Design of continuous attractor networks with monotonic tuning using a symmetry principle

Neurons that sustain elevated firing in the absence of stimuli have been found in many neural systems. In graded persistent activity, neurons can sustain firing at many levels, suggesting a widely found type of network dynamics in which networks can relax to any one of a continuum of stationary states. The reproduction of these findings in model networks of nonlinear neurons has turned out to be nontrivial. A particularly insightful model has been the "bump attractor," in which a continuous attractor emerges through an underlying symmetry in the network connectivity matrix. This model, however, cannot account for data in which the persistent firing of neurons is a monotonic-rather than a bell-shaped-function of a stored variable. Here, we show that the symmetry used in the bump attractor network can be employed to create a whole family of continuous attractor networks, including those with monotonic tuning. Our design is based on tuning the external inputs to networks that have a connectivity matrix with Toeplitz symmetry. In particular, we provide a complete analytical solution of a line attractor network with monotonic tuning and show that for many other networks, the numerical tuning of synaptic weights reduces to the computation of a single parameter

Demixed principal component analysis of neural population data

Neurons in higher cortical areas, such as the prefrontal cortex, are often tuned to a variety of sensory and motor variables, and are therefore said to display mixed selectivity. This complexity of single neuron responses can obscure what information these areas represent and how it is represented. Here we demonstrate the advantages of a new dimensionality reduction technique, demixed principal component analysis (dPCA), that decomposes population activity into a few components. In addition to systematically capturing the majority of the variance of the data, dPCA also exposes the dependence of the neural representation on task parameters such as stimuli, decisions, or rewards. To illustrate our method we reanalyze population data from four datasets comprising different species, different cortical areas and different experimental tasks. In each case, dPCA provides a concise way of visualizing the data that summarizes the task-dependent features of the population response in a single figure

Neural Decision Boundaries for Maximal Information Transmission

We consider here how to separate multidimensional signals into two categories, such that the binary decision transmits the maximum possible information transmitted about those signals. Our motivation comes from the nervous system, where neurons process multidimensional signals into a binary sequence of responses (spikes). In a small noise limit, we derive a general equation for the decision boundary that locally relates its curvature to the probability distribution of inputs. We show that for Gaussian inputs the optimal boundaries are planar, but for non-Gaussian inputs the curvature is nonzero. As an example, we consider exponentially distributed inputs, which are known to approximate a variety of signals from natural environment.Comment: 5 pages, 3 figure

Influence of Different Envelope Maskers on Signal Recognition and Neuronal Representation in the Auditory System of a Grasshopper

Background: Animals that communicate by sound face the problem that the signals arriving at the receiver often are degraded and masked by noise. Frequency filters in the receiver’s auditory system may improve the signal-to-noise ratio (SNR) by excluding parts of the spectrum which are not occupied by the species-specific signals. This solution, however, is hardly amenable to species that produce broad band signals or have ears with broad frequency tuning. In mammals auditory filters exist that work in the temporal domain of amplitude modulations (AM). Do insects also use this type of filtering? Principal Findings: Combining behavioural and neurophysiological experiments we investigated whether AM filters may improve the recognition of masked communication signals in grasshoppers. The AM pattern of the sound, its envelope, is crucial for signal recognition in these animals. We degraded the species-specific song by adding random fluctuations to its envelope. Six noise bands were used that differed in their overlap with the spectral content of the song envelope. If AM filters contribute to reduced masking, signal recognition should depend on the degree of overlap between the song envelope spectrum and the noise spectra. Contrary to this prediction, the resistance against signal degradation was the same for five of six masker bands. Most remarkably, the band with the strongest frequency overlap to the natural song envelope (0–100 Hz) impaired acceptance of degraded signals the least. To assess the noise filter capacities of singl

Probing Real Sensory Worlds of Receivers with Unsupervised Clustering

The task of an organism to extract information about the external environment from sensory signals is based entirely on the analysis of ongoing afferent spike activity provided by the sense organs. We investigate the processing of auditory stimuli by an acoustic interneuron of insects. In contrast to most previous work we do this by using stimuli and neurophysiological recordings directly in the nocturnal tropical rainforest, where the insect communicates. Different from typical recordings in sound proof laboratories, strong environmental noise from multiple sound sources interferes with the perception of acoustic signals in these realistic scenarios. We apply a recently developed unsupervised machine learning algorithm based on probabilistic inference to find frequently occurring firing patterns in the response of the acoustic interneuron. We can thus ask how much information the central nervous system of the receiver can extract from bursts without ever being told which type and which variants of bursts are characteristic for particular stimuli. Our results show that the reliability of burst coding in the time domain is so high that identical stimuli lead to extremely similar spike pattern responses, even for different preparations on different dates, and even if one of the preparations is recorded outdoors and the other one in the sound proof lab. Simultaneous recordings in two preparations exposed to the same acoustic environment reveal that characteristics of burst patterns are largely preserved among individuals of the same species. Our study shows that burst coding can provide a reliable mechanism for acoustic insects to classify and discriminate signals under very noisy real-world conditions. This gives new insights into the neural mechanisms potentially used by bushcrickets to discriminate conspecific songs from sounds of predators in similar carrier frequency bands

