Differential Effects of Exercise on fMRI of the Midbrain Ascending Arousal Network Nuclei in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and Gulf War Illness (GWI) in a Model of Postexertional Malaise (PEM).

BACKGROUND: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), Gulf War Illness (GWI) and control subjects underwent fMRI during difficult cognitive tests performed before and after submaximal exercise provocation (Washington 2020). Exercise caused increased activation in ME/CFS but decreased activation for GWI in the dorsal midbrain, left Rolandic operculum and right middle insula. Midbrain and isthmus nuclei participate in threat assessment, attention, cognition, mood, pain, sleep, and autonomic dysfunction. METHODS: Activated midbrain nuclei were inferred by a re-analysis of data from 31 control, 36 ME/CFS and 78 GWI subjects using a seed region approach and the Harvard Ascending Arousal Network. RESULTS: Before exercise, control and GWI subjects showed greater activation during cognition than ME/CFS in the left pedunculotegmental nucleus. Post exercise, ME/CFS subjects showed greater activation than GWI ones for midline periaqueductal gray, dorsal and median raphe, and right midbrain reticular formation, parabrachial complex and locus coeruleus. The change between days (delta) was positive for ME/CFS but negative for GWI, indicating reciprocal patterns of activation. The controls had no changes. CONCLUSIONS: Exercise caused the opposite effects with increased activation in ME/CFS but decreased activation in GWI, indicating different pathophysiological responses to exertion and mechanisms of disease. Midbrain and isthmus nuclei contribute to postexertional malaise in ME/CFS and GWI.

Hemispheric and Sex Differences in Mustached Bat Primary Auditory Cortex Revealed by Neural Responses to Slow Frequency Modulations.

The mustached bat (Pteronotus parnellii) is a mammalian model of cortical hemispheric asymmetry. In this species, complex social vocalizations are processed preferentially in the left Doppler-shifted constant frequency (DSCF) subregion of primary auditory cortex. Like hemispheric specializations for speech and music, this bat brain asymmetry differs between sexes (i.e., males>females) and is linked to spectrotemporal processing based on selectivities to frequency modulations (FMs) with rapid rates (>0.5 kHz/ms). Analyzing responses to the long-duration (>10 ms), slow-rate (<0.5 kHz/ms) FMs to which most DSCF neurons respond may reveal additional neural substrates underlying this asymmetry. Here, we bilaterally recorded responses from 176 DSCF neurons in male and female bats that were elicited by upward and downward FMs fixed at 0.04 kHz/ms and presented at 0-90 dB SPL. In females, we found inter-hemispheric latency differences consistent with applying different temporal windows to precisely integrate spectrotemporal information. In males, we found a substrate for asymmetry less related to spectrotemporal processing than to acoustic energy (i.e., amplitude). These results suggest that in the DSCF area, (1) hemispheric differences in spectrotemporal processing manifest differently between sexes, and (2) cortical asymmetry for social communication is driven by spectrotemporal processing differences and neural selectivities for amplitude.

Exercise alters brain activation in Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Gulf War Illness affects 25-30% of American veterans deployed to the 1990-91 Persian Gulf War and is characterized by cognitive post-exertional malaise following physical effort. Gulf War Illness remains controversial since cognitive post-exertional malaise is also present in the more common Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. An objective dissociation between neural substrates for cognitive post-exertional malaise in Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome would represent a biological basis for diagnostically distinguishing these two illnesses. Here, we used functional magnetic resonance imaging to measure neural activity in healthy controls and patients with Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome during an N-back working memory task both before and after exercise. Whole brain activation during working memory (2-Back > 0-Back) was equal between groups prior to exercise. Exercise had no effect on neural activity in healthy controls yet caused deactivation within dorsal midbrain and cerebellar vermis in Gulf War Illness relative to Myalgic Encephalomyelitis/Chronic Fatigue Syndrome patients. Further, exercise caused increased activation among Myalgic Encephalomyelitis/Chronic Fatigue Syndrome patients within the dorsal midbrain, left operculo-insular cortex (Rolandic operculum) and right middle insula. These regions-of-interest underlie threat assessment, pain, interoception, negative emotion and vigilant attention. As they only emerge post-exercise, these regional differences likely represent neural substrates of cognitive post-exertional malaise useful for developing distinct diagnostic criteria for Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Machine Learning Detects Pattern of Differences in Functional Magnetic Resonance Imaging (fMRI) Data between Chronic Fatigue Syndrome (CFS) and Gulf War Illness (GWI).

