Holes, objects, and the left hemisphere

He, Sheng

doi:10.1073/pnas.0710631105

Cited by 16 publications

(15 citation statements)

References 14 publications

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“…The proposal that the integrity of the left parietal cortex is necessary for categorical apprehension of spatial relationships accords well with general theories of hemisphere dominance that posit a leading role of left hemisphere contributions for all instances of categorical processing (Kosslyn, 1987;Jager and Postma, 2003;Wang et al, 2007;He, 2008).…”

Section: Neural Substrates Of Defective Imitationsupporting

confidence: 72%

Shared neural substrates of apraxia and aphasia

2015

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Section: Neural Substrates Of Defective Imitationsupporting

confidence: 72%

Shared neural substrates of apraxia and aphasia

2015

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“…Spontaneous neural dynamics measured during the so-called resting-state, when people lie quietly in the scanner without performing any specific task, are highly organized and correlate in a manner that recapitulates well-known functional networks (Biswal et al, 1995; Smith et al, 2009). The topography of these networks is robust over time and individuals (Damoiseaux et al, 2006; Shehzad et al, 2009) and has been linked to neurophysiological measures (He et al, 2008; Shmuel and Leopold, 2008). In addition, spontaneous BOLD signal fluctuations influence task-evoked activity (Fox et al, 2006; Mennes et al, 2011), perception (Hesselmann et al, 2008), and behavior (Fox et al, 2007), suggesting that they represent an intrinsic and functionally important component of neural dynamics (Fox and Raichle, 2007; though, see Morcom and Fletcher, 2007; Fornito and Bullmore, 2010 for caveats).…”

Section: The Genetics Of Human Brain Network Connectivitymentioning

confidence: 99%

Connectomic Intermediate Phenotypes for Psychiatric Disorders

Fornito¹,

Bullmore²

2012

Front. Psychiatry

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Psychiatric disorders are phenotypically heterogeneous entities with a complex genetic basis. To mitigate this complexity, many investigators study so-called intermediate phenotypes (IPs) that putatively provide a more direct index of the physiological effects of candidate genetic risk variants than overt psychiatric syndromes. Magnetic resonance imaging (MRI) is a particularly popular technique for measuring such phenotypes because it allows interrogation of diverse aspects of brain structure and function in vivo. Much of this work however, has focused on relatively simple measures that quantify variations in the physiology or tissue integrity of specific brain regions in isolation, contradicting an emerging consensus that most major psychiatric disorders do not arise from isolated dysfunction in one or a few brain regions, but rather from disturbed interactions within and between distributed neural circuits; i.e., they are disorders of brain connectivity. The recent proliferation of new MRI techniques for comprehensively mapping the entire connectivity architecture of the brain, termed the human connectome, has provided a rich repertoire of tools for understanding how genetic variants implicated in mental disorder impact distinct neural circuits. In this article, we review research using these connectomic techniques to understand how genetic variation influences the connectivity and topology of human brain networks. We highlight recent evidence from twin and imaging genetics studies suggesting that the penetrance of candidate risk variants for mental illness, such as those in SLC6A4, MAOA, ZNF804A, and APOE, may be higher for IPs characterized at the level of distributed neural systems than at the level of spatially localized brain regions. The findings indicate that imaging connectomics provides a powerful framework for understanding how genetic risk for psychiatric disease is expressed through altered structure and function of the human connectome.

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“…Besides the high metabolism, the resting state activity can be characterized by strong especially low frequency fluctuations in the range between 0.1 and 0.0001 Hz (see Raichle et al, 2001; He et al, 2008; He and Raichle, 2009). While higher frequency fluctuations (1–60 Hz) are certainly present in the resting state too, they though become more accentuated during subsequent stimulus-induced activity.…”

Section: The Search For the Brain’s Resting State – Spatial And Tempomentioning

confidence: 99%

“…All three, delta, up-and-down states and ISF’s, are often subsumed under the concept of slow cortical potentials (SCP) as they can be measured with EEG (with a special amplifier needed though). These SCP seem to be related to the spontaneous BOLD fluctuations (He et al, 2008; Khader et al, 2008) with both representing fluctuations in cortical excitability across time. This in turn may affect the spiking activity of neurons on the cellular level as well as activity changes on the regional level.…”

Section: The Search For the Brain’s Resting State – Spatial And Tempomentioning

confidence: 99%

Psychoanalysis and the Brain – Why Did Freud Abandon Neuroscience?

Northoff¹

2012

Front. Psychology

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Sigmund Freud, the founder of psychoanalysis, was initially a neuroscientist but abandoned neuroscience completely after he made a last attempt to link both in his writing, “Project of a Scientific Psychology,” in 1895. The reasons for his subsequent disregard of the brain remain unclear though. I here argue that one central reason may be that the approach to the brain during his time was simply not appealing to Freud. More specifically, Freud was interested in revealing the psychological predispositions of psychodynamic processes. However, he was not so much focused on the actual psychological functions themselves which though were the prime focus of the neuroscience at his time and also in current Cognitive Neuroscience. Instead, he probably would have been more interested in the brain’s resting state and its constitution of a spatiotemporal structure. I here assume that the resting state activity constitutes a statistically based virtual structure extending and linking the different discrete points in time and space within the brain. That in turn may serve as template, schemata, or grid for all subsequent neural processing during stimulus-induced activity. As such the resting state’ spatiotemporal structure may serve as the neural predisposition of what Freud described as “psychological structure.” Hence, Freud and also current neuropsychoanalysis may want to focus more on neural predispositions, the necessary non-sufficient conditions, rather than the neural correlates, i.e., sufficient, conditions of psychodynamic processes.

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Holes, objects, and the left hemisphere

Cited by 16 publications

References 14 publications

Shared neural substrates of apraxia and aphasia

Shared neural substrates of apraxia and aphasia

Connectomic Intermediate Phenotypes for Psychiatric Disorders

Psychoanalysis and the Brain – Why Did Freud Abandon Neuroscience?

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