Modulation of auditory responses by modality-specific attention in rat primary auditory cortex

How does attention modulate sensory representations? In order to probe the underlying neural mechanisms, we established a simple rodent model of modality-specific attention. Here we describe results of experiments in freely moving rats in which we have used tetrodes to record neural responses in primary auditory cortex (area A1) while subjects performed this behavior.

Subjects were first trained to perform distinct auditory and olfactory two alternative forced-choice (2AFC) tasks. Training and testing were conducted in a custom three-poke computer-controlled behavioral apparatus. Subjects initiated trials with a center-poke, which triggered presentation of a tone (either 5 or 15 Hz), an odor (either R(-)-2-Octanol or S(+)-2-Octanol), or both. Subjects responded moving to the left or right poke. Correct responses were rewarded with water. Auditory and olfactory blocks (of 50 trials each) were interleaved in a single session. In auditory blocks, pure tones were either presented with or without a null odor (caproic acid, n=2 and 3 respectively), and subjects were cued to perform the task based on auditory stimuli. In olfactory blocks, both odors and pure tones were presented simultaneously, and subjects were cued to perform the task based on olfactory stimuli.

After subjects reached consistent performance on the interleaved blocks, tetrode drives were implanted in primary auditory cortex of the left hemisphere. Single unit responses to tones were heterogeneous, and included transient, sustained, and suppressed. Among 304 responsive units recorded, 19% (58 units) showed modality-specific attentional modulation of at least one of the tone-evoked responses; in most cases, the responses to a particular auditory stimulus was enhanced in the auditory block (or, equivalently, suppressed in the olfactory block). In addition, we also observed modality-specific attentional modulation of the spontaneous activity in similar proportion of units (61 units). 

Our results suggest that shifting attention from audition to olfaction and back can modulate the activity of single neurons in primary auditory cortex

Neural Mechanisms of Selective Auditory Attention in Rats (Dissertation)

How does attention modulate sensory representations? In order to probe the underlying neural mechanisms, we established a simple rodent model of modality-specific attention. Rats were trained to perform distinct auditory two-tone discrimination and olfactory odor discrimination in a two alternative choice (2AC) paradigm. 
To determine auditory cortex’s role in this frequency discrimination task, we used GABA-A receptor agonist muscimol to transiently and reversibly inactivate auditory cortexes bilaterally in rats performing simple interleaved auditory and olfactory discrimination. With olfactory discrimination performance serving as internal control for motivation and decision making capability, we found only auditory two-tone discrimination was selectively impaired in these rats. This shows the auditory cortex is involved in this two-tone discrimination task.
To investigate the neural correlate of modality-specific attention in the auditory cortex, we trained rats to perform interleaved auditory and olfactory blocks (of 50~70 trials each) in a single session. In auditory blocks, pure tones were either presented with or without a neutral odor (caproic acid, n=2 and 3 respectively), and subjects were rewarded for discriminating auditory stimuli. In olfactory blocks, both task odors and pure tones were presented simultaneously, and subjects were rewarded for discriminating olfactory stimuli. We recorded neural responses in primary auditory cortex (area A1) in freely moving rats while subjects performed this behavior. Single unit responses to tones were heterogeneous, and included transient, sustained, and suppressed. We found 205 of 802 units recorded responsive to the stimuli we used. Of these 205 units, 18.5% showed modality-specific attentional modulation of the anticipatory activity before tone onset. In addition, we also observed in smaller proportion of units (11.2%) modality-specific attentional modulation of the tone-evoked responses; in most cases, the responses to a particular auditory stimulus was enhanced in the auditory block (or, equivalently, suppressed in the olfactory block). Attention increased choice probability of the population in the auditory block. We have also observed significant behavior choice probability in small proportions of units. 
Our results suggest that shifting attention between audition to olfaction tasks can modulate the activity of single neurons in primary auditory cortex