BACKGROUND: Gulf War Illness (GWI) and Chronic Fatigue Syndrome (CFS) are two debilitating disorders that share similar symptoms of chronic pain, fatigue, and exertional exhaustion after exercise. Many physicians continue to believe that both are psychosomatic disorders and to date no underlying etiology has been discovered. As such, uncovering objective biomarkers is important to lend credibility to criteria for diagnosis and to help differentiate the two disorders. METHODS: We assessed cognitive differences in 80 subjects with GWI and 38 with CFS by comparing corresponding fMRI scans during 2-back working memory tasks before and after exercise to model brain activation during normal activity and after exertional exhaustion, respectively. Voxels were grouped by the count of total activity into the Automated Anatomical Labeling (AAL) atlas and used in an "ensemble" series of machine learning algorithms to assess if a multi-regional pattern of differences in the fMRI scans could be detected. RESULTS: A K-Nearest Neighbor (70%/81%), Linear Support Vector Machine (SVM) (70%/77%), Decision Tree (82%/82%), Random Forest (77%/78%), AdaBoost (69%/81%), Naïve Bayes (74%/78%), Quadratic Discriminant Analysis (QDA) (73%/75%), Logistic Regression model (82%/82%), and Neural Net (76%/77%) were able to differentiate CFS from GWI before and after exercise with an average of 75% accuracy in predictions across all models before exercise and 79% after exercise. An iterative feature selection and removal process based on Recursive Feature Elimination (RFE) and Random Forest importance selected 30 regions before exercise and 33 regions after exercise that differentiated CFS from GWI across all models, and produced the ultimate best accuracies of 82% before exercise and 82% after exercise by Logistic Regression or Decision Tree by a single model, and 100% before and after exercise when selected by any six or more models. Differential activation on both days included the right anterior insula, left putamen, and bilateral orbital frontal, ventrolateral prefrontal cortex, superior, inferior, and precuneus (medial) parietal, and lateral temporal regions. Day 2 had the cerebellum, left supplementary motor area and bilateral pre- and post-central gyri. Changes between days included the right Rolandic operculum switching to the left on Day 2, and the bilateral midcingulum switching to the left anterior cingulum. CONCLUSION: We concluded that CFS and GWI are significantly differentiable using a pattern of fMRI activity based on an ensemble machine learning model.

Logistic Regression Algorithm Differentiates Gulf War Illness (GWI) Functional Magnetic Resonance Imaging (fMRI) Data from a Sedentary Control.

Gulf War Illness (GWI) is a debilitating condition characterized by dysfunction of cognition, pain, fatigue, sleep, and diverse somatic symptoms with no known underlying pathology. As such, uncovering objective biomarkers such as differential regions of activity within a Functional Magnetic Resonance Imaging (fMRI) scan is important to enhance validity of the criteria for diagnosis. Symptoms are exacerbated by mild activity, and exertional exhaustion is a key complaint amongst sufferers. We modeled this exertional exhaustion by having GWI (n = 80) and sedentary control (n = 31) subjects perform submaximal exercise stress tests on two consecutive days. Cognitive differences were assessed by comparing fMRI scans performed during 2-Back working memory tasks before and after the exercise. Machine learning algorithms were used to identify differences in brain activation patterns between the two groups on Day 1 (before exercise) and Day 2 (after exercise). The numbers of voxels with t > 3.17 (corresponding to p < 0.001 uncorrected) were determined for brain regions defined by the Automated Anatomical Labeling (AAL) atlas. Data were divided 70:30 into training and test sets. Recursive feature selection identified twenty-nine regions of interest (ROIs) that significantly distinguished GWI from control on Day 1 and 28 ROIs on Day 2. Ten regions were present in both models between the two days, including right anterior insula, orbital frontal cortex, thalamus, bilateral temporal poles, and left supramarginal gyrus and cerebellar Crus 1. The models had 70% accuracy before exercise on Day 1 and 85% accuracy after exercise on Day 2, indicating the logistic regression model significantly differentiated subjects with GWI from the sedentary control group. Exercise caused changes in these patterns that may indicate the cognitive differences caused by exertional exhaustion. A second set of predictive models was able to classify previously identified GWI exercise subgroups START, STOPP, and POTS for both Days 1 and Days 2 with 67% and 69% accuracy respectively. This study was the first of its kind to differentiate GWI and the three sub-phenotypes START, STOPP, and POTS from a sedentary control using a logistic regression estimation method.

