behaviorally relevant stimuli to be processed in greater detail, so that these stimuli can more accurately influence thoughts, actions, and future goals. Attention has been shown to modulate the spiking activity of single feature-selective neurons that encode basic stimulus properties (color, orientation, etc.). However, the combined output from many such neurons is required to form stable representations of relevant objects and little empirical work has formally investigated the relationship between attentional modulations on population responses and improvements in encoding precision. Here, we used functional MRI and voxel-based feature tuning functions to show that spatial attention induces a multiplicative scaling in orientation-selective population response profiles in early visual cortex. In turn, this multiplicative scaling correlates with an improvement in encoding precision, as evidenced by a concurrent increase in the mutual information between population responses and the orientation of attended stimuli. These data therefore demonstrate how multiplicative scaling of neural responses provides at least one mechanism by which spatial attention may improve the encoding precision of population codes. Increased encoding precision in early visual areas may then enhance the speed and accuracy of perceptual decisions computed by higher-order neural mechanisms.

Arc expression identifies the lateral amygdala fear memory trace

PubMed Central

Gouty-Colomer, L A; Hosseini, B; Marcelo, I M; Schreiber, J; Slump, D E; Yamaguchi, S; Houweling, A R; Jaarsma, D; Elgersma, Y; Kushner, S A

2016-01-01

Memories are encoded within sparsely distributed neuronal ensembles. However, the defining cellular properties of neurons within a memory trace remain incompletely understood. Using a fluorescence-based Arc reporter, we were able to visually identify the distinct subset of lateral amygdala (LA) neurons activated during auditory fear conditioning. We found that Arc-expressing neurons have enhanced intrinsic excitability and are preferentially recruited into newly encoded memory traces. Furthermore, synaptic potentiation of thalamic inputs to the LA during fear conditioning is learning-specific, postsynaptically mediated and highly localized to Arc-expressing neurons. Taken together, our findings validate the immediate-early gene Arc as a molecular marker for the LA neuronal ensemble recruited during fear learning. Moreover, these results establish a model of fear memory formation in which intrinsic excitability determines neuronal selection, whereas learning-related encoding is governed by synaptic plasticity. PMID:25802982

Neurons in Primary Motor Cortex Encode Hand Orientation in a Reach-to-Grasp Task.

PubMed

Ma, Chaolin; Ma, Xuan; Fan, Jing; He, Jiping

2017-08-01

It is disputed whether those neurons in the primary motor cortex (M1) that encode hand orientation constitute an independent channel for orientation control in reach-to-grasp behaviors. Here, we trained two monkeys to reach forward and grasp objects positioned in the frontal plane at different orientation angles, and simultaneously recorded the activity of M1 neurons. Among the 2235 neurons recorded in M1, we found that 18.7% had a high correlation exclusively with hand orientation, 15.9% with movement direction, and 29.5% with both movement direction and hand orientation. The distributions of neurons encoding hand orientation and those encoding movement direction were not uniform but coexisted in the same region. The trajectory of hand rotation was reproduced by the firing patterns of the orientation-related neurons independent of the hand reaching direction. These results suggest that hand orientation is an independent component for the control of reaching and grasping activity.

Corticothalamic Synaptic Noise as a Mechanism for Selective Attention in Thalamic Neurons.

PubMed

Béhuret, Sébastien; Deleuze, Charlotte; Bal, Thierry

2015-01-01

A reason why the thalamus is more than a passive gateway for sensory signals is that two-third of the synapses of thalamocortical neurons are directly or indirectly related to the activity of corticothalamic axons. While the responses of thalamocortical neurons evoked by sensory stimuli are well characterized, with ON- and OFF-center receptive field structures, the prevalence of synaptic noise resulting from neocortical feedback in intracellularly recorded thalamocortical neurons in vivo has attracted little attention. However, in vitro and modeling experiments point to its critical role for the integration of sensory signals. Here we combine our recent findings in a unified framework suggesting the hypothesis that corticothalamic synaptic activity is adapted to modulate the transfer efficiency of thalamocortical neurons during selective attention at three different levels: First, on ionic channels by interacting with intrinsic membrane properties, second at the neuron level by impacting on the input-output gain, and third even more effectively at the cell assembly level by boosting the information transfer of sensory features encoded in thalamic subnetworks. This top-down population control is achieved by tuning the correlations in subthreshold membrane potential fluctuations and is adapted to modulate the transfer of sensory features encoded by assemblies of thalamocortical relay neurons. We thus propose that cortically-controlled (de-)correlation of subthreshold noise is an efficient and swift dynamic mechanism for selective attention in the thalamus.

Corticothalamic Synaptic Noise as a Mechanism for Selective Attention in Thalamic Neurons

PubMed Central

Béhuret, Sébastien; Deleuze, Charlotte; Bal, Thierry

2015-01-01

A reason why the thalamus is more than a passive gateway for sensory signals is that two-third of the synapses of thalamocortical neurons are directly or indirectly related to the activity of corticothalamic axons. While the responses of thalamocortical neurons evoked by sensory stimuli are well characterized, with ON- and OFF-center receptive field structures, the prevalence of synaptic noise resulting from neocortical feedback in intracellularly recorded thalamocortical neurons in vivo has attracted little attention. However, in vitro and modeling experiments point to its critical role for the integration of sensory signals. Here we combine our recent findings in a unified framework suggesting the hypothesis that corticothalamic synaptic activity is adapted to modulate the transfer efficiency of thalamocortical neurons during selective attention at three different levels: First, on ionic channels by interacting with intrinsic membrane properties, second at the neuron level by impacting on the input-output gain, and third even more effectively at the cell assembly level by boosting the information transfer of sensory features encoded in thalamic subnetworks. This top-down population control is achieved by tuning the correlations in subthreshold membrane potential fluctuations and is adapted to modulate the transfer of sensory features encoded by assemblies of thalamocortical relay neurons. We thus propose that cortically-controlled (de-)correlation of subthreshold noise is an efficient and swift dynamic mechanism for selective attention in the thalamus. PMID:26733818

Coding of time-dependent stimuli in homogeneous and heterogeneous neural populations.

PubMed

Beiran, Manuel; Kruscha, Alexandra; Benda, Jan; Lindner, Benjamin

2018-04-01

We compare the information transmission of a time-dependent signal by two types of uncoupled neuron populations that differ in their sources of variability: i) a homogeneous population whose units receive independent noise and ii) a deterministic heterogeneous population, where each unit exhibits a different baseline firing rate ('disorder'). Our criterion for making both sources of variability quantitatively comparable is that the interspike-interval distributions are identical for both systems. Numerical simulations using leaky integrate-and-fire neurons unveil that a non-zero amount of both noise or disorder maximizes the encoding efficiency of the homogeneous and heterogeneous system, respectively, as a particular case of suprathreshold stochastic resonance. Our findings thus illustrate that heterogeneity can render similarly profitable effects for neuronal populations as dynamic noise. The optimal noise/disorder depends on the system size and the properties of the stimulus such as its intensity or cutoff frequency. We find that weak stimuli are better encoded by a noiseless heterogeneous population, whereas for strong stimuli a homogeneous population outperforms an equivalent heterogeneous system up to a moderate noise level. Furthermore, we derive analytical expressions of the coherence function for the cases of very strong noise and of vanishing intrinsic noise or heterogeneity, which predict the existence of an optimal noise intensity. Our results show that, depending on the type of signal, noise as well as heterogeneity can enhance the encoding performance of neuronal populations.

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.

Dense encoding of natural odorants by ensembles of sparsely activated neurons in the olfactory bulb

PubMed Central

Gschwend, Olivier; Beroud, Jonathan; Vincis, Roberto; Rodriguez, Ivan; Carleton, Alan

2016-01-01

Sensory information undergoes substantial transformation along sensory pathways, usually encompassing sparsening of activity. In the olfactory bulb, though natural odorants evoke dense glomerular input maps, mitral and tufted (M/T) cells tuning is considered to be sparse because of highly odor-specific firing rate change. However, experiments used to draw this conclusion were either based on recordings performed in anesthetized preparations or used monomolecular odorants presented at arbitrary concentrations. In this study, we evaluated the lifetime and population sparseness evoked by natural odorants by capturing spike temporal patterning of neuronal assemblies instead of individual M/T tonic activity. Using functional imaging and tetrode recordings in awake mice, we show that natural odorants at their native concentrations are encoded by broad assemblies of M/T cells. While reducing odorant concentrations, we observed a reduced number of activated glomeruli representations and consequently a narrowing of M/T tuning curves. We conclude that natural odorants at their native concentrations recruit M/T cells with phasic rather than tonic activity. When encoding odorants in assemblies, M/T cells carry information about a vast number of odorants (lifetime sparseness). In addition, each natural odorant activates a broad M/T cell assembly (population sparseness). PMID:27824096

Medial-lateral organization of the orbitofrontal cortex.

PubMed

Rich, Erin L; Wallis, Jonathan D

2014-07-01

Emerging evidence suggests that specific cognitive functions localize to different subregions of OFC, but the nature of these functional distinctions remains unclear. One prominent theory, derived from human neuroimaging, proposes that different stimulus valences are processed in separate orbital regions, with medial and lateral OFC processing positive and negative stimuli, respectively. Thus far, neurophysiology data have not supported this theory. We attempted to reconcile these accounts by recording neural activity from the full medial-lateral extent of the orbital surface in monkeys receiving rewards and punishments via gain or loss of secondary reinforcement. We found no convincing evidence for valence selectivity in any orbital region. Instead, we report differences between neurons in central OFC and those on the inferior-lateral orbital convexity, in that they encoded different sources of value information provided by the behavioral task. Neurons in inferior convexity encoded the value of external stimuli, whereas those in OFC encoded value information derived from the structure of the behavioral task. We interpret these results in light of recent theories of OFC function and propose that these distinctions, not valence selectivity, may shed light on a fundamental organizing principle for value processing in orbital cortex.

Anxiety Evokes Hypofrontality and Disrupts Rule-Relevant Encoding by Dorsomedial Prefrontal Cortex Neurons.

PubMed

Park, Junchol; Wood, Jesse; Bondi, Corina; Del Arco, Alberto; Moghaddam, Bita

2016-03-16

Anxiety is a debilitating symptom of most psychiatric disorders, including major depression, post-traumatic stress disorder, schizophrenia, and addiction. A detrimental aspect of anxiety is disruption of prefrontal cortex (PFC)-mediated executive functions, such as flexible decision making. Here we sought to understand how anxiety modulates PFC neuronal encoding of flexible shifting between behavioral strategies. We used a clinically substantiated anxiogenic treatment to induce sustained anxiety in rats and recorded from dorsomedial PFC (dmPFC) and orbitofrontal cortex (OFC) neurons while they were freely moving in a home cage and while they performed a PFC-dependent task that required flexible switches between rules in two distinct perceptual dimensions. Anxiety elicited a sustained background "hypofrontality" in dmPFC and OFC by reducing the firing rate of spontaneously active neuronal subpopulations. During task performance, the impact of anxiety was subtle, but, consistent with human data, behavior was selectively impaired when previously correct conditions were presented as conflicting choices. This impairment was associated with reduced recruitment of dmPFC neurons that selectively represented task rules at the time of action. OFC rule representation was not affected by anxiety. These data indicate that a neural substrate of the decision-making deficits in anxiety is diminished dmPFC neuronal encoding of task rules during conflict-related actions. Given the translational relevance of the model used here, the data provide a neuronal encoding mechanism for how anxiety biases decision making when the choice involves overcoming a conflict. They also demonstrate that PFC encoding of actions, as opposed to cues or outcome, is especially vulnerable to anxiety. A debilitating aspect of anxiety is its impact on decision making and flexible control of behavior. These cognitive constructs depend on proper functioning of the prefrontal cortex (PFC). Understanding how anxiety affects PFC encoding of cognitive events is of great clinical and evolutionary significance. Using a clinically valid experimental model, we find that, under anxiety, decision making may be skewed by salient and conflicting environmental stimuli at the expense of flexible top-down guided choices. We also find that anxiety suppresses spontaneous activity of PFC neurons, and weakens encoding of task rules by dorsomedial PFC neurons. These data provide a neuronal encoding scheme for how anxiety disengages PFC during decision making. Copyright © 2016 the authors 0270-6474/16/363322-14$15.00/0.

Pattern separation: a common function for new neurons in hippocampus and olfactory bulb.

PubMed

Sahay, Amar; Wilson, Donald A; Hen, René

2011-05-26

While adult-born neurons in the olfactory bulb (OB) and the dentate gyrus (DG) subregion of the hippocampus have fundamentally different properties, they may have more in common than meets the eye. Here, we propose that new granule cells in the OB and DG may function as modulators of principal neurons to influence pattern separation and that adult neurogenesis constitutes an adaptive mechanism to optimally encode contextual or olfactory information. See the related Perspective from Aimone, Deng, and Gage, "Resolving New Memories: A Critical Look at the Dentate Gyrus, Adult Neurogenesis, and Pattern Separation," in this issue of Neuron. Copyright © 2011 Elsevier Inc. All rights reserved.

Origin and Function of Tuning Diversity in Macaque Visual Cortex

PubMed Central

Goris, Robbe L.T.; Simoncelli, Eero P.; Movshon, J. Anthony

2016-01-01

SUMMARY Neurons in visual cortex vary in their orientation selectivity. We measured responses of V1 and V2 cells to orientation mixtures and fit them with a model whose stimulus selectivity arises from the combined effects of filtering, suppression, and response nonlinearity. The model explains the diversity of orientation selectivity with neuron-to-neuron variability in all three mechanisms, of which variability in the orientation bandwidth of linear filtering is the most important. The model also accounts for the cells’ diversity of spatial frequency selectivity. Tuning diversity is matched to the needs of visual encoding. The orientation content found in natural scenes is diverse, and neurons with different selectivities are adapted to different stimulus configurations. Single orientations are better encoded by highly selective neurons, while orientation mixtures are better encoded by less selective neurons. A diverse population of neurons therefore provides better overall discrimination capabilities for natural images than any homogeneous population. PMID:26549331

Spatially Compact Neural Clusters in the Dorsal Striatum Encode Locomotion Relevant Information.

PubMed

Barbera, Giovanni; Liang, Bo; Zhang, Lifeng; Gerfen, Charles R; Culurciello, Eugenio; Chen, Rong; Li, Yun; Lin, Da-Ting

2016-10-05

An influential striatal model postulates that neural activities in the striatal direct and indirect pathways promote and inhibit movement, respectively. Normal behavior requires coordinated activity in the direct pathway to facilitate intended locomotion and indirect pathway to inhibit unwanted locomotion. In this striatal model, neuronal population activity is assumed to encode locomotion relevant information. Here, we propose a novel encoding mechanism for the dorsal striatum. We identified spatially compact neural clusters in both the direct and indirect pathways. Detailed characterization revealed similar cluster organization between the direct and indirect pathways, and cluster activities from both pathways were correlated with mouse locomotion velocities. Using machine-learning algorithms, cluster activities could be used to decode locomotion relevant behavioral states and locomotion velocity. We propose that neural clusters in the dorsal striatum encode locomotion relevant information and that coordinated activities of direct and indirect pathway neural clusters are required for normal striatal controlled behavior. VIDEO ABSTRACT. Published by Elsevier Inc.

Divergent Routing of Positive and Negative Information from the Amygdala during Memory Retrieval.

PubMed

Beyeler, Anna; Namburi, Praneeth; Glober, Gordon F; Simonnet, Clémence; Calhoon, Gwendolyn G; Conyers, Garrett F; Luck, Robert; Wildes, Craig P; Tye, Kay M

2016-04-20

Although the basolateral amygdala (BLA) is known to play a critical role in the formation of memories of both positive and negative valence, the coding and routing of valence-related information is poorly understood. Here, we recorded BLA neurons during the retrieval of associative memories and used optogenetic-mediated phototagging to identify populations of neurons that synapse in the nucleus accumbens (NAc), the central amygdala (CeA), or ventral hippocampus (vHPC). We found that despite heterogeneous neural responses within each population, the proportions of BLA-NAc neurons excited by reward predictive cues and of BLA-CeA neurons excited by aversion predictive cues were higher than within the entire BLA. Although the BLA-vHPC projection is known to drive behaviors of innate negative valence, these neurons did not preferentially code for learned negative valence. Together, these findings suggest that valence encoding in the BLA is at least partially mediated via divergent activity of anatomically defined neural populations. Copyright © 2016 Elsevier Inc. All rights reserved.

Contextual fear conditioning depresses infralimbic excitability.

PubMed

Soler-Cedeño, Omar; Cruz, Emmanuel; Criado-Marrero, Marangelie; Porter, James T

2016-04-01

Patients with posttraumatic stress disorder (PTSD) show hypo-active ventromedial prefrontal cortices (vmPFC) that correlate with their impaired ability to discriminate between safe and dangerous contexts and cues. Previously, we found that auditory fear conditioning depresses the excitability of neurons populating the homologous structure in rodents, the infralimbic cortex (IL). However, it is undetermined if IL depression was mediated by the cued or contextual information. The objective of this study was to examine whether contextual information was sufficient to depress IL neuronal excitability. After exposing rats to context-alone, pseudoconditioning, or contextual fear conditioning, we used whole-cell current-clamp recordings to examine the excitability of IL neurons in prefrontal brain slices. We found that contextual fear conditioning reduced IL neuronal firing in response to depolarizing current steps. In addition, neurons from contextual fear conditioned animals showed increased slow afterhyperpolarization potentials (sAHPs). Moreover, the observed changes in IL excitability correlated with contextual fear expression, suggesting that IL depression may contribute to the encoding of contextual fear. Copyright © 2016 Elsevier Inc. All rights reserved.

Visual processing in the central bee brain.

PubMed

Paulk, Angelique C; Dacks, Andrew M; Phillips-Portillo, James; Fellous, Jean-Marc; Gronenberg, Wulfila

2009-08-12

Visual scenes comprise enormous amounts of information from which nervous systems extract behaviorally relevant cues. In most model systems, little is known about the transformation of visual information as it occurs along visual pathways. We examined how visual information is transformed physiologically as it is communicated from the eye to higher-order brain centers using bumblebees, which are known for their visual capabilities. We recorded intracellularly in vivo from 30 neurons in the central bumblebee brain (the lateral protocerebrum) and compared these neurons to 132 neurons from more distal areas along the visual pathway, namely the medulla and the lobula. In these three brain regions (medulla, lobula, and central brain), we examined correlations between the neurons' branching patterns and their responses primarily to color, but also to motion stimuli. Visual neurons projecting to the anterior central brain were generally color sensitive, while neurons projecting to the posterior central brain were predominantly motion sensitive. The temporal response properties differed significantly between these areas, with an increase in spike time precision across trials and a decrease in average reliable spiking as visual information processing progressed from the periphery to the central brain. These data suggest that neurons along the visual pathway to the central brain not only are segregated with regard to the physical features of the stimuli (e.g., color and motion), but also differ in the way they encode stimuli, possibly to allow for efficient parallel processing to occur.

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

Mirror neurons encode the subjective value of an observed action.

PubMed

Caggiano, Vittorio; Fogassi, Leonardo; Rizzolatti, Giacomo; Casile, Antonino; Giese, Martin A; Thier, Peter

2012-07-17

Objects grasped by an agent have a value not only for the acting agent, but also for an individual observing the grasping act. The value that the observer attributes to the object that is grasped can be pivotal for selecting a possible behavioral response. Mirror neurons in area F5 of the monkey premotor cortex have been suggested to play a crucial role in the understanding of action goals. However, it has not been addressed if these neurons are also involved in representing the value of the grasped object. Here we report that observation-related neuronal responses of F5 mirror neurons are indeed modulated by the value that the monkey associates with the grasped object. These findings suggest that during action observation F5 mirror neurons have access to key information needed to shape the behavioral responses of the observer.

Breadth of tuning in taste afferent neurons varies with stimulus strength

PubMed Central

Wu, An; Dvoryanchikov, Gennady; Pereira, Elizabeth; Chaudhari, Nirupa; Roper, Stephen D.

2015-01-01

Gustatory stimuli are detected by taste buds and transmitted to the hindbrain via sensory afferent neurons. Whether each taste quality (sweet, bitter and so on) is encoded by separate neurons (‘labelled lines') remains controversial. We used mice expressing GCaMP3 in geniculate ganglion sensory neurons to investigate taste-evoked activity. Using confocal calcium imaging, we recorded responses to oral stimulation with prototypic taste stimuli. Up to 69% of neurons respond to multiple tastants. Moreover, neurons tuned to a single taste quality at low concentration become more broadly tuned when stimuli are presented at higher concentration. Responses to sucrose and monosodium glutamate are most related. Although mice prefer dilute NaCl solutions and avoid concentrated NaCl, we found no evidence for two separate populations of sensory neurons that encode this distinction. Altogether, our data suggest that taste is encoded by activity in patterns of peripheral sensory neurons and challenge the notion of strict labelled line coding. PMID:26373451

Distinct neuronal coding schemes in memory revealed by selective erasure of fast synchronous synaptic transmission.

PubMed

Xu, Wei; Morishita, Wade; Buckmaster, Paul S; Pang, Zhiping P; Malenka, Robert C; Südhof, Thomas C

2012-03-08

Neurons encode information by firing spikes in isolation or bursts and propagate information by spike-triggered neurotransmitter release that initiates synaptic transmission. Isolated spikes trigger neurotransmitter release unreliably but with high temporal precision. In contrast, bursts of spikes trigger neurotransmission reliably (i.e., boost transmission fidelity), but the resulting synaptic responses are temporally imprecise. However, the relative physiological importance of different spike-firing modes remains unclear. Here, we show that knockdown of synaptotagmin-1, the major Ca(2+) sensor for neurotransmitter release, abrogated neurotransmission evoked by isolated spikes but only delayed, without abolishing, neurotransmission evoked by bursts of spikes. Nevertheless, knockdown of synaptotagmin-1 in the hippocampal CA1 region did not impede acquisition of recent contextual fear memories, although it did impair the precision of such memories. In contrast, knockdown of synaptotagmin-1 in the prefrontal cortex impaired all remote fear memories. These results indicate that different brain circuits and types of memory employ distinct spike-coding schemes to encode and transmit information. Copyright © 2012 Elsevier Inc. All rights reserved.

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.

Robust information propagation through noisy neural circuits

PubMed Central

Pouget, Alexandre

2017-01-01

Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these population responses, leading to insights about the role of covariability among neurons, tuning curve shape, etc. However, the informativeness of neural responses is not the only relevant feature of population codes; of potentially equal importance is how robustly that information propagates to downstream structures. For instance, to quantify the retina’s performance, one must consider not only the informativeness of the optic nerve responses, but also the amount of information that survives the spike-generating nonlinearity and noise corruption in the next stage of processing, the lateral geniculate nucleus. Our study identifies the set of covariance structures for the upstream cells that optimize the ability of information to propagate through noisy, nonlinear circuits. Within this optimal family are covariances with “differential correlations”, which are known to reduce the information encoded in neural population activities. Thus, covariance structures that maximize information in neural population codes, and those that maximize the ability of this information to propagate, can be very different. Moreover, redundancy is neither necessary nor sufficient to make population codes robust against corruption by noise: redundant codes can be very fragile, and synergistic codes can—in some cases—optimize robustness against noise. PMID:28419098

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.

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

Encoding of luminance and contrast by linear and nonlinear synapses in the retina.

PubMed

Odermatt, Benjamin; Nikolaev, Anton; Lagnado, Leon

2012-02-23

Understanding how neural circuits transmit information is technically challenging because the neural code is contained in the activity of large numbers of neurons and synapses. Here, we use genetically encoded reporters to image synaptic transmission across a population of sensory neurons-bipolar cells in the retina of live zebrafish. We demonstrate that the luminance sensitivities of these synapses varies over 10(4) with a log-normal distribution. About half the synapses made by ON and OFF cells alter their polarity of transmission as a function of luminance to generate a triphasic tuning curve with distinct maxima and minima. These nonlinear synapses signal temporal contrast with greater sensitivity than linear ones. Triphasic tuning curves increase the dynamic range over which bipolar cells signal light and improve the efficiency with which luminance information is transmitted. The most efficient synapses signaled luminance using just 1 synaptic vesicle per second per distinguishable gray level. Copyright © 2012 Elsevier Inc. All rights reserved.

A Topological Paradigm for Hippocampal Spatial Map Formation Using Persistent Homology

PubMed Central

Dabaghian, Y.; Mémoli, F.; Frank, L.; Carlsson, G.

2012-01-01

An animal's ability to navigate through space rests on its ability to create a mental map of its environment. The hippocampus is the brain region centrally responsible for such maps, and it has been assumed to encode geometric information (distances, angles). Given, however, that hippocampal output consists of patterns of spiking across many neurons, and downstream regions must be able to translate those patterns into accurate information about an animal's spatial environment, we hypothesized that 1) the temporal pattern of neuronal firing, particularly co-firing, is key to decoding spatial information, and 2) since co-firing implies spatial overlap of place fields, a map encoded by co-firing will be based on connectivity and adjacency, i.e., it will be a topological map. Here we test this topological hypothesis with a simple model of hippocampal activity, varying three parameters (firing rate, place field size, and number of neurons) in computer simulations of rat trajectories in three topologically and geometrically distinct test environments. Using a computational algorithm based on recently developed tools from Persistent Homology theory in the field of algebraic topology, we find that the patterns of neuronal co-firing can, in fact, convey topological information about the environment in a biologically realistic length of time. Furthermore, our simulations reveal a “learning region” that highlights the interplay between the parameters in combining to produce hippocampal states that are more or less adept at map formation. For example, within the learning region a lower number of neurons firing can be compensated by adjustments in firing rate or place field size, but beyond a certain point map formation begins to fail. We propose that this learning region provides a coherent theoretical lens through which to view conditions that impair spatial learning by altering place cell firing rates or spatial specificity. PMID:22912564

Simultaneous encoding of carotid sinus pressure and dP/dt by NTS target neurons of myelinated baroreceptors.

PubMed

Rogers, R F; Rose, W C; Schwaber, J S

1996-10-01

1. We seek to understand the baroreceptor signal processing that occurs centrally, beginning with the transformation of the signal at the first stage of processing. Because quantitative descriptions of the encoding of mean arterial pressure and its derivative with respect to time by baroreceptive second-order neurons have been unavailable, we characterized the responses of nucleus tractus solitarius (NTS) neurons that receive direct myelinated baroreceptor inputs to combinations of these two stimulus variables. 2. In anesthetized, paralyzed, artificially ventilated rabbits, the carotid sinus was vascularly isolated and the carotid sinus nerve was dissected free from surrounding tissue. Single-unit extracellular recordings were made from NTS neurons that received direct (with the use of physiological criteria) synaptic inputs from carotid sinus baroreceptors with myelinated axons. The vast majority of these neurons did not receive ipsilateral aortic nerve convergent inputs. With the use of a computer-controlled linear motor, a piecewise linear pressure waveform containing 32 combinations of pressure and its rate of change with respect to time (dP/dt) was delivered to the ipsilateral carotid sinus. 3. The average NTS firing frequency during the different stimulus combinations of pressure and dP/dt was a nonlinear and interdependent function of both variables. Most notable was the "extinctive" encoding of carotid sinus pressure by these neurons. This was characterized by an increase in firing frequency going from low to medium mean pressures (analyzed at certain positive dP/dt values) followed by a decrease in activity during high-pressure stimuli. All second-order neurons analyzed had their maximal firing rates when dP/dt was positive. 4. All neurons had their maximal firing frequency locations ("receptive field centers") at just 3 of 32 possible pressure-dP/dt coordinates. The responses of a small population of neurons were used to generate a composite description of the encoding of pressure and dP/dt. When combined as a composite of individually normalized values, the encoding of carotid sinus pressure and dP/dt may be approximated with the use of two-dimensional Gaussian functions. 5. We conclude that the population of NTS neurons recorded most faithfully encodes the rate and direction of (mean) pressure change, as opposed to providing the CNS with an unambiguous encoding of absolute pressure. Instead, the activity of these neurons, individually or as a population, serves as an estimate for the first derivative of the myelinated baroreceptor signal's encoding of mean pressure. We therefore speculate that the output of these individual neurons is useful in dynamic, rather than static, arterial pressure control.

Spatiotemporal encoding of search strategies by prefrontal neurons.

PubMed

Chiang, Feng-Kuei; Wallis, Joni D

2018-05-08

Working memory is capacity-limited. In everyday life we rarely notice this limitation, in part because we develop behavioral strategies that help mitigate the capacity limitation. How behavioral strategies are mediated at the neural level is unclear, but a likely locus is lateral prefrontal cortex (LPFC). Neurons in LPFC play a prominent role in working memory and have been shown to encode behavioral strategies. To examine the role of LPFC in overcoming working-memory limitations, we recorded the activity of LPFC neurons in animals trained to perform a serial self-ordered search task. This task measured the ability to prospectively plan the selection of unchosen spatial search targets while retrospectively tracking which targets were previously visited. We found that individual LPFC neurons encoded the spatial location of the current search target but also encoded the spatial location of targets up to several steps away in the search sequence. Neurons were more likely to encode prospective than retrospective targets. When subjects used a behavioral strategy of stereotyped target selection, mitigating the working-memory requirements of the task, not only did the number of selection errors decrease but there was a significant reduction in the strength of spatial encoding in LFPC. These results show that LPFC neurons have spatiotemporal mnemonic fields, in that their firing rates are modulated both by the spatial location of future selection behaviors and the temporal organization of that behavior. Furthermore, the strength of this tuning can be dynamically modulated by the demands of the task.

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

Determination of relevant neuron-neuron connections for neural prosthetics using time-delayed mutual information: tutorial and preliminary results.

PubMed

Taghva, Alexander; Song, Dong; Hampson, Robert E; Deadwyler, Sam A; Berger, Theodore W

2012-12-01

Identification of functional dependence among neurons is a necessary component in both the rational design of neural prostheses as well as in the characterization of network physiology. The objective of this article is to provide a tutorial for neurosurgeons regarding information theory, specifically time-delayed mutual information, and to compare time-delayed mutual information, an information theoretic quantity based on statistical dependence, with cross-correlation, a commonly used metric for this task in a preliminary analysis of rat hippocampal neurons. Spike trains were recorded from rats performing delayed nonmatch-to-sample task using an array of electrodes surgically implanted into the hippocampus of each hemisphere of the brain. In addition, spike train simulations of positively correlated neurons, negatively correlated neurons, and neurons correlated by nonlinear functions were generated. These were evaluated by time-delayed mutual information (MI) and cross-correlation. Application of time-delayed MI to experimental data indicated the optimal bin size for information capture in the CA3-CA1 system was 40 ms, which may provide some insight into the spatiotemporal nature of encoding in the rat hippocampus. On simulated data, time-delayed MI showed peak values at appropriate time lags in positively correlated, negatively correlated, and complexly correlated data. Cross-correlation showed peak and troughs with positively correlated and negatively correlated data, but failed to capture some higher order correlations. Comparison of time-delayed MI to cross-correlation in identification of functionally dependent neurons indicates that the methods are not equivalent. Time-delayed MI appeared to capture some interactions between CA3-CA1 neurons at physiologically plausible time delays missed by cross-correlation. It should be considered as a method for identification of functional dependence between neurons and may be useful in the development of neural prosthetics. Copyright © 2012 Elsevier Inc. All rights reserved.

Functional territories in primate substantia nigra pars reticulata separately signaling stable and flexible values

PubMed Central

Hikosaka, Okihide

2014-01-01

Gaze is strongly attracted to visual objects that have been associated with rewards. Key to this function is a basal ganglia circuit originating from the caudate nucleus (CD), mediated by the substantia nigra pars reticulata (SNr), and aiming at the superior colliculus (SC). Notably, subregions of CD encode values of visual objects differently: stably by CD tail [CD(T)] vs. flexibly by CD head [CD(H)]. Are the stable and flexible value signals processed separately throughout the CD-SNr-SC circuit? To answer this question, we identified SNr neurons by their inputs from CD and outputs to SC and examined their sensitivity to object values. The direct input from CD was identified by SNr neuron's inhibitory response to electrical stimulation of CD. We found that SNr neurons were separated into two groups: 1) neurons inhibited by CD(T) stimulation, located in the caudal-dorsal-lateral SNr (cdlSNr), and 2) neurons inhibited by CD(H) stimulation, located in the rostral-ventral-medial SNr (rvmSNr). Most of CD(T)-recipient SNr neurons encoded stable values, whereas CD(H)-recipient SNr neurons tended to encode flexible values. The output to SC was identified by SNr neuron's antidromic response to SC stimulation. Among the antidromically activated neurons, many encoded only stable values, while some encoded only flexible values. These results suggest that CD(T)-cdlSNr-SC circuit and CD(H)-rvmSNr-SC circuit transmit stable and flexible value signals, largely separately, to SC. The speed of signal transmission was faster through CD(T)-cdlSNr-SC circuit than through CD(H)-rvmSNr-SC circuit, which may reflect automatic and controlled gaze orienting guided by these circuits. PMID:25540224

Neuronal representation of individual heroin choices in the orbitofrontal cortex.

PubMed

Guillem, Karine; Brenot, Viridiana; Durand, Audrey; Ahmed, Serge H

2018-05-01

Drug addiction is a harmful preference for drug use over and at the expense of other non-drug-related activities. We previously identified in the rat orbitofrontal cortex (OFC) a mechanism that influences individual preferences between cocaine use and an alternative action rewarded by a non-drug reward (i.e. sweet water). Here, we sought to test the generality of this mechanism to a different addictive drug, heroin. OFC neuronal activity was recorded while rats responded for heroin or the alternative non-drug reward separately or while they chose between the two. First, we found that heroin-rewarded and sweet water-rewarded actions were encoded by two non-overlapping OFC neuronal populations and that the relative size of the heroin population represented individual drug choices. Second, OFC neurons encoding the preferred action-which was the non-drug action in the large majority of individuals-progressively fired more than non-preferred action-coding neurons 1 second after the onset of choice trials and around 1 second before the preferred action was actually chosen, suggesting a pre-choice neuronal competition for action selection. Together with a previous study on cocaine choice, the present study on heroin choice reveals important commonalities in how OFC neurons encode individual drug choices and preferences across different classes of drugs. It also reveals some drug-specific differences in OFC encoding activity. Notably, the proportion of neurons that non-selectively encode both the drug and the non-drug reward was higher when the drug was heroin (present study) than when it was cocaine (previous study). We will discuss the potential functional significance of these commonalities and differences in OFC neuronal activity across different drugs for understanding drug choice. © 2017 Society for the Study of Addiction.

Vocalization frequency and duration are coded in separate hindbrain nuclei.

PubMed

Chagnaud, Boris P; Baker, Robert; Bass, Andrew H

2011-06-14

Temporal patterning is an essential feature of neural networks producing precisely timed behaviours such as vocalizations that are widely used in vertebrate social communication. Here we show that intrinsic and network properties of separate hindbrain neuronal populations encode the natural call attributes of frequency and duration in vocal fish. Intracellular structure/function analyses indicate that call duration is encoded by a sustained membrane depolarization in vocal prepacemaker neurons that innervate downstream pacemaker neurons. Pacemaker neurons, in turn, encode call frequency by rhythmic, ultrafast oscillations in their membrane potential. Pharmacological manipulations show prepacemaker activity to be independent of pacemaker function, thus accounting for natural variation in duration which is the predominant feature distinguishing call types. Prepacemaker neurons also innervate key hindbrain auditory nuclei thereby effectively serving as a call-duration corollary discharge. We propose that premotor compartmentalization of neurons coding distinct acoustic attributes is a fundamental trait of hindbrain vocal pattern generators among vertebrates.

Vocalization frequency and duration are coded in separate hindbrain nuclei

PubMed Central

Chagnaud, Boris P.; Baker, Robert; Bass, Andrew H.

2011-01-01

Temporal patterning is an essential feature of neural networks producing precisely timed behaviours such as vocalizations that are widely used in vertebrate social communication. Here we show that intrinsic and network properties of separate hindbrain neuronal populations encode the natural call attributes of frequency and duration in vocal fish. Intracellular structure/function analyses indicate that call duration is encoded by a sustained membrane depolarization in vocal prepacemaker neurons that innervate downstream pacemaker neurons. Pacemaker neurons, in turn, encode call frequency by rhythmic, ultrafast oscillations in their membrane potential. Pharmacological manipulations show prepacemaker activity to be independent of pacemaker function, thus accounting for natural variation in duration which is the predominant feature distinguishing call types. Prepacemaker neurons also innervate key hindbrain auditory nuclei thereby effectively serving as a call-duration corollary discharge. We propose that premotor compartmentalization of neurons coding distinct acoustic attributes is a fundamental trait of hindbrain vocal pattern generators among vertebrates. PMID:21673667

A new supervised learning algorithm for spiking neurons.

PubMed

Xu, Yan; Zeng, Xiaoqin; Zhong, Shuiming

2013-06-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by the precise firing times of spikes. If only running time is considered, the supervised learning for a spiking neuron is equivalent to distinguishing the times of desired output spikes and the other time during the running process of the neuron through adjusting synaptic weights, which can be regarded as a classification problem. Based on this idea, this letter proposes a new supervised learning method for spiking neurons with temporal encoding; it first transforms the supervised learning into a classification problem and then solves the problem by using the perceptron learning rule. The experiment results show that the proposed method has higher learning accuracy and efficiency over the existing learning methods, so it is more powerful for solving complex and real-time problems.

Weak signal amplification and detection by higher-order sensory neurons

PubMed Central

Longtin, Andre; Maler, Leonard

2016-01-01

Sensory systems must extract behaviorally relevant information and therefore often exhibit a very high sensitivity. How the nervous system reaches such high sensitivity levels is an outstanding question in neuroscience. Weakly electric fish (Apteronotus leptorhynchus/albifrons) are an excellent model system to address this question because detailed background knowledge is available regarding their behavioral performance and its underlying neuronal substrate. Apteronotus use their electrosense to detect prey objects. Therefore, they must be able to detect electrical signals as low as 1 μV while using a sensory integration time of <200 ms. How these very weak signals are extracted and amplified by the nervous system is not yet understood. We studied the responses of cells in the early sensory processing areas, namely, the electroreceptor afferents (EAs) and pyramidal cells (PCs) of the electrosensory lobe (ELL), the first-order electrosensory processing area. In agreement with previous work we found that EAs cannot encode very weak signals with a spike count code. However, PCs can encode prey mimic signals by their firing rate, revealing a huge signal amplification between EAs and PCs and also suggesting differences in their stimulus encoding properties. Using a simple leaky integrate-and-fire (LIF) model we predict that the target neurons of PCs in the midbrain torus semicircularis (TS) are able to detect very weak signals. In particular, TS neurons could do so by assuming biologically plausible convergence rates as well as very simple decoding strategies such as temporal integration, threshold crossing, and combining the inputs of PCs. PMID:26843601

Prefrontal neurons encode context-based response execution and inhibition in reward seeking and extinction

PubMed Central

Moorman, David E.; Aston-Jones, Gary

2015-01-01

The prefrontal cortex (PFC) guides execution and inhibition of behavior based on contextual demands. In rodents, the dorsal/prelimbic (PL) medial PFC (mPFC) is frequently considered essential for execution of goal-directed behavior (“go”) whereas ventral/infralimbic (IL) mPFC is thought to control behavioral suppression (“stop”). This dichotomy is commonly seen for fear-related behaviors, and for some behaviors related to cocaine seeking. Overall, however, data for reward-directed behaviors are ambiguous, and few recordings of PL/IL activity have been performed to demonstrate single-neuron correlates. We recorded neuronal activity in PL and IL during discriminative stimulus driven sucrose seeking followed by multiple days of extinction of the reward-predicting stimulus. Contrary to a generalized PL-go/IL-stop hypothesis, we found cue-evoked activity in PL and IL during reward seeking and extinction. Upon analyzing this activity based on resultant behavior (lever press or withhold), we found that neurons in both areas encoded contextually appropriate behavioral initiation (during reward seeking) and withholding (during extinction), where context was dictated by response–outcome contingencies. Our results demonstrate that PL and IL signal contextual information for regulation of behavior, irrespective of whether that involves initiation or suppression of behavioral responses, rather than topographically encoding go vs. stop behaviors. The use of context to optimize behavior likely plays an important role in maximizing utility-promoting exertion of activity when behaviors are rewarded and conservation of energy when not. PMID:26170333

Efficient Training of Supervised Spiking Neural Network via Accurate Synaptic-Efficiency Adjustment Method.

PubMed

Xie, Xiurui; Qu, Hong; Yi, Zhang; Kurths, Jurgen

2017-06-01

The spiking neural network (SNN) is the third generation of neural networks and performs remarkably well in cognitive tasks, such as pattern recognition. The temporal neural encode mechanism found in biological hippocampus enables SNN to possess more powerful computation capability than networks with other encoding schemes. However, this temporal encoding approach requires neurons to process information serially on time, which reduces learning efficiency significantly. To keep the powerful computation capability of the temporal encoding mechanism and to overcome its low efficiency in the training of SNNs, a new training algorithm, the accurate synaptic-efficiency adjustment method is proposed in this paper. Inspired by the selective attention mechanism of the primate visual system, our algorithm selects only the target spike time as attention areas, and ignores voltage states of the untarget ones, resulting in a significant reduction of training time. Besides, our algorithm employs a cost function based on the voltage difference between the potential of the output neuron and the firing threshold of the SNN, instead of the traditional precise firing time distance. A normalized spike-timing-dependent-plasticity learning window is applied to assigning this error to different synapses for instructing their training. Comprehensive simulations are conducted to investigate the learning properties of our algorithm, with input neurons emitting both single spike and multiple spikes. Simulation results indicate that our algorithm possesses higher learning performance than the existing other methods and achieves the state-of-the-art efficiency in the training of SNN.

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

Visual Attention Model Based on Statistical Properties of Neuron Responses

PubMed Central

Duan, Haibin; Wang, Xiaohua

2015-01-01

Visual attention is a mechanism of the visual system that can select relevant objects from a specific scene. Interactions among neurons in multiple cortical areas are considered to be involved in attentional allocation. However, the characteristics of the encoded features and neuron responses in those attention related cortices are indefinite. Therefore, further investigations carried out in this study aim at demonstrating that unusual regions arousing more attention generally cause particular neuron responses. We suppose that visual saliency is obtained on the basis of neuron responses to contexts in natural scenes. A bottom-up visual attention model is proposed based on the self-information of neuron responses to test and verify the hypothesis. Four different color spaces are adopted and a novel entropy-based combination scheme is designed to make full use of color information. Valuable regions are highlighted while redundant backgrounds are suppressed in the saliency maps obtained by the proposed model. Comparative results reveal that the proposed model outperforms several state-of-the-art models. This study provides insights into the neuron responses based saliency detection and may underlie the neural mechanism of early visual cortices for bottom-up visual attention. PMID:25747859

Origin and Function of Tuning Diversity in Macaque Visual Cortex.

PubMed

Goris, Robbe L T; Simoncelli, Eero P; Movshon, J Anthony

2015-11-18

Neurons in visual cortex vary in their orientation selectivity. We measured responses of V1 and V2 cells to orientation mixtures and fit them with a model whose stimulus selectivity arises from the combined effects of filtering, suppression, and response nonlinearity. The model explains the diversity of orientation selectivity with neuron-to-neuron variability in all three mechanisms, of which variability in the orientation bandwidth of linear filtering is the most important. The model also accounts for the cells' diversity of spatial frequency selectivity. Tuning diversity is matched to the needs of visual encoding. The orientation content found in natural scenes is diverse, and neurons with different selectivities are adapted to different stimulus configurations. Single orientations are better encoded by highly selective neurons, while orientation mixtures are better encoded by less selective neurons. A diverse population of neurons therefore provides better overall discrimination capabilities for natural images than any homogeneous population. Copyright © 2015 Elsevier Inc. All rights reserved.

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

A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

PubMed

Guo, Lilin; Wang, Zhenzhong; Cabrerizo, Mercedes; Adjouadi, Malek

2017-05-01

This study introduces a novel learning algorithm for spiking neurons, called CCDS, which is able to learn and reproduce arbitrary spike patterns in a supervised fashion allowing the processing of spatiotemporal information encoded in the precise timing of spikes. Unlike the Remote Supervised Method (ReSuMe), synapse delays and axonal delays in CCDS are variants which are modulated together with weights during learning. The CCDS rule is both biologically plausible and computationally efficient. The properties of this learning rule are investigated extensively through experimental evaluations in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and classification performance. Results presented show that the CCDS learning method achieves learning accuracy and learning speed comparable with ReSuMe, but improves classification accuracy when compared to both the Spike Pattern Association Neuron (SPAN) learning rule and the Tempotron learning rule. The merit of CCDS rule is further validated on a practical example involving the automated detection of interictal spikes in EEG records of patients with epilepsy. Results again show that with proper encoding, the CCDS rule achieves good recognition performance.

Intrinsic Neuronal Properties Switch the Mode of Information Transmission in Networks

PubMed Central

Gjorgjieva, Julijana; Mease, Rebecca A.; Moody, William J.; Fairhall, Adrienne L.