Correlated connectivity and the distribution of firing rates in the neocortex

Two recent experimental observations pose a challenge to many cortical models. First, the activity in the auditory cortex is sparse, and firing rates can be described by a lognormal distribution. Second, the distribution of non-zero synaptic strengths between nearby cortical neurons can also be described by a lognormal distribution. Here we use a simple model of cortical activity to reconcile these observations. The model makes the experimentally testable prediction that synaptic efficacies onto a given cortical neuron are statistically correlated, i.e. it predicts that some neurons receive many more strong connections than other neurons. We propose a simple Hebb-like learning rule which gives rise to both lognormal firing rates and synaptic efficacies. Our results represent a first step toward reconciling sparse activity and sparse connectivity in cortical networks

Assessing spatial mismatch patterns in the Gold Coast

This research project empirically tests for the presence of spatial mismatch in the case study region of the Gold Coast, Australia. Spatial mismatch is defined as the mismatch between where low-income households reside, and suitable job opportunities (Kain 1968). Globally, several large scale empirical studies have identified a causal link between poor employment outcomes of low socio-economic residents, and the commuting distances to employment centres (Andersson et al. 2014; Dodson 2005; Ihlanfeldt 2006; Li, Campbell, & Fernandez 2013). However, to date there has been a lack of empirical analysis of the overlap between spatial dimensions of housing and employment (and the commuting such divisions necessitate) in Australia, and never in the case study region. Thus, empirical testing to identify the presence of spatial mismatch in the case study region, was considered practical in order to address the identified gap in the literature. Using Geographic Information System (GIS) software, secondary data from the 2006 and 2011 Australian Bureau of Statistics (ABS) censuses, at the Statistical Local Area (SLA) unit, was used to spatially identify three low socio-economic/high unemployment case study SLAs in the city. A map of the absolute difference in employment was developed using the ABS data in the five-year period. A buffer of 15.6km (average commuting distance Australians travel to access work (BITRE 2015)), was applied around each of the three case study SLAs; in order to identify if disadvantaged households were able to reach areas of high employment within reasonable commuting times. A secondary part of the research assessed the temporal quality of the public transport in each of the identified case study SLAs, as previous research identified that the key to reducing the effects of spatial mismatch is to improve public transport accessibility (Dodson 2005). The research identified that spatial mismatch was not considered an issue in the case study region of the Gold Coast as the number of employment opportunities grew in absolute numbers; however, the growth was mostly in part-time employment. This finding reflects several other studies, which have highlighted Australia’s shift in employment patterns towards an increase in part-time/casual employment (Australian Social Inclusion Board 2009; ABS 2016). The ABS data identified that housing affordability was not strongly spatially differentiated, with a high numbers of unemployed/low-income households, residing in inner city areas, which are subsequently close to employment centres. The public transport assessment identified that the highly disadvantaged outer suburban case study area of Nerang, provided the poorest service accessibility relative to the employment centres. This finding was confirmed with ABS (2011) identifying that households in case study areas with good access to public transport (Southport), were nearly twice as likely to not own a car, compared to those with poorer public transport access(Nerang)

Linearized models of calcium dynamics: formal equivalence to the cable equation

The dynamics of calcium and other diffusible second messengers play an important role in intracellular signaling. We show here the conditions under which nonlinear equations governing the diffusion, extrusion, and buffering of calcium can be linearized. Because the resulting partial differential equation is formally identical to the one-dimensional cable equation, quantities analogous to the input resistance, space constant, and time constant--familiar from the study of passive electrical propagation--can be defined. Using simulated calcium dynamics in an infinite cable and in a dendritic spine as examples, we bound the errors due to the linearization, and show that parameter uncertainty is so large that most nonlinearities can usually b

Probing the connectivity of neural circuits at single-neuron resolution using high-throughput DNA sequencing