A Machine Learning Approach to the Differentiation of Functional Magnetic Resonance Imaging Data of Chronic Fatigue Syndrome (CFS) From a Sedentary Control.

Chronic Fatigue Syndrome (CFS) is a debilitating condition estimated to impact at least 1 million individuals in the United States, however there persists controversy about its existence. Machine learning algorithms have become a powerful methodology for evaluating multi-regional areas of fMRI activation that can classify disease phenotype from sedentary control. Uncovering objective biomarkers such as an fMRI pattern is important for lending credibility to diagnosis of CFS. fMRI scans were evaluated for 69 patients (38 CFS and 31 Control) taken before (Day 1) and after (Day 2) a submaximal exercise test while undergoing the n-back memory paradigm. A predictive model was created by grouping fMRI voxels into the Automated Anatomical Labeling (AAL) atlas, splitting the data into a training and testing dataset, and feeding these inputs into a logistic regression to evaluate differences between CFS and control. Model results were cross-validated 10 times to ensure accuracy. Model results were able to differentiate CFS from sedentary controls at a 80% accuracy on Day 1 and 76% accuracy on Day 2 (Table 3). Recursive features selection identified 29 ROI's that significantly distinguished CFS from control on Day 1 and 28 ROI's on Day 2 with 10 regions of overlap shared with Day 1 (Figure 3). These 10 shared regions included the putamen, inferior frontal gyrus, orbital (F3O), supramarginal gyrus (SMG), temporal pole; superior temporal gyrus (T1P) and caudate ROIs. This study was able to uncover a pattern of activated neurological regions that differentiated CFS from Control. This pattern provides a first step toward developing fMRI as a diagnostic biomarker and suggests this methodology could be emulated for other disorders. We concluded that a logistic regression model performed on fMRI data significantly differentiated CFS from Control.

Exercise alters cerebellar and cortical activity related to working memory in phenotypes of Gulf War Illness.

Gulf War Illness affects 25-32% of veterans from the 1990-91 Persian Gulf War. Post-exertional malaise with cognitive dysfunction, pain and fatigue following physical and/or mental effort is a defining feature of Gulf War Illness. We modelled post-exertional malaise by assessing changes in functional magnetic resonance imaging at 3T during an N-Back working memory task performed prior to a submaximal bicycle stress test and after an identical stress test 24 h later. Serial trends in postural changes in heart rate between supine and standing defined three subgroups of veterans with Gulf War Illness: Postural Orthostatic Tachycardia Syndrome (GWI-POTS, 15%, n = 11), Stress Test Associated Reversible Tachycardia (GWI-START, 31%, n = 23) and Stress Test Originated Phantom Perception (GWI-STOPP, no postural tachycardia, 54%, n = 46). Before exercise, there were no differences in blood oxygenation level-dependent activity during the N-Back task between control (n = 31), GWI-START, GWI-STOPP and GWI-POTS subgroups. Exercise had no effects on blood oxygenation level-dependent activation in controls. GWI-START had post-exertional deactivation of cerebellar dentate nucleus and vermis regions associated with working memory. GWI-STOPP had significant activation of the anterior supplementary motor area that may be a component of the anterior salience network. There was a trend for deactivation of the vermis in GWI-POTS after exercise. These patterns of cognitive dysfunction were apparent in Gulf War Illness only after the exercise stressor. Mechanisms linking the autonomic dysfunction of Stress Test Associated Reversible Tachycardia and Postural Orthostatic Tachycardia Syndrome to cerebellar activation, and Stress Test Originated Phantom Perception to cortical sensorimotor alterations, remain unclear but may open new opportunities for understanding, diagnosing and treating Gulf War Illness.

Exercise challenge alters Default Mode Network dynamics in Gulf War Illness.