2014-01-01

Diverse ion channels and their dynamics endow single neurons with complex biophysical properties. These properties determine the heterogeneity of cell types that make up the brain, as constituents of neural circuits tuned to perform highly specific computations. How do biophysical properties of single neurons impact network function? We study a set of biophysical properties that emerge in cortical neurons during the first week of development, eventually allowing these neurons to adaptively scale the gain of their response to the amplitude of the fluctuations they encounter. During the same time period, these same neurons participate in large-scale waves of spontaneously generated electrical activity. We investigate the potential role of experimentally observed changes in intrinsic neuronal properties in determining the ability of cortical networks to propagate waves of activity. We show that such changes can strongly affect the ability of multi-layered feedforward networks to represent and transmit information on multiple timescales. With properties modeled on those observed at early stages of development, neurons are relatively insensitive to rapid fluctuations and tend to fire synchronously in response to wave-like events of large amplitude. Following developmental changes in voltage-dependent conductances, these same neurons become efficient encoders of fast input fluctuations over few layers, but lose the ability to transmit slower, population-wide input variations across many layers. Depending on the neurons' intrinsic properties, noise plays different roles in modulating neuronal input-output curves, which can dramatically impact network transmission. The developmental change in intrinsic properties supports a transformation of a networks function from the propagation of network-wide information to one in which computations are scaled to local activity. This work underscores the significance of simple changes in conductance parameters in governing how neurons represent and propagate information, and suggests a role for background synaptic noise in switching the mode of information transmission. PMID:25474701

Mirror neurons encode the subjective value of an observed action

PubMed Central

Caggiano, Vittorio; Fogassi, Leonardo; Rizzolatti, Giacomo; Casile, Antonino; Giese, Martin A.; Thier, Peter

2012-01-01

Objects grasped by an agent have a value not only for the acting agent, but also for an individual observing the grasping act. The value that the observer attributes to the object that is grasped can be pivotal for selecting a possible behavioral response. Mirror neurons in area F5 of the monkey premotor cortex have been suggested to play a crucial role in the understanding of action goals. However, it has not been addressed if these neurons are also involved in representing the value of the grasped object. Here we report that observation-related neuronal responses of F5 mirror neurons are indeed modulated by the value that the monkey associates with the grasped object. These findings suggest that during action observation F5 mirror neurons have access to key information needed to shape the behavioral responses of the observer. PMID:22753471

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.

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.

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.

Persistent spatial information in the frontal eye field during object-based short-term memory.

PubMed

Clark, Kelsey L; Noudoost, Behrad; Moore, Tirin

2012-08-08

Spatial attention is known to gate entry into visual short-term memory, and some evidence suggests that spatial signals may also play a role in binding features or protecting object representations during memory maintenance. To examine the persistence of spatial signals during object short-term memory, the activity of neurons in the frontal eye field (FEF) of macaque monkeys was recorded during an object-based delayed match-to-sample task. In this task, monkeys were trained to remember an object image over a brief delay, regardless of the locations of the sample or target presentation. FEF neurons exhibited visual, delay, and target period activity, including selectivity for sample location and target location. Delay period activity represented the sample location throughout the delay, despite the irrelevance of spatial information for successful task completion. Furthermore, neurons continued to encode sample position in a variant of the task in which the matching stimulus never appeared in their response field, confirming that FEF maintains sample location independent of subsequent behavioral relevance. FEF neurons also exhibited target-position-dependent anticipatory activity immediately before target onset, suggesting that monkeys predicted target position within blocks. These results show that FEF neurons maintain spatial information during short-term memory, even when that information is irrelevant for task performance.

Vestibular convergence patterns in vestibular nuclei neurons of alert primates

NASA Technical Reports Server (NTRS)

Dickman, J. David; Angelaki, Dora E.

2002-01-01

Sensory signal convergence is a fundamental and important aspect of brain function. Such convergence may often involve complex multidimensional interactions as those proposed for the processing of otolith and semicircular canal (SCC) information for the detection of translational head movements and the effective discrimination from physically congruent gravity signals. In the present study, we have examined the responses of primate rostral vestibular nuclei (VN) neurons that do not exhibit any eye movement-related activity using 0.5-Hz translational and three-dimensional (3D) rotational motion. Three distinct neural populations were identified. Approximately one-fourth of the cells exclusively encoded rotational movements (canal-only neurons) and were unresponsive to translation. The canal-only central neurons encoded head rotation in SCC coordinates, exhibited little orthogonal canal convergence, and were characterized with significantly higher sensitivities to rotation as compared to primary SCC afferents. Another fourth of the neurons modulated their firing rates during translation (otolith-only cells). During rotations, these neurons only responded when the axis of rotation was earth-horizontal and the head was changing orientation relative to gravity. The remaining one-half of VN neurons were sensitive to both rotations and translations (otolith + canal neurons). Unlike primary otolith afferents, however, central neurons often exhibited significant spatiotemporal (noncosine) tuning properties and a wide variety of response dynamics to translation. To characterize the pattern of SCC inputs to otolith + canal neurons, their rotational maximum sensitivity vectors were computed using exclusively responses during earth-vertical axis rotations (EVA). Maximum sensitivity vectors were distributed throughout the 3D space, suggesting strong convergence from multiple SCCs. These neurons were also tested with earth-horizontal axis rotations (EHA), which would activate both vertical canals and otolith organs. However, the recorded responses could not be predicted from a linear combination of EVA rotational and translational responses. In contrast, one-third of the neurons responded similarly during EVA and EHA rotations, although a significant response modulation was present during translation. Thus this subpopulation of otolith + canal cells, which included neurons with either high- or low-pass dynamics to translation, appear to selectively ignore the component of otolith-selective activation that is due to changes in the orientation of the head relative to gravity. Thus contrary to primary otolith afferents and otolith-only central neurons that respond equivalently to tilts relative to gravity and translational movements, approximately one-third of the otolith + canal cells seem to encode a true estimate of the translational component of the imposed passive head and body movement.

Toward functional classification of neuronal types.

PubMed

Sharpee, Tatyana O

2014-09-17

How many types of neurons are there in the brain? This basic neuroscience question remains unsettled despite many decades of research. Classification schemes have been proposed based on anatomical, electrophysiological, or molecular properties. However, different schemes do not always agree with each other. This raises the question of whether one can classify neurons based on their function directly. For example, among sensory neurons, can a classification scheme be devised that is based on their role in encoding sensory stimuli? Here, theoretical arguments are outlined for how this can be achieved using information theory by looking at optimal numbers of cell types and paying attention to two key properties: correlations between inputs and noise in neural responses. This theoretical framework could help to map the hierarchical tree relating different neuronal classes within and across species. Copyright © 2014 Elsevier Inc. All rights reserved.

Restoring the encoding properties of a stochastic neuron model by an exogenous noise

PubMed Central

Paffi, Alessandra; Camera, Francesca; Apollonio, Francesca; d'Inzeo, Guglielmo; Liberti, Micaela

2015-01-01

Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR) phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed. PMID:25999845

Determination of Relevant Neuron–Neuron Connections for Neural Prosthetics Using Time-Delayed Mutual Information: Tutorial and Preliminary Results

PubMed Central

Taghva, Alexander; Song, Dong; Hampson, Robert E.; Deadwyler, Sam A.; Berger, Theodore W.

2013-01-01

BACKGROUND Identification of functional dependence among neurons is a necessary component in both the rational design of neural prostheses as well as in the characterization of network physiology. The objective of this article is to provide a tutorial for neurosurgeons regarding information theory, specifically time-delayed mutual information, and to compare time-delayed mutual information, an information theoretic quantity based on statistical dependence, with cross-correlation, a commonly used metric for this task in a preliminary analysis of rat hippocampal neurons. METHODS Spike trains were recorded from rats performing delayed nonmatch-to-sample task using an array of electrodes surgically implanted into the hippocampus of each hemisphere of the brain. In addition, spike train simulations of positively correlated neurons, negatively correlated neurons, and neurons correlated by nonlinear functions were generated. These were evaluated by time-delayed mutual information (MI) and cross-correlation. RESULTS Application of time-delayed MI to experimental data indicated the optimal bin size for information capture in the CA3-CA1 system was 40 ms, which may provide some insight into the spatiotemporal nature of encoding in the rat hippocampus. On simulated data, time-delayed MI showed peak values at appropriate time lags in positively correlated, negatively correlated, and complexly correlated data. Cross-correlation showed peak and troughs with positively correlated and negatively correlated data, but failed to capture some higher order correlations. CONCLUSIONS Comparison of time-delayed MI to cross-correlation in identification of functionally dependent neurons indicates that the methods are not equivalent. Time-delayed MI appeared to capture some interactions between CA3-CA1 neurons at physiologically plausible time delays missed by cross-correlation. It should be considered as a method for identification of functional dependence between neurons and may be useful in the development of neural prosthetics. PMID:22120279

Towards biological plausibility of electronic noses: A spiking neural network based approach for tea odour classification.

PubMed

Sarkar, Sankho Turjo; Bhondekar, Amol P; Macaš, Martin; Kumar, Ritesh; Kaur, Rishemjit; Sharma, Anupma; Gulati, Ashu; Kumar, Amod

2015-11-01

The paper presents a novel encoding scheme for neuronal code generation for odour recognition using an electronic nose (EN). This scheme is based on channel encoding using multiple Gaussian receptive fields superimposed over the temporal EN responses. The encoded data is further applied to a spiking neural network (SNN) for pattern classification. Two forms of SNN, a back-propagation based SpikeProp and a dynamic evolving SNN are used to learn the encoded responses. The effects of information encoding on the performance of SNNs have been investigated. Statistical tests have been performed to determine the contribution of the SNN and the encoding scheme to overall odour discrimination. The approach has been implemented in odour classification of orthodox black tea (Kangra-Himachal Pradesh Region) thereby demonstrating a biomimetic approach for EN data analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cerebellar granule cells encode the expectation of reward

PubMed Central

Wagner, Mark J; Kim, Tony Hyun; Savall, Joan; Schnitzer, Mark J; Luo, Liqun

2017-01-01

The human brain contains ~60 billion cerebellar granule cells1, which outnumber all other neurons combined. Classical theories posit that a large, diverse population of granule cells allows for highly detailed representations of sensorimotor context, enabling downstream Purkinje cells to sense fine contextual changes2–6. Although evidence suggests a role for cerebellum in cognition7–10, granule cells are known to encode only sensory11–13 and motor14 context. Using two-photon calcium imaging in behaving mice, here we show that granule cells convey information about the expectation of reward. Mice initiated voluntary forelimb movements for delayed water reward. Some granule cells responded preferentially to reward or reward omission, whereas others selectively encoded reward anticipation. Reward responses were not restricted to forelimb movement, as a Pavlovian task evoked similar responses. Compared to predictable rewards, unexpected rewards elicited markedly different granule cell activity despite identical stimuli and licking responses. In both tasks, reward signals were widespread throughout multiple cerebellar lobules. Tracking the same granule cells over several days of learning revealed that cells with reward-anticipating responses emerged from those that responded at the start of learning to reward delivery, whereas reward omission responses grew stronger as learning progressed. The discovery of predictive, non-sensorimotor encoding in granule cells is a major departure from current understanding of these neurons and dramatically enriches contextual information available to postsynaptic Purkinje cells, with important implications for cognitive processing in the cerebellum. PMID:28321129

Stimulus information stored in lasting active and hidden network states is destroyed by network bursts

PubMed Central

Dranias, Mark R.; Westover, M. Brandon; Cash, Sidney; VanDongen, Antonius M. J.

2015-01-01

In both humans and animals brief synchronizing bursts of epileptiform activity known as interictal epileptiform discharges (IEDs) can, even in the absence of overt seizures, cause transient cognitive impairments (TCI) that include problems with perception or short-term memory. While no evidence from single units is available, it has been assumed that IEDs destroy information represented in neuronal networks. Cultured neuronal networks are a model for generic cortical microcircuits, and their spontaneous activity is characterized by the presence of synchronized network bursts (SNBs), which share a number of properties with IEDs, including the high degree of synchronization and their spontaneous occurrence in the absence of an external stimulus. As a model approach to understanding the processes underlying IEDs, optogenetic stimulation and multielectrode array (MEA) recordings of cultured neuronal networks were used to study whether stimulus information represented in these networks survives SNBs. When such networks are optically stimulated they encode and maintain stimulus information for as long as one second. Experiments involved recording the network response to a single stimulus and trials where two different stimuli were presented sequentially, akin to a paired pulse trial. We broke the sequential stimulus trials into encoding, delay and readout phases and found that regardless of which phase the SNB occurs, stimulus-specific information was impaired. SNBs were observed to increase the mean network firing rate, but this did not translate monotonically into increases in network entropy. It was found that the more excitable a network, the more stereotyped its response was during a network burst. These measurements speak to whether SNBs are capable of transmitting information in addition to blocking it. These results are consistent with previous reports and provide baseline predictions concerning the neural mechanisms by which IEDs might cause TCI. PMID:25755638

In monkeys making value-based decisions, amygdala neurons are sensitive to cue value as distinct from cue salience.

PubMed

Leathers, Marvin L; Olson, Carl R

2017-04-01

Neurons in the lateral intraparietal (LIP) area of macaque monkey parietal cortex respond to cues predicting rewards and penalties of variable size in a manner that depends on the motivational salience of the predicted outcome (strong for both large reward and large penalty) rather than on its value (positive for large reward and negative for large penalty). This finding suggests that LIP mediates the capture of attention by salient events and does not encode value in the service of value-based decision making. It leaves open the question whether neurons elsewhere in the brain encode value in the identical task. To resolve this issue, we recorded neuronal activity in the amygdala in the context of the task employed in the LIP study. We found that responses to reward-predicting cues were similar between areas, with the majority of reward-sensitive neurons responding more strongly to cues that predicted large reward than to those that predicted small reward. Responses to penalty-predicting cues were, however, markedly different. In the amygdala, unlike LIP, few neurons were sensitive to penalty size, few penalty-sensitive neurons favored large over small penalty, and the dependence of firing rate on penalty size was negatively correlated with its dependence on reward size. These results indicate that amygdala neurons encoded cue value under circumstances in which LIP neurons exhibited sensitivity to motivational salience. However, the representation of negative value, as reflected in sensitivity to penalty size, was weaker than the representation of positive value, as reflected in sensitivity to reward size. NEW & NOTEWORTHY This is the first study to characterize amygdala neuronal responses to cues predicting rewards and penalties of variable size in monkeys making value-based choices. Manipulating reward and penalty size allowed distinguishing activity dependent on motivational salience from activity dependent on value. This approach revealed in a previous study that neurons of the lateral intraparietal (LIP) area encode motivational salience. Here, it reveals that amygdala neurons encode value. The results establish a sharp functional distinction between the two areas. Copyright © 2017 the American Physiological Society.

Origin of information-limiting noise correlations

PubMed Central

Kanitscheider, Ingmar; Coen-Cagli, Ruben; Pouget, Alexandre

2015-01-01

The ability to discriminate between similar sensory stimuli relies on the amount of information encoded in sensory neuronal populations. Such information can be substantially reduced by correlated trial-to-trial variability. Noise correlations have been measured across a wide range of areas in the brain, but their origin is still far from clear. Here we show analytically and with simulations that optimal computation on inputs with limited information creates patterns of noise correlations that account for a broad range of experimental observations while at same time causing information to saturate in large neural populations. With the example of a network of V1 neurons extracting orientation from a noisy image, we illustrate to our knowledge the first generative model of noise correlations that is consistent both with neurophysiology and with behavioral thresholds, without invoking suboptimal encoding or decoding or internal sources of variability such as stochastic network dynamics or cortical state fluctuations. We further show that when information is limited at the input, both suboptimal connectivity and internal fluctuations could similarly reduce the asymptotic information, but they have qualitatively different effects on correlations leading to specific experimental predictions. Our study indicates that noise at the sensory periphery could have a major effect on cortical representations in widely studied discrimination tasks. It also provides an analytical framework to understand the functional relevance of different sources of experimentally measured correlations. PMID:26621747

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.

Regression-Based Identification of Behavior-Encoding Neurons During Large-Scale Optical Imaging of Neural Activity at Cellular Resolution

PubMed Central

Miri, Andrew; Daie, Kayvon; Burdine, Rebecca D.; Aksay, Emre

2011-01-01

The advent of methods for optical imaging of large-scale neural activity at cellular resolution in behaving animals presents the problem of identifying behavior-encoding cells within the resulting image time series. Rapid and precise identification of cells with particular neural encoding would facilitate targeted activity measurements and perturbations useful in characterizing the operating principles of neural circuits. Here we report a regression-based approach to semiautomatically identify neurons that is based on the correlation of fluorescence time series with quantitative measurements of behavior. The approach is illustrated with a novel preparation allowing synchronous eye tracking and two-photon laser scanning fluorescence imaging of calcium changes in populations of hindbrain neurons during spontaneous eye movement in the larval zebrafish. Putative velocity-to-position oculomotor integrator neurons were identified that showed a broad spatial distribution and diversity of encoding. Optical identification of integrator neurons was confirmed with targeted loose-patch electrical recording and laser ablation. The general regression-based approach we demonstrate should be widely applicable to calcium imaging time series in behaving animals. PMID:21084686

From rule to response: neuronal processes in the premotor and prefrontal cortex.

PubMed

Wallis, Jonathan D; Miller, Earl K

2003-09-01

The ability to use abstract rules or principles allows behavior to generalize from specific circumstances (e.g., rules learned in a specific restaurant can subsequently be applied to any dining experience). Neurons in the prefrontal cortex (PFC) encode such rules. However, to guide behavior, rules must be linked to motor responses. We investigated the neuronal mechanisms underlying this process by recording from the PFC and the premotor cortex (PMC) of monkeys trained to use two abstract rules: "same" or "different." The monkeys had to either hold or release a lever, depending on whether two successively presented pictures were the same or different, and depending on which rule was in effect. The abstract rules were represented in both regions, although they were more prevalent and were encoded earlier and more strongly in the PMC. There was a perceptual bias in the PFC, relative to the PMC, with more PFC neurons encoding the presented pictures. In contrast, neurons encoding the behavioral response were more prevalent in the PMC, and the selectivity was stronger and appeared earlier in the PMC than in the PFC.

Memory: Ironing Out a Wrinkle in Time.

PubMed

Miller, Adam M P; Frankland, Paul W; Josselyn, Sheena A

2018-05-21

Individual hippocampal neurons encode time over seconds, whereas large-scale changes in population activity of hippocampal neurons encode time over minutes and days. New research shows how the hippocampus represents these multiple timescales simultaneously. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Bursting as a source of non-linear determinism in the firing patterns of nigral dopamine neurons

PubMed Central

Jeong, Jaeseung; Shi, Wei-Xing; Hoffman, Ralph; Oh, Jihoon; Gore, John C.; Bunney, Benjamin S.; Peterson, Bradley S.

2012-01-01

Nigral dopamine (DA) neurons in vivo exhibit complex firing patterns consisting of tonic single-spikes and phasic bursts that encode information for certain types of reward-related learning and behavior. Non-linear dynamical analysis has previously demonstrated the presence of a non-linear deterministic structure in complex firing patterns of DA neurons, yet the origin of this non-linear determinism remains unknown. In this study, we hypothesized that bursting activity is the primary source of non-linear determinism in the firing patterns of DA neurons. To test this hypothesis, we investigated the dimension complexity of inter-spike interval data recorded in vivo from bursting and non-bursting DA neurons in the chloral hydrate-anesthetized rat substantia nigra. We found that bursting DA neurons exhibited non-linear determinism in their firing patterns, whereas non-bursting DA neurons showed truly stochastic firing patterns. Determinism was also detected in the isolated burst and inter-burst interval data extracted from firing patterns of bursting neurons. Moreover, less bursting DA neurons in halothane-anesthetized rats exhibited higher dimensional spiking dynamics than do more bursting DA neurons in chloral hydrate-anesthetized rats. These results strongly indicate that bursting activity is the main source of low-dimensional, non-linear determinism in the firing patterns of DA neurons. This finding furthermore suggests that bursts are the likely carriers of meaningful information in the firing activities of DA neurons. PMID:22831464

Distinct Developmental Origins Manifest in the Specialized Encoding of Movement by Adult Neurons of the External Globus Pallidus

PubMed Central

Dodson, Paul D.; Larvin, Joseph T.; Duffell, James M.; Garas, Farid N.; Doig, Natalie M.; Kessaris, Nicoletta; Duguid, Ian C.; Bogacz, Rafal; Butt, Simon J.B.; Magill, Peter J.

2015-01-01

Summary Transcriptional codes initiated during brain development are ultimately realized in adulthood as distinct cell types performing specialized roles in behavior. Focusing on the mouse external globus pallidus (GPe), we demonstrate that the potential contributions of two GABAergic GPe cell types to voluntary action are fated from early life to be distinct. Prototypic GPe neurons derive from the medial ganglionic eminence of the embryonic subpallium and express the transcription factor Nkx2-1. These neurons fire at high rates during alert rest, and encode movements through heterogeneous firing rate changes, with many neurons decreasing their activity. In contrast, arkypallidal GPe neurons originate from lateral/caudal ganglionic eminences, express the transcription factor FoxP2, fire at low rates during rest, and encode movements with robust increases in firing. We conclude that developmental diversity positions prototypic and arkypallidal neurons to fulfil distinct roles in behavior via their disparate regulation of GABA release onto different basal ganglia targets. PMID:25843402

Neural correlates of Pavlovian-to-instrumental transfer in the nucleus accumbens shell are selectively potentiated following cocaine self-administration

PubMed Central

Saddoris, Michael P.; Stamatakis, Alice; Carelli, Regina M.

2013-01-01

During Pavlovian-to-instrumental transfer (PIT), learned Pavlovian cues significantly modulate ongoing instrumental actions. This phenomenon is suggested as a mechanism under which conditioned stimuli may lead to relapse in addicted populations. Following discriminative Pavlovian learning and instrumental conditioning with sucrose, one group of rats (naive) underwent electrophysiological recordings in the nucleus accumbens core and shell during a single PIT session. Other groups, following Pavlovian and instrumental conditioning, were subsequently trained to self-administer cocaine with nosepoke responses, or received yoked saline infusions and nosepoked for water rewards, and then performed PIT while electrophysiological recordings were taken in the nucleus accumbens. Behaviorally, although both naive and saline-treated groups showed increases in lever pressing during the conditioned stimulus cue, this effect was significantly enhanced in the cocaine-treated group. Neurons in the core and shell tracked these behavioral changes. In control animals, core neurons were significantly more likely to encode general information about cues, rewards and responses than those in the shell, and positively correlated with behavioral PIT performance, whereas PIT-specific encoding in the shell, but not core, tracked PIT performance. In contrast, following cocaine exposure, there was a significant increase in neural encoding of all task-relevant events that was selective to the shell. Given that cocaine exposure enhanced both behavior and shell-specific task encoding, these findings suggest that, whereas the core is important for acquiring the information about cues and response contingencies, the shell is important for using this information to guide and modulate behavior and is specifically affected following a history of cocaine self-administration. PMID:21507084

Regulation of persistent sodium currents by glycogen synthase kinase 3 encodes daily rhythms of neuronal excitability

NASA Astrophysics Data System (ADS)

Paul, Jodi R.; Dewoskin, Daniel; McMeekin, Laura J.; Cowell, Rita M.; Forger, Daniel B.; Gamble, Karen L.

2016-11-01

How neurons encode intracellular biochemical signalling cascades into electrical signals is not fully understood. Neurons in the central circadian clock in mammals provide a model system to investigate electrical encoding of biochemical timing signals. Here, using experimental and modelling approaches, we show how the activation of glycogen synthase kinase 3 (GSK3) contributes to neuronal excitability through regulation of the persistent sodium current (INaP). INaP exhibits a day/night difference in peak magnitude and is regulated by GSK3. Using mathematical modelling, we predict and confirm that GSK3 activation of INaP affects the action potential afterhyperpolarization, which increases the spontaneous firing rate without affecting the resting membrane potential. Together, these results demonstrate a crucial link between the molecular circadian clock and electrical activity, providing examples of kinase regulation of electrical activity and the propagation of intracellular signals in neuronal networks.

Asymmetry of Neuronal Combinatorial Codes Arises from Minimizing Synaptic Weight Change.

PubMed

Leibold, Christian; Monsalve-Mercado, Mauro M

2016-08-01

Synaptic change is a costly resource, particularly for brain structures that have a high demand of synaptic plasticity. For example, building memories of object positions requires efficient use of plasticity resources since objects can easily change their location in space and yet we can memorize object locations. But how should a neural circuit ideally be set up to integrate two input streams (object location and identity) in case the overall synaptic changes should be minimized during ongoing learning? This letter provides a theoretical framework on how the two input pathways should ideally be specified. Generally the model predicts that the information-rich pathway should be plastic and encoded sparsely, whereas the pathway conveying less information should be encoded densely and undergo learning only if a neuronal representation of a novel object has to be established. As an example, we consider hippocampal area CA1, which combines place and object information. The model thereby provides a normative account of hippocampal rate remapping, that is, modulations of place field activity by changes of local cues. It may as well be applicable to other brain areas (such as neocortical layer V) that learn combinatorial codes from multiple input streams.

Neuronal adaptation, novelty detection and regularity encoding in audition

PubMed Central

Malmierca, Manuel S.; Sanchez-Vives, Maria V.; Escera, Carles; Bendixen, Alexandra

2014-01-01

The ability to detect unexpected stimuli in the acoustic environment and determine their behavioral relevance to plan an appropriate reaction is critical for survival. This perspective article brings together several viewpoints and discusses current advances in understanding the mechanisms the auditory system implements to extract relevant information from incoming inputs and to identify unexpected events. This extraordinary sensitivity relies on the capacity to codify acoustic regularities, and is based on encoding properties that are present as early as the auditory midbrain. We review state-of-the-art studies on the processing of stimulus changes using non-invasive methods to record the summed electrical potentials in humans, and those that examine single-neuron responses in animal models. Human data will be based on mismatch negativity (MMN) and enhanced middle latency responses (MLR). Animal data will be based on the activity of single neurons at the cortical and subcortical levels, relating selective responses to novel stimuli to the MMN and to stimulus-specific neural adaptation (SSA). Theoretical models of the neural mechanisms that could create SSA and novelty responses will also be discussed. PMID:25009474

Signatures of Value Comparison in Ventral Striatum Neurons

PubMed Central

Strait, Caleb E.; Sleezer, Brianna J.; Hayden, Benjamin Y.

2015-01-01

The ventral striatum (VS), like its cortical afferents, is closely associated with processing of rewards, but the relative contributions of striatal and cortical reward systems remains unclear. Most theories posit distinct roles for these structures, despite their similarities. We compared responses of VS neurons to those of ventromedial prefrontal cortex (vmPFC) Area 14 neurons, recorded in a risky choice task. Five major response patterns observed in vmPFC were also observed in VS: (1) offer value encoding, (2) value difference encoding, (3) preferential encoding of chosen relative to unchosen value, (4) a correlation between residual variance in responses and choices, and (5) prominent encoding of outcomes. We did observe some differences as well; in particular, preferential encoding of the chosen option was stronger and started earlier in VS than in vmPFC. Nonetheless, the close match between vmPFC and VS suggests that cortex and its striatal targets make overlapping contributions to economic choice. PMID:26086735

Neuronal oscillations reveal the processes underlying intentional compared to incidental learning in children and young adults.

PubMed

Köster, Moritz; Haese, André; Czernochowski, Daniela

2017-01-01

This EEG study investigated the neuronal processes during intentional compared to incidental learning in young adults and two groups of children aged 10 and 7 years. Theta (3-8 Hz) and alpha (10-16 Hz) neuronal oscillations were analyzed to compare encoding processes during an intentional and an incidental encoding task. In all three age groups, both encoding conditions were associated with an increase in event-related theta activity. Encoding-related alpha suppression increased with age. Memory performance was higher in the intentional compared to the incidental task in all age groups. Furthermore, intentional learning was associated with an improved encoding of perceptual features, which were relevant for the retrieval phase. Theta activity increased from incidental to intentional encoding. Specifically, frontal theta increased in all age groups, while parietal theta increased only in adults and older children. In younger children, parietal theta was similarly high in both encoding phases. While alpha suppression may reflect semantic processes during encoding, increased theta activity during intentional encoding may indicate perceptual binding processes, in accordance with the demands of the encoding task. Higher encoding-related alpha suppression in the older age groups, together with age differences in parietal theta activity during incidental learning in young children, is in line with recent theoretical accounts, emphasizing the role of perceptual processes in mnemonic processing in young children, whereas semantic encoding processes continue to mature throughout middle childhood.

Evaluating choices by single neurons in the frontal lobe: outcome value encoded across multiple decision variables

PubMed Central

Kennerley, Steven W.; Wallis, Jonathan D.

2009-01-01

Damage to the frontal lobe can cause severe decision-making impairments. A mechanism that may underlie this is that neurons in the frontal cortex encode many variables that contribute to the valuation of a choice, such as its costs, benefits and probability of success. However, optimal decision-making requires that one considers these variables, not only when faced with the choice, but also when evaluating the outcome of the choice, in order to adapt future behaviour appropriately. To examine the role of the frontal cortex in encoding the value of different choice outcomes, we simultaneously recorded the activity of multiple single neurons in the anterior cingulate cortex (ACC), orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) while subjects evaluated the outcome of choices involving manipulations of probability, payoff and cost. Frontal neurons encoded many of the parameters that enabled the calculation of the value of these variables, including the onset and offset of reward and the amount of work performed, and often encoded the value of outcomes across multiple decision variables. In addition, many neurons encoded both the predicted outcome during the choice phase of the task as well as the experienced outcome in the outcome phase of the task. These patterns of selectivity were more prevalent in ACC relative to OFC and LPFC. These results support a role for the frontal cortex, principally ACC, in selecting between choice alternatives and evaluating the outcome of that selection thereby ensuring that choices are optimal and adaptive. PMID:19453638

Development of schemas revealed by prior experience and NMDA receptor knock-out

PubMed Central

Dragoi, George; Tonegawa, Susumu

2013-01-01

Prior experience accelerates acquisition of novel, related information through processes like assimilation into mental schemas, but the underlying neuronal mechanisms are poorly understood. We investigated the roles that prior experience and hippocampal CA3 N-Methyl-D-aspartate receptor (NMDAR)-dependent synaptic plasticity play in CA1 place cell sequence encoding and learning during novel spatial experiences. We found that specific representations of de novo experiences on linear environments were formed on a framework of pre configured network activity expressed in the preceding sleep and were rapidly, flexibly adjusted via NMDAR-dependent activity. This prior experience accelerated encoding of subsequent experiences on contiguous or isolated novel tracks, significantly decreasing their NMDAR-dependence. Similarly, de novo learning of an alternation task was facilitated by CA3 NMDARs; this experience accelerated subsequent learning of related tasks, independent of CA3 NMDARs, consistent with a schema-based learning. These results reveal the existence of distinct neuronal encoding schemes which could explain why hippocampal dysfunction results in anterograde amnesia while sparing recollection of old, schema-based memories. DOI: http://dx.doi.org/10.7554/eLife.01326.001 PMID:24327561

Predictive Ensemble Decoding of Acoustical Features Explains Context-Dependent Receptive Fields.

PubMed

Yildiz, Izzet B; Mesgarani, Nima; Deneve, Sophie

2016-12-07

A primary goal of auditory neuroscience is to identify the sound features extracted and represented by auditory neurons. Linear encoding models, which describe neural responses as a function of the stimulus, have been primarily used for this purpose. Here, we provide theoretical arguments and experimental evidence in support of an alternative approach, based on decoding the stimulus from the neural response. We used a Bayesian normative approach to predict the responses of neurons detecting relevant auditory features, despite ambiguities and noise. We compared the model predictions to recordings from the primary auditory cortex of ferrets and found that: (1) the decoding filters of auditory neurons resemble the filters learned from the statistics of speech sounds; (2) the decoding model captures the dynamics of responses better than a linear encoding model of similar complexity; and (3) the decoding model accounts for the accuracy with which the stimulus is represented in neural activity, whereas linear encoding model performs very poorly. Most importantly, our model predicts that neuronal responses are fundamentally shaped by "explaining away," a divisive competition between alternative interpretations of the auditory scene. Neural responses in the auditory cortex are dynamic, nonlinear, and hard to predict. Traditionally, encoding models have been used to describe neural responses as a function of the stimulus. However, in addition to external stimulation, neural activity is strongly modulated by the responses of other neurons in the network. We hypothesized that auditory neurons aim to collectively decode their stimulus. In particular, a stimulus feature that is decoded (or explained away) by one neuron is not explained by another. We demonstrated that this novel Bayesian decoding model is better at capturing the dynamic responses of cortical neurons in ferrets. Whereas the linear encoding model poorly reflects selectivity of neurons, the decoding model can account for the strong nonlinearities observed in neural data. Copyright © 2016 Yildiz et al.

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.

Weak signal amplification and detection by higher-order sensory neurons.

PubMed

Jung, Sarah N; Longtin, Andre; Maler, Leonard

2016-04-01

Sensory systems must extract behaviorally relevant information and therefore often exhibit a very high sensitivity. How the nervous system reaches such high sensitivity levels is an outstanding question in neuroscience. Weakly electric fish (Apteronotus leptorhynchus/albifrons) are an excellent model system to address this question because detailed background knowledge is available regarding their behavioral performance and its underlying neuronal substrate. Apteronotus use their electrosense to detect prey objects. Therefore, they must be able to detect electrical signals as low as 1 μV while using a sensory integration time of <200 ms. How these very weak signals are extracted and amplified by the nervous system is not yet understood. We studied the responses of cells in the early sensory processing areas, namely, the electroreceptor afferents (EAs) and pyramidal cells (PCs) of the electrosensory lobe (ELL), the first-order electrosensory processing area. In agreement with previous work we found that EAs cannot encode very weak signals with a spike count code. However, PCs can encode prey mimic signals by their firing rate, revealing a huge signal amplification between EAs and PCs and also suggesting differences in their stimulus encoding properties. Using a simple leaky integrate-and-fire (LIF) model we predict that the target neurons of PCs in the midbrain torus semicircularis (TS) are able to detect very weak signals. In particular, TS neurons could do so by assuming biologically plausible convergence rates as well as very simple decoding strategies such as temporal integration, threshold crossing, and combining the inputs of PCs. Copyright © 2016 the American Physiological Society.

Dopaminergic neurons encode a distributed, asymmetric representation of temperature in Drosophila.

PubMed

Tomchik, Seth M

2013-01-30

Dopaminergic circuits modulate a wide variety of innate and learned behaviors in animals, including olfactory associative learning, arousal, and temperature-preference behavior. It is not known whether distinct or overlapping sets of dopaminergic neurons modulate these behaviors. Here, I have functionally characterized the dopaminergic circuits innervating the Drosophila mushroom body with in vivo calcium imaging and conditional silencing of genetically defined subsets of neurons. Distinct subsets of PPL1 dopaminergic neurons innervating the vertical lobes of the mushroom body responded to decreases in temperature, but not increases, with rapidly adapting bursts of activity. PAM neurons innervating the horizontal lobes did not respond to temperature shifts. Ablation of the antennae and maxillary palps reduced, but did not eliminate, the responses. Genetic silencing of dopaminergic neurons innervating the vertical mushroom body lobes substantially reduced behavioral cold avoidance, but silencing smaller subsets of these neurons had no effect. These data demonstrate that overlapping dopaminergic circuits encode a broadly distributed, asymmetric representation of temperature that overlays regions implicated previously in learning, memory, and forgetting. Thus, diverse behaviors engage overlapping sets of dopaminergic neurons that encode multimodal stimuli and innervate a single anatomical target, the mushroom body.

Input-output relation and energy efficiency in the neuron with different spike threshold dynamics.

PubMed

Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin

2015-01-01

Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na(+) and K(+) currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism.

Input-output relation and energy efficiency in the neuron with different spike threshold dynamics

PubMed Central

Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin

2015-01-01

Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na+ and K+ currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism. PMID:26074810

First-spike latency in Hodgkin's three classes of neurons.

PubMed

Wang, Hengtong; Chen, Yueling; Chen, Yong

2013-07-07

We study the first-spike latency (FSL) in Hodgkin's three classes of neurons with the Morris-Lecar neuron model. It is found that all the three classes of neurons can encode an external stimulus into FSLs. With DC inputs, the FSLs of all of the neurons decrease with input intensity. With input current decreased to the threshold, class 1 neurons show an arbitrary long FSL whereas class 2 and 3 neurons exhibit the short-limit FSLs. When the input current is sinusoidal, the amplitude, frequency and initial phase can be encoded by all the three classes of neurons. The FSLs of all of the neurons decrease with the input amplitude and frequency. When the input frequency is too high, all of the neurons respond with infinite FSLs. When the initial phase increases, the FSL decreases and then jumps to a maximal value and finally decreases linearly. With changes in the input parameters, the FSLs of the class 1 and 2 neurons exhibit similar properties. However, the FSL of the class 3 neurons became slightly longer and only produces responses for a narrow range of initial phase if input frequencies are low. Moreover, our results also show that the FSL and firing rate responses are mutually independent processes and that neurons can encode an external stimulus into different FSLs and firing rates simultaneously. This finding is consistent with the current theory of dual or multiple complementary coding mechanisms. Copyright © 2013 Elsevier Ltd. All rights reserved.

Lower layers in the motor cortex are more effective targets for penetrating microelectrodes in cortical prostheses

NASA Astrophysics Data System (ADS)

Parikh, Hirak; Marzullo, Timothy C.; Kipke, Daryl R.

2009-04-01

Improving cortical prostheses requires the development of recording neural interfaces that are efficient in terms of providing maximal control information with minimal interface complexity. While the typical approaches have targeted neurons in the motor cortex with multiple penetrating shanks, an alternative approach is to determine an efficient distribution of electrode sites within the layers of the cortex with fewer penetrating shanks. The objective of this study was to compare unit activity in the upper and lower layers of the cortex with respect to movement and direction in order to inform the design of penetrating microelectrodes. Four rats were implanted bilaterally with multi-site single-shank silicon microelectrode arrays in the neck/shoulder region of the motor cortex. We simultaneously recorded unit activity across all layers of the motor cortex while the animal was engaged in a movement direction task. Localization of the electrode array within the different layers of the cortex was determined by histology. We denoted units from layers 2 and 3 and units as upper layer units, and units from layers 5 and 6 as lower layer units. Analysis of unit spiking activity demonstrated that both the upper and lower layers encode movement and direction information. Unit responses in either cortical layer of the cortex were not preferentially associated with contralateral or ipsilateral movement. Aggregate analysis (633 neurons) and best session analysis (75 neurons) indicated that units in the lower layers (layers 5, 6) are more likely to encode direction information when compared to units in the upper layers (layers 2, 3) (p< 0.05). These results suggest that electrode sites clustered in the lower layers provide access to more salient control information for cortical neuroprostheses.

Differential Encoding of Time by Prefrontal and Striatal Network Dynamics.

PubMed

Bakhurin, Konstantin I; Goudar, Vishwa; Shobe, Justin L; Claar, Leslie D; Buonomano, Dean V; Masmanidis, Sotiris C

2017-01-25

Telling time is fundamental to many forms of learning and behavior, including the anticipation of rewarding events. Although the neural mechanisms underlying timing remain unknown, computational models have proposed that the brain represents time in the dynamics of neural networks. Consistent with this hypothesis, changing patterns of neural activity dynamically in a number of brain areas-including the striatum and cortex-has been shown to encode elapsed time. To date, however, no studies have explicitly quantified and contrasted how well different areas encode time by recording large numbers of units simultaneously from more than one area. Here, we performed large-scale extracellular recordings in the striatum and orbitofrontal cortex of mice that learned the temporal relationship between a stimulus and a reward and reported their response with anticipatory licking. We used a machine-learning algorithm to quantify how well populations of neurons encoded elapsed time from stimulus onset. Both the striatal and cortical networks encoded time, but the striatal network outperformed the orbitofrontal cortex, a finding replicated both in simultaneously and nonsimultaneously recorded corticostriatal datasets. The striatal network was also more reliable in predicting when the animals would lick up to ∼1 s before the actual lick occurred. Our results are consistent with the hypothesis that temporal information is encoded in a widely distributed manner throughout multiple brain areas, but that the striatum may have a privileged role in timing because it has a more accurate "clock" as it integrates information across multiple cortical areas. The neural representation of time is thought to be distributed across multiple functionally specialized brain structures, including the striatum and cortex. However, until now, the neural code for time has not been compared quantitatively between these areas. Here, we performed large-scale recordings in the striatum and orbitofrontal cortex of mice trained on a stimulus-reward association task involving a delay period and used a machine-learning algorithm to quantify how well populations of simultaneously recorded neurons encoded elapsed time from stimulus onset. We found that, although both areas encoded time, the striatum consistently outperformed the orbitofrontal cortex. These results suggest that the striatum may refine the code for time by integrating information from multiple inputs. Copyright © 2017 the authors 0270-6474/17/370854-17$15.00/0.

fMR-adaptation indicates selectivity to audiovisual content congruency in distributed clusters in human superior temporal cortex.

PubMed

van Atteveldt, Nienke M; Blau, Vera C; Blomert, Leo; Goebel, Rainer

2010-02-02

Efficient multisensory integration is of vital importance for adequate interaction with the environment. In addition to basic binding cues like temporal and spatial coherence, meaningful multisensory information is also bound together by content-based associations. Many functional Magnetic Resonance Imaging (fMRI) studies propose the (posterior) superior temporal cortex (STC) as the key structure for integrating meaningful multisensory information. However, a still unanswered question is how superior temporal cortex encodes content-based associations, especially in light of inconsistent results from studies comparing brain activation to semantically matching (congruent) versus nonmatching (incongruent) multisensory inputs. Here, we used fMR-adaptation (fMR-A) in order to circumvent potential problems with standard fMRI approaches, including spatial averaging and amplitude saturation confounds. We presented repetitions of audiovisual stimuli (letter-speech sound pairs) and manipulated the associative relation between the auditory and visual inputs (congruent/incongruent pairs). We predicted that if multisensory neuronal populations exist in STC and encode audiovisual content relatedness, adaptation should be affected by the manipulated audiovisual relation. The results revealed an occipital-temporal network that adapted independently of the audiovisual relation. Interestingly, several smaller clusters distributed over superior temporal cortex within that network, adapted stronger to congruent than to incongruent audiovisual repetitions, indicating sensitivity to content congruency. These results suggest that the revealed clusters contain multisensory neuronal populations that encode content relatedness by selectively responding to congruent audiovisual inputs, since unisensory neuronal populations are assumed to be insensitive to the audiovisual relation. These findings extend our previously revealed mechanism for the integration of letters and speech sounds and demonstrate that fMR-A is sensitive to multisensory congruency effects that may not be revealed in BOLD amplitude per se.

Modulation of value representation by social context in the primate orbitofrontal cortex.

PubMed

Azzi, João C B; Sirigu, Angela; Duhamel, Jean-René

2012-02-07

Primates depend for their survival on their ability to understand their social environment, and their behavior is often shaped by social circumstances. We report that the orbitofrontal cortex, a brain region involved in motivation and reward, is tuned to social information. Macaque monkeys worked to collect rewards for themselves and two monkey partners. Behaviorally, monkeys discriminated between cues signaling large and small [corrected] rewards, and between cues signaling rewards to self only and reward to both self and another monkey, with a preference for the former over the latter in both instances. Single neurons recorded during this task encoded the meaning of visual cues that predicted the magnitude of future rewards, as well as the motivational value of rewards obtained in a social context. Furthermore, neuronal activity was found to track momentary social preferences and partner's identity and social rank. The orbitofrontal cortex thus contains key neuronal mechanisms for the evaluation of social information.

Population dynamics in vasopressin cells.

PubMed

Leng, Gareth; Brown, Colin; Sabatier, Nancy; Scott, Victoria

2008-01-01

Most neurons sense and code change, and when presented with a constant stimulus they adapt, so as to be able to detect a fresh change. However, for some things it is important to know their absolute level; to encode such information, neurons must sustain their response to an unchanging stimulus while remaining able to respond to a change in that stimulus. One system that encodes the absolute level of a stimulus is the vasopressin system, which generates a hormonal signal that is proportional to plasma osmolality. Vasopressin cells sense plasma osmolality and secrete appropriate levels of vasopressin from the neurohypophysis as needed to control water excretion; this requires sustained secretion under basal conditions and the ability to increase (or decrease) secretion should plasma osmolality change. Here we explore the mechanisms that enable vasopressin cells to fulfill this function, and consider how coordination between the cells might distribute the secretory load across the population of vasopressin cells. 2008 S. Karger AG, Basel.

Memory circuits: CA2.

PubMed

Piskorowski, Rebecca A; Chevaleyre, Vivien

2018-04-26

The hippocampus is a central region in the coding of spatial, temporal and episodic memory. Recent discoveries have revealed surprising and complex roles of the small area CA2 in hippocampal function. Lesion studies have revealed that this region is required for social memory formation. Area CA2 is targeted by extra-hippocampal paraventricular inputs that release vasopressin and can act to enhance social memory performance. In vivo recordings have revealed nonconventional activity by neurons in this region that act to both initiate hippocampal sharp-wave ripple events as well as encode spatial information during immobility. Silencing of CA2 pyramidal neurons has revealed that this area also acts to control hippocampal network excitability during encoding, and this balance of excitation and inhibition is disrupted in disease. This review summarizes recent findings and attempts to integrate these results into pre-existing models. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

Visual attention mitigates information loss in small- and large-scale neural codes

PubMed Central

Sprague, Thomas C; Saproo, Sameer; Serences, John T

2015-01-01

Summary The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires processing sensory signals in a manner that protects information about relevant stimuli from degradation. Such selective processing – or selective attention – is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding. PMID:25769502

Neuronal Allocation to a Hippocampal Engram

PubMed Central

Park, Sungmo; Kramer, Emily E; Mercaldo, Valentina; Rashid, Asim J; Insel, Nathan; Frankland, Paul W; Josselyn, Sheena A

2016-01-01

The dentate gyrus (DG) is important for encoding contextual memories, but little is known about how a population of DG neurons comes to encode and support a particular memory. One possibility is that recruitment into an engram depends on a neuron's excitability. Here, we manipulated excitability by overexpressing CREB in a random population of DG neurons and examined whether this biased their recruitment to an engram supporting a contextual fear memory. To directly assess whether neurons overexpressing CREB at the time of training became critical components of the engram, we examined memory expression while the activity of these neurons was silenced. Chemogenetically (hM4Di, an inhibitory DREADD receptor) or optogenetically (iC++, a light-activated chloride channel) silencing the small number of CREB-overexpressing DG neurons attenuated memory expression, whereas silencing a similar number of random neurons not overexpressing CREB at the time of training did not. As post-encoding reactivation of the activity patterns present during initial experience is thought to be important in memory consolidation, we investigated whether post-training silencing of neurons allocated to an engram disrupted subsequent memory expression. We found that silencing neurons 5 min (but not 24 h) following training disrupted memory expression. Together these results indicate that the rules of neuronal allocation to an engram originally described in the lateral amygdala are followed in different brain regions including DG, and moreover, that disrupting the post-training activity pattern of these neurons prevents memory consolidation. PMID:27187069

Neuronal Allocation to a Hippocampal Engram.