There is growing excitement in determining the complete connectivity diagram of the brain—the "connectome". So far, the complete connectome has been established for only one organism, C. elegans, with 302 neurons connected by about 7000 synapses—and even this was a heroic task, requiring over 50 person-years of labor. Like all current approaches, this reconstruction was based on microscopy. Unfortunately, microscopy is poorly suited to the study of neural connectivity because brains are macroscopic structures, whereas synapses are microscopic. Nevertheless, there are several large-scale projects underway to scale up high-throughput microscopic approaches to the connectome.
Here we present a completely novel method for determining the brain's wiring diagram based on high-throughput DNA sequencing technology, which has not previously been applied in the context of neural connectivity. The appeal of using sequencing is that it is getting faster and cheaper exponentially: it will soon be routine to sequence an entire human genome (~3B nucleotides) within one day for $1000.
Our approach has three main components. First, we express a unique sequence of nucleotides—a DNA "barcode"—in individual neurons. A barcode consisting of a random string of even 30 nucleotides can uniquely label 10^{18} neurons, far more than the number of neurons in a mouse brain (fewer than 100 million). Second, we use a specially engineered transsynaptic virus to transport “host” barcodes from one neuron to synaptically coupled partners; after transsynaptic spread, each neuron contains copies of "invader" barcodes from other synaptically coupled neurons, as well its own "host" barcode. Third, we join pairs of host and invader barcodes into single pieces of DNA suitable for high-throughput sequencing. 
Modern sequencing technology could in principle yield the connectivity diagram of the entire mouse brain. Similar approaches can be applied to Drosophila and C. elegans. 
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Mice and rats achieve similar levels of performance in an adaptive decision-making task

Two opposing constraints exist when choosing a model organism for studying the neural basis of adaptive decision-making: (1) experimental access and (2) behavioral complexity. Available molecular and genetic approaches for studying neural circuits in the mouse fulfill the first requirement. In contrast, it is still under debate if mice can perform cognitive tasks of sufficient complexity. Here we compare learning and performance of mice and rats, the preferred behavioral rodent model, during an acoustic flexible categorization two-alternative choice task. The task required animals to switch between two categorization definitions several times within a behavioral session. We found that both species achieved similarly high performance levels. On average, rats learned the task faster than mice, although some mice were as fast as the average rat. No major differences in subjective categorization boundaries or the speed of adaptation between the two species were found. Our results demonstrate that mice are an appropriate model for the study of the neural mechanisms underlying adaptive decision-making, and suggest they might be suitable for other cognitive tasks as well

Non-Gaussian membrane potential dynamics imply sparse, synchronous activity in auditory cortex

Many models of cortical dynamics have focused on the high-firing regime, in which neurons are driven near their maximal rate. Here we consider the responses of neurons in auditory cortex under typical low-firing rate conditions, when stimuli have not been optimized to drive neurons maximally. We used whole-cell patch-clamp recording in vivo to measure subthreshold membrane potential fluctuations in rat primary auditory cortex in both the anesthetized and awake preparations. By analyzing the subthreshold membrane potential dynamics on single trials, we made inferences about the underlying population activity. We found that, during both spontaneous and evoked responses, membrane potential was highly non-Gaussian, with dynamics consisting of occasional large excursions (sometimes tens of millivolts), much larger than the small fluctuations predicted by most random walk models that predict a Gaussian distribution of membrane potential. Thus, presynaptic inputs under these conditions are organized into quiescent periods punctuated by brief highly synchronous volleys, or "bumps." These bumps were typically so brief that they could not be well characterized as "up states" or "down states." We estimate that hundreds, perhaps thousands, of presynaptic neurons participate in the largest volleys. These dynamics suggest a computational scheme in which spike timing is controlled by concerted firing among input neurons rather than by small fluctuations in a sea of background activity

Sources of PCR-induced distortions in high-throughput sequencing data sets

PCR permits the exponential and sequence-specific amplification of DNA, even from minute starting quantities. PCR is a fundamental step in preparing DNA samples for high-throughput sequencing. However, there are errors associated with PCR-mediated amplification. Here we examine the effects of four important sources of error-bias, stochasticity, template switches and polymerase errors-on sequence representation in low-input next-generation sequencing libraries. We designed a pool of diverse PCR amplicons with a defined structure, and then used Illumina sequencing to search for signatures of each process. We further developed quantitative models for each process, and compared predictions of these models to our experimental data. We find that PCR stochasticity is the major force skewing sequence representation after amplification of a pool of unique DNA amplicons. Polymerase errors become very common in later cycles of PCR but have little impact on the overall sequence distribution as they are confined to small copy numbers. PCR template switches are rare and confined to low copy numbers. Our results provide a theoretical basis for removing distortions from high-throughput sequencing data. In addition, our findings on PCR stochasticity will have particular relevance to quantification of results from single cell sequencing, in which sequences are represented by only one or a few molecules