BACKGROUND: Gulf War Illness (GWI) affects 30% of veterans from the 1991 Gulf War and has no known cause. Everyday symptoms include pain, fatigue, migraines, and dyscognition. A striking syndromic feature is post-exertional malaise (PEM). This is recognized as an exacerbation of everyday symptoms following a physically stressful or cognitively demanding activity. The underlying mechanism of PEM is unknown. We previously reported a novel paradigm that possibly captured evidence of PEM by utilizing fMRI scans taken before and after sub-maximal exercises. We hypothesized that A) exercise would be a sufficient physically stressful activity to induce PEM and B) Comparison of brain activity before and after exercise would provide evidence of PEM's effect on cognition. We reported two-exercise induced GWI phenotypes with distinct changes in brain activation patterns during the completion of a 2-back working memory task (also known as two-back > zero-back). RESULTS: Here we report unanticipated findings from the reverse contrast (zero-back > two-back), which allowed for the identification of task-related deactivation patterns. Following exercise, patients developed a significant increase in deactivation patterns within the Default Mode Network (DMN) that was not seen in controls. The DMN is comprised of regions that are consistently down regulated during external goal-directed activities and is often altered within many neurological disease states. CONCLUSIONS: Exercise-induced alterations within the DMN provides novel evidence of GWI pathophysiology. More broadly, results suggest that task-related deactivation patterns may have biomarker potential in Gulf War Illness.

A three-dimensional digital neurological atlas of the mustached bat (Pteronotus parnellii).

Substantial knowledge of auditory processing within mammalian nervous systems emerged from neurophysiological studies of the mustached bat (Pteronotus parnellii). This highly social and vocal species retrieves precise information about the velocity and range of its targets through echolocation. Such high acoustic processing demands were likely the evolutionary pressures driving the over-development at peripheral (cochlea), metencephalic (cochlear nucleus), mesencephalic (inferior colliculus), diencephalic (medial geniculate body of the thalamus), and telencephalic (auditory cortex) auditory processing levels in this species. Auditory researchers stand to benefit from a three dimensional brain atlas of this species, due to its considerable contribution to auditory neuroscience. Our MRI-based atlas was generated from 2 sets of image data of an ex-vivo male mustached bat's brain: a detailed 3D-T2-weighted-RARE scan [(59 × 63 x 85) µm3] and track density images based on super resolution diffusion tensor images [(78) µm3] reconstructed from a set of low resolution diffusion weighted images using Super-Resolution-Reconstruction (SRR). By surface-rendering these delineations and extrapolating from cortical landmarks and data from previous studies, we generated overlays that estimate the locations of classic functional subregions within mustached bat auditory cortex. This atlas is freely available from our website and can simplify future electrophysiological, microinjection, and neuroimaging studies in this and related species.

Song Processing in the Zebra Finch Auditory Forebrain Reflects Asymmetric Sensitivity to Temporal and Spectral Structure.

Despite being commonly referenced throughout neuroscientific research on songbirds, reports of hemispheric specialization in the processing of song remain controversial. The notion of such asymmetries in songbirds is further complicated by evidence that both cerebral hemispheres in humans may be specialized for different aspects of speech perception. Some studies suggest that the auditory neural substrates in the left and right hemispheres of humans process temporal and spectral elements within speech sounds, respectively. To determine whether songbirds process their conspecific songs in such a complementary, bilateral manner, we performed functional magnetic resonance imaging (fMRI) on 15 isoflurane anesthetized adult male zebra finches (Taeniopygia guttata) while presenting them with (1) non-manipulated, (2) spectrally-filtered (reduced spectral structure), and (3) temporally-filtered (reduced temporal structure) conspecific song. Our results revealed sensitivity of both primary (Field L) and secondary (caudomedial nidopallium, NCM) auditory regions to changes in spectral and temporal structure of song. On the one hand, temporally-filtered song elicited a bilateral decrease in neural responses compared to the other stimulus types. On the other hand, spectrally filtered song elicited significantly greater responses in left Field L and NCM than temporally filtered or non-manipulated song while concurrently reducing the response relative to non-manipulated song in the right auditory forebrain. The latter hemispheric difference in sensitivity to manipulations of spectral structure in song, suggests that there is an asymmetry in spectral and temporal domain processing in the zebra finch auditory forebrain bearing some resemblance to what has been observed in human auditory cortex.

Anterior-Posterior Connectivity within the Default Mode Network Increases During Maturation.