PubMed

Park, Sungmo; Kramer, Emily E; Mercaldo, Valentina; Rashid, Asim J; Insel, Nathan; Frankland, Paul W; Josselyn, Sheena A

2016-12-01

The dentate gyrus (DG) is important for encoding contextual memories, but little is known about how a population of DG neurons comes to encode and support a particular memory. One possibility is that recruitment into an engram depends on a neuron's excitability. Here, we manipulated excitability by overexpressing CREB in a random population of DG neurons and examined whether this biased their recruitment to an engram supporting a contextual fear memory. To directly assess whether neurons overexpressing CREB at the time of training became critical components of the engram, we examined memory expression while the activity of these neurons was silenced. Chemogenetically (hM4Di, an inhibitory DREADD receptor) or optogenetically (iC++, a light-activated chloride channel) silencing the small number of CREB-overexpressing DG neurons attenuated memory expression, whereas silencing a similar number of random neurons not overexpressing CREB at the time of training did not. As post-encoding reactivation of the activity patterns present during initial experience is thought to be important in memory consolidation, we investigated whether post-training silencing of neurons allocated to an engram disrupted subsequent memory expression. We found that silencing neurons 5 min (but not 24 h) following training disrupted memory expression. Together these results indicate that the rules of neuronal allocation to an engram originally described in the lateral amygdala are followed in different brain regions including DG, and moreover, that disrupting the post-training activity pattern of these neurons prevents memory consolidation.

Behavioral plasticity through the modulation of switch neurons.

PubMed

Vassiliades, Vassilis; Christodoulou, Chris

2016-02-01

A central question in artificial intelligence is how to design agents capable of switching between different behaviors in response to environmental changes. Taking inspiration from neuroscience, we address this problem by utilizing artificial neural networks (NNs) as agent controllers, and mechanisms such as neuromodulation and synaptic gating. The novel aspect of this work is the introduction of a type of artificial neuron we call "switch neuron". A switch neuron regulates the flow of information in NNs by selectively gating all but one of its incoming synaptic connections, effectively allowing only one signal to propagate forward. The allowed connection is determined by the switch neuron's level of modulatory activation which is affected by modulatory signals, such as signals that encode some information about the reward received by the agent. An important aspect of the switch neuron is that it can be used in appropriate "switch modules" in order to modulate other switch neurons. As we show, the introduction of the switch modules enables the creation of sequences of gating events. This is achieved through the design of a modulatory pathway capable of exploring in a principled manner all permutations of the connections arriving on the switch neurons. We test the model by presenting appropriate architectures in nonstationary binary association problems and T-maze tasks. The results show that for all tasks, the switch neuron architectures generate optimal adaptive behaviors, providing evidence that the switch neuron model could be a valuable tool in simulations where behavioral plasticity is required. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Modelling Odor Decoding in the Antennal Lobe by Combining Sequential Firing Rate Models with Bayesian Inference

PubMed Central

Cuevas Rivera, Dario; Bitzer, Sebastian; Kiebel, Stefan J.

2015-01-01

The olfactory information that is received by the insect brain is encoded in the form of spatiotemporal patterns in the projection neurons of the antennal lobe. These dense and overlapping patterns are transformed into a sparse code in Kenyon cells in the mushroom body. Although it is clear that this sparse code is the basis for rapid categorization of odors, it is yet unclear how the sparse code in Kenyon cells is computed and what information it represents. Here we show that this computation can be modeled by sequential firing rate patterns using Lotka-Volterra equations and Bayesian online inference. This new model can be understood as an ‘intelligent coincidence detector’, which robustly and dynamically encodes the presence of specific odor features. We found that the model is able to qualitatively reproduce experimentally observed activity in both the projection neurons and the Kenyon cells. In particular, the model explains mechanistically how sparse activity in the Kenyon cells arises from the dense code in the projection neurons. The odor classification performance of the model proved to be robust against noise and time jitter in the observed input sequences. As in recent experimental results, we found that recognition of an odor happened very early during stimulus presentation in the model. Critically, by using the model, we found surprising but simple computational explanations for several experimental phenomena. PMID:26451888

Fidelity of the ensemble code for visual motion in primate retina.

PubMed

Frechette, E S; Sher, A; Grivich, M I; Petrusca, D; Litke, A M; Chichilnisky, E J

2005-07-01

Sensory experience typically depends on the ensemble activity of hundreds or thousands of neurons, but little is known about how populations of neurons faithfully encode behaviorally important sensory information. We examined how precisely speed of movement is encoded in the population activity of magnocellular-projecting parasol retinal ganglion cells (RGCs) in macaque monkey retina. Multi-electrode recordings were used to measure the activity of approximately 100 parasol RGCs simultaneously in isolated retinas stimulated with moving bars. To examine how faithfully the retina signals motion, stimulus speed was estimated directly from recorded RGC responses using an optimized algorithm that resembles models of motion sensing in the brain. RGC population activity encoded speed with a precision of approximately 1%. The elementary motion signal was conveyed in approximately 10 ms, comparable to the interspike interval. Temporal structure in spike trains provided more precise speed estimates than time-varying firing rates. Correlated activity between RGCs had little effect on speed estimates. The spatial dispersion of RGC receptive fields along the axis of motion influenced speed estimates more strongly than along the orthogonal direction, as predicted by a simple model based on RGC response time variability and optimal pooling. on and off cells encoded speed with similar and statistically independent variability. Simulation of downstream speed estimation using populations of speed-tuned units showed that peak (winner take all) readout provided more precise speed estimates than centroid (vector average) readout. These findings reveal how faithfully the retinal population code conveys information about stimulus speed and the consequences for motion sensing in the brain.

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.

Bursting as a source of non-linear determinism in the firing patterns of nigral dopamine neurons.

PubMed

Jeong, Jaeseung; Shi, Wei-Xing; Hoffman, Ralph; Oh, Jihoon; Gore, John C; Bunney, Benjamin S; Peterson, Bradley S

2012-11-01

Nigral dopamine (DA) neurons in vivo exhibit complex firing patterns consisting of tonic single-spikes and phasic bursts that encode information for certain types of reward-related learning and behavior. Non-linear dynamical analysis has previously demonstrated the presence of a non-linear deterministic structure in complex firing patterns of DA neurons, yet the origin of this non-linear determinism remains unknown. In this study, we hypothesized that bursting activity is the primary source of non-linear determinism in the firing patterns of DA neurons. To test this hypothesis, we investigated the dimension complexity of inter-spike interval data recorded in vivo from bursting and non-bursting DA neurons in the chloral hydrate-anesthetized rat substantia nigra. We found that bursting DA neurons exhibited non-linear determinism in their firing patterns, whereas non-bursting DA neurons showed truly stochastic firing patterns. Determinism was also detected in the isolated burst and inter-burst interval data extracted from firing patterns of bursting neurons. Moreover, less bursting DA neurons in halothane-anesthetized rats exhibited higher dimensional spiking dynamics than do more bursting DA neurons in chloral hydrate-anesthetized rats. These results strongly indicate that bursting activity is the main source of low-dimensional, non-linear determinism in the firing patterns of DA neurons. This finding furthermore suggests that bursts are the likely carriers of meaningful information in the firing activities of DA neurons. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

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.

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.

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

High-yield in vitro recordings from neurons functionally characterized in vivo.

PubMed

Weiler, Simon; Bauer, Joel; Hübener, Mark; Bonhoeffer, Tobias; Rose, Tobias; Scheuss, Volker

2018-06-01

In vivo two-photon calcium imaging provides detailed information about the activity and response properties of individual neurons. However, in vitro methods are often required to study the underlying neuronal connectivity and physiology at the cellular and synaptic levels at high resolution. This protocol provides a fast and reliable workflow for combining the two approaches by characterizing the response properties of individual neurons in mice in vivo using genetically encoded calcium indicators (GECIs), followed by retrieval of the same neurons in brain slices for further analysis in vitro (e.g., circuit mapping). In this approach, a reference frame is provided by fluorescent-bead tracks and sparsely transduced neurons expressing a structural marker in order to re-identify the same neurons. The use of GECIs provides a substantial advancement over previous approaches by allowing for repeated in vivo imaging. This opens the possibility of directly correlating experience-dependent changes in neuronal activity and feature selectivity with changes in neuronal connectivity and physiology. This protocol requires expertise both in in vivo two-photon calcium imaging and in vitro electrophysiology. It takes 3 weeks or more to complete, depending on the time allotted for repeated in vivo imaging of neuronal activity.

Audiovisual Modulation in Mouse Primary Visual Cortex Depends on Cross-Modal Stimulus Configuration and Congruency.

PubMed

Meijer, Guido T; Montijn, Jorrit S; Pennartz, Cyriel M A; Lansink, Carien S

2017-09-06

The sensory neocortex is a highly connected associative network that integrates information from multiple senses, even at the level of the primary sensory areas. Although a growing body of empirical evidence supports this view, the neural mechanisms of cross-modal integration in primary sensory areas, such as the primary visual cortex (V1), are still largely unknown. Using two-photon calcium imaging in awake mice, we show that the encoding of audiovisual stimuli in V1 neuronal populations is highly dependent on the features of the stimulus constituents. When the visual and auditory stimulus features were modulated at the same rate (i.e., temporally congruent), neurons responded with either an enhancement or suppression compared with unisensory visual stimuli, and their prevalence was balanced. Temporally incongruent tones or white-noise bursts included in audiovisual stimulus pairs resulted in predominant response suppression across the neuronal population. Visual contrast did not influence multisensory processing when the audiovisual stimulus pairs were congruent; however, when white-noise bursts were used, neurons generally showed response suppression when the visual stimulus contrast was high whereas this effect was absent when the visual contrast was low. Furthermore, a small fraction of V1 neurons, predominantly those located near the lateral border of V1, responded to sound alone. These results show that V1 is involved in the encoding of cross-modal interactions in a more versatile way than previously thought. SIGNIFICANCE STATEMENT The neural substrate of cross-modal integration is not limited to specialized cortical association areas but extends to primary sensory areas. Using two-photon imaging of large groups of neurons, we show that multisensory modulation of V1 populations is strongly determined by the individual and shared features of cross-modal stimulus constituents, such as contrast, frequency, congruency, and temporal structure. Congruent audiovisual stimulation resulted in a balanced pattern of response enhancement and suppression compared with unisensory visual stimuli, whereas incongruent or dissimilar stimuli at full contrast gave rise to a population dominated by response-suppressing neurons. Our results indicate that V1 dynamically integrates nonvisual sources of information while still attributing most of its resources to coding visual information. Copyright © 2017 the authors 0270-6474/17/378783-14$15.00/0.

Phase-locking of bursting neuronal firing to dominant LFP frequency components.

PubMed

Constantinou, Maria; Elijah, Daniel H; Squirrell, Daniel; Gigg, John; Montemurro, Marcelo A

2015-10-01

Neuronal firing in the hippocampal formation relative to the phase of local field potentials (LFP) has a key role in memory processing and spatial navigation. Firing can be in either tonic or burst mode. Although bursting neurons are common in the hippocampal formation, the characteristics of their locking to LFP phase are not completely understood. We investigated phase-locking properties of bursting neurons using simulations generated by a dual compartmental model of a pyramidal neuron adapted to match the bursting activity in the subiculum of a rat. The model was driven with stochastic input signals containing a power spectral profile consistent with physiologically relevant frequencies observed in LFP. The single spikes and spike bursts fired by the model were locked to a preferred phase of the predominant frequency band where there was a peak in the power of the driving signal. Moreover, the preferred phase of locking shifted with increasing burst size, providing evidence that LFP phase can be encoded by burst size. We also provide initial support for the model results by analysing example data of spontaneous LFP and spiking activity recorded from the subiculum of a single urethane-anaesthetised rat. Subicular neurons fired single spikes, two-spike bursts and larger bursts that locked to a preferred phase of either dominant slow oscillations or theta rhythms within the LFP, according to the model prediction. Both power-modulated phase-locking and gradual shift in the preferred phase of locking as a function of burst size suggest that neurons can use bursts to encode timing information contained in LFP phase into a spike-count code. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Manipulating a "cocaine engram" in mice.

PubMed

Hsiang, Hwa-Lin Liz; Epp, Jonathan R; van den Oever, Michel C; Yan, Chen; Rashid, Asim J; Insel, Nathan; Ye, Li; Niibori, Yosuke; Deisseroth, Karl; Frankland, Paul W; Josselyn, Sheena A

2014-10-15

Experience with drugs of abuse (such as cocaine) produces powerful, long-lasting memories that may be important in the development and persistence of drug addiction. The neural mechanisms that mediate how and where these cocaine memories are encoded, consolidated and stored are unknown. Here we used conditioned place preference in mice to examine the precise neural circuits that support the memory of a cocaine-cue association (the "cocaine memory trace" or "cocaine engram"). We found that a small population of neurons (∼10%) in the lateral nucleus of amygdala (LA) were recruited at the time of cocaine-conditioning to become part of this cocaine engram. Neurons with increased levels of the transcription factor CREB were preferentially recruited or allocated to the cocaine engram. Ablating or silencing neurons overexpressing CREB (but not a similar number of random LA neurons) before testing disrupted the expression of a previously acquired cocaine memory, suggesting that neurons overexpressing CREB become a critical hub in what is likely a larger cocaine memory engram. Consistent with theories that coordinated postencoding reactivation of neurons within an engram or cell assembly is crucial for memory consolidation (Marr, 1971; Buzsáki, 1989; Wilson and McNaughton, 1994; McClelland et al., 1995; Girardeau et al., 2009; Dupret et al., 2010; Carr et al., 2011), we also found that post-training suppression, or nondiscriminate activation, of CREB overexpressing neurons impaired consolidation of the cocaine memory. These findings reveal mechanisms underlying how and where drug memories are encoded and stored in the brain and may also inform the development of treatments for drug addiction. Copyright © 2014 the authors 0270-6474/14/3414115-13$15.00/0.

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

Changes in Appetitive Associative Strength Modulates Nucleus Accumbens, But Not Orbitofrontal Cortex Neuronal Ensemble Excitability.

PubMed

Ziminski, Joseph J; Hessler, Sabine; Margetts-Smith, Gabriella; Sieburg, Meike C; Crombag, Hans S; Koya, Eisuke

2017-03-22

Cues that predict the availability of food rewards influence motivational states and elicit food-seeking behaviors. If a cue no longer predicts food availability, then animals may adapt accordingly by inhibiting food-seeking responses. Sparsely activated sets of neurons, coined "neuronal ensembles," have been shown to encode the strength of reward-cue associations. Although alterations in intrinsic excitability have been shown to underlie many learning and memory processes, little is known about these properties specifically on cue-activated neuronal ensembles. We examined the activation patterns of cue-activated orbitofrontal cortex (OFC) and nucleus accumbens (NAc) shell ensembles using wild-type and Fos-GFP mice, which express green fluorescent protein (GFP) in activated neurons, after appetitive conditioning with sucrose and extinction learning. We also investigated the neuronal excitability of recently activated, GFP+ neurons in these brain areas using whole-cell electrophysiology in brain slices. Exposure to a sucrose cue elicited activation of neurons in both the NAc shell and OFC. In the NAc shell, but not the OFC, these activated GFP+ neurons were more excitable than surrounding GFP- neurons. After extinction, the number of neurons activated in both areas was reduced and activated ensembles in neither area exhibited altered excitability. These data suggest that learning-induced alterations in the intrinsic excitability of neuronal ensembles is regulated dynamically across different brain areas. Furthermore, we show that changes in associative strength modulate the excitability profile of activated ensembles in the NAc shell. SIGNIFICANCE STATEMENT Sparsely distributed sets of neurons called "neuronal ensembles" encode learned associations about food and cues predictive of its availability. Widespread changes in neuronal excitability have been observed in limbic brain areas after associative learning, but little is known about the excitability changes that occur specifically on neuronal ensembles that encode appetitive associations. Here, we reveal that sucrose cue exposure recruited a more excitable ensemble in the nucleus accumbens, but not orbitofrontal cortex, compared with their surrounding neurons. This excitability difference was not observed when the cue's salience was diminished after extinction learning. These novel data provide evidence that the intrinsic excitability of appetitive memory-encoding ensembles is regulated differentially across brain areas and adapts dynamically to changes in associative strength. Copyright © 2017 the authors 0270-6474/17/373160-11$15.00/0.

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.

Reconstruction of Sensory Stimuli Encoded with Integrate-and-Fire Neurons with Random Thresholds

PubMed Central

Lazar, Aurel A.; Pnevmatikakis, Eftychios A.

2013-01-01

We present a general approach to the reconstruction of sensory stimuli encoded with leaky integrate-and-fire neurons with random thresholds. The stimuli are modeled as elements of a Reproducing Kernel Hilbert Space. The reconstruction is based on finding a stimulus that minimizes a regularized quadratic optimality criterion. We discuss in detail the reconstruction of sensory stimuli modeled as absolutely continuous functions as well as stimuli with absolutely continuous first-order derivatives. Reconstruction results are presented for stimuli encoded with single as well as a population of neurons. Examples are given that demonstrate the performance of the reconstruction algorithms as a function of threshold variability. PMID:24077610

Robust Encoding of Spatial Information in Orbitofrontal Cortex and Striatum.

PubMed

Yoo, Seng Bum Michael; Sleezer, Brianna J; Hayden, Benjamin Y

2018-06-01

Knowing whether core reward regions carry information about the positions of relevant objects is crucial for adjudicating between choice models. One limitation of previous studies, including our own, is that spatial positions can be consistently differentially associated with rewards, and thus position can be confounded with attention, motor plans, or target identity. We circumvented these problems by using a task in which value-and thus choices-was determined solely by a frequently changing rule, which was randomized relative to spatial position on each trial. We presented offers asynchronously, which allowed us to control for reward expectation, spatial attention, and motor plans in our analyses. We find robust encoding of the spatial position of both offers and choices in two core reward regions, orbitofrontal Area 13 and ventral striatum, as well as in dorsal striatum of macaques. The trial-by-trial correlation in noise in encoding of position was associated with variation in choice, an effect known as choice probability correlation, suggesting that the spatial encoding is associated with choice and is not incidental to it. Spatial information and reward information are not carried by separate sets of neurons, although the two forms of information are temporally dissociable. These results highlight the ubiquity of multiplexed information in association cortex and argue against the idea that these ostensible reward regions serve as part of a pure value domain.

Sound Rhythms Are Encoded by Postinhibitory Rebound Spiking in the Superior Paraolivary Nucleus

PubMed Central

Felix, Richard A.; Fridberger, Anders; Leijon, Sara; Berrebi, Albert S.; Magnusson, Anna K.

2013-01-01

The superior paraolivary nucleus (SPON) is a prominent structure in the auditory brainstem. In contrast to the principal superior olivary nuclei with identified roles in processing binaural sound localization cues, the role of the SPON in hearing is not well understood. A combined in vitro and in vivo approach was used to investigate the cellular properties of SPON neurons in the mouse. Patch-clamp recordings in brain slices revealed that brief and well timed postinhibitory rebound spiking, generated by the interaction of two subthreshold-activated ion currents, is a hallmark of SPON neurons. The Ih current determines the timing of the rebound, whereas the T-type Ca2+ current boosts the rebound to spike threshold. This precisely timed rebound spiking provides a physiological explanation for the sensitivity of SPON neurons to sinusoidally amplitude-modulated (SAM) tones in vivo, where peaks in the sound envelope drive inhibitory inputs and SPON neurons fire action potentials during the waveform troughs. Consistent with this notion, SPON neurons display intrinsic tuning to frequency-modulated sinusoidal currents (1–15Hz) in vitro and discharge with strong synchrony to SAMs with modulation frequencies between 1 and 20 Hz in vivo. The results of this study suggest that the SPON is particularly well suited to encode rhythmic sound patterns. Such temporal periodicity information is likely important for detection of communication cues, such as the acoustic envelopes of animal vocalizations and speech signals. PMID:21880918

Sound rhythms are encoded by postinhibitory rebound spiking in the superior paraolivary nucleus.

PubMed

Felix, Richard A; Fridberger, Anders; Leijon, Sara; Berrebi, Albert S; Magnusson, Anna K

2011-08-31

The superior paraolivary nucleus (SPON) is a prominent structure in the auditory brainstem. In contrast to the principal superior olivary nuclei with identified roles in processing binaural sound localization cues, the role of the SPON in hearing is not well understood. A combined in vitro and in vivo approach was used to investigate the cellular properties of SPON neurons in the mouse. Patch-clamp recordings in brain slices revealed that brief and well timed postinhibitory rebound spiking, generated by the interaction of two subthreshold-activated ion currents, is a hallmark of SPON neurons. The I(h) current determines the timing of the rebound, whereas the T-type Ca(2+) current boosts the rebound to spike threshold. This precisely timed rebound spiking provides a physiological explanation for the sensitivity of SPON neurons to sinusoidally amplitude-modulated (SAM) tones in vivo, where peaks in the sound envelope drive inhibitory inputs and SPON neurons fire action potentials during the waveform troughs. Consistent with this notion, SPON neurons display intrinsic tuning to frequency-modulated sinusoidal currents (1-15Hz) in vitro and discharge with strong synchrony to SAMs with modulation frequencies between 1 and 20 Hz in vivo. The results of this study suggest that the SPON is particularly well suited to encode rhythmic sound patterns. Such temporal periodicity information is likely important for detection of communication cues, such as the acoustic envelopes of animal vocalizations and speech signals.

Smelling time: a neural basis for olfactory scene analysis

PubMed Central

Ache, Barry W.; Hein, Andrew M.; Bobkov, Yuriy V.; Principe, Jose C.

2016-01-01

Behavioral evidence from phylogenetically diverse animals and humans suggests that olfaction could be much more involved in interpreting space and time than heretofore imagined by extracting temporal information inherent in the olfactory signal. If this is the case, the olfactory system must have neural mechanisms capable of encoding time at intervals relevant to the turbulent odor world in which many animals live. We review evidence that animals can use populations of rhythmically active or ‘bursting’ olfactory receptor neurons (bORNs) to extract and encode temporal information inherent in natural olfactory signals. We postulate that bORNs represent an unsuspected neural mechanism through which time can be accurately measured, and that ‘smelling time’ completes the requirements for true olfactory scene analysis. PMID:27594700

Hybrid Spintronic-CMOS Spiking Neural Network with On-Chip Learning: Devices, Circuits, and Systems

NASA Astrophysics Data System (ADS)

Sengupta, Abhronil; Banerjee, Aparajita; Roy, Kaushik

2016-12-01

Over the past decade, spiking neural networks (SNNs) have emerged as one of the popular architectures to emulate the brain. In SNNs, information is temporally encoded and communication between neurons is accomplished by means of spikes. In such networks, spike-timing-dependent plasticity mechanisms require the online programing of synapses based on the temporal information of spikes transmitted by spiking neurons. In this work, we propose a spintronic synapse with decoupled spike-transmission and programing-current paths. The spintronic synapse consists of a ferromagnet-heavy-metal heterostructure where the programing current through the heavy metal generates spin-orbit torque to modulate the device conductance. Low programing energy and fast programing times demonstrate the efficacy of the proposed device as a nanoelectronic synapse. We perform a simulation study based on an experimentally benchmarked device-simulation framework to demonstrate the interfacing of such spintronic synapses with CMOS neurons and learning circuits operating in the transistor subthreshold region to form a network of spiking neurons that can be utilized for pattern-recognition problems.

Odors regulate Arc expression in neuronal ensembles engaged in odor processing.

PubMed

Guthrie, K; Rayhanabad, J; Kuhl, D; Gall, C

2000-06-26

Synaptic activity is critical to developmental and plastic processes that produce long-term changes in neuronal connectivity and function. Genes expressed by neurons in an activity-dependent fashion are of particular interest since the proteins they encode may mediate neuronal plasticity. One such gene encodes the activity-regulated cytoskeleton-associated protein, Arc. The present study evaluated the effects of odor stimulation on Arc expression in rat olfactory bulb. Arc mRNA was rapidly increased in functionally linked cohorts of neurons topographically activated by odor stimuli. These included neurons surrounding individual glomeruli, mitral cells and transynaptically activated granule cells. Dendritic Arc immunoreactivity was also increased in odor-activated glomeruli. Our results suggest that odor regulation of Arc expression may contribute to activity-dependent structural changes associated with olfactory experience.

A Neuron-Based Screening Platform for Optimizing Genetically-Encoded Calcium Indicators

PubMed Central

Schreiter, Eric R.; Hasseman, Jeremy P.; Tsegaye, Getahun; Fosque, Benjamin F.; Behnam, Reza; Shields, Brenda C.; Ramirez, Melissa; Kimmel, Bruce E.; Kerr, Rex A.; Jayaraman, Vivek; Looger, Loren L.; Svoboda, Karel; Kim, Douglas S.

2013-01-01

Fluorescent protein-based sensors for detecting neuronal activity have been developed largely based on non-neuronal screening systems. However, the dynamics of neuronal state variables (e.g., voltage, calcium, etc.) are typically very rapid compared to those of non-excitable cells. We developed an electrical stimulation and fluorescence imaging platform based on dissociated rat primary neuronal cultures. We describe its use in testing genetically-encoded calcium indicators (GECIs). Efficient neuronal GECI expression was achieved using lentiviruses containing a neuronal-selective gene promoter. Action potentials (APs) and thus neuronal calcium levels were quantitatively controlled by electrical field stimulation, and fluorescence images were recorded. Images were segmented to extract fluorescence signals corresponding to individual GECI-expressing neurons, which improved sensitivity over full-field measurements. We demonstrate the superiority of screening GECIs in neurons compared with solution measurements. Neuronal screening was useful for efficient identification of variants with both improved response kinetics and high signal amplitudes. This platform can be used to screen many types of sensors with cellular resolution under realistic conditions where neuronal state variables are in relevant ranges with respect to timing and amplitude. PMID:24155972

Neural correlates of social odor recognition and the representation of individual distinctive social odors within entorhinal cortex and ventral subiculum.

PubMed

Petrulis, A; Alvarez, P; Eichenbaum, H

2005-01-01

Recognition of individual conspecifics is important for social behavior and requires the formation of memories for individually distinctive social signals. Individual recognition is often mediated by olfactory cues in mammals, especially nocturnal rodents such as golden hamsters. In hamsters, this form of recognition requires main olfactory system input to the lateral entorhinal cortex (LEnt). Here, we tested whether neurons in LEnt and the nearby ventral subiculum (VS) would show cellular correlates of this natural form of recognition memory. Two hundred ninety single neurons were recorded from both superficial (SE) and deep layers of LEnt (DE) and VS while male hamsters investigated volatile odorants from female vaginal secretions. Many neurons encoded differences between female's odors with many discriminating between odors from different individual females but not between different odor samples from the same female. Other neurons discriminated between odor samples from one female and generalized across collections from other females. LEnt and VS neurons showed enhanced or suppressed cellular activity during investigation of previously presented odors and in response to novel odors. A majority of SE neurons decreased firing to odor repetition and increased activity to novel odors. In contrast, DE neurons often showed suppressed activity in response to novel odors. Thus, neurons in LEnt and VS of male hamsters encode information that is critical for the identification and recognition of individual females by odor cues. This study reveals cellular mechanisms in LEnt and VS that may mediate a natural form of recognition memory in hamsters. These neuronal responses were similar to those observed in rats and monkeys during performance in standard recognition memory tasks. Consequently, the present data extend our understanding of the cellular basis for recognition memory and suggest that individual recognition requires similar neural mechanisms as those employed in laboratory tests of recognition memory.

Visual attention mitigates information loss in small- and large-scale neural codes.

PubMed

Sprague, Thomas C; Saproo, Sameer; Serences, John T

2015-04-01

The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires that sensory signals are processed in a manner that protects information about relevant stimuli from degradation. Such selective processing--or selective attention--is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, thereby providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding. Copyright © 2015 Elsevier Ltd. All rights reserved.

Distributed Fading Memory for Stimulus Properties in the Primary Visual Cortex

PubMed Central

Singer, Wolf; Maass, Wolfgang

2009-01-01

It is currently not known how distributed neuronal responses in early visual areas carry stimulus-related information. We made multielectrode recordings from cat primary visual cortex and applied methods from machine learning in order to analyze the temporal evolution of stimulus-related information in the spiking activity of large ensembles of around 100 neurons. We used sequences of up to three different visual stimuli (letters of the alphabet) presented for 100 ms and with intervals of 100 ms or larger. Most of the information about visual stimuli extractable by sophisticated methods of machine learning, i.e., support vector machines with nonlinear kernel functions, was also extractable by simple linear classification such as can be achieved by individual neurons. New stimuli did not erase information about previous stimuli. The responses to the most recent stimulus contained about equal amounts of information about both this and the preceding stimulus. This information was encoded both in the discharge rates (response amplitudes) of the ensemble of neurons and, when using short time constants for integration (e.g., 20 ms), in the precise timing of individual spikes (≤∼20 ms), and persisted for several 100 ms beyond the offset of stimuli. The results indicate that the network from which we recorded is endowed with fading memory and is capable of performing online computations utilizing information about temporally sequential stimuli. This result challenges models assuming frame-by-frame analyses of sequential inputs. PMID:20027205

Encoding of Tactile Stimuli by Mechanoreceptors and Interneurons of the Medicinal Leech

PubMed Central

Kretzberg, Jutta; Pirschel, Friederice; Fathiazar, Elham; Hilgen, Gerrit

2016-01-01

For many animals processing of tactile information is a crucial task in behavioral contexts like exploration, foraging, and stimulus avoidance. The leech, having infrequent access to food, developed an energy efficient reaction to tactile stimuli, avoiding unnecessary muscle movements: The local bend behavior moves only a small part of the body wall away from an object touching the skin, while the rest of the animal remains stationary. Amazingly, the precision of this localized behavioral response is similar to the spatial discrimination threshold of the human fingertip, although the leech skin is innervated by an order of magnitude fewer mechanoreceptors and each midbody ganglion contains only 400 individually identified neurons in total. Prior studies suggested that this behavior is controlled by a three-layered feed-forward network, consisting of four mechanoreceptors (P cells), approximately 20 interneurons and 10 individually characterized motor neurons, all of which encode tactile stimulus location by overlapping, symmetrical tuning curves. Additionally, encoding of mechanical force was attributed to three types of mechanoreceptors reacting to distinct intensity ranges: T cells for touch, P cells for pressure, and N cells for strong, noxious skin stimulation. In this study, we provide evidences that tactile stimulus encoding in the leech is more complex than previously thought. Combined electrophysiological, anatomical, and voltage sensitive dye approaches indicate that P and T cells both play a major role in tactile information processing resulting in local bending. Our results indicate that tactile encoding neither relies on distinct force intensity ranges of different cell types, nor location encoding is restricted to spike count tuning. Instead, we propose that P and T cells form a mixed type population, which simultaneously employs temporal response features and spike counts for multiplexed encoding of touch location and force intensity. This hypothesis is supported by our finding that previously identified local bend interneurons receive input from both P and T cells. Some of these interneurons seem to integrate mechanoreceptor inputs, while others appear to use temporal response cues, presumably acting as coincidence detectors. Further voltage sensitive dye studies can test these hypotheses how a tiny nervous system performs highly precise stimulus processing. PMID:27840612

Sensory Afferents Use Different Coding Strategies for Heat and Cold.

PubMed

Wang, Feng; Bélanger, Erik; Côté, Sylvain L; Desrosiers, Patrick; Prescott, Steven A; Côté, Daniel C; De Koninck, Yves

2018-05-15

Primary afferents transduce environmental stimuli into electrical activity that is transmitted centrally to be decoded into corresponding sensations. However, it remains unknown how afferent populations encode different somatosensory inputs. To address this, we performed two-photon Ca 2+ imaging from thousands of dorsal root ganglion (DRG) neurons in anesthetized mice while applying mechanical and thermal stimuli to hind paws. We found that approximately half of all neurons are polymodal and that heat and cold are encoded very differently. As temperature increases, more heating-sensitive neurons are activated, and most individual neurons respond more strongly, consistent with graded coding at population and single-neuron levels, respectively. In contrast, most cooling-sensitive neurons respond in an ungraded fashion, inconsistent with graded coding and suggesting combinatorial coding, based on which neurons are co-activated. Although individual neurons may respond to multiple stimuli, our results show that different stimuli activate distinct combinations of diversely tuned neurons, enabling rich population-level coding. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Peptidergic CGRPα primary sensory neurons encode heat and itch and tonically suppress sensitivity to cold

PubMed Central

McCoy, Eric S.; Taylor-Blake, Bonnie; Street, Sarah E.; Pribisko, Alaine L.; Zheng, Jihong; Zylka, Mark J.

2013-01-01

SUMMARY Calcitonin gene-related peptide (CGRP) is a classic molecular marker of peptidergic primary somatosensory neurons. Despite years of research, it is unknown if these neurons are required to sense pain or other sensory stimuli. Here, we found that genetic ablation of CGRPα-expressing sensory neurons reduced sensitivity to noxious heat, capsaicin and itch (histamine and chloroquine) and impaired thermoregulation but did not impair mechanosensation or β-alanine itch—stimuli associated with nonpeptidergic sensory neurons. Unexpectedly, ablation enhanced behavioral responses to cold stimuli and cold mimetics without altering peripheral nerve responses to cooling. Mechanistically, ablation reduced tonic and evoked activity in postsynaptic spinal neurons associated with TRPV1/heat, while profoundly increasing tonic and evoked activity in spinal neurons associated with TRPM8/cold. Our data reveal that CGRPα sensory neurons encode heat and itch and tonically cross-inhibit cold-responsive spinal neurons. Disruption of this crosstalk unmasks cold hypersensitivity, with mechanistic implications for neuropathic pain and temperature perception. PMID:23523592

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

In-situ recording of ionic currents in projection neurons and Kenyon cells in the olfactory pathway of the honeybee

PubMed Central

Rössler, Wolfgang

2018-01-01

The honeybee olfactory pathway comprises an intriguing pattern of convergence and divergence: ~60.000 olfactory sensory neurons (OSN) convey olfactory information on ~900 projection neurons (PN) in the antennal lobe (AL). To transmit this information reliably, PNs employ relatively high spiking frequencies with complex patterns. PNs project via a dual olfactory pathway to the mushroom bodies (MB). This pathway comprises the medial (m-ALT) and the lateral antennal lobe tract (l-ALT). PNs from both tracts transmit information from a wide range of similar odors, but with distinct differences in coding properties. In the MBs, PNs form synapses with many Kenyon cells (KC) that encode odors in a spatially and temporally sparse way. The transformation from complex information coding to sparse coding is a well-known phenomenon in insect olfactory coding. Intrinsic neuronal properties as well as GABAergic inhibition are thought to contribute to this change in odor representation. In the present study, we identified intrinsic neuronal properties promoting coding differences between PNs and KCs using in-situ patch-clamp recordings in the intact brain. We found very prominent K+ currents in KCs clearly differing from the PN currents. This suggests that odor coding differences between PNs and KCs may be caused by differences in their specific ion channel properties. Comparison of ionic currents of m- and l-ALT PNs did not reveal any differences at a qualitative level. PMID:29351552

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

Temporal and Rate Coding for Discrete Event Sequences in the Hippocampus.

PubMed

Terada, Satoshi; Sakurai, Yoshio; Nakahara, Hiroyuki; Fujisawa, Shigeyoshi

2017-06-21

Although the hippocampus is critical to episodic memory, neuronal representations supporting this role, especially relating to nonspatial information, remain elusive. Here, we investigated rate and temporal coding of hippocampal CA1 neurons in rats performing a cue-combination task that requires the integration of sequentially provided sound and odor cues. The majority of CA1 neurons displayed sensory cue-, combination-, or choice-specific (simply, "event"-specific) elevated discharge activities, which were sustained throughout the event period. These event cells underwent transient theta phase precession at event onset, followed by sustained phase locking to the early theta phases. As a result of this unique single neuron behavior, the theta sequences of CA1 cell assemblies of the event sequences had discrete representations. These results help to update the conceptual framework for space encoding toward a more general model of episodic event representations in the hippocampus. Copyright © 2017 Elsevier Inc. All rights reserved.

Unbiased View of Synaptic and Neuronal Gene Complement in Ctenophores: Are There Pan-neuronal and Pan-synaptic Genes across Metazoa?

PubMed Central

Moroz, Leonid L.; Kohn, Andrea B.

2015-01-01

Hypotheses of origins and evolution of neurons and synapses are controversial, mostly due to limited comparative data. Here, we investigated the genome-wide distribution of the bilaterian “synaptic” and “neuronal” protein-coding genes in non-bilaterian basal metazoans (Ctenophora, Porifera, Placozoa, and Cnidaria). First, there are no recognized genes uniquely expressed in neurons across all metazoan lineages. None of the so-called pan-neuronal genes such as embryonic lethal abnormal vision (ELAV), Musashi, or Neuroglobin are expressed exclusively in neurons of the ctenophore Pleurobrachia. Second, our comparative analysis of about 200 genes encoding canonical presynaptic and postsynaptic proteins in bilaterians suggests that there are no true “pan-synaptic” genes or genes uniquely and specifically attributed to all classes of synapses. The majority of these genes encode receptive and secretory complexes in a broad spectrum of eukaryotes. Trichoplax (Placozoa) an organism without neurons and synapses has more orthologs of bilaterian synapse-related/neuron-related genes than do ctenophores—the group with well-developed neuronal and synaptic organization. Third, the majority of genes encoding ion channels and ionotropic receptors are broadly expressed in unicellular eukaryotes and non-neuronal tissues in metazoans. Therefore, they cannot be viewed as neuronal markers. Nevertheless, the co-expression of multiple types of ion channels and receptors does correlate with the presence of neural and synaptic organization. As an illustrative example, the ctenophore genomes encode a greater diversity of ion channels and ionotropic receptors compared with the genomes of the placozoan Trichoplax and the demosponge Amphimedon. Surprisingly, both placozoans and sponges have a similar number of orthologs of “synaptic” proteins as we identified in the genomes of two ctenophores. Ctenophores have a distinct synaptic organization compared with other animals. Our analysis of transcriptomes from 10 different ctenophores did not detect recognized orthologs of synthetic enzymes encoding several classical, low-molecular-weight (neuro)transmitters; glutamate signaling machinery is one of the few exceptions. Novel peptidergic signaling molecules were predicted for ctenophores, together with the diversity of putative receptors including SCNN1/amiloride-sensitive sodium channel-like channels, many of which could be examples of a lineage-specific expansion within this group. In summary, our analysis supports the hypothesis of independent evolution of neurons and, as corollary, a parallel evolution of synapses. We suggest that the formation of synaptic machinery might occur more than once over 600 million years of animal evolution. PMID:26454853

Primate amygdala neurons evaluate the progress of self-defined economic choice sequences

PubMed Central

Grabenhorst, Fabian; Hernadi, Istvan; Schultz, Wolfram

2016-01-01

The amygdala is a prime valuation structure yet its functions in advanced behaviors are poorly understood. We tested whether individual amygdala neurons encode a critical requirement for goal-directed behavior: the evaluation of progress during sequential choices. As monkeys progressed through choice sequences toward rewards, amygdala neurons showed phasic, gradually increasing responses over successive choice steps. These responses occurred in the absence of external progress cues or motor preplanning. They were often specific to self-defined sequences, typically disappearing during instructed control sequences with similar reward expectation. Their build-up rate reflected prospectively the forthcoming choice sequence, suggesting adaptation to an internal plan. Population decoding demonstrated a high-accuracy progress code. These findings indicate that amygdala neurons evaluate the progress of planned, self-defined behavioral sequences. Such progress signals seem essential for aligning stepwise choices with internal plans. Their presence in amygdala neurons may inform understanding of human conditions with amygdala dysfunction and deregulated reward pursuit. DOI: http://dx.doi.org/10.7554/eLife.18731.001 PMID:27731795

Primate amygdala neurons evaluate the progress of self-defined economic choice sequences.

PubMed

Grabenhorst, Fabian; Hernadi, Istvan; Schultz, Wolfram

2016-10-12

The amygdala is a prime valuation structure yet its functions in advanced behaviors are poorly understood. We tested whether individual amygdala neurons encode a critical requirement for goal-directed behavior: the evaluation of progress during sequential choices. As monkeys progressed through choice sequences toward rewards, amygdala neurons showed phasic, gradually increasing responses over successive choice steps. These responses occurred in the absence of external progress cues or motor preplanning. They were often specific to self-defined sequences, typically disappearing during instructed control sequences with similar reward expectation. Their build-up rate reflected prospectively the forthcoming choice sequence, suggesting adaptation to an internal plan. Population decoding demonstrated a high-accuracy progress code. These findings indicate that amygdala neurons evaluate the progress of planned, self-defined behavioral sequences. Such progress signals seem essential for aligning stepwise choices with internal plans. Their presence in amygdala neurons may inform understanding of human conditions with amygdala dysfunction and deregulated reward pursuit.

Two-photon imaging in mice shows striosomes and matrix have overlapping but differential reinforcement-related responses

PubMed Central

Sur, Mriganka

2017-01-01

Striosomes were discovered several decades ago as neurochemically identified zones in the striatum, yet technical hurdles have hampered the study of the functions of these striatal compartments. Here we used 2-photon calcium imaging in neuronal birthdate-labeled Mash1-CreER;Ai14 mice to image simultaneously the activity of striosomal and matrix neurons as mice performed an auditory conditioning task. With this method, we identified circumscribed zones of tdTomato-labeled neuropil that correspond to striosomes as verified immunohistochemically. Neurons in both striosomes and matrix responded to reward-predicting cues and were active during or after consummatory licking. However, we found quantitative differences in response strength: striosomal neurons fired more to reward-predicting cues and encoded more information about expected outcome as mice learned the task, whereas matrix neurons were more strongly modulated by recent reward history. These findings open the possibility of harnessing in vivo imaging to determine the contributions of striosomes and matrix to striatal circuit function. PMID:29251596

On Information Metrics for Spatial Coding.

PubMed

Souza, Bryan C; Pavão, Rodrigo; Belchior, Hindiael; Tort, Adriano B L

2018-04-01

The hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon's mutual information (Shannon, 1948), and convey information rate in bits/s or bits/spike (Skaggs et al., 1993, 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Neuronal encoding of sound, gravity, and wind in the fruit fly.

PubMed

Matsuo, Eriko; Kamikouchi, Azusa

2013-04-01

The fruit fly Drosophila melanogaster responds behaviorally to sound, gravity, and wind. Exposure to male courtship songs results in reduced locomotion in females, whereas males begin to chase each other. When agitated, fruit flies tend to move against gravity. When faced with air currents, they 'freeze' in place. Based on recent studies, Johnston's hearing organ, the antennal ear of the fruit fly, serves as a sensor for all of these mechanosensory stimuli. Compartmentalization of sense cells in Johnston's organ into vibration-sensitive and deflection-sensitive neural groups allows this single organ to mediate such varied functions. Sound and gravity/wind signals sensed by these two neuronal groups travel in parallel from the fly ear to the brain, feeding into neural pathways reminiscent of the auditory and vestibular pathways in the human brain. Studies of the similarities between mammals and flies will lead to a better understanding of the principles of how sound and gravity information is encoded in the brain. Here, we review recent advances in our understanding of these principles and discuss the advantages of the fruit fly as a model system to explore the fundamental principles of how neural circuits and their ensembles process and integrate sensory information in the brain.

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.

Genetically Encoded Voltage Indicators: Opportunities and Challenges

PubMed Central

Yang, Helen H.

2016-01-01

A longstanding goal in neuroscience is to understand how spatiotemporal patterns of neuronal electrical activity underlie brain function, from sensory representations to decision making. An emerging technology for monitoring electrical dynamics, voltage imaging using genetically encoded voltage indicators (GEVIs), couples the power of genetics with the advantages of light. Here, we review the properties that determine indicator performance and applicability, discussing both recent progress and technical limitations. We then consider GEVI applications, highlighting studies that have already deployed GEVIs for biological discovery. We also examine which classes of biological questions GEVIs are primed to address and which ones are beyond their current capabilities. As GEVIs are further developed, we anticipate that they will become more broadly used by the neuroscience community to eavesdrop on brain activity with unprecedented spatiotemporal resolution. SIGNIFICANCE STATEMENT Genetically encoded voltage indicators are engineered light-emitting protein sensors that typically report neuronal voltage dynamics as changes in brightness. In this review, we systematically discuss the current state of this emerging method, considering both its advantages and limitations for imaging neural activity. We also present recent applications of this technology and discuss what is feasible now and what we anticipate will become possible with future indicator development. This review will inform neuroscientists of recent progress in the field and help potential users critically evaluate the suitability of genetically encoded voltage indicator imaging to answer their specific biological questions. PMID:27683896

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

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

Genetically encoded proton sensors reveal activity-dependent pH changes in neurons.

PubMed

Raimondo, Joseph V; Irkle, Agnese; Wefelmeyer, Winnie; Newey, Sarah E; Akerman, Colin J

2012-01-01

The regulation of hydrogen ion concentration (pH) is fundamental to cell viability, metabolism, and enzymatic function. Within the nervous system, the control of pH is also involved in diverse and dynamic processes including development, synaptic transmission, and the control of network excitability. As pH affects neuronal activity, and can also itself be altered by neuronal activity, the existence of tools to accurately measure hydrogen ion fluctuations is important for understanding the role pH plays under physiological and pathological conditions. Outside of their use as a marker of synaptic release, genetically encoded pH sensors have not been utilized to study hydrogen ion fluxes associated with network activity. By combining whole-cell patch clamp with simultaneous two-photon or confocal imaging, we quantified the amplitude and time course of neuronal, intracellular, acidic transients evoked by epileptiform activity in two separate in vitro models of temporal lobe epilepsy. In doing so, we demonstrate the suitability of three genetically encoded pH sensors: deGFP4, E(2)GFP, and Cl-sensor for investigating activity-dependent pH changes at the level of single neurons.