A family presenting with multiple endocrine neoplasia type 2B: A case report

<p>Abstract</p> <p>Introduction</p> <p>Multiple endocrine neoplasia 2B, a rare autosomal dominant syndrome, is characterized by early onset of medullary thyroid carcinoma, pheochromocytoma, marfanoid habitus and mucosal neuromas of the tongue, lips, inner cheeks and inner eyelids. Gangliomatosis of the gastrointestinal tract and its complications may also occur in patients with this disease.</p> <p>Case presentation</p> <p>We present the case of a 16-year-old Persian man diagnosed as having a non-invasive form of multiple endocrine neoplasia 2B (medullary thyroid cancer, mucosal neuroma of the tongue, lips and inner eyelids). Our patient, who had a positive family history of medullary thyroid cancer, was of normal height with no signs of marfanoid habitus.</p> <p>Conclusions</p> <p>Ophthalmological and oral manifestations of multiple endocrine neoplasia 2B, as in the case of our patient, are rare presentations of the disease; unfortunately in the case of our patient his condition had not been noted and acted upon until he presented to our department. The diagnosis in our patient's case was made only after his mother presented with the same condition. As a result, we emphasize that physicians should pay more attention to the oral and ocular signs of multiple endocrine neoplasia 2B in order to diagnose this fatal syndrome at an earlier phase.</p

A Neural Correlate of the Processing of Multi-Second Time Intervals in Primate Prefrontal Cortex

Several areas of the brain are known to participate in temporal processing. Neurons in the prefrontal cortex (PFC) are thought to contribute to perception of time intervals. However, it remains unclear whether the PFC itself can generate time intervals independently of external stimuli. Here we describe a group of PFC neurons in area 9 that became active when monkeys recognized a particular elapsed time within the range of 1–7 seconds. Another group of area 9 neurons became active only when subjects reproduced a specific interval without external cues. Both types of neurons were individually tuned to recognize or reproduce particular intervals. Moreover, the injection of muscimol, a GABA agonist, into this area bilaterally resulted in an increase in the error rate during time interval reproduction. These results suggest that area 9 may process multi-second intervals not only in perceptual recognition, but also in internal generation of time intervals

Localized microstimulation of primate pregenual cingulate cortex induces negative decision-making

The pregenual anterior cingulate cortex (pACC) has been implicated in human anxiety disorders and depression, but the circuit-level mechanisms underlying these disorders are unclear. In healthy individuals, the pACC is involved in cost-benefit evaluation. We developed a macaque version of an approach-avoidance decision task used to evaluate anxiety and depression in humans and, with multi-electrode recording and cortical microstimulation, we probed pACC function as monkeys performed this task. We found that the macaque pACC has an opponent process-like organization of neurons representing motivationally positive and negative subjective value. Spatial distribution of these two neuronal populations overlapped in the pACC, except in one subzone, where neurons with negative coding were more numerous. Notably, microstimulation in this subzone, but not elsewhere in the pACC, increased negative decision-making, and this negative biasing was blocked by anti-anxiety drug treatment. This cortical zone could be critical for regulating negative emotional valence and anxiety in decision-making.National Institutes of Health (U.S.) (Javits Merit Grant R01 NS025529)United States. Office of Naval Research (N000140710903)National Parkinson Foundation (U.S.) (Lynn Diamond Fellowship

Emergence of Tuning to Natural Stimulus Statistics along the Central Auditory Pathway

We have previously shown that neurons in primary auditory cortex (A1) of anaesthetized (ketamine/medetomidine) ferrets respond more strongly and reliably to dynamic stimuli whose statistics follow "natural" 1/f dynamics than to stimuli exhibiting pitch and amplitude modulations that are faster (1/f(0.5)) or slower (1/f(2)) than 1/f. To investigate where along the central auditory pathway this 1/f-modulation tuning arises, we have now characterized responses of neurons in the central nucleus of the inferior colliculus (ICC) and the ventral division of the mediate geniculate nucleus of the thalamus (MGV) to 1/f(gamma) distributed stimuli with gamma varying between 0.5 and 2.8. We found that, while the great majority of neurons recorded from the ICC showed a strong preference for the most rapidly varying (1/f(0.5) distributed) stimuli, responses from MGV neurons did not exhibit marked or systematic preferences for any particular gamma exponent. Only in A1 did a majority of neurons respond with higher firing rates to stimuli in which gamma takes values near 1. These results indicate that 1/f tuning emerges at forebrain levels of the ascending auditory pathway