The default mode network (DMN) supports self-referential thought processes important for successful socialization including: theory-of-mind, episodic memory, and prospection. Connectivity between DMN's nodes, which are distributed between the frontal, temporal, and parietal lobes, change with age and may continue changing into adulthood. We have previously explored the maturation of functional connections in the DMN as they relate to autism spectrum disorder (ASD) in children 6 to 18 years of age. In this chapter, we refine our earlier study of DMN functional maturation by focusing on the development of inter-nodal connectivity in a larger pool of typically developing people 6 to 25 years of age (mean = 13.22 years ± 5.36 s.d.; N = 36; 42% female). Correlations in BOLD activity (Fisher's Z) between ROIs revealed varying strengths of functional connectivity between regions, the strongest of which was between the left and right inferior parietal lobules or IPLs (Z = 0.62 ± 0.25 s.d.) and the weakest of which was between the posterior cingulate cortex (PCC) and right middle temporal gyrus or MTG (Z = 0.06 ± 0.22 s.d.). Further, connectivity between two pairs of DMN nodes significantly increased as a quadratic function of age (p < 0.05), specifically the anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC) and PCC nodes and the left IPL and right MTG nodes. The correlation between ACC/mPFC ↔ PCC connectivity and age was more significant than the correlation between left IPL ↔ right MTG connectivity and age by more than an order of magnitude. We suggest that these changes in functional connectivity in part underlie the introspective mental changes known to commonly occur between the preadolescent and adult years. A range of neurological and psychological conditions that hamper social interactions, from ASD to psychopathy, may be marked by deviations from this maturational trajectory.

Reduced Functional Connectivity of Default Mode and Set-Maintenance Networks in Ornithine Transcarbamylase Deficiency.

BACKGROUND AND PURPOSE: Ornithine transcarbamylase deficiency (OTCD) is an X-chromosome linked urea cycle disorder (UCD) that causes hyperammonemic episodes leading to white matter injury and impairments in executive functioning, working memory, and motor planning. This study aims to investigate differences in functional connectivity of two resting-state networks--default mode and set-maintenance--between OTCD patients and healthy controls. METHODS: Sixteen patients with partial OTCD and twenty-two control participants underwent a resting-state scan using 3T fMRI. Combining independent component analysis (ICA) and region-of-interest (ROI) analyses, we identified the nodes that comprised each network in each group, and assessed internodal connectivity. RESULTS: Group comparisons revealed reduced functional connectivity in the default mode network (DMN) of OTCD patients, particularly between the anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC) node and bilateral inferior parietal lobule (IPL), as well as between the ACC/mPFC node and the posterior cingulate cortex (PCC) node. Patients also showed reduced connectivity in the set-maintenance network, especially between right anterior insula/frontal operculum (aI/fO) node and bilateral superior frontal gyrus (SFG), as well as between the right aI/fO and ACC and between the ACC and right SFG. CONCLUSION: Internodal functional connectivity in the DMN and set-maintenance network is reduced in patients with partial OTCD compared to controls, most likely due to hyperammonemia-related white matter damage. Because several of the affected areas are involved in executive functioning, it is postulated that this reduced connectivity is an underlying cause of the deficits OTCD patients display in this cognitive domain.

Conjugating time and frequency: hemispheric specialization, acoustic uncertainty, and the mustached bat.

A prominent hypothesis of hemispheric specialization for human speech and music states that the left and right auditory cortices (ACs) are respectively specialized for precise calculation of two canonically-conjugate variables: time and frequency. This spectral-temporal asymmetry does not account for sex, brain-volume, or handedness, and is in opposition to closed-system hypotheses that restrict this asymmetry to humans. Mustached bats have smaller brains, but greater ethological pressures to develop such a spectral-temporal asymmetry, than humans. Using the Heisenberg-Gabor Limit (i.e., the mathematical basis of the spectral-temporal asymmetry) to frame mustached bat literature, we show that recent findings in bat AC (1) support the notion that hemispheric specialization for speech and music is based on hemispheric differences in temporal and spectral resolution, (2) discredit closed-system, handedness, and brain-volume theories, (3) underscore the importance of sex differences, and (4) provide new avenues for phonological research.

Dysmaturation of the default mode network in autism.

Two hypotheses of autism spectrum disorder (ASD) propose that this condition is characterized by deficits in Theory of Mind and by hypoconnectivity between remote cortical regions with hyperconnectivity locally. The default mode network (DMN) is a set of remote, functionally connected cortical nodes less active during executive tasks than at rest and is implicated in Theory of Mind, episodic memory, and other self-reflective processes. We show that children with ASD have reduced connectivity between DMN nodes and increased local connectivity within DMN nodes and the visual and motor resting-state networks. We show that, like the trajectory of synaptogenesis, internodal DMN functional connectivity increased as a quadratic function of age in typically developing children, peaking between, 11 and 13 years. In children with ASD, these long-distance connections fail to develop during adolescence. These findings support the "developmental disconnection model" of ASD, provide a possible mechanistic explanation for the Theory-of-Mind hypothesis of ASD, and show that the window for effectively treating ASD could be wider than previously thought.