A cortical neural prosthesis for restoring and enhancing memory

NASA Astrophysics Data System (ADS)

Berger, Theodore W.; Hampson, Robert E.; Song, Dong; Goonawardena, Anushka; Marmarelis, Vasilis Z.; Deadwyler, Sam A.

2011-08-01

A primary objective in developing a neural prosthesis is to replace neural circuitry in the brain that no longer functions appropriately. Such a goal requires artificial reconstruction of neuron-to-neuron connections in a way that can be recognized by the remaining normal circuitry, and that promotes appropriate interaction. In this study, the application of a specially designed neural prosthesis using a multi-input/multi-output (MIMO) nonlinear model is demonstrated by using trains of electrical stimulation pulses to substitute for MIMO model derived ensemble firing patterns. Ensembles of CA3 and CA1 hippocampal neurons, recorded from rats performing a delayed-nonmatch-to-sample (DNMS) memory task, exhibited successful encoding of trial-specific sample lever information in the form of different spatiotemporal firing patterns. MIMO patterns, identified online and in real-time, were employed within a closed-loop behavioral paradigm. Results showed that the model was able to predict successful performance on the same trial. Also, MIMO model-derived patterns, delivered as electrical stimulation to the same electrodes, improved performance under normal testing conditions and, more importantly, were capable of recovering performance when delivered to animals with ensemble hippocampal activity compromised by pharmacologic blockade of synaptic transmission. These integrated experimental-modeling studies show for the first time that, with sufficient information about the neural coding of memories, a neural prosthesis capable of real-time diagnosis and manipulation of the encoding process can restore and even enhance cognitive, mnemonic processes.

Slow oscillations orchestrating fast oscillations and memory consolidation.

PubMed

Mölle, Matthias; Born, Jan

2011-01-01

Slow-wave sleep (SWS) facilitates the consolidation of hippocampus-dependent declarative memory. Based on the standard two-stage memory model, we propose that memory consolidation during SWS represents a process of system consolidation which is orchestrated by the neocortical <1Hz electroencephalogram (EEG) slow oscillation and involves the reactivation of newly encoded representations and their subsequent redistribution from temporary hippocampal to neocortical long-term storage sites. Indeed, experimental induction of slow oscillations during non-rapid eye movement (non-REM) sleep by slowly alternating transcranial current stimulation distinctly improves consolidation of declarative memory. The slow oscillations temporally group neuronal activity into up-states of strongly enhanced neuronal activity and down-states of neuronal silence. In a feed-forward efferent action, this grouping is induced not only in the neocortex but also in other structures relevant to consolidation, namely the thalamus generating 10-15Hz spindles, and the hippocampus generating sharp wave-ripples, with the latter well known to accompany a replay of newly encoded memories taking place in hippocampal circuitries. The feed-forward synchronizing effect of the slow oscillation enables the formation of spindle-ripple events where ripples and accompanying reactivated hippocampal memory information become nested into the single troughs of spindles. Spindle-ripple events thus enable reactivated memory-related hippocampal information to be fed back to neocortical networks in the excitable slow oscillation up-state where they can induce enduring plastic synaptic changes underlying the effective formation of long-term memories. Copyright © 2011 Elsevier B.V. All rights reserved.

Encoding frequency contrast in primate auditory cortex

PubMed Central

Scott, Brian H.; Semple, Malcolm N.

2014-01-01

Changes in amplitude and frequency jointly determine much of the communicative significance of complex acoustic signals, including human speech. We have previously described responses of neurons in the core auditory cortex of awake rhesus macaques to sinusoidal amplitude modulation (SAM) signals. Here we report a complementary study of sinusoidal frequency modulation (SFM) in the same neurons. Responses to SFM were analogous to SAM responses in that changes in multiple parameters defining SFM stimuli (e.g., modulation frequency, modulation depth, carrier frequency) were robustly encoded in the temporal dynamics of the spike trains. For example, changes in the carrier frequency produced highly reproducible changes in shapes of the modulation period histogram, consistent with the notion that the instantaneous probability of discharge mirrors the moment-by-moment spectrum at low modulation rates. The upper limit for phase locking was similar across SAM and SFM within neurons, suggesting shared biophysical constraints on temporal processing. Using spike train classification methods, we found that neural thresholds for modulation depth discrimination are typically far lower than would be predicted from frequency tuning to static tones. This “dynamic hyperacuity” suggests a substantial central enhancement of the neural representation of frequency changes relative to the auditory periphery. Spike timing information was superior to average rate information when discriminating among SFM signals, and even when discriminating among static tones varying in frequency. This finding held even when differences in total spike count across stimuli were normalized, indicating both the primacy and generality of temporal response dynamics in cortical auditory processing. PMID:24598525

Stochastic frequency signature for chemical sensing using noninvasive neuronelectronic interface.

PubMed

Yang, Mo; Zhang, Xuan; Zhang, Yu; Ozkan, Cengiz S

2005-05-01

The detection of chemical agents is important in many areas including environmental pollutants, toxins, biological and chemical pollutants. As "smart" cells, with strong information encoding ability, neurons can be treated as independent sensing elements. A hybrid circuit of a semiconductor chip with dissociated neurons formed both sensors and transducers. Stochastic frequency spectrum was used to differentiate a mixture of chemical agents with effect on the opening of different ion channels. The frequency of spike trains revealed the concentration of the chemical agent, where the characteristic tuning curve revealed the identity. "Fatigue" experiment was performed to explore the "refreshing" ability and "memory" effect of neurons by cyclic and cascaded sensing. "Neuronelectronic noses" such as this should have wide potential applications, most notably in environmental and medical monitoring.

The Role of Inhibition in a Computational Model of an Auditory Cortical Neuron during the Encoding of Temporal Information

PubMed Central

Bendor, Daniel

2015-01-01

In auditory cortex, temporal information within a sound is represented by two complementary neural codes: a temporal representation based on stimulus-locked firing and a rate representation, where discharge rate co-varies with the timing between acoustic events but lacks a stimulus-synchronized response. Using a computational neuronal model, we find that stimulus-locked responses are generated when sound-evoked excitation is combined with strong, delayed inhibition. In contrast to this, a non-synchronized rate representation is generated when the net excitation evoked by the sound is weak, which occurs when excitation is coincident and balanced with inhibition. Using single-unit recordings from awake marmosets (Callithrix jacchus), we validate several model predictions, including differences in the temporal fidelity, discharge rates and temporal dynamics of stimulus-evoked responses between neurons with rate and temporal representations. Together these data suggest that feedforward inhibition provides a parsimonious explanation of the neural coding dichotomy observed in auditory cortex. PMID:25879843

Dynamic coding of vertical facilitated vergence by premotor saccadic burst neurons.

PubMed

Van Horn, Marion R; Cullen, Kathleen E

2008-10-01

To redirect our gaze in three-dimensional space we frequently combine saccades and vergence. These eye movements, known as disconjugate saccades, are characterized by eyes rotating by different amounts, with markedly different dynamics, and occur whenever gaze is shifted between near and far objects. How the brain ensures the precise control of binocular positioning remains controversial. It has been proposed that the traditionally assumed "conjugate" saccadic premotor pathway does not encode conjugate commands but rather encodes monocular commands for the right or left eye during saccades. Here, we directly test this proposal by recording from the premotor neurons of the horizontal saccade generator during a dissociation task that required a vergence but no horizontal conjugate saccadic command. Specifically, saccadic burst neurons (SBNs) in the paramedian pontine reticular formation were recorded while rhesus monkeys made vertical saccades made between near and far targets. During this task, we first show that peak vergence velocities were enhanced to saccade-like speeds (e.g., >150 vs. <100 degrees/s during saccade-free movements for comparable changes in vergence angle). We then quantified the discharge dynamics of SBNs during these movements and found that the majority of the neurons preferentially encode the velocity of the ipsilateral eye. Notably, a given neuron typically encoded the movement of the same eye during horizontal saccades that were made in depth. Taken together, our findings demonstrate that the brain stem saccadic burst generator encodes integrated conjugate and vergence commands, thus providing strong evidence for the proposal that the classic saccadic premotor pathway controls gaze in three-dimensional space.

Amygdala Contributions to Stimulus-Reward Encoding in the Macaque Medial and Orbital Frontal Cortex during Learning.

PubMed

Rudebeck, Peter H; Ripple, Joshua A; Mitz, Andrew R; Averbeck, Bruno B; Murray, Elisabeth A

2017-02-22

Orbitofrontal cortex (OFC), medial frontal cortex (MFC), and amygdala mediate stimulus-reward learning, but the mechanisms through which they interact are unclear. Here, we investigated how neurons in macaque OFC and MFC signaled rewards and the stimuli that predicted them during learning with and without amygdala input. Macaques performed a task that required them to evaluate two stimuli and then choose one to receive the reward associated with that option. Four main findings emerged. First, amygdala lesions slowed the acquisition and use of stimulus-reward associations. Further analyses indicated that this impairment was due, at least in part, to ineffective use of negative feedback to guide subsequent decisions. Second, the activity of neurons in OFC and MFC rapidly evolved to encode the amount of reward associated with each stimulus. Third, amygdalectomy reduced encoding of stimulus-reward associations during the evaluation of different stimuli. Reward encoding of anticipated and received reward after choices were made was not altered. Fourth, amygdala lesions led to an increase in the proportion of neurons in MFC, but not OFC, that encoded the instrumental response that monkeys made on each trial. These correlated changes in behavior and neural activity after amygdala lesions strongly suggest that the amygdala contributes to the ability to learn stimulus-reward associations rapidly by shaping encoding within OFC and MFC. SIGNIFICANCE STATEMENT Altered functional interactions among orbital frontal cortex (OFC), medial frontal cortex (MFC), and amygdala are thought to underlie several psychiatric conditions, many related to reward learning. Here, we investigated the causal contribution of the amygdala to the development of neuronal activity in macaque OFC and MFC related to rewards and the stimuli that predict them during learning. Without amygdala inputs, neurons in both OFC and MFC showed decreased encoding of stimulus-reward associations. MFC also showed increased encoding of the instrumental responses that monkeys made on each trial. Behaviorally, changes in neural activity were accompanied by slower stimulus-reward learning. The findings suggest that interactions among amygdala, OFC, and MFC contribute to learning about stimuli that predict rewards. Copyright © 2017 the authors 0270-6474/17/372186-17$15.00/0.

Amygdala Contributions to Stimulus–Reward Encoding in the Macaque Medial and Orbital Frontal Cortex during Learning

PubMed Central

Averbeck, Bruno B.

2017-01-01

Orbitofrontal cortex (OFC), medial frontal cortex (MFC), and amygdala mediate stimulus–reward learning, but the mechanisms through which they interact are unclear. Here, we investigated how neurons in macaque OFC and MFC signaled rewards and the stimuli that predicted them during learning with and without amygdala input. Macaques performed a task that required them to evaluate two stimuli and then choose one to receive the reward associated with that option. Four main findings emerged. First, amygdala lesions slowed the acquisition and use of stimulus–reward associations. Further analyses indicated that this impairment was due, at least in part, to ineffective use of negative feedback to guide subsequent decisions. Second, the activity of neurons in OFC and MFC rapidly evolved to encode the amount of reward associated with each stimulus. Third, amygdalectomy reduced encoding of stimulus–reward associations during the evaluation of different stimuli. Reward encoding of anticipated and received reward after choices were made was not altered. Fourth, amygdala lesions led to an increase in the proportion of neurons in MFC, but not OFC, that encoded the instrumental response that monkeys made on each trial. These correlated changes in behavior and neural activity after amygdala lesions strongly suggest that the amygdala contributes to the ability to learn stimulus–reward associations rapidly by shaping encoding within OFC and MFC. SIGNIFICANCE STATEMENT Altered functional interactions among orbital frontal cortex (OFC), medial frontal cortex (MFC), and amygdala are thought to underlie several psychiatric conditions, many related to reward learning. Here, we investigated the causal contribution of the amygdala to the development of neuronal activity in macaque OFC and MFC related to rewards and the stimuli that predict them during learning. Without amygdala inputs, neurons in both OFC and MFC showed decreased encoding of stimulus–reward associations. MFC also showed increased encoding of the instrumental responses that monkeys made on each trial. Behaviorally, changes in neural activity were accompanied by slower stimulus–reward learning. The findings suggest that interactions among amygdala, OFC, and MFC contribute to learning about stimuli that predict rewards. PMID:28123082

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

Sequential sensory and decision processing in posterior parietal cortex

PubMed Central

Ibos, Guilhem; Freedman, David J

2017-01-01

Decisions about the behavioral significance of sensory stimuli often require comparing sensory inference of what we are looking at to internal models of what we are looking for. Here, we test how neuronal selectivity for visual features is transformed into decision-related signals in posterior parietal cortex (area LIP). Monkeys performed a visual matching task that required them to detect target stimuli composed of conjunctions of color and motion-direction. Neuronal recordings from area LIP revealed two main findings. First, the sequential processing of visual features and the selection of target-stimuli suggest that LIP is involved in transforming sensory information into decision-related signals. Second, the patterns of color and motion selectivity and their impact on decision-related encoding suggest that LIP plays a role in detecting target stimuli by comparing bottom-up sensory inputs (what the monkeys were looking at) and top-down cognitive encoding inputs (what the monkeys were looking for). DOI: http://dx.doi.org/10.7554/eLife.23743.001 PMID:28418332

Mushroom body output neurons encode valence and guide memory-based action selection in Drosophila

PubMed Central

Aso, Yoshinori; Sitaraman, Divya; Ichinose, Toshiharu; Kaun, Karla R; Vogt, Katrin; Belliart-Guérin, Ghislain; Plaçais, Pierre-Yves; Robie, Alice A; Yamagata, Nobuhiro; Schnaitmann, Christopher; Rowell, William J; Johnston, Rebecca M; Ngo, Teri-T B; Chen, Nan; Korff, Wyatt; Nitabach, Michael N; Heberlein, Ulrike; Preat, Thomas; Branson, Kristin M; Tanimoto, Hiromu; Rubin, Gerald M

2014-01-01

Animals discriminate stimuli, learn their predictive value and use this knowledge to modify their behavior. In Drosophila, the mushroom body (MB) plays a key role in these processes. Sensory stimuli are sparsely represented by ∼2000 Kenyon cells, which converge onto 34 output neurons (MBONs) of 21 types. We studied the role of MBONs in several associative learning tasks and in sleep regulation, revealing the extent to which information flow is segregated into distinct channels and suggesting possible roles for the multi-layered MBON network. We also show that optogenetic activation of MBONs can, depending on cell type, induce repulsion or attraction in flies. The behavioral effects of MBON perturbation are combinatorial, suggesting that the MBON ensemble collectively represents valence. We propose that local, stimulus-specific dopaminergic modulation selectively alters the balance within the MBON network for those stimuli. Our results suggest that valence encoded by the MBON ensemble biases memory-based action selection. DOI: http://dx.doi.org/10.7554/eLife.04580.001 PMID:25535794

Cellular and oscillatory substrates of fear extinction learning.

PubMed

Davis, Patrick; Zaki, Yosif; Maguire, Jamie; Reijmers, Leon G

2017-11-01

The mammalian brain contains dedicated circuits for both the learned expression and suppression of fear. These circuits require precise coordination to facilitate the appropriate expression of fear behavior, but the mechanisms underlying this coordination remain unclear. Using a combination of chemogenetics, activity-based neuronal-ensemble labeling and in vivo electrophysiology, we found that fear extinction learning confers on parvalbumin-expressing (PV) interneurons in the basolateral amygdala (BLA) a dedicated role in the selective suppression of a previously encoded fear memory and BLA fear-encoding neurons. In addition, following extinction learning, PV interneurons enable a competing interaction between a 6-12 Hz oscillation and a fear-associated 3-6 Hz oscillation within the BLA. Loss of this competition increases a 3-6 Hz oscillatory signature, with BLA→medial prefrontal cortex directionality signaling the recurrence of fear expression. The discovery of cellular and oscillatory substrates of fear extinction learning that critically depend on BLA PV interneurons could inform therapies aimed at preventing the pathological recurrence of fear following extinction learning.

Cellular and Oscillatory Substrates of Fear Extinction Learning

PubMed Central

Davis, Patrick; Zaki, Yosif; Maguire, Jamie; Reijmers, Leon G.

2018-01-01

The mammalian brain contains dedicated circuits for both the learned expression and suppression of fear. These circuits require precise coordination to facilitate the appropriate expression of fear behavior, but the mechanisms underlying this coordination remain unclear. Using a novel combination of chemogenetics, activity-based neuronal-ensemble labeling, and in vivo electrophysiology, we found that fear extinction learning confers parvalbumin-expressing (PV) interneurons in the basolateral amygdala (BLA) with a dedicated role in the selective suppression of a previously encoded fear memory and BLA fear-encoding neurons. In addition, following extinction learning, PV interneurons enable a competing interaction between a 6–12 Hz oscillation and a fear-associated 3–6 Hz oscillation within the BLA. Loss of this competition increases a 3–6 Hz oscillatory signature, with BLA→mPFC directionality signaling the recurrence of fear expression. The discovery of cellular and oscillatory substrates of fear extinction learning that critically depend on BLA PV-interneurons could inform therapies aimed at preventing the pathological recurrence of fear following extinction learning. PMID:28967909

Separate Populations of Neurons in Ventral Striatum Encode Value and Motivation

PubMed Central

Gentry, Ronny N.; Goldstein, Brandon L.; Hearn, Taylor N.; Barnett, Brian R.; Kashtelyan, Vadim; Roesch, Matthew R.

2013-01-01

Neurons in the ventral striatum (VS) fire to cues that predict differently valued rewards. It is unclear whether this activity represents the value associated with the expected reward or the level of motivation induced by reward anticipation. To distinguish between the two, we trained rats on a task in which we varied value independently from motivation by manipulating the size of the reward expected on correct trials and the threat of punishment expected upon errors. We found that separate populations of neurons in VS encode expected value and motivation. PMID:23724077

Lateral orbitofrontal cortex anticipates choices and integrates prior with current information

PubMed Central

Nogueira, Ramon; Abolafia, Juan M.; Drugowitsch, Jan; Balaguer-Ballester, Emili; Sanchez-Vives, Maria V.; Moreno-Bote, Rubén

2017-01-01

Adaptive behavior requires integrating prior with current information to anticipate upcoming events. Brain structures related to this computation should bring relevant signals from the recent past into the present. Here we report that rats can integrate the most recent prior information with sensory information, thereby improving behavior on a perceptual decision-making task with outcome-dependent past trial history. We find that anticipatory signals in the orbitofrontal cortex about upcoming choice increase over time and are even present before stimulus onset. These neuronal signals also represent the stimulus and relevant second-order combinations of past state variables. The encoding of choice, stimulus and second-order past state variables resides, up to movement onset, in overlapping populations. The neuronal representation of choice before stimulus onset and its build-up once the stimulus is presented suggest that orbitofrontal cortex plays a role in transforming immediate prior and stimulus information into choices using a compact state-space representation. PMID:28337990

Unbiased View of Synaptic and Neuronal Gene Complement in Ctenophores: Are There Pan-neuronal and Pan-synaptic Genes across Metazoa?

PubMed

Moroz, Leonid L; Kohn, Andrea B

2015-12-01

Hypotheses of origins and evolution of neurons and synapses are controversial, mostly due to limited comparative data. Here, we investigated the genome-wide distribution of the bilaterian "synaptic" and "neuronal" protein-coding genes in non-bilaterian basal metazoans (Ctenophora, Porifera, Placozoa, and Cnidaria). First, there are no recognized genes uniquely expressed in neurons across all metazoan lineages. None of the so-called pan-neuronal genes such as embryonic lethal abnormal vision (ELAV), Musashi, or Neuroglobin are expressed exclusively in neurons of the ctenophore Pleurobrachia. Second, our comparative analysis of about 200 genes encoding canonical presynaptic and postsynaptic proteins in bilaterians suggests that there are no true "pan-synaptic" genes or genes uniquely and specifically attributed to all classes of synapses. The majority of these genes encode receptive and secretory complexes in a broad spectrum of eukaryotes. Trichoplax (Placozoa) an organism without neurons and synapses has more orthologs of bilaterian synapse-related/neuron-related genes than do ctenophores-the group with well-developed neuronal and synaptic organization. Third, the majority of genes encoding ion channels and ionotropic receptors are broadly expressed in unicellular eukaryotes and non-neuronal tissues in metazoans. Therefore, they cannot be viewed as neuronal markers. Nevertheless, the co-expression of multiple types of ion channels and receptors does correlate with the presence of neural and synaptic organization. As an illustrative example, the ctenophore genomes encode a greater diversity of ion channels and ionotropic receptors compared with the genomes of the placozoan Trichoplax and the demosponge Amphimedon. Surprisingly, both placozoans and sponges have a similar number of orthologs of "synaptic" proteins as we identified in the genomes of two ctenophores. Ctenophores have a distinct synaptic organization compared with other animals. Our analysis of transcriptomes from 10 different ctenophores did not detect recognized orthologs of synthetic enzymes encoding several classical, low-molecular-weight (neuro)transmitters; glutamate signaling machinery is one of the few exceptions. Novel peptidergic signaling molecules were predicted for ctenophores, together with the diversity of putative receptors including SCNN1/amiloride-sensitive sodium channel-like channels, many of which could be examples of a lineage-specific expansion within this group. In summary, our analysis supports the hypothesis of independent evolution of neurons and, as corollary, a parallel evolution of synapses. We suggest that the formation of synaptic machinery might occur more than once over 600 million years of animal evolution. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Fractional Gaussian noise-enhanced information capacity of a nonlinear neuron model with binary signal input

NASA Astrophysics Data System (ADS)

Gao, Feng-Yin; Kang, Yan-Mei; Chen, Xi; Chen, Guanrong

2018-05-01

This paper reveals the effect of fractional Gaussian noise with Hurst exponent H ∈(1 /2 ,1 ) on the information capacity of a general nonlinear neuron model with binary signal input. The fGn and its corresponding fractional Brownian motion exhibit long-range, strong-dependent increments. It extends standard Brownian motion to many types of fractional processes found in nature, such as the synaptic noise. In the paper, for the subthreshold binary signal, sufficient conditions are given based on the "forbidden interval" theorem to guarantee the occurrence of stochastic resonance, while for the suprathreshold binary signal, the simulated results show that additive fGn with Hurst exponent H ∈(1 /2 ,1 ) could increase the mutual information or bits count. The investigation indicated that the synaptic noise with the characters of long-range dependence and self-similarity might be the driving factor for the efficient encoding and decoding of the nervous system.

Neurons in the Primate Medial Basal Forebrain Signal Combined Information about Reward Uncertainty, Value, and Punishment Anticipation

PubMed Central

Leopold, David A.; Hikosaka, Okihide

2015-01-01

It has been suggested that the basal forebrain (BF) exerts strong influences on the formation of memory and behavior. However, what information is used for the memory-behavior formation is unclear. We found that a population of neurons in the medial BF (medial septum and diagonal band of Broca) of macaque monkeys encodes a unique combination of information: reward uncertainty, expected reward value, anticipation of punishment, and unexpected reward and punishment. The results were obtained while the monkeys were expecting (often with uncertainty) a rewarding or punishing outcome during a Pavlovian procedure, or unexpectedly received an outcome outside the procedure. In vivo anterograde tracing using manganese-enhanced MRI suggested that the major recipient of these signals is the intermediate hippocampal formation. Based on these findings, we hypothesize that the medial BF identifies various contexts and outcomes that are critical for memory processing in the hippocampal formation. PMID:25972172

Relaxation oscillator-realized artificial electronic neurons, their responses, and noise

NASA Astrophysics Data System (ADS)

Lim, Hyungkwang; Ahn, Hyung-Woo; Kornijcuk, Vladimir; Kim, Guhyun; Seok, Jun Yeong; Kim, Inho; Hwang, Cheol Seong; Jeong, Doo Seok

2016-05-01

A proof-of-concept relaxation oscillator-based leaky integrate-and-fire (ROLIF) neuron circuit is realized by using an amorphous chalcogenide-based threshold switch and non-ideal operational amplifier (op-amp). The proposed ROLIF neuron offers biologically plausible features such as analog-type encoding, signal amplification, unidirectional synaptic transmission, and Poisson noise. The synaptic transmission between pre- and postsynaptic neurons is achieved through a passive synapse (simple resistor). The synaptic resistor coupled to the non-ideal op-amp realizes excitatory postsynaptic potential (EPSP) evolution that evokes postsynaptic neuron spiking. In an attempt to generalize our proposed model, we theoretically examine ROLIF neuron circuits adopting different non-ideal op-amps having different gains and slew rates. The simulation results indicate the importance of gain in postsynaptic neuron spiking, irrespective of the slew rate (as long as the rate exceeds a particular value), providing the basis for the ROLIF neuron circuit design. Eventually, the behavior of a postsynaptic neuron in connection to multiple presynaptic neurons via synapses is highlighted in terms of EPSP evolution amid simultaneously incident asynchronous presynaptic spikes, which in fact reveals an important role of the random noise in spatial integration.A proof-of-concept relaxation oscillator-based leaky integrate-and-fire (ROLIF) neuron circuit is realized by using an amorphous chalcogenide-based threshold switch and non-ideal operational amplifier (op-amp). The proposed ROLIF neuron offers biologically plausible features such as analog-type encoding, signal amplification, unidirectional synaptic transmission, and Poisson noise. The synaptic transmission between pre- and postsynaptic neurons is achieved through a passive synapse (simple resistor). The synaptic resistor coupled to the non-ideal op-amp realizes excitatory postsynaptic potential (EPSP) evolution that evokes postsynaptic neuron spiking. In an attempt to generalize our proposed model, we theoretically examine ROLIF neuron circuits adopting different non-ideal op-amps having different gains and slew rates. The simulation results indicate the importance of gain in postsynaptic neuron spiking, irrespective of the slew rate (as long as the rate exceeds a particular value), providing the basis for the ROLIF neuron circuit design. Eventually, the behavior of a postsynaptic neuron in connection to multiple presynaptic neurons via synapses is highlighted in terms of EPSP evolution amid simultaneously incident asynchronous presynaptic spikes, which in fact reveals an important role of the random noise in spatial integration. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr01278g

Integration of multiple determinants in the neuronal computation of economic values.

PubMed

Raghuraman, Anantha P; Padoa-Schioppa, Camillo

2014-08-27

Economic goods may vary on multiple dimensions (determinants). A central conjecture in decision neuroscience is that choices between goods are made by comparing subjective values computed through the integration of all relevant determinants. Previous work identified three groups of neurons in the orbitofrontal cortex (OFC) of monkeys engaged in economic choices: (1) offer value cells, which encode the value of individual offers; (2) chosen value cells, which encode the value of the chosen good; and (3) chosen juice cells, which encode the identity of the chosen good. In principle, these populations could be sufficient to generate a decision. Critically, previous work did not assess whether offer value cells (the putative input to the decision) indeed encode subjective values as opposed to physical properties of the goods, and/or whether offer value cells integrate multiple determinants. To address these issues, we recorded from the OFC while monkeys chose between risky outcomes. Confirming previous observations, three populations of neurons encoded the value of individual offers, the value of the chosen option, and the value-independent choice outcome. The activity of both offer value cells and chosen value cells encoded values defined by the integration of juice quantity and probability. Furthermore, both populations reflected the subjective risk attitude of the animals. We also found additional groups of neurons encoding the risk associated with a particular option, the risky nature of the chosen option, and whether the trial outcome was positive or negative. These results provide substantial support for the conjecture described above and for the involvement of OFC in good-based decisions. Copyright © 2014 the authors 0270-6474/14/3311583-21$15.00/0.

Neuronal Correlation Parameter and the Idea of Thermodynamic Entropy of an N-Body Gravitationally Bounded System.

PubMed

Haranas, Ioannis; Gkigkitzis, Ioannis; Kotsireas, Ilias; Austerlitz, Carlos

2017-01-01

Understanding how the brain encodes information and performs computation requires statistical and functional analysis. Given the complexity of the human brain, simple methods that facilitate the interpretation of statistical correlations among different brain regions can be very useful. In this report we introduce a numerical correlation measure that may serve the interpretation of correlational neuronal data, and may assist in the evaluation of different brain states. The description of the dynamical brain system, through a global numerical measure may indicate the presence of an action principle which may facilitate a application of physics principles in the study of the human brain and cognition.

Contour Curvature As an Invariant Code for Objects in Visual Area V4

PubMed Central

Pasupathy, Anitha

2016-01-01

Size-invariant object recognition—the ability to recognize objects across transformations of scale—is a fundamental feature of biological and artificial vision. To investigate its basis in the primate cerebral cortex, we measured single neuron responses to stimuli of varying size in visual area V4, a cornerstone of the object-processing pathway, in rhesus monkeys (Macaca mulatta). Leveraging two competing models for how neuronal selectivity for the bounding contours of objects may depend on stimulus size, we show that most V4 neurons (∼70%) encode objects in a size-invariant manner, consistent with selectivity for a size-independent parameter of boundary form: for these neurons, “normalized” curvature, rather than “absolute” curvature, provided a better account of responses. Our results demonstrate the suitability of contour curvature as a basis for size-invariant object representation in the visual cortex, and posit V4 as a foundation for behaviorally relevant object codes. SIGNIFICANCE STATEMENT Size-invariant object recognition is a bedrock for many perceptual and cognitive functions. Despite growing neurophysiological evidence for invariant object representations in the primate cortex, we still lack a basic understanding of the encoding rules that govern them. Classic work in the field of visual shape theory has long postulated that a representation of objects based on information about their bounding contours is well suited to mediate such an invariant code. In this study, we provide the first empirical support for this hypothesis, and its instantiation in single neurons of visual area V4. PMID:27194333

Shared neural coding for social hierarchy and reward value in primate amygdala.

PubMed

Munuera, Jérôme; Rigotti, Mattia; Salzman, C Daniel

2018-03-01

The social brain hypothesis posits that dedicated neural systems process social information. In support of this, neurophysiological data have shown that some brain regions are specialized for representing faces. It remains unknown, however, whether distinct anatomical substrates also represent more complex social variables, such as the hierarchical rank of individuals within a social group. Here we show that the primate amygdala encodes the hierarchical rank of individuals in the same neuronal ensembles that encode the rewards associated with nonsocial stimuli. By contrast, orbitofrontal and anterior cingulate cortices lack strong representations of hierarchical rank while still representing reward values. These results challenge the conventional view that dedicated neural systems process social information. Instead, information about hierarchical rank-which contributes to the assessment of the social value of individuals within a group-is linked in the amygdala to representations of rewards associated with nonsocial stimuli.

Artificial hair cell integrated with an artificial neuron: Interplay between criticality and excitability

NASA Astrophysics Data System (ADS)

Lee, Woo Seok; Jeong, Wonhee; Ahn, Kang-Hun

2014-12-01

We provide a simple dynamical model of a hair cell with an afferent neuron where the spectral and the temporal responses are controlled by the hair bundle's criticality and the neuron's excitability. To demonstrate that these parameters, indeed, specify the resolution of the sound encoding, we fabricate a neuromorphic device that models the hair cell bundle and its afferent neuron. Then, we show that the neural response of the biomimetic system encodes sounds with either high temporal or spectral resolution or with a combination of both resolutions. Our results suggest that the hair cells may easily specialize to fulfil various roles in spite of their similar physiological structures.

Catching the engram: strategies to examine the memory trace.

PubMed

Sakaguchi, Masanori; Hayashi, Yasunori

2012-09-21

Memories are stored within neuronal ensembles in the brain. Modern genetic techniques can be used to not only visualize specific neuronal ensembles that encode memories (e.g., fear, craving) but also to selectively manipulate those neurons. These techniques are now being expanded for the study of various types of memory. In this review, we will summarize the genetic methods used to visualize and manipulate neurons involved in the representation of memory engrams. The methods will help clarify how memory is encoded, stored and processed in the brain. Furthermore, these approaches may contribute to our understanding of the pathological mechanisms associated with human memory disorders and, ultimately, may aid the development of therapeutic strategies to ameliorate these diseases.

Photoreceptive oscillators within neurons of the premammillary nucleus (PMM) and seasonal reproduction in temperate zone birds.

PubMed

Kosonsiriluk, Sunantha; Mauro, Laura J; Chaiworakul, Voravasa; Chaiseha, Yupaporn; El Halawani, Mohamed E

2013-09-01

The pathway for light transmission regulating the reproductive neuroendocrine system in temperate zone birds remains elusive. Based on the evidence provided from our studies with female turkeys, it is suggested that the circadian clock regulating reproductive seasonality is located in putatively photosensitive dopamine-melatonin (DA-MEL) neurons residing in the premammillary nucleus (PMM) of the caudal hypothalamus. Melanopsin is expressed by these neurons; a known photopigment which mediates light information pertaining to the entrainment of the clock. Exposure to a gonad stimulatory photoperiod enhances the activity of the DAergic system within DA-MEL neurons. DAergic activity encoding the light information is transmitted to the pars tuberalis, where thyroid-stimulating hormone, beta (TSHβ) cells reside, and induces the release of TSH. TSH stimulates tanycytes lining the base of the third ventricle and activates type 2 deiodinase in the ependymal which enhances triiodothyronine (T3) synthesis. T3 facilitates the release of gonadotropin-releasing hormone-I which stimulates luteinizing hormone/follicle stimulating hormone release and gonad recrudescence. These data taken together with the findings that clock genes are rhythmically expressed in the PMM where DA-MEL neurons are localized imply that endogenous oscillators containing photoreceptors within DA-MEL neurons are important in regulating the DA and MEL rhythms that drive the circadian cycle controlling seasonal reproduction. Published by Elsevier Inc.

Coding of odors by temporal binding within a model network of the locust antennal lobe.

PubMed

Patel, Mainak J; Rangan, Aaditya V; Cai, David

2013-01-01

The locust olfactory system interfaces with the external world through antennal receptor neurons (ORNs), which represent odors in a distributed, combinatorial manner. ORN axons bundle together to form the antennal nerve, which relays sensory information centrally to the antennal lobe (AL). Within the AL, an odor generates a dynamically evolving ensemble of active cells, leading to a stimulus-specific temporal progression of neuronal spiking. This experimental observation has led to the hypothesis that an odor is encoded within the AL by a dynamically evolving trajectory of projection neuron (PN) activity that can be decoded piecewise to ascertain odor identity. In order to study information coding within the locust AL, we developed a scaled-down model of the locust AL using Hodgkin-Huxley-type neurons and biologically realistic connectivity parameters and current components. Using our model, we examined correlations in the precise timing of spikes across multiple neurons, and our results suggest an alternative to the dynamic trajectory hypothesis. We propose that the dynamical interplay of fast and slow inhibition within the locust AL induces temporally stable correlations in the spiking activity of an odor-dependent neural subset, giving rise to a temporal binding code that allows rapid stimulus detection by downstream elements.

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.

Hormonal gain control of a medial preoptic area social reward circuit

PubMed Central

McHenry, Jenna A.; Otis, James M.; Rossi, Mark A.; Robinson, J. Elliott; Kosyk, Oksana; Miller, Noah W.; McElligott, Zoe A.; Budygin, Evgeny A.; Rubinow, David R.; Stuber, Garret D.

2017-01-01

Neural networks that control reproduction must integrate social and hormonal signals, tune motivation, and invigorate social interactions. However, the neurocircuit mechanisms for these processes remain unresolved. The medial preoptic area (mPOA), an essential node for social behaviors and is comprised of molecularly-diverse neurons with widespread projections. Here, we identify a steroid-responsive subset of neurotensin (Nts) expressing mPOA neurons that interface with the ventral tegmental area (VTA) to form a socially-engaged reward circuit. Using in vivo 2-photon imaging in female mice, we show that mPOANts neurons preferentially encode attractive male cues compared to non-social appetitive stimuli. Ovarian hormone signals regulate both the physiological and cue encoding properties of these cells. Furthermore, optogenetic stimulation of mPOANts-VTA circuitry promotes rewarding phenotypes, social approach, and striatal dopamine release. Collectively, these data demonstrate that steroid-sensitive mPOA neurons encode ethologically-relevant stimuli and co-opt midbrain reward circuits to promote prosocial behavior critical for species survival. PMID:28135243

Neurons in the human amygdala selective for perceived emotion

PubMed Central

Wang, Shuo; Tudusciuc, Oana; Mamelak, Adam N.; Ross, Ian B.; Adolphs, Ralph; Rutishauser, Ueli

2014-01-01

The human amygdala plays a key role in recognizing facial emotions and neurons in the monkey and human amygdala respond to the emotional expression of faces. However, it remains unknown whether these responses are driven primarily by properties of the stimulus or by the perceptual judgments of the perceiver. We investigated these questions by recording from over 200 single neurons in the amygdalae of 7 neurosurgical patients with implanted depth electrodes. We presented degraded fear and happy faces and asked subjects to discriminate their emotion by button press. During trials where subjects responded correctly, we found neurons that distinguished fear vs. happy emotions as expressed by the displayed faces. During incorrect trials, these neurons indicated the patients’ subjective judgment. Additional analysis revealed that, on average, all neuronal responses were modulated most by increases or decreases in response to happy faces, and driven predominantly by judgments about the eye region of the face stimuli. Following the same analyses, we showed that hippocampal neurons, unlike amygdala neurons, only encoded emotions but not subjective judgment. Our results suggest that the amygdala specifically encodes the subjective judgment of emotional faces, but that it plays less of a role in simply encoding aspects of the image array. The conscious percept of the emotion shown in a face may thus arise from interactions between the amygdala and its connections within a distributed cortical network, a scheme also consistent with the long response latencies observed in human amygdala recordings. PMID:24982200

Neuron Design in Neuromorphic Computing Systems and Its Application in Wireless Communications

DTIC Science & Technology

2017-03-01

0188 The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing...for data representation using hardware spike timing dependent encoding for neuromorphic processors; (b) explore the applications of neuromorphic...envisioned architecture will serve as the foundation for unprecedented capabilities in real- time applications such as the MIMO channel estimation that

Self-organization of globally continuous and locally distributed information representation.

PubMed

Wada, Koji; Kurata, Koji; Okada, Masato

2004-01-01

A number of findings suggest that the preferences of neighboring neurons in the inferior temporal (IT) cortex of macaque monkeys tend to be similar. However, a recent study reports convincingly that the preferences of neighboring neurons actually differ. These findings seem contradictory. To explain this conflict, we propose a new view of information representation in the IT cortex. This view takes into account sparse and local neuronal excitation. Since the excitation is sparse, information regarding visual objects seems to be encoded in a distributed manner. The local excitation of neurons coincides with the classical notion of a column structure. Our model consists of input layer and output layer. The main difference from conventional models is that the output layer has local and random intra-layer connections. In this paper, we adopt two rings embedded in three-dimensional space as an input signal space, and examine how resultant information representation depends on the distance between two rings that is denoted as D. We show that there exists critical value for the distance Dc. When D > Dc the output layer becomes able to form the column structure, this model can obtain the distributed representation within the column. While the output layer acquires the conventional information representation observed in the V1 cortex when D < Dc. Moreover, we consider the origin of the difference between information representation of the V1 cortex and that of the IT cortex. Our finding suggests that the difference in the information representations between the V1 and the IT cortices could be caused by difference between the input space structures.

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.

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.

Neurons and Objects: The Case of Auditory Cortex

PubMed Central

Nelken, Israel; Bar-Yosef, Omer

2008-01-01

Sounds are encoded into electrical activity in the inner ear, where they are represented (roughly) as patterns of energy in narrow frequency bands. However, sounds are perceived in terms of their high-order properties. It is generally believed that this transformation is performed along the auditory hierarchy, with low-level physical cues computed at early stages of the auditory system and high-level abstract qualities at high-order cortical areas. The functional position of primary auditory cortex (A1) in this scheme is unclear – is it ‘early’, encoding physical cues, or is it ‘late’, already encoding abstract qualities? Here we argue that neurons in cat A1 show sensitivity to high-level features of sounds. In particular, these neurons may already show sensitivity to ‘auditory objects’. The evidence for this claim comes from studies in which individual sounds are presented singly and in mixtures. Many neurons in cat A1 respond to mixtures in the same way they respond to one of the individual components of the mixture, and in many cases neurons may respond to a low-level component of the mixture rather than to the acoustically dominant one, even though the same neurons respond to the acoustically-dominant component when presented alone. PMID:18982113

Encoding of the amplitude modulation of pulsatile electrical stimulation in the feline cochlear nucleus by neurons in the inferior colliculus; effects of stimulus pulse rate

NASA Astrophysics Data System (ADS)

McCreery, Douglas; Han, Martin; Pikov, Victor; Yadav, Kamal; Pannu, Satinderpall

2013-10-01

Objectives. Persons without a functional auditory nerve cannot benefit from cochlear implants, but some hearing can be restored by an auditory brainstem implant (ABI) with stimulating electrodes implanted on the surface of the cochlear nucleus (CN). Most users benefit from their ABI, but speech recognition tends to be poorer than for users of cochlear implants. Psychophysical studies suggest that poor modulation detection may contribute to the limited performance of ABI users. In a cat model, we determined how the pulse rate of the electrical stimulus applied within or on the CN affects temporal and rate encoding of amplitude modulation (AM) by neurons in the central nucleus of the inferior colliculus (ICC). Approach. Stimulating microelectrodes were implanted chronically in and on the cats' CN, and multi-site recording microelectrodes were implanted chronically into the ICC. Encoding of AM pulse trains by neurons in the ICC was characterized as vector strength (VS), the synchrony of neural activity with the AM, and as the mean rate of neuronal action potentials (neuronal spike rate (NSR)). Main results. For intranuclear microstimulation, encoding of AM as VS was up to 3 dB greater when stimulus pulse rate was increased from 250 to 500 pps, but only for neuronal units with low best acoustic frequencies, and when the electrical stimulation was modulated at low frequencies (10-20 Hz). For stimulation on the surface of the CN, VS was similar at 250 and 500 pps, and the dynamic range of the VS was reduced for pulse rates greater than 250 pps. Modulation depth was encoded strongly as VS when the maximum stimulus amplitude was held constant across a range of modulation depth. This ‘constant maximum’ protocol allows enhancement of modulation depth while preserving overall dynamic range. However, modulation depth was not encoded as strongly as NSR. Significance. The findings have implications for improved sound processors for present and future ABIs. The performance of ABIs may benefit from using pulse rates greater than those presently used in most ABIs, and by sound processing strategies that enhance the modulation depth of the electrical stimulus while preserving dynamic range.

Frank Beach Award Winner: Steroids as Neuromodulators of Brain Circuits and Behavior

PubMed Central

Remage-Healey, Luke

2014-01-01

Neurons communicate primarily via action potentials that transmit information on the timescale of milliseconds. Neurons also integrate information via alterations in gene transcription and protein translation that are sustained for hours to days after initiation. Positioned between these two signaling timescales are the minute-by-minute actions of neuromodulators. Over the course of minutes, the classical neuromodulators (such as serotonin, dopamine, octopamine, and norepinephrine) can alter and/or stabilize neural circuit patterning as well as behavioral states. Neuromodulators allow many flexible outputs from neural circuits and can encode information content into the firing state of neural networks. The idea that steroid molecules can operate as genuine behavioral neuromodulators - synthesized by and acting within brain circuits on a minute-by-minute timescale - has gained traction in recent years. Evidence for brain steroid synthesis at synaptic terminals has converged with evidence for the rapid actions of brain-derived steroids on neural circuits and behavior. The general principle emerging from this work is that the production of steroid hormones within brain circuits can alter their functional connectivity and shift sensory representations by enhancing their information coding. Steroids produced in the brain can therefore change the information content of neuronal networks to rapidly modulate sensory experience and sensorimotor functions. PMID:25110187

Locus coeruleus and dopaminergic consolidation of everyday memory

PubMed Central

Takeuchi, Tomonori; Duszkiewicz, Adrian J.; Sonneborn, Alex; Spooner, Patrick A.; Yamasaki, Miwako; Watanabe, Masahiko; Smith, Caroline C.; Fernández, Guillén; Deisseroth, Karl; Greene, Robert W.; Morris, Richard G. M.

2016-01-01

Summary The retention of episodic-like memory is enhanced, in humans and animals, when something novel happens shortly before or after encoding. Using an everyday memory task in mice, we sought the neurons mediating this dopamine-dependent novelty effect, previously thought to originate exclusively from the tyrosine hydroxylase-expressing (TH+) neurons in the ventral tegmental area (VTA). We report that neuronal firing in the locus coeruleus (LC) is especially sensitive to environmental novelty, LC-TH+ neurons project more profusely than VTA-TH+ neurons to the hippocampus, optogenetic activation of LC-TH+ neurons mimics the novelty effect, and this novelty-associated memory enhancement is unaffected by VTA inactivation. Surprisingly, two effects of LC-TH+ photoactivation are sensitive to hippocampal D1/D5 receptor blockade and resistant to adrenoceptors blockade – memory enhancement and long lasting potentiation of synaptic transmission in CA1 ex vivo. Thus, LC-TH+ neurons can mediate post-encoding memory enhancement in a manner consistent with possible co-release of dopamine in hippocampus. PMID:27602521

Locus coeruleus and dopaminergic consolidation of everyday memory.

PubMed

Takeuchi, Tomonori; Duszkiewicz, Adrian J; Sonneborn, Alex; Spooner, Patrick A; Yamasaki, Miwako; Watanabe, Masahiko; Smith, Caroline C; Fernández, Guillén; Deisseroth, Karl; Greene, Robert W; Morris, Richard G M

2016-09-15

The retention of episodic-like memory is enhanced, in humans and animals, when something novel happens shortly before or after encoding. Using an everyday memory task in mice, we sought the neurons mediating this dopamine-dependent novelty effect, previously thought to originate exclusively from the tyrosine-hydroxylase-expressing (TH + ) neurons in the ventral tegmental area. Here we report that neuronal firing in the locus coeruleus is especially sensitive to environmental novelty, locus coeruleus TH + neurons project more profusely than ventral tegmental area TH + neurons to the hippocampus, optogenetic activation of locus coeruleus TH + neurons mimics the novelty effect, and this novelty-associated memory enhancement is unaffected by ventral tegmental area inactivation. Surprisingly, two effects of locus coeruleus TH + photoactivation are sensitive to hippocampal D 1 /D 5 receptor blockade and resistant to adrenoceptor blockade: memory enhancement and long-lasting potentiation of synaptic transmission in CA1 ex vivo. Thus, locus coeruleus TH + neurons can mediate post-encoding memory enhancement in a manner consistent with possible co-release of dopamine in the hippocampus.

Closing the Loop for Memory Prostheses: Detecting the Role of Hippocampal Neural Ensembles Using Nonlinear Models

PubMed Central

Hampson, Robert E.; Song, Dong; Chan, Rosa H.M.; Sweatt, Andrew J.; Riley, Mitchell R.; Goonawardena, Anushka V.; Marmarelis, Vasilis Z.; Gerhardt, Greg A.; Berger, Theodore W.; Deadwyler, Sam A.

2012-01-01

A major factor involved in providing closed loop feedback for control of neural function is to understand how neural ensembles encode online information critical to the final behavioral endpoint. This issue was directly assessed in rats performing a short-term delay memory task in which successful encoding of task information is dependent upon specific spatiotemporal firing patterns recorded from ensembles of CA3 and CA1 hippocampal neurons. Such patterns, extracted by a specially designed nonlinear multi-input multi-output (MIMO) nonlinear mathematical model, were used to predict successful performance online via a closed loop paradigm which regulated trial difficulty (time of retention) as a function of the “strength” of stimulus encoding. The significance of the MIMO model as a neural prosthesis has been demonstrated by substituting trains of electrical stimulation pulses to mimic these same ensemble firing patterns. This feature was used repeatedly to vary “normal” encoding as a means of understanding how neural ensembles can be “tuned” to mimic the inherent process of selecting codes of different strength and functional specificity. The capacity to enhance and tune hippocampal encoding via MIMO model detection and insertion of critical ensemble firing patterns shown here provides the basis for possible extension to other disrupted brain circuitry. PMID:22498704

Facilitation of memory encoding in primate hippocampus by a neuroprosthesis that promotes task-specific neural firing

NASA Astrophysics Data System (ADS)

Hampson, Robert E.; Song, Dong; Opris, Ioan; Santos, Lucas M.; Shin, Dae C.; Gerhardt, Greg A.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.

2013-12-01

Objective. Memory accuracy is a major problem in human disease and is the primary factor that defines Alzheimer’s, ageing and dementia resulting from impaired hippocampal function in the medial temporal lobe. Development of a hippocampal memory neuroprosthesis that facilitates normal memory encoding in nonhuman primates (NHPs) could provide the basis for improving memory in human disease states. Approach. NHPs trained to perform a short-term delayed match-to-sample (DMS) memory task were examined with multi-neuron recordings from synaptically connected hippocampal cell fields, CA1 and CA3. Recordings were analyzed utilizing a previously developed nonlinear multi-input multi-output (MIMO) neuroprosthetic model, capable of extracting CA3-to-CA1 spatiotemporal firing patterns during DMS performance. Main results. The MIMO model verified that specific CA3-to-CA1 firing patterns were critical for the successful encoding of sample phase information on more difficult DMS trials. This was validated by the delivery of successful MIMO-derived encoding patterns via electrical stimulation to the same CA1 recording locations during the sample phase which facilitated task performance in the subsequent, delayed match phase, on difficult trials that required more precise encoding of sample information. Significance. These findings provide the first successful application of a neuroprosthesis designed to enhance and/or repair memory encoding in primate brain.

Facilitation of Memory Encoding in Primate Hippocampus by a Neuroprosthesis that Promotes Task Specific Neural Firing

PubMed Central

Hampson, Robert E.; Song, Dong; Opris, Ioan; Santos, Lucas M.; Shin, Dae C.; Gerhardt, Greg A.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.

2014-01-01

Objective Memory accuracy is a major problem in human disease and is the primary factor that defines Alzheimer’s’, aging and dementia resulting from impaired hippocampal function in medial temporal lobe. Development of a hippocampal memory neuroprosthesis that facilitates normal memory encoding in nonhuman primates (NHPs) could provide the basis for improving memory in human disease states. Approach NHPs trained to perform a short-term delayed match to sample (DMS) memory task were examined with multi-neuron recordings from synaptically connected hippocampal cell fields, CA1 and CA3. Recordings were analyzed utilizing a previously developed nonlinear multi-input multi-output (MIMO) neuroprosthetic model, capable of extracting CA3-to-CA1 spatiotemporal firing patterns during DMS performance. Main Results The MIMO model verified that specific CA3-to-CA1 firing patterns were critical for successful encoding of Sample phase information on more difficult DMS trials. This was validated by delivery of successful MIMO-derived encoding patterns via electrical stimulation to the same CA1 recording locations during the Sample phase which facilitated task performance in the subsequent delayed Match phase on difficult trials that required more precise encoding of Sample information. Significance These findings provide the first successful application of a neuroprosthesis designed to enhance and/or repair memory encoding in primate brain. PMID:24216292

Bayesian Ising approximation for learning dictionaries of multispike timing patterns in premotor neurons

NASA Astrophysics Data System (ADS)

Hernandez Lahme, Damian; Sober, Samuel; Nemenman, Ilya

Important questions in computational neuroscience are whether, how much, and how information is encoded in the precise timing of neural action potentials. We recently demonstrated that, in the premotor cortex during vocal control in songbirds, spike timing is far more informative about upcoming behavior than is spike rate (Tang et al, 2014). However, identification of complete dictionaries that relate spike timing patterns with the controled behavior remains an elusive problem. Here we present a computational approach to deciphering such codes for individual neurons in the songbird premotor area RA, an analog of mammalian primary motor cortex. Specifically, we analyze which multispike patterns of neural activity predict features of the upcoming vocalization, and hence are important codewords. We use a recently introduced Bayesian Ising Approximation, which properly accounts for the fact that many codewords overlap and hence are not independent. Our results show which complex, temporally precise multispike combinations are used by individual neurons to control acoustic features of the produced song, and that these code words are different across individual neurons and across different acoustic features. This work was supported, in part, by JSMF Grant 220020321, NSF Grant 1208126, NIH Grant NS084844 and NIH Grant 1 R01 EB022872.

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.

Correlated variability modifies working memory fidelity in primate prefrontal neuronal ensembles

PubMed Central

Leavitt, Matthew L.; Pieper, Florian; Sachs, Adam J.; Martinez-Trujillo, Julio C.

2017-01-01

Neurons in the primate lateral prefrontal cortex (LPFC) encode working memory (WM) representations via sustained firing, a phenomenon hypothesized to arise from recurrent dynamics within ensembles of interconnected neurons. Here, we tested this hypothesis by using microelectrode arrays to examine spike count correlations (rsc) in LPFC neuronal ensembles during a spatial WM task. We found a pattern of pairwise rsc during WM maintenance indicative of stronger coupling between similarly tuned neurons and increased inhibition between dissimilarly tuned neurons. We then used a linear decoder to quantify the effects of the high-dimensional rsc structure on information coding in the neuronal ensembles. We found that the rsc structure could facilitate or impair coding, depending on the size of the ensemble and tuning properties of its constituent neurons. A simple optimization procedure demonstrated that near-maximum decoding performance could be achieved using a relatively small number of neurons. These WM-optimized subensembles were more signal correlation (rsignal)-diverse and anatomically dispersed than predicted by the statistics of the full recorded population of neurons, and they often contained neurons that were poorly WM-selective, yet enhanced coding fidelity by shaping the ensemble’s rsc structure. We observed a pattern of rsc between LPFC neurons indicative of recurrent dynamics as a mechanism for WM-related activity and that the rsc structure can increase the fidelity of WM representations. Thus, WM coding in LPFC neuronal ensembles arises from a complex synergy between single neuron coding properties and multidimensional, ensemble-level phenomena. PMID:28275096

Histamine Enhances Theta-Coupled Spiking and Gamma Oscillations in the Medial Entorhinal Cortex Consistent With Successful Spatial Recognition.

PubMed

Chen, Quanhui; Luo, Fenlan; Yue, Faguo; Xia, Jianxia; Xiao, Qin; Liao, Xiang; Jiang, Jun; Zhang, Jun; Hu, Bo; Gao, Dong; He, Chao; Hu, Zhian

2017-06-07

Encoding of spatial information in the superficial layers of the medial entorhinal cortex (sMEC) involves theta-modulated spiking and gamma oscillations, as well as spatially tuned grid cells and border cells. Little is known about the role of the arousal-promoting histaminergic system in the modification of information encoded in the sMEC in vivo, and how such histamine-regulated information correlates with behavioral functions. Here, we show that histamine upregulates the neural excitability of a significant proportion of neurons (16.32%, 39.18%, and 52.94% at 30 μM, 300 μM, and 3 mM, respectively) and increases local theta (4-12 Hz) and gamma power (low: 25-48 Hz; high: 60-120 Hz) in the sMEC, through activation of histamine receptor types 1 and 3. During spatial exploration, the strength of theta-modulated firing of putative principal neurons and high gamma oscillations is enhanced about 2-fold by histamine. The histamine-mediated increase of theta phase-locking of spikes and high gamma power is consistent with successful spatial recognition. These results, for the first time, reveal possible mechanisms involving the arousal-promoting histaminergic system in the modulation of spatial cognition. Published by Oxford University Press 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

A cascade model of information processing and encoding for retinal prosthesis.

PubMed

Pei, Zhi-Jun; Gao, Guan-Xin; Hao, Bo; Qiao, Qing-Li; Ai, Hui-Jian

2016-04-01

Retinal prosthesis offers a potential treatment for individuals suffering from photoreceptor degeneration diseases. Establishing biological retinal models and simulating how the biological retina convert incoming light signal into spike trains that can be properly decoded by the brain is a key issue. Some retinal models have been presented, ranking from structural models inspired by the layered architecture to functional models originated from a set of specific physiological phenomena. However, Most of these focus on stimulus image compression, edge detection and reconstruction, but do not generate spike trains corresponding to visual image. In this study, based on state-of-the-art retinal physiological mechanism, including effective visual information extraction, static nonlinear rectification of biological systems and neurons Poisson coding, a cascade model of the retina including the out plexiform layer for information processing and the inner plexiform layer for information encoding was brought forward, which integrates both anatomic connections and functional computations of retina. Using MATLAB software, spike trains corresponding to stimulus image were numerically computed by four steps: linear spatiotemporal filtering, static nonlinear rectification, radial sampling and then Poisson spike generation. The simulated results suggested that such a cascade model could recreate visual information processing and encoding functionalities of the retina, which is helpful in developing artificial retina for the retinally blind.

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

Circuit variability interacts with excitatory-inhibitory diversity of interneurons to regulate network encoding capacity.

PubMed

Tsai, Kuo-Ting; Hu, Chin-Kun; Li, Kuan-Wei; Hwang, Wen-Liang; Chou, Ya-Hui

2018-05-23

Local interneurons (LNs) in the Drosophila olfactory system exhibit neuronal diversity and variability, yet it is still unknown how these features impact information encoding capacity and reliability in a complex LN network. We employed two strategies to construct a diverse excitatory-inhibitory neural network beginning with a ring network structure and then introduced distinct types of inhibitory interneurons and circuit variability to the simulated network. The continuity of activity within the node ensemble (oscillation pattern) was used as a readout to describe the temporal dynamics of network activity. We found that inhibitory interneurons enhance the encoding capacity by protecting the network from extremely short activation periods when the network wiring complexity is very high. In addition, distinct types of interneurons have differential effects on encoding capacity and reliability. Circuit variability may enhance the encoding reliability, with or without compromising encoding capacity. Therefore, we have described how circuit variability of interneurons may interact with excitatory-inhibitory diversity to enhance the encoding capacity and distinguishability of neural networks. In this work, we evaluate the effects of different types and degrees of connection diversity on a ring model, which may simulate interneuron networks in the Drosophila olfactory system or other biological systems.

Unique processing during a period of high excitation/inhibition balance in adult-born neurons.

PubMed

Marín-Burgin, Antonia; Mongiat, Lucas A; Pardi, M Belén; Schinder, Alejandro F

2012-03-09

The adult dentate gyrus generates new granule cells (GCs) that develop over several weeks and integrate into the preexisting network. Although adult hippocampal neurogenesis has been implicated in learning and memory, the specific role of new GCs remains unclear. We examined whether immature adult-born neurons contribute to information encoding. By combining calcium imaging and electrophysiology in acute slices, we found that weak afferent activity recruits few mature GCs while activating a substantial proportion of the immature neurons. These different activation thresholds are dictated by an enhanced excitation/inhibition balance transiently expressed in immature GCs. Immature GCs exhibit low input specificity that switches with time toward a highly specific responsiveness. Therefore, activity patterns entering the dentate gyrus can undergo differential decoding by a heterogeneous population of GCs originated at different times.

Roles for Coincidence Detection in Coding Amplitude-Modulated Sounds

PubMed Central

Ashida, Go; Kretzberg, Jutta; Tollin, Daniel J.

2016-01-01

Many sensory neurons encode temporal information by detecting coincident arrivals of synaptic inputs. In the mammalian auditory brainstem, binaural neurons of the medial superior olive (MSO) are known to act as coincidence detectors, whereas in the lateral superior olive (LSO) roles of coincidence detection have remained unclear. LSO neurons receive excitatory and inhibitory inputs driven by ipsilateral and contralateral acoustic stimuli, respectively, and vary their output spike rates according to interaural level differences. In addition, LSO neurons are also sensitive to binaural phase differences of low-frequency tones and envelopes of amplitude-modulated (AM) sounds. Previous physiological recordings in vivo found considerable variations in monaural AM-tuning across neurons. To investigate the underlying mechanisms of the observed temporal tuning properties of LSO and their sources of variability, we used a simple coincidence counting model and examined how specific parameters of coincidence detection affect monaural and binaural AM coding. Spike rates and phase-locking of evoked excitatory and spontaneous inhibitory inputs had only minor effects on LSO output to monaural AM inputs. In contrast, the coincidence threshold of the model neuron affected both the overall spike rates and the half-peak positions of the AM-tuning curve, whereas the width of the coincidence window merely influenced the output spike rates. The duration of the refractory period affected only the low-frequency portion of the monaural AM-tuning curve. Unlike monaural AM coding, temporal factors, such as the coincidence window and the effective duration of inhibition, played a major role in determining the trough positions of simulated binaural phase-response curves. In addition, empirically-observed level-dependence of binaural phase-coding was reproduced in the framework of our minimalistic coincidence counting model. These modeling results suggest that coincidence detection of excitatory and inhibitory synaptic inputs is essential for LSO neurons to encode both monaural and binaural AM sounds. PMID:27322612

Measuring Fisher Information Accurately in Correlated Neural Populations

PubMed Central

Kohn, Adam; Pouget, Alexandre

2015-01-01

Neural responses are known to be variable. In order to understand how this neural variability constrains behavioral performance, we need to be able to measure the reliability with which a sensory stimulus is encoded in a given population. However, such measures are challenging for two reasons: First, they must take into account noise correlations which can have a large influence on reliability. Second, they need to be as efficient as possible, since the number of trials available in a set of neural recording is usually limited by experimental constraints. Traditionally, cross-validated decoding has been used as a reliability measure, but it only provides a lower bound on reliability and underestimates reliability substantially in small datasets. We show that, if the number of trials per condition is larger than the number of neurons, there is an alternative, direct estimate of reliability which consistently leads to smaller errors and is much faster to compute. The superior performance of the direct estimator is evident both for simulated data and for neuronal population recordings from macaque primary visual cortex. Furthermore we propose generalizations of the direct estimator which measure changes in stimulus encoding across conditions and the impact of correlations on encoding and decoding, typically denoted by Ishuffle and Idiag respectively. PMID:26030735

A new optimized GA-RBF neural network algorithm.

PubMed

Jia, Weikuan; Zhao, Dean; Shen, Tian; Su, Chunyang; Hu, Chanli; Zhao, Yuyan

2014-01-01

When confronting the complex problems, radial basis function (RBF) neural network has the advantages of adaptive and self-learning ability, but it is difficult to determine the number of hidden layer neurons, and the weights learning ability from hidden layer to the output layer is low; these deficiencies easily lead to decreasing learning ability and recognition precision. Aiming at this problem, we propose a new optimized RBF neural network algorithm based on genetic algorithm (GA-RBF algorithm), which uses genetic algorithm to optimize the weights and structure of RBF neural network; it chooses new ways of hybrid encoding and optimizing simultaneously. Using the binary encoding encodes the number of the hidden layer's neurons and using real encoding encodes the connection weights. Hidden layer neurons number and connection weights are optimized simultaneously in the new algorithm. However, the connection weights optimization is not complete; we need to use least mean square (LMS) algorithm for further leaning, and finally get a new algorithm model. Using two UCI standard data sets to test the new algorithm, the results show that the new algorithm improves the operating efficiency in dealing with complex problems and also improves the recognition precision, which proves that the new algorithm is valid.

Molecular and Cellular Mechanisms for Trapping and Activating Emotional Memories

PubMed Central

Cai, Denise J.; Sano, Yoshitake; Lee, Yong-Seok; Zhou, Yu; Bekal, Pallavi; Deisseroth, Karl; Silva, Alcino J.

2016-01-01

Recent findings suggest that memory allocation to specific neurons (i.e., neuronal allocation) in the amygdala is not random, but rather the transcription factor cAMP-response element binding protein (CREB) modulates this process, perhaps by regulating the transcription of channels that control neuronal excitability. Here, optogenetic studies in the mouse lateral amygdala (LA) were used to demonstrate that CREB and neuronal excitability regulate which neurons encode an emotional memory. To test the role of CREB in memory allocation, we overexpressed CREB in the lateral amygdala to recruit the encoding of an auditory-fear conditioning (AFC) memory to a subset of neurons. Then, post-training activation of these neurons with Channelrhodopsin-2 was sufficient to trigger recall of the memory for AFC, suggesting that CREB regulates memory allocation. To test the role of neuronal excitability in memory allocation, we used a step function opsin (SFO) to transiently increase neuronal excitability in a subset of LA neurons during AFC. Post-training activation of these neurons with Volvox Channelrhodopsin-1 was able to trigger recall of that memory. Importantly, our studies show that activation of the SFO did not affect AFC by either increasing anxiety or by strengthening the unconditioned stimulus. Our findings strongly support the hypothesis that CREB regulates memory allocation by modulating neuronal excitability. PMID:27579481

Catching the engram: strategies to examine the memory trace

PubMed Central

2012-01-01

Memories are stored within neuronal ensembles in the brain. Modern genetic techniques can be used to not only visualize specific neuronal ensembles that encode memories (e.g., fear, craving) but also to selectively manipulate those neurons. These techniques are now being expanded for the study of various types of memory. In this review, we will summarize the genetic methods used to visualize and manipulate neurons involved in the representation of memory engrams. The methods will help clarify how memory is encoded, stored and processed in the brain. Furthermore, these approaches may contribute to our understanding of the pathological mechanisms associated with human memory disorders and, ultimately, may aid the development of therapeutic strategies to ameliorate these diseases. PMID:22999350

Neurons in the human amygdala encode face identity, but not gaze direction.

PubMed

Mormann, Florian; Niediek, Johannes; Tudusciuc, Oana; Quesada, Carlos M; Coenen, Volker A; Elger, Christian E; Adolphs, Ralph

2015-11-01

The amygdala is important for face processing, and direction of eye gaze is one of the most socially salient facial signals. Recording from over 200 neurons in the amygdala of neurosurgical patients, we found robust encoding of the identity of neutral-expression faces, but not of their direction of gaze. Processing of gaze direction may rely on a predominantly cortical network rather than the amygdala.

Genetically Encoded Voltage Indicators: Opportunities and Challenges.

PubMed

Yang, Helen H; St-Pierre, François

2016-09-28

A longstanding goal in neuroscience is to understand how spatiotemporal patterns of neuronal electrical activity underlie brain function, from sensory representations to decision making. An emerging technology for monitoring electrical dynamics, voltage imaging using genetically encoded voltage indicators (GEVIs), couples the power of genetics with the advantages of light. Here, we review the properties that determine indicator performance and applicability, discussing both recent progress and technical limitations. We then consider GEVI applications, highlighting studies that have already deployed GEVIs for biological discovery. We also examine which classes of biological questions GEVIs are primed to address and which ones are beyond their current capabilities. As GEVIs are further developed, we anticipate that they will become more broadly used by the neuroscience community to eavesdrop on brain activity with unprecedented spatiotemporal resolution. Genetically encoded voltage indicators are engineered light-emitting protein sensors that typically report neuronal voltage dynamics as changes in brightness. In this review, we systematically discuss the current state of this emerging method, considering both its advantages and limitations for imaging neural activity. We also present recent applications of this technology and discuss what is feasible now and what we anticipate will become possible with future indicator development. This review will inform neuroscientists of recent progress in the field and help potential users critically evaluate the suitability of genetically encoded voltage indicator imaging to answer their specific biological questions. Copyright © 2016 the authors 0270-6474/16/369977-13$15.00/0.

Active Dentate Granule Cells Encode Experience to Promote the Addition of Adult-Born Hippocampal Neurons

PubMed Central

Kirschen, Gregory W.; Shen, Jia; Wang, Jia; Man, Guoming; Wu, Song

2017-01-01

The continuous addition of new dentate granule cells (DGCs), which is regulated exquisitely by brain activity, renders the hippocampus plastic. However, how neural circuits encode experiences to affect the addition of adult-born neurons remains unknown. Here, we used endoscopic Ca2+ imaging to track the real-time activity of individual DGCs in freely behaving mice. For the first time, we found that active DGCs responded to a novel experience by increasing their Ca2+ event frequency preferentially. This elevated activity, which we found to be associated with object exploration, returned to baseline by 1 h in the same environment, but could be dishabituated via introduction to a novel environment. To transition seamlessly between environments, we next established a freely controllable virtual reality system for unrestrained mice. We again observed increased firing of active neurons in a virtual enriched environment. Interestingly, multiple novel virtual experiences increased the number of newborn neurons accumulatively compared with a single experience. Finally, optogenetic silencing of existing DGCs during novel environmental exploration perturbed experience-induced neuronal addition. Our study shows that the adult brain conveys novel, enriched experiences to increase the addition of adult-born hippocampal neurons by increasing the firing of active DGCs. SIGNIFICANCE STATEMENT Adult brains are constantly reshaping themselves from synapses to circuits as we encounter novel experiences from moment to moment. Importantly, this reshaping includes the addition of newborn hippocampal neurons. However, it remains largely unknown how our circuits encode experience-induced brain activity to govern the addition of new hippocampal neurons. By coupling in vivo Ca2+ imaging of dentate granule neurons with a novel, unrestrained virtual reality system for rodents, we discovered that a new experience increased firing of active dentate granule neurons rapidly and robustly. Exploration in multiple novel virtual environments, compared with a single environment, promoted dentate activation and enhanced the addition of new hippocampal neurons accumulatively. Finally, silencing this activation optogenetically during novel experiences perturbed experience-induced neuronal addition. PMID:28373391

Bayesian population decoding of spiking neurons.

PubMed

Gerwinn, Sebastian; Macke, Jakob; Bethge, Matthias

2009-01-01

The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a 'spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

Impaired Dendritic Development and Memory in Sorbs2 Knock-Out Mice

PubMed Central

Zhang, Qiangge; Gao, Xian; Li, Chenchen; Feliciano, Catia; Wang, Dongqing; Zhou, Dingxi; Mei, Yuan; Monteiro, Patricia; Anand, Michelle; Itohara, Shigeyoshi; Dong, Xiaowei; Fu, Zhanyan

2016-01-01

Intellectual disability is a common neurodevelopmental disorder characterized by impaired intellectual and adaptive functioning. Both environmental insults and genetic defects contribute to the etiology of intellectual disability. Copy number variations of SORBS2 have been linked to intellectual disability. However, the neurobiological function of SORBS2 in the brain is unknown. The SORBS2 gene encodes ArgBP2 (Arg/c-Abl kinase binding protein 2) protein in non-neuronal tissues and is alternatively spliced in the brain to encode nArgBP2 protein. We found nArgBP2 colocalized with F-actin at dendritic spines and growth cones in cultured hippocampal neurons. In the mouse brain, nArgBP2 was highly expressed in the cortex, amygdala, and hippocampus, and enriched in the outer one-third of the molecular layer in dentate gyrus. Genetic deletion of Sorbs2 in mice led to reduced dendritic complexity and decreased frequency of AMPAR-miniature spontaneous EPSCs in dentate gyrus granule cells. Behavioral characterization revealed that Sorbs2 deletion led to a reduced acoustic startle response, and defective long-term object recognition memory and contextual fear memory. Together, our findings demonstrate, for the first time, an important role for nArgBP2 in neuronal dendritic development and excitatory synaptic transmission, which may thus inform exploration of neurobiological basis of SORBS2 deficiency in intellectual disability. SIGNIFICANCE STATEMENT Copy number variations of the SORBS2 gene are linked to intellectual disability, but the neurobiological mechanisms are unknown. We found that nArgBP2, the only neuronal isoform encoded by SORBS2, colocalizes with F-actin at neuronal dendritic growth cones and spines. nArgBP2 is highly expressed in the cortex, amygdala, and dentate gyrus in the mouse brain. Genetic deletion of Sorbs2 in mice leads to impaired dendritic complexity and reduced excitatory synaptic transmission in dentate gyrus granule cells, accompanied by behavioral deficits in acoustic startle response and long-term memory. This is the first study of Sorbs2 function in the brain, and our findings may facilitate the study of neurobiological mechanisms underlying SORBS2 deficiency in the development of intellectual disability. PMID:26888934

Neural Representation of a Target Auditory Memory in a Cortico-Basal Ganglia Pathway

PubMed Central

Bottjer, Sarah W.

2013-01-01

Vocal learning in songbirds, like speech acquisition in humans, entails a period of sensorimotor integration during which vocalizations are evaluated via auditory feedback and progressively refined to achieve an imitation of memorized vocal sounds. This process requires the brain to compare feedback of current vocal behavior to a memory of target vocal sounds. We report the discovery of two distinct populations of neurons in a cortico-basal ganglia circuit of juvenile songbirds (zebra finches, Taeniopygia guttata) during vocal learning: (1) one in which neurons are selectively tuned to memorized sounds and (2) another in which neurons are selectively tuned to self-produced vocalizations. These results suggest that neurons tuned to learned vocal sounds encode a memory of those target sounds, whereas neurons tuned to self-produced vocalizations encode a representation of current vocal sounds. The presence of neurons tuned to memorized sounds is limited to early stages of sensorimotor integration: after learning, the incidence of neurons encoding memorized vocal sounds was greatly diminished. In contrast to this circuit, neurons known to drive vocal behavior through a parallel cortico-basal ganglia pathway show little selective tuning until late in learning. One interpretation of these data is that representations of current and target vocal sounds in the shell circuit are used to compare ongoing patterns of vocal feedback to memorized sounds, whereas the parallel core circuit has a motor-related role in learning. Such a functional subdivision is similar to mammalian cortico-basal ganglia pathways in which associative-limbic circuits mediate goal-directed responses, whereas sensorimotor circuits support motor aspects of learning. PMID:24005299

Interaction Between Spatial and Feature Attention in Posterior Parietal Cortex

PubMed Central

Ibos, Guilhem; Freedman, David J.

2016-01-01

Summary Lateral intraparietal (LIP) neurons encode a vast array of sensory and cognitive variables. Recently, we proposed that the flexibility of feature representations in LIP reflect the bottom-up integration of sensory signals, modulated by feature-based attention (FBA), from upstream feature-selective cortical neurons. Moreover, LIP activity is also strongly modulated by the position of space-based attention (SBA). However, the mechanisms by which SBA and FBA interact to facilitate the representation of task-relevant spatial and non-spatial features in LIP remain unclear. We recorded from LIP neurons during performance of a task which required monkeys to detect specific conjunctions of color, motion-direction, and stimulus position. Here we show that FBA and SBA potentiate each other’s effect in a manner consistent with attention gating the flow of visual information along the cortical visual pathway. Our results suggest that linear bottom-up integrative mechanisms allow LIP neurons to emphasize task-relevant spatial and non-spatial features. PMID:27499082

Associative learning rapidly establishes neuronal representations of upcoming behavioral choices in crows

PubMed Central

Veit, Lena; Pidpruzhnykova, Galyna; Nieder, Andreas

2015-01-01

The ability to form associations between behaviorally relevant sensory stimuli is fundamental for goal-directed behaviors. We investigated neuronal activity in the telencephalic area nidopallium caudolaterale (NCL) while two crows (Corvus corone) performed a delayed association task. Whereas some paired associates were familiar to the crows, novel associations had to be learned and mapped to the same target stimuli within a single session. We found neurons that prospectively encoded the chosen test item during the delay for both familiar and newly learned associations. These neurons increased their selectivity during learning in parallel with the crows' increased behavioral performance. Thus, sustained activity in the NCL actively processes information for the upcoming behavioral choice. These data provide new insights into memory representations of behaviorally meaningful stimuli in birds, and how such representations are formed during learning. The findings suggest that the NCL plays a role in learning arbitrary associations, a cornerstone of corvids’ remarkable behavioral flexibility and adaptability. PMID:26598669

A connectome of a learning and memory center in the adult Drosophila brain

PubMed Central

Takemura, Shin-ya; Aso, Yoshinori; Hige, Toshihide; Wong, Allan; Lu, Zhiyuan; Xu, C Shan; Rivlin, Patricia K; Hess, Harald; Zhao, Ting; Parag, Toufiq; Berg, Stuart; Huang, Gary; Katz, William; Olbris, Donald J; Plaza, Stephen; Umayam, Lowell; Aniceto, Roxanne; Chang, Lei-Ann; Lauchie, Shirley; Ogundeyi, Omotara; Ordish, Christopher; Shinomiya, Aya; Sigmund, Christopher; Takemura, Satoko; Tran, Julie; Turner, Glenn C; Rubin, Gerald M; Scheffer, Louis K

2017-01-01

Understanding memory formation, storage and retrieval requires knowledge of the underlying neuronal circuits. In Drosophila, the mushroom body (MB) is the major site of associative learning. We reconstructed the morphologies and synaptic connections of all 983 neurons within the three functional units, or compartments, that compose the adult MB’s α lobe, using a dataset of isotropic 8 nm voxels collected by focused ion-beam milling scanning electron microscopy. We found that Kenyon cells (KCs), whose sparse activity encodes sensory information, each make multiple en passant synapses to MB output neurons (MBONs) in each compartment. Some MBONs have inputs from all KCs, while others differentially sample sensory modalities. Only 6% of KC>MBON synapses receive a direct synapse from a dopaminergic neuron (DAN). We identified two unanticipated classes of synapses, KC>DAN and DAN>MBON. DAN activation produces a slow depolarization of the MBON in these DAN>MBON synapses and can weaken memory recall. DOI: http://dx.doi.org/10.7554/eLife.26975.001 PMID:28718765

Interaction between Spatial and Feature Attention in Posterior Parietal Cortex.

PubMed

Ibos, Guilhem; Freedman, David J

2016-08-17

Lateral intraparietal (LIP) neurons encode a vast array of sensory and cognitive variables. Recently, we proposed that the flexibility of feature representations in LIP reflect the bottom-up integration of sensory signals, modulated by feature-based attention (FBA), from upstream feature-selective cortical neurons. Moreover, LIP activity is also strongly modulated by the position of space-based attention (SBA). However, the mechanisms by which SBA and FBA interact to facilitate the representation of task-relevant spatial and non-spatial features in LIP remain unclear. We recorded from LIP neurons during performance of a task that required monkeys to detect specific conjunctions of color, motion direction, and stimulus position. Here we show that FBA and SBA potentiate each other's effect in a manner consistent with attention gating the flow of visual information along the cortical visual pathway. Our results suggest that linear bottom-up integrative mechanisms allow LIP neurons to emphasize task-relevant spatial and non-spatial features. Copyright © 2016 Elsevier Inc. All rights reserved.

Control of moth flight posture is mediated by wing mechanosensory feedback.

PubMed

Dickerson, Bradley H; Aldworth, Zane N; Daniel, Thomas L

2014-07-01

Flying insects rapidly stabilize after perturbations using both visual and mechanosensory inputs for active control. Insect halteres are mechanosensory organs that encode inertial forces to aid rapid course correction during flight but serve no aerodynamic role and are specific to two orders of insects (Diptera and Strepsiptera). Aside from the literature on halteres and recent work on the antennae of the hawkmoth Manduca sexta, it is unclear how other flying insects use mechanosensory information to control body dynamics. The mechanosensory structures found on the halteres, campaniform sensilla, are also present on wings, suggesting that the wings can encode information about flight dynamics. We show that the neurons innervating these sensilla on the forewings of M. sexta exhibit spike-timing precision comparable to that seen in previous reports of campaniform sensilla, including haltere neurons. In addition, by attaching magnets to the wings of moths and subjecting these animals to a simulated pitch stimulus via a rotating magnetic field during tethered flight, we elicited the same vertical abdominal flexion reflex these animals exhibit in response to visual or inertial pitch stimuli. Our results indicate that, in addition to their role as actuators during locomotion, insect wings serve as sensors that initiate reflexes that control body dynamics. © 2014. Published by The Company of Biologists Ltd.

Monkey prefrontal neurons during Sternberg task performance: full contents of working memory or most recent item?

PubMed

Konecky, R O; Smith, M A; Olson, C R

2017-06-01

To explore the brain mechanisms underlying multi-item working memory, we monitored the activity of neurons in the dorsolateral prefrontal cortex while macaque monkeys performed spatial and chromatic versions of a Sternberg working-memory task. Each trial required holding three sequentially presented samples in working memory so as to identify a subsequent probe matching one of them. The monkeys were able to recall all three samples at levels well above chance, exhibiting modest load and recency effects. Prefrontal neurons signaled the identity of each sample during the delay period immediately following its presentation. However, as each new sample was presented, the representation of antecedent samples became weak and shifted to an anomalous code. A linear classifier operating on the basis of population activity during the final delay period was able to perform at approximately the level of the monkeys on trials requiring recall of the third sample but showed a falloff in performance on trials requiring recall of the first or second sample much steeper than observed in the monkeys. We conclude that delay-period activity in the prefrontal cortex robustly represented only the most recent item. The monkeys apparently based performance of this classic working-memory task on some storage mechanism in addition to the prefrontal delay-period firing rate. Possibilities include delay-period activity in areas outside the prefrontal cortex and changes within the prefrontal cortex not manifest at the level of the firing rate. NEW & NOTEWORTHY It has long been thought that items held in working memory are encoded by delay-period activity in the dorsolateral prefrontal cortex. Here we describe evidence contrary to that view. In monkeys performing a serial multi-item working memory task, dorsolateral prefrontal neurons encode almost exclusively the identity of the sample presented most recently. Information about earlier samples must be encoded outside the prefrontal cortex or represented within the prefrontal cortex in a cryptic code. Copyright © 2017 the American Physiological Society.

Behavioural and neurophysiological evidence for face identity and face emotion processing in animals

PubMed Central

Tate, Andrew J; Fischer, Hanno; Leigh, Andrea E; Kendrick, Keith M

2006-01-01

Visual cues from faces provide important social information relating to individual identity, sexual attraction and emotional state. Behavioural and neurophysiological studies on both monkeys and sheep have shown that specialized skills and neural systems for processing these complex cues to guide behaviour have evolved in a number of mammals and are not present exclusively in humans. Indeed, there are remarkable similarities in the ways that faces are processed by the brain in humans and other mammalian species. While human studies with brain imaging and gross neurophysiological recording approaches have revealed global aspects of the face-processing network, they cannot investigate how information is encoded by specific neural networks. Single neuron electrophysiological recording approaches in both monkeys and sheep have, however, provided some insights into the neural encoding principles involved and, particularly, the presence of a remarkable degree of high-level encoding even at the level of a specific face. Recent developments that allow simultaneous recordings to be made from many hundreds of individual neurons are also beginning to reveal evidence for global aspects of a population-based code. This review will summarize what we have learned so far from these animal-based studies about the way the mammalian brain processes the faces and the emotions they can communicate, as well as associated capacities such as how identity and emotion cues are dissociated and how face imagery might be generated. It will also try to highlight what questions and advances in knowledge still challenge us in order to provide a complete understanding of just how brain networks perform this complex and important social recognition task. PMID:17118930

Behavioural and neurophysiological evidence for face identity and face emotion processing in animals.

PubMed

Tate, Andrew J; Fischer, Hanno; Leigh, Andrea E; Kendrick, Keith M

2006-12-29

Visual cues from faces provide important social information relating to individual identity, sexual attraction and emotional state. Behavioural and neurophysiological studies on both monkeys and sheep have shown that specialized skills and neural systems for processing these complex cues to guide behaviour have evolved in a number of mammals and are not present exclusively in humans. Indeed, there are remarkable similarities in the ways that faces are processed by the brain in humans and other mammalian species. While human studies with brain imaging and gross neurophysiological recording approaches have revealed global aspects of the face-processing network, they cannot investigate how information is encoded by specific neural networks. Single neuron electrophysiological recording approaches in both monkeys and sheep have, however, provided some insights into the neural encoding principles involved and, particularly, the presence of a remarkable degree of high-level encoding even at the level of a specific face. Recent developments that allow simultaneous recordings to be made from many hundreds of individual neurons are also beginning to reveal evidence for global aspects of a population-based code. This review will summarize what we have learned so far from these animal-based studies about the way the mammalian brain processes the faces and the emotions they can communicate, as well as associated capacities such as how identity and emotion cues are dissociated and how face imagery might be generated. It will also try to highlight what questions and advances in knowledge still challenge us in order to provide a complete understanding of just how brain networks perform this complex and important social recognition task.

Rule Encoding in Orbitofrontal Cortex and Striatum Guides Selection

PubMed Central

Castagno, Meghan D.; Hayden, Benjamin Y.

2016-01-01

Active maintenance of rules, like other executive functions, is often thought to be the domain of a discrete executive system. An alternative view is that rule maintenance is a broadly distributed function relying on widespread cortical and subcortical circuits. Tentative evidence supporting this view comes from research showing some rule selectivity in the orbitofrontal cortex and dorsal striatum. We recorded in these regions and in the ventral striatum, which has not been associated previously with rule representation, as macaques performed a Wisconsin Card Sorting Task. We found robust encoding of rule category (color vs shape) and rule identity (six possible rules) in all three regions. Rule identity modulated responses to potential choice targets, suggesting that rule information guides behavior by highlighting choice targets. The effects that we observed were not explained by differences in behavioral performance across rules and thus cannot be attributed to reward expectation. Our results suggest that rule maintenance and rule-guided selection of options are distributed processes and provide new insight into orbital and striatal contributions to executive control. SIGNIFICANCE STATEMENT Rule maintenance, an important executive function, is generally thought to rely on dorsolateral brain regions. In this study, we examined activity of single neurons in orbitofrontal cortex and in ventral and dorsal striatum of macaques in a Wisconsin Card Sorting Task. Neurons in all three areas encoded rules and rule categories robustly. Rule identity also affected neural responses to potential choice options, suggesting that stored information is used to influence decisions. These results endorse the hypothesis that rule maintenance is a broadly distributed mental operation. PMID:27807165

Bovine Herpes Virus 1 (BHV-1) and Herpes Simplex Virus Type 1 (HSV-1) Promote Survival of Latently Infected Sensory Neurons, in Part by Inhibiting Apoptosis

PubMed Central

Jones, Clinton

2013-01-01

α-Herpesvirinae subfamily members, including herpes simplex virus type 1 (HSV-1) and bovine herpes virus 1 (BHV-1), initiate infection in mucosal surfaces. BHV-1 and HSV-1 enter sensory neurons by cell-cell spread where a burst of viral gene expression occurs. When compared to non-neuronal cells, viral gene expression is quickly extinguished in sensory neurons resulting in neuronal survival and latency. The HSV-1 latency associated transcript (LAT), which is abundantly expressed in latently infected neurons, inhibits apoptosis, viral transcription, and productive infection, and directly or indirectly enhances reactivation from latency in small animal models. Three anti-apoptosis genes can be substituted for LAT, which will restore wild type levels of reactivation from latency to a LAT null mutant virus. Two small non-coding RNAs encoded by LAT possess anti-apoptosis functions in transfected cells. The BHV-1 latency related RNA (LR-RNA), like LAT, is abundantly expressed during latency. The LR-RNA encodes a protein (ORF2) and two microRNAs that are expressed in certain latently infected neurons. Wild-type expression of LR gene products is required for stress-induced reactivation from latency in cattle. ORF2 has anti-apoptosis functions and interacts with certain cellular transcription factors that stimulate viral transcription and productive infection. ORF2 is predicted to promote survival of infected neurons by inhibiting apoptosis and sequestering cellular transcription factors which stimulate productive infection. In addition, the LR encoded microRNAs inhibit viral transcription and apoptosis. In summary, the ability of BHV-1 and HSV-1 to interfere with apoptosis and productive infection in sensory neurons is crucial for the life-long latency-reactivation cycle in their respective hosts. PMID:25278776

I(A) channels encoded by Kv1.4 and Kv4.2 regulate neuronal firing in the suprachiasmatic nucleus and circadian rhythms in locomotor activity.

PubMed

Granados-Fuentes, Daniel; Norris, Aaron J; Carrasquillo, Yarimar; Nerbonne, Jeanne M; Herzog, Erik D

2012-07-18

Neurons in the suprachiasmatic nucleus (SCN) display coordinated circadian changes in electrical activity that are critical for daily rhythms in physiology, metabolism, and behavior. SCN neurons depolarize spontaneously and fire repetitively during the day and hyperpolarize, drastically reducing firing rates, at night. To explore the hypothesis that rapidly activating and inactivating A-type (I(A)) voltage-gated K(+) (Kv) channels, which are also active at subthreshold membrane potentials, are critical regulators of the excitability of SCN neurons, we examined locomotor activity and SCN firing in mice lacking Kv1.4 (Kv1.4(-/-)), Kv4.2 (Kv4.2(-/-)), or Kv4.3 (Kv4.3(-/-)), the pore-forming (α) subunits of I(A) channels. Mice lacking either Kv1.4 or Kv4.2 α subunits have markedly shorter (0.5 h) periods of locomotor activity than wild-type (WT) mice. In vitro extracellular multi-electrode recordings revealed that Kv1.4(-/-) and Kv4.2(-/-) SCN neurons display circadian rhythms in repetitive firing, but with shorter periods (0.5 h) than WT cells. In contrast, the periods of wheel-running activity in Kv4.3(-/-) mice and firing in Kv4.3(-/-) SCN neurons were indistinguishable from WT animals and neurons. Quantitative real-time PCR revealed that the transcripts encoding all three Kv channel α subunits, Kv1.4, Kv4.2, and Kv4.3, are expressed constitutively throughout the day and night in the SCN. Together, these results demonstrate that Kv1.4- and Kv4.2-encoded I(A) channels regulate the intrinsic excitability of SCN neurons during the day and night and determine the period and amplitude of circadian rhythms in SCN neuron firing and locomotor behavior.

Theta phase precession and phase selectivity: a cognitive device description of neural coding

NASA Astrophysics Data System (ADS)

Zalay, Osbert C.; Bardakjian, Berj L.

2009-06-01

Information in neural systems is carried by way of phase and rate codes. Neuronal signals are processed through transformative biophysical mechanisms at the cellular and network levels. Neural coding transformations can be represented mathematically in a device called the cognitive rhythm generator (CRG). Incoming signals to the CRG are parsed through a bank of neuronal modes that orchestrate proportional, integrative and derivative transformations associated with neural coding. Mode outputs are then mixed through static nonlinearities to encode (spatio) temporal phase relationships. The static nonlinear outputs feed and modulate a ring device (limit cycle) encoding output dynamics. Small coupled CRG networks were created to investigate coding functionality associated with neuronal phase preference and theta precession in the hippocampus. Phase selectivity was found to be dependent on mode shape and polarity, while phase precession was a product of modal mixing (i.e. changes in the relative contribution or amplitude of mode outputs resulted in shifting phase preference). Nonlinear system identification was implemented to help validate the model and explain response characteristics associated with modal mixing; in particular, principal dynamic modes experimentally derived from a hippocampal neuron were inserted into a CRG and the neuron's dynamic response was successfully cloned. From our results, small CRG networks possessing disynaptic feedforward inhibition in combination with feedforward excitation exhibited frequency-dependent inhibitory-to-excitatory and excitatory-to-inhibitory transitions that were similar to transitions seen in a single CRG with quadratic modal mixing. This suggests nonlinear modal mixing to be a coding manifestation of the effect of network connectivity in shaping system dynamic behavior. We hypothesize that circuits containing disynaptic feedforward inhibition in the nervous system may be candidates for interpreting upstream rate codes to guide downstream processes such as phase precession, because of their demonstrated frequency-selective properties.