Sex-dependent hemispheric asymmetries for processing frequency-modulated sounds in the primary auditory cortex of the mustached bat.

Species-specific vocalizations of mammals, including humans, contain slow and fast frequency modulations (FMs) as well as tone and noise bursts. In this study, we established sex-specific hemispheric differences in the tonal and FM response characteristics of neurons in the Doppler-shifted constant-frequency processing area in the mustached bat's primary auditory cortex (A1). We recorded single-unit cortical activity from the right and left A1 in awake bats in response to the presentation of tone bursts and linear FM sweeps that are contained within their echolocation and/or communication sounds. Peak response latencies to neurons' preferred or best FMs were significantly longer on the right compared with the left in both sexes, and in males this right-left difference was also present for the most excitatory tone burst. Based on peak response magnitudes, right hemispheric A1 neurons in males preferred low-rate, narrowband FMs, whereas those on the left were less selective, responding to FMs with a variety of rates and bandwidths. The distributions of parameters for best FMs in females were similar on the two sides. Together, our data provide the first strong physiological support of a sex-specific, spectrotemporal hemispheric asymmetry for the representation of tones and FMs in a nonhuman mammal. Specifically, our results demonstrate a left hemispheric bias in males for the representation of a diverse array of FMs differing in rate and bandwidth. We propose that these asymmetries underlie lateralized processing of communication sounds and are common to species as divergent as bats and humans.

DSCF neurons within the primary auditory cortex of the mustached bat process frequency modulations present within social calls.

Neurons in the Doppler-shifted constant frequency processing (DSCF) area in the primary auditory cortex of mustached bats, Pteronotus parnellii, are multifunctional, responding both to echolocation and communication sounds. Simultaneous presentation of a DSCF neuron's best low and high frequencies (BF(low) and BF(high), respectively) facilitates its response. BF(low) corresponds to a frequency in the frequency-modulated (FM) component of the first harmonic in the echolocation pulse, and BF(high) corresponds to the constant frequency (CF) component in the second harmonic of the echo. We systematically varied the slopes, bandwidths, and central frequencies of FMs traversing the BF(high) region to arrive at the "best FM" for single DSCF neurons. We report that nearly half (46%) of DSCF neurons preferred linear FMs to CFs and average response magnitude to FMs was not significantly less (P = 0.08) than that to CFs at BF(high) when each test stimulus was paired with a CF at BF(low). For linear FMs ranging in slope from 0.04 to 4.0 kHz/ms and in bandwidth from 0.44 to 7.88 kHz, the majority of DSCF neurons preferred upward (55%) to downward (21%) FMs. Central frequencies of the best FMs were typically close to but did not always match a neuron's BF(high). Neurons exhibited combination-sensitivity to "call fragments" (calls that were band-pass filtered in the BF(high) region) paired with their BF(low). Our data show a close match between the modulation direction of a neuron's best FM and that of its preferred call fragment. These response properties show that DSCF neurons extract multiple parameters of FMs and are specialized for processing both FMs for communication and CFs for echolocation.

Effects of dendritic morphology on CA3 pyramidal cell electrophysiology: a simulation study.

We investigated the effect of morphological differences on neuronal firing behavior within the hippocampal CA3 pyramidal cell family by using three-dimensional reconstructions of dendritic morphology in computational simulations of electrophysiology. In this paper, we report for the first time that differences in dendritic structure within the same morphological class can have a dramatic influence on the firing rate and firing mode (spiking versus bursting and type of bursting). Our method consisted of converting morphological measurements from three-dimensional neuroanatomical data of CA3 pyramidal cells into a computational simulator format. In the simulation, active channels were distributed evenly across the cells so that the electrophysiological differences observed in the neurons would only be due to morphological differences. We found that differences in the size of the dendritic tree of CA3 pyramidal cells had a significant qualitative and quantitative effect on the electrophysiological response. Cells with larger dendritic trees: (1) had a lower burst rate, but a higher spike rate within a burst, (2) had higher thresholds for transitions from quiescent to bursting and from bursting to regular spiking and (3) tended to burst with a plateau. Dendritic tree size alone did not account for all the differences in electrophysiological responses. Differences in apical branching, such as the distribution of branch points and terminations per branch order, appear to effect the duration of a burst. These results highlight the importance of considering the contribution of morphology in electrophysiological and simulation studies.