Rapid Encoding of New Memories by Individual Neurons in the Human Brain

PubMed Central

Ison, Matias J.; Quian Quiroga, Rodrigo; Fried, Itzhak

2015-01-01

Summary The creation of memories about real-life episodes requires rapid neuronal changes that may appear after a single occurrence of an event. How is such demand met by neurons in the medial temporal lobe (MTL), which plays a fundamental role in episodic memory formation? We recorded the activity of MTL neurons in neurosurgical patients while they learned new associations. Pairs of unrelated pictures, one of a person and another of a place, were used to construct a meaningful association modeling the episodic memory of meeting a person in a particular place. We found that a large proportion of responsive MTL neurons expanded their selectivity to encode these specific associations within a few trials: cells initially responsive to one picture started firing to the associated one but not to others. Our results provide a plausible neural substrate for the inception of associations, which are crucial for the formation of episodic memories. PMID:26139375

Malondialdehyde Suppresses Cerebral Function by Breaking Homeostasis between Excitation and Inhibition in Turtle Trachemys scripta

PubMed Central

Li, Fangxu; Yang, Zhilai; Lu, Yang; Wei, Yan; Wang, Jinhui; Yin, Dazhong; He, Rongqiao

2010-01-01

The levels of malondialdehyde (MDA) are high in the brain during carbonyl stress, such as following daily activities and sleep deprivation. To examine our hypothesis that MDA is one of the major substances in the brain leading to fatigue, the influences of MDA on brain functions and neuronal encodings in red-eared turtle (Trachemys scripta) were studied. The intrathecal injections of MDA brought about sleep-like EEG and fatigue-like behaviors in a dose-dependent manner. These changes were found associated with the deterioration of encoding action potentials in cortical neurons. In addition, MDA increased the ratio of γ-aminobutyric acid to glutamate in turtle's brain, as well as the sensitivity of GABAergic neurons to inputs compared to excitatory neurons. Therefore, MDA, as a metabolic product in the brain, may weaken cerebral function during carbonyl stress through breaking the homeostasis between excitatory and inhibitory neurons. PMID:21203547

Dopamine in motivational control: rewarding, aversive, and alerting

PubMed Central

Bromberg-Martin, Ethan S.; Matsumoto, Masayuki; Hikosaka, Okihide

2010-01-01

SUMMARY Midbrain dopamine neurons are well known for their strong responses to rewards and their critical role in positive motivation. It has become increasingly clear, however, that dopamine neurons also transmit signals related to salient but non-rewarding experiences such as aversive and alerting events. Here we review recent advances in understanding the reward and non-reward functions of dopamine. Based on this data, we propose that dopamine neurons come in multiple types that are connected with distinct brain networks and have distinct roles in motivational control. Some dopamine neurons encode motivational value, supporting brain networks for seeking, evaluation, and value learning. Others encode motivational salience, supporting brain networks for orienting, cognition, and general motivation. Both types of dopamine neurons are augmented by an alerting signal involved in rapid detection of potentially important sensory cues. We hypothesize that these dopaminergic pathways for value, salience, and alerting cooperate to support adaptive behavior. PMID:21144997

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

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.

Upregulation of transmitter release probability improves a conversion of synaptic analogue signals into neuronal digital spikes

PubMed Central

2012-01-01

Action potentials at the neurons and graded signals at the synapses are primary codes in the brain. In terms of their functional interaction, the studies were focused on the influence of presynaptic spike patterns on synaptic activities. How the synapse dynamics quantitatively regulates the encoding of postsynaptic digital spikes remains unclear. We investigated this question at unitary glutamatergic synapses on cortical GABAergic neurons, especially the quantitative influences of release probability on synapse dynamics and neuronal encoding. Glutamate release probability and synaptic strength are proportionally upregulated by presynaptic sequential spikes. The upregulation of release probability and the efficiency of probability-driven synaptic facilitation are strengthened by elevating presynaptic spike frequency and Ca2+. The upregulation of release probability improves spike capacity and timing precision at postsynaptic neuron. These results suggest that the upregulation of presynaptic glutamate release facilitates a conversion of synaptic analogue signals into digital spikes in postsynaptic neurons, i.e., a functional compatibility between presynaptic and postsynaptic partners. PMID:22852823

Neurons in the Frontal Lobe Encode the Value of Multiple Decision Variables

PubMed Central

Kennerley, Steven W.; Dahmubed, Aspandiar F.; Lara, Antonio H.; Wallis, Jonathan D.

2009-01-01

A central question in behavioral science is how we select among choice alternatives to obtain consistently the most beneficial outcomes. Three variables are particularly important when making a decision: the potential payoff, the probability of success, and the cost in terms of time and effort. A key brain region in decision making is the frontal cortex as damage here impairs the ability to make optimal choices across a range of decision types. We simultaneously recorded the activity of multiple single neurons in the frontal cortex while subjects made choices involving the three aforementioned decision variables. This enabled us to contrast the relative contribution of the anterior cingulate cortex (ACC), the orbito-frontal cortex, and the lateral prefrontal cortex to the decision-making process. Neurons in all three areas encoded value relating to choices involving probability, payoff, or cost manipulations. However, the most significant signals were in the ACC, where neurons encoded multiplexed representations of the three different decision variables. This supports the notion that the ACC is an important component of the neural circuitry underlying optimal decision making. PMID:18752411

Pavlovian Fear Conditioning Activates a Common Pattern of Neurons in the Lateral Amygdala of Individual Brains

DTIC Science & Technology

2011-01-12

Abstract Understanding the physical encoding of a memory (the engram ) is a fundamental question in neuroscience. Although it has been established...assembly constitutes a spatial dimension of the engram . Citation: Bergstrom HC, McDonald CG, Johnson LR (2011) Pavlovian Fear Conditioning Activates a Common...competing interests exist. * E-mail: LukeJohnsonPhD@gmail.com Introduction Understanding the physical encoding of a memory (the engram ) in neuronal

Coordinated dynamic encoding in the retina using opposing forms of plasticity

PubMed Central

Kastner, David B.; Baccus, Stephen A.

2011-01-01

The range of natural inputs encoded by a neuron often exceeds its dynamic range. To overcome this limitation, neural populations divide their inputs among different cell classes, as with rod and cone photoreceptors, and adapt by shifting their dynamic range. We report that the dynamic behavior of retinal ganglion cells in salamanders, mice, and rabbits is divided into two opposing forms of short-term plasticity in different cell classes. One population of cells exhibited sensitization—a persistent elevated sensitivity following a strong stimulus. This novel dynamic behavior compensates for the information loss caused by the known process of adaptation occurring in a separate cell population. The two populations divide the dynamic range of inputs, with sensitizing cells encoding weak signals, and adapting cells encoding strong signals. In the two populations, the linear, threshold and adaptive properties are linked to preserve responsiveness when stimulus statistics change, with one population maintaining the ability to respond when the other fails. PMID:21909086

Cerebellar re-encoding of self-generated head movements

PubMed Central

Dugué, Guillaume P; Tihy, Matthieu; Gourévitch, Boris; Léna, Clément

2017-01-01

Head movements are primarily sensed in a reference frame tied to the head, yet they are used to calculate self-orientation relative to the world. This requires to re-encode head kinematic signals into a reference frame anchored to earth-centered landmarks such as gravity, through computations whose neuronal substrate remains to be determined. Here, we studied the encoding of self-generated head movements in the rat caudal cerebellar vermis, an area essential for graviceptive functions. We found that, contrarily to peripheral vestibular inputs, most Purkinje cells exhibited a mixed sensitivity to head rotational and gravitational information and were differentially modulated by active and passive movements. In a subpopulation of cells, this mixed sensitivity underlay a tuning to rotations about an axis defined relative to gravity. Therefore, we show that the caudal vermis hosts a re-encoded, gravitationally polarized representation of self-generated head kinematics in freely moving rats. DOI: http://dx.doi.org/10.7554/eLife.26179.001 PMID:28608779

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.

Shape encoding consistency across colors in primate V4

PubMed Central

Bushnell, Brittany N.

2012-01-01

Neurons in primate cortical area V4 are sensitive to the form and color of visual stimuli. To determine whether form selectivity remains consistent across colors, we studied the responses of single V4 neurons in awake monkeys to a set of two-dimensional shapes presented in two different colors. For each neuron, we chose two colors that were visually distinct and that evoked reliable and different responses. Across neurons, the correlation coefficient between responses in the two colors ranged from −0.03 to 0.93 (median 0.54). Neurons with highly consistent shape responses, i.e., high correlation coefficients, showed greater dispersion in their responses to the different shapes, i.e., greater shape selectivity, and also tended to have less eccentric receptive field locations; among shape-selective neurons, shape consistency ranged from 0.16 to 0.93 (median 0.63). Consistency of shape responses was independent of the physical difference between the stimulus colors used and the strength of neuronal color tuning. Finally, we found that our measurement of shape response consistency was strongly influenced by the number of stimulus repeats: consistency estimates based on fewer than 10 repeats were substantially underestimated. In conclusion, our results suggest that neurons that are likely to contribute to shape perception and discrimination exhibit shape responses that are largely consistent across colors, facilitating the use of simpler algorithms for decoding shape information from V4 neuronal populations. PMID:22673324

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

Aβ1-42 triggers the generation of a retrograde signaling complex from sentinel mRNAs in axons.

PubMed

Walker, Chandler A; Randolph, Lisa K; Matute, Carlos; Alberdi, Elena; Baleriola, Jimena; Hengst, Ulrich

2018-05-14

Neurons frequently encounter neurodegenerative signals first in their periphery. For example, exposure of axons to oligomeric Aβ 1-42 is sufficient to induce changes in the neuronal cell body that ultimately lead to degeneration. Currently, it is unclear how the information about the neurodegenerative insult is transmitted to the soma. Here, we find that the translation of pre-localized but normally silenced sentinel mRNAs in axons is induced within minutes of Aβ 1-42 addition in a Ca 2+ -dependent manner. This immediate protein synthesis following Aβ 1-42 exposure generates a retrograde signaling complex including vimentin. Inhibition of the immediate protein synthesis, knock-down of axonal vimentin synthesis, or inhibition of dynein-dependent transport to the soma prevented the normal cell body response to Aβ 1-42 These results establish that CNS axons react to neurodegenerative insults via the local translation of sentinel mRNAs encoding components of a retrograde signaling complex that transmit the information about the event to the neuronal soma. © 2018 The Authors.

Memory on time

PubMed Central

Eichenbaum, Howard

2013-01-01

Considerable recent work has shown that the hippocampus is critical for remembering the order of events in distinct experiences, a defining feature of episodic memory. Correspondingly, hippocampal neuronal activity can ‘replay’ sequential events in memories and hippocampal neuronal ensembles represent a gradually changing temporal context signal. Most strikingly, single hippocampal neurons – called time cells – encode moments in temporally structured experiences much as the well-known place cells encode locations in spatially structured experiences. These observations bridge largely disconnected literatures on the role of the hippocampus in episodic memory and spatial mapping, and suggest that the fundamental function of the hippocampus is to establish spatio-temporal frameworks for organizing memories. PMID:23318095

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.

Oscillatory encoding of visual stimulus familiarity.

PubMed

Kissinger, Samuel T; Pak, Alexandr; Tang, Yu; Masmanidis, Sotiris C; Chubykin, Alexander A

2018-06-18

Familiarity of the environment changes the way we perceive and encode incoming information. However, the neural substrates underlying this phenomenon are poorly understood. Here we describe a new form of experience-dependent low frequency oscillations in the primary visual cortex (V1) of awake adult male mice. The oscillations emerged in visually evoked potentials (VEPs) and single-unit activity following repeated visual stimulation. The oscillations were sensitive to the spatial frequency content of a visual stimulus and required the muscarinic acetylcholine receptors (mAChRs) for their induction and expression. Finally, ongoing visually evoked theta (4-6 Hz) oscillations boost the VEP amplitude of incoming visual stimuli if the stimuli are presented at the high excitability phase of the oscillations. Our results demonstrate that an oscillatory code can be used to encode familiarity and serves as a gate for oncoming sensory inputs. Significance Statement. Previous experience can influence the processing of incoming sensory information by the brain and alter perception. However, the mechanistic understanding of how this process takes place is lacking. We have discovered that persistent low frequency oscillations in the primary visual cortex encode information about familiarity and the spatial frequency of the stimulus. These familiarity evoked oscillations influence neuronal responses to the oncoming stimuli in a way that depends on the oscillation phase. Our work demonstrates a new mechanism of visual stimulus feature detection and learning. Copyright © 2018 the authors.

Cortical Specializations Underlying Fast Computations

PubMed Central

Volgushev, Maxim

2016-01-01

The time course of behaviorally relevant environmental events sets temporal constraints on neuronal processing. How does the mammalian brain make use of the increasingly complex networks of the neocortex, while making decisions and executing behavioral reactions within a reasonable time? The key parameter determining the speed of computations in neuronal networks is a time interval that neuronal ensembles need to process changes at their input and communicate results of this processing to downstream neurons. Theoretical analysis identified basic requirements for fast processing: use of neuronal populations for encoding, background activity, and fast onset dynamics of action potentials in neurons. Experimental evidence shows that populations of neocortical neurons fulfil these requirements. Indeed, they can change firing rate in response to input perturbations very quickly, within 1 to 3 ms, and encode high-frequency components of the input by phase-locking their spiking to frequencies up to 300 to 1000 Hz. This implies that time unit of computations by cortical ensembles is only few, 1 to 3 ms, which is considerably faster than the membrane time constant of individual neurons. The ability of cortical neuronal ensembles to communicate on a millisecond time scale allows for complex, multiple-step processing and precise coordination of neuronal activity in parallel processing streams, while keeping the speed of behavioral reactions within environmentally set temporal constraints. PMID:25689988

Eye Velocity Gain Fields in MSTd During Optokinetic Stimulation

PubMed Central

Brostek, Lukas; Büttner, Ulrich; Mustari, Michael J.; Glasauer, Stefan

2015-01-01

Lesion studies argue for an involvement of cortical area dorsal medial superior temporal area (MSTd) in the control of optokinetic response (OKR) eye movements to planar visual stimulation. Neural recordings during OKR suggested that MSTd neurons directly encode stimulus velocity. On the other hand, studies using radial visual flow together with voluntary smooth pursuit eye movements showed that visual motion responses were modulated by eye movement-related signals. Here, we investigated neural responses in MSTd during continuous optokinetic stimulation using an information-theoretic approach for characterizing neural tuning with high resolution. We show that the majority of MSTd neurons exhibit gain-field-like tuning functions rather than directly encoding one variable. Neural responses showed a large diversity of tuning to combinations of retinal and extraretinal input. Eye velocity-related activity was observed prior to the actual eye movements, reflecting an efference copy. The observed tuning functions resembled those emerging in a network model trained to perform summation of 2 population-coded signals. Together, our findings support the hypothesis that MSTd implements the visuomotor transformation from retinal to head-centered stimulus velocity signals for the control of OKR. PMID:24557636

Mechanisms of specificity in neuronal activity-regulated gene transcription

PubMed Central

Lyons, Michelle R.; West, Anne E.

2011-01-01

The brain is a highly adaptable organ that is capable of converting sensory information into changes in neuronal function. This plasticity allows behavior to be accommodated to the environment, providing an important evolutionary advantage. Neurons convert environmental stimuli into long-lasting changes in their physiology in part through the synaptic activity-regulated transcription of new gene products. Since the neurotransmitter-dependent regulation of Fos transcription was first discovered nearly 25 years ago, a wealth of studies have enriched our understanding of the molecular pathways that mediate activity-regulated changes in gene transcription. These findings show that a broad range of signaling pathways and transcriptional regulators can be engaged by neuronal activity to sculpt complex programs of stimulus-regulated gene transcription. However, the shear scope of the transcriptional pathways engaged by neuronal activity raises the question of how specificity in the nature of the transcriptional response is achieved in order to encode physiologically relevant responses to divergent stimuli. Here we summarize the general paradigms by which neuronal activity regulates transcription while focusing on the molecular mechanisms that confer differential stimulus-, cell-type-, and developmental-specificity upon activity-regulated programs of neuronal gene transcription. In addition, we preview some of the new technologies that will advance our future understanding of the mechanisms and consequences of activity-regulated gene transcription in the brain. PMID:21620929

Gene Transfer of Brain-derived Neurotrophic Factor (BDNF) Prevents Neurodegeneration Triggered by FXN Deficiency.

PubMed

Katsu-Jiménez, Yurika; Loría, Frida; Corona, Juan Carlos; Díaz-Nido, Javier

2016-05-01

Friedreich's ataxia is a predominantly neurodegenerative disease caused by recessive mutations that produce a deficiency of frataxin (FXN). Here, we have used a herpesviral amplicon vector carrying a gene encoding for brain-derived neurotrophic factor (BDNF) to drive its overexpression in neuronal cells and test for its effect on FXN-deficient neurons both in culture and in the mouse cerebellum in vivo. Gene transfer of BDNF to primary cultures of mouse neurons prevents the apoptosis which is triggered by the knockdown of FXN gene expression. This neuroprotective effect of BDNF is also observed in vivo in a viral vector-based knockdown mouse cerebellar model. The injection of a lentiviral vector carrying a minigene encoding for a FXN-specific short hairpin ribonucleic acid (shRNA) into the mouse cerebellar cortex triggers a FXN deficit which is accompanied by significant apoptosis of granule neurons as well as loss of calbindin in Purkinje cells. These pathological changes are accompanied by a loss of motor coordination of mice as assayed by the rota-rod test. Coinjection of a herpesviral vector encoding for BDNF efficiently prevents both the development of cerebellar neuropathology and the ataxic phenotype. These data demonstrate the potential therapeutic usefulness of neurotrophins like BDNF to protect FXN-deficient neurons from degeneration.

Infrared neural stimulation in the cochlea

PubMed Central

Richter, Claus-Peter; Rajguru, Suhrud; Bendett, Mark

2014-01-01

The application of photonics to manipulate and stimulate neurons and to study neural networks has gained momentum over the last decade. Two general methods have been used: the genetic expression of light or temperature sensitive ion channels in the plasma membrane of neurons (Optogenetics and Thermogenetics) and the direct stimulation of neurons using infrared radiation (Infrared Neural Stimulation, INS). Both approaches have their strengths and challenges, which are well understood with a profound understanding of the light tissue interaction(s). This paper compares the opportunities of the methods for the use in cochlear prostheses. Ample data are already available on the stimulation of the cochlea with INS. The data show that the stimulation is selective, feasible at rates that would be sufficient to encode acoustic information and may be beneficial over conventional pulsed electrical stimulation. A third approach, using lasers in stress confinement to generate pressure waves and to stimulate the functional cochlea mechanically will also be discussed. PMID:25075260

A Motor-Driven Mechanism for Cell-Length Sensing

PubMed Central

Rishal, Ida; Kam, Naaman; Perry, Rotem Ben-Tov; Shinder, Vera; Fisher, Elizabeth M.C.; Schiavo, Giampietro; Fainzilber, Mike

2012-01-01

Summary Size homeostasis is fundamental in cell biology, but it is not clear how large cells such as neurons can assess their own size or length. We examined a role for molecular motors in intracellular length sensing. Computational simulations suggest that spatial information can be encoded by the frequency of an oscillating retrograde signal arising from a composite negative feedback loop between bidirectional motor-dependent signals. The model predicts that decreasing either or both anterograde or retrograde signals should increase cell length, and this prediction was confirmed upon application of siRNAs for specific kinesin and/or dynein heavy chains in adult sensory neurons. Heterozygous dynein heavy chain 1 mutant sensory neurons also exhibited increased lengths both in vitro and during embryonic development. Moreover, similar length increases were observed in mouse embryonic fibroblasts upon partial downregulation of dynein heavy chain 1. Thus, molecular motors critically influence cell-length sensing and growth control. PMID:22773964

Infrared neural stimulation in the cochlea

NASA Astrophysics Data System (ADS)

Richter, Claus-Peter; Rajguru, Suhrud; Bendett, Mark

2013-03-01

The application of photonics to manipulate and stimulate neurons and to study neural networks has gained momentum over the last decade. Two general methods have been used: the genetic expression of light or temperature sensitive ion channels in the plasma membrane of neurons (Optogenetics and Thermogenetics) and the direct stimulation of neurons using infrared radiation (Infrared Neural Stimulation, INS). Both approaches have their strengths and challenges, which are well understood with a profound understanding of the light tissue interaction(s). This paper compares the opportunities of the methods for the use in cochlear prostheses. Ample data are already available on the stimulation of the cochlea with INS. The data show that the stimulation is selective, feasible at rates that would be sufficient to encode acoustic information and may be beneficial over conventional pulsed electrical stimulation. A third approach, using lasers in stress confinement to generate pressure waves and to stimulate the functional cochlea mechanically will also be discussed.

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.

Unmasking of spiral ganglion neuron firing dynamics by membrane potential and neurotrophin-3.

PubMed

Crozier, Robert A; Davis, Robin L

2014-07-16

Type I spiral ganglion neurons have a unique role relative to other sensory afferents because, as a single population, they must convey the richness, complexity, and precision of auditory information as they shape signals transmitted to the brain. To understand better the sophistication of spiral ganglion response properties, we compared somatic whole-cell current-clamp recordings from basal and apical neurons obtained during the first 2 postnatal weeks from CBA/CaJ mice. We found that during this developmental time period neuron response properties changed from uniformly excitable to differentially plastic. Low-frequency, apical and high-frequency basal neurons at postnatal day 1 (P1)-P3 were predominantly slowly accommodating (SA), firing at low thresholds with little alteration in accommodation response mode induced by changes in resting membrane potential (RMP) or added neurotrophin-3 (NT-3). In contrast, P10-P14 apical and basal neurons were predominately rapidly accommodating (RA), had higher firing thresholds, and responded to elevation of RMP and added NT-3 by transitioning to the SA category without affecting the instantaneous firing rate. Therefore, older neurons appeared to be uniformly less excitable under baseline conditions yet displayed a previously unrecognized capacity to change response modes dynamically within a remarkably stable accommodation framework. Because the soma is interposed in the signal conduction pathway, these specializations can potentially lead to shaping and filtering of the transmitted signal. These results suggest that spiral ganglion neurons possess electrophysiological mechanisms that enable them to adapt their response properties to the characteristics of incoming stimuli and thus have the capacity to encode a wide spectrum of auditory information. Copyright © 2014 the authors 0270-6474/14/349688-15$15.00/0.

Temporal information entropy of the Blood-Oxygenation Level-Dependent signals increases in the activated human primary visual cortex

NASA Astrophysics Data System (ADS)

DiNuzzo, Mauro; Mascali, Daniele; Moraschi, Marta; Bussu, Giorgia; Maraviglia, Bruno; Mangia, Silvia; Giove, Federico

2017-02-01

Time-domain analysis of blood-oxygenation level-dependent (BOLD) signals allows the identification of clusters of voxels responding to photic stimulation in primary visual cortex (V1). However, the characterization of information encoding into temporal properties of the BOLD signals of an activated cluster is poorly investigated. Here, we used Shannon entropy to determine spatial and temporal information encoding in the BOLD signal within the most strongly activated area of the human visual cortex during a hemifield photic stimulation. We determined the distribution profile of BOLD signals during epochs at rest and under stimulation within small (19-121 voxels) clusters designed to include only voxels driven by the stimulus as highly and uniformly as possible. We found consistent and significant increases (2-4% on average) in temporal information entropy during activation in contralateral but not ipsilateral V1, which was mirrored by an expected loss of spatial information entropy. These opposite changes coexisted with increases in both spatial and temporal mutual information (i.e. dependence) in contralateral V1. Thus, we showed that the first cortical stage of visual processing is characterized by a specific spatiotemporal rearrangement of intracluster BOLD responses. Our results indicate that while in the space domain BOLD maps may be incapable of capturing the functional specialization of small neuronal populations due to relatively low spatial resolution, some information encoding may still be revealed in the temporal domain by an increase of temporal information entropy.

A thesaurus for a neural population code

PubMed Central

Ganmor, Elad; Segev, Ronen; Schneidman, Elad

2015-01-01

Information is carried in the brain by the joint spiking patterns of large groups of noisy, unreliable neurons. This noise limits the capacity of the neural code and determines how information can be transmitted and read-out. To accurately decode, the brain must overcome this noise and identify which patterns are semantically similar. We use models of network encoding noise to learn a thesaurus for populations of neurons in the vertebrate retina responding to artificial and natural videos, measuring the similarity between population responses to visual stimuli based on the information they carry. This thesaurus reveals that the code is organized in clusters of synonymous activity patterns that are similar in meaning but may differ considerably in their structure. This organization is highly reminiscent of the design of engineered codes. We suggest that the brain may use this structure and show how it allows accurate decoding of novel stimuli from novel spiking patterns. DOI: http://dx.doi.org/10.7554/eLife.06134.001 PMID:26347983

Spatial interactions reveal inhibitory cortical networks in human amblyopia.

PubMed

Wong, Erwin H; Levi, Dennis M; McGraw, Paul V

2005-10-01

Humans with amblyopia have a well-documented loss of sensitivity for first-order, or luminance defined, visual information. Recent studies show that they also display a specific loss of sensitivity for second-order, or contrast defined, visual information; a type of image structure encoded by neurons found predominantly in visual area A18/V2. In the present study, we investigate whether amblyopia disrupts the normal architecture of spatial interactions in V2 by determining the contrast detection threshold of a second-order target in the presence of second-order flanking stimuli. Adjacent flanks facilitated second-order detectability in normal observers. However, in marked contrast, they suppressed detection in each eye of the majority of amblyopic observers. Furthermore, strabismic observers with no loss of visual acuity show a similar pattern of detection suppression. We speculate that amblyopia results in predominantly inhibitory cortical interactions between second-order neurons.

Non-accidental properties, metric invariance, and encoding by neurons in a model of ventral stream visual object recognition, VisNet.

PubMed

Rolls, Edmund T; Mills, W Patrick C

2018-05-01

When objects transform into different views, some properties are maintained, such as whether the edges are convex or concave, and these non-accidental properties are likely to be important in view-invariant object recognition. The metric properties, such as the degree of curvature, may change with different views, and are less likely to be useful in object recognition. It is shown that in a model of invariant visual object recognition in the ventral visual stream, VisNet, non-accidental properties are encoded much more than metric properties by neurons. Moreover, it is shown how with the temporal trace rule training in VisNet, non-accidental properties of objects become encoded by neurons, and how metric properties are treated invariantly. We also show how VisNet can generalize between different objects if they have the same non-accidental property, because the metric properties are likely to overlap. VisNet is a 4-layer unsupervised model of visual object recognition trained by competitive learning that utilizes a temporal trace learning rule to implement the learning of invariance using views that occur close together in time. A second crucial property of this model of object recognition is, when neurons in the level corresponding to the inferior temporal visual cortex respond selectively to objects, whether neurons in the intermediate layers can respond to combinations of features that may be parts of two or more objects. In an investigation using the four sides of a square presented in every possible combination, it was shown that even though different layer 4 neurons are tuned to encode each feature or feature combination orthogonally, neurons in the intermediate layers can respond to features or feature combinations present is several objects. This property is an important part of the way in which high capacity can be achieved in the four-layer ventral visual cortical pathway. These findings concerning non-accidental properties and the use of neurons in intermediate layers of the hierarchy help to emphasise fundamental underlying principles of the computations that may be implemented in the ventral cortical visual stream used in object recognition. Copyright © 2018 Elsevier Inc. All rights reserved.

Spike timing precision of neuronal circuits.

PubMed

Kilinc, Deniz; Demir, Alper

2018-06-01

Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.

Neuron-specific specificity protein 4 bigenomically regulates the transcription of all mitochondria- and nucleus-encoded cytochrome c oxidase subunit genes in neurons.

PubMed

Johar, Kaid; Priya, Anusha; Dhar, Shilpa; Liu, Qiuli; Wong-Riley, Margaret T T

2013-11-01

Neurons are highly dependent on oxidative metabolism for their energy supply, and cytochrome c oxidase (COX) is a key energy-generating enzyme in the mitochondria. A unique feature of COX is that it is one of only four proteins in mammalian cells that are bigenomically regulated. Of its thirteen subunits, three are encoded in the mitochondrial genome and ten are nuclear-encoded on nine different chromosomes. The mechanism of regulating this multisubunit, bigenomic enzyme poses a distinct challenge. In recent years, we found that nuclear respiratory factors 1 and 2 (NRF-1 and NRF-2) mediate such bigenomic coordination. The latest candidate is the specificity factor (Sp) family of proteins. In N2a cells, we found that Sp1 regulates all 13 COX subunits. However, we discovered recently that in primary neurons, it is Sp4 and not Sp1 that regulates some of the key glutamatergic receptor subunit genes. The question naturally arises as to the role of Sp4 in regulating COX in primary neurons. The present study utilized multiple approaches, including chromatin immunoprecipitation, promoter mutational analysis, knockdown and over-expression of Sp4, as well as functional assays to document that Sp4 indeed functionally regulate all 13 subunits of COX as well as mitochondrial transcription factors A and B. The present study discovered that among the specificity family of transcription factors, it is the less known neuron-specific Sp4 that regulates the expression of all 13 subunits of mitochondrial cytochrome c oxidase (COX) enzyme in primary neurons. Sp4 also regulates the three mitochondrial transcription factors (TFAM, TFB1M, and TFB2M) and a COX assembly protein SURF-1 in primary neurons. © 2013 International Society for Neurochemistry.

PMv Neuronal Firing May Be Driven by a Movement Command Trajectory within Multidimensional Gaussian Fields.

PubMed

Agarwal, Rahul; Thakor, Nitish V; Sarma, Sridevi V; Massaquoi, Steve G

2015-06-24

The premotor cortex (PM) is known to be a site of visuo-somatosensory integration for the production of movement. We sought to better understand the ventral PM (PMv) by modeling its signal encoding in greater detail. Neuronal firing data was obtained from 110 PMv neurons in two male rhesus macaques executing four reach-grasp-manipulate tasks. We found that in the large majority of neurons (∼90%) the firing patterns across the four tasks could be explained by assuming that a high-dimensional position/configuration trajectory-like signal evolving ∼250 ms before movement was encoded within a multidimensional Gaussian field (MGF). Our findings are consistent with the possibility that PMv neurons process a visually specified reference command for the intended arm/hand position trajectory with respect to a proprioceptively or visually sensed initial configuration. The estimated MGF were (hyper) disc-like, such that each neuron's firing modulated strongly only with commands that evolved along a single direction within position/configuration space. Thus, many neurons appeared to be tuned to slices of this input signal space that as a collection appeared to well cover the space. The MGF encoding models appear to be consistent with the arm-referent, bell-shaped, visual target tuning curves and target selectivity patterns observed in PMV visual-motor neurons. These findings suggest that PMv may implement a lookup table-like mechanism that helps translate intended movement trajectory into time-varying patterns of activation in motor cortex and spinal cord. MGFs provide an improved nonlinear framework for potentially decoding visually specified, intended multijoint arm/hand trajectories well in advance of movement. Copyright © 2015 the authors 0270-6474/15/359508-18$15.00/0.

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

Ventral pallidal encoding of reward-seeking behavior depends on the underlying associative structure

PubMed Central

Stout, Nakura; Acs, Deanna

2018-01-01

Despite its being historically conceptualized as a motor expression site, emerging evidence suggests the ventral pallidum (VP) plays a more active role in integrating information to generate motivation. Here, we investigated whether rat VP cue responses would encode and contribute similarly to the vigor of reward-seeking behaviors trained under Pavlovian versus instrumental contingencies, when these behavioral responses consist of superficially similar locomotor response patterns but may reflect distinct underlying decision-making processes. We find that cue-elicited activity in many VP neurons predicts the latency of instrumental reward seeking, but not of Pavlovian response latency. Further, disruption of VP signaling increases the latency of instrumental but not Pavlovian reward seeking. This suggests that VP encoding of and contributions to response vigor are specific to the ability of incentive cues to invigorate reward-seeking behaviors upon which reward delivery is contingent. PMID:29565248

Laminar activity in the hippocampus and entorhinal cortex related to novelty and episodic encoding

PubMed Central

Maass, Anne; Schütze, Hartmut; Speck, Oliver; Yonelinas, Andrew; Tempelmann, Claus; Heinze, Hans-Jochen; Berron, David; Cardenas-Blanco, Arturo; Brodersen, Kay H.; Enno Stephan, Klaas; Düzel, Emrah

2014-01-01

The ability to form long-term memories for novel events depends on information processing within the hippocampus (HC) and entorhinal cortex (EC). The HC–EC circuitry shows a quantitative segregation of anatomical directionality into different neuronal layers. Whereas superficial EC layers mainly project to dentate gyrus (DG), CA3 and apical CA1 layers, HC output is primarily sent from pyramidal CA1 layers and subiculum to deep EC layers. Here we utilize this directionality information by measuring encoding activity within HC/EC subregions with 7 T high resolution functional magnetic resonance imaging (fMRI). Multivariate Bayes decoding within HC/EC subregions shows that processing of novel information most strongly engages the input structures (superficial EC and DG/CA2–3), whereas subsequent memory is more dependent on activation of output regions (deep EC and pyramidal CA1). This suggests that while novelty processing is strongly related to HC–EC input pathways, the memory fate of a novel stimulus depends more on HC–EC output. PMID:25424131

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations.

PubMed

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-06-16

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity.

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations

PubMed Central

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-01-01

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity. PMID:27306959

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations

NASA Astrophysics Data System (ADS)

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-06-01

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity.

A three-layered model of primate prefrontal cortex encodes identity and abstract categorical structure of behavioral sequences.

PubMed

Hinaut, Xavier; Dominey, Peter Ford

2011-01-01

Categorical encoding is crucial for mastering large bodies of related sensory-motor experiences, but what is its neural substrate? In an effort to respond to this question, recent single-unit recording studies in the macaque lateral prefrontal cortex (LPFC) have demonstrated two characteristic forms of neural encoding of the sequential structure of the animal's sensory-motor experience. One population of neurons encodes the specific behavioral sequences. A second population of neurons encodes the sequence category (e.g. ABAB, AABB or AAAA) and does not differentiate sequences within the category (Shima, K., Isoda, M., Mushiake, H., Tanji, J., 2007. Categorization of behavioural sequences in the prefrontal cortex. Nature 445, 315-318.). Interestingly these neurons are intermingled in the lateral prefrontal cortex, and not topographically segregated. Thus, LPFC may provide a neurophysiological basis for sensorimotor categorization. Here we report on a neural network simulation study that reproduces and explains these results. We model a cortical circuit composed of three layers (infragranular, granular, and supragranular) of 5*5 leaky integrator neurons with a sigmoidal output function, and we examine 1000 such circuits running in parallel. Crucially the three layers are interconnected with recurrent connections, thus producing a dynamical system that is inherently sensitive to the spatiotemporal structure of the sequential inputs. The model is presented with 11 four-element sequences following Shima et al. We isolated one subpopulation of neurons each of whose activity predicts individual sequences, and a second population that predicts category independent of the specific sequence. We argue that a richly interconnected cortical circuit is capable of internally generating a neural representation of category membership, thus significantly extending the scope of recurrent network computation. In order to demonstrate that these representations can be used to create an explicit categorization capability, we introduced an additional neural structure corresponding to the striatum. We showed that via cortico-striatal plasticity, neurons in the striatum could produce an explicit representation both of the identity of each sequence, and its category membership. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quantitative analysis of sex-pheromone coding in the antennal lobe of the moth Agrotis ipsilon: a tool to study network plasticity.

PubMed

Jarriault, David; Gadenne, Christophe; Rospars, Jean-Pierre; Anton, Sylvia

2009-04-01

To find a mating partner, moths rely on pheromone communication. Released in very low amounts, female sex pheromones are used by males to identify and localize females. Depending on the physiological state (i.e. age, reproductive state), the olfactory system of the males of the noctuid moth Agrotis ipsilon is 'switched on or off'. To understand the neural basis of this behavioural plasticity, we performed a detailed characterization of the qualitative, quantitative and temporal aspects of pheromone coding in the primary centre of integration of pheromonal information, the macroglomerular complex (MGC) of the antennal lobe. MGC neurons were intracellularly recorded and stained in sexually mature virgin males. When stimulating antennae of males with the three main components of the female pheromone blend, most of the neurons showed a biphasic excitatory-inhibitory response. Although they showed different preferences, 80% of the neurons responded at least to the main pheromone component (Z-7-dodecenyl acetate). Six stained neurons responding to this component had their dendrites in the largest MGC glomerulus. Changes in the stimulus intensity and duration affected the excitatory phase but not the inhibitory phase properties. The stimulus intensity was shown to be encoded in the firing frequency, the number of spikes and the latency of the excitatory phase, whereas the stimulus duration only changed its duration. We conclude that the inhibitory input provided by local interneurons following the excitatory phase might not contribute directly to the encoding of stimulus characteristics. The data presented will serve as a basis for comparison with those of immature and mated males.

The role of cortical beta oscillations in time estimation.

PubMed

Kulashekhar, Shrikanth; Pekkola, Johanna; Palva, Jaakko Matias; Palva, Satu

2016-09-01

Estimation of time is central to perception, action, and cognition. Human functional magnetic resonance imaging (fMRI) and positron emission topography (PET) have revealed a positive correlation between the estimation of multi-second temporal durations and neuronal activity in a circuit of sensory and motor areas, prefrontal and temporal cortices, basal ganglia, and cerebellum. The systems-level mechanisms coordinating the collective neuronal activity in these areas have remained poorly understood. Synchronized oscillations regulate communication in neuronal networks and could hence serve such coordination, but their role in the estimation and maintenance of multi-second time intervals has remained largely unknown. We used source-reconstructed magnetoencephalography (MEG) to address the functional significance of local neuronal synchronization, as indexed by the amplitudes of cortical oscillations, in time-estimation. MEG was acquired during a working memory (WM) task where the subjects first estimated and then memorized the durations, or in the contrast condition, the colors of dynamic visual stimuli. Time estimation was associated with stronger beta (β, 14 - 30 Hz) band oscillations than color estimation in sensory regions and attentional cortical structures that earlier have been associated with time processing. In addition, the encoding of duration information was associated with strengthened gamma- (γ, 30 - 120 Hz), and the retrieval and maintenance with alpha- (α, 8 - 14 Hz) band oscillations. These data suggest that β oscillations may provide a mechanism for estimating short temporal durations, while γ and α oscillations support their encoding, retrieval, and maintenance in memory. Hum Brain Mapp 37:3262-3281, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Dendritic excitability modulates dendritic information processing in a purkinje cell model.

PubMed

Coop, Allan D; Cornelis, Hugo; Santamaria, Fidel

2010-01-01

Using an electrophysiological compartmental model of a Purkinje cell we quantified the contribution of individual active dendritic currents to processing of synaptic activity from granule cells. We used mutual information as a measure to quantify the information from the total excitatory input current (I(Glu)) encoded in each dendritic current. In this context, each active current was considered an information channel. Our analyses showed that most of the information was encoded by the calcium (I(CaP)) and calcium activated potassium (I(Kc)) currents. Mutual information between I(Glu) and I(CaP) and I(Kc) was sensitive to different levels of excitatory and inhibitory synaptic activity that, at the same time, resulted in the same firing rate at the soma. Since dendritic excitability could be a mechanism to regulate information processing in neurons we quantified the changes in mutual information between I(Glu) and all Purkinje cell currents as a function of the density of dendritic Ca (g(CaP)) and Kca (g(Kc)) conductances. We extended our analysis to determine the window of temporal integration of I(Glu) by I(CaP) and I(Kc) as a function of channel density and synaptic activity. The window of information integration has a stronger dependence on increasing values of g(Kc) than on g(CaP), but at high levels of synaptic stimulation information integration is reduced to a few milliseconds. Overall, our results show that different dendritic conductances differentially encode synaptic activity and that dendritic excitability and the level of synaptic activity regulate the flow of information in dendrites.

What is the function of hippocampal theta rhythm?--Linking behavioral data to phasic properties of field potential and unit recording data.

PubMed

Hasselmo, Michael E

2005-01-01

The extensive physiological data on hippocampal theta rhythm provide an opportunity to evaluate hypotheses about the role of theta rhythm for hippocampal network function. Computational models based on these hypotheses help to link behavioral data with physiological measurements of different variables during theta rhythm. This paper reviews work on network models in which theta rhythm contributes to the following functions: (1) separating the dynamics of encoding and retrieval, (2) enhancing the context-dependent retrieval of sequences, (3) buffering of novel information in entorhinal cortex (EC) for episodic encoding, and (4) timing interactions between prefrontal cortex and hippocampus for memory-guided action selection. Modeling shows how these functional mechanisms are related to physiological data from the hippocampal formation, including (1) the phase relationships of synaptic currents during theta rhythm measured by current source density analysis of electroencephalographic data from region CA1 and dentate gyrus, (2) the timing of action potentials, including the theta phase precession of single place cells during running on a linear track, the context-dependent changes in theta phase precession across trials on each day, and the context-dependent firing properties of hippocampal neurons in spatial alternation (e.g., "splitter cells"), (3) the cholinergic regulation of sustained activity in entorhinal cortical neurons, and (4) the phasic timing of prefrontal cortical neurons relative to hippocampal theta rhythm. Copyright 2005 Wiley-Liss, Inc.

Reward modulates attention independently of action value in posterior parietal cortex

PubMed Central

Peck, Christopher J.; Jangraw, David C.; Suzuki, Mototaka; Efem, Richard; Gottlieb, Jacqueline

2009-01-01

While numerous studies explored the mechanisms of reward-based decisions (the choice of action based on expected gain), few asked how reward influences attention (the selection of information relevant for a decision). Here we show that a powerful determinant of attentional priority is the association between a stimulus and an appetitive reward. A peripheral cue heralded the delivery of reward (RC+) or no reward (RC−); to experience the predicted outcome monkeys made a saccade to a target that appeared unpredictably at the same or opposite location relative to the cue. Although the RC had no operant associations (did not specify the required saccade) they automatically biased attention, such that the RC+ attracted attention and RC− repelled attention from their location. Neurons in the lateral intraparietal area (LIP) encoded these attentional biases, maintaining sustained excitation at the location of an RC+ and inhibition at the location of an RC−. Contrary to the hypothesis that LIP encodes action value, neurons did not encode the expected reward of the saccade. Moreover, the cue-evoked biases were maladaptive, interfering with the required saccade, and they biases increased rather than abating with training, strikingly at odds with an adaptive decision process. After prolonged training valence selectivity appeared at shorter latencies and automatically transferred to a novel task context, suggesting that training produced visual plasticity. The results suggest that reward predictors gain automatic attentional priority regardless of their operant associations, and this valence-specific priority is encoded in LIP independently of the expected reward of an action. PMID:19741125

Predictive encoding of moving target trajectory by neurons in the parabigeminal nucleus

PubMed Central

Ma, Rui; Cui, He; Lee, Sang-Hun; Anastasio, Thomas J.

2013-01-01

Intercepting momentarily invisible moving objects requires internally generated estimations of target trajectory. We demonstrate here that the parabigeminal nucleus (PBN) encodes such estimations, combining sensory representations of target location, extrapolated positions of briefly obscured targets, and eye position information. Cui and Malpeli (Cui H, Malpeli JG. J Neurophysiol 89: 3128–3142, 2003) reported that PBN activity for continuously visible tracked targets is determined by retinotopic target position. Here we show that when cats tracked moving, blinking targets the relationship between activity and target position was similar for ON and OFF phases (400 ms for each phase). The dynamic range of activity evoked by virtual targets was 94% of that of real targets for the first 200 ms after target offset and 64% for the next 200 ms. Activity peaked at about the same best target position for both real and virtual targets. PBN encoding of target position takes into account changes in eye position resulting from saccades, even without visual feedback. Since PBN response fields are retinotopically organized, our results suggest that activity foci associated with real and virtual targets at a given target position lie in the same physical location in the PBN, i.e., a retinotopic as well as a rate encoding of virtual-target position. We also confirm that PBN activity is specific to the intended target of a saccade and is predictive of which target will be chosen if two are offered. A Bayesian predictor-corrector model is presented that conceptually explains the differences in the dynamic ranges of PBN neuronal activity evoked during tracking of real and virtual targets. PMID:23365185

The C. elegans che-1 gene encodes a zinc finger transcription factor required for specification of the ASE chemosensory neurons.

PubMed

Uchida, Okiko; Nakano, Hiroyuki; Koga, Makoto; Ohshima, Yasumi

2003-04-01

Chemotaxis to water-soluble chemicals such as NaCl is an important behavior of C. elegans when seeking food. ASE chemosensory neurons have a major role in this behavior. We show that che-1, defined by chemotaxis defects, encodes a zinc-finger protein similar to the GLASS transcription factor required for photoreceptor cell differentiation in Drosophila, and that che-1 is essential for specification and function of ASE neurons. Expression of a che-1::gfp fusion construct was predominant in ASE. In che-1 mutants, expression of genes characterizing ASE such as seven-transmembrane receptors, guanylate cyclases and a cyclic-nucleotide gated channel is lost. Ectopic expression of che-1 cDNA induced expression of ASE-specific marker genes, a dye-filling defect in neurons other than ASE and dauer formation.

Use of suprathreshold stochastic resonance in cochlear implant coding

NASA Astrophysics Data System (ADS)

Allingham, David; Stocks, Nigel G.; Morse, Robert P.

2003-05-01

In this article we discuss the possible use of a novel form of stochastic resonance, termed suprathreshold stochastic resonance (SSR), to improve signal encoding/transmission in cochlear implants. A model, based on the leaky-integrate-and-fire (LIF) neuron, has been developed from physiological data and use to model information flow in a population of cochlear nerve fibers. It is demonstrated that information flow can, in principle, be enhanced by the SSR effect. Furthermore, SSR was found to enhance information transmission for signal parameters that are commonly encountered in cochlear implants. This, therefore, gives hope that SSR may be implemented in cochlear implants to improve speech comprehension.

Real-time modeling of primitive environments through wavelet sensors and Hebbian learning

NASA Astrophysics Data System (ADS)

Vaccaro, James M.; Yaworsky, Paul S.

1999-06-01

Modeling the world through sensory input necessarily provides a unique perspective for the observer. Given a limited perspective, objects and events cannot always be encoded precisely but must involve crude, quick approximations to deal with sensory information in a real- time manner. As an example, when avoiding an oncoming car, a pedestrian needs to identify the fact that a car is approaching before ascertaining the model or color of the vehicle. In our methodology, we use wavelet-based sensors with self-organized learning to encode basic sensory information in real-time. The wavelet-based sensors provide necessary transformations while a rank-based Hebbian learning scheme encodes a self-organized environment through translation, scale and orientation invariant sensors. Such a self-organized environment is made possible by combining wavelet sets which are orthonormal, log-scale with linear orientation and have automatically generated membership functions. In earlier work we used Gabor wavelet filters, rank-based Hebbian learning and an exponential modulation function to encode textural information from images. Many different types of modulation are possible, but based on biological findings the exponential modulation function provided a good approximation of first spike coding of `integrate and fire' neurons. These types of Hebbian encoding schemes (e.g., exponential modulation, etc.) are useful for quick response and learning, provide several advantages over contemporary neural network learning approaches, and have been found to quantize data nonlinearly. By combining wavelets with Hebbian learning we can provide a real-time front-end for modeling an intelligent process, such as the autonomous control of agents in a simulated environment.

Cortical plasticity as a mechanism for storing Bayesian priors in sensory perception.

PubMed

Köver, Hania; Bao, Shaowen

2010-05-05

Human perception of ambiguous sensory signals is biased by prior experiences. It is not known how such prior information is encoded, retrieved and combined with sensory information by neurons. Previous authors have suggested dynamic encoding mechanisms for prior information, whereby top-down modulation of firing patterns on a trial-by-trial basis creates short-term representations of priors. Although such a mechanism may well account for perceptual bias arising in the short-term, it does not account for the often irreversible and robust changes in perception that result from long-term, developmental experience. Based on the finding that more frequently experienced stimuli gain greater representations in sensory cortices during development, we reasoned that prior information could be stored in the size of cortical sensory representations. For the case of auditory perception, we use a computational model to show that prior information about sound frequency distributions may be stored in the size of primary auditory cortex frequency representations, read-out by elevated baseline activity in all neurons and combined with sensory-evoked activity to generate a perception that conforms to Bayesian integration theory. Our results suggest an alternative neural mechanism for experience-induced long-term perceptual bias in the context of auditory perception. They make the testable prediction that the extent of such perceptual prior bias is modulated by both the degree of cortical reorganization and the magnitude of spontaneous activity in primary auditory cortex. Given that cortical over-representation of frequently experienced stimuli, as well as perceptual bias towards such stimuli is a common phenomenon across sensory modalities, our model may generalize to sensory perception, rather than being specific to auditory perception.

Population coding and decoding in a neural field: a computational study.

PubMed

Wu, Si; Amari, Shun-Ichi; Nakahara, Hiroyuki

2002-05-01

This study uses a neural field model to investigate computational aspects of population coding and decoding when the stimulus is a single variable. A general prototype model for the encoding process is proposed, in which neural responses are correlated, with strength specified by a gaussian function of their difference in preferred stimuli. Based on the model, we study the effect of correlation on the Fisher information, compare the performances of three decoding methods that differ in the amount of encoding information being used, and investigate the implementation of the three methods by using a recurrent network. This study not only rediscovers main results in existing literatures in a unified way, but also reveals important new features, especially when the neural correlation is strong. As the neural correlation of firing becomes larger, the Fisher information decreases drastically. We confirm that as the width of correlation increases, the Fisher information saturates and no longer increases in proportion to the number of neurons. However, we prove that as the width increases further--wider than (sqrt)2 times the effective width of the turning function--the Fisher information increases again, and it increases without limit in proportion to the number of neurons. Furthermore, we clarify the asymptotic efficiency of the maximum likelihood inference (MLI) type of decoding methods for correlated neural signals. It shows that when the correlation covers a nonlocal range of population (excepting the uniform correlation and when the noise is extremely small), the MLI type of method, whose decoding error satisfies the Cauchy-type distribution, is not asymptotically efficient. This implies that the variance is no longer adequate to measure decoding accuracy.

BDNF mRNA abundance regulated by antidromic action potentials and AP-LTD in hippocampus.

PubMed

Bukalo, Olena; Lee, Philip R; Fields, R Douglas

2016-12-02

Action-potential-induced LTD (AP-LTD) is a form of synaptic plasticity that reduces synaptic strength in CA1 hippocampal neurons firing antidromically during sharp-wave ripples. This firing occurs during slow-wave sleep and quiet moments of wakefulness, which are periods of offline replay of neural sequences learned during encoding sensory information. Here we report that rapid and persistent down-regulation of different mRNA transcripts of the BDNF gene accompanies AP-LTD, and that AP-LTD is abolished in mice with the BDNF gene knocked out in CA1 hippocampal neurons. These findings increase understanding of the mechanism of AP-LTD and the cellular mechanisms of memory consolidation. Published by Elsevier Ireland Ltd.

Motor control by precisely timed spike patterns

PubMed Central

Srivastava, Kyle H.; Holmes, Caroline M.; Vellema, Michiel; Pack, Andrea R.; Elemans, Coen P. H.; Nemenman, Ilya; Sober, Samuel J.

2017-01-01

A fundamental problem in neuroscience is understanding how sequences of action potentials (“spikes”) encode information about sensory signals and motor outputs. Although traditional theories assume that this information is conveyed by the total number of spikes fired within a specified time interval (spike rate), recent studies have shown that additional information is carried by the millisecond-scale timing patterns of action potentials (spike timing). However, it is unknown whether or how subtle differences in spike timing drive differences in perception or behavior, leaving it unclear whether the information in spike timing actually plays a role in brain function. By examining the activity of individual motor units (the muscle fibers innervated by a single motor neuron) and manipulating patterns of activation of these neurons, we provide both correlative and causal evidence that the nervous system uses millisecond-scale variations in the timing of spikes within multispike patterns to control a vertebrate behavior—namely, respiration in the Bengalese finch, a songbird. These findings suggest that a fundamental assumption of current theories of motor coding requires revision. PMID:28100491

Visualization of Plasticity in Fear-Evoked Calcium Signals in Midbrain Dopamine Neurons

ERIC Educational Resources Information Center

Gore, Bryan B.; Soden, Marta E.; Zweifel, Larry S.

2014-01-01

Dopamine is broadly implicated in fear-related processes, yet we know very little about signaling dynamics in these neurons during active fear conditioning. We describe the direct imaging of calcium signals of dopamine neurons during Pavlovian fear conditioning using fiber-optic confocal microscopy coupled with the genetically encoded calcium…

Dynamic binding of visual features by neuronal/stimulus synchrony.

PubMed

Iwabuchi, A

1998-05-01

When people see a visual scene, certain parts of the visual scene are treated as belonging together and we regard them as a perceptual unit, which is called a "figure". People focus on figures, and the remaining parts of the scene are disregarded as "ground". In Gestalt psychology this process is called "figure-ground segregation". According to current perceptual psychology, a figure is formed by binding various visual features in a scene, and developments in neuroscience have revealed that there are many feature-encoding neurons, which respond to such features specifically. It is not known, however, how the brain binds different features of an object into a coherent visual object representation. Recently, the theory of binding by neuronal synchrony, which argues that feature binding is dynamically mediated by neuronal synchrony of feature-encoding neurons, has been proposed. This review article portrays the problem of figure-ground segregation and features binding, summarizes neurophysiological and psychophysical experiments and theory relevant to feature binding by neuronal/stimulus synchrony, and suggests possible directions for future research on this topic.

Limb-state information encoded by peripheral and central somatosensory neurons: Implications for an afferent interface

PubMed Central

Weber, Douglas J.; London, Brian M.; Hokanson, James A.; Ayers, Christopher A.; Gaunt, Robert A.; Torres, Ricardo R.; Zaaimi, Boubker; Miller, Lee E.

2013-01-01

A major issue to be addressed in the development of neural interfaces for prosthetic control is the need for somatosensory feedback. Here, we investigate two possible strategies: electrical stimulation of either dorsal root ganglia (DRG) or primary somatosensory cortex (S1). In each approach, we must determine a model that reflects the representation of limb state in terms of neural discharge. This model can then be used to design stimuli that artificially activate the nervous system to convey information about limb state to the subject. Electrically activating DRG neurons using naturalistic stimulus patterns, modeled on recordings made during passive limb movement, evoked activity in S1 that was similar to that of the original movement. We also found that S1 neural populations could accurately discriminate different patterns of DRG stimulation across a wide range of stimulus pulse-rates. In studying the neural coding of limb-state in S1, we also decoded the kinematics of active limb movement using multi-electrode recordings in the monkey. Neurons having both proprioceptive and cutaneous receptive fields contributed equally to this decoding. Some neurons were most informative of limb state in the recent past, but many others appeared to signal upcoming movements suggesting that they also were modulated by an efference copy signal. Finally, we show that a monkey was able to detect stimulation through a large percentage of electrodes implanted in area 2. We discuss the design of appropriate stimulus paradigms for conveying time-varying limb state information, and the relative merits and limitations of central and peripheral approaches. PMID:21878419

The Molecular and Cellular Basis of Bitter Taste in Drosophila

PubMed Central

Weiss, Linnea A.; Dahanukar, Anupama; Kwon, Jae Young; Banerjee, Diya; Carlson, John R.

2011-01-01

Summary The extent of diversity among bitter-sensing neurons is a fundamental issue in the field of taste. Data are limited and conflicting as to whether bitter neurons are broadly tuned and uniform, resulting in indiscriminate avoidance of bitter stimuli, or diverse, allowing a more discerning evaluation of food sources. We provide a systematic analysis of how bitter taste is encoded by the major taste organ of the Drosophila head, the labellum. Each of 16 bitter compounds is tested physiologically against all 31 bitter neurons, revealing responses that are diverse in magnitude and dynamics. Four functional classes of bitter neurons are defined. Four corresponding classes are defined through expression analysis of all 68 Gr taste receptors. A receptor-to-neuron-to-tastant map is constructed. Misexpression of one receptor confers bitter responses as predicted by the map. These results reveal a degree of complexity that greatly expands the capacity of the system to encode bitter taste. PMID:21262465

Growth Cone Localization of the mRNA Encoding the Chromatin Regulator HMGN5 Modulates Neurite Outgrowth

PubMed Central

Moretti, Francesca; Rolando, Chiara; Winker, Moritz; Ivanek, Robert; Rodriguez, Javier; Von Kriegsheim, Alex; Taylor, Verdon; Bustin, Michael

2015-01-01

Neurons exploit local mRNA translation and retrograde transport of transcription factors to regulate gene expression in response to signaling events at distal neuronal ends. Whether epigenetic factors could also be involved in such regulation is not known. We report that the mRNA encoding the high-mobility group N5 (HMGN5) chromatin binding protein localizes to growth cones of both neuron-like cells and of hippocampal neurons, where it has the potential to be translated, and that HMGN5 can be retrogradely transported into the nucleus along neurites. Loss of HMGN5 function induces transcriptional changes and impairs neurite outgrowth, while HMGN5 overexpression induces neurite outgrowth and chromatin decompaction; these effects are dependent on growth cone localization of Hmgn5 mRNA. We suggest that the localization and local translation of transcripts coding for epigenetic factors couple the dynamic neuronal outgrowth process with chromatin regulation in the nucleus. PMID:25825524

Functional imaging of hippocampal place cells at cellular resolution during virtual navigation

PubMed Central

Dombeck, Daniel A.; Harvey, Christopher D.; Tian, Lin; Looger, Loren L.; Tank, David W.

2010-01-01

Spatial navigation is a widely employed behavior in rodent studies of neuronal circuits underlying cognition, learning and memory. In vivo microscopy combined with genetically-encoded indicators provides important new tools to study neuronal circuits, but has been technically difficult to apply during navigation. We describe methods to image the activity of hippocampal CA1 neurons with sub-cellular resolution in behaving mice. Neurons expressing the genetically encoded calcium indicator GCaMP3 were imaged through a chronic hippocampal window. Head-fixed mice performed spatial behaviors within a setup combining a virtual reality system and a custom built two-photon microscope. Populations of place cells were optically identified, and the correlation between the location of their place fields in the virtual environment and their anatomical location in the local circuit was measured. The combination of virtual reality and high-resolution functional imaging should allow for a new generation of studies to probe neuronal circuit dynamics during behavior. PMID:20890294

Odor identity coding by distributed ensembles of neurons in the mouse olfactory cortex

PubMed Central

Roland, Benjamin; Deneux, Thomas; Franks, Kevin M; Bathellier, Brice; Fleischmann, Alexander

2017-01-01

Olfactory perception and behaviors critically depend on the ability to identify an odor across a wide range of concentrations. Here, we use calcium imaging to determine how odor identity is encoded in olfactory cortex. We find that, despite considerable trial-to-trial variability, odor identity can accurately be decoded from ensembles of co-active neurons that are distributed across piriform cortex without any apparent spatial organization. However, piriform response patterns change substantially over a 100-fold change in odor concentration, apparently degrading the population representation of odor identity. We show that this problem can be resolved by decoding odor identity from a subpopulation of concentration-invariant piriform neurons. These concentration-invariant neurons are overrepresented in piriform cortex but not in olfactory bulb mitral and tufted cells. We therefore propose that distinct perceptual features of odors are encoded in independent subnetworks of neurons in the olfactory cortex. DOI: http://dx.doi.org/10.7554/eLife.26337.001 PMID:28489003

Studying the mechanism of neurostimulation by infrared laser light using GCaMP6s and Rhodamine B imaging

NASA Astrophysics Data System (ADS)

Moreau, David; Lefort, Claire; Bardet, Sylvia M.; O'Connor, Rodney P.

2016-03-01

Infrared laser light radiation can be used to depolarize neurons and to stimulate neural activity. The absorption of infrared radiation and heating of biological tissue is thought to be the underlying mechanism of this phenomenon whereby local temperature increases in the plasma membrane of cells either directly influence membrane properties or act via temperature sensitive ion channels. Action potentials are typically measured electrically in neurons with microelectrodes, but they can also be observed using fluorescence microscopy techniques that use synthetic or genetically encoded calcium indicators. In this work, we studied the impact of infrared laser light on neuronal calcium signals to address the mechanism of these thermal effects. Cultured primary mouse hippocampal neurons expressing the genetically encoded calcium indicator GCaMP6s were used in combination with the temperature sensitive fluorophore Rhodamine B to measure calcium signals and temperature changes at the cellular level. Here we present our all-optical strategy for studying the influence of infrared laser light on neuronal activity.

Social and novel contexts modify hippocampal CA2 representations of space

PubMed Central

Alexander, Georgia M.; Farris, Shannon; Pirone, Jason R.; Zheng, Chenguang; Colgin, Laura L.; Dudek, Serena M.

2016-01-01

The hippocampus supports a cognitive map of space and is critical for encoding declarative memory (who, what, when and where). Recent studies have implicated hippocampal subfield CA2 in social and contextual memory but how it does so remains unknown. Here we find that in adult male rats, presentation of a social stimulus (novel or familiar rat) or a novel object induces global remapping of place fields in CA2 with no effect on neuronal firing rate or immediate early gene expression. This remapping did not occur in CA1, suggesting this effect is specific for CA2. Thus, modification of existing spatial representations might be a potential mechanism by which CA2 encodes social and novel contextual information. PMID:26806606

Detection of Interaural Time Differences in the Alligator

PubMed Central

Carr, Catherine E.; Soares, Daphne; Smolders, Jean; Simon, Jonathan Z.

2011-01-01

The auditory systems of birds and mammals use timing information from each ear to detect interaural time difference (ITD). To determine whether the Jeffress-type algorithms that underlie sensitivity to ITD in birds are an evolutionarily stable strategy, we recorded from the auditory nuclei of crocodilians, who are the sister group to the birds. In alligators, precisely timed spikes in the first-order nucleus magnocellularis (NM) encode the timing of sounds, and NM neurons project to neurons in the nucleus laminaris (NL) that detect interaural time differences. In vivo recordings from NL neurons show that the arrival time of phase-locked spikes differs between the ipsilateral and contralateral inputs. When this disparity is nullified by their best ITD, the neurons respond maximally. Thus NL neurons act as coincidence detectors. A biologically detailed model of NL with alligator parameters discriminated ITDs up to 1 kHz. The range of best ITDs represented in NL was much larger than in birds, however, and extended from 0 to 1000 μs contralateral, with a median ITD of 450 μs. Thus, crocodilians and birds employ similar algorithms for ITD detection, although crocodilians have larger heads. PMID:19553438

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders.

PubMed

Viejo, Guillaume; Cortier, Thomas; Peyrache, Adrien

2018-03-01

Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains.

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders

PubMed Central

Cortier, Thomas; Peyrache, Adrien

2018-01-01

Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains. PMID:29565979

Astrocyte glycogen and lactate: New insights into learning and memory mechanisms.

PubMed

Alberini, Cristina M; Cruz, Emmanuel; Descalzi, Giannina; Bessières, Benjamin; Gao, Virginia

2018-06-01

Memory, the ability to retain learned information, is necessary for survival. Thus far, molecular and cellular investigations of memory formation and storage have mainly focused on neuronal mechanisms. In addition to neurons, however, the brain comprises other types of cells and systems, including glia and vasculature. Accordingly, recent experimental work has begun to ask questions about the roles of non-neuronal cells in memory formation. These studies provide evidence that all types of glial cells (astrocytes, oligodendrocytes, and microglia) make important contributions to the processing of encoded information and storing memories. In this review, we summarize and discuss recent findings on the critical role of astrocytes as providers of energy for the long-lasting neuronal changes that are necessary for long-term memory formation. We focus on three main findings: first, the role of glucose metabolism and the learning- and activity-dependent metabolic coupling between astrocytes and neurons in the service of long-term memory formation; second, the role of astrocytic glucose metabolism in arousal, a state that contributes to the formation of very long-lasting and detailed memories; and finally, in light of the high energy demands of the brain during early development, we will discuss the possible role of astrocytic and neuronal glucose metabolisms in the formation of early-life memories. We conclude by proposing future directions and discussing the implications of these findings for brain health and disease. Astrocyte glycogenolysis and lactate play a critical role in memory formation. Emotionally salient experiences form strong memories by recruiting astrocytic β2 adrenergic receptors and astrocyte-generated lactate. Glycogenolysis and astrocyte-neuron metabolic coupling may also play critical roles in memory formation during development, when the energy requirements of brain metabolism are at their peak. © 2017 Wiley Periodicals, Inc.

Single neuron firing properties impact correlation-based population coding

PubMed Central

Hong, Sungho; Ratté, Stéphanie; Prescott, Steven A.; De Schutter, Erik

2012-01-01

Correlated spiking has been widely observed but its impact on neural coding remains controversial. Correlation arising from co-modulation of rates across neurons has been shown to vary with the firing rates of individual neurons. This translates into rate and correlation being equivalently tuned to the stimulus; under those conditions, correlated spiking does not provide information beyond that already available from individual neuron firing rates. Such correlations are irrelevant and can reduce coding efficiency by introducing redundancy. Using simulations and experiments in rat hippocampal neurons, we show here that pairs of neurons receiving correlated input also exhibit correlations arising from precise spike-time synchronization. Contrary to rate co-modulation, spike-time synchronization is unaffected by firing rate, thus enabling synchrony- and rate-based coding to operate independently. The type of output correlation depends on whether intrinsic neuron properties promote integration or coincidence detection: “ideal” integrators (with spike generation sensitive to stimulus mean) exhibit rate co-modulation whereas “ideal” coincidence detectors (with spike generation sensitive to stimulus variance) exhibit precise spike-time synchronization. Pyramidal neurons are sensitive to both stimulus mean and variance, and thus exhibit both types of output correlation proportioned according to which operating mode is dominant. Our results explain how different types of correlations arise based on how individual neurons generate spikes, and why spike-time synchronization and rate co-modulation can encode different stimulus properties. Our results also highlight the importance of neuronal properties for population-level coding insofar as neural networks can employ different coding schemes depending on the dominant operating mode of their constituent neurons. PMID:22279226

Developmental and sex-specific differences in expression of neuropeptides derived from allatotropin gene in the silkmoth Bombyx mori.

PubMed

Bednár, Branislav; Roller, Ladislav; Čižmár, Daniel; Mitrová, Diana; Žitňan, Dušan

2017-05-01

Allatotropin (AT) and related neuropeptides are widespread bioactive molecules that regulate development, food intake and muscle contractions in insects and other invertebrates. In moths, alternative splicing of the at gene generates three mRNA precursors encoding AT with different combinations of three structurally similar AT-like peptides (ATLI-III). We used in situ hybridization and immunohistochemistry to map the differential expression of these transcripts during the postembryonic development of Bombyx mori. Transcript encoding AT alone was expressed in numerous neurons of the central nervous system and frontal ganglion, whereas transcripts encoding AT with ATLs were produced by smaller specific subgroups of neurons in larval stages. Metamorphosis was associated with considerable developmental changes and sex-specific differences in the expression of all transcripts. The most notable was the appearance of AT/ATL transcripts (1) in the brain lateral neurosecretory cells producing prothoracicotropic hormone; (2) in the male-specific cluster of about 20 neurons in the posterior region of the terminal abdominal ganglion; (3) in the female-specific medial neurons in the abdominal ganglia AG2-7. Immunohistochemical staining showed that these neurons produced a mixture of various neuropeptides and innervated diverse peripheral organs. Our data suggest that AT/ATL neuropeptides are involved in multiple stage- and sex-specific functions during the development of B. mori.

A Bit-Encoding Based New Data Structure for Time and Memory Efficient Handling of Spike Times in an Electrophysiological Setup.

PubMed

Ljungquist, Bengt; Petersson, Per; Johansson, Anders J; Schouenborg, Jens; Garwicz, Martin

2018-04-01

Recent neuroscientific and technical developments of brain machine interfaces have put increasing demands on neuroinformatic databases and data handling software, especially when managing data in real time from large numbers of neurons. Extrapolating these developments we here set out to construct a scalable software architecture that would enable near-future massive parallel recording, organization and analysis of neurophysiological data on a standard computer. To this end we combined, for the first time in the present context, bit-encoding of spike data with a specific communication format for real time transfer and storage of neuronal data, synchronized by a common time base across all unit sources. We demonstrate that our architecture can simultaneously handle data from more than one million neurons and provide, in real time (< 25 ms), feedback based on analysis of previously recorded data. In addition to managing recordings from very large numbers of neurons in real time, it also has the capacity to handle the extensive periods of recording time necessary in certain scientific and clinical applications. Furthermore, the bit-encoding proposed has the additional advantage of allowing an extremely fast analysis of spatiotemporal spike patterns in a large number of neurons. Thus, we conclude that this architecture is well suited to support current and near-future Brain Machine Interface requirements.

The Drosophila TRPA1 Channel and Neuronal Circuits Controlling Rhythmic Behaviours and Sleep in Response to Environmental Temperature.

PubMed

Roessingh, Sanne; Stanewsky, Ralf

2017-10-03

trpA1 encodes a thermosensitive transient receptor potential channel (TRP channel) that functions in selection of preferred temperatures and noxious heat avoidance. In this review, we discuss the evidence for a role of TRPA1 in the control of rhythmic behaviours in Drosophila melanogaster . Activity levels during the afternoon and rhythmic temperature preference are both regulated by TRPA1. In contrast, TRPA1 is dispensable for temperature synchronisation of circadian clocks. We discuss the neuronal basis of TRPA1-mediated temperature effects on rhythmic behaviours, and conclude that they are mediated by partly overlapping but distinct neuronal circuits. We have previously shown that TRPA1 is required to maintain siesta sleep under warm temperature cycles. Here, we present new data investigating the neuronal circuit responsible for this regulation. First, we discuss the difficulties that remain in identifying the responsible neurons. Second, we discuss the role of clock neurons (s-LNv/DN1 network) in temperature-driven regulation of siesta sleep, and highlight the role of TRPA1 therein. Finally, we discuss the sexual dimorphic nature of siesta sleep and propose that the s-LNv/DN1 clock network could play a role in the integration of environmental information, mating status and other internal drives, to appropriately drive adaptive sleep/wake behaviour.

Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task

PubMed Central

Mochizuki, Kei

2015-01-01

While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. PMID:26490287

Molecular codes for neuronal individuality and cell assembly in the brain

PubMed Central

Yagi, Takeshi

2012-01-01

The brain contains an enormous, but finite, number of neurons. The ability of this limited number of neurons to produce nearly limitless neural information over a lifetime is typically explained by combinatorial explosion; that is, by the exponential amplification of each neuron's contribution through its incorporation into “cell assemblies” and neural networks. In development, each neuron expresses diverse cellular recognition molecules that permit the formation of the appropriate neural cell assemblies to elicit various brain functions. The mechanism for generating neuronal assemblies and networks must involve molecular codes that give neurons individuality and allow them to recognize one another and join appropriate networks. The extensive molecular diversity of cell-surface proteins on neurons is likely to contribute to their individual identities. The clustered protocadherins (Pcdh) is a large subfamily within the diverse cadherin superfamily. The clustered Pcdh genes are encoded in tandem by three gene clusters, and are present in all known vertebrate genomes. The set of clustered Pcdh genes is expressed in a random and combinatorial manner in each neuron. In addition, cis-tetramers composed of heteromultimeric clustered Pcdh isoforms represent selective binding units for cell-cell interactions. Here I present the mathematical probabilities for neuronal individuality based on the random and combinatorial expression of clustered Pcdh isoforms and their formation of cis-tetramers in each neuron. Notably, clustered Pcdh gene products are known to play crucial roles in correct axonal projections, synaptic formation, and neuronal survival. Their molecular and biological features induce a hypothesis that the diverse clustered Pcdh molecules provide the molecular code by which neuronal individuality and cell assembly permit the combinatorial explosion of networks that supports enormous processing capability and plasticity of the brain. PMID:22518100

Optogenetics: a new enlightenment age for zebrafish neurobiology.

PubMed

Del Bene, Filippo; Wyart, Claire

2012-03-01

Zebrafish became a model of choice for neurobiology because of the transparency of its brain and because of its amenability to genetic manipulation. In particular, at early stages of development the intact larva is an ideal system to apply optical techniques for deep imaging in the nervous system, as well as genetically encoded tools for targeting subsets of neurons and monitoring and manipulating their activity. For these applications,new genetically encoded optical tools, fluorescent sensors, and light-gated channels have been generated,creating the field of "optogenetics." It is now possible to monitor and control neuronal activity with minimal perturbation and unprecedented spatio-temporal resolution.We describe here the main achievements that have occurred in the last decade in imaging and manipulating neuronal activity in intact zebrafish larvae. We provide also examples of functional dissection of neuronal circuits achieved with the applications of these techniques in the visual and locomotor systems.

Image statistics underlying natural texture selectivity of neurons in macaque V4

PubMed Central

Okazawa, Gouki; Tajima, Satohiro; Komatsu, Hidehiko

2015-01-01

Our daily visual experiences are inevitably linked to recognizing the rich variety of textures. However, how the brain encodes and differentiates a plethora of natural textures remains poorly understood. Here, we show that many neurons in macaque V4 selectively encode sparse combinations of higher-order image statistics to represent natural textures. We systematically explored neural selectivity in a high-dimensional texture space by combining texture synthesis and efficient-sampling techniques. This yielded parameterized models for individual texture-selective neurons. The models provided parsimonious but powerful predictors for each neuron’s preferred textures using a sparse combination of image statistics. As a whole population, the neuronal tuning was distributed in a way suitable for categorizing textures and quantitatively predicts human ability to discriminate textures. Together, we suggest that the collective representation of visual image statistics in V4 plays a key role in organizing the natural texture perception. PMID:25535362

In silico Evolutionary Developmental Neurobiology and the Origin of Natural Language

NASA Astrophysics Data System (ADS)

Szathmáry, Eörs; Szathmáry, Zoltán; Ittzés, Péter; Orbaán, Geroő; Zachár, István; Huszár, Ferenc; Fedor, Anna; Varga, Máté; Számadó, Szabolcs

It is justified to assume that part of our genetic endowment contributes to our language skills, yet it is impossible to tell at this moment exactly how genes affect the language faculty. We complement experimental biological studies by an in silico approach in that we simulate the evolution of neuronal networks under selection for language-related skills. At the heart of this project is the Evolutionary Neurogenetic Algorithm (ENGA) that is deliberately biomimetic. The design of the system was inspired by important biological phenomena such as brain ontogenesis, neuron morphologies, and indirect genetic encoding. Neuronal networks were selected and were allowed to reproduce as a function of their performance in the given task. The selected neuronal networks in all scenarios were able to solve the communication problem they had to face. The most striking feature of the model is that it works with highly indirect genetic encoding--just as brains do.

Fly Photoreceptors Encode Phase Congruency

PubMed Central

Friederich, Uwe; Billings, Stephen A.; Hardie, Roger C.; Juusola, Mikko; Coca, Daniel

2016-01-01

More than five decades ago it was postulated that sensory neurons detect and selectively enhance behaviourally relevant features of natural signals. Although we now know that sensory neurons are tuned to efficiently encode natural stimuli, until now it was not clear what statistical features of the stimuli they encode and how. Here we reverse-engineer the neural code of Drosophila photoreceptors and show for the first time that photoreceptors exploit nonlinear dynamics to selectively enhance and encode phase-related features of temporal stimuli, such as local phase congruency, which are invariant to changes in illumination and contrast. We demonstrate that to mitigate for the inherent sensitivity to noise of the local phase congruency measure, the nonlinear coding mechanisms of the fly photoreceptors are tuned to suppress random phase signals, which explains why photoreceptor responses to naturalistic stimuli are significantly different from their responses to white noise stimuli. PMID:27336733

Impaired Dendritic Development and Memory in Sorbs2 Knock-Out Mice.

PubMed

Zhang, Qiangge; Gao, Xian; Li, Chenchen; Feliciano, Catia; Wang, Dongqing; Zhou, Dingxi; Mei, Yuan; Monteiro, Patricia; Anand, Michelle; Itohara, Shigeyoshi; Dong, Xiaowei; Fu, Zhanyan; Feng, Guoping

2016-02-17

Intellectual disability is a common neurodevelopmental disorder characterized by impaired intellectual and adaptive functioning. Both environmental insults and genetic defects contribute to the etiology of intellectual disability. Copy number variations of SORBS2 have been linked to intellectual disability. However, the neurobiological function of SORBS2 in the brain is unknown. The SORBS2 gene encodes ArgBP2 (Arg/c-Abl kinase binding protein 2) protein in non-neuronal tissues and is alternatively spliced in the brain to encode nArgBP2 protein. We found nArgBP2 colocalized with F-actin at dendritic spines and growth cones in cultured hippocampal neurons. In the mouse brain, nArgBP2 was highly expressed in the cortex, amygdala, and hippocampus, and enriched in the outer one-third of the molecular layer in dentate gyrus. Genetic deletion of Sorbs2 in mice led to reduced dendritic complexity and decreased frequency of AMPAR-miniature spontaneous EPSCs in dentate gyrus granule cells. Behavioral characterization revealed that Sorbs2 deletion led to a reduced acoustic startle response, and defective long-term object recognition memory and contextual fear memory. Together, our findings demonstrate, for the first time, an important role for nArgBP2 in neuronal dendritic development and excitatory synaptic transmission, which may thus inform exploration of neurobiological basis of SORBS2 deficiency in intellectual disability. Copy number variations of the SORBS2 gene are linked to intellectual disability, but the neurobiological mechanisms are unknown. We found that nArgBP2, the only neuronal isoform encoded by SORBS2, colocalizes with F-actin at neuronal dendritic growth cones and spines. nArgBP2 is highly expressed in the cortex, amygdala, and dentate gyrus in the mouse brain. Genetic deletion of Sorbs2 in mice leads to impaired dendritic complexity and reduced excitatory synaptic transmission in dentate gyrus granule cells, accompanied by behavioral deficits in acoustic startle response and long-term memory. This is the first study of Sorbs2 function in the brain, and our findings may facilitate the study of neurobiological mechanisms underlying SORBS2 deficiency in the development of intellectual disability. Copyright © 2016 the authors 0270-6474/16/362248-14$15.00/0.

Automatically tracking neurons in a moving and deforming brain

PubMed Central

Nguyen, Jeffrey P.; Linder, Ashley N.; Plummer, George S.; Shaevitz, Joshua W.

2017-01-01

Advances in optical neuroimaging techniques now allow neural activity to be recorded with cellular resolution in awake and behaving animals. Brain motion in these recordings pose a unique challenge. The location of individual neurons must be tracked in 3D over time to accurately extract single neuron activity traces. Recordings from small invertebrates like C. elegans are especially challenging because they undergo very large brain motion and deformation during animal movement. Here we present an automated computer vision pipeline to reliably track populations of neurons with single neuron resolution in the brain of a freely moving C. elegans undergoing large motion and deformation. 3D volumetric fluorescent images of the animal’s brain are straightened, aligned and registered, and the locations of neurons in the images are found via segmentation. Each neuron is then assigned an identity using a new time-independent machine-learning approach we call Neuron Registration Vector Encoding. In this approach, non-rigid point-set registration is used to match each segmented neuron in each volume with a set of reference volumes taken from throughout the recording. The way each neuron matches with the references defines a feature vector which is clustered to assign an identity to each neuron in each volume. Finally, thin-plate spline interpolation is used to correct errors in segmentation and check consistency of assigned identities. The Neuron Registration Vector Encoding approach proposed here is uniquely well suited for tracking neurons in brains undergoing large deformations. When applied to whole-brain calcium imaging recordings in freely moving C. elegans, this analysis pipeline located 156 neurons for the duration of an 8 minute recording and consistently found more neurons more quickly than manual or semi-automated approaches. PMID:28545068

Automatically tracking neurons in a moving and deforming brain.

PubMed

Nguyen, Jeffrey P; Linder, Ashley N; Plummer, George S; Shaevitz, Joshua W; Leifer, Andrew M

2017-05-01

Advances in optical neuroimaging techniques now allow neural activity to be recorded with cellular resolution in awake and behaving animals. Brain motion in these recordings pose a unique challenge. The location of individual neurons must be tracked in 3D over time to accurately extract single neuron activity traces. Recordings from small invertebrates like C. elegans are especially challenging because they undergo very large brain motion and deformation during animal movement. Here we present an automated computer vision pipeline to reliably track populations of neurons with single neuron resolution in the brain of a freely moving C. elegans undergoing large motion and deformation. 3D volumetric fluorescent images of the animal's brain are straightened, aligned and registered, and the locations of neurons in the images are found via segmentation. Each neuron is then assigned an identity using a new time-independent machine-learning approach we call Neuron Registration Vector Encoding. In this approach, non-rigid point-set registration is used to match each segmented neuron in each volume with a set of reference volumes taken from throughout the recording. The way each neuron matches with the references defines a feature vector which is clustered to assign an identity to each neuron in each volume. Finally, thin-plate spline interpolation is used to correct errors in segmentation and check consistency of assigned identities. The Neuron Registration Vector Encoding approach proposed here is uniquely well suited for tracking neurons in brains undergoing large deformations. When applied to whole-brain calcium imaging recordings in freely moving C. elegans, this analysis pipeline located 156 neurons for the duration of an 8 minute recording and consistently found more neurons more quickly than manual or semi-automated approaches.

Implementing Signature Neural Networks with Spiking Neurons

PubMed Central

Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm—i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data—to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks. PMID:28066221

Implementing Signature Neural Networks with Spiking Neurons.

PubMed

Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks.

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

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.

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.

Early Monocular Defocus Disrupts the Normal Development of Receptive-Field Structure in V2 Neurons of Macaque Monkeys

PubMed Central

Tao, Xiaofeng; Zhang, Bin; Shen, Guofu; Wensveen, Janice; Smith, Earl L.; Nishimoto, Shinji; Ohzawa, Izumi

2014-01-01

Experiencing different quality images in the two eyes soon after birth can cause amblyopia, a developmental vision disorder. Amblyopic humans show the reduced capacity for judging the relative position of a visual target in reference to nearby stimulus elements (position uncertainty) and often experience visual image distortion. Although abnormal pooling of local stimulus information by neurons beyond striate cortex (V1) is often suggested as a neural basis of these deficits, extrastriate neurons in the amblyopic brain have rarely been studied using microelectrode recording methods. The receptive field (RF) of neurons in visual area V2 in normal monkeys is made up of multiple subfields that are thought to reflect V1 inputs and are capable of encoding the spatial relationship between local stimulus features. We created primate models of anisometropic amblyopia and analyzed the RF subfield maps for multiple nearby V2 neurons of anesthetized monkeys by using dynamic two-dimensional noise stimuli and reverse correlation methods. Unlike in normal monkeys, the subfield maps of V2 neurons in amblyopic monkeys were severely disorganized: subfield maps showed higher heterogeneity within each neuron as well as across nearby neurons. Amblyopic V2 neurons exhibited robust binocular suppression and the strength of the suppression was positively correlated with the degree of hereogeneity and the severity of amblyopia in individual monkeys. Our results suggest that the disorganized subfield maps and robust binocular suppression of amblyopic V2 neurons are likely to adversely affect the higher stages of cortical processing resulting in position uncertainty and image distortion. PMID:25297110

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.

Rapid acquisition of novel interface control by small ensembles of arbitrarily selected primary motor cortex neurons

PubMed Central

Law, Andrew J.; Rivlis, Gil

2014-01-01

Pioneering studies demonstrated that novel degrees of freedom could be controlled individually by directly encoding the firing rate of single motor cortex neurons, without regard to each neuron's role in controlling movement of the native limb. In contrast, recent brain-computer interface work has emphasized decoding outputs from large ensembles that include substantially more neurons than the number of degrees of freedom being controlled. To bridge the gap between direct encoding by single neurons and decoding output from large ensembles, we studied monkeys controlling one degree of freedom by comodulating up to four arbitrarily selected motor cortex neurons. Performance typically exceeded random quite early in single sessions and then continued to improve to different degrees in different sessions. We therefore examined factors that might affect performance. Performance improved with larger ensembles. In contrast, other factors that might have reflected preexisting synaptic architecture—such as the similarity of preferred directions—had little if any effect on performance. Patterns of comodulation among ensemble neurons became more consistent across trials as performance improved over single sessions. Compared with the ensemble neurons, other simultaneously recorded neurons showed less modulation. Patterns of voluntarily comodulated firing among small numbers of arbitrarily selected primary motor cortex (M1) neurons thus can be found and improved rapidly, with little constraint based on the normal relationships of the individual neurons to native limb movement. This rapid flexibility in relationships among M1 neurons may in part underlie our ability to learn new movements and improve motor skill. PMID:24920030

Visual Stimuli Induce Waves of Electrical Activity in Turtle Cortex

NASA Astrophysics Data System (ADS)

Prechtl, J. C.; Cohen, L. B.; Pesaran, B.; Mitra, P. P.; Kleinfeld, D.

1997-07-01

The computations involved in the processing of a visual scene invariably involve the interactions among neurons throughout all of visual cortex. One hypothesis is that the timing of neuronal activity, as well as the amplitude of activity, provides a means to encode features of objects. The experimental data from studies on cat [Gray, C. M., Konig, P., Engel, A. K. & Singer, W. (1989) Nature (London) 338, 334-337] support a view in which only synchronous (no phase lags) activity carries information about the visual scene. In contrast, theoretical studies suggest, on the one hand, the utility of multiple phases within a population of neurons as a means to encode independent visual features and, on the other hand, the likely existence of timing differences solely on the basis of network dynamics. Here we use widefield imaging in conjunction with voltage-sensitive dyes to record electrical activity from the virtually intact, unanesthetized turtle brain. Our data consist of single-trial measurements. We analyze our data in the frequency domain to isolate coherent events that lie in different frequency bands. Low frequency oscillations (<5 Hz) are seen in both ongoing activity and activity induced by visual stimuli. These oscillations propagate parallel to the afferent input. Higher frequency activity, with spectral peaks near 10 and 20 Hz, is seen solely in response to stimulation. This activity consists of plane waves and spiral-like waves, as well as more complex patterns. The plane waves have an average phase gradient of ≈ π /2 radians/mm and propagate orthogonally to the low frequency waves. Our results show that large-scale differences in neuronal timing are present and persistent during visual processing.

Reduced Neuronal Transcription of Escargot, the Drosophila Gene Encoding a Snail-Type Transcription Factor, Promotes Longevity

PubMed Central

Symonenko, Alexander V.; Roshina, Natalia V.; Krementsova, Anna V.; Pasyukova, Elena G.

2018-01-01

In recent years, several genes involved in complex neuron specification networks have been shown to control life span. However, information on these genes is scattered, and studies to discover new neuronal genes and gene cascades contributing to life span control are needed, especially because of the recognized role of the nervous system in governing homeostasis, aging, and longevity. Previously, we demonstrated that several genes that encode RNA polymerase II transcription factors and that are involved in the development of the nervous system affect life span in Drosophila melanogaster. Among other genes, escargot (esg) was demonstrated to be causally associated with an increase in the life span of male flies. Here, we present new data on the role of esg in life span control. We show that esg affects the life spans of both mated and unmated males and females to varying degrees. By analyzing the survival and locomotion of the esg mutants, we demonstrate that esg is involved in the control of aging. We show that increased longevity is caused by decreased esg transcription. In particular, we demonstrate that esg knockdown in the nervous system increased life span, directly establishing the involvement of the neuronal esg function in life span control. Our data invite attention to the mechanisms regulating the esg transcription rate, which is changed by insertions of DNA fragments of different sizes downstream of the structural part of the gene, indicating the direction of further research. Our data agree with the previously made suggestion that alterations in gene expression during development might affect adult lifespan, due to epigenetic patterns inherited in cell lineages or predetermined during the development of the structural and functional properties of the nervous system. PMID:29760717

Rapid processing of chemosensor transients in a neuromorphic implementation of the insect macroglomerular complex

PubMed Central

Pearce, Timothy C.; Karout, Salah; Rácz, Zoltán; Capurro, Alberto; Gardner, Julian W.; Cole, Marina

2012-01-01

We present a biologically-constrained neuromorphic spiking model of the insect antennal lobe macroglomerular complex that encodes concentration ratios of chemical components existing within a blend, implemented using a set of programmable logic neuronal modeling cores. Depending upon the level of inhibition and symmetry in its inhibitory connections, the model exhibits two dynamical regimes: fixed point attractor (winner-takes-all type), and limit cycle attractor (winnerless competition type) dynamics. We show that, when driven by chemosensor input in real-time, the dynamical trajectories of the model's projection neuron population activity accurately encode the concentration ratios of binary odor mixtures in both dynamical regimes. By deploying spike timing-dependent plasticity in a subset of the synapses in the model, we demonstrate that a Hebbian-like associative learning rule is able to organize weights into a stable configuration after exposure to a randomized training set comprising a variety of input ratios. Examining the resulting local interneuron weights in the model shows that each inhibitory neuron competes to represent possible ratios across the population, forming a ratiometric representation via mutual inhibition. After training the resulting dynamical trajectories of the projection neuron population activity show amplification and better separation in their response to inputs of different ratios. Finally, we demonstrate that by using limit cycle attractor dynamics, it is possible to recover and classify blend ratio information from the early transient phases of chemosensor responses in real-time more rapidly and accurately compared to a nearest-neighbor classifier applied to the normalized chemosensor data. Our results demonstrate the potential of biologically-constrained neuromorphic spiking models in achieving rapid and efficient classification of early phase chemosensor array transients with execution times well beyond biological timescales. PMID:23874265

Visual stimuli induce waves of electrical activity in turtle cortex

PubMed Central

Prechtl, J. C.; Cohen, L. B.; Pesaran, B.; Mitra, P. P.; Kleinfeld, D.

1997-01-01

The computations involved in the processing of a visual scene invariably involve the interactions among neurons throughout all of visual cortex. One hypothesis is that the timing of neuronal activity, as well as the amplitude of activity, provides a means to encode features of objects. The experimental data from studies on cat [Gray, C. M., Konig, P., Engel, A. K. & Singer, W. (1989) Nature (London) 338, 334–337] support a view in which only synchronous (no phase lags) activity carries information about the visual scene. In contrast, theoretical studies suggest, on the one hand, the utility of multiple phases within a population of neurons as a means to encode independent visual features and, on the other hand, the likely existence of timing differences solely on the basis of network dynamics. Here we use widefield imaging in conjunction with voltage-sensitive dyes to record electrical activity from the virtually intact, unanesthetized turtle brain. Our data consist of single-trial measurements. We analyze our data in the frequency domain to isolate coherent events that lie in different frequency bands. Low frequency oscillations (<5 Hz) are seen in both ongoing activity and activity induced by visual stimuli. These oscillations propagate parallel to the afferent input. Higher frequency activity, with spectral peaks near 10 and 20 Hz, is seen solely in response to stimulation. This activity consists of plane waves and spiral-like waves, as well as more complex patterns. The plane waves have an average phase gradient of ≈π/2 radians/mm and propagate orthogonally to the low frequency waves. Our results show that large-scale differences in neuronal timing are present and persistent during visual processing. PMID:9207142

Ventral Pallidum Encodes Contextual Information and Controls Aversive Behaviors.

PubMed

Saga, Yosuke; Richard, Augustin; Sgambato-Faure, Véronique; Hoshi, Eiji; Tobler, Philippe N; Tremblay, Léon

2017-04-01

Successful avoidance of aversive outcomes is crucial for the survival of animals. Although accumulating evidence indicates that an indirect pathway in the basal ganglia is involved in aversive behavior, the ventral pallidum (VP), which is an important component of this pathway, has so far been implicated primarily in appetitive behavior. In this study, we used single-cell recordings and bicuculline (GABAA antagonist) injections to elucidate the role of VP both in the encoding of aversive context and in active avoidance. We found 2 populations of neurons that were preferentially activated by appetitive and aversive conditioned stimuli (CSs). In addition, VP showed appetitive and aversive outcome anticipatory activities. These activity patterns indicate that VP is involved in encoding and maintaining CS-induced aversive contextual information. Furthermore, the disturbance of VP activity by bicuculline injection increased the number of error trials in aversive trials. In particular, the subjects released the response bar prematurely, showed no response at all, or failed to avoid the aversive outcome. Overall, these results suggest that VP plays a central role in controlling CS-induced negative motivation to produce avoidance behavior. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Dynamical encoding of looming, receding, and focussing

NASA Astrophysics Data System (ADS)

Longtin, Andre; Clarke, Stephen Elisha; Maler, Leonard; CenterNeural Dynamics Collaboration

This talk will discuss a non-conventional neural coding task that may apply more broadly to many senses in higher vertebrates. We ask whether and how a non-visual sensory system can focus on an object. We present recent experimental and modeling work that shows how the early sensory circuitry of electric sense can perform such neuronal focusing that is manifested behaviorally. This sense is the main one used by weakly electric fish to navigate, locate prey and communicate in the murky waters of their natural habitat. We show that there is a distance at which the Fisher information of a neuron's response to a looming and receding object is maximized, and that this distance corresponds to a behaviorally relevant one chosen by these animals. Strikingly, this maximum occurs at a bifurcation between tonic firing and bursting. We further discuss how the invariance of this distance to signal attributes can arise, a process that first involves power-law spike frequency adaptation. The talk will also highlight the importance of expanding the classic dual neural encoding of contrast using ON and OFF cells in the context of looming and receding stimuli. The authors acknowledge support from CIHR and NSERC.

Distinct Fos-Expressing Neuronal Ensembles in the Ventromedial Prefrontal Cortex Mediate Food Reward and Extinction Memories

PubMed Central

Warren, Brandon L.; Mendoza, Michael P.; Cruz, Fabio C.; Leao, Rodrigo M.; Caprioli, Daniele; Rubio, F. Javier; Whitaker, Leslie R.; McPherson, Kylie B.; Bossert, Jennifer M.; Shaham, Yavin

2016-01-01

In operant learning, initial reward-associated memories are thought to be distinct from subsequent extinction-associated memories. Memories formed during operant learning are thought to be stored in “neuronal ensembles.” Thus, we hypothesize that different neuronal ensembles encode reward- and extinction-associated memories. Here, we examined prefrontal cortex neuronal ensembles involved in the recall of reward and extinction memories of food self-administration. We first trained rats to lever press for palatable food pellets for 7 d (1 h/d) and then exposed them to 0, 2, or 7 daily extinction sessions in which lever presses were not reinforced. Twenty-four hours after the last training or extinction session, we exposed the rats to either a short 15 min extinction test session or left them in their homecage (a control condition). We found maximal Fos (a neuronal activity marker) immunoreactivity in the ventral medial prefrontal cortex of rats that previously received 2 extinction sessions, suggesting that neuronal ensembles in this area encode extinction memories. We then used the Daun02 inactivation procedure to selectively disrupt ventral medial prefrontal cortex neuronal ensembles that were activated during the 15 min extinction session following 0 (no extinction) or 2 prior extinction sessions to determine the effects of inactivating the putative food reward and extinction ensembles, respectively, on subsequent nonreinforced food seeking 2 d later. Inactivation of the food reward ensembles decreased food seeking, whereas inactivation of the extinction ensembles increased food seeking. Our results indicate that distinct neuronal ensembles encoding operant reward and extinction memories intermingle within the same cortical area. SIGNIFICANCE STATEMENT A current popular hypothesis is that neuronal ensembles in different prefrontal cortex areas control reward-associated versus extinction-associated memories: the dorsal medial prefrontal cortex (mPFC) promotes reward seeking, whereas the ventral mPFC inhibits reward seeking. In this paper, we use the Daun02 chemogenetic inactivation procedure to demonstrate that Fos-expressing neuronal ensembles mediating both food reward and extinction memories intermingle within the same ventral mPFC area. PMID:27335401

Distinct Fos-Expressing Neuronal Ensembles in the Ventromedial Prefrontal Cortex Mediate Food Reward and Extinction Memories.

PubMed

Warren, Brandon L; Mendoza, Michael P; Cruz, Fabio C; Leao, Rodrigo M; Caprioli, Daniele; Rubio, F Javier; Whitaker, Leslie R; McPherson, Kylie B; Bossert, Jennifer M; Shaham, Yavin; Hope, Bruce T

2016-06-22

In operant learning, initial reward-associated memories are thought to be distinct from subsequent extinction-associated memories. Memories formed during operant learning are thought to be stored in "neuronal ensembles." Thus, we hypothesize that different neuronal ensembles encode reward- and extinction-associated memories. Here, we examined prefrontal cortex neuronal ensembles involved in the recall of reward and extinction memories of food self-administration. We first trained rats to lever press for palatable food pellets for 7 d (1 h/d) and then exposed them to 0, 2, or 7 daily extinction sessions in which lever presses were not reinforced. Twenty-four hours after the last training or extinction session, we exposed the rats to either a short 15 min extinction test session or left them in their homecage (a control condition). We found maximal Fos (a neuronal activity marker) immunoreactivity in the ventral medial prefrontal cortex of rats that previously received 2 extinction sessions, suggesting that neuronal ensembles in this area encode extinction memories. We then used the Daun02 inactivation procedure to selectively disrupt ventral medial prefrontal cortex neuronal ensembles that were activated during the 15 min extinction session following 0 (no extinction) or 2 prior extinction sessions to determine the effects of inactivating the putative food reward and extinction ensembles, respectively, on subsequent nonreinforced food seeking 2 d later. Inactivation of the food reward ensembles decreased food seeking, whereas inactivation of the extinction ensembles increased food seeking. Our results indicate that distinct neuronal ensembles encoding operant reward and extinction memories intermingle within the same cortical area. A current popular hypothesis is that neuronal ensembles in different prefrontal cortex areas control reward-associated versus extinction-associated memories: the dorsal medial prefrontal cortex (mPFC) promotes reward seeking, whereas the ventral mPFC inhibits reward seeking. In this paper, we use the Daun02 chemogenetic inactivation procedure to demonstrate that Fos-expressing neuronal ensembles mediating both food reward and extinction memories intermingle within the same ventral mPFC area. Copyright © 2016 the authors 0270-6474/16/366691-13$15.00/0.

Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

PubMed

Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

2011-01-01

One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

Inhibition delay increases neural network capacity through Stirling transform.

PubMed

Nogaret, Alain; King, Alastair

2018-03-01

Inhibitory neural networks are found to encode high volumes of information through delayed inhibition. We show that inhibition delay increases storage capacity through a Stirling transform of the minimum capacity which stabilizes locally coherent oscillations. We obtain both the exact and asymptotic formulas for the total number of dynamic attractors. Our results predict a (ln2)^{-N}-fold increase in capacity for an N-neuron network and demonstrate high-density associative memories which host a maximum number of oscillations in analog neural devices.

Inhibition delay increases neural network capacity through Stirling transform

NASA Astrophysics Data System (ADS)

Nogaret, Alain; King, Alastair

2018-03-01

Inhibitory neural networks are found to encode high volumes of information through delayed inhibition. We show that inhibition delay increases storage capacity through a Stirling transform of the minimum capacity which stabilizes locally coherent oscillations. We obtain both the exact and asymptotic formulas for the total number of dynamic attractors. Our results predict a (ln2) -N-fold increase in capacity for an N -neuron network and demonstrate high-density associative memories which host a maximum number of oscillations in analog neural devices.

Scale Invariance in Lateral Head Scans During Spatial Exploration.

PubMed

Yadav, Chetan K; Doreswamy, Yoganarasimha

2017-04-14

Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.

Scale Invariance in Lateral Head Scans During Spatial Exploration

NASA Astrophysics Data System (ADS)

Yadav, Chetan K.; Doreswamy, Yoganarasimha

2017-04-01

Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.

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

Hippocampal neural correlates for values of experienced events.

PubMed

Lee, Hyunjung; Ghim, Jeong-Wook; Kim, Hoseok; Lee, Daeyeol; Jung, MinWhan

2012-10-24

Newly experienced events are often remembered together with how rewarding the experiences are personally. Although the hippocampus is a candidate structure where subjective values are integrated with other elements of episodic memory, it is uncertain whether and how the hippocampus processes value-related information. We examined how activity of dorsal CA1 and dorsal subicular neurons in rats performing a dynamic foraging task was related to reward values that were estimated using a reinforcement learning model. CA1 neurons carried significant signals related to action values before the animal revealed its choice behaviorally, indicating that the information on the expected values of potential choice outcomes was available in CA1. Moreover, after the outcome of the animal's goal choice was revealed, CA1 neurons carried robust signals for the value of chosen action and they temporally overlapped with the signals related to the animal's goal choice and its outcome, indicating that all the signals necessary to evaluate the outcome of an experienced event converged in CA1. On the other hand, value-related signals were substantially weaker in the subiculum. These results suggest a major role of CA1 in adding values to experienced events during episodic memory encoding. Given that CA1 neuronal activity is modulated by diverse attributes of an experienced event, CA1 might be a place where all the elements of episodic memory are integrated.

Negative Correlations in Visual Cortical Networks

PubMed Central

Chelaru, Mircea I.; Dragoi, Valentin

2016-01-01

The amount of information encoded by cortical circuits depends critically on the capacity of nearby neurons to exhibit trial-to-trial (noise) correlations in their responses. Depending on their sign and relationship to signal correlations, noise correlations can either increase or decrease the population code accuracy relative to uncorrelated neuronal firing. Whereas positive noise correlations have been extensively studied using experimental and theoretical tools, the functional role of negative correlations in cortical circuits has remained elusive. We addressed this issue by performing multiple-electrode recording in the superficial layers of the primary visual cortex (V1) of alert monkey. Despite the fact that positive noise correlations decayed exponentially with the difference in the orientation preference between cells, negative correlations were uniformly distributed across the population. Using a statistical model for Fisher Information estimation, we found that a mild increase in negative correlations causes a sharp increase in network accuracy even when mean correlations were held constant. To examine the variables controlling the strength of negative correlations, we implemented a recurrent spiking network model of V1. We found that increasing local inhibition and reducing excitation causes a decrease in the firing rates of neurons while increasing the negative noise correlations, which in turn increase the population signal-to-noise ratio and network accuracy. Altogether, these results contribute to our understanding of the neuronal mechanism involved in the generation of negative correlations and their beneficial impact on cortical circuit function. PMID:25217468

In search of a recognition memory engram

PubMed Central

Brown, M.W.; Banks, P.J.

2015-01-01

A large body of data from human and animal studies using psychological, recording, imaging, and lesion techniques indicates that recognition memory involves at least two separable processes: familiarity discrimination and recollection. Familiarity discrimination for individual visual stimuli seems to be effected by a system centred on the perirhinal cortex of the temporal lobe. The fundamental change that encodes prior occurrence within the perirhinal cortex is a reduction in the responses of neurones when a stimulus is repeated. Neuronal network modelling indicates that a system based on such a change in responsiveness is potentially highly efficient in information theoretic terms. A review is given of findings indicating that perirhinal cortex acts as a storage site for recognition memory of objects and that such storage depends upon processes producing synaptic weakening. PMID:25280908

Roles of somatic A-type K(+) channels in the synaptic plasticity of hippocampal neurons.

PubMed

Yang, Yoon-Sil; Kim, Kyeong-Deok; Eun, Su-Yong; Jung, Sung-Cherl

2014-06-01

In the mammalian brain, information encoding and storage have been explained by revealing the cellular and molecular mechanisms of synaptic plasticity at various levels in the central nervous system, including the hippocampus and the cerebral cortices. The modulatory mechanisms of synaptic excitability that are correlated with neuronal tasks are fundamental factors for synaptic plasticity, and they are dependent on intracellular Ca(2+)-mediated signaling. In the present review, the A-type K(+) (IA) channel, one of the voltage-dependent cation channels, is considered as a key player in the modulation of Ca(2+) influx through synaptic NMDA receptors and their correlated signaling pathways. The cellular functions of IA channels indicate that they possibly play as integral parts of synaptic and somatic complexes, completing the initiation and stabilization of memory.

The C. elegans ceh-36 gene encodes a putative homemodomain transcription factor involved in chemosensory functions of ASE and AWC neurons.

PubMed

Koga, Makoto; Ohshima, Yasumi

2004-02-20

Chemotaxis to water-soluble chemicals such as sodium ion is an important behavior of Caenorhabditis elegans for seeking food, and ASE chemosensory neurons have a major role in this behavior. We isolated mutants defective in chemotaxis to sodium acetate. We show here that among them ks86 had a mutation in the ceh-36 gene. ceh-36 :: gfp reporter constructs were expressed in ASE and AWC neurons. In a mutant of the che-1 gene, which encodes another transcription factor and is required for specification of ASE neurons, expression of the ceh-36 :: gfp reporter in ASE is lost. This indicates that the ceh-36 gene functions downstream of the che-1 gene in ASE. In the ceh-36(ks86) mutant, expression of the tax-2 gene encoding a cyclic nucleotide-gated channel was reduced in ASE and AWC. This affords an explanation for defects of the ceh-36 mutant in the chemotaxis mediated by ASE and AWC. When a ceh-36 cDNA was expressed in an adult ceh-36 mutant by a heat shock promoter, chemotaxis to sodium acetate was recovered. These results suggest that ceh-36 is required for functions, and not for development, of ASE.

An online supervised learning method based on gradient descent for spiking neurons.

PubMed

Xu, Yan; Yang, Jing; Zhong, Shuiming

2017-09-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Learning to attend: modeling the shaping of selectivity in infero-temporal cortex in a categorization task.

PubMed

Szabo, Miruna; Deco, Gustavo; Fusi, Stefano; Del Giudice, Paolo; Mattia, Maurizio; Stetter, Martin

2006-05-01

Recent experiments on behaving monkeys have shown that learning a visual categorization task makes the neurons in infero-temporal cortex (ITC) more selective to the task-relevant features of the stimuli (Sigala and Logothetis in Nature 415 318-320, 2002). We hypothesize that such a selectivity modulation emerges from the interaction between ITC and other cortical area, presumably the prefrontal cortex (PFC), where the previously learned stimulus categories are encoded. We propose a biologically inspired model of excitatory and inhibitory spiking neurons with plastic synapses, modified according to a reward based Hebbian learning rule, to explain the experimental results and test the validity of our hypothesis. We assume that the ITC neurons, receiving feature selective inputs, form stronger connections with the category specific neurons to which they are consistently associated in rewarded trials. After learning, the top-down influence of PFC neurons enhances the selectivity of the ITC neurons encoding the behaviorally relevant features of the stimuli, as observed in the experiments. We conclude that the perceptual representation in visual areas like ITC can be strongly affected by the interaction with other areas which are devoted to higher cognitive functions.

Endogenous Sequential Cortical Activity Evoked by Visual Stimuli

PubMed Central

Miller, Jae-eun Kang; Hamm, Jordan P.; Jackson, Jesse; Yuste, Rafael

2015-01-01

Although the functional properties of individual neurons in primary visual cortex have been studied intensely, little is known about how neuronal groups could encode changing visual stimuli using temporal activity patterns. To explore this, we used in vivo two-photon calcium imaging to record the activity of neuronal populations in primary visual cortex of awake mice in the presence and absence of visual stimulation. Multidimensional analysis of the network activity allowed us to identify neuronal ensembles defined as groups of cells firing in synchrony. These synchronous groups of neurons were themselves activated in sequential temporal patterns, which repeated at much higher proportions than chance and were triggered by specific visual stimuli such as natural visual scenes. Interestingly, sequential patterns were also present in recordings of spontaneous activity without any sensory stimulation and were accompanied by precise firing sequences at the single-cell level. Moreover, intrinsic dynamics could be used to predict the occurrence of future neuronal ensembles. Our data demonstrate that visual stimuli recruit similar sequential patterns to the ones observed spontaneously, consistent with the hypothesis that already existing Hebbian cell assemblies firing in predefined temporal sequences could be the microcircuit substrate that encodes visual percepts changing in time. PMID:26063915

Dendritic GIRK Channels Gate the Integration Window, Plateau Potentials, and Induction of Synaptic Plasticity in Dorsal But Not Ventral CA1 Neurons

PubMed Central

2017-01-01

Studies comparing neuronal activity at the dorsal and ventral poles of the hippocampus have shown that the scale of spatial information increases and the precision with which space is represented declines from the dorsal to ventral end. These dorsoventral differences in neuronal output and spatial representation could arise due to differences in computations performed by dorsal and ventral CA1 neurons. In this study, we tested this hypothesis by quantifying the differences in dendritic integration and synaptic plasticity between dorsal and ventral CA1 pyramidal neurons of rat hippocampus. Using a combination of somatic and dendritic patch-clamp recordings, we show that the threshold for LTP induction is higher in dorsal CA1 neurons and that a G-protein-coupled inward-rectifying potassium channel mediated regulation of dendritic plateau potentials and dendritic excitability underlies this gating. By contrast, similar regulation of LTP is absent in ventral CA1 neurons. Additionally, we show that generation of plateau potentials and LTP induction in dorsal CA1 neurons depends on the coincident activation of Schaffer collateral and temporoammonic inputs at the distal apical dendrites. The ventral CA1 dendrites, however, can generate plateau potentials in response to temporally dispersed excitatory inputs. Overall, our results highlight the dorsoventral differences in dendritic computation that could account for the dorsoventral differences in spatial representation. SIGNIFICANCE STATEMENT The dorsal and ventral parts of the hippocampus encode spatial information at very different scales. Whereas the place-specific firing fields are small and precise at the dorsal end of the hippocampus, neurons at the ventral end have comparatively larger place fields. Here, we show that the dorsal CA1 neurons have a higher threshold for LTP induction and require coincident timing of excitatory synaptic inputs for the generation of dendritic plateau potentials. By contrast, ventral CA1 neurons can integrate temporally dispersed inputs and have a lower threshold for LTP. Together, these dorsoventral differences in the threshold for LTP induction could account for the differences in scale of spatial representation at the dorsal and ventral ends of the hippocampus. PMID:28280255

Dendritic GIRK Channels Gate the Integration Window, Plateau Potentials, and Induction of Synaptic Plasticity in Dorsal But Not Ventral CA1 Neurons.

PubMed

Malik, Ruchi; Johnston, Daniel

2017-04-05

Studies comparing neuronal activity at the dorsal and ventral poles of the hippocampus have shown that the scale of spatial information increases and the precision with which space is represented declines from the dorsal to ventral end. These dorsoventral differences in neuronal output and spatial representation could arise due to differences in computations performed by dorsal and ventral CA1 neurons. In this study, we tested this hypothesis by quantifying the differences in dendritic integration and synaptic plasticity between dorsal and ventral CA1 pyramidal neurons of rat hippocampus. Using a combination of somatic and dendritic patch-clamp recordings, we show that the threshold for LTP induction is higher in dorsal CA1 neurons and that a G-protein-coupled inward-rectifying potassium channel mediated regulation of dendritic plateau potentials and dendritic excitability underlies this gating. By contrast, similar regulation of LTP is absent in ventral CA1 neurons. Additionally, we show that generation of plateau potentials and LTP induction in dorsal CA1 neurons depends on the coincident activation of Schaffer collateral and temporoammonic inputs at the distal apical dendrites. The ventral CA1 dendrites, however, can generate plateau potentials in response to temporally dispersed excitatory inputs. Overall, our results highlight the dorsoventral differences in dendritic computation that could account for the dorsoventral differences in spatial representation. SIGNIFICANCE STATEMENT The dorsal and ventral parts of the hippocampus encode spatial information at very different scales. Whereas the place-specific firing fields are small and precise at the dorsal end of the hippocampus, neurons at the ventral end have comparatively larger place fields. Here, we show that the dorsal CA1 neurons have a higher threshold for LTP induction and require coincident timing of excitatory synaptic inputs for the generation of dendritic plateau potentials. By contrast, ventral CA1 neurons can integrate temporally dispersed inputs and have a lower threshold for LTP. Together, these dorsoventral differences in the threshold for LTP induction could account for the differences in scale of spatial representation at the dorsal and ventral ends of the hippocampus. Copyright © 2017 the authors 0270-6474/17/373940-16$15.00/0.

Amygdala inputs to prefrontal cortex guide behavior amid conflicting cues of reward and punishment

PubMed Central

Burgos-Robles, Anthony; Kimchi, Eyal Y.; Izadmehr, Ehsan M.; Porzenheim, Mary Jane; Ramos-Guasp, William A.; Nieh, Edward H.; Felix-Ortiz, Ada C.; Namburi, Praneeth; Leppla, Christopher A.; Presbrey, Kara N.; Anandalingam, Kavitha K.; Pagan-Rivera, Pablo A.; Anahtar, Melodi; Beyeler, Anna; Tye, Kay M.

2017-01-01

Orchestrating appropriate behavioral responses in the face of competing signals that predict either rewards or threats in the environment is crucial for survival. The basolateral amygdala (BLA) and prelimbic (PL) medial prefrontal cortex (mPFC) have been implicated in reward-seeking and fear-related responses, but how information flows between these reciprocally-connected structures to coordinate behavior is unknown. We recorded neuronal activity from the BLA and PL while rats performed a task where in shock- and sucrose-predictive cues were simultaneously presented to induce competition. The correlated firing primarily displayed a BLA→PL directionality during the shock-associated cue. Furthermore, the majority of optogenetically-identified PL-projecting BLA neurons recorded encoded the shock-associated cue, and more accurately predicted behavioral responses during competition than unidentified BLA neurons. Finally, BLA→PL photostimulation increased freezing, whereas both chemogenetic and optogenetic inhibition reduced freezing. The BLA→PL circuit plays a critical role in governing the selection of behavioral responses in the face of competing signals. PMID:28436980

Analysis of Neuronal Spike Trains, Deconstructed

PubMed Central

Aljadeff, Johnatan; Lansdell, Benjamin J.; Fairhall, Adrienne L.; Kleinfeld, David

2016-01-01

As information flows through the brain, neuronal firing progresses from encoding the world as sensed by the animal to driving the motor output of subsequent behavior. One of the more tractable goals of quantitative neuroscience is to develop predictive models that relate the sensory or motor streams with neuronal firing. Here we review and contrast analytical tools used to accomplish this task. We focus on classes of models in which the external variable is compared with one or more feature vectors to extract a low-dimensional representation, the history of spiking and other variables are potentially incorporated, and these factors are nonlinearly transformed to predict the occurrences of spikes. We illustrate these techniques in application to datasets of different degrees of complexity. In particular, we address the fitting of models in the presence of strong correlations in the external variable, as occurs in natural sensory stimuli and in movement. Spectral correlation between predicted and measured spike trains is introduced to contrast the relative success of different methods. PMID:27477016

Glutamate is an inhibitory neurotransmitter in the Drosophila olfactory system.

PubMed

Liu, Wendy W; Wilson, Rachel I

2013-06-18

Glutamatergic neurons are abundant in the Drosophila central nervous system, but their physiological effects are largely unknown. In this study, we investigated the effects of glutamate in the Drosophila antennal lobe, the first relay in the olfactory system and a model circuit for understanding olfactory processing. In the antennal lobe, one-third of local neurons are glutamatergic. Using in vivo whole-cell patch clamp recordings, we found that many glutamatergic local neurons are broadly tuned to odors. Iontophoresed glutamate hyperpolarizes all major cell types in the antennal lobe, and this effect is blocked by picrotoxin or by transgenic RNAi-mediated knockdown of the GluClα gene, which encodes a glutamate-gated chloride channel. Moreover, antennal lobe neurons are inhibited by selective activation of glutamatergic local neurons using a nonnative genetically encoded cation channel. Finally, transgenic knockdown of GluClα in principal neurons disinhibits the odor responses of these neurons. Thus, glutamate acts as an inhibitory neurotransmitter in the antennal lobe, broadly similar to the role of GABA in this circuit. However, because glutamate release is concentrated between glomeruli, whereas GABA release is concentrated within glomeruli, these neurotransmitters may act on different spatial and temporal scales. Thus, the existence of two parallel inhibitory transmitter systems may increase the range and flexibility of synaptic inhibition.

Primary motor cortex of the parkinsonian monkey: altered encoding of active movement

PubMed Central

Pasquereau, Benjamin; DeLong, Mahlon R.

2016-01-01

Abnormalities in the movement-related activation of the primary motor cortex (M1) are thought to be a major contributor to the motor signs of Parkinson’s disease. The existing evidence, however, variably indicates that M1 is under-activated with movement, overactivated (due to a loss of functional specificity) or activated with abnormal timing. In addition, few models consider the possibility that distinct cortical neuron subtypes may be affected differently. Those gaps in knowledge were addressed by studying the extracellular activity of antidromically-identified lamina 5b pyramidal-tract type neurons (n = 153) and intratelencephalic-type corticostriatal neurons (n = 126) in the M1 of two monkeys as they performed a step-tracking arm movement task. We compared movement-related discharge before and after the induction of parkinsonism by administration of MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) and quantified the spike rate encoding of specific kinematic parameters of movement using a generalized linear model. The fraction of M1 neurons with movement-related activity declined following MPTP but only marginally. The strength of neuronal encoding of parameters of movement was reduced markedly (mean 29% reduction in the coefficients from the generalized linear model). This relative decoupling of M1 activity from kinematics was attributable to reductions in the coefficients that estimated the spike rate encoding of movement direction (−22%), speed (−40%), acceleration (−49%) and hand position (−33%). After controlling for MPTP-induced changes in motor performance, M1 activity related to movement itself was reduced markedly (mean 36% hypoactivation). This reduced activation was strong in pyramidal tract-type neurons (−50%) but essentially absent in corticostriatal neurons. The timing of M1 activation was also abnormal, with earlier onset times, prolonged response durations, and a 43% reduction in the prevalence of movement-related changes beginning in the 150-ms period that immediately preceded movement. Overall, the results are consistent with proposals that under-activation and abnormal timing of movement-related activity in M1 contribute to parkinsonian motor signs but are not consistent with the idea that a loss of functional specificity plays an important role. Given that pyramidal tract-type neurons form the primary efferent pathway that conveys motor commands to the spinal cord, the dysfunction of movement-related activity in pyramidal tract-type neurons is likely to be a central factor in the pathophysiology of parkinsonian motor signs. PMID:26490335

Artificial neural networks using complex numbers and phase encoded weights.

PubMed

Michel, Howard E; Awwal, Abdul Ahad S

2010-04-01

The model of a simple perceptron using phase-encoded inputs and complex-valued weights is proposed. The aggregation function, activation function, and learning rule for the proposed neuron are derived and applied to Boolean logic functions and simple computer vision tasks. The complex-valued neuron (CVN) is shown to be superior to traditional perceptrons. An improvement of 135% over the theoretical maximum of 104 linearly separable problems (of three variables) solvable by conventional perceptrons is achieved without additional logic, neuron stages, or higher order terms such as those required in polynomial logic gates. The application of CVN in distortion invariant character recognition and image segmentation is demonstrated. Implementation details are discussed, and the CVN is shown to be very attractive for optical implementation since optical computations are naturally complex. The cost of the CVN is less in all cases than the traditional neuron when implemented optically. Therefore, all the benefits of the CVN can be obtained without additional cost. However, on those implementations dependent on standard serial computers, CVN will be more cost effective only in those applications where its increased power can offset the requirement for additional neurons.

A Subset of Serotonergic Neurons Evokes Hunger in Adult Drosophila.

PubMed

Albin, Stephanie D; Kaun, Karla R; Knapp, Jon-Michael; Chung, Phuong; Heberlein, Ulrike; Simpson, Julie H

2015-09-21

Hunger is a complex motivational state that drives multiple behaviors. The sensation of hunger is caused by an imbalance between energy intake and expenditure. One immediate response to hunger is increased food consumption. Hunger also modulates behaviors related to food seeking such as increased locomotion and enhanced sensory sensitivity in both insects and vertebrates. In addition, hunger can promote the expression of food-associated memory. Although progress is being made, how hunger is represented in the brain and how it coordinates these behavioral responses is not fully understood in any system. Here, we use Drosophila melanogaster to identify neurons encoding hunger. We found a small group of neurons that, when activated, induced a fed fly to eat as though it were starved, suggesting that these neurons are downstream of the metabolic regulation of hunger. Artificially activating these neurons also promotes appetitive memory performance in sated flies, indicating that these neurons are not simply feeding command neurons but likely play a more general role in encoding hunger. We determined that the neurons relevant for the feeding effect are serotonergic and project broadly within the brain, suggesting a possible mechanism for how various responses to hunger are coordinated. These findings extend our understanding of the neural circuitry that drives feeding and enable future exploration of how state influences neural activity within this circuit. Copyright © 2015 Elsevier Ltd. All rights reserved.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

PubMed

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

FMRFamide-related peptides in potato cyst nematodes.

PubMed

Kimber, M J; Fleming, C C; Bjourson, A J; Halton, D W; Maule, A G

2001-09-03

This study presents data demonstrating the presence of FMRFamide-related peptides (FaRPs) in potato cyst nematodes (PCN). Five transcripts of FaRP encoding genes, designated gpflp-1 to gpflp-5, were characterised using RACE. In terms of ORFs, gpflp-1 was 444 base pairs (bp) long and coded for four copies of the FaRP, PF3 (KSAYMRFamide) whilst gpflp-2 was 309 bp long and encoded one copy of the peptide, KNKFEFIRFamide. gpflp-3 (420 bp) Encoded two copies of KHEYLRFamide (AF2) and the genes gpflp-4 and gpflp-5 encoded a total of 11 FaRPs, most of which are novel to PCN. FMRFamide-related peptide (FaRP)-like immunoreactivity was observed in both PCN species, Globodera pallida and Globodera rostochiensis, using an antiserum raised against the invertebrate peptide, FMRFamide. Immunopositive neurones were found throughout the central nervous system in the ventral and dorsal nerve cords and the circumpharyngeal and perianal nerve rings. Reactive neurones were also present peripherally, innervating the highly muscular pharynx with a nerve net and ring-like structures. Positive immunostaining was also observed in neurones running toward the stylet protractor muscles and/or the anterior sensory apparatus. This study implicates a role for FaRPs in feeding, host penetration and sensory function of PCN. This is the first study to characterise FaRP encoding genes from a plant-parasitic nematode using a targeted PCR based RACE approach and further underlines the importance and diversity of this neuropeptide group in the phylum Nematoda.

Dynamics of Learning in Cultured Neuronal Networks with Antagonists of Glutamate Receptors

PubMed Central

Li, Yanling; Zhou, Wei; Li, Xiangning; Zeng, Shaoqun; Luo, Qingming

2007-01-01

Cognitive dysfunction may result from abnormality of ionotropic glutamate receptors. Although various forms of synaptic plasticity in learning that rely on altering of glutamate receptors have been considered, the evidence is insufficient from an informatics view. Dynamics could reflect neuroinformatics encoding, including temporal pattern encoding, spatial pattern encoding, and energy distribution. Discovering informatics encoding is fundamental and crucial to understanding the working principle of the neural system. In this article, we analyzed the dynamic characteristics of response activities during learning training in cultured hippocampal networks under normal and abnormal conditions of ionotropic glutamate receptors, respectively. The rate, which is one of the temporal configurations, was decreased markedly by inhibition of α-amino-3-hydroxy-5-methylisoxazole-4-proprionic acid (AMPA) receptors. Moreover, the energy distribution in different characteristic frequencies was changed markedly by inhibition of AMPA receptors. Spatial configurations, including regularization, correlation, and synchrony, were changed significantly by inhibition of N-methyl-d-aspartate receptors. These results suggest that temporal pattern encoding and energy distribution of response activities in cultured hippocampal neuronal networks during learning training are modulated by AMPA receptors, whereas spatial pattern encoding of response activities is modulated by N-methyl-d-aspartate receptors. PMID:17766359

Maturation profile of inferior olivary neurons expressing ionotropic glutamate receptors in rats: role in coding linear accelerations.

PubMed

Li, Chuan; Han, Lei; Ma, Chun-Wai; Lai, Suk-King; Lai, Chun-Hong; Shum, Daisy Kwok Yan; Chan, Ying-Shing

2013-07-01

Using sinusoidal oscillations of linear acceleration along both the horizontal and vertical planes to stimulate otolith organs in the inner ear, we charted the postnatal time at which responsive neurons in the rat inferior olive (IO) first showed Fos expression, an indicator of neuronal recruitment into the otolith circuit. Neurons in subnucleus dorsomedial cell column (DMCC) were activated by vertical stimulation as early as P9 and by horizontal (interaural) stimulation as early as P11. By P13, neurons in the β subnucleus of IO (IOβ) became responsive to horizontal stimulation along the interaural and antero-posterior directions. By P21, neurons in the rostral IOβ became also responsive to vertical stimulation, but those in the caudal IOβ remained responsive only to horizontal stimulation. Nearly all functionally activated neurons in DMCC and IOβ were immunopositive for the NR1 subunit of the NMDA receptor and the GluR2/3 subunit of the AMPA receptor. In situ hybridization studies further indicated abundant mRNA signals of the glutamate receptor subunits by the end of the second postnatal week. This is reinforced by whole-cell patch-clamp data in which glutamate receptor-mediated miniature excitatory postsynaptic currents of rostral IOβ neurons showed postnatal increase in amplitude, reaching the adult level by P14. Further, these neurons exhibited subthreshold oscillations in membrane potential as from P14. Taken together, our results support that ionotropic glutamate receptors in the IO enable postnatal coding of gravity-related information and that the rostral IOβ is the only IO subnucleus that encodes spatial orientations in 3-D.

Synchrony and neural coding in cerebellar circuits

PubMed Central

Person, Abigail L.; Raman, Indira M.

2012-01-01

The cerebellum regulates complex movements and is also implicated in cognitive tasks, and cerebellar dysfunction is consequently associated not only with movement disorders, but also with conditions like autism and dyslexia. How information is encoded by specific cerebellar firing patterns remains debated, however. A central question is how the cerebellar cortex transmits its integrated output to the cerebellar nuclei via GABAergic synapses from Purkinje neurons. Possible answers come from accumulating evidence that subsets of Purkinje cells synchronize their firing during behaviors that require the cerebellum. Consistent with models predicting that coherent activity of inhibitory networks has the capacity to dictate firing patterns of target neurons, recent experimental work supports the idea that inhibitory synchrony may regulate the response of cerebellar nuclear cells to Purkinje inputs, owing to the interplay between unusually fast inhibitory synaptic responses and high rates of intrinsic activity. Data from multiple laboratories lead to a working hypothesis that synchronous inhibitory input from Purkinje cells can set the timing and rate of action potentials produced by cerebellar nuclear cells, thereby relaying information out of the cerebellum. If so, then changing spatiotemporal patterns of Purkinje activity would allow different subsets of inhibitory neurons to control cerebellar output at different times. Here we explore the evidence for and against the idea that a synchrony code defines, at least in part, the input–output function between the cerebellar cortex and nuclei. We consider the literature on the existence of simple spike synchrony, convergence of Purkinje neurons onto nuclear neurons, and intrinsic properties of nuclear neurons that contribute to responses to inhibition. Finally, we discuss factors that may disrupt or modulate a synchrony code and describe the potential contributions of inhibitory synchrony to other motor circuits. PMID:23248585

Distinct roles of visual, parietal, and frontal motor cortices in memory-guided sensorimotor decisions.

PubMed

Goard, Michael J; Pho, Gerald N; Woodson, Jonathan; Sur, Mriganka

2016-08-04

Mapping specific sensory features to future motor actions is a crucial capability of mammalian nervous systems. We investigated the role of visual (V1), posterior parietal (PPC), and frontal motor (fMC) cortices for sensorimotor mapping in mice during performance of a memory-guided visual discrimination task. Large-scale calcium imaging revealed that V1, PPC, and fMC neurons exhibited heterogeneous responses spanning all task epochs (stimulus, delay, response). Population analyses demonstrated unique encoding of stimulus identity and behavioral choice information across regions, with V1 encoding stimulus, fMC encoding choice even early in the trial, and PPC multiplexing the two variables. Optogenetic inhibition during behavior revealed that all regions were necessary during the stimulus epoch, but only fMC was required during the delay and response epochs. Stimulus identity can thus be rapidly transformed into behavioral choice, requiring V1, PPC, and fMC during the transformation period, but only fMC for maintaining the choice in memory prior to execution.

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

NASA Astrophysics Data System (ADS)

Gupta, Isha; Serb, Alexantrou; Khiat, Ali; Zeitler, Ralf; Vassanelli, Stefano; Prodromakis, Themistoklis

2016-09-01

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology's potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces.

Imaging with organic indicators and high-speed charge-coupled device cameras in neurons: some applications where these classic techniques have advantages.

PubMed

Ross, William N; Miyazaki, Kenichi; Popovic, Marko A; Zecevic, Dejan

2015-04-01

Dynamic calcium and voltage imaging is a major tool in modern cellular neuroscience. Since the beginning of their use over 40 years ago, there have been major improvements in indicators, microscopes, imaging systems, and computers. While cutting edge research has trended toward the use of genetically encoded calcium or voltage indicators, two-photon microscopes, and in vivo preparations, it is worth noting that some questions still may be best approached using more classical methodologies and preparations. In this review, we highlight a few examples in neurons where the combination of charge-coupled device (CCD) imaging and classical organic indicators has revealed information that has so far been more informative than results using the more modern systems. These experiments take advantage of the high frame rates, sensitivity, and spatial integration of the best CCD cameras. These cameras can respond to the faster kinetics of organic voltage and calcium indicators, which closely reflect the fast dynamics of the underlying cellular events.

Differential inhibition onto developing and mature granule cells generates high-frequency filters with variable gain

PubMed Central

Pardi, María Belén; Ogando, Mora Belén; Schinder, Alejandro F; Marin-Burgin, Antonia

2015-01-01

Adult hippocampal neurogenesis provides the dentate gyrus with heterogeneous populations of granule cells (GC) originated at different times. The contribution of these cells to information encoding is under current investigation. Here, we show that incoming spike trains activate different populations of GC determined by the stimulation frequency and GC age. Immature GC respond to a wider range of stimulus frequencies, whereas mature GC are less responsive at high frequencies. This difference is dictated by feedforward inhibition, which restricts mature GC activation. Yet, the stronger inhibition of mature GC results in a higher temporal fidelity compared to that of immature GC. Thus, hippocampal inputs activate two populations of neurons with variable frequency filters: immature cells, with wide‐range responses, that are reliable transmitters of the incoming frequency, and mature neurons, with narrow frequency response, that are precise at informing the beginning of the stimulus, but with a sparse activity. DOI: http://dx.doi.org/10.7554/eLife.08764.001 PMID:26163657

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

PubMed Central

Gupta, Isha; Serb, Alexantrou; Khiat, Ali; Zeitler, Ralf; Vassanelli, Stefano; Prodromakis, Themistoklis

2016-01-01

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology's potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces. PMID:27666698

Emergence of spike correlations in periodically forced excitable systems

NASA Astrophysics Data System (ADS)

Reinoso, José A.; Torrent, M. C.; Masoller, Cristina

2016-09-01

In sensory neurons the presence of noise can facilitate the detection of weak information-carrying signals, which are encoded and transmitted via correlated sequences of spikes. Here we investigate the relative temporal order in spike sequences induced by a subthreshold periodic input in the presence of white Gaussian noise. To simulate the spikes, we use the FitzHugh-Nagumo model and to investigate the output sequence of interspike intervals (ISIs), we use the symbolic method of ordinal analysis. We find different types of relative temporal order in the form of preferred ordinal patterns that depend on both the strength of the noise and the period of the input signal. We also demonstrate a resonancelike behavior, as certain periods and noise levels enhance temporal ordering in the ISI sequence, maximizing the probability of the preferred patterns. Our findings could be relevant for understanding the mechanisms underlying temporal coding, by which single sensory neurons represent in spike sequences the information about weak periodic stimuli.

[Measurement and performance analysis of functional neural network].

PubMed

Li, Shan; Liu, Xinyu; Chen, Yan; Wan, Hong

2018-04-01

The measurement of network is one of the important researches in resolving neuronal population information processing mechanism using complex network theory. For the quantitative measurement problem of functional neural network, the relation between the measure indexes, i.e. the clustering coefficient, the global efficiency, the characteristic path length and the transitivity, and the network topology was analyzed. Then, the spike-based functional neural network was established and the simulation results showed that the measured network could represent the original neural connections among neurons. On the basis of the former work, the coding of functional neural network in nidopallium caudolaterale (NCL) about pigeon's motion behaviors was studied. We found that the NCL functional neural network effectively encoded the motion behaviors of the pigeon, and there were significant differences in four indexes among the left-turning, the forward and the right-turning. Overall, the establishment method of spike-based functional neural network is available and it is an effective tool to parse the brain information processing mechanism.

Efficiency turns the table on neural encoding, decoding and noise.

PubMed

Deneve, Sophie; Chalk, Matthew

2016-04-01

Sensory neurons are usually described with an encoding model, for example, a function that predicts their response from the sensory stimulus using a receptive field (RF) or a tuning curve. However, central to theories of sensory processing is the notion of 'efficient coding'. We argue here that efficient coding implies a completely different neural coding strategy. Instead of a fixed encoding model, neural populations would be described by a fixed decoding model (i.e. a model reconstructing the stimulus from the neural responses). Because the population solves a global optimization problem, individual neurons are variable, but not noisy, and have no truly invariant tuning curve or receptive field. We review recent experimental evidence and implications for neural noise correlations, robustness and adaptation. Copyright © 2016. Published by Elsevier Ltd.

Slow Temporal Integration Enables Robust Neural Coding and Perception of a Cue to Sound Source Location.

PubMed

Brown, Andrew D; Tollin, Daniel J

2016-09-21

In mammals, localization of sound sources in azimuth depends on sensitivity to interaural differences in sound timing (ITD) and level (ILD). Paradoxically, while typical ILD-sensitive neurons of the auditory brainstem require millisecond synchrony of excitatory and inhibitory inputs for the encoding of ILDs, human and animal behavioral ILD sensitivity is robust to temporal stimulus degradations (e.g., interaural decorrelation due to reverberation), or, in humans, bilateral clinical device processing. Here we demonstrate that behavioral ILD sensitivity is only modestly degraded with even complete decorrelation of left- and right-ear signals, suggesting the existence of a highly integrative ILD-coding mechanism. Correspondingly, we find that a majority of auditory midbrain neurons in the central nucleus of the inferior colliculus (of chinchilla) effectively encode ILDs despite complete decorrelation of left- and right-ear signals. We show that such responses can be accounted for by relatively long windows of bilateral excitatory-inhibitory interaction, which we explicitly measure using trains of narrowband clicks. Neural and behavioral data are compared with the outputs of a simple model of ILD processing with a single free parameter, the duration of excitatory-inhibitory interaction. Behavioral, neural, and modeling data collectively suggest that ILD sensitivity depends on binaural integration of excitation and inhibition within a ≳3 ms temporal window, significantly longer than observed in lower brainstem neurons. This relatively slow integration potentiates a unique role for the ILD system in spatial hearing that may be of particular importance when informative ITD cues are unavailable. In mammalian hearing, interaural differences in the timing (ITD) and level (ILD) of impinging sounds carry critical information about source location. However, natural sounds are often decorrelated between the ears by reverberation and background noise, degrading the fidelity of both ITD and ILD cues. Here we demonstrate that behavioral ILD sensitivity (in humans) and neural ILD sensitivity (in single neurons of the chinchilla auditory midbrain) remain robust under stimulus conditions that render ITD cues undetectable. This result can be explained by "slow" temporal integration arising from several-millisecond-long windows of excitatory-inhibitory interaction evident in midbrain, but not brainstem, neurons. Such integrative coding can account for the preservation of ILD sensitivity despite even extreme temporal degradations in ecological acoustic stimuli. Copyright © 2016 the authors 0270-6474/16/369908-14$15.00/0.

Amygdala neural activity reflects spatial attention towards stimuli promising reward or threatening punishment

PubMed Central

Peck, Christopher J; Salzman, C Daniel

2014-01-01

Humans and other animals routinely identify and attend to sensory stimuli so as to rapidly acquire rewards or avoid aversive experiences. Emotional arousal, a process mediated by the amygdala, can enhance attention to stimuli in a non-spatial manner. However, amygdala neural activity was recently shown to encode spatial information about reward-predictive stimuli, and to correlate with spatial attention allocation. If representing the motivational significance of sensory stimuli within a spatial framework reflects a general principle of amygdala function, then spatially selective neural responses should also be elicited by sensory stimuli threatening aversive events. Recordings from amygdala neurons were therefore obtained while monkeys directed spatial attention towards stimuli promising reward or threatening punishment. Neural responses encoded spatial information similarly for stimuli associated with both valences of reinforcement, and responses reflected spatial attention allocation. The amygdala therefore may act to enhance spatial attention to sensory stimuli associated with rewarding or aversive experiences. DOI: http://dx.doi.org/10.7554/eLife.04478.001 PMID:25358090

Towards Optogenetic Sensory Replacement

PubMed Central

Doroudchi, M. Mehdi; Greenberg, Kenneth P.; Zorzos, Anthony N.; Hauswirth, William W.; Fonstad, Clifton G.; Horsager, Alan; Boyden, Edward S.

2013-01-01

Over the last several years we have developed a rapidly-expanding suite of genetically-encoded reagents (e.g., ChR2, Halo, Arch, Mac, and others) that, when expressed in specific neuron types in the nervous system, enable their activities to be powerfully and precisely activated and silenced in response to light. If the genes that encode for these reagents can be delivered to cells in the body using gene therapy methods, and if the resultant protein payloads operate safely and effectively over therapeutically important periods of time, these molecules could subserve a set of precise prosthetics that use light as the trigger of information entry into the nervous system, e.g. for sensory replacement. Here we discuss the use of ChR2 to make the photoreceptor-deprived retina, as found in diseases such as retinitis pigmentosa, sensitive to light, enabling restoration of functional vision in a mouse model of blindness. We also discuss arrays of light sources that could be useful for delivering patterned sensory information into the nervous system. PMID:22255005

Interneurons in the Honeybee Primary Auditory Center Responding to Waggle Dance-Like Vibration Pulses.

PubMed

Ai, Hiroyuki; Kai, Kazuki; Kumaraswamy, Ajayrama; Ikeno, Hidetoshi; Wachtler, Thomas

2017-11-01

Female honeybees use the "waggle dance" to communicate the location of nectar sources to their hive mates. Distance information is encoded in the duration of the waggle phase (von Frisch, 1967). During the waggle phase, the dancer produces trains of vibration pulses, which are detected by the follower bees via Johnston's organ located on the antennae. To uncover the neural mechanisms underlying the encoding of distance information in the waggle dance follower, we investigated morphology, physiology, and immunohistochemistry of interneurons arborizing in the primary auditory center of the honeybee ( Apis mellifera ). We identified major interneuron types, named DL-Int-1, DL-Int-2, and bilateral DL-dSEG-LP, that responded with different spiking patterns to vibration pulses applied to the antennae. Experimental and computational analyses suggest that inhibitory connection plays a role in encoding and processing the duration of vibration pulse trains in the primary auditory center of the honeybee. SIGNIFICANCE STATEMENT The waggle dance represents a form of symbolic communication used by honeybees to convey the location of food sources via species-specific sound. The brain mechanisms used to decipher this symbolic information are unknown. We examined interneurons in the honeybee primary auditory center and identified different neuron types with specific properties. The results of our computational analyses suggest that inhibitory connection plays a role in encoding waggle dance signals. Our results are critical for understanding how the honeybee deciphers information from the sound produced by the waggle dance and provide new insights regarding how common neural mechanisms are used by different species to achieve communication. Copyright © 2017 the authors 0270-6474/17/3710624-12$15.00/0.